20140707Hymas Exhibit 5.pdf

Case No. PAC-E-14-07
Exhibit No. 5
Wifiress: Kathryn C. Hymas
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BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION
ROCKY MOUNTAIN POWER
Exhibit Accompanying Direct Testimony of Kathryn C. Hymas
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Exhibit No. 5.1
Refrigerator and Freezer Recycling Evaluation
2006-2008
Rocky Mountain Power
Exhibit No. 5 Page 1 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
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Exhibit No. 5 Page 2 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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Report
ldaho Refrigerator and Free-et
Recycling Program
200G-i2008
Prepared for:
Rocky Mountain Power
September 22,2010
Roclry Mountain Power
Exhibit No. 5 Page 3 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas*\* E:*'S $;*S R l$liCANh/ILIS
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Prepared by:
Brian Hedman
Kate Bushman
Dan Groshans
Josh Keeling
The Cadmus Group
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 4 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Table of Contents
1.
2.
Executive Summary........... ............1
lntroduction ......... ............5
Program Description ..................5
Summary of Program Participation 5
Evaluation Questions .................6
Impact Questions 6
Process Questions 6
Evaluation Methods............ ...........7
Analytical Methods... .................7
Participant Surveys
Stakeholder Interviews
Secondary Research
Secondary Data Analysis
Review of Terminology
Determination of Average Annual Gross Energy Consumption
Determination of Net Savings
Process Evaluation ...................21
3.
7
7
8
8
4.
11
11
t6
Participant Survey Findings
Stakeholder Interview Findings
22
26
5.
6.
Appendix A: Participant Survey lnstrument........... ..... 35
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Roclry Mountain Pou,er
Exhibit No. 5 Page 5 of 1365
Case No. PAC-E-14-07
Wtness: lGthryn C. Hymas
September 22,2010
Appendix B: Program Logic Model ................ 46
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 6 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
September 22,2010
PacifiCorp offers this program throughout the five state service territories where it offers
demand-side management programsl. Together these programs recycled over 20,000
refrigerators or freezers in 2009. Within PacifiCorp's Idaho service area, this program is
responsible for 38Yo of the savings that the utility realizes from residential effrciency programs.2
1. Executive Summary
The Idaho Residential Refrigerator and Freezer Recycling Program - See yalater,refrigerator@ -
(the program) offers incentives, free removal, and recycling of older and secondary inefficient
refrigerators and freezers. The Cadmus Group's evaluation of this Rocky Mountain Power
program consisted of four primary tasks displayed in Table ESl.
This evaluation covers the program years 2006,2007, and 2008.
To develop an estimate of program gtoss savings, Cadmus began with an existing data source
containing detailed energy metering information for thousands of refrigerators and freezers at the
time of manufacture. With the application of a degradation factor, these data were used to
develop per-unit energy savings estimates for every combination of appliance configuration, age,
size, and defrost type. Combining this information with data from the program database yielded
an energy savings estimate for each appliance participating in the program as well as per-unit
average annual energy consumption.
Once average annual energy consumption for participating refrigerators and freezers were
determined, Cadmus calculated average gross energy savings for each program year by applying
the program's part-time usage (part-use) factor. The part-use factor accounts for all participating
appliances not plugged in year-round prior to removal. Survey samples and targets were set to
allow part-use factors to be determined separately for refrigerators and freezers in each program
year. Table ES2 and Table ES3 show the three usage categories and survey-determined values
for each appliance type and for each year. Typically, around90% of the appliances were used
t PacifiCorp provides electric service in six state territories, but demand-side management programs are managed by
the Energy Trust of Oregon, not the Company.
2 Based on information contained in PacifiCorp s' 2009 Review of DSM Programs - Idaho located at
http://www.pacifi corp.com/es/dsm.html
Table ESl. Summary of Evaluation Approach
Action lmpact Process Details
Participant Survey x X Used for calculating the net-to-gross (NTG), and assessing implementation.
(n=373)
Stakeholder lnterviews x Provides insiqht into proqram desiqn and delivery. (n=7)
Secondary Research x Review results ol recent apoliance recvclino evaluations.
Secondary Data
Analvsis x Determine per unit savings based on age and size.
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 7 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
September 22,2010
full time. Based on reported usage data, energy savings were adjusted to determine the Annual
Per-Unit Savings shown for refrigerators in Table ES2 and for freezers in Table ES3.
Table ES2. Refrigerator Gross Per-Unit Energy Savings-Part-Time Usage Adjusted
Table ES3. Freezer Gross Per-Unit Enerry Savings-Part-Time Usage Adjusted
Net-to-gross (NTG) ratios were also calculated separately for refrigerators and freezers. The
average NTG ratios across all three years were 0.57 for refrigerators, 0.50 for freezers, and 0.56
for the program as a whole.
Table ES4 provides a summary of evaluation results for each program year and the total for all
three years.
Table ES4. Evaluated Savings Summary
Year Units
Gross Savings
(kwh)NTG Ratio Net Savinos (kWh)
2006
2007
2008
795
684
699
1,137,198
1,060,330
1,051 ,191
0.62
0.52
0.54
706,483
546,312
567.351
Total 2,178 3,248,719 0.56 1.820.146
A cost-effectiveness analysis was performed to compare the program's benefits and costs. The
energy savings used in the cost-effectiveness analysis are the evaluated kWh from this study.
Refriqerators 2006 2007 2008
Use Cateoorv
Percent
of Uniis
Percent
ol Year
Annual
Per-Unit
Savings
(kwh)
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwh)
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwh)
Not in Use 5.30/o 0.0%0 0.8%0.0%0 0.9Y0 0.0%0
Used Part Time 5.3%50.0%38 10.7%31.4%54 5.3%37.SYo 30
Used FullTime 89.3%100.0%1,294 88.5%100,0%1,428 93.8%100.0%1,401
Gross Energy
Savinos 100.0%1,332 100.0%1,482 100.0%1,431
Freezers 2006 2007 2008
Use Cateoorv
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwhl
Pelcent
of Units
Percent
of Year
Annual
Per-Unit
Savings
{kwhl
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwh)
Not in Use 11.5o/o 0.0%0 0.0%0.0%0 4.00/o 0.0%0
Used Part Time 0.0%0,0%0 8.3%16.70/o 22 4.0Y0 33.3%21
Used FullTime 88.5%100.0%1,467 91.70h 100.0%1,441 92.0o/o 100.0%1,419
Gross Energy
Savinos 100.0%1,467 100.0%1,462 100.0%1,439
The Cadmus Group, lnc. / Energy Services
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For recycled refrigerators and freezers, the analysis used a measure life of five years, based on
Califomia's Database for Energy Efficient Resources (DEER 2008 for 06-07 Updates3). This is a
reduction from the measure life of eight years used in prior evaluations. For refrigerators, a five
year measure life is conservative compared to the six year measure life adopted by the Regional
Technical Forum (RFT).
Since participants also receive a free energy-saving kit, which includes two compact fluorescent
light bulbs (CFLs), a measure life value for CFLs is also needed. For the CFLs then, the analysis
used a measure life of 6.6 years. This value is also from DEER 2008 and represents the expected
life for an interior CFL with a nominal 10,000 hour life. This is a reduction from the measure life
of nine years used in prior evaluations. For CFL measure life, DEER and the RTF are nearly
identical since both based their current values on work presented at the 2008 ACEEE Summer
Stodyo and other common sources.
The results of this analysis are sunrmarized below in Table ES5, Table ES6, and Table ES7 for
2006,2007, and 2008 respectively. Table ES8 depicts the analysis for the three years combined.
Table ES5. Program Cost-Effectiveness Summary for 2006 - IRP 46yoLF Decrement
3 http://www.energy.ca. gov/deer/
o Welcome to the Dark Side: The Effect of Switching on CFL Measure Life; Jump, Hirsch, Peters, and Moran; 2008
ACEEE Summer Study
3
Cost Effectiveness Test Levelized
$/kwh Costs Benefits Net
Benefits
Benefit /
Cost
Ratio
Total Besource + Conservation Adder (PTRC)$0.032 $111,244 $247,418 $136,174 2.22
Total Resource No Adder (TBC)$0.032 $111,244 $224,925 $113,681 2.02
Utility (UCT)$0.041 $143,004 $224,925 $81,921 1.57
Ratepayer lmpact (RlM)$0.107 $371,904 $224,925 -$146,979 0.60
Participant (PCT)NA $o $260,660 $260,660 NA
Lifecvcle Revenue lmoact ($/kWh)$0.00001 000
Table ES6. Program Cost-Effectiveness Summary for 2007 - IRP 460 LF Decrement
Cost Effectiveness Test Levelized
$/ kwh Costs Benefits Net
Benefits
Benefit /
Cost
Ratio
Total Resource + Conseruation Adder (PTRC)$0.036 $98,051 $199,052 $101,001 2.03
Total Resource No Adder (TBC)$0.036 $98,051 $180,957 $82,906 1,85
Utility (UCT)$0.04s $123,330 $180,9s7 $57,627 1.47
Ratepayer lmpact (RlM)$0.117 $318,292 $180,957 -$137,336 0.57
Participant (PCT)NA $0 $220,241 $220,241 NA
Lifecycle Revenue lmoact ($/kWh)$0.00000925
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No, 5 Page 9 of 1 365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
September 22,2010
Table ES7. Program Cost-Effectiveness Summary for 2008 - IRP 46VoLB Decrement
Cost Etfectiveness Test Levelized
$/ kwh Costs Benefits Net
Benefits
Benefit
/ Cost
Ratio
Total Resource + Conservation Adder (PTRC)$0.033 $92,326 $202,975 $1 10,649 2.20
Total Resource No Adder (TRC)$0.033 $92,326 $184,523 $92,1 97 2.00
Utility (UCT)$0.040 $113,296 $184,523 $71,227 1.63
Ratepayer lmpact (RlM)$0.1 16 $325,833 $184,523 -$141 ,31 0 0.57
Particioant (PCT)NA $0 $233,562 $233,562 NA
Lifecycle Flevenue lmpact ($/kWh)$0.00000942
Table ES8. Program Cost-Effectiveness Summary across 2006-2008 - IRP 460 LF
This evaluation draws the following conclusions:
o Program participation fell from nearly 800 appliances recycled per year in2006 to under
700 appliances recycledin200T and 2008.
o The average 56% NTG ratio is consistent with other appliance recycling progrcms
including the most recent California statewide evaluation.5
o Participants have been very satisfied with the program, with92yo giving it high scores,
and92%o very likely to recommend it to family and friends.
o Rocky Mountain Power and JACO are both satisfied with the program. All parties feel
the program runs well.
. The progam was found to be cost-effective in all three years.
o The progrrlm is well established and we have no recommendations for modification.
' CPUC Residential Retrofit High Impact Measure Evaluation Report, 2010, Cadmus et al,
http:i,/u,'u,r.r,.calrrrAq.orgipubligptjrLlipil !nqllBesicl!:.{rti4lB.!:troiivaluqliorr}teporLl I .pdf
Decrement
Cost Etfectiveness Test Levelized
$/ kwh Costs Benefits Net
Benefits
Benefit /
Cost Ratio
Total Resource + Conservation Adder (PTRC)$0.034 $282,581 $608,723 $326,143 2.15
Total Resource No Adder (TRC)$0.034 $282,581 $553,385 $270,804 1,96
Utility (UCT)$0.042 $356,058 $553,385 $197,327 1.55
Ratepayer lmpact (RlM)$0.1 13 $950,745 $553,385 -$397,360 0.58
Particioant (PCT)NA $0 $668,1 65 $668,1 6s NA
Lifecvcle Revenue lmoact ($/kWh)$0.00002045
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Roclq Mountain Power
Exhibit No. 5 Page 10 of 1365
Case No. PAC-E-1447
Witness: Kathryn C. Hymas
September 22,2010
2. lntroduction
Program Description
The Idaho Residential Refrigerator Recycling Program is part of Rocky Mountain Power's
ongoing demand-side management (DSM) resource acquisition program. The program's
overarching objective is to decrease customer electricity usage GSfh) through voluntary removal
of inefficient secondary refrigerators and standalone freezers and by recycling older primary
refrigerators. This prevents older units from remaining active at the participant's premise or
elsewhere within Rocky Mountain Power's service territory. The program's Web site encourages
anyone shopping for a replacement to look for ENERGY STAR-labeled models and also refers
them to the Home Energy Savings (HES), program where they may be eligible for an incentive.
In addition to reducing energy consumption at both household and utility levels, the program
decommissions participating appliances in an environmentally sound manner.6
The program provides residential customers with a $30 incentive, Augustl,2007 for each
recycled appliance. Participants receive an incentive for up to two refrigerators or freezers.
Renters who own the appliances may participate, and apartment complex owners or managers
are eligible if they provide tenants with appliances. Participants also receive a free energy-saving
kit that includes: two compact fluorescent light bulbs (CFLs), a refrigeratorlfreezer thermometer
card, and an energy savings brochure. Eligible units must be plugged in, working, and at least 10
cubic feet in size. Rocky Mountain Power has contracted with JACO, an appliance recycler, to
implement the program. JACO disables and removes the appliances, and recycles up to 90% of
the materials, including capture of refrigerant.
Summary of Program Participation
Rocky Mountain Power offered the program to its Idaho customers throughout 2006,2007, and
2008. At the end of these three years, 2,178 old refrigerators and freezers had been permanently
removed from the Rocky Mountain Power service territory, and decommissioned in an
environmentally responsible manner. Table I shows program participation by appliance.
Table 1: Program Participation 2006, 2007, and 2008
Measure 2006 2007 2008 Total
Refrigerators 615 565 515 1,695
Freezers 179 120 184 483
Total 794 685 699 2,178
The annual program volume dropped by about 13%o,from795 total units in 2006 to under
700 units in2007 and 2008. During this time there were some changes in the program and in the
environment in which it was operating:
6 Environmentally-sound disposal of this equipment includes: proper disposal of oils, PCBs, mercury, and CFC-l I
foam, and recycling of CFC-12, HFC-134a, plastic, glass, steel, and aluminum.
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No.5 Page 11 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
September 22,2010
o Incentive reduction. The incentive was reduced from $40 to $30 (effective August 1,
2007) to improve program cost-effectiveness.
o Economic factors. A general economic downturn in 2008 affected purchases of homes
and durable goods such as refrigerators and freezers.
These changes are noted here for informational purposes - this evaluation did not test whether
they had significant impact on the program.
Evaluation Questions
Appliance recycling programs differ from most programs in that savings are generated by
rebating removal of an operable but inefficient measure rather than rebating installation of an
efficient measure. The overarching impact and process evaluation questions driving the study are
listed below.
!mpact Questions
L What are the gross and net energy savings generated by a participating appliance?
2. What percentage of participating appliances would have been discarded and
destroyed or would have been kept but unused in the program's absence?
3. How do evaluated savings compare to previously reported savings for each program
yeat?
4. What were the program's actual costs and benefits?
Process Questions
How did participants become aware of the program?
How satisfied are participants with program delivery: schedule, communications,
implementer performance, incentive, and overall?
What improvements would participants recommend?
From the implementer's perspective: how is the program working? What could
be improved?
l.
2.
3.
4.
6The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 12 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
3. Evaluation Methods
Analytical Methods
The evaluation plan consisted of four primary tasks (see Table 2). The participant survey
informed both impact and process evaluations. A brief description of each task follows.
Additional detail regarding the methodology of each evaluation task is provided in subsequent
chapters.
Participant Surveys
The participant survey asked a number of questions to determine: sources of program
information, descriptions of recycled appliances, participants' consideration of appliance
dispo sal alternatives, pro gftrm satisfaction, and demo graphics.
The evaluation team drafted andfinalized a participant survey utilizing industry best practices
for appliance recycling evaluations. The survey included questions addressing the following,
pertinent issues:
o Verification of Measure Removal. This section of the survey contained questions related
to recall of participation, involvement in the decision process, and measure removal.
. Appliance Context and Decision-Making Processes. These questions addressed key
aspects of the customer's decision-making process, and informed freeridership, spillover,
and verification analysis.
o Program Satisfaction. These questions collected process-related questions regarding
participants' satisfaction with the program, including reasons for dissatisfaction, if
applicable. The questions also addressed the likelihood that participants would refer
others to the program.
Cooperation with survey efforts was substantial, with about 50% of sampled respondents
agreeing to respond to telephone surveys. One reason for this cooperation rate may have been
high satisfaction levels with the program (described in the Process Evaluation section, below).
Stakeholder I nterviews
To assess the program's effectiveness and implementation, the evaluation team conducted
interviews with a number of stakeholders very familiar with the program. Specifically, the
Table 2: Summary of Evaluation Approach
Action lmpact Process Details
Participant Survey x X Used for calculating the net-to-gross (NTG), and assessing implementation,
(n=373)
Stakeholder lnterviews x Provides insiqht into proqram desiqn and deliverv. (n=7)
Secondary Research X Review results of recent aooliance recyclino evaluations.
Secondary Data
Analvsis X Determine per unit savings based on age and size.
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 13 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
evaluation team interviewed seven stakeholders from Rocky Mountain Power and JACO. Details
regarding stakeholders interviewed are provided in Table 3.
Table 3: Stakeholder Interviews
Title 0rqanization
Demand Side Manaqement (DSM), Director PacifiCorp
Class 2 DSM Seoment Manaoer, All Sectors PacifiCorp
DSM Evaluation and Controls PacifiCoro
Rocky Mountain Power QI/QC Staff (2)PacifiCorp
I mplementer Operations Manager JACO
lmDlementer Warehouse Manaqer JACO
Stakeholder interviews were conducted utilizing an interview guide aimed at discussing the
program's design, delivery, management, communication, effectiveness, and future with each
respondent.
Information obtained from stakeholders was used to inform the following evaluation elements:
o Determination of program progress; and
o Identification of changes during implementation.
Secondary Research
To ensure the evaluation aligned with industry's best practices for appliance recycling
evaluations, the evaluation team gathered and reviewed multiple previous appliance recycling
evaluation final reports. In addition to examining methodologies employed in each report, the
evaluation team assessed participant survey instruments used.
Data collected through secondary research aided the following evaluation elements:
o Development of the gross savings methodology;
o Development of the participant survey instruments; and
o Development of the net savings methodology.
Secondary Data Analysis
To leverage existing appliance recycling data sources, the evaluation team obtained datasets
detailing energy consumption of thousands of refrigerators and freezers at the time of their
manufacture. With the application of a degradation factor, these data were used to develop per-
unit energy savings estimates, based on an appliance's age, size, and configuration. Combining
this information with data on program participants yielded an estimate of the program's gross
savings. Significant detail regarding this process is provided in the following chapter.
The engineering analysis informed the following evaluation elements:
o Determination of estimated per-unit energy savings;o Determination of appropriate degradation factor; and
o Estimate of program gross savings.
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 14 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Data Sources
The evaluation team utilized the following data sources to inform the impact and process
evaluations:
o Final program databases (provided by JACO);o Information gathered through participant surveys;o Information gathered through stakeholder interviews;
o Database containing results of 61,000 metered appliances;7 ando Other recent appliance recycling evaluations.
Sampling Plan
This section details the sampling plan for the participant survey and stakeholder interviews.
Participant Surveys
The sampling plan was designed to meet the study's goals, including determination of energy
savings for each of the three calendar years: 2006,2007, and 2008. Accurate determination of
energy savings required independent evaluation ofrefrigerators and freezers, as energy
consumption and operating patterns were distinct to each. Altogether, this meant six samples
were needed: one for each appliance/year combination.
In response to the request for program databases, JACO provided three files----customers, orders,
and units-for each calendar year. The "units" file included records for each appliance recycled,
and a field identifying it as a refrigerator or freezer. The next step was to aralyze each participant
database to confirm it contained information necessary to complete the data collection. These
data included: participant contact information, appliance details, and incentive amounts. Once
verified, the evaluation team assigned a random number to each participant, and prioritized the
call listed based on the random number.
To achieve results with 90% confidence and llYo precision, targets were established of
85 surveys per refrigeratorlyear combination and 55 surveys per freezerlyear combination. As
shown in Table 4, despite repeated attempts to contact participants, targets were not met in all
categories, especially for freezers, which had a relatively small participant population. Thus, the
level of precision achieved ranged from 8.6% to 27.lYo.
7 http:i/www.energy.ca.gov/appliances/databaseAistorical excel files/2009-03-01 excel based _files/Refrigeration/
IThe Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 15 of 1365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
September 22,2010
Table 4: Participant Survey Sample
Aooliance 2006 2007 2008 Total
Refriqerators 615 565 515 1.695
Freezers 179 120 184 483
Total 794 685 699 2,178
Surveys Completed 2006 2007 2008 Total
Refrioerators 75 122 113 310
Freezers 26 12 25 63
Total 101 134 138 373
Level of orecision at the 90% confidence interval 2006 2007 2008 AllYears
Refriqerators 10.870 8.7o/o 8.6%5.3%
Freezers 18.6%27.0%16.8%9.6%
The Cadmus Group, lnc. / Energy Services 10
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 16 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
4. Program Results
lmpact Findings
Impact evaluation findings are presented in the following four subsections:
1. Review of Terminology
2. Determination of Average Annual Gross Energy Consumption
3. Determination of Gross Savings
4. Determination of Net Savings
Review of Terminology
Gross and net savings were calculated by determining a program's "part-use" and NTG factors.
First used in the 2002 California Statewide Residential Appliance Recycling Program (RARP),8
the factors have become the industry standard for assessing actual outcomes from appliance
recycling. Each factor is defined below:
o Part-[.Jse Factor: Adjusts for the proportion of the year participants used the appliance
and/or the proportion of the year it would have been used had they kept it.
o NTG Factor: Adjusts for the percentage of participants that would have disposed of the
unit independently of the program in a manner that would have taken the unit out of
service.
Determination of Average Annual Gross Energy Consumption
To calculate energy consumption for early retirement of participating refrigerators and freezers,
and for distribution of energy-saving kits, the evaluation team followed these steps:
1. Develop a model to estimate the annual unit energy consumption of older appliances.
2. Adjust the annual unit energy consumption for degradation over time.
3. Adjust the annual unit energy consumption for part-time usage.
4. Determine gross savings for Energy Saving Kits.
Once gross energy consumption for the average refrigerator, freezer, and kit were known,
program level savings could be easily calculated by multiplying unit savings by the number of
units. Resulting gross program savings are shown at the end of this section.
Step 1: Model to estimate annual Unit Energy Consumption. A multivariable regression
model was developed to estimate the Unit Energy Consumption (UEC) of participating
refrigerators and freezers. Given the appropriate data, regression models provide a powerful tool
to evaluators by enabling them to predict energy consumption based on a small set of appliance
8 Measurement and Evaluation Study of 2002 Statewide Residential Appliance Recycling Program, Final Report.
KEMA-Xenergy. 2004.
The Cadmus Group, lnc. / Energy Services 11
Rocky Mountain Power
Rocky Mountiain PoweI
Exhibit No. 5 Page 17 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
September 22,2010
characteristics. Prior experience has shown that the appliance model number alone is not
suffrcient to predict energy consumption since the model number is often recorded incorrectly
(or is difficult to match due to spaces and dashes) and also since the same model number is often
manufactured for several years. In this case where a large database of appliance energy data is
available, the regression model is a good fit for the task.
The regression model was based on the California Energy Commission's energy consumption
databasee of over 61,000 specific refrigerator and freezer makes and models, manufactured
between 1978 and 2008. The database contains the UEC value for each appliance, as reported by
the manufacturers, and based on energy consumption found using the DOE-established test
procedure. The model employed the DOE-based UEC as the dependent variable, and the various
characteristics (configuration, age, size, etc.) of the tested refrigerators as the independent
variables.
To develop the regression model, all independent variables were considered that had data
available in the energy consumption database. If analysis showed standard error for a
characteristic was less than l|yq it was used in the final model. Table 5 shows these potential
independent variables, and which were included in the final regression model.
Table 5: Possible Independent Variables
Refriqerators Freezers
Characteristic ln Model Characteristic ln Model
Aqe Yes Aqe Yes
Volume in Cu Ft Yes Volume in Cu Ft Yes
Bottom Freezer Yes Uorioht Freezer Yes
Too Freezer No Chest Freezer No
lnternal Freezer No Automatic Defrost Yes
Kitchen Unit No
Sinole Door No
Side-bv-Side Yes
Throuoh-Door lce-Maker No
Automatic Defrost Yes
The final regression models predicted energy usage based on these characteristics. Model
coefficients are shown in Table 6 and Table 7.The parameters indicate the regression model fit
well with the energy consumption data. For both appliance types, age was the most important
variable (as shown by the high t-values), with other variables such as volume and automatic
defrost having similar relative importance.
'http:/iww*.energy.ca.gov/appliances/database,/historical_excel_files/2009-03-01_excel_based_files/Refrigeration/
The Cadmus Group, lnc. / Energy Services 12
Rocky Mountain Power
Roclry Mountiain Power
Exhibit No. 5 Page 18 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Table 6: Regression Model Coefficients for Refrigerator Enerry Consumption
Refiloerators: R souared = 0.7853
lndependent Variable Coetficient Standard Error t-value
lntercept -623.78 7.22 -86.37
Aoe (vears)41.20 0.13 31 2.1 8
Volume (CuFt)27.38 0.31 87.24
Side-by-Side 193.27 2.51 77.05
Bottom Freezer 176.85 4.52 39.12
Automatic Defrost 403.82 5.57 72.54
Table 7: Regression Model Coefficients for Freezer Enerry Consumption
Freezers: R squared = 0.8i158
lndeoendent Variable Coetficient Standard Error t-value
lntercept -250.72 4.49 -55.88
Aqe (years)27.89 0.12 237.52
Volume (CuFt)28.49 0.22 131.79
Uorioht Freezer 38.94 1.92 20.23
Automatic Defrost 353.10 2.71 130.24
The models were then applied to the set of appliances the program collected each year. To apply
the model, evaluators analyzedthe participant database to determine the average value for each
independent variable. Table 8 and Table 9 provide these average values for each appliance
characteristic and each year evaluated.
Because the CEC database does not include appliances manufactured before 1978, Cadmus
assumed an appliance manufactured before 1978 consumed the same amount of electricity as an
appliance manufactured in 1978. This assumption likely understates actual program savings. The
unadjusted average age for each group is shown as the "Reported Age at Time of Recycling" in
the table, and the adjusted age is shown as the "Modeled Age."
Table 8: Population Characteristics for Refrigerators
Refriqerators: ldaho Participant Unit Summary
2006 2007 2008
Total Particioant Ref rioerators 615 565 515
lndependent Variable 2006 Averaqe 2007 Averaqe 2008 Averaqe
Reoorted Aoe at Time of Recvclino ffears)27.65 26.76 25.24
Modeled Aoe ffears)23,45 22.40 21.03
Volume (Cu Ft)16.77 17.45 17.80
Side-by-Side 19Yo 13o/o 10o/o
Bottom Freezer 3Yo 2o/o 3o/o
Automatic Defrost 45o/o 85%82o/o
The Cadmus Group, lnc. / Energy Services 13
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 19 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Table 9: Population Characteristics for Freezers
Freezers: ldaho Particioant Unit Summarv
2006 2007 2008
Total Participant Freezers 179 120 184
lndeoendent Variable 2005 Averaqe 2007 Averaqe 2008 Averaqe
Reoorted Aoe at Time of Recvclino ffears)34.73 35.46 35.11
Modeled Aoe (Years)26.15 26.86 25.60
Volume (Cu Ft)16.44 17.48 18.07
Uorioht Freezer 64Vo 60%63%
Automatic Defrost 340h 2%2o/o
Step 2: Adjust the annual UEC for degradation over time. Step 1 estimates the units energy
consumption at the time of manufacture. Step 2 adjusts this consumption for increases in energy
usage occurring as refrigerators and freezers age.
This evaluation used an annual degradation factor of 1.5%o, based on the DOE National Energy
Audit Tool,r0 Quantec's 2004-2005 appliance recycling study,lr KEMA's 2005-2006 appliance
recycling study,12 and the CPUC (California) Residential Retrofit report.13
Table 10 lists UEC values adjusted by the l.5o/o degradation factor.
Table 10: UEC adjusted for degradation
Appliance Type 2006-2008 Averaqe 2006 Averaoe 2007 Averaoe 2008 Averaqe
Refrioerators 1,518 1,448 1,613 1,494
Freezers 1,592 1.658 1.571 1.542
Step 3: Adjustment for Partial Usage. Gross savings needed to be adjusted for units used only
a portion of the year. Thus, the evaluation team calculated and applied the program's part-use
factor. Retirement of appliances not previously in operation or operated only part of the year did
not yield the full year of energy savings presented in Table 10. A weighted average of the
part-use factors was used in the following three participant categories:
o Participating units not used for at least one full year prior to being recycled were
assigned a part-use factor of Uoh. As the unit was not consuming electricity, no savings
were generated by its retirement. (Note: This assumes that these units never go back into
service.)
o Recycled units operating the full year prior to participation were assigned a part-use
factor of 1007o.
For units used only a portion of the previous year, the part-use factor ranged between 0o/" and
l00oh based on reported usage.
'0 The DOE National Energy Audit Tool uses a sliding scale between lYo and 2Yo.
rr The Evaluation of the Utah Refrigerator and Freezer Recycling Program, Quantec, August 23 2005, used l%.
12 Evaluation of the Utah Refrigerator and Freezer Recycling Program, KEMA, August 3l , 2OO7 , used I %.
t3 The CPUC Residential Retrofit Report-also referenced in Footnote I above-used2.2%.
The Cadmus Group, lnc. / Energy Services 14
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 20 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
September 22,2010
Table I I and Table 12 illustrate how the part-use factors for each of these three categories were
applied to determine average part-use adjusted gross annual energy savings for refrigerators and
freezers for each program year.
Table Refrigerator Gross Per-Unit Energy Savings - Part-Use Adjusted
Step 4: Determine gross savings for Energy Saving Kits. The kits JACO distributed included:
two CFLs, a temperature strip for testing refrigerator or freezer temperatures, and a brochure
providing a number of energy-saving tips for the home. Gross savings shown here represent
savings if all elements of the kits were installed.
For each CFL in the kit, annual savings were assumed to be 33 kwh per year consistent with the
model used by the Regional Technical Forum for Energy Star CFLs in residential applications'0.
The Northwest Energy Efficiency Alliance (NEEA) uses a similar figure of 33.1 kWh/year. This
is a lower estimate for annual savings than was used in past program evaluations. However, it
reflects research that shows increased penetration of CFLs in the home and takes into account a
range of possible locations in the home.
For the temperature strip and informational brochure, we assumed 12 kWh/year, based on
previous appliance recycling evaluations." These assumptions are sunmxizedin Table 13.
laResidential, Energy Star CFLs, http:iiu,'rvw.nrvcouncil.org. rtflsupportingtlataiciefault.htm
15 Evaluation of the Utah Refrigerator and Freezer Recycling Program, KEMA, August 31,2007;The Evaluation of
the Utah Refrigerator and Freezer Recycling Program, Quantec, August 23 2005.
Refriqerators 2006 2N7 2008
Use Cateqory
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwh)
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
{kwhl
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwh)
Not in Use 5.3%0.0%0 0.8%0.0%0 0.9%0.0%0
Used Part Time 5.3%50.0%38 10.70/o 31.4o/o 54 5.3%37.5%30
Used FullTime 89.3%100.0%1,294 88.5%100.0%1,428 93.8%100.0%1,401
Gross Energy
Savinos 100.0%1,332 100.0%1,482 100.0%1,431
Table l2zEreezer Gross Per-Unit Enerry Savings - Part-Use Adjusted
Freezers 2006 2007 2008
Use Cateqorv
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwhl
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwh)
Percent
of Units
Percent
of Year
Annual
Per-Unit
Savings
(kwh)
Not in Use 11.5o/o 0.0%0 0.0%0.0%0 4.00/o 0.0%0
Used Part Time 0.0%0.0%0 8.3%16.7Yo 22 4.00/o 33.30h 21
Used FullTime 88.s%'t00,0%'t 467 91.7%100.0%1,441 92,0%100.0%1,419
Gross Energy
Savinqs 100.0%1,467 100.0%1,462 100.0%1,439
The Cadmus Group, lnc. / Energy Services 15
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 21 of 1 365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Table L3: Gross Savings for Energy Saving Kits
Savings per CFL
{kwhl
Number of CFLs per
Kit
Total CFL Savings
(kwh)
Additional Kit Savings
(kwh)
Total Savings
(kwh)
33 2 bb 12 78
Calculate Gross Program Enerry Savings
Table 14 shows resulting gross energy savings derived from the per-unit energy savings and the
number of units by year.
Table 14: Gross Program Enerry Savings
Year Gross Savinqs Per Unit (kWh)Units Gross Savinqs Per Year (kWh)
Refrigerators
2006
2007
2008
1,332
1,482
1.431
615
565
515
819,217
837,1 98
736,958
Total 1.695 2.393.373
Freezers
2006
2007
2008
1,467
1,462
1.439
'179
120
184
262,679
175,474
264,8s9
Total 483 703.012
Kits
2006
2007
2008
78
78
78
709
611
633
55,302
47,658
49,374
Total 1.953 152,334
Program
2006
2007
2008
794
685
699
1,137,198
1,060,330
1,051 ,191
Total 2,178 3.248.719
Determination of Net Savings
Assessing freeridership for appliance recycling presents a special set of challenges, as the
program's aim was not only to remove inefficient appliances from a customer's home, but to
remove it from the gdd entirely. Thus, freeridership had to be estimated based on participant
reports of what would have happened to the appliance in the program's absence.
P a rti c i p a nt S u rv ey-Based M eth o d o I ogy
To determine the NTG ratio for each progmm year and appliance type, surveys were conducted
with program participants to estimate freeridership rates. This allowed the evaluation team to
calculate program savings net of free riders (i.e., no program savings were achieved if the unit
would have been destroyed in the program's absence or remained unused in the participating
home).
Independent of program intervention, participating appliances would have been subject to four
potential scenarios:
The Cadmus Group, lnc. / Energy Services 16
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 22 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
I q-pl-.Pt ?: ?, ?9. ! .0" "
o The unit would have been kept by the participating household, but stored unused;
o The unit would have been kept by the participating household and still be used;
o The unit would have been discarded by the participating household in a manner leading
to its eventual destruction; and
o The unit would have been discarded by the participating household in a manner leading
to its continued operation elsewhere.
Of these scenarios, two-units kept but stored unused, and those discarded in a manner leading
to destruction-would be indicative of freeridership since the refrigerator or freezer would not
have continued to consume energy independently of program participation.
To inform the NTG calculation, respondents were asked what would have happened to the
participating refrigerator or freezer had it not been removed by the program. Each response-
such as "sold it to an used appliance dealer" or "hauled to a recycling center myself'-was
associated with one of the four scenario categories after a series of follow-up questions (i.e.,
"Why did you not follow through with this transaction?" and "Do you have the ability to
physically move and transport the appliance yourself?") validated the response. Once validated
and associated with one of the four potential scenarios, the individual response was determined
as indicative or not indicative of freeridership. Using this information, a participant-based NTG
value was calculated.
Figure I describes the freeridership analysis' underlying logic. The complete survey instrument
is provided in Appendix A.
The Cadmus Group, lnc. / Energy Services 17
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 23 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Figure 1: Analytical Logic for Survey-Based Net-to-Gross
---+ l-] --->
| :: didn rs'c*
|
+ iTEJE------------I- t-------------- !_____________
F ree ri ders h i p S ce n a ri os
Table 15, below, presents the four possible scenarios that could have occurred had a participating
refrigerator or freezer not been recycled through the Program; Scenarios 1 and 3 indicate
freeridership. Both scenarios are explored in fuither detail below.
The Cadmus Group, Inc. / Energy Services 18
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 24 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Table 15: Potential Freeridership Scenarios
Scenarios lndependent of Proqram Scenario lndicative of Freeridership
Unit keot but not used 1 Yes
Unit keot and used 2 No
Unit discarded and destroyedl6 3 Yes
Unit discarded. translerred, used 4 No
Scenario I
Participant respondents who reported they would have kept the unit had they not participated in
the program were asked if they would have used the unit or stored it unplugged. The product of
these responses provided the proportion of units that would have been kept and not used
(therefore not drawing electricity from the grid and being indicative of freeridership). Energy
savings associated with these units were subtracted from the program's determined gross
savings.
Scenario 3
Calculating freeridership associated with Scenario 3 (units which would have been discarded and
destroyed in the program's absence) was slightly more complex as it represented a number of
different hypothetical actions. Table 16 presents responses provided by participants related to
Scenario 3, indicating actions participants claimed they would have taken, had the program not
been available.
Table 16: Freeridership Scenario 3-Units Discarded and Destroyed
(Participant Responses)
Stated Method of Disposal ln Absence of Program lndicative of Freeridership
Sell it to a private party, either by running an ad or to someone you know No
Sell it to a used aooliance dealer Partially
Give it away to a private party, such as a friend or neighbor No
Give it awav to a charitv oroanization, such as Goodwill lndustries or a church No
Have it removed by the dealer you got your new or replacement appliance from Yes
Haul it to the dump yoursell Yes
Haul it to a recyclino center yourself Yes
Hire someone else to haul it awav for iunkino or dumpinq Yes
Otherl Yes
lAll other responses were reviewed individually and determined to be indicative of freeridership
This analysis relied on interviews with appliance dealers and other market actors. Particularly,
the response o'Had it removed by the dealer I got my replacement appliance from" was identified
as indicative of freeridership, as interviews with appliance dealers indicated the vast majority of
such units are destroyed and not resold. Furthermore, investigation into purchasing patterns of
16 It is important to note that while Scenario 3 would have led to the destruction of the appliance, it is unlikely the
unit would have been decommissioned in the environmentally responsible manner undertaken by the program.
As a result, while the energy impact might have been be equivalent, the larger environmental and societal
impacts were not.
The Cadmus Group, lnc. / Energy Services 19
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 25 of 1 365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
September 22,2010
used appliance dealers has shown dealers typically do not purchase appliances over 10 years old.
Thus, the freeridership score associated with this response was discounted by the proportion of
participant appliances over l0 years old.
Determining NTG Ratio for Energy-Saving Kits
Program participants also received energy-saving kits containing two CFLs, a temperature test
strip, and additional information about energy-saving measures that can be taken in the home.
The savings level achieved through the kits depended highly on the rate participants installed the
CFLs. Thus, the participant survey asked whether one or both of the CFLs were installed in the
home, and the resulting installation rate was used as the NTG ratio for the kits.
The CFL installation rate was based on the response of participants that recalled receiving the
energy-saving kit. Generally, the longer it has been since an event, the less people recall about it.
Figure 2 shows that this is true with regard to the energy saving kit. Less than half of participants
surveyed recall receiving the energy saving kit in 2006 while about 65Yo recalled the kit in 2007
and 2008.
tr'igure 2. Participant Responses: Was a free kit containing CFL light bulbs and enerry
,
trformation Biven to you at the time of p-ickun-, .. _*----a
2008 (n=138)
2007 (n=134)
2005 (n=101)
N Yes (%)
s No (%)
ffi Don't Know (%)
80% 700%
NfG Rafios
The freeridership calculations outlined above yielded the appliance-specific NTG ratios
presented in Table 17, below.
Table 17: NTG Ratios,2006-2008
2006 2007 2008
Hefriqerators 0.67 0.53 0.51
Freezers 0.48 0.40 0.60
Kits 0.57 0.68 0.66
The Cadmus Group, lnc. / Energy Services 20
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 26 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Alet Savings Results
Once the NTG ratios were determined for each appliance type and each year, total program gross
savings were adjusted, as presented in Table 18, to account for freeridership and (in the case of
the energy-saving kits) installation rates.
Table 18: Net Annual Enerry Savings for Refrigerators, Freezers, and Kits
Comparison of Reported Savings to Evaluated Savings
This section provides comparisons of the reported program results to the evaluated program
results. Table l9 compares the reported savings to the evaluated values at the program level.
Table 19: Program Reported Savings and Evaluated Savings
Year Evaluated Savingstz
(kwh)
Reported Savings
{kwh)
2006 1,137,198 881,260
2007 546,312 509,562
2008 1,051,191 930,993
17 Savings were reported net offree-ridership for 2007 andgross for 2006 and 2008. The evaluated savings are
reported at the comparable level.
Year
Gross Savings Per
Unit (kWh)Units
Gross Savings Per
Year (kWh)
Net-to-Gross
(NTG) Ratio
Net Energy Savings
Aooreoate (kWhl
Refrigerators
2006
2007
2008
1,332
1,482
1,431
615
565
515
819,217
837,198
736,958
0.67
0.53
0.51
548,875
443,715
375.849
Total 1,695 2.393.373 0.57 1.368.439
Freezels
2006
2007
2008
1,467
1,462
1,439
179
120
184
262,679
175,474
264.859
0.48
0.40
0.60
126,086
70,190
1 58,915
Total 483 703.012 0.50 355.191
Kits
2006
2007
2008
78
78
78
709
611
633
55,302
47,658
49,374
0.57
0.68
0.66
31,522
32,407
32.587
Total 1.953 152.334 0.63 96.516
Program
2006
2007
2008
794
685
699
1,137,198
1,060,330
1,051,191
0.62
0.52
0.54
706,483
546,312
567,351
Total 2,178 3.248.7'.tg 0.56 1.820.146
The Cadmus Group, lnc. / Energy Services 21
Rocky Mountain Power
Roclq Mountain Power
Exhibit No. 5 Page 27 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Process Evaluation
The process evaluation provided answers to the following questions:
1. How satisfied are participants with program delivery-schedule, communications,
implementer performance, incentive, and overall?
2. How did program participants become aware of the program?
3. What improvements would participant recommend?
4. From the implementer's perspective: how is the program working? What could
be improved?
Partici pant Survey Findings
Participants expressed significant satisfaction with the program, with 92oh rating it with a 7 , 8, 9 ,
or 10, on a l0-point scale. In fact, only 26 of the 373 respondents rated their program satisfaction
at a 6 or lower. Figure 3 illustrates a breakdown of participants' satisfaction responses.
Figure 3: Participant Satisfaction
I
87w
6
5
NN
On a scale of 0 to 10, with 0 being not satisfied,
and L0 being very satisfied,
how satisfied are you with the Pacific Power
Appliance Recycling Program overall?
10%200/o 30% 40o/o
Pptg:ltpff s:P_-o-lggtl:i'*u.-...**.......
60%50%
Similarly, 92%o of ctstomers said they were very likely to recommend the program to a friend or
family member. On a 10-point scale, with 10 indicating the participant was extremely likely to
recommend the program to a friend, the average rating for recommending the program was 9.3.
Further, 82Yo of the responding participants said they would have participated even if the amount
of the incentive had been less.
m Refrigerator
i
$ l-t9?1s- l
The Cadmus Group, lnc. / Energy Services 22
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 28 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Porticipont Awareness
Bill inserts (26%), television commercials (20oh), and print media (I7%) were the information
sources cited by 63%o of respondents. Table 19 shows these data and the other ways participants
learned about the program.
Table 20: Program Awareness
Refrigerator and Freezer Descriptions and Chorocteristics
According to JACO records, recycled refrigerators and freezers averaged about 28 and 36 years
old, respectively. Of those replacing their recycled appliances, 83oZ reported to have been
replaced with an ENERGY STAR-labeled appliance. However, it should be noted telephone
respondents often had difficulty accurately assessing the efficiency of their appliances.
Appliance locations also played a factor in energy use. As shown in Table 20,7loh of freezers
were located in the garage (48%) or basement (24%), but the situation differed somewhat for
refrigerators. Respondents indicatedS5oh of refrigerators were located in the kitchen (61%) or
garage (24%). Approximately 67oh of respondents indicated the location of the recycled
appliance was heated, while only l3o/o had their recycled appliance in an air-conditioned space.
Table 21: Location of Recycled Appliance
Freezer Refriqerator Total
n Percent Respondinq n Percent Bespondinq n Percent Besoondino
Kitchen 10 160h 189 610h 199 53%
Garaqe 30 480/o 74 240/o '104 28Yo
Basement 15 24Yo 21 7o/o 36 100/o
Porch/Patio 3 5o/o 11 4%14 4%
Other 5 9Yo 14 5o/o 19 5o/o
Total 63 100Vo 309 100%372 100%
include: soare room. workshoo. laundrv room. utilitv room. and bam.responses include: spare room, workshop, laundry room, utility room,
Freezer Refrioerator Total
n
Percent
Resoondino n
Percent
Resoondino n
Percent
Resoondino
Bill lnserts/Contact 14 220/o 84 270/o 98 260h
TV 1l 17o/o 62 20%73 20o/o
Newsoaoer / Maoazine/Print Media 15 24o/o 48 15%63 170h
Familv/f riends/word-of -mouth 11 17o/o 28 9o/o 39 10o/o
Retailer/Store [i.e. Sears. Best Buvl 0 0o/o 21 7%21 6Yo
Rockv Mountain Power Web site 0 0o/o 7 2%7 2o/o
lnternet Advertisino/ Online Ad 2 3Yo 3 1%5 10h
Direct mail brochure 1 ZYo 4 1%5 10h
Radio 0 }Yo 4 1%4 1o/o
Hockv Mt. Power Representative 0 1Yo 2 1o/o 2 1o/o
Other 2 3%3 1%5 1o/o
Don't know 7 11%44 140/o 51 14o/o
63 100%310 100%373 100%
The Cadmus Group, lnc. / Energy Services 23
Rocky Mountain Power
Roclly Mountain Power
Exhibit No. 5 Page 29 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
September 22,2010
Respondents were asked to describe the working condition of their recycled appliances. As
shown in Table 21, about 69%o indicated the refrigerator or freezer recycled was still in good
physical condition or needed minor repairs, and25oh said the appliance had some problems.
However, 2l respondents (6%) stated that their appliances did not work (which if true made
them ineligible to participate). This issue is discussed fuither in the Stakeholder Interview
Findings below'
Tabre 222 condition of Recycred Appriance
Freezer Refriqerator Total
n Percent Besoondino n Percent Resoondino n Percent Resoondino
ln qood condition 28 45%111 36%139 38%
Needed minor repairs 24 39%92 30%116 310/o
Had some problems 8 130/o 85 280/o 93 250k
Didn't work 2 3%19 6Yo 21 60/o
Total 62 100%307 100%369 100%
Reason and Timing for Recycling
The r.najority of participants, 62Yo, considered disposing of their appliances prior to hearing
about the program. In fact, 77o/o of participants said they were not only considering the option,
but would have removed the appliance had the program not been available.
The primary driver for recycling the appliance was they had a brand new appliance to replace it.
The second reason given was they no longer wanted the appliance, and had no need to replace it
(see Table 22). Qualitatively, many of these respondents said the appliance was old, and they no
longer needed it.
Table 23: Reason for Recycling Appliance
As shown in Table 23, respondents identified the incentive (cash), convenience, and free pickup
as the main reasons they chose to recycle the appliance through the program. Together, these
three responses repres ented 86Yo of the input received. Other reasons for participating in the
Program included: environmental benefits, it was the only program known, and utility
sponsorship.
The Cadmus Group, lnc. / Energy Services 24
Freezer Refriqerator Total
n
Percent
Resoondino n
Percent
Resoondino n
Percent
Resoondino
Brand new aooliance to reolace it 37 60%229 75%266 72o/o
No longer wanted appliance w/o
reolacement 22 35Yo 50 16%72 200/o
Used aooliance to reolace it 3 5o/o 28 9Yo 31 8%
Total 62 100%307 100%369 100%
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 30 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Table 24:M.ain Reason for Choosing Program over Other Disposal Options
Freezer Refrioerator Total
n Percent Resoondino n Percent Resoondino n Percent Resoondino
Cash 23 37o/o 138 45o/o 161 430/o
Convenient 16 25%84 27%100 270h
Free oick-uo 12 l90h 47 1SYo 59 160h
Good for environment 6 100h 17 60/o 23 6Yo
Other 6 10o/o 23 7%29 8Yo
Total 63 100%309 100%372 1000/o
Although cash was mentioned more frequently than other reasons, many participants (66%) told
us they still would have participated in the program had the $30 per appliance incentive not been
available. As noted earlier, 82Yo told us they would have participated with a lower incentive.
The convenience of using the program and free appliance pickup were the next most frequently
mentioned reasons. They saw these program aspects as valuable benefits, as many would have
had to pay to have the appliance recycled.
Energt-Saving Kits
When participants were asked whether a "free kit containing CFL light bulbs and energy
information given to you at the time of pickup?", only 60oh said yes. The rest were split between
no (20%) and don't know (19%). Of participants that recalled the kit, 76oh ruted the kit as very
useful (a rating of 7 or higher on a 1 to 10 scale).
Recommende d Improvements
When asked how they would improve the program, TTyo of participants said they had no
suggestions, and many added they were satisfied with the program. This and the other responses
to this survey question are summarizedinTable24.
The next most frequent responses were suggestions to improve the pick-up service, with most of
these focusing on the length of time they waited for pick-up after contacting the program. Other
suggestions for improvements are shown in the table.
Overall, the responses were consistent with the high satisfaction levels reported above.
Table 25: Participants recommended improvements
Freezer Refriqerator All Resoonses
Frequencv Percent Frequencv Percent Frequencv Percent
Satisfied. No suooested imorovements 48 76%240 77%288 770h
lmprove pick up 6 10o/o 17 5o/o 23 6%
lnclude other/nonworkino aooliances 2 3o/o 15 5o/o 17 5%
lncrease marketino 1 2o/o 14 5o/o 15 4Yo
Use a shorter survey 3 5%I 3Yo 12 3Yo
lncrease incentive 1 ZYo 10 30h 11 3%
Other 2 3Yo 5 2Yo 7 2%
Total 63 100%310 100%373 100%
The Cadmus Group, lnc. / Energy Services 25
Rocky Mountain Power
Rodry Mountain Power
Exhibit No. 5 Page 31 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Stakeholder I nterview Findings
Turnkey program. Rocky Mountain Power values this program because it is cost-effective, the
concept is sound, and the implementer has been able to manage many program aspects.
Running smoothly. Both Rocky Mountain Power and JACO representatives reported the
program functions smoothly at present. Neither had concerns they felt needed to be addressed
through changes in the program or its processes.
Quality Assurance and Quality Control. Rocky Mountain Power has dedicated resources to
monitor the implementation contractor and occasionally to help resolve issues when they arise
between the freld teams and program participants. The evaluators interviewed two of these
employees who provide these functions for Washington, Idaho, and Utah. From these interviews,
it is clear that they are consistently implementing a QA/QC process for the utility that includes:
o Follow-up calls. The QA/QC people contact about 5o/o of the program participants by
telephone to check their experience with the program. Typically, they contact participants
who had an appliance picked up within the last 4-6 weeks. Responses are recorded in an
excel spreadsheet and provided to the Program Manager. Their brief telephone survey
includes the following points:
o How they heard about the program
o Experience with the Call Center
o Experience with the pick up
o Whether they had received their incentive check and how long it took
o Whether they had received their energy-saving kit, and
o Other comments.
o Site Audits. In addition to the telephone surveys, these employees meet the field teams at
selected sites again targeting about 5Yo of the program pickups for this monitoring. The
QA/QC people obtain the schedule for each field team for a given day and then arrive at
the first pick up location before the JACO team. They check that the field teams follow
the defined procedures which include the following points. The field staff document what
they observe and provide a subset of the recorded data to the Program Manager.
o Crews start the day on time. There is sometimes a temptation to start earlier but
the program policy is to start the day no earlier than 7:50 am
o Crews are courteous to every residential customer and
o AU appliances picked up pass the standard test for functionality
Appliance Age. The QA/QC staff and JACO staff described the determination of age as follows:
the JACO field teams use the nameplate to determine age whenever possible. In many cases,
nameplates do not include a date of manufacture. In these cases, JACO staff estimate the age.
According to JACO's management in Utah, the insulating material in each appliance can be used
to place the appliance in one of three age groups:
o Fiberglass insulation was only used up until 1975 and indicates an appliance that is at
least 35 years old
26The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 32 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
September 22,2010
o CFC-I1 insulation was only used from 1975 until 1995
o Foam insulation other than CFC-I1 indicates that an appliance was manufactured more
recently than 1995.
The timing of these changes in manufacturing methods has been independently validated. Once
an age group has been determined, the JACO staff use additional clues such as the appliance's
design, style, and color to refine their estimate. Although the age thus determined is an
approximation, the evaluation takes a conservative approach to appliance age as described in the
Impact Evaluation above (maximum age for energy consumption is 32 yea"rs or 1978 since that is
the extent of the available data from manufacturers). Since this approach tends to reduce the
average appliance age used in the analysis, it is unlikely that the estimation of age is resulting in
a significant overstatement of program savings.
Monthly Program Meetings. It has been the practice of the Program Manager to meet regularly
with the JACO Operations Manager to check in on recent program activities. This provided an
opportunity for the Program Manager to relay any issues discovered through the QA/QC
processes. The JACO manager found this to be a valuable meeting and the evaluators agree that
it should be continued.
Functionality of recycled appliances. As shown in Table 2l above, 6oh of participants reported
the machine they recycled was not in working condition. However, all participants had described
their appliances as functional when they contacted the Call Center to arrange for a pick up.
Further, the field crews follow specific procedures to ensure that every appliance picked up is
functional. Given these apparently conflicting pieces of information, the evaluators reviewed the
field procedures with staff at JACO and with the QA/QC staff people.
At each site, the JACO team does a functionality check. This check consists of plugging in the
appliance and verifying that it is functional by one of the following standards
o Compressor motor runs. Appliance interior is felt to be cool/coldo Refrigeration coils are felt to be warm
In practice, the functionality check is limited by a number of considerations. Since an appliance
can be left outdoors for pick up, the program does not require that they be plugged in when the
JACO team arrives, only that a powered outlet (or extension cord) be available. In these cases,
the JACO team plugs in the appliance and uses the compressor motor test as the primary check.
If the compressor runs, the appliance will almost certainly be judged to be functional and picked
up. This is dictated to some extent by the time available to the JACO teams at each site.
According to the utility QA/QC people, the JACO team is typically at a particular site for
approximately ten minutes. Teams are scheduled to pick up appliances at many sites in a day (15
or more in some cases) and often in widely separated sites, which requires minimizing the time
spent at each site.
Another reason for the compressor test to be the primary hurdle can be weather conditions. If an
appliance is left outdoors and the outdoor temperature is cool or cold, it is difficult for the field
team to determine whether the appliance is cooling since the interior is already cold. In such
cases, it can be difficult to get the compressor to start even if the appliance is functional.
The Cadmus Group, lnc. / Energy Services 27
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 33 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
It must be noted that JACO and the QA/QC staffreport that there are appliances that can not be
shown to be functional and so are not picked up.
Summary
o All appliances that are picked up have been tested and shown to be functional according
to the defined procedures.
o The survey results are inconclusive. Future surveys should probe further when a
respondent reports that the appliance didn't work.
. Field procedures include disabling each appliance during the pick up (cord is cut, door
seals are disabled, and controls are disabled) which precludes any further testing.o Until additional information becomes available, no program changes are recourmended.
28The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 34 of 1 365
Case No. PAC-E-14-07
Wlness: Kathryn C. Hymas
September 22,2010
5. Cost-Effectiveness
To assess cost-effectiveness, evaluators conducted an analysis ofprogram costs and benefits
from four perspectives, using Cadmus' DSM Portfolio Pro model. These perspectives include:
l. PacifiCorp Total Resource Cost Test (PTRC): This test examines progftrm benefits
and costs from Rocky Mountain Power's and Rocky Mountain Power customers'
perspectives, combined. On the benefit side, it includes avoided energy costs, capacity
costs, and line losses plus a l0% adder to reflect non-quantified benefits. On the cost
side, it includes costs incurred by both the utility and participants.
2. Total Resource Cost Test (TRC): This test examines program benefits and costs from
Rocky Mountain Power's and Rocky Mountain Power customers' perspectives,
combined. On the benefit side, it includes avoided energy costs, capacity costs, and line
losses. On the cost side, it includes costs incurred by both the utility and participants.
3. Utility Cost Test (UCT): From Rocky Mountain Power's perspective, benefits are
avoided energy and capacity costs and line losses. Costs include any program
administration, implementation or incentive costs associated with funding the program.
4. Ratepayer Impact (RIM): All ratepayers (participants and nonparticipants) may
experience an increase in rates to recover lost revenue. This test includes all Rocky
Mountain Power pro$am costs as well as lost revenues. As benefits, this test includes all
avoided energy costs, capacity costs, and line losses.
5. Participant Cost Test (PCT): From this perspective, program benefits include bill
reductions. Costs include any customer contribution to the measure cost.
Table 25 summarizes the components of the four tests.
Table 26: Benefits and Costs Included in Various Tests
Test Benefits Costs
PTRC Present Value of Avoided Energy and Capacity Costs
with 10% Adder for Non-quantified Benefits
Program Administrative and Marketing Cost +
Participant Cost
IRC Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost +
Particioant Cost
UCT Present Value of Avoided Energy and Capacity Costs Program Administrative, Marketing and
lncentive Cost
RIM Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost +
Present Value of Lost Revenues
PCT Present Value of Bill Savings Participant Share of Measure Cost
Table 26 provides selected inputs to the cost analysis. These include the evaluated energy
savings for each year (from Table l8 above), discount rate, line loss, and progftrm costs. Other
than the energy savings, these values are provided by Rocky Mountain Power. The discount rate
is from Rocky Mountain Power's 2008 Integrated Resource Plan. Rocky Mountain Power also
provided the values for line loss and the program costs. The implementation cost is the amount
Rocky Mountain Power paid to JACO, the implementing contractor, plus the cost of the energy-
The Cadmus Group, lnc. / Energy Services 29
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 35 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
September 22,2010
saving kits. Incentives normally offset some of the measure cost, leaving a net participant share
of the measure cost. This program has no measure costs, however, so the incentives are treated as
a benefit in the participant test.
Program benefits are comprised of energy savings and their associated avoided costs. The energy
savings used in the cost-effectiveness analysis are the evaluated kWh from this study.
For recycled refrigerators and freezers, the analysis used a measure life of five years, based on
Califomia's Database for Energy Efficient Resources (DEER 2008 for 06-07 Updates3). This is a
reduction from the measure life of eight years used in prior evaluations. For refrigerators, a five
year measure life is conservative compared to the six year measure life adopted by the Regional
Technical Forum (RTF).
For CFLs, the analysis used a measure life of 6.6 years. This value is also from DEER 2008 and
represents the expected life for an interior CFL with a nominal 10,000 hour life. This is a
reduction from the measure life of nine years used in prior evaluations. For CFL measure life,
DEER and RTF are nearly identical as both based their current values on work presented at the
2008 ACEEE Summer Study and on other common sources
Table 27,Table 28, and Table 29 present the results of the cost-effectiveness analysis for the
Program in 2006, 2007 , and 2008 respectively. Table 3 0 depicts the analysis for the three years
combined. All analyses are based on the Rocky Mountain Power 2008 IRP 46% Eastside
Residential Whole Home Decrement. l8
'8 IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan Vol. II Appendices:
lrttp:iiu,r,r,u,.fracificorD.conri contentidam,/pacificorpidoc,/EnvironrrrentiEnvironinental_Concernsilntegtated-Iteso
urce-Pl*nnine 6.pcl!:
30
Table 27: Selected Cost Analysis Inputs
lnput Description 2006 2007 2008
Net Proqram Savinqs (kWh/vear)706,483 546,312 567,351
Discount Rate 7.40o/o 7.40%7.400/o
Line Loss 11.39%11,39%11.39%
Proqram Costs
lmolementation Cost $93,246 $ 83,536 $ 8t,ozz
lncentive Costs $ 31,760 $25,279 $20,970
Utility Administrative Costs $ 17,998 $ 14,51 5 $ 11,254
Total Proqram Costs $ 143,004 $ 123,330 $ 113,296
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 36 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Table 28: Program Cost-Effectiveness Summary for 2006 - IRP 46yoLF Decrement
Cost Etfectiveness Test Levelized
$/kwh Costs Benefits Net
Benefits
Benefit
/ Cost
Ratio
Total Resource + Conservation Adder (PTRC)$0.032 $111,244 $247,418 $136,174 2.22
Total Resource No Adder ffRC)$0.032 $111,244 $224,925 $1 13,681 2.02
Utility (UCT)$0.041 $143,004 $224,925 $81,921 1.57
Ratepayer lmpact (RlM)$0.107 $371,904 $224,925 -$146,979 0.60
Participant (PCT)NA $0 $260,660 $260,660 NA
Lifecvcle Revenue lmoact $0.00001 000
Table 29:Program Cost-Effectiveness Summary for2007-lNP 46oh LF Decrement
Cost Etfectiveness Test Levelized
$/kwh Costs Benefits Net
Benefits
Benefit /
Cost
Ratio
Total Resource + Conservation Adder (PTRC)$0.036 $98,051 $199,0s2 $101,001 2.03
Total Resource No Adder fiRC)$0.036 $98,0s1 $180,957 $82,906 1.85
Utility (UCT)$0,04s $123,330 $180,957 $57,627 1.47
Ratepayer lmpact (RlM)$0.117 $318,292 $180,957 -$137,336 0.57
Particioant {PCT)NA $0 $220,241 $220,241 NA
Lifecycle Revenue lmpact $0.00000925
Table 30: Program Cost-Effectiveness Summary for 2008 - IRP 46o/"LF Decrement
Cost Etfectiveness Test Levelized
$/kwh Costs Benefits Net
Benefits
Benefit/
Cost
Ratio
Total Resource + Conservation Adder (PTRC)$0.033 $92,326 $202,975 $110,649 2.20
Total Resource No Adder (TRC)$0.033 $92,326 $184,523 $92,1 97 2.00
Utility (UCT)$0.04 $1 13,296 $184,523 $71,227 1.63
Ratepayer lmpact (RlM)$0.1 16 $325,833 $184,523 -$141,310 0.57
Particioant (PCT)NA $o $233,507 $233,s07 NA
Lifecycle Revenue lmpact $0.00000942
Table 31: Program Cost-Effectiveness Summary across 2006-2008 - IRP 46ohLF
Decrement
Cost Etfectiveness Test Levelized
$/kwh Costs Benefits Net
Benefits
Benefit /
Cost
Ratio
Total Resource + Conservation Adder (PTRC)$0.034 $282,581 $608,723 $326,1 43 2.15
Total Resource No Adder (TRC)$0.034 $282,581 $553,385 $270.804 1,96
Utility (UCT)$0.042 $356,058 $553,385 $197,327 1.55
Ratepayer lmpact (RlM)$0.1 13 $950,745 $553,385 -$397,360 0.58
Particioant (PCT)NA $0 $668,1 65 $668,1 65 NA
Lifecvcle Revenue lmoact $0.0000204s
The Cadmus Group, lnc. / Energy Services 31
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 37 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
September 22,2010
Because there are no participant costs for this program, discounted participant payback, the
number of years necessary for participants to recuperate their costs through the present value of
anticipated energy savings, is not reported.
The Cadmus Group, lnc. / Energy Services 32
Rocky Mountain Power
Roclry Mountain Po\ /er
Exhibit No. 5 Page 38 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
September 22,2010
6. Conclusions
The following conclusions are based on findings presented in the previous chapters.
Conclusions
o Program participation has fallen from nearly 800 appliances recycled per year in 2006 to
under 700 appliances recycledin200T and 2008.
. Freeridership determined using the survey-based scenario analysis was about 44%o for
refrigerators and freezers, which is consistent with other appliance recycling programs
including the most recent California statewide evaluation as noted above. (This is the sole
basis for the NTG ratios, which are therefore about 56%.)
o Participants have been very satisfied with the program, virth92% giving the program
high scores and92oh very likely to recommend the program to family and friends.
Consistent with high satisfaction,TTyo had no suggestions for ways to improve the
progfilm.
o Rocky Mountain Power and JACO are both satisfied with the program. All parties feel
the program runs well.
. The progftrm was found to be cost-effective in all three years.
o The progftrm is well established and we have no recommendations for modification.
The Cadmus Group, lnc. / Energy Services 33
Rodq Mountrain Po\irer
Exhibit No. 5 Page 39 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 40 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Appendix A: Participant Suruey lnstrument
PARTICIPANT SURVEY - SEE YA LATER, REFRIGERATOR@ - APPLIANCE
RECYCLING PROGRAM
Hello, my name is from Discovery Research Group. I'm calling on behalf of:
[Utah or Idaho]: Rocky Mountain Power
[Utah]: Pacific Power
I am calling to ask you some survey questions about the See ya later, refrigerator& recycling program. Please be
assured this is not a sales call. My questions are for research purposes only. We are interested in your opinions to
help improve our programs, and understand how to assist customers in saving money on their utility bills. Your
individual answers will be used by [Rocky Mountain Power, Pacific Power] to evaluate energy efficiency
programs. [If Respondent asks how long, say]: "Less than l5 minutes."
SCREENING QUESTIONS
These questions screen or qualifu the Respondents to ensure that results are comparable across Respondents and that
potential biases are avoided. The specific checks include the following:o Respondent is the same person that contacted Rocky Mountain PowerlPacific Power about the
program
r The appliance was removed from a primary residence where Rocky Mountain Power/Pacific Power is
the electric utilityo Respondent is not a professional market researchero Respondent is not a utility employee
"Now, I need to ask a few screening questions.
l. According to our records, someone in your household contacted [Rocky Mountain Power, Pacilic
Powerl to participate in [Rocky Mountain Power, Pacific Power]'s "See ya later, refrigerator(D"
recycling program. Are you that person?
a. Yes [Go To 3]b. No
98. Don't know99. Refused
2. Is that person available to speak with?
a. Yes, [Continuelb. No, [Arrange Callback]
98. Don't know
99. Refused
[If "No - Not a convenient time," ask if Respondent would like to 1. Start now and do part of the survey, or 2.
Arrange a more convenient time we can call them at home. Emphasize thatl:
66It is important for [Rocky Mountain Power, Pacific Powerl to include your opinions in this study so they can
serve your needs better.t'
3. Which power company provides electric power to your home or primary residence?a. Rocky Mountain Power/Pacific Power
The Cadmus Group, lnc. / Energy Services 35
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 41 of 1 365
Case No. PAC-E-I4-07
Vvitness: Kathryn C. Hymas
September 22,2010
Other [Terminate]
Don't know [Terminate]
Refused [Terminate]
[Note: If Respondent has more than one home and uses Rocky Mountain Power/Pacific Power AND another
company, ask]:
"Which utility serves your primary residence in Utah/Idaho/Utah?"
Uf NOT Rocky Mountain Power/Pacific Power, Terminate and Tally.l
VERIFICATION
4. Program records indicate that you received an incentive for having [QUANTITY] [Refrigerator(s),
Freezer(s)l disposed ofby the recycling program around [Date of pickup]. Is this the correct quantity
you recall being picked up by the recycling program? [Record I number.]
MEASURES Response IF QUANTITY
DIFFERENT, Record
NUMBERHERE
A.
1l
IQUANTITY, product type 0l Yes02 No98 Don't know99 Refused
B. [QUANTITY, product type
2l
01 Yes02 No98 Don't know99 Refused
AWARENESS AND PURCHASE INFORMATION
5. How did you fust learn about [Rocky Mountain Power, Pacific Power] 's appliance pick up and
recycling program? [PROBE: Did you hear about the program from any other sources?] [Do not
read list, record one number only.]
a. Newspaper I Magazine/PrintMedia
b. Billlnserts/Contact
c. [Rocky Mountain Power, Pacific Power] Web site
d. Other Web site [If yes, which Web site[s]? _Ie. Internet Advertising/ Online Ad
f. Family/friends/word-of-mouthg. [Rocky Mountain Power, Pacific Power] Representative
h. Radioi. TVj. Billboard/outdooradk. Direct mail brochure
l. Realtor
m. Home Builders
n. Other newslettero. Retailer/Store [i.e. Sears, Best Buy, Ace Hardware]
p. Sporting event
q. Home Shows/Trade Shows
r. Appliance Recycling Contractor
b.
98.
99.
36The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 42 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
September 22,2010
s. Other [specifu, record verbatim]
98. Don't Know
99. Refused
6. How does your household tlpically learn about energy effrciency opportunities? [Do not read, prompt
if necessary. Check all that apply and record verbatim.la. Newspaper / Print Media
b. Equipment Vendor Phone callsc. Utility Bill Inserts
d. Utility Websitee. Other Web site [If yes, which Web sites?]
f. Presentations
g. Trade Shows
h. Retail stores [e.g., Sears or Best Buy]
i. Home showsj. Direct mail
k. Friends and family
l. Radio
m. TV
n. Other, [Specify]o. None, have not learned ofany energy efficiency oppornrnities
7 . Which of the information sources that you just named do you rely on the most to gather information
about energy efficient ways to save? [Do not read, prompt if necessary. Check all that apply and
record verbatim.la. Newspaper / Print Mediab. Equipment Vendor Phone callsc. Utility Bill Insertsd. Utility Websitee. Other Web sites [If yes, which Web sites?]f. Presentationsg. Trade Showsh. Retail stores [i.e. Sears or Best Buyli. Home showsj. Direct mailk. Friends and familyL Radio
m. TV
n. Other, [Specify]
8. How would you rate your current understanding of energy efficiency technologies? I'm going to read a
list and I'd like you to tell me which are true for you? Would you say you: [Read full list, check all
that apply.l
a. Have no knowledge of energy effrcient technologiesb. Are just getting started.
c. Have done some research to understand how energy use affects your bills.d. Have done some research to understand how energy efficient technologies or equipment work.
e. Have installed some energy efficient appliances or equipment.f. Which ones?g. Have installed all possible cost effective energy efficient appliances or equipment at my home.
a. Which ones?
98. Don't Know
99. Refused
The Cadmus Group, lnc. / Energy Services 37
Rocky Mountain Power
Roclly Mountain Power
Exhibit No. 5 Page 43 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
I APPLIANCE DESCRIPTION
9. ASK rF IQUANTITY] :1
Now I'm going to ask you some specific questions about the [Refrigerator, Freezer] that was picked up
and recycled.
During the time just before you decided to get rid of the [Refrigerator, Freezer], was it being used as your
main [Refrigerator, Freezer], or had it been a secondary or spare?
[Interviewer: a main refrigerator is typicatly in the kitchen, a secondary or spare is usually kept
someplace else and might or might not be running. If the person recently bought a new main
refrigerator and was just waiting for the old one to be picked up, it should be classified as "main."]
a. Mainb. Secondary or Spare
98 Don't Know
99 Refused
10. ASK rF [QUANTITY] > I
The rest of the survey focuses on just one appliance. Since you mentioned that you had more than one
appliance recycled through the program, we would like you to select just one of them and then answer the
rest of the questions about it.
Can you tell me which of the [refrigerator(s), freezer(s)] you've selected?
During the time just before you decided to get rid of this [reiterate which of the multiple units was
selected] refrigerator/freezer, was it being used as your main [Refrigerator, Freezer], or had it been a
secondary or spare?
[Interviewer: a main refrigerator is typically in the kitchen, a secondary or spare is usually kept
someplace else and might or might not be running. If the person recently bought a new main
refrigerator and was just waiting for the old one to be picked up, it should be classified as "main."]
a. Main
b. Secondary or Spare
98 Don't Know
99 Refused
IF 9 or 10: b ASK 11
I 1. How long had it been a secondary or spare? [Get months or years] [If Respondent is confused,
reinforcel: "How long had it been a spare @?"
a. Months _ 11-111b. Years _ [1-50, Half :0.5]
98 Don't Know
99 Refused
12. Thinking about the flast 12 months [IF I YEAR OR MOREI/months [ALL OTHER]I you had it as
a spare prior to getting it picked up, was it plugged in and running ...
a. All the timeb. For special occasions only
The Cadmus Group, lnc. / Energy Services 38
Rocky Mountain Power
Rocky Mountain Porer
Exhibit No. 5 Page 44 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
September 22,2010
During certain months of the year only, or
Never plugged in or running
Don't Know
Refused
Ask 13 only if 12: b or c
13. IF you were to add up the total time it was running as a spare in the last 12 months, how many months
would that be? Your best estimate is okay. [Get nearest month or half monthl
a. MONTHS [1-11, half :0.5]
b. All the time98 Don't Know99 Refused
14. Where was it located?
Kitchen
Garage
PorcMPatio
Basement
Other [Specifyl
Don't Know
Refused
15. Was the location heated?
a. Yesb. No98 Don't Know99 Refused
16. Was the location air-conditioned?
a. Yesb. No98 Don't Know99 Refused
17. Did you decide to get rid of it because you. . . [Readl
a. Got a brand new [Refrigerator, Freezerl to replace itb. Got a used [Refrigerator, Freezer] to replace itc. Or to get rid of a [Refrigerator, Freezer] you no longer wanted without replacing it [Go To 19198 Don't Know [Go To f 9l99 Retused [Go To 19]
18. Is the [Refrigerator, Freezer] you are replacing it with ENERGY STAR labeled?
Yes
No
Don't Know
Refused
c.
d.
98
99
a.
b.
c.
d.
98
99
a.
b.
98
99
The Cadmus Group, lnc. / Energy Services 39
Rocky Mountain Power
Roclq Mountain Power
Exhibit No. 5 Page 45 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Had you already considered disposing of this [Refrigerator, Freezerl before hearing about [Rocky
Mountain Power, Pacific Powerl 's appliance recycling program? By dispose we mean getting rid of
it either by selling it, giving it away, having someone pick it up, or taking it to the dump or a recycling
center.
Yes
No
Don't Know
Refused
Without the [Rocky Mountain Power, Pacific Powerl Refrigerator Recycling program, what would
you most likely have done with your old [Refrigerator, Freezer]? [Read]
Gotten rid of it
Kept it
Don't Know
Refused
IASK IF 20:al How soon would you have disposed of your old [Refrigerator, Freezer]?
have disposed of it within a year of when the Program took it, or more than a year later?
Would you
a. Within a year of when the program took itb. More than a year later98 Don't Know99 Refused
22. What was the condition of this appliance? Would you say [Read list, record one response only.]
It worked and was in good physical condition
It worked but needed minor repairs [example: door seal or handle]
It worked but had some problems [example: it wouldn't defrost]
Or, it didn't work [Go To 241
Don't Know
Refused
IIF 20=bl If you had kept the [Refrigerator, Freezer], would it have been used full time as either
your primary unit or a spare, stored unplugged, or used occasionally [example: at holidays]? [Do not
read, if needed only]: "Your best estimate is fine."
Used full time
Store it unplugged
Use it occasionally
Don't Know
Refused
CONSIDERATION OF ALTERNATIVES
24. I am now going to read a list of alternative ways that you could have disposed of this appliance. For
each, tell me if this is a method you had considered using or doing. [Programmer: Item E only if 17=
a OR b. Randomize a-i. Always place i and j last.l
a. Sell it to a private party, either by running an ad or to someone you know
b. Sell it to a used appliance dealer
c. Give it away to a private party, such as a friend, relative, or neighbor
d. Give it away to a charity organization, such as Goodwill Industries or a church
a.
b.
98
99
20.
a.
b.
98
99
a.
b.
c,
d.
98
99
a,
b.
c.
98
99
The Cadmus Group,/ Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 46 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
September 22,2010
e. Have it removed by the dealer you got your new or replacement appliance fromf. Haul it to the dump yourself and pay the disposal feeg. Haul it to a recycling center yourself and pay the disposal feeh. Hire someone else haul it away for junking or dumping
i. Keep itj. Or something else I've not mentioned
For Each:
0l Yes - considered using/doing
02 No -did not consider or did notknow about98 Don't Know
99 Refused
Katie will add a question: which one of these would have been the most likely method
ASK 25 lF 24a= 0l or 24b = 0l
25. Why did you not follow through with your consideration to sell the [Refrigerator, Freezer]?
a. Couldn't find an interested dealer/non-dealer at the price I wanted
b. Couldn't find an interested dealerinon-dealer because of the unit's condition
c. Decided recycling unit was more important than selling it
d. Other [Specify : I98 Don't Know
99 Refused
ASK 26 IF 24e:01
26. lf an appliance dealer were to take it away, how much, if anything, do you think you would have to pay
for this service?
a. Nothing / Free Serviceb. Dollars [$1 - $2000]
98 Don't Know
99 Refused
ASK 27IF 24h:01
27. lf you were to hire someone else to haul it away for junking or dumping, how much, if anything, do you
think you would have to pay for this service?
a. Nothing / Free Serviceb. Dollars [$1 - $2000]98 Don't Know99 Refused
ASK 28 and 29 lF 24t : 0l or 24g : 91
28. One factor in disposing of an appliance is being able to physically move and transport it. You
mentioned earlier that you considered hauling the [Refrigerator, Freezerl to the dump or recycling
center yourself. Do you or someone in your immediate family have the ability to do this or would you
have needed assistance such as renting or borrowing a truck?
The Cadmus Group, !nc. / Energy Services 41
Rocky Mountain Power
Roclq Mountain Power
Exhibit No. 5 Page 47 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
September 22,2010
Yes, could do it myself
Would need assistance
Don't Know
Refused
Most garbage dumps and recycling center charge a fee of at least $25 to dispose of a refrigerator or
freezer due to requirements that coolant and oil be collected and disposed of in an environmentally safe
way. Were you aware that you would have to pay a fee of at least $25 at the dump or recycling center
and would you have paid it?
Yes, I would have paid the fee
No, I wouldn't pay
Don't Know
Refused
ASK 30 lF 24c= 01 or 24d = 0l
You mentioned earlier that you considered giving the [Refrigerator, Freezer] away to a private party,
such as a friend, relative, or neighbor or to a charity. Did you identifu and contact a specific person or
charity to give the [Refrigerator, Freezer] to?
Yes
No
Don't Know
Refused
3 I . Now that you have considered some additional factors involved in keeping or disposing of your old
[Refrigerator, Freezer], what you would have most likely done if you had not disposed of it through
the [Rocky Mountain Power, Pacific Power] 's program. You said you would have [Insert most
Iikely method answer from 241. Is this still what you would have been most likely to do or something
else? [Probe if something else]: "What would you have done?'n [Read list only if needed]
a. Sold it to a private party, either by running an ad or to someone you know
b. Sold it to an used appliance dealer
c. Given it away to a private party, such as a friend or neighbor
d. Given it away to a charity organization, such as Goodwill Industries or a churche. Had it removed by the dealer you got your new or replacement appliance from
f. Hauled it to the dump yourself and pay the disposal feeg. Hauled to a recycling center yourself and pay the disposal fee
h. Had someone else pick it up for junking or dumping
i. Kept itj. Some Other Way [Specify]98 Don't Know99 Refused
32. What is the MAIN reason you chose this service over other methods of disposing of your appliance? [If
multiple are mentioned, ask]: 6'Of those, which is the main reason?n' [Do not read, accept one
answer only.]
[If Respondent says: "I didn't need or want the refrigerator," re-ask the question.]
a. Cash/incentive payment
b. Free pick-up service/others don't pick up/don't have to take it myselfc. Environmentallysafedisposal/recycled/goodforenvironment
d. Recommendation of a friend/relative
a.
b.
98
99
29,
a.
b.
98
99
30.
a.
b.
98
99
The Cadmus Group, lnc. / Energy Services 42
Rocky Mountain Power
Rocky Mountiain Po\ rer
Exhibit No. 5 Page 48 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
September 22,2010
Recommendation of retailer/dealer
Utility sponsorship of the program
Easy way/convenient
Never heard ofany others/only one I know of
Other [Specify]
Don't Know
Refused
33. Would you have participated in the program without the incentive check?
Yes
No
Don't Know
Refused
CFL INSTALLATION
34. Was a free kit containing CFL light bulbs and energy information given to you at the time of pickup?
a. Yesb. No IGo To 40]98 Don't Know I Go To 40199 Refused I Go To 401
35. On a scale of I to 10, with l0 being the very helpful, how would you rate the information found in this
kit?
Score l-10 _
Don't Know
Refused
36. Why did you assign this rating? [Do not prompt]
a. Information too general
b. Already aware of informationc. Information did not apply
d. Used the suggestions provided in informatione. Wriffen well
f. Passed information along to othersg. Other, Record _98 Don't know
99 Refused
37. Did you install the CFLs that came in the kit?
a. Yes, One of them [One of]b. Yes, Two of themc. No
98 Don't know
99 Refused
ASK 38 IF 37= a OR c
38. Why didn't you install [One of] the CFLs?a. Did not fit fixtures
e.
f.
ob'
h.
i,
98
99
a.
b.
98
99
a.
98
99
43The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 49 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
b. Intend to install later
c. Do not like styled. Do not like quality
e. Defective productf. Other, Record98 Don't Know99 Refused
ASK 39 IF 37: a OR b
39. Where did you install the CFL[s]?
a. Living room
b. Master bedroom
c. Other bedroom
d. Kitchen
e. Bathroom
f. Garage/storage
C. Outsideh. Other, Record98 Don't know99 Refused
SPILLOVER AND MARKET IMPACT
40. Since participating in the appliance pick-up and recycling program, have you participated in any other
progrcms offered by [Rocky Mountain Power, Pacific Powerl?a. Yesb. No [Go To 42198 Don't Know [Go To 42]99 Retused [Go To 42]
4l. Which programs did you participate in? [Record]
A
98 Don't Know99 Refused
42. On a scale from l-10 where I is not at all important and 10 is very important, how important or
influential was you participation in the recycling program in your decision to participate in other
[Rocky Mountain Power, Pacific Powerl energy efficiency programs?
A
98 Don't Know99 Refused
43. Besides recycling your old [Refrigerator, Freezerl, have you made other energy efficiency
improvements or purchases on your own without any assistance from a utility or other energy
organization?a. Yesb. No [Go to 46]98 Don't Know [Go to 46]
99 Retused [Go to 46]
44. What did you install? [Do not prompt]a. High efficiency dishwasherb. High efficiency washerc. High efficiency dryer
The Cadmus Group, lnc. / Energy Services 44
Rocky Mountain Power
Roclry Mountain Polr,er
Exhibit No. 5 Page 50 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
d. High efficiency refrigeratore. High efficiency water heaterf. CFLs [Compact Fluorescent Light bulbs or curly bulbslg. Other, [Record Responsel
45. On a scale from 0- I 0, with 0 indicating that you strongly disagree, and 1 0 indicating that you strongly
agree, please rate the following statement: "My experience with the See ya later, refrigerator@ program
influenced my decision to install other high efficiency equipment on my own."
a. Rating
98. Don't know
99. Refused
PROGRAM SATISFACTION
"I'd like to ask about your satisfaction with the program.'o
46. On a scale of 0 to 10, with 0 being not satisfied, and 10 being very satisfied, how satisfied are you with
the Rocky Mountain Power/Pacific Power Appliance Recycling Program overall?
a. Rating [If > 4, Go To 48]
98 Don't know
99 Refused
47. For what reason do you give it that rating?? [Do not read; mark all that apply]
a. [Record Response-Use below for codel
l. Incentive was too small.
2. Contractor never called me back.3. Contractor never showed up/showed up late.
4. Contractor was unreliable/unprofessional.
5. Difficult to get an appointment time that was convenient for me.
6. Wanted to use a different [non-programl contractor.7. Other [Record Responsel
98 Don't know
99 Refused
48. Would you have participated in the program if the amount of the rebate had been less?
a. Yes
b. No
98. Don't know
99. Refused
49. On a scale of 0-10, where 0 is not at all likely and l0 is very likely, how likely are you to recommend
the [Rocky Mountain Power, Pacific Power] Appliance Recycling Program to friends and family
members?
a. Rating
98. Don't know
99. Refused
50. Is there anything you would suggest to improve the [Rocky Mountain Power, Pacific Power]
Appliance Recycling Program? [Record response]
Thank you and terminate.
This completes the survey. [Rocky Mountain Power, Pacific Power] appreciates your participation. Thanks
for your time. Have a good evening.
45The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 51 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Appendix B: Program Logic Model
PacifiCorp Refrigerator and Freezer Recycling Program Logic Model
Marketing materials
disseminated to
customeE with
workiFfl{*[igsratoc
etcJf€g*ers
m;.1
l**'*'l
f-r,":;lt**-] savinstr I
| reareo
I
Long term energy
savinos ooals are{r"{ alniiveo
PacifrCorp gains experience
deBigning and marketing prosrams
to this market segment; infoms nexl
ls:E r'r.x'l::.r'r':.:r.!l::::rr'r'r':.:.1:.:.:.:.:.:.:.:.:.llltrI:Ittlt!:ll il:t:::t:i.t.:. t:::;r:::ri:i:i:i:::::::::::::::::::::i
:1.:Ei.rs
1 Marketing and outreach lead to targeting
communications to residential customers with
ref rigerators and f reezers.
Number of eligible potential participants that express interest;
marketing materials in bill inserts, on company Web site, in
schools, in newspapers and on radio; presence at seminars,
conferences, home shows, and community events
2 lncentives lead to customers enrolling in the
pr0gram.
Number of participants; participant interviews indicate role of
incentives on enrollment activities
3 Measurement and verification lead to the
evaluation team conducting an evaluation.
Completed evaluation informs future program cycles
4 Quality control leads to inspections being
performed.
Number of inspections indicate that quality control occurred
46The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 52 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
5 The delivery of marketing materials leads to
increased customer awareness regarding energy
efficiency and the program.
lncreased customer awareness regarding energy efficiency
identified in surveys
b Marketing efforts lead to customers enrolling in
program.
Number of participants enrolled in the program who indicate they
were reached by marketing efforts
7 Customer pafiicipation results in removing
inefficient appliances from the grid,
Number of appliances recycled due to participation in the program
8 The evaluation leads to confirming program
effectiveness.
lmplementer interviews (qualitative); evaluation identifies best
practices
I lnspections and reviews leads to confirming
program effectiveness.
lmplementer interviews (qualitative); inspections and reviews
should be indicated as improving program effectiveness
10 Education leads to program awareness.Participant intervrews (qualitative) should indicate that education
led to program awareness
11 Removing inefficient appliances from the grid
leads to increased program penetration.
Number of appliances recycled compared to overall market
12 Removal of inefficient appliances leads to kWh
and kW savings.
Energyidemand savings generated expressed in kW and kWh
13 kWh and kW savings leads to persistent demand
savings.
Energy/demand savings over time; Participant interyiews
regarding measure persistence
14 Confirming effective program operations leads to
verified program savings.
lmplementer interviews (qualitative); effective program theory and
demonstrated links indicate savings are attributable to the
pr0gram
15 Confirming effective program operations leads to
the maintenance of optimum performance.
lmplementer interviews (qualitative); program operations should
be confirmed as efiective
16 lncreased program awareness leads to fewer
inefficient appliances on the grid.
lnterviews regarding awareness and resulting behavior
17 Fewer inefficient appliances on the grid lead to
persistent energy savings,
Market study/ number of appliances recycled; participant
interviews regarding measure persistence
18 Verilied program savings leads to persistent
energy and demand savings.
Energy/demand savings over time expressed in kW and kWh
19 Verified program savings leads to Rocky Mountain
Power gaining experience with designing and
marketing programs.
lmplementer interviews (qualitative); the increased experience will
be investigated
20 Maintaining optimal performance leads to Rocky
Mountain Power gaining experience with
lmplementer interviews (qualitative); increased experience will be
investigated
The Cadmus Group, lnc. / Energy Services 47
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 53 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
September 22,2010
Fewer inefficient appliances on the grid lead to
environmental benefits.
Energy/demand savings quantified using engineering estimates,
analysis of reduced need to build power plants, environmental
impacts of power plants that were not built quantified using EPA
and other secondary data
Fewer inefficient appliances on the grid lead to
achieving long term energy savings,
Energy/demand savings, analysis of reduced need to build power
plants
Persistent energy savings lead to achieving long
term energy savings.
Energy/demand savings in kW and kWh using engineering
analysis and assessed over time
Rocky Mountain Power gaining experience with
designing and marketing programs leads to
achievement of long term energy savings goals.
lmplementer interviews (qualitative); interviews will determine if
the experience is positively impacting program processes and
outcomes
48The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 54 of 1 365
Wtness: Kathryn C. Hymas
Case No. PAC-E-14-07
YffiR0CKYMOUNTATN'ffF0WER
\ A o{vrstoN 0F PActFrc0RP
Exhibit No. 5.2
Home Energy Savings Evaluation 2006-2008
Rocky Mountain Power
Exhibit No. 5 Page 55 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
x''R*NSSCAIfIVILTS
{J-S{.L} {_l}} , .[l\$il 1 "
Report
ldaho Home Energy Savings
Program
2006-2008
Prepared for:
Rocky Mountain Power
November 12,2010
Corporate Headq uar"ters:
5f V1&ter Street
Wetertown, |1A 0247?
Tel: [phone]
Fax: $17"67].7001
Arl Emptoyee-Owned Conrpony
\$, \nly\'. { Ad iii i.i Sgf L"i ir S. {O :'}*i
7?0 $W \{ashington 5t.
Suite 4S0
Portland, Oft 97?05
Teh $03.318.?ft}
Fax: [phone]
Rocky Mountain Po\irer
Exhibit No. 5 Page 56 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Prepared by:
Brian Hedman
Charlie Bicknell
Philip Sieper
Cheryl Winch
Brian Shepherd
The Cadmus Group
M. Sami Khawaja, Ph.D.
Vice President
The Cadmus Group, Inc.
Ccrpoate Headq uarters:
57 tlt'ater Sreet
Waterir:wn. MA 02472"lbl: &17.&73.7000
Fac 617.673.7001
An E nplo)€e-Owned Cornpony
r.r,r+sr. cn$ musg!-$ll $*(:G rn
720 SW Washington St.
Sui'te 400
Ponland, (}R 97?05
Tel: 503.228.299?
Fa<; 503.228.3696
nsglv- Mqq${r f0-Y9i
Roclry Mountain Power
Exhibit No. 5 Page 57 of 1 365
Case No. PAC-E-14-07
trt ove nr UI$FI' {:'Pd I d "*
1.
Table of Contents
Analytical Methods ..................15
Evaluation Question Overview ..................15
lmpact Questions
Process Questions
Participant Surveys ..................16
Billing Analysis .....18
Dealer Surveys .......21
CFL Nonparticipants and CFL Retailer Surveys .........21
Stakeholder Interviews................ ...............22
Secondary Research .................22
Secondary Data Analysis............. ..............23
Data Sources .............. ..............23
4. Survey and lnterview Findings .......25
Customer Survey Analysis.... .....................25
Marketing 25
Individual Measure Findings .....................26
Attic Insulation
Floor Insulation
Wall Insulation
Clothes Washers
2.
15
I6
26
29
30
32
The Cadmus Group. Inc. I Energy $ervices
Rocky Mountain Power
Exhibit No. 5 Page 58 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power
Refrigerators 36
Dishwashers 38
Electric Water Heaters 40
Windows 42
Lighting Fixtures 44
Dealer Survey Analysis.... ........45
Introduction
F{ES Marketing and Program Awareness
Pricing 50
Program Perception Among Dealers and Suggestions to Improve HES 51
Clothes Washer Recycling Through HES Program 52
Utility Staff and Implementer lnterviews ................ ......................54
Program Management
Market Barriers
Future Program Issues
Program Results.. ..............63
Impact Findings .....63
Summary of Program Participation ............... ..............63
Realization Rate.......... .Error! Bookmark not defined.
Billing Analysis Results...... .....65
CFL Leakage Ana1ysis................ ...............66
NTG Estimation......... ..............70
Gost-Effectiveness Analysis........... ............... 76
Appendices........ ................ 79
Appendix A: Available Measures Tariff Information............... .................19
Appendix B: Cost-Effectiveness Inputs ...................84
Appendix C: Dealer Survey Summary ....................85
Appendix D: Dealer Sales Perceptions..... ................86
Appendix E: Attic, Floor and Wall Insulation Participant Survey Instrument ........87
Appendix F: All non-Insulation Measures Participant Survey Instrument...............88
Appendix G: CFL Nonparticipant Leakage Survey Instrument................................89
Appendix H: CFL Retailer Survey Instrument................ ........90
Appendix I: Dealer Survey Instrument............... ......................91
Novem$8i'Tf'Ydfd"*
Error! Bookmark not defined.
45
54
59
6r
5.
6.
7.
The Cadmus Group. lnc. I Energy Services
Roclry Mountain Power
Exhibit No. 5 Page 59 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power
Appendix J: Implementer Discussion Guide....... ......................92
Appendix K: Program Logic Model....... ..................93
Appendix L: Billing Analysis Final Model ..............96
Appendix M: Freeridership Matrix .......98
Appendix N: Realization Rate Matrix ...................104
t * ove rn HITF l' f:Yd Id"*
The Cadmus Group, lnc. i Energy $ervices
Rocky Mounhin Pow€r
Exhibit No. 5 Page 60 of 't 365
Case No. PAC-E-14-07
Wtn€ss: l(athryn C. Hymas
Rocky Mountain Fower r'J ove m USF l'#l'Pd f d""
1. Executive Summary
PacifiCorp (Rocky Mountain Power and Pacific Power) offers the Home Energy Savings (HES)
Program in Utah, Wyoming, Idaho, Washington, and Northern California. HES was first made
available to Rocky Mountain Power's customers in May 2006. The HES Program provides
incentives for residential customers to facilitate the purchase of efficient products and services.
This report focused on HES program activities for 2006, 2007, and 2008 in Idaho.
PacifiCorp offers this program throughout the five state service territories where it offers
demand-side management programsl. Together the demand side management programs in Idaho
acquired more than 16,363 MWh/YR of energy savings (Gross at Generation) in 2009. Within
PacifiCorp's Idaho service area; the HES program is responsible for 54Vo of the savings that the
utility realizes from residential efficiency p.ograms.2
Overview of Evaluation Activities
The program targets the following key measuresl
o Lighting: Upstream incentives for manufacturers to reduce retail prices on compact
florescent lamps (CFLs). Customer incentives for light fixtures and ceiling fans.
. Appliances: Customer incentives for clothes washers, dishwashers, refrigerators, and
high-efficiency electric storage water heaters.
HVAC: Customer incentives for high-efficiency heating and cooling equipment and
services, duct sealing, and evaporative cooling equipment.
Windows and Insulation: Customer incentives for attic, wall, and floor insulation, and
high efficiency windows.
. Appliance Recycling: Incentives for recycled clothes washers.
The Cadmus Group Inc's (Cadmus) evaluation of the HES Program consisted of eight primary
tasks, feeding into two evaluations: impact and process. The impact evaluation evaluated two
key components: the realization rate and the net-to-gross ratio (NTG). The realization rate
accounted for both measures not providing assumed program savings (those which were not
installed in originally intended location or been removed), as well as instances where the
measure was saving a customer more energy than originaliy expected due to an adopted change
in behavior or a conservative savings estimate. NTG-the combination of freeridership and
spillover--discounted savings from units that would have been installed in the program's
absence, and credits the program for savings achieved through influence, but was not accounted
for in program records. The process evaluation investigated topics such as: program satisfaction;
the event sequence from a customer learning about a program through incentive payment; and
PacifiCorp manages demand-side management programs in five of its six state jurisdictions. Programs in
Oregon are managed by the Energy Trust of Oregon.
Based on information contained in PacifiCorps' 2009 Review of DSMProgranu - Idaho located at
http ://www.pacifi corp. com/es/dsm.html
The Cadmus Group, lnc. I Hnergy Serviees
Rocky Mountain Power
Exhibit No. 5 Page 62 of 1 365
Case No. PAC-E-14-07
nsgl.v- rylgq$eil lgryer
other qualitative issues. Table I illustrates the relationships between the eight primary tasks and
three evaluation components (process, realization, and NTG).
Table L. Summary of Evaluation Approach
Participant Survey X X X
Used for calculating the NTG, and assessing
effectiveness of the program's
implementation . (n=429 customers who
purchased 549 qualifying measures)
CFL
Nonparticipant
Survey
X X X Used for calculating CFL leakage out of the
service territory. $=1 41)lrealization rate.3
CFL Retailers X X Used for calculating CFL leakage out of the
service territory. (n=1 1 )/realization rate.4
Billing Analysis X
Used for calculating insulation realization
rate. (n=258 participants and 1,032 conhol
customers)s
Retailer Surveys X Provides insight into calculating NTG and
assessino Drooram deliverv. (n=30)
Stakeholder
lnterviews x Provides insight into program design and
assessing program delivery. (n=4)
Secondary
Research X
Review results of recent residential products
and services evaluations of other utility
programs to compare for best practices
Secondary Data
Analysis X Determines per-unit savings, based on
deemed reported savings, DEER, and RTF.
Realized Gross Savings
The first step in conducting the impact evaluation was to confirm achieved gross savings from
the program. The data provided by Rocky Mountain Power's program implementation
contractor, PECI was compared to Rocky Mountain Power's previously reported results for each
of the three program years. Deemed savings values were validated by comparing the PECI
claimed values against similar measures from the 2006 and 2008 Database for Energy Efficient
Resources (DEER) in California as well as the Northwest Power and Conservation Council
Regional Technical Forum (RTF) 5th and 6th Power Plans.6 This analysis determined that the
savings per measure values used by Rocky Mountain Power were reasonable and consistent. In
the comparison of per measure values, insulation measures varied the most with the values used
3
4
5
CFL Leakage was found to be inconclusive for the Idaho Territory.
rbid
Due to too low participation in Idaho to perform an adequate billing analysis, the billing analysis was used from
the Pacific Power HES Washington territory. More detail of the billing analysis is provided in the Billing
Analysis section ofthe report.
http:/i www.enersy.ca.gov/deer/ and http://www.nwcouncil.cu'u1rtf/ respectively.
trtovernW8F TfYdfd"*
The Cadmus Group, lnc. I Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 63 of 1 365
Case No. PAC-E-14-07
n?gLy mgq$ry Pqygt
by Rocky Mountain Power. The savings for insulation measqres were higher than those assumed
in DEER but lower than the values assumed by RTF Zone 3.7
The realization rate for most measures was determined by verifying installation rates of program
measures through phone surveys. For insulation measures, we attempted to determine a
realization rate using and analyzing billing analysis methodology data however it was found that
the level of participation for the years evaluated were too low for the results to be statistically
relevant to rely on this method. Consequently, the billing analysis performed for the Pacific
Power Washington HES Program was used as a proxy for the Idaho territory based on similar
climate and appliance saturation.
The CFL realization rate represented the leakage rate outside of Rocky Mountain Power's
territories, measured through surveys of noncustomers residing in close proximity to Rocky
Mountain Power's service territory.
Cadmus' evaluated leakage of program-subsidized CFLs out of the Rocky Mountain Power
service territory. This analysis covered Rocky Mountain Power's Idaho territory during 2006
through 2009. While leakage was studied, and is presented in this report, the findings only
attempted to measure the number of bulbs for which Rocky Mountain Power provided
incentives, which ultimately left its service territory. The study did not take into account other
factors such as the rural nature of the territory, lending itself to a very high "reverse leakage"
effect or other regional programs offered by Bonneville Power Administration (BPA) and
Northwest Energy Efficiency Alliance (NEEA) in the same territory which would cut down the
number of bulbs sold through the Rocky Mountain Power CFL program. Consequently this
report assumes that the net leakage is zero, and additional study is recommended to measure
these other impacts as well as to confirm the findings from this initial leakage study.
Additionally, the self reported data collected from retailers and consumers tends to be unreliable
due to a lack of incentive for them to confirm the historic purchases. The leakage study in Idaho
has a sensitivity of + 22.8% without accounting for the "reverse leakage" effect.
Table 2 shows aggregate realization rate values for each program year, based on survey
responses, insulation bilting analyses, and CFL leakage.
Estimates of savings per square foot for wall, floor and attic insulation were derived from Regional Technical
Forum (RTF) data in conjunction with heating and cooling degree day data as RTF does not include cooling
Ioad savings calculations.
NovemUHF'l{:'Pdfd"*
The Cadmus Group, Inc. / Energy $ervices
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 64 of 1 365
Case No. PAC-E-14-07
ttovern#LIFT'fYdtd"*
Table 21 in this report's Gross Savings section shows realization rates for each measure.
Net-to-Gross
Freeridership and spillover results, determined through phone surveys, were applied to realized
gross savings to estimate the net energy savings for each measure. NTG averages for 2006,2007,
and 2008 were 0.14,0.84, and 0.83, respectively. Table 3 summarizes evaluation results for each
program year and totals all three years.
Cost-Effectiveness
Program benefits are comprised of energy savings and their associated avoided costs. The energy
savings used in the cost-effectiveness analysis are the evaluated kWh from this study.
Table 4, Table 5, and Table 6 present the results of the cost-effectiveness analysis for the
Program in 2006, 2007, and 2008 respectively. Table 7 summarizes cost-effectiveness analysis
for the program for all years (2006-2008). All analyses are based on the Rocky Mountain Power
2008 IRP 60Vo load factor (LF) eastside residential lighting decrementE. The analysis shows the
program to be cost-effective each of the three years evaluated under PTRC, TRC, UCT and PCT
cost benefit perspectives. Detailed incremental costs and measure lives can be found in Appendix
B. The mix of measures included by year influenced the cost-effectiveness tests significantly.
Specifically, the relative mix in the number of CFLs sold and the amount of insulation
participation had the most significant impact.
IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan Volume II
Appendices:
http:l/u,u,u,.pacifictu'p.oon),/corttentdan/naqi figorp/doclErrvironrnenttnvironrrren lal Concems/Inte$ated ll,eso
urqs-Plannins 6.pdf
Table 2. HES Gross Energy Savings-Installation Adjusted
Table 3. Evaluated Savings Summary
The Cadmus Group, Inc. / Energy $ervices
.*, onT,::? Y""nTiilii]fJ
Case No. PAC-E-14-07
\Mtnessi Kathrun C. Hvmas
Table 4. Cost-Effectiveness Summary for 2006 - IRP 60Vo LF Eastside Residential
Table 5. Cost-Effectiveness Summary for 2007 - IRP 60Vo LF Eastside Residential
Table 6. Cost-Effectiveness Summary for 2008 - IRP 60Vo LF Eastside Residential
Lighting Decrement
W
0.83Total Resource + Conservation Adder (PTRC)$0.089 $146,766 $121,436 -$25,330
Total Resource No Adder (TRC)$0.089 $146,766 $110,396 -$36,370 0.75
Utility (UCT)$0.065 $107,868 $1 10,396 -$2,528 1.02
Ratepayer lmpact (RlM)$0.1 37 $226,252 $ 1 1 0,396 -$115,856 0.49
Participant (PCT)$0.040 $65,539 $145,025 $79,486 2.21
Lifecvcle Revenue lmoact ($/kWh)$0.00000490
Discounted Particioant Pavback ffears)2.73
Lighting Decrement
Total Resource + Conservation Adder (PTRC)$0.061 $298,430 $385,71 6 $87,286 1.29
Total Resource No Adder (TRC)$0.061 $298,430 $350,651 $52,221 1.17
Utility (UCI)$0.053 $261,044 $350,651 $89,607 1.34
Ratepayer lmpact (RlM)$0 132 $647,746 $350,651 -$297,094 0.54
Participant (PCT)$0 034 $165,539 $514,854 $349,315 3.11
Lifecycle Revenue lmpact ($/kWh)$0.0000091 5
Discounted Particioant Pavback ffears)0.97
Lighting Decrement
W
Total Resource + Conservation Adder (PTRC)$0,1 1B $585,447 $424,308 -$1 61 ,1 39 0.72
Total Resource No Adder (TRC)$0.1 1 8 $585,447 $385,734 -$199,712 0.66
Utility (UCI)$0.091 $450,394 $385,734 -$64,659 0.86
Ratepayer lmpact (RlM)$0.1 76 $873,045 $385,734 -$487,311 0.44
Participant (PCT)$0.073 $360,706 $648,304 $287,598 1.80
Lifecycle Revenue lmpact ($/kWh)$0.00001 1 31
Discounted Particioant Pavback ffears)4.12
The Cadrnus Group. lnc. I Energy Service$
Rocky Mountain Power
Exhibit No. 5 Page 66 of 1 365
Case No. PAC-E-14{7
Rocky Mountain Power
Table 7. Cost-Effectiveness Summary for 2006-2008 - IRP 60Vo LF Eastside Residential
Lighting Decrement
Summary of Findings
Key findings from The Cadmus Group's evaluation follow below:
o 2006 was the first year the program was offered in Idaho and as seen often in the first
year, there are significant costs in setting up the program which impact the benefit/cost
ratio of the program. Although the program benefit/cost ratio improved in 2007, in 2008
the other regional programs' offered by BPA and NEEA in the same territory cut down
the number of bulbs sold through the Rocky Mountain Power CFL program, which
negatively impacted the benefit/cost ratio of the entire program.
Excluding CFL participants, program participation and gross savings between 2007 and
2008 (the two full program years) increased 547o. Additionally, participation increased
for 10 of 12 measures that had participation in 2007 and 2008. During the same period,
gross savings (kWh) increased for 6 of 12. However, CFL participation declined
dramatically between 2007 and 2008. This decline can be attributed to the misalignment
of pricing of bulbs offered through this program and those offered through the BPA and
NEEA programs. When CFL participants are included during the same period, overall
program participation and gross savings (kWh) decreased by l9%o and20 7o respectively.
The NTG factors of Rocky Mountain Power's program were consistent with those found
in recent evaluations of other utility programs offering similar measures. In particular the
freeridership is consistent with other reports, while the approach taken for the HES
spillover is more conservative compared with evaluations where spillover was quantified.
t't ove m UIIFT' 5:'Yd f d"*
o Evaluation results indicate that about a third of the total program CFLs subsidized
through the HES Program may have leaked outside the territory.lo However, due to the
During the 2006-2008 program cycles, incentives for lighting measures were offered by three regional
programs, in overlapping service territories. While the three programs (BPA, NEEA and Rocky Mountain
Power) were effectively coordinated for most of this time, each underwent restructuring at different times in
2008. The result was that the programs were out of sync in 2008 and participation in Rocky Mountain Power
program dropped off significantly, negatively impacting the program cost-effectiveness.
This level of leakage is consistent with areas that were considered in close proximity with other territories in a
recent study for California IOUs (PG&E, SCE, and SDG&E) performed by KEMA and Cadmus. The study did
W
0.91Total Resource + Conservation Adder (PTRC)$0.088 $932,1 84 $848,427 -$83,757
Total Resource No Adder (TRC)$0.088 $932,184 $771,298 -$160,887 0.83
Utility (UCT)$0.07 $741,392 $771,298 $29,905 1.04
Ratepayer lmpact (RlM)$0.1 51 $1,586,2s0 $771,298 -$814,952 0.49
Particioant (PCT)$0.051 $532,384 $1,186,449 $654,065 2.23
Lifecycle Revenue lmpact ($/kWh)$0.00001 757
The Cadmus Group. lnc. I Energy Services IU
ngg[y nngq$gin Pqrygi Novern$HF"l'f'yd8d"*
rural nature of the territory and competing programs the ooreverse leakage" would be
equal or more than the corresponding leakage, a benefit of a coordinated regional
approach to influence the adoption of a measure i.e. point-of-purchase buy-down
program designs.
o Gross savings were primarily from CFLs, clothes washer, and attic insulation, accounting
for 51Vo, 187o, and l4Vo, respectively, for the combined three years.
o The same three measures-CFls, clothes washer-tier two, and attic insulation-
accounted for 12Vo,227o, and 30Vo, respectively, of incentive dollars spent over the
combined three years.
o Overall, 837o of participants were satisfied; 53Yo of total participants were o.very
satisfied"; 30oZ were "satisfied".
o Providing standard offerings in vastly different demographic, geographic, and climatic
areas proved challenging, and required consistent analysis and monitoring.
Summary of Recommendations
Enhance the quality control process. Program site inspections in regions with greater
participation revealed the need to alter the quality control methodology to increase
effectiveness. PECI has already addressed this by increasing the number of staff
conducting inspections and instituting use of more sophisticated equipment for greater
precision during inspections (such as laser measures for square footage) for the HES
program. Procedures for selecting QC participants should also be reviewed, as customers
without phone numbers appear to have been eliminated from the pool for QC visits.
Program promotion. Relationship building should continue with dealers and trade allies
as these channels directly contact prospective participants at times when customers
decide about equipment purchases.
Benefit-Cost Ratio. The benefit-cost ratios presented indicate the program is struggling.
As described in the key findings, Cadmus would suggest that the first year of the progmm
was impacted by startup costs and 2008 was impacted by the significant reduction in the
number of CFLs. The CFL numbers in 2009 were higher than in 2001 and would indicate
that the benefit-cost ratio would look positive.
Program data collection. PECI should investigate options for more robust data
collection processes and construct a database designed to allow better and more efficient
information tracking and data transfer between implementer and utility as needed.
not take into account other factors such as the rural nature of the territory, lending itself to a very high "reverse
Ieakage" effect or other regional. Consequently this report assumes that the net leakage is zero.
The Cadmus Group. lnc. I Energy Services 11
nsshy Hagq$ef Pqyet t t oue',0 H8F'1' f 'Pd f d"""
2. Program Overview
Program Description
The Idaho Home Energy Savings Program GDS) is part of Rocky Mountain Power's ongoing
Demand-Side Management (DSM) resource acquisition program. The program's overarching
objective is to decrease customer electricity usage (kWh) by offering incentives for more
efficient products and services received or installed by Idaho customers. The incentives offered
through the program are designed to encourage customers shopping for new appliances to seek
high efficiency models, and those looking for services to use the most energy-efficient option.
The HES Program provides incentives for residential customers to purchase efficient products
and services. The program targets the following key measures, which affect a home's overall
efficiency:
. Lighting: Upstream incentives for manufacturers to reduce retail prices on compact
florescent lamps. Customer incentives for light fixtures and ceiling fans.
. Appliances: Customer incentives for clothes washers, dishwashers, refrigerators, and
high-effi ciency electric storage water heaters.
o HVAC: Customer incentives for high-efficiency heating and cooling equipment and
services, duct sealing, and evaporative cooling equipment.
o Windows and Insulation: Customer incentives for attic, wall, and floor insulation, and
for windows.
. Appliance Recycling: Incentives for recycled clothes washers.
Eligibility Req uirements
Residential electric customers in Rocky Mountain Power's service territory and landlords
owning rental properties served by Rocky Mountain Power, where tenants are billed on standard
rate schedules, qualify for the HES program.
To participate, customers must purchase a qualified product or service, complete an application,
and provide required documentation, such as product receipts. Incentive checks are issued within
45 days of receipt of a completed and approved incentive application.
lncentive Levels
The program offers incentives for qualified energy-efficient appliances, lighting, heating, and
cooling equipment, windows and insulation, and certain appliance recycling measures. Table 8
shows variations for each measure, and indicates when measures were introduced to the
program. Appendix A: Available Measures Tariff Information contains a copy of the full tariff
schedules, including a list of incentive levels for each product eligible in 2006, 2007, and 2008.
Rocky Mountain Power and PECI have made to program targets over the three years since the
measures' May 2006 introduction.
The Cadmus Group. lnc. l Energy Services 12
nggxy_ ut9qg3!1 Power
Rocky Mountain Power
Exhibit No. 5 Page 69 of 1 365
Case No. PAC-E-14-07
t*t ove m SBF"I' f,'Yd 8d"*
Table 8. Program Measures and Ineentive Variations
ll Incentive value available on December 31, 2008
CAC/Heat Pumo Tune-Uos 5/31/2006 $1 25 $1 25
Ceilino Fans 11112007 $20 $20
CentralA/C Eouioment 1t112007 $275 $275
CFL 5131t2006
Manufacturer buy-
down not-to-exceed
$1,35 and Retail price
not-to-exceed $1.50
Manufacturer buy-
down not-to-exceed
$1.35 and Retail price
not-to-exceed $0.99-
$2.75
Clothes Washer MEF 1.42-1.721 5/31/2006 $75 $0
Clothes Washer (MEF 1.72-1.99)511t2008 $50 $50
Clothes Washer (MEF 2.0+)511t2008 $100 $100
CW Recvclino 5t31t2006 $25 $25
Dishwasher 111t2007 $20 $20
Duct Sealino 5/31/2006 $200 $200
Electric Water Heater 5t31t2006 $50 $50
Evaporative Cooler 5t31t2006 $275 $1 00
Fixture 5t31t2006 $20 $20
Heat Pump Conversion 5t1t2008 $375 $375
Heat Pump Uoorade 5t1t2008 $275 $275
lnsulation: Attic 5/31/2006 $1.00/sq. ft.$.50/so. ft.
lnsulation: Floor 5t31t2006 $1.00/sq. ft.$.50/so. ft,
lnsulation: Wall 5t3112006 $1.00/sq. ft.$.50/so. ft.
Proper CAC lnstallation 11112007 $1 25 $125
Prooer CAC Sizino 1t1t2007 $75 $75
Refrioerator 5/31/2006 $20 $20
Windows 5/31/2006 $1.50/so. ft.$1.50/sq. ft.
The Cadrnus Group. lnc. / Energy Services 13
Rocky Mountain Porver
Exhibit No. 5 Page 70 of '1365
case No. PAC-EJ4{7
Whess: lcthryn C. HYmas
Roclq Mountain Power
Exhibit No. 5 Page 71 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasRocky lr,'Xountain Fower Novembef 1?; Z0t0'
3. Evaluation Methods
Analytical Methods
The evaluation plan consisted of eight primary tasks. Table 9 presents a brief description of each
task. Subsequent chapters provide additional details regarding methodologies for each evaluation
task.
Table 9. Summary of Evaluation Approach
Participant Survey X X X
Used for calculating the NTG, and assessing
implementation . (n=429 customers who
purchased 549 qualifying measures)
CFL
Nonparticipant
Survey
X X X Used for calculating CFL leakage out of the
service territory. $=141) 12
CFL Retailers X X Used for calculating CFL leakage out of the
service territorv. (p='l 'l)ts
Billing Analysis X
Used for calculating the insulation realization
rate. (n=258 participants and 1,032 control
customers)tl
Retailer Surveys X Provides insight into calculating NTG and
Drooram deliverv. (n=30)
Stakeholder
lnterviews X Provides insight into program design and
delivery. (n=4)
Secondary
Research X Reviews results of recent residential
products and services evaluations.
Secondary Data
Analysis X Determines per-unit savings, based on
deemed reported savings, DEER, and RTF.
Evaluation Question Overview
The HES Program covers a broad range of products and services, each with varying participation
levels. Evaluation questions focused on measures estimated to produce the greatest kwh savings
or incurring the largest incentive dollar costs (the primary measures). Key impact and process
evaluation questions driving the study are listed below.
!mpact Questions
1. What were the gross and net energy savings generated by a participating product or
service?
t2 CFL Irakage was found to be inconclusive for the Idaho Territory.t3 Ibid.14 Due to too low participation in Idaho to perform an adequate bilting analysis, billing analysis was used from the
Pacific Power HES Washington territory. More detail of the billing analysis is provided in the Billing Analysis
section of the report.
The Cadnrus Group. lnc. ,/ Energy Services 15
Rocky Mountain Power
Exhibit No. 5 Page 72 of 1365
Case No. PAC-E-14-07
ng!y- r,,'lgU $ein fl_qySt
2. What percentage of participating appliances and services would have been purchased
in the program's absence?
3. What additional appliances and services were purchased due to the program?
4. How many CFLs left the service territory?
5. How did evaluated savings compare to previously reported savings for each program
yeat?
6. What were actual program costs and benefits?
Process Questions
1. How did program participants become aware of the program?
2. How satisfied were participants with program delivery, including schedule,
communications, implementer perfonnance, incentive, and overall?
3. What improvements did participants recommend?
4. From the implementer's perspective: how well did the program work? What could be
improved?
Participant Surveys
The evaluation team administered a participant survey for residential appliances and service
evaluations. The surveys included questions addressing:
o Context and Decision-Making Processes. These questions addressed key aspects of the
customer's decision-making process, and informed freeridership, spillover, and
verification analysis.
o Program Satisfaction. These questions collected process-related responses regarding
participants' satisfaction with the program. The questions also addressed the likelihood
participants would refer others to the program.
Other questions sought to determine the customers' sources of program information, descriptions
of products and services, consideration of alternative products and services, and demographics.
The sampling plan addressed all of study goals, including determining energy savings for each of
the three calendar years. As energy consumption, operating patterns, and purchasing decisions
were unique to each measure, accurate determination of energy savings required independent
evaluation of each primary measure.
PECI provided multiple files, including customers, measures, retailer, gross savings, incentive
dollars, and units for each calendar year. Once the files were verified, the evaluation team
assigned each participant a random number, and prioritized the call list based on these numbers.
Table 10, Table 11, and Table 12 show numbers of participants, actual numbers of survey
responses, and precision estimate at the 90Vo confrdence interval based on the number of surveys.
t'tovemU$FT'f'?df#"*
The Cadmus Group. Xnc. I Energy $ervices 16
Rocky Mountain Power
Exhibit No. 5 Page 73 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Fower NovernHHF"I'fYdfd"*
Table L0. Measure Participationls
Ceilino Fans 4 20 24
Centrall/C Eouioment 1 2 3
CFL 918 1,593 485 2,996
Clothes Washer 151 597 378 1,126
Clothes Washer-Tier One 43 43
Clothes Washer-Tier Two 392 392
Dishwasher 96 205 301
Electric Water Heater 12 57 72 141
Evaporative Cooler 1 1
Fixture 1 18 34 53
Heat Pumo UDorade 1 1
lnsulation: Attic 2 42 127 171
lnsulation: Floor 4 19 23
lnsulation: Wdl 16 25 41
Prooer CAC lnstall 2 2
Prooer CAC Sizino 2 2
Refrioerator 51 238 263 552
Windows 26 105 131
Total '1,135 2,693 2,175 6,003
Table 11. Participant Surveys Completed
Ceilino Fans 0 0 0 0
Central/r/C Eouipment 0 0 0 0
CFL 0 0 0 0
Clothes Washer 38 71 65 174
Clothes Washer-Tier One 0 0 2 2
Clothes Washer-Tier Two 0 0 64 64
Dishwasher 0 25 54 79
Electric Water Heater 1 4 13 18
Evaoorative Cooler 0 0 0 0
Fixture 1 1 5 7
Heat Pumo Uoorade 0 0 0 0
lnsulation: Attic 0 13 36 49
lnsulation: Floor 0 2 5 7
lnsulation:Wall 0 4 5 I
Prooer CAC lnstall 0 0 0 0
Prooer CAC Sizinq 0 0 0 0
Refrioerator 18 42 EO 119
Windows 0 3 18 21
Total 58 165 326 549
l5 The participant count includes counts of individual incentives: for appliance measures, customers are limited to
one incentive per household, except for ceiling fans and fixtures; for home improvement, the number of
participants equals the number of total jobs; for HVAC, contractor incentives are not counted as a separate
participant; for CFLs, participants are estimated at 10 bulbs per participant, a rate based on information from
PECI and the PAC-E-05-10 Annual Report of Idaho Demand Side Management Activities.
The Cadmus Group, lnc. I Energy Services 17
Rocky Mountain Power
Table L2. Level of Precisionl6
Ceilinq Fans N/A N/A N/A N/A
Centrallr/C Equioment N/A N/A N/A N/A
CFL N/A N/A N/A N/A
Clothes Washer 120h 9Yo 9%1.75To
Clothes Washer-Tier One N/A N/A 57Yo 57.460/o
Clothes Washer-Tier Two N/A N/A 9Yo 9.42Yo
Dishwasher N/A 140k 100/o 7.96Yo
Electric Water Heater 82Yo 40Yo 21Yo 18.17T0
Evaporative Cooler N/A N/A N/A N/A
Fixture }Yo 820/o 34To 29.24o/o
Heat Pumo Uoqrade N/A N/A N/A N/A
lnsulation: Attic N/A 19Yo 1ZYo 9.95%
lnsulation: Floor N/A 47o/o 32Yo 26.510/o
lnsulation: Wall N/A 37Yo 34Yo 24.520/o
Prooer CAC lnstall N/A N/A N/A N/A
Prooer CAC Sizino N/A N/A N/A N/A
Refriqerator 160/o 12Yo 9Yo 6.68%
Windows N/A 45Yo 18To 16.51o/o
0verall 10.52Yo 6.2Y0 4.ZYo 3.35%
Billing Analysis
During the evaluation a billing analysis was attempted for the Idaho insulation participants. After
applying the screening criteria only 93 participants remained. This pool of participants was too
small and did not yield robust enough savings estimates to accurately assess actual energy
savings. Because the Pacific Power Washington HES program expected savings and participant
climate was a close proxy for the Idaho program the Washington billing analysis realization rate
was extrapolated to the Idaho program for insulation measure installations.lT The savings
estimate was determined from a pooled conditional savings (CSA) regression model, including
the following groups:
o lnsulation (combined attic, wall, and floor insulation for 2006-2008); and
. Nonparticipant homes, serving as the baseline.
Program Data and Billing Analysis Methodology
Several data sources were used to create the final billing analysis modeling dataset, including:
o Pmgram data were collected and provided by PECI (including account numbers,
measure type, installation dates, square footage of insulation installed, and expected
savings for the entire participant population).
l6
l7
lrvel ofprecision at the9OTo conhdence interval.
Billing analysis was only performed for the insulation measures. Energy savings achieved through installation
of other measures were not large enough, relative to the total energy consumption of households where
installed, to allow reliable billing analysis.
.*,onX""i?I""n'Jfl ""iiYg
Case No. PAC-E-14-07
ruovemHSF"I'f'Ydfd"*
The Cadmus Group. lnc. i Energy Services 18
Rggky_ Mggti?l1 fqyfl
Roclry Mountain Power
Exhibit No. 5 Page 75 of 1 365
case No. PAC-E-14-07
Wtness: Kathrvn C.JlymasNovernber 1?,7CI1S
o Control gmup data. The control group was selected from nonparticipating customers,
whose energy use matched pre-participation energy use of participating households. To
ensure adequate coverage of the nonparticipating population, the evaluation team
included four times more nonparticipants than participants in the billing analysis.
o Billing data were provided by Rocky Mountain Power, including all customer accounts
in the service territories being evaluated (Idaho, Washington, and Utah). The data
included: meter-read dates, days in the billing cycle, and five years of kWh consumption
for both participants and the large pool of nonparticipants. The final sample used in the
billing analysis savings model consisted of 258 participants and 1,032 control
customers.l8
o Weather data included daily average temperatures from January 1995 to December 2009.
The billing analysis team matched program data with billing data and separated the data into
$oups of participants and nonparticipants. Daily heating and cooling degree days were matched
to respective monthly read date periods in billing data for use in weather-adjusted savings
modeling.
Data Screening
Table 13 shows participant and nonparticipant screening criteria and attrition for Idaho and Table
14 shows participant and nonparticipant screening criteria used in the billing analysis from
Washington. To ensure the final model used complete pre- and post-participation billing data, the
analysis team selected accounts with a minimum of 300 days in the pre- and post-periods (i.e.,
before the program's 2006 launch, and after the 2006-2008 measures had been installed).
Additionally, the analysis team removed outlier accounts with less than 1,000 kWh per year or
more than 50,000 kWh per year. As expected savings were low compared to pre-period usage, a
stringent 30Vo charrge screen was used in the analysis. While typically a 50Vo-7OVo change screen
is applied to most billing analyses where major measures were done, a 307o change screen was
placed on the billing data in this case since large savings and large increases in consumption for
both participants and nonparticipants were not expected given the small expected savings relative
to the pre usage. This screen also ensures that the nonparticipants are better matched with
participants. Any account changing usage by more than 307o from the pre- and post period was
removed from analysis.
The sample for the billing analysis savings model attempted in Idaho consisted of 93 participarts and 372
control customers.
The Cadrnus Group. ln*. / Hnergy $ervices
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 76 of 1 365
Case No. PAC-E-14-07
tolovemHUiT'f?dfd"*
Table 1.3. Screen for Inclusion in Billing Analysis for Idaho
The expected engineering estimates of savings were very low compared to the pre-usage. A 307o change screen
was placed on the billing data since large savings and large increases in consumption for both participants and
nonparticipants were not expected given the small expected savings relative to the pre usage. This screen also
ensures that the nonparticipants are better matched with participants.
If the expected engineering estimates of savings exceed 70Vo of the pre-consumption, then either there was a
mismatch between the participant measure installation data and the billing data account or address, or the
participant had a vacancy in the pre-period. Either one ofthese, would have led to unreasonable savings
estimates for that customer, hence they are dropped.
l9
Original Measures Participant
Database and 10 times
Nonparticipant Sample by Zip
code
2,010 199
Matched Billing Data Sample
(accounts that could be
maooed to the billino data)
2,010 199
Less than 300 days in pre or
oost oeriod 21 1,989 199
Less than 1,000 kwh in pre or
nost oeriod 116 2 1,873 197
More than 50,000 kWh in pre
or oost oeriod 3 1,870 197
Changed Consumption by
more than 30% from pre to
oostl9
605 45 1,265 152
Expected Savings over 70%
of ore Consumotionzo 5 1,265 147
No Expected Savinos 54 1 265 93
Nonparticipant Sample
Selection 893 372 93
FinalSamole 372 93
The Cadmus Group. lnc. / Energy $ervices 20
Rocky N,{ountain Fouver
Rocky Mountain Power
Exhibit No. 5 Page 77 of 1365
Case No. PAC-E-14-07
\Mtness: Kathrun C. HvmasNovember 12, Z01S'
Table L4. Screen for Inclusion in Billing Analysis for Washington2l
Original Measures Participant
Database and 10 times
Nonparticipant Sample by Zip
code
4,120 408
Matched Billing Data Sample
(accounts that could be
mapped to the billino data)
4,120 408
Less than 300 days in pre or
oost oeriod 73 I 4,047 200
Less than 1,000 kwh in pre or
oost oeriod 80 1 3,967 398
More than 50,000 kWh in pre
or oost oeriod 21 3,946 398
Changed Consumption by
more than 30% from pre to
Dost
1,070 oo 2,876 299
Expected Savings over 70%
of pre Consumotion 11 2,876 288
No Exoected Savinos 30 2,876 258
Nonparticipant Sample
Selection 1,844 1,032 258
Final Samole '1,032 258
Dealer Surveys
Cadmus conducted interviews with 30 participating Idaho dealers. These 30 dealers were chosen
from a list of participating dealers provided by PECI. In order to ensure random selection of
dealers, the evaluation team assigned each dealer a random number. Once the random numbers
were assigned, the list was sorted in descending order by incentive totals and then again by the
random number. The sample list was verified to have representation of the more significant
measures based on gross kWh saved and dealer categories including big box stores, smaller
retailers, and contractors.
The surveys sought to collect information about the following attributes: effectiveness of
program marketing materials; dealer program promotion; and overall dealer perceptions of the
program. Additionally, dealers were asked about their methods of recycling old clothes washers.
CFL Nonparticipants and CFL Retailer Surveys
Cadmus conducted two surveys. The first targeted households not served by Rocky Mountain
Power (noncustomers) within 20 miles of Rocky Mountain Power service territory. The second
targeted retailers participating in the Rocky Mountain Power program.
The Washington billing analysis was applied to Idaho due to Idaho data limitations and relatively comparable
service territory characteristics. The billing analysis screen table shows the attrition in the Pacific Power
Washington IIES program billing analysis model as the screening criteria were applied.
2l
The Cadrnu$ GrCIup. ln*. I Hnergy $*rvic*s .){Lt
ngg[.v_ Mgq$sf |q*sr t't ove nn U$F l' f 'Yd f d"""
The household survey sample consisted of l4l randomly selected households in areas
surrounding Rocky Mountain Power's service territory. Surveyors asked these non-Rocky
Mountain Power customers: how many CFLs their household had purchased since the beginning
of 2006; stores from which they purchased those CFLs; and their percentage of purchases from
each of those stores. In each region surveyed, the goal was to complete 70 surveys with non-
Rocky Mountain Power customers to achieve a 90Vo confidence with a +l- l07o level of
precision.
The retailer survey sought to obtain information on the number of CFLs sold since the beginning
of 2006, and the percentage of sales subsidized by the program. Surveys were completed with all
11 stores reported to have CFL sales subsidized through the program.
The evaluation team combined the household and retailer survey responses to determine numbers
of CFLs purchased outside the service territory since 2006, and the percentage of those being
program bulbs.
This approach provided an estimate of historic CFL leakage, though the methodology relied on
respondents' memories. In can be difficult for people to recall specifics related to purchases of
relatively inexpensive items, such as CFLs. The reverse leakage was not quantified for this
report.
Stakeholder I nterviews
To assess the program's effectiveness and implementation, the evaluation team conducted
interviews with a number of stakeholders familiar with the program. Specifically, the evaluation
team interviewed four Rocky Mountain Power and PECI stakeholders. Table 15 provides details
regarding stakeholders interviewed.
Table 15. Stakeholder Interviews
Project managers conducted stakeholder interviews using a guide designed to examine the
program' s design, delivery, management, communication, effectiveness, and future.
Information obtained from stakeholders informed the following evaluation elements:
o Determination of program progress; and
o Identification of changes during implementation.
Secondary Research
To ensure the evaluation aligned with industry' best practices for residential product and service
evaluations, the team reviewed multiple evaluation reports for methodology and participant
survey instruments.
Class 2 DSM Segment Manager, All Sectors
The Cadmus Group. lnc. I Energy Services 22
Roclq Mountain Power
Exhibit No. 5 Page 79 of 1 365
Case No. PAC-E-14-07
ngg[v hflountain Power
Data collected through secondary research aided the following evaluation elements:
o Development of the gross savings methodology;
o Development of the participant, nonparticipant, and retailer survey instruments; and
o Development of the net savings methodology.
Secondary Data Analysis
To leverage existing participating measure data sources, the evaluation team obtained datasets
detailing energy consumption of similar measures from the 2006 and 2008 DEER database as
well as the RTF 5th and 6th Power Plans. Combining this information with data on program
participants yielded an estimate of the program's gross savings. Detail regarding this process is
provided in the following chapter.
The analysis informed the following evaluation elements:
o Determination of estimated per-unit energy savings; and
o Estimate of program gross savings.
Data Sources
The evaluation team used the following data sources to inform the impact and process
evaluations:
o Final program databases (provided by PECI).
o Information gathered through participant, nonparticipant, and retailer surveys.
o Information gathered through stakeholder interviews.
o The ENERGY STAR sales database."
o Other recent residential appliance and services evaluations.
o The 2006 and 2008 DEER database in California, and the Northwest Power and
Conservation Council RTF 5th and 6th Power Plans.23
ENERGY STAR Resources for Appliance Manufacturers and Retailers:
http ://www. energystar. gov/index.cfm?c=manuf_res.pt_appliances
hIlp:#www.ctip_fg"v.ca.gqr"1{ggq{ and }lttE:/l*,_iyrt,*.*:L:.9.ti.i:ci}.or:g/rtf7 respectively.
tu ove nt Ul$F 1' 51Yd I#"*
The Cadn"rus Group. ln*. / Energy Services 23
Rocky Mountain Po,ver
Exhibit No. 5 Page 80 of 1365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
Roclq Mountain Power
Exhibit No. 5 Page 81 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power uovemS$i"l'fYdfd"^
4. Suruey and lnterview Findings
In addition to collecting information needed to gauge freeridership and spillover, the end-use
customer surveys and dealer interviews explored a number of other topics, including marketing
efforts, new vs. existing installations, incremental costs, market trends, and program satisfaction.
Each of these areas is discussed below.
Customer Survey Analysis
Marketing
Investment in mass media channels, such as television, radio, and print advertising, was
comparatively less than more targeted approaches. [n Idaho, 387o of insulation participants heard
about the program from a friend or family member and about one-fourth heard about the
program from the contractor who installed qualifying insulation in their home. Bill inserts were
reported by 13. Survey responses indicate that newspaper and television advertising were not as
effective as word of mouth or contractor promotion. These findings appear to be in line with
investment levels and are presented in Figure l.
More than one-fourth of windows and appliances participants heard about the program from the
dealer who sold the measure or the installer who installed the measure. One-fifth of participants
indicated that they heard about the program from inserts in their monthly utility bills. Another
l)Vo indicated that they heard about the program by word-of-motfih. 24Vo of windows and
appliances participants reported hearing about the program from another utility source such as
newsletters or the Rocky Mountain Power website. These findings are shown in Figure 2 below.
Figure 1. How Insulation Participants Heard About HES Program (n = 55)
ln-store marketing material
TV ad
Newspaper
Other
Salesperson
Don't Know
Bill insert
Contractorllnstaller marketing material
Friend/Family Member
0Yo 5oh 1 0o/o 1 5Yo 20'/o 25Yo 30o/o 35o/o 40To 45Yo
The Cadmus Group. lnc. I Energy Services 25
Rocky Mountain Power
Exhibit No. 5 Page 82 of 1 365
Case No. PAC-E-14-07
Figure 2. How Windows and Appliances Participants Heard about HES Program (n =372)
utility Energy Newsletter
Utility Welcome Kit
Print Ad
Utili$ Call Center
Other
Online Ad I RMP Web Site
Brochure
Word of Mouth
Dont Know
Billinsert
Dealerllnstaller
lndividual Measure Findings
Attic lnsulation
Attic insulation participants were asked to discuss what they considered to be the most important
criteria when purchasing the measure.20Vo of the 50 participants discussed the need to regulate
the inside temperature of their home as key criteria. Another ISVo cited energy bill reductions as
key criteria for purchasing the measure. The incentive was the most important criteria for 16%o
and price was discussed by l2Vo of participants as key criteria for purchasing attic insulation.
Figure 3 below summarizes these findings as well as additional criteria discussed by attic
insulation participants.
l*'
i
I
t'tovernHUFT'fYdfd"*
The Cadmus Group. lnc. l Energy Services 26
Rocky Mountain Power
Exhibit No. 5 Page 83 ot 1 365
Case No. PAC-E-14-07
Rocky Mourntain Power NovemHHF l{1P$fd"*
Figure 3. Most Important Criteria for Purchasing Attic Insulation (n = 50)
Financing
Replace 0ld lnsulation
Contractorllnstaller Availabili$
Contractorllnstaller Pricing
Product Brand
Energy Efftciency
price
Don't Know
Program lncentive
Reduce Energy Bill
Regulate lnside Temperature
Participants cited a number of different factors that motivated them to purchase attic insulation
through the HES Program. Most respondents (427o) reported that their old insulation was no
longer sufficient or missing. The program incentive motivated I4Vo of participants to install this
measure. Both potential energy savings and potentially lower utility bills each influenced l07o of
participants to install the measure. As shown in Figure 4 below, lSVo aLso cited other factors that
influenced their decision to install attic insulation. These responses included general heating and
cooling needs, home remodeling, fixing incorrectly-installed insulation, and recommendations to
buy the measure.
Figure 4. Factors that Motivated Purchase of Attic Insulation (n = 50)
Don't Know
Reduce Energy Bill
Energy Savings
Program lncentive
I OH Insutation lnsufficienUMissing
I
Nr* iYni.iffi1%w4%
iw 1'2.
w1.2.
i
5o/o 10o/o 15o/o 20o/o 25o/o 30o/o 35% 40o/o 45o/o iI
I*..'.-.-.*.,,.,.-.****_J
Participants also discussed changes in the comfort of their home after installing attic insulation.
647o of the 44 participants reported that in general the inside temperature of their homes is
comfortable. While not specifically asked in this question, one-fourth of participants reported
lower energy bills following the installation of attic insulation. Two participants indicated that
there was no noticeable difference and one participant reported that his air conditioner and
w12%
!:!W
The Cadrnus Group. lnc. I Energy Services 27
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 84 of 1 365
Case No. PAC-E-14-07
NovernHBFI'f'Ydfd"*
furnace ran less frequently after installing attic insulation. Figure 5 below summarizes these
findings.
Participants were also asked how their air conditioner or furnace usage has changed since
installing the measure. Of the 16 respondents, SlTo indicated that their air conditioner or furnace
runs less frequently and 6Vo reported that their HVAC system provided better heating and
cooling since installing the measure. Figure 6 summarizes these findings below.
Figure 5: Reported Changes in Comfort of Home - Attic Insulation (n = 44)
l__--- L ; , :i LessNoise N ,*i i i
i ,on'tKnow ! -l i i
i o.IFurnaceRunLess X ,*l i i
t*tli uo Difference mii*iri.{i:i f-owerEnergyBills mI -- i**-*l*--**i*I -. .I-l-l
i ComfortablelnsideTemperatrr. ffi
I on .o% 20'I_*-.*
Figure 6. Changes in AClFurnace - Attic Insulation (n = 16)
I
GoolslWarms
Survey administrators also asked participants about any changes in their monthly utility bill since
installing attic insulation. Three-fourths of the 27 respondents indicated that their monthly bill
was lower than before installing attic insulation. One participant reported that their bills were
higher than before installing the measure. These findings are presented in Figure 7 below.
The Cadmus Group. lnc. / Energy Services 28
Rocky Mountain Power
Exhibit No. 5 Page 85 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Fower Novern#HF'l'51'Y$fd""'
Figure 7. Changes in Monthly Utility Bill - Attic Insulation (n - 27)
I
Higher,
4Yo
Slightly Lower,
18%
Significantly
Lower,
18o/o
No Change,
Floor lnsulation
Seven floor insulation participants discussed key criteria for purchasing the measure. In addition
to criteria related to price, two participants indicated that the R-value was important and one
participant stated that he simply needed to replace existing insulation. These findings are
summarized in Figure 8.
Figure 8. Key Criteria for Purchasing Floor Insulation (n =7)
Four indicated that following the installation of the measure, their inside temperature was
generally more comfortable. Additionally, one respondent reported that his AC/fumace runs less
frequently since installing the measure. One respondent reported that his monthly utility bill was
slightly lower following the installation of the measure.
Floor insulation participants also discussed factors that motivated them to purchase the measure.
For three (43Vo) of these participants, their old wall insulation was insufficient to meet the
heating and cooling needs of their home. Two more participants (29Vo) reported that they
2gThe Cadmus Group. lnc. / Energy Services
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 86 of 1 365
Case No. PAC-E-14-07
NovernB$i'l'f?dfd"*
installed the measure as part of a home remodeling project. These findings are summarized in
Figure 9 below.
Figure 9. Factors That Motivated Purchase of Floor Insulation (n = 7)
i
i Oon't Know
i
i HeatinglCooling Needs
i
ii Home Remodel
i
ii Old lnsulation lnsufficient
!
I
i
I
i
Wall lnsulation
Nine wall insulation participants discussed key criteria for purchasing the measure as shown in
Figure 10. Participants discussed regulating inside temperature, reducing the monthly energy
bills, higher R-value, ease of installation, and the need to replace old insulation as key criteria for
installing the measure.
Figure 1.0. Key Criteria For Purchasing Wall Insulation (n = 9)
Price
Don't Know
Contractorllnstaller Pricing
Replace Old lnsulation
Ease of lnstall
R Value
REduce Energy Bill
Regulate lnside Temperature
Following the discussion of criteria, participants cited various factors that motivated them to
purchase and install the wall insulation measure. Three participants installed the measure
because their old insulation was insufficient to meet the heating and cooling needs of their
homes. Two participants discussed other factors such as general heating and cooling needs and to
correct a prior faulty installation.
The Cadrnus Group. lnc.l Energy Services 30
S_o_qxy- Sgy$eLn lry51
Roclry Mountain Power
Exhibit No. 5 Page 87 of '1365
Case No. PAC-E-14-07
t t ove rn U$F"l' f'Yd f d"*
Figure L1. Factors that Motivated Purchase of Wall Insulation (n = 8)
_jt
ReduceEnergyBilt W t
il
Program lncentive
Energy Savings
Among five participants, three reported that since installing the measure, the inside temperature
of their homes has become more comfortable. While not directly asked in this section of the
survey, two participants indicated that their AC or furnace runs less and that their monthly utility
bills are lower. Figure 12 presents these findings below. When asked directly, three wall
insulation participants reported that their AC or furnace runs less frequently since installing the
measure. Figure 13 presents these findings. Four participants also provided information
regarding changes in their monthly utility bills since installing the measure. All four participants
reported a difference since installing the measure; with two participants each reporting lower
bills and slightly lower bills. These findings are presented in Figure 14.
Figure 12. Changes in Comfort of Home Since Installing Measure (n = 5)
Lower Energy Bills
AClFurnace Run Less
Comfortable lnside Temperature
The Cadmus Group. lnc. / Energy Services e.{gt
ngglv- Sg-q$eir fq-ysr
Rocky Mountain Power
Exhibit No. 5 Page 88 of '1365
Case No. PAC-E-14-07
lv ove rn U$i'l' f 'Pd td"*
Figure 13. Changes in AC/Turnace Since Installing Measure (n = 4)
---......-......._i
Cools/Warms Better
Runs Less Frequently
Clothes Washers
Participants were asked to list the factors that motivated them to purchase a qualifying clothes
washer. More than half (577o) of respondents indicated that their old clothes washer was broken
and therefore needed to be replaced. For the 22Vo of respondents who cited other factors, the
most common factor was appliance features such as front-loading, greater washing capacity, or
water efficiency.l3%o pwchased a new clothes washer to take advantage of potential energy
savings associated with high efficiency appliances. The program incentive motivated 27o of
participants to purchase a new clothes washer. Additionally, some participants purchased a new
clothes washer following the purchase of a new home. These findings are presented in Figure 15
below.
The Cadmus Group. Inc. / Energy Services 32
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 89 of 1 365
Case No. PAC-E-14-07
ttovernU8F l'f'Pdfd"*
Figure 1.5. Factors that Motivated Purchase of Clothes Washer (n= 226)*t
Dealer Recommendation
Program lncentive
Reduce Energy Bills
Energy Savings
Other
Old CW Not Working Properly/Broken
The majority of participants (223) installed the clothes washers in their homes; three were
installed in locations other than primary residences. These 223 participants were then asked
about changes in usage, product satisfaction, and incentive satisfaction. The weekly average of
typical wash loads was 7.7 when weighted by the distribution of participant responses. The
weekly distribution of wash cycles is presented in Figure 16.
Ot 97 participants reporting a change in their number of weekly wash loads , 8'l7o reported doing
fewer loads per week and l37o reported doing more loads per week. Figure 17 below
summarizes wash load frequencies as reported by program participants.
Figure 16. Distribution of Weekly Wash Loads - Clothes Washers (n=220\
J---,-,,-,,,,,--.-_--,*
I
N z'u.
i
Nrn
I
0o/o
35
30
25
20
15
10
5
0
.oi.r{k'ic,{"+ic,{.r{.r'i",{.-f.r{.-{.r{.*{
The Cadrnus Group. lnc. I Energy Services ?t
Rocky Mountain Power
Exhibit No. 5 Page 90 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power NovemHUFTf'Ydfd"*
Figure 17. Change in Weekly Wash Loads - Clothes Washers(n = 97)
34Vo of responding participants indicated that the new clothes washer was easier to use. More
than one-fourth reported that the new clothes washer was better in general; however not citing
any specific reason. Other participants reported greater washing capacity (l4vo) and that their
new clothes washer uses less water (87o). These findings are presented in Figure 18. Nearly all
participants (87 Vo) were satisfied overall with the amount of the incentive; while the remaining
reported that they would have been satisfied with a slightly greater incentive.
Approximately 80Vo of participants who installed high efficiency clothes washers reported that
they were very satisfied with their new appliance. Another l77o reported being somewhat
satisfied. The remaining respondents reported that they were either not very satisfied or not at all
satisfied with their new clothes washer. These findings are presented in Figure 19. Overall, 65Vo
are very satisfied with the program and 297o are somewhat satisfied with the program. Only l%o
of paticipants reported that they were not at all satisfied with the program. These results are
shown in Figure 20.
I
ii
I
I
i
I
Iii
I
I
I
ii
i
i{
I
I
II
i
I
it
The Cadmus Group. lnc. I Energy Services 34
Rocky fuXountain Pawer
Roclry Mountain Power
Exhibit No. 5 Page 91 of 1 365
Case No. PAC-E-14-07
ruovemU$,F'l'f'Y$f#"*
Figure 18. Changes in Comfort and Ease of Use - Clothes Washers (n = 135)
ii:!rr!
i aleaner Clothes aN ,*
i orier Clothes N i4%
i ottrer N sv.
I thorrercyctes N u*I unoneruyctes w 5% i ilrlrii Uses Less water N dx iiiiiii GreaterWashingGapacity W*N ltli t.tterlnGeneral NN
i aasierToUse WNi i.-.............i*..-L--.--j -
! 0% 5% '10% 15o/o 20% 25% 30o/o 35% 40o/o
Figure 19. Participant Satisfaction with Clothes Washers (n = 222)
The Cadmus Group, lnc. l HnerEy $ervic*s
Rocky Mountain Power
Rocky Mountain Por/er
Exhibit No. 5 Page 92 of 1 365
Case No. PAC-E-14-07
Novem$HF l'5:'Yd8d"*
Figure 20. Overall Program Satisfaction - Clothes Washers (n=223)
Refrigerators
Just over half of the refrigerator participants purchased a new refrigerator because their old one
was not working properly or was broken, as shown in Figure 21 below. Potential savings
associated with installing the measure was cited by 13Vo and the program incentive was cited by
3Vo. Another I0Vo reported purchasing the measure following a new home purchase.
Figure 21. Factors that Motivated Purchase of Refrigerators (n = 112)
l-.*-- .-*-* "---*, ,-** -;----- -l,iiiiii: ttomeRemodel Srz.i i i i i i i:Jiiiiiil:iiiili:i
i 'rosramncentveMi,.iili:i
:jiiliili
Features
New Home Purchase
Energy Savings
Old Ref. Not Working ProperlylBroken
Participants were asked if there had been any changes in ease of use with their new refrigerator.
About one-fourth of participants were happy with new features such as a bottom freezer and
water/ice cube dispenser. One-fifth cited more space and greater storage capacity as a key
change associated with their new refrigerator. Approximately the same number of participants
The Cadmus Group. lnc. / Energy Services ?R
Rocky Mountain Power
Exhibit No. 5 Page 93 of I 365
Case No. PAC-E-14-07
11o_y_e_yUeillS1Pdld::::Rocky Mountain Power
reported no changes in comfort and ease of use as did participants who
refrigerators were generally better. These findings are shown inFigtre 22.
Figure 22. Reported Changes for New Refrigerators (n - 87)
their
Uses Less Energy
QuiEter
Better Gooling Features
Runs Less
Less Space
N1%
N1%'tM2%.i.WN
5Yo
5Yo
30o/o20Yo10o/oSYolYo
NotAsGoodAsOld W 7%
Better ln General
No Change
More Space
Features
15o/o 25o/o
Overall, participants were very satisfied with their new refrigerators. A combined 9Vo of
participants were either not very satisfied or not at all satisfied with their refrigerator. Nearly all
participants (907o) were satisfied with the amount of the incentive and 60Vo of participants were
satisfied overall with the incentive program for energy-efficient refrigerators. Measure and
program satisfaction results are presented in Figure 23 andFigxe 24.
Figure 23. Participant Satisfaction with Refrigerators (n = 103)
Somewhat
Satisfied,
16Yo
Very Satisfied,
75%
Not At All Satisfied,
The Cadrnus Group. Xnc. / Energy Seruices
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 94 of 1 365
Case No. PAC-E-1447
l.t ove n'r USF l' f 'Yd td"*
Figure 24. Overall Program Satisfaction - Refrigerators (n = 104)
Dishwashers
Dishwasher participants discussed different factors that motivated them to purchase an energy-
efficient dishwasher. 58Vo of participants purchased a new dishwasher because their old one was
inoperable or broken. 9Vo purchased a new dishwasher because of potential energy savings
associated with installing the. Additionally, lSVo discussed other factors that motivated their
decision to purchase a new dishwasher. These include features, price, and installations following
a new home purchase. Figure 25 summarizes these findings.
Figure 25. Factors that Motivated Purchase of Dishwashers (n = 79)
i.i:iliiillii pricems1 i i i i i i iriiii
New Home Purchase ffi sg* i i ijrt!ii
Features Wsy. i i i
ilt:
rl
EnergySavings W
-.i
Other
Old DW Not Working Properly/Broken
On average, participants run their dishwashers 5.8 times per week.
Figure 26 shows the distribution of reported weekly cycles. In terms of overall satisfaction with
the new dishwasher,'70Vo of participants were very satisfied and 237o were somewhat satisfied.
38The Cadmus Group. lnc. I Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 95 of 1 355
Case No. PAC-E-14-07
Rocky Mountain Power
The remaining participants reported that they were not very satisfied or not at all satisfied with
their new dishwasher.
Figure 26. Distribution of Weekly Cycles - Dishwashers (n - 78)
NovernHHF l'f'Pd8d"*
18
16
14
12
10
8
6
4
2
0
Snp$..$'r.ls..lo"t".*tt"t^"*n""..,t
About one-fourth of dishwasher participants reported that their new dishwasher runs quieter than
their old one Figure 27. Another quarter indicated that their new dishwasher results in cleaner
dishes. Participants also indicated that their new dishwasher is generally better, easier to use, and
has greater washing and loading capacity.
Figure 27. Changes in Comfort and Ease of Use - Dishwashers (n = 38)
Not As Good As Old
No Change
Greater Washing Capacity
Easier To Use
Better ln General
Cleaner Dishes
Quieter
In terms of measure satisfaction 70Vo reported that they were very satisfied and 23Vo reported
that they were somewhat satisfied. Only ZVo reported that they were not at all satisfied with their
new dishwasher. Overall, 597o were very satisfied with the incentive program for dishwashers
and29Vo were somewhat satisfied. These findings are shown in Figure 28 and Figure 29 below.
i ..11..........11..........11.
The Cadnius Group* Xnc. / Hn*rgy $ervices {u
=*, onT,Xl? I"iTi?:i iffi;
Case No, PAC-E-'14-07
Somewhat
Satisfied,
23%
Very Satisfied,
70o/o
Figure 29. Overall Program Satisfaction - Dishwashers (n = 78)
Somewhat
Satisfied,
29o/o Very Satisfied,
59%
Electric Water Heaters
39Vo of electric water heater participants installed the measure to take advantage of potential
energy savings. Replacing an electric water heater that was broken or not working properly was a
secondary factor reported by 287o of participants. Another l77o reported that new trends and
features associated with electric water heaters motivated them to purchase the measure. These
findings are presented in Figure 30 below.
Don't Know,
BYo
NotVery
Satisfied,
3o/o
Not At All
Satisfied,
1o/o
40The Cadrnus Group. Inc. I Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 97 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power t*t ove nn flSF l' f 'ryd f d"*
Figure 30. Factors that Motivated Purchase of Electric Water Heaters (n = 18)
Recommendation
Reduce Energy Bills
TrendslFashions
Old Unit Not Working ProperlylBroken
Energy Savings
' 0o/o 5o/o'l0o/o15oh20Yo25Yo30%o35Yo40%o45Yo i
Electric water heater participants also discussed changes in comfort and ease of use associated
with their purchase. Figure 31 summarizes these results. 467o of. participants reported that hot
water lasts longer and l5Vo reported that their water heats up faster as a result of their new
electric water heater. However, 38Vo of participants who installed the measure did not feel that
there had been any change in comfort associated with their new electric water heater.
Figure 31. Changes in Comfort and Ease of Use - Electric Water Heaters (n = 13)
*-*'--*---i
No Change
Hot Water Lasts Longer
In general, participants are satisfied with their electric water heaters; with 807o reporting that
they are very satisfied and l3%o reporting that they are somewhat satisfied. Only 1Vo are not very
satisfied with the measure. Overall, program satisfaction was mixed among participants. While
only 36Vo reported that they are very satisfied, 35Vo reported that they are either not very
The Cadrnus Group. lnc. / Energy Services r+l
Roclry Mountain Power
Exhibit No. 5 Page 98 of 1 365
Case No. PAC-E-14-07
Rocky fulountain Power
satisfied or not at all satisfied with the program, commenting that the incentive amount was too
low. Additionally, 29Vo of participants could not convey their satisfaction with the program.
Figure 32 and Figure 33 present these findings.
Figure 32. Participant Satisfaction with Electric Water Heaters (n = 15)
NovernilHFT'f'Ydfd"*
Somewhat
NotVery
Satisfied,
7%
Satisfied,
13o/o
Figure 33. Overall Program Satisfaction - Electric Water Heaters (n = 14)
NotVery
Satisfied,
21o/o
Windows
More than half of the windows participants purchased the measure because their old windows
were defective or not functioning properly. About one-fifth of participants discussed other
motivating factors such as installations following a home remodel, price, quality, and style.
Potential energy savings associated with installing energy-efficient windows motivated l47o of
participants to purchase the measure. Only 5Vo of participants cited the incentive as a motivating
factor. Figure 34 presents these findings below.
The Cadmus Group. lnc. / Energy S*rvices 42
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 99 of 1 365
Case No. PAC-E-14-07
Novenr$$f"l' 51Yd f d"*
Figure 34. Factors that Motivated Windows Purchased (n = 20)
i Program lncentive
i Don't Know
i E----.. a-.,:---Energy Savings
Other
Old Windows Defective
10o/o 20o/o 30% 40o/o 50% 60%
Nine windows participants reported changes in comfort and ease of use after installing qualifying
windows. Figure 35 shows that five participants (567o) reported that new windows provide better
heating and cooling efficiency. Three reported that there had been no changes as a result of
installing the measure and one participant reported that the new windows are not as good as their
old ones.
Figure 35. Changes in Comfort and Ease of Use - Windows (n = 9)
Not As Good As Old
No Change
Better Efficiency
Windows paticipants are largely satisfied with the measure; with 87Vo reporting that they are
very satisfied and I3Vo reporting that they are somewhat satisfied. Overall, two-thirds of
participants were satisfied with the program and 27Vo were somewhat satisfied with the program.
Another 7Vo cotld not say for certain whether they were satisfied or dissatisfied. Figure 36 and
Figure 37 present these findings below.
43The Cadmus Group. lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 100 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power tot ove m HIIFI' f 'Yd f d'-*
Somewhat
Figure 36. Participant Satisfaction with Windows (n =15)
Very Satisfied,
87o/o
Figure 37. Overall Program Satisfaction - Windows (n = 15)
lSomewhat
Satisfied,
27Yo
Very Satisfied,i--"w::,---l
Lighting Fixtures
Seven lighting participants discussed various factors that influenced their decision to purchase
this measure. As shown in Figure 38, three participants purchased the measure for potential
energy savings and one participant replaced defective lighting. Two participants discussed other
factors such as measure price and that a spouse had requested they purchase the measure. One
participant was not sure what motivated him to purchase qualifying lighting.
Overall, all seven lighting participants were very satisfied with their new lighting and very
satisfied with the incentive program for lighting.
The Cadmus Group. lnc. / Energy Services 44
ntgIv-S-"tlisf le-vsi
Rocky Mountain Power
Exhibit No. 5 Page '101 of 1365
Case No. PAC-E-14-07
tu ove rn USFT' 51Yd 8d"*
Figure 38. Factors Motivating Purchase of Lighting (n = 7)
Don't Know
Old Lighting Defective
Other
Energy Savings
Dealer Survey Analysis
HES Marketing and Program Awareness
Dealers were asked at the onset of each interview how they had heard about the HES Program.
All 30 dealers reported that they knew about the program and indicated how they initially heard
about the program. 38Vo of the 30 dealers heard about the program from HES staff who delivered
marketing materials to their store. The remaining dealers heard about IIES primarily through
word of mouth, the utility, or through other dealers. Figure 39 below summarizes these findings.
Figure 39. HES Program Knowledge Dealers (n=29)
Prior Knowledge
Other Retailer
Utility
Word of llouth
HES Staff
0o 5o/o 10o/o 15Yo 20Yo 25Yo 30% 35%
Just over 64Vo of dealers also reported that they received program and marketing materials from
Rocky Mountain Power or PECI staff this past year. Dealers were asked to rate the information
provided by Rocky Mountain Power on a scale of I to l0; with 1 meaning that there was too
4.5The Cadrnus Group. lnc. / Energy Services
R qg[y_ rt t g q$*n P
-o__rygt
Rocky Mountain Power
Exhibit No. 5 Page 102 of'1365
Case No. PAC-E-14-07
Nove'nHUF l'f'Pdfd"*
little information and 10 meaning that there was too much information. Figure 40 shows that
307o of dealers rated the marketing material as a 6; indicating that in general the material was
appropriate. One fifth of dealers rated the material as 7 and another fifth rated the material as
either an 8 or a 10; indicating that the material was perhaps too cumbersome or difficult to
understand. When weighted by frequencies of dealer responses, the average rating is 6.25.
Feedback about the material was generally good as well. More than half of the 17 dealers who
responded to this question indicated that overall the materials were very informative and that
nothing was lacking. Four dealers suggested that they would like to see more information
regarding rules, qualifying models, and updated information. Two dealers requested that Rocky
Mountain Power supply them with more incentive applications each year to accommodate
growing demand for energy-efficient products.
Figure 40. Marketing Material - Dealer Ratings (n = 20)
i Ratino of 3t-
i
ii*.-.......-__-'-'_
10To 25Yo 30To 35Yo
307o of dealers reported that the product clings (i.e. product stickers) used to advertise the
program incentive were very useful. The product clings make it easier for dealers to sell energy-
efficient appliances because the efficiency ratings and incentive information are easy for
customers to see. 20Vo discussed other marketing materials such as pamphlet and website
information as the most useful. Another fifth cited incentive applications as the most useful
marketing material. Figure 41 below summarizes these findings. Additionally, dealers suggested
that Rocky Mountain Power deliver more product clings and incentive applications each year.
4.6
I Rating of 7
Rating of 6
Rating of 5
Rating of 4
The Cadmus Group. lnc. I Energy $ervices
Rocky Mountain Pourer
Roclry Mountain Power
Exhibit No. 5 Page 103 of 1365
Case No. PAC-E-14-07
uovemWSFl'5:Ydfd"*
Figure 41. Most Useful Marketing Material - Dealer Point of View (n = 20)
FAQs
Posters
List of QuallfiEd Products
Applications
Other
Product Glings
0o/o SYo 10Yo 15Yo 20o/o 25Yo 30Yo 35o/o
Overall, dealers use various methods to inform their customers of the HES incentive progam. Of
the 30 dealers, 537o inform customers about the HES Program during the initial sales
presentation. Another 207o inform customers by directing them to qualifying appliances with
product clings. Four dealers (l3%o) indicated that they do not inform customers about the
program at all. Figure 42 summarizes these findings. Additionally, about half of the 30 dealers
reported that over the last four years these tactics have increased while the other half reported
that these promotion tactics have not changed at all during the last four years.
Figure 42.Program Promotion Methods by Dealers (n = 30)
I
530h
60%
_____J
Dealers were also asked which program marketing materials seem to make the greatest
impression on customers.23Vo cited the combination of product clings and a sales person as the
most effective. Another 207o reported that customers typically respond best when a sales person
actively discusses the program. lTVo reported that customers are most likely to respond to the
product clings. Other marketing reported by dealers consisted of in-store advertising such as
posters and word of mouth among customers. One dealer reported that he does not promote the
program and one other dealer reported that he did not receive marketing materials (each accounts
Applications N gX
PosterslPrint Ads
Do Not Promote
Product Clings
Sales Presentation
The Cadmu$ Group. lnc. i Hnergy $ervices 47
Rocky Mountain Power
Exhibit No. 5 Page '104 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power
for 3Vo of dealers). Both of these dealers are contractors and generally would not promote the
program or receive marketing materials anyway. Figure 43 summarizes these findings.
Figure 43. Program Marketing Materials That Customers are Most Likely to Respond To
(n = 30)
Did Not Receive Materials
Do Not Promote
Flyers
Don't Know
Oher Marketing
Product Clings
Sales Person
Product Glings, Sales Person
In addition to the program marketing materials and signage, all 30 dealers reported that they
promote energy efficient options for customers at least some of the time. Of the 30 dealers,'ll%o
indicated that they always promote these options.lOVo reported that they often promote energy-
efficient options, and another l3Vo repofied that they sometimes promote energy-efficient
options. Figure 44 presents these findings.
Figure 44. Dealer Promotion of Energy-Efficient Options by Frequency (n - 30)
t't ove rn UITFI' f 1Yd 8d "*
The Cadmus Group.Energy
nggfv Mountain Porver
Dealers were also asked to discuss key selling points2a for energy-efficient appliances. 40Vo of
dealers reported that customers are mostly interested in the potential cost savings associated with
installing energy-efficient appliances (i.e. lower monthly energy bills). 237o cited the program
incentive as the key selling point for energy-efficient measures. Another 23Vo also cited potential
energy savings as a key selling point and two participants (7Vo) believe that product features are
the key attractor for energy-efficient appliances. Figure 45 presents these findings below.
Figure 45. Key Selling Points for Energy-Efficient Measures (n = 30)
Other
i Features
i energy Savings
i Program lncentive
:
i CostSavings
i
i
i . . ..............................................
Additionally,26 dealers were confident that on the whole their customers understand the energy-
related benefits of using high efficiency appliances. Among the four who did not think that their
customers understand energy-related benefits, some cited demographics as a possible cause.
These dealers reported that they believed that people from areas with less affluence tend to be
less concerned with energy-related benefits and more concemed with their personal budgets.
Survey administrators also asked dealers to rate their typical customer on a scale of 1 to 10 to
determine how interested a customer is in switching to an energy-efficient appliance. Responses
were most heavily weighted in the rating category of 8; indicating that overall dealers perceive
the average customer as interested in purchasing an energy-efficient appliance. When weighted
by dealer frequencies, the average rating is 7 .25. Figure 46 summarizes these ratings.
24 For the 12 dealers who cited potential cost savings as a key selling point, all ofthem also listed a secondary
selling point such as program incentive, energy savings, and product features.
4g
*-**+*
0o/o 5o/o 10Yo 15o/o 20Yo 25% 30Yo
Rocky Mountain Power
Exhibit No. 5 Page 105 of 1365
Case No. PAC-E-14-07
ru oue',n UHF"I' f 'Yd 8d"*
The Cadmus Grou$. lnc. I Energy Services
n*_gl.v_ Iy! g-V$eB ? owgt
Rocky Mountain Power
Exhibit No. 5 Page 106 of 1365
Case No. PAC-E-14-07
_ !!oos r$'qi:1 5:gd fd:l::
Figure 46: Customer Ratings by Dealers - Interest in High Efficiency Appliances (n = 28)
Rating of 10
Rating of 9
Rating of 8
Rating of 7
Rating of 6
Rating of 5
Rating of 3
Dealers were also asked to list energy-efficient appliances that their customers ztre most and least
aware of. According to more than half of the dealers surveyed, customers are keenly aware of
incentives available for clothes washers; particularly the incentives associated with front-loading
clothes washers. Customers were not as awa.re of the incentives for refrigerators or deep freezers.
A number of dealers remarked that the $20 incentive for purchasing an energy-efficient
refrigerator does not seem to incentivize people as much as the greater incentive for high-
efficiency clothes washers.
Pricing
Dealers reported different pricing methods for energy-efficient appliances. Standard-mark-up
was most frequently reported (38Vo), as shown in Figure 47 below. About one-fourth of dealers
indicated that their pricing policies reflect manufacturer recommendations for energy-efficient
appliances. The remaining dealers determined prices based on customer willingness to pay, other
dealer prices, or subcontractor installation fees.
Figure 47. Dealer Pricing Methods (n= 29)
t------- - --- -'
i tubcontractorFees Wl'u. i I i iiiii.i:iiit
Other Dealer Prices
Willingness to Pay
Don't Know
Manufaclurer Recom mendation
Standard Markup 1,,.
lYo 5Yo 10Yo 15Yo 20Yo 25o/o 30Yo 35To 40To
When discussing prices or price differences with customers, 4lVo of dealers reported that they
discuss product life-cycle costs, the value of potential energy savings associated with the
measure, costs of regular maintenance and repairs, and the discount from the program incentive.
About one-third reported that they mostly discuss the upfront cost to the customer minus the
50The Cadmu$ Group. lnc. / Energy Services
Rocky Mountain Power
Exhibit No, 5 Page 107 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power
program incentive if applicable. Another 28Vo incorporate an estimate of potential energy
savings as well as the program incentive if applicable. Figure 48 below summarizes these
findings.
Figure 48. Pricing Methods Used to Sell High Efficiency Appliances (n = 29)
Comparison of upfront equipment costs
and estimate of energy savings (program
incentive)
Comparison of upfront equipment cost
(including program incentive)
Comparison of lifecycle cost including
value of energy savings (including
program incentive)
OYo 5o/o 10Yo'l5To 20Yo 25o/o 30o/o 35o/o 40o/o 45oh
Dealers did not believe that their participation in the program affected the way in which they
present price differences to customers. About half of dealers (53Vo) said that the program and
marketing materials did not have an impact while 40Vo reported that the program did have an
impact on how they present prices to customers. Dealers also explained that for refrigerators and
dishwashers, there are very few non-efficient options on the market so they typically sell high-
effi ciency appliances anyway.
Program Perception Among Dealers and Suggestions to lmprove HES
Nearly all of the Idaho HES participating dealers offered positive feedback about the program.
Only five dealers were not happy with the program; three of which were contractors. The
following dealer quotes are most representative of the 24 positive reviews25:
"It is a goodprogram; beneficial to the customer and helps reduce their electricity/gas bill."
"Good program - great tool for us on the floor to sell products. The program can help us be
perceived as a green compony."
"Any incentive that con get the general public to upgrade and save energ/ is good. "
"I want to know more about it - think it's a good idea, but don't know much about the program "
The following dealer quotes represent some of the five negative responses about the HES
prog.am26:
These first three positive comments came from interviews with dealers/retailers and the fourth comment came
from an interview with a participating contractor.
The first two negative comments came from interviews with participating contractors and the third negative
comment came from a dealer interview.
Novem$Hi'l'51Yd8d"*
The Cadmus GrCIup. lnc. I Energy $ervices q,!
Rocky Mountain Power
Exhibit No. 5 Page 108 of 1 365
Case No. PAC-E-14-07
Rocky klountain Power
"Would be nice to get more information so I can offer it to customers. Program is under-utilized,
needs to be promoted much more than it is. I think more people would be interested in bringing
their homes up to current energy standards. "
"They are really picky about paperwork They kick applications for a missing date - a little too
piclE."
" Don't put sticker on rilirong model, and if so, don't make retail store pay the rebate the customer
thought they were getting. "
Dealers also offered suggestions on how Rocky Mountain Power can improve the program and
therefore increase market penetration of high efficiency appliances. Some dealers suggested that
the standards for efficiency change too often and make it difficult to stay current with the
program. This dealer also reported that constantly having to refer to an information sheet gives
customers the impression that staff are not knowledgeable about the program. Another dealer
suggested that Rocky Mountain Power should increase marketing efforts for smaller towns and
areas outside of major metropolitan areas.
Lastly, one dealer suggested that Rocky Mountain Power should provide information to
customers that explain why the utility is paying them to purchase an energy-efficient appliance.
This dealer also indicated that this might "allay suspicions" among customers.
Clothes Washer Recycling Through HES Program
Among 19 dealers who reported selling clothes washers, 13 of them recycle old clothes washers
when customers purchases high-efficiency models. However, only two dealers recycle clothes
washers through the HES p.oglam". Furthermore, more than three-fourths of dealers were not
aware that such a Program exists. Figure 49 and Figure 50 summarize these findings.
Figure 49. Dealers who Recycle Clothes Washers Through HES Program (n = 13)
27 The data PECI provided for the HES program in 2006-2008 did not indicate participation in the clothes washer
recycling program. It is assumed that these dealers are more recent participants in the program.
NovemHBFT'f'Pdfd"*
The Cadmus Group. lnc. I Energy Services 52
Rocky Mountain Power
Exhibit No. 5 Page 109 of 1365
Case No, PAC-E-14-07
Nov*m#HF'1'f'Y$fd"*
Figure 50. Dealers Familiar with Program Requirements (n = 13)
All 13 dealers who recycle clothes washers provided feedback regarding the type of clothes
washer typically purchased by customers who want to get rid of their old one. Just under one-
fourth of dealers reported that customers typically purchase either a high efficiency clothes
washer (MEF > 2.0) or a lower efficiency unit (MEF between 1.72 and 1.99). Other clothes
washers, as reported by three dealers, were generally described as energy-efficient models or
front-loading models. See Figure 51 below.
Figure 51: Clothes Washers Purchased After Recycling Old Unit (n = 13)
Energy Star MEF > 2.0, Energy
Star 1.72 < MEF < 1.99
Other
Energy Star 1.72 < MEF < 1.99
Energy Star MEF > 2.0
Don't Know
0% 5o/o 10o/o 15Yo 20%
More than three-fourths of dealers reported that they both deliver new clothes washers to
customers and haul the old one away to a recycler. One reported using a contractor for delivery
and hauling. Figure 52 summarizes these findings. Dealers were also asked if they test old units
for operability prior to taking it to a recycling center. Four dealers test old units for operability,
three do not test for operability, and six dealers did not know. Among the three who do not test
for operability, one reported that the testing is too time-consuming, most of them do not work,
and they do not plan to resell them anyway. Table 16 summarizes these findings.
Table 16 also presents results regarding serial number collection, frequency of clothes washer
recycling, and receipt collection. Six dealers' record model and serial number while four do not.
Additionally, only two dealers reported turning in receipts to the utility. Six dealers reported that
The Cadmus Gruup. lnc. I Hnergy Seruices
Rocky Mountain Power
Roclq Mountain Power
Exhibit No. 5 Page 1 10 of 1 365
Case No. PAC-E-14-07
trtovernH8F l'fYdfd"*
they always recycle while four reported that they do not always recycle. Survey administrators
probed further and learned that one dealer scraps old units and sells functioning parts.
Figure 52. New Clothes Washer Delivery Methods (n = 13)
Utility Staff and lmplementer Interviews
Cadmus staff interviewed multiple parties to gain an in-depth understanding of the Rocky
Mountain Power HES program. The interviews included key utility staff members as well as
implementation staff directly involved in program operations. As HES is implemented by a third
party, utility staff interviews primarily focused on high-level management and regulatory issues,
while program-level details generally were addressed in interviews with implementers. Interview
results reflected this divided focus.
Program Management
Program Design
The HES Program spans five states. As the areas served have distinctive demographic and
geographic characteristics, implementers have tailored program offerings as much as possible to
unique constituent characteristics, as tariffs allow:
"We trlt to balance customization to the five service areos with standardization that
leverages the resources available. "28
28 Implementerlnterview
Table L6. Clothes Washer Recycling Questions (n = 13)
The Cadmus Group. lnc. / Energy Services 54
Rocky Mountain Power
Exhibit No.5 Page 1 I1 of 1365
Case No. PAC-E-14-07
Sggfy_ rdgq$$ floygi
The programs' initial design was intended to create a "fuel blind" program, offering energy-
efficiency measures to all customers regardless of the utility's service. Implementers explained:
"We put every measure we could think of in the initial mix and then worked through all
the sivings analyses to determir ed the amount of deemed savings for each measure. "2e
Analysis of program cost-effectiveness provided estimated savings for each measure in each
state, reflecting the territories climate. Seeking to make each measure independently cost-
effective, program designers also included measures such as insulation and ENERGY STAR
windows in natural gas-using areas to provide comprehensive program offerings.
For the initial program design, implementers were required to manage the program so at least
half of the overall program savings could be attributable to non-lighting measures. This was
partly due to the relative ease of obtaining lighting savings, compared to other measures and the
desire to make the program have a direct impact that is more visible to customers. By contrast,
lighting's upstream incentive approach often made the program invisible to customers.
Program staff have since realized benefits of a bundled program approach including, to some
extent, avoiding duplication in management, marketing, and program delivery. The bundled
approach also offers several advantages: consistent design for the utility Web site and in
promotional materials; economies of scale; an ability to leverage synergies in product offerings;
and an ability to analyze the different markets and test new approaches with market actors.
Reflecting on how the program's structure compares with those of similar programs, one
implementer said:
"This program ls the most complex I've ever dealt with. There are savings and
efficiencies by shared marketing, but we've learned we cannot apply the same tactics in
every market. "3o
As a result, implementers provided input to program design to reflect changes in the market
place.
Key program design findings include:
o The HES Program was designed to be a comprehensive, "one stop shop" for home
efficiency measures.
o Measures included in the program had to be individually cost-effective.
o The combination of multiple measures and different state regulatory environments
resulted in a highly complex program to manage.
Program Strengths
The multiple measure approach made HES Program participation more convenient for customers
as the program offered a single application for incentives and access qualified resources for
measure installation and sales.
tnt ove m Hl$i"l' f 'Yd f d"*
2e Ibid30 Ibid
The Cadmus Group. lnc. I Energy Services 55
Roclry Mountain Power
Exhibit No. 5 Page 112 of 1365
Case No. PAC-E-14-07
Rocky htlountain Power
Program Challenges
Despite the advantage offered by some economies of scale, providing a high service level for
smaller markets represented a significant challenge. Rocky Mountain Power staff remarked on
the difficulty of tuning into each market:
"Small market point-of-sales are less sophisticated and there are fewer
dealers/retailers. They need support and training in the same way that large retailers
do, but their lower sales volume represents higher administrative costs. This makes it
tough to operate within the required cost-benefit ratio in certain markets."
Adjusting the program to meet rapid marketplace changes proved another challenge for the
program, which could not be modified until tariffs changed. One implementer characterized this
challenge as:
"Tryng to pull free market levers in an environment of regulatory controls."
A third challenged presented itself with through companion incentives from various sources,
including federal stimulus funding, federal income tax credits, manufacturers, and other utilities
serving the same customers or in adjacent territories. [n particular this was evident in the
misalignment of pricing of bulbs offered through this program and those offered through the
Bonneville Power Administration (BPA) and Northwest Energy Efficiency Alliance (NEEA)
programs. During the 2006-2008 program cycles, incentives for lighting measures were offered
by two regional programs, in overlapping service territories. While the three programs (BPA,
NEEA and Rocky Mountain Power) were effectively coordinated for most of this time, each
underwent restructuring at different times in 2008. The result was that the programs were out of
sync in 2008 and participation in Rocky Mountain Power program dropped off significantly,
negatively impacting the program cost-effectiveness.
Changes to Program and Goals
CFLs have been the most cost-effective measure, and contributed the largest component of gross
energy savings for the program. Lighting measure incentives were delivered using an upstream
approach, which provided incentives to CFL manufacturers to lower costs to retailers. [n recent
years, the program expanded from incentives on basic twister models to a variety of specialty
light bulbs. However as Rocky Mountain Power indicated in their 2008 Annual Report:
"The Home Energt Savings program under-performed in 2008 due to a
reduction in lighting savings and increased costs associated with weatherization
measures. Retail locations and delivery interactions associated with regional
lighting offerings were all contributing factors to these results. In 2006 and
2007 the Home Energy Savings program benefited from its alignment with and
savings attributions from the regional lighting progranl In 2008 Rocky
Mountain Power intended to continue its support of the regional effort when the
company made its changes to the 2008 Home Energy Savings program s
lighting measures. However due to timing differences of when the lighting
initiative redesigns occurred, the opposite occurred, the two programs ended up
not in alignment on the pricing of specialty bulbs. This lack of alignment
NovemS$'iT'f]Y$fd"*
The Cadmus Group. lnc. i Energy Services
Rocky Mountain Power
Roclry Mountain Power
Exhibit No.5 Page 113 of 1365
Case No. PAC-E-'14-07
NovemU$F l'{:'Ydfd"*
presented two options to the company; 1) the Home Energy Savings offer could
be changed again in 2008 to correct the situation or 2) Rocky Mountain Power,
though PECI, could seek other paths to ensure the program's lighting savings
were secured and wait until the next program change before aligning again
with the regional progranl Wrile the options were not mutually exclusive, the
company elected to not change the program twice in 2008 and instead to pursue
a small market strategy of enrolling smaller retailers in the market, those more
strategically located in the company's rural service areas in Idaho. Many of
these smaller retailer chains indicated an interest at the corporate level;
however delays in generating interest at the individual store level resulted in a
delay in the discounted lighting options becoming available on store shelves. As
a result, lower than anticipated CFL bulb sales contributed to reduced energy
savings through the Home Energt Savings program in 2008."
This misalignment as well as the positive response from smaller retailers to the program helped
shape changes to the program moving forward.
Insulation participant numbers increased in 2008. The increase was based on a significant
reduction in costs driven by an increase in insulation contractors and a reduction in raw material
costs. With contractors increasing their marketing activities to customers and utility incentives,
insulation participation increased beyond the 2008 estimates. Because insulation was intended to
be offered as part of a cost-effective package with other measures and does not pass cost
effectiveness standards on a standalone measure basis, adjustments to the insulation program
were also in order.
Program changes included:
o Regional program realignment;
o Enrollment of small retailers in the CFL program;
o Addition of efficient, specialty light bulbs, in addition to standard twister CFL;
. Specialized dealer incentives for duct sealing; and,
o Realignment between costs and incentives as well the addition of a per house cap to the
Insulation program.
Marketing
PECI has developed marketing plans, materials and proposed marketing budgets for each state,
with review and approval by Rocky Mountain Power. Estimated conversion targets for each
marketing tactic have driven priorities for channel and media weight. Budgets were developed,
using the previous year as a guide, and goals, expenses, and projected savings were adjusted.
Marketing efforts primarily focused on key customer contact channels through retailers, trade
allies, and the company web site. Investment in mass media channels, such as television, radio,
and print advertising, was comparatively less than more targeted approaches. Marketing
promotions drove prospective participants to the program's Web page for information and
applications. PECI also provided creative design for marketing materials, and worked with the
Rocky Mountain Power marketing team to incorporate edits and move to scheduling.
The Cadmus Group. lnc. l Energy Services
Rocky Mountain Polver
Exhibit No. 5 Page 1 14 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power
Implementers reported evaluating and building on the market approaches that proved the most
effective. Recently, implementers have started exploring a marketing segmentation approach,
targeting messages to specific customer characteristics. An online web survey has also been
introduced recently. Data from efforts will be evaluated to determine the best use of available
marketing dollars.
In summary:
o Marketing strategies have focused on retailers, trade allies, and the web site;
o PECI has started using a market segmentation approach to target specific, higher-
potential customers.
Awareness
While point-of-sale contacts with retailers and trade allies were considered the primary
mechanism for program awareness, the call center experienced increased inquiries about the
program immediately following a bill insert promotion.
Training
PECI employed two staff as designated trainers for the program. They focused on HVAC
contractors, providing training and updates on how to conduct AC tune-ups, duct sealing, and
proper procedures for insulation. A primary training issue has been identifying differences
between conditioned and unconditioned space, as this is a critical criterion for application
approval.
Rocky Mountain Power staff has remained current regarding changes in program components by
attending measurement-related conferences, staying up to date with code and standard changes,
studying current and upcoming topics (such as smart grid technology); and sitting on national
panels.
Communication
Interviews with implementers indicated PECI valued communication as an important customer
service component. They have tailored communication to the needs of their stakeholders, which
include: Rocky Mountain Power executives, regulatory stakeholders, contractors, dealers, and
customers.
For external stakeholders, such as customers, implementers have posted program updates to the
web site, provided updates to the direct services call center, and issued public notices. PECI has
called contractors directly when tariff changes have taken effect.
Internal Reporting
Implementers screen program applications for completeness prior to entering applications into a
database. The database is then used to generate a report for Rocky Mountain Power and trigger
incentive payments. Rocky Mountain Power reviews applications, and then sent them back to the
implementation project manager. PECI also fields occasional ad hoc data requests, and provide
custom reporting to program staff.
ruovenrUlfF l'f:Ydfd"*
The Cadrnus Group. lnc. / Energy $ervices 4R
Rocky Mountain Power
Exhibit No.5 Page 115 of 1365
Case No. PAC-E-14-07
Rocky h4ountain Power
Financial reports were generated weekly, with PECI pulling information from the database and
aligning it with invoice reporting to Rocky Mountain Power. On the 28'n of each month, a
participation update report is generated for each state; this report included every measure;
monthly and year-to-date progress, and goal projections. Year-end reports were generated to
review program results.
Quality Control
Quality controls have been established at a number of points in program delivery. Both PECI and
Rocky Mountain Power staff reviewed applications. Data were reconciled from the database and
incentive checks are generated. Implementers searched for anomalies in participation reporting,
seeking to identify issues before they could impact cash flow or cost-effective delivery or
customer service levels. PECI also conducted inspections on a minimum of 57o of HVAC,
insulation, and window installations. To eliminate any bias, inspectors were not provided with
incentive information.
Rocky Mountain Power staff inspected a number of applications to verify square footage,
insulation levels, window types, and other factors. If anomalies occurred in data quality or
contractor reports, they increased numbers of inspections conducted with those particular
vendors.
Based on site visits that we conducted for the Utah HES program3' we determined that the
PECI's inspections had not yielded higher realization rates. PECI stated that they have increased
staffing levels to do more inspections. Further, they have recently worked to improve tools used
in inspections, such as using laser measures for square footage.
Rocky Mountain Power staff described proactive efforts to address quality: "Continuous
improvement is driven by promptly addressing the problems but also by trying to avoid potential
problems."
In summary:
o Quality Control inspections have been established for 57o of HVAC, insulation, and
window installations.
o PECI increased staff to complete more inspections, and instituted more sophisticated
equipment for greater precision in inspections, such as laser measures for square footage.
Market Barriers
HES program participation barriers varied by measure type. The following paragraphs outline
known barriers to the primary measure types.
Lighting
The rural nature of the territory and other regional programs offered by Bonneville Power
Administration (BPA) and Northwest Energy Efficiency Alliance (NEEA) in the same territory
presented barriers for the CFL program. In particular this was evident in the misalignment of
pricing of bulbs offered through this program and those offered through the Bonneville Power
3l Site visits were only conducted in Utah due to the very high participation in the insulation measure in that state.
l.t ove rn Ul$F 1' 51Pd Id"*
The Cadrnu$ Group. Inc. / Hnergy Services qo
Rocky Mountain Power NovernUBFT'{1Ydfd"*
Administration (BPA) and Northwest Energy Efficiency Alliance (NEEA) programs. While the
three programs (BPA, NEEA and Rocky Mountain Power) were effectively coordinated for most
of this time, each underwent restructuring at different times in 2008. The result was that the
programs were out of sync in 2008 and participation in Rocky Mountain Power program dropped
off significantly.
Additional lighting market barriers included: concerns about mercury in bulbs; inconvenient
recycling options; compromises to bulb lives when placed in a dimmable socket; the tone or
color oflight produced; and delayed start ofbulbs.
The program addressed these barriers by using information about newer CFL bulb features and
specialty bulb availability. The program Web site also provided information on recycling options
for expired CFL bulbs.
Insulation
Insulation market barriers included: the process required for qualifying a home for the insulation
incentive; homeowners' processes for finding qualified installers and confirming the jobs-met
program requirements; and upfront costs.
To address these barriers, implementers worked closely with builders and contractors to try to
transform the market, working to inform builders and homeowners of the need for and value of
higher insulation levels.
Appliance
Barriers to high-efficiency appliances largely involved prices and higher incremental costs.
Awareness for the ENERGY STAR label seemed high, as many manufacturers promoted
ENERGY STAR products independently. For dishwashers, where 95Vo qrualified as ENERGY
STAR, energy savings on a per-unit basis became marginal, making the measure less cost-
effective as a program offering.
As most appliances were bought and sold at retail outlets, implementers worked to inform sales
staff of benefits from efficient equipment and reduce market barrier effects. Another approach
was continuing to advocate higher-efficiency standards; so, as a base offering, ENERGY STAR-
labeled products provided greater energy savings than non-ENERGY STAR products.
HVAC
Market barriers for high-efficiency HVAC equipment included: awareness; high incremental
costs; and, in some climates, payback periods and varying equipment efficiencies. HVAC
equipment was generally installed as needed, replacing nonfunctioning units. lmplementers
noted: "It's not typically something for which many homeowners shop around." Opportunities
for higher-efficiency equipment could be missed if plumbers or HVAC technicians were
unaware of incentives available or, in some cases, simply chose to move inventory readily
available.
The Cadrnus Group. lnc. i Energy Services 6S
Rocky Mountain Power
Exhibit No. 5 Page 1 17 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power
Implementers provided HVAC contractors with information required to help sell higher-
efficiency equipment. The program's involvement ensured units were installed to proper
standards and addressed subtle issues related to climate zones.
Future Program lssues
ln 2012, federal standards will require all light bulbs have higher efficiency ratings than current
standard incandescent bulbs. CFLs thus may essentially become the new standard, which will
significantly affect all lighting programs. While progmm staff expects continued savings from
CFLs after new regulations come into effect, they anticipate types of qualifying CFL bulbs will
change. Looking ahead to2012, progrtrm staff indicated: "There are still a lot of unknowns for
tighting. We think there will still be a lot of product out there in 2012, and we don't believe all
incandescent bulbs will be completely phased out. " lrnplementers said their strategy is still
developing, but they are looking at newer lighting technologies, such as LEDs, which may
provide interim solutions.
PECI also believes a smart gnd's impact on residential customers presents another unknown.
Currently, many utilities are exploring or proceeding with implementing smart grid technologies
in their service territories, but the extent customers will become interested in their energy
consumption remains unclear. Program participation could increase as customers become more
aware of their energy usage; alternatively, competing products or technologies may become
av ailable, supplantin g current pro gram offerin gs.
Consumer electronics may also offer a potential opportunity for energy savings that could be
explored through HES program offerings. Currently, televisions, computers, and monitors are the
only electronic equipment qualifying for ENERGY STAR labels. As home electronics
manufacturers continue to adopt energy-efficiency technologies (e.g., DVRs, game consoles, and
sound components), further opportunities may emerge for energy savings.
Program Development
In 2010, PECI plans to implement the program more proactively. These efforts will include:
tightening the quality control process; focusing on the trade ally network; and continuing to
monitor trends in data collected and evaluate associated market implications. PECI is working to
streamline the manufacturer contracting process; so changes can be made within a 30 to 60 day
timeframe. Future program development will be influenced by AARA-funded companion
incentives. Program staff and implementers will assess effects of these incentives, especially
focusing on impacts on clothes washers and electric water heaters.
Rocky Mountain Power views this program as a vehicle for incenting additional energy-saving
measures for homes, as technologies evolve.
t't ove rn UllF l' {lPd f d"*
The Cadn'ius Group. inc. I Energy Services fi{
Rocky Mountein Power
Exhibit No. 5 Page 1 18 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power
Rocky Mountain Power
Exhibit No.5 Page 119 of 1365
Case No. PAC-E-14-07
Novem$$F l'{:'Pdfd"*
5. Program Results
lmpact Findings
The following five subsections present the impact evaluation's findings:
1. Summary of Program Participation
2. Review of Terminology
3. Determination of Average Annual Gross Energy Consumption
4. Determination of Gross Savings
5. Determination of Net Savings
Summary of Program Participation
Starting May 2006 and continuing throughout 2007 and 2008, Rocky Mountain Power offered
the IIES program to its Idaho customers. By the end of this period, approximately 6,000
customers had participated in the program.
Annual program participation rose from 1,135 at the program's inception to 2,693 in 2007 and
dropped to 2,175 participants in 2008. During the two full program years (2007 and 2008), the
program participation was reduced by 19Vo, predominantly, due to CFL participant numbers
dropping off at this time. Table 17 shows annual program volumes to better illustrate
participation trends.
The Cadmus Group. lnc. l Energy Services lil
Rocky lVlountain Power
Rodq Mountain Power
Exhibit No. 5 Page 120 of 1 365
Case No. PAC-E-14-07
t*t ove rn Ul{,i'l' f 'Yd f d"*
Table 17. Annual Program Participation 2006-200832
Ceilino Fans 4 20 24
CentrallUC Eouioment 1 2 3
CFL 918 1,593 485 2,996
Clothes Washerss 151 597 378 1,126
Clothes Washer-Tier One 43 43
Clothes Washer-Tier Two 392 392
Dishwasher 96 205 301
Electric Water Heater 12 57 72 141
Evaoorative Cooler 1 1
Fixture 1 18 u 53
Heat Pump Uoqrade I 1
lnsulation: Attic 2 42 127 171
lnsulation: Floor 4 19 23
lnsulation:Wall 16 25 41
Proper CAC lnstall 2 2
Prooer CAC Sizino 2 2
Refrioerator 51 238 263 552
Windows 26 105 131
Total 1,135 2,693 2,',175 6,003
Several factors impact the varying participation:
o Increased awareness: The general population has become more aware of ENERGY
STAR products and their benefits.
o Advertising: Rocky Mountain Power increased advertising during this timeframe, and
more retailers and contractors became involved with the program.
o Other programs: Similar local and national programs were running at the same time.
o Economic factors: The economic downturn may have been a factor, especially for
potential participants planning on upgrading their home's efficiency. In the context of a
challenging home mortgage market where the ability to upgrade by moving to a new
home became more limited, incentives and education around a product's lifecycle costs
could have convinced participants to take action in their current homes. Retailers and
contractors also turned to existing housing stock improvements rather than new home
construction.
The participant count only included counts of individual incentives, For appliance measures, customers were
limited to one incentive per household, excepting ceiling fans and fixtures; for home improvement, participant
numbers of equaled numbers of total jobs; for HVAC, contractor incentives were not counted as separate
paticipants; and, for CFLs, participants were estimated at 10 bulbs per participant. The l0-bulb rate per
participant was based on information from PECI and the PAC-E-05-10 Annual Report of Idaho Demand Side
Management Activities.
The clothes washer category was modified to reflect new high efficiency standards in 2008: Clothes Washers:
513112006 - 4/3ll200g (MEF 1.42 in 2006 and 1.72+ in20[7 - 2008); Tier 1: 4lll20}8 - current (MEF 1.72-
1.99); Tier 2:4ll/2008 - current (MEF 2.0+)
The Cadmus Group. lnc. / Energy Services 64
Roclry Mountain Power
Exhibit No. 5 Page 121 of 1365
Case No. PAC-E-14-07
n_og[y_ mgq$ein N ove nt $SF'l' #lPd f d"*
Billing Analysis Results3a
After screening and matching account
participants and 1,032 nonparticipants.r)
the final analysis group consisted of 258
The final CSA regression model specification below was used to estimate savings from
insulation measures:
ADCit = cr + FTCDDi' + gz HDDi' + 9: POST, + Ba PARTPOSTI +B5 ANNUALPREI * s1
Where for customer (i) and month (t):
o ADCit = &ver&ge daily kWh consumption
o HDDit = ovorirge daily heating degree-days (base 65)
o CDDit = ayata:5e daily cooling degree-days (base 65)
o POSTT= indicator variable that is 1 in the 2009 post period for both participant and
nonparticipants, 0 otherwise.
o PARTPOSTII= indicator variable that is 1 in the 2009 post period for
otherwise.
o ANNUALPREI= the total annual2006 pre-period kWh usage.
The key coefficient determining average insulation savings was Ba. This value averaged daily
insulation savings per program participant, after accounting for nonparticipant trends. The
inclusion of the ANNUALPRE variable was used to create a fixed effects model specification,
ensuring no participants or nonparticipants had an undue influence over the final savings
estimate; this resulted in a more robust model.
As described in the Billing Analysis section, the Idaho billing analysis did not yield robust enough savings
estimates to accurately assess actual energy savings. It was found that the Pacific Power Washington HES
program expected savings and participant climate was a close proxy for the Idaho program.
The sample in Idaho consisted of 93 participants and 372 control customers which proved insufficient for the
billing analysis.
0
The Cadmus Group, Inc. l Hnergy $ervices fiq
Rocky Mountain Power
Exhibit No. 5 Page 122 of 1365
Case No. PAC-E-14-07
Rocky Mountain Fower
The above pooled model combined nonparticipants (the baseline) and combined participants for
the wall, floor, and attic insulation program.
Table 18 presents billing analysis results for wall, floor, and attic insulation in Washington36 as a
proxy for Idaho. The billing analysis realization rate for insulation measures was 887o. Presented
in Table 18 are savings for insulation measures for smaller-usage homes and higher-usage
homes. Smaller homes realized only I4Vo of the expected savings. Larger homes saved 1557o of
expected savings.
CFL Leakage Analysis
Cadmus' evaluated leakage of program-subsidized CFLs out of the Rocky Mountain Power
service territory. This analysis covered Rocky Mountain Power's Idaho territory during 2006
through 2009. While leakage was studied, and is presented in this report, the findings only
attempted to measure the number of bulbs for which Rocky Mountain Power provided
incentives, which ultimately left its service territory. The study did not measure the number of
bulbs bought within the service territory which were covered by incentives from other programs
such as BPA and NEEA. The effects of this "reverse leakage" are likely on par with the effects
of the leakage reported herein. Consequently this report assumes that the net leakage is zero for
purposes of determining NTG and cost-effectiveness, and additional study is recommended to
measure these other impacts as well as to confirm the findings from this initial leakage study.
Evaluation results indicated 33.77o of total program CFLs subsidized through the program leaked
outside the territory. The overall findings for Idaho, Utah and Washington combined came to
2.76Vo.
The self reported data collected from retailers turned out to be unreliable, due to retailers
confusing which bulbs were offered through which programs and a lack of incentive to perform a
more thorough lookup. Upon verifying self reported data collected from the residential
consumers it was found that on follow-up surveys, consumers provided varying result for the
number of bulbs and location purchased. The resulting study sensitivity of the leakage in Idaho
was t 22.8Vo.
Suney Oveniew
Cadmus conducted two surveys. The first targeted households not served by Rocky Mountain
Power (noncustomers) within 20 miles of Rocky Mountain Power's service territory. The second
targeted retailers participating in the Rocky Mountain Power program.
36 Due to too low participation in Idaho to perform an adequate billing analysis, the billing analysis was used from
the Pacific Power HES Washington territory. More detail of the billing analysis is provided in the Billing
Analysis section of the report.
r*t o ve rn S3i'1' f 'Pd td "*
Table 18. HES Attic, Floor, and Wall Insulation Realization Rate
Model Savings (Low to Medium Usage Homes, under 15,497 13.5Y0 G1lYo'38Y0
Model Savinqs (Medium to Hiqh Usaqe Homes over 15,497 k 155Y0 (106T0 -205o/o
&4.3T0 ATTo - 121Y0
The Cadmus Group. lnc. / Energy Services 66
E,h i b it f":'YPl,s""' llili ilfJ
Case No. PAC-E-14-07
The retailer survey's purpose was to obtain information on the number of CFLs stores sold since
the beginning of 2006, and the percentage of those subsidized by the program. Surveys were
completed with all of the 11 stores reported to have sold CFLs subsidized through the program.
The household survey was completed with 141 randomly selected households in areas
surrounding Rocky Mountain Power's service territory. The surveys asked respondents the
number of CFLs purchased by their household since the beginning of 2006, stores from which
they purchased those CFLs, and the percentage ofpurchases from each ofthose stores. In each
region surveyed, the goal was to complete surveys with 70 non-Rocky Mountain Power
customers to achieve a90Vo confidence at a +l- IlVo level of precision.
Household responses were combined with responses from retailer surveys to determine the
number of CFLs households outside the service territory purchased since 2006 and percentage of
those which were program bulbs.
Calculations, Analysis Prccess, and Resulb
Table 19 presents the number of program-subsidized CFLs purchased per household, the number
of households, the percentage of households that were Rocky Mountain Power customers and the
total number of CFLs calculated to have leaked out of Rocky Mountain Power's service territory
in each of the two regions surveyed.
Table 20 presents primary leakage calculation components used to determine the percentage of
program bulbs leaked outside the territory.
Calculations
The following four primary calculations were used in estimating the CFL leakage:
1. Calculate the number of program-financed CFL bulbs purchased per respondent:
Table 19. Regional Data
Table 20. Total Program Bulbs and Leakage Percent
Total Number of Households (within 20 miles
% of Households not in PC T
Total # of Leaked Prooram Bulbs
% of Prooram leaked outside the
The Cadmus Group. lnc. / Energy Services s7
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 124 of 1365
Case No. PAC-E-'14-07
ttt ove rn tSF l' f 'Yd f d"*
# of program CFL
bulbs purchased by
respondent
(household)
# of program CFLs
per household in =
each region
# of program CFLs
leaking out of
territory
# of CFLs \/
Purchased
Weighted average
number of program
CFLs per household
across all regions
(weighted by # of
households)
Average of program
CFLs purchased by , # of households in
respondent households n region
in region
% purchased from
participating X
retailer
Total number of
households in all
v zip codes within
^ 20 miles of Rocky
Mountain Power's
service territory
Retailer reported % of
CFLs sold that were
program CFLs
per person in each of the
% of the region that
v are not Rockyn Mountain Power
customers
% of households that
are not RockyX Mountain Power
customers in each zip
code
2. Calculate the number of program-financed bulbs purchased
surveyed regions:
3. Calculate the number of bulbs leaking out of the service territory in total:
4. Calculate the percent of the program-financed bulbs leaking out of the service territory:
% of program CFLs
that are leaking out
of Rocky Mountain
Power's territory
# of program CFLs
leaking out of territory
# of CFLs that
s were financed by' Rocky Mountain
Power
Assumptions
The evaluation included the following assumptions:
o Surveyed non-Rocky Mountain Power households were demographically and culturally
similar to those not surveyed in the same region.
o The 11 store/retailer responses represented a census and exceeded the confidence and
precision goal for likely responses to questions asked (such as the percentage of
participating bulbs sold).
o The percentage of individuals called that were or were not Rocky Mountain Power
customers was representative of the breakdown of customers (Rocky Mountain Power vs.
other utilities) in the rest of the region.
o Households surveyed would be able to recalI, with a fair degree of certainty; stores from
which they purchased CFLs, the numbers of CFLs purchased; and the timeframe in which
CFLs were purchased.
The Cadrnus Group, lnc. I EnerEy $ervices 68
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 125 of 1365
Case No, PAC-E-14-07
t'l ove rn UBi'l' 51Pd ld"*
CFL retailers would be able to accurately recall the number of CFL bulbs sold, and
percentage that were part of the Rocky Mountain Power program.
o Though some respondents were not able to answer all questions, they were still able to
provide information in response to a majority of the most critical cases. In these cases,
assumptions were made as placeholders for missing data. Specifically:
o For households where the interviewed individual was not able to provide the percent
purchased from the store, a straight average was used based on the_percentage
purchased by all other households from all stores. This average was 627o.37
o For retailers unwilling or unable to complete the interviews, a weighted average of
other responses was used for estimating the proportion of total CFLs sold which were
program-financed bulbs. The weighted average rt. *as 58Vo.38
o For residential households, the vast majority of CFL purchases were assumed for
residential use. Consequently, while some additional leakage may have occurred outside
the residential sector, the nonresidential sector's impact on overall leakage was assumed
to be minimal.
Additional Details on Analysis Methodology
. Zip code territory definitions and populations within 20 miles of Rocky Mountain Power'
service territory were obtained from a GIS database of service territories maintained by
Platts, a division of McGraw-Hill.
In regions where Platts did not provide a percent of Rocky Mountain Power customer
households, survey respondents for zip codes provided by Discovery were used to
calculate the percentage of households that were Rocky Mountain Power customers. This
assumed a geographically consistent distribution of population across the zip code.
Household survey respondents were asked to identify stores from which they purchased
CFLs. While matching these reports with participating stores was typically
straightforward, some responses were less precise about specific names and locations for
stores. In these instances, best efforts were used to determine whether a store being
referenced was a participating or a nonparticipating retailer. Methods used to support this
determination included Yellow Page listings of stores, Internet searches, and searches on
corporate Web sites for store locations. In some rare instances, when multiple locations
for a retailer (i.e., a retail chain) matched the location mentioned, it was assumed the
respondent referred to the location closest to his or her household.
To increase the confidence level the average used came from a collective study conducted with the Utah, Idaho,
and Washington Rocky Mountain Power territories. 10 regions were mapped out during the phone interview
process to cover the three states studied within the Rocky Mountain Power territories.
Interviews were conducted with 58 of 96 stores, and 696 randomly selected households in areas surrounding
Rocky Mountain Power's service territory.
fi0The Cadmus Group. lnc. I Energy Services
Rocky Mountein Power
Exhibit No. 5 Page 126 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power
NTG Estimation
Cadmus, with its subcontractor Discovery Research, conducted telephone surveys with 429
customers who purchased qualifying measures through the HES Program and 141 non-Rocky
Mountain Power customers CFL purchasers. The findings were drawn from: a review of gross
savings claims for the program during each year; an analysis of program participants'
freeridership; and an analysis of spillover savings generated by the program.
Except for CFLs and insulation, the realization rate was measured through participant surveys
asking about current HES measure usage. During the survey, participants were asked what they
did with the specific program measure and where it is currently installed. The resulting responses
were scored in a matrix to determine the realization rate and the resulting rates for each measure
are found in Table 2l-Table 233e.The insulation realization rate was determined through the
billing analysis.
Gross Savings
Cadmus compared deemed savings values provided by Rocky Mountain Power's program
implementation contractor and cost-effectiveness inputs provided by Rocky Mountain Power to
determine program gross savings.
Except for CFLs and insulation, the realization rate was measured through participant surveys
asking about current HES measure usage. The CFLs realization rate is assumed to be one
hundred percentao. The insulation realization rate was determined through the billing analysisal.
The realization rates for each measure are shown in Table 2l-Table 23 and the methodology is
described in greater detail in the Error! Reference source not found. section.
3e The realizarion quesrions are E1, E1l, andE18 found in Appendix F: All non'InSUlatiOn
Measures Participant Survey lnstrument. Sampre question and scoring
matrix is found in
Appendix N: Realization Rate Matrix
While leakage was studied, and is presented in this report, the findings only attempted to measure the number of
bulbs for which Rocky Mountain Power provided incentives, which ultimately left its service territory. The
study did not take into account other factors such as the rural nature ofthe territory, lending itselfto a very high
"reverse leakage" effect or other regional programs offered by BPA and NEEA in the same territory which
would cut down the number of bulbs sold through the Rocky Mountain Power CFL program. Consequently this
report assumes that the net leakage is zero.
Due to too low participation in Idaho to perform an adequate billing analysis, the billing analysis was used from
the Pacific Power HES Washington territory. More detail of the billing analysis is provided in the Billing
Analysis section of the report.
NovemBBF I'f,'Pd8d"*
4t
The Cadmus Group. lnc. i Energy $ervices 7n
Rocky [vtountain Fcwer
Rocky Mountain Power
Exhibit No. 5 Page 127 of 1 365
Case No. PAC-E-14-07
N q -us
* $Hi:I$: Pd i d::::
Table 2t, T able 22, T able 23 and
Table 24 present claimed savings and realization rates for each year.
Table 23.2008 HES Program Gross Savings and Realization Rate
Table 21,.2006 HES Program Gross Savings and Realization Rate
CFL 9,'t76 26.4 242,246 100.0 242,246
Clothes Washer 151 383.0 57.833 100.0 57,833
Electric Water Heater 12 1 18.0 1.416 100.0 1,416
Fixture 1 92.0 92 't00.0 92
lnsulation: Attic (so ft)2,800 1.3 3,675 87.6 3,221
Refrioerator 5'1 85.8 4,376 100.0 4,376
Total 12.191 309.638 99.9 309.184
Table 22.2007 HES Program Gross Savings and Realization Rate
Ceilino Fans 4 105.0 420 99.3 417
Cenkal /JC Eouioment 1 278.0 278 ool 276
CFL 15,930 26.4 420,555 100.0 420,555
Clothes Washer 597 214.4 128,011 oo2 127,110
Dishwasher vb 90.0 8,640 100.0 8,640
Electric Water Heater 57 1 18.0 6,726 87.5 5,885
Evaoorative Cooler 1 941.0 941 99.3 935
Fixture 20 92.0 3,588 100.0 3,588
lnsulation: Attic (so ft)57,055 1.3 74,885 87.6 65,633
lnsulation: Floor (sq ft)2,061 0.9 1,752 87.6 1,535
lnsulation: Wall (sq ft)16,616 1.3 22,432 87.6 19,660
Refrioerator 238 85.8 20,420 100.0 20,420
Windows (sq ft)3,449 1.3 4,570 100.0 4,570
Total 96,144 693,217 98.0 679,225
Ceilinq Fans 26 107.0 2,782 98.7 2,747
Cenkal IVC Eouioment 2 96.0 192 98,7 190
CFL 4,849 27.0 1 3'1 ,1 65 100.0 131,165
Clothes Washer 378 234.5 88,626 96.9 85,856
Clothes Washer-Tier One 43 207.7 8,933 100.0 8,933
The Cadnius Group, [n*. ,r Hnergy Services ii
Clothes Washer-Tier Two 392 238.4 93,461 100.0 93,461
Dishwasher 205 28.8 5,897 100.0 5.897
Electric Water Heater 72 90.7 6,530 100.0 6,530
Fixture 60 92.0 5,520 100.0 5,520
Heat Pumo Uoqrade 1 811.0 811 98.7 801
lnsulation: Attic (so ft)180,721 0.8 143,706 87.6 125,952
lnsulation: Floor (so ft)18 046 0.4 7.415 87.6 6.499
lnsulation: Wall (so ft)18,236 1.1 19,460 87.6 17,056
Proper CAC lnstall 2 23.0 46 98.7 45
Prooer CAC Sizino 2 67.0 134 98.7 132
Refrioerator 263 97.5 25,643 97.5 24,991
Windows (so ft)11,833 1.0 11,797 100.0 11,797
Total 235,13',1 552,'.|'.17 95.6 527,572
=*,on'l"1"Irln"JiH""iiY.:;Case No. PAC-E-14-07
Rocky Mountain Fower ltovernU8F l'5]Pdfd"*
After accounting for realization rates, verified savings identified through survey efforts were
consistent with claimed gross savings from program years 2006-2008. In addition, savings per
measure, used in planning assumptions and in calculating gross savings claims, were compared
against savings values for these same measures in the 2006 and 2008 DEER database as well as
the RTF 5th and 6'h Power Plans. This analysis determined savings per measure values used by
Rocky Mountain Power were reasonable and consistent when compared to these sources.
Freeridership
Freeridership, or the percent of savings that would have occurred in the program's absence, was
calculated through surveys with program participants. This self-report approach for calculating
freeridership is an industry-standard methodology; however, it has some inherent limitations.
One factor of particular relevance to the program is a customer self-report methodology is not
entirely accurate for capturing market transformational impacts of multiyear programs. For
example, a multiyear program may alter the availability of higher-efficiency products in a region
through influencing stocking practices at retailers, increasing dealer experience and comfort with
more efficient products, or even through impacting demand for efficient products. Customers,
when choosing between various makes and models of a given product, may not be aware the
selection of measures available has been influenced by a program. Therefore, while the customer
may correctly state that, in the program's absence, they would still have chosen between two
efficient products, the availability of those products may have been a result of the program. In
Table 24. HES Program Total Gross Savings and Realization Rate
The Cadmus Group. lnc. l Energy Services v2
Rocky Mountain Power
Rocky Mountain Power
Exhibit No.5 Page 129 of 1365
Case No. PAC-E-14-07
ru ove rn Hl.$F l' {:'Yd Id"*
this case, while the customer would count as a freerider, if the progmm had not been running, a
less-efficient option may have been available to the customer (which he or she might have
purchased).
In calculating freeridership, Cadmus and Discovery Research surveyed 429 customers
participating in 549 progam measures over the 2006-2008 program years. Participants were
selected randomly from populations purchasing measures that contributed the most to progrcm
savings and/or accounting for the majority of program costs. The freeridership matrix is
described in more derail in Appendix u: Freeridership Matrix.
The Cadmus Group. lnc. i Energy Services
n gghy_ tttt g-,1$ein [ 9. *g t
Rocky Mountain Po\irer
Exhibit No. 5 Page130 of 1365
Case No. PAC-E-14-07
t't ove nr Slff 'l' f Yd f d"*
Table 25, Table 26, and Table 27 present freeridership analysis results for each program year,
survey population, and confidence bounds based on relative precision calculated at the 90Vo
confidence interval. The average freeridership value was weighted by gross kWh savings across
the surveyed measures, and was applied to the total gross number to arrive at the net
freeridership number for each year. Table 28 summarizes HES program total freeridership.
The Cadmus Group. lnc. / Energy Services
Roclry Mountain Power
Exhibit No.5 Page 131 of 1365
Case No. PAC-E-I4-07
Rocky Mountain Power Novem$$F l'{:'Pdfd"*
Table 25.2006 HES Program Freeridership
Table 26.2007 HES Program Freeridership
Clothes Washer 25Yo QlYo - 30o/o\71
Dishwasher 24Yo fi6Yo - 32o/o\25
Electric Water Heater 13Yo /0To - 33Yo\4
Fixture 13Yo fio/o - 0o/o\1
lnsulation: Attic 17Yo $Yo - 28Yo\13
lnsulation: Floor 30To fiYo -97Yo\2
lnsulation: Wall 12To (o%o - 47o/o\4
Refriqerator 30o/o Q3o/o - 370/o\42
Windows 29Yo OYo -75Yol 3
Total 22o/o l18o/o - 260/ol 165
Table 27.2008 HES Program Freeridership
Clothes Washer 32Vo Q6o/o -380/ol 65
Clothes Washer-Tier One 10o/o fiYo - 300/,2
Clothes Washer-Tier Two 27Yo Q2Yo - 32Yo 64
Dishwasher 44Yo B8o/o - 500/o 54
Electric Water Heater 38YoQ2o/o-54%13
Fixture 61Yo (420/o - 80Yo 5
lnsulation: Attic 1l%o ftYo - 15Yo 36
lnsulation: Floor 58o/o BlYo - 85Yo 5
lnsulation: Wall 200/0 0o/o - 480/0\5
Refriqerator 24Yo 00Yo -28Yo 59
Windows 21Yo fi6Yo - 260/o\18
Total 23.3Yo QlYo.26ohl 326
Table 28. HES Program Total Freeridership
Spillover
In addition to freeridership, Cadmus
generated by program participants but
freeridership yielded the NTG value
calculated spillover: the amount of additional savings
not captured by program records. Together, spillover and
- used in calculating final net savings of a program.
The Cadmus Group. Inc. I Energy Services 76
Rocky hlountain Power
Rocky Mountain Po\rer
Exhibit No. 5 Page 1 32 of 1 365
Case No. PAC-E-14-07
N_q yp r $'siT f :Pd ldl'::
Spillover occurs when customers choose to purchase energy-efficient measures or adopt energy-
efficient practices due to a program, yet choose not to participate or are otherwise unable to
participate in a program. Because these customers are not participants, program records typically
do not include savings generated by spillover impacts.
In this evaluation, spillover was measured by asking participants purchasing a particular measure
if, as a result of the program, they would have decided to install another efficient measure or
would have undertaken some other efficiency improving activity. Deemed savings values,
consistent with those used in calculating the gross savings value, were applied to relevant
measures or practices. The sum of these savings values, divided by savings achieved through the
program for each relevant measure, yielded spillover savings as a percentage of total savings
resulting from program incentives for that measu.e.a2 Spillover participants indicated an average
rating of 7.26 for the program's influence on their decisions to purchase other measures (based
on a scale of 0 to 10, with 10 being most influential). [n total, 29.2Vo of respondents indicated
they purchased additional efficiency measures because of their participation in the HES Program.
Annual findings are presented in Table 29,Table 30, and Table 31, with totals presented in Table
Table 29. HES 2006 Program Spillover
42 Detailed data provided by PECI was utilized for Gross Savings kWh in the spillover tables' measure detail
column.
Table 30. HES 2007 Program Spillover
Clothes Washer 14.243 949 6.7Y0
Dishwasher 2,250 190 8.4Y0
Electric Water Heater 472 0 0.0%
Fixture 92 46 50.070
lnsulation: Attic 22,894 618 2.7Y0
lnsulation: Floor 995 0 0.0%
lnsulation: Wall 6.144 196 3.2Y0
Refrioerator 3,604 599 16.6%
Windows 771 0 0.0%
Total 51.465 2.597 6.5%
The Cadrnus Group, Inc. I Energy Services 76
Rocky Mountain Power
Exhibit No. 5 Page 133 of 1 365
Case No. PAC-E-14-07
Rocky h{ountain Power N overn $$i"T {lPd f d"*
Table 31. HES 2008 Program Spillover
Clothes Washer 14,275 954 6.7Yo
Clothes Washer-fier One 483 0 0.0%
Clothes Washer-fier Two 14,952 500 3.3%
Dishwasher 1.633 223 13.6Y0
Electric Water Heater 1,179 348 29.5Y0
Fixture 828 227 27.4Y0
lnsulation: Attic 22,250 1,393 6.3%
lnsulation: Floor 2,987 63 2.1Y0
lnsulation:Wall 1.734 83 4.8To
Refrioerator 5,753 392 6.8%
Windows 2,166 269 12.4T0
Total 68,240 4,451 6.4Y0
Table 32. HES Program Spillover Totals
NTG Factor
The NTG factor is the ratio of claimed savings, reported by Rocky Mountain Power, to savings
realized through the evaluation, including impacts of CFL leakage, freeridership and spillover.
Table 33 presents these findings. Across the three program years evaluated, average NTG was
measured at8l.8%o.
Table 33. HES Program NTG Factor
The Cadmus Group. lnc. I Energy Services 77
Rocky Mountain Power
Exhibit No. 5 Page 1 34 of 1 365
Case No. PAC-E-14-07
6. Cost-EffectivenessAnalysis
To assess cost-effectiveness, evaluators conducted an analysis of program costs and benefits
from five perspectives, using The Cadmus Group's DSM Portfolio Pro model. These
perspectives include:
a. PacifiCorp Total Resource Cost Test (PTRC): This test examines program benefits
and costs from Rocky Mountain Power's and Rocky Mountain Power customers'
perspectives, combined. On the benefit side, it includes avoided energy costs, capacity
costs, and line losses plus a IlVo adder to reflect non-quantified benefits. On the cost
side, it includes costs incurred by both the utility and participants.
b. Total Resource Cost Test (TRC): This test examines program benefits and costs from
Rocky Mountain Power's and Rocky Mountain Power customers' perspectives,
combined. On the benefit side, it includes avoided energy costs, capacity costs, and line
losses. On the cost side, it includes costs incurred by both the utility and participants.
c. Utility Cost Test (UCT): From Rocky Mountain Power's perspective, benefits are
avoided energy and capacity costs and line losses. Costs include any program
administration, implementation or incentive costs associated with funding the program.
d. Ratepayer Impact (RIM): All ratepayers (participants and nonparticipants) may
experience an increase in rates to recover lost revenue. This test includes all Rocky
Mountain Power program costs as well as lost revenues. As benefits, this test includes all
avoided energy costs, capacity costs, and line losses.
e. Participant Cost Test (PCT): From this perspective, program benefits include bill
reductions. Costs include any customer contribution to the measure cost.
Table 34 summarizes the various components of the five tests.
Table 34. Benefits and Costs Included in Various Tests
Table 35 provides selected inputs to the cost analysis. These include evaluated energy savings
for each year (from Table 33, above), discount rate, line loss, and program costs. Other than
energy savings, these values are provided by Rocky Mountain Power. The discount rate is from
Rocky Mountain Power's 2008 Integrated Resource Plan. Rocky Mountain Power also provided
values for line loss and the program costs. The implementation cost is the amount Rocky
Mountain Power paid to PECI, the implementing contractor.
Present Value of Avoided Energy and Capacity Costs with
'10% Adder for Non-ouantified Benefits
Program Administrative and Marketing Cost +
Participant Cost
Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost +
Present Value of Avoided Energy and Capacity Costs Program Administrative, Marketing and lncentive Cost
Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost + Present
Value of Lost Revenues
Present Value of Bill Savings Participant Share of Measure Cost
The Cadmus Group. lnc. / Energy $ervices 78
[ggIv_ !
Rockv Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 1 35 of 1 365
Case No. PAC-E-14-07
tu ove rn USF I' f,'Yd f d"*
Table 35. Selected Cost-Effectiveness Analysis Inputs
Net Prooram Savinos ftWhfuear)227,802 574,243 438,268
Discount Rate 7.40Y0 7.40Yo 7.40Yo
Line Loss 11.39%11.39%11.39Y0
Net Participant Costs $65,539 $165,539 $360,706
Program Costs
lmplementation Cost $63,1 37 $122,255 $203,679
lncentive Costs $26,641 $1 28,1 53 $225,652
Utilitv Administrative Costs $18,090 $10,636 $21,062
Total Proqram Gosts $r07,868 $261,0t14 $t150,393
Program benefits are comprised of energy savings and their associated avoided costs. The energy
savings used in the cost-effectiveness analysis are the evaluated kWh from this study.
Table 36, Table 3'7, and Table 38 present the results of the cost-effectiveness analysis for the
Program in 2006, 2007, and 2008 respectively. Table 39 summarizes cost-effectiveness analysis
for the program for all years (2006-2008). All analyses are based on the Roq\y Mountain Power
2008 IRP 6OVo load factor (LF) eastside residential righting IRP decrement.4r Detailed
incremental costs and measure lives can be found in Appendix B.
Table 36. Cost-Effectiveness Summary for 2006 - IRP 607o LF Eastside Residential
Lighting Decrement
43 IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan Volume II
Appendices:
httrr:l/wu,rv.paciiicsup.con/coutgnt,dam/paciiicorp/doclEnvironrlent'/Elrvironurerital ClorlqgqJrs/l.4tegrated Reso
urce llarnins 6.qd,[
7S
Total Resource + Conservation Adder (PTRC)$0.089 $146,766 $121,436 -$25,330 0.83
Total Resource No Adder (TRC)$0.089 $146,766 $1 10,396 -$36,370 0.75
Utility (UCT)$0.065 $107,868 $1 10,396 -$2,528 1.02
Ratepayer lmpact (RlM)$0.1 37 $226,252 $1 10,396 -$1 15,856 0.49
Participant (PCT)$0.040 $65,539 $145,025 $79,486 2.21
Lifecycle Revenue lmpact ($/kWh)$0.00000490
Discounted Particioant Pavback (Years)2.73
The Cadmus Group, lnc. I EnerEy $ervices
xgglty_ ttrlgU$nin Po*ei
Rocky Mountain Power
Exhibit No. 5 Page 1 36 of 1 365
Case No. PAC-E-14-07
NovemH$F"l'f'Ydfd"*
Table 37. Cost-Effectiveness Summary for 2007 - IRP 60Vo LF Eastside Residential
Table 38. Cost-Effectiveness Summary for 2008 - IRP 60Vo LF Bastside Residential
Table 39. Cost-Effectiveness Summary for 2006-2008 - IRP 60Vo LF Eastside Residential
Lighting Decrement
Total Resource + Conservation Adder (PTRC)$0.061 $298,430 $385,716 $87,286 1.29
Total Resource No Adder (TRC)$0.061 $298,430 $350,651 $52,221 1.17
Utility (UCT)$0.053 $261,044 $350,651 $89,607 1.34
Ratepayer lmpact (RlM)$0.1 32 $647,746 $350,651 -$297.094 0.54
Particioant (PCT)$0.034 $1 65,539 $514,854 $349,315 3.11
Lifecycle Revenue lmpact ($/kWh)$0.0000091 5
Discounted Participant Payback (Years)0.97
Lighting Decrement
NiSiAiW
Total Resource + Conservation Adder (PTRC)$0.1 1 8 $585,447 $424,308 -$1 61 ,1 39 0.72
Total Resource No Adder (TRC)$0.1 1 B $585,447 $385,734 -$199,71 2 0.66
Utility (UCf $0.091 $450,394 $385,734 -$64,659 0.86
Ratepayer lmpact (RlM)$0.1 76 $873,045 $385,734 -$487,311 0.44
Participant (PCT)$0.073 $360,706 $648,304 $287,598 1.80
Lifecycle Revenue lmpact ($/kWh)$0.00001 1 31
Discounted Particioant Pavback ffears)4.12
Lighting Decrement
Total Resource + Conservation Adder (PTRC)$0.088 $932,184 $u8,427 -$83,757 0.91
Total Resource No Adder (TRC)$0.088 $932,1 84 $771,298 -$160,887 0.83
Utility (UCT)$0.07 $741,392 $771,298 $29,905 1.04
Rateoaver lmoact (RlM)$0.1 51 $1,586,250 $771,298 -$814,952 0.49
Particioant (PCT)$0.051 $532,384 $1 ,1 86,449 $654,065 2.23
Lifecycle Revenue lmpact ($/kWh)$0.00001 757
The Cadmus Group. inc. / Energy $ervices 80
Rocky Mountain Power
Exhibit No. 5 Page 137 of '1 365
Case No. PAC-E-14-07
tu CIve n'r #HF'l f 'Yd 8d"*xgg!:y_ HrtgU$gf Pgwgi
7.Appendices
Appendix A: Available Measures Tariff lnformation
Table 40. Available Measures TariffInformation - Appliances
Ceiling Fan 1t1t2007 current ENERGY STAR
oualified
Year round $20 $0 No
Clothes
Washer*
5/31/2006 1431t200
b
Energy Star qualified.
MEF of 1.42for balance
of 2006. MEF of 1.72+
for 2007 and beyond
(until turther Energy
Star specification
chanoes)
Year round $75 $0 No
Clothes
Washer*
111t2007 4t31t2008 Energy Star qualified.
MEF of 1.42for balance
of 2006. MEF of 1.72+
for 2007 and beyond
(untilfurther Energy
Star specification
chanoes)
Year round $75 $0 No
Clothes
Washer
5t1t2008 current Washing machines:
Split measure into two
tiers for efficiency and
incentives. Tier 1:
Modified Energy Factor
(MEF) 1.72-1.99
Year round $50 $0 No
Clothes
Washer
5t1t2008 current Washing machines:
Split measure into two
tiers for efficiency and
incentives. Tier 2:
Modified Energy Factor
(MEF) 2.0+
Year round $1 00 $0 No
Clothes
Washer
Recycling
5/31/2006 current Only available to
purchasers of new
Energy Star Washing
machine who
participated in the
program. Old unit must
be ooerable to qualifv
Year round $0 $25 Yes
Dishwasher 1t1t2007 4t30t2008 Available after January
2007 when revised
Energy standards are in
effect(Energy Star-EF
0.68+)
Year round $20 $0 No
Dishwasher 5t1t2008 current Chanqe .68 Enerqv Year round $20 $0 No
The Cadnrus Group. lnc. / Energy Services 81
tgllrv Ssq$sil lovgr
Roclq Mountain Power
Exhibit No. 5 Page 1 38 of 1 365
Case No. PAC-E-14-07
trt ove r"n SSFT' f 'Yd f d"*
Factor (EF)to .65 EF to
align program eligibility
requirements with final
Energy Star
qualifications of .65.
Electric
Water
Heater*
5t3112006 4t30t2008 50-75 gallons and
0.91+ EF
B0-119 gallons and
0.85+ EF
Year round $50 $0 No
Electric
Water
Heater
5t1t2008 current 40+ gallon tank and
0.93+ EF
Year round $50 $0 No
Evaporative
Cooler*
5/31/2006 4t30t2008 Permanently installed Year round $250 $25 Yes
Evaporative
Cooler
511t2008 current Based on price,
availability, ease of
installation and
experience in other
markets, the incentive
offer will be adjusted to
$100 for the
end user, the contractor
incentive will be
discontinued, and the
measure will be
promoted at the retail
level.
Year round $1 00 $0 Yes
Fixtures 5/31/2006 current ENERGY STAR
oualified
Year round $20 $0 No
Refrioerator 5/31/2006 current ENERGY STAR rated Year round $20 $0 No
*Program is no longer active
Table 41. Idaho Available Measures Tariff Information-Home Improvement
Per square foot, R-11 in
the wall and R-19
increments based on
purchased material
rating, not rating of
overall installed levels.
Available only to
customers with electric
heat systems or ducted
unitary cooling
The Cadnrus Group, inc. i Energy Services B?
Rocky l\,4ountain Fower
Roclq Mountain Power
Exhibit No.5 Page'139 of '1365
Case No. PAC-E-14-07
N ?-us * $'_Sf:U:'Pd f d::::
of the floor area. Min R-
'19
lnsulation-
Floor*
5/31/2006 4130t2008 Per square foot, R-11 in
the wall and R-19
increments based on
purchased material
rating, not rating of
overall installed levels.
Year round $1.00/sq.
ft.
$0 No
lnsulation-
Floor
5t1t2008 current Available only to
customers with electric
heat systems or ducted
unitary cooling
equipment service 80%
of the floor area. Min R-
19
Year round $0.50/sq.
ft.
$0 No
lnsulation-
Wall'
5t31t2006 4t30t2008 Per square foot, R-11 in
the wall and R-19
increments based on
purchased material
rating, not rating of
overall installed levels.
Year round $1.00/sq.
ft.
$0 No
lnsulation-
Wall
5t112008 current Available only to
customers with electric
heat systems or ducted
unitary cooling
equipment service 80%
of the floor area. Min R-
11
Year round $0.50/sq.
ft.
$0 No
Windows 5t31t2006 curreni Available only to
customers with electric
heat systems or ducted
unitary cooling
equipment service 80%
of the floor area. U-
Factor of .32 or better
Year round $1.50/sq.
ft.
$0 No
*hogram is no longer active
The Cadrnus Group. Inc. I Energy $ervices et
Rocky Mountain Power
Rocky Mountain Power
Exhibit No. 5 Page 140 of 1365
Case No. PAC-E-14-07
ltovemU8F l'fYdfd"*
Table 42. ldaho Available Measures Tariff Information-HVA C
CAC
Equipment
11112007 current 15+ SEER/12.5+ EER
& TXV
Year round $250 $25 Yes
CAC
lnstallation
1t1t2007 current 13+ SEER & TXV &Year round $50 $75 Yes
CAC Sizing 11112007 current 13+ SEER & TXV &
best practices
installation (charge and
airflow)
Year round $50 $25 Yes
CAC/Heat
Pump
Tune-Ups
5/31/2006 current PTCS requirements
performed by program
qualified contractor
Year round $1 00 $25 Yes
Duct
Sealing
5/31/2006 current PTCS requirements
performed by program
qualified contractor
Year round $1 50 $50 Yes
Heat Pump
Conversion
5t1t2008 current Convert an electric
heating system to a
heat pump 14+ SEER &
11.5+ EER & 8.2+
HSPF
Year round $350 $25 Yes
Heat Pump
Upgrade
5t1t2008 current Upgrade a baseline
heat pump to high
efficiency heat pump
14+ SEER & 11.5+
EER & 8.2+ HSPF
Year round $250 $25 Yes
The Cadmu$ Group. lnc. / Energy Services
Rocky [vlountain Power
Rocky Mountain Power
Exhibit No. 5 Page 141 of 1365
Case No. PAC-E-I4-07
I'tovernUSi'l'51Yd f d"*
Table 43. Idaho Available Measures Tariff Information-Lighting
Screw-in, select
common wattages,
ENERGY STAR
qualified
October-
March
Manufacturer
buy-down not-
to-exceed
$1.35
Retail price
nolto-exceed
$1.50
current lncluding specialty
bulbs, and respond to
changing CFL prices,
the Company is
proposing to use the
markdown/buy-down
mid-market incentives
to bring the final cost to
the customer to $.99 -
$2.75 and to offer
lighting incentives year
round.
Year round Manufacturer
buy-down no!
to-exceed
$1.35
Retail price
not-to-exceed
$0.9e-$2.75
5t1t2008
*Program is no longer active
The Cadrnus Group, lnc. I Energy Services 85
nggfy_ tutgq$nin towgi
Rocky Mountiain Power
Exhibit No. 5 Page 142 of 1 365
Case No. PAC-E-14-07
t t ove rnH$F l'5",'Yd Id"*
Appendix Gost-Effectiveness I n puts
2006
CFL # of CFL 4.00 6.6
Clothes Washer # of Clothes Washer 300.00 14
Electric Water Heater # of Electric Water Heater 34.00 10
Fixture # of Fixture 18.00 15
lnsulation: Attic so. ft. of insulation 0.60 45
Refriqerator # of Refriqerator 99,00 19
2007
Ceilino Fans # of Ceilinq Fans 25.00 15
CentralA/C Eouioment # of Central lr/C Eouioment 587.00 't8
CFL # of CFL 4.00 6.6
Clothes Washer # of Clothes Washer 80.00 14
Dishwasher # of Dishwasher 43.00 I
Electric Water Heater # of Electric Water Heater 34.00 10
Evaporative Cooler # of Evaoorative Cooler (1,000.00)15
Fixture # of Fixture 18.00 15
lnsulation: Attic so. ft. of insulation 0.60 45
lnsulation: Floor sq. ft. of insulation 0.66 45
lnsulation: Wall sq. ft. of insulation 0.82 45
Reftiqerator # of Refrioerator 99.00 19
Windows sq. ft. of Windows 1.50 45
2008
Ceilino Fans # of Ceilinq Fans 25.00 15
Central//C Equipment # of Central y'/C Eouioment 587.00 18
CFL # of CFL 6.00 6.6
Clothes Washer # of Clothes Washer 300.00 14
Clothes Washer-Tier One # of Clothes Washer-Tier One 40.00 14
Clothes Washer-Tier Two # of Clothes Washer-Tier Two 146.00 18
Dishwasher # of Dishwasher 31.00 I
Electric Water Heater # of Eleckic Water Heater 20.00 10
Fixture # of Fixture 15.00 15
Heat Pumo Uoorade # of Heat Pumo Uoorade 700.00 18
lnsulation: Aftic sq. ft. of insulation 0.86 45
lnsulation: Floor so. ft. of insulation 0.80 45
lnsulation: Wall sq. ft, of insulation 0.81 45
Proper CAC lnstall # of Prooer CAC lnstall 185.00 18
Prooer CAC Sizino # of Prooer CAC Sizino 185.00 18
Refriqerator # of Refrioerator 66.00 't9
Windows so. ft. of Windows 1.50 45
The Cadmus Group. Inc. / Energy $ervices 8S
Rocky Mountain Power
Exhibit No. 5 Page 143 of 1 365
Case No. PAC-E-14-07
xgghv Mountain Power Novem$Hi"Tf'Pdfd"*
Appendix G: Dealer Survey Sum maryoo
oo This table excludes CFLs, Evaporative Coolers, Proper CAC Sizing, CAC Installation, CAC/Heat Pump Tune-
Ups, Clothes Washer Recycle, Duct Sealing, Room AC Recycle, Room AC Equipment, and Ceiling Fans.
These measures were not represented in the dealer survey results.
Clothes Washers-Tier One 297 16 66,919 1 ,169 40 283,403
Clothes Washers-Tier Two 76 11 17,363 392 60 93,461
Dishwasher 43 11 2,219 301 35 14,537
Electric Water Heater 68 3 7,'t00 141 39 14,672
Fixture 35 1 3,220 100 12 9,200
lnsulation: Attic 204,521 7 188,447 240,576 20 222,265
lnsulation: Floor 17,787 4 7,712 20,107 15 9,1 67
lnsulation: Wall 25,850 3 33,256 34,852 19 41,891
Refrigerator 119 14 10,643 552 47 50,439
Windows 8,074 7 8,699 15.282 47 16,367
Centrall/C Eouioment 2 1 192 3 4 470
Total 256,872 345,770 313,476 755,872
The Cadrnus Group. lnc. / Energy Services 87
Rocky Mountain Fower
Rocky Mountain Power
Exhibit No.5 Page 144 of 1365
Case No. PAC-E-14-07
w ove',n UJFT' {lPd f d"*
Appendix D: Dealer Sales Perceptions
Clothes Washer 60%99%740/o $378
Refriqerator 58%920/o 68%$224
Dishwasher 60%95%67Yo $134
Electric Water Heater 14o/o 99%53Yo $1 69
Windows 95%'t00%100%$36
lnsulation 80%100%65%$0.67
Central//C Equiomenl 20Yo 50%40Yo $1,500
Evaoorative Cooler 960/o 100%
Room AC New Purchase 12To 95%47Yo $60
The Cadmus Group. lnc. I Energy Services 88
Rocky Mountain Power
Rocky Mountain Power
Exhibit No.5 Page 145 of 1365
Case No. PAC-E-14-07
uove'nU$F 1'5:'Pd8d"*
Appendix E: Attic, FIoor and Wall Insulation
Participant Survey Instrument
Provided under separate cover.
The Cadmus Group. lnc. I Energy Services 8g
Rocky Mountain Power
Rocky Mountain Po,ver
Exhibit No. 5 Page 146 of 1365
Case No. PAC-E-14{7
NovemU5il'f'rydfd"*
Appendix F: AII non-lnsulation Measures Participant
Suruey Instrument
Provided under separate cover.
g0The Cadmus Group. lnc. i Energy Services
Rocky Mountain Fower
Roclq Mountain Power
Exhibit No. 5 Page 147 of 1365
Case No. PAC-E-14-07
Novem$HF 1'5:'Ydtd"*
Appendix G: GFL Nonparticipant Leakage Survey
lnstrument
Provided under separate cover.
The Cadmus Group, lnc. I Energy $ervices tI
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 148 of 1365
Case No. PAC-E-14-07
ttovemH{lF l'f,P6E6"*
Appendix H: CFL Retailer Suruey lnstrument
Provided under separate cover.
The Cadrnus Group. lnc. I Energy Services VZ
Rocky Mountain Power
Roclq Mountain Power
Exhibit No. 5 Page 149 of 1365
Case No. PAC-E-14-07
tuovenrU5F"l'fYdfd"*
Appendix l: Dealer Suryey lnstrument
Provided under separate cover.
The Cadmus Group, lnc. / Energy Services 93
Roclq Mountain Power
Exhibit No. 5 Page 1 50 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power t't ove nn Hl$i'T f 'Pd f d"*
Appendix J: lmplementer Discussion Guide
Provided under separate cover.
The Cadmus Group. lnc. I Energy Services g4
Ro*ky hrXountain Fower
Rocky Mountain Power
Exhibit No. 5 Page 151 of 1365
Case No. PAC-E-14-07
tiovem$HF'l $]Y$f#"*
Appendix K: Program Logic Model
Figure 53. Rocky Mountain Power Home Energy Savings (HES) Program Logic Model
ParifiCarp ltorue E*ergy $rvir g* {HES} Frogran Logic $r*rdel
: Fundi, $(F*rlffcnd Str$.,,*lltav. td*rlar koql..l{{lg& $ynsrgidic Frogra.rn$trana$Gmsilt
lrlSl.wDs,8,t
1
i trcr
\
tstBs,iSBulsa{S }
lt:.....
'\ 'r ._--_--s-i.\N DsalsJi Bsltn{s $*r i i Adw{isln$'' i Etl*salUAtli,RSild i iar>dtBrkc{l\,
i:ilE:sYlr^nFssl6$ i i $adt*r
-----.s:-lafrlrs*(, rGdAFrs]t{isDchls{{: : Barrus
t Nt!r*.!
".::::*"::i'.::Yi
^s--------_---------.i *or* LI Psrti.igafds t'']tis
.....s.......s:...........
: Fetaiere rreBate Eiltrlrtrl Ll8s{ngnnd Et EnoY SftR psrlrss i.. * ll, ..s,
s
E
rU
o)
i (o.d{rldt\ PrufritB t{Si
i IlDaNrtr tsgus{ofrsr
i
i--**--***-**"*" "'-*i Fu{i[l]rNltr es6{r8z* ii Ersttr e-d cuatr Fn{t,u i
i WNd att q*h i
s
.... Co{eufro, (GN.dlD. (GS :x sl EuffRxlns(sv
.**..-..-....-*\*.*........-*..
\j Lsg Tsm I' i $omsd 5a$ng! !i.........-...-^..-.*.-.........--......i J!
i ...............-..........-.s:-......r..........---......
,...**..., , .....-..*--l E(Mtf,A XNs, irlo rnl<ir* l-***-t
Table 44. Program Theory and Indicators
The HES program design leads to training third party
contractors and PECI staff, marketing and outreach activities,
and contracts with manufacturers
Trained third party contractors have the ability to properly
install measures
Outreach to retailers and dealers result in stock to support
sales of CFLs and ENERGY STAR products
I Marketing and outreach promote incentives for HES measures
Fcdwed tia$d ltr Fwt Bd
C.rir}{ trr$setfrfrli
a
a
a
a
a
Program design
Number of training sessions
Number of contractors attending sessions
Marketing plan established
Number of outreach events scheduled
o lnstallation paperworkcompletion. Number of trained third party contractors
discounted bulbs and ENERGY STAR
products
9
The Cadmus Group. lnc. i Hnergy $ervices $5
Rocky Mountain Power
Rocky Mountain Power
Exhibit No.5 Page 152 of 1365
Case No. PAC-E-14-07
Novem$UF l'{:'Pdf#'**
e Target markets identified
o Number of marketing collateral pieces
developed
o ResDonse rate to taroet marketinq
10 Program web site developed, updated
o Cunent incentives and information updated
on web site
o Hit rates for unioue visitors
11 Trained PECI staff process program applications
a Number of applications received
Number of applications reviewed &
orocessed
a
12 PECI invoices Rocky Mountain Power for incentive payment a Number or invoices
Amount of invoicesa
13 Manufacturers provide CFL bulbs to retailers at a discount a Number of discounted bulbs
Amount of discounta
14 Web site serves as portal for program applications o Number of Drooram forms downloaded
15.16 Applications verified by quality control process
o Number of inspections completed
o lnspection accuracy rate
o Amount of energy savings represented by
aoolications
17 The processing of applications enrolls participants in the
pr0gram
a Number of applications approved
Number of participants enrolled in the
Dr00ram
a
't8 Trained contractors promote the program to customers
o Number of marketing collateral pieces
developed for contractors. Number of contractor enrollment referrals
19 Retailers with efficient product stock promote HES measures a Number of discounted CFLs sold by retailer
Number of ENERGY STAR products solda
20 Marketing and pointof-purchase materials increase retailer
promotions of HES measures
a Number of marketing materials produced
Number of retailers promoting HES
measures
a
21 Marketing efforts result in increased program awareness
o The number of participants who report
remembering program ads and marketing
efforts
o The number of nonparticipants who report
knowledoe of the proqram
22 Web site information and promotion of web site increases
proqram awareness
o Number of program aware consumers that
credit web site as source of awareness
23 Enrolled participants receive incentives for participating in the
program
r Number of incentives paid
o Number of days to process incentive
payment. $ value of incentives paid
23 lncreased program awareness leads to increased program
participation
o Number of participants
o Number of survey respondents indicating
thev are aware of the Droqram
24 lncreased program awareness leads to increased energy
conservation awareness
o Number of survey respondents indicating
they are aware of the program and energy
conservation
25 Retailer promotions generate program awareness
. Number of program aware survey
respondents indicating they learned about
the orooram throuoh a retailer
26 Contractor oromotions oenerates Drooram awareness o Number of orooram aware survev
The Cadrnus Gr'oup, lnc. I Energy $ervices s6
Segfv Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 153 of 1365
Case No. PAC-E-14-07
Novem$Hi'l'f'Pdfd"*
respondents indicating they learned about
lncreased energy conservation awareness leads to increased
program participation
o Number of participants
o Number of survey respondents indicating
they are aware ofthe program and energy
conservation
HES measure purchases are installed in homes Number of purchases not installed (CFL
lncreased program awareness leads to purchase of HES
measures
o Number of program aware survey
lncreased program awareness leads higher sales volume of
CFLs and ENERGY STAR
r Sales volume of CFLs and ENERGY STAR
Participants recognize energy savings benefits and create
positive word-of-mouth for the program
o Number of participants that recognize energy
savings
o Number of participants that have told others
Higher sales volume of CFLs and ENERGY STAR products
result in manufacturers producing fewer of the less efficient o Production decline of less efficient products
Energy savings goals attributed to program represent long o reduction targets (KW) met in successive
lncreased energy conservation awareness leads to increased
demand for HES measures
Number of survey respondents that have
added additional HES measures to their
homes
Participants' positive promotion of the program increases
demand for HES measures
o Number of participants that heard about the
Higher CFL and ENERGY STAR product sales volume and
increased demand for efficient products make existing homes
more efficient
Decreased energy usage by participants as
shown by billing analysis results
Long term demand savings reduces need for larger fuel lnvestments in fuel contracts and power
The Cadmus Group, lnc. I Energy $ervices s7
Rocky Mountain Power
Rocky Mountein Power
Exhibit No. 5 Page 154 of 1365
Case No. PAC-E-14-07
Novem#$FT'5lYdfd"*
Appendix L: Billing Analysis Final Modelas
Table 45. Regression Model for Washington
Table 46. Regression Model for Washington - Small Homes (Quartiles L,2)
a5 The Washington billing analysis was applied to Idaho due to Idaho data limitations and relatively comparable
service territory characteristics.
lntercept 1 -23.0301 0.4816 -47.82 <0.0001
AnnualPre 1 0.002911 0.0000210 138.62 <0.0001
Post 1 -1.0256 0.2906 -3.53 <0.0001
PartPost I -2.6781 0.5491 -4.88 <0.0001
AvqHdd 1 1.0537 0.0122 86.36 <0.0001
AvqCdd 1 1.9352 0.0291 66.48 <0,0001
The Cadmus Group. lnc. / Hnergy $ervices 98
Rgqky_ Mgq$ein Pg_rygt
Rocky Mountain Power
Exhibit No.5 Page 155 of 1365
Case No. PAC-E-I4-07
_ No_y_**Hdi:1f:Pd Id::::
lntercept 1 -12.623/.0.6373 -19.81 <0.0001
AnnualPre 1 0.002975 0.0000529 56.29 <0.0001
Post 1 -0.3109 0.2384 1.30 <0.0001
PartPosl 1 -0.4120 0.4490 -0.92 <0.0001
AvqHdd 1 0.4522 0.0101 44.75 <0.0001
AvqCdd 1 1.3913 0.0239 58.31 <0.0001
Table 47. Regression Model for Washington - Large Homes (Quartiles 3r4)
The Cadmus Group. lnc. I Energy Servi*es
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Exhibit No. 5 Page 156 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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Rodry Mountain Power
Exhibit No. 5 Page 157 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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Exhibit No. 5 Page 1 58 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
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Roclry Mountain Power
Exhibit No. 5 Page 1 59 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
(}rOc$(\
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Rocky Mountain Power
Exhibit No. 5 Page 160 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power t't ovemUllF"l'f 'Yd f d1"""
Table 50. Freeridership Matrix Responses for non-Insulation measures
Yes [YES]Yes |YESI More Efficient [YES]Ail [YES]
ln the same year
IPARTTALI
No [No]No [No]Less Efficient [NO]None [NO]
ln one or two years
tNol
Don't Know [PARTIAL]Don't Know [PARIIAL]
Same level of efficieny
TYESI
Some [PARTIAL]
ln three to five years
tNol
Refused [PARTIAL]Refused [PARTIAL]Don't Know [PARTIAL]Don't Know [PARTIAL]
After more than 5 years
tNol
Refused [PARTIAL]Retused [PARTIAL]No [YES]
Don't Know IPARTIAL]
Retused IPARTIAL]
The Cadmus Group. lnc. l Hnergy Services 104
Rocky fulountain Power
Rocky Mountain Power
Exhibit No. 5 Page 161 of 1365
Case No. PAC-E-14-07
N qye r 8l[i:I$:',yd f d:l::
Table 51. Freeridership Matrix Responses for Insulation measures
Yes, but later in the
same year [PARTIAL]
More, and in the same
location [YES]
Yes, later, in one or
two years [NO]
More insulation, but in
different locations
IPARTTALI
Yes, later, in three to
five years [NO]
Yes, later, after more
than 5 years [NO]
Less insulation and in
different locations [NO]
Yes, lwould have
installed the insulation
sooner [YES]
No, I would have
installed it at the same
time [YES]
The Cadmus Group, Inc. I Energy Services 105
Roclry Mountain Power
Exhibit No. 5 Page'162 of '1365
Case No. PAC-E-14-07
Rocky Mountain Power NovemilBFT'51Pdfd"*
Appendix N: Realization Rate Matrix
Table 52. Realization Rate Matrix for non-Insulation and CFL measures
1. lt is curently installed at your home
It is installed at some other location
3. lt was installed at your home but is now permanently
removed (example: broke, burned out, don't fit, don't like, etc.
4. lt was installed at home, wasn't working properly, and
was replaced with another energy efficient clothes washer
The Cadmus Group. lnc. / Energy Services 10s
Rocky Mountain Power
Exhibit No.5 Page 163 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
o
t t*s !i.
CADMIJS
]..t\"i: Ii iY ll\:{
PacifiCorp Home Energy Savings Program Participant Survey {WA and lD}
A. lWeasune N*y
A1. Clothes Washers
A2. Refrigerators
A3. DishwashersA4. Electric Water Heaters
A5. WindowsA5. Lighting Fixtures
s. lntr*ductiun
Hello, my name is and I am calling from {$$S$$\rS'$yffiSS$A$S$"foe"}Sf$ SASjWS$
SSS{JFJ on behalf of ISSS$$ft SS}{f$S/SSSS{Y dWS{J}UfSi$J SS$$$$J. We are exploring the impacts of
energy efficiency programs offered in your area. l'm not selling anything; I just want to ask you some
questions about your energy use and the impact of promotions that have been run by $$SSiFJS
SS i$SS/SSSNY MS {"r$f f"q $rN* SS t'{/$Sj.
81. ln the last 4 years, our records indicate that you received a rebate for $.f$I.AFSC.$AN$$$SJ A:
I$dS$[$S$f A$ ANS S{J,{N$fy SSSf\.t PS$SSS&$ S$$$S$Sj. Does this sound right?
1. Yes
2. No [FR$$S; ASK As${"sT'ST$"{$N NH$$SN$$F}TS Se *"r'Htlt NA$}'!$S" !$ s{S SlJfl{sSS,
TSR$$INATI]
-98. REFUSED [Ti"{AN${ ANS YSNN.$NST$}
-99. DON'T KNOW [T${i\$UH ANS T$fifi\$ii$ATil}
92. Were you the primary decision maker when deciding to purchase fI$d$$ dfS$t$Jf${S'S$ dySeISj?
1. Yes
2. No
-98. REFUSED
-99. DON'T KNOW
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No. 5 Page 164 of 1 355
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
S. Surchnses Sutside of Frogrmm
C1, Did you purchase any of the following items in the last 4 years lfiSf SF SX${$S ftf$i$i$
ASSd.fIS&IS$S.S!NS AI}S'AS{.JS$$ SI$$SS F$'dSiN IFfSSS d"f$I$S fel SffSSffSAj} S$SSSSS $S&M$.s$
rtf$fS$SNgS i$t.SlJ
1. Yes {pR*N,tFT A$ NH[$[S SRSNT S*Li"SwlNS LlST]
A1 Clothes Washers
M Refrigerators
A3 Dishwashers
A4 Water Heaters
A5 Windows
AO Lighting Fixtures
2. No I$NdF IS $3J-98. REFUSED fSffdS r$ SSJ-99. DON',T KNOW $SN,S rS SsJ
fssp$'srss'{s'icAefss{Jssydse's s} r'sfss{.Js,&{ *:s. s$N $s$f"f fi,f$As{.is$, As- s$, sfi"spserssNr
s$d.ssrss djv Qt^issrjsJu $3J
C2. IJF $J^l * A"I F,$SS{.{S$f A$J Have you purchased one or more l$i"f'AdffI$JWSJ since the beginning of
2006?
1. Yes
CZa. How many irfS,WSJ did you purchase? Specify:2. No-98, REFUSED-99. DON'T KNOW
C3. $f$'$SError! Reference source not found.*.tJ When did you purchase $$X$il.$J?
1. Specify:-98. REFUSED-99. DON'T KNOW
C4. ff$ SJ*iJ Did you receive a rebate for $fISJlrf*I?
1. Yes
C4a. Was it a utility rebate? Specify:
2. No-98. REFUSED-99. DON'T KNOW
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No, 5 Page 165 of 1365
Case No. PAC-E-14-07
Wtnessr Kathryn C. Hymas
December 2009
c5.What were the most important criteria for you when choosing the make and model of
$f r*"*+r'31'g31qg,
!.^$ "
D1.
The efficiency
Energy Star
Price
Color
Brand
Utility rebate
Ma nufacturer rebate/Store rebate
Financing
Size
Other:
C5a. Specify:
REFUSED
DON'T KNOW
Sr*gnam Atnsaren*ss
How did you first hear about [$TIL$TY]'s Home Energy Savings program? {SS l$ST SNSNIFT.
sNs &NS\e{Hffi StStY}
Bill insert
Print ad
Radio ad
L,
2.
3.
4.
5.
6.
7.
8.
9.
10.
1.
2.
3.
4.
5.
5.
7.
8.
9.
10.
11.
Online ad or Web site
D1a. Specify:
Telemarketer
Utility Call center
Utility Welcome/Moving kit
Utility Energy newsletter
Brochure
Friend, Family member, co-worker (word of mouth)
Other
D1b. Speci
D2,
-98. REFUSED
-99. DON'T KNOW
$S"$"t s$-l Have you been to the [t]T[$-lTY] website?
1.
2.
-98.
-99.
Yes
No
REFUSED
DON'T KNOW
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountraln Power
Exhibit No. 5 Page 166 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
$S$SS.s\r S$iS'VANS Sti$$$$Si $S sSN $AS$$ st$$SS{JR$ s"t-"s$. IAI $$$yl$d$ AJ
D3. Please think back to the time when you were deciding to buy the energy saving itf$'s.'f$trSM$jt,
perhaps recalling things that occurred in your household shortly before and after $$MS$SSSX$j.
What factors motivated you to purchase Iif$M/$IS'$t$Sf? {SS N*T NS,AS; tlSS$fls.TS &t$" Tl"{S'$'
AFFTY; SN{* T$'$f,Y R$$FSN*SNT NS.$ S[NI$NHS. PR*S$: Sfi$ Tl{fiRS ANY *TNtSS $.&STSRS?}
Old equipment didn't work
Old equipment working poorly
The program incentive
The program technical assistance
Wanted to save energy
Wanted to reduce energy costs
The information provided by the Program
Past experience with this program
Because of past experience with another [utility] program
Recommendation from other utility program (Probe: What program? _)
Recommendation of dealer/retailer
Recommendationofsomeoneelse(Probe:Who?-)
Advertisementinnewspaper(Probe:Forwhatprogram?-)
Radioadvertisement(Probe:Forwhatprogram?-)
Other
D3a. Specify:
15. Environmental concerns
17. Globalwarming
18. Liked the appearance of the Energy Star J'lF$S$.JiYSd\,s$j more than the old one
19. Keeping up with the latest trends and fashions
-98. REFUSED
-99. DON'T KNOW
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
LL,
t2.
13.
L4.
15.
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No.5 Page 167 ot 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
E1.
L$ssgsJNets$t$s$\sdsmtis$sctlsm
$d$SI*"tJ Now, I would like to understand what you did with the ENERGY STAR clothes
washer. ls this ENERGY STAR clothes washer currently installed and if so, where is it installed?
{ssssRs sN$ N["$$!ts$R]
1. lt is currently installed at your home2. lt is installed at some other location
3. lt was installed at your home but is now permanently removed (example: broke, burned
out, don't fit, don't like, etc.)
4. lt was installed at home, wasn't working properly, and was replaced with another
energy efficient clothes washer through warranty
5. lt was sold or given away
5. Other
E1a. Specify:
-98. REFUSED
-99. DON'T KNOW
$fS $S*SJ Regarding your clothes washer, approximately how many wash loads do you do in a
tvpicalweek?
E2a. [ttSSS$s $SIJIVISHN I$ $l$s$l] Specify: :
-98. REFUSED
-99. DON'T KNOW
$$S $Ts'Sj How does the number of wash loads you do now compare to the number that you did
with your old clothes washer?
Same 3"SS$$ "TS S$..r
Different
E3a. lf different, do you do more or less loads now than you did before? Could you
estimate a percentage?
i. More loads now, Record percentage [$ilt]ST S$. $$tHr\TSS T$$$\N ]"S$]t, HS
'i ,}{$/^ f,{\$ "}R*.i N.$r'\$$. }s&d/u r \r3\ tuqlJu ssrsts\Li
ii. Less loads now, Record percentage lS\$tl$T SS S-S$S Tt*Si\N tu.$tttli. tiS
J\oA$3 IN J\+/:. I F\\ I HiSSl NtsS{ tNP t
REFUSED
DON'T KNOW
E2.
E3.
1.
2.
-98.
-99.
PacifiCorp HES lD & WA Multiple Measures Survey
Roclq Mountain Povver
Exhibit No. 5 Page 168 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
E4,
E5.
E6.
E7.
E8.
$iF SS*iJ
N$H#fi$!
L.
2.
3.
4.
-98.
-99.
How much of your wash do you typically dry using a clothes dryer? {*[AS CATSS*$t$fr$ [S
<25%
25-5Oo/o
so-7s%
75-LO0%
REFUSED
DON'T KNOW
$lF $3*{J Due to your new clothes washer, did your dryer usage change?
1. Yes
[S.&. About how much did it change? {SSA$ S${S$ilSS lf NHSSfr$}
i. lncreased a lot
ii. lncreased some
iii. Decreased some
iv. Decreased a lot
2. No
-98. REFUSED
-99. DON'T KNOW
ffF S3*i *I How satisfied are you with your ENERGY STAR clothes washer?
1. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied
4. Not At All Satisfied
-98. REFUSED
-99. DON'T KNOW
ff$ $S*'I.i Have there been any changes in comfort or ease of use compared to your old clothes
washer?
1. Yes
E7a. Specify:2. No-98. REFUSED-99. DON'T KNOW
$S $l*SJ Were you satisfied with the amount of the incentive?
1. Yes
2. No
E8a. Specify:-98. REFUSED-99. DON'T KNOW
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No. 5 Page 169 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
E9.$S SS*{J Were you satisfied with the timing of the incentive?
L. Yes
2. No
E9a. Specify:
-98. REFUSED
-99. DON,T KNOW
E10. $fS $i=$3 Overall, how satisfied are you with the rebate program?
1. Very Satisfied
E10a. Specify:
2.
3.
Somewhat Satisfied
E10b. Specify:
Not Very Satisfied
E10c. Specify:
Not At All Satisfied
E10d. Specify:
REFUSED
DON,T KNOW
It is currently installed at your home
It is installed at some other location
It was installed at your home but is now permanently removed (example: broke, burned
out, don't fit, don't like, etc.)
It was installed at home, wasn't working properly, and was replaced with another
energy efficient clothes washer through warranty
It was sold or given away
Something else
E11a. Specify:
REFUSED
DON'T KNOW
4.
-98.
-99.
E11.ff$^{$=SJ Now l'd like to ask you a few questions about the ENERGY STAR dishwasher you
purchased. ls it installed and where is it installed? {&HAS tlST'ANS SS*S&* $N$ NHSF*NSS}
1.
2.
3.
4.
5.
6.
-98.
-99.
ELz. ff$ $33*3J How many times a week would you estimate that you use the Energy Star dishwasher?
EL2a. Specify:
-98, REFUSED-99. DON'T KNOW
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No. 5 Page '170 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
E13.
E74.
ff$ SI3*fJ How satisfied are you with your Energy Star dish washer?
1. Very Satisfied
2. Somewhat Satisfied3. Not Very Satisfied4. Not At All Satisfied-98. REFUSED-99. DON'T KNOW
ffF SSI*SJ Have ther.e been any changes in comfort or ease of use compared to your old
dishwasher?
t. Yes
E74a. Specify:
2. No.98. REFUSED.99. DON'T KNOW
$fF SII=IJ Were you satisfied with the amount of incentive?
1. Yes
2. No
E15a. Specify:.98. REFUSED
-99. DON'T KNOW
E15.
E16. ff$$33*3J
1.
2.
-98.
-99.
El7. $$ $$S=Sj Overall, how satisfied are yru with the rebate program?
2.
3.
L Very Satisfied
EL7a. Specify:
Somewhat Satisfied
Et7b. Specify:
Not Very Satisfied
EL7c. Specify:
Were you satisfied with the timing of the incentive check?
Yes
No
E15a. Specify:
REFUSED
DON'T KNOW
Not At All Satisfied
EL7d. Specify:
REFUSED
DON'T KNOW
4.
-98.
-99.
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No. 5 Page 171 of 1365
Case No. PAC-E-14-07
Vvltness: Kathryn C. Hymas
December 2009
E18.lSS"$S"q**,**"\$S S:$$.\* $$S.qS{"$,\).\" iS A$ *S* "s\S *S , ..$$*S $S S$*"tJ Now, I would like to
understand what you did with the $T'S,\'.tJ. ls this f$]'S,\$J'currently installed and where is it
i nsta I I ed ? { N$S$R$ $rs* $ N L$ i\'t$}sN}
t.
2.
3.
4.
5.
5.
It is currently installed at your home
It is installed at some other location
It was installed at your home but is now permanently removed (example: broke, burned
out, don't fit, don't like, etc.)
It was installed at home, wasn't working properly, and was replaced with another
energy efficient IIIH$$J through warranty
It was sold or given away
Other
E18a. Specify:-98. REFUSED
-99. DON'T KNOW
E19.
E20.
E27.
How satisfied are you with $ST'SSf"I?
Very Satisfied
Somewhat Satisfied
Not Very Satisfied
Not At All Satisfied
REFUSED
DON'T KNOW
Have there been any changes in comfort or ease of use compared to your old [it-$S,$j?
Yes
E2Oa. Specify:
No
REFUSED
DON'T KNOW
Were you satisfied with the amount of incentive?
Yes
No
EZta. Specify:
REFUSED
DON'T KNOW
E22. JT$SSS=S*I Were you satisfied with the timing of the incentive check?
1.. Yes
2. No
E22a. Specify:
-98. REFUSED
-99. DON'T KNOW
$$ $3S*$3I
t.
2.
3.
4.
-98.
-99.
$"r.$$T$.,.ts!
1.
2.
-98.
-99.
$^i.$$ss\sJ
t.
2.
-98.
-99.
PacifiCorp HES lD & WA Multiple Measures Survey
Roclry Mountain Power
Exhibit No. 5 Page 172 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
December 2009
823.flF,SIS=}j
1.
2.
3.
4.
-98.
-99.
Overall, how satisfied are you with the rebate program?
Very Satisfied
E23a. Specify:
Somewhat Satisfied
E23b. Specify:
Not Very Satisfied
E23c. Specify:
Not At All Satisfied
E23d. Specify:
REFUSED
DON,T KNOW
F2.
F. Fri*r Hqulpr$e$t
[$iei:eat relevant q$sstions FS thr+ugh $$ f*r e+*h N4easure, .4.t-SS, MStr$SSS'X] iet $S'CHSI$ Al
F1. Was this purchase intended to replace an old 3'fI$Jl$J?
L. Yes
2. No
-98. REFUSED.99. DON'T KNOW
NS$- S3*XJ About how old was the $ff$Sr$J you replaced? {RSAS CATHS*NIfiS tS NSS$IS]
1. Less than 5 years old
2. 5 to less than 10 years old
3. 1.0 to less than 20 years old
4. 20 years to less than 30 years old
5. 30 or more years old.98. REFUSED
-99. DON'T KNOW
$dS S$=SJWas the old $iTS$$j in good, fair, or poor working condition?
1. Good
2. Fair
3. Poor
4. Not working.98. DON'T KNOW
-99. REFUSED
F3.
10
PacifiCorp HES lD & WA Multiple Measures Survey
Roclry Mountain Power
Exhibit No. 5 Page 173 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
F4,IJ$ A'SSAS{"JSS,$S*"t ANS fS $S=$*l What type of fuel did the old $fISS,$J use?
1. Gas
2. Electricity
-98. DON'T KNOW
-99. REFUSED
ff$ SI*SJ What did you do with the old $ds$Nfj?
1. Sold or given away
2. lnstalled in another location
3. Still in home but permanently removed (stored in garage, etc.)
4. Thrown away
-98. DON'T KNOW
-99. REFUSED
s.Sree-ridersl'lip
fS$FSSf SSL$tf"SNrS{.$SS$SNS S"S IFISS{JSi-f SS SSS fAS$f M$AS$S{. AS-"q$, N}$S$Sj\.'$$ jN
ss$rf$NA.3
G1. Prior to purchasing $ffSA,,f$f$$SSJ for which you received the rebate, had you ever purchased the
same ffI$$$...ilF$ftSSjI for another home, room or location?
F5.
G2,
G3.
1. Yes
2. No
-98. REFUSED
-99. DON'T KNOW
Prior to learning about the program, would you have purchased frfSMc/ifSSr}SJ without an
incentive?
L, Yes
2. No
-98. REFUSED
-99. DON,T KNOW
ffS $'J*J,l Would $ST-SM$IS&.fSJ have had the same level of efficiency, be more efficient, or less
efficient?
L. More efficient
2. Less efficient
3. Same level of efficiency
-98. REFUSED
-99. DON'T KNOW
TL
PacifiCorp HES lD & WA Multiple Measures Survey
Roclry Mountain Power
Exhibit No. 5 Page 1 74 of 1 365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
December 2009
G4.$$,s S$*SJ lf the rebate had not been available, would you have installed fff$S,tt'fYSJS$SJ with the
same qualifying measures, some of the qualifying measures, or none of them?
L. AII
2. None
3. Some
G4a. Specify:-98. REFUSED
-99. DON'T KNOW
fd$ SS=fJ Would you have purchased fff$'Sf$f$It$Sj at a later time if the rebate had not been
available?
G5.
7.
2.
3.
4.
5.
-98.
-99.
ln the same year
ln one or two years
ln three to five years
After more than 5 years
No
REFUSED
DON'T KNOW
H1.
lx.$pillov*r
Since participating in the program, have you added any other energy efficient equipment or
services in your home that were not rebated through the program?
1. Yes
2. No f$trfF rS i$,r-98. REFUSED ISJfiS XS rSJ-99. dON',T KNOW JS${dp rS rSJ
ffS NS*Ij Please describe the type of the equipment or services.
fssSSsS ssSsSiNSsJ
-98. REFUSED.99. dON'T KNOW
ffF $f.f* jrl On a scale of 0 to 10, where 0 is not at all influential and 10 is very influential, how
influential would you say the Home Energy Savings program was in your decision to add energy
efficient equipment or services to your home?
ISS',$SSS S$SS$NS',$j
-98. REFUSED-99. DON'T KNOW
H2,
H3.
12
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No. 5 Page 175 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
December 2009
t1.
Sermognaphics
These next questions ask about household characteristics to make sure we're getting a
re prese ntative sa m ple of [*-]T! 8"$TY] residents.
Are you the homeowner, renter, or landlord for the house in which the Energy Star ffF$Si
$$A"S$I$MS iSrSS$J i nsta I led ?
1. Homeowner
2. Renter
3. Landlord
4. Other
l1a. Specify:
-98. REFUSED
-99. DON'T KNOW
ln what type of building do you live? IffiSAS ill$T $S $$S*SilS] {SRSSS SSN '**$SS*': "$$Sxu'N [\'lA$Sr*
t$t$Ts &Rs IN ystj$ sLj$t"s$t$st"I
t2.
A one-family home detached from any other house
A one-family home attached to one or more houses
A building with 2 apartments
A building with 3 or 4 apartments
A building with 5 or more apartments
A mobile home
Other
l2a. Specify:
-98. REFUSED
-99. DON'T KNOW
About when was this building first built? IffiHAS tt$T {$ INSSSfrS]
L.
2.
3.
4.
5.
6.
7.
t3.
L,
2.
3.
4.
5.
6.
7.
-98.
-99.
Before 1970's
7970's
1gg0's
1990-94
1995-99
2000's
OTHER
l3a. Specify:
REFUSED
DON'T KNOW
13
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No. 5 Page 176 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
14.Were you living in this same home around ${NSS'$I SAYS SJ dl,f$Nru{S FSdSS YS ffJW$ S$
FASr$.*SisSXfSNtJ?
L. Yes
2. No
-98. REFUSED
-99. DON'T KNOW
15. Approximately how many square feet is the home in which the f,fI$M $t/AS$fsM$ [.VS$S'J
installed?
L.
2.
3.
4.
5.
-98.
-99.
1.
2.
3.
4.
5.
6.
7.
-98.
-99.
Under 1,000 square feet
1,000 - 1,500 square feet
1,501 - 2,000 square feet
2,O0L- 2,500 square feet
Over 2,500 square feet
REFUSED
DON'T KNOW
t5.
17.
How many people live in your home year-round?
[*H{$NS}: _people-98. REFUSED
-99. DON'T KNOW
Which of the following best describes your age?
Less than 18 years old
18-24 years old
25-34 years old
35-44 years old
45-54 years old
55-64 years old
55 or older
REFUSED
DON'T KNOW
t8.$f$'l$>SJ lncluding yourself, how many people currently living in your home year-round are in the
following age groups?
Less than 18 years old
18-24 years old
25-34 years old
35-44 years old
45-54 years old
55-64 years old
65 or older
-98. REFUSE
-99. DON'T KNOW
L4
PacifiCorp HES lD & WA Multiple Measures Survey
Roclry Mountain Power
Exhibit No. 5 Page 177 of 1365
Case No, PAC-E-14-07
\Mtness: Kathryn C. Hymas
December 2009
19. Has the total number of people living in your home year-round changed since [!NS$S"$'*A'$'il t]
t\.$sNY${s sstss rs r$}\ss *s ssNT$*$sAT$sNi?
1. Yes
2. No-98. REFUSED.99. DON'T KNOW
110. $$$f$*"tJ Do more people or less people live in your home now?
1. More
110a. How many more?
-2. Less
110b. How many less?
--98. REFUSED
-98. DON'T KNOW
$$S f$*Jj ln what year(s) did the number of people in your household change? [ftilCSRS etL
ysARs s$ c$feNsH*Nsr $F"$AN$[ ts sAt-suLAT$s FRsns r:s]
1't NET CHANGE:
2Nd NET CHANGE:
3'd NET CHANGE:
-98. REFUSED
-99. DON'T KNOW
MONTH
YEAR
YEAR
YEARMONTH
111. Did you do any remodeling, renovation or additions since {ll$$*RY SATS 3"} tu'iSNT}^lS pRi*R TS
T$Nt$ *F $AfiTI*tSAYr$NI?
1. Yes
2. No.98. REFUSED
-99. DON'T KNOW
lL2. ff$ $*.t*SJ How many remodels, renovations or additions have you done since then?
_ Remodels, renovations or additions
-98. REFUSED
-99. DON'T KNOW
15
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Po rer
Exhibit No. 5 Page 178 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
r13.fd$ f"f S*SJ l'm going to ask you several questions regarding the timeframe of your remodels,
renovations or additions. We will try to run through them quickly. IASN &-S F*R S&{${ HSf\tSSHt
T$iAT TS*${ pLA*$ $tN{f, J.qN$ARy 1, AS$S}.
a. ln what month and year did it start?
b. Did this increase or decrease your home's square footage, not counting unfinished
storage spaces, porches or garages,
Do you receive an electric bill directly from [{.ST$I"$TY}?
L. Yes
2. No.98. REFUSED
-99. DON'T KNOW
Does this bill only include your home's electric use, or does it include the electric use of other
households?
174.
t15.
I
1.
2.
-98.
-99.
Only t household
Multiple households
REFUSED
DON'T KNOW
115. This next question asks about other changes you have made that we haven't already talked
about. Since ISANUASY t, ]$SS], have you made any other changes to the appliances,
equipment or other characteristics of your home that would affect how much energy you are
using?
1. Yes
2. No
-98. REFUSED-99. DON'T KNOW
Isj{fs rsfssjr
Isffip rsJs$i
isNip rsis$J
15
ln what month and did it finish?
a. START(mm/ywy)b. lncrease or decrease?
1 lncrease
2 Decrease
3 Same/no change
D (DK)
R REFUSED
C. FINISH(mm/yyW)
Roclry Mountain Power
Exhibit No. 5 Page 179 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009PacifiCorp HES lD & WA Multiple Measures Survey
lL7 . fdF fS$*3J What types of changes did you make? $FSSISY: i*S N$T RS&S. NStSRt) A, "j.* $SS
SAfi!"t TYPS SS S$'{&f{$S S,1&SS. FNSSS: A$SYTF{[NS HI-SS?]
Heating and air conditioning measures
It7a. Central air conditioner
It7b. Room/wallairconditioner
lL7c. Evaporativecooler
ll7d. Heat pumps
l!7e. Furnace
ItTf . Programmable thermostat
lL7g. lnsulation
lL7h. Duct sealing
Laundry measures
lL7i. Clothes dryer
Kitchen appliances
It7i. Freezer
l]-7k. Range/oven
Poollspal lacuzzi
It7l. Swimming pool
lL7m. Swimming pool pump
It7n. Swimmingpoolcover
lL7o. Spa/Jacuzzi
Other
177p. Other (SPECIFY)
JASN$i$ vS$SSgr'S$$ l*"$ S'SS $A$sd $$S'$S{JRS'S$i$SISS fIS JJ"FJ
118. Did this fl3f $$SASiJS$J replace (an) existing $ff e,f$AS{.tN$.I or was it new to your home?
L. Replaced existing equipment
2. New to home
-98. REFUSED-99. DON'T KNOW
119. When did this occur? ISH*SNS Nt$lST${ A}$S YSANi
MM/YYYY
-98. REFUSED
-99. DON'T KNOW
120. IfS fS$*-$$J Was this before or after you participated in the $SS$$S"$S$-F?
1. Before
2. After.98. REFUSED
-99. DON'T KNOW
L7
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Po\,ver
Exhibit No. 5 Page 180 of 1 365
Case No. PAC-E-14{7
Wtness: Kalhryn C. Hymas
December 2009
fH$tr i3.{ AJ1JS l** lS fJ I= AJVY SS f3 p$, ,t $" $.{ ftr, t{ fSJ
lzt. What type of fuel does the new ff$I IV?SA.${JS$J use?
1. Gas
2. Electric3. Other
l2La. Specify:-98. REFUSED-99. DON'T KNOW
122. f,4Str fS J3$* SJ What was the fuel type of the Ii37 &fS'A${J*S'J you replaced?
1.
2.
3.
-98.
-99.
Gas
Electric
Other
122a. Specify:
REFUSED
DON'T KNOW
123. Did you receive a rebate for this ff3f MS'SS{JS$*I through a utility program?
fsi#F rs r$€xrffPskfg'A${Jss, fFefsivs$ffF rs $g4J
ISSfp rs rcs'xrfsrsdf,Asus$, f$'&rsi\lssKIp rs i*sf
fssfF r0 NfxrfftrM$As{.Je$, J$firsrus$x(Is rs J3$J
124.
L. Yes2. No-98. REFUSED-99. DON',T KNOW fsr{fp rS fVSNr$3f Al}fi',A${"f$& fSAfSJVS',$SIp rS $gSJ
flf rlf = fJf$.4N$ JJ$.}J Previously you mentioned you replaced your furnace, is this furnace the
primary heat source for your home?
1. Yes2. No-98. REFUSED
-99. DON'T KNOW
18
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Power
Exhibit No, 5 Page 181 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
December 2009
125. $f$ dff$*} SN' f$'Ii f $ ilSS'J What is the primary heating source for your home?
Forced air natural gas furnace
Forced air propane furnace
Heat pump
Electric baseboard heat
Gas fired boiler/radiant heat
Oil fired boiler/ radiant heat
Passive Solar
Pellet stove
Wood stove
Other
125a. Specify:
REFUSED
DON'T KNOW
126. ldSS$sS-l Do you have a gas or electric water heater?
1.
2.
3.
4.
5.
5.
7.
8.
9.
10.
-98.
-99.
1.
2.
3.
4.
5.
-98.
-99.
1.
2.
3.
4.
5.
-98.
-99.
1.
2.
3.
4.
5.
-98.
-99.
,27. IfS fSf s$$Ilj Do you have a gas or electric clothes dryer?
Gas
Electric
Both
Solar
Other
126a. Specify:
REFUSED
DON'T KNOW
Gas
Electric
Both
Other
127a. Specify:
t28.$SSISp * fSftrf Do you have a gas or electric range/oven?
None
REFUSED
DON'T KNOW
Gas
Electric
Both
Other
128a. Specify:
None
REFUSED
DON'T KNOW
19
PacifiCorp HES lD & WA Multiple Measures Survey
Rocky Mountain Po rer
Exhibit No. 5 Page 182 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
December 2009
129. On a scale of 0 to 10 where 0 indicates not at all satisfied and 10 indicates completely
satisfied, overall how satisfied were you with the Home Energy Savings program?
L. Rate:_
-98. REFUSED
-99. DON'T KNOW
t30.COMMENTS Those are all of my questions. Do you have any questions or comments for me?
1. Yes
Record Verbatim:
2. No
-98. REFUSED
-99. DON'T KNOW
THANK & TERMINATE
20
Roclry Mountain Power
Exhibit No. 5 Page 1 83 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
CANMIJS
FacifiCorp CFL Leakage Residential RDD Sunvey
A. $mtr$ctnl*tiqir'!
Hello, my name is and I am calling from Discovery Research on behalf of J"p.S$$Sd$
S$tts$S.r'SS$${y fV$Stf}VflSJS! F$$VSSj. We are exploring issues related to household lighting. l'm not
selling anything. I just want to ask you questions about some of the ways you use lighting in your home.
A1. Could I speak with the person who usually purchases the light bulbs for your household?
L. Yes2. No lTmY TS l{U${!"tSDl}tS SH TSS$\i}ls}STfl}
-98. REFUSED {YE\Y TS S*S$1"{[S{"$l^il SH FSNN.'tll$A-r$}-99. DON',T KNOW IYRY TS mS$il*$St]$LS St\ TSNI\t$N.ETS]
A2. Who provides your electricity service?
L. Pacific Power/Rocky Mountain Power ITHANP{ AN# Tflft$ttlNAT*}
2. Other
A2a. Specify:-98. REFUSED-99. DON'T KNOW
S, Aw.*rgness
81. l'd like to ask you a few questions about your awareness of different types of light bulbs.
Before this call today, had you ever heard of compact fluorescent bulbs, or CFLs?
1. YES fsJ{IS rS $ll
2. NO-98. REFUSED-99. DON'T KNOW
82. Compact fluorescent light bulbs - also known as CFLs - usually do not look like regular
incandescent bulbs. The most common type of compact fluorescent bulb is made with a glass
tube bent into a spiral, resembling a soft-serve ice cream cone, and it fits in a regular light
bulb socket. Before today, were you familiar with CFLs?
1,. YES
2. NO {T$-{AN${ Ar$S T$frtu'lll$AT$}
-98. REFUSED-99. DON'T KNOW
PacifiCorp CFL Leakage RDD Survey
Rocky Mountain Power
Exhibit No. 5 Page 184 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
October 2009
il.
c1.
Fmrahirs*s
ln the last three years have you, or has anyone else in your household, purchased any
compact fluorescent light bulbs or CFLs to use in a home?
t. YES, I HAVE $SStr $3,SJ
C1a. Would you please estimate the number of compact fluorescent light bulbs or
CFLs that you have purchased in the last three years; that is, the number of
individual bulbs, not just packs of bulbs, that you have purchased since the
beginning of 2005?
Record Number:2. YES, SOMEONE ELSE HAS [lS SN$"Y SS$rlSSt$S SL$$, A$K TS Sil$AN T* T$"{AT FHR$SN
ANS REPSAT iNTR*. {S NST F*$SiSLS. ASS CJS. !F R$SPSN*SNT ANS $S*$SSNfl SI"S[,
** N*T fiHPf;AT INTRS. JU$Y S$K $SS:
C1b. Would you please estimate the number of compact fluorescent light bulbs or
CFLs that have been purchased by members of your household in the last three
years; that is, the number of individual bulbs, not just packs of bulbs, that you
have purchased since the beginning of 2005?
Record Number:
C1c. Would you please estimate the number of compact fluorescent light bulbs or
CFLs that have been purchased by all members of your household in the last
three years; that is, the number of individual bulbs, not just packs of bulbs, that
you have purchased since the beginning of 2006?
Record Number:
3.
-98.
-99.
NO $S$$S$S',o$"dN SSS. SNJp rS StJ
REFUSED
DON'T KNOW
PacifiCorp CFL Leakage RDD Survey
Rocky Mountain Power
Exhibit No. 5 Page 185 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
October 2009
D1.
Furc$rase l"ercati*xts *t lrel Stx trh Characte ri sti cs
fASN SJ f$fSS{JS}f Error! Reference source not found. SiSi.yIS $S"$ } $J Do you know the
name and location of the store from which you purchased CFLs and the approximate date?
1. YES
Dla. What is the name of the store or stores from which you purchased CFLs, where
are they located and about when did you purchase the CFLs?
Name Store L:
D1b. Location Store L:
Dlc. Date Store 1:
D1d. Name Store 2:
D1e. Location Store 2:
D1f. Date Store 2:
Dlg. Name Store 3:
D1h. Location Store 3:
D1i. Date Store 3:
Dli. Name Store 4:
D1k. Location Store 4:
Dll. Date Store 4:
D1m. Name Store 5:
Dln. Location Store 5:
NO
REFUSED
DON,T KNOW
2.
-98.
-99.
D2. Do you recall the wattages of the CFLs that you purchased?
1.
2.
-98.
-99.
YES
D2a. Specify Wattage NN,'I$ST tSN.tN'l*N]:
NO
REFUSED
DON,T KNOW
Do you recall the wattage of the bulb that was replaced by the CFL, or the most common
wattages of the bulbs that were replaced?
1. YES
D3a. Specify Wattage [S'I$ST {SMeilSN}}:
2. NO
-98. REFUSED
-99. DON'T KNOW
D3.
PacifiCorp CFL Leakage RDD Survey
Rocky Mountain Power
Exhibit No. 5 Page 1 86 of 1 365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
October 2009
D4. Of the bulbs you purchased, how many would you estimate were specialty or designer styles
such as reflector bulbs, candelabra bulbs, dimmable or three-way bulbs?
Record number:
-98. REFUSED
-99. DON'T KNOW
N" Sem*gnaphi*s
Now I have a few last questions for statistical purposes only.
E1. What type of home do you live in? ls it a ...?
1. Single-family detached house
2. Single-family attached house (townhouse, row house, or duplex)
3. Multifamily apartment or condo building with 3 or more units
4. Mobile home or house trailer
5. OTHER JH$i{St$$E1a. [SsssiilY]:'98. REFUSED
-98. DON'T KNOW
Thank you for your time.
Roclry Mountain Power
Exhibit No. 5 Page 1 87 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
CANMUS
FacifiCorp CF'X, Leakage Retailer Sunvey
'\a*.$.srtr$$Nq:s$qrs\
Hello, my name is and I am calling from f$fSS$\.iS'.S}'SS'S$AS$,SJr$$S $ASi\,.ftiS
SSS{JSJ on behalf of f$s\$.r$f$ PS*4ISNJNS$NY $WS{"$NIASN* $S$$$NJ. We are exploring issues related to
residential lighting. l'm not selling anything. I just want to ask you four or five quick questions about
your Compact Fluorescent Lamp, or CFL sales, and the impact of promotions that have been run by
l|s.$ sf$'$$ s$wcssJss$Ny $.$s{".f.\'tKJiY $s $$s'sJ.
A1.Are you familiar with your store's CFL sales from the past couple of years?
42.
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DON',T KNOW {TtCY T* i$SSrT$FY A$"THNNATS *S$NTA{Y SS TH$$\.}$NATSI
Do you recall participating in any promotion of CFLs, or offering discounted CFL bulbs for sale
that were sponsored by $S.S$SS$$ SS\.\J$S,J$$$NY S$*tdSrt":EJNr $$\N$Nj?
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REFUSED iTHN$\$Ner[i
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Over the past four years - Since the beginning of 2006, of all the CFL bulbs you have sold,
what percent would you estimate were bulbs associated with the J"$A$$.sf$ SSiSr$,\-..d'NS$Nl"
,\$${"$Nr"t'HfNs SS \.\i'SN-i p ro m ot i o n s ?
Record Percent:
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$Ssi$ x$ $"$sJ
82.On average, how many CFLs would you say that you sold in any given month since the
beginning of 2006?
Record Number:
-98. REFUSED f$^Nis FS s,$sJ
-99. DON'T KNOW JSftT$ IS $$*J
PacifiCorp CFL Leakage RDD Survey
Roclry Mountain Power
Exhibit No. 5 Page 188 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
October 2009
83.fIS'$S > $.4AfS $3 5 Sf So, at this time would you estimate that have sold about {SSLS{dlS?S;
s"I x sfJ CFL bulbs associated with the fFASJFJS FSws$lsSSNy MSt{NIsrru p$w$s,t
promotions each month since the beginning of 2005?
1. Yes
2. No
B3a. ffF $$** SR SJ<$ SS $"4{$J What would you say is an accurate estimate of the
number of CFL bulbs associated with the fF,A$fFfS pS[41S'Sy'S$Stry S$*{JNIAfN
SSl.trS'SJ promotions that you have sold each month, since the beginning of
2006?:
B3b. fIS $$=S-3 Would you please explain why this number is f$df$SfSS$.S$r$SJ than
the number I estimated from your responses to my earlier questions about the
number of CFLs you have sold each month, and the share of those that were
associated with the l$S$f$f$ SSI$rSS/SS$J$Y i\,fS{JNfAfSr PSMJSSJ promotions?
{ts Nsss$sANY. RHA[} s-tf,i{ *tJHsTtsN$ ANs Rssp*N$ss ss& $} Atss sa A[\Js
&HV|$H TNSS$ ftESFSNSfiS AS AFFRSFSTATHJ:.98. REFUSED.99. DON'T KNOW
B,4. ln what ways, if at all, would you say that your sales of CFL bulbs associated with the sr$.S$lSI$
SSttf$SdR$Stry MS{JJS$,4IFJ FSt4x$SJ promotions, and sales of CFLs in general, have changed
in the past four years?
Record Verbatim:
-98. REFUSED
-99. DON'T KNOW
C" Cnnch.xsitrn
C1. Do you have any other comments or thoughts about CFLs, CFL promotions, or promotions
related to other devices that you would like me to take back to $SACfSJS SSTYS$/SSSffY
&fs{.Jr$rAt{* p$r#sRJ?
1. Yes
Cla. Record Verbatim:
2. No
-98. REFUSED.99. DON'T KNOW
Thank you for your time.
Rocky Mountain Power
Exhibit No. 5 Page 1 89 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Implementer Discussion Guide
PacifiCorp Home Energy Savings Program
Name & Agency of lnterviewee
Date of lnterview:
The purpose of the interview is to explore your experience with the PacifiCorp HES program. Please
feel free to let me know when there are areas that you do not have experience with so that we can
move on to those areas in which you've worked most closely.
Roles and Responsibilities
L. What is your role in the PacifiCorp Home Energy Savings Program?
a. How long have you held this position?
b. What proportion of your job is dedicated to the PacifiCorp Home Energy Savings
Program?
i. (lf a small percentage) what other roles do you play?
Program Design
2. How does the current HES Program compare with other efficiency programs that you have been
involved with? lProbe for unique feoturesl
3. What do you believe are the strengths of the HES Program?
4. What are the areas of improvement for the HES Program?
5. What would you consider the progress, or success, indicators for the program? [Probe for short
term vs. long terml
a. How have these changed over the life of the Program or since the implementation of
the current Program?
b. Are there any goals of the Program to influence awareness, perceptions, incremental
cost, or other market effects such as NATE certification? lProbe for which ones and
how the progrom might influence these odditionol outcomesl
c. Has the program exceeded certain goals? Fallen short on any? lf so, why?
6. Has the Program changed in response to any apparent issues/concerns from its original design?
a. ln your opinion, are there additional changes that you believe are needed? lf so,
specifically what are theY?
HES Program lmplementer Discussion Guide Page I
Roclry Mountain Power
Exhibit No. 5 Pase l:Tj1f3i
Wtness: Kathryn C. Hymas
Implementer Discussion Guide
PacifiCorp Home Energy Savings Program
Program Delivery
7. Could you briefly describe how the Program activities are delivered?
a. What are the roles of various parties involved in delivery? What are staffing requirements
and duties of the various staff members?
b. What training, if any, was provided to staff? What training, if any, is still desired or
required?
c. What are the key differences between states?
8. Which stakeholders and participating dealers does the Program most commonly work with? How
are these individuals identified?
9. What works particularly well about program delivery? [Probe: ot eoch stage - morketing,
instollotion, inspectionl What most needs to be changed?
Program Administration
10. What is the primary method by which customers apply for the program? How do most customers
learn about the Program?
11. ln your opinion, are there any opportunities to improve the current administrative
approach/structure?
12. What are the Program reporting processes?
a. What are the QC procedures for reporting and tracking?
b. Are internal inspections/verification conducted?
c. How effective and accurate is the data-tracking and data collection system?
d. Are data entered and reported in a timely fashion?
13. How do you collect feedback from dealers or customers? Have you summarized this info?
a. How is eligibility for the Program determined?
b. To what extent is the general customer base aware of the program?
i. What might be done to reach the unaware customers?
Program !mplementation
14. How is communication between stakeholders conducted? lProbe: formol and informoll
a. How are stakeholders informed of program changes?
15. How would you rate the effectiveness of communication with PacifiCorp/manufacturers/dealers?
Could it be improved?t
HES Program lmplementer Discussion Guide Page 2
Rocky Mountain Power
Exhibit No. 5 Page 191 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Implementer Discussion Guide
PacifiCorp Home Energy Savings Program
O 16. How was the Program marketed (in each state)?
a. What are the most effective promotional activities?
b. What has not worked and why?
Program Theory and Logic
L7. What are the market barriers to CFL lighting?
18. What are the market barriers to insulation?
19. What are the market barriers to high efficiency appliances?
20. How does the HES mitigate these market barriers? [Probe by morket octor]
Market Actor lntervention Strategies Short term goals Long term goals
Dealers
Distributors
End-use
customers
Manufacturers?
Other
Other_
Participant Response
21. What has been the response of participants to the program? What do you think they would say
about the program?
22. Has program participation varied geographically or by type of dealer? lf so, why has this been the
case?
23. Do you conduct any sort of follow-up survey with participants?
a. lf so, is this feedback recorded or tracked?
b. What feedback, if any, from customers has led to changes in program
implementation? lf so, can it be made available?
24. What have participants liked best/least about the program?
HES Program Implementer Discussion Guide Page 3
Roclq Mountain Power
Exhibit No 5 Pase ll?j,lf3i
Wtness: Kathryn C. Hymas
Implementer Discussion Guide
PacifiCorp Home Energy Savings Program
a. Have there been any major problems or complaints?
b. What challenges exist for participation?
Recent Changes to Program and Goals
25. Can you describe how the current program offerings (for 2007 and 2008) were selected?
26. Have there been any changes to the program in 2007 and 2008? [f yes] What were the changes
and how'have these changes impacted the program?
a. What impacts, if any, have you seen from switching from a one-year program cycle to
a three-year program cycle?
b. What changes do you anticipate for the lighting program given the upcoming changes
to Federal standards (EISA) in 2Ot2?
27. How do you think the dealers have responded to the Program changes? What about the end-use
customers? Manufacturers and distributors? [Probe for sotisfoction with offerings ond
o d m i n i strativ e proced u re sl
Future Trends
28. What changes are you planning on for 2009? [Probe for both offerings ond odministrotive]
29. Are there any additional ideas or comments you have? Anything that I have not asked you about
but you would like to share about your experience with the Program?
HES Program lmplementer Discussion Guide Page 4
Roclry Mountain Power
Exhibit No. 5 Page 193 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
o reffiouNrArN
Exhibit No. 5.3
Energy FinAnswer Evaluation 2008
Roclry Mountain Power
Exhibit No. 5 Page 194 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
ffiY Y,HT
N R N $..-.$CAIfh/TL]S
ffisR{-} {"JS-'" NN{1"
PacifiGorp
Energy FinAnswer
2OO8 ldaho Program Evaluation
Prepared for
PacifiCorp
Prepared by
The Cadmus Group, lnc. / Energy Services
720 SW Washington Street, Suite 400
Portland, OR 97205
503-228-2992
November 12,2010
Rocky Mountain Power
Exhibit No.5 Page 195 of 1365
Case No. PAC-E-'I4-07
Wtness: Kathryn C. Hymas
Prepared by:
Brian Hedman
Randy Spitzer
Aquila Velonis
M. Sami Khawaja, Ph.D.
Vice President
The Cadmus Group, lnc.
tCorporrta Headquaners:
57 Water Street
Watenown, MA02472
Tel: 517.673^7W0
Fax 5t7.673.7001
An fu*ployee-Awned Compony
wr.t ro. -c*dmusilraiiF-{c!r1'l
720 SWVltushington 5t.
Suite400
Portland. OR 97205"lbl: 503.2?8.2992
Fax: 503.??8.3696
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 196 of 1365
Case No. PAC-E-14-07
nov$*iBlf{E: ld'itr"
Table of Contents
Executive Summary........... .................1
Conclusions 3
Recommendations 3
lntroduction ....... ...................5
Program Description ..................5
lmpact Evaluation............. ...................7
Methodology............. .................7
Energy Savings Calculation Method ...........7
Engineering Calculations 7
Realization Rate Analysis Method ...............8
Evaluation Approach .................8
Step 1: Categorization
Step 2: Methodology Selection
Step 3: Site Visits and Data Collection
Step 4: Analysis
Free-ridership
1.
2.
3.
8
8
8
8
4.
l0
t3
t4
t4
15
15
t6
t6
t6
l7
l8
Organizational DatalFirmographics
Participation
Enrollment
Efficiency Measures
Operational Changes
Installation
Spillover
Energy-Efficiency Decision Making
Interaction with Rocky Mountain or Third-Party Staff
Satisfaction
The Cadrnus Group, lnc. / Energy Services
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 197 of l365
Case No. PAC-E-14-07
N ov#niEi$ [el'Y: ! $''ttr'
Key Findings.............. ..............18
Recommendations...... ..............19
5. Gost-Effectiveness Analysis ....... ....21
6. Alternative Analysis ..........25
Appendix B. Nonparticipant Survey............ ....... 43
Appendix C. Staff lnterview Guide..... ................. 51
Appendix D. Market Actor lnterview Guide..... ... 55
Appendix E. Energy FinAnswer Process Flow Diagram ................ 58
Appendix F. Energy FinAnswer Evaluation Plan .............59
Appendix G. Project Reports.......... .....60
Appendix H. Measure Life Methodology ............61
Appendix l. Participant and Nonparticipant Survey Results ......... 62
Appendix J. Freeridership Analyses ... 63
The Cadrnus Group, lnc. i f;nergy $ervices
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 198 of 1365
Case No. PAC-E-14-07
NovJffib"$flB:!d'|tr'
TE,..Pr-qmam
y6lneg. i:i::::.:.,:,iii:i
1. Executive Summary
The Energy FinAnswer Program offers Idaho customers an opportunity to increase their energy
efficiency through the energy-efficient design, construction, and retrofitting of commercial and
industrial processes and buildings. Customers are eligible to participate if served under Rocky
Mountain Power's general service commercial and industrial rate schedules. The program applies
to equipment purchases and design decisions for existing facilities as well as new construction and
maj or renovation proj ects.
PacifiCorp offers this program throughout the five state service territories where it manages
demand-side management programs. Together these programs acquired more than 68,000 MWhs
of first year energy savings in 2008. Within the state of Idaho, this program was responsible for
1l% of the savings that the utility realizes from commercial and industrial effrciency prog.ams'.
Expected savings and other program-related data were obtained from Rocky Mountain Power's
tracking database. Expected savings were those calculated for each installed project, and
documented based on pre and post-installation conditions as determined by Rocky Mountain
Power and its energy engineering contractors. Rocky Mountain Power provides detailed
engineering studies that determine the savings potential for each project. Customers are
responsible for installation and commissioning to ensure energy savings are achieved. At the
completion of the project Rocky Mountain Power conducts a post-installation inspection to verifu
the achieved savings and project costs. The incentive paid is based on the savings and costs
documented in the post-installation inspection report. These values were then entered in Rocky
Mountain Power's database at the conclusion of each project.
Table 1 summarizes expected savings, evaluated savings, and the realization rate for participants
who completed projects in Idaho in 2008. Evaluated savings were savings for each installed
project, as documented in this evaluation.
Table 2 summarizes expected demand savings, evaluated demand savings, andrealization rates.
PacifiCorp manages demand-side management programs in five of its six state jurisdictions. Program in Oregon
are managed by the Energy Trust of Oregon.
The program did not pass the RIM test, as is typically the case for energy efficiency programs.
Low commercial energy and demand realization rates were due to one large participant closing operations after
measure installation. Section 6 of this report provides an alternative analysis excluding the facility that had
suspended operations
Table 1. Energy Savings and Realization Rates
The Cadmus Group, ln*. / Hnergy Serrices
Rocky Mountain Power
Exhibit No. 5 Page '199 of 1365
Case No. PAC-E-'I4-07
Pa*ifiC*rp rq ovJTi{Ei$[18: !d't$'
Table 2. Demand Savings and Realization Rates
To evaluate achieved energy savings, Cadmus performed site visits at three of the five customer
sites. We were unable to schedule a visit to the fourth site, and the fifth site was at a plant had
suspended its operation until 2011. Due to uncertainty regarding this site resuming operations,
Cadmus has taken a conservative approach and not credited the full savings from that project a.
Section 6 of this report provides an alternative analysis which shows the realization rates and
cost effectiveness results for the program excluding the facility in question. These verified
projects represented 73 percent ofexpected savings.
Cadmus calculated realizationrates for both energy and demand savings based on measurements
and observations obtained from the site visits, in addition to data in the project files and
conversations with facility staff. The pre-project engineering studies and the post-installation
commissioning reports included in the files provided detailed project implementation
information.
Table 3 shows energy savings realization rates by measure type. Realization rates were highest
for motor and refrigeration measures (100%)5.
Table 4 shows demand savings realizatronrates by measure type. Realizationrates were highest
for motor measures (100%).
Section 6 ofthis report provides an alternative analysis excluding the facility that had suspended operations.
Realization rates are typically reflective of how the equipment is used once its installed, when this is the case it is
outside of the program's control.
One customer's site suspended operations after installation of program measures. Thus, the verified energy
savings were reduced to reflect only the time the customer was in operation. This is consistent with methods
approved by the California Public Utilities Commission; http://www.calmac.org/publications/SClA_06-
08 Eval Final_Report.pdf
Table 3. Evaluated Enerry Savings by Measure Type
The Cadnru$ Group, [nc. I Hnergy $ervice$
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 200 of 1365
Case No. PAC-E-14-07
r.i o u##[i] f'lY: ! d'l ff '
Table 4. Evaluated Demand Savings by Measure Type
Cadmus determined free-ridership to be 25o/o fitrough self-reporting surveys. For this evaluation
free-ridership was the only factor used to calculate the Net-to-Gross ratio8. After applying the
Net-to-Gross ratio of 75 percent to the evaluated savings, the net progftrm savings were
200,420 kwh.
Program cost-effectiveness was analyzed using Idaho-specifi c assumptions.
Table 5. Cost-Effectiveness Summary for the Program in 2008 - IRP 650 LF Decrement
Conclusions
The Energy FinAnswer program as run in 2008 was cost-effective from the PTRC, TRC, UCT,
and PCT perspectives and operates well. Customers who have completed projects are satisfied
with the professionalism of all the staff and contractors they have dealt with. Recommendations
below reflect only minor enhancements to make the program even more effective.
Recommendations
o Continue to conduct training for contractors and architects; so they can better understand
the Energy FinAnswer progrzrm and encourage customers to undertake energy-efficiency
measures in a project's early stages.
o Encourage greater discussion and presentation on the financial benefits resulting from
undertaking effi ciency proj ects.
As noted, measures were specially categorized for the closed customer's site.
This method is consistent with the Model Energy Efficiency Program lmpact Evaluation Guide authored by the EPA
as part of the National Action Plan for Energy Efficiency.
Total Besource + Conservation Adder (PTRC)$0.074 $153,420 $170,795 $17,375 1.11
Total Resource No Adder (TRC)$0.074 $153,420 $155,268 $1,848 1.01
Utility (UCT)$0,058 $121,190 $155,268 $34,078 1.28
Ratepaver lmpact (RlM)$0.122 $254,461 $155,268 -$99,193 .61
Participant (PCT)$0.029 $59,946 $160,988 $101,042 2.69
Lifecycle Revenue lmpact ($/kWh)$ 0.000003022
Discounted Particioant Pavback (vears)2.74
The Cadrnu$ Group, lnc. I Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 201 of 1 365
Case No. PAC-E-14{7
IMtness: Kathryn C. Hymas
PacifiCorp
Rocky Mountain Pourer
Exhibit No. 5 Page 202 of 1365
Case No. PAC-E-14-07
nov#iiH$IeiY: !d{tr'
2. lntroduction
Program Description
The Energy FinAnswer program offers customers an opportunity to increase their operations'
electric energy effrciency through evaluation and implementation of Energy Effrciency Measures
(EEMs) for existing facilities and new construction. Prior to May l, 2008 the only program
Idaho customers had available to them was FinAnswer Express which was operated with a
funding cap'. Consequently some of the 2008 Energy FinAnswer participants may have initiated
their projects with the FinAnswer Express program and completed them in Energy FinAnswer
once that program became available. The program is available to commercial new construction
and industrial projects of any size, as well as commercial retrofit projects larger than 20,000
square feet per electric meter. All customers served under the company's general service
commercial and industrial rate schedules in Idaho are eligible, excluding special contracts. The
program is implemented by Rocky Mountain Power staffutilizing approved energy engineering
firms.
Customers who elect to participate in the program first receive an Energy Analysis (EA), paid for
by Rocky Mountain Power, to identify energy savings opportunities and potential costs and
incentives. The savings estimates for new construction projects, where energy code applies, uses
the state energy code as a baseline. For retrofit projects the baseline can be the existing
equipment, common practice or code depending on the nature of the project. This EA is
performed by one of several Rocky Mountain Power contracted engineering firms. The firms
under contract were all selected after responding to a Rocky Mountain Power issued request for
proposal and are evaluated on their performance annually to assure that their performance meets
Rocky Mountain Power's standards. Rocky Mountain Power also uses an engineering consultant
peer review process as a quality assurance/quality control method on the work performed in the
EAs. Before the EA findings are presented to the customer a second Rocky Mountain Power
contracted engineering firm reviews the report, the savings, and cost estimates. Quality control
review and comments are addressed before the report is delivered.
Customers are required to sign an incentive agreement, based on the estimated savings and
project costs contained within the EA, before they proceed with making any equipment
purchases. Once the implementation of the EEMs is complete, including any required
commissioning and the customer has provided Rocky Mountain Power with all the appropriate
documentation, Rocky Mountain Power will perform an on-site post-installation inspection.
Based on the results of the inspection the final incentive is calculated and paid to the customer.
To help ensure persistence of electric savings from measures receiving an incentive, Rocky
Mountain Power requires that the owner commission most mechanical measures prior to
receiving an incentive payment. If the customer chooses not to commission the project, when it's
required, they receive only a partial incentive. The company provides measure-specific
'The Energy FinAnswer program actually began in Idaho in the early 90's and included optional funding repaid on
the electric bill. It also offered energy engineering services similar to the 2008 program. This program ended
when the company transitioned from a loan based financial offering to cash incentives in 2006.
The Cadmus Group, lnc. / f;nergy $ervices
le-'ilicprp
Rocky Mountain Power
Exhibit No. 5 Page 203 of 1 365
Case No. PAC-E-14-07
novdYi{Eits8gild'|tr'
commissioning procedures in the energy analysis report to facilitate this work. The required
commissioning reports contain systematic functional performance testing plans, results, and
corrective actions taken (if any) to ensure persistence of energy savingsl0.
In 2008, basic program incentives for the program were calculated as the lesser of:
o First-year energy savings (kwh), multiplied by $0.12lkwh, plus average monthly on-
peak kW reduction multiplied by $50/kW; or
o Fifty-percent of the project costs.
Qualifuing measures' pre-incentive simple paybacks had to equal or be greater than one year.
For EEMs retrofitted in existing buildings, measure cost was the total, installed cost of the
measure. For new buildings, the measure cost was the installed cost, minus the cost of code
compliance or common-practice equipment. For calculating the incentive, lighting measure
savings were limited to no more than half of total savings of the project. The 2008 program had
five Idaho projects completed in two facility types with expected savings of 395,1 81 kwh.
Expected energy savings were largest for warehouse buildings.
Table 7 shows expected savings distribution by end use. Lighting measures represented the
greatest percentage of program savings, at 32%o of expected savings.
r0 For a process flow diagram ofthe program please see Appendix E ofthis report.
Table 6. Expected Program Savings by Facility Type
Table 7. Expected Savings by End Use
oThe Cadnrus Group, lnc. i EnerEy Services
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 204 of 1 365
Case No. PAC-E-1447
nouJ#EiEf{Y: !d{tr'
3. lmpact Evaluation
Methodology
Cadmus used engineering calculations to verify savings estimates for all 2008 projects.
Overall, energy analyses conducted for the evaluation were intended to verifu the reasonableness
of original analyses underlying the utility's savings estimates. Original savings estimates
contained within the EA were based on a thorough review of prior studies and/or site inspections.
The Rocky Mountain Power project files were very detailed and thorough, greatly facilitating
this evaluation.
The evaluation sought to confirm that the basic assumptions used in the analysis were correct,
the analysis method was appropriate, measures had been installed and operated as planned and
the customer's facility remained in use. Consequently, our analysis primarily focused on
verifying the original analyses and providing revised energy and demand savings estimates
where operational changes were identified.
As described below, several steps were conducted in the energy analysis verification process.
Energy Savings Calculation Method
We applied the basic level of rigor in conducting our analyses as specified in the Califomia
Public Utilities Commission's Protocols published in 2006rr and IPMVP option A. Analysis of
projects began with a complete review of project files, which included one or more reports at
various project stages, presenting energy savings, costs, and incentive calculations and estimates.
Evaluated energy (or demand) savings were calculated by taking evaluated post-consumption
less estimated pre-consumption.
Engineering Calcu lations
We reviewed the original engineering analysis, and determined whether our site visits or phone
calls identified any changes in assumptions used in the original analysis. We also contacted the
utility program manager and energy engineer, as needed, to resolve any issues, changes, or
discrepancies that might affect estimated energy savings. If necessary, we adjusted original
savings estimates using the same basic methodology, various engineering algorithms were used
to estimate savings, based on specific measures.
As variations can occur in calculated savings due to particular engineering methods and
assumptions used, our savings calculation methods, for the most part, duplicated the engineering
method used when savings were first derived. Observation of operational characteristics became
a critical element in estimating actual savings. We used our observations of key assumptions,
validation of engineering methods, and recalculations based on observed differences to provide
evaluated savings estimates.
" http://**w.calmac.org/events,/EvaluatorsProtocols Final_AdoptedviaRuling_06- l9-2006.pdf
The Cadnrus Group, lnc. i Energy Services
Pqcl!!c9ry
Rocky Mountiain Power
Exhibit No.5 Page 205 of 1365
Case No. PAC-E-14-07
ruov#iiEiil[''{B: !#{ffi'
Realization Rate Analysis Method
For each EEM in the projects, we calculated energy and demand savings rcalizationrates as the
ratio of evaluated savings to expected savings. The energy realization rate was calculated as a
percentage, using evaluated energy savings from our calculation and the utility's expected
energy savings. The demandrealization rate was calculated similarly.
As discussed, evaluated energy and demand savings from a project reflected any changes
observed in the assumptions used in the original analyses. The realization rate accounted for
these changes in estimating evaluated savings, but the rate was always calculated relative to the
utility's expected savings estimate, without any adjustments.
Evaluation Approach
Step 1: Categorization
While there were more projects in various stages of completion, there were five completed
projects in 2008. Cadmus selected all of these for site visits. We were unable to access two sites,
one of which was at a facility now shut down; at the other site, it was not possible to schedule a
time acceptable to the customer. Consequently we visited three sites and performed a telephone
interview with the fourth. The closed site was not visited.
Step 2: Methodology Selection
Cadmus analyzed all projects using engineering calculation methods described above.
Step 3: Site Visits and Data Collection
Analyses for all projects required site visits to: verifu equipment installation and operations;
obtain data needed to perform calculations; and meet with building maintenance staff. Site visits
were completed in January 2010. Site visit information and summaries of our analyses are
provided in Appendix G.
Step 4: Analysis
Energy savings for four projects were determined using engineering calculations that
incorporated measurements and observations obtained from the site visits, in addition to data
provided in the project files and from interviews. The fifth project was given arealization rate of
5%oto reflect the period that the plant was in operation before closing.
Overall, the program achieved a68o/o energy savings realization rate, as seen in Table 8, which
shows savings by facility type. The overall rate was brought down by the closed facility; an
alternative analysis is presented in section 6.
The Cadmus Group, lnc. / Energy $ervices
Rocky Mountain Power
Exhibit No. 5 Page 206 of 1365
Case No, PAC-E-14-07
fleqilicqp-r.r ov#*iEi$ ["{Y: ! d'|tr'
Table 8. Evaluated Enerry Savings by Facility Type
Table 9. Evaluated Energy Savings by Measure Type
Table 9 presents energy savings andrealization rates by measure type.
Table l0 shows demand savings realizationrates by measure type.
Net-to-Gross
Net savings are the savings "net" of what vl'ould have occurred in the absence of the program.tT
Net-to-gross (NTG) consists of free-ridership and spillover. For this evaluation, we only
quantified free-ridership. Spillover is noted separately in Section 4 but not quantified due to the
t7
Low commercial energy and demand realization rates were due to a large participant suspending operations
after measure installation.
As noted, one customer's site closed after measure installation. Verified energy savings were reduced to reflect
the period that the plant was in operation, with the measure installed. This is consistent with methods approved
by the California Public Utilities Commission; http://www.calmac.orglpublications/SCIA_06-
0 8_Eval_Final_Repot.pdf
As noted, one customer's site closed after measure installation. Verified energy savings were reduced to reflect
the period that the plant was in operation, with the measure installed. This is consistent with methods approved
by the California Public Utilities Commission; http:i/www.calmac.orglpublications/SClA_06-
0 8_Eval_F inalReport.pdf
Model Energy Efficiency Program lmpact Evaluation Guide authored by the EPA as part of the National Action Plan
for Energy Efficiency.
t2
l3
t4
g
Table 10. Demand Savings Realization Rates by Measure Type
The Cadrnus Group, lnc. i Energy Services
FacifiCorp
Roclry Mountain Power
Exhibit No, 5 Page 207 of 1365
Case No. PAC-E-14-07
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level of complexity involved in determining the potential savings associated with Spillover for
commercial measures.
Free-ridership
Free-ridership represents the percentage of program participants who rryould have implemented
the program nleasure or practice in the absence of the program. This was quantified through
fielding telephone surveys with program participants who completed projects. While asking
participants to self-report for calculating free ridership is a standard approach, it should be noted
this methodology has some limitations in that it does not account for longer-term market trends
among contractors and supply houses, which typically occur with multiyear programs. For
example, a multiyear program may alter stocking practices at suppliers or even the market share
of higher-efficiency products available in a region. Consequently, the customer, choosing
between various makes and models of a given product, may not be aware available choices were
altered by a program. Therefore, while the customer may correctly state a choice was offered
between two efficient products, the choices available may have resulted from a program. In this
case, while the customer would count as a freerider, had the program not been running, a less-
efficient option may have been available to the customer-an option they may have otherwise
chosen.
Accuracy of self-report surveys partly depends on the respondent's memory of their decisions.
For the Energy FinAnswer program, some interviewees were asked to recall actions taken over a
year before. Participant candor may also be a factor, as respondents may tend to seek a oohalo"
effect, where the customer indicates they would have made the energy-efficient choice because
they perceive it as the response preferred by the interviewer.
In calculating free-ridership, Cadmus surveyed three program participants who completed
projects over the 2008 program year. Free-ridership analysis results are presented in Table 1 1,
along with evaluated savings numbers from Table 9 and Table 10. These savings include all
measures (not just measures for which respondents were surveyed). The free-ridership value was
applied across all measures to arrive at net savings15.
As a result of the program funding cap experienced in 2007, the addition of the Energy
FinAnswer program in 2008, removal of the funding caps and the subsequent management of the
t5 For a fuIl description of the scoring matrix refer to Appendix J
Table 11. Free-ridership Analysis
The Cadnru$ Grsup, ln*.1Hnergy Seruices 10
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 208 of 1 365
Case No. PAC-E-14-07
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remaining customers on the waiting list, there may have been some customer confusion
regarding the two progrrms and the funding available which may be reflected in the participant
surveys and interpreted as free-ridership.
The Cadrnus Group, lnc. I Energy Services 11
Rocky Mountain Pover
Exhibit No. 5 Page 209 of 1365
Case No. PAGE-1447
Whess: l(drryn C. Hymas
l-q--.ific--qry
Roclry Mountain Power
Exhibit No. 5 Page 210 of 1365
Case No. PAC-E-14-07
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4. Process Evaluation
Process Evaluation Overview
With customer, implementer, and company perspectives in mind, the evaluation determined what
program elements worked well and which could be improved, and, based on these results,
developed modifications to refine the program. This evaluation phase relied on interviews with
utility and program staff as well as on surveys of program participants who completed projects,
nonparticipants, energy engineers, and trade allies. Interview and survey activities also informed
evaluation of spillover and free-ridership impacts.
In total, 10 interviews and surveys were conducted for the process evaluation, as shown in
Table 12.
Table 12. Roctry Mountain Power FY 2010 Process Evaluation Samples
Process Evaluation
Organ izational Data/Firmog raphics
In the 2008 program year, the Idaho Energy FinAnswer program had five participants with
completed projects. Three of them were dairies, one was a refrigerated warehouse, and the other
was a chemical plant. The evaluators attempted to conduct a census of these participants, and
were able to interview contacts at the refrigerated warehouse and two dairies. Evaluators were
not able to interview anyone at the chemical plant because the plant closed down in the fall of
2009. The two dairies interviewed were small operations, with three to four employees. Under
the program, all three dairies purchased variable frequency drives and controls for milk
extraction vacuum pumps. The two dairies also installed milk-transfer pump variable frequency
drives (VFDs) and controls, and one dairy installed two well water plate coolers used to pre-cool
milk.
The refrigerated warehouse was a larger operation, with approximately 40 employees. Under the
program, the warehouse completed a lighting retrofit and installed two floating head pressure
controls. All three respondents indicated their electric bills were the largest utility contributors to
their annual operating costs. All three responded their electric bills represented l0o/o or less of
their total annual operating costs.
A total of eight eligible customers not participating in the Idaho Energy FinAnswer program
were identified and selected for interviews. We completed surveys with four of these
nonparticipants.
Those responding were diverse. One was a public school district, while the other three were
private companies providing real estate, professional, or retail services. The school district had
The Cadnrus Group. lnc. i Energy Services 13
Rocky Mountain Power
Exhibit No. 5 Page 21 1 of 1 365
Case No. PAC-E-14-07
PacifiCorp
more than 100 employees; the real estate firm had 40 employees, and the other two companies
had one employee each. Although none of the respondents were able to provide specific
estimates, all stated their energy costs made up a significant portion of their total annual
operating costs.
Participation
During this time period, company staff noted that the program was actively marketed, both to
customers and contractors. Customers were reached through contacts with Rocky Mountain
Power account management staff and/or trade allies, the Rocky Mountain Power Web site and
the quarterly Energy Insights newsletter. Additional promotion occurred through print and radio
advertisements and energy engineers were encouraged to find additional opportunities at sites
they visited.
All three participants who were interviewed leamed of the Energy FinAnswer program through
business associhtes. The two dairies leamed of the program through equipment installers or
suppliers. The refrigerated warehouse respondent learned of the Energy FinAnswer program
from a business colleague. All three respondents said they participated in the program to save
money on their utility bills. One dairy also indicated they participated to obtain the program
incentive, and because it was beneficial for the dairy as equipment installed through the program
provided more cooling for milk. The respondent added the new motors ran slower, resulting in
lower energy use and a longer useful life for the motors.
There were no progftlm aspects that initially caused respondents concern. One respondent
mentioned there was a learning curve to understanding what would be funded under the program.
Three program nonparticipants had never heard of the progftIm and were not aware incentives
were available to nonresidential customers. None of the customers participated in the Energy
FinAnswer program before 2006 or after 2008.
One nonparticipating customer, the school district, had heard of the Energy FinAnswer program
through a local contractor.
Enrollment
As part of a new strategy implemented concurrently with the evaluation period, account
managers were assigned a single project manager to work with their assigned customers' Energy
FinAnswer projects. For this program, the energy engineer assigned to a project made an initial
site visit and review to obtain additional detail on projects under consideration. The project
manager considered this visit as "program neutral" in that the energy engineer was tasked with
finding energy-saving opporrunities eligible through Energy FinAnswer or other Rocky
Mountain Power programs.
The initial no-cost site visit and review was a way to address customers' cost barriers. The
energy engineer interviewed felt the no-cost site visit and follow-on consulting services were
very influential. Many prospective participants were not familiar with the services or their value,
and would be unwilling to pay for consulting services on their own. The initial visit and review
also served to determine whether customers were interested in participating and whether they
would have sufficient funds to implement their projects.
nov#niEi$f'19:2d'{tr"
The Cadrirus Group, lnc. / Hnergy $ervices 14
Rocky Mountain Power
Exhibit No. 5 Page 212 of 1 365
Case No. PAC-E-14{7
PacifiCorp
No respondents encountered any problems, delays, or difficulties during the program application,
review, or approval processes. One respondent added all parties he encountered were polite and
professional. None of the businesses had participated in the Energy FinAnswer program before
or after 2008. One dairy had participated in an irrigation pump load-shedding program sponsored
by Rocky Mountain Power, and felt that program's application process was about the same as the
Energy FinAnswer' s application process.
Efficiency Measures
Two respondents indicated they did not install some items recommended through the program.
One respondent did not install some recommended lighting measures because the lights and
fixtures he wanted were not available through the program. Another respondent declined to
install some light switch controls in some high-traffic office areas because he did not think they
would pay offin those particular areas.
All measures installed through the program replaced existing equipment that was old, but in
working condition and experiencing no problems. One participant replaced working equipment
as part of a facility remodel/expansion. AII respondents rated their satisfaction with the new
equipment highly.
One nonparticipant installed lighting and controls through the Energy FinAnswer program in
2009 and was very satisfied with the new equipment. Other than the lighting retrofit project, the
respondent had not taken any other actions to save energy, but was considering upgrading to
high-efficiency lighting in additional buildings. Only one other nonparticipant had installed any
energy-efhciency measures, having installed insulation and a high-efficiency water heater over
that last several years without a financial incentive or tax credit. However, none of these energy-
efficiency improvements had been made in 2008.
Operational Changes
At the time respondents participated in the program, only one had an overall plan to increase
operational energy eff,rciency. Two respondents indicated they changed the manner that they
operated equipment after installing new measures, and these changes were part of an overall plan
to increase their operations' energy efficiency. The refrigerated warehouse representative stated
they had installed automatic sensors in their office rooms; so lights would not remain on when no
occupants were in the room. One dairy mentioned they had changed operating hours or operation
schedules since installing the new measures as their newly remodeled barn was larger, resulting
in fewer milking hours; therefore, the pumps ran less.
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Table 13. Equipment Satisfaction
The Cadnrus Group, lnc. / Energy $ervices 15
PacifiCorp
Roclry Mountiain Power
Exhibit No. 5 Page 2 13 of '1 365
Case No. PAC-E-14-07
ruov#ilEi$I1'fl:!d{tr'
lnstallation
No measures at the dairies had been removed since installation through the program. In the
refrigerated warehouse, two defective ballasts had to be replaced. This occurred within two
months of installation. The respondent indicated no more equipment had required replacement.
Only one respondent- the one completing a barn remodel-indicated equipment installed
through the program had been scheduled for replacement or upgrade before the program. Both
dairies indicated equipment installed through the program was included in their most recent
capital budgets.
All respondents expected to save money on their electric bills and all respondents felt the electric
savings met their expectations.
Two respondents did not anticipate additional benefits from installation of new equipment, other
than energy savings; however, one dairy farmer anticipated the life of his new pumps would be
greater.
The two dairies highly rated their satisfaction with the cost of measures installed under the
program, with scores of 8 and 9. The warehouse rated satisfaction somewhat lower,witha7,
because the cost of measures installed proved slightly higher than expected.
Company staff and the trade allies interviewed noted that the progftrm had a strong quality
control element leading to high-quality project plans and installations. Contributing to this is the
peer review process in which the energy analysis reports prepared by the assigned energy
engineers were peer reviewed by firms with similar capabilities.
Company staff also felt that the energy analysis report peer review resulted in competing firms
sharing project knowledge and approaches. The program and customers benefitted from
increased sharing of program knowledge.
Spillover
Spillover is defined as the amount of additional savings generated by program participants, but
not captured by program records. We used the same participant survey instrument to qualify
spillover, which results when customers purchase energy-efficient measures or adopt energy-
efficient practices because of a program, yet choose not to participate in the program or are
otherwise unable to participate. The nature of that behavior makes it difficult to actually quantify
the savings from each action or measure.
Since participating in the program, two of the respondents have installed other energy efficiency
measures without any assistance from a utility or other organization. The measures installed by
the respondents were timers for outdoor lighting and a new well pump. Regarding the influence
of the program on their decisions to install additional energy efficiency measures on their own,
only one of the two gave a response above a 5.
Energy-Efficiency Decision Making
The respondents rated energy efficiency's importance to operations and management of their
company, with numbers ranging from 7 to 9. When asked for reasons supporting their ratings,
two respondents who rated energy efficiency the lowest (7 and 8) stressed there was only so
much money to go around, and there were other efficiencies to consider, such as time and labor.
The Cadnrus Group, lnc. i Energy Services 1n
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 214 of 1365
Case No. PAC-E-14-07
r'rov#nilisf{g: !#{ff'
One respondent mentioned employee comfort was also an important consideration, and another
stated, although energy effrciency was important, it was not their highest priority. The
respondent (a dairy) who rated energy efficiency's importance the highest (8 to 9) noted that
because the price of milk was so low, their business was struggling to meet budgets; therefore,
every dollar they saved was important. In fact, if the program were offered today, they would not
be able to use it because they could not afford to spend money on anything not absolutely
necessary.
When asked if their business had sufficient in-house technical resources to address energy and
water cost management, both dairies said no, but that Rocky Mountain Power and Nexant were
able to provide the required assistance. The refrigerated warehouse felt they had sufficient in-
house technical resources to address energy and water cost management on their own.
Three of four nonparticipant survey respondents rated energy efficiency's importance to
company operations and management as an 8. When asked about their rating, the three
respondents gave similar responses. While they indicated energy efficiency and cost savings
were important, they felt they were not their highest priorities. A real estate firm indicated it was
typically not cost-effective to install energy-efficient measures in its investment properties since
the tenants typically pay their own electric bill. Another respondent indicated energy-efficient
equipment was often more expensive and could require a greater effort to find, install, and
operate than conventional equipment.
The respondent giving the importance of energy effrciency the highest rating (a 9) indicated
anything that could be done to save energy costs was very important since it was such a large
expenditure for that customer. This respondent was the only nonparticipant that had made
energy-efficiency improvements in the last few years without assistance from a utility or other
organization. Three of four respondents indicated they had sufficient technical resources in house
to address energy and water cost management.
Trade allies we spoke with felt if you could show customers energy management efforts
improved bottom lines, they would more likely invest in the Energy FinAnswer program.
Customers were generally motivated by incentives to undertake energy-efficiency upgrades
following the audit, particularly when, shortly after the audit, they received a significant
incentive. However, some trade allies stated incentives offered by Rocky Mountain Power were
slightly low, preventing customers from investing in improvements. Moreover, the price of
electricity has been low in Idaho, reducing the impetus to make energy-efficiency upgrades. One
trade ally noted they had conducted quite a few audits, but not many of their prospective
customers followed through on energy efficiency measures, probably due to low-cost electricity
and long payback periods. Another respondent stated more customers would invest in energy
management if Rocky Mountain Power developed a stronger message (e.g., convincing
customers that investing in energy efficiency now would reduce their costs over the long-term).
lnteraction wath Rocky Mountain or Third-Party Staff
All three Idaho Energy FinAnswer respondents reported they worked with three to four program
staff members. All three remembered working with the project manager, and two said they
worked with their Rocky Mountain Power account representative. Other staff members
mentioned were: Nexant project managers, engineers, auditors, external consultants, and
suppliers. All three described their experiences working with program staff members in the most
The Cadmus Group, lnc. I Energy Services 17
PacitiCorp
Roclry Mountain Power
Exhibit No. 5 Page 215 of 1365
Case No. PAC-E-14-07
N ov#ilEi$ r*el'fl : i #|tr'
positive terms. One respondent said program the staffwere: "Very professional. They answered
my questions, had all documents prepared, and did their job...." Another stated program staff
were'lery helpful and I am very pleased." The last respondent simply that stated program staff
'owere all great."
Only one nonparticipant had contact with Rocky Mountain Power or other program staff. The
respondent had a positive experience working with Rocky Mountain Power account
representatives and the installation contractor to complete a2009lighting retrofit project. The
respondent would not change anything about the program.
All trade allies said Rocky Mountain Power was easy to work with on the Energy FinAnswer
program, especially as they were familiar with them from other energy-management programs.
They also noted Rocky Mountain Power staff were effective project managers, and helped
facilitate the program's progress. One trade ally strongly encouraged Rocky Mountain Power to
conduct additional workshops and training for contractors and architects; so they could learn
more about the program and broaden its implementationl6. Training could also encourage
contractors and architects to become involved in the Energy FinAnswer program earlier, rather
than making later change orders, which could be expensive and time consuming.
Satisfaction
When asked whether they would participate in the program again, all respondents said yes. One
respondent qualified his yes with "if I had the money." When asked for suggestions for
improving the program, all three requested a bigger incentive. All three respondents also rated
their overall satisfaction with the program as a 9. One respondent explained his rating by adding:
"The equipment is working; it saves me money every month, and is doing what I hoped it
would."
In general, most trade allies stated the Energy FinAnswer program, similarly with the FinAnswer
Express program, was effective in leading customers to make energy management changes.
Trade allies also noted the incentives worked to involve customers. However, they noted the
incentives were slightly low-in fact, lower than other utilities they were familiar with-and
payback periods for customers were too long , potentially lasting five to seven years. Another
trade ally said the energy audit results took too long to reach the customer; though Rocky
Mountain Power improved its turnaround time on audits, they still sometimes lagged behind
other utilities.
Key Findings
The program had five Idaho participants who completed projects in 2008, overall satisfaction
was high among the three respondents interviewed, all of whom indicated their level of
satisfaction was a 9 out of a possible 10, with l0 being 'extremely satisfied'. Program staff were
very highly regarded and appreciated for their assistance and professionalism. Notably, none of
the three interviewees first heard about the program through contact with a program
representative; all had learned about it through business associates. Since this is inconsistent with
our understanding of how the program is marketed, it maybe that these customers were originally
16 Currently, the Company offers annual training sessions.
The Cadrnus Group, lnc. I Hnergy Services 4{tIU
PeiilrQg$
Rocky Mountain Power
Exhibit No. 5 Page 216 of 1 365
Case No. PAC-E-14-07
r'r ov J*iEi8 flEl 2 d )ttr'
going through the FinAnswer Express program until their options had expanded. Although all
three interviewees indicated they would participate in the program again, the economy and its
impact on their businesses' bottom lines definitely tempered their decisions at this time. In
addition, all three respondents indicated that although energy efficiency was important to them, it
was one of many competing priorities under consideration in their business.
Three of the four nonparticipants interviewed had never heard of the Energy FinAnswer
program. Even though they stated energy efficiency was important to them, none of these
respondents installed any energy-efficient measures in the year before the interviews. The one
respondent who indicated that they were in fact aware of the progrErm learned about it through a
contractor. This fact helps to support the continued outreach and support oftrade allies as a
means of increasing participation. Once aware, the respondent decided to participate in the
program in 2009. That respondent had a positive experience with the progfirm and program staff.
Quality control on the audit reports appears to be working very well, resulting in competing
energy engineering firms sharing project knowledge and approaches. This has improved report
quality, and the progftrm has benefitted by the increased communication of best practice
information.
The current project tracking system does not readily track disposition of various projects,
including projects moving to other programs. This has created a minor level of uncertainty in
maintaining a complete picture of program status and influence.
Trade allies seemed well educated about Rocky Mountain Power's various offerings. They noted
key areas reducing customer involvement have been perceived longer paybacks and low
electricity costs.
Recommendations
Continue to conduct training for contractors and architects; so they can better understand
the Energy FinAnswer program and encourage customers to undertake energy-efficiency
measures in a project's early stages.
Encourage greater discussion and presentation on the financial benefits resulting from
undertaking effi ciency proj ects.
If Rocky Mountain Power chooses to evaluate the program in the future it is
recommended that the partial participants, who did not complete a project in the
evaluation year, as well as those customers who started but elected not to complete their
project be surveyed.
The Cadnrus Group, lnc. i Energy Services 1S
Rocky Mountain power
Exhibit No. 5 page 21 7 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
H
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 218 of 1365
Case No. PAC-E-14-07
r.r ov#dl[i8 r^18: ! d'|tr'
5. Gost-EffectivenessAnalysis
To assess cost-effectiveness, evaluators conducted an analysis ofprogram costs and benefits
from five perspectives, using Cadmus' DSM Portfolio Pro model. These perspectives include:
(l) PacifiCorp Total Resource Cost Test (PTRC): This test examined program benefits and
costs from Rocky Mountain Power's and Rocky Mountain Power customers' perspectives,
combined. On the benefit side, it includes avoided energy costs, capacity costs, and line
losses plus a l0% adder to reflect non-quantified benefits. On the cost side, it includes costs
incurred by both the utility and participants.
(2) Total Resource Cost Test (TRC): This test examined program benefits and costs from
Rocky Mountain Power's and Rocky Mountain Power customers' perspectives, combined.
On the benefit side, it included avoided energy costs, capacity costs, and line losses. On the
cost side, it included costs incurred by both the utility and participants.
(3) Utility Cost Test (UCT): From Rocky Mountain Power's perspective, benefits were through
avoided energy and capacity costs and line losses. Costs included any program
administration, implementation or incentive costs associated with funding the program.
(4) Ratepayer Impact (RIM): All ratepayers (participants and nonparticipants) may experience
increases in rates to recover lost revenues. This test included all Rocky Mountain Power
program costs as well as lost revenues. As benefits, this test included all avoided energy
costs, capacity costs, and line losses.
(5) Participant Cost Test (PCT): From this perspective, progftrm benefits included bill
reductions. Costs included any customer contribution to the measure cost.
Table 14 summarizes various components of the five tests.
Table 14. Benefits and Costs Included in Various Tests
Table 15 provides selected inputs to the cost analysis. These include the evaluated energy
savings for 2008 (from Table 8 above), discount rate, line loss, and program costs. Other than the
energy savings, these values are provided by Rocky Mountain Power. The discount rate is from
Rocky Mountain Power's 2008 Integrated Resource Plan. Rocky Mountain Power also provided
the values for line loss and the program costs.
Present Value of Avoided Energy and Capacity Costs with
10% Adder for Non-ouantified Benefits
Program Administrative and Marketing Cost +
Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost +
Participant Cost
Present Value of Avoided Energy and Capacity Costs Program Administrative, Marketing and lncentive
Cost
Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost +
Present Value of Lost Revenues
Present Value of Bill
The Cadrnus Group, Inc. I Hnergy Services 21
Roclq Mountain Power
Exhibit No. 5 Page 21 9 of 1 365
Case No. PAC-E-14-07
PacifiCorp nov#illi$r^18: !#{tr'
Table 15. Selected Cost-Effectiveness Analysis Inputs
Program benefits are comprised of energy savings and their associated avoided costs. The energy
savings used in the cost-effectiveness analysis are the evaluated kWh savings from this study.
Benefits are accrued over the expected useful life of the installed measure. Measure lives are
shown in Table 16.
Table 16. Measure Life SummaryrT
Table 17 presents the results of the cost-effectiveness analysis for the Program in 2008. All
analyses are based on the Rocky Mountain Power 2008 IRP 65% Eastside Decrementl8.
'' Measures lives were calculated based on information from California's DEER database, the New England State
Program Working Group report for the ISO Forward Capacity Market, and ACEEE's report on updating Energy
Efficiency Standards. The average is achieved by weighting the savings associated with each of the measure
types. See Appendix H for a detailed explanation.
'8 IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan Volume II
Appendices:
http:i,irvrvrv.rracifiur-rrp.comr'i;ontentidam,?acifiiJorpidociEnvirorurrentlEnv ironlrrental*Concems,/Integrated:I{eso
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The Cadnru$ Group, lnc. I EnerEy $ervices 22
lg-"illq-gp
Rocky Mountain Power
Exhibit No. 5 Page 220 of 1365
Case No. PAC-E-14-07
_ r,r-o.,,#rii$Af1{!dl$:
Table 17. Cost-Effectiveness Summary for the Program in 2008 - IRP 65ohLF Decrement
Total Resource + Conservation Adder (PTRC)$0.074 $153,420 $170,795 $17,375 1.1 1
Total Resource No Adder fiRC)$0.074 $153,420 $155,268 $1,848 1.01
Utility (UCT)$0.058 $121,190 $155,268 $34,078 1.28
Ralepayer lmpact (RlM)$0.122 $254,461 $1ss,268 -$99,1 93 0.61
Participant (PCT)$0.029 $59,946 $160,988 $101,042 2.69
Lifecvcle Revenue lmoact ($/k!\th)$ 0.000003022
Discounted Particioant Pavback (vears)2.74
The Cadrnus Group, lnc. / Energy Services 23
Rocky Mountain Pil,er
Exhibit No. 5 Page 221 of 1365
Case No. PAC-E-1.1-07
Wtness: Kathryn C. Hymas
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page222 ol 1365
Case No. PAC-E-14-07
ruov$rilEitsf{B:2d'ttr"
6. Alternative Analysis
During an evaluation period in which there are a small number of completed projects, the overall
results can be significantly influenced if even one of those projects differs from its original
assumptions, as was the case with Project 6588.
Project 6588 involved a calciner at an industrial facility which had suspended operations
subsequent to the customer's participation in the program. Because the facility was no longer in
operation the verified energy savings were significantly reduced to reflect only the time that the
customer's facility was in operation with the rebated measure installed. The fact that the facility
had suspended operations was clearly outside of the program's control, as a result we reran the
cost effectiveness andrealization rate analysis for the Idaho Energy FinAnswer program
excluding project 6588 to provide another perspective. For this scenario we removed the energy
savings, incentive costs, and measure costs for the project. Table l8 shows the results of the
revised cost efflectiveness analysis. Table l9 shows the results of the revised realization rate
analysis.
Table 18. Alternative Cost-Effectiveness Summary for 2008 - IRP 65"/oLF Decrement
Total Resource + Conservation Adder
(PTRC)$0.073 $148,341 $167,485 $19,145 1.13
Total Resource No Adder ffRC)$0.073 $148,341 $152,259 $3,919 1.03
Utility (UCT)$0.059 $1 19,633 $152,259 $32,627 1.27
Ratepayer lmpact (RlM)$0.123 $250,718 $152,259 -$98,4s9 .61
Participant (PCT)$0.027 $s4,867 $157,244 $102,377 2.87
Lifecycle Revenue lmpact (dollars)$0.000002999
Discounted Particioant Pavback (vears)2.46
Table 19. Alternative Evaluated Enerry Savings by Measure Type
The Cadnrus Group, lnc. I Hnergy Services 25
Roclq Mountain Pou,er
Exhibit No. 5 Page 223 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 224 of 1 365
Case No. PAC-E-14-07
r.r ov$ni[iE f'l?: [ #ttr'
Appendix A. Participant Survey
PacifiCorp FinAnswer Participant Interview Guide
For Completed Projects
Telephone:
Cell phone:
Title:
City:
Measure with the greatest savings, and amount of savings (from column U):
@efer to this measure in the 'Installed Efficiency Measures' section.)
Hello, my rurme from The Cadmus Group, calling on behalf of:
[WAH OR IDAHOJ Rocky Mountain Power
IWAS HINGTONJ Pacifi c Power
[PACIFIC POWER/ROCKY MOUNTAIN POWER] is evaluating its FinAnswer program and
would appreciate your input. "It is important for [PACIFIC POWER/ROCKY MOUNTAIN
POWERI to include your opinions in this study so they can serve your needs better."
[NOTE: If the customer has received a FinAnswer site visit, state: 'This is a brief
follow up to the site visit you recently received.']
[NOTE: If the customer has been selected for a FinAnswer site visit but the visit has not yet
happened, state: 'We are conducting this survey to prepare for an upcoming site visit to see your
FinAnswer project. We perform site visits to get a better understanding of the energy savings you
are actually getting from the program.]
This survey is for research purposes only and this is not a marketing call. Your
responses will remain confidential. This survey will take approximately 20 minutes.
As a Thank Youfor your assistance, at the end of the suryey you we would like to
offir you a $50 gtft card, whichwill be mailed to you. Do you have a moment to
answer questions about your experience with the program?
[If a customer asks if this is the Total Quality Service survey, or states that he has recently
participated in the Total Quality Service survey, say 'this is a separate survey about your
participation and satisfaction with the FinAnswer program.']
The Cadnru$ Group, lnc. / Energy $ervices 27
P-gpilicq$-
Rocky Mountain Power
Exhibit No. 5 Page 225 of 1 365
Case No, PAC-E-14-07
r.r ov#llEi$ [elB: [ #{ff '
[If 'No -Not a convenient time," ask if Respondent would like to 1. Start now and do part of the
survey, or 2. Arrange a more convenient time we can call them at home. Emphasize that]
[If customer wants to verifu the validity of the survey, tell them that they are welcome to contact
Nancy Goddard, PacifiCorp Program Manager, at [phone].
IIF "NO" - ARRANGE CALLBACKJ
o Confirmation
1. The [PACIFIC POWER/ROCKY MOUNTAIN POWER] records show that you participated
in the FinAnswer program during [Month] of [Year], and installed (a) IMEASURE(S)J at
IADDRESS OF INSTALLATIONJ
Is that correct?
1. Yes IIF YES - GO TO QUESTION 4.J
2. No, measure is/are incorrect
3. No, date is incorrect (SKIP fO 3)
98 DK (TERMTNATE)
[IF QL: NO, MEASURE IS/ARE INCORRECT, ASKJ What measures were installed?
IRECORD RESPONSEJ
3. [tF QL: NO, DATE IS INCOfuRECT, ASKJ About when were the measures installed?
1. MONTH YEAR
98. DK (DO NOT TERMINATE)
99. REF (TERMTNATE)
4. Which of the following best describes your company's primary activities?1. Manufacturing
2. Retail
3. Dairy / Agricultural
4. Finance and Insurance
5. Food Processing
a
a
The Cadnrus Group, ln*. I Energy Services l,$
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 226 of 1365
Case No. PAC-E-14-07
ruov#dtli$fty: ld)ltr'
6. RefrigeratedWarehouse
7. Professional, Scientific, and Technical Services
8. EducationalServices
9. Health Care
10. Public Administration
1 1. Arts, Entertainment, and Recreation
12. Accommodation
13. Food Services
14. Real Estate
15. Other [SPECIFY]
Participation
5. How did you learn about the Energy FinAnswer Program?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
1. Contacted by my IPACIFIC POWER/ROCKY MOUNTAIN POWER] account
representative or other [PACIFIC POWER/ROCKY MOUNTAIN POWER] staff.
2. Contacted by program representative [IF YES ASK'Do you remember what
company they were from.']
3. Program sponsored conference or workshop
4. Program sponsoredtechnology demonstration
5. Program sponsored integrated audit
6. Trade Publication
7. Marketing by Trade Ally, vendor or contactor
8. Firm approached/contacted by Trade Ally, vendor or contractor
9. Word of mouth; from another business colleague
1 0. Through a trade organization or professional or garization/association
11. Through printed material or outreach materials sent by the Program
12. At a trade show
13. Through family, friend, or neighbor
14. Participation in other [PACIFIC POWER/ROCKY MOUNTAIN POWER] Programs
15. Past Program participants
16. Internet research./found Program on the IPACIFIC POWER/ROCKY MOUNTAIN
POWERI website
17. Other [SPECIFY]
98. Don't know
99. Refused
29The Cadrnu$ Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No, 5 Page 227 ol 1365
Case No. PAC-E-'14-07
Nev#ri$fiylldltr:
6. Why did you decide to participate in the Program?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
1. To save money on utility bills; save money on electric bills
2. To obtain a progftrm incentive
3. To replace old equipment
4. To replace broken equipment
5. To acquire the latest technology
6. To reduce maintenance costs
7. Because the Program was sponsored by IPACIFIC POWER/ROCKY MOLTNTAIN
POWERI
8. Previous experience with other [PACIFIC POWER/ROCKY MOUNTAIN POWER]
Programs
9. To help protect the environment
10. To save energy
11. Recommended by Program contact
12. Recommended by contractors/trade allies
13. Recommended by another IPACIFIC POWER/ROCKY MOUNTAIN POWER]
customer; word of mouth
14. Recommended by family, friend, or neighbor
15. Part of a broader remodeling or renovation
16. Other [SPECIFY]
98. Don't know
99. Refused
PacifiCorp
7b. Was this issue resolved?
1. Yes [Ask 7CJ
2 . No [SK1P rO 8J
Thinking back to when you were first
the Program that initially caused1. Yes
2. No /Sr17P TO 8J
98 Don't know ISKIP fO 8J
99 Retused ISKIP rO 8J
What caused your concern?
IRECORD RESPONSEJ
involved with the Program, were there any aspects of
you concern?
7.
7a.
The Cadnrus Group, inc. I Hnergy Services 30
PacifiCorp
Roclry Mountain Power
Exhibit No, 5 Page 228 of I 365
Case No. PAC-E-14-07
nov#il[i3r*elE: 2d'ttr"
Don't know ISKIP fO 8J
Retused ISKIP TO 8J
7c. How was it resolved?
IRECORD RESPONSEJ
Enrollment
8. Did you encounter any problems, delays or difficulties during the application, review or
approval processes for the Program?l. Yes
2. No /SrVP TO 1U
98 Don't know ISKIP TO 1U
99 Retused [SKIP TO ]U
9. IIF I : IESI What problems, delays or difficulties did you encounter?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
1. The process took too long2. Too many delays between steps in the process3. The process was too complex4. The applications materials were difficult to understand5. Lack of coordination and communication among Program staff6. The Program staff was not responsive; could not get questions answered7. The Program staff was not knowledgeable8. The incentives were less than I expected9. Unable to get information on the status of the application
10. Multiple requests for more information from[PACIFIC POWER/ROCKY
MOUNTAIN POWERI throughout the process
I l. Disagreement over initial energy savings calculations
12. Disagreement over final energy savings calculations
13. Other ISPECIFYJ
98. Don't know
99. Refused
9a IIF 9 : MORE THAN ONE ANSWERJ: What was the most difficult issue for you?
IRECORD RESPONSEJ
10. If you could change anything about the application process, what would you change?
IRECORD RESPONSEJ
98
99
The Cadnrus Group, lnc. / Energy $ervices 31
I Ik. [IF ] la :I'E! Who were the sponsors for these programs?
IRECORD RESPONSEJ
lld JIF I la : YESJ How did this Program's application process compare to your prior
experience? Was it easier, harder, or about the same?1. Easier
2. Harder
3. About the same
1le. JtF 1Ld : EASIER OR HARDERJ Why do you say that?
IRECORD RESPONSEJ
Recommended Efficiency Measures
12. Was any equipment, controls or other item recommended through this Program that you
did not install?
l. Yes
2. No IFNO SKIP TO 13J
98. Don't know
99. Refused
Roclq Mountain Power
Exhibit No. 5 Page 229 of 1365
Case No, PAC-E-14-07
PacitiCorp
11. Besides this project did your company participate in the FinAnswer program before 2006 or
after 2008?
1. Yes
2. No
98 Don't know
99 Refused
11a. Have you participated in other energy efficiency programs?
1. Yes
2. No [skip to 12]
98. Don't know [skip to l2]
99. Retused [skip to 12]
I lb. [IF I Ia : YESJ What other energy efficiency programs have you participated in?
IRECORD RESPONSEJ
r.r ovJfll[i$f{B: !#{ff '
The Cadmus Group, lnc. I Energy Services 32
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 230 of 1 365
Case No. PAC-E-14-07
r.r o, Jli{lits fi'fl : 2 d'{tr"
l2a. [IF IES/ What was recommended but not installed?
[RECORD RESPONSEJ
l2b. IIF fESl Why did you choose not to install these items?
IRECORD RESPONSEJ
Installed Efficiency Measures
IREFER TO THE SPREADSHEET FOR " INSTALLED MEASURE. '' IF MORE THAN ONE
MEASURE INSTALLED, PLEASE CHOOSE MEASURE WITH LARGEST SAI/INGSJ
13. Did the IINSTALLED MEASUruEJ installed through the Program replace existing
equipment or was it a totally new installation?1. Replaced existing equipment2. Totally new [IF TOTALLY NEW, "PLEASE DESCRIBE" AND, SKIP TO ]5J
98. Don't know
99. Refused
14. What was the operating condition of the equipment that the IINSTALLED MEASUREJ
replaced?l. Old equipment had failed or burned out2. Old equipment had problems, but still working3. Old equipment in working condition with no problems
4. Expanding services or production line; wanted efficient equip5. Other ISPECIFYJ98. Don't know
99. Refused
15. On a scale of 0 to 10, where 0 is not at all satisfied and l0 is very satisfied, how satisfied
would you say you are with the performance of the new [INSTALLED MEASUREJ?
IRECORD RESPONSEJ
98. Don't know
99. Refused
I5a. [If 15 <:5] Why do you say that?
IRECORD RESPONSEJ
98. Don't know
99. Refused
The Cadnrus Group, lnc. / Energy Services d$
Rocky Mountain Power
Exhibit No. 5 Page 231 of 1 365
Case No. PAC-E-14-07
PacifiCorp
Operational Changes
[INTERVIEWER: RESPONDENT WILL RECEIVE ONLY ONE SET OF QUESTIONS
REFERRING TO OPERATIONAL CHANGES FOR A SINGLE MEASURE TYPEJ
16. At the time that you installed these measures, did you have an overall plan to increase the
energy efficiency of your operations?
1. Yes2. No
98. Don't know
99. Refused
16A. Did you change the manner in which you operated [MEASURE TYPE] after the new
[MEASURE TYPE] was installed?
1. Yes2. No ISrVP rOlSJ
98. Don't know
99. Refused
l6b. Were these changes part of the overall plan to increase the energy efficiency of your
operations?1. Yes2. No [SK/P TOL9J
98. Don't know
99. Refused
l6c. What did you change?
IRECORD RESPONSEJ
t7 . IASK lF 16C MENTIONS HOURS OF OPERATIONI Did you change the number of operating hours
or change the operation schedules since measures were installed?
1. Yes
2. No lSr(/P rO 18J
98. Don't know
99. Refused
l7a. Please explain what changes were made
IRECORD RESPONSEJ
r.r ovJ?l4EiB[ei9: !$.'{tr'
The Cadnru$ Group, lnc. I Energy $ervices 34
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 232 of 1 365
Case No. PAC-E-14-07
ruovJffrlitsf{?:2d1tr'
18. Have arry [INSTALLED MEASUREJ been removed since they were installed with this
program?
1. Yes2. No /SrK/P TO 19J
98. Don't know
99. Refused
18a. What was removed?
IRECORD RESPONSEJ
18b. Why was it removed or replaced?
IRECORD RESPONSEJ
18c. About when was it removed or replaced?
IRECORD RESPONSEJ
19. How did installation of the IINSTALLED MEASUREJ fit with planned replacement and/or
maintenance? Was any of this equipment scheduled for replacemenVupgrade before the
program?l. Yes f1F YES, PROBEJ2. No /SrVP rO 20J
98. Don't know
99. Refused
I9a. Which equipment?
IRECORD RESPONSEJ
98. Don't know
99. Refused
20. was the installation of the IINSTALLED MEASUREJ INCLUDED YOUR MOST RECENT
CAPITAL BUDGET BEFORE YOU PARTICIPATED IN THE PROGMM?
1. Yes2. No
98. Don't know
99. Refused
35The Cadnrus Group, lnc. i Energy $ervices
FacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 233 of 1 365
Case No, PAC-E-14-07
ruov#iilBilf1?: [d'{tr'
21. When you installed the new IINSTALLED MEASUREJ, did you expect savings on:
2ta.Electricity?
21b. Water?
2lc. Natural Gas?
2ld. IASK IF 2]a : YESJ Do the electric energy savings meet your expectations?
1. Yes [SKIP TO22)2. No
98. Don't know
99. Refused
2le. IASK IF 2]a : Nol When do you expect these energy savings?
1. Immediately2. Within the next 6 Months ISKIP TO 22J3. Within the next year [SKIP TO 22J4. Within the next two years [SK]P TO 22J5. Never
98. Don't know ISKIP TO 22J
99. Retused ISKIP TO 22J
21f. Why do you not expect savings from the [INSTALLED MEASUREJ in the future?
[sKrP ro 23J
22. Are there any other benefits that you anticipate?
IPROBE IF NEEDED: HAVE YOU OBSERVED ANY CHANGES IN LEVEL OF
PRODUCTION OR SALES? PRODUCT QUALITY?]
IRECORD RESPONSEJ
23. How satisfied are you with the final cost to you of the IINSTALLED MEASUREJ?
Please use a scale from 0 to 10, with 0 being extremely dissatisfied and l0 being extremely
satisfied.
IRECORD RESPONSEJ
98. Don't know
99. Refused
36The Cadnru$ Group, lnc. i Energy Services
Roclv Mountain Power
Exhibit No. 5 Page 234 of 1 365
Case No. PAC-E-14-07
PacifiCorp
23a. [IF Q23<:5J Why do you say that?
24. How satisfied are you with the performance of the IINSTALLED MEASUREJ?
Please use a scale from 0 to 10, with 0 being extremely dissatisfied and l0 being extremely
satisfied.
IRECORD RESPONSEJ
98. Don't know
99. Refused
24a. [If 2a <:5J Why do you say that?
IRECORD fuESPONSEJ
Free Ridership and Market Effects
[NOTE: ONLY ASK FOR SAME MEASURES AS PRIOR QUESTIONSJ
25. On a scale from I to 10, how important were the following factors in deciding which
measures to install:
26. Regarding the installation of [INSTALLED MEASURE/MEASURE(S)J, would you have
installed the [MEASURE/ MEASURESJ without this program?
1. Yes
2. No [/F 'NO', ASK 827, THEN SKIP TO Q30J98. Don't know
99. Refused
27.Before the incentive program, had you previously installed the same type of IMEASURE]
without the program?
3. Yes
4. No
98. Don't know
99. Refused
IRECORD RESPONSEJ
r,r ov Jrillits I1?: 2d'1tr"
Factor Score
A. Information provided by program staff on measure savings
B. Information on pavback for the measure
C. The proiect incentrve
D. Familiarity with these measures
E. Had purchased these measures in the past
The Cadrnu$ Group, lnc. i Energy Services 1aUT
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 235 of 1 365
Case No. PAC-E-14-07
ruou#Jl[iEfffild)tff'
29.
98.
28. Without the program, would you have installed units to the same level of efficiency?
1. Yes
2. No
98. Don't know
99. Retused
Without the program, would you have installed all of the measures or some of the measures?
l. All
2. Some
Don't know
99. Refused
29a.llf 29:Some] Which measures would you have installed?
_ IRECORD RESPONSEJ
30. Without the program, would you have installed these measures...
1. In the same year?
2. In one to two years?
3. In three to five years?
4. More than five years out?
98. Don't know
99. Refused
31. Would you have installed the exact same unit(s) if the amount of the progftrm incentive was
less than the current value?
1. Yes
2. No
98. Don't know
99. Refused
32. How much less? Would you say...
1. 25%oless
2. 50olo less
3. 75olo less
98. Don't know
99. Refused
The Cadmus Group, lnc. / Energy $ervices 38
eqfjlic_o_fp_
Rocky Mountain Power
Exhibit No. 5 Page 236 of 1 365
Case No. PAC-E-14-07
r.r ovJIfi Ets r*el9: 2d )ltr'
33. In your opinion was the difference in price between the energy efficient models and the
conventional models:
1. Very dramatic
2. Somewhat dramatic but significant
3. Not at all different
98. Don't know
99. Refused
Enerry Efficiency Decision Making
Next, I would like to ask you some questions about the decision making process in regards to
energy efficiency purchases and upgrades.
34. Using a 0 to l0 rating scale, where 0 means not at all important and 10 means extremely
important, please rate how important energy efficiency is to the operations and
management of your company?
1. [RECORD RESPONSEJ
98. Don't know
99. Refused
34a. Why do you say that?
35. Do you have sufficient in house technical resources to address the management of energy
and water costs?
1. Yes
2. No
98.Don't know
99.Refused
35b. [1F35:NOJ For this project, were [PACIFIC POWER/ROCKY MOUNTAIN POWER]
or Nexant able to provide you with the needed technical assistance?
IRECORD RESPONSEJ
Spillover
36. Besides installing the measures through this program, since this project have you made any
other energy efficiency improvements or purchases on your own without any assistance
from a utility or other orgarization?1. Yes
2. No /SKIP TO 3U
98. Don't know ISKIP fO 3U
99. Retused ISKIP TO 3U
The Cadmus Group, lnc. I Energy Services 3g
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 237 of 1 365
Case No. PAC-E-14-07
nov#nitriEIlB: [d{ff'
36a. What did you purchase or install?
IRECORD RESPONSEJ
36b. JtF 36 : YESJ I'm going to read a statement about the equipment that you purchased on
your own. On a scale from 0 to 10, with 0 indicating that you strongly disagree, and 10
indicating that you strongly agree, please rate the following statement.
"My experience with the [ProgramJ influenced my decision to install other high
efficiency equipment on my own."
IRECORD RATINGJ
98. Don't know
99. Refused
Interaction with [PACIFIC POWER/ROCKY MOUNTAIN POWER] or 3rd Party Staff
We are also interested in learning more about your interactions with the Program staff
37. How many people did you work with throughout your participation in the Program? This
would include people from Nexant, [PACIFIC POWER/ROCKY MOUNTAIN POWER],
contractors, etc.
Number of people
[sKrP TO 40 rF :0J
38. In what capacity did they work with you?
[PROBE IF NEEDED. WAS IT PROJECT MANAGERS, ACCOUNT REPS, THIRD PARTY
STAFF, CONTRACTORS ; MULTIP LE RESP ONSEJ
1. _IPACIFIC POWER/ROCKY MOUNTAIN POWERI Account
Representatives
2.-tPACIFICPowER/RoCKYMoUNTAINPowER]EnergyEfficiency
Project Managers
Nexant Energy Efficiency Project Managers
4. Installation Contractors
5. External Consultant
Other ISPECIFYJ
IRECORD COMMENTSJ
39. Please describe your overall experience working with these people in relation to this
project._ [RECORD RESP ONSEJ
4SThe Cadnrus Sroup, lnc. I Energy $ervices
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 238 of 1365
Case No. PAC-E-14-07
NovJIffliEf{fl. !#|ff'
Satisfaction
40. Would you participate in the Program again?l. Yes2. No
40a. IIF 40 : NOJ Why not?
IRECORD RESPONSEJ
41. If you could change anything about the Program, what would you change?
IRECORD RESPONSEJ
98. Don't know
99. Refused
42. Using a scale from 0 to 10, with 0 being extremely dissatisfied and 10 being extremely
satisfied, how satisfied are you with your overall experience with the Program?
IRECORD RESPONSEJ
98. Don't know
99. Refused
42a. IIF Q42 <:5J Why do you say that?
Organizational DatalFirmographics
I have a few last questions about your business or organization
43. Approximately, what percent of your total annual operating costs does your electricity bill
represent?
IRECORD RESPONSEJ
98. Don't know
99. Refused
44. Approximately, what percent of your total annual operating costs does your natural gas bill
represent?
IRECORD RESPONSEJ
98. Don't know
99. Retused
The Cadnrus Group, lnc. i Energy Services 41
PacifiCorp
Roclq Mountain Power
Exhibit No. 5 Page 239 of 1365
Case No. PAC-E-14-07
ruov$niEiEf{B: !#{ffi'
45. Approximately, what percent of your total annual operating costs does your water bill
represent?
IRECORD RESPONSEJ
98. Don't know
99. Refused
46. How many people does your firm employ?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Thank you for your time. Your opinions ,re very valuable to this research for [PACIFIC
POWER/ROCKY MOUNTATN POWERI.
4.1T4The Cadrnu$ Group, lnc. / Hnergy Services
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 240 of 1 365
Case No. PAC-E-14-07
r'rov#l[its[18: 2#{ff'
Appendix B. Nonparticipant Suruey
FinAnswer Nonparticipant Interview Guide
Company:
Name:
Telephone:
Title:
City:
Cell phone:
Fax:
State:zip:
Interview date:Time:
Hello, my name is from calling on behalf of [PACIFIC
POWER/ROCKY MOUNTAIN POWERI. We are conducting a study on behalf of [PACIFIC
POWER/ROCKY MOUNTAIN POWERI regarding energy efficiency programs. May I speak with
[designated respondentJ or with the person who is responsible for overseeing energy
management for your organization?
IIF DIRECTED TO A DIFFERENT RESPONDENT, REPEAT INTRODUCTIONJ
My questions are for research purposes only. We are interested in your opinions to help improve
our programs, and understand how to assist customers in saving money on their utility bills.
Your individual answers will be used by [PACIFIC POWERIROCKY MOUNTAIN POWER] to
evaluate energy efficiency programs. IIF RESPONDENT ASKS HOW LONG, SAY:
,, APP ROXIMATELY ] 5 MINUTES.''J
[If a customer asks if this is the Total Quality Service survey, or states that he has recently
participated in the Total Quality Service survey, say 'this is a separate survey about our energy
efficiency pro grams.' ]
[If customer wants to veriff the validity of the survey, tell them that they are welcome to contact
Nancy Goddard, PacifiCorp Program Manager, at [phone].
Screening:
52. First, I need to validate my records.
The Cadrnus Group, lnc. i Energy $ervices AA,
rq_cj!!c9ry
Roclry Mountain Power
Exhibit No. 5 Page 241 of 1 365
Case No. PAC-E-14-07
ruov##Eitsfflg: ?d'{ff'
33. Which electric company provides electric power to your business?
t Pacific Power/Rocky Mountain Power CONTINUE
2 OT}IER..... ....TERMINATEAND TALLY
98 DON',T KNOW .RETURN TO Q.B AND RESCREEN
lntroduction
l. Which of the following best describes your company's primary activities?
1. Manufacturing
2. Retail
3. Dairy / Agricultural
4. Finance and Insurance
5. Food Processing
6. RefrigeratedWarehouse
7. Professional, Scientific, and Technical Services
8. EducationalServices
9. Health Care
10. Public Administration
I 1. Arts, Entertainment, and Recreation
12. Accommodation
13. Food Services
14. Real Estate
15. Other ISPECIFYJ
Participation
2. Have you heard of the IPACIFIC POWER/ROCKY MOUNTAIN POWER] FinAnswer
Program?1. Yes [CONTINUEJ2. No lSrK/P TO 10J
98. Don't know
99. Refused
3. How did you learn about the FinAnswer Program?
The Cadnrus Group, lnc. i Energy Services
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 242 of 1 365
Case No. PAC-E-14-07
r.r ov#ilEits r-elYl ! d'ltr'
IDO NOT READ RESPONSES; MARKALL THAT APPLYJ
1. Contacted by my [PACIFIC POWERIROCKY MOLINTAIN POWER] account
representative or other [PACIFIC POWER/ROCKY MOUNTAIN POWER] staff
2. Contacted by program representative [IF YES ASK 'Do you remember what
company they were from?']
3. Firm contacted the Program
4. Program sponsored conference or workshop
5. Programsponsoredtechnologydemonstration
6. Program sponsored integrated audit
7. Trade Publication8. Marketing by Trade Ally, vendor or contactor
9. Firm approached/contacted by Trade Ally, vendor or contractor
10. Word of mouth; from another business colleague
1 1. Through a trade organization or professional organizationlassociation
12. Through printed material or outreach materials sent by the Program
13. At a trade show
14. Through family, friend, or neighbor
15. Panicipation in other IPACIFIC POWER/ROCKY MOUNTAIN POWER] Programs
16. Past Program participants
t7. Internet research/found Program on [PACIFIC POWER/ROCKY MOUNTAIN
POWERI website
Other ISPECIFYJ
Don't know
Refused
4. What are the reasons you have not had the opportunity to participate in the Program?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
IRECORD RESPONSEJ
98. Don't know
99. Refused
5. Regarding the FinAnswer program, have you either begun participation in the program and
dropped out, or had a project application rejected?
1. Dropped out
2. Application rejected
3. No /SrKIP TO 10J
98. Don'tknow ISKIP TO 10J
99. Retused ISKIP TO 10J
18.
98.
99.
45The Cadrnus Group. lnc. I Energy Services
PacifiCorp
Roctry Mountain Power
Exhibit No. 5 Page 243 of 1 365
Case No. PAC-E-14-07
r.r ovdTii[its r^elB: ! d ltr'
Program Drop-Outs and Rejected Applications
ASKTHIS SECTION ONLY IF RESPONDENT IS: (1) PROGMM DROP-OW (2) fuEJECTED
APPLICATION
6. Thinking back to when you were first considered the Program, were there any aspects of the
Program that initially caused you concern?
1 Yes
2 No ISrKIP TO 5DJ
98 Don't know ISKIP TO 5DJ
99 Retused ISKIP TO 5DJ
6a. What caused your concern?
IRECORD RESPONSEJ
6b. Was this issue resolved?
1. Yes
2. No ISrUP TO SDJ
98 Don't know ISKIP TO 5DJ
99 Retused ISKIP TO SDJ
6c. How was it resolved?
IRECORD RESPONSEJ
ASK ONLY IF RESPONDENT IS A PROGRAM DROP-OUT
6d. Why did your business drop out of the Program?
IRECORD RESPONSEJ
ASK ONLY IF RESPONDENT'S APPLICATION WAS REJECTED
6e. Do you know why your application to participate in the program was denied?
IRECORD RESPONSEJ
ASK FOR BOTH GROUPS
6f. Was the underlying problem resolved to your satisfaction? If not, why not?
The Cadmus Group, lnc. i Energy Services 4S
PacifiCorp
RoclV Mountain Power
Exhibit No. 5 Page 244 of 1 365
Case No. PAC-E-14-07
Nov##Etsf19l2d'1tr'
We are also interested in learning more about your interactions and experience with the Program
staff.
7. How many people did you work with during your time with the Program? This would
include people from Nexant, IPACIFIC POWER/ROCKY MOUNTAIN POWER],
contractors, etc.
number of people
8. Who worked with you with you on this project?
IPROBE IF NEEDED, WAS IT PROJECT MANAGERS, ACCOUNT REPS, THIRD PARTY
STAFF, CONTRACTORS ; MULTIP LE RESP ONSEJ
7. IPACIFIC POWER/ROCKY MOUNTAIN POWER] Account
Representatives8. IPACIFIC POWER/ROCKY MOI-INTAIN POWER] Energy Efficiency
Project Managers
9.Another Energy Efficiency Project Manager UF YES ASK'Do you
remember what company they were from.']
10. _ Installation Contractors
1 l. External Consultant
t2.Other ISPECIFYJ
IRECORD COMMENTSJ
If you could change anlthing about the Program, what would you change?
IRECORD RESPONSEJ
98. Don't know
99. Refused
10. Did your company participate in the FinAnswer program before 2006? After 2008?
lnstalled Efficiency Measures
11. In the past year, have you installed any energy efficiency measures in your building(s)?3. Yes [CONTINUEJ4. No IIFNO SKIP TO ENERGY EFFICIENCY DECISION MAK]NGJ
98. Don't know
99. Refused
lla. What measures have you installed? IDO NOT READ. RECORD ALL EQUIPMENT,
LIGMING, CONTROLS, OTHER ITEMS INSTALLEDJ
1. Lighting2, HVAC
9.
The Cadmus Group, lnc. I Energy $ervices 47
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 245 of 1 365
Case No. PAC-E-'14-07
ru ov#nTEi$ f'l'fl : 2 d'{tr'
3. Controls4. VFD5. Compressed Air measures6. Other ISPECIFYJ
98. Don't know
99. Refused
1lb. Did
1.
13.
t4.
15.
16.
17.
18.
T9,
20.
2r.
98.
99.
2.
98.
99.
you receive a financial incentive or tax credit for installing this equipment?
Yes [Specify the incentive and/ or tax credit amount, and the agency/program
offering the incentive/tax credit.]
No IFNO SKIP TO ENERGY EFFICIENCY DECISION MAKINGJ
Don't know
Refused
Previous experience with other IPACIFIC POWER/ROCKY MOLINTAIN POWER]
Programs
To help protect the environment
To save energy
Recommended by Program contact
Recommended by contractors/trade allies
Recommended by another word of mouth
Recommended by family, friend, or neighbor
Part of a broader remodeling or renovation
Other ISPECIFYJ
Don't know
Refused
12. Why did you decide to install this equipment?
IDO NOT READ KESPONSES; MARKALL THAT APPLYJ
1. To save money on electric bills
2. To obtain a rebate; Program incentive
3. It was scheduled for replacement/upgrade
4. To replace old equipment
5. To replace broken equipment
6. To acquire the latest technology
7. To reduce maintenance costs
8. Because IPACIFIC POWER/ROCKY MOUNTAIN POWER] account manager
suggested it
9. Because Nexant engineer suggested it
10. Because we had funds available in this fiscal year
I l. Because we lose funds if we don't replace it now.
12. Because the Program was sponsored by [PACIFIC POWER/R.OCKY MOUNTAIN
POWERI
4SThe Cadmus Group, lnc. I Energy $eruices
P-egjfic--o_lp_
Roclry Mountain Po /er
Exhibit No. 5 Page 246 of l365
Case No. PAC-E-14-07
ruov#*i[i$ff5l ldltr'
l2a. Have you taken any other actions to save energy in your buildings?
IRECORD RESPONSEJ
13. What actions have you taken?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Energy Efficiency Decision Making
Next, I will ask some questions about the decision making process in regards to energy
efficiency purchases and upgrades.
14. Using a 0 to 10 rating scale, where 0 means not at all important and l0 means extremely
important, please rate how important energy efficiency is to the operations and
management of your company?
IRECORD RESPONSEJ
98. Don't know
99. Refused
15. Why do you say that?
IRECORD RESPONSEJ
16. Do you have sufficient technical resources in house to address the management of energy
and water costs?1. Yes /Sr(IP NEXT QUESTIONJ2. No
98. Don't know
99. Refused
Organ izational Data/Fi rmog raph ics
I have a few last questions about your business or organization
17. Approximately, what percentage of your total annual operating costs is spent in electricity
bills?
IRECORD RESPONSEJ
98. Don't know
99. Refused
The Cadnrus Group, lnc. / Energy Services 49
Roclq Mountain Power
Exhibit No. 5 Page 247 of 1 365
Case No. PAC-E-14-07
PacifiCorp
18. Approximately, what percentage of your total annual operating costs is spent in natural gas
bills?
[RECORD RESPONSEJ
98. Don't know
99. Refused
19. Approximately, what percentage of your total annual operating costs is spent in water
bills?
IRECORD RESPONSEI
98. Don't know
99. Refused
20. How many people does your firm employ?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Thank you for your time. Your opinions are very valuable to this research for [PACIFIC
POWER/ROCKY MOT.INTAIN POWERI.
N ov JYiil[i$ r-elBi !#|ff '
The Cadmus Group, lnc. / Energy Services 5CI
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 248 of 1365
Case No. PAC-E-14-07
ruov#niEi$f''lB:!d{tr'
Appendix C. Staff lnterview Guide
Program Discussion Guide - Enerry FinAnswer Program
Name
Title
Company
Program
Date
Program Overview
1. Can you briefly describe how the progam operates?
a. What is the program theory - how do you expect the programs to change the way
that the target market behaves with respect to energy efficiency?
2. How has the program evolved or changed since the last evaluation in 2004?
3. How do you coordinate activities internally? [marketing, service delivery, work with
TAs, etc.]
4. Are you providing training to:
a. PacifiCorp staff
b. Implementers
c. Trade allies
d. What feedback have you gotten back?
5. What improvements could be made in the administration of the programs?
Application process
6. Could you please describe your understanding of the application process:
a. How do the participants enter the program?
b. What issues are there?
The Cadnrus Group, lnc. i Energy Services tr.t
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 249 of 1 365
Case No. PAC-E-14-07
r,rov#niEiBfffl ld)ltr'
Eligibility criteria and the verification process
7. Please describe the verification process?
a. Participanteligibility
b. What if they are not eligible?
Marketing
8. Do you do anything to promote the program? [What marketing and outreach activities
have been and are being conducted? What's worked best?]
Savings estimation techniques
9. How are savings estimated for the program as a whole and for individual projects?
10. Are the estimations generally felt to be accurate? Is there a way to improve the manner in
which savings are calculated?
1L How are savings verified for the individual projects?
What materials had to be submitted with the applications [invoices, drawings]?
Who received the applications and what the steps were for reviewing and
approving applications and setting up payments?
c. What post-inspections are required?
Participant interaction and satisfaction
12. What aspects of the progftrms do customers seem to be most interested in or most
satisfied with?
a. Any concems? How were they addressed?
a.
b.
The Cadmus Group, lnc. / Energy $ervices 52
Rocky Mountain Power
Exhibit No. 5 Page 250 of 1 365
Case No. PAC-E-14-07
lspilrc-orp-
Program data collection
13. Who is responsible for collecting and tracking participation data?
a. How effective and accurate is the data-tracking and data collection system?
b. Are data entered and reported in a timely fashion?
c. Have there been any difficulties with the data tracking systems?
14. Have the implementers had any problems meeting the tracking and reporting
requirements?
15. Would you recommend any changes to the procedures?
Trade Allies - Communication
16. Is PacifiCorp involved in the recruitment or management of Trade Allies, retailers or
contractors?
a. Describe the relationship between these parties
17. How frequently do you contact people, and how is the communication carried out?
18. How often do trade allies contact you?
19. Have you had any particular challenges in working with trade allies?
20. How are their problems and questions dealt with?
21. What kinds of things have been done or are being planned to identifu trade allies and get
them involved?
22.What has/has not worked well?
23. How would you change or improve communications, either within the program, or with
trade allies?
ruov#lAEitsfl?:2#1tr'
The Cadrnus Group, lnc. I Energy Services 53
PacifiCorp
Rocky Mountain Power
Exhibit No, 5 Page 251 of 1 365
Case No. PAC-E-14-07
r.r o v Jf illiB ["'lY: 2 d{tr'
Implementation Barriers
24.Has the level of program participation met your expectations?
a. Why do you think this has been the case?
25. Have any challenges resulted from perceptions or attitudes about the value of the
program among the target population? If so, what?
26. How have you dealt with those perceptions and attitudes?
27.How about any challenges resulting from perceptions or attitudes about the value of the
programs Ermong the vendors?
a. How have these been dealt with?
Close
O 28. What would you say are the program's strongest points?
29. What are its weakest points?
30. Other than what we've discussed above, what would you change about the program?
The Cadrnus Group, lnc. i Energy Services 54
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 252 of 1 365
Case No. PAC-E-14-07
ruov#i{Eitsf{^fl1ldItr'
Appendix D. Market Actor lnterview Guide
Market Actor Interview Survey Guide - Enerry FinAnswer Program
Interviewee information:
Name:
Organization:
Title:
Telephone
Hello, my name is from The Cadmus Group, calling on behalf of:
[Utah or ldaho] Rocky Mountain Power
[Washington] Pacifi c Power
[Roct<y Mountain Power, Pacific Power] is evaluating its FinAnswer program and
would appreciate your input. This survey is for research purposes only and this is
not a marketing call. Your responses will remain confidential. The questions focus
on how the program operated in the 2006-2008 time period. Do you have a moment
to answer questions about your experience with the program?
[If "No - Not a convenient time,'n ask if Respondent would like to 1. Start now and do part
of the survey, or 2. Arrange a more convenient time we can call them at home. Emphasize
thatl
"It is important for Rocky Mountain PowerlPacific Power to include your opinions in this
study so they can serve your needs better."
[If "No" - Arrange callbackl
Program Overview
l. When did you first start providing services for the program?
What did you see as the purpose of the program?
Who else was involved in carrying out the program? How were they involved? [PROBE
on contractors, engineering firms, energy services companies, retailers, and equipment
manufacturers.]
Have there been changes over time in the services or measures people are interested in?
What are the changes?
2.
aJ.
4.
The Cadmus Group, lnc. / f;nergy $ervices RA
PacifiCorp
Roclry Mountain Power
Exhibit No, 5 Page 253 of 1365
Case No. PAC-E-14-07
r'r ov#ri{trits f'lE: I d {tr'
Program Entry
5. How did a prospective customer find out about the program?
6. Who provided program leads? IDO NOT READ]
a. Program staff
b. Nexant (program implementer)
c. Engineering firms,
d. Energy services companies
e. Retailersf. Other
Participant interaction and satisfaction
7. Did customers express any concerns about the program? How were the concems
addressed?
Pacific Power/Roclry Mountain Power Communication
8. Did your company have any particular challenges in working with Rocky Mountain
Power?
9. How were these challenges dealt with?
Implementation Barriers
10. Did any challenges result from perceptions or attitudes about the value of the progmm
among the Pacific Power/Rocky Mountain Power customers? If so, what were they?
I 1. How did you deal with those perceptions and auitudes?
12. Did anything else make it difficult for you to bring in participants and./or carry out
program requirements? If so, what?
13. How have you dealt with those perceptions and attitudes?
Program data collection
14. Please describe the program's data collection and tracking requirements.
a. Were there any difficulties meeting those requirements?
The Cadmus Group, lnc. / Energy Services 56
PacifiCorp
Roclry Mountain Power
E$ibit No. 5 Page 254 of 1365
Casc No. PAC-E-1447
r,rov#ffiffflI2#1ff"
15. Would you recornmend any changes to the procedures?
Close
16. Other than what we've discussed above, what would you have changed about the
program as it operated in 2006 through 2008?
17. What would you change about the program as it is currently operated?
18. Is there anything else you would like to add?
The Cadrnus Group, lnc. I Energy $ervices 57
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 255 of 1 365
Case No. PAC-E-14-07
r.rov#i{[i&fffl2d{tr'
Appendix E. Energy FinAnswer Process FIow Diagram
Provided under separate cover.
The Cadrnus Group, lnc. / Energy $ervices 58
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 256 of 1 365
Case No. PAC-E-14{7
Nov##Htsref5l2#1ff'
Appendix F. Energy FinAnswer Evaluation Plan
Provided under separate cover.
The Cadnrus Group, lnc. I Energy Services
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 257 of 1 365
Case No. PAC-E-14-07
r,r ovJYff [i$ f'lE: ! #|tr'
Appendix G. Project Reports
Provided under separate cover.
Project 6588
Project 8078
Project 8101
Project 8128
Project 8133
The Cadmus Group, lnc. I Energy $ervices 6CI
PacifiCorp
Roclq Mountain Power
Exhibit No. 5 Page 258 of 1 365
Case No. PAC-E-14-07
nov#niEi3l1'f:2#{tr'
Appendix H. Measure Life Methodology
Measure lifetimes by general measure type were determined for various states and program years
(2005-2008) for the following PC programs:
. Energy Finanswer
o Finanswer Expresso Self Direction
o Retrocommissioning
This analysis was performed in an Excel workbook. Comprehensive economic useful life (EUL)
information for the various individual measures in the portfolio, including sources, were
compiled on a master sheet named "Measure Life." Some of the sources used were DEER 2008,
ACEEE, and the "Measure Life Report" prepared by GDS Associates in2007. When multiple
values for the same measure were available, an average was taken. For example, the measure life
of air compressor improvements in the GDS report was 13 and 15 years for retrofit and new
construction, respectively. Therefore, the final average measure life used in this analysis was 14
years for air compressor improvements. Where measure names in the data sets or in the sources
were open to interpretation, comments were added to clarify to what measure was being
referenced.
Project data, such as measure narne, type, and savings, were organized as sets on individual
worksheets representing each state/program/year combination. Measure type includes the
following main categories (shown with their respective sources):
For each data set, the EUL for the applicable measure types was determined by weighting the
EULs of component measures by total kWh savings. Using the Idaho Energy Finanswer Express
2008 project data as an example, there are 3 measure types (Lighting, HVAC, and Motors).
Lighting measures include Package, Package Trade Ally, and Other. Each of these individual
measures has an associated lifetime (74,14, and 15, respectively). To determine what the overall
EUL should be, the total kWh savings for each measure from this data set was used to weight the
EULs. This process was repeated for the HVAC and Motor measure types to complete the
analysis.
Refrigeration
Lighting
HVAC
Controls
Motors
Additional Measures
Air Compressors
Building Shell
Nonlighting
Hot Water
Traffic Signals
x
x
x
x
x
x
x
x
x
x
x
The Cadmus Group, lnc. i f;nerEy $er*ices 6l
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 259 of 1 365
Case No. PAC-E-14-07
r,r ovdTiitriE relf I ! d'|ff '
Appendix l. Participant and Nonparticipant Survey
Results
Provided under separate cover.
The Cadmus Group, lnc. i Hnergy $eruices a/"
Rocky Mountiain Power
Exhibit No. 5 Page 260 of 1365
Case No, PAC-E-14-07
!-'r_p.,#i{F+39.i8d1tr:
Appendix J. Freeridership Analyses
Freeridership quantifies the percentage of participants who report they would have installed a
measure in the absence of the program.
Energy FinAnswer Program
Freeridership survey data was analyzed for the Energy FinAnswer program using a scoring
matrix approach. This s approach is acknowledged in the National Action Plan for Energy
Efficiency: Model Energy Efficiency Program Impact Evaluation Guidere (Guide).
A survey was designed to understand why customers installed a given measure, and the influence
the program had over those decisions.
In conducting surveys with the battery of questions, Cadmus randomly selected customers
participating in the Energy FinAnswer program. Results of the survey questions were used in a
scoring matrix to determine each participant's freeridership score between 0 and l00o/o.
There are six core questions asked in the survey are written to obtain objective responses and are
used in the freeridership scoring matrix:
o Would the participant have installed the measure without the program?
o Had the participant already ordered or installed the measure before leaming about the
program?
o Would the participant have installed the measure to the same level effrciency without the
progftrm incentive?o Would the participant have installed the same quantity of measures without the program?
o In absence of the program, when would the respondent have installed the measures?
o Was the measure included in included the participant's most recent capital budget?
Cadmus has developed a transparent, straightforward matrix approach to assign a score to all
participants based on their responses.
Patterns ofresponses to these questions are assigned freerider scores, and confidence and
precision estimates are calculated based on the distribution of the scores.
The table below shows the scoring matrix that was used for Energy FinAnswer. This matrix is
expanded from the general format of the scoring matrix included in the Guide. If a respondent
had a non-response, "Don't Know" or "Refused", the respondent was assigned a "Partial" for
that given question. This allows for respondents who had a non-response, 'oDon't Know" or
"Refused" answer for a question to be left in the analysis sample.
'' http://www.epa.gov/cleanenergy/documents/suca./evaluation_guide.pdf
The Cadnrus Group, lnc. i Energy Services 63
PacifiCorp
Roclq Mountain Power
Exhibit No, 5 Page 261 of '1365
Case No. PAC-E-14-07
n ov Jfl{h"i} ['lE: ! dltr"
Yas Partial x x x x f6sPartial 100.00o/o
Yes Yes x x x x fesYss 100.000/0
Partial Yes x x x )arlialYes 100.00%
No x x x x x ,lo 0.00%
Partial No x x x x rartialNo 0.00%
Partial Partial x x x x >artialPartial 25.OOo/
Yes NO No x x x /esNoNo 0.000/o
Yss NO Partial No No Yes r6sNoPanralNoNoYes 0.00o/o
Yes No Partial No No Partial /esNoPartialNoNoPartial 0.00%
Yes No Partial No No No fesNoParlialNoNoNo 0.00o/o
Y6s No Partial NO Partial Yes f gsNoPartialNoPartialYes 0.00%
Yes No Partial No Partial Partial f asNoPartialNoPartialPartial 0.00o/o
Yes No Partial No Partial No /esNoPartialNoPartialNo 0-00o/o
Yes NO Partial No Yes Yes fBsNoPartialNoYesYes 12.500k
Yes No Partial No Yes Partial YesNoPartialNoYesPartial 0.00o/o
Yes No Partial No Yes No YesNoParlialNoYesNo 0.00%
Yes No Panial Partial No Yes f esNoPartialPartialNoYes 0.00%
Yos No Partial Partial No Partial f esNoPartialPartialNoPartial 0.00%
Yes No Partial Partial No No /esNoPartial PartialNoNo 0.00o/o
Yes No Partial Partial Parlial Yes /esNoPartial PartialPartialYes 0.o00/.
Yss No Partial Partial Partial Partial /esNoPartial Partial Pertial Partial 0.00%
Yes NO Partial Partial Partial No /esNoPartial Pafl ial PartialNo 0.00%
Yes No Pariial Partial Yes Yes f esNoPartial Pafl ialYasYes 17 5r|0/"
Yes No Partial Parlial Yas Parlial f esNoPanial PartialYesParlial 0.00%
Yss No Partial Partial Yes No f esNoPartial PartialYesNo 0.00o/o
Yes No Partial Yas No Yes /esNoPartialYesNoYes 0.0@/o
Yes No Partial Yes No Padial /esNoPartialYesNoPartial o.000/"
Yes No Partial Yes No No fesNoPartialYesNoNo 0.0@/o
Yes No Parlial Yes Partial Yes r'esNoParlialYesPartialYes 12.50o/o
Yes No Parlial Yes Parlial Partial /esNoPartialYesPartialPartial 0.00%
Yes No Partial Yes Partial No f esNoPartialYesPartialNo 0.000/0
Yes No Partial Yes Yes Yes /6sNoPartialYssYesYas 25.OOok
Yes No Pariial Yes Y6s Partial /esNoPartialYesYesPartial 12.500/"
Yes No Partial Yes Yes No fesNoPartialYesYesNo 0.00o/o
Yes No Yes No No Yes YcsNoYesNoNoYgs 0.00%
Yes No Yes NO NO Partial fesNoYesNoNoPartial 0.00%
Yes No Yes NO NO No fesNoYesNoNoNo 0.00%
Yes No Yes No Partial Yes fesNoYssNoPartialYes 0.00%
Y6s No Yes No Partial Partial /esNoYesNoPartial Pariial 0.00%
Yss No Yes No Partial No r/esNoYesNoPartialNo 0.00%
Yss No Yes No Yes Yes fesNoYesNoYesYes 0.00%
Yes No Yos No Yes Partial YesNoYssNoYgsParlial 0.00%
Yes No Yes No Yes No fesNoYesNoYosNo 0.00%
Yss No Yes Panial No Yes fesNoYssPartaalNoYes 0.0@/o
Yes No Yes Partial No Partial f esNoYesPartialNoPartial 0.00%
Yes No Yes Partial No No fesNoYesPartialNoNo 0.00%
Yas No Yes Panial Partial Yes r'esNoYesPartialPartialYes 12.500/.
Yes No Yes Partial Partial Partial /esNoYesPartialPartial Partial 0.00%
Ygs No Yes Partial Partial No f esNoYesPartialPartialNo 0.00%
Yes No Yes Panial Yes Yes fesNoYssPartialYesYes 25.O0Yo
Yes No Yes Partial Yes Partial /esNoYesPartialYesPartial 12.500k
Yes No Yes Partial Yes No /esNoYesPartialYesNo 0.00%
Yes No Yes Yes No Yes fesNoY6sYesNoYes 0.00%
Yes No Yos Yes No Partial fesNoYesYesNoPartial 0.00%
Yos No Yes Yes No No r'esNoYesYesNoNo 0.00%
Yes No Y6s Yes Partial Yes r/esNoY6sYesParlialYes 25.OOoh
Yes No Yes Yes Partial Partial r/esNoYesYosPartialPartial 12.500k
Yes No Yes Yes Partial No fesNoYesYesPartialNo 0.00%
Yes No Yes Yes Yes Yes /esNoYesYesYesYes 50.o0%
Yes NO Yes Yes Yes Pailial /esNoYesYesYesPadial 25.00o/o
Yes No Yes Yss Y€s No fesNoYesYesYesNo 12.50Yo
The Cadnrus Group, lnc. I Hnergy Services
Rocky Mountain Power
Exhibit No. 5 Page 262 of 1 365
Case No. PAC-E-14-07
PacifiCorp
The Freeridership Designation
If customers both did not know about the measure before hearing about the program and had no
plans to install the measure, they are not freeriders. Likewise, if they knew about the program,
but had no plans to install the measure, they are not freeriders. Customers who indicated they
would have installed the measure without the program or had already installed the measure when
they leamed of the program are 1O0-percent freeriders.
Customers can also be partial freeriders. Partial scores are assigned to customers that indicated a
likelihood that they would have installed the measure without the program, but that the program
had some influence over the timing of their decision, the level of efficiency they would have
chosen or the number of measures they would have chosen.
ruovJYflEEffIi2#itr'
The Cadrnus Group, lnc. / Energy Services 65
a-]
$
Rocky Mountain Power
Exhibit No. 5 Page 263 of 1365
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Exhibit No. 5 Page 265 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
I
rcffiI*OUNT*N
Exhibit No. 5.4
FinAnswer Express Evaluation 2006-2008
Roclq Mountain Power
Exhibit No. 5 Page 266 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
-x-'ffiffiCAI:}hIITJS
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PacifiGorp FinAnswer Express
2006-2008 ldaho Program
Evaluation
Prepared for
PacifiCorp
Prepared by
The Cadmus Group, lnc. / Energy Services
720 SW Washington Street, Suite 400
Portland, OR 97205
503-228-2992
December 6, 2010
Rocky Mountain Po,ver
Exhibit No. 5 Page 267 of 1365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
Prepared by:
Brian Hedman
Randy Spitzer
Aquila Velonis
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Exhibit No. 5 Page 268 of 1 365
Case No. PAC-E-14-07
neUd??iBSB. !#{tr'
Table of Contents
Conclusions
Recommendations
2. lntroduction ......... .................7
Program Description ..................7
3. lmpact Evaluation............. ...................9
Energy Analysis Methodology............. .......9
Energy Savings Calculation Method ...........9
Engineering Calculations 9
Evaluation Approach ...............10
Step 1: Categorization
Step 2: Methodology Selection
Step 3: Site Visits and Data Collection
Step 4: Analysis
Freeridership 13
4. Process Evaluation............ .............. 15
Process Evaluation Overview ....................15
Process Evaluation ...................15
Organizational DatalFirmographics
Participation
Enrollment
Efficiency Measures
Operational Changes
Installation
Spillover
Energy-Efficiency Decision Making
5
5
10
1l
1l
1l
15
t7
18
18
t9
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20
20
The Cadrnus Group, lnc. / Energy Services
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 269 of 1 365
Case No. PAC-E:14-07
ne#??iBffi'B: [d'{ff"
Interaction with Rocky Mountain or Third-Party Staff
Satisfaction
2t
2t
Key Findings.............. ..............21
Recommendations........ ............22
5. Cost-Effectiveness Analysis ....... ....23
6. Alternative Analysis ..........27
Appendix A. Participant Survey... ........ 31
Appendix B. Nonparticipant Survey ....48
Appendix G Staff lnterview Guide..... ... 56
Appendix D. Market Actor lnterview Guide..... ... 60
Appendix E. FinAnswer Express Process Flow Diagrams ............ 63
Appendix F. FinAnswer Express Evaluation Plan ...........64
Appendix G. Project Reports ...............65
Appendix H. Measure Life Methodology ............ 66
Appendix l. Participant and Nonparticipant Survey Results ......... 67
Appendix J. Freeridership Analyses ...68
The Cadrnus Group, lnc. I HnerEy $er,rices
FacifiCorp
Rocky Mountain Povver
Exhibit No. 5 Page 270 of 1365
Case No. PAC-E-'14-07
WtnesF: Kathfln fi. Iy":esuecernser b. lul t,t
1. Executive Summary
The FinAnswer Express Program offers Idaho customers an opportunity to increase energy
effrciency through energy-efficient design and construction of commercial and industrial buildings.
Customers become eligible to participate if served under Rocky Mountain Power's commercial
and industrial general service rate schedulesl. The progftrm applies to existing customers' retrofit
and major renovation projects and to new facility construction. Nexant was selected as part of a
competitive procurement process to provide trade ally coordination and application processing
services for this program. A Trade Ally network has been established and managed by Nexant and
it is a significant component for program delivery as well as marketing and awareness.
During early spring of 2007, all available 2007 funding for the FinAnswer Express program was
fully committed and new requests for service (either studies or incentive agreements) were
placed on a waiting list. In February 2008, the Company filed to add Energy FinAnswer,
improve the existing programs, remove the funding availability language from existing tariffs,
and requested an increase in the collection rate. The Idaho Public Utility Commission
approved Rocky Mountain Power's filing effective May 1, 2008. Those on the waiting list were
contacted, and many moved forward with their projects either in FinAnswer Express or Energy
FinAnswer.
PacifiCorp offers this program throughout the five state service territories where it manages
demand-side management programs2. Together these programs acquired more than 54,000 MWhs
of first year energy savings in 2008. Within the state of Idaho, this program was responsible for
37Yo of the savings that the utility realizes from commercial and industrial efficiency programs.
Expected savings and other progftrm-related data were downloaded from Rocky Mountain
Power's tracking database. Expected savings were those calculated for each installed project and,
in some cases, documented based on pre and post-installation conditions as determined by Rocky
Mountain Power. These values were then entered in Rocky Mountain Power's database at the
conclusion of each project.
Table 1 summarizes expected savings, evaluated savings, and the realizationrates for 2006-2008
Idaho participants. Savings were evaluated for each installed project.
I
2
Irrigation customers may participate in a separate program directed specifically at irrigation energy savings.
PacifiCorp manages demand-side management programs in five of its six state jurisdictions. Programs in
Oregon are managed by the Energy Trust of Oregon.
The program did not pass the RIM test, as is typically the case for energy effrciency progmms.
The Frogram was cost-effective:fror,ra multiple perspectives,.,in ldaho, using 200$,InP.deaiaffibfii
The Cadnru$ Grsup, lnc. / Energy Service*
PacifiCorp
Rocky Mountain Power
Exhibit No.5 Page 271 of 1365
Case No. PAC-E-14-07
ne#??iBflB:2#{tr'
Table 1. Enerry Savings and Realization Rates
lommercial 17 757,833 780,122 103%103%
:ood Store 6 1,155,814 1,035,423 90%90%
ndustrial 21 1,963,039 1,404,717 720/o 103%
)ther 3 112,235 58,721 52o/oa 90%
ichool 1 417,177 374,004 90%52o/o
Iotal 48 4,406,ogg 3,652,997 83Yo 96%
Table 2 summarizes expected demand savings, evaluated demand savings, andrealization rates.
Table 2. Demand Savings and Realization Rates
lommercial 145 143 99%99%
:ood Store 46 42 91o/o 92Yo
ndustrial 310 228 74o/o 98%
)ther 3 3 100%100%
ichool 80 80 100%100%
l'otal 584 496 85Yo 98Yo
To evaluate achieved energy savings, Cadmus performed site visits for 3l projects at 25
customer locations, covering 91 unique incentives. We also verified 101 additional projects,
covering 189 unique incentives, by reviewing project documentation and speaking with facility
staff. Verified projects represented 98 percent of expected savings. We were unable to schedule a
visit for one large project which was completed in 2007 because the plant had suspended
operations until 201 1. Due to this uncertainty Cadmus has taken a conservative approach and not
credited the full savings from that project. Section 6 of this report provides an alternative
analysis that illustrates the impact of this project on realization rates and cost effectiveness
results.
Based on measurements and observations obtained from the site visits, in addition to data
provided in the project files and conversations with facility staff, Cadmus calculated realization
rates for both energy and demand savings. Table 3 shows energy savings r-ealization rates by
measnre type. Realizationrates were highest for control measures (100%)).
o The low 'Other' energy realization rate was due to one measure no longer being used and one heat pump not
used for heating purposes.5 PacifiCorp tries to be conservative in their saving estimates but realization rates include factors that are difficult
to predict and are typically reflective of how the equipment is used once it's installed, which is under direct
customer control.
The Cadrnus Group, lnc. / Energy Services
f-e-qifi9qP-
Rocky Mountain Power
Exhibit No. 5 Page 272 of 1 365
Case No. PAC-E-14-07
neHd??iB5ilB:9d'{tr'
Table 3. Evaluated Enerry Savings by Measure Type
]ontrols 1 36.719 36.719 100%
IVAC 54 663,075 506.731 76%
-iohtino 22 2.246.592 2,227j50 99%
vlotors 201 890,1 02 360,911 41o/oo
lefrioeration 15 s69,610 521.476 92o/o
lotal 293 4.406.098 3.652.987 83Yo
Table 4 shows demand savings realization rates by measure type. Realization rates were highest
for HVAC measures (100%).
Cadmus determined freeridership to be 59 percent through self-reporting surveys. For this
evaluation freeridership was the only factor used to calculate the Net-to-Gross ratio8. After
applying the Net-to-Gross ratio of 4l percent to the evaluated savings, the net program savings
were 1,497,725 kwh.
When Cadmus examined just the respondents with less than 100 MWh in savings, the Net-to-
Gross ratio increased to 76 percerfi. With this set of parameters, net program savings were
2,776,270 kwh. Section 6 of this report contains an alternative analysis of cost-effectiveness
which uses the Net-to-Gross ratio of 76 percent.
Program cost-effectiveness was analyzed using Idaho-specifi c assumptions.
One customer's site suspended operations after installation of program measures. Partial credit was given for
savings up to the point that the plant closed, consistent with treatment of closed facilities in other jurisdictions.
As noted, one customer's site suspended operations after installation of program measures, and verified energy
savings were reduced to reflect only the period the customer was in operation.
The method employed is consistent with the Model Energy Efficiency Program Impact Evaluation Guide
authored by the EPA as part of the National Action Plan for Energy Efficiency.
Table 4. Evaluated Demand Savings by Measure Type
The Cadmu$ Group, lnc. I f;nerEy Service*
Peqlicqis
Rocky Mountain Power
Exhibit No, 5 Page 273 of 1 365
Case No. PAC-E-14-07
neJ$??iB6?'B:9d1tr'
Table 5. Cost-Effectiveness Summary for the Program in 2006 - IRP
Table 6. Cost-Effectiveness Summary for the Program in2007 - IRP
Table 7. Cost-Effectiveness Summary for the Program in 2008 - IRP
65y. LF Decremen t - 59o/o Freeridership
Total Resource + Conservation Adder (PTRC)$0.041 $226,936 $334,375 $107,439 1.47
Total Hesource No Adder (TRC)$0.041 $226,936 $303,978 $77,041 1.34
Utility (UCT)$0.029 $163.789 $303,978 $1 40,1 89 1.86
Ratepayer lmpact (RlM)$0.093 $520,525 $303,978 -s216 548 0.58
Particioant (PCT)$0.022 $123,710 $417,299 $293,589 3.37
Lifecycle Revenue lmoact ($/kWh)$0.000007456
Discounted Particioant Pavback (years)1.70
650/0 LF Decrement - 59o/o Freeridership
ffi
0.98Total Resource + Conservation Adder (PTRC)$0.076 $271,088 $265.551 -$5,536
Total Resource No Adder (TRC)$0,076 $271,088 $241,410 -$29,678 0.89
Utility (UCT)$0.051 $181,556 $241,410 $59.854 1.33
Ratepayer lmpact (RlM)$0.105 $374,731 $241,410 -$133,321 0.64
Participant (PCT)$0.055 $197,380 $301,023 $103,643 1.53
Lifecycle Revenue lmpact ($/kWh)$ 0.000004104
Discounted Participant Payback (years)5.77
650/" LF Decrement - 59"/o Freeridership
Total Resource + Conservation Adder (PTRC)$0.044 $216,275 $366,320 $150,045 't.69
Total Resource No Adder (TRC)$0.044 $216,275 $333,018 $1 16,743 1.54
Utility (UCT)$0.034 $166,756 $333.018 $166,262 2,00
Ratepayer lmpact (RlM)$0.097 $473,708 $333,018 -$140,690 0.70
Participant (PCT)$0.028 $135,241 $392,674 $257,433 2.90
Lifecycle Revenue lmpact ($/kWh)$ 0.00000474
Discounted Particioant Pavback (vears)1.55
4The Cadmu$ GrCIup, lnc. I Energy Services
Pe-.jl!9-otp*__
Roclry Mountain Power
Exhibit No. 5 Page 274 of 1 365
Case No. PAC-E-14-07
neSd??iB#B:2d{tr"
Table 8. Cost-Effectiveness Summary for the Program Across 2006-2008 - IRP
Conclusions
Overall, the program is cost-effective and functioning well. The participating customers are
satisfied with their involvement and their results.
Table 9. Customer Satisfaction
* l0 : Extremely Satisfied
The program has very good quality assurance and quality control procedures. Savings estimates
for each measure are established conservatively, which is reflected in the high realization rates.
Recommendations reflect suggestions for only minor program enhancements.
Recommendations
o Much like the Energy FinAnswer program, most of the participation appears to come
through one on one interaction between customers, Rocky Mountain Power and/or their
support staff, as well as through trade allies or contractors. This evaluation found a lack
of awareness of the program amongst nonparticipants. The company may wish to
consider adding additional communication strategies to help expand awareness.
65oh LB Decrement - 59o Freeridership
Total Resource + Conservation Adder (PTRC)$0.051 $666,844 $899,209 $232,364 1.35
Total Resource No Adder ffRC)$0.051 $666,8,14 $817.462 $150.618 1.23
Utility (UCT)$0.036 $477.404 $817.462 $340,059 1.71
Ratepayer lmpact (RlM)$0.097 $1.280,1 16 $817,462 -$462,653 0,64
Participant (PCT)$0.032 $424/36 $1,038,008 $613,271 2.44
Lilecycle Revenue lmpact ($/kWh)$ 0.00001 593
The Cadntus Group, lnc. I Hnergy Services
Roclry Mountain Power
Exhibit No. 5 Page 275 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
FacifiCorp
Rocky Mountaln Po\,ver
Exhibit No. 5 Page 276 of 1 365
Case No. PAC-E-I4-07
neJ$?7iil5?'B:ld)ttr'
2. Introduction
Program Description
The 2006-2008 FinAnswer Express program offered customers an opportunity to increase their
operations' energy efficiency through implementation of Energy Effrciency Measures (EEMs)
for existing facilities and new construction projects. The program allows for customers to apply
and receive incentives for prescriptive measures approved by Rocky Mountain Power. The
eligible measures are outlined in extensive lists maintained by Rocky Mountain Power in
conjunction with the implementation contractor. Custom incentives are available for measures
that are not included on the prescriptive measure lists. All customers served under the company's
standard general service commercial and industrial rate schedules were eligiblee. The program is
implemented by Nexant and Rocky Mountain Power.
Any new construction or existing customer on an eligible rate schedule, regardless of size or
load, is eligible to participate in the program. The 2006-2008 program processed 293 unique
EEMs and incentives for projects installed in Idaho, with expected savings of 4,406,098 kwh.
Customers who choose to take advantage of the program offerings can choose from a participating
vendor in Rocky Mountain Power's Energy Efficiency Alliance (Trade Ally Network) for energy
savings through installation of new lighting, motors, controls, HVAC equipment, or any other
qualifying measures. If customers have a custom project that doesn't fit the prescriptive measure
listing they can use an independent consultant to help them analyze their opportunities. The Trade
Ally Network is an important part of the program delivery and has worked well to increase
program awareness since being established. It is managed by Nexantlo.
For EEMs retrofitted in existing facilities, the measure cost was defined as the total, installed
cost of the measure. For new facilities, the measure cost was the installed cost, minus the cost of
code compliant or cornmon-practice equipment. Lighting projects in new construction or major
renovation projects had to be 10o/o lower than the lighting power density allowed by state energy
code. The savings estimates for the new construction projects where there was an applicable
energy code used the building code as a baseline. For retrofit projects the baseline may have
been the existing equipment, common practice or code depending on the nature of the project.
For linear fluorescent lighting retrofit projects Rocky Mountain Power assumed that the baseline
was energy saving T12 lamps with magnetic ballasts.
In some cases, the implementation contractor performed an on-site inspection, confirming pre
and post conditions for certain projects to verifu accuracy of applications and incentives paid.
For a process flow diagram of how the program operates please see Appendix E of this report.
e Irrigation customers may participate in a separate program specifically directed towards irrigation savings.r0 Nexant was selected as part of a competitive procurement process.
The Cadmus Group, lnc. I Energy $ervices
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 277 of 1 365
Case No. PAC-E-14-07
ueSd??iB$'JB: !d{tr'
Idaho FinAnswer Express Program customers completed 293 EEMs in 48 facilities from 2006-
2008. See Table 10 for a description of savings by facility type. Expected energy savings were
largest for industrial facilities.
Table 10. Expected Program Savings by Facility Type
lommercial 17 28Yo 757,833 17%
:ood Storage b 8o/o 1,'155,814 26%
ndustrial 21 62.o/o 1,963,039 450
Ither 3 1o/o 112,235 2o/o
ichool 1 1o/o 417,177 100h
l'otal 48 100%4,406,ogg 100%
Table I I shows expected savings' distribution by end use. Lighting measures represented the
greatest percentage of program savings, at 5l%o, followed by motors at20%o.
Table 11. Expected Savings by End Use
The Cadnru$ Group, lnc. / Energy Service*
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 278 of 1 365
Case No. PAC-E-14-07
ue#??iB6?'B: !#{tr'
3. lmpact Evaluation
Energy Analysis Methodology
Cadmus used engineering calculations to verify savings estimates for all but 13 of the 2006-2008
EEMs.
Overall, the energy analyses evaluation Cadmus conducted verified the reasonableness of the
original analyses underlying the utility's savings estimates. Original estimateS typically were
based on a thorough review of prior studies and/or site inspections. The evaluation sought to
confirm that basic assumptions used in the analysis were corect, the analysis method was
appropriate, measures had been installed and operated as planned and the customer's facility
remained in use. During the review, Cadmus noted projects where changes in operating
conditions were identified and provided revised energy and demand savings estimates. The
revised analyses contained instances ofdecreased and increased savings.
As described below, the energy analysis verification process required a series of steps.
Energy Savings Calculation Method
Cadmus applied the basic level of rigor in conducting the analyses as specified in the Califomia
Public Utilities Commission's Protocols published in 2006tr and IPMVP option A. Analysis of
projects began with a complete review of project files, which included one or more reports at
various project stages that reported energy savings, costs, and incentive calculations and
estimates. Evaluated energy (or demand) savings were calculated by taking evaluated post-
consumption less estimated pre-consumption.
Engineering Calculations
Cadmus reviewed the original energy savings assumptions, and determined whether the site
visits or phone calls identified any changes in assumptions from that analysis. Cadmus also
contacted the utility program manager and energy engineer, as needed, to resolve any issues,
changes, or discrepancies that might affect estimated energy savings. If necessary, Cadmus
adjusted original savings estimates using the same basic methodology, or worked with the energy
engineer who originally analyzed the project to revise estimates.
Various engineering algorithms were used to estimate savings, based on specific measures. As
variations can occur in calculated savings due to particular engineering methods and assumptions
used, the savings calculation methods duplicated the engineering method used when savings
were first derived. For some projects this included reviewing the lighting and HVAC analysis
tools used by PacifiCorp. Cadmus reviewed both of these tools as part of this evaluation.
Cadmus used the observations of key assumptions, validation of engineering methods, and
recalculations based on observed differences to provide evaluated savings estimates.
tt http://www.calmac.org/events/EvaluatorsProtocols_Final_AdoptedviaRuling_06- l9-2006.pdf
The Cadnrus Group, lnc. I Hnergy $ervices
Rocky Mountain Power
Exhibit No. 5 Page 279 of 1 365
Case No. PAC-E-14-07
PacifiCorp ueUffiilA?'B:!d'{tr'
Lighting Tool
The tool calculated energy savings based on total annual operating hours, which were based on
daily occupancy schedules, weeks operated per year, and whether they were open on major
holidays. Square footage was also used in new construction to determine baseline lighting power
density (LPD). Business type was used in 2007 and in more recent versions of the calculator to
determine the coincidence factor. The differences in lighting wattages used for fixture types were
selected from a drop-down menu. Cadmus' review found these wattages and types to be
comparable to those found in other commonly used lighting wattage tables. Cadmus agreed with
the savings methodology, which incorporated straightforward calculations used in standard
lighting savings calculations and did not alter the methodology, or make a recommendation to
change it. Therefore, in the verification of the saving impacts, Cadmus used the tool to adjust
inputs such as annual operating schedule, fixture types and fixture counts as appropriate based on
our review and site visit data collection.
HVAC Tool
The tool uses inputs of equivalent fulI load hours (EFLH), unit capacity in BtuH and unit EER
and SEER to calculate savings as compared to energy usage of a baseline unit with EER and
SEER at code. Baseline EER and SEER were determined by the equipment size and category.
This is a standard calculation to quantify savings from this measure. Cadmus found this to be the
same equation that many utilities include in their technical resource manuals. During the
verification process, Cadmus agreed with the methodology, and only adjusted inputs of
equipment size, EFLH, EER and SEER, based on information gathered onsite or through
verification phone calls.
Realization Rate Analysis Method
For each EEM in the projects, Cadmus calculated energy and demand savings realization rates as
the ratio of evaluated savings to expected savings. The energy realization rate was calculated as a
percentage, using evaluated energy savings from Cadmus' calculations and the utility's expected
energy savings. The demandrealization rate was calculated similarly. If the evaluation confirmed
the original savings estimate, the realization rate would be considered 100%u
As discussed, evaluated energy and demand savings from a project reflected any changes
observed in assumptions used in the original analyses. The realization rate accounted for these
changes in estimating evaluated savings.
Evaluation Approach
Step 1: Categorization
Cadmus originally planned to visit 25oh of the sample of projects for each given program year.
Cadmus was able, however, to increase that number due to multiple projects at individual sites
across program years. Remaining projects in the sample were verified through file reviews and
phone interviews. The number of projects verified through this means also increased from the
The Cadmus Group, inc. / Hn*rgy $ervice*1CI
PacifiCorp
Roclq Mountain Power
Exhibit No, 5 Page 280 of 1 365
Case No. PAC-E-1447
neHS??iBflB: ldItr"
original plan due to overlap. The realization rates for all 7 projects outside of the sample were
extrapolated by measure, based on the findings of the on-site and file based realization rates.
Step 2: Methodology Selection
Cadmus analyzed all projects using the engineering calculation methods described above.
Step 3: Site Visits and Data Collection
On-site verification was used to verify equipment installation and operations, obtain data needed
to perform calculations, and meet with building maintenance staff. Site visits were completed in
January 2010. Site visit information and summaries of the analyses are provided in Appendix G.
Step 4: Analysis
Energy savings were determined for 280 EEMs using engineering calculations incorporating
measurements and observations obtained from the site visits and information obtained from
project files and interviews. Remaining project realization rates were determined through
extrapolation. To extrapolate the realization rates to the other measures, Cadmus first weighted
the evaluatedrealization rates, by energy savings for each measure category. The weighted
realization rate was then applied to the remaining measures within that category that did not have
arealization rate calculated by the Cadmus engineering staff.
Overall, the program achieved a83%o energy savings rcalization rate, as seen in Table 12, which
shows savings by facility type.
Table 12. Evaluated Enerry Savings by Facility Type
(l'c,o6l
Commercial 2 15,246 10,701 70o/o
Food Store 6 1.155.814 1,035,423 90%
lndustrial 7 90,116 81,138 90%
Other 2 54,553 41,346 76Vo
School 1 371,047 328,498 89%
Sub Total 18 1.686.776 1,497,106 89%
t*ooN
Commercial 7 108,381 104.573 96%
lndustrial 15 1,308,085 726.764 56%
Sub Total 22 1,416,466 831,338 59%
oooeC\t
Commercial 10 634,996 666.501 105%
lndustrial I 564,049 595,1 62 106%
Other 1 57,682 17,375 30%
School 1 46,130 45,506 99%
Sub Total 21 1,302,856 1.324.543 102Y0
TotalAllYears 6112 4.406.098 3.652.987 83%
t2 Some customers participated in multiple years so this count of unique buildings is higher.
The Cadnrus Group, lnc. / EnerEy $ervices 1'X
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 281 of 1 365
Case No. PAC-E-14-07
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I rable 13 presents "T"r'lltT'*o *:,:"ton'1,.':,
i."'_:.
*r..
Table 14 shows demand savings realization rates by measure type.
Table 14. Demand Savings Realization Rates by Measure Type
Iitltt
@oo6t
Controls 1 0o/o
HVAC 6 0.72 0.66 92o/o
Liohtino I 79.30 76.56 970
Motors 20 4.71 4.42 94Yo
Refrioeration 14 46.00 42.32 92o/o
Sub Total 50 130.73 123.97 95Yo
t-oo(\t
HVAC 5 28.03 27.97 't00%
Liohtino 4 149.83 140.88 940
Motors 86 98.25 24.87 25o/o1a
Refrioeration 1 0Yo
Sub Total 96 276.11 193.72 700h
@oo6t
HVAC 43 15.21 15.21 't00%
Liohtino o 147.04 151.14 103%
Motors 95 15.25 12.10 790
Sub Total 147 ln.51 178.45 101o/o
TotalAllYears 293 584.35 496.14 85Yo
'' One customer's site suspended operations after installation of program measures and verified energy savings
were reduced to reflect only the period the customer was in operation.
'o One customer's site suspended operations after installation of program measures and verified energy savings
were reduced to reflect only the period the customer was in operation.
Table 13. Evaluated Energy Savings by Measure Type
(ooo(\t
Controls 1 36,719 36,719 100%
HVAC 6 304,570 192.251 63%
Liohtino I 665,038 651,270 98%
Motors 20 119,280 107,151 90%
Flefrioeration 14 561 ,169 509,714 91%
Sub Total 50 1.686.776 1.497.106 89%
oo6l
HVAC 5 29,752 28,822 97o/o
Liqhtinq 4 660,488 608,156 92o/o
Motors 86 717,785 182,598 250/013
Refrioeration 1 8,441 11,762 139%
Sub Total 96 1,416.466 831,338 59%
GOoo6t
HVAC 43 328,753 285,658 87o/o
Lishtinq 9 921,066 967,723 105%
Motors 95 53,037 7'1,'163 134o/o
Sub Total 147 1,302.856 1.324.543 102o/o
TotalAllYears 293 4.406.098 3.652.987 830/o
The Cadnrus Group, lnc. i Energy Service$12
Fa*ifiCorp
'*, on,X.l"I'YnTH:iiff;
Case No. PAC-E-14-07
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Net-to-Gross
Net savings are the savings "net" of what would have occurred in the absence of the program's.
Net-to-gross (NTG) consists of freeridership and spillover. For this evaluation, Cadmus only
quantified freeridership. Spillover is noted separately in Section 4 but not quantified due to the
level of complexity involved in determining the potential savings associated with Spillover for
commercial measures.
Freeridership
Freeridership represents the percentage of program participants who would have implemented
the program measure or practice in the absence of the program. This was quantified through
telephone surveys with program participants who completed projects. While asking participants
to self-report for calculating free ridership is a standard approach, it should be noted this
methodology has some limitations in that it does not account for longer-term market trends
among contractors and supply houses, which typically occur with multiyear programs. For
example, a multiyear program may alter stocking practices at retailers or even the market share
of higher-efEciency products available in a region. Consequently, the customer, choosing
between various makes and models of a given product, may not be aware that the choices
available were altered by a program. Therefore, while the customer may correctly state a choice
was offered between two efficient products, the opportunity to make a higher efficient choice
may have resulted from a progrilm. In this case, while the customer would count as a freerider, a
less-efficient option may have been available to the customer had the program not been
running-an option they otherwise may have chosen.
Accuracy of self-report surveys partly depends on the respondent's memory of their decisions.
For the FinAnswer Express program, some interviewees interviewed were asked to recall actions
taken more than ayear before. Participant candor may also be a factor, as responses may tend to
reflect a "halo" effect, where customers indicate they would have made the energy-efficient
choice because they perceive it to be the response preferred by the interviewer.
In calculating freeridership, Cadmus surveyed 19 program participants. Three of these
respondents had savings associated with their participation in excess of 100 MWh. Of these three
customers, two indicated they would have installed the measures without the program, and had
previously installed similar measures outside the program. As these customers were responsible
for a significant portion of savings, freeridership was calculated as 59o/o. Given the mix of the
respondent population, Cadmus calculated another freeridership estimate, excluding the three
customers mentioned earlier. That exercise resulted in a24o/o freeridership score16. Both types of
freeridership analysis results are presented in Table 15 and Table 16, along with evaluated
savings numbers from Table 13 and Table 14. These savings included all measures (not just
measures for which respondents were surveyed). The freeridership value was applied across all
measures to arrive at net savings for all years.
tt Model Energy Efficiency Program Impact Evaluation Guide authored by the EPA as part of the National Action
Plan for Energy Efficiency.t6 For a full description of the scoring matrix refer to Appendix J
The Cadrnus Group, lnc. I Energy $ervices 13
PacifiCorp
Rocky Mountain Power
Exhibit No, 5 Page 283 of I 365
Case No. PAC-E-14-07
ne#??iB$?'B: ldltr'
Table 15. Freeridership Analysis (All Respondents)
Table 16. Freeridership Analysis (Excluding Respondents with Savings >100 MWh)
As a result of the program funding cap experienced in 2007, the addition of the Energy
FinAnswer program in 2008, removal of the funding caps and the subsequent management of the
remaining customers on the waiting list, there may have been some customer confusion
regarding the two programs and the funding available which may be reflected in the participant
surveys and interpreted as freeridership.
17 Reported at9}%oconfidencerE Reported atg}ohconfidence
41%(+l- 160/oln
The Cadmu$ Group, lnc. / Energy $er,rices 14
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 284 of 1 365
Case No. PAC-E-14-07
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4.Process Evaluation
Process Evaluation Overview
With customer, trade ally, implementer, and company perspectives in mind, the evaluation
looked at what has worked well, what can be improved, and recommended modifications for
refining the program. This evaluation phase relied on interviews with utility and program staff as
well as surveys of participants who completed projects, nonparticipants, and market actors for
the incentive program. Interview and survey activities also informed evaluation of spillover and
freeridership impacts, which can be used as a starting point for ongoing evaluations.
In total, 51 interviews and surveys were conducted for the process evaluation, as shown in
Table 17.
Table 17. Rocky Mountain Power FY 2010 Process Evaluation Samples
Process Evaluation
Organ izational Data/Fi rmog raph ics
A total of 19 participants who completed projects were interviewed for this study. Cadmus' goal
was to interview 25 participants, but in some cases, no remaining staff recalled the project;
others declined to participate, participants frequently failed to return our calls, and others had
invalid contact information.
Responding participants were a diverse group. Table 18 shows respondents' primary business
activities. The largest number of respondents,3To/o, were dairies or agricultural farms.
Table 18. Primary Business Activities of Participants
Although most respondents had less than25 employees, several had employment into the
hundreds. The five respondents with 100 to 500 employees, were all manufacturers or food
The Cadnrus Group, lnc. / finergy Seruices 15
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 285 of 1 365
Case No. PAC-E-14-07
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processors. Figure lshows the frequency of respondents with the corresponding numbers of
employees.
Figure 1. Number of Employees
10 - 25 50 - 100 100 - 500 >1000
Number of Employees
Respondents undertook a wide range of efficiency measures, with lighting being the most
corlmon. Table 19 shows a summary of the measures respondents were asked about.
Table 19. Measures Respondents were Asked About
Most respondents were unable to estimate the percentage their electric bill represented of their
total annual operating costs. Of the respondents who were able to estimate these percentages,
their electric bills represented roughly 15% of their total annual operating costs.
Cadmus was also able to interview 25 eligible customers not participating in the Idaho
FinAnswer Express program from 2006 to 2008. The companies' primary activities are described
in Table 20.
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Table 20. Business Activities of Nonparticipants
Professional, Scientific, and Technical Services
The Cadnru$ Group, lnc. i Energy $ervice*16
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 286 of 1 365
Case No. PAC-E-14-07
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Company sizes varied as well. Eighteen companies employed less than 10 people; five employed
between 10 and 30 people; and two employed over 30 people.
Seven respondents indicated their electricity bills were less than l0o/o of their total annual
operating costs; four indicated they were between llYo and20Yo; and one respondent said they
were25%o of the company's operating cost.
Participation
The program implementer, Nexant, noted customers often found out about the program through
them as well as Rocky Mountain Power account managers and architecture and engineering
firms. They also noted the program's trade ally network has been proactive in identiffing and
facilitating FinAnswer Express projects. Nearly half of participants interviewed learned about the
FinAnswer Express program when contacted by a trade ally, vendor, or contractor. A third of
respondents were contacted by a Rocky Mountain Power account representative or other staff
member. Table 2l indicates how respondents learned about the program. Respondents were
allowed to indicate multiple methods.
Table 21. How Participants Learned of th0 Enerry FinAnswer Express Program
When asked to list all reasons why they participated in the FinAnswer Express progftlm, almost
90olo of respondents participated to save money on their utility bills. Nearly 58% also indicated
they participated to receive the program incentive. The third-largest number of respondents
(32%) decided to participate in the program to replace old equipment. Their responses are shown
inTable22.
Contacted by trade ally, vendor, or contractor
lnternet research or Rockv Mountain Web site
Table 22. Reason for Participating in the Program
To obtain a Drooram incentive
Part of a broader remodelino or renovation
The Cadrnus Group, lnc. i Hnergy $ervices lt
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 287 of 1 365
Case No. PAC-E-14-07
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The implementer noted that building market awareness and acceptance were challenges for any
program because of ongoing change with those selling the products. Two of the 25 program
nonparticipants had heard of the FinAnswer Express progfttm; one had participated in the
program in a different state, and the other heard of it through a trade publication and was
approached by a contractor. Neither respondent had attempted to participate in the program in
Idaho.
Most trade allies contributing to this program heard about the program directly from Nexant or
learned about it from Rocky Mountain Power outreach efforts. Several trade allies were also
involved with other Rocky Mountain Power programs. As a consequence, significant cross-
selling occurred to customers involved in other Rocky Mountain Power programs.
Enrollment
No participants interviewed encountered any problems, delays, or difficulties during the
program's application, review, or approval processes. One respondent, having had to wait for
someone from Washington to arrive to conduct an inspection, suggested a local firm be used in
the future. Three of the respondents said they had participated in the FinAnswer Express
program either before 2006 or after 2008.
Most trade allies made contact with prospective FinAnswer Express program customers through
previous work with those customers. In addition, trade allies tapped into their strong network of
contractors to introduce and involve customers in the program. Trade allies said Rocky Mountain
Power provided some additional customer leads for them as well.
Efficiency Measures
The implementer reported that they worked to increase types of eligible measures over time.
Program offerings increased significantly in2007, including additional motor categories and
VFDs. There was also a significant increase in chillers and drives on the mechanical side. Three
participants interviewed indicated they did not install items recommended through the program.
One respondent did not install a plate cooler due to the amount of water the equipment required.
Another respondent declined to install a VFD Motor because the respondent's service was single
phase, and the equipment required three phase. The final respondent could not say what measure
was recommended or the reason for not installing.
For 74%o of respondents, the energy-saving measure installed through the program replaced
existing equipment. When asked about operating condition of equipment replaced: l4Yo of
respondents indicated it had failed or bumed out,64%o responded it was old and had problems,
but was still working, and 21Yo said it had no problems.
All participants rated their satisfaction with the new equipment highly: an 8 to l0 on a l0-point
scale. The average rating was 9.4.
Three nonparticipants said they had installed energy-efficiency measures in the last year, but
received no incentives or tax credits. One retail company put in efficient gas heaters, one
manufacturer put in a low-watt portable heater, and one professional services company installed
an efficient heat pump, water heater, and refrigerator.
The Cadmus Group, lnc. / Energy Services 18
Rocky Mountain Power
Exhibit No. 5 Page 288 of 1365
Case No. PAC-E-14-07
PacifiCorp neSd??iB5?'B:2#1tr"
Trade allies noted some customers were initially skeptical about program benefits, but, once they
began investing in the efficiency measures, they came onboard the program. Customers generally
started slowly, mainly focusing on lighting improvements (e.g., switching from T12 to T8
lighting). However, over time, customers worked with trade allies on more complex measures,
such as HVAC and ventilation controls, refrigeration upgrades, EMS systems, anti-sweat
controls, and efficiency improvements to drives and motors. Trade allies said some customers
also worked with them on water management improvements.
Operational Changes
At the time respondents participated in the program, 11 had an overall plan to increase their
operations' energy efficiency. These plans ranged from considering efficient equipment when
replacing old equipment to setting a specific goal to reduce energy use by 25%o.T\e remaining
eight respondents did not have a formal plan in place. Respondents with the greatest number of
employees were more likely to have an energy-efficiency plan established than those with a
smaller number of employees.
Four respondents indicated they changed the manner they operated equipment after installing the
new measures. Three of these respondents indicated they used their lights less. One respondent, a
dairy, was able to use their compressors less frequently. Two of the four respondents making
operational changes did so as part of their overall plan to increase their operations' energy
efficiency.
lnstallation
Only one respondent removed or replaced any measures since installation with the program. This
respondent replaced some motors that were damaged.
Six of the 14 respondents that replaced existing equipment through the program had scheduled
the equipment for replacement or upgrade before the program. Five of these respondents
included the project in their most recent capital budgets.
All respondents expected to save money on their electric bills. While 2l%o of respondents did not
know whether electric savings met their expectations, the remainingT9%o felt the savings did.
Most respondents (63%) stated they observed benefits other than energy savings from equipment
installation. The largest additional benefit reported was better quality equipment, as shown in
Table23.
Table 23. Additional Benefits Associated with Measure
When asked to rate their satisfaction with the measures' final cost on a 10-point scale,
respondents gave satisfaction an average rating of8.1. Over 63% ofrespondents rated their
satisfaction as 8. Table 24 shows ratings provided by respondents.
The Cadnrus Group, lnc. i Energy $ervices 1A
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Case No. PAC-E-14-07Pacificorp ne#?ffBfJB:2d)ttr",...........".......-...............:
Table 24. Satisfaction with the Final Cost of Measure
Spillover
Spillover is defined as the amount of additional savings generated by program participants, but
not captured by program records. Cadmus used the same participant survey instrument to qualifu
spillover, resulting when customers purchase energy-efficient measures or adopt energy-efficient
practices because of a program, yet choose not to participate in that program or are otherwise
unable to participate. The nature of this behavior makes it difficult to actually quantify savings
from each action or measure.
Since participating in the program, six respondents installed other energy-effrciency measures
without assistance from a utility or another organization. Measures installed by respondents
included: CFL light bulbs, new doors, insulation, motors and lamps, occupancy sensors,
measures to reduce water usage, and some behavioral changes. Regarding the program's
influence on their decisions to install additional energy-efficiency measures on their own, the
average rating was 7 .7 on a l0-point scale.
Energy-Efficiency Decision Making
Almost all respondents mentioned the importance of energy efficiency to cut costs. The three
respondents that rated its importance at less than seven explained they only explored energy
efficiency when it was cost-effective and did not have many opportunities to improve efficiency.
Table 25 shows results for program participants.
Table 25. Importance of Enerry Efficiency to Program Participants
When asked if their business had sufficient in-house technical resources to address management
of energy costs, 10 respondents answered "yes" and 9 answered o'no."
Ratings nonparticipants gave to energy efficiency's importance varied, but only one respondent
rated it less than 5. Almost all other respondents felt energy efficiency was important, and, when
asked for reasons supporting these high ratings, respondents overwhelmingly referred to cost
savings. Some respondents also mentioned the importance of helping the environment. Table 26
shows results for program nonparticipants.
The Cadmus Group, [nc. I HnerEy Services 2S
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 290 of 1 365
Case No. PAC-E-14-07
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Table 26. Importance of Energy Efficiency to Program Nonparticipants
When asked if their business had sufficient in-house technical resources to address management
of energy costs, 11 respondents answered "yes" and 12 answered "no."
lnteraction with Rocky Mountain or Third-Party Staff
Fifteen program participants interviewed reported they worked with program staff members.
Numbers of staff worked with ranged from one to 10, and included account representatives,
energy efficiency project managers, installation contractors, external consultants, and one
govemment affairs representative. All respondents described their experiences working with
progftrm staff members in positive terms. Many respondents said the experience was "good" or
"very good."
Satisfaction
When asked if they would participate in the program again, 18 of the l9 respondents said yes,
and one respondent did not answer. When asked for suggestions to improve the program,
10 responded they would not change anything at all, and three said the incentive should be
increased. Other suggestions were to increase the program's visibility, make the rules and
timelines less strict, and to follow up with participants in a more timely manner. As shown in
Table 27 all respondents rated their overall satisfaction with the program as 7 or greater.
Key Findings
Among the 19 participants interviewed, satisfaction with program and program staff was high. In
addition, most respondents indicated energy efficiency was important to them because of its
potential to cut costs: nearly all respondents indicated they participated in the program to save on
energy costs. Many participants also reported the program incentive was an important part of
their participation. Most participants learned of the program after being contacted by a trade ally,
vendor or contractor, or Rocky Mountain Power.
Nonparticipant interviews revealed many customers not participating in the FinAnswer Express
program were unaware of it. Twenty-three of 25 nonparticipants interviewed had never heard of
the FinAnswer Express program. Even though the majority of respondents stated energy
Table 27 . Program Satisfaction
The Cadmus Group, lnc. i Energy Services 21
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 291 of 1 365
Case No. PAC-E-14-07
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efficiency was important to them, only three had installed any energy-efficient measures in the
last year.
Recommendations
o Much like the Energy FinAnswer program, most of the participation appears to come
through one on one interaction between customers, Rocky Mountain Power and/or their
support stafi as well as through trade allies or contractors. This evaluation found a lack
of awareness of the pro$am amongst nonparticipants. The company may wish to
consider adding additional communication strategies to help expand awareness.
The Cadmus Group, lnc. / Energy Services 22
E-hibitf":"PPYs""'!i*iiYr:J
Case No, PAC-E-14-07Pacificorp neJ$??iB6'lB:!d'{tr'.,...-.---------..-.......-.......:.
5. Gost-Effectiveness Analysis
To assess cost-effectiveness, evaluators conducted an analysis ofprogram costs and benefits
from five perspectives, using Cadmus' DSM Portfolio Pro model. These perspectives include:
(1) PacifiCorp Total Resource Cost Test (PTRC): This test examined program benefits and
costs from Rocky Mountain Power's and Rocky Mountain Power customers' perspectives,
combined. On the benefit side, it includes avoided energy costs, capacity costs, and line
losses plus a l0%o adder to reflect non-quantified benefits. On the cost side, it includes costs
incurred by both the utility and participants.
(2) Totat Resource Cost Test (TRC): This test examined program benefits and costs from
Rocky Mountain Power's and Rocky Mountain Power customers' perspectives, combined.
On the benefit side, it included avoided energy costs, capacity costs, and line losses. On the
cost side, it included costs incurred by both the utility and participants.
(3) Utility Cost Test (UCT): From Rocky Mountain Power's perspective, benefits were through
avoided energy and capacity costs and line losses. Costs included any program
administration, implementation or incentive costs associated with funding the program.
(4) Ratepayer Impact (RIM): All ratepayers (participants and nonparticipants) may experience
increases in rates to recover lost revenues. This test included all Rocky Mountain Power
program costs as well as lost revenues. As benefits, this test included all avoided energy
costs, capacity costs, and line losses.
(5) Participant Cost Test (PCT): From this perspective, progrirm benefits included bill
reductions. Costs included any customer contribution to the measure cost.
Table 28 summarizes various components of the five tests.
Table 28. Benefits and Costs Included in Various Tests
Table 29 provides selected inputs to the cost analysis. These include the evaluated energy
savings for each year (from Table 2Sabove), discount rate, line loss, and program costs. Other
than the energy savings, these values are provided by Rocky Mountain Power. The discount rate
is from Rocky Mountain Power's 2008 Integrated Resource Plan. Rocky Mountain Power also
provided the values for line loss and the program costs.
Present Value of Avoided Energy and Capacity Costs with
10% Adder for Non-quantified Benefits
Program Administrative and Marketing Cost +
Participant Cost
Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost +
Present Value of Avoided Energy and Capacity Costs Program Administrative, Marketing and lncentive
Cost
Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost +
Present Value of Lost Revenues
Present Value of Bill Savings
The Cadr,rus Group, lnc. i Energy Services IJ
E,h i bit f":"YPYsTl!1ii ilfJ
Case No. PAC-E-I4-07Pacificorp ne$??iB6?'B:!d1tr'................----------.------:--
Table 29. Selected Cost-Effectiveness Analysis Inputs (59% Freeridership)
Net Prooram Savinos ftWh/vear)1.497.106 831,338 1,324,543
Discount Rate 7.400h 7.400/o 7,400/o
Line Loss 10.7% Commercial
10.39% lndustrial
10.7% Commercial
10.39% lndustrial
10,7% Commercial
10.39% lndustrial
Commercial Retail Rate $0.0660 $0.0669 $0,0679
lndustrial Retail Rate $0.0414 $0,0463 $0.0497
Net Participant Costs $123,710 $197,380 $135.241
Prooram Costs
Prooram Manaoement Costs $s6,452 $32,s55 $54,844
Enqineerinq Costs $31.910 $35,947 $16,672
lncentive Costs $60,563 $107,848 $85,722
Utilitu Administrative Costs $14,864 $5,206 $9,518
Total Proqram Costs $163.789 $181.556 $166.756
Program benefits are comprised of energy savings and their associated avoided costs. The energy
savings used in the cost-effectiveness analysis are the evaluated kWh savings from this study.
Benefits are accrued over the expected useful life of the installed measure. Measure lives are
shown in Table 30.
Tabte 30. Measure Life Summaryre
Table 31, Table 32, and Table 33 present the results of the cost-effectiveness analysis for the
Program ln,2006,2007, and 2008 respectively using a freeridership of 59oh as described in
Section 3 of this report. Table 34 presents the results of the cost-effectiveness analysis for the
Program for 2006-2008 combined. All analyses are based on the Rocky Mountain Power 2008
IRP 65% Eastside System Decrement20.
Measures lives were calculated based on information from California's DEER database, the New England State
Program Working Group report for the ISO Forward Capacity Market, and ACEEE's report on updating Energy
Efficiency Standards. The average is achieved by weighting the savings associated with each of the measure
types in a given year. See Appendix H for a detailed explanation.
IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan Volume II
Appendices:
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The Cadnru$ Group, lnc. i Energy Services 24
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Roclry Mountain Power
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Case No. PAC-E-14-07
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Table 31. Cost-Effectiveness Summary for the Program in 2006 - IRP
650/" LF Decrement - 59o Freeridership
Table 32. Cost-Effectiveness Summary for the Program in 2007 - IRP
Table 33. Cost-Effectiveness Summary for the Program in 2008 - IRP
Table 34. Cost-Effectiveness Summary for the Program Across 2006-2008 - IRP
65" LF Decrement - 59oh Freeridership
rElilligull
Total Resource + Conservation Adder (PTRC)$0.041 $226.936 $334.37s $107.439 1.47
Total Resource No Adder (TRC)$0,041 $226,936 $303,978 $77,041 1.34
Utilitv (UCT)$0.029 $163,789 $303.978 $140,189 1.86
Ratepayer lmpact (RlM)$0.093 $520,52s $303,978 -$216,548 0.58
Participant (PCT)$0.022 $123,71 0 $417,299 $293,589 3.37
Lifecvcle Revenue lmoact ($/kWh)$0.000007456
Discounted Participant Pavback (vears)1.70
65oh LB Decrement - 59o/o Freeridership
Total Resource + Conservation Adder (PTRC)$0.076 $271,088 s265.551 -$5,536 0.98
Total Hesource No Adder (TRC)$0.076 $271,088 $241,410 -$29.678 0.89
Utility (UCT)$0.0s1 $181,s56 $241,410 $59,854 1.33
Ratepaver lmoact (RlM)$0.105 $374,731 $241,410 -$133,321 0,64
Participant (PCT)$0.055 $197,380 $301,023 $103,643 1.53
Lifecycle Revenue lmoact ($/kWh)$ 0.0000041 04
Discounted Particioant Pavback (vears)5.77
65"/" LF Decrement - 59"h Freeridership
;ffiflt*#r
Total Resource + Conservation Adder (PTRC)$0.044 $216,275 $366,320 $150,045 1.69
Total Resource No Adder (THC)$0.044 $216.275 $333,018 $1 16,743 1.54
Utility (UCT)$0,034 $166,756 $333,018 $166,262 2.00
Ratepayer lmpact (RlM)$0.097 $473,708 $333,018 -$140,690 0.70
Particioant (PCT)$0.028 s't35 24'l $392,674 $257.433 2.90
Lifecvcle Revenue lmoact ($/kWh)$ 0.00000474
Discounted Parlicioant Payback (vears)1.55
Total Resource + Conseruation Adder (PTRC)$0.0s1 $666,844 $899,209 $232,364 1.35
Total Resource No Adder (THC)$0 osl $666.844 $817.462 $1 50.618 1.23
Utilitv (UCT)$0.036 $477,404 $817,462 $340,059 1.71
Ratepaver lmpact (RlM)$0.097 $1,280,116 $817,462 -$462,653 0.64
Particioant (PCT)$0.032 $424,736 $1,038,008 $613,271 2.44
Lifecvcle Bevenue lmpact ($/kWh)$ 0.00001593
The Cadnru$ Group, lnc. I Energy $ervices 25
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 295 of 1 365
Case No. PAC-E-14-07
\MtnesF: KathA/n Q. tlyrnesuecemser b. lurtl
Table 35, Table 36, and Table 37 present the results of the cost-effectiveness analysis for the
Program in 2006, 2007, and 2008 respectively using a freeridershtp of 24% as described in
Section three of this report. All analyses are based on the Rocky Mountain Power 2008 IRP 65%
Eastside Decrement.
Table 35. Cost-Effectiveness Summary for the Program in 2006 - IRP
Table 36. Cost-Effectiveness Summary for the Program in 2007 - IRP
Table 37. Cost-Effectiveness Summary for the Program in 2008 - IRP
650/0 LF Decrement - 24o Freeridership
-i&ulnTotal Besource + Conservation Adder (PTRC)$0,032 $332,543 $619,81 I $287,275 1.86
Total Resource No Adder ffBC)$0.032 $332,543 $563,471 $230,928 1.69
Utilitv (UCT)$0.016 $399,682 $563,471 $399,682 3.44
Ratepayer lmoact (RlM)$0.08 $825,056 $563,471 -$261,275 0.68
Particioant (PCT)$0.022 $229,316 $721,830 $492,514 3.15
Lifecycle Revenue lmoact ($/kWh)$ 0.000009007
Discounted Particioant Pavback (vears)2.48
650A LB Decrement - 24o/o Freeridership
Total Resource + Conservation Adder (PTRC)$0.066 $439.583 $492,242 $52,659 1.12
Total Resource No Adder (TRC)$0.066 $439,583 $447,492 $7,909 1.02
Utilitv (UCT)$0.027 $181 ,556 $M7,492 $265,936 2.46
Ratepaver lmpact (RlM)$0.081 $539,636 $447,492 -$92,144 0.83
Participant (PCT)$0.055 $365,875 $465,928 s1 00 054 1.27
Lifecvcle Revenue lmoact ($/kWh)$ 0,000002837
Discounted Particioant Payback (years)9.66
650 LBDecrement-24o Freeridership
ffiffitt+t
Total Resource + Conservation Adder (PTHC)$0,037 $331,724 $679,031 $347,307 2.0s
Total Resource No Adder ffRC)$0.037 $331,724 $617,301 $285,577 1.86
Utilitv (UCT)$0.018 $166,756 $617.301 $450,545 3.70
Ratepayer lmpact (RlM)$0.081 $735,741 $617,301 -$118,439 0.84
Participant (PCT)$0.028 $250,690 $654,706 $404,016 2.61
Lifecvcle Revenue lmoact ($/kWh)$ 0.00000399
Discounted Particioant Pavback (vears)2.84
The Cadnru$ Group, lnc. / Hnergy Services 2fi
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 296 of 1 365
Case No, PAC-E-14-07
ne#d??iB6"lB:?d'{tr'
6. Alternative Analysis
During an evaluation period in which there are some completed projects that represent a
disproportionate amount savings compared to the whole, the overall results can be significantly
influenced if even one of those projects differs from its original assumptions, as was the case
with one particular industrial customer.
The referenced customer participated in the FinAnswer Express program multiple times in all
three program yeils. Because the facility is currently idle for an indefinite amount of time the
verified energy savings were significantly reduced to reflect only the time the customer was
operating. The fact that the facility has been idle for a prolonged period of time is clearly outside
of the program's control. As a result Cadmus reran the cost effectiveness andrealization rate
analysis for the Idaho FinAnswer Express program excluding this customer's projects in order to
provide another perspective. For this scenario Cadmus removed the energy savings, incentive
costs, and measure costs for the customer. Table 38 shows the results of the revised realization
rate analysis.
Table 38. Evaluated Energy Savings by Measure Type
-iEuiir@oo6t
Controls 1 36.719 36,719 100%
HVAC 6 304,570 192,251 63%
Liohtino I 665,038 651,270 98%
Motors 11 109,879 't05 390 96%
Refrioeration 14 561,169 509,714 91%
Sub Total 41 1,677,375 1.495.346 89%
I\oo6t
HVAC 5 29,752 28,822 970k
Liqhtinq 3 601,647 598,752 100%
Motors 57 107,051 102.405 96%
Refrioeration 1 8,441 11,762 139o/o
Sub Total 66 746,891 741.741 990/o
@eo6t
HVAC 43 328,753 285,658 87Vo
Liohtino I 921,066 968,535 105%
Motors 74 43,774 70,372 161%
Sub Total 126 1,293,593 1,324,564 102Y0
TotalAllYears 233 3,717,859 3,561,650 96%
Table 39 and Table 40 show the results of the revised freeridership analysis for the two scenarios
illustrated in section three.
Table 39. Freeridership Analysis (All Respondents)
Freeridershio 59%G/.160/o\21
Evaluated Savinqs 3,561,650
Net Savrnos 1,460,277
21 Reported atg}Yoconfidence
The Cadrnu$ Group, lnc. I Hnergy Services 27
Rocky Mountain Power
Exhibit No. 5 Page 297 of I 365
Case No. PAC-E-14-07
FacifiCorp WtnesF: KathAn Q. tlyr[asLiecem$er b" lu'rL|
Table 40. Freeridership Analysis (Excluding Respondents with Savings >100kwh)
Freeridershio 24% kL 16o/o\22
Evaluated Savinqs 3,561,650
Net Savinos 2,706,854
Table 41, Table 42, and Table 43 present the results of the cost-effectiveness analysis for the
Program in2006,2007, and 2008 respectively using and a freeridership of 59Yo as described in
Section three of this report. All analyses are based on the Rocky Mountain Power 2008 IRP 65%
Eastside Decrement.
Table 41. Cost-Effectiveness Summary for the Program in 2006 - IRP
65oh LF Decrement - 59o Freeridership
Total Resource + Conservation Adder (PTRC)$0.041 $226,426 $333,665 $107,239 1.47
Total Resource No Adder fiRC)$0.041 $226,426 $303,332 $76,906 1,34
Utilitv (UCT)$0.029 $162,461 $303,332 $140,871 1.87
Rateoaver lmoact (BlM)$0.09s $s18,634 $303,332 -$215,302 0.58
ParticiDant (PCT)$0.022 $123,200 $415,407 $292,208 3.37
Lifecvcle Revenue lmoact ($/kWh)$0,000007413
Discounted Participant Payback (vears)1.72
Table 42. Cost-Effectiveness Summary for the Program in2007 - IRP
22 Reported atg\o/oconfidence
65" LEDecrement-Sgo Freeridership
ffi*Tffi
Total Resource + Conservation Adder (PTRC)$0.069 $211,070 $225,377 $14,306 1.07
Total Resource No Adder (TRC)$0.069 $211,070 $204,888 -$6,182 0.97
Utilitv (UCT)$0.048 $145.942 $204,888 $s8,946 1.40
Ratepaver lmoact (RlM)$0.102 $310,736 $204,888 -$105,848 0.66
Participant (PCT)$0.045 $137,362 $237,028 $99,665 1.73
Lifecvcle Revenue lmoact ($/kWh)$ 0.000003258
Discounted Particioant Pavback (vears)4.84
The Cadnru$ GrCIup, lnc. I Hnergy $ervices
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 298 of 1 365
Case No. PAC-E-'14-07
ne#?fiilSB:ld'ttr'
Table 43. Cost-Effectiveness Summary for the Program in 2008 - IRP
65yo LF Decrement - 59oh Freeridership
Table 44,Table 45, and Table 46 present the results of the cost-effectiveness analysis for the
Program n2006,2007, and 2008 respectively using a freeridership of 24% as described in
Section three of this report. All analyses are based on the Rocky Mountain Power 2008 IRP 65%
Eastside Decrement.
Table 44. Cost-Effectiveness Summary for the Program in 2006 - IRP
65" LFDecrement-24o Freeridership
Total Resource + Conservation Adder (PTRC)$0.046 $215,615 $353,99s $138,381 1.64
Total Resource No Adder (TRC)$0.046 $215,615 $321,814 $106,199 1.49
Utility (UCT)$0.035 $165,257 $321,814 $156,557 1.95
Ratepaver lmpact (RlM)$0.098 $461,572 $321,814 -$139,758 0.70
Particioant (PCT)$0.028 $134,581 $380,538 $245,957 2.83
Lifecvcle Revenue lmoact ($/kWh)$ 0.00000471
Discounted Particioant Pavback (vears)1.62
Total Resource + Conservation Adder (PTRC)$0.032 $331,596 $618,501 $286,905 1.87
Total Resource No Adder (TRC)$0.032 $331,596 $562,274 $230,677 1.70
Utility (UCT)$0.016 $162,461 $562,274 $399,813 3.46
Ratepayer lmpact (RlM)$0.079 $822,683 $562,274 -$260,410 0.68
Particioant (PCT)$0.022 $228,370 $719,457 $491,087 3.15
Lifecycle Revenue lmpact ($/kWh)$ 0.000008966
Discounted Particioant Pavback (vears)2.49
Table 45. Cost-Effectiveness Summary for the Program in2007 - IRP
65oh LB Decrement - 24o Freeridership
Total Resource + Conservation Adder (PTRC)$0.0s8 $328,331 $417,nl $89,440 1.27
Total Resource No Adder (TRC)$0.058 $328,331 $379,792 $51,461 1.16
Utility (UCT)$0.026 $145,942 $379,792 $233,850 2.60
Ratepaver lmoact (RlM)$0.08 $451,413 $379,792 -$71,621 0.84
Particioant (PCT)$0.045 $254,623 $377,705 $123,082 1.48
Lifecycle Bevenue lmpact ($/kWh)$ 0.000002205
Discounted Particioant Pavback (vears)7.69
The Cadrnus Group, lnc. i Energy Services 2g
l-q-rL{icqP
Roclry Mountain Power
Exhibit No. 5 Page 299 of I 365
Case No. PAC-E-14-07
ne#??iL$?'B: !d'{ff'
Table 46. Cost-Effectiveness Summary for the Program in 2008 - IRP
65oh LF Decremen t - 24oh Freeridership
Total Resource + Conservation Adder (PTRC)$0.038 $330,501 $656,1 87 $325.686 1,99
Total Resource No Adder ffRC)$0.038 $330.501 $596,533 $266,033 1.80
Utility (UCT)$0,019 $165,257 $s96,533 $$1.2n 2,54
Ratepayer lmpact (RlM)$0.081 $714,524 $s96,533 -$117,991 0.83
Participant (PCT)$0.028 $249,467 $633,490 $384.024 2.54
Lifecvcle Revenue lmoact ($/kWh)$ 0,00000398
Discounted Particioant Pavback (years)2,94
The Cadmus Group, lnc. I EnerEy $ervices 2n
Pq--cjficptp
Rocky Mountain Power
Exhibit No. 5 Page 300 of 1 365
Case No. PAC-E-14{7
oeIS?frBA?'B:!d'|tr"
Appendix A. Participant Suruey
FinAnswer Express Participant Interview Guide
Company:
Name:
Telephone:
Cell phone:
Fax:
State:zip:
Interview date:Time:
Measure with the greatest savings, and amount of savings (from column W):
(Refer to this measure in the 'Installed Efficiency Measures' section.)
Hello, my name is from The Cadmus Group, calling on behalf of:
[Utah or Idaho] Rocky Mountain Power
[Washington] Pacific Power
IPACIFIC POWERyROCKY MOUNTAIN POWER] is evaluating its FinAnswer Express program
and would appreciate your input. "It is important for [PACIFIC POWER/ROCKY MOUNTAIN
POWER] to include your opinions in this study so they can serve your needs better."
[NOTE: If the customer has received a FinAnswer Express site visit, state: 'This is
a brief follow up to the site visit you recently received.']
[NOTE: If the customer has been selected for a FinAnswer Express site visit but the
visit has not yet happened, state: oWe are conducting this survey to prepare for an
upcoming site visit to see your FinAnswer Express project. We perform site visits
to get a better understanding of the energy savings you are actually getting from the
program.]
This survey is for research purposes only and this is not a marketing call. Your
responses will remain confidential. This survey will take approximately 20 minutes.
As a Thank Youfor your assistance, at the end of the survey you we would like to
offer you a $50 gift card, which will be mailed to you. Do you have a moment to
answer questions about your experience with the program?
Title:
City:
The Cadrnus Group, lnc. / Hnergy $ervices 31
I Isthatcorrect?
l.Yes IIF YES - GO TO QUESTION 4.J
2. No, measure is/are incorrect
3. No, date is incorrect (Skip to 3)
98. DK (TERMTNATE)
2. [IF Ql: No, measure is/are incorrect, ASK] What measures were installed?
IRECORD RESPONSEJ
3. IIF Ql: No, date is incorrect, ASK] About when were the measures installed?
1. MONTH YEAR
98. DK (do not terminate)
99. REF (TERMTNATE)
Roclry Mountain Power
Exhibit No. 5 Page 301 of 1365
Case No. PAC-E-14-07
ne#??iil$ilB: ld'tffi'FacifiConp
[If a customer asks if this is the Total Quality Service survey, or states that he has recently
participated in the Total Quality Service survey, say 'this is a separate survey about your
participation and satisfaction with the FinAnswer Express program.']
[If "No - Not a convenient time," ask if Respondent would like to 1. Start now and do part of the
survey, or 2. Artange a more convenient time we can call them at home.
[If customer wants to verifr the validity of the survey, tell them that they are welcome to contact
Nancy Goddard, PacifiCorp Program Manager, at [phone].
IIF "NO" - ARRANGE CALLBACKJ
. Confirmation
1. The [PACIFIC POWER/ROCKY MOUNTAIN POWER] records show that you participated
in the FinAnswer Express program during [Month] of [Year], and at that time received [AN
INCENTIVE/INCENTIVESI for the installation of (a) IMEASURE(s)] at IADDRESS OF
INSTALLATION]
The Cadnrus Group, lnc. / f;nergy $ervices 3/^
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 302 of I 365
Case No. PAC-E-14-07
neS??iB#Bl [d'{S"
4. Which of the following best describes yoru company's primary activities?
1. Manufacturing
2. Retail
3. Dairy / Agricultural
4. Finance and Insurance
5. Food Processing
6. RefrigeratedWarehouse
7. Professional, Scientific, and Technical Services
8. Educational Services
9. Health Care
10. Public Administration
1 1. Arts, Entertainment, and Recreation
12. Accommodation
13. Food Services
14. Real Estate
15. Other [SPECIFY]
Participation
5. How did you leam about the FinAnswer Express?
IDO NOT READ RESPONSES; MARKALLTHAT APPLYJ
l. Contacted by my IPACIFIC POWER/ROCKY MOUNTAIN POWER] account
representative or other [PACIFIC POWER/ROCKY MOUNTAIN POWER] staff
2. Contacted by program representative [IF YES ASK 'Do you remember what
company they were from?']
3. Program sponsored conference or workshop
4. Program sponsoredtechnology demonstration
5. Program sponsored integrated audit
6. Trade Publication
7. Marketing by Trade Ally, vendor or contactor
8. Firm approached/contacted by Trade Ally, vendor or contractor
9. Word of mouth; from another business colleague
1 0. Through a trade organization or professional orgarization/association
1 1. Through printed material or outreach materials sent by the Program
12. At a trade show
13. Through family, friend, or neighbor
14. Participation in other [PACIFIC POWER/ROCKY MOUNTAIN POWER] Programs
15. Past Program participants
16. Internet research/found Program on the IPACIFIC POWER/ROCKY MOLTNTAIN
POWERI website
The Cadnrus Group, lnc. i Energy $ervices .:-)
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 303 of 1 365
Case No. PAC-E-14-07
neffi"il6?'B:ld't$'
17. Other [SPECIFY]
98. Don't know
99. Refused
6. Why did you decide to participate in the Program?
IDO NOT READ RESPONSES; MARKALLTHAT APPLYJ
1. To save money on utility bills; save money on electric bills
2. To obtain a program incentive
3. To replace old equipment
4. To replace broken equipment
5. To acquire the latest technology
6. To reduce maintenance costs
7. Because the Program was sponsored by [PACIFIC POWER/ROCKY MOI-]NTAIN
POWERI
8. Previous experience with other IPACIFIC POWER/ROCKY MOUNTAIN POWER]
Programs
9. To help protect the environment
10. To save energy
11. Recommended by Program contact
12. Recommended by contractors/trade allies
13. Recommended by another IPACIFIC POWER/ROCKY MOUNTAIN POWER]
customer; word of mouth
L4. Recommended by family, friend, or neighbor
15. Part of a broader remodeling or renovation
16. Other ISPECIFY]
98. Don't know
99. Refused
7. Thinking back to when you were first involved with the Program, were there any aspects of
the Program that initially caused you concern?1. Yes
2. No ISrVP TO 8J
98. Don't know ISKIP TO 8J
99. Retused ISKIP TO 8J
7a. What caused your concern?
IRECORD RESPONSEJ
The Cadmus Group, lnc. i Energy Services 34
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 304 of 1365
Case No. PAC-E-14-07
oeSd??iE#B: ?d)ttr'
7b.
7c.
Was this issue resolved?
1. Yes [Ask 7CJ
2 . No ISrVP rO 8J
98. Don't know ISKIP fO 8J
99. Retused ISK]P rO 8J
How was it resolved?
IRECORD RESPONSEJ
Enrollment
8. Did you encounter any problems, delays or difficulties during the application, review and
approval process for the Program?1. Yes
2. No /SrUP TO 10CJ
98 Don't know ISKIP fO ])CJ
99 Retused ISKIP rO 10CJ
9. IIF 8 : I/ESI What problems, delays or difficulties did you encounter?
[DO NOT READ RESPONSES; MARK ALL THAT APPLYJ
l. The process took too long2. Too many delays between steps in the process3. The process was too complex4. The application materials were difficult to understand5. Lack of coordination and communication among Program staff6. The Program staff was not responsive; could not get questions answered7. The Program staff was not knowledgeable8. The incentives were less than I expected9. Unable to get information on the status of the application
10. Multiple requests for more information from[PACIFIC POWER/ROCKY
MOUNTAIN POWERI throughout the process
Disagreement over initial energy savings calculations
Disagreement over final energy savings calculations
Other ISPECIFYJ
Don't know
Refused
11.
12.
13.
98.
99.
The Cadnrus Group, lnc. / Hnergy Services 35
PacifiCorp
Rocky Mountiain Power
Exhibit No. 5 Page 305 of 1365
Case No, PAC-E-14-07
ne#??iB6?'B: !d'|tr'
9a-[IF 9: MORE THAN ONE ANSWERJ; What was the most difficult issue for you?
IRECORD RESPONSEJ
10. If you could change anything about the application process, what would you change?
IRECORD RESPONSEJ
11. Besides this project did your company participate in the FinAnswer Express program before
2006? After 2008?
1. Yes
2. No
98 Don't know
99 Retused
1La. Have you participated in other energy efficiency programs?
1. Yes
2. No [skip to 12]
98. Don't know [skip to 12]
99. Retused [skip to 12]
l lb. [IF 11a : YESJ What other energy efficiency programs have you participated in?
IRECORD RESPONSEJ
llc. [IF ] la : IES/ Who were the sponsors for these programs?
IRECORD RESPONSEJ
lld, IIF I ]a: YESJ How did this Program's application process compare to your prior
experience? Was it easier, harder, or about the same?1. Easier
2. Harder
3. About the same
1le. JtF ILd : EASIER OR HARDERJ Why do you say that?
IRECORD RESPONSEJ
The Cadnrus Group, lnc. I Energy $ervices Jb
PacifiCorp
Roclry Mountiain Po^rer
Exhibit No. 5 Page 306 of 1 365
Case No. PAC-E-14-07
oeud?fi86?8. !#tff'
Recommended Efficiency Measures
12. Was any equipment, lighting, controls or other item recommended through this Program that
you did not install?
l. Yes
2. No /1FNO SKIP TO ]3J
98. Don't know
99. Refused
I2a. IIF YESJ What was recommended but not installed?
IRECORD RESPONSEJ
l2b. [tF YESJ Why did you choose not to install these items?
IRECORD RESPONSEJ
Installed Efficiency Measures
IREFER TO THE SPREADSHEET FOR "INSTALLED MEASURE.'' IF MORE THAN ONE
MEASURE INSTALLED, PLEASE CHOOSE MEASURE WITH LARGEST SAVINGSJ
13. Did the [INSTALLED MEASUREJ installed through the Program replace existing equipment
or was it a totally new installation?1. Replaced existing equipment2. Totally new [IF TOTALLY NEW, "PLEASE DESCRIBE" AND, SKIP TO l5J
98. Don't know
99. Refused
14. What was the operating condition of the equipment that the IINSTALLED MEASUREJ
replaced?1. Old equipment had failed or burned out2. Old equipment had problems, but still working3. Old equipment in working condition with no problems4. Expanding services or production line; wanted effrcient equip5. Other ISPECIFYJ
98. Don't know
99. Retused
The Cadnrus Group, lnc. I Energy Services 37
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 307 of 1365
Case No, PAC-E-14-07
neJ$??iE5?'B:$d{tr'
15. On a scale of 0 to 10, where 0 is not at all satisfied and l0 is very satisfied, how satisfied
would you say you are with the performance of the new [INSTALLED MEASUfuEJ?
IruECORD RESPONSEJ
98. Don't know
99. Refused
15a. Uf 15 <:51 Why do you say that?
[RECORD RESPONSEJ
98. Don't know
99. Refused
Operational Changes
STNTERVIEWER: RESPONDENT WILL RECEIVE ONLY ONE SET OF QUESTIONS
REFERRING TO OPERATIONAL CHANGES FOR A SINGLE MEASURE TYPE (LIGHTING,
WAC, CONTROL^S, OR OTHERJJ
16. At the time that you participated in the program, did you have an overall plan to increase the
energy efficiency of your operations?
16A.Did you change the manner in which you operated [MEASURE TYPE] after the new
IMEASURE TYPE] was installed?1. Yes2. No ISKIP rO 18J
98. Don't know
99. Refused
l6b. Were these changes part of the overall plan to increase the energy efficiency of your
operations?
1. Yes2. No [SK1P To 18J
98. Don't know
99. Refused
16c. What did you change?
IRECORD RESPONSEJ
3SThe Cadnrus Group, lnc. i Energy $ervices
E.hi bit fi:"YP:lTlfl :iilfJ
Case No. PAC-E-14{7
17. IASK IF 168 MENTIONS HOURS OF OPEMTIONJ Did you change the number of
operating hours or change the operation schedules since measures were installed?1. Yes2. No /SIUP TO 18J
98. Don't know
99. Refused
17a. Please explain what changes were made
[RECORD RESPONSEJ
18. Has theAlave any [INSTALLED MEASUREJ been removed since they were installed with
this program?1. Yes2. No ISrVP TO lg|
98. Don't know ISKIP TO 19J
99. Retused
18a. What was removed?
IRECORD RESPONSEJ
98. Don't know
99. Refused
18b. Why was it removed or replaced?
IRECORD RESPONSEJ
98. Don't know
99. Refused
18c. About when was it removed or replaced?
IRECORD RESPONSEJ
98. Don't know
99. Refused
The Cadrnus Group, lnc. / Energy $eruices 3g
lsqilic-orp
Rocky Mountain Power
Exhibit No. 5 Page 309 of 1365
Case No. PAC-E-14-07
ne#?fiB$?'B: !d'{tr'
19. How did installation of the [TNSTALLED MEASUREJ fit with planned replacement and/or
maintenance? Was any of this equipment scheduled for replacemenVupgrade before the
program?1. Yes [IF YES, PROBEJ2. No /SrUP TO 20J
98. Don't know
99. Refused
19a. Which equipment
IRECORD RESPONSEJ
98. Don't know
99. Refused
20. Was the installation of the JTNSTALLED MEASUREJ included your most recent capital
BUDGET BEFORE YOU PARTICIPATED IN THE PROGMM?
1. Yes2. No
98. Don't know
99. Refused
21. When you installed the new IINSTALLED MEASUREJ, did you expect savings on:
2ld. IASK IF 2]a: YESJ Do the electric energy savings meet your expectations?
3. Yes [SKIP TO 22)4. No
98. Don't know
99. Refused
Yes No Don't Know Refused
2la. Electricity?
2lb. Water?
21c. Natural Gas?
40The Sadmus Group, lnc. I Energy Services
-l_r-"ili9qP
Roclq Mountain Po,ver
Exhibit No. 5 Page 310 of 1365
Case No. PAC-E-14-07
ueffi'BS'B:?#|tr'
2le. IASK IF 2]a :NoJ When do you expect these energy savings?
l. Immediately2. Within the next 6 Months ISK]P TO 22J3. Within the next year [SKIP fO 22J4. Within the next two years ISKIP TO 22J5. Never
98. Don't know ISKIP TO 22J
99. Retused ISKIP TO 22J
zlf. Why do you not expect savings from the IINSTALLED MEASUREJ in the future?
[sKrP TO 22J
22. Are there any other benefits that you anticipate?
IPROBE IF NEEDED: HAVE YOU OBSERVED ANY CHANGES IN LEI/EL OF
PRODUCTION OR SALES? PRODUCT QUALITYU
IRECORD RESPONSEJ
23. How satisfied are you with the final cost to you of the [TNSTALLED MEASUREJ?
Please use a scale from 0 to 10, with 0 being extremely dissatisfied and l0 being extremely
satisfied.
IRECORD RESPONSEJ
98. Don't know
99. Refused
23a. IIF Q23<:5/ Why do you say that?
IRECORD RESPONSEJ
98. Don't know
99. Refused
24. How satisfied are you with the performance of the IINSTALLED MEASUREJ?
Please use a scale from 0 to 10, with 0 being extremely dissatisfied and 10 being extremely
satisfied.
IRECORD RESPONSEJ
98. Don't know
99. Refused
The Cadnrus Group, lnc. / Energy $ervices 41
lqqlic-otp
Roclry Mountain Power
Exhibit No. 5 Page 31 1 of 1 365
Case No. PAC-E-14-07
ne#??iBf;lBl ldIff'
24a. llf 24 <:51 Why do you say that?
IRECORD RESPONSEJ
Freeridership and Market Effects
[NOTE: ONLY ASK FOR SAME MEASURE AS PRIOR QUESTIONSJ
25. On a scale from 1 to 10, how important were the following factors in deciding which measures to
install:
Factor Score
A. lnformation provided by
program staffon measure
savings
B. Information on payback for
the measure
C. The oroiect incentive
D. Familiarity with these
measures
E. Had purchased these
measures in the past
26. Regarding the installation of [INSTALLED MEASURE/MEASURE(S)J, would you have
installed the [MEASURE/ANY OF THE MEASURES] without the incentive?1. Yes2. No IIF 'NO', ASK 827, THEN SKIP fO 830J
98. Don't know
99. Refused
27. Before the incentive program, had you previously installed the same type of [MEASURE] without
participating in a program?
1. Yes
2. No
98. Don't know
99. Refused
28. Without the program, would you have installed units to the same level of efficiency?
1. Yes
2. No
3. Don't know
4. Refused
The Cadrnu$ Group, lnc. i Energy Ser*ices 42
PacifiCorp
Roclry Mountain Po rer
Exhibit No. 5 Page 312 of 1365
Case No. PAC-E-14-07
oeHffiEflB:2d1tr"
29. Without the program, would you have installed all of the measures or some of the measures?1. All2. Some3. Don't know4. Refused
29a- llf 29:Some] Which measures would you have installed?
_ IRECORD RESPONSEJ
30. Without the program, would you have installed these measures...
l. ln the same year?
2. ln one to two years?
3. In three to five years?
4. More than five years out?
5. Don't know6. Refused
31. Would you have installed the exact same unit(s) if the amount of the program incentive
was less than the current value?
l.
2.
J.
4.
Yes
No
Don't know
Refused
32. How much less? Would you say...l. 25o/oless2. 50% less3. 75% less4. Don't know5. Refused
33. In your opinion was the difference in price between the energy efficient models and the
conventional models:
1. Very dramatic
2. Somewhat dramatic but significant
3. Not at all different
4. Don't know5. Refused
The Cadrnus Group, lnc. i Energy Services ie
PacifiCorp
Roclq Mountain Power
Exhibit No. 5 Page 31 3 of 1 365
Case No. PAC-E-14-07
ne#??iBS'B: !#{tr'
Energy Efficiency Decision Making
Next, I would like to ask you some questions about the decision making process in regards to
energy efficiency purchases and upgrades.
34. Using a 0 to l0 rating scale, where 0 means not at all important and 10 means extremely
important, please rate how important energy efficiency is to the operations and
management of your company?
IRECORD RESPONSEJ
98. Don't know
99. Refused
34a. Why do you say that?
35. Do you have sufficient in house technical resources in house to address the management of
energy and water costs?
1. Yes
2. No
98. Don't know
99. Refused
35a. IIF 35:NOJ For this project, as [PACIFIC POWER/ROCKY MOUNTAN POWER] or
Nexant able to provide you with the needed technical assistance?
IRECORD RESPONSEJ
Spillover
36. Besides installing the measures through this program, since this project have you made any
other energy efficiency improvements or purchases on your own without any
assistance from a utility or other organization?l. Yes
2. No 1SrKlP TO 3U
98 Don't know ISKIP TO 3U
99 Retused ISKIP TO 3U
36a. JtF 36 : YESJ What did you purchase or install?
IRECORD RESPONSEJ
AA.t*lThe Cadmu* Group, lnc. I Energy $ervices
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 314 of 1365
Case No. PAC-E-14-07
neHdlffBflB: ld'ttr"
36b JtF 36 : YESJ I'm going to read a statement about the equipment that you purchased on
your own. On a scale from 0 to 10, with 0 indicating that you strongly disagree, and 10
indicating that you strongly agree, please rate the following statement.
"My experience with the [ProgramJ itfluenced my decision to install other high
efhciency equipment on my own."
IRECORD RATINGJ
98. Don't know
99. Refused
Interaction with IPACIFIC POWER/ROCKY MOUNTAIN POWER] or 3rd Party Staff
We are also interested in leaming more about your interactions with the Program staff
37. How many people did you work with throughout your participation in the Program? This
would include people from Nexant, IPACIFIC POWER/ROCKY MOUNTAIN POWER],
contractors, etc.
Number of people
ISK]P TO 4t rF :0J
38. In what capacity did they work with you?
IPROBE IF NEEDED. WAS IT PROJECT MANAGERS, ACCOUNT KEPS, THIRD PARTY
STAFF, CONTMCTORS; MULTIPLE RESPONSEJ
1. _IPACIFIC POWER/ROCKY MOUNTAIN POWERI Account
Representatives
2.-tPACIFICPowER/RoCKYMoUNTAINPowER]EnergyEfficiency
Project Managers
Nexant Energy Efficiency Project Managers
lnstallation Contractors5. External Consultant
6.Other ISPECIFYJ
IRECORD COMMENTSJ
39. Please describe your overall experience working with these people in relation to thisproject._ IRECORD RESPONSEJ
4.
The Cadmus Group, lnc. i Hnergy $ervices AE
o
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 31 5 of 1 365
Case No. PAC-E-14-07
nedfi??iil&'B: !d'{ff'
Satisfaction
40. Would you participate in the Program again?1. Yes2. No
40a [IF 40 : NOJ Why not?
IRECORD RESPONSEJ
41. If you could change anything about the Program, what would you change?
IRECORD RESPONSEJ
98. Don't know
99. Refused
42. Using a scale from 0 to 10, with 0 being extremely dissatisfied and 10 being extremely
satisfied, how satisfied are you with your overall experience with the Program?
IRECORD RESPONSEJ
98. Don't know
99. Refused
42a. IIF 42 <:5J Why do you say that?
Organ izationa! Data/Fi rmog raph ics
I have a few last questions about your business or organization
43. Approximately, what percent of your total annual operating costs does your electricity bill
represent?
IRECORD RESPONSEJ
98. Don't know
99. Refused
44. Approximately, what percent of your total annual operating costs does your natural gas bill
represent?
IRECORD RESPONSEJ
98. Don't know
99. Refused
46The Cadnrus Group, lnc. I Energy $ervices
PacifiCorp
Roclq Mountain Po$,er
Exhibit No. 5 Page 316 of 1 365
Case No. PAC-E-14-07
neIS??iES'B:2d'1tr"
45. Approximately, what percent of your total annual operating costs does your water bill
represent?
IRECORD RESPONSEJ
98. Don't know
99. Refused
46. How many people does your firm employ?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Thank you for your time. Your opinions are very valuable to this research for [PACIFIC
POWER/ROCKY MOUNTATN POWERI.
The Cadrnus Group, lnc. / fnergy $ervices 47
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 3'17 of 1365
Case No. PAC-E-14{7
ueH#B{?'B: ld)ttr'
Appendix B. Nonparticipant Suruey
Company:
Name:
Title:
City:
FinAnswer Express Nonparticipant Interview Guide
Telephone:
Cell phone:
Fax:
State:zip:
Interview date:Time:
SIC Code (a-digit) NAIC:
Hello, my name is from , calling on behalf of IPACIFIC
POWERyROCKY MOUNTAIN POWERI. We are conducting a study on behalf of IPACIFIC
POWER/ROCKY MOUNTAIN POWER] regarding energy efficiency programs. May I speak with
[designated respondentJ or with the person who is responsible for overseeing energy
management for your organization?
[IF DIRECTED TO A DIFFERENT RESPONDENT, REPEAT INTRODUCTIONJ
My questions are for research pu{poses only. We are interested in your opinions to help improve
our programs, and understand how to assist customers in saving money on their utility bills.
Your individual answers will be used by [PACIFIC POWER/ROCKY MOUNTAIN POWER] to
evaluate energy efficiency programs. As a Thank Youfor your assistance, ot the end of the
survey you we would like to offer you a $50 gift card, which will be mailed to you [IF
RESPONDENT ASKS HOW LONG THE SURVEY IS, SAY: ,.APPROXIMATELY 15
MINUTES."J
[If a customer asks if this is the Total Quality Service survey, or states that he has recently
participated in the Total Quality Service survey, say 'this is a separate survey about our energy
efficiency programs.']
[If customer wants to verifu the validity of the survey, tell them that they are welcome to contact
Nancy Goddard, PacifiCorp Program Manager, at [phone].
48The Cadrnus Group, lnc. i Energy Services
PacifiCorp
Screening:
52. First, I need to validate my records.
53. Which electric company provides electric power to your business?
Rocky Mountain Poirer
Exhibit No. 5 Page 318 of 1365
Case No. PAC-E-14-07
ne#d??i#'lBl 2d'|tr'
t Pacific Power/Rocky Mountain Power CONTINUE
2 OTHER.... .....TERMINATEAND TALLY
98 DON'T KNOW .RETURN TO Q.B AND RESCREEN
lntroduction
6. Which of the following best describes your company's primary activities?
1. Manufacturing
2. Retail
3. Dairy / Agricultural
4. Finance and Insurance
5. Food Processing
6. RefrigeratedWarehouse
7. Professional, Scientific, and Technical Services
8. EducationalServices
9. Health Care
10. Public Administration
11. Arts, Entertainment, and Recreation
12. Accommodation
13. Food Services
14. Real Estate
1s. Other ISPECIFYJ
49The Cadmu$ Group, lnc. / Energy Services
teqiflcqrp
Rocky Mountain Power
Exhibit No. 5 Page 319 of 1365
Case No, PAC-E-14-07
neJ$??iil6"lB:!d'{tr'
Participation
7. Have you heard of the [PACIFIC POWERyROCKY MOUNTAIN POWER] FinAnswer
Express Program?1. Yes [CONTINUEJ2. No [SK1P TO 1LJ
98. Don't know
99. Refused
8. How did you learn about the FinAnswer Express Program?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
1. Contacted by my [PACIFIC POWER/ROCKY MOUNTAIN POWER] account
representative or other [PACIFIC POWER/ROCKY MOUNTAIN POWER] staff2. Contacted by program representative [IF YES ASK'Do you remember what
company they were from?']3. Program sponsored conference orworkshop4. Programsponsoredtechnologydemonstration5. Program sponsored integrated audit6. Trade Publication7. Marketing by Trade Ally, vendor or contactor8. Firm approached/contacted by Trade Ally, vendor or contractor9. Word of mouth; from another business colleague
10. Through a trade organization or professional organizatior/association
1 1. Through printed material or outreach materials sent by the Program
12. At a trade show
13. Through family, friend, or neighbor
14. Participation in other [PACIFIC POWER/ROCKY MOUNTAIN POWER] Programs
15. Past Program participants
16. Intemet research/found Program on [PACIFIC POWER/ROCKY MOUNTAIN
POWERI website
Other ISPECIFYJ
Don't know
Refused
9. What are the reasons you have not had the opportunity to participate in the Program?
IDO NOT READ RESPONSES; MARKALL THAT APPLYJ
IRECORD RESPONSEJ
98. Don't know
99. Refused
10. Regarding the FinAnswer Express program, have you either begun participation in the
program and dropped out, or had a project application rejected?
1. Dropped out
17.
98.
99.
The Cadmus Group, [nc. I Energy $errrices 50
PacifiCorp
Rocky Mountain Power
Exhlbit No. 5 Page 320 of 1365
Case No. PAC-E-14-07
oel$??iBflB: !d,{tr'
2. Applicationrejected
3. No [SrKlP TO 10J
98. Don't know [SKIP TO 10J
99. Retused ISKIP rO 10J
Program Drop-Outs and Rejected Applications
ASK THIS SECTION ONLY IF RESPONDENT IS: (1) PROGMM DROP-OW (2) REJECTED
APPLICATION
I l. Thinking back to when you were first considered the Program, were there any aspects of the
Program that initially caused you concern?
1. Yes
2. No ISrVP TO SDJ
98 Don't know ISK]P fO SDJ
99 Retused [SKIP TO SDJ
6a. What caused your concem?
IRECORD RESPONSEJ
6b. Was this issue resolved?
1. Yes
2 . No ISrVP TO 5DJ
98 Don't know ISKIP TO SDJ
99 Retused ISKIP TO 5DJ
6c. How was it resolved?
IRECORD RESPONSEJ
ASK ONLY IF RESPONDENT IS A PROGMM DROP-OW
6d. Why did your business drop out of the Program?
IRECORD RESPONSEJ
The Cadnrus Group, lnc. / Energy Services 51
PacifiCorp
Roclq Mountain Power
Exhibit No. 5 Page 321 of 1365
Case No. PAC-E-14-07
ueHd??iBS'B: id'{tr'
ASK ONLY IF RESPONDENT'S APPLICATION WAS REIECTED
6e. Do you know why your application to participate in the progftIm was denied?
IfuECORD RESPONSEJ
ASK FOR BOTH GROUPS
6f . Was the underlying problem resolved to your satisfaction? If not, why not?
We are also interested in learning more about your interactions and experience with the Program
staff
12. How many people did you work with during your time with the Program? This would
include people from Nexant, IPACIFIC POWER/ROCKY MOUNTAIN POWER],
contractors, etc.
number of people
O 1i. Who worked with you with you on this project?
IPROBE IF NEEDED. WAS IT PROJECT MANAGERS, ACCOUNT REPS, THIRD PARTY
STAFF, CONTMCTO RS ; MULTIP LE RESP ONSEJ
7. IPACIFIC POWER/ROCKY MOLINTAIN POWER] Account
Representatives8. IPACIFIC POWER/ROCKY MOUNTAIN POWER] Energy Efficiency
Project Managers9. Another Energy Efficiency Project Managers IIF YES ASK'Do you
remember what company they were from.']
10. _ Installation Contractors
I l. External Consultant12. Other ISPECIFYJ
[RECORD COMMENTSJ
14. If you could change anything about the Program, what would you change?
IRECORD RESPONSEJ
98. Don't know
99. Refused
O 15. Did your company participate in the FinAnswer program before 2006? After 2008?
The Cadmus Group, lnc. I Hnergy Services 52
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 322 of 1365
Case No. PAC-E-14-07
ne$d?fiE$Bl!#tff"
lnstalled Efficiency Measures
16. In the past year, have you installed any energy efficiency measures in your building(s)?3. Yes [CONTINUEJ4, No //FNO SKIP TO ENERGY EFFICIENCY DECISION MAKINGJ
98. Don't know
99. Refused
lla. What measures have you installed? IDO NOT READ. RECORD ALL EQUIPMENT,
LIGHTING, CONTROLS, OTHER ITEMS INSTALLEDJ
l. Lighting2, HVAC3. Controls4. VFD5. Compressed Air measures6. Other ISPECIFYJ98. Don't know
99. Refused
I lb. Did you receive a financial incentive or tax credit for installing this equipment?
1. Yes [Speciff the incentive and/ or tax credit amount, and the agency/program
offering the incentive/tax credit.]
No /IFNO SKIP TO ENERGY EFFICIENCY DECISION MAKINGJ
Don't know
Refused
17. Why did you decide to install this equipment?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
1. To save money on electric bills
2. To obtain a rebate; Program incentive
3. It was scheduled for replacement/upgrade
4. To replace old equipment
5. To replace broken equipment
6. To acquire the latest technology7. To reduce maintenance costs
8. Because [PACIFIC POWER/ROCKY MOLINTAIN POWER] account manager
suggested it
9. Because Nexant engineer suggested it
10. Because we had funds available in this fiscal year
1 1. Because we lose funds if we don't replace it now.
12. Because the Program was sponsored by IPACIFIC POWER&.OCKY MOUNTAIN
POWERI
13. Previous experience with other [PACIFIC POWER/ROCKY MOUNTAIN POWER]
Programs
2.
98.
99.
The Cadmus Group, lnc. / Energy $ervices 53
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 323 of 1 365
Case No. PAC-E-14-07
ne#d??iBfJB:!#{tr'
14.
15.
r6.
t7.
18.
19.
20.
2t.
98.
99.
To help protect the environment
To save energy
Recommended by Program contact
Recommended by contractors/trade allies
Recommended by another word of mouth
Recommended by family, friend, or neighbor
Part of a broader remodeling or renovation
Other ISPECIFYJ
Don't know
Refused
l2a . Have you taken any other actions to save energy in your buildings?
IRECORD RESPONSEJ
18. What actions have you taken?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Energy Efficiency Decision Making
Next, I will ask some questions about the decision making process in regards to energy
effrciency purchases and upgrades.
19. Using a 0 to 10 rating scale, where 0 means not at all important and l0 means extremely
important, please rate how important energy efficiency is to the operations and management
of your company?
IRECORD RESPONSEJ
98. Don't know
99. Refused
20. Why do you say that?
IRECORD RESPONSEJ
2l . Do you have sufficient in house technical resources to address the management of energy and
water costs?
1. Yes /SK1P NEXT SUESTIONJ2. No
98. Don't know
99. Refused
The Cadnrus Group, lnc. i Energy Serrrices 54
PacifiCorp
Rocky Mountain Po,er
Exhibit No. 5 Page 324 of 1365
Case No. PAC-E-14-07
oeI[??iE&'B: !#{tr'
Organ izational Data/Firmog raph ics
I have a few last questions about your business or organization
22. Approximately, what percentage of your total annual operating costs is spent in electricity
bills?
[RECORD RESPONSEJ
98. Don't know
99. Refused
23. Approximately, what percentage of your total annual operating costs is spent in natural gas
bills?
IRECORD RESPONSEJ
98. Don't know
99. Refused
24. Approximately, what percentage of your total annual operating costs is spent in water bills?
_IRECORD RESPONSE\
98. Don't know
99. Refused
25. How many people does your firm employ?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Thank you for your time. Your opinions ilre very valuable to this research for [PACIFIC
POWER/ROCKY MOUNTATN POWERI.
The Cadrnus Group, lnc. / Energy Services 55
PacitiCorp
1.
2.
aJ.
4.
Appendix C Staff lnterview Guide
FinAnswer Express Program Discussion Guide
Name
Title
Company
Program
Date
Program Overview
Can you briefly describe how the progftrm operates?
a. What is the program theory - how do you expect the programs to change the way
that the target market behaves with respect to energy efficiency?
How has the program evolved or changed since the last evaluation in 2004?
How do you coordinate activities intemally? [marketing, service delivery, work with
TAs, etc.]
Are you providing training to:
a. PacifiCorp staff
b. Implementers
c. Trade allies
d. What feedback have you gotten back?
5. What improvements could be made in the administration of the programs?
Application process
6. Could you please describe your understanding of the application process:
a. How do the participants enter the program?
b. What issues are there?
Eligibility criteria and the verification process
7. Please describe the verification process?
Rocky Mountain Power
Exhibit No, 5 Page 325 of 1365
Case No. PAC-E-'14-07
ne$?fi$6?'B: !d'{tr'
The Cadnrus Group, lnc. I Energy Services 5S
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 326 of 1 365
Case No. PAC-E-14{7
neI$??rB{?'B: ?d'|ff"
Participant eligibility
What if they are not eligible?
Marketing
8. Do you do anlthing to promote the program? [What marketing and outreach activities
have been and are being conducted? What's worked best?]
Savings estimation techniques
9. How are savings estimated for the program as a whole and for individual projects?
10. Are the estimations generally felt to be accurate? Is there a way to improve the manner in
which savings are calculated?
11. How are savings verified for the individual projects?
What materials had to be submitted with the applications [invoices, drawings]?
Who received the applications and what the steps were for reviewing and
approving applications and setting up payments?
c. What post-inspections are required?
Participant interaction and satisfaction
12. What aspects of the programs do customers seem to be most interested in or most
satisfied with?
a. Any concerns? How were they addressed?
Program data collection
13. Who is responsible for collecting and tracking participation data?
a. How effective and accurate is the data-tracking and data collection system?
b. Are data entered and reported in a timely fashion?
a.
b.
a.
b.
The Cadmus Group, lnc. I Hnergy $ervices
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 327 of l365
Case No, PAC-E-14-07
neil$?ffB$?'B: !$Itr'
c. Have there been any diffrculties with the data tracking systems?
14. Have the implementers had any problems meeting the tracking and reporting
requirements?
15. Would you recommend any changes to the procedures?
Trade AIIies - Communication
16. Is PacifiCorp involved in the recruitment or management of Trade Allies, retailers or
contractors?
a. Describe the relationship between these parties
17. How frequently do you contact people, and how is the communication carried out?
18. How often do trade allies contact you?
19. Have you had any particular challenges in working with trade allies?
20. How are their problems and questions dealt with?
21. What kinds of things have been done or are being planned to identiff trade allies and get
them involved?
22.What hasftras not worked'well?
23. How would you change or improve communications, either within the program, or with
trade allies?
Implementation Barriers
24.Has the level of program participation met your expectations?
a. Why do you think this has been the case?
25.Have any challenges resulted from perceptions or attitudes about the value of the
progftrm among the target population? If so, what?
58The Cadnrus Group, lnc. i Energy $ervices
PacifiCorp
Roclq Mountain Power
Exhibit No. 5 Page 328 of 1 365
Case No. PAC-E-14-07
peJS??iBSBl2d)lff'
26. How have you dealt with those perceptions and auitudes?
27.How about any challenges resulting from perceptions or attitudes about the value of the
programs among the vendors?
a.How have these been dealt with?
Close
28. What would you say are the program's strongest points?
29.What are its weakest points?
30. Other than what we've discussed above, what would you change about the program?
The Cadnrus Group, lnc. i f;nergy $ervices 5S
Pq_*:licqfp
Rocky Mountain Power
Exhibit No. 5 Page 329 of 1365
Case No. PAC-E-I4-07
ne#??i$6?'B: $d{ff'
Appendix D. Market Actor Interview Guide
Market Actor Interview Guide - FinAnswer Express Program
Organization:
Telephone
my name is from The Cadmus Group, calling on behalf of:
[Utah or Idaho] Rocky Mountain Power
[Washington] Pacific Power
[Rocky Mountain Power, Pacific Power] is evaluating its FinAnswer Express
program and would appreciate your input. This survey is for research purposes only
and this is not a marketing call. Your responses will remain confidential. The
questions focus on how the program operated in the 2006-2008 time period. Do you
have a moment to answer questions about your experience with the program?
[If "No - Not a convenient time," ask if Respondent would like to 1. Start now and do part
of the survey, or 2. Arrange a more convenient time we can call them at home. Emphasize
thatl
"It is important for Rocky Mountain Power/Pacific Power to include your opinions in this
study so they can serve your needs better."
[If 6'Noo'- Arrange callback]
Program Overview
1. When did you first start providing services for the program?
What did you see as the purpose of the program?
Who else was involved in carrying out the program? How were they involved? [PROBE on
contractors, engineering firms, energy services companies, retailers, and equipment
manufacturers.]
4. Have there been changes over time in the services or measures people are interested in?
What are the changes?
Program Entry
5. How did a prospective customer find out about the program?
2.
aJ.
The Cadrnus Group' lnc. i Energy $ervices sCI
PacifiCorp
Rocky Mountain Po\ryer
Exhibit No. 5 Page 330 of 1365
Case No. PAC-E-14-07
neUd?fiB#B: ld'ttr'
6. Who provided program leads? [DO NOT READ]
a. Program staff
b. Nexant (program implementer)
c. Engineering firms,
d. Energy services companies
e. Retailersf. Other
Participant interaction and satisfaction
7. Did customers express any concerns about the program? How were the concerns addressed?
Pacific Power/Rocky Mountain Power Communication
8. Did your company have any particular challenges in working with Rocky Mountain Power?
9. How were these challenges dealt with?
Implementation Barriers
10. Did any challenges result from perceptions or attitudes about the value of the program
among the Pacific Power/Rocky Mountain Power customers? If so, what were they?
11. How did you deal with those perceptions and attitudes?
12. Did anl.thing else make it difficult for you to bring in participants and/or ca:ry out program
requirements? If so, what?
13. How have you dealt with those perceptions and attitudes?
Program data collection
14. Please describe the program's data collection and tracking requirements.
a. Were there any difficulties meeting those requirements?
15. Would you recommend any changes to the procedures?
CIose
The Cadmus Group, lnc. I Energy Services 61
Roclry Mountain Power
Exhibit No. 5 Page 331 of 1365
Case No. PAC-E-14-07
PacifiCorp
16. Other than what we've discussed above, what would you have changed about the program
as it operated in 2006 through 2008?
17. What would you change about the program as it is currently operated?
18. Is there anything else you would like to add?
neI$??iB6ilB: !#{tr'
The Cadrnus Group, lnc. I Energy $ervices at
PacifiCorp
Roclq Mountain Power
Exhibit No. 5 Page 332 of 1 365
Case No. PAC-E-14{7
oe#lirt6?'B:2d1tr'
Appendix E. FinAnswer Express Process Flow
Diagrams
Lighting and non-lighting process flow diagrams are provided under separate cover.
The Cadrnus Group, lnc. / Energy $ervices 63
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 333 of 1 365
Case No. PAC-E-'14-07
DeI$?fiLA?Bir#{ff'
Appendix F. FinAnswer Express Evaluation Plan
Provided under separate cover.
The Cadmus Group, lnc. / Energy $ervices 64
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 334 of 1 365
Case No. PAC-E-14{7
oeJ$?iB6ilB: !d{tr"
Appendix G. Project Reports
Provided under separate cover. (Some Project numbers are duplicative since there were multiple
incentives filed under singular invoices from the implementation contractor)
60731
60731
60731
60731
60732
60732
60732
60732
60733
60733
60733
60734
60734
60734
60734
60735
60735
60735
60735
60736
60736
60736
60736
60743
60789
60790
60796
60812
60812
60847
60847
60848
60878
60880
60881
60909
60909
60909
60909
60916
60963
60963
60963
60964
60964
60964
60964
60964
60982
60983
61021
61021
61022
61022
61 023
61 036
61 037
61 037
61 037
61 069
61 069
61 069
61 069
61 069
61 070
61 070
61156
61157
61157
61157
61157
61157
61157
61157
61171
61175
61 189
61 189
61189
61189
61189
61189
61189
61189
61189
61197
61198
61198
61 198
61 199
61 199
61 199
61 199
61230
61231
61231
61231
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61231
61231
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61231
61278
61278
61279
61279
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61318
61318
61318
61318
61318
61318
61318
61318
61318
61318
61327
61327
61344
61344
61344
61344
61344
61 358
61 358
61 358
61 358
61 358
61358
61 358
61 358
61358
61414
61414
61414
61414
61414
61414
61414
61428
61428
61428
61428
61428
61428
61428
61428
61430
61435
61436
61436
61436
61436
61469
61469
61469
61469
61469
6'1469
61 506
61 507
61 507
61 507
61 507
61 507
61 507
61510
61511
61511
61511
61511
6151 1
6151 1
6151 1
61 530
61 536
61536
61 537
61 537
61 537
61 537
61 537
61 537
61 548
61 548
61 549
61 549
61 549
61 549
6't549
61552
61559
61 559
61 559
61559 61655
61560 61655
61560 6165561560 6168361560 61683
61571 61683
61571 6168361612 61683
61612 6170461613 6170461613 6172361613 61730
61613 61730
61613 6173061613 61730
61613 61730
61613 6173061613 6173061613 61730
61613 6173061613 6173061616 61730
61632 6173061632 61730
61632 61730
61632 6173061632 61730
61632 61730
61654 6173061654 6173061655 61730
61655 6173161655 61731
61731
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61 731
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61 731
61731
The Cadmus Group, lnc. i Energy Services 65
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 335 of 1365
Case No. PAC-E-14-07
ne#?ffBfJB:E#itr'
Appendix H. Measure Life Methodology
Measure lifetimes by general measure type were determined for various states and program years
(2005-2008) for the following PacifiCorp progftIms:
. f,nergy Finanswero Finanswer Express
o Self Directiono Retrocommissioning
This analysis was performed in an Excel workbook. Comprehensive economic useful life (EUL)
information for the various individual measures in the portfolio, including sources, were
compiled on a master sheet named "Measure Life." Some of the sources used were DEER 2008,
ACEEE, and the "Measure Life Report" prepared by GDS Associates in2007. When multiple
values for the same measure were available, an average was taken. For example, the measure life
of air compressor improvements in the GDS report was l3 and 15 years for retrofit and new
construction, respectively. Therefore, the final average measure life used in this analysis was 14
years for air compressor improvements. Where measure rurmes in the data sets or in the sources
were open to interpretation, comments were added to clarify to what measure was being
referenced.
Project data, such as measure ntlme, type, and savings, were organized as sets on individual
worksheets representing each state/program/year combination. Measure type includes the
following main categories (shown with their respective sources):
For each data set, the EUL for the applicable measure types was determined by weighting the
EULs of component measures by total kWh savings. Using the Idaho Energy Finanswer Express
2008 project data as an example, there are 3 measure types (Lighting, HVAC, and Motors).
Lighting measures include Package, Package Trade Ally, and Other. Each of these individual
measures has an associated lifetime (14, 14, and 15, respectively). To determine what the overall
EUL should be, the total kWh savings for each measure from this data set was used to weight the
EULs. This process was repeated for the HVAC and Motor measure types to complete the
analysis.
Refrigeration
Lighting
HVAC
Controls
Motors
Additional Measures
Air Compressors
Building Shell
Nonlighting
Hot Water
Traffic Signals
x
x
x
x
x
x
x
x
x
x
x
The Cadmus Group, lnc. i Hnergy Serrices bt]
Rocky Mountain Po\ rer
Exhibit No. 5 Page 336 of 1 365
Case No. PAC-E-14-07
oeI$??iE#B:ld,ttr'
Appendix l. Participant and Nonparticipant Survey
Results
Provided under separate cover.
The Cadmus Group, lnc. I Energy $ervices 67
Ir-.i[9-r-ry
Rocky Mountain Power
Exhibit No. 5 Page 337 of I 365
Case No. PAC-E-14-07
ne#??iB6?"#: rd'{tr'
Appendix J. Freeridership Analyses
Freeridership quantifies the percentage of participants who report they would have installed a
measure in the absence of the progam.
Energy FinAnswer Express Program
Freeridership survey data was analyzed for the FinAnswer Express program using a scoring
matrix approach. This s approach is acknowledged in the National Action Plan for Energy
Efficiency: Model Energy Efficiency Program Impact Evaluation Guide15 (Guide).
A survey was designed to understand why customers installed a given measure, and the influence
the program had over those decisions.
In conducting surveys with the battery of questions, Cadmus randomly selected customers
participating in the FinAnswer Express program. Results of the survey questions were used in a
scoring matrix to determine each participant's freeridership score between 0 and 100%.
There are six core questions asked in the survey are written to obtain objective responses and are
used in the freeridership scoring matrix:
o Would the participant have installed the measure without the program?
. Had the participant already ordered or installed the measure before leaming about the
program?
o Would the participant have installed the measure to the same level efficiency without the
program incentive?
o Would the participant have installed the same quantity of measures without the program?o In absence of the program, when would the respondent have installed the measures?o Was the measure included in included the participant's most recent capital budget?
Cadmus has developed a transparent, straightforward matrix approach to assign a score to all
participants based on their responses.
Pattems of responses to these questions are assigned freerider scores, and confidence and
precision estimates are calculated based on the distribution of the scores.
The table below shows the scoring matrix that was used for FinAnswer Express. This matrix is
expanded from the general format of the scoring matrix included in the Guide. If a respondent
had a non-response, "Don't Know" or "Refused", the respondent was assigned a "Partial" for
that given question. This allows for respondents who had a non-response, "Don't Know" or
"Refused" answer for a question to be left in the analysis sample.
" http://ww*.epa.gov/cleanenergy/documents/suca,ievaluation_guide.pdf
The Cadmus Group, lnc. i Hnergy $ervices 6S
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 338 of 1365
Case No. PAC-E-14-07
WtnesF: KathA/n fijJlyrlesuecernoer 0, ru'ru
Yes Partial x x x x /esPartial 100.00%
Yes Yes x x x x /esYes 100.00%
Partial Yes x x x x )artialYes '100.00%
No x x x x x ,lo 0.0oo/o
Panial No x x x x )artialNo 0.000/0
Partial Partial x x x x ,artialPartial 25.OOo/
Yss No NO x x /esNoNo 0.00%
Yes No Partial NO NO Yes /esNoParlialNoNoYes 0.00o/o
Yes No Partial No No Parlial 'esNoPartialNoNoPartial 0.00%
Yes No Partial No No No fesNoParlialNoNoNo 0.00o/o
Yes No Partial No Partial Yes r/asNoPartialNoPartialYes 0.00%
YBS No Partial No Partial Partial /6sNoPartialNoPartialPartial 0.00%
Yg6 No Partial No Parlial No ,/esNoPartialNoPartialNo 0.000/"
Yes No Partial No Yes Yes /esNoPartialNoYesYss 12.500k
Yes No Partial No Yes Partial /esNoPartialNoY6sPanial 0.00o/o
Yes No Partial No Yes No /esNoPartialNoYesNo 0.00o/o
Y6s No Partial Partial NO Yes /esNoParlial PartialNoYes 0.00o/o
Yes No Partial Partial No Partial /esNoPartialPartialNoPartial 0.00%
Yes No Parlial Partial No No f 6sNoPartialPartialNoNo 0.00%
Yes No Partial Partial Partial Yes r/6sNoPartialPartialPartialYes 0.00%
Yes No Partial Partial Partial Partial r/esNoPartialPattialPartial Partial 0.00%
Yes NO Partial Pailial Partial No 'esNoPartialPartialPariialNo 0.00o/o
Yes No Partial Partial Yes Yss /esNoPartialPartialYesYes 12.ilo/
Yas No Partial Partial Yes Partial /esNoPanialPartialYesPartial 0.00o/o
Yos No Partial Partial Yes No f esNoPanialPartialYesNo 0.00P/"
Yes No Partial Yes No Yos /esNoPartialY6sNoYos 0.00P/"
Yes No Panial Yes No Partial f ssNoPartialYesNoParlial 0.00%
Yes No Partial Yes No No r/esNoPartialYesNoNo 0.00%
Yes No Partial Yes Partial Yes |/esNoPartialYesPartialYes 12.soP/o
Yes No Partial Yes Partial Parlial /osNoPartialYesPartialPartial 0.00%
Yss No Parlial Yes Partial No /esNoParlialYosPartialNo 0.000/0
Yes No Padial Yes Yes Yss /esNoPartialYesYesYes 25.OOYo
Yes NO Partial Yes Yes Partial /ssNoPartialYesYesPartial 12.50o/o
Yes NO Partial Yes Yes No /ssNoParlialYesYesNo 0.0oo/o
Yes No Yes No No Yes fasNoYesNoNoYes 0.00o/o
Yes No Yes No No Partial rosNoYesNoNoPariial 0.00o/o
Y6s No Yes No No NO /esNoYesNoNoNo 0.00o/o
Yes No Yes No Partial Yes rosNoYesNoPartialYes 0.00%
Yes No Yas No Partial Partial f esNoYesNoPartialPartial 0.Offlo
Yes No Yes No Parlial No /esNoY6sNoPartialNo 0.00%
Yes No Yes No Yes Yes /esNoYesNoYesYas 0.00%
Yes No Yes No Yes Partial /osNoYasNoYesPartial 0.00%
Yes NO Yes No Yes No /esNoYesNoYesNo 0.00%
Yes NO YeS Partial No Yes fesNoYesPartialNoYes 0.00o/o
Yes No Yes Partial No Partial /esNoYesPariialNoParlial 0.00o/o
Yos No Yes Partial No No /esNoYesPartialNoNo 0.00o/o
Y6s No Yes Partial Partial Yes /esNoYesPartialPartialYos 12.50o/o
Yes No Yss Partial Partial Partial /6sNoYesParlialPartaalPartial 0.00%
Yes No Y6s Partial Partial No /6sNoYssPartialPartialNo 0.00o/o
Yos No Yes Partial Yes Yes /esNoYesPartialYesYes 25.Wk
Yes No Yes Partial Yes Partial /esNoYesPartialYesPartial 12.5@k
Yes NO Yes Partial Yes No /esNoYesPartialYesNo 0.00o/o
Yes No Yes Yes No Yes r/esNoYesYesNoYes 0.00o/o
Yes No Y6s Yes No Partial /esNoYesYesNoParlial 0.00%
Yes No Yes Yes NO NO /esNoYssYesNoNo 0.00%
Yes No Yes Yes Partial Yes /esNoYesYesPartialYes 25.0OYo
Yes No Yes Yes Partial Partial /esNoYesYesPartialPartial 12.500k
Yes No Yes Yes Partial No /ssNoYesYesPartialNo 0.00o/o
Yos No Yes Yes Yes Yes /esNoY6sYesYesYas 50.00%
Yes No Yes Yes Yes Partial /esNoYesYesYesParlial 25.QOo/o
Ygs No Yes Yes Yes No /esNoYasYosYosNo 12.500k
The Cadmus Group, lnc. I Energli Service$6$
Pa*ifiConp
Rocky Mountain Power
Exhibit No.5 Page 339 of 1365
Case No. PAC-E-14-07
ue{d??iBA?'B: [#{ffi'
The Freeridership Designation
If customers both did not know about the measure before hearing about the program and had no
plans to install the measure, ttrey are not freeriders. Likewise, if they knew about the program,
but had no plans to install the measure, they are not freeriders. Customers who indicated they
would have installed the measure without the program or had already installed the measure when
they learned ofthe program are 1O0-percent freeriders.
Customers can also be partial freeriders. Partial scores are assigned to customers that indicated a
likelihood that they would have installed the measure without the program, but that the program
had some influence over the timing of their decision, the level of efficiency they would have
chosen or the number of measures they would have chosen.
The Cadmu* Group, [nc. / finerEy Services 70
EEA Prrtlclpant EEA Coordlnetor
Support as necBsary
Rocky lt{qgffeBttorer
Exhibit No. 5 Page 340 oI 1 355
Case No. PAC-E-14{7
Witness: Kathryn C. Hymas
i - -- -- -- - -- - - - - -- - -- - - .- -- -- -- I ! - - - ' - ' - ' - - ' - - - - ' - ' ' - ' ' ' - l
Support as n@sery ie Suppon s n@s8ry iL--------------------------i : L-----------r,-,--------------i
Sign L6tt€r of lntent and
rEtum to EEA P8rticipant
Reviry Lightrng T@l
including @sb, wings &
io€nwe stirete
Upload LEhting T@l intc
FTP Sne (Fil€Zilla) for
proiect nu[rb6r assignment
and eligibllity @nfirrotion
Eniar proiect into databae
and seaie lD #
Pertcm Cuslorer EllgibilityEyia UploedinfotoFTP
Submit to Nexant
and Scffi (ECG)
for r€view /
approval
ffidt*s
@m6nts ftom
Nexanl and S@tt
(ECG)
Rgviw inspection Eport.
Update pDjecl / Lighting
Tool as needed. Post to FTP
Site
Pepare lnentve
AgBement induding prciecl
name & lD. Pdide to EEA
Particlpant
and PC $gnature
and Etu.n to EEA
Coodinalor
Complela prciocl
Not ty EEA
Pariicipant and
prcvile mvoices ,/
supporting
documentation
Reviw final prcjed
documentation Comple,te
rcviBw form. Upload Final
Lightiog T@l liles into FTP
site. Mail compbte proiect
filss b NeEnt
lnspeclion Repon;
update poect /
Lit hijng T@l as
Prepare inal
prcjed
drumentation
and Eviw form
Roclry Mountain Power
Exhibit No, 5 Page 341 of '1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
FTNANSwER EXpRESS@ NoN-LTGHTTNG TNcENTIVE pRocESS
Eligible customer purchases
qualifying equipment
Give customer an
application and
assist in filling it out
Does customer want
EEA Participant to
do so all the time?
Customer submits
application and
supporting
documentation to
Rocky Mountain
Power
Have customer
complete an On-Going
lncentive Agreement
and keep it on file
Have customer complete
application with payment
release to EEA
Participant on page 2
As equipment is
purchased:
Credit customers'
invoice for incentive
Copy On-Going
lncentive Agreement
Fill out the Product
lncentive Worksheet
Attach supporting
documentation.
Send package to
Rockv Mountain
Credit customers' invoice
for incentive and send
application to Rocky
Mountain PowerRocky Mountain Power
sends the incentive by
check to customer within
6 weeks
Rocky Mountain Power sends
the incentive reimbursement
check to EEA Participant
within 6 weeks
Rocky Mountain Power sends
the incentive reimbursement
check to EEA Participant
within 6 weeks
EEA Participant
Exhibit No. 5 Page 342 of '1365
Case No. PAC-E-14-07
Roclry Mountain Power
Wtness: Kathryn C. Hymas
ffiROCKYMOUNTAIN
rePOWER
\ rorusroiroFPAcFrcoHP
Exhibit No. 5.5
Irrigation Energy Savers Evaluation 2006-2008
Roclry Mountain Power
Exhibit No. 5 Page 343 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
..R. -N,. -N.-$...irCAIfh/ITJS
{;,Nr{il}E-I:$r'},- S}"} {-: "
PacifiGorp lrrigation Energy
Savers 2006-2008 ldaho
Program Evaluation
Prepared for
PacifiCorp
Prepared by
The Cadmus Group lnc. / Energy Services
720 SW Washington Street, Suite 400
Portland, OR 97205
503-228-2992
March 16,2011
Roclry Mountain Poiler
Exhlbit No. 5 Page 344 of 1 365
Cas€ No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Prepared by:
Brian Hedman
Rick Ogle
Ashley Buckman
Randy Spitzer
Coryorm Headquaners:
57 YlAtarStreet
Whtorrswn HA0247:
Tel: [phone]ffi
Farc 617.673,7001
An Erployee-Owed fatrgwty
wr$radrnusgrsup,g{Fr\'l
720 $/t' Ylbtling$n St.
Suitc4(F
Fortlard. OR9n05
Te[ 503.X28.]992
Fax; 503,2?8.3-696
Rocky Mountain Power
Exhibit No, 5 Page 345 of I 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 1S. 2011
Table of Contents
Executive Summary........... .......1
Conclusions................ ................3
Recommendations...... ................5
lntroduction ..............7
Program Description ..................7
Expected Savings..... ..................8
lmpact Evaluation............. .........9
Evaluation Approach .................9
Overview of the P1an.......... ..................9
Analysis of Field Data.......... ..............12
Evaluated Savings and Realization Rates ....................14
Discussion of Results. ..............15
Field Observations ............15
RTF Estimated Savings............... .......16
Net-to-Gross............... ..............17
Freeridership............... ......17
Conclusions................ ..............18
Recommendations...... ..............18
Process Evaluation............ .... 19
Process Evaluation Overview ....................19
Participation and Enrollment ..............19
Energy-Efficiency Measures ..............22
Operational Changes.. .......23
Installation ......23
Spillover... .......25
Energy-Efficiency Decision Making ....................27
Interaction with Rocky Mountain Power or Third-Party Staff.......... .......29
Satisfaction .....30
Conclusions................ ..............31
Recommendations...... ..............31
Cost-Effectiveness Analysis........... ..... 33
The Cadmus Group lnc. I Energy Services
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 346 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
Appendix A. lrrigation Energy Savers Process Flow Diagrams .... 39
Appendix B. Site Visit Results ............. 41
AppendixG.ParticipantExchangeSurveylnstrument........... .......47
Appendix D. Participant Non-Exchange Survey 1nstrument......................... 60
Appendix E. Nonparticipant Survey lnstrument........... ...74
Appendix F. Staff and lmplementer lnterview Guide ....... 80
Appendix G. Market Actor lnterview Guide ....... 84
The Cadmus Group lnc. / Energy Services
Pq{lr!op
Executive Summary
The Irrigation Energy Savers Program (the program) offers agricultural customers in Idaho the
opportunity to increase the efficiency of their irrigation system(s) through energy-efficiency
upgrades and education. Customers served under Rocky Mountain Power's Schedule 10
irrigation rate are eligible to participate. The program includes prescriptive and custom incentive
options, as well as an equipment exchange component, to help growers improve the efficiency of
their inigation systems.
Cadmus obtained expected savings and other program-related data from Rocky Mountain Power's
tracking database and records of program implementation. Expected savings were calculated for
each installed measure and documented based on original measure savings estimates. To increase
the precision of the estimates, the evaluation of savings was conducted on the program as a whole,
encompassing calendar years 2006-2008.
To evaluate achieved energy savings, Cadmus and its subcontractor, IRZ Consulting
(collectively referred to as the Cadmus team, or the team), performed site visits for 79 unique
participants representing 123 sites and 140 projects. Based on measurements and observations
obtained from these site visits, in addition to data provided in the project files and conversations
with irrigators, Cadmus calculated evaluated energy savings and the associated realization rate
for each of two participation categories. The first category consisted of sites that participated in
the equipment exchange and pivot and linear system upgrade components of the program,
including sites at which a system consultation and/or system analysis was also performed. The
second category included those sites that received only a system consultation and/or system
analysis.
Overall, Cadmus calculated energy savings at a precision of +551 percent for the equipment
exchange, pivot and linear system upgrade, and combined project category. The system
consultation and/or system analysis only category was calculated at +86 percent precision. Both
categories are reportedata90 percent confidence interval. Due to this high uncertainty, Cadmus
The analysis was based on the East Commercial Cooling l6 percent load factor decrement which most closely
represents irrigation usage.
Cadmus utilized the Regional Technical Forum's Eastern Idaho-specific proposed deemed savings, measure
costs, and measure lives for this cost-effectiveness scenario.
Enaluated bhbrgyl,,$avings from this prograrn;,determined,through billing analysis, fell short of
planning e$raateS,,when normalized for water and crbppr+g:,practioes using,the:baSt....avail5bil,
data. IJtilieing the i4005=200S XRP decrement valueil ,and,ev.aluated savings, the program was
only cost effeCtive fr ...the F'articipant Cosf Test (PC$);,,prspective during:the 2006.2CI08,,::,..::'.:.:,:.:,:.:,'
program oy,ble, Utilifih$ expected savings estimates, the piogr-am was cost:,,eff,ective:from the
PacifiCorp Total Resowce Cost Test (PTRC), Total neiource Cost Test (TRC), Utility Cost Test
(uCT), ana FCf perspectives. When program cost effectiveness was assessed using third parry2
data for deemed savings and cost estimates, which removes the analytical complexity of
normalizing for water.,.rmd.l0iOpping practices,:$ere appli0ablq,:::the,,program was cost:ef,:fffiive, ,,
frorn the PTRC, TRC:;:;:.UO . and PCT,perspective:s,
Rocky Mountain Power
Exhibit No. 5 Page 347 of 1 365
Case No. PAC-E-14-07
VMtness: Kathrun C. Hvmashfiarch 1$. 2r111
The Cacimus Greup lnc. ,'*nergli $ervices
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 348 of 1 365
Case No. PAC-E-14-07
Witness: Kethrvn C. HvmasMarch 16" 2011
concluded that the savings estimate is inconclusive and calculated high case and low case
savings based on the upper and lower bounds of the precision estimates. Table I summarizes
expected energy savings, evaluated energy savings, and realization rates by participation
category, including high and low case savings estimates.
Table 1. Evaluated Enerry Savings by Participation Category
System Consultation and / or
The Regional Technical Forum (RTF) recently proposed new savings estimates, measure costs,
and measure lives for irrigation equipment.4 As a second approach to estimating savings,
Cadmus calculated expected savings based on the number of measures incented through the
Program and the proposed RTF deemed savings estimates. The results are presented in Table 2.
Table 2. Savings Based on RTF Proposed Deemed Savings Estimates
Cadmus also fielded two participant surveys; one that focused on the exchange aspect of the
program and one that focused on the non-exchange aspects, resulting in separate freeridership
estimates for each group. Cadmus determined freeridership to be 27 percent among exchange
participants and 26 percent among non-exchange participants, or a weighted average of 26.5
percent overall. For this evaluation, freeridership was the only factor used to calculate the net-to-
' Due to the broad error band around the evaluated results, the results are inconclusive.o http://www.nwcouncil.or gl energy lrtf/meetings/20 1 0/0 I /Default.htm5 The RTF did not propose deemed savings estimates for sprinkler packages, system consultations, or system
analyses. Sprinkler package savings are based on the RTF per unit savings estimates for individual components,
and an estimate of the number of components included in a typical sprinkler package incented by the Irrigation
Energy Savers Program. Savings for system consultations and analyses were carried over from the Program's
expected savings estimates.
2The Cadrnu$ Group lnc. i Energy Services
PacifiConp
Roclry Mountain Power
Exhibit No. 5 Page 349 of 1365
Case No. PAC-E-14-07
Wtness: Kathrun C. Hvmas
h,{arch 1S. 2$11
gross (NTG) ratio.6Applying the NTG ratio of 73.5 percent to the evaluated savings listed in
Table 1 resulted in net program savings of 1,492,790 kwh (Table 8).
Cadmus determined program cost-effectiveness for five scenarios:
o Scenario 1: Expected Savings
o Scenario 2: Evaluated Savings
o Scenario 3: High Case Evaluated Savings
o Scenario 4: Low Case Evaluated Savings
o Scenario 5: RTF's Proposed Deemed Savings, utilizing Eastern Idaho-specific savings
and cost estimates (2010).
Table 3 presents a summary of program cost-effectiveness from 2006 to 2008 for each of the
scenarios described above using Idaho-specifi c assumptions.
Conclusions
Overall, the program is successful in getting customers engaged in systematic equipment
replacement, which helps minimize pumping energy and wasted water and improve overall
operational efficiencies. However, it remains difficult to normalize both pre- and post-
installation conditions for water and cropping practices and measure the electric energy savings
through field studies and billing analysis.
Most of the participating customers are very satisfied with their involvement in the program and
with the performance of the installed energy-efficiency measures. Table 4 presents customer
satisfaction with the program as a whole, as well as their satisfaction with the measures installed
through the program. In addition, over 97 percent of surveyed participants indicated they would
participate in the progrilm again.
This method is consistent with the Model Energy Efficiency Program Impact Evaluation Guide authored by the
EPA as part of the National Action Plan for Energy Efficiency.
Table 3. Cost-Effectiveness Summary for the Program - 2006-2008
Total Resource + Conservation Adder (PTRC)1.10 0.43 1.12 0.05 1 .10
Total Resource No Adder (TRC)1,00 0.39 1.02 0.05 1.00
Utility (UCT)1.45 0.57 1.47 0.07 1.80
Ratepayer lmpact (RlM)0.61 0,38 0.63 0.06 0.67
Participant (PCT)1.82 1.05 1.79 0.66 1.61
The Cadrnus GrCIup [nc. / Energy $en:ices
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 350 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 201f
Table 4. Overall Satisfaction with the Program
10 - Extremelv satisfied 46 59
I 25 29
8 26 24
7 14 3
6 4 0
5 3 4
4 1 0
3 0 0
2 0 0
1 - Extremelv Dissatisfied 0 0
Total 119 119
Cadmus has drawn several other conclusions, which are suilrmarized below:
At the onset of the evaluation, the field team recognized that measuring savings for
systems where measure installations were limited to the exchange of nozzles, gaskets,
drains, and/or the installation pivot packages would be difficult to do through billing
analysis and, even after normalizing with the best available water and cropping history
data, might yield inconclusive results. The impact analysis reaffirmed this complexity,
but identified the opportunity to educate growers on more systematic approaches to
measuring and controlling water application.
Due to the variation in savings observed in the results of the field work, true program
savings are likely to be somewhere between the evaluated savings values and the original
program and RTF engineering estimates.
The RTF estimated savings for measures equivalent to those incented through the
program yield a realization rate in excess of 100 percent when compared to PacifiCorp's
expected savings.
Despite a low evaluated savings realization rate, the installed measures have a beneficial
impact on the irrigation systems. When old worn-out components are replaced with new
ones, a system will perform better. In the case of an irrigation system, that typically
means that water is more efficiently distributed and uniformly applied. However, without
precise tracking of water application using established water management techniques,
evaluation approaches that rely on billing analysis may continue to yield inconclusive
results.
While many participants had general plans to replace their equipment eventually, most
would not have replaced all of the equipment covered by the program. Half would not
have been able to undertake upgrades for several years without the progftrm.
Energy efficiency was reported by survey respondents as being important, primarily
because of the cost savings. Participating irrigation equipment vendors reported that some
customers were reluctant to invest in the program measures because of the up-front costs.
The Cadmus Group Inc. i f;nergy $ervices
PacifiCorp
Roclry Mountain Power
Exhibit No.5 Page 351 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
o Survey respondents reported that although energy efficiency is important, they often
don't have the necessary technical knowledge to address it.
Recommendations
o Collect information on water application and cropping practices from participating sites
as part of the participation process.
o Promote overall grower education on water management and tracking practices. Growers
need to know that potential energy savings achieved by replacing equipment may be
substantially increased by implementing irrigation water management.
o Refine progrurm marketing to decrease confusion between the Irrigation Energy Savers
and Direct Load Control programs, and to decrease customer concems regarding system
shut-off.
o Consider increasing incentives, particularly for linear and pivot sprinkler packages, to get
more customers involved.
. Engage an evaluation firm to design a prelpost evaluation strategy to refine the savings
estimates.
The Cadrnus Group lnc. i Hnergy Services
Roclry Mountain Po,ver
Exhibit No. 5 Pege 352 of 1365
Case No. PAC-E{4-07
\Mtness: lGthryn C. Hymas
teeilicqry
Rocky Mountiain Power
Exhibit No. 5 Page 353 of 1365
Case No. PAC-E-14-07
VMtness: Kathrun C. HvmasMarch 16. 2011
lntroduction
Program Description
The Irrigation Energy Savers Program oflers Idaho customers under Rocky Mountain Power's
Schedule 10 the opportunity to increase the efficiency of their agricultural inigation systems
through implementation of energy-efficiency measures and education. The program offers the
following prescriptive and custom incentive options:
. Prescriptive Incentive Options:
o Equipment exchange (nozzles, gaskets, drains)
o Pivot and linear equipment upgrades
o Custom Incentive Options:
o System consultations and pump tests (service incentives)
o System analyses (service incentive)
o $0.121kwh, up to 50 percent of the eligible costs, for site-specific projects that save
energy as determined by the program administrator.
The prescriptive incentive options are available to customers who wish to replace existing
equipment with qualifying new equipment, while the custom options are available for customers
wishing to install new equipment or expand or redesign their existing system. Specifically, the
equipment exchange option is for customers with handlines, wheellines, and solid set sprinkler
systems, and requires participants to exchange their worn nozzles, gaskets, or drains for
equivalent new equipment. The pivot and linear system upgrade option is available for customers
with center pivot and linear move systems and provides incentives for the replacement of
existing equipment with new low pressure drains, sprinkler pressure regulators, or sprinkler
packages.
The custom incentive options were designed to address system upgrades not included in the
prescriptive incentive offerings. The program provides customers with service incentives
consisting of system consultations and pump tests to help them determine the pumping efficiency
of their system and to suggest efficiency improvements. The system analysis component
provides a service incentive, in addition to supporting calculations, for incentives available on
equipment installed as part of a system expansion or redesign. Customers who are adding
capacity, changing their water source, or replacing all or part of their system may qualiff for
incentives under the system analysis component.
Customers interested in participating in the program can choose from a list of participating
vendors in Rocky Mountain Power's service territory or contact the program administrator. A list
of participating vendors is available on the Company's web site.
The program was administered by Franklin Soil and Water Conservation District and Rocky
Mountain Power from 2006-2008. In2009, Nexant assumed implementation responsibilities.
The Cadmus Group lnc. i Energy Services
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 354 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
For the prescriptive incentive offers, the program administrator performed an on-site inspection
on a statistically significant sample to confirm pre- and post-installation conditions, and to verifr
the accuracy of applications and incentives paid. Appendix A of this report presents process flow
diagrams illustrating how the Irrigation Energy Savers Program operates.
Expected Savings
At the onset of the evaluation, Cadmus developed a participant-level database from vendor
invoices and records of program implementation to supplement the measure-level expected
savings PacifiCorp provided. Expected savings as indicated by PacifiCorp total 7,003,117 kwh.
The measure-level database developed by Cadmus captured a total of 7,002,101 kWh in
expected savings for projects with a valid Site ID, a difference of only 0.015 percent when
compared to PacifiCorp's records. Therefore, the participant-level database developed by
Cadmus was used to determine the number of individual measures installed through the program
and the expected savings used to calculate the program realization rate, which is discussed in a
later section.
According to implementation records, the program incented 222,234 unique measures from
2006-2008, with expected savings of 7,002,101 kwh. Irrigation Energy Savers Program
customers exchanged 81,791 nozzles, 127,939 gaskets, and 11,447 drains, and purchased 782
pressure regulators and 187 sprinkler packages. In addition, progftIm implementers performed 81
system consultations and 7 system analyses. Measures were installed on at least 610 unique
service points.T Table 5 presents expected energy savings by measure. Gasket exchanges
represented the greatest percentage of program expected savings at 44 percent, followed by
sprinkler packages at29 percent.
Table 5. Expected Enerry Savings by Measure
Nozzles 81,791 973,313 140/o
Gaskets 127,939 3,108,91 I 44Yo
Drains 11,447 278,162 40h
Pressure Reoulators 782 88,366 1o/o
Sprinkler Packages 187 2,018,104 29o/o
Svstem Consultations 81 259,200 4o/o
System Analyses 7 276,038 4%
Total 222,234 7,002,101 100%
Measures exchanged as a single transaction were often installed across several sites, but not all of the sites were
specified at the time of exchange. Therefore, there is some imprecision surrounding the exact number of
affected sites. However, the number of unknown sites was not significant.
IThe Cadmus Group lnc. / Energy Services
le-qilrQqrp
Rocky Mountain Power
Exhibit No. 5 Page 355 of '1 365
Case No. PAC-E-14-07
VMtness: Kathrun C. Hvmasfr4arch 16. 2011
lmpact Evaluation
Evaluation Approach
To review and evaluate Rocky Mountain Power's Inigation Energy Savers Program in Idaho an
irrigation field evaluation plan was developed by the Cadmus team and presented to Rocky
Mountain Power. This plan laid out procedures for both the collection and analysis of data.
Overyiew of the Plan
The Irrigation Energy Savers Program in Idaho offered several possible measures:
1. Exchange: Growers exchanged old nozzles, gaskets, and/or low pressure drains for new
ones.
2. Non-Exchange: Growers purchased new sprinkler packages and/or pressure regulators for
pivots.
3. System Consultation: A consultant met with the grower to conduct a site inspection of the
irrigation system and discuss possible changes, including exchange and/or non-exchange
measures, which could be implemented to reduce power usage.
4. System Analysis: Similar to a system consultation, but included measurements of system
parameters (i.e. flow rates, pressures, power usage, etc.), the calculation of potential
savings for identified system modifications, and the installation of energy-efficient
equipment.
A popular non-exchange measure that was tied to system analyses was the installation of a
variable frequency drive (VFD). A VFD is used to control a pump motor so that the discharge
pressure can be maintained regardless of the discharge rate. Reducing the pumping head when
lower discharge rates are needed reduces the power used.
From records of program implementation and participation, a random sample set of participants
was identified by measure and by year of implementation. The sample set was adjusted when
individual participants could not accommodate a field evaluation of their system within the
window allocated to complete the field work. Additional sites were selected as replacements for
the sites that could not accommodate a field visit. The target number of projects to be evaluated
was 140. The Cadmus team performed site visits for 79 unique participants representng I23
sites and 140 projects.
The utility records for three years prior to and up to three years after the implementation of
measures were compiled for each account in the sample. Seasonal cropping and weather data for
these same years were also documented for each participant in the sample. The crop and weather
data were used in the analysis phase to normalize the energy usage by determining energy usage
per required unit volume of water pumped. Where possible the pumps associated with the meter
records were flow tested by the field evaluation teams using an ultrasonic (non-invasive)
portable flow meter. The volume of water pumped was based on these actual field flow
measurements and the documented historic hours of operation. These normalized records were
The Cadmus Group lnc. i f;nergy $ervices
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 356 of 1365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasMarch 16. 2011
used to compare the energy usage before and after measrue implementation. If the flow could not
be measured directly, most often because systems that had been shut down for the season, the
team utilized available information (i.e., pump and motor sizes, measured lifts, reported
operating pressures, system sizes and package rates, and the monthly demands (kW) from the
utility records) to estimate the typical pumping conditions. Any inaccuracy that resulted from
these estimates was applied to both pre- and post-installation conditions and therefore
minimized.
Each recruited participant was interviewed and an on-site visit was conducted. During each visit,
an inspection of each affected system was made to:
. Verifu that the measure components wer€ present and operating as intended
o Measure operational parameters, such as flow rates and pressures, while the system was
operating under normal conditions
Gather cropping history corresponding to utility record years
Verifu baseline assumptions
Document any changes to system operations post implementation
Based on the site visit findings, the post-implementation energy usage was calculated and
compared to the pre-implementation usage to determine the verified energy savings.
Site Visit Protocol
During each site visit, the following information was gathered through customer interview
questions, field observations, and measurements. For the purpose of the field measurements, the
system needed to be operating. This was not always possible due to the farm's irrigation
schedule and other operational practices. In these cases, as much information was gathered as
possible. For the convenience of the participant, the field staff gathered all relevant field data
while the system was operating to avoid system starting and stopping.
Interview Questionnalre: During each site visit, the participant was asked some basic questions,
such as:
o What measure(s) was (were) implemented and when? This was to confirm the records
provided.
o What were the crops grown during the three years before and up to three years after these
changes?
How do you decide to irrigate (hours per day to irrigate, how often to change sets, time
interval per pivot revolution, what pressure, variable flow operation)?
Have there been any changes to the operation of the system since measure
implementation (number of irrigations, frequency of irrigations, length of irrigations,
operating pressure)?
o Have there been any other changes made (system conversion, pump rebuild or replaced,
other efficiency measures, changes in well water conditions)?
a
a
a
The Cadrnus Group lnc. I Energy Services 10
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 357 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. Hvmashflarch 1S. 2011
System Inspection: Each system was visually observed to veriS, that the documented measures
had actually been implemented.
o Nozzle exchange/replacement: SAE drill bits were used to validate nozzle sizes. If
nozzles were not replaced, the age was estimated and the wear measured using drill bits.
o Gasket and/or drain exchange/replacement: joints and/or drains were inspected for leaks.
o Regulator and/or sprinkler package replacement: a spot check of the system components
was made to identiff and veriff that appropriate types were installed.
Field Measurements: Where applicable, the following measurements were made during each site
visit:
o Using an ultrasound flow meter, the total irrigation flow rate was measured.
o Pumping lift was measured, when practical. For low lift systems, this measurement was
made using a tape measure. For well systems, this lift was to be measured using an
airline, if in place, or an e-tape using available access port(s) when available. However, in
cases where no access ports or airlines were found, Cadmus relied on information
provided by the growers - e.g. how deep the pump was set in the well. If the grower
reported no changes to the well or pump system, this value was estimated using the same
assumptions for pre- and post-installation conditions.
o The pump discharge pressure was measured using an accurate pressure gauge.
o For booster pumps the incoming pressure was also measured, if possible, using an
accurate pressure gauge.
o The type and size of fittings and/or valves between the free water surface and the point
where pressure measurements were made was documented. A picture was taken of the
pumping station as part of this documentation, including pump nameplate data if
available.
o For instantaneous power usage, the revolutions or pulses on the utility meter were
counted per time interval and the meter constants (K6, PTR, and Multiplier), as displayed
on the meter face, were documented. Other loads on the pumping station utility meter,
such as pivot motors, end gun and system booster pumps, were noted and disaggregated
from the total.
o A basic map of the system layout was sketched showing pipeline types, sizes, and
lengths, as well as the position of all laterals and/or pivots during the time of the visit.
o For each irrigation lateral in operation, the pressure at the first and last sprinkler was
measured using an accurate pressure gauge and pitot tube, while the sprinkler system was
operating normally.
o For set-move and solid-set systems, the distances between sprinklers and between risers
or laterals were measured.
. The lengths of pivots, both to the end of steel and of total coverage, were determined
through farm records as available from project files or by field measurement.
The Cadrnus Group lnc. i Energy Services 1',|
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 358 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
Analysis of Field Data
In order to determine the effectiveness of measures implemented, the following calculations
were performed using the field measurements and utility records:
1. Head losses associated with the fittings and/or valves were estimated from field
observations and the measured flow rate.
2. The work being done by each pump, the water horsepower (WfP) was calculated using:
WHp=exTDH 13960where: Q = amount of system water flow in gallons per minute (gpm)
TDH = total dynamic head in feet (ft), based on lift, head losses, and pressures
The electrical demand for each pump motor was calculated from the count of utility
meter revolutions or pulses per time interval and the corresponding meter constants:
Demand (kW) = 3.6 x [Rev or Pulse] x Kh x CTR x PTR x Multiplier / Time interval (sec)
The demand was converted to electrical horsepower by:
EHP = Demand 10.746
The overall effrciency of the pumping unit was then calculated by:
Effor".arr: WHP,IEHP x 100
The rate of power usage to pump a volume of water was then calculated by:
E* (kWh/acre-foot) = 1.0227 x TDH / (Effo,".l1/ 100)
For each of the three years before the first measure was implemented and up to three
years after, the annual crop water requirement was estimated for each field and/or crop.
These estimates were based on the reported weather and crop water requirements from
the AgriMet Station closest to the particular system. There are four AgriMet Stations in
eastern Idaho at Ashton, Fort Hall, Kettle Butte, and Monteview. It is important to note
that these are only estimates because they cannot account for variations in weather
conditions between where the system is and even the closest station, nor the differences
in planting dates. Because the field work and analysis was undertaken during the 2010
season, only partial crop water requirement data were available.
Using these estimated crop water requirements and the acreage of each field and/or crop,
the total volume of crop water required was calculated. This represents the net irrigation
requirement to fully satisfu the entire crop water requirement. If more water is applied,
over irrigation has occurred, and if less water is applied deficit irrigation has occurred.
No inigation system can apply water in perfect uniformity. Therefore, to ensure that the
crop water requirement is satisfied across each field, some over irrigation is required. On
the other hand, some crops such as wheat may be deficit irrigated to save the water for
other higher value and water-sensitive crops such as potatoes.
For each of the three years before the first measure was implemented and up to three
years after, the annual power usage of the pump station was obtained from the utility. If
the utility meter measured power for uses other than just the pump station or pump(s) in
3.
4.
5.
6.
7.
8.
9.
The Sadnrus Group lnc. i Energy Services 12
FacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 359 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. Hvmastularch 16. 2CI11.............1.....................
question, that usage was estimated and subtracted from the total usage. This accounting
for other uses was subjective and may have reduced the accuracy of the calculations for
the particular systems. This information was provided by the growers while the field team
was on site. Because the field work and analysis was undertaken during the 2010 season,
only partial power usage records were available for 2010.
10. Dividing the total annual power usage by the rate of power usage (E*) gives the total
volume of water pumped that year. Then dividing the volume of water required for
irrigation by the volume of water pumped gives an indication of the overall irrigation
efficiency. As previously mentioned, an irrigation efficiency of less than 100 percent
indicates some degree of over irrigation and, conversely, one higher than 100 percent
indicates deficit irrigation. The inigation efficiencies calculated for each system were for
the entire system, not for a specific field or crop. Average irrigation efficiency for both
the three pre-measure years and post-measure years were calculated. Differences in these
pre- and post-efficiencies can indicate changes in irrigation practices.
Since only partial crop water requirement data and power usage records were available
for 2010, that year was largely excluded for use of comparison. Additionally, 2009 was
an unusually wet year and farmers reacted and scheduled their inigations differently as a
result of the rain fall. The timing of the rain events and the different stages of crop growth
affected the farmer's perception of the rain's benefiU consequently, this resulted in some
extreme irrigation efficiency numbers in2009. If we could not determine a reasonable
cause for the extremity we disregarded these numbers when determining the averages.
I l. For each year after the first measure was implemented the following calculations were
made. First, dividing the volume of crop water requirement by the pre-measure average
irrigation efficiency provided the water quantity that would have been pumped as the
system existed and was operated prior to the implementation of the measure. Second,
multiplying the volume of water that would have been pumped by the previously
calculated rate of power usage (E*) gives the total usage of power that would have been
required. Third, subtracting the actual power usage from this calculated-required-usage
gives the estimated savings. And fourth, dividing the savings by the calculated-required-
usage gives the percent savings. The calculated usages and savings for each year were
also averaged.
For the purposes of the impact evaluation, Cadmus placed sites into one of two categories,
depending on program activities and measures installed at the site. The first category consisted of
sites that participated in the equipment exchange and pivot and linear system upgrade
components of the program, including sites at which a system consultation and/or system
analysis was also performed. The second category included those sites that received only a
system consultation and/or system analysis. Appendix B presents site visit results.
To calculate evaluated savings, Cadmus determined annual participant usage and multiplied this
value by the percent savings results from the site visits. To calculate total participant usage,
Cadmus pulled usage data for each site at which at which measures were installed. Usage data
for the year prior to the first year of participation was utilized. If energy usage was zero in the
year prior to participation, Cadmus used data for the first year of participation. If energy usage
The Cadmus Group lnc. i Energy Senrices 13
PacifiConp
Rocky Mountain Power
Exhibit No. 5 Page 360 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
data was zero inthe year of participation, but participation occurred after the irrigation season
began, Cadmus used data for the year following participation.
In some cases, a valid site ID was not documented in the records of program implementation
Cadmus used to build the participant data set. In these instances, Cadmus utilized utility usage
records to compile a list of all site IDs associated with the account or meter number listed in the
invoice (or provided by PacifiCorp). If only one site ID was associated with the account or meter
number, Cadmus assumed this was the site where measures were installed. If multiple site IDs
were associated with the account number, Cadmus retrieved usage data for all associated site IDs
and used the site with the largest annual usage (in the year prior to the first installation) in the
calculation of total annual usage. Usage for each site was only counted once. If usage data did
not correlate with participation records, or if Cadmus was unable to determine the correct site ID
or a pool of potential site IDs, measures and savings associated with the unverifiable site IDs
were excluded from the analysis unless they were also associated with a valid site ID. In total, 11
sites, representing 59,389 kWh of expected savings, were not included in the calculation of
expected savings or in the subsequent analysis.
Evaluated Savings and Realization Rates
As discussed above, Cadmus calculated percent savings for each measure category and
multiplied this by the total usage calculated for that category to determine evaluated energy
savings. Overall, Cadmus calculated energy savings at a precision of +551 percent for the
equipment exchange, pivot and linear system upgrade, and combined project category. The
system consultation and,/or system analysis only category was calculated at +86 percent
precision. Both categories are reported at a 90 percent confidence interval. Due to this high
uncertainty, Cadmus concluded that the savings estimates are inconclusive and calculated high
case and low case savings based on the upper and lower bounds of the precision analysis.
Cadmus calculated an energy savings realization rate for both categories as the ratio of evaluated
savings to expected savings. As discussed, evaluated energy savings reflect any deviation from
expected conditions observed dwing the on-site verification. Overall, the program achieved a 29
percent energy savings realization rate when considering only evaluated savings, as seen in Table
6, which presents energy savings andrealization rates by measure category, including the high
and low case evaluated savings estimates.
The Cadrnus Group lnc. i Energy Services 14
PacifiConp
Rocky Mountain Power
Exhibit No.5 Page 361 of 1365
Case No, PAC-E-14-07
\Mtness: Kathrvn C. HvmasMarch 16. 2011
Table 6. Evaluated Enerry Savings by Participation Category
Discussion of Results
Field Observations
The vast majority of participants were very open to have their systems inspected. In fact, a
majority went out of their way to facilitate the site visits. In spite of this openness and interest in
the audits, many were unclear as to what measure was installed on which system and when. On a
small number of audits, the farmer would direct a team to a system that did not match the utility
site ID associated with the sample, but would insist that measures were installed on that system.
In these cases, the team made sure that the power records used for evaluation matched the actual
field read utility site ID and/or meter number.
A major issue affecting the ability to assess the effectiveness of the nozzle and/or gasket
exchange for handlines was how the portable pipe is stored during the winter. At the end of an
irrigation season, portable pipe is hauled out of the fields and stacked. If a farmer has multiple
fields, the pipe is typically brought to a common stack yard. In the spring, the pipe is hauled back
to the fields, but not necessarily to the same field it came out of the previous fall. After a few
seasons, the result is that the pipe is shuffled around the farm, making savings analysis difficult.
Another issue affecting the assessment of all of the measures was the fact that most systems were
not on a single field associated with just one pump or meter. Most systems were a blend of
handlines and/or wheel lines in corners around pivots, or in small odd-shaped fields. In some
cases, the team observed systems with numerous fields, of which only a portion of the total
acreage or flow was associated with the installed measure, or systems with multiple measures
installed over a period of several years. And in some cases, farms had pumps or meters from
multiple locations supplying a corlmon pipeline system on which only one or a few measures
were installed. All of these factors increased the uncertainty of the analysis.
When asked how soil moisture was measured and the decision to irrigate was made, the most
common answer given by the farmers was to use a shovel and the 'feel' method. With
experience, an irrigator can learn to gage the relative moisture content of a soil by feeling it. This
method is subjective, however, and does not allow for precise control. Some farmers stated that
they used a local consultant to monitor soil moisture and make recommendations for irrigation
scheduling for their fields.
E Due to the broad error band around the evaluated results, the results are inconclusive.
System Consultation and / or
The Cadmus Group lnc. ,'Energy Services 15
*qili9p-rp
Roclry Mountain Power
Exhibit No. 5 Page 362 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
For most farmers, irrigation scheduling is driven by the number of sets needed to cover a field
and the number of moves per day, usually one (24 hour set time) or two (12 hour set time), rather
than by the soil moisture. Water is more accurately delivered with replaced gaskets and nozzles;
however, pumping time is not reduced if the grower does not adjust the irrigation schedule to
account for this improved efficiency. Many of the pump panels had timers whereby set times
could be precisely controlled, but their use was seldom observed. Unless water application is
more precisely tracked using well established water management techniques, the energy savings
associated with the replacement of gaskets andnozzles will remain difficult to measure through
inferential methods such as billing analysis. This results in the low realization rate for the
measure category that included equipment exchanges.
When asked their opinion of how effective the measures were, growers provided various
answers. Typically, all farmers thought the programs were worthwhile and that their systems had
improved. Those with the strongest opinions were those who installed VFDs as a result of a
system consultation or system analysis. All believed strongly that the VFD had reduced their
power usage. They were more enthused, however, about how the VFD had simplified the
operation of their system, reducing both the risk of over pressurizing their system and the hours
required to make changes.
RTF Estimated Savings
The Regional Technical Forum (RTF) was formed in 1999 with the intent of providing
standardized protocols for regional entities to use when determining energy savings and impacts.
In that capacity, the RTF originally approved deemed savings for irrigation measures in 2005.
The RTF subsequently established a subcommittee in 2009 to review the original assumptions
and provide recommendations on potential improvements or corrections. The subcommittee
revised the deemed savings and measure costs based on a review of available literature, proposed
technologies, and the experience of those serving on the subcommittee. The RTF subcommittee
requested and reviewed project level information provided by the Company that was obtained
from Idaho Irrigation Energy Savers participant projects.
To provide an alternate analysis that minimized the complexity of normalizing for water and
cropping practices, Cadmus calculated savings using the revised estimates from the RTF. Table 7
presents estimated savings based on proposed RTF savingse and the number of measures
installed through the Irrigation Energy Savers Program.
' http ://www.nwcouncil. orgl energy lrtfl meetingsl2}l 0/0 I /Default.htm
The Cadrnus Group lnc. i Energy Services 16
PacifiCorp
Rocky Mountain Power
Exhibit No.5 Page 363 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 1S. 2011
Table 7. Savings Based on RTF Proposed Deemed Savings Estimates
Netto-Gross
Net savings are the savings "net" of what would have occumed in the absence of the program."
Net-to-gross (NTG) is typically calculated from the results of freeridership and spillover;
however, for this evaluation we only quantified freeridership. Spillover is noted separately in
Section 4, but was not quantified due to the level of complexity involved in determining the
potential savings associated with spillover for irrigation measures.
Freeridership
Freeridership is defined as the percentage of savings that would have occurred in the program's
absence. Cadmus quantified this amount by analyzing the results of our telephone surveys with
program participants. The accuracy ofself-report surveys partly depends on the respondent's
memory of their decisions. For the Irrigation Energy Savers Program, some interviewees were
asked to recall actions taken four years ago. Participant candor may also be a factor, as
participants' responses may tend to reflect a "halo" effect, where customers indicate they would
have made the energy-efficient choice because they perceive it to be the response preferred by
the interviewer.
Cadmus fielded two participant surveys; one that focused on the exchange aspect of the program
(70 respondents) and one that focused on the non-exchange aspects (49 respondents), resulting in
separate freeridership estimates for each group. Respondents were asked several questions about
what influenced their energy-efficient actions. Based on responses to these questions, Cadmus
determined freeridership to be 27 percent among exchange participants and 26 percent among
non-exchange participants, or 26.5 percent as a whole. For this evaluation, freeridership was the
only factor used to calculate the net-to-gross Q.{TG) ratio.l2 Applying the NTG ratio of 73.5
lt
The RTF did not propose deemed savings estimates for sprinkler packages, system consultations, or system
analyses. Sprinkler package savings are based on the RTF per unit savings estimates for individual components,
and an estimate of the number of components included in a typical sprinkler package incented by the Inigation
Energy Savers Program. Savings for system consultations and analyses were carried over from the Program's
expected savings estimates.
Model Energy Efficiency Program Impact Evaluation Guide authored by the EPA as pafi of the National Action
Plan for Energy Efficiency.
This method is consistent with the Model Energy Efficiency Program Impact Evaluation Guide authored by the
EPA as part of the National Action Plan for Energy Efficiency.
l0
t2
The Cadnrus GrCIup lnc. i Hnengy Services 17
E"h i bit lx":"$ys""' :lliiil'g
Case No. PAC-E-14-07
Witness: Kathrun C. HvmasMarch 16. 201'f
percent to the evaluated savings listed in Table 1 resulted in net program savings of 1,492,790
kwh13 flable 8).
. Reported at 90% confidence
Conclusions
At the onset of the evaluation, the field team recognized that measuring savings for systems
where measure installations were limited to the exchange of nozzles, gaskets, drains, and/or the
installation pivot packages would be difficult to do through billing analysis and, even after
normalizing with the best available water and cropping history data, might yield inconclusive
results. The results presented in Table 6 reaffirmed this complexity, but identified the
opportunity to educate growers on more systematic approaches to measuring and controlling
water application.
Actual program savings are likely to be somewhere between the evaluated savings values and the
original program and RTF estimates. The RTF estimated savings for measures equivalent to
those incented through the program yield a realization rate in excess of 100 percent as compared
to PacifiCorp's expected savings.
Despite a low savings realization rate, the installed measures have a beneficial impact on the
irrigation systems. When old worn-out components are replaced with new ones, a system will
perform better. In the case of an irrigation system, that typically means that water is more
efficiently distributed and uniformly applied. However, without precise tracking of water
application using established water management techniques, evaluation approaches that rely on
billing analysis may continue to yield inconclusive results.
Recommendations
o Collect information on water application and cropping practices from participating sites
as part of the participation process.
o Promote overall grower education on water management and tracking practices. Growers
need to know that potential energy savings achieved by replacing equipment may be
substantially increased by implementing irrigation water management.
" Net energy savings were only calculated for evaluated savings.
Table 8. Freeridership Analysis (All Respondents), 2006-2008
Exchange, Non-Exchange, and Combined Projects
1,583,142 1,163,610
Combined Score / Total
The Cadmus Group Inc. / Energy $ervice*18
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 365 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. Hvmasftllarch 1S. 2011
Process Evaluation
Process Evaluation Overview
With customer, vendor, implementer, and Company perspectives in mind, the Cadmus team
conducted a process evaluation of the Inigation Energy Savers program to assess what has
worked well and what can be improved. This evaluation relied on interviews with utility and
program staff, as well as on surveys of participants, nonparticipants, and participating inigation
equipment vendors. Interview and survey activities also informed Cadmus' evaluation of
spillover and freeridership impacts.
Due to potential differences in the decision-making process associated with different program
offerings, Cadmus fielded two participant surveys; one focused on the exchange aspect of the
program and one focused on the non-exchange aspects. As discussed above, a participant
database was developed based on invoices and outputs from PacifiCorp's records; Cadmus used
the database to develop the survey sample frames. Cadmus randomly selected participants for
both the exchange and non-exchange surveys. In addition, Cadmus interviewed nonparticipating
customers, program implementers, and irrigation equipment vendors. Survey instruments and
interview guides can be found in Appendices C, D, E, F, and G.
In total, 198 interviews and surveys were conducted for the process evaluation, as shown in
Table 9.
Both exchange and non-exchange participants reported energy efficiency to be very important to
the operation and management of their businesses, as demonstrated by a median score of 9 on a
scale from 1 to 10. When asked why energy efficiency is of high importance, 67 percent of
respondents mentioned cost savings.
Among respondents from both the exchange and non-exchange programs, customers devoted an
average of 16.2 percent of their annual operating costs to electricity.
Participation and Enrollment
Program staff noted that growers are a tight-knit community, and that word-of-mouth is a major
factor in marketing and promoting the program (a statement which is supported by the
participant survey results). As shown in Table 10, participants heard about the program from a
Table 9. Process Evaluation Samples
The Cadmus Group lnc. i Energy Services 19
Roclry Mountain Power
Exhibit No. 5 Page 366 of 1365
Case No. PAC-E-14-07
?eqili9qp
\Mtness: Kathrun C. HvmasMarch 16. 2011
wide range of sources, with the most common being irrigation contractors and equipment dealers
and word-of-mouth.
When asked why they participated in the Irrigation Energy Savers Program, both exchange and
non-exchange participants cited replacing old equipment and saving money on their electric and
water bills most often. Table 11 presents participant responses.
Table 11. Reason Measures
A few exchange participants reported having some concerns when they initially heard about the
program. Three of them were not sure if the information they had was accurate, but then found
that the program worked as stated. One respondent noted that certain parts of his or her system
were not covered by the equipment exchange program.
Non-exchange participants also voiced some initial concerns. Thirty-seven percent of those
surveyed had concerns when signing up for the program. As shown in Table 12, the most
common concerns were related to the shut-off period and the effectiveness of the equipment
replacement packages. The reference to a shut-off period indicates some confusion between the
Irrigation Energy Savers program and the irrigation load control program.
Table 10. How Participants Learned of the Irrigation Enerry Savers Program
-Multiple responses allowed.
Word-of-mouth: Family, friend, or
Printed material or outreach materials sent
Other Rocky Mountain Power staff
for Participating in the Program - Equipment Exchange
lMultiple responses allowed.
To replace old or broken equipment
To save monev on electric bills
To save money on water bills
To reduce maintenance costs
Part of a broader maintenance or renovation
The Cadmus Group lnc. ,'Energy Services 2A
Rocky Mountain Power
Exhibit No. 5 Page 367 of 1365
Case No. PAC-E-14-07
PacifiCorp
Wtness: Kathrvn C. Hvmashflanch 16. 2011
Most non-exchange applications went smoothly, with l6 percent of respondents (8 total)
reporting problems with the application process. Five said there were delays in the application
process, including one case of lost paperwork.
When asked what they would like changed about the application process, one exchange
participant suggested that there could have been more advertising from Rocky Mountain Power
or from a source other than the irrigation contractor. Non-exchange participants voiced liule need
for application process changes. Feedback from participants suggested that:
o The process should be quicker or require less paperwork,
. The website should be easier to navigate,
o There should be an easier way to contact a representative, and
o There should be an option to apply for the program directly, instead of through a third
party.
After participation in this program, all but one exchange and two non-exchange respondents
indicated they would participate in this program again.
Most participating equipment vendors made contact with prospective customers on the Energy
Savers program through their previous work with those customers, or through advertising. In
addition, the vendors tapped into their strong network of contractors to introduce customers to
the program and get them involved. Vendors stated that Rocky Mountain Power provided some
additional customer leads to them. Customers heard about the Energy Savers progrirm from the
equipment dealers or through advertisements on the Internet and television, as well as word-of-
mouth.
Results from the nonparticipant interviews suggest there is some confusion between the
Irrigation Energy Savers and Direct Load Control programs. Thirty-seven nonparticipants did not
participate in the Irrigation Energy Savers program because they did not want to lose control of
their inigation schedule, and several expressed concern that inigation intemrptions would occur
when they needed to irrigate the most.
The Sadmus Group [nc. i Energy Services 21
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 368 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 201'f
Energy-Efficiency Measu res
Exchange Measures
The program staff Cadmus interviewed noted that they are interested in increasing the number of
measures offered through this program. Several of the survey respondents had similar
sentiments which are discussed later in this report.
The irrigation equipment replaced under the program came in a range of conditions. Most
frequently, respondents reported exchanging equipment that had problems, but was still working.
In addition, 56 percent of respondents mentioned that in their opinion the replaced equipment
had been wasting water, and27 percent mentioned that the equipment had been wasting energy
(Table 13).
The vast majority of exchange respondents reported being satisfied with the performance of the
new equipment; on a scale of I to 10, the median score was a 9. Only 3 percent had a neutral
opinion, and none reported being dissatisfied.
Non-Exchange Measures
Seventy-eight percent of non-exchange respondents (38) applied all of the recommendations that
were suggested by the program. Cost was the reason cited by 16 percent of respondents (8) who
did not implement all of the recommendations. One participant hadn't had time to make the
changes yet, and one did not replace one pump, as it was no longer necessary in his or her
system.
Forty-three percent of non-exchange respondents replaced existing equipment through the
program, 12 percent installed only new equipment, and20 percent did both. The remaining
respondents participated through other means. As was the case with exchange participants, the
condition of the equipment replaced through the Program varied. As shown in Table 14,
respondents most commonly replaced old equipment that had problems, but was still functional.
Table 13. Condition of Exchanged Equipment
Old equipment had problems, but was still
Old eouioment in workino condition with no
Old equioment had failed or burned out
The Cadmus Group lnc. i Energy $ervices 22
feqili$qtp
Rocky Mountain Power
Exhibit No. 5 Page 369 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
Table 14. Condition of Replaced Equipment
Old equipment had problems, but was still
Old eouioment had failed or burned out
Old eouioment in workino condition with no
services or production line; wanted efficient equipment
Respondents were satisfied overall with the performance of the measures. On a scale of 1 to 10,
the median satisfaction rating was an 8, and the lowest scores were two 5's. Both of the
respondents that gave a rating of 5 did not feel that their sprinkler packages were worth the work
to install them. In particular, one respondent found his or her sprinkler systems to be too
restrictive and the other had trouble turning the sprinkler system on after the new equipment was
installed.
Irrigation Equipment Dealers
Participating vendors stated that nearly all of the customers reacted favorably to the Irrigation
Energy Savers program, including a big push for the program when it was first introduced. The
efficiency options that were most popular with customers were equipment exchanges,
particularly for nozzles and gaskets. Dealers also stated that the equipment exchange of sprinkler
packages on pivot and linear systems was highly utilized. Some customers were initially
skeptical about the costs and benefits of the Energy Savers program, but that once they began
investing in the efficiency measures they got on-board with the program. Several participating
vendors indicated that, as part of the equipment exchange, there was initially a problem with
buildup of non-recyclable materials, but that over time, with the assistance of Rocky Mountain
Power, they were able to effectively unload the materials.
Operational Changes
At the time they participated in the equipment exchange, 61 percent of respondents had an
overall plan for increasing the efficiency of their systems. However, only 23 percent of exchange
respondents changed the manner in which they operated the equipment; all of these participants
said these changes were part of their overall plan to increase energy efficiency. This is consistent
with the observations and savings noted in the site visits.
Sixty-six percent of non-exchange respondents had overall plans to improve the energy
efficiency of their irrigation systems, and 39 percent changed the way they operated their
equipment after installing the new measures. All but one made those changes as part of their
overall plans to increase energy efficiency.
lnstallation
Forty percent of exchange respondents reported already having some of the equipment scheduled
for replacement before hearing about the program, although only 29 percent had scheduled
purchases specifically within their budgets. Gaskets andnozzles were most commonly
The Cadmus Group lnc. i Energy Seruices 23
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 370 of 1 365
Case No. PAC-E-14-07
Wtnessi Kathrun C. HvmasMarch 16. 201f
mentioned amongst those who had scheduled replacements. Drains, rain birds, sprinkler heads,
hand lines, wheel lines, and pivots were also mentioned.
As mentioned earlier, many exchange respondents knew that the equipment they were replacing
wasted energy or water, so they expected energy savings from these measures. Of the 74 percent
that expected electric savings, 83 percent reported that the amount of electric savings met their
expectations. Respondents also reported the additional benefits of improved crop quality and
yield as a result of their participation in the progftrm (see Table 15).
Only four exchange respondents (six percent) reported replacing equipment installed through the
program. Three replaced broken or worn equipment, and one replaced gaskets with new gaskets.
Thirty-three percent of non-exchange respondents had plans for replacing some of the equipment
covered by the program before hearing about the program. This primarily included sprinklers,
regulators, andnozzles. Only 23 percent of respondents receiving audit or consultation services
had already budgeted for that service. Thirty-three percent of installed measures were also
previously accounted for in budgets.
When questioned on a measure-by-measure basis, non-exchange respondents expected electricity
savings from 60 percent of the measures. Seventy-one percent of respondents indicated that their
energy savings expectations were met.
Non-exchange respondents also saw additional benefits beyond energy. As shown in Table 16,
the most corlmon benefits were a more uniform distribution of water, improved crop yields, and
improved crop quality.
Table 16. Additional Benelits Associated with Non-Exchange Measures
The Cadmus Group lnc. i Energy Services 24
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 37 1 of 1 365
Case No. PAC-E-14-07
Witness: Kathrun C. Hvmasltllarch 'lS" 2011
Ten percent of non-exchange respondents (four participants) reported removing equipment that
had been installed as part of the progftrm. Two respondents replaced nozzles for proper
fi.rnctioning of the system, and two respondents switched out equipment because they changed to
gravity fed systems.
Spillover
Exchange
Prior to participating in this program from 2006-2008, 23 percent of exchange respondents had
participated in an energy-efficiency progftlm. Six participated in other programs related to
inigation equipment.
After program participation, 53 percent of respondents claim to have purchased additional
energy-efficient measures on their own. These included additional nozzle and gasket
replacements, as well as upgrades to pipes and lines, pumps, pivots, sprinklers, and rain birds.
One individual installed a windmill (Table 17).
Table 17. Measures Installed Outside the Program
Most respondents agree that their participation in the equipment exchange program influenced
their decision to install other high-effrciency equipment; on a scale of 1 to 10, the median score
was 7. These results are presented in Figure l.
The Cadmus Group lnc. i Enengy $ervices 25
PacifiCorp
Rocky Mountain Porver
Exhibit No. 5 Page 372 of 1 365
Case No. PAC-E-I447
Witness: Kathrun C. Hvmashlarch 16. 2011
f igure 1. Influence of Equipment Exchange Component in Decision to Install Additional
Efficient Equipment
5% tO% t5o/o 20% 25% 30%
Percent of Exchange Respondents i!lit
Non-Exchange
After participating in the program, 33 percent of non-exchange respondents made additional
energy-efficient improvements. As shown in Table 18, the most common improvements were
pumps and VFDs, followed by sprinkler packages.
When asked how much participating in this program influenced them to make these additional
energy-efficient improvements, there was a wide range of responses, with a median score of 7 on
a scale of I to 10 (Figure 2).
o1o
ccooo:3E 8o,'=od' -EUJ I
EE 5
lto P9E )tE LoogE 3EC#E z
tr t
The Cadmu$ Group lnc. i Energy Services 26
leerli!qH
Roclq Mountain Power
Exhibit No, 5 Page 373 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch '!6. 2011
Figure 2. Influence of Influence of Non-Exchange Component in Decision to Install
Additional Effi cient Equipment
0% 5% 70% ts% 20% 2s% 30%
Percent of Non-Exchange Respondents
Energy-Efficiency Decision Making
Exchange
Exchange participants were asked a less detailed set of questions due to the nature of the
exchange component and the lack of an explicit decision tree as compared to the non-exchange
measures. Respondents find energy efficiency to be very important to the operations and
management of their business. On a scale of 1 to 10, the median score was 9. When asked why,
74 percent ofall respondents mentioned costs. Respondents devoted an average of 18 percent of
their annual budgets to electricity and 9.5 percent to water bills.
Respondents were evenly split between those who felt they had sufficient technical resources in
house to address the management of electric and water costs, and those who did not.
Non-Exchange Measures
Non-exchange respondents reported that energy efficiency is very important to their business. On
a scale of I to 10, the median score of 9 was largely attributed to cost, as specified by 59 percent
of respondents. Some mentioned it was a large portion of their operating budgets. Two
respondents mentioned that they are dependent on energy to operate their businesses. Of the few
who did not rank energy efficiency as important, three mentioned that ensuring their crop is
produced is their first and foremost priority, and energy efficiency comes after that goal is met.
Despite those results,4T percent of non-exchange respondents reported that they do not have
sufficient in-house technical resources at their sites to address the management of electric and
water costs. Most commonly, non-exchange participants reported a need for education and
o--Ep s
.EiT 8o i'i?5 7'IoHE 5
hEotl )iEbg 4
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7
The Cadrnus Group lnc. i Energy Services 27
Rocky Mountain Power
Exhibit No. 5 Page 374 of'1365
Case No. PAC-E-14-07
PacifiCorp
equipment to help them gauge and monitor their energy use. Rocky Mountain Power has taken
steps to address this lack of technical expertise by changing implementation contractors.
Table 19. Desired Technical Assistance
For this program, 88 percent of respondents either did not need assistance or received adequate
assistance from Rocky Mountain Power or Franklin Soil and Water Conservation District.
Irrigation Equipment Vendors
Participating irrigation equipment vendors reported that, overall, customers were interested in
participating in the program because they were attracted by the financial incentives and
recognized the need for efficiency improvements at their site. Some customers were somewhat
reluctant initially to get involved in the program because of the financial investment required, but
vendors said that once they showed customers that energy management efforts improved their
bottom line, the customers usually invested in the program. Nevertheless, it was often a
challenge to convince customers to lay out the cash up-front. Most customers were sufficiently
motivated by the incentives to undertake energy efficiency upgrades following the audit.
However, some equipment vendors stated that the incentives offered by Rocky Mountain Power
were a little low. In particular, some customers stated that Rocky Mountain Power should
increase its incentives on sprinkler pivots and linear systems, as the incentives only covered
about half the price for the product (e.g., sprinkler regulators are at least $10 per head but the
incentive was only $6 per head). Similarly, customers noted that, while the incentives on straight
board nozzles covered 100 percent ofthe product cost, the incentive on the flow controlnozzle
was $4, which covered about half the cost. Finally, vendors noted that customers asked for
incentives for some other products, such as sprinkler heads and discharge hoses from the
mainline to the wheel line, and that the pump upgrade component of the program was unclear,
reducing customer participation.
A couple of irrigation equipment vendors also questioned the incentive limit of $900 per
package. Specifically, they pointed out that, if a customer spends $1000 on new equipment, then
$900 in compensation is too high. On the other hand, for a customer that spends $5000, a $900
incentive package is too low. These vendors stated that Rocky Mountain Power should not use a
'oone size fits all" incentive program, because it does not make sense in energy efficiency terms
to more fully compensate the smaller systems as opposed to the larger systems.
Witness: Kathrvn C. HvmasMarch 1S. 2011
Don't know what helo is needed
The Cadmus Group lnc. i Energy $ervices 28
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 375 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 201f
lnteraction with Rocky Mountain Power or Third-Party Staff
Exchange
Exchange respondents worked with an average of three program representatives as part of the
equipment exchange. As shown in Table 20,84 percent of exchange respondents worked with
irrigation dealers, 31 percent worked with Rocky Mountain Power account representatives, and
30 percent worked with other Rocky Mountain Power staff.
Table 20. Interaction with Rocky Mountain Power or Third-Party Staff - Exchange
Overwhelmingly, exchange respondents had positive feedback on about the program
representatives they worked with. Eighty-nine percent of exchange respondents either said that
their experience was good or that the people were helpful.
Non-Exchange
On average, non-exchange respondents interacted with two program representatives while
participating in the program. The most common interactions were with installation contractors
and Rocky Mountain Power account representatives, as shown in Table 21.
Table 21. Interaction with Rocky Mountain Power or Third-Party Staff- Non-Exchange
Measures
Non-exchange respondents were very pleased with the interactions they had with program
representatives. Eighty-two percent provided positive feedback, stating that program
representatives were easy to work with, informative and helpful when it came to questions about
Measures
Franklin Soil and Water Conservation District
Franklin Soil and Water Conservation District
The Cadmus Group lnc. i Energy Services 29
Iepifi9_se
Rocky Mountain Power
Exhibit No. 5 Page 376 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
both the program and the irrigation equipment. Only five respondents (11 percent) provided
neutral feedback, and in four of these cases, their concerns related to slow payment or measure
installation.
Irrigation Equipment Vendors
All irrigation equipment dealers reported that Rocky Mountain Power staffwas easy to work
with and helpful regarding the Irrigation Energy Savers program. During the2006-2008 program
cycle, some vendors expressed concerns over the time it took to receive payments from Rocky
Mountain Power (e.g., 3 to 4 months), but that payment speed improved over time. However,
some dealers stated the amount of paperwork for the program was a bit high.
Satisfaction
Exchange
Exchange respondents were very satisfied overall with the progftrm. On a scale of 1 to 10, there
were no scores below 6, and the median score was a 9.
Respondents made several suggestions for program improvement. Most commonly, exchange
participants suggested expanding program offerings to include additional measures (mentioned
six times). Nearly a quarter of exchange respondents said they would not change anything about
the program.
Non-Exchange
Overall, non-exchange respondents were satisfied with the program. On a scale of 1 to 10, the
median score was an 8. Only two participants reported that they would not participate in the
program again: one that uses a gravity fed system, and one that did not find the program
solutions to be cost effective. The most common suggestions from non-exchange participants for
improving the program were increasing the incentive amount and reimbursing them faster. Other
suggestions include providing a list of local contacts.
In addition, one person suggested a post-installation audit to determine the effectiveness of the
newly installed system. There were also two suggestions from this group for expanding the
program to include rain birds and small pivots.
Irrigation Equipment Vendors
In general, most equipment vendors stated the Energy Savers program was very effective in
getting customers to make energy management changes, and participants were strong proponents
of the program. For example, dealers noted that water pressure improved significantly with new
gaskets andnozzles. They also stated that the incentives for most products were sufficient.
However, some participants did indicate that the incentives for some products, e.g., pivot and
linear sprinkler systems, were too low, and that some additional sprinkler products should be
incentivized.
The Cadmus Group lnc. i Energy Services 30
Rocky Mountiain Power
Exhibit No. 5 Page 377 of 1 365
Case No. PAC-E-14-07
PacifiCorp Wtness: Kathrvn C. HvmasMarch 16. 2011.................-.....--........:
Conclusions
Overall, the program is successful in getting customers engaged in systematic equipment
replacement, which helps minimize pumping energy and wasted water and improve
overall operational effrciencies.
Most of the participating customers are very satisfied with their involvement in the
program and with the performance of the installed energy-efficiency measures. Table 4
presents customer satisfaction with the program as a whole, as well as their satisfaction
with the measures installed through the program. In addition, over 97 percent of surveyed
participants indicated they would participate in the program again.
While many participants had general plans to replace their equipment eventually, most
would not have replaced all of the equipment covered by the program. Half would not
have been able to undertake upgrades for several years without the program.
Energy efficiency was reported by survey respondents as being important, primarily
because of the cost savings. Participating irrigation vendors reported that some customers
were reluctant to invest in the program measures because of the up-front costs.
Survey respondents reported that although energy efficiency is important, they often
don't have the necessary technical knowledge to address it.
Recommendations
o Promote grower education on water management and tracking practices.
o Refine program marketing to decrease confusion between the Irrigation Energy Savers
and Direct Load Control programs, and to decrease customer concerns regarding system
shut off.
o Consider increasing incentives, particularly for linear and pivot sprinkler packages, to get
more customers involved.
The Cadmus Group lnc. i Enengy Servlces 31
Roclry Mountain Po,er
Exhibit No. 5 Page 378 of 1 365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 379 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
Cost-Effectiveness Ana lys is
To assess cost-effectiveness, Cadmus conducted an analysis of program costs and benefits from a
Total Resource Cost test perspective including a l0 percent benefit for DSM, as well as from the
Participant, Program Administrator, Rate Impact, and standard Total Resource Cost perspectives,
using Cadmus' DSM Portfolio Pro model. These five perspectives follow methods and
guidelines consistent with the California Standard Practice Manual. The perspectives are defined
as follows:
(1) PacifiCorp Total Resource Cost Test (PTRC): This test examined progftrm benefits and
costs from the Company and customers' perspectives, combined. On the benefit side, it
includes avoided energy costs, capacity costs, and line losses plus a 10 percent adder to
reflect non-quantified benefits. On the cost side, it includes costs incurred by both the utility
and participants.
(2) Total Resource Cost Test (TRC): This test examined progftrm benefits and costs from
Company and customer's customers' perspectives, combined. On the benefit side, it included
avoided energy costs, capacity costs, and line losses. On the cost side, it included costs
incurred by both the utility and participants.
(3) Utility Cost Test (UCT): From Rocky Mountain Power's perspective, benefits were
achieved through avoided energy and capacity costs and line losses. Costs included any
program administration, implementation, or incentive costs associated with funding the
progftrm.
(4) Ratepayer Impact (RIM): All ratepayers (participants and nonparticipants) may experience
increases in rates to recover lost revenues. This test included all Rocky Mountain Power
program costs as well as lost revenues. As benefits, this test included all avoided energy
costs, capacity costs, and line losses.
(5) Participant Cost Test (PCT): From this perspective, program benefits included bill
reductions. Costs included any customer contribution to the measure cost.
Table 22 summarizes various components of the five tests.
Table 22. Benefits and Costs Included in Various Tests
PTRC Present Value of Avoided Energy and Capacity Costs
with 10% Adder for Non-quantified Benefits Program Administrative and Marketing Cost + Participant Cost
THC Present Value of Avoided Enerov and Caoacitu Costs Program Administrative and Marketing Cost + Participant Cost
UCT Present Value of Avoided Energy and Capacity Costs Program Administrative, Marketing, and lncentive Cost
RIM Present Value of Avoided Energy and Capacity Costs Program Administrative and Marketing Cost + Present Value of
Lost Revenues
PCT Present Value of Bill Savinqs Participant Share of Measure Cost
The Cadrnus Group lnc. / Energy Services 33
Ieqi{9-orp-
Roclry Mountain Power
Exhibit No. 5 Page 380 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
Cadmus determined program cost-effectiveness for five savings scenarios:
Scenario l: Expected Savingsla
Scenario 2: Ev alttated Savings
Scenario 3: High Case Evaluated Savings
Scenario 4: Low Case Evaluated Savings
RTF's Proposed Deemed Savingsls
Table 23 presents selected measure-level assumptions used to generate the inputs for each cost-
effectiveness scenario. In addition to savings estimates, Cadmus utilized proposed measure cost
estimates and measure lives developed by the RTF to calculate cost effectiveness for the RTF
scenario.
Table 23. Selected Per-Unit Assumptions Used for Cost-Effectiveness Analysis
Nozzles 1 1.9 36.7 $0.40 $2j2 4 4
Gaskets 24.3 22.1 $1.78 $3.92 4 5
Drains 24.3 22.1 $2.65 $13.67 4 5
Pressure Requlators 113.0 37,6 $8.s0 $6.13 4 5
Sorinkler Packaoes 10,792.0 11,204,4 $3,820.00 $2,936.33 4 5
Svstem Consultations 3,200.0 3,200.0 $0.00 $0.00 7 7
System Analyses 55,089.5 55,089.5 $57,082.60 $57,082.60 7 7
Table 24 provides selected inputs to the cost-effectiveness analysis. These include the energy
savings for each scenario, measure lives, discount rates, line losses, and program costs. Program
benefits are comprised of energy savings and their associated avoided costs. Benefits are accrued
over the expected useful life of the installed measure.
Cadmus used measure cost and measure life assumptions from Review and Development of Utah Power's
Irrigation Program in ldaho, John Fazio, August 37,2005, for the expected and evaluated cost-effectiveness
scenarios. Expected savings are also based on this document.
http://www.nwcouncil.org I energy /rtf/meetings/20 I 0/0 l,rDefault.htm
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The Cadrnus Group lnc. i Energy Services 34
le_cili9prP_
Roclry Mountain Power
Exhibit No. 5 Page 38 1 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasMarch 16. 2011
Table 24. Selected Cost-Effectiveness Analysis Inputs
Net Prooram Savinos (kWh/vear)7,002,101 2,031,007 5,855,488 228,273 8,750,208
Discount Rate 7.40o/o 7.400/o 7.400/0 7.400/0 7.40Vo
Line Loss 10.392%10.39270 10.392%10.392%10.392%
Schedule 10 Retail Rate $0.0347 $0.0347 $0.0347 $0.0347 $0,0347
Net Participant Costs $872,760 $872,760 $872,760 $872,760 $1,146,375
Proqram Costs
Proqram Manaqement Costs $176,812 $176,812 $176,812 $176,812 $176,812
Enoineerino Costs $11,554 $11,554 $11,554 $11,554 $11,554
lncentive Costs $528,496 $528,496 $528,496 $528,496 $528,496
Utilitv Administrative Costs $72,036 $72,036 $72,036 $72,036 $72,036
Total Prooram Costs $788,897 $788,897 $788,897 $788,897 $788,897
Table 25,Table26,Table27,Table28,and Table 29 presentthe results of our cost-effectiveness
analysis for the Irrigation Energy Savers Program from five perspectives across all program
years, using a freeridership of 26.5 percent. The analysis was based on the East Commercial
Cooling 16 percent load factor decrement which most closely represents irrigation usage.'u
t Table 25. Cost-Effectiveness Summary for the Program 2006-2008 - Scenario L: Expected
Savings
Total Resource + Conservation Adder (PTRC)$0.044 $1,112,799 $1,226,204 $1 13,405 1.10
Total Resource No Adder (TRC)$0.044 $1,112,799 $1,114,731 $1,932 1.00
Utility (UCI $0.031 $768,535 $1,114,731 $346,1 96 1.45
Ratepayer lmpact (RlM)$0.073 $1,924,562 $1,114,731 -$709,831 0.61
Participant (PCT)$0.035 $872,760 $1,584,522 $711,762 1.82
Lifecvcle Revenue lmoact (dollars)$0.000058589
Discounted Participant Payback (years)5.23
16 IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan Volume II
Appendices, available online: http:/iwww.pacificorp.com lcontentldant/pacificorp/doc/Environment/
Environmental Concerns /Integrated_Resource_Planning_6.pdf
The Cadrnus Group lrrc. i Energy $ervices 35
E"h i bit f"""YPYsTlH:ii5fJ
Case No. PAC-E-14-07
Table 26. Cost-Effectiveness Summary for the Program 2006-2008 - Scenario 2: Evaluated
Table 27. Cost-Effectiveness Summary for the Program 2006-2008 - Scenario 3: Evaluated
Table 28. Cost-Effectiveness Summary for the Program 2006-2008 - Scenario 4: Evaluated
Savings Low Case
Savings
Total Resource + Conservation Adder (PTRC)$0.125 $1,112,799 $479,573 -$633,226 0.43
Total Resource No Adder ffRC)$0.12s $1,112,799 $435,975 -$676,824 0.39
Utility (UCT)$0.086 $768,535 $435,975 -$332,560 0.57
Ratepayer lmpact (RlM)$0.130 $1,1s7,946 $435,975 -$721,971 0.38
Participant (PCT)$0.098 $872,760 $917,907 $45,147 1.05
Lif ecvcle Revenue lmoact (dollars)$0.000042121
Discounted Participant Pavback (vears)5.96
Savings High Case
Total Resource + Conservation Adder (PTRC)$0.047 $1,1 12,799 $1,246,933 $134,133 1.12
Total Resource No Adder (TRC)$0.047 $1,112,799 $1,133,575 $20,776 1.02
Utility (UCT)$0.032 $768,535 $'1,133,575 $365,040 1.47
Ratepayer lmpact (RlM)$0.075 $1,900,212 $1,133,575 -$666,637 0.63
Participant (PCT)$0.036 $872,760 $1,560,172 $687,413 1.79
Lifecvcle Revenue lmoact (dollars)$0.000045333
Discounted Particioant Pavback (vears)2.12
Total Besource + Conservation Adder (PTRC)$1.053 $1,112,799 $58,101 -$1,054,698 0.05
Total Resource No Adder fiRC)$1.053 $1,112,799 $52,819 -$1,059,990 0.05
Utility (UCT)$0.727 $768,535 $52,819 -$715,716 0.07
Ratepayer lmpact (RlM)$0,771 $81 5,1 20 $52,819 -$762,300 0.06
Participant (PCT)$0.825 $872,760 $57s,080 -$297,680 0.66
Lilecvcle Revenue lmoact (dollars)$0.000039232
Discounted Participant Payback (years)0.00
The Cadmus Group lnc. i Energy Services 36
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 383 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
Table 29. Cost-Effectiveness Summary for the Program 2006-2008 - Scenario 5: RTF
Proposed Deemed Savings
Total Resource + Conservation Adder (PTRC)$0.044 $1,386,415 $1,525,277 $138,862 1.10
Total Resource No Adder fiRC)$0.044 $1,386,415 $1 ,386,615 $201 1.00
Utility (UCT)$0.025 $768,535 $1,386,615 $618,080 1.80
Ratepayer lmpact (RlM)$0.067 $2,083,472 $'l ,386,615 -$696,857 0.67
Particioant (PCT)$0.037 $1,146,375 $1,843,432 $697,057 1.61
Lifecycle Revenue lmpact (dollars)$0.000047388
Discounted Particioant Pavback (years)2.49
The Cadmus Group lnc. i Hnergy $ervices 37
Roclry Mountain Power
Exhibit No. 5 Page 384 of I 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 385 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasMarch 16. 2011
Appendix A. Irrigation Energy Savers Process Flow
Diagrams
Equipment Exchange Overview
Participating
Dealers
Program
Administration
The Cadmus Greup lnc. i Hnengy $ervices 39
-?-q-pili9srp--
Roclry Mountain Power
Exhibit No. 5 Page 386 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
Pivot Package/Linear Equipment Upgrade Overview
Eligible
Customers
Participating
Dealers
Program
Administration
The Cadmus Group lnc. i Energy Services 40
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PacifiC*np
Roclq Mountain Power
Exhibit No.5 Page 393 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. Hvmastularch 1S. 2CI11
Appendix G. Participant Exchange Survey lnstrument
Irrigation Energy Savers
Equipment Exchange Participant Interview Guide
Telephone:
Cell phone:
Fax:
State:
Company:
Name:
Title:
City:zip:
lnterview date:Time:
Hello, my name is
Mountain Power.
from [interview firm], calling on behalf of Rocky
We are conducting a study for Rocky Mountain Power regarding their energy
efficiency programs. Could I please speak with [CUSTOMER OF RECORDJ or the
person who most often pays the electric bills?
[If "Yes," continue with introduction below]
[If 'No, this site is under new ownership or that person is no longer involved at this
site," ask respondent if they have any contact information for the person you are
trying to reach. If they do, record the information and try reaching the party at the
new number. If they do not, thank them and end ca11.]
Introduction
Rocky Mountain Power is evaluating its Irrigation Energy Savers Program and would appreciate
your input. "It is important for Rocky Mountain Power to include your opinions in this study so
they can serve your needs better."
This survey is for research purposes only and this is not a marketing call. Your
individual responses will be kept strictly confidential and only reported in
aggregate. The survey will take approximately 20 minutes. As a Thank You for
vour assistance. at the end of the survev we would like to offer vou a $25 sift card,
which will be mailed to vou
Do you have a moment to answer some questions about yorr experience with the
program?
INOTE: If the customer states that he has participated in an Irrigation Energy Savers site visit, or
has been scheduled for a site visit, state: "'We are conducting this survey in addition to the site
visit. We perform site visits to get a better understanding of the energy savings you get from the
program, while this survey is focused on your energy effrciency decisions and your satisfaction
with the program."]
The Cadmus Group lnc. i Hnergy $ervices 47
?q-cifiQqP_
Roclry Mountain Power
Exhibit No. 5 Page 394 of I 365
Case No. PAC-E-'14-07
Witness: Kathrun C. HvmasMarch 16. 201{
[If "No -Not a convenient time," ask if Respondent would like to 1. Start now and do part of the
survey, or 2. Arrange a more convenient time we can call them at work or at home.]
[If customer wants to verifu the validity of the survey, tell them that they are welcome to contact
Hallie Gallinger, PacifiCorp Program Manager, at [phone].
[If "No" - Arrange callback]
[If "Refused" - Thank and terminate.
Confirmation
I would like to give you a bit more background on this survey. All of these questions are about
your participation in the Irrigation Energy Savers Equipment Exchange program in the 2006
through 2008 time period. These questions are not about participation after 2008. We understand
that you may have also participated in other Irrigation Energy Savers program options, but this
survey focuses specifically on the equipment exchange option.
1. The Rocky Mountain Power records show that you participated in the Irrigation Energy
Savers progftrm during [Year(s)], and at that time exchanged NAME THE TYPES OF
E QU I P MENT EXC HANG E D./Is that correct?
1. Yes [F' YES + GO TO QUESTION 5.J
2. No, type of equipment exchanged is incorrect3. No, type of participation incorrect (SKIP TO 3)
98. No, date is incorrect (SKIP fO 4)
99. 98 DK (TERMTNATE)
2. IIF QL: NO, TYPE OF EQUIPMENT EXCHANGED IS INCORRECT, ASKJ What did you
exchange?
IRECORD RESPONSEJ
3. FF QL: NO,TYPE OF PARTICIPATION IS INCORRECT, ASKJ How did you participate?
IRECORD RESPONSE, SWITCH TO OTHER SURVEYJ
4. IIF Q1-- NO, DATE IS INCORRECT, ASKJ About when did you participate in these
activities?
1.MONTH
-YEAR
98. DK (DO NOr TERMTNATE)
99. REF qERMTNATE)
Participation
5. How did you first learn about the Irrigation Energy Savers Equipment Exchange?
IDO NOT READ RESPONSES; MARKALL THAT APPLYJ
l. Contacted by my Rocky Mountain Power account representative
2. Contacted by other Rocky Mountain Power staff
The Cadmus Group lnc. i Energy Services 48
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 395 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
3. Contacted by Franklin Soil and Water Conservation District
4. Contacted by Nexant
5. Program sponsored a presentation
6. Trade Publication
7. Word of mouth; from another business colleague
8. Through an equipment dealer
9. Through an irrigation contractor
10. Through a trade organization or professional organization/association
11. Through printed material or outreach materials sent by the Program
12. At a trade show
13. Through family, friend, or neighbor
14. Participation in other Rocky Mountain Power Programs
15. Had exchanged equipment through the program previously
16. Internet research/found Program on the Rocky Mountain Power website
17. Other ISPECIFY]
98. Don't know
99. Refused
6. Why did you decide to participate in the equipment exchange?
IDO NOT READ RESPONSES; MARKALL THAT APPLYJ
l. To save money on electric bills
2. To save money on water bills
3. To replace old equipment
4. To replace broken equipment
5. To reduce maintenance costs
6. Because the Program was sponsored by ROCKY MOI-INTAIN POWER
7. Previous experience with other Rocky Mountain Power Programs
8. To help protect the environment
9. To save energy
10. Recommended by Program contact
11. Recommended by contractors/trade allies
12. Recommended by another Rocky Mountain Power customer; word of mouth
13. Recommended by family, friend, or neighbor
l4.Part of a broader maintenance or renovation
15. Other ISPECIFY]
98. Don't know
99. Refused
The Cadrnus Group lnc. i Enengy Services 49
PacifiCorp
Rocky Mountein Power
Exhibit No. 5 Page 396 of 1 365
Case No. PAC-E-14-07
Witness: Kalhrvn C. HvmasMarch 16. 2011
7. Thinking back to when you were first involved with this exchange, were there any aspects
of the Program that initially caused you concern?1. Yes
2. No /SIK1P TO ENROLLMENTJ
98 Don't know [SKIP TO ENROLLMENTJ
99 Retused ISKIP TO ENROLLMENTJ
7a. IIF 7 : YES, ASKJ What caused your concern?
IRECORD RESPONSEJ
7b. IIF 7 : YES, ASKJ Was this issue resolved?I Yes2 No lSrK/P TO ENROLLMENTJ98 Don't know ISKIP TO ENROLLMENTJ
99 Retused ISKIP TO ENROLLMENTJ
7c. IIF 7 : YES, ASKJ How was it resolved?
IRECORD RESPONSEJ
Enrollment
8. Did you encounter any problems or difficulties during the application, review or approval
processes for this exchange?l. Yes
2. No ISrUP TO 10J
98. Don't know ISKIP fO 10J
99. Retused [SKIP rO 10J
9. [IF 8 : YESJ Whatproblems, delays or difficulties did you encounter?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
l. The process took too long2. The process was too complex3. The applications materials were difficult to understand4. The equipment dealer was not knowledgeable5. The Program staff was not knowledgeable6. Other ISPECIFYJ98. Don't know
99. Refused
9a IIF 9 : MORE THAN ONE ANSWERJ: What was the most difficult issue for you?
[RECORD RESPONSEJ
10. If you could change anything about the application process, what would you change?
IRECORD RESPONSEJ
The Cadmus Group lnc. i Energy Services 50
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 397 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
l0a. Before this equipment exchange had you participated in this program or other energy
efficiency programs?l. Yes
2. No [IF NO skip to Exchanged Effrciency Measures]
98. Don't know [IF DON'T KNOWREFUSED, skip to Exchanged Efficiency Measures]
99. Refused [IF DON'T KNOWREFUSED, skip to Exchanged Efficiency Measures]
l}b. IIF ]0a: YESJ What energy efficiency pro$ams have you participated in?
[RECORD RESPONSEJ
l}c. [IF 10o: YESJ Who were the sponsors of these programs?
IruECORD RESPONSEJ
Exchanged Efficiency Measures
11. What was the operating condition of the equipment that was replaced through this
exchange? MULTIPLE RESPONSES OK.l
1. Old equipment had failed or burned out
2. Old equipment had problems, but still working
3. Old equipment wasted water
4. Old equipment wasted energy
5. Old equipment in working condition with no problems
6. Other ISPECIFYJ
98. Don't know
99. Refused
On a scale of 1 to 10, where 1 is not at all satisfied and 10 is very satisfied, how
satisfied would you say you are with the performance of the new measures installed as
a result of this exchange?
IRECORD RESPONSEJ
98. Don't know
99. Refused
l2a. [If 12 <:5] Why do you say that?
IRECORD RESPONSEJ
Operational Changes
13. At the time that you participated in this equipment exchange, did you have an overall
plan to increase the energy efficiency of your operations?
1. Yes
12.
The Cadrnus Group lnc. i Energy Services 51
SpiliQqP-
Rocky Mountain Po\ rer
Exhibil No. 5 Page 398 of 1 365
Case No. PAC-E-14{7
Wtness: Kathrvn C. HvmasMarch 16. 2011
2. No
98. Don't know
99. Refused
13a. Did you change the manner in which you operated equipment after the exchanged
equipment was installed?l. Yes
2. No fSrKlP TO 15J
98. Don't know
99. Refused
l3b. Were these changes part of the overall plan to increase the energy efficiency of your
operations?1. Yes
2. No lSKlP TO 15J
98. Don'tknow ISKIP fO 15J
99. Retused ISKIP rO 15J
13c. What did you change?
[RECORD RESPONSEJ
14. IASK IF 13C MENTIONS DURATION OR FREQUENCY OF SCHEDULINGJ Did you
change the duration or frequency of irrigation scheduling since the measures were installed?1. Yes2. No /SrVP TO 15J
98. Don't know
99. Refused
l4a. Please explain what changes were made
IRECORD RESPONSEJ
15. Have any measures installed through this project been removed?
1. Yes
2. No /S(1P TO 16J
98. Don't know
99. Refused
15a. What was removed?
IRECORD RESPONSEJ
15b. Why was it removed or replaced?
IRECORD RESPONSEJ
The Cadmus Group lnc. i Energy Services 52
PacifiCorp
Roclq Mountain Power
Exhibit No. 5 Page 399 of '1365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 1S, 2011
15c.About when was it removed or replaced?
IRECORD RESPONSEJ
Thinking about the equipment that you exchanged, was replacement of any of the
equipment scheduled before you heard about the program?1. Yes [IF YES, PROBEJ2. No 1SIK1P TO IU
98. Don't know
99. Refused
l6a. What replacement was scheduled?
IfuECORD RESPONSEJ
17. [FR]Was money for exchange equipment included in your most recent budget before you
participated in the program?
1. Yes
2. No
98. Don't know
99. Refused
98. Don't know
99. Refused
18. When you exchanged this equipment, did you expect savings on:
18c. IASK IF ]8a : YESJ Do the electric energy savings meet your expectations?1. Yes /Sr(/P TO lSeJ2. No
98. Don't know
99. Refused
l8d. IASK IF l8c :NoJ When do you expect these energy savings?1. Immediately2. Within the next 6 Months3. Within the next year4. Within the next two years5. Never [IF NEVER, ASK "Why do you not expect savings from this in the future?"]
98. Don't know
99. Refused
Yes No Don't Know Refused
l8a. Electricitv?
18b. Water?
The Cadmus Group lnc. / Energy Services 53
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 400 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16" 2011
18e. IASK IF ]8b : YESJ Do the water savings meet your expectations?l. Yes [SK1P TO ISg.J
2. No
98. Don't know
99. Refused
l8f. IASK IF ]8e :NoJ When do you expect these water savings?
1. Immediately
2. Within the next 6 Months
3. Within the next year
4. Within the next two years
5. Never IIF NEVER, ASK 'Why do you not expect savings from this equipment
exchange in the future?l
98. Don't know
99. Refused
18g. Are there any other benefits that you anticipate?
IPROBE IF NEEDED: HAVE YOU OBSERVED ANY CHANGES IN LEVEL OF
P RODUCTION? P RO DUCT SUALITY? J
IRECORD RESPONSEJ
19. How satisfied are you with the equipment exchange?
Please use a scale from 1 to 10, with I being extremely dissatisfied and l0 being extremely
satisfied.
IRECORD RESPONSEJ
98. Don't know
99. Refused
l9a. IIF 819<:5/ V/hy do you say that?
Freeridership and Market Effects
20. On a scale from I to 10, how important were the following factors in deciding which energy
efficiency actions to take:
Factor Score
Information provided by
equipment dealer on measure
savings
Equipment provided at no cost to
me
The Cadmus Group lnc. i Energy Services 54
PacifiConp
Rocky Mountain Power
Exhibit No. 5 Page 401 of '1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
Familiaritv with these measures
Able to get rid of old equipment
throush the exchanse
Had replaced this type of
eouioment in the oast
21. [FR]Before this program, had you previously replaced similar equipment?l. Yes2. No [IF NO, SKIP TO 22]
98. Don't know
99. Refused
2la.What equipment had you replaced? IRECORD RESPONSEJ
22. [FR] Regarding the equipment you replaced through this project, would you have replaced all
of the equipment or some of the equipment without the program?1. All2. Some3. None UF NO, SKIP TO 241
98. Don't know99. Refused
22a. [ASK IF 22 :"All" or "Some J What would you have replaced? IRECORD
RESPONSEJ
22b. [ASK IF 22 :YesJ [FR] Would you have replaced the equipment to the...1. Same level of efficiency2. Higher level of efficiency3. Lower level of efficiency98. Don't know99. Refused
23. IASK IF 22 :YesJ [FR]Without the program, would you have replaced this
equipment...4. In the same year?
5. In one to two years?
6. In three to five years?
7. More than five years out?
98. Don't know
99. Refused
The Cadmus Group lnc. i Energy Services 55
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 402 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
Energy Efficiency Decision Making
Next,I would like to ask you some questions about the decision making process in regards to
energy efficiency purchases and upgrades.
24. Using a I to l0 rating scale, where 0 means not at all important and 10 means extremely
important, please rate how important energy efficiency is to the operations and
management of your business?
IRECORD RESPONSEJ
98. Don't know
99. Refused
24b. Why do you say that?
IRECORD RESPONSEJ
25. Do you have sufficient technical resources in house to address the management of
energy and water costs?l. Yes
2. No
98. Don't know
99. Refused
Spillover
26. After this equipment exchange, did you participate in other energy efficiency program
activity sponsored by this utility?l. Yes [RECORD NAME OF PROGRAMJ
2. No [IF NO, SKIP TO 28]
98. Don't know
99. Refused
JtF26:YES,ASKJWhatdidyoudothroughtheprogram(s)?-[RECoRD
RESPONSEJ
After this equipment exchange, have you since made any other energy efficiency
improvements or purchases on your own without any assistance from a utility or other
organization?l. Yes
2. No ISrUP TO INTERACTIONJ
98. Don't know ISKIP TO INTEMCTIONJ
99. Retused ISKIP TO INTERACTIONJ
27.
28.
The Cadrnus Group lnc. / Hnergy $ervices 56
?eqili9-0rp
Rocky Mountain Power
Exhibit No. 5 Page 403 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
28a. [IF 28 : YESJ What did you purchase or install?
[RECORD RESPONSEJ
28b IIF 28 : YESJ I'm going to read a statement about the equipment that you purchased on
your own. On a scale from 1 to 10, with I indicating that you strongly disagree, and l0
indicating that you strongly agree, please rate the following statement.
"My experience with the Irrigation Energy Savers program influenced my decision to
install other high efficiency equipment on my own."
IRECORD RATINGJ
98. Don't know
99. Refused
lnteraction with Rocky Mountain Power or 3rd Party Staff
We are also interested in learning more about your interactions with the Program staff.
29. How many people did you work with in this equipment exchange? This would
include irrigation dealers, installation contractors, people from Franklin Soil and Water
Conservation District or Nexant, people from Rocky Mountain Power and others
Number of people
O [sKrP ro 32 rF:oJ
30. Who worked with you with you on this project?
IPROBE IF NEEDED, WAS IT PROJECT MANAGERS, ACCOUNT REPS, THIRD
PARTY STAFF, CONTRACTORS; MULTIPLE RESPONSEJ
1. Irrigation Dealers
2. Installation Contractors
3. Rocky Mountain Power Account Representatives
4. Other Rocky Mountain Power Energy Staff
5. Franklin Soil and Water Conservation District
6. Nexant Staff7. Other ISPECIFYJ
31. Please describe your overall experience working with these people in relation to thisproject._ [RECORD RESPONSEJ
Satisfaction
32. Would you participate in the equipment exchange again?1. Yes [IF YES, SKIP TO 33]2. No
The Cadnrus Group [nc. i Enengy Services 57
?srilr9p:e
Rocky Mountain Power
Exhibit No. 5 Page 404 of 'l 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
32a [tF 32 : NO] Why not?
IRECORD RESPONSEJ
33. If you could change anything about the equipment exchange, what would you change?
IRECORD RESPONSEJ
98. Don't know
99. Refused
34. Using a scale from 1 to 10, with 1 being extremely dissatisfied and 10 being extremely
satisfied, how satisfied are you with your overall experience with the equipment
exchange?
IRECORD RESPONSEJ
98. Don't know
99. Refused
34a. StF Q34 <:5J Why do you say that?
Organ izationa ! Data/Fi rmog raph ics
I have a few last questions about your business or organization
Approximately, what percent of your total annual operating costs do your electricity
bills represent?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Approximately, what percent of your total annual operating costs do your water bills
represent?
[RECORD RESPONSEJ
98. Don't know
99. Refused
How many people does your business employ full time?
IRECORD RESPONSE]
98. Don't know
99. Refused
35.
36.
37.
The Cadrnus Group lnc. i Energy Service*58
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 405 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
38.How many people does your business employ seasonally?
IRECORD RESPONSEI
98. Don't know
99. Refused
39. Finally, in order to send you the $50 gift certificate for participating in this survey, I need
you to confirm the spelling of your name and your mailing address:
Thank you for your time. Your opinions Ere very valuable to this research for Rocky Mountain
Power. As part of this evaluation, we will be conducting site visits and may contact you in the
future to arrange a time to conduct a site visit.
The Cadmus Group lnc. i Energy Seruices 59
PacifiCorp
Roclq Mountain Power
Exhibit No, 5 Page 406 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasMarch 16, 201f
Appendix D. Participant Non-Exchange Suruey
lnstrument
Irrigation Energy Savers
Non-Exchange Participant Interview Guide
Company:
Name:
Telephone:
Cell phone:Title: Fax:
City:State:zip:
Interview date: Time:
Hello, my name is _ from
Rocky Mountain Power.
calling on behalf of
We are conducting a study for Rocky Mountain Power regarding their energy
efficiency programs. Could I please speak with ICUSTOMER OF RECORDJ or the
person who most often pays the electric bills?
[If "Yes," continue with introduction below]
[If 'No, this site is under new ownership or that person is no longer involved at this
site," ask respondent if they have any contact information for the person you are
trying to reach. If they do, record the information and try reaching the party at the
new number. If they do not, thank them and end call.]
Introduction
Rocky Mountain Power is evaluating its Irrigation Energy Savers Program and would appreciate
your input. "It is important for Rocky Mountain Power to include your opinions in this study so
they can serve your needs better."
This survey is for research purposes only and this is not a marketing call. Your
individual responses will be kept strictly confidential and only reported in
aggregate. The survey will take approximately 20 minutes.
As a Thank You for vour assistance, at the end of the survev we would like to
offer vou a $25 eift card, which will be mailed to vou.
Do you have a moment to answer some questions about your experience with the
program?
INOTE: If the customer states that he has participated in an Irrigation Energy Savers site visit, or
has been scheduled for a site visit, state: o''We are conducting this survey in addition to the site
visit. We perform site visits to get a better understanding of the energy savings you get from the
60The Cadmus Group lnc. / Energy $ervices
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 407 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
program, while this survey is focused on your energy efficiency decisions and your satisfaction
with the program."]
[If "No - Not a convenient time," ask if Respondent would like to 1. Start now and do part of
the survey, or 2. Arrange a more convenient time we can call them at work or at home.]
[If customer wants to veriff the validity of the survey, tell them that they are welcome to contact
Hallie Gallinger, PacifiCorp Program Manager, at [phone].1
[If 'No" - Arrange callback]
[If "Refused" - Thank and terminate.]
Confirmation
I would like to give you a bit more background on this survey. All of these questions are about
your participation in the Inigation Energy Savers program from 2006-2008. These questions are
not about participation after 2008. We understand that you may have also participated in the
equipment exchange option, but this survey focuses specifically on the pivot and linear
equipment upgrade, system consultation and system analysis options.
The Rocky Mountain Power records show that you participated in the Inigation Energy Savers
program during [YEAR(S)], and at that time:
1. RECEIVED ON-SITE SYSTEM CONSULTATION; AND/OR
2. RECEIVED SYSTEM ANALYSIS AND SYSTEM REDESIGN OR EXPANSION,
AND/OR
3. RECEIVED INCENTIVES FOR PIVOT AND LINEAR SYSTEM EQUIPMENT;
1. Is that correct?
1. Yes [1F CONFIRMATION RESPONSE I IS SELECTEDI + GO TO QUESTION 2A;
IF CONFIRMATION RESPONSE 2 AND/OR 3 ARE SELECTED, GO TO QUESTION
4l
2. No, type of participation incorrect
100.No, date is incorrect (SKIP fO 3)
101.98 DK (TERMTNATE)
2. IIF Q]: NO, TYPE OF PARTICIPATION IS INCORRECT, ASKJ What type of service
was received?
IRECORD RESPONSEJIIF RESPONSE IS "ON-SITE CONSULTATION"
ASK 2AJ
[IF CONFIRMATION: 1) RECEIVED ON-SITE SYSTEM CONSULTATION, ASK]
2a. Did you have also have pump testing as a result of the system consultation?
1. Yes
2. No
98. Don't know
The Cadnrus Greup lnc. ,'Energy $ervices 61
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 408 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
99. Refused
3. IIF 81: NO, DATE IS INCORRECT, ASKJ About when were these services provided?1. MONTH _YEAR
98. DK (DO NOT TERMTNATE)
99. REF (TERMTNATE)
Participation
4. How did you first learn about the Irrigation Energy Savers?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJl. Contacted by my Rocky Mountain Power account representative
2. Contacted by other Rocky Mountain Power staff
3. Contacted by Franklin Soil and Water Conservation District
4. Contacted by Nexant Staff
5. Program sponsored a presentation
6. Trade Publication
7. Word of mouth; from another business colleague
8. Through an equipment dealer
9. Through a trade organization or professional organization/association
10. Through printed material or outreach materials sent by the Program
I l. At a trade show
12. Through family, friend, or neighbor
13. Participation in other Rocky Mountain Power Programs
14. Past Program participants
15. Internet research/found Program on the Rocky Mountain Power website
16. Other [SPECIFY]
98. Don't know
99. Retused
5. Why did you decide to participate in the Program?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
1. To save money on electric bills
2. To save money on water bills
3. To obtain a program incentive
4. To replace old equipment
5. To replace broken equipment
6. To acquire the latest technology
7. To reduce maintenance costs
8. Because the Program was sponsored by ROCKY MOLINTAIN POWER
9. Previous experience with other Rocky Mountain Power Programs
The Cadrnus Group lnc. i Energy $ervices 62
t IREC0RD RESPONSEJ
6b. [IF 6 : Yes, ASKJ Was this issue resolved?I Yes2 No ISKIP rO 7J
98 Don't know ISKIP TO ENROLLMENTJ
99 Refused ISKIP TO ENROLLMENTJ
6c. IIF 6 : Yes, ASKJ How was it resolved?
IRECORD RESPONSEJ
Enrollment
7. Did you encounter any problems, delays or difficulties during the application, review or
approval processes for the Program?
1. Yes
2. No ISK1P rO 9J
98 Don't know [SKIP fO 9J
99 Retused ISKIP rO 9J
8. IIF 7 : IES/ What problems, delays or difficulties did you encounter?
IDO NOT READ RESPONSES; MARKALL THAT APPLYJ
l. The process took too long
2. The process was too complex
Rocky Mountain Power
Exhibit No, 5 Page 409 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. Hvmashdarch 16. 2011PacifiCorp
10. To help protect the environment
I l. To save energy
12. Recommended by Program contact
13. Recommended by contractors/trade allies
14. Recommended by another Rocky Mountain Power customer; word of mouth
15. Recommended by family, friend, or neighbor
16. Part of a broader maintenance or renovation
17. Other [SPECIFY]
98. Don't know
99. Refused
6. Thinking back to when you were first involved with the Program, were there any aspects of
the Program that initially caused you concern?1. Yes
2. No ISrUP TO ENROLLMENTJ
98 Don't know ISK]P TO ENROLLMENTJ
99 Retused ISKIP TO ENROLLMENTJ
6a. [IF 6 : Yes, ASKJ What caused your concem?
The Cadmus Group lnc. i Energy Services 63
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 410 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
3. The applications materials were difficult to understand
4.
5. The Program staffwas not knowledgeable
6. The incentives were less than I expected
7. Multiple requests for more information from Rocky Mountain Power throughout the
process
8. Disagreement over initial energy savings calculations
9. Disagreement over final energy savings calculations10. Other ISPECIFYJ98. Don't know
99. Refused
8a" [IF 8 : MORE THAN ONE ANSWERJ; What was the most difficult issue for you?
IRECORD RESPONSEJ
9. If you could change anything about the application process, what would you change?
IRECORD RESPONSEJ
10. After this project did your business participate in the program after 2008?
l. Yes
2. No
98 Don't know
99 Refused
l0a. Have you participated in other energy effrciency programs?1. Yes2. No IIFNO SKIP TO 1IJ98 Don't know IIF DON'T KNOW/REFUSED, SKIP TO 1LJ99 Retused IIF DON'T KNOW/REFUSED, SK]P TO 1LJ
l}b. IIF ]0a: YESJ What other energy efficiency progftrms have you participated in?
IRECORD RESPONSEJ
l}c. fiF l0a: YESJ Who were the sponsors for these programs?
IRECORD RESPONSEJ
10d. IIF I0a: YESJ How did this program's application process compare to your prior
experience? Was it easier, harder, or about the same?l. Easier
2. Harder
3. About the same
The Cadmus Group lnc. / Energy Seruices 64
PacifiCorp
Rocky Mountain Power
Exhibit No, 5 Page 41 1 of 1 365
Case No. PAC-E-I4-07
Wtness: Kalhryn C. HvmasMarch 16. 2011
10e. IIF 10d : EASIER OR HARDERJ Why do you say that?
IRECORD RESPONSEJ
Recommended Efficiency Measu res
11. Were there any equipment, controls, services or other actions recommended through this
Program that you didn't put into place?
1. Yes2. No /1FNO SKIP TO ]2J
98. Don't know |tF DON'T KNOW, SKIP TO 12J
99. Retused [IF R, SKIP TO 12J
11a. IIF YESJ What was recommended that you didn't put in place?
IRECORD RESPONSEJ
1lb. IIF YESJ Why did you choose not to?
IRECORD RESPONSEJ
I nstalled Efficiency Measu res
12. Did this project replace existing equipment, add new equipment, do both, or do neither?
1. Only replaced existing equipment OK
2. Only added new equipment [IF TOTALLY NEW, "PLEASE DESCfuIBE" AND, SKIP
TO L4JOK
3. Replaced existing equipment and added new equipment OK
4. Neither replaced nor added equipment [SKIP TO Q 15J
98. Don't know ISKIP fO Q 15J OK
99. Retused [SKIP TO Q 15J
13. What was the operating condition of the equipment that the IINSTALLED MEASUREJ
replaced?
1. Old equipment had failed or burned out
2. Old equipment had problems, but still working
3. Old equipment in working condition with no problems
4. Expanding services or production line; wanted efficient equipment
5. Other ISPECIFY]
98. Don't know
99. Refused
14. On a scale of I to 10, where 1 is not at all satisfied and 10 is very satisfied, how satisfied
would you say you are with the performance of the new [INSTALLED MEASUREJ?
[RECORD RESPONSEJ
98. Don't know
99. Refused
The Cadmus Group lnc. i Energy $eruices 65
feqrli9prp-
Rocky Mountiain Power
Exhibit No. 5 Page 412 of 1365
Case No, PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
l4a. [If 14 <=5] Why do you say that?
IRECORD RESPONSEJ
Operational Changes
15. At the time that you participated in the program,
the energy efficiency of your operations?
l. Yes [ASK NEXT QUESTIONJ2. No /SrUP TO I6J
98. Don't know
99. Refused
did you have an overall plan to increase
15a. Did you change the manner in which you operated equipment after the new measure(s)
was/were installed?l. Yes [ASK NEXT QUESTIONJ2. No ISrVP rO 16J
98. Don't know ISKIP TO 16J
99. Retused ISKIP TO 16J
l5b. Were these changes part of the overall plan to increase the energy efficiency of your
operations?1. Yes
2. No /SrUP TO I6J
98. Don'tknow ISKIPTO 16J
99. Retused ISKIP TO 16J
15c. What did you change?
[RECORD RESPONSEJ
IASK IF 15c MENTIONS DURATION OR FREQUENCY OF SCHEDULINGI Did
you change the duration or frequency of irrigation scheduling since the measures
were installed?
No [Skip to 16]
Don't know
Refused
15d. Please explain what changes were made
IRECORD RESPONSEJ
1.
2.
98.
99.
The Cadmus Group lnc. i Energy Services 66
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 41 3 of 1 365
Cese No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
16. Have any measures installed through this project been removed?l. Yes
2. No [Skipto 18]
98. Don't know
99. Retused
l7a. What was removed or replaced?
[RECORD RESPONSEJ
l7b. Why was it removed or replaced?
[RECORD RESPONSEJ
l7c. About when was it removed or replaced?
IRECORD RESPONSEJ
18. Thinking about the equipment you installed through this program, was any of this
equipment scheduled for replacement/upgrade before you heard of the program?l. Yes [If yes, probe]
2. No [Skip to 19]
98. Don't know ISKIP TO 19J
99. Retused ISKIP TO 19J
18a. Which equipment?
IRECORD RESPONSEJ
IIF THEY RECEIVED ]) ON-SITE SYSTEM CONSULTATION OR PUMP TESTING; OR 2)
SYSTEM ANALYSIS AND SYSTEM REDESIGN OR EXPANSION, ASK:
19. [FR] Was money for the ITYPE OF SERVICE -l) Onsite system consultation or pump
testing, 2) System analysis and redesign or expansionJ you received through this project in
your budget before you participated in the program?
1. Yes
2. No
98. Don't know
99. Refused
IIF THEY KECEIVED 3) INCENTIVES FOR PIVOT AND LINEAR SYSTEM EQUIPMENT,
ASK:
20. [FR]Was money for the installation of the [INSTALLED MEASUREJ in your budget
before you participated in the program?
1. Yes
2. No
98. Don't know
99. Refused
The Cadnrus Group lnc. / Energy Services 67
PacifiCorp
Rocky Mountain Porver
Exhibit No. 5 Page 414 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
2t.When you installed the new JTNSTALLED MEASURE(S)J, didyou expect savings on:
2lc. IASK IF 2]a : YESJ Do the electric energy savings meet your expectations?
1. Yes [Sr(IP TO 2le]
2. No
98. Don't know
99. Refused
2ld. IASK IF 2]c :NoJ When do you expect these energy savings?
1. Immediately
2. Within the next 6 Months
3. Within the next year
4. Within the next two years
5. Never IIF NEVER, ASK'Why do you not expect savings from the IINSTALLED
MEASUREJ in the tuture?l
98. Don't know
99. Refused
2le. IASK IF 21b -- YESJ Do
1. Yes 1Sr(1P TO 22J
2. No
98. Don't know
99. Refused
the water savings meet your expectations?
2lf. IASK IF 2]e :NoJ When do you expect these water savings?
3. Immediately
4. Within the next 6 Months
5. Within the next year
6. Within the next two years
7. Never IIF NEVER, ASK 'Why do you not expect savings from the IINSTALLED
MEASUREI in the tuture?l
98. Don't know
99. Refused
22. Are there any other benefits that you anticipate?
IPROBE IF NEEDED: HAVE YOU OBSERVED ANY CHANGES IN LEVEL OF
PRODUCTION OR SALES? PRODUCT SUALITYU
IRECORD RESPONSEJ
Yes No Don't Know Refused
2la. Electricitv?
21b. Water?
The Cadmus Group lnc. i Energy Servlces 68
te-_ciIQqt,r
Rocky Mountain Power
Exhibit No. 5 Page 41 5 of I 365
Case No. PAC-E-'14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
23. How satisfied are you with the final cost to you of the [INSTALLED MEASURESJ?
Please use a scale from I to 10, with 1 being extremely dissatisfied and 10 being extremely
satisfied.
98. Don't know
99. Refused
23a. IIF Q23<:.V WhV do you say that?
Freeridership and Market Effects
[NOTE., ONLY ASK FOR SAME MEASURE AS PRIOR QUESTIONSJ
24. On a scale from 1 to 10, how important were the following factors in deciding which
energy efficiency actions to take:
Factor Score
Information provided by
program staff on measure
savinss
Information on payback for the
measure
The oroiect incentive
My previous familiarity with
these measures
Had purchased these measures in
the past
25. Regarding the actions you took to save energy through this project, would you have
taken any of these actions without the program?
1. Yes2. No98. Don't know
99. Refused
26. Before this program, had you previously taken similar types of actions to save
energy?
1. Yes
2. No [IF NO, SKIP TO 271
98. Don't know99. Refused
26a.What actions have you taken?
IRECORD RESPONSEJ
The Cadnrus Group [nc. I Energy Servi*es 69
Rocky Mountain Power
Exhibit No. 5 Page 416 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
28.
27. [FR] Viithout this progftrm, would you have taken all of the actions, some of the
actions or none of the actions?1. All2. Some3. None ISK]P rO 29J98. Don't know ISKIP TO 29J99. Retused ISKIP TO 29J
IRECORD RESPONSEJ
27a- [FR] [If 27:Some] Which actions would you have taken?
27b. [FR] Without this program, would you have added or replaced the equipment to the...1. Same level of efficiency2. Higher level of efficiency3. Lower level of efficiency98. Don't know
99. Refused
[FR]Without the program, would you have taken these actions...
l. In the same year?
2. In one to two years?
3. In three to five years?
4. More than five years out?98. Don't know
99. Refused
Energy Efficiency Decision Making
Next, I would like to ask you some questions about the decision making process in regards to
energy efficiency purchases and upgrades.
29. Using a I to l0 rating scale, where 1 means not at all important and 10 means
extremely important, please rate how important energy efficiency is to the operations and
management of your business.
IRECORD RESPONSEJ
98. Don't know
99. Refused
29a.Why do you say that?
IRECORD RESPONSEJ
30. Do you have sufficient technical resources in house to address the management of
energy and water costs?
70The Cadmus Group lnc. i Energy Services
?eqiflFerp
Roclry Mountain Power
Exhibit No. 5 Page 417 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011..-.,.........-----..........-t---------------------
1. Yes /SrUP TO 30bJ2. No
98. Don't know ISKIP TO 30bJ
99. Retused ISKIP TO 30bJ
30a. What additional technical assistance do you need? IRECORD RESPONSEJ
30b. For this project specifically, were ROCKY MOUNTAIN POWER, Franklin Soil and
Water Conservation District, or Nexant able to provide you with the needed technical
assistance?
1. Yes2. No
3. Did not need technical assistance [SKIP TO 3 U98. Don't know
99. Retused ISKIP TO 3U
30c. What additional technical assistance did you need? [RECORD RESPONSEJ
30d. Who provided technical assistance? IRECORD RESPONSEJ
Spillover
31. Besides installing the measures through this program, have you since made any other
energy efficiency improvements or purchases on your own without any assistance from a
utility or other orgarization?1. Yes
2. No ISK1P TO INTEMCTION J
98. Don't know ISKIP TO INTERACTIONJ
99. Retused ISK]P TO INTEMCTIONJ
3la. [tF 31 : YESJ What improvements or purchases did you make?
IRECORD RESPONSEJ
3lb. JtF 3I : YESJ I'm going to read a statement about the equipment that you purchased on
your own. On a scale from 1 to 10, with 1 indicating that you strongly disagree, and 10
indicating that you strongly agree, please rate the following statement.
"My experience with the Irrigation Energy Savers program influenced my decision to
make other energy efficiency improvements or purchases on my own."
IRECORD RATINGJ
98. Don't know
99. Refused
The Cadnrus Group lnc. i Energy Services 71
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 418 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
Interaction with Rocky Mountain Power or 3rd Pafi Staff
We are also interested in learning more about your interactions with the Program staff
32. How many people did you work with throughout your participation in the Program?
This would include people from Franklin Soil and Water Conservation District, Nexant,
ROCKY MOLINTAIN POWER, contractors, etc.
Number of people
[SKIP TO 35 IF:0J
33. Who worked with you with you on this project?
IPROBE IF NEEDED, T4/AS IT PROJECT MANAGERS, ACCOUNT REPS, THIRD
PARTY STAFF, CONTRACTORS; MULTIPLE RESPONSEJ
1. Rocky Mountain Power Account Representatives2. Other Rocky Mountain Power Energy Staff3. Franklin Soil and Water Conservation District4. Nexant Staff5. Installation Contractors6. External Consultant7. Other ISPECIFYJ
34. Please describe your overall experience working with these people in relation to thisproject._ IRECORD RESP ONSEJ
Satisfaction
35. Would you participate in the Program again?
1. Yes
2. No
35a" JtF 35 : NOJ Why not?
IRECORD RESPONSEJ
36. If you could change anything about the Program, what would you change?
IRECORD RESPONSEJ
98. Don't know
99. Refused
37. Using a scale from 1 to 10, with 1 being extremely dissatisfied and 10 being extremely
satisfied, how satisfied are you with your overall experience with the Program?
IRECORD RESPONSEJ
98. Don't know
99. Refused
The Cadmus Group lnc. i Hnergy Services 72
Psti{icqn..P
Roclq Mountain Power
Exhibit No. 5 Page 419 of 1365
Case No. PAC-E-14-07
VMtness: Kathrvn C. HvmasMarch 16" 2011
t
37a. IIF Q37 <:5J Why do you say that?
Organ izational Data/Fi rmog raph ics
I have a few last questions about your business or organization
38. Approximately, what percent of your total annual operating costs do your electricity
bills represent?
[RECORD RESPONSEJ
98. Don't know
99. Refused
39. Approximately, what percent of your total annual operating costs do your water bills
represent?
IRECORD RESPONSEJ
98. Don't know
99. Refused
40. How many people does your business employ full time?
I e8. D",,.m;o* RESP.NSEI
99. Refused
41. How many people does your business employ seasonally?
IRECORD RESPONSEI
98. Don't know
99. Refused
Finally, in order to send you the $25 gift certificate for participating in this survey, I need you to
confirm the spelling of your name and your mailing address:
Thank you for your time. Your opinions are very valuable to this research for Rocky Mountain
Power.
73The Cadmus Group lnc. i Energy $ervices
fle-"ili9qp
Rocky Mountain Power
Exhibit No. 5 Page 420 of 1 365
Case No. PAC-EI4-07
Wtness: Kathrvn C. HvmasMarch 16" ?01f
Appendix E. Nonparticipant Survey Instrument
Irrigation Energy Savers Non - Participant Interview Guide
Title:
Interview date:Time:
SIC Code (a-digit) NAIC:
Hello, my name is from , calling on behalf of
Rocky Mountain Power. We are conducting a study for Rocky Mountain Power
regarding their energy efficiency programs. Could I please speak with
or the person who most often pays the electric bills?
IIF DIRECTED TO A DIFFERENT RESPONDENT, REPEAT INTRODUCTIONJ
Our records indicate that you have not participated in Rocky Mountain Power's Irrigation
Energy Savers Program. Is that correct?
JIF YES, CONTINUE.J
AF NO, THANK, TERMINATE SURVEY AND TALLY.J
My questions are for research purposes only. We are interested in your opinions to help improve
Rocky Mountain Power's programs and understand how to assist customers in saving money on
their utility bills. Your individual responses will be kept confidential and only reported in
aggregate. Are you willing to participate? [IF RESPONDENT ASKS HOW LONG, SAY:
,, AP PROXIMATELY ] 5 MINUTES.'' J
As a Thank You for vour assistance, at the end of the survev we would like to
offer vou a $25 eift card, which will be mailed to vou
[If a customer asks if this is the Total Quality Service survey, or states that he has recently
participated in the Total Quality Service survey, say 'this is a separate survey about Rocky
Mountain Power' s energy effi ciency programs.' ]
[If customer wants to veriff the validity of the survey, tell them that they are welcome to contact
Hallie Gallinger, PacifiCorp Program Manager, at [phone].
The Cadmus Group lnc. ,/ Energy $ervices 74
PacifiCorp
Roclry Mountain Power
Exhibit No. 5 Page 421 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch -'!6. 201 1
O Screening:
52. First, I need to validate my records.
53. Which electric company provides electric power to your business?
1. Rocky Mountain Power ICONTINUE]2. OTHER [TERMTNATE AND TALLY]
98. DON'T KNOW ITERMINATE AND TALLY]
Participation
3. Have you heard of the Rocky Mountain Power Irrigation Energy Savers Program?
1. Yes [Continue]
2. No [Skip to 11]
98. Don't know [Skip to 11]
99. Retused [Skip to 11]
5. How did you first leam about the Irrigation Energy Savers program?
IDO NOT READ RESPONSES; MARKALL THAT APPLYJ
17. Contacted by my Rocky Mountain Power account representative
18. Contacted by other Rocky Mountain Power staff
19. Contacted by Franklin Soil and Water Conservation District
20. Contacted by Nexant Staff
21. Program sponsored a presentation
22.Trade Publication
23. Word of mouth; from another business colleague
24. Through an equipment dealer
25. Through a trade organization or professional organization/association
26. Through printed material or outreach materials sent by the Program
27. At a trade show
28. Through family, friend, or neighbor
29. Participation in other Rocky Mountain Power Programs
30. Past Program participants
31. Internet research/found Program on the Rocky Mountain Power website
32. Other ISPECIFY]
98. Don't know
99. Refused
The Cadmu$ Group lnc. i Energy Services 75
lr--cili9-q-r-
Rocky Mountain Po^rer
Exhibit No. 5 Page 422 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
3. Regarding the Inigation Energy Savers program, from 2006 through 2008 have you either
begun participation in the program and dropped out, or had a project application rejected?
1. Dropped o:ut ISKIP fO 5J
2. Application rejected ISKIP fO 5J
3. No
98. Don't know
99. Refused
4. What are the reasons you have not been in the Program?
[RECORD RESPONSE AND SKIP TO 1U
98. Don't know
99. Refused
Program Drop-Outs and Rejected Applications
ASK THIS SECTION ONLY IF RESPONDENT IS: (t) PROGRAM DROP-OUT (2) REJECTED
APPLICATION
Thinking back to when you were first considered the Program, were there any aspects of the
Program that initially caused you concern?
1. Yes
2. No /SIVP TO 5CJ
98. Don't know ISKIP TO 5CJ
99. Retused ISKIP TO SCJ
What were the aspects that caused concern?
IRECORD RESPONSEJ
5b. How was it resolved?
IRECORD RESPONSEJ
ASK ONLY IF RESPONDENT IS A PROGRAM DROP-OW
5c. Why did your business drop out of the Program?
IRECORD RESPONSEJ
ASK ONLY IF RESPONDENT'S APPLICATION WAS REJECTED
5d. Do you know why your application to participate in the program was denied?
IRECORD RESPONSEJ
ASK FOR BOTH GROUPS
5e. Was the underlying problem resolved to your satisfaction? If not, why not?
5.
5a.
The Cadmus Group lnc. i Energy Services 76
?e{lr9orp-
Rocky Mountain Power
Exhibit No. 5 Page 423 of 1 365
Case No. PAC-E-I4-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
We are also interested in learning more about your interactions and experience with the Program
staff.
6. How many people did you work with during your time with the Program? This would
include people from Franklin Soil and Water Conservation District, Nexant, Rocky
Mountain Power, contractors, and others.
Number of people
[sKrP TO 9 rF: 0J
7. Who worked with you with you on this project?
IPROBE IF NEEDED. WAS IT PROJECT MANAGERS, ACCOUNT REPS, THIRD
PARTY STAFF, CONTMCTORS; MULTIPLE RESPONSEJ
Rocky Mountain Power Account Representatives
Other Rocky Mountain Power Energy Staff
Franklin Soil and Water Conservation District
Nexant Staff
Installation Contractors
External Consultant
Other ISPECIFYJ
8. Please describe your overall experience working with these people in relation to thisproject._ IRECO RD RESP ONSEJ
9. If you could change anything about the Program, what would you change?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Efficiency Measures lnstalled or Instituted
10. In the past year, have you taken any of the following actions?1. Installed pivot and linear system equipment2. Replaced drains, gaskets, nozzles, regulators or sprinkler packages3. Received on-site system consultation or pump testing4. Received system analysis5. Expanded or redesigned your irrigation system
6. Installed a VFD to a pump7. Other actions [SPECIFYJ8. No actions IIF NO, SKIP TO ENERGY EFFICIENCY DECISION MAKINGJ
I la. Did you receive a financial incentive or tax credit for any these actions?
1. Yes [Specify the incentive and/ or tax credit amount, and the agency/program
offering the incentive/tax credit.]
2. No //FNO SKIP TO ENERGY EFFICIENCY DECISION MAKINGJ
3.
4.
5.
6.
7.
8.
9.
The Cadmus Group lnc. i Energy Services 77
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 424 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasMarch 16. 2011
98. Don't know
99. Refused
11. Why did you decide to take these actions?
IDO NOT READ RESPONSES; MARK ALL THAT APPLYJ
1. To save money on water bills
2. To save money on electric bills
3. To obtain a program rebate or incentive
4. It was scheduled for replacement/upgrade
5. To replace old equipment
6. To replace broken equipment
7. To acquire the latest technology
8. To reduce maintenance costs
9. Because IROCKY MOUNTAIN POWER] account manager suggested it
10. Because a Nexant engineer suggested it
11. Because we had funds available in this fiscal year
12. Previous experience with other IROCKY MOUNTAIN POWER] Programs
13. To help protect the environment
14. To save energy
15. Recommended by Program contact
16. Recommended by contractors/trade allies
17. Recommended by another word of mouth
18. Recommended by family, friend, or neighbor
19. Part of a broader expansion or redesign
20. Other ISPECIFYJ
Energy Efficiency Decision Making
Next, I will ask some questions about the decision making process in regards to energy
efficiency purchases and upgrades.
12. Using a 1 to 10 rating scale, where 1 means not at all important and 10 means extremely
important, please rate how important energy effrciency is to the operations and management
ofyour business?
IRECORD RESPONSEJ
98. Don't know
99. Refused
13. Why do you say that?
IRECORD RESPONSEJ
14. Do you have sufficient technical resources in house to address the management of energy and
water costs?
1. Yes ISK1P NEXT QUESTIONJ
The Cadmus Group lnc. I Energy $ervices 78
Rocky Mountain Power
Exhibit No. 5 Page 425 of 1 365
Case No. PAC-E-'|4-07
PacifiCorp
2. No
98. Don't know
99. Refused
15a. IIF ]S:NOJ What type of technical resources would be most helpful?
IRECORD RESPONSEJ
98. Don't know
99. Refused
Organizational Data/Firmog raph ics
I have a few final questions about your business or organization.
15. Approximately, what percent of your total annual operating costs do your electricity bills
represent?
IRECORD RESPONSEJ
98. Don't know
99. Refused
17. Approximately, what percent of your total annual operating costs do your water bills
represent?
IRECORD RESPONSEI
98. Don't know
99. Refused
18. How many people does your business employ full time?
IRECORD RESPONSEJ
98. Don't know
99. Refused
19. How many people does your business employ seasonally?
IRECORD RESPONSEI
98. Don't know
99. Refused
20. Finally, in order to send you the $25 gift certificate for participating in this survey, I need
you to confirm the spelling of your name and your mailing address:
Thank you for your time. Your opinions are very valuable to this research for Rocky Mountain
Power.
Witness: Kathrun C. HvmasMarch 16. 201f
79The Cadrnus Group lnc. i Energy Services
PacifiCorp
Rocky Mountain Power
Exhibit No, 5 Page 426 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasManch 16. 2011
Appendix F. Staff and lmplementer lnterview Guide
Irrigation Energy Savers Program Discussion Guide
Name(s)
Title(s)
Company
Date
Program Overuiew1. How do you describe the program to others? (What do you see as the key features and
benefits of the program?)
2. What do you consider the broader progftrm goals for the program? What are the market
transformation goals for the program?
3. The program offers four energy saving options:
Fixed Incentive Options include:. Equipment exchange (nozzles, gaskets, drains). Pivot and linear equipment upgrades (pressure regulators, sprinkler packages, and
drains)
Custom Incentive Options include:. System consultation and pump tests. System analysis
4. For Equipment Exchange:
a. What processes are in place to ensure that appropriate equipment is exchanged and
installed?
b. What issues, if any, are there related to the application review and verification of
equipment exchange?c. What if anything would increase participation in the Equipment Exchange option?
5. For the Pivot Package and Linear System Upgrades:
a. What processes are in place to ensure that appropriate equipment is replaced?
b. What issues, if any, are there related to the application review and system upgrades?
c. What if anything would increase participation in the Pivot and Linear System
Upgrades option?
6. For System Consultation, Pump Tests, and System Analysis:
a. These programs require that a customer sign a letter of intent before on-site visits are
arranged. What if any issues arise regarding this or other elements of the application
process?
b. What is the conversion rate from completion of a report and implementation of
recommended improvements? How does it differ by program option?
The Cadmus Greup lnc. i Enengy $ervices BO
?ecili9qrB
Rocky Mountain Power
Exhibit No. 5 Page 427 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
7.
c. What is the approximate length of time between completion of a report and
implementation of recommendations?
d. How do customers generally respond to the recommendations? Do they tend to adopt
some, most, or all recommendations? What seems to influence adoption
recofirmendations?
Are some options more successful than others in terms of customer uptake and measure
performance?
Are there particular challenges associated with each option? What are these challenges?
The fixed incentive portion of the Irrigation Energy Savers Program requires that:. Customers be served on rate schedule 10. Incentives apply only to measures approved by Rocky Mountain Power
Do you think these requirements limit participation? How do they limit participation?
How would you describe the role of the various market actors in project implementation:. Customers, contractors, engineering firms, energy services companies, retailers, and
equipment manufacturers
Are there any specific issues related to the various eligible program measures? What
measures, if any, do you think should be added to the program?
How has the program evolved or changed over time?
How do you coordinate activities internally? [Marketing, service delivery, work with
TAs. etc.l
Are you providing training to:
a. Rocky Mountain Power staff
b. Implementers
c. Trade allies
15. What feedback have you gotten back on the training?
16. What improvements could be made in the administration of the programs?
Application process
17 . What issues, if any, are there related to the application process?
Eligibility criteria
18. What issues, if any, are there related to the eligibility?
8.
9.
10.
11.
t2
13
14.
The Cadmus Group lnc, i Energy Services 81
Rocky Mountain Power
Exhibit No. 5 Page 428 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011l-qpifr?qrp
27.
28.
29.
30.
Marketing
19. What do you do to promote the program? [What marketing and outreach activities have
been and are being conducted? What's worked best?]
Savings estimation techniques
20. How are savings calculated for the program as a whole and for individual projects? What
issues if any arise related to veriffing savings? How are these issues addressed?
21. Is there a way to improve the manner in which savings are calculated?
Participant interaction and satisfaction
22. What aspects of the progftrms do customers seem to be most interested in or most
satisfied with?
a. Any concerns? How were they addressed?
Program data collection
23. Who is responsible for collecting and tracking participation data?
a. How ef[ective and accurate is the data-tracking and data collection system?
b. Are data entered and reported in a timely fashion?
c. Have there been any difficulties with the data tracking systems?
24. Have the implementers had any problems meeting the tracking and reporting
requirements?
25. Would you recommend any changes to the procedures?
Trade Allies - Communication
26. Is Rocky Mountain Power involved in the recruitment or management of Trade Allies,
retailers or contractors? Please describe the relationship between these parties?
Have you had any particular challenges in working with trade allies?
How are their problems and questions dealt with?
What has/has not worked well?
How would you change or improve communications, either within the program, or with
trade allies?
The Cadmus Group lnc. / Energy Services 82
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 429 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 201'f
Implementation Barriers
3 1. Has the level of program participation met your expectations? Why do you think this has
been the case?
32. Have any challenges resulted from perceptions or attitudes about the value of the
progftrm among the target population? If so, what?
33. How have you dealt with those perceptions and attitudes?
34. How about any challenges resulting from perceptions or attitudes about the value of the
programs among the vendors? How have these been dealt with?
Close
35. What would you say are the program's strongest points? What are its weakest points?
36. Other than what we've discussed above, what would you change about the program?
83The Cadrnus Group lnc. i Energy Services
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 430 of 'l 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 18. 2011
Appendix G. Market Actor lnterview Guide
Market Actor Interview Guide - Idaho Irrigation Enerry Savers Program
Interviewee information:
Name:
Organization:
Title:
Telephone:
Hello, my name is
Mountain Power.
from The Cadmus Group, calling on behalf of Rocky
Rocky Mountain Power is evaluating its Irrigation Energy Savers Program and
would like your input regarding the program and how it has operated over time.
This interview is part of a process evaluation we are conducting to understand how
the program has functioned over time, and identiff opportunities for improving the
program. Our focus is on the program as it was operating in 2006 through 2008.
This survey is for research purposes only and this is not a marketing call. Your
responses will remain confidential. Do you have a moment to answer questions
about your experience with the program?
[If "No - Not a convenient time," ask if Respondent would like to L. Start now and do part
of the survey, or 2. Arrange a more convenient time we can call them at home. Emphasize
thatl
"It is important for Rocky Mountain Power to include your opinions in this study so they
can serre your needs better.t'
[If "No" - Arrange callback]
Screening Questions
1. [Roclry Mountain Powerl records show that in [Yearl you were a participating dealer in
Rocky Mountain Power's Irrigation Energy Savers program. Is that correct?
a. Yes [Go To Question 2]
b. No, market actor was not a participating dealer Rocky Mountain Power's Irrigation
Energy Savers program in [Year]. [Terminate]
98. Don't know [Terminate]
99. Refused [Terminate]
2. During what time frame were you a participating dealer?
l. [Month] _lYearl_
The Cadrnus Group [nc. i Energy Services 84
PacifiCorp
Rocky Mountain Power
Exhibit No.5 Page 431 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 16. 2011
98. Don't know
99. Refused
3. Did you provide equipment for the Equipment Exchange, Pivot and Linear System Upgrades
or both?
1 Equipment Exchange
2 Pivot and Linear System Upgrades
3 Both
Program Overview
4. When did you become a participating dealer for the Irrigation Energy Savers program?
5. What did you see as the purpose of the program?
6. Who else was involved in program? How were they involved? IPROBE on Franklin Soil and
Conservation District, PacifiCorp, other retailers, equipment manufacturers.]
7. At the start of the program were there particular measures or services that were more popular
than others? If so, what were they? Why do you think they were more popular?
8. Have there been changes over time in the services or measures people are interested in? What
are the changes?
Program Entry
9. How did a prospective customer find out about the program?
Equipment dealers,
Contractors
Engineering firms,
Energy services companies
Retailers,
Equipment manufacturers
Drilling companies
Electricians
Drive dealers
Other
The Cadrnus Group lnc. i Energy Services 85
PacifiCorp
Rocky Mountain Power
Exhibit No. 5 Page 432 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasMarch 1S. 2011
Partici pant interaction and satisfaction
10. Did customers express any concems about the program? How were the concerns addressed?
Rocky Mountain Power - Communication
11. Did your company have any particular challenges in working with Rocky Mountain Power?
12. How were these challenges dealt with?
lmplementation Barriers
13. Did any challenges result from perceptions or attitudes about the value of the program among
the Rocky Mountain Power customers? If so, what were they?
14. How did you deal with those perceptions and attitudes?
15. [If they participated in the Equipment Exchangel Did you have any issues regarding
buildup of non-recyclable materials (i.e. rubber) at your business? How were these issues
addressed?
Program data collection
16. Please describe the program's data collection and tracking requirements.
a. Were there any difficulties meeting those requirements?
17. Would you recommend any changes to the procedures?
Close
18. Other than what we've discussed above, what would you change about the program as it was
operated in 2006 through 2008?
19. What would you change about the program as it is currently operated?
20. Is there anything else you would like to add?
The Cadmus Group lnc. i Energy Services 86
Roclry Mountain Power
Exhibit No. 5 Page 433 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
re
ROCKY MOUNTAIN
POWER
A OIVISION OF PACIFICORP
Exhibit No. 5.6
Low Income Weath erization Evaluatio n 2009 -20 l0
Rocky Mountain Power
Exhibit No. 5 Page 434 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
t $:\'8i"$ "N \$ 4..,.,.R &..{:CAI)h/fTJS
ilH.il"$[."IS:}- $Nil:"
Final Report
I daho Low-l ncome Weatherization
Program Evaluation (2OO7-2OO9)
Prepared for:
PacifiCorp
Prepared by
The Cadmus Group, lnc. / Energy Services
720 SW Washington Street, Suite 400
Portland, OR 97205
503-228-2992
April 20,2011
Roclry Mountain Power
Exhibit No. 5 Page 435 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Prepared by:
Brian Hedman
Scott Reeves
Jamie Drakos
Cynthia Kan
Kate Bushman
Doug Burns
Matei Perussi
The Cadmus Group, lnc, / Energy Services
I
Cor-porat* Fleadquaners:
57 V&rer Street
\tfatertown, HA 02472
Tel: [phone]
Fa;c: 617.673;7001
An firgloyee-Owned Compony
\njw\.rf!Ls* fi i{,i$$r s ij j}, {L\ i'x
720 SW Vlkhington St.
Suite 400
Porttand. OR 97205
Tel: [phone]
Fax: 5O3.?2&3696
Roclq Mountain Power
Exhibit No. 5 Page 436 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Idaho Low-lncome Weatherization Program Evaluation
Table of Contents
Executive SummaryES-l
Program Overview. ............... 1
Evaluation Approach ............ 1
Major Findings ......2
Recommendations... .............4
1. Process Evaluation............ ............1
Program Services ................. 1
Methodology............ .............2
Process Findings ..................3
Process Evaluation Conclusions ............ ............ 11
2. Impact Evaluation............. ........... 13
lntroduction.............. ........... 13
Data and Document Review ............... 13
Program Participation and Savings ....14
Billing Analysis.. .................. 15
3. Non-Energy Benefits......... .......... 19
Participant lmpacts ............. 19
Economic lmpacts .............. 19
Payment Analysis and Arrearage 1mpacts........... ...............22
4. Cost-Effectiveness Analysis........... ..........27
Appendix A: Participant Survey lnstrument
Appendix B: Stakeholder lnterview Guide
The Cadmus Group, lnc. i EnerEy $ervices
Rocky Mountain Power
Exhibit No. 5 Page 437 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l*ow-lncome Weatherization Program Evaluation
Executive Summary
Program Overview
Rocky Mountain Power's Low-Income Weatherization Program in Idaho is aimed at lowering
low-income customers' energy consumption and utility bills. The progrirm provides, at no cost to
an income-qualified customer, a complete home energy audit, installation of energy-efficient
measures, and energy education.
Evaluation Approach
Rocky Mountain Power contracted with The Cadmus Group Inc. (Cadmus) to conduct impact
and process evaluations of the Program for program yearc2007, 2008, and2009. The process
evaluation was designed to assess program delivery and efficacy, bottlenecks, barriers, best
practices, and any opportunities for improvement. The impact evaluation assessed energy
impacts, non-energy benefits, and program cost-effectiveness. The major tasks associated with
the evaluation are described in more detail below.
Data Collection
Data required for this evaluation, and their sources are listed in Table 1.
Process Approach
Telephone surveys were conducted with 31 program participants to assess multiple aspects of the
program. These questions focused primarily on installation verification, client satisfaction levels,
program delivery, recall of energy education recommendations, and certain non-energy benefits.
An in-depth discussion with a key delivery agency staff person was conducted to ensure that all
facets of program delivery were assessed, including bottlenecks, client and agency satisfaction,
best practices, methods of improving delivery, and agency assessment of non-energy benefits.
Finally, an interview was conducted with the statewide inspector from the Community Action
Program Association of Idaho (CAPAI) to provide insight into the issues identified through this
evaluation and by the inspector, as well as to discuss improvements that have been made at the
agency level.
Evaluation of Program Energy Savings
Estimated and actual program energy savings were assessed in the following manners:
Table l. Data Sources
Customer account data with low-income identifier
Economic data for non-enerqv benefit calculation IMPLAN 2009 Data for ldaho
The Cadnrus Group, lnc. i Energy Services ES-1
Roclry Mountain Power
Exhibit No. 5 Page 438 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Frogram Evaluation
o Expected Savings: Based on a review of data from Rocky Mountain Power's 2007,2008,
and 2009 annual reports, we calculated average expected electric savings per participant.
o Actual Savings: A pooled conditional savings analysis (CSA) regression model was run
to estimate weather-normalized, program-induced energy (kwh) savings based on
participant and nonparticipant billing data.
Assessment of Non-Energy Benefits
A series of non-energy benefits were evaluated for this analysis, including:
o Payment behavior and participant arrearages
o Benefits to the regional economy (e.g., employment, value added, output)
o Benefits to participants (e.g., improved comfort, health and safety, mobility)
Assessment of Cost-Effectiveness
To assess cost-effectiveness, evaluators conducted an analysis ofprogram costs and benefits
from various perspectives, using Cadmus' DSM Portfolio Pro model.
Major Findings
Electric Savings
Overall, gross participant savings for program participants are calculated at 1,972 kWh (10.8
percent of pre-progr{rm energy consumption), which approximates the expected participant
savings of 2,01 5 kWh, the average savings reported by Rocky Mountain Power across the 2007 ,
2008, and 2009 program years. Table 2 provides the total program participation and savings for
the years evaluated.
Table 2. Program Evaluated Savings by Year
After adjusting for savings observed in the nonparticipant control group, we calculated the
program induced adjusted gross participant savings as 1,308 kwh (7.2 percent of pre-program
energy consumption). Figure 1 provides the savings impact with regard to each type of estimated
savings.
Participation and
The Cadmus Group, lnc. i Energy $ervices ES-2
Roclry Mountain Power
Exhibit No. 5 Page 439 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-[ncome Weatherization Frogran"l Evaluation
2,5O0
2,O0O
1,500
1,000
500
0
Figure 1. Savings Estimate Comparison
2,015 \g7z
6EOtr
.!ti.c3ta
I Expected (RMP Annual
Report)
S Participant Gross
N Nonparticipant Gross
r Participant Adjusted
Gross
Participant adjusted gross savings reflects the naturally occurring savings in the non-participant
control group. Several factors may have contributed to nonparticipant savings:
o Overall economic downturn, which has inspired many households to reduce expenditures. High saturations of secondary wood heating in Idahoo A 43.5 percent rate increase for Rocky Mountain Power customers between the years of
analysis from 2006 and2009 (this residential rate increase consisted of: 8.4 percent
general rate case order, 2.2 percent energy efficiency rider increase, and 32.6 percent due
to the elimination of the BPA credit).
Non-Energy Benefits
Non-energy benefits were also attributed to program, providing ancillary impacts to participants,
the utility, and the state economy. We monetized several of these and include them in a scenario
for estimating program cost-effectiveness :
o A reduction of annual arrearages of $8,331o An estimated 7.7 net job-years of employment
. Approximately $144,946 added to the Idaho economy
Cost-Effectiveness
Under the cost-effectiveness tests that did not include non-energy benefits, the program was
found to have benefit-cost ratios of less than l, except under the participant cost test (see Table
3). When all benefits (energy and non-energy) are included, the program is cost-effective from
both the total resource cost (TRC) and PacifiCorp total resource cost (PTRC) perspectives, at
I .15 and 1 .23 respectively, as shown below in Table 4.
Types of Savings
The Cadrnus Group, lnc. / Energy Services ES-3
Table 3. Program Cost-Effectiveness Summary Without Non-Enerry Benelits 2007-2009*
Total Resource + Conservation Adder (PTRC)$0,099 $426,022 $372,019 -$54,004 0,87
Total Resource No Adder (THC)$0.0e9 $426,022 $338,1 99 -$87,824 0.79
Utilitv (UCT)$0.099 $426,022 $338,199 -$87,824 0.79
Ratepaver lmpact (RlM)$0.189 $815,476 $338,199 -$477,277 0.41
Participant (PCT)$0.083 $35s,470 $744,924 $389,454 2.10
Lifecycle Revenue lmpact $0.00001 046
Rocky Mountain Power
Exhibit No, 5 Page 440 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
ldaho Low-lncome Weatherization Frogram Hvaluation
-The calculations are based on the program components in place during the period 2007-2009 when Bocky Mountain Power provided a rebate
covering 750lo of the cost ol approved measures. As ol 1212U10, they are covering 85% of these costs, which will reduce the net benefits from
the utility and rate impact perspectives.
* The calculations are based on the program components in place during the period 2007-2009 when Rocky Mountain Power provided a rebate
covering 75% of the cost ol approved measures. As ol 12128110, they are covering 850/o of these costs, which will reduce the net benefits from
the utility and rate impact perspectives.
Recommendations
The program, with energy savings and non-energy benefits considered, passes the TRC and
PTRC tests. Below we provide suggested program enhancements that could help to improve the
program impact results and overall delivery of the program.
Consider Prioritizing Refrigerator Replacements
We understand that the agencies, in an effort to supply the services and measures that are most
cost-prohibitive for low-income customers, do not prioritize refrigerator replacements. This
enables the agency to spread its weatherization services across a broader array of customers.
However, low-income customers with older, inefficient refrigerators could experience significant
electric savings from the installation of newer refrigerators. The installation of new refrigerators
is also likely to help increase the program's cost-eflectiveness. At a minimum, agencies should
suggest to households with older and more inefficient refrigerators that purchasing a new
refrigerator could reduce their electric use.
Assist CAPAI in Development of Uniform Energy Education Curriculum
CAPAI mentioned their desire to establish a uniform energy education curriculum in order to
ensure that a consistent energy-saving message is being delivered to customers. Rocky Mountain
Power stands to benefit from improved energy education, as behavior changes could lead to
Table 4. Program Cost-Effectiveness Summary Including Non-Enerry Benefits 2007-2009*
Total Resource + Conservation Adder (PTRC)$0.099 $426,022 $s25,295 $99,273 1.23
Total Resource No Adder (TRC)$0.099 $426,022 $491,475 $65,453 1.15
Utility (UCI $0.099 $426,022 $346,529 -$79,493 0.81
Ratepaver lmpact (RlM)$0.189 $815,476 $346,529 -$468,947 0.42
Participant (PCT)$0.083 $355,470 $744,924 $389,454 2.10
Lifecvcle Revenue lmoact $0.00001028
The Cadmus Group, lnc. / Energy Services ES-4
Roclry Mountain Power
Exhibil No. 5 Page 441 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l*ow-lncome Weatherization Program Evaluation
higher realization of energy savings. Rocky Mountain Power should continue working with
CAPAI to expedite the development and implementation of a uniform statewide curriculum.
Work with Agencies to Determine if Electronic Reporting is Feasible
Rocky Mountain Power is currently upgrading their computer tracking system. The new system
will enhance the Company's ability to track:
o Measure quantities (i.e., number of CFLs installed per home)o Costs for each measure, including the portion that Rocky Mountain Power paid and the
total costo Invoice data
o Project completion dateo Account and participant contact information for each customer's home
o Identifier for agency completing the work on the customer's home
The influx of federal dollars from the Recovery Act has allowed many states and individual
agencies to invest in constructing or refining their databases. Rocky Mountain Power should
work with the agencies to determine if an electronic transfer of the tracking information is
feasible to increase efficiency and reduce elrors.
Increase Rocky Mountain Power Recognition
Less than one-third of participants surveyed knew that Rocky Mountain Power had paid for some
of the measure installations in their homes. Agency staff, when reviewing Rocky Mountain
Power's educational literature with participants, should indicate who contributed to the services.
Rocky Mountain Power could also consider providing branded electroluminescent night lights to
participant customers to increase recognition of their contribution to the program.
The Cadmus Group, lnc. / Energy Services ES.5
Rocky Mountain Power
Exhibit No. 5 Page 442 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncorne Weatherization Program Evatruation
1. Process Evaluation
Program Services
Eastern Idaho Community Action Partnership and Southeastem Idaho Community Action
Agency provide weatherization and efficiency upgrades to income-qualified households in
Idaho. The agencies implement the program, with monitoring oversight from the Community
Action Partnership Association of Idaho (CAPAI). The program leverages funding from Rocky
Mountain Power, the U.S. Department of Energy (DOE), and U.S. Department of Health and
Human Services (HHS), among others, to fund comprehensive weatherization of Rocky
Mountain Power customer homes. The gas provider in the territory, Intermountain Gas, does not
provide weatherization program funding.
Rocky Mountain Power's funding of the progftrm focuses on electricity-saving measures, as
delineated in Rocky Mountain Power's tariff.t Measures are categorized as either major or
supplemental. Major measures include wall and floor insulation and window replacement, and
can be installed only in homes with electric heating systems. Supplemental measures target other
electric end-uses such as lighting and water heat. Supplemental measures not related to heating
can be installed in homes without an electric heating system. Supplemental measures related to
water heating efficiencies require that the home have an electric water heater. Rocky Mountain
Power also provides reimbursement for administrative expenses as well as a limited amount of
funding for measures that promote customer home health and safety.
Program Operations
The agencies employ energy auditors who are trained to evaluate and measure the performance
of a home. Using an energy audit tool, they identi$, the energy-saving opportunities and energy-
efficiency measures to install in each home. Agencies follow DOE Weatherization Assistance
Program guidelines, which require measures to pass a cost-effectiveness test (savings to
investment ratio, or SIR, equal to one or greater).The auditors also focus on enhancing health and
safety in the customer's home, especially in instances where the home has been tightened and
may need ventilation.
After the work on the home is completed, the agencies submit invoices and documentation to
Rocky Mountain Power. Rocky Mountain Power then paid a rebate of 75 percent of the installed
cost of each eligible measure, plus a 15 percent administrative payment.'Idaho's annual Rocky
Mountain Power funding for this program during the2007-2009 program was capped at
$150,000.3 Rocky Mountain Power funding of health and safety measures is limited to 15
percent of the cost of all jobs performed by each agency.
Rocky Mountain Power, Electric Service Schedule No. 21, State of Idaho, Low Income Weatherization Services
Optional for lncome Qualifying Customers, Issued January 10,2007 and revised December 28,2010.
As of December 28, 20 10, Rocky Moruttain Power will be providing a rebate of 85%o for each qualifuing
measure.
As of December 28,2010, the costs for the Rocky Mountain Power program expenses will be capped at
$300,000.
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 443 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Frogram Evaluation
Methodology
Data collection for this portion of the evaluation consisted of:
o Telephone survey with a sample of program participants
o Telephone interview with community action agency staff
o Telephone interview with CAPAI staff
o In-person interview with program staff from Rocky Mountain Power
Participant Suruey
Telephone surveys were conducted with a sample of program participants to assess multiple
aspects of the program. Survey questions asked about the following topics:
o Program awareness
o Installationverificationo Client satisfaction with measures
o Recall of energy education recommendationso Non-energy benefits such as improved health and reduced mobility
. Program satisfaction
Sample Selection Methodology
The phone survey was fielded in December 2010 using the population of participants. Of the
total population of 266, viable contact information (name and telephone number) was available
for only 201. This was due primarily to phone numbers that had been disconnected or changed.
Although target sample sizes were calculated based on the total population, the limited number
of contacts in combination with the small number of participants restricted the achievement of
desired targets.
The objective was to achieve 90 complete surveys to target l0 percent precision at the 90 percent
confidence level in each of two strata: participants with insulation and those without. Table 5
presents the desired and achieved samples.
Participants were initially called in randomized order, but the targets had not been met after an
attempt to contact every participant. Subsequently, up to six attempts were made to contact each
participant at varying times of day and on both weekdays and weekends. Ultimately, the 31
surveys completed resulted in an overall precision of 90 percent confidence and *14 percent
precision.
Table 5. Target and Achieved Samples for Participant Survey
The Cadrnus Group, lnc. I Energy Services
Roclq Mountain Po\iler
Exhibit No. 5 Page 444 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
Table 6 below provides the full distribution of measure installations for the participants of the
Idaho sample.
lnterviews with Stakeholders (Agency, State Administrator & Rocky
Mountain Power Program Manager)
Three interviews were conducted with agency, CAPAI, and Rocky Mountain Power staff to
gather information about the program's processes and functioning. Topics discussed in the
interview included the following:
o Program goals
Impact and adequacy of Rocky Mountain Power funding
Impact of American Recovery and Reinvestment Act (Recovery Act) funding for low-
income weatherization
Provision of energy education
Volume of homes, prioritization, and wait-listing
Invoicing and payments
Staff training
Reporting and monitoring
Program achievements and lessons learned
Process Findings
This section discusses first the findings of the participant surveys, and then the findings of
stakeholder interviews. The conclusion summarizes and synthesizes information from both
surveys and interviews.
Participant Su rvey Find ings
Program Awareness
Of those participants who recalled how they first heard of the program, 10 reported that they
heard about it via word of mouth. Only two participants reported learning about the program
directly from Rocky Mountain Power. Furthermore, when asked whether they were aware that
Rocky Mountain Power provided funding for these services, 74 percerfi (23 out of 31) said they
were not. The local agencies that supply weatherization services do not generally inform
o
o
a
o
a
a
o
a
Air Sealino/lnf iltration Control
The Cadmus Group, lnc. i Energy Services
Roclry Mountain Power
Exhibit No. 5 Page 445 of '1365
Case No. PAC-E-'14-07
Witness: Kathryn C. Hymas
ldaho l-ow-lncome Weatherization Program Evaluation
customers that Rocky Mountain Power is providing funding for their services. The agencies
work with a variety of funds to pay for the cost of weatherization.
Installation Verification
When customers were asked to verifr Rocky Mountain Power's records of the measures installed
in their home, there were eight instances in which the customer's recollection did not match
Rocky Mountain Power records. Although it may seem unlikely, this is a common occurrence in
energy conservation programs, where even households purchasing and installing sizable
measures do not always recall their participation.a Those measures not recalled by participants
in Rocky Mountain Power's weatherization program were insulation, air sealing, furnace
repair/replacement, and windows (see Table 7 below for details).
Measure Satisfaction
Customers were asked questions about selected measures that were installed in their homes. The
measure-specific satisfaction ratings are presented in Table 7.
Table 7. Measure Satisfaction Ratings
CFLs 4 8 2 3 1 18
Ref rioerator/Freezer 2 3
lnsulation 5 10 2 1 2 2 22
Air Sealino 7 4 2 2 3 18
Furnace
Reoair/Reolacement 2 1 2 6
Windows 10 3 3 1 1 18
Thermal Door 4 6 1 1 12
CFLs
A majority of recipients were satisfied with their new CFLs, 12 out of 18 (67 percent) giving
them a good or excellent rating. Half of the participants surveyed (9 out of I 8) stated that the
agency staff installed the bulbs in their home, while the other half reported that agency staff
simply left the bulbs. When asked to elaborate on their stated level of satisfaction with the bulbs,
four respondents gave a negative response: that the bulbs burned out quickly. The remaining
comments were all positive, and included: I don't have to change the bulb frequently (mentioned
by 4 respondents), they save electricity (Z),they give good light (2), and they lower the electric
bill (1).
Recipients of CFLs were also asked whether they had replaced any of the CFLs, and if so why.
Seven respondents reported replacing their CFLs, with an average of four bulbs each. Of those
bulb replacers, 43 percent (3 respondents) reported using incandescent bulbs in place of the
CFLs. None of these seven respondents provided a reason for replacing the bulbs.
o Sarah Castor, The Energy Trust of Oregon, presentation at Behavior, Energy, and Climate Change, November,
2010.
nThe Cadmus Group, lnc. i Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 446 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho tr-ow-lncome Weatherieation Program Hvaluation
Refrigerators and Fre ezers
All three surveyed recipients of refrigerators and freezers rated this measure good or excellent.
When asked to elaborate on their satisfaction ratings, they cited electricity savings and bill
savings, as well as satisfaction with the new appliance working better than the one it replaced.
Insulation
Of the 22 recipients of insulation, seven reported noticing that the insulation kept their home
wanner in the winter and cooler in the summer. Other reasons for satisfaction with their new
insulation included reduced energy use, bill savings, the house being more comfortable, and the
fact that it was free. Only one negative comment was reported: that not enough insulation was
installed in the home.
Furnaces
The four respondents who remembered having work performed on their furnaces were asked
whether their furnaces worked prior to these services. Two said no, their furnaces did not work at
all. The comments from the four respondents on the furnace work included that the contractor
did a nice job, they needed a furnace anyway, and it keeps the house wanner.
Windows
Eighteen survey respondents had work performed on windows in their homes. Of these, most (14
out of 18, or 78 percent) stated that the windows were replaced, and six respondents reported that
prior to these services there had been broken or cracked glass in their windows. Seven
respondents said the contractor did a nice job, and three reported that the new windows kept their
homes warner. Negative comments included two people reporting that they did not like the way
the new windows worked, and one stating that the windows did not keep the house more
comfortable.
Thermal Doors
Respondents receiving thermal doors were generally pleased, with 10 out of 12 (80 percent)
giving a good or excellent rating. Their explanations were various, but included: keeping the
house warrner, that they needed a new door anyway, the contractor did a nice job, and that the
house is more safe and secure. There were only two negative comments: in one case the
respondent reported that the contractor didn't finish the job, and the other respondent did not like
the way the door worked.
Energy Education
The majority of participants surveyed (21 of the 3 1 , 68 percent) recalled receiving a pamphlet or
booklet with information about how to save energy. Of those, 19 (61 percent of all respondents)
reported reading the pamphlet after the agency staff left their homes.
Respondents were asked about tips given by agency staff about how to save money on their
electric bills. Thirteen of the 3l respondents (42 percent) remembered getting energy-saving tips.
Of those, the most commonly recalled tips were lowering the hot water thermostat to 120 degrees
(recalled by 8 respondents, representing 26 percent of all respondents), and keeping thermostats
low in winter (5 percent) and high in summer (16 percent). The same two tips were also the most
common responses when participants were asked which tips they had put into use in their homes.
The Cadnrus Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 447 of 1 365
Case No. PAC-E-I4-07
Wtness: Kathryn C. Hymas
ldaho l-ow-lncome Weatherization Program Evaluation
Qualitative Non-Energy Benefi tss
The participant surveys included questions to evaluate certain qualitative non-energy benefits of
the program. These questions were asked only to the22 participants who had received insulation
measures. Homes with insulation were targeted for these questions because insulation typically
has the largest impact on heat retention, levels of comfort, reduction in illnesses, and a decrease
in forced mobility.
Improved Comfort
When asked whether their homes were more comfortable to live in after the weatherization work
was performed,T2 percent of respondents (16 out of the 22homes that received insulation)
responded affirmatively. An additional 23 percent reported that the level of comfort had
remained about the same, and 5 percent were unsure.
Red uced E lectricily Expens es
The same subset of 22 respondents receiving insulation was asked whether they noticed any
change in their electric bills, since a reduction in household electricity expenses is an important
benefit of low-income weatherization programs. Nearly half ( I 0 out of the 22, 45 percent) said
their bills had been noticeably more affordable since the work was performed, while the same
number of respondents said their bitls had stayed about the same.6
Improved Health
If insufficiently heated homes are causing or exacerbating illness, weatherization and efficiency
improvements can improve a family's overall health. When Idaho insulation recipients were
asked whether the work performed on their home had any impact on their health, only three said
yes. These three cited getting better sleep and not being as cold in their homes, but none
specified that they had suffered fewer illnesses.
Reduced Mobility
Finally, weatheization programs have been linked to participants being able to stay in their
homes when they otherwise might have been forced to move. This results in various benefits,
including avoiding the cost of moving homes, as well as keeping children in the same school,
avoiding absences, and avoiding employment disruptions. This benefit was examined from two
perspectives: participant surveys and analysis of payment data. The latter is discussed in Section
3, Non-Energy Benefits.
In the participant survey, insulation recipients were asked whether having this work done made
them more likely to be able to stay in their homes, and 15 out of 22 (68 percent) said yes. While
this finding is only speculative, it does show that many participants felt more confident about
being able to stay in their homes.
The total number of participants surveyed is less than that required to achieved a level of statistical significance
that would allow these benefits to be quantified. Section 3, Non-Energy Benefits, describes the program's
quantifiable benefits including economic benefits and the reduction in arrearage.
In the 2006-2009 period, rates for Rocky Mountain Power customers rose significantly, in part because of the
elimination of the Bonneville Power Administration (BPA) credit to customers of investor-owned utilities. Net
residential retail rates paid by customers in Idaho increased 44percent (this increase includes: 8.4Yo generalrate
case,2.2o/o energy efficiency rider increase , 32.6%0 elimination of BPA credit).
The Cadrrus Group, lnc. I Energy Services
Roclq Mountain Power
Exhibit No. 5 Page /t48 of 1 365
Case No. PAC-E-14-07
Wtness: Kalhryn C. Hymasldaho l-ow-!ncome Weatherization Prooram Evaluation
Program Delivery and Satisfaction
We asked participants to rate their satisfaction with the program overall. As shown in Figure 2, a
vast majority of respondents reported being very satisfied.
Figure 2. Participants' Overall Satisfaction with the Services Provided
80%
70%
60%
50%
4Oo/o
30%
20%
LO%
0o/o
Very Satisfied Somewhat
Satisfied
Not at all Don't
satisfied know/refused
Not very
satisfied
When asked to identifu areas for improvement, most respondents could not think of anlthing that
needed to improve. One person surveyed suggested that Rocky Mountain Power provide more
funding so that more people have access to these services.
We also asked participants about their interactions with the agency staff, finding that 23 out of
31 respondents (74 percent) reported that staff members were very courteous. Two of the 31
individuals surveyed mentioned that some contractors had an attitude of "not caring" about the
work. Twenty-seven respondents (87 percent) reported that agency staff had adequately
explained the work that would be completed in their home.
Participants were asked if they knew who to call if they had any problems, and 10 of the 3l (32
percent) said no. This may indicate that agencies did not always give participants contact
information for any necessary follow-up.
All respondents were asked if the changes made to their home caused any problems. Four out of
31 (13 percent) cited difficulties, and thee gave further details:
When they turned down my water heater it caused problems with my
water. And since they made the vent go from through the attic to through
the roof, and the kids have reported sounds of mice in the attic.
The door - it's leaking air.
When they put the insulation in the attic, they covered up the fan. The
exhaust got covered in the insulation and it got burnt out.
All four respondents citing problems stated that the problems were not resolved to their
satisfaction.
The Cadrnus Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 449 of 1 365
Case No. PAC-E-14{7
Witness: Kathryn C. Hymas
ldaho Low-[ncon:e Weatherizatlon Program Evaluation
Process Stakeholder !nterview Findings
The three interviews with program stakeholders (Rocky Mountain Power, one of the two
agencies, and CAPAI) conducted for this process evaluation all followed a similar structure. The
interview guide addressed the topics listed in the methodology section on page 3, but allowed for
conversation to move in different directions should other subjects of interest arise. All the
individuals interviewed were cooperative and understood the importance of the evaluation and
their feedback.
Program Goals
All stakeholders agreed that the program's primary goal was to save energy. The agency staff
also specified that a goal was to reduce participants' heating bills. All parties agreed that these
goals were being met. No targets are set in terms of number of participants or kWh savings for
just the Rocky Mountain Power portion of the program. Agencies do strive to complete
weatherization of a certain number of homes every year based on goals for their federal funding.
Impact and Adequacy of Rocky Mountain Power Funding
Stakeholders reported that the Rocky Mountain Power funding supplemented other funding
sources and enabled agencies to complete more homes per year. The additional funding supports
a higher volume of homes than would otherwise be possible. The Idaho agencies are able to
exhaust the funding provided by Rocky Mountain Power each year due to the relatively high
percentage of electrically heated homes in the state. According to the agency, between 35 and 48
percent of homes served are electrically heated, the remainder being heated with natural gas,
heating oil, or other fuels. The area natural gas provider, Intermountain Gas, does not provide
funding for their customer homes treated by the weatherization program.
While measure feasibility is determined by the home energy audit, agencies are able to exercise
discretion in selecting measures for homes. For example, only a small number of refrigerators
were replaced in Idaho. When asked to explain why, the agency interviewed pointed out that
although it tests refrigerators to see whether an upgrade is cost-effective, it must prioritize its
limited funds. The agency indicated that refrigerators are less expensive, readily available, and
easy to install. Measures like insulation are more expensive, less likely to be purchased, more
difficult to install, but provide a greater benefit to the participant.
Impact of Recovery Act Funding on Low-Income Weatherization
In2009, the Recovery Act brought an influx of additional funding for weatherizationprograms.
While this only affected part of one program year covered by this evaluation (2009), the effect
was notable, according to stakeholders. The agency staff member interviewed reported that prior
to the Recovery Act it was completing about 220 total homes ayear on average, and with the
increase in funding they are completing over 400 ayear. The state administrator from CAPAI
reported that as of the date of the interview (November 19,2010),3,113 homes had been
weatherized in Idaho with the support of the Recovery Act funding.
This fast increase in volume came with some challenges. The state administrator reported that
the Recovery Act's Davis-Bacon wage requirements caused some delay in ramping up, as it took
some time to establish procedures for compliance. Agencies also had to juggle other funding
sources, such as Rocky Mountain Power, in with the huge quantity and demand of the Recovery
IThe Cadrnus Group, lnc. i Energy Services
Roclq Mountain Power
Exhibit No. 5 Page 450 of I 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymasldaho Low-lncorne Weatherization Program Evaluation
Act funding. The agency reported that in addition to Davis-Bacon requirements, the Recovery
Act has specific requirements relating to lead abatement and historic preservation.
Increased weatherization funding from the Recovery Act allowed for investment in
improvements to the organization and implementation of the existing program in Idaho. The state
administrator hired additional technical monitoring staff, and agencies trained and hired staff and
contractors to meet the increased volume, working toward the job-creation objective of the
Recovery Act. In addition, the agency staff member interviewed reported that it instituted a
policy that final inspection of weatherized homes be conducted by an auditor who had not done
the initial audit or the work on the home. This change, instituted in summer 2009, was reported
to have improved quality. The state administrator reported that with the Recovery Act funding
the agencies have: increased their administrative and organizational capacity, and strengthened
their long term planning skills. Agencies also gained greater cohesiveness in working together as
a statewide team. Both the state administrator and the agency interviewed speculated that these
improvements will continue to benefit the program after the Recovery Act funding is exhausted.
Provision of Energy Education
The agencies aim to educate their clients about energy use in their homes. The agency staff
interviewed explained that most of the energy education occurs during the initial audit. Auditors
give residents the Rocky Mountain Power booklet and explain what actions they can take to
reduce energy use. When the crew returns to complete the work, crew members discuss their
work plan for the home with the resident.
The state administrator pointed out that while each home gets some energy education message, it
may not always be a consistent message from home to home. CAPAI has taken steps toward
developing a statewide energy education curriculum, but for the moment the audit works well to
engage residents in thinking about energy use.
Prioritization and Wait-Listing
Homes are prioritized based on DOE requirements, which give preference to homes with elderly
residents or young children under six, as well as handicapped individuals. Wait lists for low-
income weatherization programs can be quite long, due to high demand for services. The state
administrator estimated that agency waiting lists average about two years in Idaho, but that wait
time can be as long as 12 years in some cases. The agency staffmember interviewed reported
that prior to the Recovery Act funding, its waiting list was approximately two years long, but that
after stimulus funding came in it increased to around three years. The increase in the wait list is
due to two reasons: 1) increased eligibility to 200% of the Federal Poverty Level (FPL)
expanded the enrollmentT, and 2) the economic downturn resulted in an increase of potential
applicants.
The DOE guidelines for program year 2010 have maintained the 200% of FPL income eligibility requirement.
However, consistent with the Rocky Mountain Power tariff, homes served with their dollars are only spent on
households whose income are at or below 150% FPL.
()The Cadrnus Group, lnc. i fnergy Services
.*, o n nl"l"P,YnTl!%f ilf;
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
ldaho Low-lncorne Weatherization Program Evaluation
Invoicing and Payments
In the Idaho program, the agencies send invoices directly to Rocky Mountain Power for
processing and payment. Rocky Mountain Power does not provide any up-front funding, but
pays rebates after the work has been completed and it has received an invoice. The agency
interviewed reported typically sending invoices on a monthly basis and including a report of
work done in each home along with customer information. Rocky Mountain Power stated that
both of the Idaho agencies invoice on a timely basis, and that there have not been any issues with
invoicing or data. CAPAI, the state administrator, is not involved in the invoicing or payment
process.
Staff Training
A variety of training prepares agency staffto work for the weatherizationprogram. According to
the agency, inspectors and auditors are both certified by the State of Idaho, while weatherization
crews are mostly trained in-house. The exception to this rule is lead renovator training, which is
provided by an outside company and paid for by federal funding CAPAI receives. The agency,
CAPAI, and Rocky Mountain Power all agreed that the level of staff training was sufficient.
CAPAI pointed out that the agency sends an inspector to approve each home, so there is a built-
in process that allows them to identify individuals or specific tasks needing additional training.
Reporting and Monitoring
Program reporting to Rocky Mountain Power occurs in conjunction with invoicing. Agencies
submit a cover invoice requesting payment on the homes submitted, which includes:
o Invoice number,o Date, ando Total dollar amount.
Additionally, agencies submit a one-page form on each completed home, detailing:
o Home occupant (owner versus renter)
o Client's name (or owner's name in case of rental)o Account numbero Primary heat typeo Water heat typeo Air Conditioning typeo Date measures installed
. Type of structure (single family, multi-family, manufactured home)o Total cost per measure
. Rocky Mountain Power rebate for each measure
o Calculation of agency administrative fee billed to Rocky Mountain Powero Total reimbursement requested
o kWh savings estimated for total job
o Total cost of all measures
They also keep the property owner's signature on file, authorizing the agency to work on the
property and Rocky Mountain Power to provide a rebate. No additional documentation or
reporting aside from invoicing is required.
The Cadmus Group, lnc. / Snergy Services 10
Roclry Mountain Power
Exhibit No. 5 Page 452 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho tr*ow-lncome Weatherization Program Evaluation
CAPAI, in compliance with DOE requirements, monitors a minimum of 5 percent of the homes
that are weatherized through the program. According to CAPAI, Rocky Mountain Power's
involvement in monitoring is relatively new, but Rocky Mountain Power is now engaged in the
process. CAPAI noted that it does not submit any monitoring reports to Rocky Mountain Power,
but would be willing to if Rocky Mountain Power desired that.
Any issues that are identified through monitoring are written up, and agencies are given 30 days
to submit a description of their plan to correct the problem. CAPAI reported that this system
works well for all parties. One example given was the documentation for DOE's lead safety
requirements: at first the agencies were not meeting the new DOE lead-safety documentation
standards. CAPAI and the agencies worked to establish a formalized process for their paperwork
and DOE is now very pleased with Idaho's lead-safety documentation.
Program Achievements and Lessons Learned
Both CAPAI and the agency noted that ramping up to spend the Recovery Act funding was a big
achievement in 2009. They report that the increase in volume of homes was challenging, but it
led all parties involved in the progftrm to pull together, and they believe that the agencies were
able to improve the consistency and quality of their work through the ramp-up. Furthermore,
CAPAI highlighted the fact that the Recovery Act built capacity at the agency level by forcing
them to see things from a big-picture perspective and to be more effective planners and project
managers.
Process Evaluation Conclusions
The participant survey and process interviews provided a comprehensive overview of this
program. Overall, respondents felt that Rocky Mountain Power's contribution to the program is
working effectively to increase the number of homes weatherized, and that the administration of
both the Rocky Mountain Power funding and the program in general is functioning smoothly.
The Sadmus Group, lnc. i Energy Services 1'1
Rocky Mountain Power
Exhibit No. 5 Page 453 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power
Exhibit No. 5 Page 454 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
2. lmpact Evaluation
This section describes the approach used to develop the Low-Income Weatherization Program's
expected savings estimate and adjusted gross energy savings, based on utility electric billing
data. First, a review of program participant data and annual reports is provided. Next, the billing
analysis approach is presented, including explanation of which customers were included in this
analysis, the data analyzed, and the selection of a nonparticipant sample. This is followed by
discussion of the model developed for this study, and the results of our analyses.
lntrod uction
A statistical billing analysis was conducted to determine kWh savings and realization rates for
the program for 2007, 2008, and 2009 progftlm participation years.
Typical measures installed and the frequency of installation are listed in Table 9 on page 15.
Measures most frequently installed include: air sealing and infiltration control, pipe insulation,
compact fluorescent lighting, window glass replacement, thermal door installation, and ceiling
insulation.
The savings estimate was determined from a pooled conditional savings analysis (CSA)
regression model. This model included data from a group of nonparticipant homes, which served
as the baseline.
Impact evaluation data were obtained from a number of different sources, including:
o Program data: Rocky Mountain Power provided information regarding the program's
participants and installed measures. Specifically, these data included square footage and the
list of measures installed per home. However, these data did not include quantity of measures
installed (such as number of CFLs) or measure-specific savings estimates.
c Billing records: Rocky Mountain Power provided participant and nonparticipant meter
records from January 2006 through October 2010. The nonparticipant population was
identified based on their receipt of energy assistance on their Rocky Mountain Power bill and
homes that did not receive weatherization with Rocky Mountain Power funds during the
progftlm period.
o Weather data: Cadmus collected Idaho weather data for four representative stations for the
corresponding time period from the National Weather Service G\fOAA).
Cadmus first matched participant accounts from program data with billing data. This separated
billing data into groups of participants and nonparticipants. Daily heating and cooling degree
days were then matched to each of the respective monthly read date periods in the billing data for
use in weather-adjusted savings modeling.
Data and Document Review
Correct Participant Data Corresponding to Sites
The initial data extract of program participants included names and account numbers that didn't
always correspond to those of program participants. While most customer names and account
The Cadmus Group, lnc. / Energy $ervices 13
Roclq Mountain Power
Exhibit No. 5 Page 455 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
numbers did match participants, some corresponded to previous occupants, in some cases from
more than five years back. We therefore relied on site ID and address to match the participants
with the billing and payment data.
lnvoice Date
The date field in the program data exfract indicated the date that Rocky Mountain Power entered
the program data into its system. Invoice date is not tracked in their database. Delays between the
invoice date and the date a job was entered in the system made it difficult to determine the
specific program year in which jobs were completed.s Annual program costs are associated with
invoice date and were inconsistent with tracking of weatherization jobs occurring for a given
year. For this reason, and because there were small numbers ofjobs in each year, we summarized
program impacts across all program years rather than providing annual values. Another issue
associated with this date field is that we were unable to identi$ the date weatherization was
completed and therefore unable to specifically determine start and end dates for the pre- and
post-consumption periods for the billing analysis.
Quantity and Cost Data Collection
The data collection system tracks measure names and total measure costs per home, but does not
collect the quantity of the installed measures (e.g., number of CFLs). Measure quantity is
necessary in most cases for calculating deemed savings estimates and is also helpful for
assessing cost-effectiveness at the measure level. For this project, expected savings estimates
(based on annual reports) as well as cost-effectiveness, are calculated at the program level.
Program Participation and Savings
Cadmus reviewed progrilm data and annual reports to determine average annual savings and
participant levels, as well as the distribution of measures installed over the program years being
evaluated. Table 8 provides a sunmary of Rocky Mountain Power's 2007,2008, and2009
program results.
'Average per participant savings derived from 2007, 2008, and 2009 annual reports
Average savings per participant reported by the utility were used as a benchmark to check the
results of the billing analysis and to calculate the realization rate.
Rocky Mountain Power indicated that these delays occurred during a period of understaffing and that its current
protocol is for jobs to be entered into its tracking system in the same month in which they are invoiced.
Participation determined by PacifiCorp database entries.
The Cadrnus Group, lnc. I Hnergy $ervices 1AIt
Table 8. Average Annual Savings and Participant Levelse
Rocky Mountain Po\,ver
Exhibit No. 5 Page 456 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l-ow-lncome Weatherization Program Evaluation
Frequency of installed measures is tracked for each participant household in Rocky Mountain
Power's data collection system for the program. Table 9 lists the frequency of homes receiving
diflerent weatherization measures across the three program years. Note that the frequency
reflects the number of homes that have received a specific type of measure, such as CFLs, rather
than the total number of individual measures installed through the program.
Table 9. Frequency of Measure Installations
lnfiltration controls 52 49 91 192
Pipe insulation 48 54 66 168
CFLs 10 61 92 163
Windows - double glass replacement 35 39 79 153
Doors - thermaldoor replacement 39 51 62 152
Ceiling insulation 27 32 56 115
Attic ventilation 15 21 22 58
Floor insulation 17 13 25 55
Furnace repair (electric)2 14 24 40
Duct sealing and insulation 1 3 17 21
Water heater wrap 7 12 19
Water heater replacemenl 2 4 13 19
Windows - storm windows 5 3 10 18
Wall insulation 3 I 7 18
Furnace replacement (electric)1 4 12 17
Ref rigerator replacement 1 8 I
Heat exchanger 1 1
Of the total266 participants, approximately 150 (56 percent) received at least one type of
insulation measure, while 246 (93 percent) received a mix of other shell measures aimed at
infiltration control (including air sealing, attic ventilation, duct sealing and insulation, double
glass window replacement, and window weather-stripping). There are 144 participants (54
percent) that received both insulation and infiltration, while 252 participants (95 percent)
received either insulation or infiltration. Only 14 sites (about 5 percent) received neither
insulation nor infiltration measures. The majority of these sites were electrically heated and
received installations consisting of pipe insulation, CFLs, and health and safety measures.
Billing Analysis
Methodology
Rocky Mountain Power provided monthly billing data for all residential customers from January
2006 to October 2010. They also provided a customer information file, which contained a list of
The Cadmus Group, lnc. i Energy Services 15
Rocky Mountain Power
Exhibit No. 5 Page 457 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Idaho tr*ow-[ncome Weatherization Frogran"l Hvaiuaticn
customers that had received energy assistance for their Rocky Mountain Power bill, and were
assumed to meet income requirements for the weatherization program.
Data Screening
Once participant billing data were combined with residential nonparticipant billing data, we
conducted a series ofsteps to screen participant and nonparticipant usage data. These screens
ensured the analysis was conducted with a clean, reliable dataset.
The first screening step was to summarize the monthly kWh usage and the total number of
billing days for the pre-installation (2006) and post-installation (October 2009 - September
2010) periods for each account. Pre- and post-period total usage was norrnalized to 365 days to
prevent bias if more or fewer days occurred in each time period. Participant and nonparticipant
sites were removed from analysis if any of the following applied:
1 . Fewer than l0 months of pre- and post-billing data were available.
2. Fewer than 250 billing days or more than 400 billing days in either the pre- or post-
period.
3. Total annual pre- or post-consumption of less than 1000 kWh; total annual pre- or post-
consumption more than 50,000 kWh.
4. An account changing usage from the pre- to post-period by more that70 percent.
These criteria, commonly used in billing data analyses, were selected to ensure sufficient data
were available, and to reduce chances of including sites where significant confounding changes
(other than the measures installed through the program) affecting energy consumption occurred.
After application of the screening criteria, 166 participants remained in the analysis from the
original population of 266 participants.
Non partici pant Selection
An appropriate research approach for conducting impact analysis is a "quasi-experimental"
research design. In this case, this approach consists of comparing the change in pre- to post-
energy consumption between participants and a comparison group of customers who, though
eligible, did not participate in the program. By accounting for non-program-related factors that
can affect energy use from the pre- to the post-program periods, this method can provide
estimates of "net" program impacts.
Quartiles of participant annual pre-period kWh usage were obtained for this group. The
nonparticipant population was first reduced by matching to participantzip codes.
Nonparticipants were then assigned to their respective participant quartiles, and a random sample
of four times more nonparticipants than participants was selected for each quartile. The final
nonparticipant group consisted o,f 664 nonparticipants, matched to the participant quartiles. Once
the nonparticipant quartile usage matching was performed, average daily participant pre-
consumption (2006) was 50.0 kwh, and average daily nonparticipant pre-consumption was 50.2
kWh. Through this method and the proximity of these consumption estimates, we felt the
nonparticipant group was well matched to participants for this analysis.
Once the screened participant group of 166 participants and matching nonparticipant group were
selected, accounts were matched back to billing data to obtain final, screened, monthly modeling
billing data.
The Cadmus Group, [nc. i f,nergy $ervices 1$
Roclry Mountain Power
Exhibit No. 5 Page 458 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l-ow-lncome Weatherization Program Evaluation
Billing Analysis Results
The final CSA regression monthly model specification below was used to estimate savings from
insulation measures:
ADCit=cr*BIANNUALPREi+BTPOST,+B3PARTPOST1,+B4CDDir+B5HDD;1+B6MOVER1+e1
Where for customer (i) and month (t):
o ADCit = average daily kWh consumption
o ANNUALPREi: the total annual2006 pre- period kWh usage.
o POSTT: indicator variable that is I in the post- period for both participants and
nonparticipants, 0 otherwise.
o PARTPOSTI: indicator variable that is I in the post- period for participants, 0 otherwise.
o HDDit = average daily heating degree-days (base 65)
o CDDit: average daily cooling degree-days (base 65)
o MOVE&= indicator variable that is 1 if the customer account number is different in the pre-
and post- periods (indicating the same customer is not living at the same site)
The key coefficient determining average program savings was B3. This coefficient represents the
average daily savings per program participant, after accounting for nonparticipant trends. The
inclusion of the ANNUALPRE variable was used to ensure no participants or nonparticipants
had an undue influence over the final savings estimate; resulting in a more robust model.
Table l0 summarizes overall adjusted gross kWh model savings results for the program. The
table compares average, expected savings with the average per participant model savings to
obtain an adjusted gross realization rate of 65 percent. A common measure of model reliability is
the relative precision of an estimate, defined as 1.645*standard error/Beta (or l.645lt-value).
This reliability measure indicates the estimated coefficient's relative precision-the higher the
precision (percent error relative to the savings) the lower the estimate's reliability.
As sample sizes were rather small, a large error bound occurred for the final model savings
estimate. The relative precision at the 90 percent confidence level for the program savings
estimate was26 percent. As participant pre- period usage wx 18,274 kwh, the 1,308 kWh
savings represented approximately 6 percent savings.
Table 10. Model Realization Rate Summary, kWh/Year
We investigated whether homes in the nonparticipant sample may have been weatherized outside
of the progrtrm using non- Rocky Mountain Power funding resulting in weatherization savings
untracked by the utility. In reviewing agency tracking data, as well as speaking with an agency
Adjusted Gross Savings and
The Cadmus Group, lnc. I Energy Services 17
Rocky Mountain Power
Exhibit No. 5 Page 459 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
ldaho tr-CIw-lncon:e Weatherizatlon Progran'l Evaluaticn
contact, we found that thirteen percent of low-income customers listed as non-participants had
had their homes weatheized solely with federal dollars. We adjusted the nonparticipant savings
estimate to account for these homes.
Table 1l provides a comparison of pre- and post-usage and savings estimates between the
participant and nonparticipant groups. The model estimate of participant gross savings was
consistent with the expected savings, showing a difference of 0.2 percent when comparing each
as a percentage ofpre- period usage.
- Nonparticipant annual post- usage adjusted upward to account tor weatherized homes
In addition to nonparticipant homes receiving weatherization, the savings observed in the non-
participant sample may be attributed to a few other factors.
o Between2006 and2009 residential rates in Idaho increased by 44 percent due to the
reduction of the Bonneville Residential Exchange Credit.o Effects of the U.S. economic recession are present in the post- period of this analysis.
These factors would likely also affect the participant population, however, after receiving
weatherization, the impact of these on their household would have been less than for the
participating population.
Table 1I. Savings Comparison
The Cadrnu$ Group, lnc. / flnergy $ervices 1S
Rocky Mountiain Power
Exhibit No. 5 Page 460 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Wealherlzation Program Evaluation
3. Non-Energy Benefits
Non-energy benefits of low-income programs are those that create positive change within the
homes of participants. Additional non-energy benefits accruing to the program and to society as
a whole include: changes in bill payment behavior and community economic benefits.
Participant surveys, as described in the process evaluation, were used to assess non-energy
benefits at the household level in the form of increased comfort, more disposable income, fewer
illnesses, and the ability to remain in the home. Additionally, billing and payment data were used
to estimate the program's impact on amearages and participant mobility. The economic impacts
of the program were modeled using the IMPLAN input/output model.
Participant lmpacts
In the participant survey, participants who had received Rocky Mountain Power -funded
insulation were asked a series of questions related to non-energy benefits resulting from the
program. These questions focused on the areas of increased comfort, reduced electricity
payments, improved health, and reduced mobility. Results for these findings were not quantified
and are presented in the process evaluation section.
Low-income households move on a more frequent basis than other households. One benefit of
weatherization can be that participants are less likely to need to move because of inability to pay
utility bills. These reductions in mobility were analyzed through the payment analysis by
comparing the number of times an account changed for a specific site between the pre- and post-
periods for participants and nonparticipants. While 38 percent of participants moved homes
between the pre- and the post-periods, 43 percent of nonparticipants moved homes in the same
time period. The difference between these impacts was not statistically significant, however, so
no economic impact was estimated.
Economic Impacts
Economic impacts occurring as a result of the program include jobs, income earned from
employment, value added to the regional economy, and total economic output. Direct monetary
changes to the Idaho regional economy as a result of the progftrm include:
o Program Spending: The program pays for retrofitting activities, including
administration, construction labor and materials. Some program spending, such as
payment processing in Oregon, occurs outside the region and is not included in the
regional analysis.
o Program Costs: The program is funded by customer dollars, which are collected from all
Rocky Mountain Power customers in Idaho.
o Low-Income Avoided Electric Payments: Well-weatherizedhomes use less energy than
average homes and result in an increase in disposable income for participants.
o Electric Provider Reduced Demand: Energy savings at the household level will result
in reduced final demand for electricity.
The Cadrnus Group, lnc. i Energy Services ,to
Rocky Mountain Power
Exhibit No. 5 Page 461 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Frogran'l Evaluation
To determine the impacts of these "events," we use an input/output model which contains, at its
core, a matrix that represents the regional economy. This matrix tracks what households and
industries buy and sell from each other. Because all industries are interconnected, a change in
one sector will affect other sectors, which affect other sectors, and so on, causing a domino
effect.
There are direct, indirect, and induced impacts based on how the changes ripple through the
economy. The direct effects are due to direct program spending, for example, purchase of
efficient windows for use in a weatherized house. Indirect effects arise from changes in demand
for products used in sectors directly af[ected by program activities. For example, if glass is an
input used in window manufacturing, an increase in demand for glass would be considered an
indirect effect. Induced effects are a result of changes in worker or household spending on
consumer goods and services in the general economy.
We used IMPLAN v3.0 for the analysis of economic impacts and purchased the 2009 (most
recent) Idaho-state level data package. Model inputs are sunmarized in Table 12.
Table
- Equipment includes insulation and other hardware. This model assumes that goods were purchased in ldaho, but the model also has a
"regional purchase" coefficient which takes into consideration were goods were produced.
.- The 25 percent contribulion from the federal governmenl is considered to be exogenous to the ldaho economy and is not reflected as a cost
to ldaho ratepayers.
The program expenditures, which were spread out over 2007-2009 in nominal dollars, were
adjusted to 2009 dollars using the U.S. Bureau of Labor Statistics' Consumer Price Index
inflation calculator. The expenditures across these years of analysis are included in the program
spending category. Program savings, which are used to calculate avoided electric payments and
reduced demand, were calculated to be 1,308 kWh per participant annually, or 32,700 kWh per
participant over 25 years, which is the weighted measure life of the weatherization program's
energy efficiency installations. Avoided electric payments are set equal to the net-present value
12.IMPLAN Model Inputs
Program spending
75o/opaid for by Rocky Mountain Power, 25% from federal
govemment**
Rocky Mountain Power staff travel occurring in ldaho
These expenses occur outside of ldaho and are modeled as
Rocky Mountain Power program dollars spent outside the
Ratepayer funding fhis figure is the same as program spending minus the
federal government's share for weatherization. ln our model
it is a cost to all ldaho Rocky Mountain Power customer
households.
Participants have lower
electricity bills
This is modeled as an increase in disposable spending
amongst eligible households (maximum participant
household income for a 3 person household is $27,465)
Rocky Mountain Power lost
revenue
Utility loses an amount of final demand equal to the avoided
electric payments
The Cadmus Group, [nc. I Hnergy $eruices tu
Rocky Mountain Power
Exhibit No. 5 Page 462 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Progran-l Evaluation
of participant benefits, which are the participant dollar savings and are equal to the amount of the
utility's lost revenue.
Results from IMPLAN Model
The macroeconomic impacts of the 2007-2009 program expenditures include the net creation of
7.7 totaljob-yearsl0 in the Idaho economy over the 25-year weighted measure life. A summary
of the direct, indirect, and induced employment increase are given in Table 13.
This table also contains the income, value added, and outputll of the regional economy. Impacts
occurring outside the Idaho economy are outside the scope of the study. The results indicate that
the program has an overall positive effect on the Idaho economy (total effect row). Direct losses
accrue primarily to Rocky Mountain Power (negative total value added and output), but this is
countered by the positive indirect and induced effect in the greater economy.
The total employment increase as a result of program funding is shown by sector in Table 14,
below. This chart shows the top ten industries were jobs are being created.
r0 Eachjob-year represents one year ofemployment for one person.
" Labor Income: Labor income represents all forms of employment income, including employee compensation
(wages and benefits) and proprietor income.
Value Added: Value added is the difference between an industry's total output and the cost of its intermediate
inputs. It equals gross output (sales or receipts and other operating income, plus inventory change) minus
intermediate inputs (consumption of goods and services purchased from other industries or imported). Value
added consists of compensation of employees, taxes on production and imports less subsidies (formerly indirect
business taxes and nontax payments), and gross operating surplus (formerly "other value added").
Output: Output represents the value of industry production. In IMPLAN these are annual production estimates
for the year of the data set and are in producer prices. For manufacturers this would be sales plus/minus change
in inventory. For service sectors production : sales. For retail and wholesale trade, output: gross margin and
not gross sales.
Table 13. Economic Impacts Summary
The Cadrnus Group, lnc. I Energy Services tl
Rodry Mountain Power
Exhibit No. 5 Page 463 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l*ow-lncome Weatherization Program Evaluation
Table 14. Top Ten Industries by Total Employment
40
Maint & repair construct ol
residential struc 3.1 $1 10,459 $136,664 $283,869
319
Wholesale trade
businesses 1.7 $96,1 23 $165,034 $2s4,329
437
. Special (S&LG Non-Ed
Emo & Pavroll)0.9 $41,275 $46,889 $46,889
360 Real estate establishments 0.4 $2.479 s18.605 $24.745
394
Offices of physicians-
dentists- and other he 0.2 $15,1 36 $16,153 $26,697
329
Retail Stores - General
merchandise 0.2 $4,433 $7,215 $8,496
413
Food services and drinking
nlaees 0.2 $2.769 $3 941 $8,154
324
Retail Stores - Food and
beveraoe 0.1 $4.312 $7.033 $8,327
397 Private hospitals 0.1 $7,363 $7,860 $16,056
398
Nursing and residential
care facilities 0.1 $3,161 $3,412 $5,843
-Sector 437 represents state and local government housing programs and authorities.
The sector receiving the largest impact is the construction, maintenance, and repair of residential
structures industry. Rocky Mountain Power's funding of the 2007-2009Idaho low-income
weatherization program resulted in 3.1 additional jobs in this sector for one year. The next
largest impact was on the wholesale trade business, which is a result of purchases of
weatherization materials such as insulation.
Payment Analysis and Arrearage lmpacts
Monthly energy bills and payment histories were used to quantiff the program impacts on
payment patterns and customer arrearages. Changes between the pre- and post- periods were
compared between the participant and nonparticipant groups to measure the net effects of the
program.
Methodology
Rocky Mountain Power provided monthly payment data for the low income customer sample
from January 2006 to October 2010. The sample included all participants in addition to a
nonparticipant pool that had been identified as customers that had received energy assistance on
their Rocky Mountain Power bills. These Rocky Mountain Power payment datasets included the
following information:o Payment transaction datelz (monthly)
o Actual billed amounto Actual paid amount
t2 Payment transaction date is the date the payment was processed by Rocky Mountain Power.
The Cadmus Group, lnc. / Hnergy $ervices 22
E-h i bit f":"YPYsT;H:i ii'g
*,"!31i,*;il?.=;],fr 3i
ldaho Low-lncome Weatherization Program Evaluation
o Source of payment (i.e., customers vs. extemal source)o Arrearage amount (customer's monthly unpaid ending account balance)o Disconnection / reconnection data (date occurred, fee)
In this analysis, four specific measurements were analyzed:
1. How the number of payments changed during the pre- and post- periods.
2. The total payment amounts that individuals made during the pre- and post- periods.
3. The proportion of payments to the amount billed during the pre- and post- periods.
4. The number of reconnections required during the pre- and post- periods.
Data Screening
To ensure the analysis was conducted with a clean, reliable dataset, we screened participant and
nonparticipant payment data.
The first screening step was to summarizethe monthly payment data and the total number of
billing days for the pre- (2006) and post- (October 2009 - September 2010) periods for each
account. Pre- and post-period payment information was nornalized to 365 days to prevent bias if
more or fewer days occtrred in each time period. Participant and nonparticipant sites were
removed from analysis if any of the following screens applied:
o Removal of sites with substantially more or less than 365 days in the measurement
periods (<330 and >400).
o Removal of sites with fewer than 11 bills or more than 13 bills in the pre- or post-
periods.
o Removal of sites with billed amount more than $2,500 in the pre- period or more than
$3,400 in the post- period.o Removal of sites where the total payment amount was over 150 percent of the billed
amount in either the pre- or post- period.
These criteria were selected to ensure sufficient data were available, and to reduce chances of
including sites where significant changes (other than the measures installed through the program)
affecting payments occurred. After applying the screening criteria, 229 participants and 1,429
nonparticipants remained from the original counts of 266 and2,334, respectively.
Payment Analysis Results
Number of Customer Payments
Table 15 shows the change in the average number of customer payments made out of the 12
month pre- and post-periods, with participants showing a slight increase(3 percent) in the number
of payments they were able to make (not including any energy assistance payments). However,
the nonparticipants experienced an 11 percent reduction in the number of payments they could
make (8.8 to 7.8 percent).
The Cadmus Group, lnc. / Hnergy $ervices 1.1
Roclry Mountain Power
Exhibit No. 5 Page 465 of 1 355
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l*ow-[ncorne Weatherization Frogram Hvaluation
Table 15. Changes in Number of Customer Payments
- Significant at the 95 percent level
Payment Amounts
The total amount of individual monthly bills increased substantially between the pre- and post-
periods. As shown in Table 16, the annual average bills went from $941 to $1,378 for
participants and from $981 to $1,563 for nonparticipants. This amounts to a net difference of
$145 between the participants and nonparticipants.
Table 16. Payment Amounts Summary
Total Billed
Amount $941 $1,378 -$437 $981 $1.563 -$582 $145 -*
Customer Pmt $s95 $826 -$231 $783 $770 $13 -$244 r**
Customer
Shortfall s346 $552 -$206 $1 98 s793 -$595 $389
ExtemalPmt $226 $307 -$80 $1 10 $438 -$328 $248 -*'
Net Shortfall $120 $245 -$126 $88 $355 -$267 $141
-.- Signilicant at the 95% level
The panicipants were able to make larger payments in the post-period while the non-participants
made somewhat smaller payment then before. This resulted in a more pronounced shortfall for
the nonparticipants (shortfall representing the unpaid portion of the customer's energy bill).
Table 16 shows that the participant shortfall, before external payments are applied, had increased
by $206 while the nonparticipant shortfall had increased by $595.
ln both cases, participants and nonparticipants required additional extemal agency payments in
the post-period to cover their energy bills.l3 Here again, the participants fair better. Table 16
shows the average amount of external payments to participants increased by $80 while those to
nonparticipants increased by $328. Overall, both participants and nonparticipants' net shortfall
increased. The participants' increased by $126 while the non participants' increased by $267.
IJ In the post-perio4 the amount of energy assistance Idaho state had available to assist low-income customers
was almost double the pre-period. Rocky Morurtain Power reports the amount of energy assistance they
received for their customers increased from almost $400,000 in2007 and 2008 to almost $800,000 in 2009.
The Cadrnus Group, lnc. i Energy Services 24
Rocky Mountain Power
Exhibit No. 5 Page 466 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
Figure 3 below provides a visual depiction of the change in percent of bills paid by customers
compared to external payments between the pre- and post- periods for participants and
nonparticipants.
Figure 3. Payment Impact Summary
s1,600
S1,4oo
s1,200
s1,ooo
Seoo
Sooo
S40o
s2oo
S-
Participants Participants Nonparticipants Nonparticipants(pre) (post) (pre) (post)
Participant and Nonparticipant Payments
The values (arrearage amounts) associated with the figure are provided in Table 16 above. While
an overall increase in bills affected all customers, participants were able to pay a larger portion
of their electric bill as a result of the program when compared with nonparticipants.
Number of Reconnects
We examined the number of reconnects (or disconnections) in two ways: first, as the number of
total reconnections and secondly, as the number of households with reconnections. Table l7
shows both participants and nonparticipants had a reduction in the total number of reconnections
between the pre- and post- periods.
::::::: ShOftfall
N External Payments
I Customer Payments
Table 17. Reconnection Summary
Number of Sites
with 1+
Reconnects
The Cadmus Group, lnc. i Energy Services 3C,
Rocky Mountain Power
Exhibit No, 5 Page 467 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
Participants had 59-percent fewer reconnections while nonparticipants had 33-percent fewer.
Similarly, both showed a drop in the total number of households experiencing a disconnection. A
comparison of average reconnection charges between the participants and nonparticipants reveals
a similar story. Both groups had lower total charges in the post- period; however, there was more
improvement for the participants.
Change in Arrearage
Arrearage is that portion of a customer's bill they do not pay in a given month (their unpaid
ending balance). Table 18, below, shows the program impact on customer arrearage amounts.
TabIe
*** Significant at the 95% level
The average customer arrearage represents their ending balance amount across the l2-month
period. In order to determine how the program impacts a customer's ability to cover their bill, we
exclude any external payment amounts. The arrearage value also takes into account the existing
arrearage for each customer prior to the l2-month pre- and post- periods. Participant arrears
levels increased by $54 (from $100 to $154) between the pre- and post- periods, while
nonparticiparfi arrearages increased by $10a. The percent change improvement between
participants and nonparticipants is 31 percent, which results in an average participant arearage
improvement of $31.
t4 This amount is based on the net percent change multiplied by the average pre-period participant arrearage.
18. Arrearage Summary
The Cadmus Group, lnc. / Energy Services lo
Rocky Mountain Power
Exhibit No. 5 Page 468 of 1 365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
ldaho Low-lncorre Weatherization Program Evaluation
4. Cost-Effectiveness Analysis
To assess cost-effectiveness, we conducted an analysis ofprogram costs and benefits from four
different perspectives, using Cadmus' DSM Portfolio Pro model consistent with the evaluations
recently conducted on Rocky Mountain Power's residential and C&I portfolio. The tests include:
a. PacifiCorp Total Resource Cost Test (PTRC): This test examines program
benefits and costs from Rocky Mountain Power's and Rocky Mountain Power
customers' perspectives, combined. On the benefit side, it includes avoided
energy costs, capacity costs, and line losses, plus a 10 percent adder to reflect
non-quantified benefits. On the cost side, it includes costs incurred by both the
utility and participants.
b. Total Resource Cost Test (TRC): This test examines program benefits and costs
from Rocky Mountain Power's and Rocky Mountain Power customers'
perspectives, combined. On the benefit side, it includes avoided energy costs,
capacity costs, and line losses. On the cost side, it includes costs incurred by both
the utility and participants.
c. Utility Cost Test (UCT): From Rocky Mountain Power's perspective, benefits
are avoided energy and capacity costs and line losses. Costs include any program
administration, implementation or incentive costs associated with funding the
program.
d. Ratepayer Impact (RIM): All ratepayers (participants and nonparticipants) may
experience an increase in rates to recover lost revenue. This test includes all
Rocky Mountain Power program costs as well as lost revenues. As benefits, this
test includes all avoided energy costs, capacity costs, and line losses.
e. Participant Cost Test (PCT): From this perspective, program benefits include
bill reductions. Costs include any customer contribution to the measure cost.
Table 19, below, summarizes the components of the four tests.
* Present Value of Avoided Energy and Capacity Costs includes avoided line losses occuning from reduction in customer electric use.
Table 20 below provides selected inputs to the cost analysis. These include the evaluated energy
savings for each year (based on the per-participant savings of 1,308 kwh, shown in Table 10 on
Table L9: Benefits and Costs Included in Various Tests
Present Value of Avoided Energy and Capacity Costs.
with 10% Adder for Non-ouantified Benefits Program Administrative and Marketing Cost
Present Value of Avoided Energy and Capacity Costs.Program Administrative and Marketing Cost
Present Value of Avoided Energy and Capacity Costs.
Present Value ol Avoided Energy and Capacity Costs-Program Administrative and Marketing Cost +
Present Value of Lost Hevenues
Present Value of Bill Savings Participant Share of Measure Cost (which is
The Cadmus Group, lnc. / EnerEy $ervices 27
Roclry Mountain Power
Exhibit No. 5 Page 469 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-!ncome Weatherization Program Evaluaticn
page 17 above), discount rate, line loss, and program costs. All of these values other than the
energy savings are provided by Rocky Mountain Power. The discount rate is from Rocky
Mountain Power's 2008 Integrated Resource Plan. Rocky Mountain Power also provided the
values for line loss and the program costs.
Program benefits are comprised of energy savings and their associated avoided costs. The energy
savings used in the cost-effectiveness analysis are the evaluated kWh from this study. The
analysis used a weighted average measure life of 25 years, based on planning assumptions and
weighted by savings and frequency of installations.
Two scenarios are described in Table 2l andTable23:
Table 21 presents the results of the cost-effectiveness analysis for the program for the
evaluation period (2007-2009) without taking into account any non-energy benefits aside
from those represented by the 10 percent conservation adder included in the PTRC.
Table 23 depicts the analysis for the same period and includes non-energy benefits, as
listed nTable22.
All analyses used the avoided costs associated with the Rocky Mountain Power 2008 IRP 46
Percent Load Factor Eastside Residential Whole Home Decrement.ls
As shown in Table 21, cost-effectiveness analysis results for this base-case scenario indicate that
the program is not cost-effective from any of the perspectives other than the participant cost test
(PCT) perspective. A benefit-cost ratio of 1.0 or greater is considered cost-effective. This
analysis is based on the incentives provided during the period 2007-2009 where Rocky Mountain
Power funded 75oh of measure costs. As of December 28,2010 the Rocky Mountain Power
incentive funds 85% of measure costs which may lead to a lower benefit-cost ratio.
't IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan Vol. II Appendices:
httJr:ru.X}l=i:jrciftc{Ijt ggmiocntelrtidAmlpacj.fLgorFidoc,Envim#llgfEnvilglfq$rtal .Concemsr'lnte.'grated,_lleso
urce,,,"I']I+it ginglirslf
Table 20: Selected Cost Analysis Inputs
Program Participants 64 89 113
Program Savings (kWffiear)83,686 1 16,376 147,758
Discount Rate 7.40%7.400/0 7,400h
Line Loss 11,39%11.39%11.39%
Prooram Costs
Aoencv Administrative Costs $10,545 $17,221 $18,819
lncentive Costs $79,904 $139,01 5 $168,557
Utility Administrative Costs $10,838 $8,341 $10,443
Total Proqram Costs $101.287 $164.578 s197.819
The Cadrnus Group, lnc. I Energy $ervices 28
Rocky Mountain Power
Exhibit No. 5 Page 470 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
Table 21: Program Cost-Effectiveness Summary for 2007-2009r
Total Resource + Conservation Adder (PTRC)$0.099 $426,022 $372,019 -$54,004 0,87
Total Besource No Adder (TRC)$0.099 $426,022 $338,199 -$87,824 0.79
Utility ruCr)$0.099 $426,022 $338,1 99 -$87,824 0.79
Rateoaver lmoact (RlM)$0.189 $815,476 $338,199 -$4n,277 0,41
Particioant (PCT)$0.083 $355,470 $744,924 $389,454 2.10
Lifecvcle Revenue lmoact $0,00001 046
Table 22provides the non-energy benefits that have been quantified through our analysis. The
cost-test perspective is also listed for each benefit to indicate where these benefits will be added
in the following cost-effectiveness scenario.
As shown in Table 23, in addition to the PCT, the program is cost-effective from the TRC and
PTRC perspectives with the addition of non-energy benefits.
Table 23: Program Cost-Effectiveness Summary Including Non-Energy Benefits 2007-2009
16 Lifecycle revenue impact is the change in dollars per kWh over the lifetime of the program.
Total Resource + Conservation Adder (PTRC)$0,099 $426.022 $525,295 $99,273 1.23
Total Resource No Adder (TRC)$0.099 $426,022 $491,475 $65,453 1.15
Utility (UCI)$0,099 $426,022 $346,529 -$79,493 0.81
Ratepayer lmpact (RlM)$0.189 $815,476 $346,529 -$468,947 0.42
Participant (PCT)$0.083 $355,470 $744,924 $389,454 2.10
Lifecvcle Hevenue lmpacl $0.00001 028
The Cadmus Group, lnc. I Energy Services zv
Roclq Mountain Power
Exhibit No. 5 Page 471 of 1 365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
Appendix A: Participant Suruey lnstrument
PARTICIPANT SURVEY
Rocky Mountain Power Low Income Weatherization Program 2007-2009
TO RESPONDENT: Hello, my nzlme is (FIRST NAME) from and I'm
calling on behalf of Rocky Mountain Power.
We are talking with people who received energy-saving services from (The Agency) during the
past few years.
ITF RESPONDENT EXPRESSES RESERVATIONS AT THIS POINT, USE THE FOLLOWING
SCRIPT TO PERSUADE. IF RESPONDENT DOES NOT EXPRES,SRESERVATIONS, SKIP TO
SI.J:
We'd like to ask some questions about your opinion of the services you received to help
improve the programs and understand how to assist customers in saving money on their energy
bills. Please be assured this is not a sales call and my questions are for research purposes only.
All of your answers are confidential, and will not be shared with Rocky Mountain Power or (The
Agency) in any way that identifies you.
S. SCREENING QUESTIONS
S1. Do you remember receiving services such as new light bulbs, having a refrigerator replaced,
or getting new insulation through (The Agency)?
1 Yes IGO TO 54]
2 No LGO rO S2l
98 Don't knoddon't remember IGO TO 52)
99 Refused
52. Is there anyone else at your home we could talk to who might know more about these
services?
1. Yes UFSO, ASKIFYOU MAYSPEAKTOTHISPERSON NOWI
2. No/ Don't know/don't remember
lF NO OR DON'T KNOW: Thank you. We are only able to talk with people who remember receiving these
services. We appreciate your help. [TERMINATE politely.]
53. Are you still living in the same home where you received these services?
1 Yes IGO rO All
2No
98 Don't knoddon't remember
The Cadrnus Croup, lnc. i' Energy Senvices A_I
E"hibitf"TyPys"JHiiiilfJ
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
ldaho Low-lncome Weatherization Program Evaluation
99 Refused
lF NO OR DON'T KNOW: Thank you. We are only able to talk with people who still live in the home
where the services were performed. We appreciate your help. [TERMINATE politely.]
A. PARTICIPATION / VERTFTCATION
41. How did you first hear about the program? flNTERVIEWER RECORD AND VERIFY ANSWER, DO NOT
READ L1STI
1 Agency staff
2 lnformation with my Electric bill
3 Rocky Mountain Power website
4 Other website fiF YES, WHICH WEBSITE(S)?I
5 Through another energy assistance program
6 Another public service agency
7 Written materials at Agency
8 Written materials at a public service agency
9 Family/friends/word-of-mouth
10 Rocky Mountain Power Representative
11 Radio
12 TV
13 HVAC Contractor
14 Other ISPECIFY AND RECORD VERBATIM]
98 Don't know/don't remember
99 Refused
A2. Did you know Rocky Mountain Power paid for part of these services?
1 Yes
2No
98 Don't know
99 Refused
IFALLOWTNG MEASURE LIST FOR EACH pARTtCtqANT, ASK MEASURE-SPECIFtC QUESTIONS ONLY FOR
THOSE MEASURES THE PARTICIPANT RECE|VEDI
ilF MEASURE=CFLs, READ A3, ELSE SKIP TO A1-01
43. Our records show that you received several new light bulbs. Did the agency staff install these new
light bulbs directly into light fixtures or did they leave them with you? IDO NOT READ LIST - CHOOSE
APPROPRTATE ANSWER BASED ON RESPONSEI:
1 The new light bulbs were installed by the agency staff directly in the light fixture
2 The agency staff left behind new lights for me to install
3 I didn't receive new light bulbs /SK/P TO A10l
98 Don't know /SK/P TO A10l
99 Refused ISKIP TO A10]
The Cadmus Croup, lnc. r' [nergy Senvices A-2
Rocky Mountain Power
Exhibit No. 5 Page 473 of 1 365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
ldaho l-ow-[ncome Weatherlzation Frograrn Hvaluation
44. How would you rate your new light bulbs? Would you say they were [READ LIST]:
1 Excellent
2 Good
3 Fair
4 Poor
98 Don't know /SK/P TO A10l
99 Refused ISKIP TO A10]
A5. Why did you give the light bulbs a(nl (RESPONSE FROM A4) rating? [DO NOT READ, RECORD FIRST
THREE RESPONSES/
Negative
1 I don't like the color of the light
2 The light is too bright
3 The light is too dim
4 They flicker
5 They take too long to light up
6 They don't fit well in my fixtures
7 They don't look nice in my fixtures
8 I just didn't like them
9 They burn out quickly
Positive
10 They're better than the bulbs I had
11 They're just fine or I just like them
12 I like the way they look
13 They give good light
14 They save energy/electricity
15 They lower the electric bill
16 They [will] save me money
17 They were free
18 I needed new light bulbs anyway
19 I won't have to change hard to reach fixture
20 I won't have to change the bulb frequently
21 Other [SPECIFY]
98 Don't know
99 Other
46. Did you replace any of the light bulbs that were installed with different ones?
1 Yes
2 No ISKIP TO QUESTION A1-0]
98 Don't know [SK/P TO QUESTION A10]
99 Refused [SKIP TO QUESTION A10]
ilF ANSWER = YES lN A6, READ A7, ELSE SKIP TO A10l
A7. How many light bulbs did you replaced?
IRECORD N U M BE R VERBATI U M]-
The Cadrnus firCIup,;' [nergy Services A-3
Rocky Mountain Por/er
Exhibit No. 5 Page 474 ot 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Idaho l-ow-[ncorne Weatherization Frogram fivaluation
A8. Did you replace these with incandescent light bulbs or energy-saving light bulbs (CFLs)?
1 lncandescent
2 CFL
98 Don't know /SK/P TO A10l
99 Refused ISKIP TO A10]
A9. Why did you replace these bulbs?
IRECO RD An swe r VERBATI U M ]-
fiF MEASURE=REFRIGERATOR OR FREEZER, READ A70, ELSE SKIP TO A73l
A10. Our records show that you received a new refrigerator(s) or freezer. ls this correct?
1 Yes
2 No [sKtP TO QUESTI?N A13]
98 Don't know /SK/P TO QUESTION A13l
99 Refused ISKIP TO QUESTTON A73]
ilF A10 = YES, READ AL1, ELSE SKIP TO A13l
A11. How would you rate the new refrigerator or freezer that was installed in your home? Would you
say it was IREAD LIST]:
1 Excellent
2 Good
3 Fair
4 Poor
98 Don't know /SK/P TO A13l
99 Refused ISKIP TO A13]
A12. Why did you give it a(nl (RESPONSE FROM A77) rating? IDO NOT READ, RECORD FIRST THREE
RESPONSES/
Negative
L l don't like the way it looks
2 I don't like the color
3 The refrigerator or freezer is too small
4 The refrigerator or freezer is too large
5 lt doesn't keep the food at the right temperature
6 lt stopped working
7 I just didn't like it
Positive
8 lt saves energy/electricity
9 lt lowers the electric bill
L0 lt was free
11 I like the way it looks
12 I like the color
13 The refrigerator or freezer is a good size
14 lt keeps the food at the right temperature
15 lt works
L6 I was glad not to have to clean out my old refrigerator
The Cadmus firo*p, lnc. r' [nergy Senvices A-4
Rocky Mountain Power
Exhibit No.5 Page 475 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
17 I needed a new refrigerator or freezer anyway
18 My old refrigerator stopped working/wasn't working well
19 lt is just fine or I just like it
20 Other ISPE0IFY]
98 Don't know
99 Other
flF MEASURE=INSUUTION, READ A73, OTHERWISE SKIP TO A15l
A13. Our records show you received some new insulation. IPROVIDE DESCRIPTION OF INSUUTION lF
RESPONDENT lS NOT SURE: flufu moterial put in ottic or walls to keep your home more comfortablel
How would you rate the new insulation that was installed in your home? Would you say it was
[READ LIST]:
L Excellent
2 Good
3 Fair
4 Poor
5 Didn't receive insulation ISKIP TO A15]
98 Don't know /SK/P TO A15l
99 Refused ISKIP TO A15]
A14. Why did you give the insulation a (RESPONSE FROM A73) roting? IDO NOT READ, RECORD FIRST
THREE RESPONSESI
Negative
1 lt wasn't enough
2 lt was too much
3 lt didn't help keep the house more comfortable
4 The contractor didn't finish
5 The contractor left a mess
Positive
6 lt saves energy/electricity
7 lt lowers the electric bill
8 lt was free
9 The house is more comfortable
10 The contractor did a nice job
11 I needed additional insulation anyway
12 lt keeps the house warmer / cooler
13 Other ISPEAF\
98 Don't know
99 Refused
ilF MEASURE=INFILTRATION / CRACK SEALTNG READ A75, ELSE SKIP TO A16l
A15. Our records show that you had some cracks sealed up on your home where outside air used to leak
in. How would you rate the work that was done to seal these cracks? Would you say it was IREAD
LtsTl:
1 Excellent
The Cadmus Croup, lnc. 1' [nergy Senvices A-5
,,n, on rl"1'IrYntH:iilfJ
*,f:::,h;i?';1,i;:1
ldaho Low-lncome Weatherization Program Evaluation
2 Good
3 Fair
4 Poor
5 Didn't receive air sealing
98 Don't know
99 Refused
ilF MEASURE=FURNACE REPAIR/REPUCEMENT READ A16, ELSE SKIP TO A19l
A16. Our records show that you had your furnace either replaced or repaired. How would you rate the
work that was done on your furnace? Would you say itwas [READ LIST]:
1 Excellent
2 Good
3 Fair
4 Poor
5 Didn't receive furnace repair/replacement ISKIP TO A19]
98 Don't know
99 Refused ISKIP TO A19]
A17. Before the work was done, did your furnace work?
1 Yes, it worked fine
2 Worked but had problems
3 No, it did not work at all
98 Don't know/don't remember
99 Refused
A18. Why did you give the work on your furnace a (RESPONSE FROM A76) roting? IDO NOT READ,
RECORD FTRST THREE RESPONSESI
Negative
1 My furnace worked better before
2 I didn't need a new furnacefurnace repairs
3 lt didn't help keep the house more comfortable
4 The contractor didn't finish
5 The contractor left a mess
Positive
6 lt saves energy/electricity
7 lt lowers the electric bill
8 lt was free
9 The house is more comfortable
10 The contractor did a nice job
11 I needed a new furnace anyway
12 lt keeps the house warmer
13 Other lSPEqFn
98 Don't know
99 Refused
fiF MEASURE=WINDOWS READ A79, ELSE SKIP TO A23l
The Cadmus Group, lnc. r' fnergy Services A-6
'*. on,X"l"I'YnTl9:iilfJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
tdaho Low-lncome Weatherization Program Evaluation
A19. Our records show that you had some work performed on one or more windows in your home. Can
you tell me whether they replaced windows or repaired existing windows?
1 Replaced
2 Repaired
3 Replaced some and repaired some
98 Don't know/don't remember
99 Refused ISKIPTO A23]
A20. Was the glass broken or cracked in any of the windows they worked on?
1 Yes, glass was broken
2 No, glass was intact
98 Don't know/don't remember
99 Refused
A21. How would you rate the work that was done on your windows? Would you say itwas [READ LIST]:
1 Excellent
2 Good
3 Fair
4 Poor
5 Didn't receive windows ISKIP TO A23]
98 Don't know
99 Refused ISKIP TO A23]
A22. Why did you give it a (RESPONSE FROM A27) rating? [DO NOT READ, RECORD FIRST THREE
RESPONSESI
Negative
1 I liked my old windows better
2 | don't like the way the new window looks
3 I don't like the way the new window works (opens/does not open, etc.)
4 My home is not as secure
5 I didn't need new windows or repairs
6 lt didn't help keep the house more comfortable
7 The contractor didn't finish
8 The contractor left a mess
Positive
9 lt saves energy/electricity
10 lt lowers the electric bill
11 lt was free
12 I like the way it looks
13 The house is more comfortable
14 The house is more secure/safer
1.5 The contractor did a nice job
16 I needed a new window or window repair anyway
17 lt keeps the house warmer
18 Other ISPECIFY
98 Don't know
The Cadrnus Croup, lnc. i Energy Services A-7
E,hibitf":"YPYs""'HiiiffJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncorne Weatherization Program Evaluation
99 Refused
fiF MEASURE=THERMAL DOOR READ A23, ELSE SKIP TO B1l
A23. Our records show that you had a thermal door installed. How would you rate the work that was
done on your door? Would you say itwas [READ LIST]:
1 Excellent
2 Good
3 Fair
4 Poor
5 Didn't receive door [SKIP TO 81]
98 Don't know
99 Refused [SKIP TO 81]
A24. Why did you give it a (RESPONSE FROM A23) roting? IDO NOT READ, RECORD FIRST THREE
RESPONSES/
Negative
1 I liked my old door better
2 I don't like the way the new door looks
3 I don't like the way the new door works (e.g., problem with lock, handle)
4 My home is not as secure/safe
5 I didn't need new door
5 lt didn't help keep the house more comfortable
7 The contractor didn't finish
8 The contractor left a mess
Positive
9 lt saves energy/electricity
10 lt lowers the electric bill
l.L lt was free
12 I like the way it looks
13 The house is more comfortable
14 The house is more secure/safer
15 The contractor did a nice job
16 I needed a new door anyway
17 lt keeps the house warmer
18 Other lSPEdFn
98 Don't know
99 Refused
B. Energy Education / Non-Energy Benefits
81. Do you remember receiving a booklet or pamphlet with information about how to save energy?1 Yes2 No [sKtP To QUEST|ON 83]
98 Don't know ISKIP TO QUESTION 83]
99 Refused ISKIP TO QUESTION 83]
The Cadmus Croup, lnc. i [nergy Services A-8
Roclry Mountain Power
Exhibit No. 5 Page 479 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l-ow-[ncorne Weatherization Prograrm HvaIuation
82. Did you read the pamphlet or look at it after the agency staff left your home?
1 Yes
2No
98 Don't know
99 Refused
83. Did the agency staff who came to your home give you any tips on how you could save money on
your energy bill?
3 Yes
4 No ISKIP To QUEST|ON 87]
98 Don't know
99 Refused ISKIP TO QUESTION 87]
B4. Can you please list any tips you remember about how to use less hot water in order to lower
your energy bill?
[F o'Yes ", DO NOT PROMPT BUT MARK ALL THAT APPLY; IF "Don't Know ", PROMT
WITH LIST OF TIPS BELOW; 1F "No," DO NOT PROMPT, MARK 'No," AND GO TO NEXT
SUESTTONJ1 Lower hot water thermostat to 120F
2 Take short showers instead of baths
3 Repair leaky faucets
4 Turn off water while shaving, brushing teeth or doing the dishes
5 Wash only full loads of dishes and clothes
6 Use cold water when possible
7 Wash clothes in cold water
8 Other ISPECIFY)9No
98 Don't know IMARK ONLY lF AFTER PROMPTS THE RESPONDENT STILL INDICATES "Don't Know"l
99 Refused
85. Can you please list any tips you remember about how to save money on heating or cooling
your home?
[F "Yes ", DO NOT PROMPT BUT MARK ALL THAT APPLY; IF "Don't Know ", PROMT
WITH LIST OF TIPS BELOW; IF'No," DO NOT PROMPT, MARK 'No," AND GO TO NEXT
QUESTTONJ1 Set thermostats high in summer and low in winter
2 Use ceiling fans, window fans, or table fans instead of air conditioners
3 Use open windows with fans to cross ventilate on cool nights instead of air conditioners
4 Close windows, doors, shades and drapes during the day to keep the sun's heat out
5 Plant leafy green trees on the sunny side of your home
6 Clean cooling coils and filters on your air conditioners monthly in the summer
7 Use the recirculate setting so your air conditioner doesn't have to work as hard
8 Plant trees to shade air conditioners but not block air flow
9 Check furnace filter monthly and change if needed
10 Other ISPEC|FYI
11 No
The Cadnrus Croup, lr'!c. ,,' [merEy Senvices A-9
Rocky Mountain Power
Exhibit No. 5 Page 480 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l-ow-[ncome We*therlzation Program Evaluation
98 Don't know [MARK ONLY lF AFTER PROMPTSTHE RESPONDENT STILL INDICATES "Don't Know"]
99 Refused
86. Can you please list any tips you remember about how to use your appliances - like
refrigerators, washers, dryers, stove tops or ovens - so that they use less energy and save you
money?
[F "Yes ", DO NOT PROMPT BW MARK ALL THAT APPLY; IF "Don't Know", PROMT
WITH LIST OF TIPS BELOW; /F'No," DO NOT PROMPT, MARK ooNo," AND GO TO NEXT
SUESTTONJ1 Remove lint from dryer trap between loads2 Vent dryer to outdoors
3 Unplug second refrigerator or freezer
4 Use 38 to 40 degrees F for fresh food and 0 to 5 for the freezer
5 Clean condenser coils on refrigerators and freezers
5 Make sure your refrigerator door seals are tight
7 Use a microwave, toaster oven or crockpot before conventional oven
8 Avoid preheating the oven
9 Use smallest pan necessary for cooking
10 Defrost frozen foods in refrigerator
11. Heat water for beverages in the microwave oven
12 Clean inside surfaces of microwave
13 Other [SPEqFn
14 No
98 Don't know IMARK ONLY lF AFTER PROMPTS THE RESPONDENT STILL INDICATES "Don't Know"l
99 Refused
87. Of the energy saving tips you remember, which ones have you practiced at your own home?
IIF NECESSARY, PROMPT WITH ANSWERS TO PREVIOUS RE',^9PONSES FROM 84, 85, 86)
1. ISPECIFY2 Other ISPECIFY3 None
98 Don't know [MAR K ONLY lF AFTER PROMPTS THE RESPONDENT STILL INDICATES "Don't Know"]
99 Refused
UF MESURE = INSULATION, ASK 88-872, ELSE SKIP TO B13l
B8. Since (The Agency) completed the work your home, would you say that your home is IREAD LIST]:
1 More comfortable to live in
2 Just about as comfortable to live in as it was before the weatherization
3 Less comfortable to live in
98 Don't know/don't remember
99 Refused
89. Since this work was completed, would you say that your electric bills have been IREAD LIST]:
1 More affordable
2 About the same
3 Less affordable
The Cadmus Croup, lnc. 1' Energy Ser"vices A-l 0
E-h i b,' nl":'Y':lTlF[iiYg
*,"?3ii*?;if?*;l,i*I
ldaho l*ow-lncome Weatherization Frogram Evaluation
98 Don't know/don't remember
99 Refused
B10. Would you say that your health has been affected in any way since this work was performed on
your home?
1 Yes
2No
98 Don't know/don't remember
99 Refused
ilF 810 = 1, READ 877, ELSE SKIP TO B72l
B11. Why do you say that? IDO NOT READ, CHOOSE MULTIPL]
1 I recently had an illness (associated with this work)
2 I recently had an illness and my health has improved because of this work
3 I recently had an illness (not associated with this work)
4 I recently had an injury (associated with this work)
5 I recently had an injury and my health has improved because of this work
6 I recently had an injury (not associated with this work)
7 lt is more comfortable in my home and l'm healthier
8 I haven't needed to visit the doctor/hospital as frequently
9 I haven't had to make repairs as much
10 l'm not as worried about my home
11 I feel safer (more secure) in my home
12 Other lSPEgFn
98 Don't know/don't remember
99 Refused
812. Do you think having your home weatherized made you more likely to be able to stay in your home?1 Yes, more likely to stay
2 No, just as likely to stay
3 No, more likely to move
98 Don't know
99 Refused
B13. What were the biggest benefits you got from having your home weatherized?7 lsPEqFn2 No benefits
98 Don't know/don't remember
99 Refused
814. Did having these changes made to your home create any problems for you?
1 Yes ISPECIFY2 No ISKIP TO QUEST\1NCT]
98 Don't know/don't remember ISKIP TO QUESTION Cl]
99 Refused [SKIP TO QUESTTON Cl]
B15. Was the problem resolved to your satisfaction?
1 Yes ISKIP TO QUESTION Cl]
The Cadmus Croup, lnc. / [nergy Senvices A-11
E,h i br f":"YPYsTlg:iil'g
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
2No
98 Don't know/don't remember ISKIP TO QUESTION C1]
99 Refused ISKIP TO QUESTTON C1]
llF 875=2, READ 816l
B15. How would you have liked them to resolve this problem?
ISPEC|FY AND RECORD VERBATTM]
C. OVERALL PROGRAM SATISFACTION
TO RESPONDENT: Next, I have a few questions about (The Agency's) service in providing these services
to you and your home.
C1. How courteous and respectful was the agency staff? Would you say they were IREAD LIST]:
1 Very courteous
2 Somewhat courteous
3 Not very courteous
4 Not at all courteous
98 Don't know/don't remember
99 Refused
C2. Before agency staff came to your home to perform work, did you understand what they were going
to do in your home?
1 Yes
2No
98 Don't know/don't remember
99 Refused
C3. Were you happy with their plan?
1 Yes
2No
98 Don't know/don't remember
99 Refused
C4. How satisfied are you overall with the services this program provided? Would you say that you are
IREAD LIST]:
1 Very satisfied
2 Somewhat satisfied
3 Not very satisfied
4 Not at all satisfied
98 Don't know
99 Refused
C5. How would you improve the program?
IRECORD VERBATTM]
The Cadmus Croup, lnc. i' Energy Services A-l 2
Roclq Mountain Power
Exhibit No. 5 Page 483 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho [-ow-[ncome Weatherization Frogram Hvaluation
C5. Do you know who to call if you have any problems?
1 Yes
2No
98 Don't know/don't remember
99 Refused
IIF NO OR DON'T KNOW, PROVIDE THE APPROPRIATE CONTACT INFORMATION _
SEE AGENCY PHONE NUMBER ON PARTICIPANT INFORMATION PROVIDEDJ
D. HOUSEHOLD CHARACTERISTICS / DEMOGRAPHICS
I just have a few more general questions for you.
D1. Which of the following best describes your home?
1 Single family house
2 A unit in a multifamily apartment
3 Manufactured or mobile home
98 Don't Know
99 Refused
D2. Do you rent or own your property?
1 Own
2 Rent
3 Other ISPEAF\_
98 Don't Know
99 Refused
D3. How is your home heated? IREADI1 Electricity
2 Natural gas
3 Propane
4 Other ISPECIFY-
98 Don't Know
99 Refused
D4. How is your water heated? IREADI1 Electricity
2 Natural gas
3 Wood
4 Propane5 Other ISPECIFY
98 Don't Know
99 Refused
D5. Do you have in your home any: IREAD - MARK NUMBER THAT APPLIES FOR EACHI
1 Roomair-conditioners
2 Centralair-conditioners
The Cadrmus Group, lnc. i' Energy Senvices A-l 3
Roclry Mountiain Power
Exhibit No. 5 Page 484 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherlzation Frogran"r Evaluation
3 Swamp coolers
4 Fans or ceiling fans
5 Other ISPECIFYI
98 Don't Know
99 Refused
D6. Which best describes how your energy bills are paid? [READ]1 I pay the energy bills
2 My landlord pays the energy bills
3 A relative pays the energy bills
4 Other [SPECIFY_
98 Don't Know
99 Refused
D7. Do you recall receiving energy assistance from [THE AGENCY]? IREAD - MARK ALL THAT APPLW UF
NECESSARY TO EXPLAIN 'ENERGY ASSISTANCE,' EXPLAIN "The program moy have been colled LIHEAP
and it helps you poy your energy bills"l
1 Never
2 Not recently
3 ln the past few years
4 Before the work was completed
5 After the work was completed
6 Other ISPECIFY
98 Don't Know
99 Refused
ln the past few years, how many people typically lived in your home at the same time?
_IRECORD RESPONSE]
98 Don't know
99 Refused
Have any of the following changes occurred in your home in the past few years IREAD LIST]?
1 Family or roommates moved in
2 Family or roommates moved out
3 Using more rooms in the house now
4 Using less rooms in the house now
98 Don't know
99 Refused
DL0. How many persons are living in your home in the following age groups IREAD LIST - RECORD
NUMBER]?
1 Under the age of 6
2 Between 6 and 18
3 Between 19 and 60
4 Overthe age of60
98 Don't know
99 Refused
D8.
D9.
The Cadnrus Croup, lnc. i [nergy Senvices A-l 4
E h i bit f":"YP:!""'lg:iilfJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
D11. Can you please tell us your age?
_IRECORD RESPONSE]
98 Don't know
99 Refused
[DO NOT ASK, B\JT RECORD GENDER OF RESP2NDENT (MALE/FEMALE):-]
That concludes the survey. Thank you for your time today, Rocky Mountain Power appreciates your
feedback.
The Cadmus Group, lnc. i' [nergy Senvices A-l 5
Roclry Mountain Po\ryer
Exhibit No. 5 Page 486 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
Appendix B: Stakeholder lnterview Guide
Rocky Mountain Power Low-lncome Weatherization Program
Stakeholder lnterview Guide
The Cadmus Group, Inc. has been hired by PacifiCorp to conduct a process evaluation of the
low-income weatherization program. The process evaluation focuses at a high level on how
the program flows and whether it was delivered as intended. We are interviewing a variety of
program stakeholders including staff from: Rocky Mountain Power, Utah Housing and
Community Development (HCD), the Community Action Partnership of Idaho (CAPAI), and
local community action agencies (CAAs). None of the comments you share today will be
attributed to you as an individual. However, some comments may be attributed to your
organization.
Can you begin by telling us your title and role in the weatherization program?
Program Design and Implementation
l. (Utility only) What are the goals for Rocky Mountain Power's funding of the program?
a. Are these goals being met? fProbe for participation goals, kWh goals, and agency-
specifi c performance goals.]
2. (Utility, State, Agency Assoc., CAAs) Did the Rocky Mountain Power funding have an
impact on the program (number of households served, amount of money spent in a home,
or the depth of the weathenzation work performed)?
3. (Utility, State, Agency Assoc., CAAs) Were Rocky Mountain Power funds exhausted in
each program year (2007-2009)?
4. (Utility, State, Agency Assoc., CAAs) What are the restrictions placed on Rocky
Mountain Power funds?
a. How are Rocky Mountain Power funds incorporated into the other dollars
available for weatherization?
5. (Utility, State, Agency Assoc., CAAs) What is the typical Rocky Mountain Power cost
share of a project - is it by measure or total house?
a. What percent of health and safety installations are paid by Rocky Mountain
Power - are there any specific constraints with how these funds are spent?
6. (Utility, State, Agency Assoc., CAAs) Have the goals of the program changed because of
the ARRA weatherization funding? How has the use of utility funding changed?
7. (CAAs) What were the total homes in Rocky Mountain Power service territory
completed for years 2007 ,2008, and 2009? What was the percent of homes completed by
different heating source (e.g. electric, gas, other)?
8. (CAAs) Were more homes completed in Rocky Mountain Power service territory than
were tracked by Rocky Mountain Power? In other words, does Rocky Mountain Power
funding touch every home weatherized in their own serviced territory and, if not, how
many other homes are weatheized?
The Cadmus Croup, lrtrc. i' [mergy Senvices B-1
Roclry Mountain Power
Exhibit No. 5 Page 487 of 'l 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho l*ow-lncome Weatherization Frogram Evaluation
9. How is it decided to use Rocky Mountain Power funding for a specific home?
a. Are most homes billed to Rocky Mountain Power electrically-heated, non-
electrically heated, or is there another method of selection?
10. (Utility, State, Agency Assoc., CAAs) Who delivers weatherization services in the field,
community action agency staff or contractors? Does that differ from agency to agency?
I l. (Utility, State, Agency Assoc., CAAs) Does the program provide energy education for
the resident? If so, what materials are used and how is it provided to participants?
12. (Utility, State, Agency Assoc., CAAs) How large is the waiting list, generally - both in
terms of size and length of wait time?
13. (Utility, State, Agency Assoc., CAAs) How are homes or residents prioritized for
weatherization?
14. (Utility, State, Agency Assoc.) Are there any Native American tribes participating in
weatherization? Are they implementing and administrating the program themselves?
15. (Utility, State, Agency Assoc., CAAs) How is Rocky Mountain Power invoiced for their
contribution? Do agencies provide invoices or do they have funds available to access
from Rocky Mountain Power at the beginning of the program year? Please explain this
process.
16. (Utility, State, Agency Assoc., CAAs) Are payments made in a timely manner?
17. (Utility, State, Agency Assoc., CAAs) How would you rate the communication between
Rocky Mountain Power, [Utah HCD/CAPAI], and the CAAs? Are there any changes you
would suggest to improve communication?
Program Training and Qualifications
18. (Utility, State, Agency Assoc., CAAs) What training is required for CAA staff or
contractors delivering the program? Are there any certifications necessary?
19. (Utility, State, Agency Assoc., CAAs) In your opinion, is this training sufficient?
20. (State, Agency Assoc.) If reoccurring issues are identified through monitoring, are those
issues addressed in trainings?
Program Reporting and Monitoring
21. (Utility, State, Agency Assoc., CAAs) What are Rocky Mountain Power's reporting
requirements and expectations?
22. (Utility, State, Agency Assoc., CAAs) What project tracking is required of the CAA's? Is
there a centralized state database that is maintained on the program?
23. (Utility, State, Agency Assoc., CAAs) Does most reporting occur electronically? Is there
a move towards electronic record keeping?
24. (Utility, State, Agency Assoc., CAAs) What data are reported to Rocky Mountain Power?
How frequently does Rocky Mountain Power receive reports?
25. (Utility, State, Agency Assoc., CAAs) Are there any problems with data collection or
reporting that you haven't already mentioned?
26. (Utility, State, Agency Assoc.) How many projects were monitored in 2007-2009, and
what is the monitoring rate? Is this sufficient, in your opinion?
27. (Utility, State, Agency Assoc.) What percentage of those monitoring visits found
problems to be resolved? What problems were most common?
The Cadrnus Croup, lnc. i' Energy Services B-2
Roclry Mountain Power
Exhibit No. 5 Page 488 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ldaho Low-lncome Weatherization Program Evaluation
28. (Utility, State, Agency Assoc.) When oversights are found, how is the problem
addressed?
Program Achievements
29. How do you think the program performed in the 2007-2009 period? What are the
program successes, or most important achievements?
30. What are the obstacles or challenges with the program? Were there any bottlenecks?
31. Are there any progam lessons learned over the past 3 years?
32. How would you rate the quality of the program?
33. Do you have any suggestions for program improvements?
34. Is there any information you would like to see the evaluation deliver to help with
program process?
The Cadrnus Croup, lnc. i Energy Senvices B-3
Rocky Mountain Power
Exhibit No. 5 Page 489 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
I reffiouNrAIN
Exhibit No. 5.7
Irrigation Load Control Evaluation 2009-2010
Rocky Mountain Power
Exhibit No, 5 Page 490 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
CAilh{T}S
ilRSLli), lNil.
March 24,2011
Jeff Bumgarner
Jim Stewart, Hossein Haeri and Brian Hedman
lmpacts of Rocky Mountain Power's ldaho lrrigation Load Control
Program
Rocky Mountain Power retained The Cadmus Group to evaluate the 2009 and 2010 demand
impacts of the company's irrigation load control program offered to the customers in Idaho. This
document summarizes the results of Cadmus's study.
Background
In 2009, the Program enrolled 2,032 customers and had approximately 260 MW of participating
load in Schedule 72 (schedule forward) and Schedule 72A (option dispatch). In 2010, the
Program enrolled 1,975 customers and had approximately 283 MW of participating load. In both
years, over 98 percent of the Program load was enrolled through the dispatch option.
During the 2008 Program Season the Company began noticing voltage excursions outside
industry acceptable standards during dispatch events. In 2010 the Company implemented a
process to reduce load and retum load to normal operating levels in phases to minimize the
impact on the company's transmission and distribution system. As a result, the Company was
still unable to take the entire participating load off during the peak time period between 2:00p
and 6:00p. As a consequence, the current level of participation is beyond what RMP can
effectively dispatch. This has reduced the Program's cost-effectiveness.
Technical Approach
The Cadmus Group estimated the hourly load reductions achieved by the Program in 2009 and
2010. The analysis was conducted using SCADA system data for five sub-stations (Amps, Big
Grassey, Bonneville, Jefferson, and Rigby) that accounted for most (77 percent) of the controlled
irrigation load in Idaho. For each substation and event hour, Cadmus estimated a reference load,
what the load would have been in the absence of the event, and compared it to the observed load
during curtailment events. Results were extrapolated as representative of the remaining circuits
to account for total program loads.
The reference load for an event hour was estimated in two ways: (1) as the unconditional average
load in the same hour of the two weekdays preceding and following the event; and (2) as the
conditional average load estimated using a regression of hourly demand on weather, calendar and
time effects, and indicators for event hours and hours preceding and following the event. The
The Cadmus Group, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 r 503.228.2992 + Fax [phone]
An Employee-Owned Company . wwrar.cadmusgroup.com
Jeff Burngarner
February 24, 2011
Rocky Mountain Power
Exhibit No. 5 Page 491 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 2 of 22
difference between the observed load and the actual yielded the estimate of the load reduction in
the event hour.
For both estimation approaches, the estimated load reduction in each hour was compared to the
expected load reduction (nominal load reduction) adjusted for opt-outs and a load reduction
realization rate was calculated. There are several aspects of this methodology that are worth
noting before considering the results. Nominal load is defined as the sum of customers' average
billing demands for June, July and August for the two prior years.
o The impact analysis is based on SCADA data at the substation level. Since the majority
of the loads being served by these substations consist of inigation, the amount of "noise"
in the data resulting from the variability of non-irrigation loads is expected to be minimal.
Moreover, the hourly demand model used to estimate the load impacts largely accounts
for such noise in the substation data.l
. Program management staggers (stair-steps) the dispatching of loads at the beginning and
end of events for grid reliability purposes. The hourly analysis of loads does not account
for the staggering. As a result, the estimated load impacts in the first and last hours are
an estimate of the average load reduction over the hour and may not represent the true
reduction at the beginning (likely to be smaller than estimated) or end of the hour (likely
to be larger).
. The analysis adjusts for, in the calculation of realization rate, the required scheduling of
22 percent of the available participating loads outside of the 2:00p-6:00p time period.
This scheduling restriction was implemented in 2010 to accommodate the Grid control
voltage limitations previously noted. While this did not impact realization rates, it did
impact the decrease in aggregate reduction from 205 MW in2009 to 156 MW in 2010.
Results Summary and Conclusions
With these limitations in mind, the evaluation team analyzed the substation data for the 2:00p to
6:00p time horizon and reached the following conclusions:
o In 2009, the maximum hourly load reduction on the five substations was 158 MW which
extrapolates to 205 MW for the entire program. This reduction occurred on July l7 and
represented 86 percent of the nominal load (program resources) adjusted for opt-outs in
the hour. Tlte realization rates, which show how much load was shed relative to
expectation, ranged from a low of 17 percent on August 5 to the July 17 high of 86
percent. In 2010, the maximum hourly load reduction at the five substations was 120
t Of the five substations only the Rigby substation serves other loads, including small businesses, a college, a
hospital and the cities of Rexburg, Rigby, Ririe, Menan, and smaller towns.
The Cadmus Group, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 r 503.228.2992 o Fax [phone]
An Employee-Owned Company . www.cadmusgroup.com
Jeff Bumgarner
February 24, ZO11
Roclry Mountain Power
Exhibit No. 5 Page 492 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 3 of 22
MW which extrapolates to 156 MW for all Idaho irrigation program loads. This occurred
on July 8 and represented 77 percent of the opt-out-adjusted nominal load in the hour.
Program benefits are calculated based on 156 MW of system impact. On July 20, aload
reduction of 120 MW resulted in the maximum realization rate of 82 percent. During
hours when events are traditionally called, realization rates ranged from a low of 29
percent on August 24 to the high of 82 percent on July 20.
Realization rates were calculated based on expected loads, or in the case of the Rocky
Mountain Program, loads that could safely be dispatched without adversely impacting
line voltages. This is an important distinction worth noting. Had the calculation of
realization rates been based on total participating loads, this would have resulted in lower
realization rates. As program cost-effectiveness is calculated on actual load reductions
relative to a program's costs (rather than a realization rate), realizations rates should not
be considered the definitive measurement of a program's effectiveness and value.
The load reductions and realization rates in any year may not be representative of typical
load impacts the program might achieve because of annual weather-related variations in
irrigation demand.
. Rocky Mountain Power system peak coincides with hours when events are traditionally
called (hours 2:00p to 6:00p). In 2009, all of the top 10 non-event, summer hours
occurred during the traditional event window. Rocky Mountain Power system peak hours
do not coincide with morning and early afternoon / evening hours when loads were
dispatched in 2010 because of transmission and distribution constraints.
o While the Program has been operationally effective, it has not been as cost-effective as it
could be. In 2009 and20t0, the Program enrolled more load on some substations than it
could dispatch during peak hours because of transmission and distribution constraints.
To increase future cost-effectiveness, RMP needs to either upgrade its transmission and
distribution system in Idaho to remove the operating constraints or limit enrollment in the
Program to a level consistent with the system's ability to dispatch resources during peak
hours.
In addition, since the inception of the program Rocky Mountain Power has been educating
irrigators about efficient irrigation practices and the benefits of irrigating during off-peak
hours. Rocky Mountain Power estimates that because of education irrigators have shifted
between 5 and 7 percent of their loads between 2:00p and 6:00p to off peak. The estimation
of the reference load for this analysis is not taken into consideration in this analysis. If the
benefits from education were taken into consideration the load shifting from education would
have the effect of funher improving measured impact or realization rate.
The Cadmus Group, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 " 503.228.2992 r Fax [phone]
An Employee-Owned Company . www.cadmusgroup.com
Rocky Mountain Power
Exhibit No. 5 Page 493 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 4 af 22Jeff Burngarner
February 24, 2A11
Objectives
The objectives of this evaluation were:
o To estimate the irrigation load reductions from Rocky Mountain Power's irrigation direct
load control program in 2009 and 2010.
o To estimate ex-post realization rates, the ratio of the ex-post impacts to the nominal program
loads that can be shed.
Program Operations
RMP operates two irrigation load control programs in Idaho. The first is "schedule forward"
(Schedule 72) and involves direct control of irrigation loads on a scheduled basis. Enrollment in
this program has been decreasing annually with the implementation of the dispatch program
option. In July 2009, there were 4.1 MWs of nominal load in this program. The second is the
dispatch option (Schedule 72a). RMP calls "events" with 24 hours advance notice and uses
simplex technology to shed irrigation loads during event hours (a maximum of four hours per
day per customer during weekdays).' The event hours are typically between 2:00p to 6:00p. In
July of 2009, there were 254 MWs of nominal irrigation load in both programs. In July of 2010,
there were 282 MWs of nominal load.
Event History
In 2009, RMP called six events that each lasted four hours. The events occurred between 2:00p
and 6:00p. Table 1 shows the dates and hours of the events.
Table 1. Event Days and Hours in 2009
30-Jun 4 hours
771u1 4 hours
23-Jul 4 hours
3-Aug 4 hours
5-Aug 4 hours13-Aue 4 hours
Hours for all events occurred
during hours 2:00p to 6:00p.
In 2010, RMP called 11 events, excluding three one-hour events in early June and one four-hour
event for irrigators served by the Big Grassey substation and for grid operations purposes.3 In
additionto a larger number of events in 2010, there were also a larger number of hours when
2 Participants may opt out of a maximum of five events per season.
3 The regression models control for the grid operations events, but we do not report the estimated load reductions.
The Cadmus Croup, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 . 503.228.2992 . Fax [phone]
An Employee-Owned Company . www.cadmusgroup.corn
Jeff Bumgarner
February 24,2011
Rocky Mountain Power
Exhibit No. 5 Page 494 of 1 365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 5 of 22
RMP dispatched program resources. Resources were dispatched during not just 2:00p-6:00p but
also hours before and after this window because of transmission and distribution constraints.
Table 2 shows the dates and number of hours for the 2010 events.
Table 2. Event Days and Hours in 2010
29-Jun 8 hours*
8Jul 8 hours*
15-Jul 8 hours*15Jul 8 hours*
19-Jul 12 hours**
20Jul 12 hours**
26Jul 12 hours**
2-Aug 12 hours**
5-Aug 12 hours**
24-Aug 12 hours**
25-Aus 12 hours**
*Hours for all substations:
11:00a -7:00p.** For all substations except
Big Grassey, event hours
occurred 11:00a - 7:00p.
Beginning July 19, RMP also
dispatched Big Grassey
customer loads from 7:00a -
11:00a.
Between the first event on June 29,2010 and the fourth event on July 16,2010, RMP dispatched
program resources on event days in three blocks over eight hours: 1 1:00a -3:00p, 2:00p - 6:00p,
and 3:00p7:00p. Figure I illustrates the dispatch of program resources during these time
blocks.
Figure 1. Summer 2010 Irrigation Direct Load Control Dispatch Blocks
The Cadmus Group, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 . 503.228.2992 . Fax [phone]
An Employee-Owned Company . www.cadmusgroup.com
Roclry Mountain Power
Exhibit No. 5 Page 495 of 1 365
Case No. PAC-E-'l4-07
Wtness: Kathryn C. Hymas
Page 6 of ?2Jeff Eurngarner
February 24, 20tr 1
-iE-
rE-
Beginning with the fifth event on July 19 and ending with the final (l1ft) event on August 26,
RMP dispatched additional resources betweenT artand 11 am on the Big Grassey substation.a
Resources associated with the other substations continued to be dispatched in three blocks
between 1 1:00a and 7:00p.
Tables 3 and 4 show loads at the five substations that RMP expected it could shed during each
month of 2009 and 201 0 based on the historical demand of enrolled customers. This is known as
the 'nominal' load. The estimates of nominal load in Tables 3 and 4 do not take into account
customers that opted out of events.
Ln2009, the nominal load varied across months but not hours, as all available program resources
were dispatched during the 2:00p - 6:00p window. Nominal loads were highest during July
when irrigation demand was greatest.
Table 3. Program Nominal Resources (MlY) in 2009 for Five Substations
a In addition, there was an AMD dispatch block on Amps 3 days/week from 6:00p -12:00a. This involved a small
amount of load, approximately 1.75 MW per dispatch or 5.3MW in total. All AMD dispatches from all
substations accounted for -15 MW of participating load.
The Cadmus Croup. lnc.
720 SWWash!ngton Stneet, Suite 400, Portiand, OR 97205 a 503.228.2992 c Fax [phone]
An Ernployee-Owned Company " www.cadrnusgroup"corn
Program Nominal
lrrigation Load (MW)
served by substations
Source: Table 14, Schedule 72 and 72A ldaho lrrigation Load
Programs 2009 Credit Rider lnitiative Final Report and personal
communications with Bill Marek about percentage of program
nominal load served by Amps, Big Grassey, Bonneville, Jefferson,
and Rigby substations. Loads are not adjusted for opt-outs.
Nominal load is the load that RMP expected it could shed based
on program enrollment and transmission and distribution
constraints.
Jeff Bumgarner
February 24,2A11
Rocky Mountain Power
Exhibit No. 5 Page 496 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
PageT of 22
In 2010, the nominal loads on the five substations varied between months and event hour, as
program resources were dispatched in several four-hour blocks, as described above. The nominal
loads do not take into account the gradual ramping down and up of loads at the beginning and
end of the period or opt outs.
Table 4. Program Nominal Resources (MW) in 2010 for Five Substations
June 0.0 47.0 47.0 49.0 89.3 148.8 148.8 148.8 110.1 5.8 1.6
July lJuly
19 0.0 50.7 50.7 53.0 96.5 160.7 t60.7 160.7 118.9 5.2 1.8
July 20-
Julv 31 17.7 42.6 42.6 44.9 88.4 15L.7 15L.7 151.7 109.9 6.2 1.8
August 16.9 42.0 42.O 44.2 87.7 149.6 L49_6 149.6 108.3 6.2 7_7
Source: Schedule 72 and 72A ldaho lrrigation Load Programs 2010 Credit Rider lnitiative Final Report and
personal communications with Bill Marek. Loads are not adjusted for opt outs. Nominal load is the load that
RMP expected it could shed based on program enrollment and transmission and distribution constraints.
Data
RMP provided Cadmus with 60 second interval data for five substations (Amps, Big Grassey,
Bonneville, Jefferson, Rigby) that served irrigators in its Idaho service territory in 2009 and
2010. The substations accounted for approximately 77 percent of RMP's irrigation load
subscribed in the program in Idaho in 2010. RMP also provided Cadmus with data about the
days and hours when direct load control resources were dispatched.
Cadmus performed a number of quality checks on and adjustments to the interval data before
analyzing the load impacts. We first put the 60 second interval data on an hourly basis by
calculating average hourly loads for each substation. The hourly load data were then plotted and
examined for inegularities. While the minute interval data did exhibit some random spikes and
drops in load (normal perturbations in electrical Grid operations), these abnormalities were not
evident after the minute interval data were averaged over the hour.
Next, we obtained hourly and daily weather data for Rexburg and Idaho Falls weather stations
from the National Weather Service and merged it with the hourly load data. The weather
variables in the analysis include the daily evapotranspiration rate, temperature (hourly), and
rainfall (hourly).s
5 The evapotranspiration rate was a weighted average of crop-specific ETRs, with weights equal to the share of land
planted in the crops.
The Cadmus Group, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 r 503.?28.2992 r Fax [phone]
An Employee-Owned Company . www.cadmusgroup"com
Jeff Bumgarner
February 24, 2A11
Roclq Mountain Power
Exhibit No. 5 Page 497 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page B of 22
Last, Cadmus mapped information on the occurrence of load control event hours to the data. We
created separate indicator variables for each hour of each event, which were included in the
model.
lmpact Estimation Approach
The Cadmus approach to estimating the load reductions in each event was to estimate a reference
load (what demand would have been in each hour of an event if the event had not occurred) in
each hour during an event window. The difference between the actual load and the reference
load in an event hour is the estimate of the program's impact during that event hour.
Figure 2 illustrates the approach. It shows the hourly loads for the Bonneville substation on July
23, 2009, when RMP called the third event of the summer. The event window was 2:00p to
6:00p. The red (solid) line is the observed load. The blue (dashed) line is the reference load that
was generated with a regression model. The impact of the event in each hour is the difference
between the metered load (red line) and the reference load (blue line). The figure depicts an
estimated average hourly impact of approximately 38 MW.
The reference load can be estimated in several ways. One is a day matching approach. This
involves estimating the (unconditional) average of the loads in the same hour in the two
weekdays immediately preceding and following the event. If irrigation demand conditions,
which are a function of weather, evapotranspiration, crop maturity, and other factors, on the
reference days are similar to those on the event day, the reference load will likely represent well
what demand would have been, and the difference between observed and reference loads will be
an accurate estimate of the true load reduction. However, if any of the demand conditions
change, the load reduction estimates will be biased.
Figure 2. Illustration of Event Impact Estimation Approach
0 'i'--r-'r-i-'r--:..-'r-'r--:'-'r-----t'-r-'T--:--'r-'r--.--'r--r--r..-j--r-'r-.-.i
0 2 4 6 I 10121416182022
llour
The Cadmus Croup, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 " 503.228.2992 + Fax [phone]
,4n Employee-Owned Cornpany . www.cadmusgroup.com
Jeff Bumgarner
February 24,2A11
Roclry Mountain Power
Exhibit No. 5 Page 498 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 9 of 22
The second approach is multivariate regression in which loads are modeled as a function of
weather, time, and calendar variables. This method accounts for differences in demand
conditions between event and non-event days and will generate a more accurate reference load.
Cadmus determined that because of trends in irrigation demand over the growing season that the
day matching approach would not be appropriate. Reference loads were estimated using an
hourly demand regression models.
Conditional Demand lmpact Estimation
Using regression analysis, Cadmus also modeled hourly demand as a function of weather (evapo-
transpiration, temperature, and rainfall), calendar and time effects (week of month, day of the
week, and hour), and load in the same hour in the previous day.6 The models also included
separate indicator variables for each hour of each event and for each of the six hours following
and preceding each event. The coefficients on the event hour variables represent the differences
between the observed loads and the reference loads in the event hours. The Appendix describes
the model specification in greater detail.
Cadmus estimated separate demand models for each of the substations and event months (June,
July, and August). Thus, there were a total of 15 substation models (5 stations x 3 months). We
estimated separate substation month models for two reasons. First, each substation has a
somewhat different load shape over the suflrmer, reflecting differences between stations in
cropping practices and irrigation and non-irrigation demand.T Second, each substation's load
shape varies significantly over the summer, reflecting changes in crop maturity, evapo-
transpiration, soil-type temperature, wind, relative humidity, solar radiation, and rainfall over the
growing season.
Model Estimation and Diagnostics
Cadmus estimated the models by Generalized Least Squares (GLS) under the assumption of
auto-correlated errors, that is, load in each hour is assumed to be correlated with the load during
a preceding hour. The error term was modeled as an autoregressive process with lag one.
We performed a number of tests to evaluate the predictive ability of the substation regression
models. These tests included inspection of the signs and statistical significance of the models'
coefficients, estimation of overall explanatory power of each model, represented bV RL' statistic,
6 Loads were modeled as a function of the average temperature in the preceding 24 hours, total rainfall in the
preceding 24 hours, and average daily evapo-transpiration over the preceding three days. The week of month
variables capture changes in irrigation demand related to changes in cropping activities. The days of the week
and hour of the day variables capture inigation demand that varies by day and hour.
7 The Rigby substation is different from the other stations in that it has significant non-irrigation loads.
The Cadmus Croup, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 r 503.228.2992 r Fax [phone]
An Employee-Owned Company . www.cadmusgroup.com
Roclq Mountain Power
Exhibit No. 5 Page 499 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pagel0of22.Jeff Eumgarner
February 24, 2A11
and tests of the predictive ability of the models in hours when events could have been called on
non-event days.8 We used the results of the tests in selecting the final model specifications.
The models predict accurately what loads would have been in hours when events were not but
could have been called. Table 6 reports the median absolute percentage error, the median of the
percentage difference between the observed load and the load predicted by the model (lkw-
model predicted kw)l/kw, during non-event hours on July weekdays between 2 and 6 pm.
Table 6. Median Absolute Percentage Error for July 2009
2:00 PM
3:00 PM
4:00 PM
5:00 PM
0.74o/o L.45o/o !.35o/o 1.54% 0.72o/o
0.86% L.44% 7.28% 7.480/o 0.670/o
L.62o/o 1.29% O.87% 1.28% 0.64%
0.95% t.o4% 7.09% !.850/o 0.67%
Note: Absolute percent error is = | predicted MW - actual MW l/ actual
MW.
For example, in 50 percent of the 3 pm non-event hours at the Bonneville station, the regression
model predicts a load that is within 1.28 percent of the actual load. The median absolute
prediction error ranges from less than 0.7 percent to just below two percent. Fifty percent
(N:10) of the substation-hour median percentage errors are less 1.2 percent.
Estimated Load Reductions in 2009
Table 7 reports an estimate of the total load reduction for the Amps, Big Grassey, Bonneville,
Jefferson, and Rigby substations and all Idaho irrigation in each event hour during surnmer
2009.e The estimate for Idaho was obtained by dividing the substation estimate by the substation
percentage of the Idaho irrigation load (77 percent). The Table also reports the realization rate
for each event hour (2:00p-6:00p time window), which is the ratio of the estimated total load
reduction in a given hour to the nominal load adjusted for inigation loads that opted out of the
event.l0 The realization rate is a function of the estimated load reduction (the numerator) and
expectations about loads that can be shed (the denominator). It may be less than or equal to 100
percent depending on technical performance of the control equipment (i.e., signals and
transmitted and received and pumps are shut off) and whether inigation demand during the
season was less than or greater than expected.
8 [n general, the coefficients of the models have the expected signs and are statistically significant. Loads were
increasing in the evapo-transpiration rate and temperature and decreasing in rainfall. Loads were generally
highest during the aftemoon and early evening hours. Also, based on their R2 statistics, the models explain a
large percentage ofthe variation in irrigation loads.
e The Appendix contains estimates of the reduction in load at the substation level in each event hour.
t0 Cadmus adjusted the nominal load for an event by subtracting the amount of load that opted out the event.
The Cadmus Group, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 a 503.228.2992 * Fax [phone]
An trnployee-Owned Company . www.cadrnusgroup.conn
Roclry Mountain Power
Exhibit No. 5 Page 500 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pagel1of22Jeff Bumgarner
February 24,2A11
Table 7. Estimated Load Reductions and Realization Rates in 2009
30-Jun Event 1 Hour 1 -41.8 -54.3 24.8%
Hour 2 -71.8 -93.2 42.60/o
Hour 3 -70.7 -91.8 42.O%
Hour 4 -66.4 -86.3 39.5o/o
17-Jul Event 2 Hour 1 -111.1 -L44.3 60.8o/o
Hour 2 -t57.8 -204.9 86.3%
Hour 3 -158.0 -20s.2 85.4o/o
Hour 4 -151.6 -196.9 82.9o/o
23Jul Event 3 Hour 1 -1o2.4 -133.0 55.7%
Hour 2 -137.7 -778.9 74.9%
Hour 3 -138.5 -180.0 75.3o/o
Hour 4 -135.5 -177.2 74.2o/o
3-Aus Event 4 Hour 1 -33.6 -43.6 78.5o/o
Hour 2 -50.0 -5s.0 27.5o/o
Hour 3 -48.1 -62.s 26.50/o
Hour 4 -48.0 -62.4 26.5o/o
5-Aue Event 5 Hour 1 -30.8 -40.0 L7.0o/o
Hour 2 -50.0 -65.0 27.6%
Hour 3 -49.0 -63.7 27.1o/o
Hour 4 -47.4 -61.5 26.2%
13-Aue Event 6 Hour 1 -35.6 -47.6 79.9o/o
Hour 2 -45.9 -s9.6 24.9o/o
Hour 3 -45.4 -58.9 24.60/o
Hour 4 -45.6 -s9.2 24.7%
Notes: Estimates of load reductions for 5 substations based on regression
model. Estimated load reductions for all ldaho lrrigation estimated as 5
substation load reduction divided by 0.77. Realization rate is the ratio of
the estimated load reduction to the opt-out adiusted nominal load.
The Program reduced irrigation loads in each event hour. The estimated load reductions ranged
from -158 MW to -31 MW and were different from zero at the 5 percent significance level.ll
The estimated reductions in Idaho irrigation loads ranged from 40 MW to 205 MW. The
" The Appendix contains estimated confidence intervals for the estimated load reductions in all event hours.
The Cadmus Group, lnc.
720 SW Washington Street, Suite 400, Portland, OR 97205 . 503.228.2992 . Fax [phone]
An Employee-Owned Company . ww\,v.cadmusgroup.com
Jeff Bumgarner
February 24, 2011
Roclry Mountain Power
Exhibit No. 5 Page 501 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pagel2af22
estimates also exhibit the expected patterns. First, during each event, the estimated load
reduction in the first hour was the smallest, consistent with the staggering of the event initiation
for grid reliability. (During hours two, three, and four, there is very little difference in the
estimated load reductions.) Second, the load reductions over the summer reflected the seasonal
pattern of irrigation demand. The load reductions were largest in July, when loads and irrigation
demand were at their peak. The maximum load reductions on the five substations of 158 MW
and in Idaho irrigation loads of 205 MW were achieved on July 17 (event 2) during event hour 3.
The estimated load reductions were significantly smaller in June and August, when irrigation
demand was much lower.
The realization rates, which show how much load was shed relative to expectation in any given
hour, ranged from a low of 17 percent during hour 1 of event 5 to a high of 86 percent during
hour 3 of Event 2. As expected, realization rates were significantly higher in July than in June or
August because of irrigation practices and crop maturity. Nominal loads were not adjusted
downward to reflect the lower irrigation demand in June and August. Hence, the low realization
rates were due not to Program performance but rather to below average irrigation demand and
the fact that nominal rates during June and August are lower. RMP may want to consider
adjusting its estimates of nominal loads to reflect changes in irrigation demand.
Estimated Load Reductions in 2010
During events in 2010, program resources were dispatched in three or four blocks over 8 or 12
hours. Loads were dispatched outside of the 2:00p to 6:00p window because of potential adverse
impacts on the transmission and distribution system. Table 8 reports an estimate of the
maximum hourly load reduction in each block of each event during summer 2OlO.12 Cadmus
reports the maximum in each block of hours instead of in each hour because of the large number
of event hours. The load reductions cover the Amps, Big Grassey, Bonneville, Jefferson, and
Rigby substations. It should be noted that loads that were shed between 7:00a and 10:00a or
11:00a and 1:00p resumed at the end of the event, leaving less opportunity for load reductions in
subsequent hours (note: loads that were were controlled between 7:00a and 10:00a and 11:00a
and 1:00p resumed at the end of the event, leaving less opportunity for load reductions in
subsequent hours).
The load impacts were greatest during 2:00p - 6:00p, when most Schedule 72a resources were
dispatched (see Table 4). The maximum hourly load reduction occurred on July 8, when
irrigation loads on the five substations were reduced by approximately 120 MW and the Idaho
irrigation load was reduced by 156 MW. Load impacts were smaller in June and August, when
irrigation demand was lower.
'' The Appendix contains estimates of the load reduction in each event hour.
The Cadmus Croup, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 " 503.228.2992 + Fax [phone]
An Employee-Owned Company . www,cadmusgroup.com
Rocky Mountain Power
Exhibit No. 5 Page 502 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page '13 af 22Jeff Bumgarner
February 24,2A11
Table 8. Estimated Load Reductions in 2010
29Jun Event 1 5 Substations N/A -34.8 -87.0 -61.7
:::ifi Ili.,:lS::Ir:,rip€tiEr+|:**ffi:l..49j1t?,:=SitC;gi.i..l ::5ii:::l::l:lEfit:
8-Jul Event 2 5 Substations N/A -49.6 -119.8 -85.7
#l*i::tSi:l aatib ::i,]:],.*t/*:i6*i4 :,;I9)iu.:;t$1!3
15-Jul Event 3 5 Substations N/A -44.2 -707.0 -86.6
Alliiil iFi li'ris6ti$H r:rrr:r:.r:r:irr.ri:.*ilsgii0r.iirii:riiii ,,,:ii,,i,,,i*t.l[tiS
16-Jul Event 4 5 Substations -39.9 0.0 -100.5 -77.7
fi tl'..I.Dj.ilff iEetio,ni.i.i .ti,*l E Sii0rrir iits0is +fC$rS
19-Jul Event 5 5 Substations -40.2 -17.9 -103.1 -83.3
Atl..itDrlr iEatisn f;52,:2:,:,:,:,i*ilil;},rr:rj:.+it$gil9 +10Eri2
20Jul Event 6 5 Substations -48.3 -15.1 105.4 -82.2
i*ilils:] s5tiUrh i6tsril Ntu9ll +tA6ii9
26-Jul Event 7 5 Substations -36.1 -12.2 -89.7 -75.8
r.Atl.ID, r,rigaE0H :::;:::::l.45r9,tttt,,,,.rg$i9...:rri:irr!+',f, lt6rSi:::;i ,*,98iAi:i
2-Aus Event 8 5 Substations -2.4 -3.1 -6.7 1.3
., r xffigari6B -,5.L :xii**i0 L-t. i
5-Aue Event 9 5 Substations -8.7 -10.0 -42.2 -31.5
lIli*Dr:ilr,*isatieh ir1.3 ';x2.9 i:::!"'- -,i;;:i#i*;fl':;i
24-Aue Event 10 5 Substations -25.5 -6.0 -41.3 -31.8
*lliiiiifi iiill*iFatioa i,,ii"3gi:2,,,,,,,,x8 irr::+$3l, iir:irl i:,::;-;l[:1r3:i:::ii
26-Aue Event 11 5 Substations -20.4 -2.6 -44.3 -30.6
#liiiiilEiiiirri*Etiff$,i:nil615,;i,;$,i.ti[:r:'..: t::::::i*9i
Notes: Estimates of load reductions for 5 substations based on regression model. Estimated load
reductions for all ldaho lrrigation estimated as 5 substation load reduction divided by 0.77.
Realization rate is the ratio of the estimated load reduction to the opt-out adjusted nominal load.
The hourly MW impacts were smaller in 2010 than in 2009 because load control resources were
dispatched over a larger number of hours. The dispatching of resources in the moming and early
afternoon and early evening to address transmission and distribution issues meant that there was
less potential to reduce loads during peak hours. To put the 2010 load impacts in perspective,
Table 9 reports realization rates, the ratio of the estimated load impact to the nominal load in the
hour adjusted for opt outs.13 The nominal loads during peak hours were smaller in 2010 than in
2009 because programs resources were dispatched before and after the 2:00p - 6:00p period.
The realization rates account for the smaller amount of load that could have been shed between
2:00p and 6:00p.
13 The load opting out was subtracted from the nominal load for hours 2:00p - 6:00p for each event.
The Cadmus Croup, lnc.
720 SWWashirrgton Street, Suite 400, Portland, OR 97205 ' 503.?28.2992 + Fax [phone]
An [mployee-Owned Cornpany + ww\,v.cadmusgroup.com
Rocky Mountain Power
Exhibit No. 5 Page 503 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pagel4af22Jeff Bumgarner
February 24,2A11
Table 9. Estimated Realization Rates in 2010 (Based on Nominal Capacity)
29-Jun Event 1 N/A 77.Oo/o 60.3o/o s6.0%
8-Ju Event 2 N/A 93.7%77.4%72.1%
15-Ju Event 3 N/A 83.5%75.Oo/o 72.9o/o
15-Ju Event 4 N/A o.o%74.0%70.8%
19-Ju Event 5 234.9o/o 39.8%76.7o/o 75.8%
20-Ju Event 5 282.0%o 33.7%82.0o/o 74.8%
26-Ju Event 7 2tL.3o/o 27.2o/o 53.9o/o 69.Oo/o
2-Aug Event 8 74.7o/o 6.9o/o 4.50/o -1.2o/o
5-Aus Event 9 57.4%22.5%29.7o/o 29.to/o
24-Aue Event 10 L57.4o/o 73.5o/o 28.60/o 29.40/o
25-Aue Event 11 727.7%5.Oo/o 30.2%28.2%
Notes: Realization rate is the ratio of the estimated load reduction to the opt-
out adjusted nominal load. Opt out loads obtained from Schedule 72 &72A
ldaho lrrieation Load Control Prosrams: 2009 Credit Rider lnitiative Final Reoort.
During hours when events are traditionally called, the realization rates ranged between 29
percent on August 24 and 82 percent on July 20.14 (We ignore the August 2 event, as load
reductions were uniformly and abnormally low.ls; During peak irrigation demand between the
first and third weeks of July, the realization rate ranged between 77 and 82 percent of nominal
load. These impacts are slightly lower than but still close to those in 2009. The difference in
realization rates may reflect the fact that inigation demand in 2010 was relatively low because of
cooler weather throughout the summer.
Conclusions
Rocky Mountain Power asked Cadmus to evaluate the demand impacts of its Idaho irrigation
load control program. In 2010, the Program enrolled 1,975 customers and had approximately
283 MW of participating load. However, this participating load was more than RMP could
dispatch during peak hours because of transmission and distribution system constraints. This has
had the effect of reducing the Program's cost-effectiveness.
'o On some event days, the maximum hourly realization rate between 7:00a and l0:00a exceeded 100 percent. This
indicates that in these hours either the Program achieved significantly greater demand reductions than expected,
or the nominal loads are too low,
15 Irrigation demand is typically very low at the beginning of August when hay is harvested and water to field crops
is turned off to initiate the crop maturation process prior to harvest. Accordingly, potential demand reductions
are very small. However, the nominal load covers all of August and does not reflect haying and crop
maturation. The small, negative demand reduction in the 6:00 p hour is statistically indistinguishable from zero.
The Cadmus Croup, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 ' 503.228.2992 i Fax [phone]
An Employee-Owned Company o ww\,v.cadmusgroup.com
Jeff Bumgarner
February 24, 2011
Rocky Mountain Power
Exhibit No. 5 Page 504 of 1365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
Pagel5of22
Cadmus estimated the hourly load reductions from the Program in 2009 and 2010 using
regression analysis of SCADA data from five substations in Idaho. In addition, Cadmus
examined the coincidence of the progftlm impacts with the PacifiCorp system peak demands.
There are several noteworthy aspects of the methodology:
o The impact analysis was based on SCADA dataatthe substation level. Since the majority
of the loads being served by these substations consist of irrigation, the amount of "noise"
in the data resulting from the variability of non-irrigation loads is expected to be minimal.
The estimation methodology did not consider Rocky Mountain Power's education of
irrigators about efficient irrigation practices. If the benefits from education were taken
into consideration the load shifting from education would have the effect of improving
measured impact or realization rate.
The hourly analysis of loads did not account for staggering in the dispatching of loads at
the beginning and end of events for grid reliability purposes. As a result, the estimated
load impacts in the first and last hours are an estimate of the average load reduction over
the hour and may not represent the true reduction at the beginning (likely to be smaller
than estimated) or end of the hour (likely to be larger).
In the calculation of realization rates, the analysis adjusts for the required scheduling of
22 percent of the available participating loads outside of the 2:00p-6:00p time period.
This scheduling restriction was implemented in 2010 to accommodate the Grid control
voltage limitations previously noted. While this did not impact hourly realization rates, it
did have a significant effect on the difference between the nominal loads and the
aggregated reductions achieved.
The analysis of substation loads showed the following:
o In 2009, the maximum hourly load reduction on the five substations was 158 MW or 205
MW for all Idaho irrigation program loads. This represented 86 percent of the nominal
program resources dispatched in that hour. The realization rates, which show how much
load was shed relative to expectation, ranged from a low of 17 percent on August 5 to the
July 17 high of 86 percent. In 2010, the maximum hourly load reduction was 120 MW
or 156 MW for all Idaho irrigation program loads. This occurred on July 8 and
represented 77 percent of the opt-out-adjusted nominal load dispatched in the hour. On
The Cadmus Croup, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 " 503.228.2992 r Fax [phone]
An Employee-Owned Company . www.cadmusgroup.com
o
Jeff Bumgarner
February 24,2A11
Rocky Mountarn Power
Exhibit No. 5 Page 505 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pagel6of22
Jlly 20, a load reduction of 120 MW resulted in the maximum realization rate of 82
percent.
o Realization rates were calculated based on expected loads, or in the case of the Rocky
Mountain Program, loads that could safely be dispatched without adversely impacting
line voltages. This is an important distinction worth noting. Had the calculation of
realization rates been based on total participating loads, this would have resulted in lower
realization rates. As program cost-effectiveness is calculated on actual load reductions
relative to a program's costs (rather than a realizationrate),realizations rates should not
be considered the definitive measurement of a program's effectiveness and value.
o The load reductions and realization rates in any year may not be representative of typical
load impacts the program might achieve because of annual variations in irrigation
demand.
o PacifiCorp system peak coincides with hours when events are traditionally called (hours
2:00p-5:00p).
Recommendations
While the Program has achieved significant load reductions, the cost-effective has been
adversely impacted by the level of participation on a megawatt basis. As noted above, in 2009
and 2010, the Program enrolled more load on some substations than it could dispatch during
peak hours because of transmission and distribution constraints. RMP could reduce enrollments
to a level consistent with the system's ability to dispatch loads. Or if technically feasible, RMP
could increase the Program's cost-effectiveness by upgrading the transmission and distribution
system to alleviate constraints on when load can be dispatched.
The Cadmus Croup, lnc.
720 5W Washlngton Street, Suite 400, Portland, OR 97205 r 503.228.2992 r Fax [phone]
An tmployee-Owned Company . www.cadmusgroup.corn
Rocky Mountain Power
Exhibit No. 5 Page 506 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 'tr 7 af 22Jeff Eumgarner
February 24,2011
Appendix
Substation Hourly Load Model
Let j:1,2..., J index the events andlrl,2..., H index hours of each event. Also, let MWi be the
electricity load of substation i at time (hour) t. Then (suppressing the index i) substation i's MW
demand at time t (corresponding to a week of the month, day, and hour) can be written as:
MWs =
as * a1 EvapTR7Zhour, * a2 tempZLhour, * asratnf allZ4hour, *
Xir=, r*weekofmonth*, *Z6a=t6adayof weeka: *Lzt3=ryphourof dayw + eMWt-24 +
Z!1=rLfl=rpl;eventltourint*Llj=rLfr=teinpreeventltourint*Z!,=rZfr=ralnposteventhourint*€t
The right hand side variables in the model are defined as follows:
o EvapTRT2hou4is the average evapo-transpiration rate over the previous 72 hourst at time t.
o Temp24hourtis the average temperature over the previous 24 hours at time t.
o Rainfall24hourl is the total rainfall over the previous 24 hours.
o Weekofmonth* equals one if time t is in week w, w: 1 to 3, and equals zero, otherwise.
Dayau d:1 to 6, and hourof dayk, k:1 to23, are defined similarly.
o Eventhoill.1m equals one if time t is in hour h, h: 1 to H, of event j, j: 1 to J, and equals zero,
otherwi se. P r e ev e ntho ur int and P o s t ev e ntho ur jtu ar e defi ned similarly.
o rt isthe error term of the model representing random influences on the demand of customer i
at time t.
The parameters to be estimated and their interpretations are as follows:
o phj is the impact of hour h of event j on demand. It is the difference between the estimate of
what demand would have been if an event had not been called (reference load) and the actual
demand in the hour.
o (Dhj is the impact of hour h after event j on demand. The coefficients capture any shifting of
irrigation loads in response to the load control events.
. 0r,: is the impact of hour h before event j on demand. The coefficients capture any shifting of
inigation loads because of the load control events.
. cro is substation load at the omitted hour (Sundays at the 12 am hour in the first month).
The Cadmus Croup, Inc.
720 SWWashington Street, Suite 400, Portland, OR 97205 r 503.228.2992 + Fax [phone]
,4n Employee-Owned Company . www.cadmusgroup.com
Jeff Bumgarner
February 24,2A11
Rocky Mountain Porer
Exhibit No. 5 Page 507 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
PagelBaf22
or is the impact of average evapo-transpiration rate in the previous 72 hours on demand. o2
shows the impact of temperature in the previous 24 hours on demand. cr,3 lneosures the
impact of rainfall in the previous 24 hours on demand.
fi*, w:l to 3, is the impact of week of month w on demand.
. 6d, d=l to 6, is the impact of day of the week don demand.
. Tk, k:l to 23,is the impact of hour fr on demand.
The Cadmus Group, lnc.
720 SWWashington Street, Suite 400, Portland, OR 97205 r 503.228.2992 r Fax [phone]
An Employee-Owned Company . www.cadmusgroup.com
Jeff Eumgarner
February 24, 2A11
Roclq Mountain Power
Exhibit No. 5 Page 508 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page19of22
Appendix Table A.1. 2010 Estimated Hourly Load Reductions with 95 Percent Confidence
Intervals
30-Jun Event 1 Hour 1 -41.8 -55 -28 -54.3 168.4 24.8o/"
Hour 2 -71.8 -85 -57 -93.2 158.4 42.6%
Hour 3 -70.7 -86 -56 -91.8 764.4 42.O%
Hour 4 -66.4 -82 -50 -86.3 1,68.4 39.5/o
t7)ul Event 2 Hour 1 -171,.1 -125 -97 -t44.3 182.8 60.8o/o
Hour 2 -157.8 -172 -L44 -204.9 182.8 86.3%
Hour 3 -158.0 -\72 -144 -205.2 182.8 86.4o/o
Hour 4 -151.6 -166 -138 -196.9 182.8 82.90/o
23-Jul Event 3 Hour 1 -702.4 -115 -89 -133.0 184.0 55.7%
Hour 2 -737.7 -]^52 -124 -178.9 184.0 74.9%
Hour 3 -138.6 -153 -124 -180.0 184.0 75.3%
Hour 4 -136.5 -150 -722 -177.2 184.0 74.2o/o
3-Aus Event 4 Hour 1 -33.5 -42 -25 -43.6 181.5 L85%
Hour 2 -s0.0 -58 -42 -6s.0 181.5 27.60/o
Hour 3 -48.1 -57 -40 -62.5 181.5 26.5%
Hour 4 -48.0 -56 -40 -62.4 181.5 26.s%
5-Aue Event 5 Hour 1 -30.8 -39 -22 -40.0 181.0 t7.o%
Hour 2 -50.0 -59 -47 -6s.0 r.81.0 27.60/o
Hour 3 -49.0 -58 -40 -63.7 181.0 27.7%
Hour 4 -47.4 -55 -39 -61.6 181.0 26.2%
13-Aue Event 6 Hour L -36.6 -45 -28 -47.6 784.2 19.9%
Hour 2 -45.9 -54 -37 -59.6 184.2 24.9%
Hour 3 -45.4 -54 -37 -s8.9 184.2 24.6%
Hour 4 -45.6 -54 -37 -59.2 784.2 24.7%
Notes: Estimates of load reductions for 5 substations based on regression model. Estimated load reductions for all
ldaho lrrigation estimated as 5 substation load reduction divided by 0.77. Realization rate is the ratio of the
estimated load reduction to the opt-out adiusted nominal load.
The Cadmus Croup, lnc.
720 SW Washington Street, Suite 400, Portland, OR 97205 . 503.228.2992 t
An Employee-Owned Company . www.cadmusgroup.com
Fax [phone]
Jeff Bumgarner
February 24, ZAI 1
Rocky Mountain Power
Exhibit No. 5 Page 509 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Page 20 of 22
Appendix Table A.2.2010 Estimated Hourly Load Reductions with 95 Percent Confidence
Intervals
29-Jun Event 1 11:00 AM 11AM-1PM -32.7 -42.2 -23.7 -42.4 47.O -69.6%47.O
29-Jun Event 1 12:00 PM 11AM-1PM -34.8 -44.O -25.6 -45.2 47.O -74.t%47.0
29-Ju n Event 1 1:00 PM 11AM-1PM -28.3 -37.L -19.5 -36.8 49.0 -57.8%49.0
29-Jun Event 1 2:00 PM 2PM.5PM -49.2 -58.9 -39.4 -53.8 84.8 -58.0%89.3
29-Jun Event 1 3:00 PM 2PM.5PM -87.O -96.8 -77.2 113.0 L44.3 -60.3%148.8
29-Jun Event 1 4:00 PM 2PM-5PM -82.7 -92.5 -73.0 -107.5 744.3 -57.4%148.8
29-Jun Event 1 5:00 PM 2PM.5PM -75.8 -8s.3 -66.3 -98.5 744.3 -52.6%148.8
29-Jun Event 1 5:00 PM 6PM -61.7 -70.9 -52.5 -80.1 110.1 -56.0%110.1
8-Jul Event 2 11:00 AM 11AM.1PM -48.7 -67.5 -29.9 -63.2 50.7 -96.0/o so.7
8Jul Event 2 12:00 PM 11AM.1PM -49.6 -67.9 -31.3 -54.4 50.7 -97.8%50.7
8-Jul Event 2 1:00 PM 11AM.1PM -39.0 -55.6 -2L.4 -50.6 53.0 -73.6%53.0
8-Jul Event 2 2:00 PM 2PM-5PM -77.2 -90.3 -52.1 -92.4 90.5 -78.6%96.5
SJul Event 2 3:00 PM 2 PM.5 PM -119.8 138.9 -100.6 -155.S 1S4.8 -77.4%160.7
8Jul Event 2 4:00 PM 2 PM.5 PM -114.5 -133.5 -95.5 L48.7 154.8 -74.0%160.7
8-Jul Event 2 5:00 PM 2PM.5PM 104.9 723.5 -86.2 L36.2 154.8 -67.8%L60.7
SJul Event 2 6:00 PM 6PM -45.7 -103.7 -67.6 111.3 118.9 -72.t%118.9
15-Jul Event 3 11:00 AM 11AM-1PM -47.3 -60.1 -22.5 -53.6 50.7 -8t.4%o 50.7
15Jul Event 3 12:00 PM 11AM.1PM -44.2 -62.6 -25.9 -57.4 50.7 -87.2%so.7
15Jul Event 3 1:00 PM 11AM-1PM -43.1 -51.0 -25.2 -55.0 53.0 -87.3%53.0
15-Jul Event 3 2:00 PM 2PM-5PM -65.6 -84.7 -45.5 -85.2 75.5 -85.6%96.5
15-Jul Event 3 3:00 PM 2PM-5PM -707.O -126.2 -87.8 139.0 140.9 -76.O%L60.7
15Jul Event 3 4:00 PM 2PM-5PM -704.4 123.5 -85.4 135.6 140.9 '74.lYo L60.7
15-lul Event 3 5:00 PM 2PM-5PM -100.1 118.8 -87.4 130.0 140.9 -77.0%L60.7
15-Jul Event 3 6:00 PM 6PM -86.6 -104.7 -68.6 112.5 118.9 -72.9%118.9
16-Jul Event 4 7:00 AM 7 AM. 10 AM -37.5 -56.4 18.6 -48.7 77.7 -219.1%77.7
16-Jul Event 4 8:00 AM 7 AM- 10 AM -39.9 -58.3 -27.5 -51.8 77.7 -233.2%17.1
16Jul Event 4 9:00 AM 7 AM- 10 AM -35.2 -52.8 -r7.5 -45.7 77.7 -205.5%17.7
16Jul Event 4 10:00 AM 7 AM. 10 AM -o.2 -8.8 8.3 -0.3 77.7 7.4%77.7
16-Jul Event 4 11:00 AM 11AM-1PM 0.0 -4.4 8.4 0.0 42.5 o.o%42.6
16-Jul Event 4 12:00 PM 11AM-1PM 0.1 -8.0 8.2 o.2 42.6 o.3%42.6
16-Jul Event 4 1:00 PM 11AM.1PM 0.4 -7.4 8.2 0.5 44.9 os%44.9
16Jul Event 4 2:00 PM 2PM-5PM -60.6 -79.8 -41.5 -78.7 72.6 -43.s%88.4
15-Jul Event 4 3:00 PM 2PM-5PM -100.5 119.8 -8L.2 130.5 135.9 -74.O%L57.7
16-Jul Event 4 4:00 PM 2PM-5PM -98.6 1L7.7 -79.4 L28.0 135.9 -72.5Yo L51.7
16-Jul Event 4 5:00 PM 2PM-5PM '93.4 1L2.2 -74.6 t27.3 135.9 -68.7Yo L57.7
16-lul Event 4 5:00 PM 5PM -77.7 -95.9 -59.5 -101.0 109.9 -70.4%109.9
19Jul Event 5 7:00 AM 7 AM. 10 AM -37.4 -55.2 -18.5 -48.5 L7.L -zta.s%77.L
19-Jul Event 5 8:00 AM 7 AM. 10 AM -40.2 -58.5 -71.4 -52.2 t7.l -234.9%77.7
19-Jul Event 5 9:OO AM 7 AM. 10 AM -39.8 -57.S -22.2 -57.7 L7.7 -232.8%L7.7
19-Jul Event 5 10:00 AM 7 AM. 10 AM -18.1 -26.7 -9.5 -23.5 t7.t -105.8%77.7
19-Jul Event 5 11:00 AM 11AM.1PM -t7.9 -26.3 -9.4 23.2 42.6 -47.9%42.6
19-Jul Event S 12:00 PM 11AM.1PM -L6.7 -24.9 -8.6 -21.7 42.6 -39.3%42.6
19-Jul Event 5 1:00 PM 11AM-1PM -t4.6 -22.4 -6.7 18.9 44.9 -32.4%44.9
19-Jul Event 5 2:00 PM 2PM-5PM -51.3 -80.4 -42.2 -79.6 7r.7 -86.2%88.4
19Jul Event 5 3:00 PM 2 PM.5 PM -103.1 122.3 -83.9 133.9 134.5 -76.7%L57.7
19-Jul Event 5 4:00 PM 2PM-5PM -70r.2 120.3 -82.2 131.5 134.5 -75.3%L57.7
19-Jul Event 5 5:00 PM 2PM-5PM -98.5 LL7.3 -80.0 r28.7 734.5 -73.4%t57.7
19Jul Event 5 6:00 PM 6PM -83.3 -tol.4 -65.3 -108.2 109.9 -75.8%109.9
The Cadmus Croup, lnc.
72A SW Washington Street, Suite 400, Portland, OR 97205 ' 503.228.2992 .
An Employee-Owned Company . ww\,v.cadmusgroup.com
Fax [phone]
Rocky Mountain Power
Exhibit No. 5 Page 510 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 21 af 22Jeff Bumgarner
February 24,2A11
20-Jul Event 6 7:00 AM 7 AM. 10 AM -46.4 -65.3 -27.5 -60.2 t7.L -27!.LYo 77.7
20-Jul Event 6 8:00 AM 7 AM. 10 AM -48.3 -55.5 -29.9 -62.7 t7.t -242.O%77.7
2GJul Event 6 9:00 AM 7 AM. 10 AM -44.4 -62.1 -26.8 -s7.7 L7.L '259.7/o 77.7
20-Jul Event 6 10:00 AM 7 AM- 10 AM -L2.7 -2t.4 -4.7 -16.5 77.L -745%17.7
2O-Jul Event 6 11:00 AM 11 AM. 1 PM -13.6 -22.r -s.2 42.6 -32.O%42.6
20-Jul Event 6 12:00 PM 11AM.1PM -14.8 -23.0 -6.6 -19.2 42.6 -34.6%42.6
20-Jul Event 6 1:00 PM 11AM.1PM -15.1 -23.O -7.3 -19.7 44.9 -33.7%44.9
2O-Jul Event 5 2:00 PM 2PM.5PM -7L.5 -90.7 -52.3 -92.9 65.2 -709.6%88.4
20Jul Event 6 3:00 PM 2PM.5PM -105.4 -724.8 -86.1 -136.9 128.6 -82.OYo t51.7
20-Jul Event 6 4:00 PM 2PM.5PM -102.0 -127.2 -82.8 -132.5 t28.6 '79.3Yo L51.7
20-Jul Event 5 5:00 PM 2PM.5PM -98.0 116.9 -79.1 -727.3 724.6 -76.2%LST.7
20-Jul Event 6 6:00 PM 6PM -82.2 -100.5 -63.9 -706.7 109.9 -74.8%109.9
26-Ju Event 7 7:00 AM 7 AM- 10 AM -32.9 -5L.7 -14.0 -42.7 L7.\-192.1%L7.7
264u Event 7 8:00 AM 7 AM. 10 AM -36.1 -54.5 -t7.8 -46.9 77.7 -2tr.3%t7.7
26-Ju Event 7 9:00 AM 7 AM- 10 AM -35.0 -52.6 -L7.3 -45.4 L7.7 -204.3%L7.7
26-Ju Event 7 10:00 AM 7 AM- 10 AM -10.4 -18.9 -1.8 -13.5 17.7 -60.7Yo L7.7
26-Ju Event 7 11:00 AM 11AM-1PM 11.0 -19.3 -2.6 14.2 42.6 -25.7%42.6
26.Ju Event 7 12:00 PM 11AM.1PM -11.1 -19.3 -3.0 -L4.4 42.6 -26.r%42.6
26)u Event 7 1:00 PM 11AM.1PM -72.2 -20.0 -4.4 -15.9 44.9 27.2Yo 44.9
25)ul Event 7 2:00 PM 2PM-5PM -54.7 -73.8 -35.6 -71.0 76.9 -7L.L%88.4
26-Jul Event 7 3:00 PM 2PM-5PM -89.7 -108.9 -70.5 115.5 140.3 -63.9%LSL.7
26-Jul Event 7 4:00 PM 2PM-5PM -88.8 -LO7.9 -69.7 115.3 140.3 -63.3%LsL.7
25-Jul Event 7 5:00 PM 2PM-5PM -8S.3 -104.1 -66.s 110.8 140.3 -60.4%tsl.7
26-Jul Event 7 6:00 PM 5PM -75.4 -94.1 -57.5 -98.4 109.9 -69.O%109.9
25Jul Event 8 7:OO AM 7 AM. 10 AM 24.7 t4.1 34.0 31.3 17 _t L40.8%17.7
2-Aus Event 8 8:00 AM 7 AM. 10 AM 25.3 15.5 34.9 32.4 77.L L47.7%77.7
2.AUS Event 8 9:00 AM 7 AM- 10 AM 29.7 20.4 38.9 38.5 77.1 L73.5%L7.7
2-Aus Event 8 10:00 AM 7 AM. 10 AM -2.4 -6.6 7.7 -3.1 77.1 -74.7%77.7
2-Aue Event 8 11:00 AM 11AM-1PM -2.O -b.r 2.O -2.6 42.6 -4.8%42.6
2-AuE Event 8 12:00 PM 11AM-1PM -2.7 -5.0 1.8 2.7 42.6 -4.9%42.6
2-Aus Event 8 1:00 PM 11 AM. 1 PM -3.1 -6.8 0.5 -4.0 44_9 -6.9%44.9
2.AUP Event 8 2:00 PM 2PM-5PM 11.6 1.5 zL.7 15.1 83.6 t3.9%88.4
2-Aus Event 8 3:00 PM 2 PM.5 PM 3.8 -6.3 14.0 5.0 L46.9 2.6%Lst.7
2-Aue Event 8 4:00 PM 2 PM.5 PM -3.0 13.1 7.O -3.9 L46.9 -2.t%L5L.7
2-Aus Event 8 5:00 PM 2 PM.5 PM -6.7 -16.5 3.2 -8.6 146.9 -4.5%t5t.7
2-Aue Event 8 5:00 PM 6PM 1.3 -a.2 10.9 t.7 109.9 7.2Yo 109.9
5-Aue Event 9 7:00 AM 7 AM- 10 AM -8.0 -18.0 2.O -10.4 16.9 '47.3Yo 76.9
5-Aus Event 9 8:00 AM 7 AM. 10 AM -8.7 18.4 1.0 -1 1.3 16.9 -5L.4%16.9
5-Aug Event 9 9:00 AM 7 AM. 10 AM -6.9 -76_7 2.4 -9.0 16.9 -4L.Oo/.16.9
5-Aue Event 9 10:00 AM 7 AM. 10 AM -8.2 -72.4 -3.9 -10.6 16.9 -48.SYo 16.9
5-AuE Event 9 11:00 AM T1AM.1PM -8.3 -72.5 -4.2 -10.8 42.0 -79.9Yo 42.O
5-Aug Event 9 12:00 PM 11AM.1PM -8.5 -12.6 -4.7 tl.2 42.0 -20.s%42.O
5-Aus Event 9 1:00 PM 11AM.1PM -10.0 -13.7 -6.2 -t2.9 44.2 -22.5%44.2
5-Aus Event 9 2:00 PM 2PM-5PM -19.3 -29.5 -9.2 25.1 79.6 -24.3%87.7
5-Aug Event 9 3:00 PM 2PM-5PM -47.7 -51.9 -31.5 -54.2 r42.O -29.4%r49.6
5-Aus Event 9 4:00 PM 2PM-5PM -42.2 -52.4 -32.0 -54.8 t42.O -29.7%L49.6
5-Aue Event 9 5:00 PM 2PM-5PM -39.1 -49.1 -29.L -50.8 t42.O 27.5%t49.6
5-Aus Event 9 5:00 PM 6PM -3 1.5 -41.2 -2L.9 -41.0 108.3 -29.7%108.3
24-AUP,Event 10 7:00 AM 7 AM. 10 AM -25.5 35.5 -15.6 -33.2 16.9 L51.4%16.9
24-Aue Event 10 8:00 AM 7 AM- 10 AM -24.9 -34.6 15.2 -32.3 16.9 -t47.6%16.9
24-AuE Event 10 9:00 AM 7 AM. 10 AM -22.1 -31.4 -72.9 28.8 15.9 t37.3%L6.9
The Cadmus Group, lnc.
Street, Suite 400, Portland, OR 97205 r 503.228.2992 .
An Employee-Owned Company . ww\,v.cadmusgroup.com
720 SW Washington Fax [phone]
Rocky Mountain Power
Exhibit No.5 Page 511 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 22 of 22Jeff Bumgarner
February 24,2A11
24-Aus Event 10 10:00 AM 7 AM. 10 AM -5.0 -9.3 -o.1 -6.5 16.9 -29.6%16.9
24-Aus Event 10 11:00 AM 11AM.1PM -5.2 -9.3 -1.0 -6.7 42.O -12.3%42.O
24-Aug Event 10 12:00 PM 11AM.1PM -5.5 -9.5 -1.5 -7.7 42.O -L3.t%42.O
24-Avs.Event 10 1:00 PM 11AM.1PM -6.0 -9.8 -2.2 -7.8 44.2 -13.5%44.2
24-Aus Event 10 2:00 PM 2PM-5PM -32.0 -42.7 -27.9 -4L.6 81.9 '39.7o/o 87.1
24-Aus Event 10 3:00 PM 2PM-5PM -40.8 -50.9 -30.5 -52.9 744.3 -28.20/"149.6
24-Aue Event 10 4:00 PM 2PM-5PM -39.0 -49.0 -28.9 -50.6 t44.3 -27.O%749.6
24-Aua Event 10 5:00 PM 2PM-5PM -41.3 -51.1 -31.4 -53.6 t44.3 -28.6%149.6
24-Aue Event 10 6:00 PM 5PM 31.8 -41.3 -22.3 -41.3 108.3 -29.4o/o 108.3
26-Aue Event 11 7:00 AM 7 AM- 10 AM -20.4 -30.4 -10.5 -26.5 16.9 -72L.L%o 16.9
26-Aus Event 11 8:00 AM 7 AM. 10 AM -19.0 28.7 -9.3 -24.7 16.9 LLz,7%16.9
26-Aus Event 11 9:00 AM 7 AM- 10 AM -18.4 -27.6 -9.1 -23.8 16.9 -708.8%16.9
26-Auc Event 11 1O:00 AM 7 AM- 10 AM -2.5 -6.7 7.7 -3.2 15.9 -74.8/o 16.9
25-Aue Event 11 11:00 AM 11AM-1PM -2.0 -6.0 2.7 -2.6 42.O -4.7%42.O
26-Aup Event 11 12:00 PM 11 AM .1 PM -2.6 -6.5 7.2 -3.4 42.O -6.3%42.O
26-Aus Event 11 1:00 PM 11AM-1PM -2.5 -6.2 7.2 -3.3 44.2 -s.7%44.2
26-Aus Event 11 2:00 PM 2PM.5PM -31.9 -42.O -21.8 -41.5 84.0 -38.O%87.7
26-Aus Event 11 3:00 PM 2PM.5PM -44.3 -54.4 -34.7 -57.5 746.4 -30.2%L49.6
25-Aus Event 11 4:00 PM 2PM-5PM -40.5 -50.6 -30.4 -52.6 L46.4 27.lYo t49.6
26-Aue Event 11 5:OO PM 2PM-5PM -37.7 -47.O -27.1 -48.1 746.4 -25.3%t49.6
26-Aue Event 11 6:00 PM 6PM -30.6 -40.2 -20.9 -39.7 108.3 -28.2%108.3
The Cadmus Croup, lnc.
720 SW Washington Street, Suite 400. Portland, OR 97205 + 503.228.2992 .
An Employee-Owned Company i www.caclmusgroup"com
Fax [phone]
Rocky Mountain Pcn,er
Exhibit No. 5 Page 512 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
WROCKYMOUNTAINxffirowrn
x A fivrsroN 0F PAcFrcoHP
Exhibit No. 5.8
Refrigerator and Frcezer Recycling Evaluation
2009-2010
Rocky Mountain Power
Exhibit No. 5 Page 51 3 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
$rNsxsN Nsgxms-^t)
TAilMIJS
February 3, 2012
i"-\...-..^ ... ...^ ...i 1... . .
The Cadmus Group, lnc. / Energy Services
720 SW Washington Street, Suite 400
Portland, 0R 97205
503.228.2992
i:f *r.t.l i"..s \,,: ij .,,til i .'
Rocky Mountain Power
Roclry Mountain Power
Exhibit No. 5 Page 514 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Principal I nvestigators:
Kate Bushman
Josh Keeling
Jason Christensen
Hossein Haeri
Steve Cofer
The Cadmus Group, lnc.
720 5\f{ Ylkhingtan St.
S*ite 400
Ponlard, OR 97:05
T6l: 503.?38.??91
Farc 503^?.18.3696
Corporta l{eadquanex:
57 Warer Sr.eet
V1futen$w'l MA0?47:
Tet: 61I.673,.7000
Fax: 617.673,7G01
An Employee-Owned Compony
*:r,ri\q{t.{.}* $}u$$t'e ii g.:fiil l'l
Rocky fulountain Power ldaho Evaluatiot't 200S-201S Report
Rocky Mountain Power
Exhibit No. 5 Page 51 5 of 1 365
Case No. PAC-E-'14-07
#ts?i:'5#S."rUT?
Table of Gontents
Glossary of Terms ......1
Executive Summary........... .......3
Summary of Key Findings... ........................3
Summary and Recommendations ................7
Program Participation ............... ...................8
lmpact Evaluation............. ...... 11
Methodology............. ...............1 1
Estimating Average Gross Unit Consumption.............. .................15
In-Service Rates .....19
Evaluated Gross Savings..... .......................21
Net-to-Gross............... ..............23
Process Evaluation............ .... 31
Methodology............. ...............31
Program Implementation and Delivery.... ....................32
Marketing. ..............35
Customer Response.. ................40
Quality Assurance. ...................43
Cost-Effectiveness............ ..... 44
Appendix A: Participant Demographics ...........48
Appendix B: CFL Engineering Calculations and Assumptions................... 50
Appendix G: Precision Calculations ........ ......... 56
Appendix D: Participant Suruey lnstrument........... ......... 58
Appendix E: Nonparticipant Suruey lnstrument........... .................77
The Cadrnus Group lnc. i Energy $ervices
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclry Mountain Po\ryer
Exhibit No. 5 Page 516 of 1365
Case No. PAC-E-14-ol
#ts?'fr#ffiT,"aHT?
Glossary of Terms
Analysis of Covariance (ANCOVA)
An ANCOVA model is an ANOVA model with a continuous variable added.
Analysis of Variance (ANOVA)
An ANOVA model explains the variation in the independent variable, based on a series of
characteristics (expressed as binary variables equaling either zero or one).
Evaluated Gross Savings
Evaluated gross savings represent total savings the evaluator finds result from a program, before
adjusting for freeridership or spillover. They are most often calculated for a given measure, i, as:
Eualuated Gross Savingsi - Verif ied Partictpatloni * Untt Consumpttoni
Evaluated Net Savings
Evaluated net savings are the savings "net" of what would have occurred in the program's
absence. These savings can be attributed to the program. Net savings are calculated as:
Net Savtngs = Evaluated Gross Savings * NTG
Freeridership
Freeridership in energy-efficiency programs is defined as participants that would have adopted
the energy-efficient measure in the program's absence. This is often expressed as the
freeridership rate, or the proportion of evaluated gross savings that can be classified as
freeridership.
In-Service Rate (ISR)
The ISR (also called the installation rate) is the proportion of incented measures actually
installed.
Net-to-Gross (NTG)
The NTG ratio is the ratio of net savings to gross savings. Analytically, NTG is defined as:
NTG = L - Freeridershtp Rate * Spillouer Rote
P-Value
A p-value indicates the probability that a statistical finding might be due to chance. A p-value
less than 0.10 indicates one can say, with 90 percent confidence, that the finding was due to the
intervention.
Part-Use Factor
The part-use factor is the proportion of the year that equipment is operated. That is, if a given
measure has a part-use factor of 0.5, it operated for six months out of the year, on average.
Net Realization Rate
The realization rate is calculated by comparing evaluated net savings to reported gross savings.
The Cadrnus Group, lnc. / Energy $ervices
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No.5 Page 517 of 1365
Case No. PAC-E-14-07
CB$?l]'ffiT,"2UT?
Rf
The R2 (coefficient of determination) indicates the proportion of variance explained by a
regression equation, and takes values between zero and one. An Rf of zero indicates the
independent variables have no explanatory power. An R'? of one indicates the 100 percent of
variability in the dependent variable is explained by changes in the independent variables.
Spillover
Spillover is the adoption of an energy-efficiency measure induced by the program's presence, but
not directly frurded by the program. As with freeridership, this is expressed as a proportion of
evaluated gross savings (or the spillover rate).
T-Test
In regression analysis, a t-test is applied to determine whether the estimated coefficient diflers
significantly from zero. A t-test with a p-value less than 0.10 indicates that there is a 90 percent
probability that the estimated coeffrcient is different from zero.
The Cadnrus Group, [nc. / Energy Services
Rocky Mountain Power ldaho Evaluation 2CI0$*2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 518 of 1 365
Case No. PAC-E-14-07
#8?'fi{ilT,"2UTI
Executive Summary
Rocky Mountain Power contracted with The Cadmus Group Inc. (Cadmus) to conduct impact
and process evaluations for program years 2009 and 2010 ofits Idaho See ya later, refrigeratorG'
(SYLR) progftlm. The impact study sought to evaluate the program's energy savings on a gross
and net savings basis. The process evaluation-utilizing structured interviews with utility
progrulm and implementation staff, and surveys with program participants and nonparticipants-
sought to assess program effectiveness, marketing, and participants' experiences and satisfaction
levels.
Evaluation data consisted of the following primary sources:
o Telephone surveys with 151 participating Idaho customers;
o Telephone surveys with 51 nonparticipating Idaho customers;
o Reviews of Idaho program materials and marketing documents; and
o In-depth interviews with program management and progftlm administrator staff;
As well as the following secondary sources:
. Cadmus' appliance metering data from 452 refigerators and 41 freezers; and
o Cadmus' light logger metering data from 750 unique fixtures across four states.
The SYLR program, delivered on Rocky Mountain Power's behalf by JACO Environmental, Inc.
(the program administrator), has sought to decrease electricity usage (kwh) through voluntary
removal and recycling of inefficient refrigerators and freezers. Participants receive a $30
incentive for each qualified refrigerator or freezer recycled through the program. Participants
also receive a free energy-saving kit, which includes two l3-watt compact fluorescent lamps
(CFLs), a refrigerator thermometer card, energy-saving educational materials, and information
on other Rocky Mountain Power efficiency programs relevant to residential customers.
Summary of Key Findings
Key lmpact Findings
The impact evaluation resulted in the following key findings:
o In 2009, the SYLR program recycled 717 refrigerators and freezers; in 2010,
participation increased to 800 total units.
o Evaluated unadjusted unit energy consumption values (UECs) for refrigerators (1,259
kVfh) were slightly higher than the reported savings (1,149 kwh). Evaluated unadjusted
UECs for freezers (1,125 kwh) were lower than reported values (1,590 kWh). The
reported value used for freezers was higher than the typical range of UECs Cadmus has
recently estimated for this measure.
o For refrigerators, the part-use factor, which indicates the portion of the year the appliance
operated, was 0.95, consistent with the average value in similar programs. Freezer part-
The Cadmus Group, [nc. i Energy Services 3
Rocky h4ountain Power ldaho Evaluation 2009-201CI Report
Rocky Mountain Power
Exhibit No. 5 Page 519 of 1365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasFebruary 3. 2012
use (0.93) was higher than the level Cadmus typically finds in this type of program,
indicating most freezers were used full-time.
o Applying adjustments for part-use, gross per-unit savings were determined to be 1,190
kWh for refrigerators, 1,041 kWh for freezers.
. Applying adjustments for freeridership and spillover, net per-unit savings were
determined to be 578 for refrigerators, 589 for freezers.
o Gross savings for energy-saving kits (74 kwh) were found to be lower than the reported
per-unit savings of 81 kWh. Cadmus' evaluation employed inputs specific to the SYLR
progftlm participants in Idaho to determine evaluated savings.
o Participants reported installing 84 percent of CFLs provided in the energy-saving kit, and
this installation rate was incorporated in Cadmus' gross savings estimate. Cadmus made
no net adjustment to savings from energy-saving kits, since this was an add-on measure
distributed to all participants.
o Cadmus estimated freeridership for refrigerators and freezers at 51 percent. This report
examines comparable recycling programs and their evaluated freeridership levels.
Cadmus combined freeridership and spillover (which accounted for less than 1 percent of
savings) to determine the overall program net-to-gross ratio of 0.53, which is in the mid-
to-low range compared to other appliance recycling programs
Table I summarizes program participation, gross savings (reported and evaluated), and evaluated
net savings for 2009-2010.
'Throughout the report, table totals may not add up exactly due to rounding.
"Appendix C provides a detailed methodology for precision calculations.
Table 1. 2009-2010 P
The Cadrnus Group, lnc. / Energy Services
Rocky [fiountain Power ldaho Evaluation 2009-201CI Report
Rocky Mountain Power
Exhibit No. 5 Page 520 of 1365
Case No. PAC-E-14-07
CEE?IffT,"2UT?
Table 2 and Table 3 report savings by program year.
Key Process Findings
The process evaluation provided the following key findings:
o Collaboration between Rocky Mountain Power and the program administrator proved
effective, due to a longstanding working relationship in Idaho and other states.
o In 2009 and 2010, the SYLR progftrm did not meet its participation targets: the 2009
program year achieved only 45 percent of expected participation; and, with increased
participation and a reduced goal, the 2010 program year achieved 82 percent. Program
staff reported a reduced incentive, economic conditions, and program maturation led to
lower participation, compared to earlier years of program implementation. Cadmus has
observed downward trends in participation in other similar programs.
o Participants reported high satisfaction levels with the program. Eighty-one percent of
surveyed participants reported being very satisfied with the program; only 1 percent
reported dissatisfaction. This level of satisfaction is similar to what Cadmus has found in
other similar programs. A majority of participants expressed satisfaction with incentive
levels. The participant swvey did not identify significant customer complaints.
o Participants learned of the program through various channels, the three most common
being: bill inserts, print advertising, and word-of-mouth. Both the online signup process
Table 2.2009 P
t14.4o/o
Table 3. 2010
The Cadmus Group, lnc. / Energy $ervices
Rocky fvlountain Power ldaho Evaluation 200S-2010 Report
Roclq Mountain Power
Exhibit No. 5 Page 521 of 1365
Case No. PAC-E-14-07
\Mtness: Kathrun C. HvmasFebruary 3. 2012
and the telephone signup process proved simple and easy to understand, and participants
reported high satisfaction levels with both.
o A review of Rocky Mountain Power's marketing materials and online presence suggested
additional marketing strategies that, if implemented, may further expand program
awareness and participation. For example, Cadmus recommends increased consistency in
online branding, and expanded retail partnerships.
Cost-Effectiveness Resu lts
As shown in Table 4, the program proved cost-effective across the evaluation period for four of
the five primary cost-effectiveness tests: PacifiCorp total resource cost (PTRC), total resource
cost (TRC); participant cost (PCT); and utility cost (UCT) perspectives.
The program was cost effective with the relatively high benefit-to-cost ratios of 2.38 and 2.16
from the PTRC and TRC perspectives and remained relatively stable over the two program
years. The program did not prove cost-effective from the rate impact measure (2M) perspective,
which measures impacts of programs on customer rates. Most programs do not pass the RIM test
due to the adverse impact of lost revenue. Levelized cost per kWh, presented in Table 4,
represents the present value ofprogram life cycle costs, divided by total energy savings produced
by the program over the lives of the measures. This metric proves useful for comparing demand-
side management (DSM) programs' energy costs with those of supply-side resources.
Table 5 and Table 6 show the program's cost-effectiveness for 2009 and 2010 program years,
respectively.
Table 4.2009-2010 Evaluated P
Total Resource + Conservation Adder
Table 5.2009 Evaluated m Cost-Effectiveness Summ
Total Resource + Conservation Adder
Total Resource No Adder
$21,510
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Case No. PAC-E-14-07
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Table 6.2010 Evaluated P Cost-Effectiveness Summ
Total Resource + Conservation Adder
Summary and Recommendations
Although participation was slightly lower than expected in both 2009 and 2010, the Idaho SYLR
program ran smoothly with no implementation issues, and experienced high customer
satisfaction.
Based on evaluation findings, Cadmus offers the following recommendations:
o Rocky Mountain Power should continue implementing the SYLR program to achieve
cost-effective energy savings.
Rocky Mountain Power should adjust its expected per-unit savings to reflect estimates
calculated in this evaluation. Cadmus recommends tracking program savings using the
evaluated per-unit gross savings values of 1,190 kWh for refrigerators and 1,041 kWh for
freezers.
Although Rocky Mountain Power did not apply a Waste Heat Factor (WHF) adjustment
to CFL savings estimates, the WHF should be applied to all future planning and
evaluated CFL savings values. Cadmus recommends tracking program savings from
energy-saving kits using the WHF-adjusted gross savings value of 63 kWh.l
Per-unit savings can be greatly affected by changes in appliance characteristics, such as
configuration, age, and size. The program administrator tracks these characteristics, and
Rocky Mountain Power should closely monitor changes in participating units'
characteristics. This could be achieved by summaizing participation data on an annual
basis, and noting changes in average participant unit characteristics.
The program administrator and Rocky Mountain Power should continue with plans to
improve reporting processes to eliminate the possibility of reporting discrepancies and
increase accuracy of reported results. Cadmus identified minor discrepancies in reported
number of participant units, and Rocky Mountain Power has since worked with the
program administrator to prevent discrepancies between program administrator and
Rocky Mountain Power reporting by including additional documentation in monthly
reports.
' Appendix B outlines Cadmus' recommended WHF approach and value. For this SYLR program period, the WHF
was determined to be 85-2%.
The Cadmus Group, lnc. i Energy Services
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
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Program Description
The Idaho See ya later, refrigeratoro 1S1,'I-R1 resiclential r:efrigeratr.rr anil lreezer recycling
progrirm seryes as part of Rocky Mountain Power's ongoing demand-side management (DSM)
resource acquisition strategy.' The program's overarching objective seeks to decrease electricity
usage GVfh) through removal and recycling of inefficient secondary refrigerators and freezers,
and older primary refrigerators. This prevents older units from remaining in service at a
participant's premise or elsewhere within Rocky Mountain Power's Idaho service territory. The
program encourages those shopping for replacement units to consider ENERGY STAR@-labeled
models, and refers them to the Home Energy Savings (HES) program, where they may be
eligible for incentives for other energy-efficiency measures and services. In addition to reducing
energy consumption at the household and utility levels, the program recycles participating
appliances in an environmentally sound manner.3
Launched in 2005, the program provides residential customers with a $30 incentive for each
recycled appliance. Participants receive an incentive for up to two refrigerators or freezers.
Renters owning their appliances may participate, and apartment complex owners or managers are
eligible if they provide tenants with appliances. Panicipants also receive a free energy-saving kit,
which includes: two 13-watt compact fluorescent lamps (CFLs), a refrigeratorlfreezer
thermometer card, energy savings educational materials, and information on other company
efficiency programs relevant to residential customers. Qualifying refrigerators and freezers must
be: in working condition when picked up; and at least 10 cubic feet or more in size. Rocky
Mountain Power contracted with JACO Environmental, Inc. (the program administrator), to
deliver the program in Idaho. The program administrator disables and removes the appliances,
and recycles at least 95 percent of the materials, including refrigerant capture.
Program Participation
Program participation in appliance recycling programs typically follows a seasonal pattern, with
the highest participation during summer, and declining into winter. As shown in Figure 1, the
SYLR program saw periodic participation surges in2009, with most occurring during summer.
Participation declined at the end of summer, and peaked again in the late autumn months. During
the program's second year, participation increased slightly, beginning in July 2010.
2 See ya later, refrigerator@ has been registered to PacihCorp through the U.S. Patent and Trademark Office since
April 6, 2010, under registration number 3770705.
3 Environmentally-sound disposal of this equipment includes: proper disposal of oils, PCBs, mercury, and CFC-11
foam; and recycling of CFC-12, HFC-134a, plastic, glass, steel, and aluminum.
IThe Cadmus Group, lnc. i Energy Services
Rocky Mountain Power ldaho Hvaluation 2009-2010 Report
Roclly Mountain Power
Exhibit No. 5 Page 524 of 1365
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Figure 1. Program Participation by Month and Year
100
.=tr
=60t!
oF 40
20
0-i
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
12009 2010
As programs mature, the composition of recycled appliances tends to change. In their infancy,
programs recycle more secondary appliances (particularly those in use for only a portion of the
year) in customer populations. Such units tend to be older, smaller, located in unconditioned
spaces, such as garages or basements, and to be less efficient. Such refrigerators also are much
more likely to be single-door units.
Figure 2 shows five-year trends in unit age and size. Freezers' and refrigerators' average unit
ages showed a slightly declining trend, while average size showed an increasing trend (newer
units tend to be larger). These trends follow patterns Cadmus has observed in similar programs
elsewhere.
Figure 2. Average Unit Age and Size by Year
I oo-i -- - |lii rt"i ii i ls ,.:-ri:.l i.
i ,ol - i
l6/\{'.'-'.-....'..M..? rs ^.ih-- i - igzol -- - ioi :u!.- i I.< r) l' - -iii10 I --- """"" iii!.iis -i-.--. .. -.-- * ... -..- -iiiii0 .i-****-----,r*-.---..----------...r.-----.*--*,"".--j*
20
18
16
t4
t2
10
8
6
4
2
0
o
ttt
2006 2007 2008 2009 2010
:ft fsfliggr2lor Age .,,,,1::j:i,,,,.t. Freezer Age
{ssSNRefrigerator Size Ns$ss Freezer Size
The Cadmus Group, lnc. I Energy Services
The program's refrigerator configurations also matched the expected trends. Single-door units
accounted for fewer units during 2010, while side-by-side units (a more modern, albeit less
effi cient, confi guration) increased.
Figure 3.rator Con tion Year
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 525 of 1365
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\Mtnessi Kathrvn C. HvmasFebruary 3, 2012
700%
90%
80%
70o/o
60%
5Oo/o
40%
3Oo/o
2Oo/o
lOo/o
Oo/o
2010
As shown in Figure 4, freezer configurations showed some variation, but did not display an
appreciable trend.
Figure 4.Freezer Configurations by Year
I Single Door
N Side by Side
STop Freezer
I Bottom Freezer
LO0%
90%
80%
70%
60%
s0%
40%
30%
20%
to%
Oo/o
N Upright
I Chest
2010
The Cadmus Group, lnc. / Hnergy Services 10
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclry Mountain Power
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lmpact Evaluation
Methodology
This report presents two values for evaluated savings: evaluated gross savings, and evaluated net
savings. The evaluation defined reported gross savings as electricity savings (kV/h) Rocky
Mountain Power reported to Cadmus and contained in its 2009 and 2010 annual program reports.
To determine evaluated net savings, Cadmus applied four steps to reported gross program
savings, as shown in Table 7.
Step one (veriffing accuracy of data in the participant database) included reviewing the program
tracking database to ensure participants and reported savings matched the 2009 and 2010 annual
reports.
Step two (performing a statistical/engineering analysis to evaluate per-unit savings) involved
estimating refrigerator and freezer savings as well as CFL savings assumptions, such as delta
watts and hours-of-use.
Step three (adjusting evaluated gross savings with the actual installation ratelpart-use factor)
determined the mean proportion of the year in which recycled appliances were used as well as
the number of CFLs program participants installed (and remained installed). Using a telephone
survey, information was collected to estimate an installation and persistence rate (referred to as
the In-Service Rate or ISR), which was then used in calculating evaluated gross savings.
The first three steps resulted in evaluated gross savings. The fourth step (applying net-to-gross
[NTG] adjustments) determined the net savings. Through participant and nonparticipant
telephone surveys, Cadmus estimated effects for freeridership and spillover.a
Sampling Approach
Cadmus developed survey samples of randomly selected program participants and
nonparticipants, seeking precision of t10 percent at the 90 percent confidence level for
individual estimates at the measure level. The evaluation determined sample sizes, assuming a
0.5 coefficient of variation. For small population sizes, Cadmus applied a finite population
adjustment to achieve precision estimates. Table 8 shows planned and achieved sample sizes by
target group.
a This report' s Net-to-Gross section provides a detailed description of the estimation of these parameters.
Table 7. Impact Steps
Evaluated Gross Savings
Perform statisticaUengineering analysis to evaluate per-unit
Adjust evaluated gross savings with actual installation
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Table 8. Samnle Sizes Ta
Table 9 details the screening process for eligible participants. The 151 participants were
randomly selected from 1,372 unique participants with Idaho mailing addresses, valid phone
numbers, and valid Rocky Mountain Power customer account numbers. Fifty-one
nonparticipants were selected through screening questions from a random sample of 2,000
Rocky Mountain Power customers residing in Idaho.
able 9. Particinant and Nonnarticinant Su
IIEIISII|SSIgiTU
TotalRecords 1,517 2,000
No Customer Number 6 0
Duolicate Records (bv customer name and phone number)139 0
Elioible oarticioants in call list 1.372 2,000
Comoleted Survevs 151 51
ResDonse Rate*11Yo 3o/o
Coooeration Rate*"49%30k
'The response rate is defined as the number of customers completing a suryey, divided by the
number of eligible participants in the catl list.
" The cooperation rate is defined as the number of customers completing a survey, divided by the
number of customers reached by phone.
California and Michigan evaluations conducted between May 2009 and
Collectively, these evaluations offered a wide distribution of appliance
configurations, usage scenarios (primary or secondary), and climate conditions.
diverse nature provided an effective secondary data souroe for estimating energy
Idaho-specific metering could not be conducted.
Cadmus prefers using in-home metering data for estimating energy consumption, as opposed to
Department of Energy's (DOE's) testing protocols, for two reasons.
First, metering the appliance in its original location captures impacts of critical external factors
on appliance energy use (such as door openings, unit locations, and weather); these factors
cannot be accounted for when relying on DOE databases, which contain data on units metered
under controlled conditions.
s In situ metering involves metering units in the environment in which they are typically used. This contrasts with
lab testing, where units are metered under controlled conditions.
6 Southern Califomia Edison, Pacific Gas & Electric, San Diego Gas & Electric, DTE Energy, and
Consumers Energy.
April 2}ll.6
ages, sizes,
The dataset's
savings when
Regression Analysis
Cadmus developed a multivariate regression model to estimate gross unit energy consumption
(UEC) for retired refrigerators and freezers. Cadmus estimated model coefficients using an
aggregated in situ metering' dataset, composed of over 400 appliances, metered as part of four
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Second, most existing DOE databases estimate energy consumption at the time of appliance
manufacture, not of unit retirement.T Consequently, evaluations require devising and applying
additional assumptions in appliance degradation. In-home metering data reflect observed usage
of appliances actually participating in appliance recycling programs at the time of retirement and
as used in the homes from which they were removed.
Each observation in the aggregated dataset represents an appliance metered for a minimum of
10 days in a manner consistent with its preprogram use (i.e., in the same location, cooling food,
and used by the home's occupants). Cadmus mapped weather data to participating homes' ZIP
code-specific National Oceanic and Atmospheric Administration weather stations, and collected
additional on-site data on relevant appliance characteristics to ensure data consistency with
program administrator tracking databases.
Cadmus' approach to model specification weighed the impacts of including alternative
independent variables, using a variety of criteria. The model specification process sought to
include variables adequately reflecting progftrm design, while maintaining model simplicity. For
each set of estimated parameters, the analysis assessed variance inflation factors (VIFs), adjusted
R2s, and measures of statistical significance.s
Cadmus used the following modeling considerations in the specification process:
. Using an ordinary least squares method to estimate model parameters. Data were
approximately normally distributed, an important condition for the analysis. An
examination of the final model's residual plot supported this hypothesis of normality.
Considering all relevant appliance characteristics for inclusion in the model. These
included: configuration, defrost type, age, size, and (in the case of refrigerators) primary
or secondary designations. Age was considered as a continuous variable (capturing
degradation), as dummy variables for decades of manufacture (to approximate vintages),
and as a dummy variable for units manufactured before enactment of 1990's National
Appliance Energy Conservation Act (NAECA), which required new refrigerators and
freezers to be more energy efficient.
Considering two environmental factors in the in situ model. In addition to terms
pertaining to appliance characteristics, the analysis considered two environmental factors
in the in situ model: cooling degree-days (CDD) and primary or secondary appliances.
Appliances in warmer climate zones were assumed to consume greater energy-as were
primary appliances -due to more frequent door openings.
Including interaction terms only for theoretical importance to the model. The model
only included one interaction term, between units located in garages and CDDs, to
account for additional impacts of warmer temperatures on refrigerators in unconditioned
spaces.
' The Califomia Energy Commission maintains one such database, which can be accessed online at
http://www.energy.ca.gov/appliances/database,/historical excel files/Refrigerationr
8 VIFs, R2s, and statistical significance are tests of the validity of a regression model. ln this case VIFs under 5 were
deemed sufTicient.
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o Considering transformations of explanatory variables. These included logged and
squared values, based on theoretical and empirical grounds.
Kit Savings Algorithm and Assumptions
With each pickup ordered, participants received an energy-saving kit, which contained:
o Two 13-watt CFLs;
. One refrigerator thermometer; and
o Energy-savings educational materials and other program references.
The following algorithm estimated CFL savings:
LWatts *1SR xH0U x365Evaluated Per Untt Savings (kwllper untt) -1,000
Where:
o AWatts: Wattage of baseline bulb - Wattage of ENERGY STAR CFL
o ISR : In-service rate or the percentage of units installed
o HOU = Hours of use; per day
o 365 : Constant; days per year
o 1,000: Constant; conversion of watts to kilowatts
The ISR captured CFLs installed, removed, and replaced by other energy-efficient light bulbs.
Specifically:
Installed - RemovedCFL In - Servi"ce Rate (lSR o/o) -Sent
Cadmus estimated wattage changes by comparing lumen outputs of kit CFLs to their
incandescent equivalents. The l3-watt kit CFLs output 900 lumens, equivalent to a 60-watt
incandescent bulb. Cadmus chose to use 60 watts as the baseline because it is the incandescent
bulb of equivalent lighting output (measured in lumens). Cadmus found this represented the most
reasonable, cost-effective assumption for calculating CFL savings, and provided a consistent
approach across the other Cadmus Idaho evaluations.
Cadmus calculated average hours of use (HOU) using ANCOVAe model coefficients, estimated
from a combined multistate, multiyear database of light logger data, compiled by recent Cadmus
CFL HOU studies. This model expressed average HOU as a function of room type, existing CFL
saturations, and the presence of children in a home. Appendix B provides a more detailed
exploration of the impact methodology used to estimate CFL HOU.
Figure 5 shows distributions of bulbs by room Wpes. The values for all explanatory variables,
save existing CFL saturations, were based on response data from the participant survey. Data on
CFL saturations were not available from Rocky Mountain Power's service territory in Idaho, so
' ANCOVA, or analysis of covariance, refers to a type of statistical modeling.
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Cadmus calculated an average from comparison households in service areas where the history of
CFL incentive programs is similar to Idaho's.
I Living Space
s Kitchen
S Basement
I Outdoor
H,l Bedroom
n Bathroom
N Other
Rocky Mountain Power lD SYLR Participant Survey: Question E6.
Estimating Average Gross Unit Consumption
Cadmus used regression models to estimate consumption for refrigerators (Table l0) and
freezers (Table l l). Each independent variable's coefficient indicated the influence of that
variable on daily consumption, holding all other variables constant. A positive coefficient
indicated an upward influence on consumption; a negative coefficient indicated a downward
effect.
The value of the coefficient indicates the marginal impact on the unit energy consumption (UEC)
of a one-point increase in the independent variable. For instance, a 1 cubic foot increase in
refrigerator size results in a 0.081 kWh increase in daily consumption. In the case of dummy
variables, the value of the coefficient represents the difference in consumption if the given
condition is true. For example, in the refrigerator model, the coeffrcient for the variable that
indicates a refrigerator was a primary unit is 0.663, indicating, all else being equal, a primary
refrigerator consumes 0.663 kWh per day more than a secondary unit.
In the refrigerator model, there is no dummy variable for units manufactured after the 1990s.
These units are considered the baseline, and, therefore, all other dummy coefficient values are
relative to this baseline. For example, the coefficient for the variable that indicates a unit was
manufactured before 1980 is 1.372. This coefficient implies that units manufactured in the 1970s
consume 1.372 kwh per day more than units manufactured in the 2000s.
Figure 5. Locations of Installed Bulbs
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Refrigerator Regression Model
Table l0 shows the model used to estimate refrigerators' annual energy consumption and its
estimated parameters.
Table 10. Refrigerator UEC Regression Model Estimates
The results indicated:
1. Older refrigerators use more electricity, due to degradation and changes in effrciency
over time. The impact of vintage on daily consumption, represented by the decade-of-
manufacture coefficients, drops from 0.960 in the 1980s to 0.199 in the 1990s. This
shows the effect of the 1990 enactment of the NAECA standard, which required new
refrigerators to be more energy efficient.
Larger refrigerators consume more energy.
Single-door units consume less energy, as these units typically do not have full freezers.
Side-by-side refrigerators experience higher consumption due to greater exposure to
outside air when opened and due to through-door features common in these units.
Primary appliances experience higher consumption due to increased usage.
At higher temperatures, refrigerators in unconditioned spaces consume more energy.'0
r0 It is also likely units in unconditioned spaces, such as garages, consume less energy at extremely cold
temperatures. Comprehensive in-home metering of refrigerators and freezers in winter months has not been
extensive.
2.
J.
4.
5.
6.
ndent Variable = Ave
: Unit Manufactured in 1970s
: Unit Manufactured in 1980s
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E-hrb*f":"YPYs""'Hi,,"iruf;
Case No. PAC-E-14-07
Rocky Mountain Power ldaho Evaluation 200S-2010 Report #ts"imffiT,tZBT?
Freezer Regression Model
Table l1 details final model specifications used to estimate energy consumption of participating
freezers and its results.
Table 11. Freezer UEC Regression Model Estimates
2 = 0.40)Variable = Av Dailv kWh. R'=
lntercept -0.590 0.003
Aoe (vears)0.040 <.0001
Dummv: Unit Manufactured Pre-1 990 0.566 <.0001
Size (ft.3)0,109 <,0001
Dummv: Chest Freezer -0.265 <.0001
lnteraction: CDD x Dummv: in Garaoe 0.059 <,0001
The results show:
1. Older freezers experienced higher consumption due to year-on-year degradation.
2. Freezers manufactured before the 1990 NAECA standard consumed more energy.
3. Larger freezers consumed more energy.
4. Chest freezers consumed less energy than upright units, due to reduced heat infiltration
from door openings in these units.
5. At higher temperatures, freezers in unconditioned spaces consumed more energy.
Extrapolation
After estimating the final regression models, Cadmus analyzed the corresponding characteristics
(the independent variables) for participating appliances (as captured in the program administrator
program database). Table 12 summarizes program averages or proportions for each independent
variable.
able 2. 2009-2010 Participant Mean Explanatorv Variables*
Refriqerator
Aoe (vears)24.90
Dummv: Unit Manufactured in 1970s 0.26
Dummv: Unit Manufactured in 1980s 0.38
Dummy: Unit Manufactured in 1990s 0.31
Size (ft.s)17.96
Dummv: Sinole Door 0.07
Dummv: Side-bv-Side 0.16
Dummv: Primarv Aooliance 0.57
lnteraction: CDD x Dummy: in Garaoe 0.20
Freezer
Aoe (vears)32.83
Dummy: Unit Manufactured Pre-1990 0.88
Size (ft.s)17.69
Dummv: Chest Freezer 0,29
CDD 0.37-CDDs are the weighted average CDDs from TMY3 data for weather stations mapped to
participating appliance zip codes. TMY3 is a typical meteorological year, using median daily
values for a variety of weather data collected from 1 991-2005.
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Rocky Mlountain Power ldaho Evaiuatlon 2009-2010 Report
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Exhibit No. 5 Page 533 of 1 365
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Cadmus applied average participant refrigerator and freezer characteristics to the regression
models to estimate average daily and, subsequently, annual UEC. This approach ensured the
resulting UEC would be based on specific units recycled through Rocky Mountain Power's
program. For example, using values from Table 11 and Table 12, the estimated annual UEC for
freezers can be calculated as:ll
Freezer UEC = 365 days
* (-0.590 + 0.040 x [32.83 years old) + 0.566
,rl}Bo/ounitsmanufacturedpre - 19901 + 0.109 *l\7.69 ft.'l-0.265
* f29o/o units that are chest f reezers) + 0.059
x [0.37 Unconditioned CDDI) x t,L25 kWh
Figure 6 compares distributions of estimated UEC values for refrigerators and freezers.
Figure 6.2009--2010 Distribution of Estimated Annual UECs by Appliance Type for
Participant Units
qoo oS nS "oo
noo +" *oOooOS*S*S*S
Annual kWh
f Refrigerators N Freezers
Ctr""
rr This equation illustrates the inputs, but Cadmus' analysis took a slightly different approach to calculating average
UECs. The analysis used the regression coefficients to predict an average daily UEC for each unit in the
administrator tracking database. The annualized average of these predictions represented the average UEC for
the participant population during the program period. This approach ensured the resulting UEC would be based
on specific units recycled through Rocky Mountain Power's program. The two approaches would be
mathematically identical if the tracking database were 100 percent complete. Due to rare instances of missing
data, results from the two approaches differ slightly.
t5%
14%
t2%
r0%
8o/o
6%
4o/o
2%
-t--T'
600 6so ^S\f \r \t
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Rocky Mountain Power ldaho Evaluation 200S-2010 Report
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Exhibit No. 5 Page 534 of 1 365
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Kit Savings
Table 13 shows final inputs and unadjusted gross savings estimated for CFLs distributed in the
energy-saving kits.
Table 13. U usted CFL ot Includi for In-Service Rate)
Cadmus did not calculate savings from the refrigeratorlfreezer thermometer or from educational
materials provided in the kits, as these savings were likely small and quite difficult to quantiff
accurately. However, participant survey results indicated 99 percent of participants found the
information provided in the kit at least somewhat helpful, and approximately 67 percent of
participants reported using the refrigerator thermometer. Of those installing the thermometer,
21 percent reported decreasing their refrigerator temperatures.
UEC Summary
Table 14 reports evaluated per-unit average annual energy consumption for refrigerators and
freezers recycled by the SYLR during the 2009-2010 program period. The following section
describes adjustments to these estimates used to determine gross per-unit saving estimates for
participant refrigerators and freezers. The results indicated an evaluated freezer value 465 kWh
lower than the reported value, with a refrigerator value 110 kwh higher.
The evaluation shows Rocky Mountain Power used a slightly low reported value for refrigerators
(though only marginally different from the regression analysis' average
annual UEC).
ln-Service Rates
Appliance Part-Use Factor
Participants used some refrigerators and freezers recycled through the program for part of the
year. Cadmus calculated a weighted average part-use factor, representing the three participant
usage categories, as defined by the appliance's operational status during the year before it was
recycled. For example, participants not using their appliance at all received a part-use factor of
zero as no immediate savings were generated by their appliance's retirement. Table 15 shows
part-use factors for the three usage categories.
Table 14. Estimates of Per-Unit Annual Ene
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Rocky Mountain Power ldaho Evaluatlon 2009-2010 Report
Roclry Mountain Power
Exhibit No. 5 Page 535 of 1365
Case No. PAC-E-14-07
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Table 15. Part-Use Factors
Not runnino for at least one full
*Participants using their appliances part of the year received a pan-use factor derived from
the proportion of total months they used the appliance.
Table 16 shows participants using their appliances for only part of the year had average part-use
factors of 0.54 for refrigerators and 0.40 for freezers. Thus, the average freezer recycler, using a
freezer for part of the year, used it for approximately five months, on average.
Using participant survey data, Cadmus assessed the percentage of participants in each of the
three usage categories (no usage, full-year usage, and partial usage). These percentages informed
weighted average usage for each appliance type: the part-use factor. Refrigerators and freezers
had part-use factors of 0.95 and 0.93, respectively, indicating that, prior to recycling, the average
unit ran a high percentage of the time.
Table 16. Part-Use Factors and Evaluated
'"Not in Use'refers to units that were simply not plugged in, as inoperable units were excluded from the program.
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CFL lnstallation Rate
On average, participants initially installed 1.7 of the two bulbs received, resulting in an 84
percent installation rate. Figure 7 shows the proportion of participants installing zero, one, or two
bulbs.
Figure 7. Number of Bulbs Installed
n=67
Rocky Mountain Power lD SYLR Participant Survey: Question E4.
Evaluated Gross Savings
Table 17 provides estimates of per-unit evaluated gross energy savings. Cadmus determined
estimated energy consumption of units through the in situmetering study, adjusting it by part-use
factors determined from the participant survey.
Table 17. Part-Use usted Per-Unit Evaluated Gross Ene Sav Measure
-For Energy-Saving Kits calculation methods, see Appendix B.
Tracking Database Review
The program administrator manager reported three types of program data tracked:
o Data on recycled appliances (stored in a'oUnits" database);
Information about pickups (stored in an "Orders" database); and
Data about customers (stored in a "Customers" database).
These integrated databases allowed the program administrator to record information collected via
the call center or Website, along with on-site data collected during pickups, and post-pickup data
recorded during recycling. The program administrator's client Web portal provided the Rocky
a
a
The Cadmus Group, lnc. / energy Services 21
Rocky Mountain Power ldaho Evaluation 2CI09-2010 Report
Rodry Mountain Power
Exhibit No. 5 Page 537 of 1365
Case No. PAC-E-14-07
d$ts?iffiT,"2HT2
Mountain Power program manager with real-time access to collection data and other progfttm
results.
Every month, the program administrator completed a monthly report using a template provided
by Rocky Mountain Power, documenting the number of units recycled that month and the
number of kits distributed. Rocky Mountain Power received the monthly report on the 25ih of
every month, and used monthly reports to compile its annual DSM reports.
During the evaluation, Cadmus learned the monthly reports documented a slightly different
number of recycled units than the complete Units database, provided by the program
administrator for evaluation purposes. Upon further examination of the data, the program
administrator could not identifu the source of this discrepancy, but confirmed the discrepancy did
not affect invoicing, as invoicing occurred separately from monthly reporting. The program
administrator and Rocky Mountain Power have planned changes to the reporting processes to
prevent such discrepancies from occurring in the future. For the impact evaluation activities,
Cadmus assumed the program administrator's Units database provided the most reliable source
of the total number of units recycled. Table 18 details reporting discrepancies.
Table l9 compares total reported and evaluated gross savings by measure.
Table 19.2009-2010 vs. Evaluated Sa
Energy-Saving
Kir
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Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclry Mountain Power
Exhibit No. 5 Page 538 of 1 365
Case No. PAC-E-14{7
#ts?'frff5."ztsT?
Net-to-Gross
Cadmus' analysis estimated net savings for recycled refrigerators using the following formula:
Net sauings = Gross Savings * (1 - Freeridership Ratio * Spillover Rati.o)
Where:
Gross Savings:Evaluated in situ UEC for the recycled unit, adjusted for
part-use;
The proportion of program savings that would have occurred in
the program's absence;
Non-programmatic savings induced by the program, expressed as
a proportion of gross savings;
Freeridership Ratio:
Spillover:
Freeridership
Assessing freeridership for appliance recycling programs can be challenging, as the programs not
only seek to remove ineffrcient appliances from the customers' homes, but seek to remove them
from the utility grid. Thus, freeridership must be estimated based on participants' reports of what
would have happened to the appliance in the program's absence. This invites the risk of biased
responses from participants, as participants must assess what they would have done
hypothetically. Such assessments very often suffer from social desirability bias, which results
from the respondents' tendency to answer questions in a manner that will be viewed favorably by
others. To counteract this potential bias, Cadmus collected additional data from nonparticipantsl2
about how they actually disposed of their appliances.
Table 20 presents four possible scenarios, assuming participating refrigerators or freezers had not
been recycled through the program. As Scenarios 1 and 3 indicate freeridership, the report
addresses those scenarios in further detail.
Table 20. Potential Freeridersh Scenarios
Scenarios 1 and 2
For participants reporting they would have kept units had they not participated in the program,
the survey asked whether they would have used the unit or would have stored it unplugged.
These responses provided the proportion of units that would have been kept and not used at this
12 Nonparticipants were defined as Rocky Mountain Power customers disposing of a working refrigerator or freezer
outside of the SYLRprogram during 2009 or2010.
The Cadrnu$ Group, lnc. I Energy Services 23
Roclry Mountain Power
Exhibit No. 5 Page 539 of 1365
Case No. PAC-E-14-O7
Rocky lvlountain Power ldaho Hvaiuation 2CI0$*2010 Report Wtness: Kathrun C. HvmasFebruary 3. 2012
time (therefore, not .drawing electricity from the grid-an indication of freeridership). To
maintain conservative estimates, energy savings associated with these units were subtracted from
the program's evaluated gross savings.
Scenarios 3 and 4
Calculating freeridership associated with Scenarios 3 and 4 (units discarded and destroyed in the
program's absence, and units transferred to another owner in the program's absence) proved
slightly more complex, as they included a number of different hypothetical actions. Table 2l
presents participants' Scenario 3 and 4 responses, indicating actions participants claimed they
would have taken had the program not been available.
Table 21. Freeridersh Scenarios 3 and 4 rtic nses)
Rocky Mountain Power lD SYLR Participant Survey: Question F17.*Cadmus' prior market research has indicated that used appliance dealers do not resell units over 15 years old. Thus the
analysis assumed units over 15 years of age would not have remained on the grid.1s--Although it is possible that some dealers resell used units that are picked up, Cadmus' prior market research has shown that a
majority of dealers do not resell these units. Cadmus's assumption that none of these appliances were resold is conservative, but
since it affects only a small portion of participants, it has a minimal efiect on overall NTG.
13 An example of the market research that informed these assumptions can be found in the Ameren Illinois PY2
Appliance Recycling Evaluation Report, available online at httl::il'ilsag,,.iirgi'e.r:p.lya_tig[*tlgp.ilgrents..
Sell it to a private party, either by
an ad or to someone vou know
Sell it to a used aooliance dealer
Give it away to a private party, such as
Give it away to a charity organization,
such as Goodwill lndustries or a church
Have it removed by the dealer you got
Haul it to the dump or recycling center
Hire someone else to haul it away for
The Cadrnus GrCIup, lnc. / Hnergy $ervices 24
Rccky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No, 5 Page 540 of 1 365
Case No, PAC-E-14-07
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Table 22,below, provides comparable responses for nonparticipants.
'Refrigerators and freezers pooled due to smaller sample size.
Rocky Mountain Power lD SYLR Nonparticipant Survey: Question A6.
The freeridership calculations outlined above yield the
presented in Table 23.
appliance-specific, freeridership ratios
Table 23.Pa nt and N nt Freeridersh Res
. The number of respondents factored into the freerider score differs from total number of participants and nonparticipants
surveyed, because some respondents gave a response of "Don't know'to one or more essential questions.
"For ease of interpretation, this report uses absolute precision for proportion estimates,
Cadmus averaged the freeridership ratio estimates for participating and nonparticipating
appliances to arrive at final, measure-level freeridership ratios. Calculating the average used
inverse variance weights ensured placing greater weight on values with a higher degree of
certainty.
Table 24. Freeridershi Ratios
Table 22. Freeridership Scenario 3 and 4 (N
Sell it to a private party, either by
an ad or to someone vou know
Sell it to a used aooliance dealer
Give it away to a private party, such as
Give it away to a charity organization,
such as Goodwill lndustries or a church
Have it removed by the dealer you got
Haul it to the dump or recycling center
Hire someone else to haul it away for
The Cadrnus Group, lnc.I Energy $ervices 25
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No.5 Page 541 of 1365
Case No. PAC-E-14-07
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Spillover
Spillover refers to additional savings generated by program participants due to their program
participation, but not captured by program records. Spillover occurs when participants purchase
energy-efficient measures or adopt energy-efficient practices due to a program, but they choose
not to participate (or are otherwise unable to participate) in the program. As these customers are
not participants, they do not appear in program records of savings generated by spillover
impacts.
Spillover examples include:
o Program participants adopting additional measures without an incentive.
o Consumers acting on the programs' influence, resulting from changes in available
energy-using equipment in the marketplace.
. Changes brought about by more efficient practices employed by architects and engineers,
ultimately forcing consumer behaviors into desired patterns.
. Changes in nonparticipants' behaviors resulting from direct marketing or changes in
stocking practices.
The energy-efficiency program's spillover effect serves as an additional impact, which
added to the program's results, in contrast with freerider impacts (which reduce net
attributable to the program).
Methodology
For the SYLR program, Cadmus measured spillover by asking a sample of participants
purchasing and receiving an incentive for a particular measure if, due to the program, they
installed another effrcient measure or undertook other energy-efficiency activities. Respondents
were asked to rate the relative influence of the SYLR program and incentive on their decisions to
pursue additional savings.
Spillover questions sought to determine whether program participants installed any other energy-
saving measures since participating in the program. Savings participants received from additional
measures would be considered spillover savings if the program significantly influenced their
decisions to purchase additional measures, and if they did not receive additional incentives for
those measures.
SYLR program participants were specifically asked whether they installed the following
measures, which were associated with quantifiable spillover:
1. High-efficiency dishwashers
2. High-efficiency washers
3. High-efficiency refrigerators
4. High-efficiency water heaters
5. CFLs
If the participant installed one or more of these measures, they were asked additional questions
about which year they purchased the measure, and whether they received an incentive for the
can be
savings
The Cadmus Group, lnc. / Energy $ervices 26
Rocky [tilountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 542 of 1365
Case No. PAC-E-14-07
Wtnes: Kathryn C. HvmasFebruary 3, 2012
measure. If applicable, participants were asked how influential the SYLR program was on their
purchasing decisions (participants could answer not at all, not very, somewhat, or very
influential). Participants expressed mixed responses regarding the program's influence on these
actions, with data indicating 45 percent found the program "somewhat" or "very" influential.
Figure 8. Program Influence on Installing Additional Measures
(with 907o Conlidence Intervals)
Not at all
influential
Not very
influential
Somewhat Very
influential influential
Sixty percent of participants claimed to have installed energy-efficient measures or changed their
behaviors after participating in the SYLR program. However, only five such purchases represent
quantifiable savings: energy-efficient refrigerators, clothes washers, dishwashers, water heaters,
and CFLs. Other measures, such as weatherization and HVAC, are difficult to quantifu
accurately based on survey data, and thus were not included in the spillover analysis. Figure 9
shows distributions of reported actions taken, including those not associated with spillover
savings
Bocky Mountain Power lD SYLR Participant Survey: Question SP7,
The Caclmus Group, lnc. i Hnergy Services 27
Rocky fiflountain Power ldaho Hvaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 543 of 1365
Case No. PAC-E-14-07
FUts?X]#ffiS,"2UT?
Figure 9. Other Energy-Effi lnstalled Since Participating in the Program
I CFLS
N Weatherization/HVAC
S High efficiencywasher
f High efficiency dryer
u\\ High efficie ncy dishwasher
S High efficiency refrigerator
N High efficiency water heater
lllll Behavioral change/other
n= 133
Rocky Mountain Power lD SYLR Participant Survey: Question SP6.
Cadmus calculated participant spillover by estimating savings attributable to additional measures
installed, and whether respondents credited Rocky Mountain Power with influencing their
decisions. Measures were counted if they were eligible for program incentives but incentives
were not requested. NTG ratios then were calculated, accounting for estimated freeridership and
spillover effects.
Spillover Savings Analysis
For calculating spillover savings, Cadmus used a top-down approach. The analysis began using a
subset containing only survey respondents who indicated they installed additional energy-savings
measures after participating in the SYLR program, but without receiving any incentives. From
this subset, Cadmus removed participants who indicated the program had little influence on their
decisions to purchase additional measures.
For the remaining participants with legitimate spillover savings, Cadmus estimated energy
savings from additional measures installed. Savings values, calculated by Cadmus, were matched
to additional measures installed by survey participants.
The Cadnrus Greup, [nc. / Hnergy $ervices 28
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Case No. PAC-E-14-07
Rocky rvrountain Pcyg.gglg. Evaruation 200s-2010 Report ___ - . #B?tffifT.c:$.T2_
Table 25, below, summarizes participant survey spillover responses. Appliance per-unit savings
were derived from Cadmus'evaluation of 2009 and 2010 Home Energy Savings gross savings
values. Cadmus assumed CFL savings equaled those calculated for energy-saving kits. Total
spillover savings represented 0.75 percent ofrefrigerator and freezer savings.
Final Net-to-Gross
As summarizedin Table 26,the evaluation determined final net savings (and, subsequently, the
NTG ratio) as gross savings, adjusted for freeridership and spillover.
The NTG ratios found for the 2009-2010 progftrm period was slightly lower than average for
similar programs in other service areas. Table 27 compares NTG ratios for similar appliance
recycling programs evaluated over the last few decades. As shown, NTG ratios for the Idaho
2009 and 2010 SYLR program fell within the range of these values. The main driver behind the
somewhat low NTG ratios was the high proportion of participants indicating that without the
program they most likely would have taken their appliance to the dump. This trend was
corroborated by nonparticipant survey data indicating that a high proportion of nonparticipant
appliance disposers took their appliances to the dump. This is most likely due to the rural
composition of Rocky Mountain Power's Idaho service territory, since rural areas may have less
access to other disposal methods (such as resale) that would not indicate freeridership.
Table 26. Final NTG Ratios
The Cadmus Group. lnc. I Energy Services 29
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountiain Power
Exhibit No. 5 Page 545 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasFebruary 3, 2012
Results for Pacific Gas & Electric, from Residential Retrofit High lmpact
Measure Evaluation Report, California Public Utility Commission, The Cadmus
PoweMise Appliance Recycling Program, Salt River Project, FY 2009
lmpact and Process Evaluation of Ontario Power Authority's 2007 Great
EM&V Study of 2004-2005 Statewide ResidentialAppliance Recycling
ADM Associates, lnc.
ResidentialAooliance Tum-ln Prooram in Wisconsin. PA
Evaluation of the Washington Refrigerator and Freezer Recycling Program,
PY 2005-2006, KEMA-
Measurement and Evaluation Study of 2002 Statewide Residential Appliance
Measurement and Verification Report for NCPA SB5X Refrigerator Recycling,
Final Reoort, Robert Monis & Associates
Measurement and Verification of SB5X Energy Efficiency Programs for the
Final Reoort. Heschono Mahone
lmpact Evaluation of the Spare Refrigerator Recycling Program, CEC Study
#537, Final Report to SCE,
lmpact Evaluation of 1994 Spare Refrigerator Recycling Program, Project lD
515, Final Reoort to SCE-The methodology that KEMA applied in the 2002 Califomia study and the 2005-2006 Washington study included part-use as
one component of the NTG adjustment, resulting in lower than average NTG ratios.
Summary of lmpact Findings
Table 28 and Table 29 summarize impact evaluation findings.
Table 28.2009-2010 Per-Unit Sa Measure
Table 29.2009-2010 m Savi Measure
The Cadmu$ Group, lnc. I Energy Services 30
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 546 of 1 365
Case No. PAC-E-14{7
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Process Evaluation
This section presents detailed staff interview findings as well as
survey results. Focus areas include:
and nonparticipant
a
a
o
a
Delivery structure and effectiveness of the implementation strategy;
Marketing approach and relative success;
Customer satisfaction; and
Internal and external communications.
Methodology
The research conducted to support the process evaluation followed three major steps:
1. Document review.
2. Utility staff and administrator interviews.
3. Participant and nonparticipant surveys.
Cadmus reviewed program materials, including:
o Past evaluations;
o Marketing and communication materials designed to promote participation and educate
target audiences on the program;
o Logic models; and
o The program's Website.
This review sought to assess:
o The general look and feel of marketing materials;
o Brand and message consistency, program accessibility; and
o Stakeholder forms and information.
Review results helped inform the design of stakeholder interview guides and customer surveys,
and development of specific recommendations regarding program marketing.
Next, Cadmus developed stakeholder interview guides to collect information about key topics
from program management staff. JACO Environmental implements the SYLR program (as they
do in other Rocky Mountain Power service territories operating appliance recycling programs).
Cadmus interviewed two main program staff: program managers at Rocky Mountain Power and
at JACO, both of whom oversee the programs in all five states offering appliance recycling
progftrms (Idaho, Washington, California, Utah, and Wyoming). Issues discussed included:
. Program history;
o Process flow;
o Program design versus program implementation;
o Changes in implementation and program marketing; and
The Cadmus Group, lnc. i Energy Services 31
Rocky Mlountain Power ldaho Evaiuation 2009-2010 Report
Roclq Mountain Power
Exhibit No. 5 Page 547 ot 1365
Case No. PAC-E-14-07
VMtness: Kethrun C. HvmasFebruary 3" 2012
o Strengths and areas for improvement.
Cadmus staff conducted stakeholder interviews by phone, and, for follow-up questions and
clarifications, contacted stakeholders via e-mail.
Finally, Cadmus conducted telephone surveys with participant and nonparticipant customers.
Cadmus designed survey instruments to collect data about the following topics:
o Customer information. Data characterizing participants and allowing extrapolation of
results to the entire program population.
o Program process. Survey questions collecting information to inform the following
performance indicators :
o Is the program's design appropriate to meet its goals?
o Is program marketing effective?
o What are participation motivations and barriers?
o Are program incentives set correctly?
o Is the program process effective?
o Are customer satisfaction goals being met?
o What are the program's strengths or areas for improvements?
Program lmplementation and Delivery
Drawing on stakeholder interviews and participant and nonparticipant survey response data, this
section discusses implementation and delivery of the SYLR progmm.
Program Status
In 2005, the SYLR program launched in Idaho. During its early implementation years, the
program experienced participation levels higher than the national average. According to the
program administrator, Rocky Mountain Power and the program administrator established
program goals for the 2009-2010 period, based on prior program performance and on harvest
rates in comparable programs elsewhere. The contract between Rocky Mountain Power and the
program administrator included these projected participation levels, although lower-than-
expected participation did not result in a financial penalty.
For this two-year period, Idaho experienced lower-than-expected participation as compared to
the goals included in the contract: the 2009 program year achieved only 45 percent of its
participation goal; and, with increased participation, the 2010 program year achieved 82 percent.
Despite the low achievement rates compared to contract goals, program administrator staff noted
participation levels remained robust when compared to the national average.
Program staff noted several possible reasons for the slow 2009 and 2010 performance:
o The incentive amount decreased from $40 to $30 in 2008, driving a decline in
participation that year. This trend of lower participation associated with a lower incentive
may have continued in 2009 and 2010, since participation levels remained essentially
constant during that period.
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Rocky fi/lountain Power ldaho Evaluation 200S-201CI Report
Roclry Mountain Power
Exhibit No. 5 Page 548 of 1 365
Case No. PAC-E-14-07
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o The economic downturn, beginning shortly before the evaluation period, may have
caused diminished demand for program services. During difficult economic times,
customers are less likely to move to new homes or remodel, and thus less likely to
dispose of appliances.
o Demand for appliance recycling may also be declining after five years of implementation.
Participation declines are expected as programs mature and eliminate backlogs of older
appliances.
Staff offered two possible explanations for increased participation in 2010:
o The program manager noted that Idaho Power launched a similar program under the same
name during the evaluation period, and this may have caused a marketing spillover effect.
For example, Idaho Power advertising may have increased awareness among Rocky
Mountain Power customers.
o Increased participation in 2010 may have been influenced by the availability of new
refrigerators rebates, funded by the American Recovery and Reinvestment Act.
Delivery Structure and Processes
Rocky Mountain Power and program administrator staff reported the program had been designed
similarly to SYLR programs already operating in the company's other service territories. The
Idaho program leveraged existing infrastructure by operating through the same call center used
to implement the program in other states, fumishing the Idaho program with experienced
customer service representatives.
During 2009 and 2010, two main subcontractors contributed to program implementation:
o Runyon, Saltzman & Einhorn served as the marketing subcontractor, supporting the
progftrm administrator's program marketing, advertising, and public relations activities.
. Appliance Distribution served as the appliance pickup subcontractor, with multiple crews
responsible for picking up and transporting appliances to the recycling facility.
The program delivery process followed four main steps:
1. Marketing.
2. Sign-up/scheduling.
3. Appliance pick-up.
4. Incentive payment.
Marketing (described in greater detail below) targeted owners of older and secondary
refrigerators, although participating appliances had no minimum age requirements.
Rocky Mountain Power's Idaho customers, interested in disposing of an eligible appliance, could
obtain information or sign up to participate through Rocky Mountain Power's Website, or by
calling the program administrator toll-free. When participants signed up, the program
administrator collected data on how customers learned of the program, verified eligibility, and
The Cadrnus Group, lnc. / Energy Services 33
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Roclry Mountain Power
Exhibit No. 5 Page 549 of 1 365
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scheduled pick-up times. The customer received a window of time for appliance pickup on a
specific day, and was required to have the appliance plugged in and running upon pickup.ra
Times between scheduling and pickup averaged 17 days. The program administrator noted
pickup wait times tended to be shortest in urban areas, while customers in outlying areas
experienced longer waits.
This wait time was somewhat longer than that of other programs, however, longer waits are
expected for a mostly-rural service territory such as Rocky Mountain Power's in Idaho.
Furthermore, the high customer satisfaction found in the participant survey indicates that longer
wait times did not have an appreciable negative effect on the participant experience.
At the scheduled time, the contractor picking up the appliance verified the unit was in working
condition, and collected data about the appliance's age, size, configuration, and features. During
appliance pickup, participants received an energy-saving kit, containing: two l3-watt CFLs, a
refrigerator thermometer, energy-savings educational materials, and information about Rocky
Mountain Power's other energy-efficiency program offerings. Both program managers described
these kits as effective program components.
During the 2009-2010 program period, Appliance Distribution's facility received picked-up
appliances for decommissioning and recycling. The program administrator then assumed
responsibility for mailing incentive checks to participants.
Forms and lncentives
Unlike many incentive programs, the SYLR program requires minimal paperwork for
participating customers. The signup process can be completed by phone or online, and neither
process requires the customer to fill out lengthy forms. Customers signing up by phone are asked
for information, including their address and the location of the unit as well as a few screening
questions. Customers signing up online respond to these questions through a brief, one-page
online form. Customers appreciated the simplicity of the sign-up process: over 99 percent of
surveyed customers reported being very or somewhat satisfied with the program sign-up process.
Participating customers reported high satisfaction levels with the incentive amount. Sixty-five
percent of surveyed participants said they were very satisfied with the incentive amount, with an
additional 32 percent reporting they were somewhat satisfied. Furthermore, 75 percent of
participants claimed they would have participated in the program had the incentive amount been
lower, and 74 percent said they would have participated even if no incentive had been offered.
These results, however, may reflect social desirability bias.ls
u The program administrator estimated that typically 2-3 percent of pickups are ineligible for participation because
the appliance is found not to be working. Similarly, the program administrator reported that roughly l-2 percent
of units scheduled to be picked up are ineligible for participation due to their size.
rs Social desirability bias is the tendency for respondents to exaggerate their inclination to "do the right thing."
The Cadmus Group, lnc. I Energy $ervice*34
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Rocky Mountain Power
Exhibit No. 5 Page 550 of 1 365
Case No. PAC-E-14-07
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Marketing
Approach
The program administrator markets the SYLR program through an array of channels
which include:
Newspaper advertisements;
Radio and television advertisements;
Online advertising;
A program Website;
Customer information sheets;
Bill inserts;
Retailer referrals;
Point-of-purchase advertising; and
Social media outreach through Rocky Mountain Power.
The program administrator oversees Runyon, Saltzman & Einhorn, the marketing subcontractor,
which develops marketing materials and works with the progrirm administrator to develop an
overall strategy and approach. The program administrator and program manager described the
process as collaborative, emphasizing that, as part of this process, Rocky Mountain Power must
approve every piece of marketing collateral.
In addition to overseeing the collaborative process of creating and disseminating marketing
material, the program administrator analyzes participation data to inform marketing strategy
decisions. For example, the program administrator reported that bill inserts typically provoked
spikes in program activity; so the timing of bill inserts has been coordinated to periods requiring
increased volume.
Materials Review
Cadmus' review of SYLR program promotional materials evaluated the messaging content, look
and feel, and user accessibility of collateral materials, online promotional elements, and other
user forms and educational materials. Cadmus then incorporated insights gained through
interviews with program and implementation staff to apply context and develop conclusions. The
high-level findings, presented below, indicate Rocky Mountain Power's ongoing marketing
efforts have been effective. After the program's slow start in 2009, 2010 marketing efforts
helped improve participation, as indicated by program staff.
Cadmus' findings include the following:
o The SYLR marketing plan has been well constructed: Rocky Mountain Power's 2010
marketing plan includes best practice tactics, and provides an appropriate range of media
channels to drive participation.
a
a
a
a
a
a
a
o
o
a
The Cadrnus Group, lnc. / EnerEy Services 35
Rocky ltllountain Power ldaho Evaluation 200S*2010 Repo*
Roclry Mountiain Power
Exhibit No. 5 Page 551 of 1 365
Case No. PAC-E-14-07
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c SYLR program mnrketing collateral presents a consistent look and feel: Program Web
pages, bill inserts, and other collateral include consistently uncluttered and clear designs,
bold colors, and large typefaces.
c SYLR program marketing collateral provides consistent messaging.' Marketing content
includes basic calls-to-action and motivating messages. This helps reinforce word-of-
mouth recoflrmendations and awareness.
o Trade ally support would bokter program success, but mty be difftcult in ldaho:
According to program staff, the limited presence of national big box retailers in the
service territory may limit the potential for large-scale retail program support.
Table 30 and Table 3l compare SYLR program marketing approach elements to best practice
elements in energy-efficiency program marketing. Rocky Mountain Power currently appears to
utilize several best practice marketing channels, but additional, remaining opportunities could
increase participation.
'For the SYLR program, these could be distributed to potential participants by appliance retailers.
"Social media (e.9, Twitter, Flickr, YouTube, Facebook) offer channels for utilities to connect with customers. Many utilities'
communications efforts leverage one or more social media platform(s).
able 30. SYLR Prosram Use of Best Practice M Channels in 2009-2010
yesDirect Mail
Newsoaoer Ads iarticles Yes
RadioiTV Ads Yes
0nline Advertisino Yes
Website Yes
Customer lnformation Sheets Yes
Betailer lnlormation Sheets-No
Telemarketino No
Bill lnserts Yes
Brochures No
Newsletters Yes
P resentationsiMeetinos No
Events No
Refenals/Retai I Partnerships No
Point of Purchase No
Tests/Demonstrations No
Social Media Outreach**Rockv Mountain Power
The Cadrnus Group, lnc. i Energy $ervices 36
Rocky hrtountain Power ldaho Evaluation 2009-2010 Report
Roclq Mountain Power
Exhibit No. 5 Page 552 of 1 365
Case No. PAC-E-14-07
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Table 31 summarizes use of online best practices in the SYLR Website, and provides rationale
and additional information regarding particular online findings. Generally, the program
administrator's experience with other utilities and regions has provided practical expertise in
developing effective marketing tools.
Effectiveness
According to program managers and per the marketing materials review, the SYLR program's
overall marketing approach has been effective and responsive to changes in participation and
market conditions. The program administrator reported tracking increased program activity in
response to particular marketing pieces to evaluate the effectiveness of different marketing
activities. Cadmus gathered further information about marketing effectiveness through the
participant surveys. As shown in Figure 10, most participants learned of the program through
two mechanisms: bill inserts and print media. Another 15 percent learned about the program
through a friend or family member, a strong indication of high program satisfaction.
able 31. SYLR use of Website tsest Practices
Navigation Program highlighted on
home oaoe
No Users often enter utility sites through the home page.
Easy "one-click" access to a program makes
participation easier, and provides greater program
exposure. Other utilities have found a recycling
reoistration button on the home oaoe effective,
Navigation Number of clicks from
home page
Three
Content Description leads with
benefits (i.e., What's in it
for the participant?)
Home Page:WattSmart
Programs and lncentives 0R
Save Energy (non-specific)
SYLR Program Page:"Get
Paid to Recycle Your Old
Refrioerator or Freezer.'
The SYLR program has a compelling, clear benefit
statement.
Content Clear call to action Yes The program's "why" has been clearly presented,
Cadmus recommends including the call to action-
"schedule your free pick up"-at the top and bottom of
the page. Further, more consistent branding between
the recycling page and the JACO ZIP code page would
orovide a more inteorated user exoerience.
Marketinq Contact capture Yes
Content Description of each
individual program offered
Yes
User
Ernerience
Participant eligibility
reorriremenls
Yes User experience refers to the online process and
interactivity from the use/s perspective. Easy
downloads and online forms increase the likelihood that
targets will participate and move forward with program
activity. SYLR provides such documents online.
User
Exoerience
Downloadable application
forms
nla
User
Exoerience
Online registration
orocess
Yes
Marketing Downloadable program
information in orint format
No Easy and simple-to-share marketing materials increase
"word of mouth" activity, in-person or online, As most
SYLR participants surveyed expressed satisfaction and
would recommend the program, this element presents a
particularlv important opportunity.
Marketing Social media nshare'
elements included (e.9.
Facebook. Twitter. etc,)
No
The Cadnru$ Group, lnc. I Energy $ervices 37
Rocky !\flountain Power ldaho Evaluatlon 2009-2010 Report
Rocky Mountain Power
Exhibit No.5 Page 553 of 1365
Case No. PAC-E-14-07
#E?T#ST,"a,HT?
S N ewspa per/Ma ga zi ne/Pri nt
Media
x Fa m i lylF riends/Word-Of-
Mouth
ITV
:llt Retailer/Store
S Rocky Mountain
Power/Pacif ic Power Website
S lnternet Advertisi ng/Onl i ne
Ad
l{r Other
n= 135
filky il;ou]rtai'iFo*er lD SYLR Pan,c,pant Surrey, Ouestl(il -*""""""'--"""""""""""""'i
The survey also asked whether SYLR progftrm participants later participated in other Rocky
Mountain Power energy-efficiency programs. Ten percent of participants took part in other
programs after participating in the SYLR program, and, as shown in Figure 11, the vast majority
of respondents stated they were more likely participate in future Rocky Mountain Power
programs.
38The Cadmus Sroup, lnc. i Hnergy Services
Rocky fvlountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 554 of 1365
Case No. PAC-E-14-07
flg[?"fiffiS,"2UT?
Figure 11. Likelihood of Participating in Another Roclcy Mountain Power Program
Rocky Mountain Power lD SYLR Participant Survey: Question SP4.
'Confidence intervals indicated by black bars in figure.
Targeting
Compared to customers in the general population, appliance recycling program participants
tended to be homeowners in single-family residences, averaged roughly 56 years of age, and had
children. Table 32 shows average demographics for participants surveyed.
The vast majority (92 percent) of participants lived in single-family residences, with less than
7 percent living in multifamily or manufactured homes. Respondents' ages reflected roughly
two-thirds of participant respondents were over age 50. As contact information derived from
self-reported information (i.e., landlines or cell phones), the survey experienced no bias for
respondents with landlines.
Comparison with Nonparticipants
A nonparticipant population differing demographically from the participant population may
indicate misplaced or incomplete targeting of marketing efforts. Cadmus tested for similarities
between nonparticipant and participant populations to rule out marketing not reaching some
eligible demographic groups. For example, if a large portion of nonparticipants lived in mobile
(with 907" Confidence Intervals)*
Much more likely Somewhat more
likely
Table 32. Partici
The Cadnrus Group, inc. / Energy $ervices 39
Rocky Mountain Power ldaho Evaiuatiot"t 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 555 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasFebruary 3, 2012
homes (and few participants lived in mobile homes), the mobile home market may have been
overlooked.
Cadmus found no statistically significant differences between participants and nonparticipants.
Table 33 shows t-tests' results for differences between the two groups'6 for a series of relevant
characteristics. In all cases, p-values exceeded 0.10, indicating demographics did not differ with
90 percent confidence.
Home types also did not differ significantly. Cadmus' chi-square test for independence between
the two groups indicated they could not be said to differ with 90 percent confidence (p-value :
o.gg).17
Table 33. T-Tests for Demographic Differences between
Participants and Nonparticipants
Participants' and nonparticipants' similar demographics indicate marketing has been targeted
appropriately.
Customer Response
Satisfaction
The program experienced high overall satisfaction rates. Approximately 81 percent of
participants reported being very satisfied with the program, with only 1 percent reporting
dissatisfaction. As shown in Figure 12, when asked about progftlm specifics, such as scheduling
and incentive amounts, participants expressed similar satisfaction levels.
16 All t-tests conducted assumed unequal sample sizes and variances.
'7 A chi-square test is a statistical test used in this case to determine whether the distribution of home types for
participants differed statistically from the distribution of home types for nonparticipants.
The Cadmus Group, lnc. I Hnergy $ervices 40
Rocky Mountain Pcwer ldaho Hvaluation 2CI0S-20X0 Report
Rocky Mountain Power
Exhibit No. 5 Page 556 of l365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasFebruary 3. ?012
Figure 12. Overall Program Satisfaction (with 90% Confidence Intervals
Very satisfied Somewhat satisfied
too%
9Oo/o
80o/o
70%
60%
50%
40%
30%
20%
to%
0%
Somewhat
d issatisfied
Very dissatisfied
n= 151
Roc$ Mountain Power lD SYLB Participant Survey: Question G1.
Participants' willingness to recommend the program to others reflected their positive perceptions
of the program. Figure 13 shows participants' self-reported likelihood of recommending the
program ran quite high, with 97 percent saying they were somewhat or very likely to recommend
the program.
Figure 13. Likelihood of Recommending Program to Others
(with 90%o Confidence Intervals
90%
80%
70%
60%
50%
40%
30%
20%
70%
o%
Very likely Somewhat likely Notverylikely Notatall likely
n= L50
Rocky Mountain Power lD SYLR Participant Survey: Question G10
The Cadrnus Group, lnc. / Energy $ervices 41
Roclry Mountain Power
Exhibit No. 5 Page 557 of 1 365
Case No. PAC-E-14-07
Rocky Mlountain Power ldaho Evaiuation 200S-2010 Report Wtness: Kathrun C. HvmasFebruary 3, 2012
Though most customers reported positive experiences with the program, some participants
expressed concerns over difficulties in scheduling convenient pickup times. Though this problem
was experienced by a small minority of participants (with approximately 7 percent of
participants finding this somewhat difficult, and only 2 percent finding this very difficult), it
served as the only significant complaint identified through customer surveys.
Figure 14. Level of Difficulty with Scheduling: Participant Survey Results
(with 907o Confidence Intervals)
Very easy Somewhat easy Somewhat
difficult
Rocky Mountain Power lD SYLR Participant Survey: Question G4.
Program managers reported scheduling delays as a cause for attrition of potential participants,
and thus an issue that may have affected participation levels. Participant survey results indicated
participating customers generally expressed satisfaction with the scheduling process, but the
participant survey did not reflect the opinions of customers not participating due to scheduling
problems.
Nonparticipant surveys also cited scheduling issues, although the issue did not seem to be a
leading cause of nonparticipation: of 18 nonparticipant respondents who had heard of the
program prior to disposing of their appliances, two reported not taking advantage of the program
as they could not schedule convenient pickup times. This represents only 4 percent of surveyed
nonparticipants.
Barriers
Overall, participant surveys did not reveal significant complaints or issues, and though the
SYLR process evaluation, Cadmus noted no significant barriers. The program functions
smoothly, likely due to its longevity in the Idaho market and the program administrator's
experience.
90%
80%
70%
50%
so%
The Cadmus Group, lnc. I Energy Services 42
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 558 of 1365
Case No. PAC-E-14-07
PU$?'fiffiT,'2UT?
Quality Assurance
Though the program administrator manager reported data collection at numerous points
throughout the participation process, Cadmus identified data entry and pickups as two areas with
established quality assurance procedures for the program:
o When data, collected in the field by appliance pickup contractors, are translated into the
database, opportunities arise to identifu and correct erors.
o The progftIm administrator manager reported an independent quality assurance
contractor, hired by Rocky Mountain Power, follows pickup crews for a sample of
pickups to observe pickup procedures and customer service. The quality assurance
contractor also interviews participating customers to assess their satisfaction with the
service.
43The Cadmus Group, lnc. i Energy Services
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclq Mountain Power
Exhibit No. 5 Page 559 of 1365
Case No. PAC-E-14-07
VMtness: Kathrvn C. HvmasFebruary 3, 2012
Cost-Effectiveness
In assessing cost-effectiveness, Cadmus analyzed program costs and benefits from five different
perspectives, using Cadmus' DSM Portfolio Prol8 model. Benefit-to-cost ratios conducted for
these tests were based on methods described in the California Standard Practice Manual (SPM)
for assessing DSM programs' cost-effectiveness. Tests utilized included the following:
a. PaciliCorp Total Resource Cost Test (PTRC): This test examined program benefits
and costs from Rocky Mountain Power's and Rocky Mountain Power customers'
perspectives, combined. On the benefit side, it included avoided energy costs, capacity
costs, and line losses, plus a 10 percent adder to reflect nonquantified benefits. On the
cost side, it included costs incurred by both the utility and participants.
b. Total Resource Cost Test (TRC): This test examined program benefits and costs from
Rocky Mountain Power's and Rocky Mountain Power customers' perspectives,
combined. On the benefit side, it included avoided energy costs, capacity costs, and line
losses. On the cost side, it included costs incurred by both the utility and participants.
c. Utility Cost Test (UCT): From Rocky Mountain Power's perspective, benefits included
avoided energy, capacity costs, and line losses. Costs included program administration,
implementation, or incentive costs associated with program funding.
d. Ratepayer Impact (RIM): All ratepayers (participants and nonparticipants) may
experience rate increases designed to recover lost revenues. This test included all Rocky
Mountain Power program costs as well as lost revenues. Benefits included avoided
energy costs, capacity costs, and line losses.
e. Participant Cost Test (PCT): From this perspective, program benefits included bill
reductions and incentives received. Costs included a measure's incremental cost
(compared to the baseline measures), plus installation costs incurred by the customer.
Table 34 summarizes the five tests' components.
'Present value of avoided energy and capacity costs includes avoided line losses occurring from reductions in customer
electric use.
't DSM Portfolio Pro has been independently reviewed by various utilities, their consultants, and a number of
regulatory bodies, including the Iowa Utility Board, the Public Service Commission of New York, the Colorado
Public Utilities Commission, and the Nevada Public Utilities Commission.
Table 34. Benefits and Costs Included in Various Tests
Present value of avoided energy and capacity costs.
with 10% adder for non-quantified benefits
Present value of avoided enerov and caoacitv costs-
Present value of avoided energy and capacity costs-
Present value of avoided enerqv and caoacitv costs*incentive costs + Dresent value of lost revenues
Present value of bill savinos and incentives received lncremental measure cost and installation cost
The Cadmus Group, lnc. i Energy Services 44
Rocky fulountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No, 5 Page 560 of 1 365
Case No. PAC-E-14{7
Vvitness: Kathrun C. HvmasFebruary 3, 2012
Table 35 provides selected cost analysis inputs, including: evaluated energy savings for each
year, discount rate, line loss, and program costs. Rocky Mountain Power provided all of these
values, except energy savings. The discount rate derived from Rocky Mountain Power's 2008
Integrated Resource Plan. Rocky Mountain Power also provided the values for line loss and
program costs.
Table 35. Selected C Analysis Iaostn
Particioation
Refrioerator Recvclino 555 628 1 .183
Freezer Recvclino 162 172 334
Enerov-Savino Kit 675 741 1 ,416
Prooram Savinos (kWh/veadt 520,480 572,1 68 1.092.648
Discount Rate 7.40o/o 7.40o/o 7.40%
Line Loss 11.39%9.96%N/A
lnflation Bate 1,90%1.90%1.90%
Total Prooram Costs $86,376 $1 42.1 6 1 $228.537- Savings reflect impacts at generation, and have been increased for line losses. Since per-unit savings and
adjustments for spillover and freeridership are modeled as rounded values, the total savings shown here may differ
from the total savings reported elsewhere by around 1%, However, this minor discrepancy caused by rounding in the
cost-effectiveness model does not have an appreciable effect on benefit-cost ratios.
Program benefits included energy savings and their associated avoided costs. The cost-
effectiveness analysis used energy savings derived from this study's evaluated kWh. Analysis
used a weighted average measure life of 8.2 years, based on the measures' lifetimes, and
weighted by savings and frequency of installations." AU analyses used avoided costs associated
with Rocky Mountain Power's 2008 IRP 46 Percent Load Factor Eastside Residential Whole
Home Decrement.2o
Cadmus analyzed cost-effectiveness for two scenarios. The first assumed zero percent
freeridership and spillover (NTG equaling 100 percent). The second incorporated evaluated
freeridership and spillover.
Table 36 presents program cost-effectiveness analysis results with NTG equaling
100 percent for all program measures for the evaluation period (2009-2010), though not
accounting for non-energy benefits (except those represented by the 10 percent conservation
adder included in the PTRC). For this scenario, cost-effectiveness analysis results indicated the
program was cost-efflective from all perspectives, except the RIM (a 1.0 or greater benefit-cost
ratio would be considered cost-effective). Most programs do not pass the RIM test due to the
adverse impact of lost revenue.
le Measure lives for recycled refrigerators, recycled freezers, and kit CFLs were derived from the most recently
published workbooks available from the Regional Technical Forum:
http:r'iwq'w.nrvcouncil.orgienergyirtflnreasures,i'es.iltesCIiLLigirting;v2 0.xlsm, and
http:,r'www.n'rvcouncil.orgienerg);, rtf,"nteasuresire sril;riqReclrcle*[rY I 0v2-1l.xls
'o IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan, Vol. II Appendices:
urce....Plan n il g.5..pdll
The Cadmus Group, lnc. i Energy Services 45
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclq Mountain Power
Exhibit No. 5 Page 561 of 1365
Case No. PAC-E-14-07
\Mtnesi Kathrun C. HvmasFebruary 3, 2012
Table 36. P m Cost-Effectiveness for 2009-2010 (NTG = 100
Table 37 presents program cost-effectiveness analysis results, including evaluated NTG for all
program measures for the evaluation period (2009-2010), though not accounting for non-energy
benefits (except those represented by the 10 percent conservation adder included in the PTRC).
For this scenario, cost-effectiveness analysis results indicated the program was cost-effective
from all perspectives, except the RIM (a 1.0 or greater benefit-cost ratio would be considered
cost-effective). Most programs do not pass the RIM test due to the adverse impact of lost
revenue.
Table 37. Program Cost-Effectiveness Summa for 2009-2010 Evaluated NTG
Table 38 and Table 39 show the program's cost-effectiveness in 2009 and 2010, respectively,
with the evaluated NTG.
Table 38.Cost-Effectiveness Summ for 2009 (Evaluated NTG
-Lifecycle revenue impact defined as the change in dollars per kWh over the program's lifetime.
Total Resource + Conservation Adder
Total Resource No Adder
Total Resource + Conservation Adder
Total Resource No Adder
The Cadrnus Group, lnc. i Energy Services 46
Rocky Mountain Power ldahs Evaluation 2009-2010 Report
Rocky Mountain Po\ rer
Exhibit No. 5 Page 562 of 1365
Case No. PAC-E-14-07
#ts?li'{F$T,"2UT?
Table 39.Cost-Effectiveness for 2010 (Evaluated NTG
The Cadmus Group, lnc. i Energy Services
Rocky Mountain Power ldal'lo Evaluation 2CI0$-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 563 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasFebruary 3, 2012
AppendixA: Participant Demographics
Over 92 percent of SYLR program
Roughly 98 percent of participants
home types and home ownership.
participants lived in single-family homes or mobile homes.
owned their residences. Table 40 summarizes participant
able 40. Home Characteristics
Home Tvoe (n = 150)
Sinole-familv home 92.0%r3.6%
Townhouse or duolex 2.0o/o t1.9%
Mobile home or trailer 5.30/o t3.0%
Aoartment buildino with 4 or more units 0.70/o t1j%
Own/Rent (n = 150)
0wn 98.0%*1S%
Rent 2.0Y0 t19%
Table 41 shows average house ages, participant ages, and household sizes.
Figure 15 shows distributions of participants' ages.
Figure 15. Distributions of Participant Ages
tt%
30%
25%
fi 20o/o
!,tr
fl uu,
oG,
E toy"s
5o/o
o%
30s 40s 50s
Respondent Age
60s
Table 41. Household Characteristics
The Cadrnus Group, lnc. / Energy Services 48
E,hibitfi:YpYs'"'!H:iil'#
Case No. PAC-E-14-07
Rocky Mountain Powe_r.l_daho Evaluation20S9-2010.Reporl _..- ._*#B?'fr{illT,c2UTT
Program participants averaged 56.3 years old, with 50 percent of participants over 60 years old.
Nineteen percent of participants were in their 20s or 30s. Figure l6 shows distributions of
household sizes.
On average, three people lived in households participating in the program. Two-person
households accounted for nearly half of program participants.
49
Figure 16. Distributions of Household Sizes
50%
45%
40o/o
i tsN
i zor"
fl zsxoE 20%!**
TOYo
5%
Oo/o
Lvd-*- t% '*t% '1% I%-
4s678
Number of Residents
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclry Mountain Power
Exhibit No. 5 Page 565 of 1 365
Case No. PAC-E-14-07
#ts?tffiT,"zUT?
Appendix B: GFL Engineering Galculations and
Assumptions
Cadmus estimated CFL hours of use (HOU) using a multistate modeling approach, built on light
logger data collected from four states: Missouri, Michigan, Ohio, and Maryland. Cadmus chose
these data rather than data from the most recent California evaluation for the following reasons:
1. These states compare more favorably to Idaho in terms of latitude (a factor in seasonal
variations of daylight hours).
2. All these states have relatively new CFL programs compared to California, where
residential CFL programs have been in place for a number of years.
3. These states have a more comparable distribution of urban versus rural population (as
shown in Figure 17).
Figure 17. Urban vs. Rural Comparison between States
LA0%
90%
80%
70%
60%
s0%
40%
California HOU Sample
Ave rage
Source:2000 US Census
Metering Protocol
Following whole-house lighting audits, Cadmus installed up to five loggers in each participant
home. Metering periods varied by utility, ranging from three months to one year. For homes with
five or fewer CFL fixture groups, Cadmus field staff installed light loggers on every CFL fixture.
For homes with more than five CFL fixture groups, field staff randomly selected which five
fixtures to meter. This method relied on systematic sampling, which involved installing a logger
on every nth CFL fixture (the nft number also based on the number of totaf posibl.
CFL fixtures).
During the logger removal process, field staff collected additional data for evaluating data
quality and for determining if loggers had failed, had been tampered with, or had been removed.
Moreover, prior to removing each logger, field staff noted whether the logger had been correctly
installed and the orientation of its sensor.
N Rural
I Urban
The Cadmus Group, lnc. I Energy Services 50
Rocky Mountain Power
Exhibit No. 5 Page 566 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho Evaluation 2009-2010 Report FUS?'frffiT,"2fT?
Model Specification
To estimate HOU, Cadmus determined the total "on" time for each individual light logger per
day, using the following guidelines:
o If a light logger did not record any light for an entire day, the day's HOU was set to zero.
o If a light logger registered a light turned on at 8:30 p.m. on Monday, and turned off at
l:30 a.m. on Tuesday morning, 3.5 hours were added to Monday's HOU and 1.5 hours to
Tuesday's HOU.
Cadmus modeled both weekday and weekend daily HOU as a function of room type, the
presence of children in the home, and CFL saturations in the home. This was done using two
analyses of covariance (ANCOVA) models, one for each day type.
ANCOVA models are regression models, which model a continuous variable as a function of a
single, continuous explanatory variable (in this case, CFL saturation) and a set of binary
variables. This way, an ANCOVA model simply serves as an analysis of variance (ANOVA)
model with a continuous explanatory variable added. Cadmus chose this specification due to its
simplicity, making it suitable in a wide variety of contexts. Though the model lacks the
specificity of other methods, it offers estimates not nearly as sensitive to small differences in
explanatory variables, compared to more complex methods. Therefore, these models can produce
consistent estimates of average daily HOU for a given region, using its specific distribution of
bulbs by room and household type, and by the existing CFL saturation.
Cadmus specified final models as cross-sectional, ANCOVA regressions for day-type'' 6;, and
bulb (i), as:
Average Datly H)U i,r
= Bo * P{FL Soturationi * B2Kidsi * psKitcheni * paBasementi
* B50utdoori * B6Bedroomi * BTBathroomi I Br0theri
Where:
o CFL Saturation: the proportion of CFL bulbs in the home;
o Kids = a dummy variable22 equal to one, if the household has children under 18 living in
the home, and zero otherwise;
o Kitchen : a dummy variable equal to one, if the bulb is in the kitchen, and zero
otherwise;
o Basement : a dummy variable equal to one, if the bulb is in the basement, and zero
otherwise;
o Outdoor: a dummy variable equal to one, if the bulb is outdoors, and zero otherwise;
2r The two day-types for this analysis were weekend and weekday. Cadmus defned weekends as Saturday and
Sunday as well as the following federal recognized holidays: Christmas, Thanksgiving, Labor Day, Memorial
Day, New Year's Day, Fourth of July, Presidents' Day, and Veterans' Day.
" Dummy variables are binary, taking only values of either zero or one. Coefficients for these variables can be
interpreted as the difference in mean values between the two mutually exclusive groups.
The Cadmus Group, lnc. I Energy Services 51
Rocky fulountain Power ldaho Evaluation 200S-2010 Report
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Exhibit No. 5 Page 567 of 1365
Case No. PAC-E-14-07
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o Bedroom : a dummy variable equal to one, if the bulb is in the bedroom, and zero
otherwise;
o Bathroom : a dummy variable equal to one. if the bulb is in the bathroom. and zero
otherwise; and
o Other: a dummy variable equals to one, if the bulb is in a low-use room (such as a utility
room, laundry room, or closet), and zero otherwise.
Cadmus tested the potential influences of other demographic and regional variables in model
specifications, such as: latitude, income, education, and home characteristics.
However, these variables were not included as their estimated coefficients did not differ
significantly from zero or produced signs inconsistent with expectations.
Final Estimates and Extrapolation
As shown in Table 42, not all the two models' estimated coeffrcients difflered significantly from
zero for both day types, most likely due to differences in schedules between days. Nevertheless,
Cadmus included the same independent variables in each model for better cross comparability.
Table 42. HOU Model ANCOVA Estimates
lnterceot23 2.58 <.0001 2.90 <.0001
CFL Saturation -1.05 0.0359 -0.32 0.6657
Kids 0.80 <.0001 0.51 0.1 1 35
Kitchen '1.18 0.0001 0.35 0.4049
Basement -0.2s 0.5489 -1.50 0,0134
Outdoor 2.80 <.0001 1.46 0,1 347
Bedroom 1.10 <.0001 -2.02 <.0001
Bathroom -0.98 0.0019 -1.54 0.0025
Other -1.30 0.0071 -2,16 0.0008
P-values indicate the degree of confidence to which analysis asseds the given coefficient equals
zero. ln other words, it is the probability that the effect of a given variable on HOU is random.
Therefore, a lower p-value indicates a higher degree of confidence in the estimated effect.
Cadmus used these model parameters to predict average daily use for SYLR by taking the sum of
the product of each coefficient shown in Table 42, and its corresponding average independent
variable. Table 43 shows independent variables used for SYLR. Except for CFL saturation,
Cadmus estimated independent variables using 2009-2010 participant survey data. Due to a lack
of detailed CFL saturation data for Rocky Mountain Power's Idaho service area, Cadmus used
secondary data to estimate CFL saturations by ,oo*.'o
23 The models' intercept can be interpreted as the average HOU in the main living space (defined as the dining room,
hallways, living rooms, and office/den areas) when existing CFL saturations are zero and no children live in the
home.
'o Cadmus used an average CFL saturation for service areas with relatively new programs, taken from: Albee, K., et.
al. (2011). "One Analysis to Rule Them All and ln the Darkness Give Them CFLs." In proceedings of the 20l l
IEPEC Conference. Boston, MA: Intemational Energy Program Evaluation Conference.
The Cadrrrus Group, lnc. / Energy Services 52
Rocky Mourntain Power ldaha Evaiuation 2CISS-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 568 of 1365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasFebruary 3, 2012
Table 43. W HOU Estimation
CFL Saturation 200/o
Kids 36%
Kitchen 210h
Basement 7o/o
Outdoor 60/
Bedroom 15o/o
Bathroom 7%
Other 11Yo
nput Values
Using these values, the following equation calculateda2.6S average weekday HOU:
Average Dai'b|H,ur+
(-1.05 x 0.20 + 0.8 x 0.36 + 1.18 x0.zr+ [-0.25] *0.07 +z.B
* 0.06+ [-L.1] x 015 + [-0.98] *0.07 + [-1.3] * 0.11) -2.68
Using the same method, Cadmus calculated the weekend HOU using parameter estimates from
the weekend model. The weighted average of these two values then provided the average annual
HOU:
Precision calculations for model estimates accounted for sampling erors in model estimates and
sample inputs, which largely arose from participant surveys. Precision of individual HOU
estimates can be impacted by the precision of logger data model estimates and the accuracy of
model inputs used for extrapolation. Cadmus estimated the final relative precision for the CFL
HOU in the SYLR program to be t7 percent with 90 percent confidence.
Waste Heat Factor
The waste heat factor (WHF) is an adjustment representing interactive effects of lighting
measures on heating and cooling equipment operation. For this evaluation, Cadmus did not apply
the WHF adjustment to lighting savings estimates as Rocky Mountain Power did not include it in
their initial planning estimates. However, Cadmus recommends including this adjustment for
future planning estimates and evaluations, and therefore calculated the WHF for SYLR using the
method described below.
For use in future planning estimates and evaluations, Cadmus calculated SYLR's WHF using
ASHRAE data on heating and cooling degree days (HDD and CDD, respectively) in Rocky
53
Table 44. HOU
The Cadmus Group, lnc. I Energy $ervices
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Case No. PAC-E-14-07
Rocky hilountain Power ldaho Evaluation 2009-2010 Report #ts?t'5i$5."2UT?
Mountain Power's service territory. In addition, Cadmus used the 2006 Energy Decisions Survey
datis to determine the saturation of heating and cooling equipment types in Idaho.
To determine the portion of the year that heating or cooling equipment operates, and, therefore,
when lighting would affect heating or cooling energy consumption, Cadmus used the Northwest
Power and Conservation Council's workbook used to estimate the interactions for ENERGY
STAR lighting savings in the 6n Regional Power Plan.26 This calculator estimates the heating
and cooling interaction based on building simulation models for a variety of HVAC equipment
and cities around the region. Cadmus estimated the savings for Pocatello, as representative for
the Idaho territory, by using a weighted average of HDD and CDD from the cities across the
region to most closely match that for Pocatello. This calculator determined the heating and
cooling interactions for zonal heating and heat pumps. To estimate the interaction for electric
forced air furnaces, a heating system efficiency of 75%o (to account for duct losses) was included.
The cooling interaction from heat pumps was used for all electric cooling systems. These
interactions are provided in the table below.
These interactions are then weighted by the market share of the electric heating and cooling
systems. The heating interaction was calculated as follows:
Heating Interactton = -l{Urtrrtlnteraction * Market Share)i - -l7o/o
where the summation is across the three electric heating types. In addition, the cooling
interaction was calculated as follows:
Cooltng Interactlon : o/oSpCoollnteracti"on x Electric Cooling MarketShare - L.Bo/o
Indoor WHF = 1 * Heating Interaction * Cooling Interacti.on
- 7 _ L7o/o * L.Bo/o = 84.30/o
The combined -15.7%o adjustment could be applied to electricity savings for all interior lighting
measures to account for a net increase in electric heating and cooling load due to more efficient
lighting. Weighting for the interior/exterior distribution estimated in participant surveys,
Cadmus found the final WHF to be 85.2%o (as shown below).
WHF = 1 * (Heating Interactton* Cooltng lnteractton) xo/o Intertor Ltghting
2shfi'u:r'iwww.pacificorp.comicontent,/damipacificorpr'cloc,/Energ):-Sources,'Demanrl-Sicie-lvlanagement,/DSlv1 Voiu
mel_20I I_Studl,.pdf
26 http:llwww.nwcouncil.org/energy/powerplan/6/supplycurvesires,iEstarlighting_NewFY0gvl_0.xls
Table 45. HVAC Interactions
= l_ * (-L7o/o + t.8o/o) x 94.3o/o - B5.Zo/o
The Cadmus Group, inc. I Energy Services 54
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclq Mountain Power
Exhibit No. 5 Page 570 of '1365
Case No. PAC-E-14-07
PBts?t,lffT,"2UT?
Applying this adjustment to the evaluated gross per-unit savings estimates for energy-saving kits
yields a WHF-adjusted gross per-unit savings estimate of 63 kWh.
The Cadrnus Group, lnc. i Energy Services 55
ftocky lVlourntain Power ldaho Evaluatlot'l 200S-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 571 of l365
Case No. PAC-E-14-07
\Mtness: Kathrun C. HvmasFebruary 3. 2012
Appendix G: Precision Galculations
To determine the uncertainty level for results, Cadmus considered the effect of sampling error on
all estimates presented in the report. Sampling error refers to uncertainty introduced by the use of
sampled data to infer characteristics of the overall population. These data include survey results,
meter data, and data from secondary sources. Cadmus used sampled data to estimate parameters
for per-unit savings calculations (such as installation rates) or for the consumption of specific
equipment types (such as in billing analysis).
Sampling error has been reflected in confidence intervals about estimates. Unless otherwise
noted, Cadmus estimated intervals at 90 percent confidence; meaning one could be 90 percent
confident the true population value fell within the given interval. Cadmus calculated confidence
intervals for means, proportion, regression estimates, and any calculated values using sample
estimates as an input. Cadmus calculated all confidence intervals using standard formulae to
estimate uncertainty for proportions and means. For mean values, Cadmus used the following
formula:
Conf i.dence Intervalmean = meqn * t.645 *
Where s2 equals the sample variance, and 1.645 equals the z-score for a 90 percent confidence
interval.
In some cases, uncertainty of estimates derived from multiple sources. For example, for summed
estimates, such as those for total program savings, the root of the sum of the squared standard
erors was calculated to estimate the confidence interval:27
Conf tdence Intervalx+v = (X + y) * 7.645 x
In some cases, Cadmus multiplied estimates. For instance, net savings calculations involved
combining gross estimates with an in-service rate and/or NTG ratio estimated from participant
surveys. For these results, Cadmus calculated combined standard erors for the final estimates. In
cases where the relationship was multiplicative, Cadmus used the following formula:28
confidence rnteruatx*y = x * y + 1.64s.
Jt, (#) . r, (*) . (#) (#)
27 This approach to aggregation errors follows methods outlined in Appendix D from Schiller, Steven et. al.
"National Action Plan for Energy Efficiency". Model Enerry Efficiency Program Impact Evaluation Guide.
2007. lv*'w.epa. gol:,/eeactionplan.
28 Derived from Goodman, Leo, "The Variance of the Product of K Random Variables," Journal of the American
Statistical Association. I 962.
(#) .(#)
s2
n
The Cadmus Group, lnc. i Energy Services 56
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclq Mountain Power
Exhibit No. 5 Page 572 of 1 365
Case No. PAC-E-14-07
CBts?'fiffi5,"2UTT
In some cases, a ratio of two estimates was required. An example would be estimating the
spillover ratio, expressed as the ratio of spillover savings to program savings. For this
calculation, Cadmus used the following formula:2e
xxConftdence Intervalx /t = V + L6aS * V
To ensure transparency of the error aggregation process, Cadmus reported precision for both
individual and combined estimates, where relevant.
'e This formula assumes no covariance. Stuart, A. and Ord, J. Kendall's Advanced Theory of Statistics (6th Edition).
Edward Arnold. 1998.
/s2x\ /s2r\
\""),\"?)
Y2 v2
The Cadmus Group, lnc. I Energy $ervices 57
Rocky Mountain Power ldaho Evaluation 200S-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 573 of 1 365
Case No. PAC-E-14-07
#ts?'frffiT."2UT?
Appendix D: Participant Suruey Instrument
Rocky Mountain Power
See Ya Later Refrigerator Program 2009-2010
Participant Survey
!ntroduction
[TO RESPONDENT]: Hello, my name is [INSERT FIRST NAME] from Discovery Research Group. I'm calling
on behalf of [UTILITY]. I am calling to ask you some survey questions about the See ya later, Refrigerator
recycling program.
[rF RESPONDENT EXPRESSES RESERVATTONS AT THIS POINT, USE THE FOttOWtNG SCRTPT TO
PERSUADE. !F RESPONDENT DOES NOT EXPRESS RESERVATTONS SKrp TO Sll:
l'm not selling anything, we are interested in your opinions to help improve our programs, and
understand how to assist customers in saving money on their utility bills. Your responses will remain
confidential.
Screening Questions
51. According to our records, someone in your household signed up to recycle an appliance through
the [UTILITY] "See ya Later, Refrigerator" program. Are you that person?
1. Yes
2. No
-98. DON',T KNOW [TERMINATE]
-99. REFUSED [TERMTNATE]
52. [ASK lF S1=2] ls that person available to speak with?
7. Yes [CONTINUE WITH NEW RESPONDENTI
2. No [TERMINATE, ARRANGE CALLBACK lF POSSIBIE]
Measure Verification
A1. [ASK lF QUANTITY_REF>0] Program records indicate that you received an incentive for having
[INSERT QUANTITY_REF] refrigerator(s) recycled by the program around [INSERT DATE OF
PICKUP]. ls this correct?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED [TERMTNATE]
The Cadnrus Group, lnc. I Energy $ervices 58
Rocky Mountain Power
Exhibit No. 5 Page 574 of 1365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasFebruary 3. 2012Rocky Mountain Power ldaho Evaluation 200S-201CI Report
A2. [ASK IF A1=2 OR A1=98 ] How many refrigerators did you recycle through the [INSERT UTILITY]
program?
7. IRECORD]
-98. REFUSED
-99. DON'T KNOW
[lF A2=0, RECODE QUANTITY_REF=0]
A3. IASK lF QUANTITY_FRZ>0] Program records indicate that you received an incentive for having
[INSERT qUANTITY_FRZ] freezer(s) recycled by the program around [INSERT DATE OF PICKUP]. ls
this correct?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED [TERMTNATE]
A4. [ASK lF A3=2 OR A3=98] How many freezers did you recycle through the IINSERT UTILITY]
program?
L. IRECORD].98. REFUSED
-99. DON'T KNOW
[tF A4=0, RECODE qUANTIW-FRZ=0]
Awareness
81. How did you learn about the IINSERT UTILITY] appliance recycling program? IDO NOT READ LIST.
RECORD UP TO 3 RESPONSESI
7. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power/Pacific Power website
4. Other website
5. lnternet Advertising/Online Ad
6. Family/friends/word-of-mouth
7. Rocky Mountain Power/Pacific Power Representative
8. Radio
9. TV
10. Billboard/outdoor ad
11. Retailer/Store
12. Sporting event
13. Home Shows/Trade Shows
14. Appliance Recycling Contractor
15. Other [RECORD VERBATUM]
troThe Cadrnus Group, lnc. / Energy $ervices
Rocky frrlountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 575 of 1365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasFebruary 3, 2012
-98. [DO NOT READI DON'T KNOW
-99. [DO NOT READI REFUSED
82. What are the best ways for INSERT UTlttW] to inform you about energy-efficiency offerings like
the appliance recycling program? [DO NOT READ. PROMPT lF NECESSARY. RECORD UP TO THREE
RESPONSESI
1. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power website
4. Other website
5. lnternet Advertising/Online Ad
6. Family/friends/word-of-mouth
7. Rocky Mountain Power Representative
8. Radio
9.TV
10. Billboard/outdoor ad
11. Retailer/Store
12. Sporting event
13. Home Shows/Trade Shows
L4. Appliance Recycling Contractor
15. E-mailfrom Rocky Mountain Power
16. Other [RECORD VERBATUMI
-98, DON'T KNOW
-99. REFUSED
83. How would you rate your current understanding of energy-efficiency? Would you say you... [READ
LrsT. RECORD FrRST RESPONSEI
1.. Have no knowledge of energy-efficiency
2. Are somewhat knowledgeable about energy-efficiency
3. Are very knowledgeable about energy-efficiency
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
Appliance Description
llF QUANTITY-REF=0, SKIP TO H4I
H1. IASK !F QUANTITY_REF=1AND QUANTITY_FRZ=0] When you decided to get rid of the refrigerator,
were you using it as your main refrigerator, or had it been a secondary or spare?
[!F RESPONDENT lS UNSURE: "A main refrigerator is typically in the kitchen, and a spare refrigerator is
usually in the garage or basement and might not be in use all the time."]
60The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 576 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho Evaluation 2009-2010 Report #ts?'m{ffT."2UT?
L. Main
2. Secondary or Spare
-98. DON'T KNOW
-99. REFUSED
[ASK lF QUANTITY_REF>1, OR lF QUANTITY_REF>=1AND QUANITITY_FRZ>OIThe next few
questions focus on just one appliance. Since you recycled more than one refrigerator through the
program, please answer these questions about the first refrigerator you recycled.
H2a. Can you please tell me if this first appliance was a refrigerator or a freezer?
L. Refrigerator
2. Freezer
-98. DON'T KNOW
-99. REFUSED
H2.During the time just before you decided to get rid of this refrigerator, was it being used as your main
refrigerator, or had it been a secondary or spare?
[F RESPONDENT !S UNSURE: "A main refrigerator is typically in the kitchen, and a spare refrigerator is
usually in the garage or basement and might not be in use al! the time."l
1. Main
2. Secondary or Spare
.98. DON'T KNOW
-99. REFUSED
H3. [ASK lF H1=2 OR H2=21How long were you using it as a spare before you recycled it through the
program?
1. [RECORD VATUE rN MONTHS. rF RESPONDENT ANSWERS rN YEARS, MUITIPIY BY 12 AND
RECORD VALUE rN MONTHSI
-98. DON'T KNOW
-99. REFUSED
H4. [lF QUANTITY_REF=0, AND QUANTITY_FRZ>1, SAY: "The next few questions focus on just one
appliance. Since you recycled more than one freezer through the program, please answer these
questions about the first freezer you recycled."] During the year before you recycled it, was the
appliance plugged in and running... [READ LISTI
7. Allthe time
2. For special occasions only
3. During certain months of the year only
4. Never plugged in or running
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
The Cadrnus Group, lnc. / Energy Services 61
Rocky Mountain Power ldahCI Evaiuation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 577 of 1 365
Case No. PAC-E-1447
CBt?t#ffT,'2UT?
H5. [ASK lF H4=2 OR H4=3] lf you were to add up the total time it was running as a spare in the last
year before you recycled it, how many months would that be? [lF RESPONDENT lS UNSURE: 'Your
best estimate is okay."l
1. [RECORD MONTHS 1-121
-98. DON'T KNOW
-99. REFUSED
H6. Where was the UNSERT APPLIANCE TYPET located during most of the year before you recycled it?
1. Kitchen
2. Garage
3. Porch/Patio
4. Basement
5. Yard/Outside
6. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
H7. Was the location heated?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H8. Was the location air-conditioned?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H9. Would you say the IINSERT APPLIANCE WPEI you recycled... IREAD tlST. RECORD FIRST
RESPONSEI
1. Worked and was in good physical condition
2. Worked but needed minor repairs
3. Worked but had some major problems
4. Didn't work
-98. [DO NOT READ]DON'T KNOW
-99. [DO NOT READIREFUSED
The Cadmus Group, lnc. i Energy Services 62
Rocky Mountain Power
Exhibit No. 5 Page 578 of 1 365
Case No. PAC-E-14-07
Rocky f$ountain Fower ldaho Evaluation 2009-2010 Report
H10. Did you get a new INSERT APPLIANCE TYPE] to replace the one you recycled?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H11. [ASK lF H10=21 Do you plan to get a replacement appliance in the near future?
1. Yes
2. No
.98. DON'T KNOW
-99. REFUSED
H12. [ASK lF H10=1] Would you have purchased the new [INSERT APPIIANCE TYPE] without the S30
incentive you received for recycling the old one?
1,. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H13. [F H10=1AND H12=2] Just to confirm: you would 4! have replaced your old INSERT APPLIANCE
TYPEI without the INSERT UTILITY] incentive for recycling, is that correct?
1,. Correct
2. lncorrect
-98. DON'T KNOW
-99. REFUSED
H14. ls the INSERT APPIIANCE TYPE] you replaced it with an ENERGY STAR or high efficiency model?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H15. Had you already considered getting rid of this INSERT APPLIANCE TYPE] before hearing about
[! NSERT UTtLITYI's a ppl ia nce recycl i ng progra m?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
Wtnes: Kethrun C. HvmasFebruary 3. 2012
The Cadmus Group, lnc. i Energy Services 63
Rocky Mountain Power
Exhibit No. 5 Page 579 of 1 365
Case No. PAC-E-14-07
Rocky tulountain Power ldaho Evaluation 2009-2010 Report #ts?i-{ilT,"2UT?
Hl6.Without the [INSERT UTltlTYl refrigerator recycling program, what would you most likely have
done with your old IINSERT APPLIANCE TYPEI? Would you have... [READ tlsTl
L. Gotten rid of it
2. Kept it
-98. IDO NOT READI DON',T KNOW
-99. IDO NOT READI REFUSED
H17. [ASK H17=U Would you have gotten rid of it within a year of when the program took it, or more
than a year later?
1. Within a year of when the program took it
2. More than a year later
-98. DON'T KNOW
-99. REFUSED
H18. [ASK H15=2] lf you had kept it, would you have used itfulltime, stored it unplugged, or used it
occasionally?
7. Used fulltime
2. Stored it unplugged
3. Used it occasionally
-98. DON'T KNOW
-99. REFUSED
Consideration of Alternatives & Freeridership
Now I have a few questions about the different options you might have considered before recycling your
appliance.
F1. Did you seriously consider selling it to someone through an ad or to someone you know?
1,. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
F2. Did you seriously consider selling it to a used appliance dealer?
1.. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
The Cadrnu$ Group, lnc. i Energy Services 64
Rocky [\ilountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Po rer
Exhibit No. 5 Page 580 of 1 365
Case No. PAC-E-14-07
#ts"im{fyT."2UT?
F4.
F5.
F6.
F7,
F8.
F3. Did you seriously consider giving it away to someone for free?
7. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
Did you seriously consider giving it away to a charity organization, such as Goodwill, [F STATE = UT,
lD, SAY "Deseret lndustries"] or a church?
1. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
Did you seriously consider having it removed by the dealer you got your new or replacement
appliance from?
L. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
Did you seriously consider hauling it to the dump yourself?
1. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
Did you seriously consider hauling it to a recycling center yourself and paying the disposal fee?
1. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
Did you seriously consider hiring someone else to haul it away for junking or dumping?
1. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. i Energy Services 65
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclry Mountain Power
Exhibit No. 5 Page 581 of 1 355
Case No. PAC-E-14-07
#ts?'fi,1i$T,"2UT?
F9. Did you seriously consider keeping it?
1. Yes - considered
2. No - did not consider or did not know about
-98. DON'T KNOW
-99. REFUSED
F10. Did you consider any other ways of getting rid of your INSERT APPLIANCE TYPEI that I haven't
mentioned?
1. Yes [RECORD VERBATTM]
2. No
-98. DON'T KNOW
-99. REFUSED
FL1. [ASK lF F1=1 OR F2=1] Why did you not follow through with your consideration to sell the [INSERT
APPTTANCE TYPEI?
1. Couldn't find an interested buyer
2. Decided recycling unit was more important than selling it
3. Other [RECORD VERBATTM]
-98. DON'T KNOW
.99. REFUSED
F12. [ASK lF F5=1] lf an appliance dealer were to take it away,
would have to pay for this service?
7. Nothing/Free Service
2. [RECORD AMOUNT]
-98. DON'T KNOW
-99. REFUSED
how much, if anything, do you think you
F13. [ASKtFFS=Ulf youweretohiresomeoneelsetohaulitawayforjunkingordumping,howmuch,if
anything, do you think you would have to pay for this service?
t. Nothing/Free Service
2. [RECORD AMOUNT]
-98. DON'T KNOW
-99. REFUSED
F14. IASK lF F6=1 or F7=tlYou mentioned earlier that you considered hauling the IINSERT APPLIANCE
TYPEI to the dump or recycling center yourself. Do you have the ability to do this or would you
have needed assistance such as renting or borrowing a truck?
The Cadmus Group, lnc. / Energy Services 66
Rocky [\llountain Power ldaho Evaluation 200S-2010 Report
Roclry Mountain Power
Exhibit No. 5 Page 582 of 1 365
Case No. PAC-E-14-07
C8ts"fiffiT,"2BTI
1. Yes, could do it myself
2. Would need assistance
-98. DON'T KNOW
-99. REFUSED
F15. [ASK lF F6=1 or F7=Ll Most dumps and recycling centers charge a fee of at least S25 to dispose of a
refrigerator or freezer. Were you aware that you would have to pay a fee??
1. Yes, I would have paid the fee
2. No, I wouldn't pay
-98. DON'T KNOW
-99. REFUSED
F16. IASK F3=1 or F4=1] You mentioned that you considered giving the [tNSERT APPLIANCE TYPE] away.
Did you identify and contact a specific person or charity to give the [INSERT APPLIANCE TYPE] to?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
F17. Now that we have talked about various ways you could have gotten rid of your INSERT APPLIANCE
TYPE], what do you really think you would have most likely done with it without the [INSERT
UTIIITYI program? IREAD LIST ONLY IF NEEDED]
L. Sold it to a private party, either by running an ad or to someone you know
2. Sold it to an used appliance dealer
3. Given it away to a private party, such as a friend or neighbor
4. Given it away to a charity organization, such as Goodwill lndustries or a church
5. Had it removed by the dealer you got your new or replacement appliance from
6. Hauled it to the dump yourself and pay the disposal fee
7. Hauled to a recycling center yourself and pay the disposal fee
8. Had someone else pick it up for junking or dumping
9. Kept it
10. Some other way IRECORD VERBATTM]
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ]REFUSED
F18. What is the main reason you chose the flNSERT UTILIW] program over other methods of disposing
of your appliance? [DO NOT READ. RECORD ONLY ONE RESPONSE]
The Cadmus Group, lnc. / Energy Services 67
Rocky fvlountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 583 of 1 365
Case No. PAC-E-14-07
#E?'fi{ilT,"2BTT
t. Cash/incentive payment
2. Free pick-up service/others don't pick up/don't have to take it myself
3. Environmentally safe disposal/recycled/good for environment
4. Recommendation of a friend/relative
5. Recommendation of retailer/dealer
6. Utility sponsorship of the program
7. Easy way/convenient
8. Never heard of any others/only one I know of
9. Other [RECORD VERBATIMI
-98. DON'T KNOW
-99. REFUSED
F19. Would you have participated in the program without the incentive check?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
CFL INSTALLATION
E1. Was a free kit containing CFL light bulbs and energy information given to you at the time of pickup?
t. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
[rF E1<>1 SKIP TO SPll
E2. How would you rate the information found in this kit? Would you say it was... IREAD tlST]
1. Very helpful
Z. Somewhat helpful
3. Not very helpful
4. Not at all helpful
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
E3. [ASK lF E2<>98 Or E2<>99] Why did you assign this rating? [DO NOT READ LIST. RECORD
MUTTTPTEI
t. lnformation too general
2. Already aware of information
3. lnformation did not apply
4. Used the suggestions provided in information
5. Written well
68The Cadrnus Group, lnc. i Energy Services
Rocky Mountain Power ldaho Evaluation 2009-201CI Report
Rocky Mountain Por/er
Exhibit No. 5 Page 584 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathrun C. HvmasFebruaf 3. 2012
E5.
6. Passed information along to others
7. Other [RECORD VERBATIM]
-98. DON'T KNOW
-99. REFUSED
E4. How many of the CFLs that came in the kit did you install?
L. None
2. One
3. Two
3. Other [RECORD]
-98. DON'T KNOW
.99. REFUSED
[ASK !F E4=1 OR E4=21 Why didn't you install [lF E4=1, "them?" lF E4=2, 'the other CFt?" [DO NOT
READ LIST. RECORD MULTTPLEI
7. Did not fit fixtures
2. Intend to install later
3. Do not like style
4. Do not like quality
5. Defective product
6. Other [RECORD VERBATIM]
.98. DON'T KNOW
-99. REFUSED
[AsK lF E4=2 OR E4=3] Where did you install the CFL(s)? [DO NOT READ. RECORD UP TO TWO]
1. Living room
2. Master bedroom
3. Other bedroom
4. Kitchen
5. Bathroom
6. Garage/storage
7. Outside
8. Closet
9. Hallway
10. Other [RECORD VERBATIM]
-98. DON'T KNOW
-99. REFUSED
E6.
69The Cadmus Group, lnc. I Energy Service$
Rocky Mountain Power ldaho Evaluation 2009*2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 585 of 1365
Case No. PAC-E-14-07
#ts?'frffiT,"aHTT
E7. Did you install the refrigerator thermometer included in your energy-saving kit?
L. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
[lF E7=1, ASK E8. ELSE, SKIP TO E9l
E8. After installing the thermometer, did you change the temperature setting on your refrigerator?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
E9. Do you remember receiving a booklet with information about how to save energy?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
[F E9=1, ASK E10, EISE SKIP TO SPU
E10. Have you followed any of the advice mentioned in the booklet? lf so, which ones?
t. Yes, [RECORD VERBATIMI
2. No
-98. DON'T KNOW
-99. REFUSED
Spillover and Market lmpact
SP1. Since participating in the appliance recycling program, have you participated in any other incentive
programs offered by [INSERT UTILITYI?
t. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
SP2. IASK SPI=U Which programs did you participate in?
1. [RECORD VERBATIM]
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. i Energy Services 70
Roclry Mountain Power
Exhibit No. 5 Page 586 of I 365
Case No. PAC-E-14-07
#ts?t5ffS,"aUT?Rocky fulountain Power ldaho Evaluation 2009-2010 Report
SP3. [ASK SP1=1lHow influential was the recycling program in your decision to participate in other
INSERT UTILITY] energy efficiency programs? Would you say it was... [READ tlST]
1. Very influential
2. Somewhat influential
3. Not very influential
4. Not at all influential
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
SP4. [ASK !F SP1=21 Based on your experience in recycling your appliance, how likely are you to
participate in another utility energy efficiency program? Would you say you are... [READ LIST]
1. Much more likely
2. Somewhat more likely
3. No more or less likely
4. Less likely to participate in another program
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
SP5. Besides recycling your old IAPPLIANCE TYPE], have you made other energy efficiency
improvements or purchases on your own without any assistance from a utility or other energy
organization?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
SP6. [ASK !F F5=1] What did you install? [DO NOT READ. RECORD MULTIPLEI
1. High efficiency dishwasher
2. High efficiency washer
3. High efficiency dryer
4. High efficiency refrigerator
5. High efficiency water heater
6. CFLs (Compact Fluorescent Light bulbs or curly bulbs)
7. Other [RECORD VERBATIMI
-98. DON'T KNOW
-99. REFUSED
SP7. IASK tF F5=UHow much did your experience with the See ya later, refrigerator program influence
your decision to install other high efficiency equipment on your own? Would you say it was...
IREAD USTI
The Cadmus Group, lnc. i Energy Services 71
Rocky Mountain Power
Exhibit No, 5 Page 587 of 1 365
Case No. PAC-E-14-07
PBts?t#T,"2UT?Rocky Mountain Power ldaho Evaluation 2009-2010 Report
1. Very influential
2. Somewhat influential
3. Not very influential
4. Not at all influential
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READI REFUSED
Program Satisfaction
G1. How satisfied are you with the INSERT UTILITY] Appliance Recycling Program overall? Would you
say you are... [READ tlST]
1. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
c2. [ASK lF G7.=2,3, or 4] Why do you give it that rating? [DO NOT READ. RECORD MULTIPLE]
1. lncentive was too small.
2. Contractor never called me back.
3. Contractor never showed up/showed up late.
4. Contractor was unreliable/unprofessional.
5. Difficult to get an appointment time that was convenient for me.
6. Wanted to use a different [non-program] contractor.
7. Other [RECORD VERBATIM]
-98. DON'T KNOW
-99. REFUSED
G3. How satisfied are you with the sign-up process for the program? Would you say you are... IREAD
LrsTI
1. Very satisfied
2. Somewhat satisfied
3. Somewhat dissatisfied
4. Very dissatisfied
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
The Cadrnus Group, lnc. I Energy Services 72
Roclq Mountain Power
Exhibit No. 5 Page 588 of 1 365
Case No. PAC-E-14-O7
Rocky Mountain Power ldaho Evaluation 2009-2010 Report flS?'i-ffT,"2UT?
G4. How easy was it to schedule a convenient pickup time? Would you say it was... [READ LIST]
t. Veryeasy
2. Somewhat easy
3. Somewhat difficult
4. Very difficult
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
G5. How satisfied are you with the appliance pick-up portion of the program? Would you say you are...
IREAD LISTI
1. Very satisfied
2. Somewhat satisfied
3. Somewhat dissatisfied
4. Very dissatisfied
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READI REFUSED
G6. Did the crew that picked up your appliance check to see if it was working before they took it away?
7. Yes
2. No
-98. DON'T KNOW
.99. REFUSED
G7. How satisfied are you with how quickly you received your incentive? Would you say you are...
IREAD USTI
1. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. [DO NOT READI DON',T KNOW
-99. IDO NOT READ] REFUSED
G8. How satisfied are you with the amount of the incentive? Would you say you are... IREAD LIST]
1. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
73The Cadrnus Group, lnc. i Energy Services
Roclry Mountain Power
Exhibit No. 5 Page 589 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho Hvaluation 2CI09-2010 Report dBts?"fifrT$."2HT?
G9. Would you have participated in the program if the amount of the incentive had been less?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
G10. How likely are you to recommend the INSERT UTILIW] Appliance Recycling Program to friends and
family members? Would you say you are... [READ LIST]
1. Very likely
2. Somewhat likely
3. Not very likely
4. Not at all likely
-98. IDO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
G11. ls there anything you would suggest to improve the [INSERT UTILITY] Appliance Recycling
Program?
1. IRECORD VERBATIM]
-98. DON'T KNOW
-99. REFUSED
Demographics
I have just a few more questions about your household. Again, all your answers will be strictly
confidential.
D1. Which of the following best describes your house? [READ tlSTl:
t. Single-family home
2. Townhouse or duplex
3. Mobile home or trailer
4. Apartment building with 4 or more units
5. Other [RECORD]
-98. [DO NOT READI REFUSED
-99. [DO NOT READI DON',T KNOW
D2. Do you rent or own your home?
1. Own
2. Rent
3. Other [RECORD]
-98. REFUSED
-99. DON'T KNOW
The Cadrnus Group, inc. / Energy Services 74
Rocky Mountiain Power
Exhibit No. 5 Page 590 of 1365
Case No. PAC-E-14-07
#ts?'i5ilT,"2UT?Rocky klountain Power ldaho Evaluation 2009-2010 Report
D3. How long have you lived at that location?
1. Less than one year
2. 2-5 years
3. More than 5 years
-98. REFUSED
-99. DON'T KNOW
D4. lncluding yourself and any children, how many people currently live in your home?
1. [RECORD]
-98. REFUSED
-99. DON'T KNOW
D5. Can you please tell me in what year you were born?
1. [RECORD]
-98. REFUSED
-99. DON'T KNOW
D6. ln 2010, was your pre-tax household income above or below 550,000?
7. Below S50,0002. Above 550,0003. Exactly 550,000
-98. DON',T KNOW ISKIP TO CU
-es. REFUSED [SK|P TO C1]
D7. [ASK lF D6=1] Which of the following categories best represents your household income in 2010?
Please stop me when I read your category:
t. Under S10,0002. Slo,ooo to under S2o,ooo3. 52o,oooto under S3o,00o4. S3o,o00 to under S4o,oo0
5. 540,000 to under 550,000
-98. REFUSED
-99. DON'T KNOW
D8. [ASK lF D5=2] Which of the following categories best represents your household income in 2010?
Please stop me when I read your category:
L. 550,000 to under 560,000
2. 560,000 to under 575,0003. 575,000 to under Sloo,ooo4. S100,000 to under S15o,ooo
5. S150,000 to under 5200,0006. S2oo,ooo or more
-98. REFUSED
.99. DON'T KNOW
The Cadmus Group, lnc. I Energy $ervices 75
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountiain Power
Exhibit No. 5 Page 591 of 1 365
Case No. PAC-E-'14-07
#ts?tff-J."2UT?
c1.
c2.
Conclusion
How satisfied are you with the service that [INSERT UTltlTY] provides overall? Would you say you
are... [READ LIST]
1. Very satisfied
2. Somewhat satisfied
3. Somewhat dissatisfied
4. Very dissatisfied
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
Do you have any additional feedback or comments?
1. Yes [RECORD VERBATUM]
2. No
-98. REFUSED
-99. DON'T KNOW
That concludes the survey. Thank you very much for your time and feedback.
The Cadnrus Group, lnc. / Energy $ervices 76
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 592 of 1 365
Case No. PAC-E-I4-07
Wtness: Kathryn C. HvmasFebruary 3. 2012
Appendix E: Nonparticipant Suruey Instrument
Rocky Mountain Power
See Ya Later Refrigerator Program 2009-2010
Nonparticipant Survey
lntroduction
[TO RESPONDENT]: Hello, my name is INSERT FTRST NAME] from Discovery Research Group. l'm calling
on behalf of [UTltlTYl. I am calling to ask you some survey questions that will help [UTILITY] improve
their energy-efficiency programs.
lrF RESPONDENT EXPRESSES RESERVATIONS AT THIS PO|NT, USE THE FOttOWtNG SCRTPT TO
PERSUADE. tF RESPONDENT DOES NOT EXPRESS RESERVATTONS SKIP TO S1l:
l'm not selling anything, we are interested in your opinions to help improve our programs, and
understand how to assist customers in saving money on their utility bills. Your responses will remain
confidential.
S. Screening Questions
51. Did you discard a refrigerator or freezer in 2009 or 2010? By discard, we mean getting rid of it either
by selling it, giving it away, having someone pick it up, or taking it to the dump or a recycling center.
1. Yes, refrigerator(s)
2. Yes, freezer(s)
3. Yes, both appliances
4. No [TERMINATE]
-98. Don't know [TERMINATE]
-99. Refused [TERMINATE]
52. Did the appliance(s)work? [F RESPONDENT lS UNSURE, SAY: "Even if it didn't get cold, did the
appliance turn on when it was plugged in?"1
L. Yes
2. No [TERMINATE]
-98. Don't know [TERMINATEI
-99. Refused [TERMINATEI
53. Did you have the appliance(s) picked up through INSERT UTtLtTY]'s See Ya Later, Refrigerator
program?
The Cadmus Group, lnc. i Energy Services 77
Rocky [tilountain Power ldaho Evaluation 2009*2010 Report
Rocky Mountain Power
Exhibit No. 5 Page 593 of 1365
Case No. PAC-E-14-07
#ts?i{FyT."2UT?
7. Yes [TERMINATE]
2. No
-98. Don't know [TERMTNATE]
-99. Refused [TERMINATE]
54. [INSERT UTILITYI offers an incentive to pick up and recycle old working refrigerators and freezers. A
contractor would have picked the appliance up at your home and you would have been paid S30 later in
the mail. Are you sure your appliance wasn't picked up by the utility program?
t. Yes, l'm sure it wasn't picked up by the program or I received no incentive
2. No, I did get the incentive check [TERMINATE]
-98.1 still don't know for sure [TERMINATE]
-99. Refused [TERMINATE]
[TERMINATION SCRIPT: "Those are all the questions we have for you. Thank you very much for your
time."l
N. Nonparticipant Awareness
N1. Were you aware of the INSERT UTILITYI appliance recycling program prior to getting rid of your
appliance?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
[lF N1=1, ASK N2, EISE SKIP TO N4]
N2. How did you learn about the [INSERT UTIIITYI appliance recycling program? [DO NOT READ LIST.
RECORD UP TO 3 RESPONSESI
1. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power website
4. Other website
5. lnternet Advertising/Online Ad
6. Family/friends/word-of-mouth
7. Rocky Mountain Power Representative
8. Radio
9. TV
10. Billboard/outdoor ad
11. Retailer/Store
12. Sporting event
13. Home Shows/Trade Shows
14. Appliance Recycling Contractor
15. Other [RECORD VERBATIM]
15. Postcard
The Cadrnus Group, Inc. i Energy Services 78
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclry Mountain Power
Exhibit No. 5 Page 594 of 1 365
Case No. PAC-E-14-07
CBE?'fi{ilT,'zUT?
17. Direct mail
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
N3. What made you decide not to have your appliance picked up through the [INSERT UTILITYI
appliance recycling program? [DO NOT READ. RECORD UP TO THREE RESPONSES.I
1. Unit didn't qualify
2. Did not know how to sign up
3. Was not able to schedule convenient pickup time
4. Too much hassle
5. Other IRECORD VERBATUMI
-98. DON'T KNOW
-99. REFUSED
N4. What are the best ways for INSERT UTILIW] to inform you about energy-efficiency offerings like
the appliance recycling program? [DO NOT READ. PROMPT lF NECESSARY. RECORD UP TO THREE
RESPONSESI
1. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power website
4. Other website
5. lnternet Advertising/Online Ad
6. Family/friends/word-of-mouth
7. Rocky Mountain Power Representative
8. Radio
9. TV
10. Billboard/outdoor ad
11. Retailer/Store
12. Sporting event
13. Home Shows/Trade Shows
14. Appliance Recycling Contractor
15. E-mail from Rocky Mountain Power/Pacific Power
16. Other [RECORD VERBATUM]
17. Postcard
18. Direct mail
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. / Energy Services 79
Rocky Mountain Power ldaho Evaluation 2009-2010 Report
Roclry Mountain Power
Exhibit No. 5 Page 595 of '1365
Case No. PAC-E-14-07
CBts"fi{ffT,"2tT?
N5. How would you rate your current understanding of energy-efficiency? Would you say you... [READ
rtsT. REcoRD FrRST RESPONSEI
1. Have no knowledge of energy-efficiency
2. Are somewhat knowledgeable about energy-efficiency
3. Are very knowledgeable about energy-efficiency
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
A. Appliance Characteristics
[lF MORE THAN ONE APPLIANCE DISCARDED, SAY:I For the rest of the survey, l'd like you to focus on
only one of the appliances you got r:id of. Please answer these questions about the appliance you
discarded most recently.
A1. At the time you discarded it, approximately how old was the appliance?
[RECORD AGE IN YEARS]
-98.Don't know
-99. Refused
A2. Before you made the decision to get rid of the appliance, in what room was the appliance
used/located?
L. Kitchen
2. Garage
3. Porch/patio
4. Basement
5. Other ISPECIFYI
-98.Don't know
-99. Refused
43. Would you say the appliance ...? [READ LIST, RECORD ONLY ONE RESPONSE]
7. Worked and was in good physical condition
2. Worked but needed minor repairs
3. Worked but had some major problems
-98.[DO NOT READ]Don't know
-99. [DO NOT READ]Refused
80The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page595 of 1365
Case No. PAC-E-14-07
CBts?'fi5F$T,"2tsTIRocky Mountain Power ldaho Evaluation 2009-2010 Report
44. Did you get a new appliance to replace the one you got rid of?
1. Yes
2. No
-98. Don't know
-99. Refused
UF A4=1, ASK 45. ELSE SKIP TO A6l
A5. ls the appliance you replaced it with an ENERGY STAR or high efficiency model?
1. Yes
2. No
-98. Don't know
-99. Refused
A5. How did you get rid of your old appliance? [!F NEEDED, PROMPT: "For example, did you sell it or
give it away?"1
1. Sold it to a private party, either by running an ad or to someone you know
2. Sold it to an used appliance dealer
3. Gave it away to a private party, such as a friend or neighbor
4. Gave it away to a charity organization, such as Goodwill lndustries or a church
5. Had it removed by the dealer you got your new or replacement appliance from
6. Hauled it to the dump yourself
7. Hauled to a recycling center yourself
8. Had someone else pick it up for junking or dumping
9. Kept it
10. Some other way [RECORD VERBATIM]
-98.Don't know
-99. Refused
Demographics
D1. Which of the following best describes your house? [READ LIST]:
1. Single-family home
2. Townhouse or duplex
3. Mobile home or trailer
4. Apartment building with 4 or more units
5. Other [RECORD]
-98. [DO NOT READJ REFUSED
-99. [DO NOT READI DON',T KNOW
The Cadrnus Group, lnc. / Energy Services 81
Rocky Mountain Power
Exhibit No. 5 Page 597 of '1365
Case No. PAC-E-14-07
CgB"im$i$T,'2UT?Rocky tu'lountain Power ldaho Evaiuation 200S-2010 Report
D2. Do you rent or own your home?
1. Own
2. Rent
3. Other IRECORD]
-98. REFUSED
-99. DON'T KNOW
D3. How long have you lived at that location?
1. Less than one year
2. 2-5 years
3. More than 5 years
-98. REFUSED
-99. DON'T KNOW
D4. lncluding yourself and any children, how many people currently live in your home?
1. [RECORDI
-98. REFUSED
-99. DON'T KNOW
D5. Can you please tell me in what year you were born?
1.. IRECORD]
-98. REFUSED
-99. DON'T KNOW
D6. ln 2010, was your pre-tax household income above or below 550,000?
1. Below 550,0002. Above 550,0003. Exactly S5o,ooo
-98. DON',T KNOW [SKIP TO CU
-99. REFUSED [SK|P TO C1]
D7. [ASK lF D5=U Which of the following categories best represents your household income in 2010?
Please stop me when I read your category:
1. Under $10,0002. SLo,ooo to under S2o,ooo3. 520,000 to under Seo,ooo4. Sg0,0oo to under S4o,o0o
5. S4o,ooo to under S5o,ooo
-98. REFUSED
-99. DON'T KNOW
D8. [ASK lF D5=2] Which of the following categories best represents your household income in 2010?
Please stop me when I read your category:
The Cadmu$ Group, lnc. I Energy Services 82
Rocky Mountain Power ldaho Evaluation 2009-201CI Report
Rocky Mountain Power
Exhibit No. 5 Page 598 of 1 365
Case No. PAC-E-14-07
CEE?'fiffT,"zHTT
1. 550,000 to under 560,0002. 560,000 to under 575,0003. 575,000 to under 5100,0004. S100,000 to under S150,000
5. S150,000 to under 5200,0006. 5200,000 or more
-98. REFUSED
-99. DON'T KNOW
CLOSING SCRIPT: Those are all the questions we have. INSERT UTltlTYl appreciates your input. Thank
you for your time.
83The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 599 of 1 365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
I
reffiI*OUNTA*
Exhibit No. 5.9
Home Energy Savings Evaluation 2009-2010
Rocky Mountain Power
Exhibit No. 5 Page 600 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
S$rxmN Nmpmrt
ilANMUS
February 3, 2A12
$),**r.r tr.'''":-.'ri jl r:'
' r \...i\r{.ri \iir r+rJr
The Cadmus Group, lnc. i Energy Services
720 SW Washington Street, Suite 400
Portland, OR 97205
5CI3.228.2992
iir*rr*r";..\ iti'ir"r r *rvur
Rocky Mountain Power
NNN
research / into /action '"'
Rocky Mountain Power
Exhibit No. 5 Page 601 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Principal I nvestigators:
Katie Parkinson
Hossein Haeri
Jeana Swedenburg
The Cadmus Group, lnc.
Jun Suzuki
Research lnto Action, Inc
Corpqrate Headquanen:
57 \{ater Street
\Ahtenown, f'lA02.{7?
Tel:61L673^7000
Fax: [phone]
An Ernployee-Owned Compony
ur.ttn**,ldittusgr.e u p. *$ fii
720 SW Uhshington St.
Suite 400
Ponland. $R 97205
lbl: 503.1?8.2992
Faxr 503,?38.3696
E,hibitfo*YP:1""'ii*f ilfJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES Evaluation 2009-201Q Fin{..S.gg_ort February 9J9_1-1
Table of Contents
Glossary of Terms ......1
Executive Summary........... .......3
Overview of Evaluation Activities.............. ...................3
Key Findings.............. ................3
Summary and Recommendations ................7
lntroduction ....... .........9
Program Description ..................9
Evaluated Gross and Net Savings Methodology ............. ..............10
lmpact Evaluation............. ...... 18
Lighting.... ..............18
Appliances, HVAC, and Weatherization... ..................37
Process Evaluation Findings............ ... 59
Program Implementation and Delivery.... ....................59
Marketing. ..............67
Quality Assurance. ...................73
Customer Response.. ................74
Communication......... ...............78
Summary and Recommendations ..............78
Cost-Effectiveness............ ..... 85
Appendices........ ...... 89
The Cadrnus Group, lnc. I Hnergy Services
Roclry Mountain Power
Exhibit No. 5 Page 603 of I 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mqr.rntain Powelldaho HE$ .Ev?.luation 2009-20'10 .Fi!gl.ftep_ort..-.._. Febnuary 3, 2012
Glossary of Terms
Analysis of Covariance (ANCOVA)
An ANCOVA model is an ANOVA model with a continuous variable added. An ANOVA
model explains the variation in the independent variable, based on a series of characteristics
(expressed as binary variables equaling either zero or one).
Evaluated Gross Savings
Evaluated gross savings represent the total savings of a program, based on validated savings and
installations, before adjusting for behavioral effects such as freeridership or spillover. They are
most often calculated for a given measure, i, as:
Evaluated Gross Savtngsi = Verif ted Installationsi x lJnis Consumptioni
Evaluated Net Savings
Evaluated net savings are the savings "net" of what would have occurred in the program's
absence. These savings are the observed impacts attributable to the program. Net savings are
calculated as:
Net Savings = Evaluated Gross Savtngs * NTG
Freeridership
Freeridership in energy-efficiency progftlms is defined as participants who would have adopted
the energy-efficient measure in the program's absence. This is often expressed as the
freeridership rate, or the proportion of evaluated gross savings that can be classified as
freeridership.
Gross Realization Rate
The ratio of evaluated gross
administrator.
savings and the savings reported (or claimed)by the program
In-Service Rate (ISR)
The ISR (also called the installation rate) is the proportion of incented measures actually
installed.
Net-to-Gross (NTG)
The NTG ratio is the ratio of net savings to evaluated gross savings. Analytically, NTG is
defined as:
NTG - (l - Freeridership Rate) * Spillover Rate
P-Value
A p-value indicates the probability that a statistical finding might be due to chance. A p-value
less than 0.10 indicates one can say, with 90 percent confidence, that the finding was due to the
intervention.
The Cadmus Group. lnc. I Energy Services
E,h i bn'[:"YP},e"J:n:iil'g
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rojly_Yl_qgntlin Power ldaho HES Evaluation 2009*_?010.Fjnal.Rep_o1.. ....f,gbru_?y_3, _2_9Jl
Spillover
Spillover is the adoption of an energy-efficiency measure induced by the program's presence, but
not directly funded by the progam. As with freeridership, this is expressed as a fraction of
evaluated gross savings (or the spillover rate).
T-Test
In regression analysis, a t-test is applied to determine whether the estimated coefficient differs
significantly from zero. A t-test with a p-value less than 0.10 indicates that there is a 90 percent
probability that the estimated coefficient is different from zero.
The Cadmus Group, lnc. I Energy $ervices 2
.-n, on,X"l"$Yr"J;H:i ilfJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Sgcky ttrlountain Power t{aho HEE*8-y-alu$g.n.?00_9:?-?l-t-Linal [g!'q$*_-_.. _ _ [eb.nyary 3, ?012
Executive Summary
Rocky Mountain Power offers the Home Energy Savings (HES) Program in Idaho, Utah,
Wyoming, Washington, and Northern Califomia. In 2006, Rocky Mountain Power first offered
the HES Program in Idaho. The program provides residential customers with incentives to help
facilitate the purchase of energy-efficient products and services through upstream (manufacturer
and retailer) and downstream (customer) incentive mechanisms. During the 2009 and 2010
program years, Rocky Mountain Power reported 4,679,965 kWh total gross savings acquired
through the program and pafiicipation exceeded 11,000 customers. The largest of Idaho Rocky
Mountain Power's residential programs, the HES Program contributed 67 percent of residential
program savings, and 18 percent of all Idaho program savings in2009 and 2010.
The HES Program offers energy-efficiency measures in four categories:
o Lighting.' Upstream incentives for manufacturers to reduce retail prices on compact
florescent lamps (CFLs), and incentives to customers for light fixtures and ceiling fans.
. Appliances.' Customer incentives for clothes washers, dishwashers, refrigerators, and
high-effi ciency electric storage water heaters.
o Heating, ventilation, and air conditioning (HVAQ.' Customer incentives for high-
efficiency heating and cooling equipment and services, duct sealing, and evaporative
cooling equipment.
o Windows and insulation: Ctstomer incentives for attic, wall, and floor insulation, and
high-effi ciency windows.
Rocky Mountain Power contracted with The Cadmus Group, Inc., (Cadmus) to conduct process
and impact evaluations of the Idaho HES Program for program years 2009 and 2010. The impact
evaluation assessed energy impacts and program cost-effectiveness. The process evaluation
assessed: program delivery and efficacy, bottlenecks, barriers, best practices, and opportunities
for improvements. This document presents these evaluations' results.
Overview of Evaluation Activities
The HES Program evaluation consisted of primary and secondary data collection activities,
informing the impact and process evaluation components. The impact evaluation estimated two
key components: gross savings and the net-to-gross ratio (NTG). The gross savings calculations
included adjustments for the installation rate and engineering inputs. NTG-the combination of
freeridership and spillover--discounted savings from units that would have been installed in the
program's absence, and credited the program for unaccounted savings achieved through the
program's influence.
The process evaluation investigated topics such as: participant satisfaction; implementation and
delivery processes; marketing methods; quality assurance; and other qualitative issues.
Key Findings
Launched in2006, the HES Program provides incentives for 2lenergy-saving measures typically
found in residential households. Cadmus' evaluation focused on the top 10 measures, which
The tadmus Group, Inc. / Energy Seruices
E-h i bit f"TYPYsTiH:iiY#
Case No. PAC-E-14-07
Rocky Mountain-Pgwer tdaho HES Evaluation 2009-2911 flnil-tgpg$-. #t["fifr!vd,c#T]
collectively contributed to over 99 percent of HES Program savings. Cadmus collected primary
data on the top savings measures, and performed engineering reviews utilizing secondary data
for the remaining measures. In contrast to other Rocky Mountain Power territories, where CFLs
contribute the majority of savings, CFLs accounted for only 32 percent of total HES Program
savings. Insulation contributed the most to measure savings in Idaho, at 52 percent.
Key lmpact Findings
Key impact evaluation findings include the following:
. Appliances.' Incented appliances experienced a 100 percent installation rate. Evaluated
gross savings realization rates ranged from 20 percent (ceiling fans) to 185 percent (tier
two clothes washers). The HES Program's non-lighting measures had an 86 percent NTG
ratio (see Table 1).
o HVAC: Incented HVAC equipment experienced a 100 percent installation rate.
Evaluated gross savings realization rates ranged from 56 percent (heat pump upgrade) to
164 percent (heat pump conversion) due to changes in usage, home size, and fuel type
saturation assumptions input into the energy modeling software. The HES Program non-
lighting measures had an 86 percent NTG ratio estimate (see Table 1).
o Windows and Insulation: Incerfied windows and insulation experienced a 100 percent
installation rate. Evaluated gross savings realization rates ranged from 95 percent (attic
insulation) to 139 percent (windows) due to changes in assumptions regarding home size
and fuel type saturations used in energy modeling. The HES windows and insulation
measures had an 87 percent NTG ratio estimate (see Table 1).
. Lighting; Incented CFLs experienced a75 percent installation rate, based on storage and
removal practice behaviors, as reported through surveys. The HES lighting component
experienced a 103 percent evaluated gross savings realization rate and an 85 percent
NTG (see Table 1).
Table I summarizes evaluated savings estimates compared to reported values.
Throughout the report, totals in tables may not add up exactly due to rounding
-Appendix B describes the methodology for calculating precision.*'Each incented insulation or window home is counted as one unit.
Table 1.2009 and 2010 HES Program Savings*
The Cadmus Group, Inc. I Energy $ervices
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Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report February 3, 2012
Throughout the report, totals in tables may not add up exactly due to rounding.
*Appendix B describes the mehodology for calculating precision.*'Each incented insulation or window home is counted as one unit.
'Throughout the report, totals in tables may not add up exactly due to rounding.
"Appendix B describes the methodology for calculating precision.
***Each incented insulation or window home is counted as one unit.
Key Process Evaluation Findings
Key process evaluation findings include the following:
o Seventy-one percent of lighting retailers reported plans to educate consumers about
EISA, using marketing materials such as in-store displays, brochures, and flyers.
o Program staff reported "blow and go" insulation contractors negatively affected Idaho's
program, in attempting to profit off Rocky Mountain Power's generous incentives while
providing customers with poor quality work. This resulted in many upset customers, and
multiple complaints reported to the Public Utilities Commission.
o While recognizing the importance of the HES Program's quality control (QC)
process, implementer staff reported having full-time QC inspectors staffed in Idaho
did not prove cost-effective. They questioned, however, how to conduct QC
inspections within 45 days of equipment's installation without Idaho QC inspectors.
o Nearly one-third (31 percent) of insulation participants waited more than eight weeks
for their incentive checks to arrive in the mail. More than half (52 percent) expressed
dissatisfaction with this result.
o HES Program satisfaction generally ran high. All surveyed customers reported high
satisfaction levels regarding progrilm incentive amounts, purchased measures, and
overall program experiences. In fact, 94 percent of participants expressed being
"very" or "somewhat" satisfied with their overall HES Program experience.
The
Table 2.2009II8S Program Savings*
Table 3.2010 HES Program Savings*
Cadmus Group, lnc. I Energy Services
Rocky ltllountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 608 of I 365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
February 3, 2012
Cost-Effectiveness Resu lts
As shown in Table 4, the HES Program proved cost-effective across the evaluation period for
four of the five primary cost tests: the PacifiCorp total resource cost (PTRC); the total resource
cost (TRC); the participant cost (PCT); and the utility cost (UCT).
The program proved cost-effective, with relatively high benefit-to-cost ratios of 1.82 and 2.00
from the TRC and PTRC perspectives, and remained relatively stable over the two program
years. The program did not prove cost-effective from the rate impact measure (RIM) perspective,
which measures impacts of programs on customer rates. Most programs do not pass the RIM test
due to lost revenue impacts. Levelized cost per kWh, shown in Table 4, represents the present
value of program life cycle costs, divided by total energy savings produced by the program over
the lives of the measures. This metric proves useful for comparing demand-side management
(DSM) programs' energy costs with those of supply-side resources.
Table 5 and Table 6 show HES Program cost-effectiveness for the 2009 and 2010 program years,
respectively.
Table 4.2009-2010 Evaluated Net Program Cost-Effectiveness Summary*
Total Resource + Conservation Adder (PTRC)$0.063 $2,330,972 $4,660,884 $2,329,912 2.00
Total Resource No Adder (TRC)$0.063 $2,330,972 $4,237,167 $ 1 ,906,1 96 1.82
Utility (UCT)$0.040 $1,468,881 $4,237,167 $2,768,287 2.88
Ratepayer lmpact (RlM)$0.126 $4,M5,616 $4,237,167 ($408,449)0.91
Participant (PCT)$0.045 $1,900,600 $4,449,773 $2,549,173 2.34
*Savings Values used are net of freeridership and spillover effects
Table 5.2009 Evaluated Net Program Cost-Effectiveness Summary*
Total Resource + Conservation Adder (PIRC)$0.065 $783,065 $1,263,640 $480,575 1.61
Total Resource No Adder (TRC)$0.065 $783,065 $1,148,764 $365,699 1.47
Utility (UCT)$0.042 $498,348 $1,148,764 $650,416 2.31
Ratepayer lmpact (RlM)$0.1 25 $1,496,793 $1,148,764 ($348,02e)0.77
Participant (PCT)$0.M5 $629,910 $1,415,876 $785,966 2.25
tSavings Values used are net of freeridership and spillover effects
The Cadmus Group, lnc. I Energy $ervices
Table 6.2010 Evaluated Net Program Cost-Effectiveness Summary*
Total Resource + Conservation Adder (PTRC)$0.062 $1,662,452 $3,648,640 $1,986,188 2.19
Total Resource No Adder (TRC)$0.062 $1,662,452 $3,316,945 $1,654,494 2.00
Utility (UCI)$0.039 $1,042,352 $3,316,945 $2,274,593 3.18
Ratepayer lmpact (RIM)$0.1 27 $3,381,836 $3,316,945 ($64,891)0.98
Participant (PCT)$0.044 $1,30/,721 $3,258,406 $1,893,685 2.39
*Savings Values used are net of freeridership and spillover effects
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Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report February 3, 2012
Summary and Recommendations
Rocky Mountain Power implemented several changes in 2010, adjusting program operations,
delivery structures, and marketing approaches, which led to significant improvements in
participation and savings. Conclusions and recommendations presented here have been drawn
from process evaluation interviews, surveys, and other conducted analyses. While Cadmus'
process evaluation found several aspects of HES Program operations and delivery have
improved, the program may benefit from additional changes to continue to adapt to the Idaho
market as the program matures. Based on this evaluation's findings, Cadmus offers the following
observations and recommendations :
o Unlike other service territories, most Idaho lighting retailers plan to educate
customers about EISA legislation.
o Recommcndation: To support Idaho lighting retailers planning to educate customers
about EISA, Rocky Mountain Power should consider providing educational point-of-
purchase materials about EISA, framed in the context of increased availability of
utility-supported, high-efficiency lighting options. This will further aid retailers in
preparing customers for changes in lighting availability.
The EISA standard will impact Rocky Mountain Power savings anolysis of CFLs.
o Recommendation: Baseline wattage assumptions will need to be updated to
account for the new EISA standards. The EISA standard established an equivalent
baseline by rated lamp lumens. If the actual baseline wattage replaced is not
known (i.e. no surveys were conducted), the recommended approach uses the
CFL rated lumens and equivalent lumens in EISA to determine baseline wattage.
This approach can be use for program evaluations in2012 and beyond.
Rocky Mountain Power impact analysis of CFLs does not include a waste heat factor
(\YHF) in the planning estimates.
o Recommendation: Cadmus recommends using the approach outlined in Appendix
L and including this adjustment for future planning estimates and evaluations.
The Cadmus Group, lnc. I Energy Services
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Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain P.ower ldaho.HES.Eva.luation 2009-2_010 Filal Report February-*l 20.13
o Trade allies served as the program's most valuable resource to increase program
awareness. However, customer complaints resultedfrom contractor behavior, resulting
in unreliable insulation installation.
o Recommendation: Create a transparent and authentic message, describing adjusted
incentives and improved program qualification guidelines. Promote this message to
restore customer trust.
o Due to a dispersed customer community and low overall participation volumes, QC
inspections prove costly in ldaho.
o Recommcndation: Outsource the QC process to a locally-based QC firm.
Subcontracting with a locally-based firm that has viable outside work would decrease
travel costs, and eliminate concerns of maintaining a full-time staff member, who
would have idle time between installation inspections.
o In 2009 and 2010, installation contractorc may not have been completing incentive
applications in a timely manner. Installation contractors assume the responsibility
for completing incentive forms on behalf of their customers; however, one-third of
insulation customers reported waiting more than eight weeks to receive their
incentive. Recommendation: In 2010, Rocky Mountain Power decreased insulation
incentives to steer low quality contractors away from the HES Program. If these
efforts do not improve customer satisfaction regarding incentive wait times, consider
requiring installation contractors to provide incentive amounts as a deduction from
the customer's bill up front, receiving reimbursement when correctly submitting the
incentive application. This would further motivate contractors to complete and submit
incentive forms in a timely manner.
o Surveled customers reported high satisfaction levels regarding program incentives,
purchased meosures, and overall program experiences.
For more detail, please see the Summary and Recommendations in this report's Process
Evaluation Findings section.
The Cadmus Group,Inc. ,/ Energy Services
Roclry Mountain Power
Exhibit No. 5 Page 61 1 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C, Hymas
Rocky Mou.ntain Pow*ej ldaho HEE. Evalualion 2909-2010 Final Report February 3, 2CI12
lntroduction
Program Description
In 2006, Home Energy Savings GIES) launched in Idaho. Portland Energy Conservation, Inc.
(PECl/program implementer) implemented the HES Program, which provided incentives to
residential Rocky Mountain Power customers purchasing qualifuing, high-effrciency appliances
and weatherization measures. Prescriptive incentives offered included the following measures:
o Clothes washers;
o Dishwashers;
o Water heaters;
o Refrigerators;
o Insulation;
o Windows;
o Central air conditioning units;
o Evaporative coolers,
o Heat pumps;
o Duct sealingi and
o Fluorescent fixtures and ceiling fans.
To encourage dealers to promote energy-efficient equipment incentives and to properly size,
install, and maintain equipment, Rocky Mountain Power also offered dealer incentives for
quali$ing central air conditioning, duct sealing, and heat pump measures bought or installed
through the HES Program.
The HES Program included an upstream lighting component, applying incentives for eligible
compact fluorescent lamps (CFLs) at the manufacturer level, and discounting for end-use
customers purchasing high-efficiency lighting fixtures. Table 7 lists HES Program measures with
the applicable customer and dealer incentive amounts.
YThe Cadmus Group. lnc. l Energy Services
Table 7.IIES Program Incentives by Measure
Clothes Washers
Clothes Washer-Tier One fi.72 - 1.99 MEF)Units $50 $50
Clothes Washer-Tier Two (2.0 + MEF)Units $100 $1 00
Clothes Washer Recyclinq Units N/A
Dishwasher EF 0.68 or higher Units $20 $20
Electric Water Heater 40+ Gallons (EF 0.93 or hiqher)Units $50 $s0
Refrigerator ENERGY STAR Refrigerator Units $20 $20
lnsulation
Attic (R-19 +)Square Feet Up to $0.50
Floor (R-19 +)Square Feet Up to $0.50
Wall (R-11+ or fill cavity)Square Feet Up to $0.50
Electrically heated homes: Attic (R-19 +)Square Feet Up to $0.30
Electrically heated homes: Wall (R-11 +)Square Feet Up to $0.45
Electrically heated homes: Floor (R-19 +)Square Feet Up to $0.25
Electrically cooled homes: Attic (R-19 +)Square Feet Up to $0.15
Electrically heated homes: Wall (R-11 +)Square Feet Up to $0.30
Windows Eneroy efficient windows Square Feet up to $1.50 up to $1.50
Room Air Conditioner ENERGY STAR Room Air Conditioner Units $30
Evaporative Cooler Permanently lnstalled Units $100 $1 00
CentralAir
Conditioner
CAC/HP Tune up Proiects $100 $100 $25
cAc (15 SEER)Units $250 $250 $50
CAC TXV and lnstall Prolects $50 $50 $75
CAC TXV and Sizing Projects $50 $50 $2s
Duct Sealing Program Qualifi ed Contractor Projects $150 $1 50 $50
Heat Pumps Heat Pump Conversion (8.2+ HSPF)Proiects $350 $350 $25
Heat Pump Upgrade (8.2+ HSPF)Projects $250 $2s0 $25
Ceilino Fans ENERGY STAR Ceilino Fans Units $20 $20
Fixtures ENERGY STAR Fixtures Units $20 $20
CFLs CFLs-Soiral and soecialty Lamps
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Case No. PAC-E-1447
Witness: Kathryn C. Hymas
Rocky fillountain Power ldaho HE$ Evaluation 2009-2010 Final Report Februany 3,2CI1?
Evaluated Gross and Net Savings Methodology
This report presents two saving values: evaluated gross and net savings. To determine evaluated
net savings, Cadmus applied four steps to reported gross program savings (as shown in Table 8).
Reported gross savings have been defined as electricity savings (kwh) reported to Cadmus by
Rocky Mountain Power.
The Cadrnus Group. lnc. l Energy Services 10
.,n, o n nlo*IrYnT;iiliil'#
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
Rocky Nllountain Power ldaho l-iES Evaluation 2009-20'tr0 Final Repori February 3, 2012
Step one (verifu participant database) included a review of the program tracking database to
ensure participants and reported savings matched 2009 and 2010 annual reports.
Step two (perform an engineering review) included a review of measure saving assumptions,
equations, and inputs.
Step three (adjust gross savings with the installation rate) determined the number of measures
program participants installed (and remaining in installation). This value was determined through
a telephone survey, and using the installation and persistence rate (referred to as in-service rate
or ISR) in calculating evaluated gross savings.
Together, the first three steps determined evaluated gross savings. A fourth step (applying net
adjustments) determined evaluated net savings.
Cadmus' evaluation included the following data collection activities:
o Management Staff Interviews: In October 2011, Cadmus conducted an in-depth
interview with PacifiCorp's HES Program manager.
Program Partner Interviews: In October and November 2011, Cadmus interviewed
two program management staff from the program implementer, which provided
progftlm implementation, incentive processing, and verification services for the HES
Program.
Participant Telephone Survey: Cadmus conducted 380 interviews with customers
receiving incentives from Rocky Mountain Power for clothes washers, refrigerators,
dishwashers, windows, insulation, room air conditioners, fixtures, heat pumps, ceiling
fans, and electric water heaters.
Insulation Participant Verification Site Visit: Cadmus performed 72 site visits with
insulation participants, veriSing amounts, quantities, and locations of installed
insulation.
Participant Retailer/Contractor Survey: Cadmus conducted 23 intewiews with
trade allies supplying discounted CFLs, appliances, HVAC, or insulation through
HES. Many trade allies answered questions about multiple measures, resulting in 9
completed sections for lighting, 10 sections for appliances, and 11 sections for
weatherization.
In-territory Lighting Survey: Cadmus performed 250 interviews with Rocky
Mountain Power customers purchasing CFLs during the 2009 and 2010 program
years.
Table 8. Impact Steps
Validate Accuracy of Data in
Perform Engineering Review to Validate Saving Calculations
Gross Savinos with Actual lnstallation Rate
Apply Net-to-Gross (NTG) Adjustments
The Cadmus Group, lnc. I Energy Services
E-hibitf":"YPYs""'Sn:iilfJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky [t/[*untain Power ldaho HE$ Evaluation 2009*20'tr0 Final Report Febnuary 3, 2CI12
Out-of-Territory Lighting Survey (Leakage): Cadmus performed 70 intervrews
with residents outside of Rocky Mountain Power's territory, quantifuing incentivized
CFLs leaving the service territory.
Marketing Materials Review: Cadmus reviewed marketing and communications
developed to promote participation and to educate target audiences about HES
Program details. The review addressed specific marketing elements, regarding:
general look and feel; brand and message consistency; program accessibility; and
online and interactive properties.
o Appendix A provides data collection instruments.
Sample Design and Data Gollection Methods
Cadmus developed samples, seeking to achieve precision of *10 percent at the 90 percent
confidence level for individual estimates at the measure level, with sample sizes determined
assuming a coefficient of variation (CV) of 0.5.r For small population sizes, a finite population
adjustment factor was applied. Table 9 shows the final sample disposition for various data
collection activities.
For nearly all data collection, Cadmus drew samples using either simple or stratified random
sampling.2
Management and Program Partner Interviews
Cadmus interviewed a census of the Rocky Mountain Power HES Program staff and program
partners, provided by Rocky Mountain Power.
Participant Telephone Survey
Cadmus stratified the participant telephone survey (appliances, HVAC, and weatherization) by
measure to ensure statistically meaningful results for each measure.
' A measure of the dispersion of data points in a data series.
2 Simple random samples are drawn from the entire population, whereas stratified random samples are drawn
randomly from subpopulations (strata), and then weighted to extrapolate to the greater population.
Table 9. Sample Disposition for Various Data Collection Activity
lnsulation Participant Veriflcation Site Visits
ln-Tenitory Lighting Survey
Tlre Cadrnus Group. lnc. / Energy Services 1e
Rocky Mountain Power
Exhibit No. 5 Page 615 of 1 365
Case No. PAC-E-'14-07
Witness: Kathryn C. Hymas
Roc-ky-Mountatl Pcwer.l-daho F{_E*9 E_y_aluation.2009*2010 Final Report February 3, 20L.?_.
Table 10. Participant Telephone Survey Sample Sizes
Clothes Washer 2,433 69 72
CentralAC 203 52 0
Refrigerator 773 65 70
Dishwasher u4 65 75
Windows 243 55 44
Fixtures 64 34 6
Electric Water Heater 193 52 46
lnsulation 1,431 67 67
Excluded Measures 392 0 0
Totals 6,576 459 380
Four out of eight measures met survey targets, as shown in Table l0 which provides: the number
of contacts available, targets, and completed surveys. Targets not met resulted from the small
number of contacts available, despite survey best practices (e.g., multiple attempts, calls at
different times of day, calls over weekends, and scheduling call-backs). Survey targets were
initially calculated using the number of filed participants from Rocky Mountain Power's 2009
and 2010 annual reports as the program population. Due to missing phone numbers and duplicate
records, the number of eligible contacts was much smaller than the progfttm population. This
made it difficult to achieve the target number of surveys. For example, while there were 203
participants who received a Central AC measures, these participants only represented nine
unique phone numbers, making it impossible to achieve the initial target of 52 surveys.
Table 11 details the screening process, which resulted in 5,338 eligible survey participants,
drawn from 6,576, randomly selected, unique participants with Idaho mailing addresses, valid
phone numbers, and valid Rocky Mountain Power customer numbers.
. Response rate: the number of customers completing a survey, divided by the
number of eligible participants in call list.
'Cooperation rate: the number of customers completing a survey, divided by the
number of customers reached by phone.
Table 11. Participant Telephone Survey Sample
The Cadmus Group, lnc. I Energy Services 13
Rocky Mountain Power
Exhibit No. 5 Page 616 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Ro*y_..Ugu.n1?in_3>wer ldaho l-lES Evaluation 2009-2010 Final Report February 3, 2012
Insulation Participants Verification Site Visits
As shown in Table 12, Cadmus stratified sampled attic insulation participants for verification
site visits.
Table 12. Insulation Site Visit Sample Size
Attic lnsulation 1,355 67 72
Retailer/Contractor Su rveys
In nearly all cases, Cadmus drew random samples, with sampled units having equal probabilities
of being chosen. For the survey's CFL section, however, the team weighted the probability of
selecting a given retailer, based on their total CFL sales. This ensured capturing a sufficient
number of large retailers in the sample, while retaining the desired statistical properties of a
random sample.
Cadmus selected appliance and window retailers for interviews based on their products and
business types, ensuring they adequately represented the greater population. This approach,
intended solely for qualitative analysis, offered an advantage over random sampling of samples
too small to produce statistically valid estimates.
Table 13 details the screening process for eligible participants, resulting in 23 participants
randomly selected from 60 unique Idaho retailers.
Table
. Response rate: the number of customers completing a survey, divided by the
number of eligible participants in call list.* Cooperation rate: the number of customers completing a survey, divided by the
number of customers reached by phone.
14 shows responses by retailer or contractor, indicating sections answered by each.
Table 13. Retailer Participant Survey Sample
Duplicate Records (by customer number and phone number)
The Cadmus Group, lnc. l Energy Services 14
E h i bit f":"YPYsT:l",li i]fJ
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HE$ Evaluation 2009-2010 Final Report February 3,2CI12
Table 14. Retailer Participant Surveys
Retailer 1 X
Retailer 2 X
Retailer 3 X
Retailer 4 X
Retailer 5 X X
Retailer 6 X
Retailer 7 X
Retailer 8 X X
Retailer 9 X
Retailer 10 X
Retailer 11 X
Retailer 12 X
Retailer 13 X
Retailer 14 X X
Retailer 15 X
Retailer 16 X X
Retailer 17 X
Retailer 18 X
Retailer 19 X
Retailer 20 X
Retailer 21 X
Retailer 22 X X X
Retailer 23 X X
As shown in Table 15, which provides the number of contacts available, targets and completed
surveys, participating lighting retailers did not meet survey targets, due to the small number of
contacts available, despite survey best practices (e.g., multiple attempts, calls at different times
of day, and scheduling call-backs). Three contacts in the lighting strata also had duplicate contact
information.
In-Territory Lighting Survey
Cadmus drew the in-territory lighting survey sample from a random list of Idaho Rocky
Mountain Power residential customers, provided by Rocky Mountain Power. Surveyors screened
respondents to identifu recent CFL purchasers for the survey.
Table 15. Retailer Suruey Dispositions
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R.ocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 618 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
February 3,2012
Table 16 details the screening process for eligible participants, which randomly selected 250
participants from 8,733 unique customers with Idaho mailing addresses, valid phone numbers,
and valid Rocky Mountain Power customer numbers.
, Response rate: the number of customers completing a survey, divided by the
number of eligible participants in call list.* Cooperation rate: the number of customers completing a survey, divided by the
number ofcustomers reached by phone.
Out-of-Territory Lighting Su rvey
Cadmus identified potential out-of-territory lighting survey contacts using locations (ZIP Code).
A market research firm, Market Systems Group,3 provided contact information for households in
eachZlP Code. Contacts were called at random, using survey best practices.
. Response rate: the number of customers completing a survey, divided by the
number of eligible participants in call list.
- Cooperation rate: the number of customers completing a survey, divided by the
number of customers reached by phone.
Marketing Materials Review
The process evaluation included Cadmus' review of marketing and communications developed
to promote participation and educate target audiences regarding HES Program details. As
appropriate, Cadmus also integrated findings on marketing approaches and effectiveness into
analysis from program staff interviews and customer surveys.
Data inputs used for the marketing and messaging review included:
3 hftpj,',, wlvu,JU!:s- g.cor"pi ltr"ebllnijq},.gLiip.I
Table 16. In-Territory Lighting Survey Sample
Duplicate records (by customer number and phone number)
Held out for ARP nonparticipant
Table 17. Out-of-Territory Lighting Telephone Survey Sample
The Cadmus Group. lnc. I Energy Services 16
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No.5 Page 619 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
February 3,2012
o Collateral (e.g., promotional material, advertising, and educational pieces);
o Presentation decks;
o Online promotional elements; and
o Marketing media mix and timing.
Where applicable, the review included specific comments regarding the following:
. General look and feel;
o Brand and message consistency;
o Program accessibility; and
. Stakeholdercriteria, including:
o Incentive forms
o Web-based marketing and educational collateral
o Searchable retailer listings
o Online processes availability
The marketing review also included a qualitative evaluation of online resources available
Rocky Mountain Power, and comparisons with other interactive resources.a
a The online review assumed Rocky Mountain Power.net as an initial entry point for HES Program participants.
from
The Cadrnus Group, lnc. I Energy $eruices 17
E,hibrtf":"YPYs""';H'"iilfJ
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky_..Mo_y.Ital.LP_glu_gr_ldaho HES Evaluatiol_2.909:2919_ ril_ql Report February 3, 2012
lmpact Evaluation
This section provides impact findings for the HES Program, based on analysis of data using the
following methods:
o Participant and nonparticipant surveys;
. Billing analysis;
. Engineering reviews;
o Site visits; and
o Secondary research.
Each data collection element contributed to gross or net savings estimates. Table 18 summarizes
evaluation activities and each effort's goals.
As noted, HES offered a number of different products and measures, which required different
evaluation methods. To address the complexities and details of each individual measure group,
the impact findings have been organized into two sections:
1. Lighting
2. Appliances, HVAC, and Weatherization
Lighting
During the 2009-2010 program years, Rocky Mountain Power incented over 47,000 CFL bulbs
through eight different retailers in 20 stores. The bulbs contributed to 32 percent of total HES
savings, and, as shown in Table 19, included only standard twister CFL bulbs.
Table 18. Summary of Evaluation Approach
Participant Surveys (Appliance, HVAC, and Weatherization Measures)X X x
ln-Teritory Lighting Surveys X X
OutotTenitory Lighting Surveys X
Participant Retailer/Contractor Surveys x X
Billing Analysis X
lnsulation Participant Verification Site Visits X
Stakeholder lnterviews (Management Staff and lmplementers)X
Secondary Research X
Secondary Data Analysis X
The Cadmus Group, lnc. I Energy $ervices
E-h i br f""'YPYs"J:11,,"i i#J
Case No, PAC-E-'14-07
VMtness: Kathryn C. Hymas
R_o-g.$y Wountain fswer lda"ho HE$ Hvqluglg_n 2009*2CI10 Final Report Februai'y 3, 2S14
Table 19.Incented CFL Bulbs by Type
Spiral (Standard)47,462 100%
Total 47,462 100%
Source: 2009-2010 lD HES PECI tracking data
Generally, CFL buy-down programs offer an effective alternative to traditional mail-in
incentives, given their ease of participation, widespread accessibility, and low administrative
costs. For such programs, utility incentives pass through manufacturers to retailers, which reduce
bulb prices to the end consumer. The programs motivate retailer participation through reduced
bulb prices without losses in their profits. At the customer level, participation may be so
seamless that participants do not know they have purchased an incentivized bulb or have
participated in a utility program.
Upstream programs, however, offer particular evaluation challenges. Calculating metrics, such as
installation rates and attributions, traditionally relies on finding participants and incentivized
products; in this instance, however, purchasers may not be aware of their participation in a
utility-sponsored program.
Consequently, calculation of various CFL lighting component inputs required use of primary and
secondary data collection activities, as shown in Table 20. Lighting trends reported in the
in-territory lighting surveys of Rocky Mountain Power's Idaho residential customers served as a
proxy for HES lighting participants, in lieu of verifiable participation data.
Evaluated Gross Savings Approach-Lighting
Three different parameters informed the calculation of gross savings for the lighting component:
ISRs, delta watts, and hours-of-use (HOU). The following algorithm provided gross lighting
savings:
AWatts*ISR*HOU*365Evaluated Per Unit Sautngs (kwltper untt) =L,000
Where:
lWatts : Difference in wattage between baseline bulb and evaluated bulb
: In-service rate, or percentage ofincented units installed
: Hours-of-use; daily lighting operating hours
1SR
HOU
Table 20. Idaho Lighting Activities
lnstallation Rate, lnstallation Location, Hours-of-Use
The Cadrnus Group. Inc. ,/ Energy Services 19
E,h i bit f":"$ys""'iri:i ilfJ
Case No. PAC-E-14-07
Rocky MountaiLfjwer ldqlg..l!-E-S Evaluation 200e*2010 Final Report Ftf?'JJilT,c#T"i
The annual savings algorithm derived from industry-standard engineering practices, consistent
with the methodology used by the Northwest Regional Technical Forum (RTF) for calculating
energy use and savings for residential lighting. Each methodology component is discussed in
detail below.
In-Service Rate
The ISR (also known as the installation rate) was determined using in-territory lighting surveys
of250 recent CFL purchasers. The survey asked those purchasing CFLs during 2009 or 2010 a
series of questions to determine whether the purchased CFLs had been installed, and, if so, in
which rooms. As shown in Table 21 and Table 22, respondents installed 75 percent of bulbs
purchased in 2009 and 2010, with bulbs most commonly installed in living spaces (such as
family and living rooms) and bedrooms.
This evaluation did not include stored bulbs as part of the ISR input, as they had not been
installed during the 2009-2010 program period and, as such, did not contribute to first-year
program savings. ln 2012, the evaluation team plans to survey a statistically significant portion
of respondents that reported in-storage CFLs during the 2009-2010 phone survey. These
respondents will be asked a series of questions to determine if any of the stored CFLs were
installed during the 201 I-2012 program period. Additional installations, if any, will be credited
in the 20ll-2012 evaluation.
Delta Watts
Delta Watts represent the wattage difference between a baseline bulb and an equivalent CFL
energy efficient bulb. For the HES Program, specific CFL products may be sold by participating
Idaho retailers. Rocky Mountain Power provided 2009-2010 CFL sales data by Stock Keeping
20
Table 21. CFL Installation Rate (n=250)
Table 22. CFL Installation Locations (n=231)
'Percents may not add to 100 percent due to rounding.
The Cadrnus Group, lnc. ,r Energy Services
E-h i bit f":"YPYr"J;gii ?#;
Case No. PAC-E-14-07
no-*y n*ountai! power-ldaho HES Evg-$.!ion 2Q!s-201Q-f-ineltep.g-rt - #'["r"i#ilT,c2HT[
Unit (SKU)5 number (model number and bulb type) for the 46 products eligible at the eight retail
outlets. Sales data indicated sales of 474,626 incented CFLs. Product sales data included CFL
wattages, though lumen data or light outputs for bulbs were not available.
To determine per-bulb savings, the study estimated the baseline incandescent wattage for each
CFL bulb sold. Table 23 shows the baseline wattage, established using the comparable light
output of the purchased CFL. Groups of lume! ranges (bins) were developed based on 2007's
Energy Independence and Security Act (EISA).7
Table 23. Lumen Bins by Baseline Wattage and Estimated CFL Wattage
Analysis of listed eligible ENERGY STAR CFL products provided estimates of CFL Wattage
bins for each associated lumen bin.
Of 46 eligible products included in the HES Program, 18 CFL SKU numbers were verified
online for each retailer, with each model's rated lumens recorded. For the remaining 28 CFL
products, estimated lumens were based on analysis of eligible ENERGY STAR CFL products.
ENERGY STAR Analysis
This analysis used a downloaded list of ENERGY STAR-qualified CFL bulb products, last
updated on May 24,2011. The database consisted of 5,245 CFL products and their associated
wattages and lumens. The list required data cleaning to remove or update: database
inconsistencies; missing values; decimal places; outliers; and incorrect entries. Cleaning
removed or updated nine entries, resulting in a o'cleaned" database of 5,243 CFL products.
The final database also included 117 three-way CFL bulb types. Analysis used middle wattages,
as specified by manufacturers.
Analysis broke out the ENERGY STAR CFL product list into lumen bins, specified by the EISA
lumen requirements, and extrapolated to the higher lumens bins. Table 24 shows the number of
CFL products by lumen bin, per the ENERGY STAR database.
5 SKU represents the unique make and model indicator for a specific retailer.
u Sales in the tracking database differed from that reported in annual reports due to different reporting and tracking
calendars. For the purpose of this evaluation, the CFLs in the database were verified.
'Congress signed EISA into law on December 19,2007. The new law contains provisions for phasing in more
efficient incandescent lamps based on rated lumens. For example, a 100 watt incandescent lamp with a rated
lumenrangeof l,490to2,600willberequiredtohaveaminimum of T2watts,effectiveJanuary 1,2012.
Tlre Cadmus Group, lnc. ,/ Energy Services 2"1
Rocky Mountain Power
Exhibit No. 5 Page 624 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Rocky. Moun-teil.PcJver ldq.ll-o- HE$ Evaluation 2009*2OJ 0 Final. Report Fehruary 3, 2012
Table 24. ENERGY STAR Product Counts by Lumen Bin
Lumens varied significantly for CFL wattages where multiple ENERGY STAR products existed.
For example, 381 CFL products had 20 watts, with lighting outputs ranging from 850 to
2,150lumens. Calculating median lumens for each bulb wattage addressed these variations.
As shown in Figure 1, the calculated trend line exhibited a relatively linear pattern: as CFL
wattages increased, comparable baseline wattages also increased. Reported baseline wattages and
delta wattages were based on a Rocky Mountain Power HES 2009-2010 savings analysis. Based
on the trend of median lumens and the specified lumen bins, lumens for the 28 remaining CFLs
products could be estimated. For each incented CFL, a baseline wattage was established using
purchased CFLs' comparable light output.
Figure 1. Median Lumens of CFL Wattage
* t$ledian Lumrns
CFLW*tt*ga
SoLE r-
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Table 25 represents all eligible 2009-2010 CFL products
(and their associated wattages). Evaluated and reported
assumptions by eligible CFL products. Documentation
baseline incandescent wattages. Analysis, as described in
baseline wattage.
purchased through the HES Program
delta wattages show differences in
provided by PECI supplied reported
this report, determined the evaluated
The Cadmus Group, lnc. I Energy Services 2?
E,h i bit f":"YPYs""'sgiiiff;
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Recly Mountain Psjrrer ldahqHE-S Evaluation 200-9:.2.!'10 Final Report February 3, 2012
Table 25. Evaluated and Reported Delta Wattage of 2009-2010
CFLs and Baseline Wattages
Cadmus uses this approach to determine an equivalent baseline by equivalent lumens of each
lamp, as this remains consistent with the 2007 EISA. Cadmus recommends using the lamp lumen
methodology to determine baseline wattage for program evaluations in 2012 and beyond; the
2007 EISA has established an equivalent baseline by rated lamp lumens. This approach does not
necessarily apply to specialty bulbs, as the 2007 EISA excludes certain types of bulbs (such as
three-way lamps, plant light lamps, shatter-resistant lamps, and others).
Hours-of-Use
The average HOU, calculated using ANCOVA model coefficients, drew from combined,
multistate, multiyear data from recent CFL HOU metering studies.s This model expressed
average HOU as a function of room type, existing CFL saturation, and the presence of children
in the home. Appendix C provides a more detailed exploration of the impact methodology used
to estimate CFL HOU.
All necessary independent variables were estimated, except for existing CFL saturation, using
response data from the participant telephone surveys, srrnmarized in Table 22. For CFL
saturations, data from comparison households in service areas with relatively young CFL
progmms were averaged,e as these data were not available for Rocky Mountain Power's Idaho
service area.
The weekend HOU was calculated using parameter estimates from the ANCOVA model. As
shown in Table 26, the weighted average of these two values provided an average annual HOU
of 2.35 hours per bulb.
E The Cadmus Group, Inc. 2010 Evaluation, Measurement, and Verification Reporr. Dayton Power and Light.
March 15,201.1
e Albee, K., et al. One Analysis to Rule Them Alt and In the Darkness Give Them CFZs. Proceedings of the 2011
lnternational Energy Program Evaluation Conference, Boston, MA.
10 40 30 40 30
11 40 29 50 39
12 60 48 50 3B
13 60 47 50 37
15 60 45 60 45
18 75 57 75 57
20 75 55 75 55
23 100 77 100 77
25 100 75 't00 75
26 100 74 't00 74
The Cadrnus Group, lnc. I Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 626 of 1 365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES_.E_valuation-.2009:8:19 fi-naj.Report Febnuary-3, 2012
Lighting Findings
Table 27 presents resulting evaluated gross savings, by bulb wattage. Evaluated per-unit savings
included HOUs, delta Watts, and ISRs, as discussed above. Rocky Mountain Power's reported
per-unit savings, based on program analysis documentation, included an 80 percent installation
service rate and additional 80 percent NTG and leakage adjustment factor.ro For comparison
pulposes, the additional 80 percent factor is not included inTable 27.
Table 2T.Evaluated and Reported Per Unit CFL Savings by Bulb Wattage for 2009-2010
ffi
26.401019.28
11 18.63 34.40
12 30.84 33.60
13 30.20 32.80
15 28.92 39.20
18 36.63 49.60
20 35.34 48.1 6
23 49.48 67.20
25 48.'t9 65.68
26 47.55 64.80
As shown in Table 28, the HES Program realized
annually. The evaluated per unit gross savings is
number of CFLs sold. A review of Rocky Mountain
kWh annual filed reported savings.
evaluated gross savings of I,521,467 kWh
32.06 kWh annual, weighted by the total
Power's documentation indicated 1,480,350
Table 26. HOU by Day Type
Table 28. Evaluated and Reported Program CFL Savings for 2009-2010
'Total CFLs reported in the 2009 and 2010 Rocky Mountain Power database.
'o The program analysis documentation included an additional factor that includes NTG and/or leakage rate.
The Cadmus Group. lnc. I Energy Services 24
E-hibi,,X":"YPIs""';g:iiff;
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES Evaluation 2009*2010 Final Report Fehruary 3, 2012
Estimating Net Savings-Lighting
Upstream energy-efficiency programs, such as the HES Program's lighting component, present
several evaluation challenges. By design, such programs remain largely invisible to consumers,
and many customers may be unaware they took part in the program. Evaluations of upstream
programs implemented elsewhere have indicated the majority of customer participants did not
know of their participation status.
Light bulbs' relatively low cost further complicates NTG analysis of upstream lighting programs.
Consumers can accurately recall details about buying light bulbs (e.g., how many individual light
bulbs and packages purchased, when the purchase occurred) for only a short time after the
purchase. This applies to incandescent bulbs as well as CFLs, especially as consumers become
familiar with CFLs and no longer view them as novelty items.
In addition to sales of program-discounted CFLs, utility marketing and outreach efforts often
lead to higher sales of non-program CFLs. This spillover effect especially occurs when retailers
reduce non-progftlm CFL prices to keep them competitive with incented lamps. Non-program
CFL sales (i.e., sales of non-discounted CFLs during program promotions, and CFL sales outside
of program promotional periods) can occur at participating and nonparticipating retailers.
Limiting NTG analysis to the few consumers who recall purchasing a program-discounted CFL
can signifi cantly underestimate program impacts.
Three different approaches provided CFL NTG:
o First, interviews with participating retailers and contractors sought to obtain their
estimates of net program impacts.
Second, the secondary literature was searched for estimates.
Third, willingness-to-pay research was conducted to estimate a demand curve for CFLs,
from which a freerider rate was inferred.
Participant Retailer/Contractor Surveys
The HES Program lamps' NTG was estimated using responses from in-depth participating
retailer interviews. Of 23 participating retailers interviewed across various distribution channels,
six addressed the HES Program's lighting component, with four answering the required battery
of NTG questions. The representative group of retailers providing data included: Adjacent
Agreement, Platt Retail, Platt Ship, and True Value. Responses represented 8 percent of 2009-
2010 HES incented lamp sales and 18 percent of participating stores and contractors in Idaho.
A series of questions asked of store representatives sought to estimate percentages of all CFLs
they would have sold in the HES Program's absence as well as percentages of total CFL sales
incented through the HES Program during 2009 and 2010. The participant retailer/contractor
survey accounted for freeridership and spillover, with questions addressing participating
retailers' lift in total CFL sales resulting from the HES Program (i.e., CFLs attributable to the
HES Program, including non-program CFLs). Appendix A provides interview guides for each of
these groups.
The Cadmus Group. lnc. I Energy Services
E,hibitf":"YP}s""'3niii]fJ
Case No. PAC-E-14-07
Ro-cky rr/ountain Power.l-d-?lro...HES Evaluation zOgg*4lO rinat neport -- #t[?;#lT,c#TI.
NTG questions included:
l. "If the HES incentives were not available during 2009 and 2010, do you thinkyour sales
of standard ENERGY STAR CFL bulbs would have been about the same, lower, or
higher?
2. "By what percent would your [store'sJ sales of standard ENERGY STAR CFLs have been
fiower/higherJ without the Home Energt Savings program?"
3. "During 2009 & 2010, what percent of your [store'sJ total CFL sales would you estimate
are CFLs purchased through the HES Lighting Program?"
In assessing responses to the above questions, NTG was estimated as follows:
l. For question2 and 3 responses recorded in percentile ranges, calculations used midpoints
ofeach range.
2. The HES Program tracking database provided program lamp sales data by store. This
included estimated numbers of CFLs sold through the HES Program per retailer.
3. The following equation provided estimated total CFL sales by retailer:
Total CFL Sales =
Number of CFLs SoldThroughthe Program
o/o Program CFLs sold over past two years (Q #3)
4. The following equation provided estimated sales, by retailer, in the HES Program's
absence:
Sales wtthout Program
= Total CFL Sales x (1 - o/o Lower Sales wi.thout program(Q #2))
5. The following equation provided estimated lift or CFL sales attributable to the HES
Program by retailer:
Lift : Total CFL Sales - Sales w fout Program
6. The following equation estimated NTG by retailer:
NTG =
Lif t in CFL Sales f or Each Retailer
C F L s S o ld T ltr oug lt the P r o g r am (T r ackin g D at ab as e)
To ensure accuracy and reliability to question I and 2 responses, survey administrators
confirmed question responses by asking: "Just to confirm, your sales of standard ENERGY STAR
CFLs would have been [insert % from D7J fiower/higherJ in 2009 and 20]0 f the Rocky
Mountain Power program was not available?"
Individual NTG ratios were weighted by distributions of program lamps sold by each of the four
retailers providing useable NTG responses. For example, Cadmus weighted Retailer 1's results
by the percentage of HES program lamps they sold. This weighting approach ensured the final
NTG estimate reflected distributions of program CFLs, with high-volume retailers more heavily
weighted. To calculate weights for each store, program lamp sales for each store were calculated
as a percentage of total lamps sold by all retailers, then divided by the sum percentage of all four
The Cadnrus Group, lnc. I Energy Services
E,h i b it ]X"""$Ys";'3$:iiff;
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
R-ocky.lr/lount_ain Pcwer. I.daho HES Eyaluation ?009*2010..Fina] ftgpgrt___ FebrLrany 3, 201?
stores' lamp sales, relative to the program lamp total. Table 29 presents resulting lamp sales and
Source: Questions D14 and D15 of the retailer participant survey.
As shown in Table 30, below, a I.47 mean store-weighted NTG estimate resulted. A relatively
high estimate, individual NTG estimates indicated considerable variation across stores
interviewed. Additionally, the post-weighting method tended to ampliff NTG estimates for
stores representing larger proportions of program bulb sales. For stores representing lower
program bulb sales, the post-weighting method could understate NTG estimates. The study
compared store NTG estimates based on each store's proportion of program bulbs sold, finding
larger stores (i.e., stores representing more than I percent of total program sales) resulted in
relatively more stable NTG ratios than stores representing smaller proportions of program bulb
sales.
Potentinl Bias and Uncertainty
Potential bias sources contributing to uncertainty around the store-weighted NTG estimate
include the following:
o The small sample of market actor responses resulted in a wide range of NTG estimates
(as shown in Table 30). Responses from this small sample may not sufficiently represent
all stores of the same name or all stores within each retail distribution channel.
'r Retailer names are disguised for confidentiality purposes. The retailer number associated with each retailer does
not correspond to other numbered retailers in subsequent tables.
Table 29.Interviewed Retailer Program Lamp Sales and Weights
Table 30. Responses to NTG Questions and Weighted NTG Estimate
Source: Questions D5 and D7 of the retailer participant survey.
The Cadmus Group. lnc. I Energy Services tt
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Case No. PAC-EI4-07
&pry-.ldountall*lo.y.err !-daho HES Evaruation -.zoos-zoro Final Repo* Ftt[?'r]i;ilvi,l#Tl-
. Program lamp sales for the four retailers contributing to NTG represented only 8 percent
of total lamps sold through the HES Program in Idaho (50,514).
o Some retailers could not provide estimates of program lamp sales or discuss how their
sales would have been impacted without HES incentives (known as non-response bias).
Therefore, the 1.47 NTG estimate indicates large uncertainty, due to the small sample and
potential biases from non-response. Additionally, responses from this small sample size may not
accurately represent all participating HES retailers in Idaho.
Secondary Data Review
For a second NTG estimate, Cadmus reviewed the literature on upstream lighting programs to
identiff NTG ratios for comparable programs that might be applied to Rocky Mountain Power's
Idaho lighting program. This review indicated utilities across the United States have employed a
number of different methodologies to derive NTG ratios; some utilities even combine
methodologies to derive NTGs. These methodologies include:
c Participant and nonparticipant retailer interviews.Interviews with corporate- and store-
level retailers include questions regarding retailers' total monthly or annual CFLs sales,
monthly or annual program sales, and changes observed in CFL sales and buying patterns
resulting from the program. Retailer interviews also often ask about changes in customer
awareness and CFL stocking patterns.
Consumer telephone survqls. Consumer telephone surveys query a random sample of a
sponsoring utility's customers about their recent light bulb purchases. Surveys may
include questions about: quantities of CFLs recently purchased; quantities of
incandescent and other light bulbs recently purchased; consumers' awareness of and
experience with different types of energy-efficient lighting; and consumers' recollection
of sponsoring utilities' identification.
Revealed preference-intercept surveys. Revealed preference-intercept surveys-
administered in stores, at the time of light bulb purchases-1uery consumers about their
lighting product preferences, based on their actual purchasing behaviors.
Willingness to pay WfD assessments. WTP assessments describe lighting product
features to survey respondents, and then ask respondents how much they would be
willing to pay for products with various feature combinations. These assessments are
more theoretical than revealed preferences in that they rely on respondents' hypothetical
purchasing decisions (rather than in-store, time-of-purchase decisions captured by
revealed preference intercept surveys).
Conjoint/price elasticity analysis. In conjoint analysis, survey respondents choose
between different light bulbs (e.g., A-line, flood, incandescent), characterized by six or
fewer distinct attributes (e.g., bulb type, price, lifetime, price promotion, brand, light
color, recommendation). A conjoint software program (e.g., Sawtooth) determines price
elasticity by simulating participants' willingness-to-pay for CFLs with different attribute
configurations at various price points. To estimate an NTG ratio from such a model,
evaluators estimate elasticity associated with CFLs using estimated market shares at the
average, non-discounted price, and at the average, fully-discounted price. Both price
tilcil*G G;ilp, ffi;:"r ffi'sy $*;;-28
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Case No. PAC-E-14-07
ryg$l n{ountain pgwe-r ldaho H.ES E-valuatio-n ?g9-9:gq]0 Final Report ffi#ilT,c#TI
points are estimated using a regression. The ratio between these market shares provides
the freeridership value. The NTG ratio then equals one minus the freeridership value.
o Multistate regression analysk This approach pools data collected through customer
telephone and in-home audit lighting surveys, administered in multiple program and non-
program areas across the U.S., into a single regression model. Pooled data are used in an
equation predicting CFL purchases and NTG ratios by controlling for factors affecting
CFL sales, such as income, education, homeownership status, home size, electricity rates,
and concentrations of big-box stores.
o Secondary researcft. Secondary research studies NTG estimates derived by residential
lighting programs elsewhere in the U.S., selecting the most appropriate NTG ratio for the
utility being examined. Secondary research activities include: reviewing applicable past
evaluations and conference papers; contacting utilities currently offering programs; and
searching industry evaluation databases.
Table 31, below, summarizes secondary research findings from other recent, upstream,
residential lighting progftlms across the U.S. For utilities using multiple NTG approaches, the
table shows NTG for each approach as well as the final NTG the utility selected for the overall
progmm.
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Case No. PAC-E-14-07
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Secondary sources show overall NTG ratios for other upstream residential lighting programs,
ranging from0.47 to 1.0.
When studying these programs to identifu NTG ratios most applicable to Rocky Mountain
Power's program, Cadmus the Rocky Mountain Power's program years evaluated program years
(2009 and 2010) represented PY4 and PY5. Newer upstream lighting programs typically
experience higher NTG ratios than more mature programs. Therefore, the study focused on NTG
ratios from comparison programs' third through seventh years, excluding data points from PYI
and PY2 programs, due to their relative immaturity. Similarly, the study excluded data points
from PY8 and older programs, given they operated significantly longer than Rocky Mountain
Power's Idaho lighting program. Averaging PY3 through PY7 NTG values from the comparison
programs resulted in a 0.70 NTG ratio for Rocky Mountain Power's upstream residential lighting
program.
Lighting Customer WTP (In-Territory Lighting Surveys)
In August 2011,250 in-territory lighting surveys were conducted, randomly drawn from a Rocky
Mountain Power list of 10,978 Idaho residential customers. The survey asked respondents a
battery of questions designed to determine their WTP for CFLs in the absence of HES Program
markdowns. After determining how many CFLs participants purchased in 2009 and 2010, the
survey asked participants:
1. Whether they would generally purchase more CFLs, fewer CFLs, or the same number of
CFLs at various un-incented hypothetical price levels.
2. What quantity of CFLs they would hypothetically purchase at various un-incented prices.
Specifically, questions asked respondents to indicate how many lamps they would purchase at
four hypothetical per-CFL prices: $18.00, $12.00, $6.00, and $0.50. Two-hundred and eight
respondents answered for all four prices.
CFL demand was assumed to relate inversely to price, indicating participants would purchase
more CFLs at lower prices. Estimating participant willingness to pay for un-incented lamps
required estimating a demand curve for survey participants, which related hypothetical prices
and quantities. Figure 2 illustrates the program lamp demand function, based on responses from
in-tenitory lighting surveys. The Y-axis shows prices, and the X-axis shows quantities of lamps
purchased at each price. The figure also shows an equation describing the relationship between
price and quantity.
o
The Cadmus Group, lnc. I Energy Services 31
,*, oo,l"l'Irln"JlHiii]'#
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES ?0.!_9*29._19 Final Report Fglruary 3.2012
Figure 2. Demand Schedule for Hypothetical Lamp Purchases
$20
$18
$16
$14
$12
$10
$a
$6
$4
$z
$o
Estimating the number of lamps purchased at the average program price per lamp (net lamps)
and the number of lamps purchased without the program incentive (freeridership) required
estimating quantities of lamps that would be purchased at the average, incented price of $1.24
and at the average, un-incented price of $2.55. As shown in Figure 3, 3,855 would be purchased
at the average incented price of $1.24, and 2,954 would be purchased at the average
un-incented price of $2.55.
Figure 3. Modeled CFL Quantities for FR Estimation
Lamps to the left of the vertical line from the un-incented price ($2.55)-in this case 2,954
lamps-represent freerider (FR) lamps, which would have been purchased without the incentive.
$1s
$1{
$12
€,.9 $to4
$8
$6
$4
$2
$o 2,000 3,000 4s0
Ourntity of CFLs
The Cadrnus Group, lnc. / Energy Services 32
E,h i b it f":'YPYeTSi?:i ilfJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky tvl.o_unlg.Ln Po:{_er ldglro HH$ ?90t*?S]0...filal.Repo*... . Le-bl'-uary 3,.201?
Only lamps to the right of this value and to the left of the incented lamp price represent program
effects. This results in the following equation for FR:
FR _ I_(Qcf loun-tncented - Qcf lors:untnrrntrd)
Qcf loug-tnr"nt"a
Where:
Qcflavg_incented = 3,855; quantity of CFLs purchased at the average price of
incented lamps ($1.24)
Qc/lo,g_onince,ted : 2,954; quantity of CFLs purchased at the average price of un-
rncented lamps ($2.55)
Responses to the in-territory lighting survey produced a 77 percent FR estimate, and, thus an
NTG estimate of 23 percent.
This approach produced the overall program effect minus freeridership, but the approach does
not account for potential program spillover; which upstream lighting programs could produce. .
Upstream programs primarily produce spillover by reducing prices of lamps sold without
incentives. CFL incentives' wide availability has reduced the price of un-incented and incented
lamps. Thus, the observed un-incented CFL price of $2.55 runs substantially below recent prices
in other markets. For instance, recent research in Maryland indicates an un-incented CFL price of
$4.53. Other research indicates un-incented prices between $3.37 and $3.50.
A recent lighting shelf survey of lighting retailers in Maryland indicates un-incented prices as
high as $6.10 per lamp. These higher prices better reflect CFL costs in the absence of program
incentives. As the un-incented price estimate rises, the FR rate declines, as fewer lamps would
have been purchased in the program's absence. An un-incented lamp at $3.37 would experience
a 68 percent FR rate. A $4.53 price produces a 58 percent FR rate. A $6.10 price per lamp
produces a 48 percent FR rate. Program impacts of un-incented lamps cannot be quantified with
data available, though $4.00 represents a reasonable value. This cost results in a 62 percent FR
estimated rate from WTP data, with a 0.38 NTG value.
Statistical Significance and Uncertainty
Random digit dial customer phone surveys avoid bias through the very randomness of the
selection process. With every sample, however, random error occurs, reflecting those selected to
participate in the study. This is the error due to sampling, for which we can estimate a margin of
error within a given degree of confidence. For instance, this study's sample reported a
willingness to purchase 1,966 CFLs in aggregate at a price of $6.00 per CFL.
A 90 percent confidence interval was constructed for random error around the sum of CFLs
purchased at each hypothetical price level. Table 32 shows error due to sampling for the sum of
purchased CFLs at each price. The estimates' relative precision ranged from 12.1 to 27.3 percent,
indicating the NTG estimate from this approach had a high degree of stability. A NTG value of
0.22 for the observed prices and 0.43 at the hypothetical $4.00 spillover price would be within a
JJThe Cadmus Group, lnc. / Energy Services
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Case No. PAC-E-14{7
Witness: Kathryn C. Hymas
8ogf.y*ftl!_g-yntain Power ldaho HES 20Q9-2010 Final Report _.. . .*-* February 3, 2012
90 percent confidence interval of the observed data.r2 This, again, suggests a quite stable
estimate.
Table 32.90 Percent Confidence Interval and Summary Statistics
Random error reported in Table 32 did not include systematic measurement errors associated
with this WTP methodology, such as the social desirability bias. For instance, if some
respondents experienced social pressures to report their CFL purchases, they could report
making more purchases at higher prices than they actually would.
NTG Findings
Identifuing NTG for the HES lighting program produced three values:
o Retailer/contractor surveys: 1.47
o Secondary literature review: 0.70
o WTP research: 0.38
Each approach faced limitations. Few retailer surveys, for example, were fielded, and
respondents had difficulty responding to questions related to NTG. Further, large variability
across responses occurred, with program effect estimates from 58 to 500 percent. The secondary
literature review also provided a wide range of estimates, underscoring the inherent difficulty in
estimating NTG. WTP research required respondents to answer difficult, hypothetical questions.
Moreover, research from around the counffy indicates WTP estimates of NTG often run lower
than estimates derived from other methodologies.
Given the inherent uncertainty in estimating NTG, an approach triangulating the methods
reduces each method's effect of unknown error. In principal, Cadmus would combine the three
estimates weighted by some measure of each estimate's certainty, such as its variance. This
would decrease the retailer survey's power in the overall NTG estimate due to wide
disagreement among retailers. As Cadmus could not directly estimate variance for the WTP
estimate, it could not be brought into this scheme. In such a case, equal weighting would prove a
reasonable approach. An approach equally weighting each three estimates offered a blended
NTG value of 0.85.
12 We arrived at these values by assuming the estimate of quantities purchased at $6.00 and $0.50 were off at the
limit of the confidence intervals, in opposite directions, i.e. at the lower limit at $6.00 and at the upper limit at
$0.50. We then re-estimated NTG for observed and hypothetical unincented prices based on a curve through
these points. We ignored the fact that the joint probability of our estimate being at the limit in opposite
directions at both prices is less than l07o; however, this would only bring the limit NTG estimate closer to the
mean estimate so we consider ours a conservative value.
for the CFL WTP Study (n = 208 respondents)
Source: Questions F1-F6 of the out-otterritory lighting survey.
$18.00 per CFL
$'12.00 per CFL
The Cadmus Group, lnc. I Hnergy Services 34
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CFL Leakage
Background
Before selecting stores for participation, program implementer contracted with Buxton, a market
research firm, to identiff likely CFL customers for retailers within Rocky Mountain Power's
service area. The progftrm implementer used Buxton's proprietary tool, Micro Analyzer, to
identifu stores with high proportions of likely CFL purchasers.'3 This tool defined profiles for
each store, including a drive-time based polygon of likely customers around each retailer and its
respective mix of 66 consumer segments. The program implementer then mapped these profiles
to the Idaho Rocky Mountain Power service areas to determine proportions of likely customers
belonging to each area utility. The program implementer targets participant retailers where
90 percent of customers within a 10 minute drive time fall within Rocky Mountain Power's
service territory. The final analysis dataset contained the proportion of likely customers by utility
for each retailer in Rocky Mountain Power's service area.
Methodology
To quantify CFL leakage impacts, defined as the proportion of incented CFLs purchased by non-
Rocky Mountain Power customers, an analysis used market research data and primary out-of-
territory lighting survey data. Combining the market data and sales data received from the
program implementer, likely leakage values could be estimated by mapping the proportion of
total sales by store to the estimated proportion of likely CFL purchasers not served by Rocky
Mountain Power. Likely leakage by store was then defined as the product of the proportion of
total incented CFL sales and the proportion of non-Rocky Mountain Power likely purchasers for
each store. That is, for each store, 'i':
Potenttal Leakagei
_ 1 Incented CFLsi \- \Zthtcented CFkt)
lNon - Rocky lvlountatn Power Likely CFL PurchcserS;\
\ tikely CFL Purchds€rsi I
Once likely leakage had been calculated for each store, leakage could be aggregated to the ZIP
code level. For ZIP codes with likely leakage, an out-of-territory lighting survey was conducted:
a random digit dial survey of non-Rocky Mountain Power customers purchasing CFLs during the
past two years. Table 33 summarizes these data.
13 A brief overview of Buxton's database and analytics can be found on its Website:
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The Cadmus Group, lnc. i Energy $ervices sl]
Table 33. Likely CFL Leakage by Store
1438189 54Yo 25.2o/o 11.5Y0 11.50/o
187853 920/o 24.1Yo 2.0o/o 2.00/o
125 Missing 18.0Yo N/A 1.3T0
881 I 93%9.20/o 0.70/o 0.70/o
4848 Missing 4.9Y0 N/A 3.0%
1438312 Missing 4.9Yo N/A 0.3%
1435561 85%3.6%0.6%0.6%
8819 93%2.20/o 0.2o/o 0.2Y0
10119M 100%1.9Yo 0.0%0.0%
1021710 100%1.0Y0 0.0%0.0%
1438213 Missing 0.9%N/A 0.0%
5328 100%0.6%0.0%0.0%
63491 I Missing 0.6%N/A 0.0%
677715 Missinq 0.6%N/A 0.0%
679013 Missing 0.6%N/A 0.0%
639810 Missing 0.6%N/A 0.20
677715 Missino 0.4Yo N/A 0.0%
1416554 520/o 0.3%0.1Yo 0.10/o
214 Missinq 0.3%N/A 0.0%
365631 58%0.0%0.0%0.0%
5491 Missing 0.3%N/A 0.20/o
947912 74To 0.0%0.0%0.0%
Total 100%15.0%20.1%
*"Missing'o indicates the Buxton analysis did not include that particular store.
'*, on,X"l"IrYr"J8giiiy#
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power tdaho HES 2009-2010 Finai Report February 3, 2012
For a small number of participating stores, the Buxton dataset did not contain data on likely
customers.la In these cases, Cadmus used data from stores within the same ZIP code.If data for
other stores with matching ZIP codes were not available, Cadmus used the proportion of that ZIP
code within Rocky Mountain Power's service area.l5 The rightmost column of Table 34, labeled
Potential Leakage with Imputation, reflects the proportion of the ZIP code within Rocky
Mountain Power's service territory for those stores without Buxton data. This imputation
increased the potential leakage from 15.0% to 20.loh (Table 33). Based on Cadmus' imputation,
the HES program had 20 percent potential leakage, which is twice that of the program
implementer's 10 percent target,
'o The implementer has reported that stores without Buxton data have since been removed from the program
l5 This imputation likely overstates leakage to a degree, as it assumes equal distributions of all customers across the
givenZIP code. Therefore, leakage values should be viewed as conservative estimates.
The Cadmu$ Group, lnc. / Energy Service$3S
E,h i bit f"*YPYs"J;iUi iffJ
Case No. PAC-E-14-07
n-o*y mountaln power ldatu -H-E-s 200e--2CI10 r-inai Report #'[?1]XiilT,c#T'd
Based on data available from Buxton market research, average CFLs per household were
expected to be approximately equivalent between Rocky Mountain Power and non-Rocky
Mountain Power customers in these leakage-prone areas: the two populations should be equally
likely to purchase CFLs. Cadmus tested this hypothesis using a survey sample of 57 non-Rocky
Mountain Power customers, and comparing them with CFL participant survey data.
In comparing the two populations, Cadmus evaluated the statistical significance of the difference
in mean CFL purchases using a t-test. In this test, the null hypothesis assumed the two means
would not be statistically different, whereas the alternate hypothesis assumed they would be. If
the test resulted in a p-value below 0.10, the two means could be said to differ with 90 percent
confidence, as shown in Table 34.
Table 34. T-Test for the Difference in Mean CFL Purchases Between Roclcy Mountain
*P-values indicate the degree of confidence to which Cadmus can assert that the given value equals zero. ln
the t-test shown above, it represents the probability that the two means are equal. Because this value is
greater than 10 percent, Cadmus cannot assert with 90 percent confidence that the two values are different.
Findings
As shown, CFL purchases did not differ significantly (with 90 percent confidence) between the
two groups. Based on the test results, Cadmus chose not to adjust the likely leakage estimated
from the Buxton research.
As the sum of each store-specific likely leakage value, program-wide CFL leakage equaled
20.1 percent.
Appliances, HVAC, and Weatherization
As the HES Program contains several measures, this section addresses evaluated gross and
savings estimates for the following:
o Clothes washers
o Dishwashers
o Water heaters
o Refrigerators
o Insulation
o Windows
o Room air conditioning units
o Central air conditioning units
Power and Non-Rocky Mountain Power Customers
The Cadmus Group, lnc. / Energy Services .5/
E,h i bit f":"YPYsT:liliilfJ
Case No. PAC-B-14-07
\Mtness: Kathryn C. Hymas
[g_?.]y Mountain.Polwgr ldaho HES 2009*2010 Final Report February 3,3{2*
o Evaporative coolers
o Heat pumps
o Duct sealing
o Fluorescent light fixtures
o Ceiling fans
As these measures greatly differ, Cadmus utilized the most effective evaluation techniques for
specific measures incented, as shown in Table 35.
Table 35. Gross Savings Evaluation Methodolory, by Measure
The following sections discuss each methodology and evaluated savings in depth.
Calculation of Gross Savings
Calculation of gross savings for these measures involved two steps for each measure group:
determination of installation rates; and an engineering review or whole house model. Cadmus
enhanced the insulation savings estimates through site visits and billing analyses, described in
detail below.
Installation Rate
For each measure group, participant telephone surveys asked participants a simple series of
questions to determine whether or not they installed incentivized products. For products with
multiple measurement units, such as windows, participants could be awarded credit for partially
installing incented units. This proved unnecessary, as survey results indicated complete
installation of each measure surveyed, resulting in 100 percent installation rates. The evaluation
team assigned the average installation rate of surveyed measures (in this case, 100 percent) to
low savings measure groups which were not surveyed (such as duct sealing and permanently
installed evaporative coolers).
The Cadrnus Group, lnc. / Hnergy $ervices 38
.*, o,,,X"l"I'$"J;fl if iYg
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Rocky fifiolr.ntaf Iower_ldaho._hl.f-$-2009*2010 Final Report _._.._Eebruelyj3,_?-913
Review Tracking Database
Cadmus reviewed the program implementer's lighting and HES participant databases to check
for duplicate records and ineligible participants. Table 36 shows the outcome of the tracking
database review, while Table 37 shows validation of the measure-level tracking database.
As measures invoiced on December 18, 2008, did not fall within 2008 reporting, these records
were dropped from the database. For some measures, the program implementer not only tracked
participants, but contractors providing the units. Cadmus identified and dropped 339 records,
Table 36. Tracking Database Review
Measure Quantitv or Gross kWh Savinos Eouals Zero
Table 37. Measure Level Tracking Database Validation
Clothes Washer 2,412 2,412 577,285 577,284
Dishwasher 841 841 i:rIs-;$*:U:i:i::::i ii1iiir11;;89i$0511i,,
Electric Water Heater 192 192 17,414 17,414
Refrigerator 770 770 75,075 75,075
lnsulation: Attic (square feet)2,341,138 2,341,137 Removed participants with
zero oross kWh savinos
lnsulation: Floor (square
feet'l 28,1 03 28,1 03 Removed participants with
zero qross kWh savinos
lnsulation: Wall (square feet)46,308 46,308 Removed participants with
zero oross kWh savinos
Windows (square feet)B,;ffrfr 47,373 47,373 Removed participants with
zero oross kWh savinqs
CAC/HP Tune Up 98 98 4,032 4,032
Evaporative Cooler 3 3 975 975
CentrallVC Equipment 3 3 288 288
Duct Sealinq 83 83 5,432 5,432
Heat Pump Conversion 2 2 6,294 6,294
Heat Pump Upgrade 4 4 3,244 3,244
Proper CAC lnstall 1 1 23 23
Proper CAC Sizing 1 67 67
Ceilinq Fans 22 22 2,354 2,354
Fixtures 130 130 11,960 11,960
CAC Tune Up 98 98 2,940 2,940
Total 1,822,995 1,777,126 3,199,615 3,199,630
The Cadmus Sroup, lnc. i Energy $ervices
E,hibitrl":"YPYeTlfl iiiH
Case No. PAC-E-14-07
Roc-gy Mou-ntain Power ldall-o--t1E*[300s*zolo rin-alnepo* -- - $f,?;#iryi,c#T]
where either the total gross kWh savings or the measure quantity equaled zero. Fifty-eight
insulation and windows records had a non-zero measure quantity and zero gross kWh savings.
One dishwasher invoiced in 2010 was incorrectly reported in 2009, with an incorrect model
number. Consequently, database savings exceeded filed savings by 15 kwh.
Cadmus also reviewed the program implementer's tracking of 2009 and 2010 upstream lighting
measures. As shown in Table 38, the total number of CFLs in the filing exceeded the quantity in
the program implementer's tracking database by 96 bulbs.
To calculate evaluated gross and net savings, Cadmus used measures quantities that could be
verified through documentation obtained through a database or invoice
En gineering Review-Appliances
The engineering review used data from the participant phone surveys and secondary data to
evaluate gross savings for clothes washers, refrigerators, dishwashers, ceiling fans, and light
fixtures. As shown in Table 39, realization rates ranged between 20 percent and 185 percent.
Appendix K provides a more detailed analysis.
Table 38. Lighting Database Review
Table 39. Engineering Review Summary - Appliances
2009-10
Clothes Washers Clothes Washer-Tier One
(1.72 - 1.99 MEF)231 284 123Y0
Clothes Washers Clothes Washer-Tier Two
(2.0 + MEF)241 M7 185%
2009-1 0 Refrigerator ENERGY STAR Refrigerator 97.5 65.5 67Yo
2009-'10 Dishwasher ENERGY STAR Dishwasher 35 JO 1030/o
2009-10 Ceiling Fans Ceiling Fans 107 21 20o/o
2009-1 0 Fixtures Fixtures 92 108 117Y0
En gineerin g Review-Systems
The engineering review used data from the
evaluate gross savings for water heating and
realization rates ranged between 56 percent
detailed analysis.
participant phone surveys and secondary data to
HVAC related measures. As shown in Table 40
and 164 percent. Appendix K provides a more
The Cadmus Group, Inc. / Hnergy Services 4S
Table 40. Engineering Review Summary - IIVAC
2009-10 Water Heaters RTF Defined Standard 91 97 107o/o
2009-1 0 Heat Pump System
Conversion Electric Fumace 3,147 5,182 lMYo
2009-1 0 Heat Pump Upgrade HSPF 7.7 811 470 56%
2009-1 0 Heat Pump Tune-Up Operating Heat Pump
Svstem 576 505 88%
2009-1 0 CentralA/C Equipment SEER 13 96 96 100%
2009-l 0 Proper CAC lnstall Standard Practice
lnstallation 23 23 100%
2009-1 0 Proper CAC Sizing Oversized CAC System 67 67 100%
2009-1 0 CAC Tune-Up Operatinq CAC System 30 30 100%
2009-'t0 Evaporative Coolers CAC System 325 325 100%
2009-1 0 Duct Sealing Leaky Ducts, per RTF
definition 40 52 130Yo
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Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES 2009-2010 Final Report Febryqry 3, ,20!4
Billing Analysis
Billing analysis assessed actual net energy savings associated with insulation measure
installations.'6 Cadmus determined the savings estimate using a pooled, conditional savings
regression model, which included the following groups:
o Insulation (combined attic, wall, and floor insulation for 2009-2010); and
o Nonparticipant homes, serving as the comparison group.
t6 nilling analysis was only performed for insulation measures. Energy savings achieved through installation of
other measures were not large enough, relative to the total energy consumption of households installed, to allow
reliable billing analysis.
The Cadmus Group, lnc. I Hnergy $ervices n4
E-hibitf":"YPYs""';:";:iilfJ
Case No. PAC-E-14-07
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Table 41 presents an overall gross savings estimate for wall, floor, and attic insulation measures.
The billing analysis estimated overall insulation savings of 1,293 kWh. Average insulation had
average expected savings of 1,796 kwh, translating to a72 percent realization rate for insulation
measures. With average participant pre-usage of 18,612 kwh, savings represented a 7 percent
reduction in energy usage from insulation measures.
Table 41 also presents an adjusted gross overall savings estimate for wall, floor, and attic
insulation measures, including the control group. The billing analysis estimated savings of 736
kWh. Average insulation had expected savings of 1,796 kwh, translating to a 4l percent
realization rate for insulation measures. With average participant pre-usage of 18,612 kwh,
savings represented a 4 percent reduction in energy usage from insulation measures.
As the nonparticipant group showed unusually high savings, compared to other Pacific Power
service territories, and because of high rate of nonparticipant time of use (TOU) program
participation in Idaho, Cadmus recommends using the unadjusted gross participant savings
estimate of 1,293 kWh from Table 41, and applying a freeridership correction to the gross
savings estimate and realization rate.
Appendix G provides methods and results for the billing analysis.
Whole-House Energy Modeling
Typical Participant Home
For the insulation and windows measures developed by the program implementer, Cadmus
developed a typical participant home to simulate savings for comparison to billing analysis
results. The typical home's characteristics were determined from the implementer's participant
database and from survey information collected through this project. This typical participant
home was used as the base case for each insulation measure upgrade. Therefore, the resulting
home would be poorly insulated on all surfaces, and did not represent an average pre-
participation home. As energy savings result from improvements to the thermal conductive
properties of each home's surface, use of a single baseline home proved appropriate.Table 42
shows the base home's general characteristics. Table 43 shows HVAC systems used in the
simulations.
Table 41. HES Attic, Floor, and Wall Insulation Realization Rates
41Yo (35Y0470/o\
Table 42. Characteristics of Typical Modeled Homes
Assumed typical HES pailcipant
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Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountaln Power ldaho &{ES 20CI9*2010 Final Report February 3,2012
Windows
Cadmus used whole-House Energy simulation results to determine evaluated savings for
windows, with billing analysis savings as 75.3 percent of modeled insulation results. Billing
analysis results better reflect actual usage and home attributes than that of an average (typical)
home model. Therefore, the study used 75.3 percent of the modeled home estimate to adjust
windows simulated savings to evaluated gross savings.
Table 44 shows final evaluated gross savings for windows.
On-Site Inspections
The American Recovery and Reinvestment Act of 2009 and an influx in utility funds spurred a
nationwide fear of dishonest insulation contractors, allegedly installing insulation in residences
ia
Home Conditioned Floor Area 1,820 Square Feet Average Participant Home
Foundation Type 8" uninsulated concrete wall Engineering Assumption
Walls
R-0 Continuous lnsulation, R-3.4 Cavity
lnsulation, 0.9 inches thick, 16/1.5x3.5,
Wdl stud soacino/size
Construction created from the weighted average
participant insulation level reported before
measure installation.
Attic
R-2.7 Continuous lnsulation, R-13 Cavity
lnsulation, 3.5 inches thick, 2411.5x3.5,
Chord rafter spacinq/size
Construction created from the weighted average
participant insulation level reported before
measure installation.
Framed Floor
R-0 Continuous lnsulation, R-1.8 Cavity
lnsulation, 0.5 inches thick, 2411.5x11.5,
Floor Joist soacinqisize
Construction created from the weighted average
particlpant insulation level reported before
measure installation.
Windows U-Value 0.49, SHGC 0.58 Matches models previously developed by
imolementer.
lnfiltration 9.84 ACH at 50 Pa Proportional, based on home size, to models
previouslv developed bv the imolementer.
Heating System/Cooling
system Varies by model
Equipment sized to 120 percent of the design
heating or cooling load. Efficiencies chosen to
match implementer assumptions.
Duct Leakage 246 al25Pa Matches models previously developed by
imolementer.
Thermostat Non-Programmable, Heating 68"F,
Coolino 71'F
Result of surveys to all home energy savers
oarticioants in the state.
Table 43. Typical HVAC Systems Used
Table 44. Evaluated Gross Savings-Windows
Electric Furnace M CAC
Gas Furnace w/ CAC
The Cadrnus Group, lnc. / Energy Services
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Case No. PAC-E-14-07
Rocky.Mountain Poye.I.lg.glro ryE-s-.?-0-0-e*,q10 rinar Report -- F[f,"i.6iryi,c#T"i
not qualiffing for incentives. Additionally, several claims emerged that "rebate chaser"
contractors did not install claimed insulation amounts. The insulation site visits conducted with
insulation participants sought to evaluate the quality and quantity of Rocky Mountain Power
incented measures. Based on these visits, Cadmus could not conclude claimed and verified
squa.re footages differed significantly, or that installers underestimated pre-existing attic
insulation R-Values. Cadmus found participants and contractors did underreport added insulation
R-Values.
Approach
To veriff claimed insulation savings, Cadmus completed 72 site visits at homes receiving attic
insulation. Specifically, the site visits sought to:
l. Verifu installed insulation square footage matched that claimed in the program
implementer's tracking database; and ensured the maximum incentive amount did not
exceed the claimed incentive.lT
2. Confirm customers met HES insulation eligibility requirements, including:
a. The home was constructed before 2008.
b. The home had electric heat or gas heat, or a central air conditioning system or heat
pump serving at least 80 percent of its floor area.
c. The home had preexisting attic or floor insulation below R-18, with added attic or
floor insulation of R-19 or more.
3. Check measure insulation install quality, specifically veriffing levels of attic insulation
installed.
To verifu attic insulation R-Values, field staff first visually identified the insulation type for each
insulation layer (e.g., loose-fill fiber glass, loose-fill rock wool, loose-fill cellulose, fiber glass
batt, perlite, or polystyrene). Field staff then measured the average thickness of each layer, and
calculated the corresponding R-Value, based on an assumed R per inch for the given insulation
typ.."
Cadmus verified attic insulation at 72 sites. Unless otherwise noted, attic insulation results met
90 percent confidence and 10 percent precision levels.
Table 45. Sites Verified by Insulation Type
Attic lnsulation | 1,355 I 72
Field staff also collected data on insulation characteristics in participants' homes, as summarized
in Appendix H.
'7 The HES Insulation Incentive Application indicates participants can receive up to $0.30 per square foot of
insulation installed.
r8 Cadmus used R-values per inch assumptions consistent with Rocky Mountain Power's HES Insulation Calculator:
http :/,/homeenergysavings.net {Downloads/InsulationCalculator.pdf
The Cadrnus Group, lnc. / Energy Services 44
E,hibitf""'YPl/s""';H:i?L"J
Case No. PAC-E-14-07
RCIsky.M-oulgin p.gfver tdgh-o HEs 2s0s-2CI10 rinar Repofi - .""..... -. ............. ..._...... .Ftt[?g{i.[-'1d.jcdja,
Attic Insulation Findings
Claimed and Observed Insulation Square Footage
Cadmus calculated attic insulation square footage for each insulation type, and compared it to
claimed square footage in the program implementer's database. The 72 attic insulation sites
averaged 1,279 claimed square feet; sites averaged 1,308 verified square feet, or roughly an
29-square foot (or 2.3 percent) difference. Figure 4 shows distributions of differences between
reported and verified square footage across sites.
Figure 4. Verified Attic Insulation Square Feet, Compared to Claimed Footage (n=72)
20%
L8%
75o/o
74%
12%
70%
8%
6%
4%
2%
Oo/"
-'t- --"'
I
At 60 percent of sites, observed square footage differed from claimed footage by less than
100 square feet. As shown above, the number of sites where verified square footage exceeded
claimed square footage roughly equaled the number of sites where claimed footage exceeded that
verified.
Cadmus performed a difference of means t-test to check for a statistically significant difference
between reported and verified square footage. Table 46 shows t-test results.
Table 46. Reported and Verified Square Footage Difference of Means T-Test
As this test's p-value did not fall below 0.10, insufficient evidence emerged to conclude claimed
and verified square footages significantly differed. Therefore, small observed differences could
be attributed to random error.
47; "W *
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iesizggisooTover i By100toisysoto99iBy1to49i iBy1to49i By50to i ayrootoi syov300i2eei:ijiesi2sei300
Claimed ExceedsVerified (square feet) i *o I Verified ExceedsClaimed (square feet)
iDifference i
The Cadmus Group, Inc. / Energy $ervices 45
E,hi bit f":"yp:!TiH:i;y."J
Case No. PAC-E-14-07
Eggfy yrountain power raano nEs eoos*zoro rinalFefo* --.-..-.-...-.-.* #'[?[ff3]#T"d
Rocky Mountain Power allowed participants to receive incentives for attic insulation on a
square-foot basis.. The insignificant differences between claimed and verified attic insulation
square footage indicated, on average, Rocky Mountain Power paid correct incentive amounts.
Attic Insulation Qualification Requirements
To determine if participants met program qualification requirements, Cadmus verified heating
fuel, cooling system types, home construction years, old insulation R-values, and added
insulation R-values. Table 47 summarizes the percentage of eligible and ineligible participants.
Table 47. Attic Insulation Criteria*
*Five participants receiving added insulation less than R-19 also had preexisting insulation greater than R-18.**At nine sites, field staff could not verify the thickness and type of insulation due to access to entire attics. Though they reviewed
contractors' paperuork at these sites to verify insulation, these sites were excluded from R-Value calculations.
Verified preexisting attic insulation R-values averaged R 1.0 less than that verified. For added
attic insulation, average verified R-values exceeded claimed R-Values by R 5.2. Table 48 shows
average differences between claimed and verified preexisting and added attic insulation
R-Values.
Table 48. Average Differences between Claimed and Verilied R-Values
While claimed and verified R-Values for preexisting insulation differed, the difference did not
prove statistically significant at the 10 percent level. In other words, insufficient evidence exists
to conclude participants or installers underestimated or overestimated preexisting attic insulation
R-Values. The difference between claimed and verified added attic insulation is significant at the
5 percent level, thus contractors and participants underreported R-Yalues for added attic
insulation.
4S
Total ln-Eligible 22 35Yo t9.9%
Gas Heatinq System and CAC/Heat Pump Serves < 80% of Floor Area 7 11Yo r6.5%
Pre-existing lnsulation greater than R-18 I 14Yo !7.30/o
Added lnsulation Less than R-l9 1 2o/o 12.60/0
Pre-existing insulation greater than R-18 and added insulation less than R-19 5 $Yo r5.6%
TotalEligible 41 65%r9.9%
Total Verified for Eligibility 63 100Y0
Could Not Verify*9
Total Participants 72
The Cadmus Group, lnc. / Energy $ervices
E,h i bit f":"yPysT;iiliilf;
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Rocky Mountain Poyer ldaho HES 20S$*2010 Finat Report Febnuary 3, ?01?
Attic Insulation Quality
As properly installed attic insulation should be level in most places, field staff inspected attic
insulation thicknesses in multiple places at each site, reporting minimum and maximum
thicknesses. Figure 5 shows distributions of minimum/maximum thickness differences across 69
sites where field staff had sufficient attic access to verifu a minimum and maximum thickness.
Figure 5. Range of Added Attic Insulation Thickness (n=69)
n=59
Mean = 4.8
Std Dev = 3.5
o2345678910ttL213t4
Range of Attic lnsulation Thickness (in.) - Max Thickness Minus
Minimum Thickness
On average, maximum attic insulation thickness exceeded minimum thickness by 4.8 inches. At
7 percent of the sites, maximum attic insulation thickness exceeded the minimum thickness by
10 inches or more.
Net Savings Approach
Cadmus implemented a NTG methodology addressing the HES Program in 2009 and 2010.
Freeridership and spillover comprised NTG's two components. Freeriders---rustomers who
would have purchased a measure without a program's influence-reduced savings attributable to
Rocky Mountain Power's programs. Spillover-additional savings obtained by the customer's
decision to invest in additional efficiency measures or activities due to their program
participation-increased savings attributable to the program, and improved program cost-
effectiveness. The following formula provided final NTG ratios for each program category:
Net-to-gross ratio : (1 - Freeridership) + Spillover
The freeridership component drew from a previously developed approach, which ascertained
freeridership using patterns or responses of a series of six simple questions. The questions-
allowing "yes," "no," or "don't know" responses-asked whether participants would have
installed the same equipment in the program's absence, at the same time, at the same amount,
20%
t8%
t6o/o
t4o/o
t2%
tlo/o
8o/o
6%
4o/o
2%
o%
t7%
tao.tsth
o
eoaLoo.
47The Cadnrus Group, lnc. i Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 650 of 'l 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountai_n tower ldaho HES 2009-201.0 FiLg!-.SUort -__ February 3, 2012
and at the same efficiency. Question response patterns were assigned freerider scores, and the
confidence and precision estimates were estimated on score distributions.le
Cadmus estimated participant spillover by estimating: savings attributable to additional measures
installed; and whether respondents credited Rocky Mountain Power with influencing their
decisions. Measures counted if eligible for program incentives, but incentives were not
requested. NTG ratios then accounted for freeridership and spillover.
Appendix I provides a detailed explanation of Cadmus'NTG methodology, including:
o A description of how Cadmus categorized Rocky Mountain Power's HES Program into
similar measures;
o An explanation of survey designs; and
o Descriptions of Cadmus' freeridership and spillover evaluation methodologies.
It also provides:
o Full-text versions of NTG survey questions administered to participants;
o The freeridership scoring matrix, showing all possible combinations of responses to the
freeridership survey questions; and
. Scores Cadmus assigned each combination.
Though this methodology could be used for evaluating NTG for appliances, windows, and
insulation, it did not apply for CFLs. As the HES Program incented CFLs at the retailer level,
participants did not know they participated in a program or purchased an incented CFL.
Therefore, estimating freeridership and spillover by surveying participants did not provide a
viable option. To determine the CFL NTG estimate, Cadmus triangulated results of the
participant retailer surveys, the customer's willingness to pay for analysis, and the secondary
data review.
Summary of Results
Table 49 summarizes HES Program freeridership, spillover, and NTG percentages. For this
analysis, Cadmus divided measures into two categories: appliances and insulation/windows.
Appendix I provides a detailed explanation why measures were separated into categories for
NTG analysis.
t'This approach follows methods outlined in: Schiller, Steven et. al. "National Action Plan for Energy Efficiency."
Model Energy Efficiency Program Impact Evaluation Guide. 2007. rvu,rv.eroa.scv,,_eeaclionplirn.
4SThe Cadmus Group, lnc. / Energy $ervices
E"h i bit f":"YPYsTiF[iiYg
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
8o__cky Mou.nElin Power ld-aho HES 2$09-2010 Final.Repofi _Fe.try-{.y_3, 2012
Table 49. HES NTG Ratio
Although large differences occurred between appliances and insulation/windows when looking at
freeridership and spillover independently, similar NTG ratios resulted. Participants purchasing
appliances indicated an 86 percent NTG ratio, meaning 86 percent of gross savings for appliance
measures could be attributed to the HES Program. Participants purchasing insulation or windows
evidenced a similar NTG ratio (87 percent), meaning 87 percent of gross savings for insulation
measures could be attributed to the HES Program.
Table 49 also shows the HES Program's overall NTG ratio (87 percent), a savings-weighted
average of appliances and insulation/windows NTG ratios. This value has been applied to HES
measures not represented in the participant survey, including electric and gas duct sealing. It
should not be used for planning purposes, as it does not represent data specifically collected for
those measures.
Freeridership Analysis
After conducting participant suryeys, Cadmus converted resulting responses into a freeridership
score for each participant, using the Excel-based matrix approach described in Appendix I's
freeridership methodology section. Each participant's freerider score derived from translating
responses into a matrix value, and then using a rules-based calculation to obtain the final score.
This section presents all combinations of responses received for the HES Program, and scores
assigned to each combination. The following figures show participants' responses rarely
reflected each potential combination, but tended to group around subsets of common patterns.
Freeridership scores, confidence intervals, and precision estimates were calculated for each
measure category, based on distributions of scores within the matrix.
Table 50 shows freeridership estimation results for insulation and appliance measures. The
sections following the table discuss in-depth freeridership analysis by measure category.
Table 50. HES Freeridership Results By Measure
r 0.03Appliances26933Yo
Clothes Washer 72 37Yo t 0.05
Dishwasher 75 42Yo r 0.06
Fixture o 610/o !0.27
Electric Water Heater 46 1SYo r 0.09
Refrigerator 70 44Yo r 0.05
lnsulationMindows 11',\13Yo r 0.05
HES Overall Non-Lishtins 380 20%! 0.03
The Cadrnus Group, lnc. i Energy Services 4S
E'h i bit f":"YPYsTSFi:iiffJ
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Ro_cky_Mountajn.Pa.wer ldaho HES 2009-2010 Fin_a.!_Re_port February._3, ?Q.13.
Grouped together as appliances, the five measures evidence a 33 percent overall freeridership
score, with an absolute precision of 3 percentage points. Insulation and windows measures had
an average freeridership score of 13 percent, with an absolute precision of 5 percentage points.
Combined, all HES measures resulted in a 20 percent average score, with an absolute precision
ofl percentage points.
Table 51 shows unique response combinations resulting from the HES appliance measures
participant survey, freeridership scores assigned to each combination, and numbers of responses
for each combination. The table shows participant responses tend to group around subsets of
cofilmon response patterns.
The Cadrnus Group, lnc. i Energy $ervices 50
E,h I bit f":"yPysTHJ:i iffJ
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Rocky Itllountain Pojrr_er ldaho H_ES 2019-2010 Final Report.-._._.__** .*_ February_3,..2i12_
Table 51. Frequency of Freeridership Scoring Combinations-HES Appliances
Yes No Yes x Yes Partial Yes x x x x 50%104
No No Yes x Yes Partial Yes x x x x 25Yo 27
Yes Yes x x x x x x x x x 100%26
Yes No Yes x Yes Pailal Partial x x x x 25Yo 23
Yes No No Yes No Partial Yes x x x x lYo 11
Yes No No Yes Yes Partial Yes x x x x 50Yo '10
No Yes x x x x x x x x X 10070 I
No No Yes x Yes Partial Partial x x x x 13o/o 6
Yes No Yes x No Partial Yes x x x x }Yo 5
Yes No No Yes No Partial Partial x x x x lYo 5
Yes No No Remove x x x x x X x 0o/o 4
No No No Yes Yes Partial Yes x x x x 25.0Y0 3
No No No Yes No Partial Yes x x x x }Yo 3
Yes No Yes x Partial Partial Yes x x x x 25Yo 3
Yes No No No x x X Yes x x x 1Yo 3
Yes No No Yes Yes Partial Partial x x x x 25Yo 2
No No Yes x Yes Partial No x x x x }Yo 2
No No No No x x x Yes x x x lYo 2
Yes No No No x x x No No Partial Partial 13Yo 2
No No Yes x Partial Partial Yes x x X x 12.SYo 2
Yes No Yes x No Partial No X x x x }Yo 1
No No No Yes No Partial No x x x x }Yo 1
Yes No Yes x Yes Partial NO x x x x 0.0%1
Yes No No Yes Partial Partial Partial x x x x 13Yo I
No No No No x x x Partial Yes Partial No 0.0%1
Yes No No Yes Partial Partial No x x x x }Yo I
No No No Yes Yes Partial Partial x x x x 13Yo I
No No No No x x x No Parti
al Partial Partial 1Yo 1
No No No Yes No Partial Partial x x x x 0.0%1
Yes No No Yes Yes Partial No x x x x 1Yo 1
No No No No x x x No Yes Partial Partial lYo 1
No No Yes x No Partial Yes x x x x lYo 1
Yes No No Yes Partial Partial Yes x x x x 25Yo 1
No No Yes x No Partial Partial x x x x }Yo 1
No No No No x x x No NO Partial Yes 13Yo 1
Yes No No No x x x No Yes Partial Partial 0%1
Yes No No No x x x No Yes Partial No 0.0%1
The Cadmus Group, lnc. / Energy Seruices 51
Rocky Mountain Power*''-
t""": i,X:?i'"t1,,1:3;
Rocky Moultain tgwer ldaho HEs 20CI9*2010 Final Report -... . #tff;;ffi'vd,c.#i"d
Four common patterns appeared in the respondents' answers to freeridership questions,
representing 67 percent (180 out of the 269) of total appliance participants interviewed:
. One-hundred and four respondents planned to purchase measures before hearing about
incentives. They indicated they would have purchased a measure of the same efFrciency
at the same time without the incentive, but, as they had not already purchased the
measure when hearing about the incentive, they were considered 50 percent freeriders.
o Twenty-seven respondents said they had not already purchased nor were planning to
purchase the measure when they heard about the incentive. However, they were scored as
25 percent freeriders as they said they would have purchased the same measure at the
same time without the incentive, and it would have been just as energy efficient.
o Twenty-six respondents had already purchased the measure when they heard about the
incentive, and, therefore, were considered 100 percent freeriders.
o Twenty-three respondents planned to purchase measures before hearing about incentives.
They indicated they would have purchased a measure of the same effrciency, but they
would have purchased the measure later the same year and not at the same time. Due to
the uncertainty they would have purchased the measure the same year, they were
considered 25 percent freeriders.
As shown in Table 52, below, different patterns emerged from insulation and windows
participants' answers to the freeridership questions.
o Most notably, 22 percent of respondents who installed insulation or windows indicated
they would not have installed the measure without the program incentive, and were
considered zero percent freeriders.
The Cadrnus Group, Inc. I Energy $ervices 52
Table 52. Frequency of Freeridership Scoring Combinations-HES InsulationAilindows
No No No No x x x Yes x x x 0o/o 25
Yes No Yes x Yes Partial Yes x x x x 50%19
Yes No Yes x Yes Partial Partial x x x x 25Yo 10
No No Yes x Yes Partial No x x x x }Yo b
Yes Yes x x x x x x x x x 100%6
No No Yes x Yes Partial Partial x x x x 13Yo 5
Yes No Yes x Yes Partial No x X x x lYo 5
No Yes x x x x x X x x X 100%5
No No No No x x x No No Partial No 1Yo 3
No No No Remove x x x x x x x 0o/o 3
No No No Yes Yes Partial No x x x x }Yo 3
Yes No Yes x Partial Partial Partial x x x x 13o/o 2
Yes No No Yes Partial Partial No x x x x lYo 2
Yes No No No x x x Yes x x x 0o/o 2
Yes No Yes x No Partial Yes x x x x }Yo 2
Yes No Yes x Partial Partial Yes x x x x 25Yo 2
Yes No Yes x No Partial Partial x x x x l%o 2
No No No No x x x No No Partial Partial 0o/o 1
No No No No x x x Partial Yes Partial Partial }Yo I
No No Yes x Yes Partial Yes x x X x 25Yo 1
Yes No No Yes Yes Partial No x x x x }Yo 1
No No No No x x x No Yes Partial Partial 1Yo 1
No No No Yes No Partial No x x x x }Yo I
No No Yes x No Partial No x x x x 1Yo I
Yes No Yes x Partial Partial No x x x x 0o/o 1
No No Yes x Partial Partial No x x x x }Yo 1
'*, on'l"l"P'Ynt8i?liiYg
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES ?S0S-2010 Final Report February 3,2CI12
Freeridership for appliance and insulation/windows participants can also be compared by looking
at the respondents' distribution by the freeridership score each one has been assigned. Figure 6
and Figure 7, below, show freeridership score distributions for appliances and
insulation/windows participants, respectively.
The Cadnrus Group, lnc. / Hnergy Services 53
,-n, on,X"""$In""'S:1iiiff;
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky fifiountain Fower lciaho ]-{E$ ?S0S-2010 Final Reporl Februany 3, ?S12
Figure 6. Distribution of Freeridership Scores-HES Appliances
a* zs^o+"
OItr5 20"il?t
E rs.ntu(,
# 1r.0x
5.0%
0-09b
12.5!.S t5.0s
Frearidership Score
50.0ti-100.0N
Figure 7. Distribution of Freeridership Scores-HES InsulationAilindows
5r)"oyh
30"[s
J.il^0s
L0;CIt\
0.il$ii
.....17"1$;...............
11.7S,
r10"0?d
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o
ou
{to.
12.5S) 25.0H 50.0Yd
Freeridership Sc,ore
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Approximately 55 percent of respondents installing insulation or windows showed no
freeridership, compared to 18 percent of respondents installing an appliance. Conversely, almost
55 percent of respondents installing an appliance were defined as 50 or 100 percent freeriders,
compared to only 27 percent of respondents installing insulation or windows.
Respondents were asked to explain, in their own words, the HES incentive's influences on their
decisions to purchase the equipment. A few responses follow below for those scoring as
100 percent freeriders (measures indicated in parentheses):
The Cadmus Sroup, inc. ,/Hnergy $env-ices s4
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Case No. PAC-E-14-07
nocry nn.o.y.$g.it pawe-r lda[o F{r$ 2s0s-?010 rinat Repo* .-.......-..... - #'[?'i{iilT,"#TI
o "Whenwe were purchasing the water heater [Retailer XJ told us about the program."
(Electric Water Heater)
o "I needed it anyway." (Dishwasher)
o "It didn't have anything to do with it because I didn't lvtow anything about it until after I
bought the washer.." (Clothes Washer)
o " I needed to get one anway. Regardless f they had it or not, I would have still got one. "
(Clothes Washer)
o "We saw the sticker lcnowing it was qualffied, but it didn't matter. I still picked out the
r efr iger ator I w ante d. " (Refriger otor)
o "I purchased them because I needed them. When I found out there was an incentive, I
applied for it. " (lYindows)
Spillover Analysis
This section presents a detailed analysis of additional, energy-efficient measures customers
installed after participating in the HES Program. While many participants subsequently installed
more energy-effrcient measures after receiving incentives from Rocky Mountain Power, the
analysis indicates only one-fifth of additional purchases were reported as significantly influenced
by HES Program participation; therefore, the four-fifths not significantly influenced cannot be
considered spillover. Additionally? some participants significantly influenced by the HES
Program applied for incentives for additional measures they installed, and could not be included
in the spillover analysis.
As detailed in Appendix I's spillover methodology section, Cadmus used adjusted savings values
from the deemed savings analysis to estimate spillover measure savings.
Cadmus estimated the spillover percentage for a program category by dividing the sum of
additional spillover savings, reported by participants for a given program category, by total
incentivized gross savings achieved by all respondents in the program category.
Table 53 shows spillover analysis results for all HES appliance and insulation measures.
Though indicating higher potential spillover savings, most residential participants installing
additional energy-efficient equipment reported the HES Program did not greatly influence their
purchasing decisions. Further, some applied for incentives for additional measures purchased.
Table 54 summarizes numbers of participants excluded from the spillover analysis due to
receiving incentives.
Table 53. Spillover Savings Analysis
The Cadmus Group, inc. i Energy Services qfi
Rocky Mountain Power
Exhibit No. 5 Page 658 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
RockyrUl?untain Power ldaho HES 2.9!9:2010 Final Report ._-"_ Febr.uary 3, 2012
Overall, surveyed HES Program participants highly influenced by the HES Program installed
5l additional measures. Participants received incentives for 16 of these measures, leaving
35 measures qualified for spillover savings. Table 55 displays 35 additional measures installed
by HES appliance and insulation/windows participants, qualifring as spillover. Of this 35,
insulation installed outside the HES Program accounted for the largest proportion of spillover
savings (59 percent).
Table 55. HES Spillover Measures
Aopliances Ceiling Fans 3 21 63
Aooliances CFLs 4 32 128
Appliances Clothes Washer 3 424 1,273
Aopliances Dishwasher 1 36 36
Aooliances Electric Water Heater 3 97 290
Aooliances Fixture 3 108 324
Aooliances lnsulation SO 4 1,189 4,758
Aooliances Refrigerator 2 oo 131
Aooliances Windows SO 4 276 1,105
Aooliances 8,107
lnsulationMindows Ceiling Fans 1 21 21
lnsulationMindows CFLs 3 32 96
lnsulationMindows Dishwasher 1 36 36
lnsulationMindows Electric Water Heater 1 97 97
lnsulationMindows Fixture 1 108 108
lnsulationMindows Refrigerator 1 66 66
lnsulationMindows 423
HES Overall Non-Liohtino 8,530
NTG Findings
NTG analysis results showed predictable trends. Appliance participants showed higher
freeridership levels than insulation/windows participants, consistent with Cadmus' previous
estimates in previous years for Rocky Mountain Power (and with similar programs and measures
Table 54. Effects of Program Influence and Incentives on HES Spillover
The Cadmus Group, lnc. / Energy Services $6
Rocky Mountain Power
Exhibit No. 5 Page 659 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Rocky Mountain tgwer ldaho i:lES 2009-2-0j..9 Finai Report ...f_e_!ru-aly_3, 2S12
at other utilities). NTG ratio ran somewhat higher for the 2009 and 2010 program years than for
previous years of other states in Rocky Mountain Power's service territory. Upcoming 2009 and
2010 NTG evaluations in other states may help determine whether increasing NTG ratios
represent a trend or Idaho presents an anomaly.
The HES Program evidences moderate participant spillover, which develops slowly, depending
on increased familiarity with energy efficiency and experiences with program-incented
measures. Because customers interviewed in 2011 participated in the HES Program during the
2009 and 2010 program years, adequate time had elapsed following program participation to
yield purchases potentially qualifring as HES Program spillover. If Rocky Mountain Power
interviewed 2011 HES Program participants about the program's influence on their additional
energy-effrciency purchases, lower spillover estimation levels would likely emerge.
Freeridership is More than a Ratio
Response distributions used for estimating average freeridership ratios contain information that
can help program managers more effectively manage their programs. In reviewing these
distributions, two notable issues emerged.
First, it appears HES Program's appliance components could become more efficient through
tightened eligibility requirements or different marketing. This study's survey asked respondents
whether they had installed equipment before hearing about the HES incentive. The 35 appliance
respondents answering "yes" were classified as freeriders. As shown in Table 56, removing the
"already installed" responses from analysis significantly lowered the freerider ratio for
appliances, falling from 33 percent to 23 percent.
*Unweighted estimates
The appliance measures' high freeridership levels may relate to a relationship between an
appliance's retail cost and the incentive's size. A recent study Cadmus conducted for a Pacific
Northwest utility tested the hypothesis that incentive levels affect freeridership. The study
graphed the proportion of total measure costs covered by the incentive with the freeridership
ratio found in the analysis.
As shown in Figure 8, a strong inverse relationship occurred between the proportion of the total
measure cost covered by the incentive and the freeridership ratio. The graph's upper left side
represents residential appliances, which typically offer small incentives relative to appliance
costs. Where incentive amounts do not affect purchasing decisions, high freeridership can be
expected. The trend line's righthand end represents nonresidential prescriptive and grocer
programs, which evidence low freeridership rates and incentives covering 60 percent of total
costs, per program records.
Table 56. Effect on Freeridership of Removing 'oAlready Installed" Responses
The Cadrnus Group, lnc. / Energy Services
Rocky Mountain Power
Exhibit No. 5 Page 660 of 1 355
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES 2009*2010 Final Report February 3, 2012
Figure 8. Proportion of Measure Cost Incented and Freeridership Ratio
Comparison of Total Measure Costs,
lncentives and, Free Rider Scores
6096
50%
4096
3096
2096
109{
00,{'
;
OYo 30?o 40o/o 50Yo 8096
lncentives as Percent of Total Measure Cost
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o
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The Cadmus Group, lnc. / Energy Services 5S
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Case No. PAC-E-I4-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HE$ 200S-2010 Final Report February 3, 2012
Process Evaluation Findings
This section provides detailed process evaluation findings for the HES Program. Findings
resulted from the previously detailed extensive data collection activities, including retailer/
confractor surveys, program staff and market actor interviews, participant surveys, and secondary
research.
Program lmplementation and Delivery
Program Status
The HES Program provided cash incentives to residential customers for purchases of energy-
efficient products, home improvements, and heating and cooling equipment and
services. Implementation staff described the HES Program as an d la carte, energy-efficiency
program, allowing customers to install multiple measures to create customized efficiency
portfolios. The HES Program operated under a basic premise to "allow customers to pick what
they need and apply for an incentive." Accessible to all customers (even those who a.re not
homeowners), the HES Program provided energy-saving opportunities for Rocky Mountain
Power's entire customer community. According to the program implementer, Idaho's HES
program fell short of meeting its goals in2009, but increased participation and savings numbers
to reach Rocky Mountain Power's savings foreeast in 2010.
Delivery Structure and Processes
For most qualifring program measures, customers received incentives through a mail-in process,
administered by the implementer. However, because the HES Program's lighting component
used an upstream mechanism, the program implementer paid lighting incentives directly to
manufacturers of qualifying light bulbs. Local retailers and contractors supported the program
by: upselling their customers to higher-efficiency equipment measures; installing equipment and
service measures; and promoting available incentives. As part of the HES Program, Rocky
Mountain Power also offered incentives to contractors for meeting quality installation standards,
proper sizing, and tune-ups of qualified HVAC measures.
According to implementer staff, the program implementer primarily used an allocation system to
target lighting retailers. For each retail partner location, program implementer staff analyzed the
customer base, assigning stores an allocation ranking, determined by the percentage of Rocky
Mountain Power customers in that location. Targeted potential retailers needed a Rocky
Mountain Power customer base of 90 percent or higher to participate. The allocation ranking
sought to minimize leakage of incented bulbs to customers outside Rocky Mountain Power's
service territory.
Program stakeholders noted that program implementer staff working on Rocky Mountain
Power's HES Programs originally had not been assigned to specific states; rather;
implementation staff focused on all five states' programs. In 2010, the program implementer
began assigning staff to specific service territories, with state management positions created to
streamline program implementation within each individual state. Additionally, the program
implementer created a two-channel structure to better manage relationships with participating
retailers and contractors (trade allies) in each state. Implementer staff divided into two teams,
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focusing entirely on either retailer or contractor channels. A channel manager assigned to these
teams assumed responsibility for all relationships and activities tied to their respective delivery
channels.
The contractor channel is segmented by types of contractors working with the HES Program.
Table 57 defines different contractor types participating in the program and each category's
requirements.
In addition, HVAC contractors held to the following participation requirements:
o Read and agree to abide by terms outlined in the Contractor Program Manual;
. Submit a completed participation agreement;
. Submit a completed W-9 form;
. Hold a valid state business and contractor license;
o Hold general liability insurance and worker's compensation in amounts required by
the state;
. Supply three satisfactory customer references and three satisfactory trade references to
the program;
o Have no unresolved claims with the Better Business Bureau; and
o Agree to participate in the program's quality control (QC) process.
In Idaho, select HVAC measures qualified for split incentives, which were paid to participating
contractors and customers. The contractor could receive a portion (no more than half) of the
incentive for installing the measure, and the customer received the remaining portion after
installation. These incentives fuither motivated Idaho contractors to participate in the program
and promote qualiffing measures to their customers.
bi-i
Table 57. Types of HES Contractors
Participating weatherization
contractor
lnstall eligible weatherization
measures
Must attend program haining
and meet Rocky Mountain
Power's installation quality
standards
Must meet Rocky Mountain
Power's installation quality
standards
Participatin g HVAC contractor
Sellqualified HVAC products to
customers, but do not install the
Meet standard participation
requirements (these are
Qualified HVAC contractor
Offer installation services to
customers in addition to selling
qualified HVAC measures
Must successfully complete
program approved training in
addition to meeting the
standard participation
Eligible for program
dealer incentives
The Cadmus Group, lnc. / Energy Services
Rocky Mountain Power tdaho HES 2S09-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 663 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
February 3, 2012
As noted in the Evaluated Gross and Net Savings Methodology, Cadmus conducted telephone
surveys with retailers and contractors, as well as with appliance, HVAC, and lighting customers.
For the process evaluation, Cadmus refers to these groups as indicated in Table 58.
TariffApproach
A tariff represents the rules of engagement for a conservation program. Tariffs are very detailed,
specifring: exactly which measures are offered; eligibility specifications for each measure;
incentives offered; and the market eligible to participate. These strict guidelines must be adhered
to during the time frame established by the tariff.
In 2010, Rocky Mountain Power changed its tariff approach. Rather than filing a tariff with
specific qualifications listed for each measure, revised language allowed specifications to
flexibly align with ever-changing ENERGY STAR specifications. This allowed program staff to
change qualifications for eligible measures without making formal tariff changes every time
ENERGY STAR specifications changed (which can be a time consuming process).
This proactive tariff approach allowed program staff to take advantage of increasing federal
efficiency standards without having to refile measure specifications with each technology
improvement. According to implementer staff, the change has been an HES program success,
allowing program stakeholders to anticipate and adjust to changes.
Implementation Challenges
As the smallest of Rocky Mountain Power's territories, Idaho's implementation needs could be
overlooked if resources were needed in one of the larger territories. According to program staff,
Idaho's 2010 program year faced challenges primarily due to an out-of-date tariff, which had not
been updated to account for lighting incentives on CFL multipacks and specialty bulbs, and,
therefore, did not provide savings and participation numbers as robust as those in other
territories.
Although implementer staff proposed tariff changes to be filed at the end of 2009, other
territories' frlings took priority. Program staff admitted: "...being a smaller state, Idaho kept
getting pushed to the side. To add another filing when you are trying to file in two other states is
just impossible; we just don't have the people to be able to do that."
Implementer staff anticipated Rocky Mountain Power's new tariff approach should resolve this
issue.
According to implementer staff, delivering the HES Program's lighting component also proved
challenging. Rocky Mountain Power's territory overlapped with other utility territories
Table 58. Survey Respondents Reference Guide
Participant Retailer/Con tractor
Participant Retailer/Contractor Survey respondents who indicated they sold lighting products
Participant Telephone Survey respondents (including appliance, HVAC, and weatherization
The Cadmus Group, lnc. i Energy Services 61
Rocky Mountain Power
Exhibit No. 5 Page 664 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES 2009-2010 Final Report Febnuary 3, 2012
throughout the state, which created opportunities, but also created confusion and presented
barriers for implementer staff. In addition to out-of-date lighting incentives written into the tariff,
Rocky Mountain Power did not have broad coverage in Idaho, making it diffrcult to reach the
90 percent allocation rate to target lighting retailers. Implementer staff found several retailers
only served 70 to 80 percent of Rocky Mountain Power customers, and, in turn could not be
targeted to participate in the program.
To increase lighting savings in the Rocky Mountain Power's territory, implementer staff began
reaching out to other Idaho utilities, procuring agreements to "buy the bulbs" Rocky Mountain
Power customers buy at lighting retailers, where neighboring utilities incent high-efficiency
bulbs. Rocky Mountain Power had to reimburse the other utilities' incentives for these bulbs to
claim savings from their customers' purchases. Implementer staff found building relationships
with competing utilities challenging, commenting: "The relationship needed to coordinate the
lighting program is not where I wish it would be." Building these relationships, however,
remains essential to the program's success.
Idaho's unique retail structure also presented obstacles for implementer staff. With the state's
much smaller national retailer presence than Rocky Mountain Power's other service territories,
local retailers play a larger role in Idaho's HES Program. In states with more prevalent national
retailers, program staff noted the program implementer only had to contact one representative at
a retail chain's corporate office, and the corporate representative communicated with all of the
chain's locations within the Rocky Mountain Power service territory in that state. In Idaho,
however, none of the surveyed trade allies learned of the program through their corporate offices
(see Figure 15, below).
Recruiting participating contractors in Idaho also proved difficult; generally, the contractor pool
did not have the qualifications of those in other territories. Program staff reported they
encouraged Utah contractors to expand their business into Idaho, heightening the work quality
available to Idaho customers. Per program staff, no protocol tracks whether Utah contractors
actually cross state lines to perform HES Program installations in Idaho.
"Blow and go" insulation contractors also challenged Idaho's program. Due to the generous
incentives available, Idaho insulation contractors tried to complete as many insulation jobs as
possible, representing themselves as employees of Rocky Mountain Power and doing poor
quality work. This issue upset many customers, prompting multiple complaints to the Public
Utilities Commission. Rocky Mountain Power addressed the issue by adjusting the incentive
amount, and clearly defining incentive qualifications in the tariff. According to program staff, the
tariff changes "drove away the riff-raff'; so only quality contractors continued to work for the
program.
These barriers led Rocky Mountain Power and the program implementer to increase field staff to
raise their local presence and delivery capacity in Idaho. Starting in 2010, the program
implementer added locally based staff to increase program outreach to individual retailers and
qualified contractors. Implementer staff reported needing more staff on the ground to deliver the
message and engage prospective customers in the program. The program implementer's field
staff now visits trade allies every month, recruiting new retailers and contractors, and expanding
relationships with participating trade allies.
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Energy Independence and Security Act
EISA, an omnibus energy policy law requiring 25 percent greater efficiency for light bulbs, with
new standards phased in from 20l2tt'rough2074,2a effectively phases out 100-, 75-,60-, and 40-
watt incandescent light bulbs currently in the market. EISA standards will eventually phase out
the current lighting savings baseline in the DSM market. Program staff noted Rocky Mountain
Power is working to diversifu its lighting portfolio in response to EISA legislation, offering
program incentives for all energy-efficient lighting options, including an expanded selection of
specialty CFLs. In addition, EISA will require informative Lighting Facts labels be displayed on
all light bulb packaging. Figure 9 shows an example of the type of label that will be required.
Figure 9. Sample Lighting Facts Label
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In-territory lighting survey responses indicated lighting customers preferred CFLs to other
energy-efficient lighting options. When presented with a choice to purchase a more efficient
incandescent bulb or a CFL, LED, or halogen bulb, 40 percent of lighting customers chose CFLs.
Only 3 percent claimed they would purchase halogen bulbs. Figure 10 illustrates the fulI
distribution of choices lighting customers made regarding energy-efficient lighting technologies.
"Something else" responses included: "depends on the price," "some of each," and "whichever
[bulb] is cheaper."
'o http ://www .epa.gov I cfl/
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Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Pg]ryerElglo. i-{ES 2009-201_0.Fin-a.l..BgQglt-. _._ Fg.Uruary 3, 2012
Figure 10. Enerry-Efficient Technologies Lighting Customers are Most Likely to Purchase
I CFL
S lncandescent bulb
S LED
I Halogen
ffiiSomething else
f; Don't know
Rocky Mountain Power lD HES Residential Lighting Survey Question J2.
EISA Awareness
All seven surveyed lighting retailers expressed familiarity with the EISA legislation. Fifty-seven
percent of lighting retailers indicated their stores had already started changing stocking practices
to prepare for EISA, and an additional 29 percent reported plans to implement such stocking
changes. Such practices included phasing out incandescent inventories and increasing stocks of
energy-efficient bulbs, such as CFLs and LEDs. Seventy-one percent of lighting retailers planned
to educate consumers about EISA, using marketing materials such as in-store displays,
brochures, and flyers.
Half (50 percent) of surveyed lighting customers knew of impending EISA changes (per the in-
territory lighting survey). Two of the three lighting retailers receiving feedback from customers
regarding EISA found customers upset about the upcoming change in lighting availability. The
other lighting retailer stated customers welcomed receiving EISA information provided by their
store.
Familiarity with Energy-Effi cient Lighting O ptions
Of 250 in-territory lighting customers responding to the familiarity questions, 82 percent
recognized the terms "compact fluorescent bulb" or "CFL" before hearing a description of the
bulb's twisted shape. Surveyed lighting customers primarily reported being "somewhat familiar"
with CFLs (50 percent). Figure 11 illustrates familiarity with CFLs reported by surveyed lighting
customers.
The Cadrnus Group, lnc. I Energy $ervices s4
Rocky Mountain Power ldaho l"lES 2009*2S10 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 667 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
February 3, 2012
Figure 11. Familiarity of CFLs Among Lighting Customers*
(with 907, Confidence Intervals)**
60%'t
2%T
..............".. -..........ffi
Very Familiar Somewhat familiar Not too familiar Not at all familiar
n= 249
Rocky Mountain Power lD HES Residential Light Survey Question C3.
* "Don't know' responses removed from this figure.
**Nearly all reported values fell within a t10 percent interval with 90 percent confidence. To ensure an apparent
uncertainty level for this analysis, the report provides confidence intervals (represented by the black line) around
summary results, where appropriate. Appendix C provides a more detailed discussion of this methodology.
Trade allies recognizedcustomers' awareness of CFL bulbs. Twenty-two percent2l of trade allies
considered, of all energy-efficient products sold, CFLs were the most widely-known by
customers, and were most likely to be purchased without requiring additional advertising. Survey
respondents generally did not draw a distinction between standard and specialty CFLs in terms of
customer awareness. However, availability of energy-efficient induction lighting, bright white,
and daylight CFLs came up separately during interviews as being least known by customers.
CFLs only trailed clothes washers and dryers as energy-efficient products with which customers
were most familiar.
In addition to high CFL awareness, more than half of lighting customers (63 percent) knew of
LED bulbs. However, only 5 percent actually purchased LEDs for standard lighting sockets in
2009 and 2010. Eighty-three percent of lighting customers reported replacing incandescent bulbs
in their homes with CFLs.
CFL Concerns
Although lighting customers expressed familiarity with CFL bulbs and preferred the technology
over other energy-efficient lighting options, Cadmus' lighting survey indicated lighting
" Multiple responses allowed.
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o,Ii zoNr
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The Cadmus Group, lnc. i Energy Services 65
Rocky Mountain Power
Exhibit No. 5 Page 668 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES 2009*2010 Final Report February 3, 2012
customers had concerns regarding CFLs. As shown in Figure 12, unsatisfied lighting customers
expressed concems about bulb lifetimes, lighting quality, and mercury content.
Figure 12. Reasons Lighting Customers are Dissatislied with CFLs
(with 907o Confidence Intervals)
50o/o
45%
40%
35%
3Oo/o
25%
20%
o6
oCL
oc,
o
tro(,
or 75o/o
10% -i -
5%
Short lifetime Not bright
enough
Slow to warm
up
Mercury
conte nt
High price
n=4L
Rocky Mountain Power lD HES Residential Lighting Survey Queston G3.
Cadmus' in-territory lighting survey also found most lighting customers did not utilize proper
disposal methods for CFLs. Of lighting customers having CFLs burn out in their homes within
the past 12 months, 83 percent threw the bulb in the trash. Only l l percent recycled the bulb
appropriately. Only one surveyed lighting customers had been to the Rocky Mountain Power's
CFL disposal Webpage to learn about proper CFL disposal.
Seventy-four percent22 of lighting customers did not express concerns about CFL disposal;
however, of customers reporting having concerns, 13 percent23 mentioned mercury content.
Figure 13 illustrates distributions of lighting customers' disposal concerns.
'2 Multiple responses allowed,
2' Multiple responses allowed.
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Case No. PAC-E-14-07
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Figure 13. Concerns with CFL Disposal among Lighting Customers
(with 907o Confidence Intervals)
None
Mercury
Requires special disposal
Rocky Mountain Power lD HES Residential Lighting Survey Question K6.
Marketing
Approach
Program marketing materials in Idaho initially drew upon HES Program marketing in other
territories. Implementer staff, quickly realizing customized marketing messages might prove
more effective in Idaho, developed key messages to resonate within Rocky Mountain Power's
various territories. The tone,language, and colors of marketing materials adopted an Idaho focus.
Implementer staff estimated the multi-purchase HES Program customer market in all five states
increased by 50 percent from 2008 to 2009, and another 30 percent from 2009 to 2010, due to
this marketing change.
Rocky Mountain Power and the program implementer created and distributed program marketing
materials, with Rocky Mountain Power using bill inserts, radio ads, print ads, newspaper ads,
and other print media to market the program. The program implementer provided point-of-
purchase displays, aisle violators, incentive applications, brochures, Rocky Mountain Power-
branded CFL price tags, and cling-on advertisements (product clings) to aid the program's trade
allies in promoting the program.
Effectiveness
According to participant telephone survey results, retailers provided the most effective program
promotion avenue. Forty-one percent of appliance and weatherization participants first heard
about the HES Program through retailers. As shown in Figure 14, appliance and weatherization
participants reported bill inserts (16 percenQ and word of mouth (14 percent) as other common
sources of program awareness. Twenty-three percent of appliance and weatherization
participants first heard about the HES program through a variety of other communication
channels, but none of these comprised more than 8 percent of the total.
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Case No. PAC-E-14-07
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Rocky Mountain l?wer ldaho HES 2009-2010 Finat Report _ ... Febrgary 3, 2013
Figure 14. How Appliance and Weatherization Participants First Heard about the Program
I Paid media (Print ads,
billboards, W, radio, etc.)
#..I Online
S Rocky Mountain Power
representative
I Other
N Don't Know
n=378 i......^..^^..^^^.*-....-J
Rocky Mountain Power lD HES Participant Survey Question M1.
Eighty percent of lighting retailers (and 77 percent of trade allies overall) mentioned receiving
point-of-purchase marketing materials from program staff. Forty-eight percent of surveyed trade
allies found posters or product clings the most useful marketing materials they received. Other
useful materials (each mentioned by two trade allies) included applications to hand out to
customers, and flyers or brochures. Despite lighting retailers' reported use of point-of-purchase
materials to increase program participation, only 6 percent of lighting customers knew Rocky
Mountain Power discounted CFLs through the HES Program. Of customers aware of the lighting
discounts, 25 percent learned of the program through bill inserts.
Surveys also found participants rarely accessed HES Program information online: 25 percent of
appliance and weatheization participants and only two lighting customers had visited the HES
Website.
Trade Ally and Market Partner Promotion
According to program stakeholders, trade allies proved key to increasing program awareness
among customers. The program implementer worked directly with retailers and contractors to
ensure they knew of the program and its incentives, providing them with promotional materials.
Retailers and contractors, in turn, promoted the program to customers to increase sales of high-
efficiency equipment and products.
As Idaho's retail structure relied heavily on local retailers, implementer staff shifted their
outreach focus from national retail chains to smaller, independent retailers. According to the
implementer, retailer staff provided a key source of information for customers. The program
implementer specifically pointed to independent retailers as the reason the HES Program
achieved its savings, noting independent retailers allowed implementer staff to train store
employees how to explain the program at the customer level. Further, independent retailers
allowed implementer staff to conduct contests to motivate sales associates to sell more energy-
ffiWord of mouth
The Cadnrus Group, lnc. I f;nergy $ervices 6S
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Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
8g.g[y-Mountain Foj,i,er ldgtg_FES 2009-2010 Final Repo$_ .__ .__ February 3, 2012
efficient products and generate participation. National chains do not allow such activities due to
corporate policies.
Participant retailer/contractor surveys indicated 30 percent of participating retailers and
contractors learned of the HES Program through calls or visits from HES field staff. However, an
additional 13 percent reported Rocky Mountain Power as their information source. These
respondents may have mistakenly identified implementer staff as utility representatives. Further,
74 percent of trade allies found HES field staff "very helpful" in addressing their needs. Trade
allies reported learning of the program through the methods illustrated in Figure 15.
Figure 15. How Trade Allies Learned About the HES Program
N Colleagues
N Rocky Mountain Power
I HES Website
$, other
N Don't know
n=23
Rocky Mountain Power lD HES Retailer Participant Survey Question C1.
Almost all trade allies surveyed (83 percent)24 reported often or always recommending energy-
efficient options to customers. Trade allies surveyed found product clings (26 percent)2s and
simply talking with customers (22 percent)26 the most effective marketing tactics. Two trade
allies also mentioned posters as effective marketing materials. When asked to provide
suggestions for changing marketing materials, three trade allies simply wanted more materials or
larger signs, and one requested reimbursement for flyers the store created to promote the energy-
efficient products incented by the program.
More than half the trade allies (57 percent)2i reported informing their customers of available
incentives by citing the program when talking to customers. Trade allies also reported using
product clings and print ads as other typical means to inform customers of available incentives.
Figure 16 depicts ways trade allies informed customers of available incentives for energy-
efficient products.
2o Multiple responses allowed.
25 Multiple responses allowed.
'u Multiple responses allowed.
27 Multiple responses allowed.
I HES field staff called or
stopped by
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Case No. PAC-E-14-07
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Rocky M-qu.ntajn P_Ur_g.r..l{g[o i-lES 2009*2Q]9- rinal Report __ - Fe.lgg.ry 3, PJi
Figure 16. Trade Allies' Methods of Informing Customers of Incentives Available for
Qualiffing Enerry-Efficient Products (with 907o Confidence Intervals)
Mention program when talking to
customers
Print ads
Product clings on qualifying
appliances
Posterson retail floor
Television ads
Rebate applications
Don't need to inform; customers
already know
Don't know
Materials Review
Cadmus reviewed program promotional material for HES; the following key findings present
high-level findings from this review:
. Rocly Mountain Power uses a well-constructed HES strategic marketing plan: The
2010 plan includes best practice tactics, providing the appropriate range of media and
retail channels to drive participation.
o lVattSmart branding allows greater flexibility: The global WattSmart brand provides
opportunities for cross-marketing between and within HES programs, and for greater
customer awareness.
o ldaho territory characteristics make HES program marketing more chollenging:
Program implementer staff resource limits, fewer trade allies, and close boundaries of
other utility service territories present market penetration difficulties.
o HES Program marketing collateral presents a consistent look and feel: Point-of-
purchase, bill inserts, md other collateral consistently include uncluttered and clear
designs, bold colors, and large typefaces.
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o HES Program marketing collateral provides consistent messaging: Marketing content
for trade allies and end-user customers includes basic calls-to-action and motivating
messages, helping all stakeholders choose program measures and easily share
information with friends, family, and colleagues.
o Promotional programs coordinated by the implementerfor the retailer help drive retail-
level marketing supparf Quick qtizzes and gift card contests help drive excitement and
promotional effort by retail staff.
o Online marketing information does not include service-territory segmented messaging,
as described by program staff: HES program information online is the same for every
state section.
o The lVebsite does not offer marketing collateral materials available for downlood: The
marketing plan includes creating this resource, but has not been made immediately
accessible via clear navigation.
o Marketing metrics and tracking appear unavailable.' Source code tracking tactics,
identified in the marketing plan along with associated results, could not be reviewed due
to unavailability.
Table 59 and Table 60 compare current HES marketing plan elements to best practice elements
in energy-efficiency program marketing. Findings indicate Rocky Mountain Power currently
utilizes a significant majority of best practice marketing channels (Table 59), and the program
Website largely utilizes common efficiency program online marketing best practices.
The Cadrnus Group, lnc. i Energy Services 71
E h i bit il":"YPYsTSfl :iiYg
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Ro__gky l\{ou.nt-qin .P.o]v-gl_ldp.h.o*!lFS-?.90-$--2010 Fimal Report _ February 3, 3QJ 2
Table 59. HES Program use of Best Practice Marketing Channels
Direct Mail {
Newspaper Ads /articles {
RadioffV Ads .v
Online Advertising v
Website ./
Customer lnformation Sheets ./
Contractor lnformation Sheets v
Telemarketrng
Bill lnserts ./
Brochures {
Newsletters {
Presentations/Meetin gs .i
Events ,V
Referrals ./
Point of Purchase {
Branded Promo ltems {
Tests/Demonstrations v
Social Media Outreach *Generally Via Rocky Mountain Power
*Social media (e.9., Twitter, Flickr, YouTube, Facebook) offers channels for utilities to
connect with customers. Most utilities leverage one or more social media platform(s) in
their commu n ication efforts.
The Cadmus Group, lnc. I Energy Services 72
Rocky Mountain Power ldaho HE$ 3009*2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 675 of I 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
February 3,2012
Table 60. HES Program use of Website Best Practices
Program highlighted on Rocky Mountain Power home page Yes
Number of Clicks from Rocky Mountain Power home page 2or 3
Description leads with benefits (i.e., What's in it for the participant?)WattSmart Programs and
lncentives or Save Enerqy
Message consistency from Rocky Mountain Power home to subpage Yes
Clear call to action Strong and active
Many access ooints Yes
Contact capture No
Description of each individual program offered Yes
Participant eligibility requirements Yes
Contractor participation and eligibility requirements Available via ohone inouirv
Contractor Listing Yes
Conhactor Search Enoine No
0nline Contractor Applicatlon Process No
Downloadable lncentive Forms Yes
Online lncentive Application Process No
Downloadable program information in print format for contractors to share with customers No
HES Social Media elements included (e.9. Facebook, Twitter, etc.)No
Quality Assurance
The program implementer conducted on-site QC inspections on 5 percent of all HVAC and
weatherization installations, ensuring "service measure" installations have been conducted to
HES Program standards.
The pass rate of these inspections served as a component in determining the program's overall
effectiveness. However, conducting these inspections proved costly in a territory such as Idaho.
In territories with dispersed population centers and less volume, implementers found QC staff
could not be cost-effectively maintained at all times. Though implementer staff recognized
inspection staff could not be maintained cost-effectively in every state, they questioned how
otherwise to conduct the QC inspections within 45 days of the equipment's installation.
The program implementer also performed quality inspections at all participating retail locations.
The program implementer's quality assurance (QA) protocol held participating retailers
responsible for correctly displaying all provided promotional materials. The program
implementer visited each store to ensure marketing materials remained up to date, to take
pictures of all displayed promotions, and to confirm appropriate display of marketing materials.
The program implementer also checked correct price displays and Rocky Mountain Power's
logo, and verified products on display were qualified products.
In 2010, the QC process for verifuing program data changed. Implementer staff utilized a
business rules engine to validate program data, where, as in the past, data entry staff had
conducted visual checks. As data came in through incentive applications, implementer staff
The Cadmus Group, lnc. I Energy $ervices
Rocky Mountain Power
Exhibit No. 5 Page 676 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
RockL_U!-o.u.nlqi!_.Power tdaho HEs 200$*2911 ftg.l Re_p-.o.* . *.[-qbluary 3, 2012
entered the data into a tracking system. The business rules engine then verified all data entered
were consistent with those eligible for incentives. If data fell outside the parameters written in
the tariff, they were rejected. Data rejection most commonly occurred if missing information, or
application data did not meet incentive qualifications.
Implementer staff estimated 20 percent of the business engines' rejections resulted from missing
information. Implementer staff tried to resolve these rejections by redesigning the incentive
applications. If information was missing, the implementer sent the customer a leffer detailing
missing materials. If no response occurred within two weeks, another letter was sent. If the
second letter did not generate a response, a third and final attempt for resolution was to send the
application back to the customer, with an explanation of information missing. Implementer staff
approximated 70 percent of missing information issues were resolved after the first letter, and
95 percent were resolved after the second letter. Another 3 percent of these issues were resolved
after the third attempt for resolution from implementer staff.
If measure data specified on an application did not qualiff for an incentive, implementer staff
sent a letter to the customer, explaining the specific reasons why their application was not
approved for an incentive, and offered solutions for ways the customer could quickly resolve the
issue.
Rocky Mountain Power's call center handled customer complaints, with call center agents
attempting to resolve issues on the first call. If customers had more serious complaints, the call
agent contacted the appropriate program manager at Rocky Mountain Power or the progftlm
implementer. The agent directed all customer complaint correspondence to Rocky Mountain
Power's regulatory group for recording. The program implementer program staff personally
called customers to resolve their issues. Customer complaints regarding participating trade allies
were taken very seriously. If several customers complained about a trade ally, the program
implementer informed Rocky Mountain Power, which usually removed the retailer or contractor
as a promotional partner. In extreme cases, Rocky Mountain Power could take legal action
against the trade ally in question.
A customer might also complain to the public utilities commission. In such cases, Rocky
Mountain Power took a more formal approach. The program implementer provided all customer
correspondence data to Rocky Mountain Power's regulatory group. Correspondence data
included any e-mails, phone conversations, meeting dates, and meeting summaries with any
party involved in the complaint. Rocky Mountain Power's regulatory group then coordinated the
customer complaint with the commission until the issue was fully resolved.
Customer Response
Satisfaction
Overall, appliance and weatherization participants expressed strong satisfaction with the
incentives' timing and amounts (as drawn from the participant telephone surveys). However,
some important differences in satisfaction emerged between customers with appliance or HVAC
measures installed and those customers with weatherization measures installed. Forty-four
percent of participating appliance customers received incentive payments within four to six
weeks of submiuing their incentive applications, and an additional 16 percent received payments
in less than four weeks. Among insulation customers, however, only 21 percent received
The Cadmus Group, lnc. I Hnergy Services v4
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Case No. PAC-E-14-07
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payments in four to six weeks. Further, 3l percent of insulation customers reported their
payment taking more than eight weeks to arrive, compared to 10 percent of customers who
installed other measures. While 90 percent of appliance customers expressed satisfaction with
the time required to receive their checks in the mail, less than half (48 percent) of insulation
customers expressed the same satisfaction level. Insulation customers generally expressed
dissatisfaction due to excessive paperwork, waiting for incentives for a much longer time than
promised.
Despite dissatisfaction with long wait times for incentives, a larger percentage of insulation
customers (79 percent) said they were "very satisfied" with incentive amount received, compared
to appliance customers (51 percent). Only 3 percent of customers overall reported being not very
or not all satisfied with their incentive amount.
While insulation customers were more likely to have measures installed by a contractor,
compared to customers purchasing other measures (97 percent compared to 53 percent), both
participant groups were "very satisfied" with the work done by their contractors (88 percent).
Customers also expressed strong satisfaction with measures purchased through the HES
Program. Ninety-four percent of appliance and weatherization participants reported being "very"
(75 percent) or "somewhat" (19 percent) satisfied with measures purchased through the HES
Program. Eighty-one percent of lighting customers were "very" (41 percent) or 'osomewhat"
(40 percent) satisfied with CFLs currently installed in their homes, and 66 percent were "very"
(58 percent) or "somewhat" (8 percent) satisfied with LED bulbs they purchased in 2009 and
2010.
Surveyed appliance and weatherization participants generally expressed high customer
satisfaction levels. As shown in Figure 17, 94 percent of appliance and weatherization
were "very" (53 percent) or "somewhat" (41 percent) satisfied with their overall
HES Program experience.
Figure 17. Appliance and Weatherization Participant Satisfaction with the HES Program
I Very satisfied
NSomewhat satisfied
ffi Not very satisfied
il Not at all satisfied
:r:r:r Don't know
7%L%
The Cadnru* Grnup, lnc. I Energy Services
E,h i bit f":"ypys?ifl :ii:fJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Ro_cllt Mggntain Power ldaho HES.*2-00-k2*81.0 Final Report ....[_q!ry-a$ 3-?012
Rocky Mountain Power lD HES Participant Telephone Survey Question F9.
Cadmus compared Idaho HES Program's overall satisfaction rating to appliance and
weatherization customer satisfaction of the HES program, and to similar progftrms in other
service territories. As shown in Table 61, satisfaction results generally ran high for prescriptive
incentive progftIms. All programs compared, including Idaho's, reported satisfaction between 84
to 98 percent, with Idaho's HES program at the satisfaction level midrange.
Barriers
Perceptions Regarding Energy Effi ciency
During management staff and partner interviews, HES
economy, coupled with a lack of general knowledge
presented a participation barrier for the program.
Despite these perceptions, 92 percent of surveyed trade allies believed customers understood the
energy-related benefits of higher-efficiency products. Twenty-six percent2s of trade allies
reported energy savings and environmental benefits as selling points for energy-efficient
products. In addition, almost two-thirds of surveyed trade allies (65 percent) reported a typical
customer as "somewhat interested" or "very interested" when told about the energy-saving
potential of ENERGY STAR appliances. More than two-thirds (70 percent) used availability of
high-efficiency products to attract customers to their businesses.
Surveys of appliance and weatherization participants deviated from the opinions of program
trade allies. While 22 percerrte of appliance and weatherization participants were motivated to
purchase high-efficiency equipment to save energy, 40 percent3o simply needed new equipment.
Figure 18 illustrates the ful1 distribution of appliance and weatheization participants' purchasing
motivations.
2t Multiple responses allowed.
2' Multiple responses allowed.
'o Multiple responses allowed.
program staff expressed that the poor
regarding energy efficiency in Idaho,
Table 61. Benchmarking of Satisfaction Results
A Midwest Utility Rebate Program
The Cadrnu$ Group, lnc. i Energy $ervices /tl
E,hibitf"""yPys""'si?tiil'g
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mounlg_in Power lda.|o HE$ 2,S_0--9*201.0_Final Report February 3, 2Ql2*
Figure 18. Factors that Motivated Appliance and Weatherization
Participants to Purchase a Quali$ing Measure
Old equipment didn't work/ working poorly
Wantedto save energy
Wanted to reduce energy costs
Other
The program incentive
Maintain or increase comfort of home
Word of mouth
Environmental concerns
Don't know
20% 30% 4Oo/o 50%
n=379
Rocky Mountain Power lD HES Participant Telephone Survey Question M4
Economic Constraints
According to implementer staff, economic pressures across the country reflected customers'
tendency to prioritize costs in their purchasing decisions. Trade allies confirmed this: when asked
why they believed customers chose not to participate, 35 percent3l of trade allies replied energy-
efficient measures were too expensive. Further, the majority of trade allies (61 percent)32
reported potential cost savings tended to sell high-efficiency products.
Trade ally suggestions for broader program improvements included increasing incentive amounts
(or pairing them with tax credits); however, most trade allies (61 percent) reported incentives
were set at the right levels.
Cadmus compared Rocky Mountain Power's 2010 HES incentive levels for a variety of
measures to those of other utilities in Idaho, including: Avista Utilities; Idaho Power; Kootenai
Electric Cooperative (KEC); and Questar. Research revealed HES presented competitive
incentives. A portion of trade allies believing incentives were not set at correct levels suggested
increasing incentive amounts, however, as shown in Table 62, Rocky Mountain Power's
appliance, HVAC, and weatheization incentives compared to other utilities studied. Further,
Rocky Mountain Power offered a wider variety of HVAC measure is than other Idaho utilities.
3' Multiple responses allowed.
" Multiple responses allowed.
o
coCL6oc,
o
co
or
to%
I
The Cadrnus Group, lnc. I Energy Services 77
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Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Socky Mountain.Power*l$aho HES 2009-201.0.Fjn31.-Beport February 3, 2012
Sources: Avista: http://www.avistautilities.com/savings/rebates/PagesMashingtonandldahoCustomerRebates.aspx
ldaho Power: http://www.idahopower.com/EnergyEfficiency/Residential/default.cfm?tab=Residential
KEC: http//www.kec.com/rebates.php
Questar: http//www.thermwise.com/utindex.html
Communication
To ensure program success, the program implementer communicated with program staff and
trade allies through channel teams. The retailer channel offered close relationships with store
staff at every location, while the program implementer focused on exciting store personnel about
the program, and disseminating information to as many qualified retailers as possible. The
retailer charrnel also offered freld staff an opportunity to conduct on-the-ground outreach to store
stafe to ensure they understood all program aspects.
The program implementer's contractor channel worked similarly to the retailer channel. The
team reached out to contractors, informing them of the program, and attempting to recruit new
participants. Once contractors agreed to participate, the contractor channel team met them in the
field for training on how to discuss the program with customers and promote program measures.
Rocky Mountain Power and program implementer staff agreed the channel structure served as a
very effective communication tool.
Summary and Recommendations
Rocky Mountain Power implemented several changes in 2010 to program operations, delivery
structures, and marketing approaches, leading to significant improvements in participation and
savings. Specifically, from 2OO9 to 2010,33 participation and reported savings increased
39 percent and 144 percent, respectively. Conclusions and recommendations have been drawn
33 According to a comparison of the 2009 Demand Side Management Annual Report and the 2010 Energy
Efficiency and Peak Reduction Annual Report.
Table 62. Benchmarking Idaho Utitity Incentive Levels
Clothes Washer $50 - $100 $50 $50 $30 - $70 $50
Dishwasher $20 $25 N/A N/A N/A
Water Heater $50 $50 N/A $50 - $1 50 $50 - $350
Reftigerator $20 $25 $30 $15 N/A
lnsulation (Attic)Up to $0.50
oer s0.ft.$0.25 per sq.ft.$0.15 per sq.ft.$0.35 per sq.ft. -
$ 1 .1 2 0er sq.ft.
$0.07 per sq.ft. - $0.20
oer s0.ft.
lnsulation (Wdl)Up to $0.50
oer so.ft $0.50 per sq.ft.N/A 0.35 per sq.ft. -
$1.12 oer s0.ft.$0.30 per sq,ft,
Ceilinq Fans $20 N/A Up to $20 N/A N/A
Evaporative Cooler $1 00 N/A $1 50 N/A N/A
Heat Pumps $250 - $350 $200 - $400 $750 $300 - $1,300 N/A
The Cadrnus Group, lnc. I Energy $ervices
Rocky Mountain Power
Exhibit No. 5 Page 681 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C, Hymas
Rocky Mountain Power ldaho HES 2009*2010 Final Report February 3,2012
from process evaluation interviews, surveys, and other analysis conducted. While Cadmus'
process evaluation found several HES Program operations and delivery aspects have improved,
the program may benefit from additional changes to provide additional value to customers,
prepare for upcoming changes in the lighting market, and continue to increase participation and
savings results as the HES Program matures.
Some of the following conclusions include recommendations, while others indicate the current
approach appears to be working well.
Program Design and lmplementation
o Management of retailer and contractor delivery channels by the program implementer
provides the structure for communication and program success among program
implementers and trade allies. The program implementer's revised delivery structure
has reduced many of the HES Program's implementation barriers by streamlining
program staff responsibilities, creating a mechanism for building relationships with
retailers and contractors, and increasing the total number of trade allies promoting the
program to end-use customers.
o The implementation of a Jlexible tariff approach provided a positive change for the
Idaho HES Prograza Allowing for "floating specifications" in the tariff will ensure
program requirements evolve with ENERGY STAR specifications. The proactive
approach will also alleviate administrative burdens of filing tariff changes.
o Customer complaints resultfrom unreliable insulation contractor behavior.' "Blow and
Go" insulation contractors have deceived Idaho customers, and have presented
themselves as Rocky Mountain Power representatives. In order to reassure nervous
customers and other quality contractors in the HES Program, implementer staff promoted
these program changes through bill inserts and marketing collateral, and on the program
Website to restore customer trust.
o
o More ldaho-based outreach staff have been placed in the frcld to meet with
individual retailers. Field staff visit participating and potential trade allies more
frequently than implemented initially. The strategy proved helpful to increase retailer
and contractor participation, especially in a diverse retailer and contractor market,
such as Idaho's.
EISA Awareness and Concerns
o Unlike other service territories, most Idaho lighting retailers plan to educate
customers about EISA legislation. Half of lighting customers knew of EISA changes;
one retailer added customers appreciate being kept informed.
o Recommendation: To support Idaho lighting retailers planning to educate customers
about EISA, Rocky Mountain Power should consider providing educational point-of-
purchase materials about EISA, framed in the context of increased availability of
utility-supported, high-effrciency lighting options. This will further aid retailers in
preparing customers for changes in lighting availability.
7$The Cadnrus Group, lnc. / Energy Services
E'hibitf":YP}s""'il"l:ii]fJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mouniain Power ldaho HES 2009-2010 Final Report February 3, 2012
Recommendation: Train lighting retailers to properly educate and prepare customers
for EISA changes, specifically the Lighting Facts label required to be displayed on all
lighting packages. Supply retailers with point-of-purchase materials that will show
customers how to interpret the label, and easily find the Rocky Mountain Power-
incented bulbs they need. Although this would not produce directly measureable
savings impacts, increased customer satisfaction could indirectly increase customers'
willingness to participate in other HES Program components.
EISA legislation and ingrained customer preferences, once fully implemented, could
have wide-ranging of impacts on utility lighting progftrms. Lighting participant
surveys indicated customers tend to purchase CFLs over other energy-effrcient
lighting options (despite survey findings indicating many customers have concerns
about CFL quality and other issues). When presented with choices to purchase a more
efficient incandescent bulb, CFL, LED, or halogen bulb, more than one-third of
lighting customers chose CFLs. With a history of more than a decade of successful
utility market transformation activities, customers' CFL preference likely result from
familiarity with CFLs as an energy-efficient, inexpensive option. Additionally, as
reported in the impact evaluation's WTP section, CFL demand relates inversely to
price, indicating participants tend to purchase products at lower prices. It can be
assumed this same theory would apply to other lighting options.
However, due to the phase out of incandescent bulbs resulting from EISA, the
lighting savings baseline in the DSM market will likely increase, resulting in
approximately
75 percent lower savings per CFL to be attributed to utility lighting programs.
Program stakeholders report Rocky Mountain Power's plans to offer a robust variety
of ElSA-compliant bulbs through its lighting portfolio. However, given customers'
preference for CFLs over other energy-efficiency lighting options on the market,
Rocky Mountain Power may still face challenges in meeting its lighting savings
targets due to the adjusted baseline.
Recommcndation: Given the changes in the evolving lighting industry, explore
which higher-efficiency lighting options (e.9., LEDs) garner the most savings per
unit. Align marketing messages with preferred lighting options to heighten awareness
using market transformation tactics.
Recommendation: The evolving lighting market can act as a platform to clari$,
marketing messages about lighting options and bulbs best for each customer's
intended use. Continue to enhance marketing collateral that compares prices of
various lighting options with expected lifetime savings associated with those options
to demonstrate the long-term value of higher-efficiency options. The potential long-
term savings attributed to qualiffing measures served as the primary purchasing
motivator for appliance and weatherization participants. These same marketing tactics
should be considered for the lighting market, given the elimination of traditional,
inexpensive options. Messaging should also highlight comparisons of lighting quality
and other factors consumers tend to focus on in satisfaction surveys.
The Cadmus Group, lnc. / Energy Services 8CI
Rocky firtrountain Fower ldaho HHS 2SS9*?01S Finat Repofi
Rocky Mountain Power
Exhibit No. 5 Page 683 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fel:nuary 3, ?CI1?
o Lighting customers do not know of proper CFL disposal methods. More than three-
quarters of surveyed CFL owners threw CFL bulbs in the trash during the past 12
months.
o Recommendation: Continue with plans to provide recycling centers at all
participating retail locations; so customers can simply bring in spent bulbs when
purchasing replacements. Recycling centers could convey a positive public image to
enhance Rocky Mountain Power's reputation within the community, and add public
relations value to the program, particularly with interveners. Rocky Mountain Power
should raise awareness of the availability of recycling centers through bill inserts,
training for retail staff, and other outreach tactics.
The EISA standard will impact Rocky Mountain Power savings analysis of CFLs.
o Recommendation: Baseline wattage assumptions will need to be updated to
account for the new EISA standards. The EISA standard established an equivalent
baseline by rated lamp lumens. If the actual baseline wattage replaced is not
known (i.e. no surveys were conducted), the recommended approach uses the
CFL rated lumens and equivalent lumens in EISA to determine baseline wattage.
This approach cart be use for program evaluations in2012 and beyond.
Rocky Mountain Power impact analysis of CFLs does not include a wuste heat factor
WHD in the planning estimates.
o Recommcndation: The WHF is an adjustment representing the interactive effects
of lighting measures on heating and cooling equipment operation. Cadmus did not
apply the WHF adjustment to lighting savings estimates as Rocky Mountain
Power did not include it in their initial planning estimates. However, Cadmus
recommends using the approach outlined in Appendix L and including this
adjustment for future planning. estimates and evaluations.
Marketing and Participation Decisions
o Program staff report service territory-focused marketing messages beneJit program
participatioz. The program implementer considers the shift from ooone-size-fits-all"
marketing messages to those targeting particular segments may contribute to increased,
multipurchase HES participation.
o Trade allies (both retailers and contractors) provide a valuable channel to incresse
program awareness. Idaho trade allies drive more than one-third of total participation in
the HES program.
o Recommendation: As the baseline for lighting savings changes, non-lighting savings
garnered from the HES Program may have an increased significance. If needed,
continue to recruit new trade allies from within Idaho to broaden program awareness
throughout the service territory. The HES program has an effective trade ally
presence; an increased trade ally network could lead to heightened incentive
awarene ss, filther increasing pro gram participation.
The Cadnrus Group, Inc. I Hnergy Senrices Sd
E-hi bit f"'"YPYs""'!n:i ilfJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Ro*gflr Mountai! Power ldaho HES 2009*2010_final Report February.3, 2012
o Recommendation: To ensure trade allies find it easy to participate and continue to
promote the HES program, carry on with plans to offer them online application
access.
o Recommendation: Continue with plans to provide trade ally-focused marketing
collateral for downloads within the trade ally section of the program Web pages. If
possible, marketing materials should offer personalization and./or co-branding options
for trade ally promotion.
According to trade allies, product clings serve as the most useful promotional material
provided through the HES Program- The most common recommendation for changing
program marketing materials has simply been to provide more materials.
o Recommendution: Provide a greater quantity of materials for trade allies'
promotional use. Develop a Web-based tool, allowing trade allies to order these
materials as needed.
Customers do not connect upstream lighting products they purchase with Rocky
Mountain Power's HES Program incentives. Although most HES Program savings
accrue through the lighting component, very few lighting customers knew Rocky
Mountain Power's HES Program provided CFL discounts.
o Recommendation: Ensure lighting retailers are trained to inform customers that
incented lighting products have been discounted by Rocky Mountain Power.
Rocky Mountain Power has created compelling, broad-reaching marketing materials.
Cadmus understands marketing represents a key lever for controlling program
participation. The utility's marketing materials, use of marketing channels, and its online
presence largely remain consistent with utility program best practices. The
recommendations below offer additional marketing opportunities.
o Recommendation: Track metrics and provide results to evaluators. Metrics help
Rocky Mountain Power assess return-on-marketing investments, and fine-tune
marketing resource allocations. Currently PECI tracks online activity, progftrm
events, call-in phone numbers and conversion information In-house marketing
evaluations can also include:
o Interviews;
o Focus groups;
o Sampling(i.e., surveys prior to and during the campaign);
o Broadcast-generated impressions (i.e., assess the total number of
customers registering the brand message through print, radio, outdoor,
sponsorship, and TV marketing);
o Customerengagement/CRM Reports;
o Recommendation: Continue to leverage on- and offline social networks to leverage
customer satisfaction levels. Social networks (such as stakeholder trade associations,
community networks, Chambers of Commerce, Linkedln groups, and e-mail
The Cadmus Group, lnc. / Energy Services 82
E,hibi*X":"YPYsT8tsliil'fl
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES 2009-2010 Final Report February 3,2012
networks) provide low-cost, high-volume information distribution vehicles. Continue
to consider implementing innovative tactics, such as Living Social and/or Groupon
coupon-focused lead generation vehicles.
o Recommendation: Broaden promotion of the program's URL. Only 6 percent of
participants and 13 percent of trade allies cited the Website as a referral source.
Online marketing can be one of the most cost-effective tools to generate interest and
leads in remote geographies. Rocky Mountain Power should emphasize its Website in
marketing materials as a key tool for obtaining detailed program information.
However, marketing channels should continue to focus on approaches reported most
effective with customers: bill inserts and in-store displays.
o The HES Website content does not reflect market segmentation described by
program staff. Program descriptions for each state are identical.
o Recommendation: Mirror segment-driven messages found within collateral and
promotional events on the Website.
Quality Assurance
. QC inspections prove costly in ldaho due to its dispersed customer community and
overall low participation volume. While Idaho's HES participation volume does not
merit the budget for a full-time, locally-based QC staff, travel between installation sites
presents budget constraints for the program implementer, which must conduct QC
inspections within 45 days of a service measure installation.
o Recommendation: Outsource the QC process to a locally-based QC firm.
Subcontracting with a locally-based firm with viable outside work would decrease
travel costs, and eliminate the concerns of a full-time staff member with idle time
between installation inspections.
Satisfaction and Perceived Barriers
o Program satisfaction generally runs high. Surveyed customers reported high satisfaction
levels regarding program incentives, purchased measures, and overall program
experience. In benchmarking program satisfaction against results from other states and
other utilities' programs, Cadmus found customer satisfaction to be consistent with good
performance.
c Installstion contractors may not be completing incentive applications in a timely
manner.Installation contractors assume the responsibility for completing incentive forms
on behalf of their customers; however, one-third of insulation customers reported waiting
more than eight weeks to receive their incentive. In benchmarking program satisfaction
against results from other states and other utilities' programs, Cadmus found customer
satisfaction consi stent with good performanc e.
o Recommendation: To improve customer satisfaction, consider requiring
installation contractors to provide incentive amounts as a deduction from the
customer's bill upfront, then receive reimbursement when correctly submitting the
incentive application. This would further motivate contractors to filI out and
submit incentive forms in a timely manner.
The Cadmus Group, lnc. i Energy Services UJ
E-hi b,t f":"YPYsTlHiiil'g
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES 2009-2010 Final Report Februany 3, 2012
The need for new equipment most often motivates participating customers to purchase
qualiJicd meosures. Many participants reported participating in the HES Program as their
old equipment ceased working or functioned poorly.
o Recommendation: Continue to utilize marketing messages that target the equipment
replacement market. Trade allies should be trained to capture this market's interest by
promoting the HES Program when contacted to install new equipment in emergency
replacement situations.
Energt savings motivate customers to purchase high-elficiency products. Retailers
most frequently reported cost savings on bills as the "selling point" for higher-efficiency
products.
o Recommendation: Continue to leverage customer's interest in saving energy by
providing trade allies with materials focusing on potential energy cost savings,
associated with qualified measures. Information could include estimated annual
and lifetime cost savings, compared to the use of a standard efficiency model, and
using accurate Rocky Mountain Power rates.
84The Cadmus Group, lnc. i Energy Services
r,n, on,l"l"Ir}r"J;g'"iiY#
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power tdaho HES 2009*2010 Final Report February 3, 2012
Gost-Effectiveness
In assessing cost-effectiveness, Cadmus analyzed program costs and benefits from five different
perspectives, using Cadmus' DSM Portfolio Pro3a model (as used for recent evaluations of
Rocky Mountain Power's residential portfolio). Benefit-to-cost ratios conducted for these tests
were based on methods described in the California Standard Practice Manual for assessing DSM
programs' cost-effectiveness. Tests utilized included the following:
PacffiCorp Total Resource Cost Test (PTRC): This test examined the program's
benefits and costs from Rocky Mountain Power's and participants' perspectives,
combined. On the benefit side, the test includes avoided energy costs, capacity costs, and
avoided line losses, plus a l0 percent adder to reflect non-quantified benefits. On the cost
side, it included costs incurred by both the utility and participants.
Total Resource Cost Test (TRC): This test examined program benefits and costs from
Rocky Mountain Power's and participants' perspectives, combined. On the benefit side, it
included avoided energy costs, capacity costs, and avoided line losses. On the cost side, it
included costs incurred by both the utility and participants.
Utility Cost Test (UCT): From Rocky Mountain Power's perspective, benefits included
avoided energy, capacity costs, and avoided line losses. Costs included program
administration, implementation, or incentive costs associated with program funding.
d. Ratepayer Impact (RIM): All ratepayers (participants and nonparticipants) perspective.
This test included all Rocky Mountain Power program costs as well as lost revenues.
Benefits included avoided energy costs, capacity costs, and line losses..
e. Participant Cost Test (PCT): From this perspective, program benefits included bill
reductions and incentives received. Costs included a share of the measure's incremental
cost (compared to the baseline measures), plus installation costs incurred by the
customer.
Table 63 summarizes the five tests' components.
Table 63. Benefits and Costs Included in Various Tests
'o DSM Portfolio Pro has been independently reviewed by various utilities, their consultants, and a number of
regulatory bodies, including the Iowa Utility Board, the Public Service Commission of New York, the Colorado
Public Utilities Commission, and the Nevada Public Utilities Commission.
b.
c.
Present value of avoided energy and capacity costs,* with 10
t adder for non-ouantified benefits Program administrative and marketing cost
Present value of avoided energy and capacity costs'Program administrative and marketing cost
Present value of avoided energy and capacity costs*
Present value of avoided energy and capacity costs*Program administrative, marketing, and incentive cost
+ oresent value of lost revenues
Present value of bill savings and incentives received lncremental measure cost and installation cost
"Present value of avoided energy and capacity costs includes avoided line losses occurring from reductions in customer electric use.
The Cadmus Group, lnc. / Energy Services B5
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Case No, PAC-E-14-07
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Table 64 provides selected cost analysis inputs, including: evaluated energy savings for each
year, discount rate, line loss, and program costs. Rocky Mountain Power provided all of these
values, except energy savings. The discount rate derived from Rocky Mountain Power's 2008
Integrated Resource Plan. Rocky Mountain Power also provided the values for line loss and
program costs.
Program benefits included energy savings and their associated avoided costs. The cost-
effectiveness analysis used energy savings derived from this study's evaluated kwh. Analysis
used a weighted average measure life of 17.5 years, based on measure lifetimes, and weighted by
savings and frequency of installations. All analyses used avoided costs associated with Rocky
Mountain Power's 2008 IRP 46 Percent Load Factor Eastside Residential Whole Home
Decrement.3s
Cadmus analyzed cost-effectiveness for two scenarios. The first assumed no freeridership and
spillover (NTG equaling 100 percent). The second incorporated evaluated freeridership and
spillover.
Table 65, below, presents progrtrm cost-effectiveness analysis results, with NTG equaling
100 percent for all program measures for the evaluation period (2009-2010), though not
accounting for non-energy benefits (except those represented by the 10 percent conservation
adder included in the PTRC). For this scenario, cost-effectiveness analysis results indicated the
program was cost-effective from all perspectives except the RIM (a 1.0 or greater benefit-cost
ratio is considered cost-effective). Most programs do not pass the RIM test due to adverse
impacts of lost revenue.
" IRP decrements are detailed in Appendix G of PacifiCorp's 2008 Integrated Resource Plan, Vol. II Appendices:
U*:t*Plpriningjipdf
Table 64. Selected Cost Analysis Inputs*
*Savings reflect impacts at generation and have been increased for line losses.
$476,6'13
The Cadrnus Group, lnc. / Energy Services Hb
Table 65. Program Cost-Effectiveness Summary for 2009-2010 (NTG = 100 percent)
Total Resource + Conservation Adder (PTRC)$0.061 $2,583,024 $5,359,130 $2,776,106 2.07
Total Resource No Adder (TRC)$0.061 $2,583,024 $4,871,936 $2,288,912 1.89
Utility (UCI)$0 035 $1,468,881 $4,871,936 $3,403,056 3.32
Ratepayer lmpact (RlM)$0 121 $5,1 32,1 97 $4,871,936 ($260,261)0.95
Participant (PCT)$0.045 $1,900,600 $4,449,773 $2,549,1 73 2.34
=*,on,X"l"IrYn""':11,,"iiYgCase No. PAC-E-I4-07
Vvitness: Kathryn C. Hymas
Rocky tuIo.y.$gin-Rlwer [-d-a.ho HES 2009*2010 Final Repo( ... .. ... ........ . .. ....-._".--&b]ggrij,-2$i {
Table 66 presents program cost-effectiveness analysis results, including evaluated NTG for all
program measures for the evaluation period (2009-2010), though not accounting for non-energy
benefits (except those represented by the 10 percent conservation adder included in the PTRC).
For this scenario, cost-effectiveness analysis results indicated the program was cost-effective
from all perspectives except the RIM (a 1.0 or greater benefit-cost ratio is considered cost-
effective). Most programs do not pass the RIM test due to adverse impacts of lost revenue.
Table 67 presents program cost-effectiveness analysis results, including evaluated NTG for all
program measures for the 2009 evaluation period, though not accounting for non-energy benefits
(except those represented by the 10 percent conservation adder included in the PTRC). For this
scenario, cost-effectiveness analysis results indicated the program was cost-effective from all
perspectives except the RIM (a 1.0 or greater benefit-cost ratio is considered cost-effective).
Most programs do not pass the RIM test due to adverse impacts of lost revenue.
Table 66. Program Cost-Effectiveness Summary for 2009-2010 (Evaluated NTG)
Total Resource + Conservation Adder (PTRC)
Total Resource No Adder (TRC)$1 ,906,196
The Cadmus Group, lnc. / Energy Services s7
.*, on'X"1'l'InTlH:iiffJ
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES 2009-2010 Final Report February 3, 2012
Table 68 presents program cost-effectiveness analysis results, including evaluated NTG for all
program measures for the 2010 evaluation period, though not accounting for non-energy benefits
(except those represented by the 10 percent conservation adder included in the PTRC). For this
scenario, cost-effectiveness analysis results indicated the program was cost-effective from all
perspectives except the RIM (a 1.0 or greater benefit-cost ratio is considered cost-effective).
Most programs do not pass the RIM test due to adverse impacts of lost revenue.
Table 68. Program Cost-Effectiveness Summary for 2010 (Evaluated NTG)
Table 67. Program Cost-Effectiveness Summary for 2009 @valuated NTG)
Total Resource + Conservation Adder (PTRC)$0.065 $783,065 $1,263,640 $480,575 1.61
Total Resource No Adder (TRC)$0.065 $783,065 $1,148,7M $365,699 1.47
Utility (UCT)$0.042 $498,348 $1,148,764 $650,416 2.31
Ratepayer lmpact (RlM)$0.125 $1,496,793 $1,148,764 ($348,029)0.77
Participant (PCT)$0.045 $629,910 $1,415,876 $785,966 2.25
Total Resource + Conservation Adder (PTRC)$0.062 $1,662,452 $3,648,640 $1,986,188 2.19
Total Resource No Adder (TRC)$0.062 $1,662,452 $3,316,945 $1,654,494 2.00
Utility (UCT)$0.039 $1,042,352 $3,316,945 $2,274,593 3.18
Ratepayer lmpact (RlM)$0.127 $3,381,836 $3,316,945 ($64,8e1)0.98
Participant (PCT)$0.044 $1,30/,721 $3,258,406 $1,893,685 2.39
The Cadmus Group, lnc. / Energy Services 8S
E'h i bit f"""PPYsT:fl iiYS
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
Rocky Mountain Power ldaho HES 2009-2010 Final Repo( February 3, 2012
Appendices
Appendix A: Survey and Data Collection Instruments
Appendix B: Precision Calculations
Appendix C: HOU Methodolory
Appendix D: Lighting NTG (Retailer Surveys)
Appendix E: Lighting NTG (Secondary Review)
Appendix F: Lighting NTG (WTP)
Appendix G: Billing Analysis
Appendix H: Insulation Site Visits
Appendix I: NTG Evaluation Methodolory
Appendix J: Marketing Materials
Appendix K: Engineering Review and Whole House Modeling
Appendix L: Waste Heat Factor Review
Please find this report's appendices attached as a separate file.
The Cadrnus Group, lnc. I Energy Services
E hi bit f"YPllT:Hiii["J
Case No. PAC-E-14{7
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report PgS?"frffT,WT?
Appendix A. Survey lnstruments and Data Collection
Tools
Appendix A. Survey Instruments and Data Collection Tools ........A1
1. Management Staff and Program Partner lnteruiew Guide........................A2
2. Participant Telephone Survey (Appliances, HVAC and Weatherization)A6
3. lnsulation Participant Site Visit Verification Form ....A29
4. Participant Retailer/Contractor Survey............ ..........A35
5. ln-Territory Lighting Survey ..........A51
6. Out-of-Territory Lighting Survey (Leakage) ............. .A72
The Cadmus Group, lnc. / Energy Services Appendix 41
Roclry Mountain Power
Exhibit No. 5 Page 693 of '1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report Cgts?'fr#S,"2UTT
1. Management Staff and Program Partner lnteruiew
Guide
Program/l mplementation Staff:
Contact Name:
Survey Date:
Contact Phone Number:
lnterviewer lnitials:
Contact Title:
[Make it clear to the interviewee, that this process evaluation interview covers the 2009 and 2010
program years, and to the extent possible, we would like to try to attach their responses (events, activities
referenced, transitions, evolution) to the appropriate program year.]
General
1. What is your role in the program?
2. Who do you work closely with (on the program), both internally and at other agencies? ln what
capacity?
1. [DO NOT SKIP THIS QUESTION] What are your top three successes or most important achievements?
2. [DO NOT SKIP THIS QUESTION] What your three biggest challenges or concerns with the program? Do
you have suggestions for addressing them?
3. Do you have suggestions for improving the program?
Program History and Design
t. How did the program concept come about?
2.
3. When was the program launched [in the relevant state]?
4. Were perceived barriers identified and used in the program design? lf so, how does the design
address barriers?
5. How has the program progressed over the last two years (2009, 2010)?
a. What barriers or challenges has the program faced? What was done to address them?
b. Are you happy with the program's performance with regards to:
i. Local delivery capacity in the states in which the program is offered
ii. Program delivery and implementation (internal and external)
iii. Tracking processes and reporting
The Cadrnus Group, lnc. i Energy Services Appendix 4,2
Rocky Mountain Power
Exhibit No. 5 Page 694 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report #S?"SffiT,"2UT?
iv. Awareness of the program and energy efficiency
v. Participation and savings
What program components are key to meeting program goals?
6. Were there been any design changes during the 2009 and/or 2010 program years? (e.g., targeted
customers, measures promoted, delivery process, incentive levels) [try to attach dates [2009 or 2010
program yearl to design changes and probe why they were made] Any planned? Why?
7. Do you have any design changes (including changes to the program's marketing and educational
components) planned in response to the EISA legislation?
8. What steps are you taking to minimize leakage of incentivized CFLs to customers outside of the
PacifiCorp service territories?
Program Goals
1. What are the program's process goals, if any? (e.g. participation of customers (including, customers
in all regions of the service territory; single family and multifamily, etc.), of contractors market
transformation, increase awareness, education of trade allies?)
2. Do you use metrics to track progress against process goals? lf so, what are they?
3. Have there been any changes to goals in 2009/2010? Why?
4. Do you think the program has succeeded in addressing participation barriers (mentioned above)?
5. How do you think the program performed against its goals in 2009 and 2010?
Trade Allies and Partners
7. Who implements the program?
2. What are their responsibilities?
3. How do you communicate with them? How often? Have the communications been effective? Does
their performance meet your expectations? How do you address issues that arise?
4. Who are the program's trade allies? How are they targeted? ls there any formal relationship?
5. Who do you consider a "Partner"? What makes them a partner? How are they invited or chosen to
be a partner?
6. Do you offer tangible benefits to trade allies and/or partners? What benefits do they get? What role do
you expect them to play? What is level of interaction do you have with them (e.g., do you provide
training)?
Coordination with JACO [CALIFORNIA ONLY]
1. How long has appliance recycling been offered through HES?
2. How do you coordinate with JACO? (E.g., are there regular meetings?)
3. Does JACO report any participation data to PECI? lf so, how often and in what format?
The Cadmus Group, lnc. i Energy Services Appendix A3
Roclq Mountain Power
Exhibit No. 5 Page 695 of 1 365
Case No. PAC-E-14-07
Rocky !\ilountain Power ldaho FIES Evaluation 2009-2010 Final Report #ts?m#$T,t2B?T
4. ln 2009 - 2070, was appliance recycling promoted through partnerships with appliance retailers?
5. Were there cross-promotional activities, e.g., promoting appliance recycling to recipients of the
refrigerator rebate?
Program Marketing
1. Who does the marketing? (Utility or external firm?)
2. Do you have a marketing plan? A schedule of activities? [get a copy if possible]
3. ls your advertising more focused on general efficiency program marketing or program specific
marketing?
4. What marketing channels and approaches are used? (to consumers, to trade allies?)
5. Are social marketing tactics used (e.g. attendance at community events, twitter, Flickr, Facebook?)
[probe] Do you feel these tactics have been effective?
6. What collateral is used? [get copies] (bring checklist table)
7. What role do trade allies play in marketing the program?
8. Are they incented to promote the program? How? Are these incentives effective?
9. How is marketing effectiveness measured?
10. What marketing methods and messages do you think have been most effective?
11. Are the customer incentive levels appropriately set?
Internal Program Management
7. How many staff run the program? What are their roles? How do you coordinate with other programs
or other offices (e.g. marketing, call center, research staff, database management); Organization
chart? Do you feel management and administration is effective overall? Budget adequate?
Paperwork/admin right or overwhelming?
2. Overall internal program management working? Areas for improvement?
External Program Management
1. How is the third party administrator organized?
2. Are you happy with the third party administrator? Anything that needs to be improved? Good
reporting? Useful? Timely?
3. What types of trade allies are most active? Are you satisfied?
Customer Response
1. Do you feel program is meeting the needs of your customers?
2. ls program participation meeting your expectations? Why?
The Cadmus Group, lnc. I Energy Services Appendix A4
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 696 of 1 365
Case No. PAC-E-14-07
#ts?'fiffT,'2UT?
3. How effective is the program at connecting with the "hard to reach" market? Are there any customer
groups you feel may be overlooked?
5. Do you have any direct contact with customers?
6. How do you collect, document, track and respond to complaints? How is that process working?
7. What feedback have you received so far? From whom (e.9., directly from customers, from the
implementation partner)?
Data Management
L. How does program data get entered? ls there a process to upload data to a central tracking system?
What is the QAQC process for data entry and transfers? Who checks? How often? How are errors
handled/corrected?
2. ls it easy to get data extracts and reports?
3. How do you use the database?
Final Thoughts
4. Are there any specific questions or issues would you like us to investigate during the evaluation or
include in a customer or trade ally survey?
5. What do you anticipate for the future of the program? Expand, scale back (perhaps for specific
measures) or stay about the same level?
6. What information can the evaluation deliver to inform the program's processes?
List of Requested Material
1. Reports, participant & measure tracking databases, budget tracking
2. Marketing plan, marketing collateral (e.g., brochures, Web text, etc.), research, materials, market
metrics, social media metrics
3. Flow diagrams and org charts
4. Application forms
5. Survey instruments or results to date
The Cadrnus Group, lnc. / Hnergy $ervices Appendix A5
Rocky Mountain Power
Exhibit No. 5 Page 697 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009*2010 Final Report #[?"fr#5,t2UTT
Pacific Power
Rocky Mountain Power
[TO RESPONDENT] Hello, l'm INSERT FIRST NAME] I am calling from [DISCOVERY RESEARCH] on behalf
of [INSERT UTILITY]. We are exploring the impacts of energy efficiency programs offered in your area.
l'm not selling anything; I just want to ask you some questions about your energy use and the impact of
promotions that have been run by [INSERT UTtLlTYl.
Responses to Customer Questions [lF NEEDED]
(Timing: This survey should take about 15 minutes of your time. ls this a good time for us to speak with
you?
(Who are you with: I'm with DISCOVERY RESEARCH, an independent research firm that has been hired
by [INSERT UTttlTY] to conduct this research. I am calling to learn about your experiences with the
[INSERT MEASURE] that you received through INSERT UTILITY]'s Home Energy Savings program.
(Sales concern: I am not selling anything; we would simply like to learn about your experience with the
products you bought and received an incentive for through the program. Your responses will be kept
confidential. lf you would like to talk with someone from [INSERT UTILITY] about this study, feel free to
call 1-800-942-0266, or visit their website: httn://www.hgmeenerfvsavings-netl)
2. Participant Telephone Suruey (Appliances, HVAC
and Weatherization)
luTrLrrYI
Washington, and California:
Utah, Wyoming, and ldaho:
IMEASUREI
AL. Clothes Washer
A2. Refrigerator
43. Dishwasher
A4. Window
A5. Fixture
A6. Heat Pump
A7. Ceiling Fan
A8. Electric Water Heater
A9. Room AC
A10. Attic lnsulation
A11. Wall lnsulation
A12. Floor lnsulation
!ntroduction
The Cadmus Group, lnc. I Energy Services Appendix AS
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclq Mountain Power
Exhibit No. 5 Page 698 of 1 365
Case No. PAC-E-14-07
#B?[{ffT,'2flT}
(Who is doing this study: INSERT UTlLlTYl, your electric utility, is conducting evaluations of several of
its efficiency programs, including the Home Energy Savings program.)
(Why are you conducting this study: Studies like this help [INSERT UTILITY] better understand
customers' needs and interests in energy programs and services.)
51. Our records show that in INSERT YEARI your household received an incentive from [INSERT
UTILITY] for installing energy efficient equipment. We're talking with customers about their
experiences with the incentive program. Are you the best person to talk with about this?
t. Yes
2. No, not available [SCHEDUIE CALTBACK]
3. No, no such person [THANK AND TERMINATE]
-98. DON'T KNOW [TRY TO REACH RTGHT PERSON; OTHERWISE TERMINATEI
-99. REFUSED [THANK AND TERMTNATEI
52. Were you the primary decision maker when deciding to purchase INSERT MEASURE](S)?
L. Yes
2. No
Have you ever been employed in the market research field?
L. Yes [THANK AND TERMINATE]
2. No [CONTINUE]
-98. DON',T KNOW [THANK AND TERMTNATE]
-99. REFUSED [THANK AND TERMTNATEI
Have you, or anyone in your household, ever been employed by or affiliated with [INSERT UTltlTY]
or any of its affiliates?
t. Yes [THANK AND TERMINATE]
2. No [CoNTtNUE]
-98. DON',T KNOW [THANK AND TERMTNATE]
-99. REFUSED ITHANK AND TERMTNATE]
Measure Verification
Now I have a few questions to verify my records are correct.
s3.
s4.
The Cadrnu$ Group, lnc. / Energy Services Appendix A7
Rocky Mountiain Power
Exhibit No. 5 Page 699 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report #S?'fr5ilTH,"2UT?
C1. [INSERT UTILITY] records show that you applied for an incentive for INSERT QUANTITYI [F
MEASURE = WINDOWS OR INSUIATION, SAY "square feet of'AFTER QUANTITY] [INSERT
MEASUREI(S). ls that correct? [DO NOT READ RESPONSES]
1. Yes
2. No, quantity is incorrect
3. No, measure is incorrect
4. No, both quantity and measure are incorrect
-98. DON'T KNOW
-99. REFUSED [TERMTNATE]
C2. [ASK lF CL=27 How many [!F MEASURE = WINDOWS OR INSUIATION SAY "square feet
of'l[MEASUREI(S] did you apply for an incentive? [NUMERIC OPEN ENDED. DOCUMENT AND USE AS
QUANTTW FOR REMATNDER OF SURVEYI
[F NEEDED SAY: "We know you may have applied for other incentives, but for this survey, we'd like to
focus on just this one type of equipment."l
7. IRECORD]
-98. DON'T KNOW
-99. REFUSED
C3. IASK lF Cl = 3 OR 4 OR 98] Please tell me for what type of equipment you applied for an incentive?
[PROBE FOR MEASURE AND QUANTITY THEN SAY: "Thanks for your time, but unfortunately you
do not qualify for this survey." THEN THANK AND TERMINATEI
1. [RECORD VERBATIM]
-98. DON'T KNOW - THANK AND TERMINATE
-99. REFUSED - THANK AND TERMINATE
C4. Did you have a chance to install [!F QUANTITY MEASURE = l SAY "the [INSERT MEASUREI", lF
QUANTITY MEASURE > 1 SAY ,,ANy Of the [INSERT QUANTITYI IINSERT MEASUREI(S)", IF
MEASURE = WINDOWS OR INSUIATION, SAY "all of the [QUANTITY] square feet of the
windows"l at any point? [lF RESPONDENT SAYS THAT A CONTRACTOR OR SOMEONE EISE
INSTAILED tT, THEN CODE ANSWER AS "YES"I [DO NOT READ RESPONSES]
1. Yes
2. No
-98. DON',T KNOW [SKIP TO E1]
-99. REFUSED ISK|P TO E1]
C5. [ASK lF QUANTITY MEASURE > 1] How many [lF MEASURE = WINDOWS OR INSULATION, SAY
"square feet"l are installed now?
7. [RECORD # 1-10,000]
2. None
-98. DON'T KNOW
-99. REFUSED
The Cadrnus Group, lnc. / Energy Services Appendix AB
Rocky Mountain Power
Exhibit No. 5 Page 700 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report #ts?'iffiT,"2UT?
C6. [ASK !F C4 = 2, OR C5 = 2, OR C5 < QUANTITY MEASURE.IF QUANTITY MEASURE tS > l SAY: "Why
haven't you had a chance to install all [QUlruflTY] of the [MEASUREf', lF qUANTITY MEASURE=I
SAY: "Why haven't you had a chance to installthe [MEASURE]? [MULTIPLE RESPONSE UP TO 3;
DO NOT READI
L. Failed or broken unit
2. Removed because did not like it
3. Have not had time to install it yet
4. ln-storage
5. Back up equipment to install when other equipment fails
6. Have not hired a contractor to install it yet
7. Purchased more than was needed
8. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
Program Awareness & Purchase Decisions
M1. How did you first hear about INSERT UTILITYI's Home Energy Savings program? [DO NOT
PROMPT. RECORD ONIY THE FTRST WAY HEARD ABOUT THE PROGRAMI
1. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power/Pacific Power website
4. Home Energy Savings website
5. Other website
6. lnternet Advertising/Online Ad
7. Family/friends/word-of-mouth
8. Rocky Mountain Power/Pacific Power Representative
9. Radio
10. TV
11. Billboard/outdoor ad
12. Retailer/Store
13. Sporting event
14. Home Shows/Trade Shows (Home and Garden Shows)
15. Social Media
15. Other IRECORD VERBATUMI
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
M2. [F M1 <> 4] Have you been to the Home Energy Savings Website? [DO NOT READ RESPONSES]
1. Yes
2. No
The Cadmus Group, lnc. / Energy Services Appendix A9
Rocky Mountain Po[rer
Exhibit No. 5 Page 701 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho l-lES Evaluation 2009-2010 Final Report #ts?"frffiT,"2UT?
M3. [F M2 = t, OR Ml = 4l Was the website... [READ]
1. Very helpful
2. Somewhat helpful
3. Somewhat unhelpful
4. Very unhelpful
-98. IDO NOT READ] DON'T KNOW
-99. IDO NOT READ] REFUSED
M4. Please think back to the time when you were deciding to buy the energy saving [MEASUREI(s].
What factors motivated you to purchase the [MEASURE](s]? [DO NOT READ. tNDICATE ALL THAT
APPLY. ONCE THEY RESPONDENT HAS FINISHED, SAY: "Are there any other factors?"1
1. Old equipment didn't work
2. Old equipment working poorly
3. The program incentive
4. The program technical assistance
5. Wanted to save energy
6. Wanted to reduce energy costs
7. Environmentalconcerns
8. Recommendation from other utility IPRoBE: "What utility?" RECORD]
9. Recommendation of dealer/retailer [PROBE: "From which store?" RECORD]
10. Recommendation from friend, family member, or colleague
l-1. Recommendation from a contractor
t2. Advertisement in newspaper [PROBE: "For what program?" RECORDI
13. Radio advertisement [PROBE: "For what program?" RECORD]
14. Health or medical reasons
15. Maintain or increase comfort of home
L6. Other IRECORDI
-98. DON'T KNOW
-99. REFUSED
M5. [tF TYPE OF INSULATION = ATTIC] What type of insulation was in the attic before installation
IRECORD MULTTPLE RESPONSESI?
7. Fiberglass batts
2. Blown in Fiberglass
3. Blown in Cellulose
4. Rockwool
5. Spray Foam
6. Foam boards
7. No insulation before [SKIP TO l1l
8. other [RECORD].98. DON'T KNOW
.99. REFUSED
The Cadnru$ Group, lnc. i Energy Services Appendix 410
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 702 of 1365
Case No. PAC-E-14{7
Wtness: Kathrun C. HvmasFebruary 3, 2012
M6. [lF WPE OF INSUIATION = ATTIC] How thick (in inches) was the attic insulation before installation?
1. IRECORD].98. DON'T KNOW
-99. REFUSED
Measure Usage
E1.A Do you have a clothes washer in your home?
1. Yes
2. No [SKIP TO E9l
-98. DON',T KNOW ISK|P TO E9]
-99. REFUSED [SK!P TO E9]
E1. B Approximately how many loads of clothes does your household wash in a typical week?
t. [RECORD]2. Don't have a clothes washer/or uses a Laundromat ISKIP TO E9]
-98. DON'T KNOW
-99. REFUSED
E2. [ASK lF MEASURE = CLOTHES WASHER AND C4 = 1l How does the number of wash loads you do
now compare to the number that you did with your old clothes washer? IDO NOT READ
RESPONSESI
1. Same
2. Different
-98. DON'T KNOW
-99. REFUSED
E3. [ASK lF E2 = 2]Do you do more or fewer loads now than you did before? Could you estimate a
percentage?
L. More loads now, Record percentage [MUST BE GREATER THAN tOOyqEG L25o/o FOR25%
MOREI
2. Fewer loads now, Record percentage IMUST BE LESS THAN I,OOyo,EGTS% FOR 25% LESS
THAN BEFORE]
.98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. / Energy Services Appendix Al l
Rocky Mountain Power
Exhibit No. 5 Page 703 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report #ts?"fiffT,"2uT?
E4. On what percentage of loads do you use a high spin cycle? [READ CATEGORIES lF NEEDED]
1. Never
2. LESSTHAN2S%
3. 25-50%
4. 50-75%
5. 75-tOO%
-98. [DO NOT READ]DON',T KNOW
-99. [DO NOT READ]REFUSED
E5. IASK !F E4 = 1-51 When you do not use the high spin cycle, what is your reason?
7. Noise/vibration
2. lmpact on clothing
3. Other [RECORD]
-98. [DO NOT READ]DON',T KNOW
-99. IDO NOT READ]REFUSED
E6. [ASK lF E4 = 1-5] On what floor of the building is your washing machine located?
1. Basement
2. First floor
3. Second floor or higher
-99. [DO NOT READ]REFUSED
E7. What percentage of your loads do you dry using a clothes dryer? [READ CATEGORIES lF
NEEDEDI
1. Never [SKIP TO E9]
2, LESSTHAN 25%
3. 25-50%
4. 5A-75%
5. 75-700%
-98. DON',T KNOW [SKIP TO E9]
-99. REFUSED [SK!P TO E9]
E8. When you dry your clothes do you... [READ]
t. Use a timer to determine drying times.
2. Use the dryer's moisture sensor to determine when the load is dry.
3. Other [SPECIFYI
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
E9. How many times a week do you use the dishwasher?
1. [RECORD]
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. I Energy Services Appendix 412
Rocky klountain Power ldaho HE$ Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 704 of 1365
Case No. PAC-E-14-07
#ts?tsiT,"2UTT
MEASUREEI0. [ASK lF MEASURE = WINDOWS AND C4 = 1] What type of windows did you have before
the new windows were installed? [lF MEASURE <> WINDOWS] What type of windows do you
have?
1. Single pane [OLDER WINDOWSI
2. Double Pane [NEWER WINDOWSI
3. Triple Pane [RAREI
-98. DON'T KNOW
-99. REFUSED
811. [ASK lF MEASURE = WINDOWS AND C4= 1] What type of window frames (not window trim, which
is almost always wood) did you have before the new windows were installed? [F MEASURE <>
WINDOWS] What type of window frames do you have?
1. Wood
2. Vinyl
3. Metal
-98. DON'T KNOW
-99. REFUSED
E12. How many showers per week are taken at your home?
1. IRECORDI
-98. DON'T KNOW
-99. REFUSED
E13. How many baths per week are taken at your home?
1. IRECORD]
-98. DON'T KNOW
-99. REFUSED
[Ask E14-E15 if MEASURE = heat pump and C4= U
E14. What type of heating system did you have before the new heat pump was installed?
1,. Furnace
2. Boiler
3. Air Source Heat Pump
4. Ground Source Heat Pump
5. Stove
6. Baseboard
7. No heating system before [SKIP TO E15]
8. Other [SPECIFY]
-98. [DO NOT READI DON',T KNOW
-99, [DO NOT READ] REFUSED
The Cadmu$ Group, lnc. I Energy Service*.Appendix 413
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 705 of 1 355
Case No. PAC-E-14-07
#ts?'i'ffiT,"2UTT
E15. How many years old was the previous heating system?
1. [RECORD]
-98. DON'T KNOW
-99. REFUSED
E15. What type of fuel does the new heating system use... [READ]
1. Gas
2. Electric
3. Oil
4. Propane
5. Coal
6. Wood
7. Other [SPECIFY]
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
lAsK E17-E19 !F MEASURE <> HEAT PUMPI
E17. What type of heating system do you have now... IREAD]
1. Furnace
2. Boiler
3. Air Source Heat Pump
4. Ground Source Heat Pump
5. Stove
5. Baseboard
7. No heating system [SKIP TO E20]
8. OTHER [SPECTFY]
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
E18. How many years old is the heating system?
1. IRECORD]
-98. DON'T KNOW
-99. REFUSED
E19. What type of fuel does the heating system use... [READI
1. Gas
2. Electric
3. Oil
4. Propane
5. Coal
6. Wood
7. Other [SPECIFYI
The Cadmus Group, lnc. / Energy $ervices Appendix 414
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 706 of 1365
Case No. PAC-E-14-07
CBB?tffiT,"2UT?
-98. IDO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
[Ask E20- E21if MEASURE = heat pump and C4 = 1l
E20. What type of cooling system did you have before the new heat pump was installed? IREAD]
1. Central Air Conditioner
2. Room Air Conditioner
3. Evaporative Cooler
4. Air Source Heat Pump
5. Ground Source Heat Pump
6. Whole house fan
7: No cooling system before [SKIP TO E24]
8. Other [SPECIFY]
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
E21. How many years old was the previous cooling system?
1. IRECORD]
-98. DON'T KNOW
-99. REFUSED
lAsK E22-E23 tF MEASURE <> HEAT PUMPI
E22. What type of cooling do you have now? A... [READI
1. Central Air Conditioner
2. Room Air Conditioner
3. Evaporative Cooler
4. Air Source Heat Pump
5. Ground Source Heat Pump
5. Whole house fan
7. No cooling system [SKIP TO E24]
8. OTHER [SPECTFY]-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
E23. How many years old is your current cooling system?
L. IRECORDI.98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. i Energy Services Appendix 415
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 707 of 1 365
Case No. PAC-E-14{7
#ts?"fr5Fil5,'zUTT
F1.
E24. llF MEASURE = UGHTING FIXTURES AND C4=11 in which room(S) [S/ARE] the lighting fixture(s)
installed? [MULTtPLE RESPONSES ALTOWED]
1. Living/family room
2. Bedroom
3. Unoccupied bedroom
4. Bathroom
5. Kitchen
6. Garage
7. Office
8. Attic
9. Closet/storage
10. Hallway
11. Exterior
-98. DON'T KNOW
-99. REFUSED
Satisfaction
Overall, how satisfied are you with your [INSERT MEASUREI(S] Would you say you are...? [READ
CATEGORIES; RECORD FIRST RESPONSE ONLYI
t. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied
4. Not At All Satisfied
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
[ASK lF MEASURE= WINDOWS, HEAT PUMP, ELECTRIC WATER HEATER, OR INSUIATION] Did a
contractor install the [tNSERT MEASURE](S) for you?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
IASK lF F2=1] How satisfied were you with the contractor that installed the [tNSERT MEASUREI(S]
for you? [READ CATEGORIES; RECORD FIRST RESPONSE ONLY]
1. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied
4. Not At All Satisfied
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
F2.
F3.
The Cadmus Group, lnc. i Energy Services Appendix A16
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 708 of 1 365
Case No. PAC-E-14{7
Cgts?'iffiT,"2UT?
F5.
F6.
F7.
F8.
F4. [!F F3 = 3 or 4l Why were you not satisfied with the contractor that installed the [INSERT
MEASUREI(S) ?
L. IRECORD]
-98. DON'T KNOW
-99. REFUSED
How satisfied were you with the amount of the incentive you received for the [INSERT
MEASUREI(S)?
7. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied [PROBE FOR REASON AND RECORDI
4. Not At All Satisfied [PROBE FOR REASON AND RECORD]
-98. DON'T KNOW
-99. REFUSED
After you submitted the incentive application for the INSERT MEASUREI(S), how long did it take to
receive the incentive check from [INSERT UTltlTY]? Was it... [READ CATEGORIES lF NEEDED,
RECORD ONLY FTRST RESPONSEI
1. Less than 4 weeks
2. Between 4 and 6 weeks
3. Between 7 and 8 weeks
4. More than 8 weeks
5. Have not received the incentive yet
-98. IDO NOT READ] DON',T KNOW SKrp rO F7
-99. [DO NOT READI REFUSED SK|P TO F7
[ASK lF F6<> 5l Were you satisfied with how long it took to receive the incentive?
L. Yes
2. No [PROBE FOR REASON AND RECORD]
-98. DON'T KNOW
-99, REFUSED
How satisfied were you with the application process?
1. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied [PROBE FOR REASON AND RECORDI
4. Not At AllSatisfied [PROBE FOR REASON AND RECORD]
F8. Overall, how satisfied are you with the Home Energy Savings incentive program? IREAD
CATEGORIES; RECORD ONIY FIRST RESPONSEI
L. Very Satisfied [PROBE FOR REASON AND RECORDI
2. Somewhat Satisfied IPROBE FOR REASON AND RECORD]
3. Not Very Satisfied IPROBE FOR REASON AND RECORD]
4. Not At AllSatisfied [PROBE FOR REASON AND RECORDI
The Cadmus Group, lnc. i Energy $ervices Appendix 417
Rocky Mountain Power
Exhibit No. 5 Page 709 of 1 365
Case No. PAC-EI4-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report Cgts?tffiT."2tsT?
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
F10. Did your participation in [UTlttTY]'s HES Program cause your satisfaction with [UTILITY] to...
1. lncrease
2. Stay the same2. Decrease
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
Prior Equipment [FOR ALL BUT INSULATIONI
G1. Was the purchase of your new [INSERT MEASURE](S] intended to replace an old [INSERT INSERT
MEASURE TYPEI?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
G2. [ASK !F G1 = U What did you do with the old INSERT MEASURE TYPE] after you got your new
lrNSERT MEASUREI(S)? [READ CATEGORIES lF NEEDED]
1. Sold or given away
2. Recycled
3. lnstalled in another location in the home
4. Still in home but permanently removed ISTORED lN GARAGE, ETC.]
5. Thrown away
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
lmpact of Other Programs
H1. Did you receive financial assistance, an incentive or a rebate from a source other than [UTILITY] for
purchasing the [INSERT MEASURE](S)?
t. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. i Energy Services Appendix A18
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mounlain Power
Exhibit No. 5 Page 71 0 of 1 365
Case No. PAC-E-14{7
dgts?tffiT,"2UT?
H2.[ASK lF H1= 1l Who did you receive it from? INDICATE ALt THAT APPIYI
7. Dealer
2. Manufacturer
3. Localgovernment
4. State tax credit
5. Federal tax credit
6. Other State rebate/assistance
7. Beartooth Electric Coop
8. Bighorn Rec
9. Bighorn County EC
10. Black Hills Power & Light
11. Bridger Valley EA72. Carbon Power & Light
13. Cheyenne Light Fuel & Power
14. Fall River REC
L5. Garland Light & Power
15. High Plains Power
17. High West Energy
18. Lower Valley Energy
19. Montana-Dakota Utilities
20. Niobrara Electric
21. Powder River Energy
22. Wheatland REA
23. Wyrulec Company
24. Yampa Valley Electric
25. Energy West
26. Frannie-Deaver
27. MGTC lnc.
28. Pinedale
29. Questar Gas Co.
30. Source Gas
31. Town of Walden
32. Wyoming Gas Co.
33. Other utility [RECORDI
34. other [RECORDI
-98. DON'T KNOW
-99. REFUSED
[ASK !F Hl= 1] About how much did you receive from [FOR EACH MENTIONED lN H2]?
L. [RECORD. ROUND TO NEAREST WHOLE DOTLAR]
2. I have not received anything back yet
-98. DON'T KNOW
-99. REFUSED
H3.
The Cadmus Group, lnc. / Hnergy Services Appendix 419
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 71 1 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasFebruary 3. 2012
H4. [ASK lF H1 = 1] How influential would you say the [FOR EACH MENTIONED lN H2l incentive was in
your decision to purchase the INSERT MEASURE](S)? Was it... IREAD]
1. Very influential
2. Somewhat influential
3. Moderatelyinfluential
4. Not at all influential
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
Freeridership
Now l'd like to talk with you a little more about the [INSERT MEASURE](S) you installed.
11. When you first heard about the incentive from [Utility], had you already been planning to
purchase the Ilnsert MEASUREI(s]?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
12. Ok. Had you already purchased or installed the new INSERT MEASURE](S) before you learned
about the incentive from the Home Energy Savings Program?
1. Yes
2. No
.98. DON'T KNOW
-99. REFUSED
llF l1 AND 12 BOTH = 1 SKIP TOl12I
13. IASK lF 12 = 2, -98, -99] Would you have installed the same INSERT MEASURE](S) without the
incentive from the Home Energy Savings program?
t. Yes
2. No
-98. DON'T KNOW
.99. REFUSED
flF t3 = 7 THEN SKIP TO tsl
The Cadmus Group, lnc. I Energy Services Appendix A20
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
RoclSy Mountain Power
Exhibit No. 5 Page 712 of 1365
Case No. PAC-E-14-07
CBS?I#T,"2UT?
14. [ASK lF 13 = 2, -98 OR -99] Help me understand, would you have installed something without the
Home Energy Savings program incentive? [DO NOT READ RESPONSES]
1. Yes, lwould have installed something
2. No, lwould not have installed anything
.98. DON'T KNOW
-99. REFUSED
[lF la = 2 SKIP TO 18. lF 14 = -98 OR -99 SKIP TO 112]
15. [ASK lF 13 = 1 OR 14 = 1] Let me make sure I understand. When you say you would have installed a
[MEASUREI(S), would you have installed the same [ONE(S]| that IWAS/WERE] [lF MEASURE =
WINDOWS, HEAT PUMP OR INSULATION, SAY "iust as enerBy efficient"; ALt OTHER SAY "ENERGY
STAR qualified"l ?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
16. [ASK lF 13 = 1OR 14 = l AND QTY MEASURE>I] And would you have installed the same quantity of
IMEASUREI(s)?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
17. [ASK lF 13 = 1 OR 14 = 1l And would you have installed the [INSERT MEASUREI(S)... [READI
1. At the same time
2. Within one years?
3. ln more than one year?
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READI REFUSED
lskip to l12l
18. [ASK lF 13 =2 OR l4=2] To confirm, when you say you would not have installed the same
[MEASURE](S], do you mean you would not have installed the [INSERT MEASUREI(S] at all?
t. Yes
2. No
-98. DON'T KNOW
-99, REFUSED
[!F 18 = 1 SKIP TO l12l
The Cadmus Group, lnc. / Energy Services Appendix A21
Rocky Mountain Power
Exhibit No. 5 Page 713 of I 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report Pgts?tffiT,t2UT?
19.[ASK lF 18 = 2, -98, -99] Again, help me understand. Would you have installed the same type of
IINSERT MEASUREI(S) but [T/THEY] would q! have been as energy- efficient?
L. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
110. [ASK lF !8= 2, -98, -99 AND qTY MEASURE>I]Would it have been the same [INSERT MEASUREI(S]
but fewer of them?
t. Yes
2. No
.98. DON'T KNOW
.99. REFUSED
111. [ASK lF !8 = 2, -98, -99]And, would you have installed the same IINSERT MEASUREI(S)... [READ]
1. At the same time
2. Within one years?
3. ln more than one year?
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
172. ln your own words, please tell me the influence the Home Energy Saving incentive had on your
decision to purchase INSERT MEASURE](S]?
IRecord Response]
Spillover
J1. Since participating in the program, have you added any other energy efficient equipment or
services in your home that were not incentivized through the Home Energy Savings Program?
1,. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. / Energy Services Appendix 422
Rocky Mountain Power ldaho HES Evaluation 200$-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 714 ot 1365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasFebruary 3. 2012
J3.
[lF Jt = 2, -98 OR -99 SKIP TO Jsl
J2. Did you purchase any of the following items since the beginning of 2009, not including the
[MEASUREI that we have been discussing today? ILIST OF OTHER EIIGIBLE APPTIANCES AND
MEASURES OTHER THAN THOSE LTSTED lN PROGRAM RECORDS. PROMPT tF NEEDEDI
1. Clothes Washers
2. Refrigerators
3. Dishwashers
4. Windows
5. Fixtures
6. Heat Pumps
7. Ceiling Fans
8. Electric Water Heater
9. CFLs
10. lnsulation
11. Other [RECORD]
12. None
-98. DON'T KNOW
.99. REFUSED
llF lZ = 12, -98 OR -99 SKIP TO J6. REPEAT J3 THROUGH J5 FOR Att RESPONSES TO J2l
When did you purchase [!NSERT MEASURE WPE]?
1. 2009
2. 2010
3. 2071
-98. DON'T KNOW
-99. REFUSED
Did you receive an incentive for INSERT MEASURE TYPEI?
7. Yes [PROBE AND RECORDI
2. No
-98. DON'T KNOW
-99. REFUSED
J5. How influential would you say the Home Energy Savings program was in your decision to add
energy efficient equipment or services to your home? Was it...
1. Highly lnfluential
2. Somewhatlnfluential
3. Not at all influential
-98. DON'T KNOW
-99. REFUSED
J4,
The Cadmus Group, lnc. I Energy Services Appendix A23
Rocky &flountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No.5 Page 715 of 1365
Case No. PAC-E-14-07
#ts?'m5fi!T,"2UTT
J6. Have you participated in and received an incentive from any other [UTlLlTYl energy efficiency
Program?
1. Yes [PROBE AND RECORDI
2. No
-98. DON'T KNOW
-99. REFUSED
J7. IlF J6 = 1] On a scale of 0 to 10, where 0 is not at all influential and 10 is very influential; how
influential would you say the Home Energy Savings program was in your decision to participate in
other [INSERT UTltlTY] program[s]?
L. [RECORD]2. No
-98. DON'T KNOW
-99. REFUSED
Demographics
I have just a few more questions about your household. Again, all your answers will be strictly
confidential.
Which of the following best describes your house? [READ tlST]:
1. Single-family home
2. Townhouse or duplex
3. Mobile home or trailer
4. Apartment building with 4 or more units
5. Other [RECORD]
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
Do you rent or own your home?
1. Own
2. Rent
3. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
D3. lncluding yourself and any children, how many people currently live in your home?
1. IRECORDI
-98. DON'T KNOW
.99. REFUSED
D1.
D2.
The Cadrnus Group, lnc. I Energy Services Appendix 424
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 716 of'1365
Case No. PAC-E-14-07
cgts?'i{ilT..2uTT
D8. About when was this building first built? [READ tlST tF NEEDEDI
1. Before 1970's
2. 1970',s
3. 1980',s
4. 1990-94
5. 1995-99
6. 2000's
7. OTHER [RECORDI
-98. IDO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
D15. How many floors are in your building?
7. IRECORDI. -98. DON'T KNOW
-99. REFUSED
D16.What type of foundation does your home have? [READ LIST lF NEEDED]
1. Fullfinishedbasement
2. Unfinished Basement
3. Crawlspace
4. Slab on Grade
s. oTHER [RECORD]
-98. [DO NOT READ] DON',T KNOW
-ee. [Do NoT READ] REFUSED
D9. Approximately how many square feet is the home in which the [MEASUREI(S] was installed? [READ
LrsT rF NEEDEDI
L. Under 1,000 square feet
2. 1,000 - 1,500 square feet
3. 1,501 - 2,000 square feet4. 2,001- 2,500 square feet
5. Over 2,500 square feet
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
D17. What type of thermostat do you use to adjust the temperature in your home?
1. A programmable thermostat, and you use the automatic settings
2. A programmable thermostat but you don't use the automatic settings
3. A non-programmable thermostat, and you have no controls INOTE: USUALLY lN A BUILDING
wtTH3OR4APARTMENTSI.
4. OTHER [RECORD]
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. / Energy Services Appendix A2S
Rocky Mountain Power
Exhibit No. 5 Page 71 7 of 1 365
Case No. PAC-E-14-07
Witness: Kathrvn C. HvmasFebruary 3. 2012Rocky Mountain Power ldaho HE$ Evaluation 2009-2010 Final Report
D18.What are the temperature settings in winter when you are heating your home and... [READ
QUESTION "What are the temperature setting..." FOR l AND 2, FOR 3 AND 4 ONLY REPEAT
QUESTTON !F NECESSARYI
1. At home. [RECORD]2. Asleep at night. [RECORD]
3. Out during the day. [RECORD. NA lF SOMEONE ALWAYS HOME]
4. Away on vacation. [RECORD]
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
D19.What are the temperature settings in summer when you are cooling your home and... [READ
QUESTION "What are the temperature setting..." FOR l AND 2, FOR 3 AND 4 ONLY REPEAT
QUESTION tF NECESSARYI
7. At home. [RECORD]2. Asleep at night. [RECORD]3. Out during the day. [RECORD. NA lF SOMEONE ALWAYS HOME]
4. Away on vacation. [RECORD]
-98. [DO NOT READ] DON'T KNOW
-99. IDO NOT READ] REFUSED
D20. How many weeks out of the year do you go on vacation... [READ]
1. During the winter. [RECORD]2. During the summer [RECORD]
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
D21. [ASK lF MEASURE = HEAT PUMP OR E20 * 7 ,98 OR 99] How many weeks out of the year do use
your [F MEASURE = HEAT PUMP SAY "heat pump" OTHERWISE INSERT ANSWER FROM E20] to
cool your home? (Please remember to not include those weeks in the summer when on vacation),
1. [RECORD 1-1oo]
-98. DON'T KNOW
-99. REFUSED
D13. [SKIP lF MEASURE = ELECTRTC WATER HEATER] What is the fuel used by your primary water
heater?
1. Electric
2. Natural Gas
3. Fueloil
4. Other IRECORD]
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. i Energy Services Appendix A26
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclq Mountain Po/ver
Exhibit No. 5 Page 71 I of 1 365
Case No. PAC-E-14-07
Cgts?'fitr$T,"zUT?
D4.
D14. [F D13 = 1-41 How old is the primary water heater? [RECORD RESPONSE lN YEARSI
1. [RECORD 1-100]
-98. DON'T KNOW
-99. REFUSED
D5.
Can you please tell me in what year you were born?
1. IRECORDI
-98. DON'T KNOW
-99. REFUSED
ln 2010, was your pre-tax household income above or below 550,000?
1. Below 550,000
2. Above 550,0003. Exactly 550,000
-98. DON'T KNOW
-99. REFUSED
llF D5 = -98 OR -99 SKIP TO LlI
D6. [ASK lF D5=11 Which of the following categories best represents your household income in 2010?
Please stop me when I read your category:
7. Under S10,0002. S10,000 to under 520,0003. $20,000 to under S3o,ooo4. 530,000 to under 540,0005. 540,000 to under 550,000
-98. DON'T KNOW
-99. REFUSED
D7. [ASK lF D5=2] Which of the following categories best represents your household income in 2010?
Please stop me when I read your category:t. 550,000 to under Sso,ooo2. 560,000 to under 575,0003. $75,000 to under 5100,0004. S100,000 to under S15o,ooo5. S150,000 to under 5200,0006. S200,ooo or more
-98. DON'T KNOW
-99. REFUSED
The Cadrnu$ Group, lnc. I Energy Services Appendix 427
Roclry Mountain Power
Exhibit No, 5 Page 719 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho l-lH$ Evaluation 200$*2010 Final Report #8?"m#ffT,"2HTT
Conclusion
11. Do you have any additional feedback or comments?
7. Yes [RECORD VERBATUM]
2. No
.98. DON'T KNOW
.99. REFUSED
L2. Sex [DO NOT READ]
1. Female
2. Male
-98. DON'T KNOW
That concludes the survey. Thank you very much for your time and feedback.
The Cadmus Group, lnc. / Hnergy $ervices Appendix A2S
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Por/er
Exhibit No. 5 Page 720 of 1 365
Case No. PAC-E-14-07
Cgts?'frffiT,"2UTI
3. Insulation Participant Site Visit Verification Form
Camplete {or Each lnsulation f$easurethat Raceivcd lncen$ye {per Tracking Batabase}
Site Verificatisn FEnn - lnsulation HIM
lnspEctisn DEte
lnspediofl Start TEne
lnsedion Erd]lr$e
lnsecbr F{arrE I lnitiEls
fiirnary CQntad Name
PTWIg 1
Pfnne 2
Ffpne 3
ernfiil
Altemate Gfidact Narne
FfEne 1
PfEne 2
PtfrIfie 3
emsil
A*lrss I
A&lresst
City
${ate
AFCsde
Ca(rnr.rslS
Progrem IOU
Aeot.stt J SiE NuBrher
Sfigffial Site Visit Dale
ftwalsitevisitTrme
Ners Gffifinned *die
New GsnfifinsdTirne
lncEntiYe Paid
lfliiidsor S($atIrE
The Cadmus Group, lnc. / Energy Services Appendix 429
Racky tulountain Power ldaho HES Hvaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 721 of 1365
Case No. PAC-E-'14-07
C$ts?'frffiT,'zUT?
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rgsr rm$,erffi*T t)$i$
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tff usuo ilL trIie Yes f Nfi
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i;o$tina: SEt trrlinfs. lsrrriri
Cot*ir$ Set 6ad{ (l&iint}
b\t$fl Atr,c'li
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bttlen a{Wsrk
MetrB$ S$dte{rni$etio$Cusl Sft f InsS f Ellhe{
PrifiIa$i, Heahn$ F$el Tyse Ebctri{: i Gas i PraSarEI
fiif Ceclf Wsodn{hss
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T:mu
F$rna$€t'' Bt$lerl Aiv Souree
Heat F$fliFfGrffi$d Sourse
Iteat PUTTSJ
Stove'Sasehaard
Yr liBatirs Ssst instegled
l-*estir$ Sei Psturt {Wi$tl
HeaNlri{ bgX HIIEB {bYlfll}
WhenAuav
i-ketirlq Set 8aE$, {'u$}st}
b\ttetr siVt,trf,
Meurgd d0de{Tnilratim Cnst $E I lnsp i Slhsr
Seco$dary Heuting F$el
Tuwe
Eledris ISasf Prspcnel
GilX foalll(,bsd&her
$ecerdmJ Hesttng SlEtrent
Ttpe
Flffisc€d Boilerl Air Bsurce
lieat P$ffSJGrsrrnd $sqJrce
l*eat PurryI
SisrrerEasetloard
$'hat psrcefitase af the
heetin€ seassn is the
secss$da{ s* ftesling sysbm
utedt
Yr ++estin6 S,JSI lns.tslled
The Cadmus Greup, lnc. / Energy Services Appendix 430
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 722 of 1365
Case No. PAC-E-14-07
#B?'iff{lT,'2UTI
Dust SRf ldBa$setrEfltC
inw*rc f Pririanl Jfithw
6uS $Rf C$u,rlBtisri I
lsr!$ioe J PrirrN I StNes
R€s*red, ffitffif
$eqrnred
EeryIred
fte$*red:
ftBsltred
fie$iife$
Fesjirredl
Yes f iCs
Fibtrgtsxbattsi tshfln in
Fitlergkssf tsq*n in
Cell$sseffio**odffi prartt
Fnan*Feml bsffii Bttlsr
LJJSI iil-{ f t1llE;N{TSfEIBT6'
inu$mf Frintpd i[t$rs
Cr"rS SH.i flalfi*al!0o r'
IIY{SElFr$rtedJ*.ther
Yen I Ng,t N,;\
Fe$:}.redl
R-ltrdue lBfsrxnetinfl sn
$.tnirnum T&l Thichpss
$difie{efii tB}Ers ot
ffsierl*. SsEribe
ind*!*$n* layermshrifil
xtd th*ckessesof
iridiu*$uS tryess.
SrBEsl{l atth insi}alis$ sf*
f,*d efilc ins*la{i<xr rua}erid
gn$t SRJ tmp Estir*ate /
FiME[assbal]$ tskvn i*
F,iberyrks$Effimi*
frelfidmeffisclnrmdf$pay
FserlFffir hfixdsrGEler
l\hff Im$Jlflti(sr n'IBtEs$d
Ft8Sedcnlns*JGl s
The Cadmu$ Group, lnc. I Energy Services Appendix 431
Rockv &Jlot;ntain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 723 of 1365
Case No. PAC-E-14-07
dgts?'i{fyT,'zUTT
fleE;lred
ln orderhrcsuttyndl
insttktisrt b,tle effe$ilNe it
mwt fNl: the er$[re wel$ f,rS
i*eel$y be e'Je$$ ssread. The
kr$s$|dwl csnpanf $wuklbe
drillins$rYrBll M€ssrls
cs$$wdlirs$atim
ug req[dar irnte$,EH caliefi$qi
$IE ilrqisity sf tfs* rr'idl, lbffi}
reas{o&e hat+ffir ar$ tCIR}e
top. $ded$, a diunmnd
funrptisr of srtll' holes
ryuxirnatety 1 -Srne$es apart
shsjN hE pre$e!}t- tlria$s{fr
nkcqla{em mout}et en an
erterbr$ffillsd see if
insuletisr cwl he seen.
RE{.lirgd
.*mt*e w.dls lx4 ss*ffi
sftis$ir$isr?
0*r$ fiornemaflsr $it$ess
eanlsclsr lfi stfi$ing vsall
ins:utation?
*yes. sdi$ is th* SJfrfe
tu6h{B ol lhe rftssl]S tldl
iq$uld$ffi?
lf yes, Olg ltls udt hetre
my pr*ex*inE insl$etisrn?
It $q is tle{e e$[de$]cE h8t
h*uffii$msNdhs$tffi
SaeeF
Printed effi lns$ J Ultfer
The Cadmus Group, lnc. I Energy Services Appendix 432
Rocky klountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 724 of 1365
Case No. PAC-E-14-07
#8?'m5ffT,"2H??
lncsrtive Rec.eired
llllas insulation placed
berreuth lhe flocr+ up in
the joints underneath lhe
tir*t ficor?
Ho:ur rnany sq:uare feel of
insulatioo wes instatrled
llgneath the fruav?
lf yes. *ftat type cf
in*uletiosr $.as inslelled?
l-lssi thick r*as the
insrlstio{r instalhd"
Was insulatisn placed in
the rim ioi*i olt the
perlm*ter of the
hasement?
l-law rnany square {eet sf
insslstis,n qms i*stalled in
&e rir* jaist?
lf 1es. *hattype of
insulalien ums instatled?
l-lo*. lhick l*rss the
insr.lletlon instalted?
Ws* insulation ptrrc*d o*
the bss.e$?e$t wells?
Hsw rnanysquam feet sf
insulalinn rvas installed on
the basemerdwalls?
It yes. what gpe of
insulatisn was installed?
l-isw lhick was the
insr"rlatisn instalEed?
Method of deternrination
$lethod of determination
thrrec't i musrrect
Conect d incereet
Flbergtass bettsJ Blwn in
Fiberglmsi Blown in
CeEuhserf Isckermll5pray
Foa*rlFearn boerdg: 0lher
Flbergloss bathJ Blown in
FiberglassJ Elovrr in
Ceff ubsafFlochlroolf $pay
Foarnfoarn boardsJ frther
Fiberglass lr.attd Bbwn in
Fiberg*msf Eh*'n in
Ceff ulose,Rockwoo&Spruy
Foan'u'Foarn baardsil Other
U$st SR / lnsp Estrffate,r
$lher
Cust SH I lnsp i lnrroice I
Prinied on lfistrtr J Sther
Required
Requred
Reguired
The Cadrnus Group, lnc. i Energy Services Appendix 433
Rocky lrilountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 725 of 1365
Case No. PAC-E-14-07
Cgts?"fi#ilT,"2UTT
nGtr Fkr Sh€*ch. trliode :fiile6uresr*e$r$
The Cadrnus Group, lnc. I Energy Services Appendix A34
Rocky Mountain Power
Exhibit No. 5 Page 726 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report #8?"frfrTT,"2UT?
4. Participant Retailer/Contractor Survey
Retailer Name:
Contact Name:
Survey Date:
Contact Phone Number:
lnterviewer lnitials:
Contact Title:
National ENERGY STAR Partner: Yes No
Retailer Segment
1. Department or discount department store (e.g., Dollar, Target, Wal-Mart, Costco)
2. Drug store (e.g., CVS, Walgreens)
3. Electronics (Radio Shack, Best Buy, Ultimate Electronics)
4. Furniture or home furnishing store (e.g., Bed Bath & Beyond, lkea)
5. Grocery store (e.g., Jewel, Dominicks...)
6. Hardware store (e.g., Ace, True Value)
7. Home improvement store (e.g., Home Depot, Lowe's)
8. Lighting specialty store
9. Other [RECORD]
Introduction
ITO RESPONDENT] Hello, my name is INSERT FIRST NAMEI and I am calling from [THE CADMUS
GROUPI on behalf of [PACIFICORP/PACIFIC POWER/ROCKY MOUNTAIN POWER]. May I please
speak with [!NSERT CONTACTI
[!F CONTACT lS AVATLABLE, CONTINUE; lF UNAVAITABE TRY TO RESCHEDULE, lF CONTACT CONTINUES
TO BE UNAVAILBLE SAY "I AM HOPING TO SPEAK WITH SOMEONE WHO IS FAMILIAR WITH PACIFIC
POWER/ROCKY MOUNTAIN POWER'S HOME ENERGY SAVINGS PROGRAM. CAN YOU DIRECT ME TO
SOMEONE ELSE WHO IS KNOWLEDGABLE ABOUT THESE ENERGY.EFFICIENT PRODUCTS?
REINTRODUCE, THEN CONTINUEI
We are currently evaluating the Home Energy Savings Program and I have a few questions l'd like to ask
you about your store and the products you carry. Your responses will remain confidential.
luTrLtw REGroNl
Utah, Wyoming and ldaho = Rocky Mountain Power
Washington and California = Pacific Power
IRESPONSES TO RETATLER QUESTTONS - MAY BE USED tF NECESSARYI
The Cadmu$ Group, lnc. i Energy Services Appendix A35
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 727 ol 1365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasFebfuary 3, 2012
(TlMlNG: This survey should take about 15 minutes of your time. ls this a good time for us to speak with
you? [lF NOT, SET UP CALI BACK APPOINTMENT])
(WHO ARE YOU WITH: I'm with ITHE CADMUS GROUP] an independent research firm that has been
hired by PacifiCorp/PP/RMP to evaluate the Home Energy Savings program.)
(SALES CONCERN: I am not selling anything; we would simply like to learn about your experience with
the Home Energy Savings program. Your individual responses and your company-specific information
will remain confidential. lf you would like to talk with someone from [PACIFIC POWER/ROCKY
MOUNTAIN POWERI about this study, feel free to call [see provided retailer contact list])
(WHY ARE YOU CONDUCTTNG THIS STUDY: Studies like this help IPACIFtC POWER/ROCKY MOUNTAIN
POWERI. better understand customers' need and interest in energy programs and services. Sharing your
opinions and experiences will help us as we consider modifications and improvements to the program
going forward.)
B1.
82,
Do you have 15 minutes to talk?
t. Yes
2. No IARRANGE CALLBACK]
IF lNlTlAt CONTACT WAS NOT REACHED, ASK 82] Are you familiar with the energy-efficient
product lines you carry, and the products for which there are energy-efficient or ENERGY STAR
models available?
1. Yes
2. No [SAY: "Can you provide me with a contact name and phone number for a person at
your store who might be more familiar with the energy-efficient products you carry?" [lF
NO, THANK AND TERMINATE, IF YES . EITHER HANG UP AND RESTART, OR CONTINUE
wtTH SURVEY lF TRANSFERREDI
[F lNlTlAL CONTACI WAS REACHED, ASK 83] Our records show that you are a contact for
[UTltlTY]'s Home Energy Savings Program and hence are familiar with the energy-efficient products
that you carry. ls that correct?
1. Yes
2. No [SAY: "Can you provide me with a contact name and phone number for a person at
your store who might be more familiar with the energy-efficient products you carry?" [lF
NO, THANK AND TERMINATE, IF YES . EITHER HANG UP AND RESTART, OR CONTINUE
WITH SURVEY IF TRANSFERRED]
83.
The Cadmus Group, lnc. i f;nergy Services Appendix A3$
Roclq Mountain Power
Exhibit No. 5 Page 728 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report Cgts?t{ilT,"2UTI
84. The questions I will be asking you focus on the calendar years 2009 and 2010. Were you employed
at this store during those years?
L. Yes
2. No [SAY: "Can you provide me with a contact name and phone number for a person at
your store who was employed during that time and is familiar with the energy-efficient
products that you carry?" [!F NO, THANK AND TERMTNATE, lF YES - EITHER HANG UP AND
RESTART, OR CONTINUE WITH SURVEY IF TRANSFERREDI
1. [RETNTRODUCE tF NECESSARY, OR ARRANGE CAIIBACK]
Interaction with Program / Program staff
C1. How did you initially find out about the HES program?
t. HES field staff called
2. HES field staff stopped by
3. Received a marketing package/materials
4. From another retailer
5. From the utility
6. At a presentation [RECORD WHTCH PRESENTATIONI
7. Manufacturer
8. Other [RECORDI
-98. DON'T KNOW
-99. REFUSED
C2. How helpful are the HES staff at addressing your needs? Would you say they are...[READ LISTI
1. Not at all helpful
2. Not very helpful
3. Somewhat helpful
4. Very helpful
5. I have never interacted with the HES staff
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
C3. What could they have done better?
1. IRECORDI2. Nothing
-98. DON'T KNOW
-99. REFUSED
llF C1 = 3 SKIP TO Csl
The Cadrnus Group, lnc. / Energy $ervices Appendix 437
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 729 of 1 365
Case No. PAC-E-14-07
#E?tffT,"2UT?
C4. Did you receive marketing materials from [PACIFICORP/ROCKY MOUNTAIN POWER] or Portland
Energy Conservation, lnc. (PECI) staff?
t. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
llF c4<>1 SKIP TO DU
C5. How would you describe the amount of marketing materials provided? Would you say there
was...[READ LIST]
3. No information/materials provided
4. Some information/materials provided, but not enough
5. A good amount of information/materials
5. Too much information/materials
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
C6. Was there any information lacking?
1. Yes [RECORDI2. No
-98. DON'T KNOW
-99. REFUSED
C7. What type of marketing materials did you receive? [DO NOT READ]
1. FAQs
2. Applications to hand out to customers
3. Posters
4. Product clings
5. List of qualified products
6. End caps
7. Aisle violators
8. Other IRECORD]
-98. DON'T KNOW
-99. REFUSED
C8. What type of marketing materials did you find most useful? IDO NOT READ]
1. FAQs
2. Applications to hand out to customers
3. Posters
4. Product clings
5. List of qualified products
6. Other [RECORD]
The Cadmu$ Group, lnc. i Energy Services Appendix 438
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountiain Power
Exhibit No. 5 Page 730 of 1 365
Case No. PAC-E-14-07
PgB?'iffiT."2UTz
-98. DON'T KNOW
-99. REFUSED
C9. Do you have any suggestions for changing the marketing materials?
1. [RECORDI
-98. DON'T KNOW
-99. REFUSED
CFL Pricing
Now I would like to ask you a few questions about the energy-efficient products that you sell. Please
remember that questions that I will ask you focus on the years 2009 and 2010.
D1. Did you sell compact fluorescent lamps (or CFLs) during those years?
1.. Yes
2. No [SKIP TO El]
-98. DON',T KNOW [SK!P TO E1]
-99. REFUSED [SKTPTO E1]
D2. Which of the following types of light bulbs did your store stock in 2009 and 2010? [READ LIST;
MAY HAVE MUITIPLE RESPONSESI
L. Standard ENERGY STAR compact fluorescent light bulbs, or CFLs, that are 42 watts or less. By
"standard ENERGY STAR CFLS" I mean bulbs with the ENERGY STAR label that are not
dimmable or reflectors, and have just one light level.
2. Specialty CFLs, such as dimmable, 3-way, spotlights, or reflector CFLS.
3. Both Standard and Specialty
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
D3. Did you sell compact fluorescent lamps (or CFLs) that were discounted through the Home Energy
Savings Program?
1. Yes
2. No [SKIP TO E1]
-98. DON',T KNOW [SK!P TO El]
-99. REFUSED [TO El]
D4. Did your participation in the program, or the materials you received from the program, affect the
way you presented the price differences for high-efficiency products to your customer?
1,. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. / Energy Services Appendix A3$
Rocky Mountain Power ldaho HE$ Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 731 of 1365
ease No. PAC-E-14-07
VMtness: Kathrun C. HvmasFebruary 3. 2012
D6.
D5.lf the HES incentives were not available during 2009 and 2010, do you think your sales of standard
ENERGY STAR CFL bulbs would have been about the same, lower, or higher? [IMPORTANT
QUESTION FOR NTG: PROBE !F DON,T KNOWI
1. Same [SKIP TO D11]
2. Lower
3. Higher
-98. DON',T KNOW ISKIP TO D11]
-99. REFUSED [SK!P TO D11]
Why do you think sales of CFL bulbs would have been [IOWER/HIGHER] [cHEcK TO MAKE SURE
THAT THE EXPIANAT|ON MATCHES THE RESPONSE TO THE PREVIOUS SECTTONI?
!. IRECORD]
-98. DON'T KNOW
-99. REFUSED
[ASK lF D5= 2 OR 31, By what percent would your sales of standard ENERGY STAR CFLs have been
[LOWER/HIGHER] without the Home Energy Savings program? [IMPORTANT qUESTION FOR NTG:
PROBE IF DON'T KNOW]
1. Less than 10%
2. to%-Lg%
3. 2O%-29o/o
4. 30%-39%
5. 40-49%
6. 50%-59%
7.60%-69%
8. 70%-79%
9. 80%-89%
70. 90% or more
-98. DON'T KNOW
-99. REFUSED
Just to confirm, your sales of standard ENERGY STAR CFLs would have been [INSERT % FROM D7]
ILOWER/HIGHERI in 2009 and 2010 if the [PACIFIC POWER/ROCKY MOUNTAIN POWER] program
was not available?
1. Yes [PROBE: WHY?]
2. No [PROBE: WHY?]
-98. DON'T KNOW
-99. REFUSED
D7,
llF D2 <> 2 SKIP TO D1lI
D9. You said that during 2009 and 2010 your sales of standard CFLs without the Home Energy Savings
lncentive program would have been [LOWER, SAME, HIGHER]as/than with the program. How
about for specialty ENERGY STAR CFLs, such as dimmable, 3-way, or reflectors- would your sales
D8.
The Cadmus Group, lnc. I Energy $ervi*es Appendix 440
Rocky Mountain Power ldaho HES Evaluation 2009*2010 Final Report
Rocky Mountain Power
Exhibit No, 5 Page 732 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathrun C. HvmasFebiuary 3. 2012
of specialty ENERGY STAR CFLs have been about the same, lower, or higher without the [PACIFIC
POWER/ROCKY MOUNTAIN POWERI incentives? [IMPORTANT QUESTTON FOR NTG: PROBE lF
DON'T KNOWI
1. Same
2. Lower
3. Higher
-98. DON'T KNOW
-99. REFUSED
D10. [ASK lF D9 = 2 OR 3] By what percent would your sales of specialty ENERGY STAR CFLs have been
ILOWER/HIGHER] without the program? [!MPORTANT QUESTION FOR NTG: PROBE lF DON'T
KNOWI
L. Less than 10%
2. t0%-L9%
3. 20%-29%
4. 30%-39%
5. 40-49%
6. 5OYo-59o/o
7. 60%-69%
8. 70%-79%
9. 80%-89%
LO.90% or more
-98. DON'T KNOW
-99. REFUSED
Dl1. Can you estimate the percent of customers who were buying CFLs for their own homes, the
percentage who were buying CFLs for their own businesses, and the percentage who were builders
or contractors buying them for construction or retrofit projects?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
ltF D11 <>1 SKIP TO D14l
D12. What's your percent estimate of this breakdown? [tF NEEDED PROMPT: "ls it about 50%
contractors, 50% homeowners, etc."]
% of customers buying CFLs for their own homesL.
2.
3.
-98.
-99.
% of customers buying CFLs for their own businesses
% of customers buying CFLs for construction/retrofit projects
DON'T KNOW
REFUSED
[F D12 = -98 OR -99 SKIP TO D14l
The Cadmus Group, lnc. / Energy $ervices Appendix A4t
Rocky ftflountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 733 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasFebruary 3. 2012
D13. What information is this based on? [F NEEDED, PROMPT: "Size of purchase, interaction with
customers, etc."l
1. [RECORDI
-98. DON'T KNOW
-99. REFUSED
D14. Considering data you might have available or your personal knowledge, what would you estimate
the total soles in dollars and in number of bulbs of all CFLs to be for your store over the course of a
year? [THIS INCIUDES PROGRAM BUTBS AND NON-PROGRAM BULBS, STANDARD AND SPECIALTY
BULBSIIIF CAN'T ESTIMATE YEAR, ASK TO ESTIMATE MONTH; AISO TRY TO GET ANSWER !N BOTH
ss AND UNTTSI
1. IRECORD]
-98. DON'T KNOW
-99. REFUSED
D15. During 2009 & 2010, what percent of your total CFL sales would you estimate are CFLs purchased
through the HES Lighting Program? Would it be...[READI [!MPORTANT QUESTION FOR NTG: PROBE
IF DON'T KNOW]
1. Less than 10%
2. too/o-Lg%
3. 20%-29%
4. 30%-39%
5. 40-49%
6. so%-59%
7.60%-69%
8. 70%-79%
9. 80%-89%
10. 90% or more
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
D16. Are you familiar with the coming energy efficiency requirements for light bulbs from the Energy
lndependence and Security Act of 2007? lt is commonly referred to as EISA.
1. Yes
2. No
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READI Refused
[lf D15=1 SKIP TO D18l
D17. EISA requires new efficiency requirements for common light bulbs. The new federal standards
in EISA require the same amount of light output be produced with fewer watts. The standards
outlined in EISA will be phased in over the next 3 years starting in2OL2. Does this sound
familiar?
The Cadrrrus Group, lnc. i Energy $ervices Appendix A42
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 734 of 1 365
Case No. PAC-E-14-07
#ts?'fiffiT,"2UT?
1. Yes
2. No
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] Refused
ltf D17<>1 SKIP TO D22l
D18. Has your store changed stocking practices to prepare for EISA? lf so, how?
t. Yes [RECORD]2. No
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READI Refused
D19. Does your store or company plan on making any other stocking changes in preparation for EISA?
1. Yes [RECORD]2. No
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] Refused
D20. Does your store have any plans to help educate customers on EISA with marketing materials
such as in-store displays?
1. Yes [RECORD]2. No
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] Refused
Dz1.,. Have you received any feedback from your customers on EISA?
1. Yes IRECORD]2. No
-98. IDO NOT READ] DON',T KNOW
-99. IDO NOT READ] Refused
D22. [lF D17<>1] Since you're not familiar with EISA, would you like program staff to follow-up with
you to provide you information on EISA?
1. Yes
2. No
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI Refused
E. Program Promotion
The next few questions focus on how you market energy efficiency and the Home Energy Savings
program.
The Cadrnus Group, lnc. I Energy Services Appendix A43
Roclry Mountain Power
Exhibit No. 5 Page 735 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report Cgts?"ffffT,t2UTT
E1. How do you typically inform your customers of the incentives available for qualifying energy-
efficient products? [DO NOT READ; RECORD MULTIPtE RESPONSES]
7. Radio ads
2. TV ads
3. Print ads4. Post posters on the retail floor
5. Product clings on qualifying appliances
6. Put out applications
7. I mention the program when I assist customers
8. I don't inform customers of the program
9. I only mention if they ask about energy efficient appliances
10. Don't need to inform, they already know about it
11. I rely on marketing by the program.
12. Other [RECORD]
13. Did not promote the Program [PROBE: WHY NOT?I
-98. DON'T KNOW
-99. REFUSED
The Cadrnu$ Group, lnc. I Energy Services Appendix 444
E,h i bit f":"YPYsTrH:iilfJ
Case No. PAC-E-1447
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report Cgts?'frfr?T,"2UT?
E3. What types of marketing materials seem to be most effective?
1. Product clings
2. Posters
3. Flyer/handout
4. List of qualified products
5. Send them to the website
6. They prefer talking with salesperson
7. End-caps
8. Aisle violators
9. Bill inserts
10. ln-store tabling
1L. Other IRECORD]
-98. DON'T KNOW
-99. REFUSED
E4. Do you use the availability of high-efficiency products to attract customers to your business?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
E5. How often do you and your sales staff recommend the more energy-efficient options to
customers? Would you say...[READ LIST]
1. Never
2. Rarely
3. Sometimes
4. Often
5. Always
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
E6. What tends to be the selling point for the higher efficiency products?
1. Cost saving on bill
2. Energy savings
3. lncentive Amount
4. Environmental benefits
s. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
E7. Do you think your customers understand the energy-related benefits?
7. Yes
2. No
o
The Cadrnus Group, lnc. i Energy Services Appendix 445
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 737 of 1 365
Case No. PAC-E-14-07
CBts?"i-ffiT,"2UTz
E8.
E9.
-98. DON'T KNOW
-99. REFUSED
What types of programs or incentives do you think [PACIFICORP/PACIFIC POWER/ROCKY
MOUNTAIN POWERI should offer to make energy-efficient products or equipment more attractive
to your customers?
7. [RECORD]
-98. DON'T KNOW
-99. REFUSED
Of all the energy-efficient products you sell, which one or two do you believe customers are the
least aware of?
t. IRECORDI
-98. DON'T KNOW
-99. REFUSED
E9a. Do you have any suggestions for how [INSERT UTltlTYl could help promote these technologies?
1. Yes [RECORD]2. No
.98. DON'T KNOW
.99. REFUSED
E10. Of all the energy-efficient products you sell, which one or two do you believe customers are the
most aware of or most likely to purchase without any additional advertising or promotions?
1. [RECORD]
-98. DON'T KNOW
-99. REFUSED
E11. Why do you think most customers choose not to participate in the program?
7. Measures too expensive
2. lncentive applications are too complex
3. Program is too much of a hassle
4. Customers are unaware of the benefits of energy efficiency
-98. DON'T KNOW
-99. REFUSED
E12. Do you think that the incentives are set at the right level?
7. Yes
2. No [RECORD ANSWERI
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. I Energy Services Appendix 446
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclly Mountain Po,er
Exhibit No. 5 Page 738 of 1 365
Case No. PAC-E-14{7
PBS?IffiT,'2UT?
SaIes
Now I have a few questions about the products you sell.
F1. Which of these appliances or pieces of equipment does your store sell? [READ tlST, RECORD
MULTTPLE RESPONSESI
1. Clothes Washers
2. Refrigerators
3. Dishwashers
4. Water heaters - electric, natural gas, heat pump water heaters
5. Lighting Fixtures
6. Ceiling Fans
7. Windows
8. lnsulation
9. Central A/C Equipment
10. Evaporative Cooler
11. Room AC
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
[REPEAT QUESTIONS F2.F3 FOR EACH MEASURE THAT THE RETAILER CARRIESI
F2. During 2009 and 2010, how many [tF MEASURE=INSUIATION, "square feet of'] UNSERT
MEASUREI would you estimate that your store sold?
7. [RECORD]
-98. DON',T KNOW [ATTEMPT TO GET A RANGE TO NEAREST 50 OR 100]
-99. REFUSED IATTEMPT TO GET A RANGE TO NEAREST 50 OR 100]
The Cadrnus Group, lnc. / Energy Services Appendix A47
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclq Mountain Power
Exhibit No. 5 Page 739 of 1365
Case No. PAC-E-14-07
Vvitness: Kathrun C. HvmasFebruary 3, 2012
F3. What percent of the [MEASUREI you sold during 2009 and 2010 were high-efficiency (ENERGY
STAR6) rated or above?
1. [RECORD %]
F1 F2 F3
Carry Product?
(Y/N)
QTY SOID
(#l
% Energy Star
(o/ol
Clothes Washers
Refrigerators
Dishwashers
Electric Water Heaters
Lighting Fixtures
Ceiling Fans
Windows
Central A/C
Evaporative Cooler
Room AC
IEND REPEATED SEQUENCEI
F4. How would you rate the typical customer when you tell them about the energy-saving potential of
ENERGY STAR appliances? Would you say they are:
1. Not at all interested
2. Not very interested
3. Somewhat interested
4. Very interested
-98. DON'T KNOW
-99. REFUSED
F5. During 2009 and 2010, did the NUMBER of energy efficiency PRODUCTS you offer customers
increased, decreased or stayed the same?
1. lncrease
2. Same
3. Decrease
-98. DON'T KNOW
-99. REFUSED
llF F5 = 2 OR -98 OR -99 SKIP TO GU
The Cadrnus Group, lnc. i Energy Services Appendix 448
Rocky Mountain Power
Exhibit No. 5 Page 740 of 1 365
Case No. PAC-E-'14-07
Cg8?i#T,"2UTIRocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
F6. What do you think are the main reasons for this change?
1. [RECORDI.98. DON'T KNOW
.99. REFUSED
Program Satisfaction
We're almost done. ljust have a few quick questions about your overall satisfaction with the program.
G1. How easy was it for your store to participate in [UTlLtWl's Home Energy Saving Program? Would
you say it was...
1. Very easy
2. Somewhat easy
3. Not very easy
4. Not at all easy
-98. DON'T KNOW
-99. REFUSED
G2. How satisfied are you with your overall program experience? Would you say you are...
1. Very satisfied
2. Somewhat satisfied
3. Not very satisfied
4. Not at all satisfied
-98. DON'T KNOW
-99. REFUSED
G3. Are there any changes you would recommend to improve the Home Energy Services Program?
1. Yes [RECORD]
2. No
.98. DON'T KNOW
-99. REFUSED
Conclusion
H1. What is the best way to contact your store about [PACIFIC POWER/ROCKY MOUNTAIN POWERI
programs and services?
1. HES field staff call
2. HES field staff visit
3. Mail marketingpackage/materials
The Cadrnus Group, lnc. / Energy Services Appendix A49
Roclry Mountain Power
Exhibit No. 5 Page 741 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Finat Report dg$?'fi{ffT,t2uT?
4. Through manufacturerfield reps
5. Through corporate office
6. At a presentation/trade show [RECORD]7. Email
8. Other IRECORD]
-98. DON'T KNOW
-99. REFUSED
H2. Those are all of the questions I have for you; but if I have a quick follow-up question at a later date
would it be alright if I called back at that time?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H3. Do you have any final questions or comments for INSERT UTILITY]?
1. Yes [RECORDI2. No
-98. DON'T KNOW
-99. REFUSED
Thank you again for your time.
The Cadmus Group, lnc. I Energy Services Appendix 450
Rocky Mountain Power
Exhibit No. 5 Page 742 of I 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report CgB?;ffT,t2UTE
5. ln-Territory Lighting Suruey
luilLrrYI
Washington and California: Pacific Power
Utah, Wyoming, and ldaho: Rocky Mountain Power
Introduction
ITO RESPONDENT] Hello, l'm INSERT FIRST NAMEI, calling from Discovery Research, on behalf of
llNsERT UTIUTY]. Can I speak with INSERT NAMEI?
Hello, we are conducting a survey about household lighting and home energy use and would like to ask
you some questions about your household's lighting and energy use. We would greatly appreciate your
opinions.
llF NOT AVAILABLE, ASK FOR AN ADULT tN THE HOUSEHOLD WHO tS RESPONSTBTE FOR PURCHASING
THE TIGHT BULBS. IF NO ONE APPROPRIATE IS AVAILABLE, TRY TO RESCHEDULE AND THEN
TERMINATE. IF TRANSFERRED TO ANOTHER PERSON, REPEAT INTRO AND THEN CONTINUE.]
Responses to Customer Questions [!F NEEDEDI
(Timing: This survey should take about 15 minutes of your time. ls this a good time for us to speak with
you?)
(Who are you with: I'm with DISCOVERY RESEARCH, an independent research firm that has been hired
by [INSERT UTIIITY] to conduct this research. I am calling to learn about your household lighting and
home energy use)
(Sales concern: I am not selling anything; we would simply like to learn about your household lighting
and home energy use. Your responses will be kept confidential. lf you would like to talk with someone
from INSERT UTILITY] about this study, feel free to call 1-800-942-0266, or visit their website:
http ://www. homeenergvsavi nes. net/)
(Who is doing this study: [INSERT UTtLlTYl, your electric utility, is conducting evaluations of several of
its efficiency programs, including the Home Energy Savings program.)
(Why are you conducting this study: Studies like this help INSERT UTILITY] better understand customers'
need and interest in energy programs and services.)
The Cadnru$ Group, lnc. i Energy Services Appendix 451
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 743 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. HvmasFebruary 3, 2012
s2.
s3.
s4.
This call may be monitored for quality assurance. First, Are you the person who usually purchases
light bulbs for your household?
1. Yes
2. No, but person who does can come to phone ISTART OVER AT INTRO SCREEN WITH NEW
RESPONDENTI
3. No, and the person who does is not available [SCHEDUIE CALLBACK]
-98. DON',T KNOW ITHANK AND TERMINATE]
-99. REFUSED [THANK AND TERMINATE]
Have you ever been employed in the market research field?
L. Yes [THANK AND TERMINATEI
2. No [CONTINUEI
-98. DON',T KNOW [THANK AND TERMINATE]
-99. REFUSED ITHANK AND TERMTNATE]
Have you, or anyone in your household, ever been employed by or affiliated with [INSERT UTltlTYl
or any of its affiliates?
7. Yes [THANK AND TERMINATE]
2. No [CoNTtNUE]
-98. DON',T KNOW ITHANK AND TERMINATEI
-99. REFUSED [THANK AND TERMTNATE]
The Cadmus Group, lnc. I Energy Services Appendix A52
Rocky Mountain Power
Exhibit No. 5 Page 744 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report #ts?'frffiT,"2UT?
Familiarity with CFLs
First, I would like to ask you about your familiarity with different types of light bulbs.
C1. Before this call today, had you ever heard of compact fluorescent bulbs, or CFLs?
1. Yes [SKIP TO C3l
2. No
C2. Compact fluorescent light bulbs - also known as CFLs - usually do not look like traditional
incandescent light bulbs. The most common type of compact fluorescent bulb is made with a glass
tube bent into a spiral, resembling soft-serve ice cream, and it fits in a regular light bulb socket.
Before today, were you familiar with CFLs?
t. Yes
2. No [THANK AND TERMINATE]
C3. How familiar are you with CFLs? Would you say that you are... [READ]
1. Very familiar
2. Somewhat familiar
3. Not too familiar, or
4. Not at all familiar
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
CFL Purchases
Now I have some questions about your lighting purchases during the last two calendar years, 2009 and
20L0.
E1. Did you purchase or receive any CFLs in 2009 or 2010?
1. Yes
2. No [THANK AND TERMINATEI
-98. DON',T KNOW ITHANK AND TERMTNATE]
-99. REFUSED [THANK AND TERMTNATE]
E2. IASK lF El= 1l During 2009 and 2010, how many CFLs did you or your household purchase or
acquire? Please try to estimate the total number of individuol CFL bulbs, as opposed to packages.
[lF "DON'T KNOW," PROBE: "ls it less than or more than five bulbs?" WORK FROM THERE TO
GET AN ESTTMATEI
INUMERIC OPEN END: RECORD NUMBER OF CFLS, NOT A RANGE.I [!F QUANTTTY=O, THANK AND
TERMINATE]
The Cadmus Group, lnc. I Energy Services Appendix A53
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclq Mountain Power
Exhibit No. 5 Page 745 of 1365
Case No. PAC-E-14-07
Wtnes: Kathrun C. HvmasFebruary 3. 2012
E3.
E4.
E5.
E6.
1. IRECORD f oF cFtsl
-98. DON,T KNOW [PROBE FOR ESTIMATES; IF UNABLE TO GET AN ANSWER, THANK AND
TERMINATE]
-99. REFUSED [THANK AND TERMINATE]
Of these INSERT QUANTITY FROM E2] CFLs that you acquired in 2009 and 2010, how many did you
buy at a retail store as opposed to receiving them for free?
1. [RECORD # oF CFLs]
2. NONE
-98. DON'T KNOW
-99. REFUSED
[ASK lF E3=1] How many, if any, of the ilNSERT QUANTITY FROM E3] CFLs that you bought at a
retail store were part of a [INSERT UTIITY] sponsored sale?
1. [REcoRD # oF CFLsI
2, NONE
-98. DON'T KNOW
-99. REFUSED
How many did you receive for free from an individual or organization?
t. [REcoRD # oF CFLs]
2, NONE
-98. DON'T KNOW
-99. REFUSED
[ASK lF E3+ E5< QUANTITY FROM 0] Thanks, that accounts for [E3+E5] of the total quantity that
you bought during those two years. Can you tell me where you got the IINSERT QUANTITY OF 0
MINUS (E3+E5)l other bulbs from?
t. [RECORD VERBATUM] OR ADJUST E3 AND Es ACCORDTNGLY
-98. REFUSED
-99. DON'T KNOW
E7. [ASK rF
of bulb?
t.
2.
-98.
-99.
E4.1 > 0l Did the utility discount influence your decision to purchase CFLs over another type
Yes
No
DON'T KNOW
REFUSED
The Cadmus Group, lnc. i Energy Services Appendix A54
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 746 of 1 365
Case No. PAC-E-14-07
Cgts?t5ffT,'2UT?
E8. What [!F E7=01 lS ASKED SAY "othe/'] factors influenced your decision to buy CFLs over other types
of bulbs? [Do NoT READ] [MUITIPLE RESPONSES AIIOWED]
t. Energy savings
2. Cost savings on electricity bill
3. Price of bulb
4. Environmental concerns
5. Quality of light
6. Lifetime of bulb
7. Other [RECORD]
.98. DON'T KNOW
-99. REFUSED
E9. [SKIP lF E3 = 2i i.e. "did not buy any bulbs, only received free bulbs"] Where did you buy the
majority of your CFL bulbs purchased in 2009-2010? [MUtTlPtE RESPONSES ALLOWED. DO NOT
READ]
1. Ace Hardware [RECORD CITY AND STATE]
2. Albertsons IRECORD CITY AND STATE]
3. Bed Bath and Beyond [RECORD CITYAND STATE]
4. Best Buy IRECORD CITY AND STATE]
5. CVS [RECORD CrTY AND STATE]
5. Decker's Food Center [RECORD CITY AND STATE]
7. Discount Grocery [RECORD CIW AND STATE]
8. Do it Best Hardware [RECORD CITY AND STATEI
9. Dollar Tree [RECORD CITY AND STATE]
10. Family Dollar [RECORD CIW AND STATE]
11. Home Depot [RECORD CITY AND STATE]
12. Kennedy Hardware lnc. [RECORD CITY AND STATEI
13. Kmart [RECORD CIW AND STATE]
14. Lighting One [RECORD CITY AND STATE]
15. Loaf'N Jug [RECORD CITY AND STATE]
16. Lowe's [RECORD CtW AND STATE]
17. Office Depot [RECORD CITY AND STATE]
18. Red Eagle Food Store [RECORD CITY AND STATE]
19. Rite Aid [RECORD CITY AND STATE]
20. Ridley's Family Market [RECORD CITY AND STATE]
21. Safeway IRECORD CITY AND STATE]
22. Sam's Club [RECORD CITY AND STATE]
23. Staples [RECORD CITY AND STATEI
24. The Home Depot [RECORD CIW AND STATEI
25. True Value Hardware [RECORD CITY AND STATE]
26. Walgreens [RECORD CITY AND STATEI
27. Walmart [RECORD CITY AND STATE]
28. Whole Foods [RECORD CITY AND STATEI
29. Other [REcoRD VERBATIM] [REcoRD clTY AND STATEI
The Cadmus Group, [nc. i Energy Services Appendix A55
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 747 of 1 365
Case No. PAC-E-14-07
Cgts?t#{T,'2UTI
-98. DON'T KNOW
-99. REFUSED
Now l'd like to ask you a few questions about where the [READ lN QUANTITY FROM [INSERT E2] CFLs
you acquired in 2009 and 2010 are now.
E10. How many are currently installed in your home?
1. IRECORD # OF CFLs] [lF THIS QUANTITY = E2 QUANTIW, SKIP TO E14, lE "ALL BULBS ARE
lNsrAtLED tN HOME"I
2. NONE
-98. DON'T KNOW
.99. REFUSED
E11. How many are in storage for later use?
1. [RECORD # OF CFLs]
2. NONE
-98. DON'T KNOW
-99. REFUSED
E12. How many were discarded or given away?
1. IRECORD # oF CFts]
2. NONE
-98. DON'T KNOW
-99. REFUSED
E13. IASK tF E10+ E11+E12<> QUANTITY FROM 0] Thanks, that accounts for [E10+ E11+E12] of the total
quantity that you bought during those two years. Can you tell me where the [INSERT QUANTIW OF
0 MINUS (E8+ E9+ E10)l other bulbs are now?
7. IRECORD VERBATUM]
-98. REFUSED
-99. DON'T KNOW
The Cadmus Group, lnc. i Energy Services Appendix 456
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 748 of 'l 365
Case No. PAC-E-14-07
dg8?'fi{#T,'2UT}
Ela. [Skip if E10 = 0l Of the [INSERT QUANTITY E10l bulbs that are currently installed in your home that
were purchased during 2009 and 2010, can you tell me how many CLFs are installed in each room
in your house?
1. Bedroom [RECORD]2. Bedroom (unoccupied) [RECORDI3. Basement [RECORD]4. Bathroom [RECORDI5. Closet IRECORD]6. Dining [RECORD]7. Foyer [RECORD]8. Garage [RECORDI9. Hallway [RECORDI
10. Kitchen [RECORDI
11. Office/Den [RECORD]
1.2. Living Space [RECORD]
13. Storage [RECORD]
14. Outdoor [RECORD]
15. Utility [RECORDI
16. Other [RECORD VERBATIMI
-98. DON'T KNOW
-99. REFUSED
E15. [ASK rF TOTAT BUTBS tN E14 <qUANTIW FROM E10 (tF TOTAT NUMBER OF BUTBS LTSTED rN EACH
ROOM DOES NOT MATCH THE NUMBER OF BULBS INSTALLED STATED !N E10l Thanks, that
accounts for [TOTAL BULBS lN 8114] of the total quantity that are currently installed in your home.
Can you tell me where the IQUANTITY OF E10 MINUS TOTAT BULBS lN E14] other bulbs are
installed?
1. [RECORD VERBATUM]
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. / Energy Services Appendix A57
Roclry Mountain Power
Exhibit No. 5 Page 749 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009*2010 Final Report Pgts?t'#T,"2UT?
Program Awareness
84. [UTltlTY] offers discounts on CFLs at participating retailers in your area through a program called
Home Energy Savings. Before today, were you aware of this program?
1. Yes
2. No
[lF B4=1, OTHERWISE SKIP TO Fll
81. How did you first hear about the INSERT UTltlTY]'s Home Energy Savings program? [DO NOT
READ UST. RECORD FIRST RESPONSE. ONE ANSWER ONLYI
1. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power/Pacific Power website
4. Home Energy Savings website
5. Other website
6. lnternet Advertising/Online Ad
7. Family/friends/word-of-mouth
8. Rocky Mountain Power/Pacific Power Representative
9. Radio
L0. w
L1. Billboard/outdoor ad
12. Retailer/Store
13. Sporting event
L4. Home Shows/Trade Shows (Home and Garden Shows)
15. Social Media
16. Other [RECORD VERBATUM]
-98. IDO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
82. [ASK lF B1<>4] Have you ever visited the Home Energy Savings website?
1. Yes
2. No
83. [ASK lF 82 = L OR B1=4] Was the website... [READ]
7. Very helpful
2. Somewhat helpful
3. Somewhat unhelpful
4. Very unhelpful
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
The Cadrnus Group, lnc. / Energy Services Appendix A58
Rocky Mountain Power ldaho HES Evaluation 2009*2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 750 of 1 365
Case No. PAC-E-14-07
CgB?'frff{T,'zUT?
85. [ASK lF B2=1 OR 81 = 4] Have you ever viewed the list of participating retailers on INSERT
UTILITYI's Home Energy Savings website?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
Willingness to Pay
I am going to ask you a few questions about prices of CFL bulbs. Thinking about the [INSERT QUANTITY
FROM E2l CFLs that you purchased in 2009 and 2010 please tell me if you would have purchased more,
less or the same amount of CFLs at each price. [RANDOM ORDER OF QUESTIONS, EITHER ASCENDING
oR DECENDTNG PRTCESI
F1. lf the bulbs were S18, would you have bought more, less or the same amount? IPROBE lF
DON'T KNOWI
1. More
2. Fewer
3. Same number
-98. DON'T KNOW
-99. REFUSED
[F Fl = 1 OR 2] And how many CFLs would you have purchased if each bulb had cost S18?
IPROBE tF DON',T KNOWI
1. IRECORD NUMBER]
.98. DON'T KNOW
.99. REFUSED
lf the bulbs were $12, would you have bought more or less than [INSERT QUANTTW FROM Ezl
CFLs? [PROBE lF DON'T KNOW]
1. More
2. Fewer
3. Same number
-98. DON'T KNOW
.99. REFUSED
[tF F3 = l OR 2] And how many would you have purchased at $12? [PROBE tF DoN'T KNow]
1. IRECORD NUMBER]
-98. DON'T KNOW
-99. REFUSED
F2,
F3.
F4.
The Cadrnus Group, lnc. / Energy Services Appendix 459
Rocky Mountain Power
Exhibit No. 5 Page 751 of 1 355
Case No. PAC-E-14-07
Rocky tulountain Power ldaho HES Evaluation 2009-2010 Final Report #S?'frffT,"2UT?
Thanks. ljust have two more prices that I would like to ask you about.
F5. lf the bulbs were 56, would you have bought more or less than [INSERT QUANTITY FROM E2l CFLs?
IPROBE IF DON',T KNOWI
1. More
2. Fewer
3. Same number
-98. DON'T KNOW
-99. REFUSED
F6. [!F fS = 1 OR 2l And how many would you have purchased at 56? [PROBE lF DON'T KNOWI
1.. IRECORD NUMBER]
-98. DON'T KNOW
-99. REFUSED
F7. lf the bulbs were 50.50, would you have bought more or less than [INSERT QUANTITY FROM E2]
CFLs? [PROBE lF DON'T KNOW]
1. More
2. Fewer
3. Same number
-98. DON'T KNOW
-99. REFUSED
F8. llF F7 = 1 OR 2] And how many would you have purchased at 50.50? [PROBE lF DON'T KNOW]
t. [RECORD NUMBERI
-98. DON'T KNOW
-99. REFUSED
CFL Satisfaction
IASK CFr SATTSFACTTON SECTTON ONLY rF E8 > 0 (CURRENTTY HAS CFLS TNSTATLED)I
G1. Approximately how long ago did you FIRST use a compact fluorescent light bulb? [RECORD EITHER
MONTHS OR YEARSI
L. Months IRECORD]2. Years [RECORD]
-98. DON'T KNOW
-99. REFUSED
The Cadrnus Group, lnc. / Energy Services Appendix A60
Rocky l\dountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 752 of 1 365
Cas No. PAC-E-14-07
dgts?"fr#-J,"2UT?
G2.
G3.
How satisfied are you with the compact fluorescent light bulb(s) currently in your home? Would
you say you are... [READI
1. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied4. Not At All Satisfied
-98. IDO NOT READ] DON',T KNOW
-99. [DO NOT READI REFUSED
[!F G2= 3 OR 4l And why do you say that?
1. IRECORD VERBATUMI
-98. DON'T KNOW
-99. REFUSED
Behavioral Changes
H1. Think about the last CFL that you installed in your home. What type of bulb was in the socket
before you installed the CFL?
7. lncandescent (or "traditional" bulbs)
2, CFL
3. LED
4. Florescent
5. Halogen
6. Empty
7. Has never installed a CFL
-98. DON'T KNOW
-99. REFUSED
[!F Hl = 6,7,98 OR 99 SKIP TO Jl]
H2. Was the bulb still working when you removed it?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H3. [lF H2 = 1l Was the bulb you removed... [READ]
7. Moved to a different socket
2. Stored for later use
3. Thrown away
4. Recycled
5. Other [RECORD]
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READI REFUSED
The Cadmus Group, lnc. i Energy Services Appendix 461
Rocky Mountain Power ldaho FIE$ Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 753 of 1 365
Case No. PAC-E-14-07
Witness: Kathrun C. HvmasFebruary 3. 2012
H4.Since installing the CFL in that socket, has your use of that light... [READ]
1. lncreased
2. Stayed the same
3. Decreased
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
[lF H4 = I OR 3] After you replaced the bulb with a CFL did your use flNCREASE/DECREASEI by..,
IREADI
1. More than t hour a day, or
2. Less than or equal to t hour a day
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
UF H4 = 1 OR 3l Why did your use of the socket INCREASE/DECREASEI?
1. IRECORD VERBATUMI
-98. DON'T KNOW
-99. REFUSED
EISA Awareness
The Energy lndependence and Security Act of 2007 sets new federal efficiency standards for
lighting that will be phased in beginning in 2012. These standards will require that traditional
incandescent light bulbs improve their efficiency by about 25% over current levels. Most traditional
incandescent light bulbs will not meet the efficiency standard and will not be sold. Before this call
today, had you ever heard of this new federal standard for lighting?
L. Yes
2. No
Manufacturers are developing more efficient incandescent bulbs that will meet the new federal
standards. Given the choice of purchasing a more efficient incandescent bulb or a CFL, LED or
halogen bulb, which do you think you would purchase?
L. lncandescent bulb
2, CFL
3. LED
4. Halogen
5. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
H5.
H6,
J1.
J2.
The Cadmus Group, lnc. I Energy Services Appendix 462
Rocky lVlountain Power ldaho l-lES Evaluation 200$-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 754 of 1 365
Case No. PAC-E-14-07
Wtness: Kathiln C. HvmasFebruary 3, 2012
CFL Disposal
K1. Have you had any CFLs burn out in the past 12 months?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
K2. Have you disposed of any CFLs in the past 12 months?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
K3. IASK lF K2=1] How did you dispose of the CFL(s)? [DO NOT READ. ATLOW MUITIPIE RESPONSE]
1. Threw away in trash
2. Recycled / dropped off at hazardous waste center
3. Brought to a Home Depot or another retail store to recycle
4. Held onto/stored at home
5. Other IRECORD]
.98. DON'T KNOW
-99. REFUSED
[SKIP TO K5 lF 82 =21 Have you visited the Home Energy Savings or [UTltlTYl's webpage on CFL
disposal?
1. Yes
2. No
[!F K4 = 1] How satisfied were you with the information provided on [UTlLlTYl's CFL disposal
webpage?
1. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied
4. Not At All Satisfied
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
What concerns, if any, do you have with the disposal of CFLs? [DO NOT READ. ALLOW MULTIPLE
RESPONSESI
K4.
K5.
K6.
The Cadmus Group, lnc. i Energy Services Appendix 463
Roclry Mountain Power
Exhibit No. 5 Page 755 of 1365
Case No. PAC-E-14-07
Rocky ttrlountain Power ldaho HES Evaluation 2009-2010 Final Report #8?"fr#iiH,"2UT?
1. None
2. Mercury
3. Requires special disposal/Must be recycled
4. Fire hazard
5. Other [RECORDI
-98. DON'T KNOW
-99. REFUSED
[lF RESPONDENT ASKS: Why should I be concerned about the disposal of CFLs? ANSWER: CFLs contain
a very small amount of mercury sealed within the glass tubing. The Environmental Protection Agency
(EPA) recommends that consumers take advantage of available recycling options offered by
manufacturers and retailers. Many stores that sell CFLs also recycle them. You can find a listing of
participating retailers and CFL recycling locations on [UTltlTY]'s Proper CFL Disposal webpage [tF
UTltlry = RoCKY MoUNTAIN POWERI (http:/&tww.,fgqkv-mq;.mtgjnngy.v-ef,net/S.fldisposal: [if UTILITY
= PACIFtC POwER] htln:/lunryf,pacificop"u{e"r.ngt/gfldisnqra!).I
LED Usage
Now I would like to ask you about your experience with LED bulbs.
M1. LEDs or light emitting diodes are bulbs that are comprised of many smaller nodular shaped lights
that are very bright. Common uses for LEDs include car brake lights and flashlights. We are
interested in the LEDs that have been developed to replace traditional household lighting. How
familiar are you with LEDs? Would you say that you are... [READI
L. Very Familiar
2. Somewhat familiar
3. Not too familiar, or
4. Not at all familiar
-98. DON',T KNOW [DO NOT READI
-99 REFUSED [DO NOT READ]
M2. Did you or someone in your household purchase any LED bulbs for standard lighting sockets in
2009 and 2010 to be installed in your home?
1. Yes
2. No
-98. DON',T KNOW [DO NOT READ]
-99 REFUSED [DO NOT READ]
The Cadmus Group, lnc. i Energy $ervices Appendix 464
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 756 of 'l 365
Case No. PAC-E-14-07
#ts?'mffiT,'2UTI
[lF M2 = 2, 98 OR 99 SKIP TO D1]
M3. How many did you purchase during 2009 and 2010?
L. IRECORD NUMBERI
-98. DON'T KNOW
-99. REFUSED
M4. Of the LED bulbs that are currently installed in your home can you tell me how many LEDs are
installed in each room in your house?
1. Bedroom [RECORDI2. Bedroom (unoccupied) [RECORDI3. Basement [RECORD]4. Bathroom [RECORD]5. Closet [RECORD]6. Dining [RECORD]7. Foyer [RECORD]8. Garage [RECORD]9. Hallway [RECORD]
10. Kitchen [RECORDI
11. Office/Den [RECoRD]
12. Living Space IRECORD]
13. Storage [RECORDI
14. Outdoor [RECORD]
L5. Utility [RECORDI
15. Other IRECORD VERBATIMI
-98. DON'T KNOW
-99. REFUSED
M5. How satisfied are you with the LED bulbs currently in your home? Would you say you are... [READ]
t. very satisfied
2. Somewhat Satisfied
3. Not Very Satisfied
4. Not At All Satisfied
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
M6. [lF M5 = 3 OR 4] And why do you say that?
1.. IRECORD VERBATTM]
-98. DON'T KNOW
-99. REFUSED
The Cadmus Group, lnc. i Energy Services Appendix AS5
Rocky Mountain Power
Exhibit No. 5 Page 757 of '1365
Case No. PAC-E-'14-07
Rocky Mountain Power ldaho HE$ Evaluation 2009-2010 Final Report Pgts?'fr#$T,"2U?T
M7. The retail cost of a comparable LED bulb for use in a traditional light socket is approximately $20
per bulb. lf LEDs cost twice as much per bulb or S40, do you think you would have purchased
more, fewer or the same number of LEDs?
L. More
2. Fewer
3. Same number
-98. DON'T KNOW
-99. REFUSED
M8. [lF M7 = 1 OR 2l How many LEDs would you have purchased if each bulb had cost twice as much
per bulb?
1. IRECORD NUMBER]
2. NONE
-98. DON'T KNOW
.99. REFUSED
M9. lf LEDs cost half as much per bulb (or S10), do you think you would have purchased more, fewer or
the same number of LEDs?
1. More
2. Fewer
3. Same number
-98. DON'T KNOW
.99. REFUSED
M10. [!F M9 = 1 OR 2] How many would you have purchased if each bulb had cost half as much?
1. [RECORD NUMBER]
2. NONE
.98. DON'T KNOW
.99. REFUSED
M11. lf LEDs cost one quarter as much per bulb (or S5), do you think you would have purchased more,
fewer or the same number of LEDs?
1. More
2. Fewer
3. Same number
-98. DON'T KNOW
-99. REFUSED
M12. [F M11 = 1 OR 2] How many would you have purchased if each bulb had cost one quarter as
much?
t. IRECORD NUMBERI
2. NONE
-98. DON'T KNOW
.99. REFUSED
The Cadmus Group, lnc. i Hnergy $ervices Appendix AS6
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Po /er
Exhibit No. 5 Page 758 of 1 365
Case No. PAC-E-14-07
#BffifyT,"2UT?
Demographics
I have just a few more questions about your household. Again, all your answers will be strictly
confidential.
D1. Which of the following best describes your house? [READ LISTI:
Single-family home
Townhouse or duplex
Mobile home or trailer
Apartment building with 4 or more units
Other [RECORD]
[DO NOT READ] DON',T KNOW
IDO NOT READI REFUSED
D2.Do you rent or own your home?
1. Own2. Rent
3. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
About when was this building first built? IREAD LIST lF NEEDEDI
1. Before !970's
2. 7970',s
3. 1980',s4. 1990-945. 1995-99
5. 2000's
7. OTHER IRECORD]
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
Approximately how many square feet is your home? [READ tlST lF NEEDED]
1. Under 1,000 square feet
2. 1,000 - 1,500 square feet
3. 1,501- 2,000 square feet4. 2,00t- 2,500 square feet
5. Over 2,500 square feet
-98. [DO NOT READI DON',T KNOW
-99. IDO NOT READI REFUSED
7.
2.
3.
4.
5.
-98.
-99.
D3.
D4.
The Cadmus Group, lnc. i Energy $ervices Appendix 467
Roclry Mountain Power
Exhibit No. 5 Page 759 of 1 365
Case No. PAC-E-14-07
Cgts?'fi5iiiT,"2UT?Rocky klountain Power ldaho HES Evaluation 2009-2010 Final Report
D5. What is the primary heating source for your home? [READ tlST lF NEEDED]
1. Forced air natural gas furnace
2. Forced air propane furnace
3. Air Source Heat PumP
4. Ground Source Heat PumP
5. Electric baseboard heat
6. Gas fired boiler/radiant heat
7. Oil fired boiler/radiant heat
8. Passive Solar
9. Pellet stove
10. Wood stove
11. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
D5. [lF D5 = 1-11] How old is the primary heating system? [RECORD RESPONSE lN YEARS]
7. [RECORD 1-100]
-98. DON'T KNOW
-99. REFUSED
D7. What type of air conditioning system, if any, do you use in your home? [INDICATE Att THAT
APPTYI
1. CentralAirConditioner
2. Room Air Conditioner
3. Evaporative Cooler
4. Air Source Heat Pump
5. Ground Source Heat PumP
6. Whole house fan
7. No cooling system before
8. Other [SPECIFY]
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
D8. [SKIP lF D7 = 7] How many years old is your primary cooling system? [RECORD RESPONSE !N
YEARSI
1. IRECORD]
-98. DON'T KNOW
-99. REFUSED
The Cadnru$ Group, lnc. / Energy Services Appendix 468
Rocky Mountain Power
Exhibit No. 5 Page 760 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report #ts?'fjffiTH,t2UTT
D9. What is the fuel used by your primary water heater?
L. Electric
2. NaturalGas
3. Fuel oil
4. other [RECORD]
-98. DON'T KNOW
-99. REFUSED
D10. How old is the primary water heater? IRECORD RESPONSE lN YEARS]
1.. [RECORD 1-100]
.98. DON'T KNOW
-99. REFUSED
Dll.lncluding yourself and any children, how many people currently live in your home?
7. IRECORDI
-98. DON'T KNOW
-99. REFUSED
D12. [lF Dll > U Are any of the people living in your home dependent children under the age of 18?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
D13. Can you please tell me in what year you were born?
1. IRECORD]
-98. DON'T KNOW
-99. REFUSED
D74. ln 2010, was your pre-tax household income above or below 550,000?
1. Below 550,0002. Above 550,0003. Exactly 550,000
.98. DON'T KNOW
-99. REFUSED
llF D14 = -98 OR -99 SKIP TO tU
The Cadrnu$ Group, lnc. i Energy Services Appendix 469
Rocky &flountain Power ldaho l-lES Evaluation 2009*2010 Final Report
Rocky Mountain Power
Exhibit No.5 Page 761 of 1365
Case No. PAC-E-14-07
CBts?'i{iiiT,"2UTT
D15. [ASK IF D14=1] Which of the following categories best represents your household income in
2O7O? Please stop me when I read your category:
7. Under S10,0002. S1o,oo0 to under S2o,ooo3. $2o,oooto under S3o,ooo4. Sgo,ooo to under 540,0005. S4o,ooo to under S5o,oo0
-98. DON'T KNOW
-99. REFUSED
D15. [ASK lF Dt4=27 Which of the following categories best represents your household income in
2O1O? Please stop me when I read your category:
1. 550,000 to under 560,0002. 560,000 to under 575,0003. S75,ooo to under 5100,0004. S100,000 to under S150,0005. S15o,ooo to under 5200,0006. S2oo,ooo or more
-98. DON'T KNOW
-99. REFUSED
Conclusion
11. How satisfied are you with the service that INSERT UTILITY] provides overall? Would you say you
are... [READI
1. Very Satisfied
2. Somewhat Satisfied
3. Not Very Satisfied
4. Not At All Satisfied
-98. IDO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
L2. IASK !F E4.1 > 0] Did [UTlLlTYl's discount program cause your satisfaction with [UTtLlTYl to...
1,. lncrease
2. Stay the same
2. Decrease
-98. [DO NOT READ]
-99. IDO NOT READ]
DON'T KNOW
REFUSED
13. Do you have any additional feedback or comments?
7. Yes [RECORD VERBATUM]
2. No
-98. DON'T KNOW
-99. REFUSED
The Cadrnus Grcup, lnc. i Energy Services Appendix A70
=,n, o,,,l"TPr$T lFi:i?ffJ
Case No. PAC-E-14-07
Rocky hflountain Power ldaho HES Evaluation 2009*2010 Final Report #g?'i'{ilT,t2UT?
L4. Sex [INTERVIEWER: DO NOT READ]
1. Female
2. Male
-98. DON'T KNOW
That concludes the survey. Thank you very much for your time and feedback.
The Cadrnus Group, lnc. I Energy Services Appendix A71
Rocky Mountain Power
Exhibit No. 5 Page 763 of 1365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho l-lES Evaluation 2009-2010 Final Report CgB?"frffiT,tZHT?
6. Out-of-Territory Lighting Suruey (Leakage)
IKEY FOR TNTRODUCilONI
Washington California : Pacific Power
Utah ldaho: Rocky Mountain Power
Introduction
[TO RESPONDENT]: Hello, my name is [INSERT FIRST NAME] and I am calling from Discovery Research
on behalf of [PACIFtC POWER/ROCKY MOUNTAIN POWER]. We are exploring issues related to
household lighting. l'm not selling anything. I just want to ask you questions about some of the ways
you use lighting in your home.
RESPONSES TO CUSTOMER QUESTIONS [IF NEEDED]
(TlMlNG: "THIS SURVEY SHOULD TAKE ONLY 5 MINUTES OF YOUR TIME. lS THIS A GOOD TIME FOR US
TO SPEAK WITH YOU? IF NOT, SET UP CALL BACK APPOINTMENT OR OFFER TO LET THEM CALL US
BACK.")
(WHY ARE YOU CONDUCTING THIS STUDY: "Studies like this help electricity providers better
understand customers' need and interest in energy programs and services.")
51. Could I speak with the person who usually purchases the light bulbs for your household?
7. Yes
2. No, not available [schedule callback]
3. No, no such person/refused [Thank and terminate]
52. Who provides your electricity service? IPROBE tF DON'T KNOW]
7. Pacific Power/Rocky Mountain Power [TERMINATE]
2. Other [RECORD]
-98. DON',T KNOW [TERMINATE]
-99. REFUSED [TEMINATE]
Awareness
A1. l'd like to ask you a few questions about your awareness of different types of light bulbs. Before
this call, had you ever heard of compact fluorescent bulbs, or CFLs?
7. Yes
2. No
The Cadmu$ Group, lnc. / Energy Services Appendix 472
Rocky Mountain Power ldaho HES Evaluation 200$-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 764 ot 1 365
Case No. PAC-E-14-07
CBts?'fif$T,"2UT?
llF A1 = I SKIP TO P1l
A2. Compact fluorescent light bulbs - also known as CFLs - usually do not look like regular
incandescent bulbs. The most common type of compact fluorescent bulb is made with a glass tube
bent into a spiral, resembling a soft-serve ice cream cone, and it fits in a regular light bulb socket.
Before today, were you familiar with CFLs?
L. Yes
2. No [TERMINATEI
Purchases
P1. ln the last two calendar years (2009 & 2010) have you, or has anyone else in your household,
purchased any compact fluorescent light bulbs or CFLs to use in a home?
1. Yes, I have
2. Yes, someone else in my household has
3. No [Terminate]
-98. DON'T KNOW [Terminatel
-99. REFUSED [Terminatel
llF PI=Z,- 98 or- 99 Thank and Terminatel
P1a. May I please speak with that person?
L. Yes [REINTRODUCE and go to AU
2. No [TERMINATE]
P2. IASK lF P1=1] Would you please estimate the number of compact fluorescent light bulbs or CFLs
that have been purchased by you or members of your household in the previous two calendar
years; that is, the number of individual CFLs, not the number of pockages of CFLs that you
purchased in 2009 and 2010. [!F "DON'T KNOW," PROBE: "ls it Iess than or more than five
bulbs?" WORK FROM THERE TO GET AN ESTIMATEI
[NUMERIC OPEN END: RECORD NUMBER OF CFLS, NOTA RANGE.]
1. [PROBE FOR A NUMBER, RECORD]
2. NONE ITERMTNATE]
-98. DON',T KNOW [TERMTNATE]
-99. REFUSED [TERMTNATEI
Purchase Locations and Bulb Characteristics
IASK PTl THROUGH Pr7 ONrY !F P2>01
The Cadrnus Group, tnc. / Energy $ervices Appendix A73
Rocky Mountain Power
Exhibit No. 5 Page 765 of 1 365
Case No. PAC-E-14-07
Rocky fiilountain Power ldaho HES Evaluation 2009*201S Final Report #8?'fr#$T,"2U?T
PL1. For the CFLs that you purchased in 2009 and 2010, do you know the names and locations of the
stores from which you purchased CFLs and the approximate dates?
1. Yes
2. No
PL2. [F PLl = 1] For each CFL purchase you made in 2009 and 2010, can you please tell me the name of
the store or stores from which you purchased CFLs, where are they located [CITY/TOWN], the
number of bulbs that you bought there [NUMBER OF BULBSI, and the approximate date when you
made those purchases [MONTH AND YEAR]?
1. Name Store 1[RECORDI
2. Location Store 1 IRECORD]3. Date Store 1 [RECORD]4. Name Store 2 [RECORD]5. Location Store 2 [RECORD]6. Date Store 2 [RECORDI7. Name Store 3 [RECORD]8. Location Store 3 [RECORDI9. Date Store 3 [RECORD]
10. Name Store 4 [RECORDI
11. Location Store 4 [RECORDI
12. Date Store 4 [RECORD]
PL3. [lF Pt1=21 For the CFLs that you purchased in 2009 and 2010, were any of the bulbs purchased at
the following stores and if so, how many [READ LIST]?
1. [SrOREll2. [STORE2I3. [STORE3]4. [Do NoT READ] No
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
[!F PL3 = 4,98 or 99 TERMINATE]
PL4. Of the bulbs you purchased in 2009 and 2010, how many would you estimate were specialty or
designer styles such as reflector bulbs, candelabra bulbs, dimmable or three-way bulbs?
1. [RECORDI2, NONE
-98. DON'T KNOW
-99. REFUSED
PLs. Did you receive an incentive or rebate from an Electric/Utility Company for any of the bulbs you
purchased?
1. Yes
2. No
The Cadrnus Group, [nc. i Hnergy Services Appendix 474
Rocky Mountain Poiver
Exhibit No. 5 Page 766 of 1 365
Case No. PAC-E-1447
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report CEts?tffT,"ZUTI
[F PL5 = 2, -98 OR -99 SKIP TO Dl]
PL6. What is the name of the utility company that provided the incentive or rebate for your purchase?
IRECORD MUTTTPTE rF NECESSARYI
t. Company l record
2. Company 2 record
3. Company 3 record
4. Company 4 record
-98. DON'T KNOW
-99. REFUSED
PL7. IREPEAT Pt7 FOR EACH ANSWER IN PLGI How many of the [INSERT # OF BUTBS PURCHASED FROM
P2l CFLS you purchased were rebated by [INSERT UTILITY FROM Pt6l?
1. [RECORD]2, NONE
-98. DON'T KNOW
Demographics
I have just a few more questions about your household. Again, all your answers will be strictly
confidential.
D1. Which of the following best describes your house...[READ LIST]:
1.. Single-family home
2. Townhouse or duplex
3. Mobile home or trailer
4. Apartment building with 4 or more units
5. Other [RECORD]
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
D2. Do you rent or own your home?
1. Own
2. Rent
3. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
D3. lncluding yourself and any children, how many people currently live in your home?
1. [RECORD]
-98. DON'T KNOW
-99. REFUSED
The Cadrnu$ Group, lnc. / Energy Services Appendix A75
Rocky Mountain Power
Exhibit No. 5 Page 767 of 1 365
Case No. PAC-E-14-07
#ts?tffT,'2UT?Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
D4. Can you please tell me in what year you were born?
t. [RECORDI
-98. DON'T KNOW
-99. REFUSED
D5. ln 2010, was your pre-tax household income above or below 550,000?
1. Below 550,0002. Above 550,000
3. Exactly S50,ooo
-98. DON'T KNOW
-99. REFUSED
[F D5 = -98 OR -99 SKIP TO Cll
D5. IASK lF D5=1] Which of the following categories best represents your household income in 2010?
Please stop me when I read your category:
7. Under S10,000
2. 510,000 to under 520,0003. 520,000 to under 530,0004. 530,000 to under 540,0005. 540,000 to under 550,000
-98. DON'T KNOW
-99. REFUSED
D7. [ASK !F D5=2] Which of the following categories best represents your household income in 2010?
Please stop me when I read your category:
L. 550,000 to under 560,0002. Soo,ooo to under S75,ooo3. 575,000 to under $100,0004. S1o0,0ooto under S150,ooo5. S150,000 to under 5200,0006. 5200,000 or more
-98. DON'T KNOW
-99. REFUSED
Conclusion
C1. Do you have any questions or comments for me?
1. Yes IRECORD VERBATUM]
2. No
-98. DON'T KNOW
-99. REFUSED
That concludes the survey. Thank you very much for your time and feedback.
The Cadmus Group, Inc. / Energy Services Appendix A7S
Rocky [rlountain Power ldaho HE$ Evaluation 2009*2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 768 of'1365
Case No. PAC-E-14-07
#ts?'fr{fiiT,"2UTT
Appendix B. Precision Calculations
To determine the level of uncertainty for results, Cadmus considered the effect of sampling error
on all estimates presented in the report. Sampling error refers to the uncertainty that is introduced
by the use of sampled data to infer characteristics of the overall population. These data include
survey results, meter data, and those from secondary sources. Cadmus used sampled data to
estimate parameters for per-unit savings calculations (such as installation rates) or in the
consumption of specific equipment types (such as in billing analysis).
Sampling error is reflected in confidence intervals about the estimates. Unless otherwise noted,
Cadmus estimated intervals at 90 percent confidence; meaning one can be 90 percent confident
the true population value lies within the given interval. Cadmus calculated confidence intervals
for means, proportion, regression estimates, and any calculated values using sample estimates as
an input. Cadmus calculated all confidence intervals using standard formulae to estimate
uncertainty for proportions and means. Mean values used the following formula:
Conf idence Interualmean = mean * L.645 *
Where s2 is equal to the sample variance, and 1.645 is the z-score for a 90 percent confidence
interval.
In some cases, uncertainty of estimates came from several sources. For example, in cases of
summed estimates, such as those for total program savings, the root of the sum of the squared
standard errors was calculated to estimate the confidence interval:l
Conf idence Interval*+y = (X + Y) * L.645 *
In some cases, Cadmus multiplied estimates. For instance, net savings calculations involved
combining gross estimates with an in-service rate and/or NTG ratio estimated from participant
surveys. For these results, Cadmus calculated combined standard errors for the final estimates. In
cases where the relationship was multiplicative, Cadmus used the following formula:2
Confi.d.ence Interval**y = X * Y + L.645..J \r;)*''\*).\;)(;)
' This approach to aggregation errors follow the methods outlined in Appendix D from Schiller, Steven et. al.
"National Action Plan for Energy Efficiency". Model Energy Efficiency Program Impact Evaluation Guide.
2007. x'rvw.eua. govieeactionplan.
2 Derived from Goodman, Leo, "The Variance of the Product of K Random Variables," Journal of the American
Statistical Association. 1962.
s2
n
The Cadmus Group, [nc. / Energy Services Appendix B1
Rocky klountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 769 of 1365
Case No. PAC-E-14-07
Cgts?'frf{T,'2UT?
In some cases, a ratio of two estimates was needed, for example, in estimating the spillover ratio,
which was expressed as the ratio of spillover savings to program savings. For this calculation,
Cadmus used the following formula:3
xx
Confidence Intervalx /y = V + L.6aS x V
To ensure transparency of the error aggregation process, Cadmus reported precision for both
individual and combined estimates, where relevant.
3 Stuurt, A. and Ord, J. Kendall's Advanced Theory of Statistics (6th Edition). Edward Amold. 1998.
(#) (#)
v2 aT
The Cadnrus Group, lnc. I Energy Services Appendix B?
Roclry Mountain Power
Exhibit No. 5 Page 770 of 1 365
Case No. PAC-E-'I4-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report Cgts?'i'ffiH,"2UTI
Appendix G. Hours of Use Methodology
Cadmus estimated CFL hours of use (HOU) using a multistate modeling approach, built on light
logger data collected from four states: Missouri, Michigan, Ohio, and Maryland. Cadmus chose
these data rather than those from the most recent California evaluation for the following reasons:
l. These states are more comparable to Idaho in terms of latitude (a factor in seasonal
variation in daylight hours).
2. These states all have relatively new CFL programs (unlike California, where programs
have been in place for a number of years).
3. These states have a more comparable distribution of urban versus rural population (as
shown in Figure C1).
Figure Cl. Urban vs. Rural Comparison Between States
HOU Sample
Average
Source: 2000 US Census
Metering Protocol
Following whole-house lighting audits, Cadmus installed up to five loggers in each participant
home. Metering periods varied by utility, ranging from three months to one year. For homes
where five or fewer CFL fixture groups had been identified, Cadmus field staff installed light
loggers on every CFL fixture. For homes with more than five CFL fixture groups, field staff
randomly selected which five fixtures to meter. This method relied on a systematic sampling that
involved installing a logger on every nft CFL fixture (the nth number also based on the number of
total possible CFL fixtures, and randomly generated).
During the logger removal process, field staff collected additional data for evaluating data
quality and for determining if loggers had failed, had been tampered with, or had been removed.
The Cadnrus Group, lnc. i Energy Services Appendix C1
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 771 of 1365
Case No. PAC-E-14-07
#ts?'fr#5,"2UT?
Moreover, prior to removing each logger, field staff noted whether the logger was correctly
installed, and where its sensor was oriented.
Model Specification
To estimate HOU, Cadmus determined the total 'oon" time for each individual light logger per
day, using the following guidelines:
. If a light logger did not record any light for an entire day, the day's HOU was set to zero.
o If a light logger registered a light turned on at 8:30 p.m. on Monday, and tumed off at
1:30 a.m. on Tuesday morning, 3.5 hours were added to Monday's HOU and 1.5 hours to
Tuesday's HOU.
Cadmus then modeled weekday and weekend daily HOU as a function of room type, the
presence of children in the home, and CFL saturations in the home. This used two analysis of
covariance (ANCOVA) models, one for each day type.
ANCOVA models are regression models where a continuous variable is modeled as a function of
a single continuous explanatory variable (in this case, CFL saturation) and a set of binary
variables. This way, an ANCOVA model simply serves as an analysis of variance (ANOVA)
model with a continuous explanatory variable added. Cadmus chose this specification because of
its simplicity, making it suitable to a wide variety of contexts. Though the model lacked the
specificity of other methods, its estimates were not nearly as sensitive to small differences in
explanatory variables, compared to more complex methods. Therefore, these models could
produce consistent estimates of the average daily HOU for a given region using its specific
distribution of bulbs by room and household type, and by the existing CFL saturation.
Cadmus specified the final models as cross-sectional, ANCOVA regressions for day-type' (i),
and bulb (i), as:
Average
'o"'-';o'l'Brrru Saturattoni + p2Kidsi * BrKttcheni * BrBasementi
* Ss)utdoori * B5Bedroomi + BrBathroomi * pr)theri
Where:
. CFL Saturation: the proportion of bulbs in the home that are CFLs;
. Kids: a dummy variable2 equal to one if the household has children under 18 living in
the home ard zero otherwise;
. Kitchen: a dummy variable equal to one if the bulb is in the kitchen and zero otherwise;
. Basement : a dummy variable equal to one if the bulb is in the basement and zero
otherwise;
I The two day-types for this analysis were weekend and weekday. We defined weekend as Saturday and Sunday, as
well as the following federal recognized holidays: Christmas, Thanksgiving, Labor Day, Memorial Day, New
Year's Day, Fourth of July, Presidents' Day, and Veterans' Day.
' Dummy variables are binary, which take only values of either zero or one. Coeffrcients for these variables can be
interpreted as the difference in mean values between the two mutually exclusive groups.
The Cadmus Group, lnc. i Energy Services Appendix C2
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 772 of'1365
Case No. PAC-E-14-07
PgB?iffiT,"2UT?
. Outdoor: a dummy variable equal to one if the bulb is in the outdoor and zero otherwise;
. Bedroom : a dummy variable equal to one if the bulb is in the bedroom and zero
otherwise;
. Bathroom : a dummy variable equal to one if the bulb is in the bathroom and zero
otherwise; and
. Other = a dummy variable equals to one if the bulb is in a low-use room (such as a utility
room, laundry room, or closet) and zero otherwise.
Cadmus tested the potential influences of other demographic and regional variables in the model
specification, such as latitude, income, education, home characteristics. However, these variables
were not included as their estimated coefficients did not differ significantly from zero, or
produced signs inconsistent with expectations.
Final Estimates and Extrapolation
As shown in Table Cl, not all estimated coefficients of the two models differed significantly
from zero for both day types, most likely due to differences in schedules between days.
Nevertheless, the same independent variables were included in each model for better cross-
comparability.
Table Cl. HOU Model ANCOVA Estimates
lntercept4 2.58 <.0001 2.90 <,0001
CFL Saturation 1.05 0.0359 -0,32 0.6657
Kids 0.80 <.0001 0.51 0.1 135
Kitchen 1.18 0.0001 0.35 0.4049
Basement -0.25 0.5489 -1.50 0.0134
Outdoor 2.80 <,0001 1,46 0.1347
Bedroom 1.10 <.0001 -2.02 <.0001
Bathroom -0.98 0.0019 -1.54 0.0025
Other -1.30 0.0071 -2.16 0.0008
Cadmus used these model parameters to predict average daily use for HES by taking the sum of
the product of each coefficient shown in Table Cl and its corresponding average independent
variable. Table C2 shows independent variables used for HES. Except for CFL saturation,
3 P-values indicate the degree of confidence to which analysis asserts the given coefficient equals zero. In other
words, it is the probability the effect of a given variable on HOU is random. Therefore, a lower p-value
indicates a higher degree of confidence in the estimated effect.
a The models' intercept can be interpreted as the average HOU in the main living space (defined as the dining room,
hallways, living rooms, and office/den areas) when existing CFL saturations are zero and no children live in the
home.
The Cadrnus Group, lnc. I Energy Services Appendix C3
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 773 of 1365
Case No. PAC-E-14-07
#Sffi5fiiT,"zUTU
Cadmus estimated independent variables using 2009-2010 participant survey data. Cadmus used
CFL saturation from Rocky Mountain Power's most recent potential study.5
Table C2. Weekday HOU Estimation Input Values
Using these values, the following equation calculateda2.45 average weekday HOU:
Auerage DailyH,ur+
(-1,0s * 0,20 + 0.8 * 0.40 + 1.18 xo.r4+ [-0.25] x 0.08 +z.B
* 0.04 + [-1.1] x 0.22+ [-0.98] * 0.74+ [-1.3] * 0.07) = 2.47
Using the same method, Cadmus calculated weekend HOU using parameter estimates from the
weekend model. The weighted average of these two values then provided the average annual
HOU:
Precision calculations for model estimates accounted for sampling errors in model estimates and
sample inputs, which largely arose from participant surveys. (Precision of individual HOU
estimates can be impacted by the precision of logger data model estimates and the accuracy of
model inputs used for extrapolation.) Cadmus estimated the final relative precision for CFL
HOU in the HES program to be +3.9 percent with 90 percent confidence.
5http:ilitt:rvrr.pacificorrr.qgi:ticontentlslg:i:ipirgiitg$rB:.s}:glF*nerg.v- Sources,iDeuran
-e-.1 l,-20-U -$udy"pdf
Table C3. HOU by Day Type
The Cadrnus Group, lnc. i Energy Services Appendix C4
Rocky tulountain Power ldaho HE$ Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 774 of 1365
Case No. PAC-E-14-07
dg$?'fiSFilT,'2BTT
Appendix D. Lighting Net Savings Approach
(Retailer Surveys)
Cadmus estimated NTG for HES program lamps using responses from in-depth participating
retailer interviews. Cadmus interviewed 23 rctailers across various distribution channels, and
obtained responses about HES Program lighting components from six of these retailers, with four
retailers providing useable responses for the NTG battery. Table D1 presents participating
retailers and numbers of program lamps each sold.
Table Dl. Retailers in Sample and Program Lamp Sales
Retailer 1 7 17,602 34,85%
Retailer 2 2 2,723 5.39%
Retailer 3 4 1,190 2.360/0
Retailer 4 1 138 0.270h
Retailer 5 1 't,091 2.160/o
Retailer 6 3 5,078 10.05%
Retailer 7 2 1,413 2.800/o
Retailer 8 1 12,170 24.09o/o
Retailer 9 1 9,109 18.03%
Total 22 50,514 100%
As shown in Table
questions accounted
program.
D2, the four lighting retailers who adequately responded to the NTG
for approximately 8 percent of total program lamps sold through the HES
Table D2.Interviewed Retailer Locations and Program Lamp Sales
During these interviews, Cadmus asked store representatives a standard battery of questions to
inform NTG estimation of HES program lamps. Specifically, Cadmus asked a series of questions
designed to estimate the percentage of all CFLs retailers would have sold in the program's
absence as well as the percentage of CFL sales they sold through the HES lighting progrtlm
during 2009 and 2010. These surveys also accounted for freeridership and spillover, using
t Retailer names are disguised for confidentiality purposes. The retailer number associated with each retailer/retailer
location does not correspond to other numbered retailers in subsequent tables.
The Cadmus Group, lnc. / Energy Services Appendix D1
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No, 5 Page 775 of 1 365
Case No. PAC-E-14-07
Wtness: Kathrun C. HvmasFebfuary 3, 2012
questions about lift in total CFL sales due to the program (e.g., CFL sales attributable to the
program, including non-progrErm CFLs). Appendix A includes the retailer interview guide.
The program NTG battery of questions included:
l. "If the HES incentives were not ovailable during 2009 and 2010, do you thinkyour sales
of standard ENERGY STAR CFL bulbs would have been about the same, lower, or
higher?
2. "By what percent would your [store'sJ sales of standard ENERGY STAR CFLs have been
fiower/higherJ without the Home Energt Savings program? "
3. "During 2009 & 2010, what percent of your [store'sJ total CFL sales would you estimate
are CFLs purchased through the HES Lighting Program?"
By assessing retailers' responses to the above questions, Cadmus estimated NTG as follows:
1. As responses to questions 2 and 3 fell in ranges, Cadmus used the midpoint of each range
for the following calculations.
2. Cadmus obtained progftrm lamp sales data by store from the program tacking database.
This provided an estimate of the number of program CFLs sold by each retailer.
3. Cadmus estimated total CFL sales by retailer using the following equation:
Total CFL Sales =
Number of CFLs SoldThroughthe Program
o/o Program CFLs sold over past two years (Q #3)
4. Cadmus estimated sales in program's absence by retailer using the following equation:
Sales without Program
- Total CFL Sales x (1 - o/o Lower Sales w /out program(Q #2))
5. Next, Cadmus estimated lift, or CFL sales attributable to the program by each retailer,
using the following equation:
Lift - Total CFL Sales - Sales wfout Program
6. Finally, Cadmus estimated NTG by retailer using the following equation:
NTG _Lift in CFL Sales f or Each Retai.ler
C F Ls S old T hr oug h the Pr o gr am (T r acking D at ab as e)
To ensure the accuracy and reliability of retailer responses to questions I and 2, survey
administrators repeated responses to these questions back to each retailer in the following
manner:
The Cadmus Group, lnc. i Energy Services Appendix D2
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclq Mountain Power
Exhibit No. 5 Page 776 of 1 365
Case No. PAC-E-1447
Wtness: Kethrvn C. HvmasFebruary 3, 2012
uJust to confirm, your sales of standard ENERGY STAR CFLs would have been [insert %
from D7J fiower/higherJ in 2009 and 2010 f the [Pacifrc Power/Rocky Mountain
PowerJ program was not available? "
Of six retailers that reported participating in the HES Program's lighting component, four
provided useable responses to the NTG questions. Cadmus excluded the remaining retailers from
the NTG analysis due to insufficient responses, such as "don't lvtow" or when they refused to
answer. Such non-response bias commonly occurs with retailer interviews. These refusals
prevented Cadmus from achieving the desired number of completed interviews, as described in
the sample plan, and may have contributed to uncertainty and bias around the NTG estimates.
Cadmus also weighted individual NTG ratios by the distribution of program lamps sold by each
of the four retailers providing useable responses to the NTG survey questions. For example,
Cadmus weighted the results from True Value by the percentage of HES program lamps they
sold. This weighting approach ensured the final NTG estimation reflected the distribution of
program CFLs, given Cadmus weighted high-volume retailers more heavily in the final NTG
calculation.
To calculate the weight for each store, Cadmus first calculated the percentage of each stores'
program lamp sales, out of 50,514 lamps sold by all retailers, then divided the quotient by the
sum percent of all four stores' lamp sales. As shown in Table D3, these four retailers accounted
for 8 percent of all HES program lamp sales among Idaho retailers.
Table D3. Interviewed Retailer Location Program Lamp Sales and Weights
As shown in Table D4, the calculations resulted in a 1.47 store-weighted NTG.
Table D4. Responses to NTG Questions and Weighted NTG Estimate
The Cadmus Group, lnc. i Energy Services Appendix D3
Rocky Mountain Fower ldaho HES Evaiuation ?009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 777 ol 1365
Case No. PAC-E-14-07
#ts?t5Fii5,"2UT?
Cadmus believes potential bias sources contributed to uncertainty around the 1.47 store-weighted
NTG estimate.
Generally, Cadmus interviewed a small sample of market actors, with responses resulting in a
wide range of NTG estimates. Additionally, responses from this small sample size may not
sufficiently represent all retail stores with the same name, or all stores within each retail
distribution channel. Other potential bias sources creating uncertainty around the store-weighted
NTG estimate included:
o Program lamp sales for the six retailers contributing to NTG represented only 8 percent
of total lamps sold through the HES program (50,514).
o Non-response bias: some retailers could not provide estimates of program lamp sales or
estimate how sales would have been impacted without the HES incentives.
Therefore, at the 90 percent confidence level, Cadmus estimated uncertainty around the
1.47 NTG estimate at approximately + l.T6,representing a relative precision of + 119 percent
(see Table D5 for these statistics).
Table D5. Confidence Interval Estimation and Summary Statistics
The Cadmus Group, lnc. / Energy Services Appendix D4
Rocky Mountain Power ldaho HES Evaluation 2009{010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 778 of 1 365
Case No. PAC-E-14-07
#ts?t5ffiT,"2UT?
Appendix E. Lighting Net-to-Gross Secondary
Data Review
California
The 2006-2008 Upstream Lighting Program (implemented by PG&E, SCE, and SDG&E)
provided manufacturer and distributor buy-downs or retailer instant discounts for eligible
lighting products, which were sold through participating retailers. Kema and Cadmus evaluated
the program in 2010.
Cadmus derived the final recommended net-to-gross Q.{TG) ratio estimates from supplier
interviews and revealed-preference intercept surveys. Cadmus based the supply-side, self-
reported NTG method on information collected during in-depth interviews and through surveys
with manufacturers, retail buyers, and retail store managers. Cadmus analyzed the results to
determine the NTG ratio by channel for basic CFLs, specialty CFLs, and energy-efficient
fixtures. The final NTG recommendations are: 0.49 for PG&E; 0.64 for SCE; and 0.48 for
SDG&E.
Colorado
The Colorado Home Lighting Program, first implemented in 2006, sought to provide energy
savings for Xcel Energy's DSM residential progftlm portfolio. The program's NTG ratios
derived from four different data collection sources:
1. Self-report, end-use customer telephone surveys;
2. Supply-side interviews;
3. A multistate regression model using on-site audit results; and
4. Benchmarking of other utilities around the country.
Cadmus incorporated questions in an end-use customer telephone survey to determine
freeridership and spillover levels. Cadmus also established NTG calculations for the retail
channel, based on retail store manager interviews. Cadmus based the third method of calculating
the NTG ratio-the multistate regression model---on data from 16 different geographic regions
in the U.S., and incorporated data from telephone surveys of over 9,300 households and on-site
saturation surveys from approximately 1,400 households. Finally, Cadmus gathered NTG values
from secondary data on other lighting programs across the country. Cadmus and Nexus
recommended an overall NTG ratio of 1.0, based on the range of values Cadmus established
through the four calculation methods.
lllinois
Through the Lighting and Appliance Program, launched in August 2008, Ameren Illinois
encourages its customers to purchase high-efficiency lighting products (such as CFLs) and
ENERGY STAR-rated dehumidifiers, ceiling fans, and room air conditioners. For the program's
lighting portion, Ameren provides upstream buy-downs to CFL manufacturers, and markets the
program through participating retail stores and an online store selling discounted CFLs. The
program discounts several types of lights, with an average incentive of $1.04 for each standard
The Cadmus Group, [nc. I Energy Services Appendix E1
Roclry Mountain Power
Exhibit No. 5 Page 779 of I 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report CgE?'fi#T,t2UT?
CFL, and $1.86 for each specialty bulb. In 2011, Cadmus evaluated Program Year 2
(2009 -20 I 0) operations.
Maine
Implemented from 2003 to 2006, the Efficiency Maine Residential Lighting Program sought to
transform the lighting market towards energy efficiency, rather than achieve specific levels of
energy savings or sales volumes. Nexus evaluated the program in2007.
Nexus determined spillover and freeridership using results from three different telephone surveys
conducted with Maine residents, including:
1. Surveys with participants purchasing a lighting product through the coupon program after
November 2005;
2. Surveys with participants purchasing a bulb through the coupon program prior to
November 2005; and
3. Surveys with the general customer population.
The study determined freeridership using:
o Respondents' awareness of efficient lighting products prior to their purchases through the
program;
o Their intent to purchase the product (either at the same time or within three months of the
program purchase); and
. Their willingness to pay the average retail price for products they purchased.
In a final analysis, Nexus recommendeda0.94 NTG ratio.
Massachusetts
The Massachusetts ENERGY STAR Lighting Program incented its residential customers to use
ENERGY STAR-qualified lighting. Nexus evaluated the 2010 and early 2011 program in its
2010 Annual Report.
A panel of experts determined the most accurate NTG ratios Nexus developed for the program.
Methodologies Nexus used to calculate the NTG ratios the panel assessed included:
1. Willingness-to-pay assessments;
2. Supplier self-reports;
3. Active purchaser revealed preferences;
4. A multistate regression model; and
5. A conjoint/pricing elasticity analysis (for specialty bulbs only).
In the final analysis, Nexus recommended a0.47 NTG value.
The Cadmus Group, lnc. / Hnergy Services Appendix E2
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 780 of 1365
Case No. PAC-E-14-07
Cgts?'i'ST,"2UTI
Missouri
A market transformation program, launched in 2009, the Ameren Missouri Lighting and
Appliance Program seeks to deliver energy savings through higher sales of residential, energy-
efficient ENERGY STAR products, including CFLs. The program discounts ENERGY STAR
CFLs and ENERGY STAR lighting fixtures, with an average incentive of $1.09 per bulb and
$15 per fixture. In 2011, Cadmus evaluated Program Year 2 (2009-2010) operations.
Cadmus determined the program's NTG ratio using a multistate fiued model to predict per-
household CFL purchases with the program. For the model, Cadmus used actual bulb purchases
per household the program supported from January through June 2010. To predict purchases
made through the program, Cadmus included assumptions in the model that the program had not
supported any bulbs during the first six months of 2010 (the without-progftrm scenario). The
analysis recommended a 0.96 NTG value.
New Mexico
The Southwestern Public Service (SPS) Company Home Lighting and Recycling Program
provides two ways for customers to purchase energy-saving CFLs:
1. Mail order, and
2. Instant rebates at retail stores.
SPS worked with retailers and manufacturers to buy-down bulb prices to roughly $1.00 each.
Implemented in 2009, Xcel Energy evaluated the program the same year.
Xcel Energy used information collected through surveys of program participants to develop
freeridership estimates. Those surveys questioned customers about their knowledge of energy
efficiency, their reasons for participating, and measure implementation decisions they would
have made in the program's absence. Xcel Energy's analysis recommended a 0.81 final NTG
value.
Pennsylvania
The PPL Electric Compact Fluorescent Lighting Campaign provides incentives to CFL
manufacturers, reducing retail prices of ENERGY STAR CFL bulbs. Cadmus' NTG analysis
addressed December 1,2010, through February 28,2011.
Cadmus based the NTG analysis on findings drawn from participant and nonparticipant
telephone surveys. Analysis incorporated all respondents purchasing one or more CFLs in the
three months prior to the survey, regardless of whether or not they knew of the CFL Campaign.
The freeridership estimates calculated from the customer surveys indicated NTG ratios from0.72
to 0.93. Cadmus chose a 0.85 value, estimated from the higher end of the range. Cadmus based
this estimation on assuming it unlikely all recent CFL purchasers unaware of the CFL campaign
before participating in the customer survey would have purchased the same quantity of CFLs
without the program incentive.
The Cadnrus Group, lnc. I Energy Services Appendix E3
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 781 of 1365
Case No. PAC-E-'14-07
#ts?'m5ffT,'2UT?
Utah and Washington
Rocky Mountain Power's residential lighting programs, within the 2006-2008 Utah Home
Energy Savings Program and the 2006-2008 Washington Home Energy Savings Program, offer
upstream incentives for manufacturers to reduce retail prices on CFL bulbs. Both programs were
implemented from 2006 to 2008, and were evaluated by Cadmus in 2010.
Cadmus determined freeridership and spillover results through participant and nonparticipant
phone surveys. Additionally, Cadmus used CFL retailer interviews to calculate CFL leakage, and
conducted a secondary data analysis to determine per-unit savings, based on deemed reported
savings, DEER, and RTF. Finally, Cadmus prepared a third data analysis to compare NTG
values across progftlms. Final NTG values recommended for the Utah Home Energy Savings
Program included: 0.84 for PY2006; 0.822 for PY2007; and 0.868 for PY2008.
Final NTG values recommended for the Washington Home Energy Savings Program included:
0.919 for PY2006;0.894 for PY2007; and 0.807 for PY2008.
Wisconsin
The Wisconsin Focus on Energy ENERGY STAR
launched in 2001. The program provides:
Program is a statewide program,
$2 instant and mail-in rebates for purchases of CFLs;
$15 instant and mail-in rebates for purchases of fixtures; and
$20 instant rebates for purchases oftorchieres.
In 2010, PA Consulting Group and NMR Group, Inc., established the program's most recent
NTG ratio.
NTG analysis included three steps:
1. Analysis of retailer-provided 2008 CFL sales data, and a review of secondary research
sales data and NTG values;
2. Analysis of the 2008 CFL reward database; and
3. Calculation of NTG estimates.
In 2010, PA ConsultingAlMR Group used a multistate modeling effort to establish a
0.62 program NTG value. In a 2010 memo, these evaluators stated the multistate modeling
method preferable, with advantages including :
o The ability to isolate program effects on CFL use and purchases;
o Use of a large sample size of households and a diversity of states; and
o Inclusion of nonprogram factors influencing CFL use.
Final NTG values used in analysis included: 0.75 for PY2007; 0.67 for PY2008; and 0.62 for
PY2010.
o
o
o
The Cadmus Group, lnc. I EnerEy Services Appendix E4
Rocky [\frountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 782 of 1365
Case No. PAC-E-I4-07
CBts?'frffi'T,'2UTT
Appendix F. Lighting NTc-Gustomer Willingness
to Pay
In August 2011, Cadmus conducted 250 in-territory lighting phone surveys a random digit dial
(RDD) process. This survey asked respondents a battery of questions to determine their
willingness to pay for CFLs in absence of HES program mark-downs as well as a baffery of
freeridership and spillover questions.
After determining how many CFLs participants purchased in2009 and 2010, the surveys asked
participants to indicate whether they would:
1. Generally purchase more CFLs, fewer CFLs, or the same number of CFLs at various un-
incentivized hypothetical price levels; and
2. The quantity of CFLs they would hypothetically purchase at various un-incented prices.
Specifically, Cadmus determined the average price of an un-incented standard twister CFL at
$2.55,r and then asked participants how many lamps they would purchase at the following
hypothetical prices: $18.00 per CFL, $12.00 per CFL, $6.00 per CFL, and $0.50 per CFL.
CFL demand was assumed to relate inversely to price, indicating participants would purchase
more CFLs at lower prices. Estimating participant willingness to pay for un-incented lamps
required estimating a demand curve for survey participants, which related hypothetical prices
and quantities. Figure Fl, below, illustrates the program lamp demand function, based on
responses from the in-territory lighting telephone survey. The Y-axis shows prices, and the
X-axis shows the quantity of lamps that would be purchased at each price. The figure also shows
an equation describing the relationship between price and quantity.
I Estimating the average price for an un-incentivized CFL first required reviewing CFL pricing data by participating
retailers, as provided by Rocky Mountain Power. Each store's average un-incented per-lamp price was then
determined for non-specialty twister-style CFLs. Finally, a weighted average of store prices and each stores'
distribution of program lamps were calculated. The same procedure followed for incented, non-specialty,
twister-style CFLs.
The Cadmus Group, lnc. i Energy Services Appendix F1
Rocky Mountain Power ldaho HES Evaluation 200$-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 783 of 1365
Case No. PAC-E-14-07
#S?"fr#fii.i,'zUT?
Figure Fl. Demand Schedule for Hypothetical Lamps
After plotting the data points shown in Figure Fl, Cadmus specified an exponential function to
relate these quantities with hypothetical prices, as represented by the following equation:
Equation Fl:
To estimate the number of lamps that would be purchased at the average program price per lamp
(net lamps), and the number of lamps that would be purchased without the program incentive
(freeridership), Cadmus solved Equation Fl for x; the quantity of lamps. This determined
3,855 CFLs would be purchased at the average incented price of $1.24, and 2,954lamps would
be purchased at the average un-incented price of $2.55. Figure F2 shows these modeled
quantities.
$20
$18
$16
$14
$12o.3 stoc$8
$s
$c
$z
lso
t
II
t..............-..........
Figure F2. Modeled CFL Quantities for NTG Estimation
$f,0
$18
$16
$14
$12{).3 $toL
$l
$6
$4
$2
$0
N =ModdedQ[rts
2,000 3,000 4000 5,000 6,800
Ouantity of CFLs
The Cadmus Group, [nc. / Energy $eruices .Appendix F2
Rocky Mountain Fower ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 784 of 1 365
Case No. PAC-E-14-07
#ts?t#liT."2UT?
The following equation estimated the NTG of HES progftrm lamps:
Equation F2; NTG :(Qcf lous-rnr"nt"a - Qcf loug-rnrnr"fira)
Qcf lous-tncented.
Qcfl*g_incented : 3,855; the quantity of CFLs that would be purchased at the
average price of incented lamps ($1.24).
Qc/lavg_unincented : 2,954; the quantity of CFLs that would be purchased at the
average price of un-incented lamps ($2.SS;.
Responses to the in-territory lighting survey produced a 77 percent FR estimate, and, thus an
NTG estimate of 23 percent.
This approach produced the overall progftlm effect minus freeridership, but the approach does
not account for potential program spillover; which upstream lighting programs could produce. .
Upstream programs primarily produce spillover by reducing prices of lamps sold without
incentives. CFL incentives' wide availability has reduced the price of un-incented and incented
lamps. Thus, the observed un-incented CFL price of $2.55 runs substantially below recent prices
in other markets. For instance, recent research in Maryland indicates an un-incented CFL price of
$4.53. Other research indicates un-incented prices between $3.37 and $3.50.
A recent lighting shelf survey of lighting retailers in Maryland indicates un-incented prices as
high as $6.10 per lamp. These higherprices betterreflect CFL costs inthe absence of program
incentives. As the un-incented price estimate rises, the FR rate declines, as fewer lamps would
have been purchased in the program's absence. An un-incented lamp at $3.37 would experience
a 68 percent FR rate. A $4.53 price produces a 58 percent FR rate. A $6.10 price per lamp
produces a 48 percent FR rate. Program impacts of un-incented lamps cannot be quantified with
data available, though $4.00 represents a reasonable value. This cost results ina62 percent FR
estimated rate from WTP data, with a 0.38 NTG value.
Statistical Significance and Uncertainty
A RDD phone survey seeks to avoid bias through the randomness of the selection process. Some
bias may enter the estimate due to certain types of people more likely to be home or to agree to
participate in the survey. Such bias can be addressed through post-weighting responses to more
closely reflect the population's known demographic characteristics.
Every sample, however, is subject to a type of random error that reflects the particular group of
people participating in the study. This is the error due to sampling, for which we can estimate a
margin of error within a given degree of confidence. For instance, members in this sample
reported they would purchase a combined total of 1,966 CFLs at a price of $6.00 per CFL. Had a
different group of people been sample, one could expect, by the random circumstance of those in
the sample, that totals could be somewhat larger or smaller. Applying classical sampling theory
allowed determination of likely boundaries within which that error would fall, allowing
The Cadmus Group, lnc. i Energy Services Appendix F3
Rocky Mountain Power ldatro l-lES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 785 of 1 365
Case No. PAC-E-14-07
Winess: Kathrvn C. HvmasFebruary 3, 2012
constructing of a 90 percent confidence interval for this random error around the sum of CFLs
and LEDs that reportedly would be purchased at each hypothetical price level.
Table Fl presents the sampling error for the sum of purchased bulbs at each CFL price. The
estimates' relative precision ranged from 12.1 to 27.3 percent, indicating this approach's NTG
estimate had a high degree of stability. A NTG value of 0.22 for the observed prices and 0.43 at
the hypothetical $4.00 spillover price would be within a 90 percent confidence interval of the
observed data.2 This, again, suggests quite a stable estimate.
Table Bl.90o/o Confidence Interval and Summary Statistics-CFls (n=208 Respondents)
' These values were determined by assuming the estimate of quantities purchased at $6.00 and $0.50 were off at the
limit of the confidence intervals, in opposite directions (i.e. at the lower limit at $6.00 and the upper limit at
$0.50). The study then reestimated NTG for observed and hypothetical unincented prices, based on a curye
through these points. This did not account for the fact that the joint probability of the estimate being at the limit
in opposite directions at both prices is less than l0 percent; however, this would only bring the limit NTG
estimate closer to the mean estimate; so this can be considered a conservative value.
$18,00 per CFL
1 ,612 - 2,320
The Cadmu$ Group, lnc. i Energy $ervices Appendix F4
Rocky Mountain Power ldaho HE$ Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 786 of 1 365
Case No. PAC-E-14-07
Cg$?t{illT,"zUTT
Appendix G. Billing Analysis Final Models
Billing analysis assessed actual net energy savings associated with insulation measure
installations.' Cadmus determined the savings estimate from a pooled, conditional savings (CSA)
regression model, which included the following groups:
o Insulation (combined attic, wall, and floor insulation for 2009-2010); and
o Nonparticipant homes, serving as the comparison group.2
The bilting analysis obtained a gross realization rate of 72 percentfor insulation measures.
Program Data and Billing Analysis Methodology
Creating the final database for billing analysis used the following sources:
o Program data, collected and provided by the program implementer (including account
numbers, measure types, installation dates, square footage of insulation installed, electric
heat sources, and expected savings for the entire participant population).
o Control groap data, drawn from a random sample of about 15,000 nonparticipating
customers in the Idaho territory with complete billing data from January 2007 through
September 2011. Control group energy use was matched to quartiles of participant pre-
participation energy to ensure comparability of the two groups. To ensure adequate
coverage of the nonparticipating population, Cadmus included four times more
nonparticipants than participants.
o Billing data, provided by Rocky Mountain Power, included all 1,372 Idaho HES
participant accounts with insulation measures, and the random sample of approximately
15,000 Idaho nonparticipating customers. Data included: meter-read dates, and kWh
consumption from January 2007 through September 20ll for participants and
nonparticipants. The billing analysis used a final sample consisting of 1,027 participants,
and 4,I08 control customers.
o Idaho weather data, including daily average temperatures from January 2007 to
October 2011 for three weather stations corresponding with HES participants' locations.
Cadmus first matched program data with billing data, mapping daily heating and cooling degree
days to respective monthly read date periods using ZIP codes.
The billing analysis pre-period was defined, as2007, prior to measure installations.3 The post-
period was defined as the period from October 2010 through September 20fi.4
' nilling analysis was performed only for insulation measures. Energy savings achieved through installation of other
measures were not large enough, relative to total energy consumption of the households in which they were
installed, to allow reliable billing analysis.
2 The nonparticipant group from Idaho experienced high participation in a TOU program. They showed unusually
high savings, possibly attributable to TOU program participation and because all billing analysis savings
included only participants. Their inclusion led to an unusually low realization rate of 4l percent. These gross
savings estimates must be adjusted with freeridership estimates to obtain net savings.
The Cadmus Group, lnc. / Energy $ervices Appendix G1
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 787 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasFebruary 3, 2012
Data Screening
Table G1 shows participant and nonparticipant screening criteria used in the billing analysis. To
ensure the final model used complete pre- and post-participation billing data, Cadmus selected
accounts with a minimum of 300 days in the pre- and post-periods (i.e., before the earliest
installation, and after the latest reported installation in 2010). Additionally, Cadmus removed
outlier accounts with less than 1,500 kWh per year' o. more than 55,000 kWh per year. The
analysis dropped accounts showing a change in consumption more than 30 percent of pre-
program usage. This screen also ensured a better match between nonparticipants and participants.
-lf expected engineering estimates of savings exceeded 70% of pre-consumption, a mismatch occurred between participant
measure installation data and billing data accounts or addresses, or the participant had a vacancy during the pre-period. As
either would have led to unreasonable savings estimates for that customer, they were dropped.
Billing Analysis Results
After screening and matching accounts, the final analysis group consisted of 1,027 participants
and 4, 1 08 nonparticipants.
The following final CSA regression model specification estimated savings from insulation
measures:
ADq = q+ P,HD4, + p2CD4, + APosT + B PARTPOST+ B'ANNUALPRP+ e,,
3 Several 2009 participants installed measures in 2008; thus 2007 was used as the pre-period, before any installation
occurred.
a For participants installing measures after October 2010 the post-period included only months after the measures
were installed. Participants installing measures late in 2010 had less than l0 months of post-period and were
removed from the analysis.
s The minimum participant usage was 1,500 kWh per year. This screen removed very low usage nonparticipants.
Table GL. Screen for Inclusion in Billing Analysis
Original measures database and random
nonoarticioant samole 15,417 1,372
Matched billing data sample (keeping only
nonparticipant residential accounts in participant
ZIP codes only, participant accounts that could be
matched to the billino data addresses)
1,597 122 13,820 1,250
Less than 300 days in pre- or post-period 406 138 13,414 1.112
Less than 1,500 kwh in pre- or post-period 57 13,357 1,112
More than 55,000 kwh in pre- or post-period 79 3 13,278 1,109
Changed consumption by more than 50% from
ore to Dost 1,288 60 1 1,990 '1,049
Expected savings over 70o/o of pre-consumption-3 11,990 1,046
No expected savings 19 11,990 1,027
Nonparticipant sample selection 7,882 4,108 1,027
FinalSample 4,108 1,027
The Cadmus Group, lnc. / energy $ervices Appendix GZ
E,h i b* f":'PPYsTlF.l:i ilfJ
Case No. PAC-E-14-07
Rocky trf,ountain Pow_e.r ldaho HES Evaluation..2009-2010 Final Report #8?'frffiT.c2tT2
Where for customer (i) and month (t):
c ADCit = Average daily kWh consumption.
o HDDit: Average daily heating degree-days (base 65).
o CDDit: Average daily cooling degree-days (base 65).
o POSTF Indicator variable of 1 in the post-period for participants and nonparticipants,
0 otherwise.
o PARTPOSTI- Indicator variable of 1 in the post-period for participants, 0 otherwise.
o ANNUALPRE i: Annual pre period 2007 usage.
The Ba key coefficient determined average insulation savings. This value averaged daily
insulation savings per progftrm participant, after accounting for non program-related trends.
Including the annual pre usage for each customer as an independent variable ensured no
customers had an undue influence over the final savings estimate, resulting in more robust model
parameter estimates.
The above-pooled model combined nonparticipants (the baseline) and participants for the HES
Program's wall, floor, ffid attic insulation components. Attic insulation was installed in
98 percent of participant homes. Impacts of wall and floor measures could not be separated, as
less than 2 percent of homes installed them.
Table G2 presents overall gross savings estimates for wall, floor, and attic insulation measures.
The billing analysis estimated overall insulation savings of 1,293 kWh. The average insulation
experienced average expected savings of 1,796 kwh, translating to a 72 percent realization rate
for insulation measures. With average participant pre-usage of 18,612 kwh, savings represented
a7 percent reduction in energy usage from insulation measures.
Table G2. HES Attic, Floor, and Wall Insulation Gross Realization Rate
Table G3 presents adjusted gross overall savings estimates for wall, floor, and attic insulation
measures, including the control group. The billing analysis estimated savings of 736 kWh. The
average insulation experienced expected savings of 1,796 kwh, translating to a 4l percent
realization rate for insulation measures. With average participant pre-usage of 18,612 kwh,
savings represented a 4 percent reduction in energy usage from insulation measures.
Table G3. HES Attic, Floor, and Wall Insulation Adjusted Gross Realization Rate
As the nonparticipant group showed unusually high savings, compared to other Pacific Power
service territories, and due to the high nonparticipant time of use (TOU) progftlm participation
rate in Idaho, Cadmus recommends using the unadjusted gross participant savings estimate of
The Cadrnu$ Group, lnc. / Hnergy Services Appendix G3
Roclq Mountain Power
Exhibit No. 5 Page 789 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HE$ Evaluation 2009-2010 Final Report CgB?"fiffiT,"2UT?
1,293 kwh from Table G2, and applying a freeridership correction to the gross savings estimate
andrealization rate.
Table G4 and Table G5 summarize model outputs for all the regression models used in the
previous table.
Billing Analysis Regression Models
Table G4. Regression Model for ldaho-Participants Only
Model 4 20216229 5054057 14521.8 <.0001
Enor 24549 8543850 348.03252
Corrected Total 24553 28760079
Root MSE 18.65563 R-Square 0.7029
Dependent Mean 49,44939 Adj. R-Square 0.7029
Coefficient of Variation 37.72671
lntercept 1 -21.56426 03n37 -57.14 <.0001
AnnualPre 1 0.00257 0.00001 297 197.87 <.0001
Post 1 -3.54355 0.22849 -15.51 <.0001
AvgHdd 1 1.10951 0.0089 124.63 <.0001
AvgCdd 1.84022 0.05538 33.23 <.0001
The Cadrnus Group, lnc. I Energy Services Appendix G4
Rocky [i4ountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountiain Power
Exhibit No. 5 Page 790 of 1365
Case No. PAC-E-14{7
PBS?'frffT,"2UT?
Table G5. Regression Model for ldaho-Participants * Nonparticipants
Model 5 r03953372 20790674 58036.5 <.0001
Error 122n2 43981 141 358.2343
Conected Total 122m 't47934513
Root MSE 18.92708 B-Square 0.7027
Dependent Mean 50.21415 Adj. R-Square 0.7027
Coefficient of Variation 37.69272
lntercept 1 .22,81593 0.17187 -132.75 <.0001
AnnualPre 0,00266 0.00000593 449.23 <,0001
Post -1.48328 0.1 0956 -13.54 <.0001
PartPost 1 -2.01574 0.18326 -11 <.0001
AvgHdd 1.08309 0.00403 268.96 <.0001
AvgCdd 1 1.8103 0.02648 68.37 <.0001
The Cadmus Group, lnc. / Energy $ervices Appendix G5
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 791 of 1365
Case No. PAC-E-14-07
Wtnessi Kathrvn C. HvmasFebruary 3. 2012
tio':vl
o
tro
o4
Appendix H. lnsulation Site Visit Verification: Home
Gharacteristics of ID HES lnsulation Participants
General Home Characteristics
Figure Hl. Distribution of Home Age
---- 54v;
soz .$ Mean = 1975
Std Dev = !8.4
40% '{ Min = 1900
Max = 2008
to%
o%
Before 1920s 1940s 1950s 1960s 1970s 1980s 1990s 2000s
1920
Decade Constructed
Figure H2. Distribution of Home Size (Square Feet)
Lo/ot%
40%
35%
30%
25%
20%
t5%
70%
5%
o%
Less than 1,000 to
1,000 1,499
1,500 to 2,000 to 2,500 to1,999 2,499 2,999
Home Size (Square Feet)
3,000 to 3,500 or
3,499 greater
n=72
Mean = 1,905
Std Dev = 778
Min = 900
Max = 4,000
6o
lh
o
tro{J
o.L
6%
The Cadmus Group, lnc. I Energy Services Appendix H1
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclq Mountain Power
Exhibit No. 5 Page 792 of 1 365
Case No. PAC-E-14-07
Cgts?'iffiT,"2UT?
Figure H3. Basement Type
I Crawlspace
m Full finished basement
m Partially finished
basement
I Slab
rit: Unfinished basement
Figure H4. Number of Occupants
The Cadrnu$ Group, lnc. I Energy $ervices Appendix FlZ
Rocky Mountain Power
Exhibit No. 5 Page 793 of 1 365
Case No. PAC-E-14-07
Rocky fulountain Power ldaho [-lH$ Evaluation 2009-2010 Final Report Wtness: Kathrun C. HvmasFebruary 3. 2012
Heating and Cooling
Figure H5. Primary Heating System Types
I Gas Furnace
N Electric Furnace
N Electric Other
I Electric Radiant Heat
ffi Electric Baseboard
s Electric Ground Source Heat
Pump
N Propane Furnace
P,:j Electric Air Source Heat Pump
n=72o
Figure H6. Primary Cooling System Types
I No cooling system
N Central air conditioning
N Ground-source heat pump
r Ductless mini-split air
conditioner
n=62
-**--t
i
ii
I
i
i
inpi
i
The Cadrnus Group, lnc. i Hnergy Services Appendix l-tS
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 794 of 1365
Case No. PAC-E-14-07
#B?'fi{ru}s,"2BTT
Figure H7. Winter Heating Temperature Set Points
(with 90 Percent Confidence Intervals)
i
EutgJf;66
o
CLtrd64
Home Away Work
(n = 66)(n = 53)(n = 62)I (n=bb) (n=b3) (n=bz)
Figure H8. Summer Cooling Temperature Set Points
(with 90 Percent Confidence Intervals)
Away
(n = 16)
79
78
77
76
75
74
73
72
7t
70
69
68
l!
oL,
G
o
CL
Eo
The Cadrnu$ Group, lnc. / Energy Services Appendix 1""{4
Rocky hrlountain Power ldaha HES Evaiuation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 795 of '1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasFebruary 3. 2012
Appendix I. Net-to-Gross Evaluation Methodology
Net-to-gross (NTG) estimates serye as a critical part of demand-side management (DSM)
program impact evaluations, allowing utilities to determine portions of gross energy savings
influenced by and attributable to their DSM programs, free from other influences. Freeridership
and spillover comprise NTG's two components. Freeriders are customers who would have
purchased a measure without any program's influence. Spillover is the amount of additional
savings obtained by customers investing in additional energy-efficient measures or activities due
to their progftlm participation. Various methods can be used to estimate program freeridership
and spillover. This evaluation's baseline approach used self-reports through participant surveys.
Program Categorization
Prior to designing the NTG surveys, Cadmus worked with Rocky Mountain Power to conduct a
thorough review of its DSM programs, determining the following:
o Each program's unique characteristics As each DSM program and measure operates
differently, a clear understanding of these programs had to be determined. This helped
inform the survey design and question wording, assuring acknowledgement and
accounting for nuances.
o The appropriate interviewee. This step proved critical, as survey questions had to reach
the right decision makers. For example, a review of an ENERGY STAR Homes program
may indicate home builders as decision makers, not customers purchasing homes. Thus,
survey questions would be worded to apply to home builders, not homeowners.
Following the program review, Cadmus aggregated the HES Program measures into three
distinct categories:
. Appliances (clothes washers, dishwashers, fixtures, heat pump best practices, heat pump
system conversions, heat pump tune-ups, heat pump upgrades, and refrigerators);
o Insulation and windows; and
o Compact fluorescent lamps (CFLs).
Creating these program categories required striking a balance between each measure's unique
characteristics (requiring NTG influences to be measured differently) and retaining a sufficiently
large participant population to obtain a statistically significant and reliable sample.
The described methodology could not be used to evaluate NTG for CFLs. As the HES program
incents CFLs at the retailer level, participants often do not know they have participated in a
program or have purchased an incented CFL. Therefore, calculating freeridership and spillover
by surveying upstream measure participants did not prove viable.
Survey Design
Direct questions (such as: "Would you have installed measure X without the program
incentive?") tend to result in exaggerated "yes" responses. Participants tend to provide answers
they believe surveyors seek; so a question becomes the equivalent of asking: "Would you have
The Cadmus Group, lnc. / Energy Servi*es Appendix l1
Rocky Mountain Power ldaho hlE$ Evaluation 2009-2010 Final Report
Roclq Mountain Power
Exhibit No. 5 Page 796 of 1 365
Case No. PAC-E-14-07
dgts?'fr##T,"zUTT
done the right thing on your own?" An effective solution for avoiding such bias involves asking
a question in several different ways, then checking for consistent responses.
Cadmus designed survey questions to determine why customers installed a given measure, and
what influence the program had on their decisions. The survey sought to establish what decision
makers might have done in the program's absence, using five core freeridership questions to
address that issue:
o Would participants have installed measures without the program?
o Had participants ordered or installed the measures before learning about the program?
o Would participants have installed the measures at the same efficiency levels without the
program incentive?
o Would participants have installed the same quantity of measures without the program?
o In the program's absence, when would respondents have installed the measures?
The spillover survey sought to answer three primary questions:
o Since participating in the program evaluated, did participants install additional energy-
efficient equipment or services incented through a utility program?
o How influential was the evaluated program on the participants' decisions to install
additional energy-efficient equipment in their homes?
o Did customers receive incentives for additional measures installed?
Freeridership Survey Questions
The residential survey's freeridership portion included 11 questions, addressing the five core
freeridership questions. The survey's design included several skip patterns, allowing interviewers
to confirm answers previously provided by respondents by asking the same question in a
different format. Freeridership questions (as asked in the survey format) included:
1. When you first heard about the incentive from Rocky Mountain Power, had you already
been planning to purchase the measure?
2. Ok. Had you already purchased or installed the new measure before you leamed about
the incentive from the Home Energy Savings program?
3. lAsk f question 2 is No or Don't Know) Would you have installed the same measure
without the incentive from the Home Energy Savings program?
4. [Ask if question 3 is No or Don't Knowl Help me understand, would you have installed
something without the Home Energy Savings program incentive?
5. lAsk if question 3 or question 4 is Yes) Let me make sure I understand. When you say you
would have installed the measure, would you have installed the same one that was just as
energy efficient?
6. lAsk if question 3 or question 4 is Yes AND measure quantity > 1] And would you have
installed the same quantity?
The Cadmus Group, lnc. i Hnergy $ervices Appendix 12
Rocky fVlountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 797 of 1365
Case No. PAC-E-14-07
#ts?t{ffT,"2HTS
7. lAsk if question 3 or question 4 is Yesf And would you have installed the measure at the
same time?
lAsk if question 3 or question 4 is Nol To confirm, when you say you would not have
installed the same measure, do you mean you would not have installed the measure at all?
[Ask if question 8 is No or Don't Know] Again, help me understand. Would you have
installed the same type of measure but it would not have been as energy-efficient?
10.lAsk if question 8 is No or Don't Know AND measure quantity > 1] Would it have been
the same measures but fewer of them?
1I.lAsk if question 8 is No or Don't KnowlAnd, would you have installed the same measure
at the same time?
Spillover Suruey Questions
As noted, spillover questions sought to determine whether program participants installed other
energy-saving measures since participating in the program. Savings participants received from
additional measures would be considered spillover savings if the program significantly
influenced their decisions to purchase additional measwes, and if they did not receive additional
incentives for those measures.
Surveys specifically asked residential participants whether they installed the following measures:
l. Clothes washers
2. Refrigerators
3. Dishwashers
4. Windows
5. Fixtures
6. Heat pumps
7. Ceiling fans
8. Electric water heaters
9. CFLs
10. Insulation
If the participant installed one or more of these measures, additional questions asked what year
they purchased the measure, if they received an incentive for the measure, and how influential
(highly influential, somewhat influential, not at all influential) the HES program was on their
purchasing decisions.
Cadmus combined the freeridership and spillover questions in the same survey, simultaneously
asking the questions using telephone interviews of randomly selected program participants. Prior
to beginning the live participant phone calls, Cadmus worked with the survey company to pretest
the survey, ensuring all appropriate prompts and skip pattems would be followed. Cadmus also
monitored initial phone calls to verifr:
The survey respondents understood the questions; and
Adjustments were not required.
8.
9.
a
a
The Cadmus Group, lnc. / Energy $ervices Appendix l3
Rocky [tilountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mouniain Po\ryer
Exhibit No. 5 Page 798 of 1 365
Case No. PAC-E-14-07
#ts?'frffiT,'2UT2
Freeridersh i p Methodology
Cadmus developed a transparent, straightforward matrix for assigning scores to participants,
based on their objective responses to targeted survey questions. Question response patterns
received freeridership scores, with confidence and precision estimates calculated on the
distribution of these scores (a specific approach cited in the NAPEE Handbook on DSM
Evaluation, 2007 edition, page 5-l).
Response patterns and scoring weights remained explicit; they could be discussed and changed,
with results shown in real time. The approach provided other important features, including:
o Derivation of a partial freeridership score, based on the likelihood of a respondent taking
similar actions in the incentive's absence.
o Use of a rules-based approach for consistency among multiple respondents.
o Use of open-ended questions to ensure quantitative scores matched respondents' more
detailed explanations regarding program attribution.
. The ability to change weightings in a "what if' exercise, testing the response
set's stability.
Cadmus' method offered a key advantage in introducing the concept of partial freeridership.
Experience has shown program participants do not fall neatly into freerider and not-freerider
categories. For example, partial freeridership scores were assigned to participants with plans to
install the measure; though, the program exerted some influence over their decisions, other
market characteristics outside the program proved influential. Further, with partial freeridership,
"don't know" and "refused" responses could be used to assign partial credit, rather than
removing respondents entirely from the analysis.
The study assessed freeridership at three levels:
o It converted each participant survey response into a freeridership matrix terminology.
o Each participant's combination of responses then received a score from the matrix.
o All participants were aggregated into an average freeridership score for the entire
program category.
Convert Responses to Matrix Terminology
The study independently evaluated each survey question's response, assessing participants'
freeridership levels for each question, with each survey response option converted into values of:
o "Yes'o (100 percent freerider)
o "No" (0 percent freerider)
o "Partial" (50 percent freerider)
Table Il lists 11 survey questions, their corresponding response options, and values which they
converted to (in parentheses). "Don't knof' and "refused'o responses converted to "partial" for
all but the first three questions. For those questions, if a participant was unsure whether they had
The Cadrnus Group, lnc. I Energy $ervices Appendix 14
Rocky [t4ountain Power ldaho l-lE$ Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 799 of 1 365
Case No. PAC-E-14-07
#ts?'frffiT,'rUT?
already purchased or were planning to purchase the measure before learning about the incentive,
they were considered an unlikely freerider.
Table I1. Assignments of HES Survey Response Options into Matrix Terminolory
Participant Freeridersh ip Scoring
Following conversion of survey responses into matrix terminology, a freeridership matrix could
be created, allowing each participant's combined responses to be assigned a freeridership score.
All combinations of survey question responses were considered in creating the matrix, with each
combination receiving a freeridership score of 0 to 100 percent. Using this matrix, every
participant combination of responses was assigned a score of 0 to 100 percent.
Program Category Freeridership Scoring
After assigning a freeridership score to every survey respondent, Cadmus calculated a savings-
weighted average freerider score for the program category. Respondent freerider scores were
individually weighted by estimated savings of equipment installed, using the following
calculation:
$Br.Mls BFBsS*fid Sl"Esrt"$fr6rsft$ =
Yes
(Yes)
Yes
(Yes)Yes (Yes)
Yes, I
would have
installed
something.
ffes)
Yes
(Yes)
Yes
(Yes)
At the
same
time
(Yes)
Yes
(Yes)
Yes
(Yes)
Yes
(Yes)
At the
same
time
(Yes)
No
(No)No (No)No (No)
No, I would
not have
installed
anything,
(No)
No (No)No (No)
Within
0ne
year
(Partial)
No (No)No (No)No (No)
Within
0ne
year
(Partial)
Don't
Know
(No)
Don't
Know
(No)
Don't
Know (No)
Don't Know
(Partial)
Don't
Know
(Partial)
Don't
Know
(Partial)
ln more
than
0ne
year
(No)
Don't
Know
(Partial)
Don't
Know
(Partial)
Don't
Know
(Partial)
ln more
than
0ne
year
(No)
Refuse
d (No)
Refuse
d (No)
Refused
(No)
Refused
(Partial)
Refused
(Partial)
Refused
(Paniaf
Don't
Know
(Padial)
Refused
(Partial)
Refused
(Partial)
Refused
(Partial)
Don't
Know
/Partial)
Refused
(Partial
Befused
(Partial
$ssrel.rr [SSstM trsfisf]E ffi[ryt
The Cadrnu$ Group, lnc. I Energy Services Appendix l5
Rocky Mountain Power ldaho FIE$ Evaluation 2009-2010 Final Report
Roclq Mountain Power
Exhibit No. 5 Page 800 of 'l 365
Case No. PAC-E-14-07
Witness: Kathrun C. HvmasFebruary 3. 2012
The Cadmus Freeridership Scoring Model
Cadmus developed an Excel-based model to assist with freeridership calculation, and to improve
consistency and quality of results. The model translated raw survey responses into matrix
terminology, and then assigned each participant's response pattem a score from the matrix.
Program participants in the sample could then be aggregated by program categories to calculate
average freerider scores.
The model incorporated the following inputs:
o Raw survey responses for each participant, along with program categories for their
incented measures, and energy savings from those measures, if applicable;
o Figures converting raw survey responses into matrix terminologies for each program
category; and
o Custom freeridership scoring matrices for each unique survey type.
The model used a simple interface, allowing users to quickly reproduce a scoring analysis for
any program category. It displayed each participant's combination of responses and
corresponding freeridership score, then producing a summary table that provided the average
score and precision estimates for the program category. The model used the sample size and a
two-tailed test target at the 90 percent confidence interval to determine the average score's
precision.
Table 12 shows a sunmary table example for the HES appliances program category, with the
final freeridership score appearing in the lower right corner. The example program category
averaged 33 percent freeridership, meaning 33 percent of energy savings, derived from
freeriders, and should be removed from gross program savings. Based on a269 response sample
size, the program had an absolute precision of3 percentage points.
Spillover Methodology
Spillover refers to additional savings generated by program participants through program
participation, but not captured by program records. Spillover occurs when participants choose to
purchase energy-efficient measures or adopt energy-efficient practices because of a program, but
do not participate (or otherwise cannot participate) in the program. As these customers do not
participate, they typically do not appear in program records of savings generated by spillover
impacts.
Table 12. Freerider Scoring Model Output
The Cadmus Group, lnc. / Energy $ervices Appendix 16
Rocky tulountain Power ldaho HE$ Evaluation 200$-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 801 of 1 365
Case No. PAC-E-14-07
#B?"fr#ilT."2UT?
Spillover examples include:
. Program participants adopting additional measures without an incentive.
o Consumers acting on the programs' influence, resulting from changes in available
energy-using equipment in the marketplace.
o Changes brought about by more efficient practices employed by architects and engineers,
ultimately forcing consumer behaviors into desired patterns.
o Changes in nonparticipants' behaviors, resulting from direct marketing or changes in
stocking practices.
The energy-efficiency programs' spillover effect serves as an additional impact, which can be
added to the program's direct results.
For the HES Program, Cadmus measured spillover by asking a sample of participants purchasing
and receiving an incentive for a particular measure if, due to the program, they installed another
effrcient measure or undertook another energy-efficiency activity. Respondents were asked to
rate the HES Program's (and incentive's) relative influence (either highly, somewhat, or not at
all influential) on their decisions to pursue additional savings.
Participant Spi I lover Analysis
Calculating spillover savings used a top-down approach. The analysis began a subset containing
only survey respondents indicating they installed additional energy-savings measures after
participating in the HES program. From this subset, participants were removed if they indicated
the program had little influence on their decisions to purchase additional measures, thus retaining
only participants rating the incentive as highly influential. Participants also were removed if they
applied for HES incentives covering additional measures they installed.
For remaining participants with spillover savings, energy savings were estimated for additional
measures installed. Cadmus engineers calculated savings values, which were matched to
additional measures installed by survey participants.
The spillover percentage per program category was calculated by dividing the sum of additional
spillover savings reported by respondents for a given program category by total incentivized
gross savings achieved by all respondents in the program category:
5g+$$d,rur+.t1 .$g.r'er $tes$$Pt [xx$'*h S :$su$1I s$des.ts
Frsxrsm $l:EesurCI h*tt 8,x*{lngp :fem lfil,trr Stmr.rp Ssaps,s$sstg
The Cadmus Group, lnc. I Energy Services Appendix 17
Rocky Mountain Po /er
Exhibit No. 5 Page 802 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HE$ Evaluation 2009*2010 Final Report CEts?tffiT,"2UT?
Appendix J. Marketing Materials Review
lnteractive Best Practices
Leverage fi rst impressions
o Include a simple, attention-grabbing, and relevant offer.
. Keep offer highlights above the fold.
o Offer clear calls to actions.
Communicate value
o Always ask: "What's in it for my reader?"
o Make offer attractive and easy to access.
o Target to site visitor as much as possible.
Keep it simple
o Design clear and intuitive navigation.
o Do not make your visitor hunt for the program/offer.
. Offer simple forms.
o Request the minimum contact information for lead capture.
Focus on "conversaon" to maximize results
o Make the "submit" or conversion button prominent.
o Offer more information and assistance in exchange for contact information.
o Become customer-centric; offer not only information, but also support.
Build trust
o Communicate your privacy policy clearly.
o Make sure visitors know where any contact information will (and will not) be used.
o Offer educational value; residents and businesses appreciate more information multiple
energy-effi ciency programs.
Test, measure, fine tune, repeat
Website designers serious about leveraging their online presence constantly test multiple landing
page variables in image, copy, look and feel, offer, and lead marketing.
The Cadrnus Group, lnc. / Energy $eruices Appendix J1
Rocky Mountain Power ldaho HES Evaluation 2009*2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 803 of 1 365
Case No. PAC-E-14-07
Wtness: Kalhrvn C. HvmasFebruary 3. 2012
Appendix K. Engineering Review and Whole House
Energy Modeling
Engineering Review
The engineering review used data from the participant phone surveys and secondary data to
evaluate gross savings for clothes washers, refrigerators, dishwashers, ceiling fans and light
fixtures. As shown in Table Kl, realization rates ranged between 20 percent and 185 percent.
Clothes Washers
The clothes washer deemed savings values for 2009 and 2010 were based on the Bonneville
Power Administration's (BPA) Planning, Tracking and Reporting System (PTR).l Each clothes
washer measure received a PTR value, based on the configuration of a modified energy factor
(MEF) level, water heater fuel, and dryer fueI.
Cadmus calculated savings based on a 202 metering study,2 which metered more than 100
clothes washers in California homes for three weeks. The largest in situ metering study on
residential clothes washers and dryers conducted in the last decade, this study indicated higher
consumption and savings values than those often estimated. The dryers experienced the majority
of energy consumption and savings, as high-efficiency washing machines removed more
moisture from clothes, allowing shorter drying times.
As a phone survey of clothes washer program participants found approximately 81 percent of
washer loads are dried in dryers, average dryer savings per washer cycle were reduced by
19 percent to account for this.
t http :/iwww.ptr.nwcouncil.org
'The Cadmus Group, Inc. "Do the Savings Come Out in the Wash? A Large Scale Study of In-Situ Residential
Laundry Systems." 2010.http:llwww.cadmusgroup.com/pdfs,4Do_the_Savings_Come_Out_in_the_Wash.pdf
Table Kl. Engineering Review Summary Table
2009-201 0
Clothes Washers Clothes Washer-Tier
One 1.72 - 1,99 MEF)231 284 123Y0
Clothes Washers Clothes Washer-Tier Two
(2.0 + MEF)241 447 185%
2009-201 0 Refrigerator ENERGY STAR Refrioerator 97.5 65.5 67Yo
2009-201 0 Dishwasher ENERGY STAR Dishwasher 35 36 103%
2009-201 0 Ceiling Fans Ceilinq Fans 107 21 20%
2009-201 0 Fixtures Fixtures 92 108 1170/0
The Cadrnus Graup, lnc. i Energy $ervices Appendix Kl
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 804 of 1365
Case No. PAC-E-14-07
#ts?'fr#$.J."2UTE
Cadmus determined annual electricity savings by multiplying the metering study's adjusted
kWh/cycle values by 403 cycles/year, which, based on the phone survey, was determined the
average number of yearly clothes washer cycles.
The 2006 PacifiCorp Energy Decisions Survey indicated 50 percent of Idaho residential
customers used electric heaters for domestic hot water (DHSD, and 84 percent used electric
dryers. Cadmus developed savings values for each tier by taking weighted averages based on
these parameters and measure data for sales distributions, based on MEF.
The following calculation determined adjusted unit savings:
adjusted kWh savings/cycle x cycles/year : annual kWh savings
As shown in Table K2, which compares assumptions used for reported and evaluated savings,
some configurations with gas dryers indicated negative savings due to clothes washers with a
high-efficiency rating possibly using more energy in the spin cycle to remove more moisture
from clothes. Though removing more moisture in the washer can reduce total energy used for
laundry, electricity savings may not be realized if customers use a non-electric dryer.
Table K2. Clothes Washer Calculations, 2009-2010
Cycles per year Unknown 403
Percentage of Washer Loads Dried in a Dryer Unknown 810h
Water
Heater Fuel
Electric N/A 50%
Gas N/A 50%
Dryer Fuel
Electric N/A 840/o
Gas N/A 16o/o
Gross Unit
Savings
(kWh/year)
Electric DHW & Electric Dryer
MEF 1.72-1.99 295 301
MEF 2.0+320 557
Electric DHW & Gas Dryer
MEF 1.72-1,99 128 -32
MEF 2.0+170 114
Gas DHW & Electric Dryer MEF 1.72-1.99 188 325
MEF 2,0+211 448
Gas DHW & Gas Dryer MEF 1.72-1.99 37 -8.1
MEF 2.0+44 4.7
As shown in Table K3, weighted average evaluated savings values were higher than reported
savings for all tiers.
The Cadmus Group, lnc. i Energy Services Appendix K2
Rocky lulountain Power ldaho l-{ES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 805 of 1365
Case No. PAC-E-14-07
Wtnessi Kathryn C. HvmasFebruary 3, 2012
Table K3. Clothes Washer Savings, 2009-2010
1.72-1.99
Electric DHW & Electric Dryer 29s
Eleclric DHW & Gas Dryer 128
Gas DHW & Electric Dryer 188
Gas DHW & Gas Dryer 37
Weighted average 231 284 52
2.0+
Electric DHW & Electric Dryer 320
Electric DHW & Gas Dryer 170
Gas DHW & Electric Dryer 211
Gas DHW & Gas Dryer 44
Weighted average 241 447 206
Refrigerators
Although the PTR provided a deemed savings value for refrigerators, that value has since been
updated in the PTR, based on a database of available models in August 2008.
For 2009 and 2010, Cadmus used the methodology shown in the Regional Technical Forum's
July 2011 analysis3 to estimate gross per-unit energy savings, as shown in Table K4. The July
20ll analysis included the assumption that 32 percent of baseline units were ENERGY STAR@-
qualified. This assumption embedded net-to-gross in the savings calculated. Cadmus modified
the analysis to assume that 0 percent of baseline units would be ENERGY STAR-qualified.
Dishwashers
Deemed savings values for dishwashers were based on data from the Northwest Power and
Conservation Council's Regional Technical Forum (RTF) FY07 analysis. Cadmus based these
values on the analysis' more recent FY09 version, included in the 6ft Power Plan.
The 6d' Power Plan values used included electricity consumption per cycle of eight
configurations of the energy factor (EF) and the water heater fuel. The 6th Power Plan used an EF
of 65 for the baseline-the efficiency level required for a dishwasher to qualifu for a rebate in
Idaho in2009-2010.
3 http://www.nwcouncil.org I energy lrtfl measures/measure.asp?id= I 22
Table K4. Refrigerator Savings, 2009-2010
The Cadmus Group, lnc. i Energy $ervices Appendix K3
E,h i bir f":'YPysTlH:iilfJ
Case No. PAC-E-14-07
Rocky hflountainjower ldaho HES Evaluatioj.._-t?s-20t0 Final Report FtBTfrry3l?Ull
Based on research of available models, Cadmus used a baseline of 62 EF to calculate savings per
cycle, then multiplying savings per cycle for each configuration by 256 cyclesiyear (the average
reported by customers surveyed). The following equation determined adjusted unit savings:
adjusted kWh savings/cycle x cycles/yeor : annuol kwh savings
Table K5 compares assumptions used for deemed and adjusted savings values.
Table K5. Dishwasher Calculations, 2009-2010
Cycles per year 215 256
Gross Unit Savings
(kWh/year)
Machine
EF 0,65-0.67 I EF 0.65-0.67 11
EF 0.68-0.71 13 EF 0.68-0.71 22
EF 0.72-0.79 18 EF 0.72-0.82 37
EF 0.8+24 EF 0.83+97
Hot
Water
EF 0.65-0.67 32 EF 0.65-0.67 8.0
EF 0.68-0.71 43 EF 0,68-0.71 14
EF 0.72-0.79 56 EF 0.72-0.82 20
EF 0.8+80 EF 0.83+33
The adjusted values for each of the eight EF level configurations and for water heater fuel were
applied to each dishwasher measure. The EF level groups used in deemed savings and updated
values did not match exactly. Consequently, Table K6 also provides a weighted average.
Table K6. Dishwasher Savings, 2009-2010
Electric 0,6s-0.67 41 0.65-0.67 19
Electric 0.68-0.71 56 0.68-0.71 36
Electric 0.72-0.79 73 0.72-0.82 57
Electric 0.8+104 0.83+130
Electric Weighted average 61 Weiohted averaoe 46 -15
Gas 0.65-0.67 I 0.65-0.67 11
Gas 0.68-0.71 13 0.68-0.71 22
Gas 0,72-0.79 18 0.72-0,82 37
Gas 0.8+24 0.83+97
Gas Weighted average 14 Weighted average 28 14
Any Weighted average 35 Weighted average 36 1
Ceiling Fans
For both 2009 and 2010 program years, the HES Program offered ENERGY STAR ceiling fans.
Reported ceiling fan saving values derived from the sum of motor savings (from the ENERGY
The Cadnnus Group, lnc. / Energy Seruices Appendix K4
Rocky Mountain Power ldaho HES Evaluation 2009*2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 807 of 1365
Case No. PAC-E-14-07
Vvitness: Kathrun C. HvmasFebruary 3. 2012
STAR savings calculator) and lighting savings (from the PTR). PTR-based CFL savings for an
average room type were multiplied by three to calculate assumed numbers of bulbs per ceiling
fan.
Cadmus used the same motor savings value as the ENERGY STAR calculator, calculating
lighting savings via a methodology similar to that used for CFL lamps. The following equation
reflects the ceiling fan savings methodology, and Table KT lists the input assumptions:
lkwh: (MotorkWh) + (((/Watts) /1000) *I,SR * (HOU * 365) * WHF * Number of Bulbs)
lWatts:Wb^,-W"6
Where:
MotorkWh: Motor savings per ceiling fixture (kwh).
W"f: Wattage of efficient ENERGY STAR CFL.
Wb^r: Wattage of baseline fixture.
HOU: Hours of use per day.
ISR: In Service Rate or percentage of incented units installed.
WHF : Waste Heat Factor for energy to account for HVAC interaction affects (heating
and cooling).
365 = Constant (days per year).
I000 : Constant (conversion watts to kilowatts).
Number of Bulbs = Number of bulbs per fixture.
. ENERGY STAR Ceiling Fan Calculator:
http://www.energystar.gov/index.cfm?fuseaction=find_a_product.showProductGroup&pgw_code=CF.. ENERGY STAR Qualified Product List (ENERGY STAR Ceiling Fans with Light Kits Product List, August 15, 201 1 ).
The ceiling fan hours-of-use (HOUs) derived from room location assumptions, with common
rooms identified as typical locations for ceiling fans. This differed from the CFL HOU analysis,
which included all room locations in calculating overall daily HOUs. Ceiling fan rooms
consisted of main living spaces, kitchens, and bedrooms.
able I(7. Ce tr'an Input Assum ns
MotorkWh o ENERGY STAR Calculatof
Weff 20.28 Median ceiling tan lamp wattage based on ENERGY STAR Qualified Product List--
Woas"75 Comparable incandescent wattage, based on Cadmus'CFL lamp analysis
HOU 2.52 Cadmus' hours-of-use model and PacifiCorp's HES Residential Survey
ISR 1 Assume all fixtures were installed
WHF 1.00 Based on Cadmus'CFL lamp analysis (assume allfans are indoor)
Number ol Bulbs 0.30 Model data: averaoe number of bulbs based on 200$-2010 oarticiDant oroduct data
The Cadnrus Group, lnc. i EnerEy $ervices Appendix K5
Rocky Mountain Power ldaho HE$ Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 808 of 1365
Case No. PAC-E-14-07
\Mtness: Kathrvn C. HvmasFebruary 3. 2012
PacifiCorp's savings analysis documentation assumed all ceiling fans included a three-bulb
lighting fixture; however, the company's 20091010 participant data specified only models and
brands, not numbers of bulbs. The two program years only had I I participants, and the program
paid only 22 ceiling fan incentives.
Using reported model numbers, Cadmus verified the number of bulbs per fixture by conducting
Web searches and referring to ENERGY STAR product lists. As shown in Table K8, of 22
ceiling fans sold, three had lighting fixtures attached. Research determined fixtures averaged
0.30 bulbs.
Table K8. C l'an L Ifits
No Lioht Kit 5 17 0
Light Kit 1 3 6
Model Not Found 2 2 0
Total 8 22 b
Table K9 shows reported and evaluated ceiling fan per-unit savings.
able K9. Ceilins Fan Per-Unit Sav
Motor per Unit Savings (kWh)6.0 6.0
CFL per Bulb Savings (kWh)33.8 50.4
CFL per Fan Savings (kWh)101.4 15.1
TotalCeiling Fan Savings (kWh)107.4 21.1
.Filed kWh savings rounded down to 107 kwh.
The largest per-unit savings variance resulted from the assumed number of bulbs per fixture.
Though PacifiCorp's HES Program allowed ENERGY STAR ceiling fans with and without light
fixtures, the savings analysis assumed installation of ceiling fans exclusively with light fixtures.
Table K10 shows evaluated savings of 465 kWh for the 22 ENERGY STAR ceiling fans
receiving incentives.
Table KLO. Evaluated and Fan Savi for 2009-2010
ENERGY SIAR Fixtures
In both 2009 and 2010 program years, HES offered ENERGY STAR fixtures, with these
fixtures' 2009-2010 reported saving values based on the PTR. Using the PTR" Regional
Technical Forum, and 6th Power Planning assumptions, Cadmus calculated total fixture savings,
based on an assumption of two bulbs per fixture.
The Cadmus Group, inc. I Energy $ervices Appendix K6
Rocky flflountain Power ldahs HES Evaluation 2009-2010 Final Report
Roclry Mountain Power
Exhibit No. 5 Page 809 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasFebruary 3. 2012
Cadmus' calculation of lighting savings derived from a methodology similar to that used for CFL
lamp analysis. Using the ENERGY STAR fixtures calculation and input assumptions, shown in
Table Kll, the following equation provided savings:
lkwh : (lWatts) /1000) * I,SR * (HOU * 365) * WHF * Number of Bulbs
lWatts:Wase-Wa1
Where:
W6:Wattage of efficient ENERGY STAR CFL.
Wb^": Wattage of baseline fixture.
HOU: Hours of use per day.
1SR : In Service Rate or percentage of incented units installed.
WHF: Waste Heat Factor for energy to account for HVAC interaction affects (heating
and cooling).
365 : Constant (days per year).
1000: Constant (conversion watts to kilowatts).
Number of Bulbs:Number of bulbs per fixture.
K ENERGY STAR F
Cadmus based its ENERGY STAR fixture HOUs on CFL HOU analysis with all room locations
included in determining overall daily HOUs. As described in the CFL analysis, Cadmus used an
HOUs model and data collected from the HES residential survey, which detailed lighting
information by room type.
Over two years, the HES Program had 64 participants, and incented 130 ENERGY STAR
fixtures. PacifiCorp's 2009-2010 participant data specified the model and brand, but not
numbers of bulbs per fixture. As the HES participant data did not include wattages, the efficient
CFL wattage (W"n) was based on the ENERGY STAR fixture product list, with a medium
wattage of 18 watts per lamp for each fixture.
To veriff the number of bulbs per fixture, Cadmus relied on reported model numbers, and used
Web searches and ENERGY STAR product lists, resulting in an average 2.2 number of bulbs per
fixture.
able ixture t Assu
Wefl 18 Median fixture lamp wattage based on ENEHGY STAR Qualified Product List-
Wuare 75 Comparable incandescent wattage based on Cadmus'CFL lamp analysis
HOU 2.35 Cadmus' hours of use model and PacifiCorp's HES Residential Survey
ISR 1 Assume allfixtures were installed
WHF 1.00 Based on Cadmus'CFL lamp analysis
Number of Bulbs 2.2 Model data; average number of bulbs based on 2009-2010 participant product data
-ENERGY STAR Qualified Product List (ENERGY STAR Residential Light Fixtures Product List; August 15, 201 1 ).
The Cadmu$ Group, lnc. i Hnergy Services Appendix K7
Rocky fulountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No, 5 Page 8'10 of '1 365
Case No. PAC-E-14-07
#8?'fr$ffT,"2UT?
Table Kl2 shows reported and evaluated ENERGY STAR fixture per unit savings
Table K12. ENERGY STAR Fixture Per Unit
The large variance in numbers of bulbs per fixture directly impacted total fixture savings. As
shown in Table Kl3, the HES Program reported evaluated savings for ENERGY STAR fixtures
of 14,040 kWh for 130 products incented.
Table K13. Evaluated and ed ENERGY STAR Fixture Sav for 2009-2010
Engineering Review: Systems
The engineering review used data from participant phone surveys and secondary data to evaluate
gross savings for water heaters, heat pumps, central air conditioners, room air conditioners,
evaporative coolers, duct insulation, and HVAC commissioning.
For these measures, the RTF methodology and savings were used to determine savings achieved
by program participants. As shown in Table Kl4, realization rates ranged from 56 percent to
164 percent.
Number of Bulbs per Fixture
Total Fixture Savings (kWh)
The Cadrnus Group, lnc. / Energy Services Appendix KB
Rocky Mountain Power
Exhibit No. 5 Page 81 1 of 1 365
Case No. PAC-E-14-07
Rocky Mountain Power ldaho HE$ Evaluation 2009-2010 Final Report #ts?t.IilT"2UT?
Table K14. En Review Summary Table
2009-2010 Water Heaters RTF Defined Standard 91 97 1070k
2009-2010 Heat Pump System
Conversion Electric Fumace 3,147 5,182 1640k
2009-201 0 Heat Pump Upgrade HSPF 7.7 811 470 56%
2009-201 0 Heat Pump Tune-
Llo
Operating Heat Pump
Svstem 576 505 88%
2009-201 0 CentralA/C
Eouioment SEER 13 96 96 100%
2009-201 0 Proper CAC lnstall Standard Practice
lnstallation 23 23 100%
2009-201 0 Proper CAC Sizing Oversized CAC
Svstem 67 67 100%
2009-201 0 CAC Tune-Up Operating GAC
Svstem 30 30 100%
2009-201 0 Evaporative Coolers CAC System 325 325 100%
2009-201 0 Duct Sealing Leaky Ducts, per RTF
definition 40 52 130%
Water Heaters
Water heater deemed savings values for 2009 and 2010 derived from the BPA's PTR.4 The
actual gross savings estimate used a weighted average of various scenarios analyzed in the PTR.
Both the PTR and the RTF use the WHAM5 method for calculating savings at different
tank sizes.
Cadmus utilized the same methodology for determining annual electricity savings, which were
calculated by tank size using the same base case energy factors as used by the RTF.6 Average
savings for water heaters rebated equaled gross evaluated per-unit water heater savings.
Heat Pumps
Heat Pump Upgrades and Conversions' deemed savings were provided by the Energy Trust of
Oregon.
To determine deemed savings, Cadmus utilized the most recent RTF information available for
these measures. Currently, RTF savings are calculated using SEEM modelingT of single-family
homes, and final savings represent weighted averages of multiple models, using weights
representing the region. Savings determined for this progrulm were associated with Heating
Zone 3.
o http:i/www.ptr.nwcouncil.org
' h1$ut$yst.i..e..lils,.ensr&!:ep.v.!Lu.illingyappLlansq*$.+sd.srdqtesl&ntiai.,:p-dfir.d-:Zp#:
6 http:iirvrvrv.nlvcouncil.org,'energ],',tttl/measuresimeasure.asp?ici:102
7 ttip:ir'wwrv.nrry-qlpncil.o.Eiene'rgy,,-i-'r.[:ms.:qrtjltg5i?0 I I i ii5r'SEEl\4.ziF
The Cadmus Group, lnc. I Hnergy Services Appendix K$
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Roclq Mountain Power
Exhibit No. 5 Page 812 of 1365
Case No. PAC-E-14-07
PBB?',iffS,"2UTT
HP Tune-Up deemed savings for 2009 and 2010 derived from the BPA's PTR.8 Cadmus
determined this method reasonable for calculating savings for this measure, thus utilizing the
same deemed savings values for evaluated gross savings.
Central Air Conditioners and Evaporative Coolers
Deemed savings for central air conditioning (CAC) equipment, proper CAC installation, proper
CAC sizing, and evaporative coolers derived from Cadmus' (as Quantec, LLC) evaluation of the
Nexant Cool Cash program.e Savings for Idaho were determined using a degree day adjustment
to account for climate differences. Cadmus determined this method reasonable for calculating
savings for these measures, and thus utilized the same deemed savings values for evaluated gross
savings.
CAC Tune-Up deemed savings for 2009 and 2010 derived from the BPA's PTR.r0 Cadmus
determined this method reasonable for calculating savings for this measure, and thus utilized the
same deemed savings value for evaluated gross savings.
Duct Sealing
Duct Sealing deemed savings values for 2009 and 2010 derived from BPA's PTR.11 The deemed
value was calculated as 75 percent of savings estimated for duct sealing of a gas furnace and a
CAC system. The 75 percent multiplier was to be the "duct location multiplier," with no further
explanation provided.
Cadmus determined evaluated deemed savings using the most recent RTF values based on
SEEM modeling runs. Evaluated gross energy savings derived from a weighted average of RTF
provided savings, based on HVAC system types and participant locations.
Whole-House Energy Modeling
To independently confirm energy savings resulting from insulation and windows measures
outside of the billing analysis, Cadmus developed a series of building simulations.
PEC! Gross Savings
PECl-developed per measure kWh savings derived from an FY 2007 RTF PTR Software
Version 4.5, found in: Idaho_Unit Energ,t Savings Estimate Savings Summary_2009 & 2010.
These calculated savings usually provided the basis of reported savings, described below. To
veriff these savings, Cadmus developed independent estimates of realized savings.
Cadmus Gross Savings Realized
For all measures, Cadmus used a residential energy simulation model-Architectural Energy
Corporation's Rem-Rate Yl2.96-.to estimate realized savings. (RESNET@ accredits Rem-Rate
for modeling residential homes.)
E http://www.ptr.nwcouncil.org
'2006 Evaportative Cooling and Central Air Conditioning Incentive Program: Evaluation
'o http ://www.ptr.nwcouncil.org
t t http ://www.ptr.nwcouncil.org
The Cadrnus Group, lnc. / Energy Services Appendix K10
Rocky frfiountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 813 of 1365
Case No. PAC-E-14-07
Cg8?t5iii5,'zUTE
Based on surveys, site visits, and the program implementer's measure tracking database, Cadmus
determined a typical home's characteristics, then using these characteristics as inputs into Rem-
Rate (see Table Kl5 and Table K 16). Differences in modeled overall energy use between a
baseline home (such as one with no wall insulation) and an efficient home (after installation of
wall insulation) provided the measure's realized gtoss savings.
Typical Participant Home
For insulation and windows measures developed by the progftrm implementer, Cadmus
developed a typical participant home to use as a base case for each insulation measure upgrade,
when simulating savings for comparison to billing analysis results.
Typical home characteristics derived from the implementer's participant database and survey
information collected through this project. Such a home would be poorly insulated on all
surfaces, and did not represent average pre-participation homes, but, rather, the average
participant surface. As energy savings result from improvements to thermal conductive
properties of homes' surfaces, use of one baseline home proved appropriate. Table K15 shows
the base home's general characteristics.
Table K15. Characteristics of Modeled Homes
Weather location Pocatello,lD Closest available weather file
Home Tvpe Single Family Assumed typical HES participant
Home Conditioned Floor Area 1,820 Square Feet Average Participant Home
Foundation Tvoe 8' uninsulated concrete wall Engineering Assumption
Wdls
R-0 Continuous lnsulation, R-3.4 Cavity
lnsulation, 0.9 inches thick, 16/1.5x3.5,
Wall stud soacino/size
Construction created from the weighted average
participant insulation level reported before
measure installation.
Attic
R-2.7 Continuous lnsulation, R-13 Cavity
lnsulation, 3.5 inches thick, 2411,5x3.5,
Chord rafter spacino/size
Construction created from the weighted average
participant insulation level reported before
measure installation.
Framed Floor
B-0 Continuous lnsulation, R-1.8 Cavity
lnsulation, 0.5 inches thick, 2411.5x11,5,
Floor Joist soacino/size
Construction created from the weighted average
participant insulation level reported before
measure installation.
Windows U-Value 0.49, SHGC 0.58 Matches models previously developed by
imolementer.
lnfiltration 9.84 ACH at 50 Pa Proportional, based on home size, to models
oreviouslv develooed bv the implementer.
Heating System/Cooling
system Varies by model
Equipment sized to 120 percent of the design
heating or cooling load. Efficiencies chosen to
match imolementer assumotions.
Duct Leakage 246 al25 Pa Matches models previously developed by
imolementer.
Thermostat Non-Programmable, Heating 68" F,
Coolino 71 o F
Result of surveys to all home energy savers
participants in the state.
The Cadrmus Group, lnc. i Hnergy Services Appendix K11
Rocky Mountain Power
Exhibit No. 5 Page 814 of 1365
Cese No. PAC-E-14-07
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report #ts?iffT,"2UT?
Table K 16 shows HVAC systems used in the simulations.
Summary of Results
Cadmus simulated surface improvements to various surfaces and to windows. Energy savings
were then determined by comparing the efficient model for the surface analyzed to the base case
home, described above.
Table Kl7 shows base properties and effrcient thermal properties simulated for each surface. The
base and the efficient R-Values represent the savings-weighted average for the participant
population.
able Kl7. Base and Elficient Therma res
lnsulation: Attic 15.7 28.5
lnsulation:Wall 1.8 23.9
lnsulation: Floor 3.4 15.2
Windows 49/58 3432
Table Kl8 shows savings calculated using the simulation runs.
Average energy savings per home were then calculated for homes included in the billing
analysis. Table K19 compares average participant home savings, determined from the billing
analysis, to savings calculated through Cadmus' modeling for the same customers.
Windows: Gross Evaluated Savings
As the billing analysis did not include savings attributable to windows installations, simulation
results were used to determine evaluated savings for this measure. The ratio of billing savings
Table K 16.
Table K18. Simulation Results
Table Kl9. Com Results to M
The Cadrnus Group, lnc. I Energy Services Appendix K12
Rocky Mountain Power ldaho l-'iE$ Evaluation 2CI09-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 815 of 1365
Case No. PAC-E-14-07
Wtness: Kathrvn C. HvmasFebruary 3. 2012
shown in Table Kl9 was used to adjust simulated savings to evaluated gross savings, as shown
in Table K20.
K20.able Evaluated Gross Windows
Electric Furnace Mo CAC 3,11 2.34
Electric Furnace w/ CAC 5.31 4.00
Gas Fumace w/ CAC 2,21 't.66
Otheril CAC 2.21 1,66
Recommendations
Cadmus compared results of simulation-modeled savings to reported savings and the most recent
RTF simulated savings. The RTF (and, therefore, the program implementer) developed weighted
savings estimates from multiple simulation scenarios.
Cadmus developed a single home, representing the participant population in 2009 and 2010. As
inputs to each model were not the same, savings estimated for each scenario were not the same,
though similar.
Table K21 compares savings calculated by Cadmus (using the simulation model) and savings
reported by the progrilm implementer (representing a weighted average of multiple simulations).
In multiple cases, the program implementer used different savings between the two years, and
sometimes within the same year. Table K21 shows the range of savings reported.
Considering the data shown in Table K2I, and the difference between the billing analysis and
simulated savings, Cadmus recommends PacifiCorp use a billing analysis-adjusted version of the
RTF values for estimating gross energy savings for these measures. The program implementer
should weight savings by heating type and insulation level, based on most recent participation.
Cadmus further recommends adding a category for Heat Pump System, for use in estimating
savings. Energy savings occurring at homes heated by air-source heat pumps will differ
substantially from savings for a home using an electric furnace or zonal electric heat.
G
Table K21. Savin
2.16-2.32
The Cadmu$ Group, lnc. i Energy Ser*ices Appendix K13
Rocky Mountain Fower ldaho HES Evaluation 2009-2010 Final Report
Rodry Mountain Power
Exhibit No. 5 Page 816 of 1365
Case No. PAC-E-14-07
Witness: Kathrun C. HvmasFebruary 3. 2012
Appendix L. Waste Heat Factor
The waste heat factor (WHF) is an adjustment representing the interactive effects of lighting
measures on heating and cooling equipment operation. Cadmus did not apply the WHF
adjustment to lighting savings estimates as Rocky Mountain Power did not include it in their
initial planning estimates. However, Cadmus recommends using the following approach for
future planning estimates and evaluations.
Cadmus calculated HES's WHF using ASHRAE data on heating and cooling degree days (HDD
and CDD, respectively) in Rocky Mountain Power's service territory. In addition, Cadmus used
the 2006 Energy Decisions Survey datar to determine the saturation of heating and cooling
equipment types in Idaho.
To determine the portion of the year that heating or cooling equipment operates, and, therefore,
when lighting would affect heating or cooling energy, Cadmus used the Northwest Power and
Conservation Council's workbook used to estimate the interactions for ENERGY STAR lighting
savings in the 6ft Regional Power Plan.2 This calculator estimates the heating and cooling
interaction based on building simulation models for a variety of HVAC equipment and cities
around the region. Cadmus estimated the savings for Pocatello, as representative for the Idaho
territory, by using a weighted average of HDD and CDD from the cities across the region to most
closely match that for Pocatello. This calculator determined the heating and cooling interactions
for zonal heating and heat pumps. To estimate the interaction for electric forced air furnaces, a
heating system efficiency of 75Yo (to account for duct losses) was included. The cooling
interaction from heat pumps was used for all electric cooling systems. These interactions are
provided in the table below:
Table Ll. Interactions
These interactions are then weighted by the market share of the electric heating and cooling
systems.
The heating interaction was calculated as follows:
Heating Interacti.on = -\{Votrrtlnteracti.on * Market Share)i - -L7o/o
Where the summation is over the three electric heating types. In addition,
lhttp:i,'wrvlv.pacificorp"comicontent,'dam,bacificorp,'cloc,'Ilnerg),*Si-rnrces,,'l)emand Siclerlv(anagement;'lJSfo1 Volum
eI ?01 l_Stud.v.pdf
2 http://*ww.nwcouncil.org/energy/powerplan/6/supplycurves/res/Estarlighting_NewFY09v1-0.xls
The Cadmus Group, lnc. i Energy $ervices Appendix L1
Rocky Mountain Power ldaho HES Evaluation 2009-2010 Final Report
Rocky Mountain Power
Exhibit No. 5 Page 81 7 of 1 365
Case No. PAC-E-14-07
CBts?tffT,"2UT?
Cooling Interaction - o/oSpCoollnteraction x Electric Cooling MarketShare = L.Bo/o
Total electric WHF = 1 * Heating Interaction * Cooling Interaction
- t _ t7o/o * 1.Bo/o = 84.30/o
The combined -15.7%o adjustment was applied to electricity savings for all interior lighting
measures to account for a net increase in electric heating and cooling load due to more effrcient
lighting. Weighting for the distribution interior/exterior distribution found in participant surveys,
Cadmus found the final WHF to be 85.0% (as shown below).
Interi.or Total Electrtc WHF
= 1 * (Heating Interaction * Cooltng Interaction) * o/o Interi.or Lighting
= 1 * (-L7o/o * 1.Bo/o) * 95.60/o = 85.070
The Cadmus Group, lnc. ,'Energy Services Appendix L2
Rocky Mountain Power
Exhibit No, 5 Page 81 I of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
wRocKYM0UNTArN
rcF0WER
X A ortlutoN oF PAcrFrcoHP
Exhibit No. 5.10
Refrigerator and Frcezer Recycling Evaluation
20tt-2012
I
Rocky Mountain Power
Exhibit No. 5 Page 819 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
Nmm$*p NmvsmNmNm Nmwms NSmNm
Nmm pm NmNms* rm$sNgwymNmsss
Sssgsffi N\ NwmNusmNNwsN NwpwsN
RSNN-NSRR
tii\si-1sr Ii:, :l$t]
N*cky \\srsutni* S*rver
Tl-re Cedmus ilr*up, Inr:,
Rocky Mountain Power
Exhibit No. 5 Page 820 of 1 365
Case No. PAC-E-14-07
Fr*pnre$ h3*:
Jassst Chrlstensen
Htttily h,$t$ter
3*sl^t ${eel!l'lg
Kstq Sushmtnn
$t*us S.ufer
*"{*ssuivt Flaurio F$t.S.
*mdrnus
Roclry Mountain Power
Exhibit No. 5 Page 82 1 of 1365
Case No. PAC-E-14-07
T'mh$s m$ S*ffites\ts
Summary of Key Findings ........................1
Key lmpact Findings .........................1
Key Process Findings ........................3
Cost-Effectiveness Results ...............3
Summary and Recommendations ..........5
Program Description and Overview................ .................6
Program Participation .........5
Methodo1ogy................. ....................... 10
Sampling Approach .......................1.0
lmpact Estimation Method ............11
Kit Savings Algorithm and Assumptions .......... .....................L2
Evaluated Gross Savings................. ......L4
Gross Annual Unit Energy Consumption................. .............74
Refrigerator Regression Mode1......... ................ 15
Freezer Regression Model .............15
Extrapolation................. ................. 15
Kit Savings .............,.....16
UEC Summary ............... .................16
ln-Service Rates.......... .......L7
Appliance Part-Use Factor .............L7
CFL lnstallation Rate .....................19
Tracking Database Review and Verification ............ ...........19
Freeridership................. .................2L
Secondary Market lmpacts ...........22
lntegration of Freeridership and Secondary Market lmpacts .................23
lnduced Rep1acement................. ......................24
Rocky Mountiain Po\iver
Exhibit No. 5 Page 822 of 1 365
Case No. PAC-E-14{7
Spillover ....................... 25
Final Net-to-Gross......... .....,............ 28
Summary of lmpact Findings...... .........28
Methodo1ogy................. .....30
Program lmplementation and Delivery...... ..............31
Program History Program Management ................. .............31
Program Staffing and Training ........32
Delivery Structure and Processes ............... .......32
Forms and 1ncentives............... .......33
Approach... ...................34
Targeting ..................... 35
Comparison with Nonparticipants .....................35
Customer Response.... ........37
Satisfaction ..................37
Barriers....... .................. 39
Quality Assurance/Quality Contro1................ ...........39
Benchmarking............... ......40
Appendix A: Participant Demographics............. ............46
Appendix B: Precision Calculations ..............48
Appendix C: Participant Survey lnstrument. ...................49
Appendix D: Nonparticipant Survey lnstrument. ............69
Appendix E: Logic Mode1......... .....................76
Appendix F: Refrigerator NTG Combined Decision Tree............ ......79
Appendix G: Freezer NTG Combined Decision Tree ........... ..............80
Appendix H: CFL Engineering Calculations and Assumptions........... ....................81
Waste Heat Factor ..............84
Roclry Mountain Power
Exhibit No. 5 Page 823 of 1365
Case No. PAC-E-14-07
S$*ss*ry s$ Tevms
Analysis of Covariance (ANCOVA)
An ANCOVA model is an ANOVA modelwith a continuous variable added.
Analysis of Variance (ANOVA)
An ANOVA model explains the variation in the independent variable, based on a series of characteristics
(expressed as binary variables with values of zero or one, indicating the absence or presence of the
cha racteristics).
Coefficient of Determination (R2)
The R2 indicates the proportion of variance in a dependent variable explained by a regression equation,
and takes values between zero and one. An R2 of zero indicates that the independent variables have no
explanatory power. An R2 of one indicates that 100% of the variability in the dependent variable is
explained by changes in the independent variables.
Evaluated Gross Savings
Evaluated gross savings represent the total savings resulting from a program, before adjusting for
freeridership or spillover. They are most often calculated for a given measure, 'i,' as:
Evaluated Gross Savingsi = V eri.f ied Participationi * Unit Consumptioni
Evaluated Net Savings
Evaluated net savings are the total savings resulting from a program, net of what would have occurred in
the program's absence. These savings can be attributed to the program, and are calculated as:
Net Savtngs = Evaluated Gross Sauings * Net - to - Gross
Freeridership
Freeridership in energy-efficiency programs is participants who would have adopted the energy-efficient
measure in the program's absence. This is often expressed as the freeridership rate, or the proportion of
evaluated gross savings that can be classified as freeridership.
Gross Unit Energy Savings
For the SYLR program, gross unit energy savings are the evaluated in situ unit energy consumption for
the recycled unit, adjusted for part-use.
ln-Service Rate (lSR)
The ISR (also called the installation rate) is the proportion of incented measures actually installed.
Rocky Mountain Power
Exhibit No. 5 Page 824 of 'l 365
Case No. PAC-E-1447
Net-to-Gross (NTG) Ratio
The NTG ratio is a ratio of net savings to gross savings. Analytically, NTG is defined as:
NTG ratio =
Net savings
Gross savings
Net Realization Rate
The net realization rate is a comparison of evaluated net savings to reported gross savings.
P-Value
A p-value indicates the probability that a statistical finding might be due to chance. A p-value less than
0.10 indicates that, with 90% confidence, the finding is statistically significant.
Part-Use Factor
The part-use factor is the portion of the year that equipment is operating. That is, if a given measure has
a part-use factor of 0.5, it was operational for six months out of the year, on average.
Spillover
Spillover is the adoption of an energy-efficiency measure that was induced by the program's presence,
but was not directly funded by the program. As with freeridership, the spillover rate is expressed as a
proportion of evaluated gross savings.
T-Test
The t-test is a general statistical test of difference. ln regression analysis, a t-test is applied to determine
whether the estimated coefficient differs significantly from zero. A t-test with a p-value less than 0.10
indicates that there is a 90% probability that the estimated coefficient is different from zero.
tv
Roclry Mountain Power
Exhibit No. 5 Page 825 of 1365
Case No. PAC-E-14-07
Sxe*utive $umrmas"y
Rocky Mountain Power contracted with Cadmus to conduct an impact and process evaluation of its See
ya later, refrigerator@ (SYLR) Program for the 2011 and 2072 program years. To evaluate program gross
and net energy savings for the impact evaluation, Cadmus used secondary meter data analysis, surveys
of program participants and nonparticipants, and a review of the program tracking data. To evaluate the
effectiveness of program processes, Cadmus conducted in-depth interviews with program staff involved
in different aspects of the program.
The evaluation data consisted of:
o Telephone surveys with 218 participating ldaho customers;
o Telephone surveys with 51 nonparticipating ldaho customers;
o Review of ldaho program materials; and
o ln-depth interviews with program management and program administrator staff.
Scssttmmrpu *$ N*y Ssst$sstgs
${*y lmpast S$mS$m$s
The key impact evaluation findings are:
o ln 20L1, the SYLR Program recycled 7L0 refrigerators and freezers and distributed 460 energy-
savings kits; in 2012, participation decreased to 561 total units and 42L energy-savings kits.
o The part-use factor (portion of the year that the equipment is in operation) for both
refrigerators and freezers fell within expected ranges at 0.84 and 0.93, respectively.
o After adjusting for part-use, the gross per-unit savings were 7,022 kWh for refrigerators and
1,033 kwh for freezers.
o The net per-unit savings were 550 kWh for refrigerators and 492 kWh for freezers. These values
are lower than the evaluated per-unit savings for 2009-20L0,1 primarily due to changes in the
evaluation methodology.2
o The overall NTG increased from 49%in the 2009-2010 evaluationto 52%.
o Gross savings for energy-savings kits (47 kWh) were 36% lower than the reported per-unit
savings of 74 kWh.
o Participants reported installing 73% of the compact fluorescent lamps (CFLs) provided in the
energy-savings kit offered through the program. ln addition,TSYo of surveyed participants
recalled receiving the kit containing CFLs.
The evaluated per-unit net savings in the 2009-2010 evaluation were 578 for refrigerators and 589 kWh for
freezers, with NTGs of 49o/o and 57Yo, respectively.
See the lmpact Estimation Method section for more detail.
Rocky Mountain Power
Exhibit No. 5 Page 826 of 1 365
Case No. PAC-E-14-07
Table 1 summarizes program participation, gross savings (reported and evaluated), and evaluated net
savings for 2011 and2OL2.3 Table 2 and Table 3 show savings for each program year.
Txb$s 1. 3$\t **S [$iR Fr*gr-tn-l $*vings hy N$e*sur*
i Refrigerator
' Recycling
, rt""i"t.
: Recycling
t,034
337
t,226,921
360,242
1,055,959
348,193
86%
97%
569,193
165,719
46o/o
46%
47%
i6}{
Energy- )
Savings Kit :
ll.'jffii.:.:
Refrigerator
Recyc!ing
Freezer
l::v:!ilq
Energy-
Savings Kit
....',.,.,,: . , .fOi i
93,197 | 44,247
'''''''':::::' : : ::::':: :1:6$$j!6il,'...,',.r'.'l'#9i$ 8
47o/o 44,247935
1,3[6
542
168
488
l-*9S,:,:
641,44!
L84,3L3
48,501
87dtilS5
554,034
173,580
23,Ltt
*$'ur?a$
SES',',.'i
85%
94o/o
48%
Efi$S
77Sj:t5t
298,358
82,6t4
23,1\t
$.$4jES$
47o/o
45%
48o/o
$s?6
3 Throughout this report, the table totals may not sum due to rounding. Precision estimates, for means and totals
(such as savings) are expressed in relative terms, while those for proportions and ratios (such as NTG) are
expressed in absolute terms.
Tshls R. R$XX Sr*grmr$\ Ssvin$$ hy N.$*asure
Refrigerator
Recycling 492 585,480 502,924 860/o 270,835
Roclq Mountain Power
Exhibit No. 5 Page 827 of 1365
Case No. PAC-E-14-07
460/o
: Freezer
; Regvcl!ns
i Energy-
159
447
1rtr0S,,,,,,,,
L75,929
44,696
774,6t3
21,135
99%
47%
83,105
21,135
47o/o
47%Savings Kit
rot$l 806,105 59S;67I 3IS;875
N*y Sr**ess FimSings
The following are the key process evaluation findings:
o Collaboration between Rocky Mountain Power and the program administrator proved effective,
due to a longstanding working relationship. Program staff reported effective communication
and smooth implementation.
Participant satisfaction was high in 2011 and 2OL2 program years: 98% of the surveyed
participants reported being very or somewhat satisfied with the program. An overwhelming
majority of participants expressed satisfaction with the program sign-up process and incentive
levels. The survey did not reveal notable complaints.
Participants learned of the program through various channels, the two most common being bill
inserts and word-of-mouth. The online sign-up process and the telephone sign-up process both
proved simple and easy to understand, and participants reported high satisfaction levels with
both channels.
Smst-Sffqqtit,*r'lsss R*su lts
As shown in Table 4, the program was cost-effective across the evaluation period according to four of
the five primary cost-effectiveness tests: PacifiCorp's Total Resource Cost (PTRC) test, Total Resource
Cost (TRC), Utility Cost Test (UCT), and Participant Cost Test (PCT).
The program was cost-effective with benefit/cost ratios of L.72 and 1.57 from the PTRC and TRC test
perspectives. The SYLR program was not cost-effective based on the Ratepayer lmpact Measure (RlM)
test.a
' The RIM test is included as a measure of the program's impact on all ratepayers, and it is common for
demand-side management (DSM) programs to have a RIM ratio of less than one. The ldaho Public Utilities
Commission (like most other regulators) does not require DSM programs to pass the RIM test.
Tah$s $" t$t} Fr*gram Scrr$srgs hy N$easure
Roclry Mountain Power
Exhibit No. 5 Page 828 of 1 365
Case No. PAC-E-14-07
PTRC
TRC
UCT
nrM
0,049-5
i
0,0a95
|
0.0495 :
s2o3ro?g
s2o3f028
s2031028
isa+1aa
So
Sls-oroos
S318,186
s3181186
s31q.185
s7t9,259
Srao,szo
I
s11s,1s7 :
S11s,1s7
1
-121-6:!92 i
57!9,259 i
1..7.2
1.57
-tf7
0.55
Ni;PCT
Table 5 and Table 5 show the program's cost-effectiveness for the 2011 and 20!2 program years,
respectively. The 2012 program year shows higher benefit/cost ratios because longer measure lives
were used for the 2012 analysis in order to maintain consistency with Rocky Mountain Power's annual
reports.
PTRC 0.0543 s107,033
TRC 0.0543 s107,033 s14s,319
0.0543 s1o1o33
5 _267,7:s',8-
So
5141r319
s14s1319
s315,895
l?03:799
i18sr292
S18sr262
5t85,262
543tlt4.
ls_181-8
Ssa,zgg
s38128
-Sr..zr,sas
S316,895
1-:19
1-,-3-9
1-:36
0.54
N/A
UCT
RiM
icr
Tuhl* $. R$tt Sval*ated Fr*grar* {*st-Hff*cti\rsnsss Sr*r*s"r"lsry
0.0451 119?,97-8
119?,92-8
l!:021878
s318,84-1
SO
S1oo,91o r
s82,383
1.98
1.80-9:-9f-i1
0.0451 s8_2r383
;5-r1a-,s-s-o
$43!,2t4
1:80
0.58
NIA
Tabl* $" RStl r*S 3$3$ Svaluated Fnogrnrn $cst-Sffectivs$ss$ Suntmxry
Tah$s 5" t$t\ Svai*r*tod Fr*grorx {*st-Sfteuti\rensss Sumrsrrsrp
Rocky Mountain Power
Exhibit No, 5 Page 829 of 1 365
Case No. PAC-E-14-07
$sssstmmry sn$ Ssssr??itts$tdsft*ms
Although participation was slightly lower than expected in both 2011 and 2012, the SYLR Program ran
smoothly with no major implementation issues, and experienced high customer satisfaction. The
program cost-effectively achieved net savings of 779,159 kWh over the two-year period.
Based on evaluation results, Cadmus offers the following recommendations:
r Rocky Mountain Power should consider adjusting its expected per-unit savings for future
program years to reflect the evaluated per-unit gross savings values of 7,022 kWh for
refrigerators, 1,033 kWh for freezers, and 47 kWh for kits, as found in this evaluation.
o The program administrator and Rocky Mountain Power should continue with to improved
tracking of energy-savings kit delivery, including recording whether or not a kit was delivered.
This change has already been implemented beginning in 2013.
o Rocky Mountain Power should consider revising the measures provided in the kits, as the Energy
lndependence and Security Act of 2007 (EISA) standards in 2014 will lead to decreased savings
for 50-watt replacement CFLs. lf kit measures are revised, Rocky Mountain Power should update
expected per-unit savings for kits accordingly.
o For future cost-effectiveness calculations, Cadmus recommends that Rocky Mountain Power
update measure lives to align them with the values adopted in the most recent Regional
Technical Forum (RTF) measure workbooks:
r Refrigerators: 7 yearst
. Freezers: 5 years
. CFLs (kits): 6 yearst
Refrigerators and freezers found in:
http://rtf.nw council.orgl lmeasures/res/ResFridgeFreezeDecommissioning_v2_5.xlsm
CFLs found in: http://rt{.4.:ry..c_q.ur]lil.o!'el$gasuI.es/res/Res-CtLliqhtine vZ 2.xls.rn
Roclry Mountain Power
Exhibit No. 5 Page 830 of 1 365
Case No. PAC-E-14-07
Sr*grarm Ses*n$ptlon and Sverulew
The ldaho See ya later, refrigerator (SYLR) residential refrigerator and freezer recycling program serves
as part of Rocky Mountain Power's ongoing demand-side management (DSM) resource acquisition
strategy.T Rocky Mountain Power's overarching objective with the program is to decrease electricity
usage (kWh) by removing and recycling inefficient secondary refrigerators and freezers and older
primary refrigerators. The program encourages those shopping for replacement units to consider
ENERGY STAR@-labeled models, and refers them to the Home Energy Savings (HES) Program, where they
may be eligible for incentives for other energy-efficiency measures and services. ln addition to reducing
energy consumption and lowering participants' electricity bill, participating appliances are rerycled in an
environmentally sound manner. t
ln operation since 2005, the SYLR Program provides residential customers with a S30 incentive for each
recycled appliance. Participants receive an incentive for up to two refrigerators or freezers. Renters who
own their appliances may participate, and apartment complex owners or managers who provide tenants
with appliances are eligible. Participants also receive an energy-savings kit, which includes: two 13-watt
CFLs, a refrigerator/freezer thermometer card, energy-savings educational materials, and information
on other Rocky Mountain Power residential efficiency programs.
Qualifying refrigerators and freezers must be in working condition when picked up and be at least 10
cubic feet in size. Rocky Mountain Power contracted with JACO Environmental, lnc. (the program
administrator) to implement the program in ldaho. The program administrator disables and removes the
appliances, and recycles at least 95% of the materials, including the refrigerant.
$r* grrssm $*'sSfcfpm$rslt
Participation in the SYLR Program tends to be seasonal, with the highest participation during summer.
As shown in Figure 1, the SYLR Program saw a steady increase in participation from spring through
summer.
See ya later, refrigeratoro has been registered to Pacificorp through the U.S. Patent and Trademark Office
since April 6,2010, under registration number 3770705.
Environmentally-sound disposal of this equipment includes: proper disposal of oils, polychlorinated biphenyls
(PCBs), mercury, and chlorofluorocarbon-11 (CFC-11) from foam; and recycling of CFC-12, hydrofluorocarbon-
134a (HFC-134a), plastic, glass, steel, and aluminum.
6
Rocky Mountain Power
Exhibit No. 5 Page 831 of l365
Case No. PAC-E-14-07
$igure \. Sr*gr**'r Ssrtiripation hy $\$*ntl: and Yesr
MAY
r::i2011 Ztjlz
Figure 2 shows the program's seven-year trends in program units' age and size. During this period, the
average unit age and size has had an upward trend, with some variation over time.
$igus* t" As*v*t$s \.S*lt A$s *nd Sin* h\, \'esr
20
18
16
14
12
10
I
6
4
2
U
The refrigerator configurations of program units also changed, with single-door units becoming more
common from 2009 to2012 (Figure 3).
cl.E 1s0
EE roo
5B
G
aNa
45
40
35
^306
E2s
o2Ob8-15
10
5
o
Fig*rs $. R*$rig*rat*r eo*figuration hy Yuar
Rocky Mountain Power
Exhibit No. 5 Page 832 of 1 365
Case No. PAC-E-14-07
N* Top Freezer
i:rir Single Doofr
m Side-by-Side
m Bottom Freezer
10a%
9ff/a
807o
7ff/o
60%
507o
40o/5
30u/o
2ff/a
Lffo
AYo
2010 2011
I.*.*....*...........**........*...i
As shown in Figure 4, freezer configurations did not exhibit an appreciable trend from 2006 lo 20L2.
$igsr* $. $r**r*r fl*nfigurstion hy Yssy
100%
9096
8O7o
70%
60%
s0%
4tr/o
3OYo
Z$r'o
1Otso
a%
N Upright
s Clrest
2006 2ffi7 2008 2089
These trends are consistent with Cadmus' observations of other recycling programs. As recycling
programs mature, the composition of recycled appliances tends to change. ln their infancy, these
I
Rocky Mountain Power
Exhibit No.5 Page 833 of 1365
Case No. PAC-E-14-07
programs recycle more secondary appliances (particularly those in use for only a portion of the year).
Such units tend to be older, smaller, and located in unconditioned spaces, such as garages or
basements. They also tend to be less efficient.
Rocky Mountain Power
Exhibit No. 5 Page 834 of 1 365
Case No. PAC-E-14-07
Nmpa*t Suem$u*t$mn
$Me$$rs$mfsg$,
This section describes the methodology Cadmus used to evaluate the program's impact. The report
presents two types of evaluated savings: evaluated gross savings and evaluated net savings. To
determine these values, Cadmus applied four steps (shown in Table 7) to the reported gross program
savings. The evaluation defined reported gross savings as electricity savings (kwh) that Rocky Mountain
Power included in its 2011 and20L2 annual program reports.
1i
3
Verify accuracy of data ln program database
Eva luated Gross Savings Perform statistical/engi""eii"i r".tviiii" "ritrri" p"i-r"ii r#;;
Er.t"riea rueiia;ift;
Adjust evaluated gross savings with installation rate/part-use factor
Apply net-to-gross adjustments
Step one (verifying the accuracy of data in the program database) included reviewing the program
tracking database to ensure that participation and reported savings matched the 2011 and 2012 annual
reports.
Step two (performing a statistical/engineering analysis to evaluate per-unit savings) involved estimating
refrigerator, freezer, and CFL savings.
Step three (adjusting the evaluated gross savings with the installation rate/part-use factor) determined
the mean proportion of the year in which recycled appliances were used, as well as the number of CFLs
program participants installed. Using a telephone survey, Cadmus collected information to estimate an
installation rate and part-use factor, which Cadmus then used to calculate evaluated gross savings.
Step four (applying net-to-gross INTG] adjustments) determined the net savings. Through participant
and nonparticipant telephone surveys, Cadmus estimated freeridership, secondary market effects (i.e.,
the program's impact on the availability of used appliances), induced replacement, and spillover.e
$ump$ivlg Appr*n*$'l
Cadmus developed survey samples of randomly selected program participants and nonparticipants,
seeking precision of !L0% at the 90% confidence level at the measure level. The evaluation determined
sample sizes assuming a 0.5 coefficient of variation (CV). Cadmus applied a finite population correction
to determine the necessary sample size. Table 8 shows the planned and achieved sample sizes by target
group.
Tsh$s T. impact $stin'lsti*n Stsps
t This report's Net-to-Gross section provides a detailed description of how Cadmus estimated these parameters.
Rocky Mountain Power
Exhibit No. 5 Page 835 of 1365
Case No. PAC-E-14-O7
T*h$e $" Ssnrp$* $la*s hy T*rg*t $ro*p
lartj:ieag: iNonparticipants i N/A 70i 51
*Due to the small population, Cadmus was unable to attain the target number of completed surveys. However, all
efforts were made to attain the target without placing undue burden on customers: up to five attempts were
made to reach each participant, and (as described below) surveys were conducted in three rounds to capture
feedback close to the time of participation.
Cadmus randomly selected 218 survey participants from the population of L,377 unique participants.
Participant surveys were conducted in three rounds:
. Quarters 1 and 2 of 207L;
r Quarters 3 and 4 of 20Lt; and
. Quarters 1 through 4 of 20L2.
This approach allowed Cadmus to provide Rocky Mountain Power with interim results from the 2011
surveys, as well as ensuring that customers were contacted close to the time when they participated in
the program. All results presented in this report are weighted to reflect the distribution of participants
across the evaluation period.
Cadmus selected the 51 nonparticipants through screening questions that were asked from a random
sample of Rocky Mountain Power customers residing in ldaho. For this evaluation, nonparticipants are
defined as customers who had recently disposed of a refrigerator or freezer outside of the Rocky
Mountain Power program.
inrpast $sti snnt$*n $Vtqth*$
Cadmus' impact evaluation methodology for the 20tL-2O12 program years was informed by recent
guidelines developed by the U.S. Department of Energy (DOE). ln 2011, DOE launched the Uniform
Methods Project (UMP) with the goal to "strengthen the credibility of energy savings determinations by
improving EM&V, increasing the consistency ond tronsparency of how energy sovings ore determined."Lo
The UMP identified seven common residentialand commercial DSM measures and enlisted a set of
subject matter experts to draft evaluation protocols for each measure or subject area. Refrigerator
recycling was one of the seven identified measures. The DOE recruited Cadmus to manage the UM P
process, as well as be the lead author, for the refrigerator recycling protocol.
Through a collaborative process that included reviews by a technical advisory group and a steering
committee, as well as a public review and response period, the UMP resulted in a set of protocols that
10 U.S. Department of Energy. "About the Uniform Methods Project." Last modified January 21,2013. Accessed
June 4, 2013. http:,//wwwl.eer"e.enerev.sov/office eere/de ump about.html.
LL
Rocky Mountain Power
Exhibit No. 5 Page 836 of 1 365
Case No. PAC-E-14-07
capture the collective consensus of the evaluation community. Each protocol establishes broadly
accepted best practices for evaluating the key measures in the category, including identifying and
explaining key parameters, data sources, and gross- and net-related algorithms.
This evaluation follows the methodology outlined in the refrigerator recycling protocol, which largely
mirrors the method Cadmus used for evaluating the 2009-2010 SYLR program, with the changes
recommended by UMP. The most notable changes between the 2009-2010 Cadmus SYLR impact
evaluation and the 2077-2OL2 evaluation methodologies are outlined below. Each is discussed in greater
detail in the Evaluated Gross Savings and Net-to-Gross sections.
1. Prospective Port-Use. UMP recommends that part-use be assessed based on how the recycled
appliance would likely have been used if not recycled, rather than how it was previously used.
For example, if a primary refrigerator would have become a secondary refrigerator independent
of the program, its part-use should reflect the average usage of secondary refrigerators and not
primary refrigerators.
2. lnduced Replocement. UMP recommends that appliance replacement is unavoidable and
naturally occurring. As a result, program savings should notbe estimated as the difference in
energy consumption between the recycled appliance and the appliance that replaces it. The
exception to this rule is when recycling programs induce a replacement that otherwise would
not have occurred.
3. Secondary Market lmpocts. UMP considers the program's impact on the used appliance market.
The secondary market impact adjustment accounts for changes in the availability of used
appliances due to the program. Therefore, in this impact evaluation, Cadmus accounted for the
program's impact on the used appliance market.
4. Regression Model Specification. UMP stipulates a model specification for estimating each
appliance's annual energy consumption when it is not feasible to use utility-specific in situ
metering and modeling. The UMP model reflects the availability of more winter metering data
and the need to create a more universal and weather symmetrical model (i.e., one that accounts
for the effects of heating and cooling degree days [HDDs, CDDs]).
More information about UMP is available on the DOE's Website.ll
Kit S*vis'rgs Algorithm snS Ass$Nspti*ns
With each appliance pick up scheduled, participants received an energy-savings kit, which contained:
o Two 13-watt CFLs;
o One refrigerator thermometer; and
o Energy-savings educational materials and other program references.
t' U.S. Department of Energy. "Uniform Methods Project for Determining Energy Efficiency Program Savings."
Last modified April 9,2013. Accessed June 14,20L3. http:,/lwwwl.eer:e.enersv.eov/office eere/cie umn"html.
12
Rocky Mountain Power
Exhibit No. 5 Page 837 of 1 365
Case No. PAC-E-14-07
The following algorithm estimated CFL savings:
Evaluated Per Untt Sautngs (kwhper unit) =
LWatts,* I.SR * HOU x WHF * 365
1,000
Where:
AWatts =
ISR =
HOU =
WHF =
365 =
1,000 =
Wattage of baseline bulb minus wattage of kit CFL
ln-service rate, or the percentage of units installed
Hours-of-use (per day)
Waste heat factor, adjustment to account for lighting impacts on HVAC
consumption
Constant for days per year
Constant for conversion of watts to kilowatts
The ISR captured CFLs installed, removed, and replaced by other energy-efficient light bulbs. Specifically:
cFL In - Service Rate (lSR oro, - Installed - Removed or Replaced
Reported
Cadmus estimated the baseline wattage by comparing the lumen output of kit CFLS to their
incandescent equivalents. Each 13-watt CFL within the kit has 900 lumens of output. The baseline
incandescent equivalent wattages are determined based on the lumens output of the bulb.
A 50-watt incandescent bulb has a range of 750-1,049 lumens,t' which is within the range to be
equivalent to the 13-watt kit CFL. Cadmus chose to use 50 watts as the baseline because it is the
incandescent bulb of equivalent lighting output.
Cadmus calculated average HOU using ANCOVA13 model coefficients, estimated from a combined
multistate, multiyear database of light logger data, compiled by recent Cadmus CFL HOU studies. This
model expressed average HOU as a function of room type, existing CFL saturations, and the presence of
children in a home. Appendix H provides a more detailed exploration of the impact methodology used to
estimate CFL HOU.
Congress signed EISA into law on December L9,2007. The new law contains provisions for phasing in more
efficient incandescent lamps based on rated lumens. The 60-watt incandescent bulb lumens ranges were
based on rated lumen ranges as defined by EISA.
ANCOVA, or analysis of covariance, refers to a type of statistical modeling.
rz
13
L3
Rocky Mountain Po/ver
Exhibit No. 5 Page 838 of 1365
Case No. PAC-E-14-07
The values for all explanatory variables were based on response data from the participant survey, except
for CFL saturation. Data on CFL saturations were taken from the Northwest Energy Efficiency Alliance
2011 residential building stock assessment.to Figure 5 shows distributions of bulbs by room types.
Figure $. Losation cf $u|hs lnstalle$
F Livring Space
s Kitchen
iiii Basement
s Outcloor
rr,l Bedroorn
I Bathroom
ffi Other
$r.us$s s $ss* Sr*ss Ss rsss.l gts
Snsss Ammusl ltrnit Sn*rgy SsnsumptiCIrt
Cadmus used the UMP-specified regression model to estimate the unit energy consumption (UEC) for
refrigerators, and followed the UMP recommendation to use a similar modelto estimate freezer UEC.
The coefficient of each independent variable indicates the influence of that variable on daily
consumption, holding all other variables constant.
o A positive coefficient indicates an upward influence on consumption
o A negative coefficient indicates a downward effect on consumption
The value of the coefficient indicates the marginal impact of a one-point increase in the independent
variable on UEC. (For instance, a 1-cubic foot increase in refrigerator size results in a 0.059 kWh increase
in daily consumption.)
14 Northwest Energy Efficiency Alliance. 2071 Residentiol Building Stock Assessment: Single-Fomily Chorocteristics
and Energy Use. Septemb er 18, 2072. hltp:/lng.eg.g.rqldo_g:lreneflp/fesiden.t!.e!:.b. uildjrjg*J.q._c.k;a.::.e.lsmen}:
sinele-fa milv-cha racteristics-a nd -energv-use.pdf?sfvrsn=8
14
Roclry Mountain Power
Exhibit No. 5 Page 839 of 1365
Case No. PAC-E-14-07
ln the case of dummy variables, the value of the coefficient represents the difference in consumption if
the given condition is true. For example, in Cadmus' refrigerator model, the coefficient for the variable
indicating whether a refrigerator was a primary unit is 0.560; this means that, all else being equal, a
primary refrigerator consumes 0.560 kwh more per day than a secondary unit.
Se$rig*rator Negressien M*Sel
Table 9 shows the UMP model specification Cadmus used to estimate annual energy consumption of
refrigerators in 2011 and20!2, along with the model's estimated coefficients.
nt \fariahl* * Auersss Sally k\Sl"l. S-squars = $.$$l
i ltst*Pl
I Age (years)
0.805 0.165
0.021 0.152
l-?"Yrrr:,*niilr"gi;"i??i -i Size (cubic feet)
i:9-9-01-,
<.0001 :
0.560 0.008
-0.040 0.001
0.025 0.188
$reeper R*gnessi*m Ntsdei
Table 10 details the final model specifications Cadmus used to estimate the energy consumption of
participating freezers, along with the results.
TmSl* S.$. SrErsrx*r \3S{ N*gr*ssissr $S*Se$ $stisnates
{S*p*r:$*nt \islishls = A$*rege $sily tt\&J}'1. N-squar* * $.i}$}
Sxtrapci*ti*sn
After estimating the final regression models, Cadmus analyzed the corresponding characteristics (the
independent variables) for participating appliances (as captured in the program administrator's program
database). Table 11 summarizes the program averages or proportions for each independent variable.
1.035 <.0001
f*bl* $. R*frig*rat*r llSS Regnessl*n tr\$o$sl Sstinrnt*s
75
FreezeriF
Rocky Mountain Power
Exhibit No. 5 Page 840 of 1 365
Case No. PAC-E-14-07
25.42.
Dummy: Manufactured Pre-1990
Refrigerator
i Dummy: Primary 0.57 i
i lnteraction: Unconditioned Space x HDDs*
: lnteraction: Unconditioned Space x CDDs* i 0.28 i
ffi;"'Cht"d .*raC" fr"rn Typi.rl M"t"".l"Ci*lY"rr' (TlVlY3) drt, f"^r"rth;;Gti"*
that Cadmus mapped to participating appliance ZIP codes. TMY3 uses median daily values for a variety of weather
data collected from 1991-2005.
To estimate the average annual UEC, Cadmus applied the model coefficients to the independent
variables. For example, using values from Table 10 and Table l-1., the estimated annual UEC for freezers
can be calculated as:
Freezer UEC = 365 days
* (-0.955 + 0.0454 * 134.28 years oldl + 0.543
* l\2o/o ttni"ts manuf actured pre - 19901 + A.Lz * 177.7L f L3 ) + 0.298
* l30o/ounits that are chest freezersl - 0.031 x [7.81 HDDs) + 0.082
x [0.28 CDD)) = 7,L!l kW
l{it $av}ngs
Table 12 shows final inputs and gross savings estimated for CFLs distributed in the energy-savings kits.
L$$*i $gl$.tft15F$
Table 13 reports the evaluated average annual UEC for refrigerators and freezers recycled through the
SYLR Program during 2011 and 20\2.The section following the table describes adjustments Cadmus
made to these estimates to determine the gross per-unit savings estimates for participant refrigerators
and freezers.
T*hle I"3. 3$11-3$te Farticip*nt Mean Sxplanat*ry Variahles
T*hle tt" u*n*dj*sst*$ {$}- Suvl*gs {N*t l**$uSi$$ ASjirst$r'\snt .$*r In-S*ruie* Rete}
16
Rocky Mountain Power
Exhibit No. 5 Page 841 of 1365
Case No. PAC-E-14-07
Freezers t,7tt i''''''':47i: Energy-Savings Kits
$m-Ssrxssss Ss$'ss
Sppl i*n*s S*rt-["ts* S*qt*r
Participants used some of the refrigerators and freezers recycled through the program for part of the
year. Cadmus calculated a weighted average part-use factor, representing the three participant usage
categories (operated year-round, operated for a portion of the preceding year, or unplugged and not
operated), as defined by the appliance's operational status during the year before it was recycled. For
example, Cadmus gave participants who did not use their appliance at all the year before it was recycled
a part-use factor of zero, as no immediate savings were generated by their appliance's retirement.
Using information gathered through the participant surveys, Cadmus took the following steps to
determine part-use, as outlined in UMP.
1. Cadmus determined whether recycled refrigerators were primary or secondary units. Cadmus
considered all stand-alone freezers as secondary units.
2. Cadmus asked those participants who indicated they had recycled a secondary refrigerator or
freezer if the appliance had been operated year-round, operated for a portion of the preceding
year, or unplugged and not operated. Cadmus assumed that all primary units were operated
year-round.
3. Cadmus asked participants who indicated that they only operated their secondary refrigerator
or freezer for only a portion of the preceding year to estimate the total number of months the
appliance was plugged in. This allowed for calculating the portion of the year for which the
appliance was in use. Cadmus determined that the average secondary refrigerator and freezer
operating part-time had part-use factors of 0.28 and 0.37, respectively.
These three steps resulted in information about how refrigerators and freezers were operated prior to
recycling (Table 14).
Tahle 3$. Sstimatss *f Fer-LJ*it Ansrual Snengy $unsunr5rtiun
77
Roclq Mountain Power
Exhibit No. 5 Page 842 of 1 365
Case No. PAC-E-14-07
Tahle 1$"
i Average
{PriIn**::,ati,:::::::::::::::::,: Ii
iiise{$;rrda =}:=.....::,I ii Not in Use i
,Io-l,r-u."--i*-* 3% i o-:00i -- ^-**--.^
i weighted i tooyo 1 o.r, i sM
r-59 npS?
Nist*vi*al F*vt-\Jse Fsst$r$ by Sat*$*rV
; uya ftrt rjle
i u-:"9llI'l_"
I Weighted
i Average
L7%0.28 :i 8!o/o , r.oo i t,zt7 i 89% r.oo i t,ttt 1
i:i:::i tO}% : O.SS i t,o+g i IOOq'o : O.go i t,OgS i
Next, Cadmus asked surveyed participants how they would likely have operated their appliances had
they not recycled them through SYLR. For example, if surveyed participants indicated they would have
kept a primary refrigerator independent of SYLR, Cadmus asked whether they would have continued to
use the appliance as their primary refrigerator or if they would have relocated and used it as a
seconda ry refrigerator.
Cadmus then combined the part-use factors listed in Table 14 with participants' self-reported action had
the program not been available. This resulted in the distribution of likely future usage scenarios and
corresponding part-use estimates. The weighted average of these future scenarios, shown in Table 15,
produced SYLR's 2Afi-2012 part-use factor for refrigerators (0.84) and freezers (0.93).1s
Since the future usage of discarded refrigerators is unknown, Cadmus applied the weighted average part-use
value of all refrigerators that would have been discarded independent of the program (0.85). This approach
acknowledges that the next owner of discarded appliances might use them as primary or secondary units.
18
Roclry Mountain Power
Exhibit No. 5 Page 843 of 1 365
Case No. PAC-E-14-07
Kept (as primary unit)1.00 3%
Primary Kept (as secondary unit)0.78
i i ?i:"19:9 j
i Secondary Kept
0.85 i 37o/o
o.7a , tgi;i
. 0.86 3t%
0.93
Discarded
*Sl- tnsta$**tt*n Nute
On average, survey data indicated participants initially installed 1.45 of the two bulbs received, resulting
in a73% installation rate. This is slightly down from the 84% found in the 2009-2010 evaluation. Figure 6
shows the proportion of participants installing zero, one, or two bulbs.
N*mher st Sullrs InstalleS
Trsck$ r'lg Sstm h*r se R*visw a n$ \teri$icntl*n
The program administrator tracked and provided Cadmus with three types of program data:
1,. Data on recycled appliances (stored in a "Units" database);
2. lnformation about appliance pick ups (stored in an "Orders" database); and
3. Data about customers (stored in a "Customers" database).
These integrated databases allowed the program administrator to record information collected via the
call center or Website, along with on-site data collected during pick ups and post-pick-up data recorded
T*Nle LS" Ssrt-Us$ Fast$$s by Npplin*ce Typ*
$igusrs $.
19
Rocky Mountain Power
Exhibit No. 5 Page 844 of 1 365
Case No. PAC-E-14-07
during recycling. The program administrator's client Web portal provided the Rocky Mountain Power
program manager with real-time access to collected data and other program results.
Cadmus reviewed the program administrator's databases and compared participation recorded in the
databases with the participation reported in Rocky Mountain Power's annual reports. Reported
quantities matched the database, as shown in Table 15 below.
tJenJissts'*m sf, St Secipie* ts
The program administrator's database did not include records on the energy-saving kits reported.
Therefore, Cadmus used its participant survey to verify the receipt of kits. There was a discrepancy
between the number of reported and verified energy-savings kits. Approximately 25% of survey
respondents did not recall receiving the kit when their appliance was picked up.
Cadmus identified this low recall issue in the preliminary analysis of the 2011 participant survey. To
ensure the low recall was not due to how the survey was worded, Cadmus added a screening question
to the participant survey to ensure that the person who was present when the appliance was picked up
was the same person who took the survey. This ensured that a respondent who did not recall receiving a
kit was actually present when the kit was provided. Cadmus also interviewed the program administrator
facility manager to assess any possible process changes that might have explained the discrepancies.
This interview yielded no explanation for the fact that only 75% of participants reported receiving a kit,
although the manager did mention that some customers decline kits at pickup.16 Therefore, Cadmus
applied an adjustment to the number of verified kits based on the survey.
Table 15 outlines the reported and verified measure quantities.
f-qfiie-"Je-!g-r
ft:"lqr:
Energy-
Savings Kits
542 492 1,034 : L,O34
327
0%:
oYy
26%
158
I
558 l
15-e 16?
504 447
337 : 337
i
1,262 | 935
N*$-S*s-Srmss
Cadmus used the following formula to estimate net savings for recycled refrigerators:
Net sauings = Gross Savings - Freeridership and Secondary Market lfiLpacts
- Induced Replacement * Spillouer
tt The Process Evaluation discusses additional tracking of kit receipt, which was implemented beginning in 2013.
Tabl* t$. $$13 am$ SSSI Rep*rte$ snS \t*ri$is$ lV$*asure Susrrtitiss
20
Roclry Mountain Power
Exhibit No. 5 Page 845 of 1365
Case No. PAC-E-14-07
Where:
Gross Savings
Freeridership ond
Secondory Market lmpocts =
lnduced Replacement
Spillover
= The evaluated in situ UEC for the recycled unit, adjusted for
part-use;
Program savings that would have occurred in the program's
absence;
Average additional energy consumed by replacement units
purchased due to the program;
Non-programmatic savings induced by the program.
Applying the UMP protocol introduced an additional parameter related to net savings-secondary
market impacts-and requires a decision-tree approach to calculating and presenting net program
savings. Cadmus did not follow this approach for the 2009-2010 impact evaluation.
The decision tree-populated by the responses of surveyed participants-presents savings under all
possible scenarios for participants' actions concerning the discarded equipment. Cadmus used a
weighted average of savings under these scenarios to calculate the net savings attributable to the
program. Throughout this chapter, specific portions of the decision tree are included to highlight specific
aspects of the net savings analysis. Cadmus also provided the entire decision trees in Appendix F
(refrigerators) and Appendix G (freezers).
Freeri$*rship
The first step of the Cadmus freeridership analysis was to ask participants if they had considered
discarding the participating appliance prior to learning about the program. lf the participant indicated no
previous consideration to dispose of the appliance, Cadmus categorized them as a non-freerider and
excluded them from the subsequent freeridership analysis.
Next, Cadmus asked all the remaining participants (i.e., those who had considered discarding their
existing appliance before learning about SYLR) a series of questions to determine the distribution of
participating units likely to have been kept versus discarded absent the program. There are three
possible scenarios independent of program intervention:
1. Unit is discarded and transferred to someone else.
2. Unit is discarded and destroyed.
3. Unit is kept in the home.
2L
Roclq Mountain Power
Exhibit No. 5 Page 846 of 1 365
Case No. PAC-E-14-07
To determine the percentage of participants in each of the three scenarios, Cadmus asked surveyed
participants about the likely fate of their recycled appliance had it not been decommissioned through
the SYLR Program. Cadmus categorized their responses into the following options:
o Kept the appliance.
o Sold the appliance to a private party (either an acquaintance or through a posted
advertisement).
o Sold or gave the appliance to a used appliance dealer.
o Gave the appliance to a private party, such as a friend or neighbor.
o Gave the appliance to a charity organization.
o Left the appliance on the curb with a "Free" sign.
o Had the appliance removed by the dealer from whom the new or replacement refrigerator was
obtained.
o Hauled the appliance to a landfill or recycling center.
o Had the appliance picked up by local waste management company.
Once Cadmus determined the final assessments of participants' actions independent of SYLR, Cadmus
calculated the percent of refrigerators and freezers that would have been kept or discarded (the results
are shown in Table 17).
Kepl
Discarded
No
vrii"i ov oii;;iJ M;ih;d
$ec*n$nry N$as'k*t [$]Ss*ts
lf a participant would have directly or indirectly (through a market actor) transferred the program-
recycled unit to another Rocky Mountain Power customer absent the program, Cadmus determined
what that would-be acquirer might have done since that unit was unavailable due to the program. Some
would-be acquirers would find another unit, while others would not. This possibility reflects the
awareness that some acquirers were in the market for a refrigerator and would acquire another unit,
while others were not (and would have taken the unit opportunistically). lt is difficult to quantify this
absent program-specific information regarding the change in the total number of refrigerators and
freezers (both overall and for used appliances) that were in use before and after implementing the
program. Without this information, UMP recommends that the evaluators assume that half of the
would-be acquirers found an alternate unit. Without information to the contrary, Cadmus applied the
UMP recommendation to this evaluation.
Table 13. Fisr*$ SlstriSut!*n *f Kept and $!ss*r$*S Appil**ct
22
Rocky Mountain Power
Exhibit No. 5 Page 847 of 1 365
Case No. PAC-E-14-07
Next, Cadmus determined whether the alternate unit was likely to be another used appliance (similar to
those recycled through the program) or a new standard-efficiency unit (presuming fewer used
appliances are available due to program activity).17
For the reasons discussed above, it is difficult to estimate this distribution definitively. The UMP again
recommends a midpoint approach when primary research is unavailable: evaluators should assume that
half of the would-be acquirers would find a similar used appliance, and half would acquire a new,
sta nda rd-efficiency u nit.
Cadmus used the ENERGY STAR Website to determine the energy consumption of these new, standard-
efficiency appliances. Specifically, Cadmus averaged the reported energy consumption of new, standard-
efficiency appliances of comparable sizes and similar configurations as the program units.
Figure 7 details Cadmus' methodology for assessing the program's impact on the secondary refrigerator
market and for applying the recommended midpoint assumptions when primary data were unavailable
(a freezer-specific diagram is provided in Appendix G). As evident in the figure, accounting for market
effects results in three savings scenarios: full per-unit gross savings, no savings, and partial savings (i.e.,
the difference between the energy consumption of the program unit and the new, standard-efficiency
appliance that was acquired instead).
$igure T^ Sse*si$ary Nt*rk*t trnS:s*\ $*r S*$rig*rat+rs
Bll?9.fi$s!rf,rxi!rD6r:::::::i:::8sl!&{4il: : :::::::
$dlrsBi!:.$iriSl}:;
- r'-;;*f- '*---i
i I{22 I.r _ i {622 i -.'i' ^ \i rr.tt is:'sxrsrr,r.: uec j:,ri - .i rq*r rs:'ua$rk\i uec j - :.L-----I-------i
lsltegn*ti*m s$ $reerlS*rshigr nl'l$ Ses*n$sry S$nrk*t $,mpnets
After estimating the parameters of the freeridership and secondary market impacts, Cadmus used the
UMP decision tree to calculate the average per-unit program savings net of their combined effect.
Figure 8 shows how Cadmus integrated these values into an estimate of savings net of freeridership and
secondary market impacts. Again, Cadmus applied secondary market impacts as a result of UMP: this
was not accounted for in previous SYLR evaluations.
It is also possible that the would-be acquirer would select a new ENERGY STAR@ unit. However, most
customers who are in the market for a used appliance would upgrade to the next lowest price point (a
standa rd-efficiency u nit).
2i
Rocky Mountain Power
Exhibit No. 5 Page 848 of 1 365
Case No. PAC-E-14-07
To ensure that survey participants provided the most reliable responses possible, and to mitigate
socially desirable response bias to the greatest extent possible, Cadmus averaged the participant and
nonparticipant transfer and disposed ratios.
$rlgur* S. fistinratissr *t Net $awings $sr S*$rig*rat*ss
:::1 rurtiusE::::::::::
i;iqiq$U:iltlt:*S
::ii+t!Iefi!!!t!,::
i.:*l
L gJJNIEY,FRT$!*LlNlthi *s*Ige $$ o{ fpr$ridstship a{d,s-e?n\tdats :hs*a,t iB}pnbt
lmducES Nsplar*rn*s'lt
UMP states that evaluators must account for the energy consumption of replacement units only when
the program induced that replacement (i.e., when the participant would not have purchased the
replacement refrigerator in the absence of the recycling program). ln the case of non-induced
replacements, the energy consumption of the replacement appliance is not germane to the savings
analysis, since that appliance would have been purchased or acquired regardless of the program. The
acquisition of another appliance in conjunction with participation in SYLR does not necessarily indicate
induced replacement. Again, this is consistent with the methods outlined in the UMP.
Cadmus used the results of the participant surveys to determine which of the replacement refrigerators
and freezers were acquired by SYLR participants due to the program. The survey results indicated that
SYLR reduced the total number of used appliances operating within Rocky Mountain Power's ldaho
service territory, and raised the average efficiency of the active appliance stock. Across both appliance
types, 20% of participants did not replace their recycled appliance.
Next, Cadmus used participant survey results to estimate the proportion of replacements that were
induced by the customer's participation in SYLR. Specifically, Cadmus had asked each participant
indicating they replaced the participating appliance: "Would you have purchosed the new
refrigerator/freezer without the incentive you received for recycling the old one?" Since an incentive of
S30 is unlikely to be sufficient motivation for most participants to purchase an otherwise unplanned-for
replacement unit (which can cost SSOO to 52,000), Cadmus asked a follow-up question of participants
who responded"No." This question, intended to confirm the participant's assertion that the program
24
Rocky Mountain Power
Exhibit No. 5 Page 849 of 1365
Case No. PAC-E-14-07
alone caused them to replace their appliance, was: "Just to confirm: you would not hove reploced your
old refrigerotor/freezer without the Rocky Mountoin Power incentive for recycling, is that correct?"
To further increase the reliability of these self-reported actions, the induced replacement analysis also
considered: 1) whether the refrigerator was a primary unit, and 2) the participant's stated intentions in
the absence of the program. For example, if a participant would have discarded their primary
refrigerator independent of the program, it is not possible that the replacement was induced (since it is
extremely unlikely the participant would live without a primary refrigerator). However, for all other
usage types and stated intention combinations, induced replacement was a viable response.
Sigus* $" $stin'rati** *f $nduc*d Rsplacement
XFgSPENE{9[rnnPfBlll
siliibiqqtsr'ilE$g{1l :utsiaB&INi;*:..*,: . /*-.:*-ii- r." ;, i,.i '{r4 I -\-*-***J..,r','i \ El'Ri..usc'srnt'419.-!6c ;
i :,s,s 'l+*:'ii .tu i'.\*-i::,,:ii' :i:::I EnRi-.US6'gT$.tlAili-.JGc j
.::.s6'---*-{\,::::: ......; ,; - - -r-,lli il;:iiii+--.:i lsti iTr.*-ii e I:.\..,...,,-"...-ii::: ,.. \........................................,...,.,.l - iri:i c i;!: =! : : \..,..................-....-...--------.1:!:!
iN$$Jf SR,.ltlltl$r insu$sd, C6{r$utltFlria,t
As expected, only a portion of the total replacements was induced: the program induced 7% of all
refrigerator and freezer participants to acquire a replacement unit.
$pi$l*ssr
Spillover refers to additional savings generated by program participants due to their program
participation, but not captured by program records. Spillover occurs when participants choose to
purchase additional energy-efficient measures or adopt energy-efficient practices due to a program, but
do not participate in another program to receive an incentive for those additional measures. These
customers' savings are not automatically counted toward the utility's programmatic savings.
Cadmus estimated spillover from program participants' adopting additional measures as a result of their
participation. A small effect revealed by a survey may translate into a large effect for the population,
because survey results are applied to the population of eligible participants.
Energy-efficiency programs' spillover impacts get added to program results. ln contrast, freeriders'
impacts reduce a programs' net savings.
:::::::::::::::::,:::::::l:i:::wi*)**\
\......**..i
::::::::ii:iii iiltlt:i:::::i::ltl :;pry\
r--...:......1
i:i::::iiit i ltl l:li:i:::i:i:i:::ii:i
ro"\L_:J
::iia: 4M
tii:i:. BA.ir.. l^n'srRlitRRu: . *Er,::::::\-*-,-.-----..."-...**.-...,-
TsSSs I^S. i$tX-[$]]: Nvl$r"sus$ SspNn*e*sr**t Nntss
25
Rocky Mountain Power
Exhibit No. 5 Page 850 of 1 365
Case No. PAC-E-14-07
For the SYLR program, Cadmus measured spillover by asking a sample of participants who purchased
and received an incentive for a particular measure il due to the program, they installed another
efficient measure or undertook other energy-efficienry activities. Respondents were asked to rate the
relative influence of the SYLR Program and incentive on their decisions to pursue additional savings.
Spillover questions were used to determine whether program participants installed any other energy-
saving measures since participating in the program. Savings participants received from additional
measures were considered spillover savings if the program significantly influenced their decisions to
purchase additional measures, and if they did not receive additional incentives for those measures.
SYLR program participants were specifically asked whether they installed the following measures, which
were associated with quantifiable spillover:
o High-efficiencydishwashers
o High-efficiencywashingmachines
o High-efficiencyrefrigerators
o High-efficiency water heaters
lf the participant installed one or more of these measures, they were asked additional questions about
which year they purchased the measure, and whether they received an incentive for the measure. lf
applicable, participants were asked how influential the SYLR program was on their purchasing decisions
(participants could answer not at all, not very, somewhat, or very influential). Participants expressed
mixed responses regarding the program's influence on these actions, with 18% finding the program very
influential (Figure 10).
26
Rocky Mountain Power
Exhibit No. 5 Page 851 of '1365
Case No. PAC-E-14-07
$igurs t$" $ssgran'r $*$luence *sr l*stn$ling Ad$iti***l N.$ens*rcs
{wittt $$$.'o S*nficlelree I nt*rr.s ls}
sffi6
45%
4ff/a
35%
3tr4
25?;
7#o
15%
tffo
s%
o%
Very Infiuential Somewhat
influential
Not very
infiuential
Not at all
influential
n=112
Eighteen percent of participants claimed to have installed energy-efficient measures or changed their
behaviors after participating in the SYLR program. However, only three such purchases represent
quantifiable savings: energy-efficient refrigerators, clothes washers, and dishwashers. Other measures,
such as weatherization, water heaters, and HVAC, are difficult to quantify accurately based on survey
data, and thus were not included in the spillover analysis. ln addition, CFLs, which are commonly
mentioned, were not counted because of a high likelihood of double-counting savings claimed by the
HES Program through upstream CFL sales. Cadmus calculated participant spillover by estimating savings
attributable to additional measures installed, and whether respondents stated that Rocky Mountain
Power was very influential in their decisions. Measures were counted if they were eligible for program
incentives but incentives were not requested.
For calculating spillover savings, Cadmus used a top-down approach. The analysis began using a subset
containing only survey respondents who indicated they installed additional energy-savings measures
after participating in the SYLR program, but without receiving any incentives. From this subset, Cadmus
removed participants who indicated the program was not very influential on their decisions to purchase
additional measures.
For the remaining participants with legitimate spillover savings, Cadmus estimated energy savings from
additional measures installed. The savings values, calculated by Cadmus, were matched to additional
measures installed by survey participants.
27
Rocky Mountain Power
Exhibit No. 5 Page 852 of I 365
Case No. PAC-E-14-07
Table 19 summarizes participant survey spillover responses. Appliance per-unit savings were derived
from Cadmus' evaluation of 2017 and 20L2 HES gross savings values. Cadmus assumed CFL savings
equaled those calculated for energy-savings kits. Total spillover savings represented 0.O3% of
refrigerator and !% of freezer savings.
The spillover results for the SYLR Program are shown in Table 19.
976 95,013
t29,245 0.03%
$i*sl N*t-t$-$r"s$s
As summarized in Table 20, Cadmus determined the final net savings as gross savings less freeridership,
secondary market impacts, and induced replacement kwh plus the spillover savings.
34
Ta$le 3.$. Fr*grarn $pillsver im 3$I3 an$ 3$3I
TuSt* R$. fi,$S"S" anS A$XR NITS Rrt$*s
Refrigelator
Freezer
1,o22
1,033
445
515
25
3J
0.3
11
55O: 54%
492: 48%
After adjusting for freeridership and spillover, the net per-unit savings were 550 kWh for refrigerators
and 492 kWh for freezers. These values are somewhat lower than the evaluated per-unit savings for
2OO9-207O, primarily due to changes in evaluation methodology.
Ssmt,mws$s s"$ .$g.tt$s*$ $sst$$st gs
Table 21 summarizes the results of Cadmus' impact analysis for 201.7 and 2012.
28
Rocky Mountain Power
Exhibit No. 5 Page 853 of 1365
Case No. PAC-E-14-07
L,034i 1,226,921 i 1,056,958 569,193 46%
Tahle 3I" R$15. a*$ 3*13 Pr*grarn Sasings [sy fVts*sure
Refrigerator
necvclilg
Freezer
RegVclinS
Energy-
45%
47%
40%
7to/o
97%
47
337
935
360,242
93,797
348,193
44,247
L65,719
44,247Savings Kit
Tstnl 2,3OS : 3",680,350 tr;449,39$779,15$:St$'6
ToS$* 3t.I$tt $r*grasn Sar,ings hy $\$s*sur*
Refrigerator :
negvcllns
iFreezer a
necvglins
,Energy-
i
Savings Kit i
,:,:,.,,.:,:::,:,:l::::,l'ESal,.,.,i
542
158
488
r' ,, ,, 1r1$E;
541,441
184,373
48,501
554,034
173,580
23,ttl
86o/o
94%
48%
298,358
82,614
23,ttt
26%
40%
tt%
*s$il
47%
45%
48%
!$696.
Refrigerator
Recvcling
Freezer
Recycling
Energy-
Savings Kit
,, ', ,. ,'. iotii
46%
47%
47o/o
46%'
25% :
I
i40'% :
\\% |
492
169
447
E?41L5:$, :: .,, .......,.,.?50.I*5
585,480
I '02,924
i
T75 9V9 : t74,6!!
44,696 : 21,135
...,..s69.$ : ,, I,,,,4's4rsss
8t60/o a 270:831
:
es%
i
83:10s
47% : 21,!35
Tsh$* f.$. S$X"R $rsgrsm Ssxrisrgs Ny lVlessurn
*;*S,S i ' ,S$S'trSs
29
87?1s 3v5;$?,5
Rocky Mountain Power
Exhibit No. 5 Page 854 of 1 365
Case No. PAC-E-14-07
Pr*cess Sw*luati*n
This section presents detailed staff interview findings and participant and nonparticipant survey results.
The areas of focus include:
o Effectiveness of the delivery structure and implementation strategy;
o Marketingapproaches;
o Customer satisfaction; and
o lnternal and external communications.
NF*f$r*Ssf*gy
Cadmus conducted the following process evaluation research:
o Document review, including:
r Past evaluations,
. Logic models, and
. The program Website.
. Utility staff and administrator interviews.
o Participant and nonparticipant surveys.
Cadmus developed stakeholder interview guides to collect information about key topics from program
management staff. JACO Environmental implements the SYLR Program (the program administrator).
Cadmus conducted three stakeholder interviews: one each with the program managers at Rocky
Mountain Power and JACO (both of whom oversee appliance recycling programs in all five of
PacifiCorp's service territory states), and one with the manager of JACO's appliance recycling facility in
Salt Lake City, Utah. The following items were discussed during the interviews:
o Program history;
o Process flow;
Program design versus program implementation;
Changes in implementation and program marketing; and
Strengths and areas for improvement.
Cadmus conducted interviews by phone, and then contacted interviewees via e-mail for follow-up
questions and clarifications.
a
a
o
i0
*$ss gsmstt "\xg$em*m Ss *s*st mmN $s$$unerpu
Drawing on stakeholder interviews and participant and nonparticipant survey response data, this section
discusses the SYLR Program implementation and delivery. Cadmus updated logic models to reflect the
2011 and 2012 prograrn processes based on information gathered through program staff interviews (see
Appendix E).
Ss*grem i"{$st*r1. *n$ $r*gram N$nnagems*t
The SYLR Program launched in ldaho in 2005. According to program staff, during the first four years of
implementation, the program experienced participation levels higher than the national average.
Beginning in 2009, participation began to decline in response to a reduction in the incentive amount and
a weak national economy. Since that time, program participation in ldaho has leveled off.
According to the program administrator, they worked with Rocky Mountain Power to establish 2077-
2OL2 program goals based on prior program performance and harvest rates.18 The contract between
Rocky Mountain Power and the program administrator included these projected participation levels, but
did not apply any penalty in the case of lower-than-expected participation. Beginning in 20L3, Rocky
Mountain Power issued a new RFP and designed the contract so that the program administrator will
incur a financial penalty if the SYLR Program does not meet its participation goals. Additionally, Rocky
Mountain Power aligned the participation goals for 2013 more closely with recent program
performance.
Rocky Mountain Power receives a monthly invoice and report from the program administrator that
includes the number of pick ups, the reason(s) each unit was rejected, and the time lapse for mailing
incentive checks. ln 2OL!, Rocky Mountain Power staff observed reporting inconsistencies, so in 20!2
they began comparing monthly reports, invoices, and the dashboard to make sure they are consistent.
This improved monitoring appears to have resolved any inconsistencies, and this evaluation verified that
2011 and 2012 reported unit counts were consistent with the program administrator's databases.
18 The harvest rate isthe number of units recycled through the program in a given year divided bythe total
number of residential customer accounts in the service territory.
Roclq Mountain Power
Exhibit No, 5 Page 855 of 1 365
Case No. PAC-E-14-07
ln addition, Cadmus conducted telephone surveys with participant and nonparticipant customers.
Cadmus designed the survey instruments to collect data about the following topics:
o Customer informotion. Demographic information and household characteristics.
t Program process. Details to inform the following performance indicators:
. What are the participation motivations and barriers?
. Are program incentives set correctly?
. ls the program process effective?
. How satisfied are customers with the program?
. What are the program's strengths and/or areas for improvement?
37
Roclry Mountrain Power
Exhibit No. 5 Page 856 of 1 365
Case No. PAC-E-14-07
Srmgrnm $taffi*g *nS Training
JACO Environmental implemented the SYLR Program for Rocky Mountain Power in 2OL!-2072, and has
been the implementer since the program's inception. The program staff also included a Rocky Mountain
Power program manager, PECI as a marketing contractor, and Appliance Distribution as a subcontractor
to JACO. Appliance Distribution's role and the addition of PECI are discussed in more detail in the
Delivery Structure and Marketing sections below.
All program stakeholders reported that staffing levels were adequate, and the working relationships
among parties involved in program implementation were effective. Training occurred as needed for new
employees, but no major staff changes were reported for the 2071-20L2 program, with the exception of
PECI's new role as marketing contractor.
$eliv*rtr- $tructur* amS Fro*esses
Rocky Mountain Power and the program administrator reported that they designed the program
similarly to other appliance recycling programs already operating in other states.
Rocky Mountain Power and the program administrator followed four main program delivery steps:
7. Marketing.
2. Sign-up/scheduling.
3. Appliance pick up.
4. lncentive payment.
They tailored the marketing messages to appeal to owners of older and secondary refrigerators,
although there were no minimum age requirements for appliances to participate.
Rocky Mountain Power's ldaho customers who were interested in disposing of an eligible appliance
could obtain information or sign up to participate through Rocky Mountain Power's Website or by
calling the program administrator toll-free. When participants signed up, the program administrator
collected details about how customers learned of the program, verified eligibility, and scheduled pick-up
times. The customer received a window of time for appliance pick up on a specific day, and was required
to have the appliance plugged in and running upon pick up.t' ln 2011, the program administrator
reduced the pick-up window from four hours to two hours, in order to provide better customer service
and to match the two hour pick-up window offered by Sears.
The time between scheduling and pick up in 2011-20L2 averaged 17 days, which was relatively
consistent with that in 2009-2010. The program administrator noted that pick-up wait times tended to
be shortest in urban areas, while customers in outlying areas experienced longer waits.
1s The program administrator estimated thal2-3% of pick ups were typically ineligible for participation because
the appliance was not working. Similarly, the program administrator reported that roughly 1-2% of units
scheduled for pick up were ineligible for participation due to their size.
i2
Rocky Mountain Power
Exhibit No. 5 Page 857 of 1 365
Case No. PAC-E-14-07
At the scheduled time, the program administrator picked up and verified that the appliance was in
working condition, and collected data about the appliance age, size, configuration, and features. ln late
2011, the pick-up crew began using hand-held computer devices to perform a variety of quality
assurance and quality control (aA/aC) functions and enable the pick-up process. The program
administrator took a photo of each unit and recorded its model number and unit number. Customers
signed the hand-held device when the pick up was complete.
During appliance pick up, the program administrator provided participants with an energy-savings kit
containing: two L3-watt CFLs, a refrigerator thermometer, energy-savings educational materials, and
information about Rocky Mountain Power's other energy-efficiency program offerings. During 2011and
2072,the receipt of the kit was not tracked in the program administrator's database. However,
beginning in 2013, the program administrator added tracking of the kit for each customer. Under the
new tracking procedure, each participant will indicate on the hand-held device whether or not they
received a kit at the time of their pick-up.
The program administrator brought appliances to Appliance Distribution's facility in Salt Lake City for
decommissioning and recycling. The program administrator then mailed incentive checks to participants.
$srrms nn$ tn*ent$rses
The SYLR Program requires minimal paperwork from participating customers. The sign-up process can
be completed by phone or online, and does not require the customer to fill out lengthy forms.
Customers who sign up by phone are asked for information, including their address, the location of the
unit, and a few screening questions. Customers who sign up online respond to these questions through
a briel one-page online form.
Customers appreciated the simplicity of the sign-up process: 98% of surveyed customers reported being
very or somewhat satisfied with the program sign-up process. Customers were also satisfied with the
convenience of the pick-up process: 92% reporled that it was very easy or somewhat easy to schedule a
convenient pick-up time.
Participating customers reported high satisfaction levels with the incentive amount (98% reported being
very satisfied or somewhat satisfied). Also, 82% said they would have participated in the program with a
lower incentive, and 70% said they would have participated without an incentive at all.
33
Rocky Mountain Power
Exhibit No. 5 Page 858 of 1 365
Case No. PAC-E-14-07
$Wsrdcs*fsrgr
Appr*ach
The program marketing components underwent several changes during 20L! and 2012:
o ln 2011., the program administrator rebranded the kits and incentive checks with the Rocky
Mountain Power logo, instead of the JACO logo. Program staff reported that these changes,
while small, are important because they affect the customers' perception of the program.
o The program administrator updated the marketing materials it distributes with messages
coordinated with the Home Energy Savings Program, which provides customers with an
incentive for purchasing an energy-efficient appliance. According to program staff, it is natural
to promote recycling when advertising incentives for efficient new appliances.
Participants became aware of the program through a variety of ways. Bill inserts and word-of-mouth
were the most frequently mentioned channels (Figure 11), which is consistent with findings from prior
program evaluations. ln a separate question, 7L% of participants indicated that bill inserts are the best
way for Rocky Mountain Power to communicate energy-efficiency opportunities. Other popular
responses included print media and e-mails, at L2% and 10% respectively,
Other website -$ rV"
Rocky Mountain Porver,/Pacific lower,.. $ Z%
lnternet Advertising/Online Acl .,ffi ,*
Rocky Mountain Pouer,/Pacific Fower... ffi SV,
Retailer/Store ffi eW
NewspaperlMagazine/PrintMedia ffi Ay;
iv ffi t+o.
Familyff riends/word-of-mouth
Bill lnserts 54%
o%7ffo 2S/o 3tr/s 407a 507o 60Yo
ln2Ol2, the program administrator selected PECI (the program administrator for HES)to replace Runyon
Saltzman & Einhorn as the marketing subcontractor. ln prior years, Runyon Saltzman & Einhorn had
developed marketing materials and worked with the program administrator to develop an overall
marketing strategy and approach. The Rocky Mountain Power and program administrator staff reported
that the program administrator had already contracted with PECI to work on collateral for similar
Radio S a'*
19%
$igurs 3"3.. tr"luwr Farticipa*ts Learne$ Ah*ut the Frcgrarn*
34
Rocky Mountain Power
Exhibit No. 5 Page 859 of 1365
Case No. PAC-E-t4-07
appliance recycling programs in Oregon; because Rocky Mountain Power and the program administrator
were pleased with the results of those efforts, they wanted to shift their business to PECI. While
administrator staff reported that the first six months working with PECI were a challenge because the
primary SYLR staff had left, the working relationship appears to have improved over time. According to
program and administrator staff, the program administrator closely examines past pick-up trends and
uses that information to develop marketing plans.
Another change in 2012 was that mass media, which used to be handled by Runyon Saltzman & Einhorn,
is now handled by a marketing contractor to PacifiCorp. Observations about the seasonality of the
program-with higher participation in the spring and fall-led program administrator staff to
recommend that TV ads and bill inserts align with seasonal trends. Program staff reported that TV is an
effective medium for the SYLR Program, which is the only energy-efficiency program with W
advertisements.
Targetimg
Program and administrator staff reported that they do not exclusively target specific customer segments
for the SYLR Program, just any customer who has a second refrigerator or freezer. Administrator staff
noted that PECI sent out a mailing to customers who participated in the Home Energy Savings Program
and received a rebate for a new appliance, as these customers may have an extra unit that could be
recycled. PECI also receives market data from retailers with the ZIP codes where most new units are
purchased.
Compared to customers in the general population, SYLR Program participants were more likely to be
homeowners of a single-family residence. The 201L-2012 demographic results are consistent with the
2009-2010 survey, with an increase in the number of participants earning 550,000 or less. Table24
shows the average demographics for participants surveyed.
...sSte R$" Fsstisip**t $*m+gr*pilics
Average Head of Houlehold Aee
Homegwnellhip
Ay"l:g: I-orlenolo sile llymbgr of neootel
Proportion Earning Less Than S50k
s5.3
gig%
59.6
gii;t"
2.93.1
50.7o/o 59.4o/o
The vast majority of 2OL'J. and 2O!2 participants (95%) live in a single-family residence. As the participant
contact information was self-reported (and could have been a landline or cell phone), the survey was
less likely to experience bias for respondents with landlines, as often seen in random-digit-dial surveys.
Sur*pnris*m r**tth $\*np* rtlci pns'tts
When a nonparticipant population differs demographically from the participant population, it could be
due to misplaced or incomplete targeting of marketing efforts. Cadmus tested the similarities between
nonparticipants and participants to rule out marketing not reaching some eligible demographic groups.
35
Roclry Mountain Power
Exhibit No. 5 Page 860 of 1 365
Case No. PAC-E-14-07
For example, if a large portion of nonparticipants live in mobile homes but few participants live in
mobile homes, the mobile home market may have been overlooked.
One area in which participants and nonparticipants differed was the number of years they have lived in
their home. As shown in Figure L2,87% of participants have lived in their home for more than five years,
compared to just 5L% of nonparticipants.
$igure 3^h" Yeass S-$veS nt Cusrr*nt Nesi$enre
irmx .,- -----*-
909o -i--
80?;
70#r
6Oflo
Sff/o
4tr/s
30e/s
More than 5 years
"" N 2-5 years
""'& Less than one year
I
Table 25 shows the results of t-tests for differences between participants and nonparticipants20 for a
series of relevant characteristics. Age, average household size, and homeownership were significantly
different between participants and nonparticipants, with p-values of 0.00 for age and average
household size and 0.01 for homeownership.
Home types did not differ significantly: Cadmus' chi-square test for independence between the two
groups indicated they do not differ with 90% confidence (p-value=0.99).
TnLrSe 3S. t-Tssts f*r $snt*glnphic $i$$sr*srues Setw".**st
Pafticipants (n=212)Non- Farticipants {n=45}
Farti*lp**ts a*$ N*npnrticipastts
Average Head of Household Age
s ngle ramiit H;.;";;;i;ni,
Averasg H9y::h:!9 li* ("ym!91 ol oeonlef
Proportion Earning Less Than $50k
15 , 0:00
!8o/o , 0:0,1.
0.95 i 0.00
59.7
iii;/"
).i
43.6
ian
3.9
600/o 50%
20 All t-tests assumed unequal sample sizes and variances.
36
95%o.29
Roclry Mountain Power
Exhibit No. 5 Page 861 of 1 365
Case No. PAC-E-14-07
$ss $*stt s$" r$ss.$$ssss
$utis$nsti*n
Participants experienced high overall satisfaction rates with the program: approximately 99% of
participants reported being somewhat or very satisfied with the program (see Figure 13). When asked
about program specifics, such as scheduling and incentive amounts, participants expressed similar
satisfaction levels. These high levels of customer satisfaction are common for utility appliance recycling
programs.
$igun* tr$" $v*raNl $rsgr*r* Sstis$i:et!*r$
9096
8096
7B%
6096
5O9/o
4B%
3A%
Zff/o
80.2%
o.0%a.7%
Very dissatisfied Sonrelvhat Sornewhat satisfied Very satisfied
dissatisfied
in=Z16)
Participants' willingness to recommend the program to others reflects their positive perceptions of the
program. Figure 14 shows that 99% of participants said they were somewhat or very likely to
recommend the program.
109o
o%
I
i
I
I
i19.lYo
Rocky Mountain Power
Exhibit No. 5 Page 862 of'1365
Case No. PAC-E-14-07
$igure t$. Likelihood of R***mrnunding $rogram t$ Sthers
90Yo
8ff/o
70%
60%
5OYo
4Wo
30%
2tr4
1ff.d
OYc
Not at atl likely Not uery likely Sonrewhat likely Very likefy
{n=215}
Ninety-two percent of customers reported having positive experiences with the program scheduling
process, with 8% expressing scheduling concerns (Figure 15).
7ff/o
6ff/o
Sff/o
4fflo
3ff/t
20,8d
Itr/o
o%
Very difficult Somewhat difficult Sorrcwhat easy Very easy
{n=215)r'll,
Program and administrator staff noted that the SYLR Program rarely receives customer complaints. The
pick-up staffs' use of hand-held computers allows them to communicate quickly with their call center,
Figur* 3S. Level *f Sifti*r,rlty uuith $ch*duli*g
38
Roclry Mountain Power
Exhibit No. 5 Page 863 of 1 365
Case No. PAC-E-14-07
enabling all involved parties to communication efficiently and knowledgeably with the customer if there
are any problems, such as with locating their home or picking up the unit.
Customers have gone out of their way to compliment program administrator staff and find ways to
encourage more recycling. For example, the SYLR facility manager in Salt Lake City was contacted by a
Salt Lake City resident who thinks highly of the SYLR Program and wants her Girl Scouts troop to
promote it. The troop would ask participating customers to donate their incentive to the troop; this
model has been implemented successfully in other states where the program administrator operates
appliance recycling programs.
$srriers
Overall, participants did not report notable complaints or issues during the surveys, and based on the
SYLR process evaluation, Cadmus noted no significant barriers. The program functions smoothly, likely
due to its longevity in the ldaho market and the program administrator's experience.
$ss$S$^w Sss sssst seJ S s,s sr's$Ss $sst $ssS
The SYLR Program has multiple aA/qC checkpoints to facilitate quality service delivery and accurate
data tracking. The biggest change during 2OL7-2OL2 was the pick-up and warehouse crews using hand-
held devices. When a pick-up crew arrives at a customer's home, they verify that the unit is in working
condition and fits the size criteria. lf the unit passes those two tests and therefore meets the program
criteria, the crew enters the model number, unit number, size, and age into the hand-held device, and
takes a picture of the unitfrom a specific angle. lf the unit does not meetthe program criteria, they still
take a picture and record why the unit was not accepted. The pick-up crew also indicates if they caused
any damage during their visit. The information they uploaded to the hand-held device reaches the
program administrator database within five minutes and is available to all authorized program users.
When the unit arrives at the warehouse, the warehouse staff scans the unit and the appliance picture
taken by the pick-up staff appears. This serves as a verification that the correct unit arrived at the
warehouse to be processed for recycling.
The program administrator and Rocky Mountain Power track the time it takes for a customer to receive
their incentive check, and they track the time between when a customer sets an appointment and their
unit is picked up. On a quarterly basis, the program administrator verifies that the incentive processing
time is below the requirement (30 days); they reported that this requirement is consistently met.
According to Cadmus' assessment of the program administrator's tracking data, the average time
between the pickup date and the check date was 20 days. However approximately 8% of records
showed a wait longer than 30 days, and the maximum wait was 51 days. The program administrator also
examines why units were rejected and tracks the volume of rejections to make sure there is no increase.
ln addition to the OA/aC performed by Rocky Mountain Power and the program administrator, an
independent contractor performs follow-up inspections at a random sample of participant homes. These
39
Roclg Mountain Power
Exhibit No. 5 Page 864 ot 1365
Case No. PAC-E-14-07
inspections ensure that pick-up procedures were followed and any issues are reported to Rocky
Mountain Power and the program administrator.
$este$rmcrr&$srg
Cadmus benchmarked the 2011-2012 SYLR Program against four other similar utility appliance recycling
programs. Since the reports for three of those benchmarked utility programs are not publically available,
all four programs are cited in this report anonymously as Utility 1, Utility 2, Utility 3, and Utility 4. Utility
2 and Utility 3 offered their appliance recycling programs in 20tt, while Utility 1 and Utility 4 offered
theirs in 2012.
Figure 16 shows a comparison of the three common methods utilities use to inform participants about
their respective appliance recycling programs. A higher proportion of participants learned of the SYLR
Program through bill inserts compared to all but one of the benchmarked counterparts.
S$gure S$" M*in Nlet$r*S f*r l'learlng Abont Pr*grem
9Wo
8096
7Wa
6Wo
Sff/o
4CP/o
30k
2W\
70%
a%
ffiW
'i:',:iiiili iiiilttr}r6 ::
W''''''''''''''''''''''$im&IuBffis
ffiffi _ ___iffi. s%
Utility 1
(n=182)
Utility 2
(n=183)
**'96
Utility 3
(n=1ao)
# Ner,vspaper/Magazi ne/Print
Media
w
s Farnilyfriendsy'word-of-nrouth
n Bill lnserts
Utility 4 Rocky
in=14O) Mountain
Power
in=198)
Figure 17 compares participants who stated being either somewhat or very satisfied with their
respective appliance recycling program, or who rated their program overall as a 7 or higher out of 10.
The SYLR Program had overall customer satisfaction levels in the same range as the other four
programs."
27 Using a two sample t-test, Cadmus confirmed that the difference in satisfaction levels between the SYLR
Program and the benchmarked utility programs was insignificant.
40
Rocky Mountain Power
Exhibit No. 5 Page 865 of 1 365
Case No. PAC-E-14-07
t $i*qur* \?. Sver*Ii Srsgr*nr S*tisfa*tiur-T
Utility 1
{n=196}
Utility 2
in=197}
Utility 3
{n= 1a7}
Lltility 4
{n=139)
Rocky
Mountaln
Power {n=215)
o
t
41
Rocky Mountain Power
Exhibit No. 5 Page 866 of 1 365
Case No. PAC-E-14-07
S*st-S$fe*t$weness
ln assessing cost-effectiveness, Cadmus analyzed program costs and benefits from five different
perspectives, using Cadmus' DSM Portfolio Pro22 model. The benefit/cost ratios Cadmus used for these
tests are described in the California Standard Practice Manual for assessing DSM program cost-
effectiveness. The five tests perspectives were:
1. PacifiCorp Total Resource Cost (PTRC)Test: This test examined program benefits and costs from
Rocky Mountain Power and Rock Mountain Power customers' perspectives, combined. On the
benefit side, it included avoided energy costs, capacity costs, and line losses, plus a 10% adder
to reflect non-quantified benefits. On the cost side, it included costs incurred by both the utility
and participants.
2. Total Resource Cost (TRC) Test: This test also examined program benefits and costs from Rocky
Mountain Power and Rocky Mountain Power customers' perspectives, combined. On the benefit
side, it included avoided energy costs, capacity costs, and line losses. On the cost side, it
included costs incurred by both the utility and participants.
3. Utility Cost Test (UCT): This test examined program benefits and costs from Rocky Mountain
Power's perspective only. The benefits included avoided energy, capacity costs, and line losses.
The costs included program administration, implementation, and incentive costs associated with
program funding.
4. Ratepayer lmpact Measure (RtMlTest: All ratepayers (participants and nonparticipants) may
experience rate increases designed to recover lost revenues. The benefits included avoided
energy costs, capacity costs, and line losses. This test included all Rocky Mountain Power
program costs and lost revenues.
5. Participant Cost Test (PCT): From this perspective, program benefits included bill reductions
and incentives received. Costs included a measure's incremental cost (compared to the baseline
measures), plus installation costs incurred by the customer.
Table 26 summarizes the five tests' components.
DSM Portfolio Pro has been independently reviewed byvarious utilities, their consultants, and a number of
regulatory bodies, including the lowa Utility Board, the Public Service Commission of New York, the Colorado
Public Utilities Commission, and the Nevada Public Utilities Commission.
42
Roclq Mountain Power
Exhibit No. 5 Page 867 of 1 365
Case No. PAC-E-14-07
TRC
UCT
Present value of avoided energy and capacity
costs* with LO% adder for non-quantified
benefits
Present value ofavoided energy and capacity
costs*
Present value of avoided energy and capacity
costs*
Program administrative and marketing costs
and costs incurred by participants**
Program administrative and marketing costs
and costs incurred by participants**
erogram administrative, marketing, and
incentive costs
RIM
PCT
i Present value of avoided energy and capacity
costs*
I Present value of bill savings and incentives
r received
* lncludes avoided line losses.
** lncentlve costs are typically excluded from the TRC as transfer payments. However, for appliance
recycling programs such as SYLR, participants do not incur costs. Therefore, the incentive cost is treated
differently from incentives in typical DSM programs. lt is not excluded from the TRC, and instead it is
treated as an administrative cost since it is not offsetting any participant costs. This means that for SYLR the
UCT and the TRC costs are equal.
f able 27 provides cost analysis inputs, including the evaluated energy savings for each year, and the
discount rate, line loss, and program costs. Rocky Mountain Power provided allof these values, except
the evaluated energy savings and evaluated participation. Cadmus derived the discount rate and
inflation from Rocky Mountain Power's 201-1 lntegrated Resource Plan.
: Program administrative, marketing, and
I incentive costs, plus the present value of lost
revenues
r lncremental measure and installation costs
Tabls E$" S*ns$its ssld Csst$ lrtclu$ed in \dsriuus Tests
43
Rocky Mountain Power
Exhibit No. 5 Page 868 of 1365
Case No. PAC-E-14-07
T*hle 3?. Seluete$ C*st Analysis lnputs
Participati,on
:_,
Refrigerators 492 L,034
168 337Freezers
il&t-i*i"e;Kiii
MBasur€,liv€s .:::,
488 447 93s
Refrigeratols
Freezers
5.0 5.0 N/A
NiA
NiA
9.05.0
In"lqv:l,Yilg: Kit:
Program Savings
(kWh/year)*
5.06.5
75t0,725
|
7.t7% |
698,672 ,
7.17% ,
1,449,398
Line Loss 9.96% . L1.47% |
Discount Rate
lnflation Rate
rJiat proeram coiii
N/A
NiA
NiA1.8%
Sioi,ois
1.8%
Sioz,si8 s209,911;iha;;;ri;s; ieiiect ilpaits it ,eiei;;hi6 a";rsy ueniiiii iicount for line losses. the totit ijrl"gi ;h"t;
here differ from the total savings reported elsewhere in this report by approximately !% due to rounding in the
cost-effectiveness model.
The SYLR Program benefits included energy savings and their associated avoided costs. For the cost-
effectiveness analysis, Cadmus used energy savings derived from this study's evaluated kWh. The
measure lives used (Table 27)were from annual report data provided by Rocky Mountain Power.
Maintaining consistency with the annual reports allows for more direct comparison of reported and
evaluated results.23 For all of analyses, Cadmus used the avoided costs associated with PacifiCorp's 2017
tRP 35 Percent Lood Foctor Eastside Residentiot Whole Home Decrement.za
Table 28 presents the program cost-effectiveness analysis results, including the evaluated NTG25 for all
program measures for the evaluation period (zO1-L-zOLzl, but not accounting for non-energy benefits
(except those represented by the 10% conservation adder included in the PTRC test). The cost-
effectiveness analysis results indicate that the program was cost-effective from all perspectives, except
the RIM test.26 A benefit/cost ratio greater than 1.0 is considered cost-effective.
For future cost-effectiveness analysis, Cadmus suggests updating measure lives to align with the values used in
the most recent RTF measure workbooks.
The IRP decrements are detailed in Addendum, Chapter 2 of PacifiCorp's 2011 lntegrated Resource Plan:
http:1/www.paqificor:p.cortr/content/aaml'pacificorp,/doc/Enerey Sources/lnteg!"ated Resourqe Planl?011lBP
l2!1 1 I BP-Addend u m...20110677.pdf
Evaluated NTG is 53.9% for refrigerators and 47.6% f or freezers.
The RIM test is included as a measure of the program's impact on all ratepayers, and it is common for DSM
programs to have a RIM ratio of less than one. The ldaho Public Utilities Commission (like most other
regulators) does not require DSM programs to pass the RIM test.
25
26
44
Roclry Mountain Power
Exhibit No. 5 Page 869 of 1 365
Case No. PAC-E-I4-07
PTRC
iRc
ucr
nrM
Paf
0:0495
0.0495
0.049s
slsor09s
s318,185
s318.186
s318,185
5t45,976
s1151157
s11sf1s7
:5246F8_r:
5719,259
t.72
t:.'7
-757
0.s6
Nl;SO 5719,259
Table 29 and Table 30 show the program's evaluated cost-effectiveness for the 2011 and 2012 program
years, respectively.
0:0543
0:0543
0.0543
s1o7:033
S1o7r033
s1071033
s267,258
5159r851
S145,319
s1451319
514s,319
s521818
S38r286
S38f286
-S121,939
L.49
1:36
1':36
0.54
N/A
Tabl* 3$. t$3.I en$ P$tt Eualuated Srograrn S*st-Sf$e*tiue$ess $umtmnry
Tahl* R$" 3$i\ Srs*lusts$ $ns$rs$r S*st-&tfectivsrlsss Surt,tmsry
PTRC 0.0451 s102,878
SO s316,895 S310,89s
s203,788 S1oo,91o 1.98
Tah$* $S" t$tR Srs*lunt*d Sr*gran'r {*st-Sffectivs$}sss Sumrnary
TRC 0.0451 s102,878
0.0451 5ro2F78
s318.841
SO
5185262
Stas,zez
5L8s?62
543t,2t4
s8_2r383
s82f383
1S11a,sa-o
543r,214
1:80
1r80
0.58
NiA
UCT
niv
Paf
45
Rocky Mountain Power
Exhibit No, 5 Page 870 of 1365
Case No. PAC-E-14-07
&ppemS$x A: Sartt*$pant S*m*gnmph$*s
Tshle A-1. Flsrne Type Sherccteristics
+l *me,,,lyp* {nsz $lt}
Single-family home 9to/o
2o/o
3.3o/o
1.5o/o
i..i%
!.20/o
Townhome or duplex
Mobile home or trailer
Apartment building with four or more units
60/o
7%
u67;;;i..fi;n[ai
Own 95%2.5o/o
Rent
Participant Age (n=195)
NilbiliR;;iffiis i;=riii
5%2.5o/o
TsNls A-t. $Ssus*h*l$ {hsr*ctevistiss
Figur* A-1. *lstrihuti*r'ls *$ !{*usehsl$ $ixes
t,
oa,
o
CL
c)I
\p
45%
4U/o
35%
3Cffo
75%
2ff/o
L5%
1Po
5Ya
0%
1 t5?L
55
Number of Residents
46
10
Roclry Mountain Power
Exhibit No. 5 Page 871 of 1365
Case No, PAC-E-14-07
Sigt*s"e A-3. Sistvihutisns st F*rtiti$a$t A$$s
: --^/i J57o : 316/,
t
oE
oato
o
$6\
laS/^ .r .......
i
2596 -i
i
2ff/o ;
{ Eo/- ..i ........
ii 10% 1B?/o'*".
ffi wEot . 2o1J/O l
on:3-111 ffi--
112A
1796
ffi L\o/b
ffiffi,1"
M M ffi::::
Rocky Mountain Power
Exhibit No. 5 Page 872 of 1 365
Case No. PAC-E-14-07
&pp*ndix $: Fn"ea$s$mc\ *n**L$$**l*ns
To determine the uncertainty level of savings results, Cadmus considered the effect of sampling error on
all estimates presented in the report. Sampling error refers to uncertainty introduced by the use of
sampled data to infer characteristics of the overall population. These data include survey results, meter
data, and data from secondary sources. Cadmus used sampled data to estimate the parameters of per-
unit savings calculations (such as installation rates) and to estimate the consumption of specific
equipment types (such as in billing analysis).
Sampling error has been reflected in estimated confidence intervals. Unless otherwise noted, Cadmus
estimated intervals at9O% confidence, indicating a90% confidence that the true population value fell
within the given interval. Cadmus calculated confidence intervals for means, proportions, regression
estimates, and any calculated values using sample estimates as an input. Cadmus calculated all
confidence intervals using the following standard formula for estimating uncertainty for proportions and
means:
Where:
L.645
s'
Conf idence lnterval^ean = medn * L.645 *
the z-score for a 90% confidence interval, and
the sample variance.
ln some cases, the uncertainty of estimates came from multip.le sources. For example, for summed
estimates, such as those for total program savings, Cadmus calculated the root of the sum of the
squared standard errors to estimate the confidence interval:27
Conf i.dence Intervalx*y = (N + D t 7.645 *
ln some cases, Cadmus multiplied estimates. For instance, net savings calculations involved combining
gross estimates with an ISR and/or NTG ratio estimated from participant surveys. For these results,
Cadmus calculated combined standard errors for the final estimates. ln cases where the relationship was
multiplicative, Cadmus used the following formula:28
conf id"ence Intervatx*r = X * Y + t.6+s. ]f' (;i) . f'l;)- (;f,) (;i)
To ensure transparency of the error aggregation process, Cadmus reported precision for both individual
and combined estimates, where relevant.
Th is a pproach to aggregating errors follows methods outlined in: Schiller, Steven, el al. " Nationol Action Plan
for Energy Efficiency." Appendix D.2007. Available online: www.epaepv/eeaetionplan.
Cadmus derived this formula from: Goodman, Leo. "The Variance of the Product of K Random Variables."
Journal of the American Statistical Association (1962).
t:
n
(#).(#)
48
Rocky Mountain Power
Exhibit No. 5 Page 873 of 1 365
Case No. PAC-E-'14-07
App*r'l$ix S: Ssrticiss$\t $uru*ey $mstrur*emt
$*$r*N*e$ism
Hello, my name is [INSERT FIRST NAME] from [INSERT COMPANY NAMEI. I'm calling on behalf of
[UTltlTYI to ask you some survey questions about the See ya later, refrigerator recycling program.
ltF RESPONDENT DOES NOT EXPRESS RESERVATIONS SKIP TO 51, lF RESPONDENT EXPRESSES
RESERVATIONS AT THIS POINT, PERSUADE:I l'm not selling anything, we are interested in your opinions
to help improve our programs, and to understand how to assist customers in saving money on their
utility bills. Your responses will remain confidential.
*$creesim gr Sses $sssss
51. According to our records, someone in your household signed up to recycle an appliance through
the [UTILITY] See ya later, refrigerator Program. Are you that person?
1. Yes
2. No
-98. DON',T KNOW [TERMINATEI
-99. REFUSED ITERMTNATEI
[ASK lF S1=2] ls that person available to speak with?
7. Yes [START FROM SI W|TH NEW RESPONDENT]
2. No [TERMINATE, ARRANGE CALLBACK lF POSSIBIE]
Were you present during the appliance pick-up?
1. Yes
2. No
-98. DON',T KNOW [TERMINATEI
-99. REFUSED [TERMTNATE]
[ASK lF S3=2] ls that person available to speak with?
1. Yes ISTART FROM SI WITH NEw RESPONDENTI
2. No [TERMINATE, ARRANGE CALLBACK lF POSSIBIE]
s2.
s3.
s4.
49
Rocky Mountain Power
Exhibit No. 5 Page 874 of 1365
Case No. PAC-E-14-07
db$e*s wre t derr*Sicc $j*n
A1. [ASK lF QUANTTW_REF>0] Program records indicate that you received an incentive for having
[INSERT QUANTTW_REF] refrigerator(s) recycled by the program around [INSERT DATE OF PICK-
UPl. ls this correct?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED [TERMINATE]
43.
[ASK lF A1=2 OR 98] How many refrigerators did you recycle through the [INSERT UTILITY]
program?
1. [RECORD] [lF A2=0, RECODE QUANTITY-REF=0I
-98. REFUSED
-99. DON'T KNOW
[ASK tF QUANTITY_FRZ>0I Program records indicate that you received an incentive for having
[INSERT QUANTTTY_FRZ] freezer(s) recycled by the program around [INSERT DATE OF PICKUPI.
ls this correct?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED [TERMTNATE]
IASK !F A3=2 OR 98] How many freezers did you recycle through the [INSERT UTILITY] program?
L. [RECORD] [lF A4=0, RECODE QUANTITY-FRZ=0]
-98. REFUSED
-99. DON'T KNOW
44,
50
"Swsr*stsss
81. How did you learn about the [INSERT UTILITYI appliance recycling program? [DO NOT READ
LtsT. RECORD UP TO THREE RESPONSESI
7. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power/Pacific Power Website
4. Other Website
5. lnternet Advertising/Online Ad
6. Family/Friends/Word-of-Mouth
7. Rocky Mountain Power/Pacific Power Representative
8. Radio
9. TV
10. Billboard/Outdoor Ad
L1. Retailer/Store
12. Sporting Event
13. Home Shows/Trade Shows
14. Appliance Recycling Contractor
15. Other [RECORD VERBATUMI
-98. DON'T KNOW
-99. REFUSED
51
82,
Roclry Mountain Power
Exhibit No. 5 Page 876 of 1 365
Case No. PAC-E-'14-07
What are the best ways for [INSERT UTILITY] to inform you about energy-efficiency offerings like
the appliance recycling program? [DO NOT READ. PROMPT lF NECESSARY. RECORD UP TO
THREE RESPONSESI
1. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power/Pacific Power Website
4. Other Website
5. lnternet Advertising/Online Ad
6. Family/Friends/Word-of-Mouth
7. Rocky Mountain Power/Pacific Power Representative
8. Radio
9. TV
10. Billboard/Outdoor Ad
11. Retailer/Store
12. Sporting Event
13. Home Shows/Trade Shows
14. Appliance Recycling Contractor
15. E-mailfrom Rocky Mountain Power/Pacific Power
16. Other IRECORD VERBATUMI
-98. DON'T KNOW
-99. REFUSED
How would you rate your current understanding of energy-efficiency? Would you say you...
IREAD LIST. RECORD FrRST RESPONSEI
L. Have no knowledge of energy-efficiency
2. Are somewhat knowledgeable about energy-efficiency
3. Are very knowledgeable about energy-efficiency
-98. IDO NOT READ] DON',T KNOW
-99. [DO NOT READI REFUSED
Appf$sst** Sescnptf*m
H1. [READ lN APPLIANCE CHARACTERTSTICS INCLUDED lN PARTICIPANT SAMPLE [TYPE = "REF" OR
"FRZ"I [TYPE DETAIL = CONFIGURATION (TOP FREEZER, CHEST, ETC.)] [ASK lF
QUANTITY_REF>0, AND QUANITITY_FRZ>O1 The next few questions focus on just one appliance.
Since you recycled more than one appliance, please answer these questions about the [INSERT
TYPEI [!NSERT TYPE DETATLI.
83.
52
Rocky Mountain Power
Exhibit No. 5 Page 877 of 1 365
Case No. PAC-E-14-07
H2,During the time just before you decided to get rid of the appliance, was it being used as your
main appliance, or had it been a secondary or spare? [lF RESPONDENT RECYCTED MORE THAN
ONE APPLIANCE, DIRECT THEM TO RESPOND REGARDING THE FIRST APPLIANCE THEY
RECYCLED.] [lF RESPONDENT lS UNSURE: ] A main refrigerator is typically in the kitchen, and a
spare refrigerator is usually in the garage or basement and might not be in use all the time.
1. Main
2. Secondary or Spare
-98. DON'T KNOW
-99. REFUSED
[ASK tF H2=21How long were you using it as a spare before you recycled it through the
program?
1. [RECORD VALUE lN MONTHS. lF RESPONDENT ANSWERS tN YEARS, MULTtpLy By 12 AND
RECORD VATUE tN MONTHSI
-98. DON'T KNOW
-99. REFUSED
During the year before you recycled it, was the appliance plugged in and running... [READ LIST]
1. Allthe time
2. For special occasions only
3. During certain months of the year only
4. Never plugged in or running
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
[ASK lF H4=2 OR H4=31 lf you were to add up the total time it was running as a spare in the last
year before you recycled it, how many months would that be? [!F RESPONDENT !S UNSURE:]
Your best estimate is okay.
1.. [RECORD MONTHS 1-121
-98. DON'T KNOW
-99. REFUSED
H3.
H4,
H5.
53
Roclry Mountain Power
Exhibit No. 5 Page 878 of 1 365
Case No. PAC-E-14-07
H6.Where was the [INSERT APPLIANCE TYPE] located during most of the year before you recycled
it?
L. Kitchen
2. Garage
3. Porch/Patio
4. Basement
5. Yard/Outside
6. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
Was the location heated?
L. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
Was the location air-conditioned?
t. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
Would you say the [!NSERT APPLIANCE WPE] you recycled... IREAD tlST. RECORD FIRST
RESPONSEI
1. Worked and was in good physical condition
2. Worked but needed minor repairs
3. Worked but had some major problems
4. Didn't work
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
H10. Did you get a new [INSERT APPLIANCE TYPE] to replace the one you recycled?
1,. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H7,
H8.
H9.
54
Rocky Mountain Power
Exhibit No. 5 Page 879 of 1 365
Case No. PAC-E-14-07
H11. [ASK tF H10=2] Do you plan to get a replacement appliance in the near future?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
HLz. IASK lF H10=1] Would you have purchased the new INSERT APPLIANCE TYPE] without the 530
incentive you received for recycling the old one?
1. Yes
2. No
.98. DON'T KNOW
-99. REFUSED
H13. [lF H10=1 AND H12=2] Just to confirm: you would 4! have replaced your old INSERT
APPLIANCE TYPEI without the [INSERT UTltlW] incentive for recycling, is that correct?
1. Correct
2. lncorrect
-98. DON'T KNOW
-99. REFUSED
H14. ls the [INSERT APPIIANCE TYPE] you replaced it with an ENERGY STAR or high-efficiency model?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H15. Had you already considered getting rid of this [INSERT APPLIANCE WPE] before hearing about
Il NSERT UTI LITY]'s a ppl ia nce recycl i ng progra m?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
H16. Without the existence of [INSERT UTltlTY] appliance recycling program, what would you most
likely have done with your old [INSERT APPLIANCE TYPE]? Would you have... [READ LIST]
t. Gotten rid of it
2. Kept it
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
55
Roclry Mountain Power
Exhibit No. 5 Page 880 of 1365
Case No. PAC-E-14-07
H77. [ASK H15=1] Would you have gotten rid of it within a year of when the program took it, or more
than a year later?
1. Within a year of when the program took it
2. More than a year later
-98. DON'T KNOW
-99. REFUSED
H18. [ASK H15=2] lf you had kept it, would you have used it full time, stored it unplugged, or used it
occasionally?
L. Used fulltime
2. Stored it unplugged
3. Used it occasionally
.98. DON'T KNOW
-99. REFUSED
H19. lf you had kept the [REFRIGERATOR, FREEZERI, would you have kept it in the same location you
mentioned earlier? That is would it have been located in [READ lN ANSWER FROM H6]?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
Ss$srSsrstf*m o$ Sf$ss$rsfr$es sst$ $resrudersfrfs
Now I have a few questions about the different options you might have considered before recycling your
appliance. For each statement, please tell me whether you gave serious consideration to the associated
action.
How would you have disposed of the unit if the program had not been available? [ALIOW ONIY
ONE ANSWERI [PROGRAMMER: LIST SHOUTD BE READ !N RANDOM ORDER]
1. Selling it to a private party (friend, family member, craigslist) [SKIP TO NEXT SECTION]
2. Selling it to a used appliance dealer
3. Giving it away for free private party (friend, family, craigslist) [SKIP TO NEXT SECTION]
4. Leave it on curb with free sign[SKIP TO NEXT SECTIONI
5. Give it away to charity organization
6. Having it removed by the dealer you got your new or replacement [INSERT APPLIANCE
TYPEI from [SKIP TO NEXT SECTIONI
7. Taking it to a dump or recycling center yourself [or friend or family member]
8. Hiring someone to take it to a dump or recycling center [SKIP TO NEXT SECIION]
F1.
56
Roclq Mountain Power
Exhibit No. 5 Page 881 of 1365
Case No. PAC-E-14-07
[READ !N UNIT AGE INCIUDED !N PARTTCIPANT SAMPTE] [lF F1=2 AND AGE >15 OR F1=5 OR
F1=7, THEN READ FZ ATONG WITH THE CORRESPONDING DETAIIS:I
[READ lF FL=2 AND AGE >151 Used appliance dealers typically only buy units that are less than
15 years old and are in very good condition.
[READ lF F1=5] Many charity organizations (such as Goodwill, Salvation Army) do not accept
large appliances.
[READ lF F1=7] Appliances are heavy and require a truck, trailer, or large vehicle to relocate.
Local waste transfer stations charge a fee to dispose of large appliances.
[lf F1=2 and AGE >15 OR F1=5 OR F1=7] lf you had not been able to [READ tN ANSWER FROM
Fll, how would you have disposed of it? [AILOW ONIY ONE ANSWER BUT DO NOT ALLOW
PREVTOUS ANSWERI
1. Selling it to a private party (friend, family member, craigslist)
2. Selling it to a used appliance dealer
3. Giving it away for free private party (friend, family member, craigslist)
4. Leave it on curb with free sign
5. Give it away to charity organization
5. Having it removed by the dealer you got your new or replacement [INSERT APPLIANCE
TYPEI from
7. Taking it to a dump or recycling center yourself (or friend or family member)
8. Hiring someone to take it to a dump or recycling center
9. Kept it
F19. Would you have participated in the program without the incentive check?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
$.*{. dsts$sjderfi*sr
E1. Was a free kit containing two CFL light bulbs and energy information given to you at the time of
pick-up?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
57
E2.
Rocky Mountain Power
Exhibit No, 5 Page 882 of 1 365
Case No. PAC-E-14-07
[lF E1*1, SKIP TO SP1] How would you rate the information found in this kit? Would you say it
was... [READ tlST]
1. Very helpful
2. Somewhat helpful
3. Not very helpful
4. Not at all helpful
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
IASK IF E2*98 OR 991 Why did you assign this rating? [DO NOT READ LIST. RECORD MUITIPLEI
1. lnformation was too general
2. Already aware of information
3. lnformation did not apply
4. Used the suggestions provided in information
5. Written well
6. Passed information along to others
7. Other [RECORD VERBATIM]
-98. DON'T KNOW
-99. REFUSED
How many of the CFLs that came in the kit did you install?
1. None
2. One
3. Two
-98. DON'T KNOW
-99. REFUSED
ESa. [ASK lF E4=2 OR 3l What type of bulbs were in the socket before you installed the CFLs? IREAD
usT rF NECESSARYI
1. lncandescent (or "traditional" bulbs)
2. Another CFL
3. LED
4. Florescent
5. Halogen
6. Empty
-98. DON'T KNOW
-99. REFUSED
E4.
58
E5.
Rocky Mountain Power
Exhibit No. 5 Page 883 of 1 365
Case No. PAC-E-14-07
E5b. [ASK lF E4=1 OR 2l Why didn't you install [lF E4=1, "them?" lF E4=2, 'the other CFL?" [DO NOT
READ ttST. RECORD MULTIPIEI
1. Did not fit fixtures
2. lntend to install later
3. Do not like style
4. Do not like quality
5. Defective product
6. Other [RECORD VERBATIM]
-98. DON'T KNOW
.99. REFUSED
[ASK lF E4=2 OR 3] Where did you install the CFL(s)? IDO NOT READ. RECORD UP TO TWO]
L. Bedroom
2. Bedroom(unoccupied)
3. Basement
4. Bathroom
5. Closet
5. Dining Room
7. Foyer
8. Garage
9. Hallway
10. Kitchen
11. Office/Den
12. Living Space
13. Storage
14. Outdoor
15. Utility
16. Other [RECORD VERBATIM]
-98. DON'T KNOW
.99. REFUSED
Did you install the refrigerator thermometer included in your energy-savings kit?
1. Yes
2. No
.98. DON'T KNOW
.99. REFUSED
E7.
59
Rocky Mountain Po,er
Exhibit No. 5 Page 884 of 1 365
Case No. PAC-E-14-07
E8.[ASK lF E7=1, ELSE SKIP TO E10l After installing the thermometer, did you change the
temperature setting on your refrigerator?
1. Yes
2. No
-98. DON'T KNOW
.99. REFUSED
[ASK lF E7=1, ELSE SKIP TO E10l Did you increase or decrease the temperature setting in your
refrigerator?
1. lncrease
2. Decrease
-98. DON'T KNOW
-99. REFUSED
E10. Do you remember receiving a booklet with information about how to save energy?
L. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
E11. IASK lF E10=1, ELSE SKIP TO SP1] Have you followed any of the advice mentioned in the
booklet? lf so, what advice?
1. Yes, [RECORD VERBATIM]
2. No
-98. DON'T KNOW
-99. REFUSED
$pr$f*v*r smd &$sr&sf $$rSs$S
SP1. Since participating in the See ya later, refrigerator Program, have you participated in any other
incentive programs offered by [INSERT UTILITY]?
t. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
E9.
60
RoclV Mountain Power
Exhibit No. 5 Page 885 of 1365
Case No. PAC-E-14-07
SP2. [ASK lF SPI=U Which programs did you participate in?
1. [RECORD VERBATIMI
-98. DON'T KNOW
-99. REFUSED
SP3. [ASK lF SP1=11 How influential was the recycling program in your decision to participate in other
[INSERT UTILtW] energy-efficiency programs? Would you say it was... [READ tlST]
t. Very influential
2. Somewhat influential
3. Not very influential
4. Not at all influential
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
SP4. IASK !F SP1=2] Based on your experience in recycling your appliance, how likely are you to
participate in another utility energy-efficiency program? Would you say you are... [READ LISTI
1. Much more likely
2. Somewhat more likely
3. No more or less likely
4. Less likely to participate in another program
-98. [DO NOT READ] DON'T KNOW
-99. [DO NOT READ] REFUSED
SP5. Besides recycling your old [APPIIANCE TYPE], have you made other energy-efficiency
improvements or purchases on your own since participating in the appliance recycling program?
7. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
SP6. [ASK !F SP5=1] What did you install or purchase? [DO NOT READ. RECORD MUITIPLE]
1. High-efficiencydishwasher
2. High-efficiency washing machine
4. High-efficiency refrigerator
5. High-efficiency water heater
5. CFLs
7. Other [RECORD VERBATIM]
-98. DON'T KNOW
.99. REFUSED
67
Roclry Mountain Power
Exhibit No. 5 Page 886 of 1 365
Case No, PAC-E-14-07
SP6a. [ASK !F SP5=1] Did you receive an incentive for any of those items?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
SP7. [ASK lF SPS=U How much did your experience with the See ya later, refrigerator Program
influence your decision to install other high-efficiency equipment on your own? Would you say
it was... [READ LIST]
1. Very influential
2. Somewhat influential
3. Not very influential
4. Not at all influential
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
Sr*gr*mt Sofssf*ctf**
G1. How satisfied are you with the [INSERT UTILIW] See ya later, refrigerator Program overall?
Would you say you are... [READ LIST]
1. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
G2.[ASK lF Gt=2,3, or 4] Why do you give it that rating? [DO NOT READ. RECORD MULTIPLE]
1. lncentive was too small
2. Contractor never called me back
3. Contractor never showed up/showed up late
4. Contractorwas unreliable/unprofessional
5. Difficult to get an appointment time that was convenient for me
6. Wanted to use a different (non-program) contractor
7. Other [RECORD VERBATIM]
-98. DON'T KNOW
-99. REFUSED
62
G3.
G4,
G5.
Rocky Mountain Power
Exhibit No. 5 Page 887 of 1365
Case No. PAC-E-14-07
How satisfied are you with the sign-up process for the program? Would you say you are... [READ
usrl
1. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READI REFUSED
How easy was it to schedule a convenient pick-up time? Would you say it was... [READ LIST]
1. Very easy
2. Somewhat easy
3. Somewhat difficult
4. Very difficult
-98. [DO NOT READ] DON',T KNOW
-99, [DO NOT READ] REFUSED
How satisfied are you with the appliance pick-up portion of the program? Would you say you
are... [READ LIST]
1. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. [DO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
Did the crew that picked up your appliance check to see if it was working before they took it
away?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
G6.
63
Rocky Mountain Power
Exhibit No. 5 Page 888 of 1 365
Case No. PAC-E-14-07
G7,How satisfied are you with how quickly you received your incentive? Would you say you are...
IREAD LrSTI
L. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. IDO NOT READ] DON',T KNOW
-99. IDO NOT READI REFUSED
How satisfied are you with the amount of the incentive? Would you say you are... IREAD IISTI
1. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. [DO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
Would you have participated in the program if the amount of the incentive had been less?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
G8.
G9.
G10. How likely are you to recommend the [INSERT UTltlTY] See ya later, refrigerator Program to
friends and family members? Would you say you are... [READ tlST]
1. Very likely
2. Somewhat likely
3. Not very likely
4. Not at all likely
-98. [DO NOT READI DON',T KNOW
-99. IDO NOT READ] REFUSED
G11. ls there anything you would suggest to improve the [INSERT UTIIITYI See ya later, refrigerator
Program?
1. [RECORD VERBATTM]
-98. DON'T KNOW
-99. REFUSED
54
D1.
Roclry Mountain Power
Exhibit No. 5 Page 889 of 1 365
Case No. PAC-E-14-07
Ssrtts*srspSsss
I have just a few more questions about your household. Again, all your answers will be strictly
confidential.
Which of the following best describes your house? [READ tlST]:
1. Single-family home
2. Townhouse or duplex
3. Mobile home or trailer
4. Apartment building with four or more units
s. Other IRECORD]
-98. [DO NOT READ] REFUSED
-99. IDO NOT READ] DON',T KNOW
D1A. About how old is your home?
1.. [RECORD # YEARS OLD - tF ACTUAL YEAR tS PROVIDED, TRANSTATE TO YEARS REIATIVE TO
20111
.98. DON'T KNOW
-99. REFUSED
D2,Do you rent or own your home?
1,. Own
2. Rent
3. Other [RECORD]
-98. REFUSED
-99. DON'T KNOW
How long have you lived at that location?
t. Less than one year
2. Two to five years
3. More than five years
-98. REFUSED
-99. DON'T KNOW
lncluding yourself and any children, how many people currently live in your home?
1. IRECORD]
-98. REFUSED
-99. DON'T KNOW
D3.
D4.
65
Rocky Mountain Power
Exhibit No. 5 Page 890 of 1365
Case No. PAC-E-14-07
D5.
D6.
D4a. [ASK lF D4 >U Are any of the people living in your home under the age of 18?
L. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
Can you please tell me in what year you were born?
1. IRECORDI
-98. REFUSED
-99. DON'T KNOW
ln 2010, was your pre-tax household income above or below 550,000?
1. Below 550,000
2. Above 550,000
3. Exactly S50,000
-98. DON',T KNOW [SK!P TO Cl]
-99. REFUSED ISKIP TO CU
IASK IF D6=1] Which of the following categories best represents your household income in
2010? Please stop me when I read your category:
t. Under S10,000
2. S10,000 to under 520,000
3. 520,000 to under S3o,o00
4. 530,000 to under 540,000
5. 540,000 to under 550,000
-98. REFUSED
-99. DON'T KNOW
[ASK lF D5=2] Which of the following categories best represents your household income in
201-0? Please stop me when I read your category:
t. 550,000 to under $60,000
2. 550,000 to under 575,000
3. 575,000 to under S100,000
4. S100,000 to under 5150,000
5. S150,000 to under 5200,000
6. 5200,000 or more
-98. REFUSED
-99. DON'T KNOW
D7.
D8.
66
Rocky Mountain Power
Exhibit No.5 Page 891 of 1365
Case No. PAC-E-14-07
D9.What is the primary heating source for your home? [READ LIST lF NEEDED]
1. Forced air natural gas furnace
2. Forced air propane furnace
3. Air source heat pump
4. Ground source heat pump
5. Electric baseboard heat
6. Gas fired boiler/radiant heat
7. Oil fired boiler/radiant heat
8. Passive solar
9. Pellet stove
10. Wood stove
11. Other [RECORD]
-98. DON'T KNOW
-99. REFUSED
D10. [lF D9=1-11] How old is the primary heating system? [RECORD RESPONSE lN YEARS]
1. IRECORD 1-100]
-98.Don't Know
-99. Refused
D1.1. What type of air conditioning system, if any, do you use in your home? [READ tlST lF
NECESSARY, INDICATE AtL THAT APPLYI
1. Central Air Conditioner
2. Room Air Conditioner
3. Evaporative Cooler
4. Air Source Heat Pump
5. Ground Source Heat Pump
6. Whole House Fan
7. No Cooling System Before
8. Other IRECORD]
-98. IDO NOT READ] DON',T KNOW
-99. [DO NOT READ] REFUSED
Dt2. [ASK lF DLl*71How old is your primary cooling system?
L. [RECORD RESPONSE lN YEARSI
-98. DON'T KNOW
-99, REFUSED
67
Roclry Mountain Po,ver
Exhibit No. 5 Page 892 of 1 365
Case No. PAC-E-14{7
$*staj*ssssr
C1. How satisfied are you with the service that [INSERT UTltlTY] provides overall? Would you say
you are... IREAD tlST]
1. Very satisfied
2. Somewhat satisfied
3. Somewhatdissatisfied
4. Very dissatisfied
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READI REFUSED
Do you have any additional feedback or comments?
1. Yes [RECORD VERBATUM]
2. No
-98. REFUSED
-99. DON'T KNOW
That concludes the survey. Thank you very much for your time and feedback.
c2.
68
Roclq Mountain Power
Exhibit No. 5 Page 893 of 1 365
Case No. PAC-E-14-07
Appest$$x $: N*npmrt$c$pmnt $urseg $srstvusmssnN
Jm$r*Sss$i**t
Hello, my name is [INSERT FIRST NAMEI from IINSERT COMPANY NAME]. l'm calling on behalf of
[UTILITY] to ask you some survey questions that will help [UTlLlTYl improve their energy-efficiency
programs.
[tF RESPONDENT DOES NOT EXPRESS RESERVATTONS, SKIP TO 51. tF RESPONDENT EXPRESSES
RESERVATIONS AT THIS POINT, USE THE FOLLOWING SCRIPT TO PERSUADEI: l'm not selling anything,
we are interested in your opinions to help improve our programs, and to understand how to assist
customers in saving money on their utility bills. Your responses will remain confidential.
.$" Ssss*r"s.,..er$ Ssesffstts
51. Did you discard a refrigerator or freezer in 201L or 2012? By discard, we mean getting rid of it
either by selling it, giving it away, having someone pick it up, or taking it to the dump or a
recycling center.
1. Yes, refrigerator(s)
2. Yes, freezer(s)
3. Yes, both appliances
4. No [TERMINATE]
-98. DON',T KNOW [TERMINATE]
-99. REFUSED [TERMTNATE]
Did the appliance(s) work? [lF RESPONDENT lS UNSURE, SAY:I Even if it didn't get cold, did the
appliance turn on when it was plugged in?
7. Yes
2. No [TERMINATE]
-98. DON',T KNOW [TERMINATEI
-99. REFUSED ITERMTNATEI
Did you have the appliance(s) picked up through [INSERT UTILITY]'s See ya later, refrigerator
Program?
1. Yes [TERMTNATE]
2. No
-98. DON',T KNOW ITERMINATE]
-99. REFUSED ITERMTNATE]
s2.
s3.
59
s4.[INSERT UTltlTY] offers an incentive to pick up and recycle old working refrigerators and
freezers. lf you had participated, a contractor would have picked the appliance up at your home
and provided you with S30 later in the mail. Are you sure your appliance wasn't picked up by the
utility program?
1. Yes, l'm sure it wasn't picked up by the program or I received no incentive
2. No, I did get the incentive check [TERMINATE]
-98.I still don't know for sure ITERMINATE]
-99. REFUSED [TERMTNATE]
[TERMINATION SCRIPT: "Those are all the questions we have for you. Thank you very much for your
time."]
&{. Sei.*psr$i'cipem $, S ursrs$sss
N1. Were you aware of the [INSERT UTltlTY]appliance recycling program priorto getting rid of your
appliance?
1. Yes
2. No
-98. DON'T KNOW
-99. REFUSED
70
Rocky Mountain Power
Exhibit No. 5 Page 895 of 1 365
Case No. PAC-E-'14-07
N2.[ASK tF N1=1, ELSE SKIP TO N4] How did you learn about the [INSERT UTILITY] appliance
recycling program? [DO NOT READ LIST. RECORD UP TO THREE RESPONSESI
1. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power/Pacific Power Website
4. Other Website
5. lnternet Advertising/Online Ad
6. Family/Friends/Word-of-Mouth
7. Rocky Mountain Power/Pacific Power Representative
8. Radio
9. TV
10. Billboard/Outdoor Ad
11. Retailer/Store
12. Sporting Event
13. Home Shows/Trade Shows
14. Appliance Recycling Contractor
15. Other IRECORD VERBATIM]
16. Postcard
17. Direct Mail
-98. IDO NOT READ] DON',T KNOW
-99. IDO NOT READ] REFUSED
What made you decide not to have your appliance picked up through the [INSERT UTILITY]
appliance recycling program? [DO NOT READ. RECORD UP TO THREE RESPONSES.]
1. Unit didn't qualify
2. Did not know how to sign up
3. Was not able to schedule a convenient pick-up time
4. Too much hassle
s. Other [RECORD VERBATUM]
-98. DON'T KNOW
-99. REFUSED
N3.
71
N4.
Rocky Mountrain Power
Exhibit No. 5 Page 896 of 1 365
Case No. PAC-E-1447
What are the best ways for [INSERT UTILITY] to inform you about energy-efficiency offerings like
the appliance recycling program? IDO NOT READ. PROMPT tF NECESSARY. RECORD UP TO
THREE RESPONSESI
L. Newspaper/Magazine/Print Media
2. Bill lnserts
3. Rocky Mountain Power/Pacific Power Website
4. Other Website
5. lnternet Advertising/Online Ad
6. Family/Friends/Word-of-Mouth
7. Rocky Mountain Power/Pacific Power Representative
8. Radio
9. TV
10. Billboard/Outdoor Ad
11. Retailer/Store
12. Sporting Event
13. Home Shows/Trade Shows
14. Appliance Recycling Contractor
15. E-mailfrom Rocky Mountain Power/Pacific Power
16. Other [RECORD VERBATUMI
17. Postcard
18. Direct Mail
-98. DON'T KNOW
-99. REFUSED
How would you rate your current understanding of energy efficiency? Would you say you...
IREAD L!ST. RECORD FIRST RESPONSEI
1. Have no knowledge of energy efficiency
2. Are somewhat knowledgeable about energy efficiency
3. Are very knowledgeable about energy efficiency
-98. [DO NOT READI DON',T KNOW
-99. [DO NOT READ] REFUSED
"$" "$ppdismss $Ssessferfs fsss
[!F MORE THAN ONE APPIIANCE WAS DISCARDED, SAY:] For the rest of the survey, l'd like you to focus
on only one of the appliances you got rid of. Please answer these questions about the appliance you
discarded most recently.
[!F ONIY ONE APPIIANCE WAS DISCARDED, SAY:] For the rest of the survey, we would like to ask you
about the appliance you discarded.
N5.
72
Rocky Mountain Power
Exhibit No. 5 Page 897 of 1 365
Case No. PAC-E-14-07
A1.
42.
44.
A5.
43.
At the time you discarded it, approximately how old was the appliance?
1. [RECORD AGE lN YEARS]
-98.Don't know
-99. Refused
Before you made the decision to get rid of the appliance, in what room was the appliance
used/located?
1. Kitchen
2. Garage
3. Porch/patio
4. Basement
s. other [RECORD]
-98.DON'T KNOW
-99. REFUSED
Would you say the appliance ...? [READ LIST, RECORD ONLY ONE RESPONSEI
1. Worked and was in good physical condition
2. Worked but needed minor repairs
3. Worked but had some major problems
-98.[DO NOT READ] DON',T KNOW
-99.[DO NOT READ] REFUSED
Did you get a new appliance to replace the one you got rid of?
1. Yes
2. No
-98.DON'T KNOW
-99. REFUSED
[ASK lF A4=L, ELSE SKIP TO A5] ls the appliance you replaced it with an ENERGY STAR or high-
efficiency model?
1. Yes
2. No
-98.DON'T KNOW
-99. REFUSED
73
A6.
Serst*grrsgSics
D1. Which of the following best describes your house? [READ LIST]:
1. Single-family home
2. Townhouse or duplex
3. Mobile home or trailer
4. Apartment building with four or more units
s. other [RECORD]
-98. [DO NOT READ] REFUSED
-99. [DO NOT READ] DON',T KNOW
Do you rent or own your home?
L. Own
2. Rent
3. Other [RECORDI
-98. REFUSED
-99. DON'T KNOW
How long have you lived at that location?
1.. Less than one year
2. Two to five years
3. More than five years
-98. REFUSED
-99. DON'T KNOW
Rocky Mountain Power
Exhibit No. 5 Page 898 of 'l 365
Case No. PAC-E-14-07
How did you get rid of your old appliance? [lF NEEDED, PROMPT:] For example, did you sell it or
give it away?
1. Sold it to a private party, either by running an ad or to selling to someone I know
2. Sold it to a used appliance dealer
3. Gave it away to a private party, such as a friend or neighbor
4. Gave it away to a charity organization, such as Goodwill lndustries or a church
5. Had it removed by the dealer I got my new or replacement appliance from
6. Hauled it to the dump myself
7. Hauled to a recycling center myself
8. Had someone else pick it up for junking or dumping
9. Kept it
10. Some other way IRECORD VERBATIM]
-98.DON'T KNOW
-99. REFUSED
D2.
D3.
74
D6.
Roclry Mountain Power
Exhibit No. 5 Page 899 of 1365
Case No. PAC-E-14-07
D4,lncluding yourself and any children, how many people currently live in your home?
L. [RECORD]
.98. REFUSED
-99. DON'T KNOW
Can you please tell me in what year you were born?
1. [RECORDI
-98. REFUSED
-99. DON'T KNOW
In 2010, was your pre-tax household income above or below 550,000?
7. Below 550,000
2. Above 550,000
3. Exactly 550,000
-98. DON',T KNOW [SK!P TO CIOSING STATEMENT]
-99. REFUSED [sKrP TO CLOSTNG STATEMENTI
[ASK tF D5=1] Which of the following categories best represents your household income in
2010? Please stop me when I read your category:
1. Under 510,000
2. S10,000 to under 520,000
3. 520,000 to under 530,000
4. Sgo,ooo to under S4o,ooo
5. 540,000 to under 550,000
.98. REFUSED
.99. DON'T KNOW
[ASK lF D5=2] Which of the following categories best represents your household income in
2O7O? Please stop me when I read your category:
1. S5o,ooo to under 560,000
2. 560,000 to under 575,000
3. $75,000 to under 5100,000
4. 5100,000 to under 5150,000
5. S150,000 to under 5200,000
6. 5200,000 or more
-98. REFUSED
-99. DON'T KNOW
D5.
D7,
CLOSING SCRIPT: Those are all the questions I have. IINSERT UTltlTY] appreciates your input. Thank you
for your time.
D8.
75
Roclq Mountain Power
Exhibit No. 5 Page 900 of 1 365
Case No. PAC-E-14-07
&pg:*m$ix $: Lmg$* N$sSe$
75
Rocky Mountain Power
Table E-t lists the working hypotheses and indicators for each numbered item in the logic model.
t2
ii3
Marketing and outreach lead to targeting
communications to residential customers
with refrigerators and freezers and those
who recently purchased a new unit.
i;;iliGr [;J io .r'1o.";r ";;;iii;; i; ih;
, relevant to the evaluation.
4 : Quality control lead to inspections being
, oerfoT-"9: .5 ; The delivery of marketing materials lead to
I: increased customer awareness regarding
, gneley eff.lclenw an! ]he r1os13m:.
5 i Marketing efforts lead to customers
i enrolling in program.
''''i
I Customer participation results in removing
i inefficient appliances from the grid.
i The evaluation leads to confirming program
effectiveness.
lnspections and reviews lead to confirming
program effectiveness.
10 i Education leads to program awareness.
Removing inefficient appliances from the
grid teads lo in:reased pfoclam peneiiatign:
Removal of inefficient appliances leads to
kWh and kW lavine1,
kWh and kW savings leads to persistent
{ema1d yvins: . .
Confirming effective program operations
lead to verified program savings.
Rocky Mountain Power
Exhibit No. 5 Page 902 of 1 365
Case No. PAC-E-14-07
Number of eligible potential participants that express
interest; marketing materials in bill inserts, on company
website, in schools, in newspapers and on radio; presence
at seminars, conferences, home shows, and community
events
N;rb;.;i ;rniiipr"ii; p;,.ti.il;;i i;i"*i"*' i"iiiri" "irole of incentives on enrollment activities
Number of inspections indicate that quality control
occurred
r;;;;;;il ilit"r"i r*ri;;;;; ;&;;Jiil;;;igv ;ffi;i#t
identified in surveys
N;;ue'."f priiiiipr"ir "nioir"o in *,e proei;; ;h;
!n!1cLte 1l9y w91e leached by m1$etilc "ff-olfNumber of appliances recycled due to participation in the
program
il pie,;t; i"iJirie*s iq;;iiliir;i; ;;"irr[ion ia"niiir"i
best practices
lmplementer interviewi (qualliative); inspeiiions anJ
1eviewl !1{ica}eg 1: imployin-c plggf m gffggljvene;:
Participant interviews (qualitative) indicate that education
led to program awareness
N;;uo;i;tpii;;;; i;;t;i;d ;,il;"0 io ","i.rrmarket
Energy/demand savings generated expressed in kW and
kwhi#;tl;il;il ;ili;;;;;"i ii,"; p,,tilipini i,t",,i;;
191ult1 lndicalinc r"S:-yf geSigence
lmplementer interviews (qualitative); effective program
theory and demonstrated links indicate savings are
attributable to the program
lmplementer interviews (qualitative); program operations
confirmed as effective
lri.i"t"* r"i, iti r"grrJing r*;r;;;;; ; ;J ;;illiil;
behavior
M;;k;i;iily i"rriii "r ""muJ. ot appiianlei ieivli;Ji
participantilterviewres.y,,,,,,,,,,,,,.!!11ega1d jnemeasure
; plo-913m:
: Measurement and verification provided data Completed evaluation informs future program cycles
7
8
LI
13
ii
15
15
Confirming effective program operations
lead to the maintenance of optimum
performance.
lncreased program awareness lead to fewer
ineffi.gielt annllancel on the erid:
Fewer inefficient appliances on the grid lead
lo per:i:tent energy- savings.
Yahle $-I^, See ya later. refrig*rat*r Frogran'r lcgic $vt*d*l linlcs: Working Nyp*theses amS lndicatqrrs
L7
77
Rocky Mountain Power
Exhibit No. 5 Page 903 of 1365
Case No. PAC-E-14-07
18 Verified program savings lead to persistent
energy and demand savings.
Verified program savings lead to Rocky
Mountain Power gaining experience with
desiSninS and malkellnS plograms:
Maintaining optimal performance lead to
Rocky Mountain Power gaining experience
with designing and marketing programs,
Fewer inefficient appliances on the grid lead
to environmental benefits.
Fewer inefficient appliances on the grid lead
to achieving tong term energy savings,
Persistent energy savings lead to achieving
long-term energy savings.
Rocky Mountain Power gained experience
with designing and marketing programs,
which lead to achievement of long-term
energy savings goals.
persistence
i";,;tid;;;;J;;;i;s;o,; ii;;;il;ii"a in tw ,no
kwh
lmplementer interview results (qualitative); results of
increased experience investigation
irpier"nter interview r"irrii iqririiritr"il i"iriti ri
increased experience investigation
eneigy/Oemand savings quantified using engineering
estimates; analysis of reduced need to build power plants;
environmental impacts of power plants that were not built
quantified using data from the U.S. Environmental
Protection Agency and other secondary data
rnergy/UemanA iJvineii i".tviit oi i"OuleU neeO to build
powel llants
Energy/demand savings expressed in kW and kWh using
engineering analysis and assessed over time
r;tffi;;iei inieirie* i"irii' i.qriiiiiiiv;i ;;s;;Ji;;
whether the experience is positively impacting program
processes and outcomes
19
20
2t
78
Rocky Mountain Power
Exhibit No. 5 Page 904 of 1 365
Case No. PAC-E-14-07
Nppe*$ix S: Ns$rig*sstss" NTS S*snhNs"r*S Seq$s$srs T's"**
;ij**,,***-.--l:li-***--'r
rnr iq,.{ ltzt iT*r :i -::-- ::r- r
:.:'. F* i :::': j-::::-:r
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:,i:;i;;i;;;;;i;. ..,,.,,,.:,,,, :
Fi[{..FR-:*I*i-tlrlry{s; S^rr\s rxi rii iiesr.{te€}iilj ass*K$ri*ry {s$el:i*rFNi
t:::::::::::a,aa:a:a,a:::a:::l::at:::::::'::::.:l:::,:'t':'t:::::::::::::':::::t:a'aa.:,
'll::l :,, '
i***i"*-*\ =,,_*"^"*.ir*******--.] -,'.\--.'i*-j
iiii:,.:;;;:;.,:.,.,,.ii,.,,,i***'*T'**-""-"i * r"*-,;'*)i..*'.-.**.:-..-.*.*.l *'!--:*'
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i"ll)""rL:,:J]
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::::::i j:;:::::::Rls-{t:Nsimi:;: r:::r: :r:rt:: ::::::::::laT{{t, ;::::
,.i,ifls**o{|Y,.,.,.,. ii i:ii::tr[l:iiiiiii
,.-i:,:,. ::::.i,-- ---- -\- .i I l',r: =:::::i ls I
* ! ,:i*;.'''' \- ' \-....:*--.1
ilil'flil+fl]=:. l$[:,$]
sf! q{ qn} *iti\ istlr+so-}*1r lF}tovsR :,:viBdNi'} tr$s.Jw}
79
Rocky Mountain Power
Exhibit No. 5 Page 905 of 1 365
Case No. PAC-E-14-07
&ppss:S$x $: $r.ssss$ NTS Sssmh$steS S**isi*n T'ss*
$ltNQt:{qr$E.f:sr{::::
::ii iiii lill:iillt$i0$tq:rtit::r;::
i*'*'*--;*-"*""""'i, * iii:i*"*\1-_- : .J-i:,J:.ji
--*-:--.-:__-_- . .:: *i ,,f,ffiNET..FR*SiS.lt$yhi Sa{irts ssl rri lw$r!{eplri, ard se*{r.l*r\ r*i\rt hs*s
:l:::l:l:i&iSBS;:i:i:::::l{R${p-&?s*3 SN3$rDA4mn:::i:i:i:::iiii, iiiiifll$Iqi|I6lli.iiN.*ffiS::::i:i:i:::i:i:::ii: i ::SlW tnfnslFs\wflr$.tt.::.:: ffiiffi6r.r.r.:.
:!$ !*+i n I -.-------....-.,1::i:::::: i::::1..* - -rrl
$lnuc$q-.hrrthr !$d!re$ C$r$s:i*t{fl
:::iii:ii,::ti!$tfr.:F,s$rd|F..1l1.Rli:;i:::::ri tl
:.:.ii ii :;::;.iirwlil9glr"ff 'q'$iiiii:iiriiiiirrrll*****;-i,$::::,"::::==:=*S,{5sit nctr-,iN,s:Nta^s.s.s _jilHilH::*:::::::i,il[i:liuiI ---."*... .-...... ..:
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ii:iii:.iligl';:..;.;.;i-.-...-\
!iriiiiiiii:iil:iii;:ii:i:ii:i::::J*'..'*1\*:**j
tl:ltltltlt:tl:lt::l :lt:tl:t::::t:
i*i
[sl:'fil*ffif,,= i":fffiq*l
SS-r+t*.-SSt.lrSn rNStaF$-i*Ir arlII$l€R :vSP-irSt{li3;sRi
r+J'I l$e's-Il{sfi! lqc*.&sii+**/
:[T: :_ \: jl 5& I;i*irl i,wrs:r.sxili:..iS: .;i
80
Rocky Mountain Power
Exhibit No. 5 Page 906 of 1 365
Case No. PAC-E-14-07
&pBemSix ${: SF$" Smg$steering Cm$cu$mti*c}s nnd Assts$T}$tisr$$
$Ss*rs-s${,Jss
Cadmus estimated CFL HOU using a multistate modeling approach, built on light logger data collected
from five states: Maine, Maryland, Michigan, Missouri, and Ohio. Cadmus chose these data rather than
data from the most recent California evaluation primarily because allthese states have relatively new
CFL programs compared to California, where residential CFL programs have been in place for more
years.
tV$etering Srst**ml
Following whole-house lighting audits, Cadmus installed up to five loggers in each participant home.
Metering periods varied by utility, ranging from three months to one year. For homes with five or fewer
CFL fixture groups, Cadmus installed light loggers on every CFL fixture. For homes with more than five
CFL fixture groups, Cadmus randomly selected which five fixtures to meter. This method relied on
systematic sampling, which involved installing a logger on every ntn CFL fixture (the n'h number was also
based on the number of total possible CFL fixtures).
During the logger removal process, Cadmus collected additional data for evaluating data quality and for
determining if loggers had failed, been tampered with, or been removed. Moreover, prior to removing
each logger, Cadmus noted whether the logger had been correctly installed and the orientation of its
sensor.
lVls$el $pecifi*atisrn
To estimate HOU, Cadmus determined the total time each individual light logger was on per day, using
the following guidelines:
o lf a light logger did not record any light for an entire day, the day's HOU was set to zero.
o lf a light logger registered a light turned on at 8:30 p.m. on Monday, and turned off at l,:30 a.m.
on Tuesday morning, 3.5 hours were added to Monday's HOU and 1.5 hours to Tuesday's HOU.
Cadmus modeled both weekday and weekend daily HOU as a function of room type, the presence of
children in the home, and CFL saturations in the home. This was done using two analyses of covariance
(ANCOVA) models, one for each day type.
ANCOVA are regression models for a continuous variable as a function of a single, continuous
explanatory variable (in this case, CFL saturation) and a set of binary variables. This way, an ANCOVA
model simply serves as an analysis of variance (ANOVA) model with a continuous explanatory variable
added. Cadmus chose this specification due to its simplicity, making it suitable in a wide variety of
contexts. Though the model lacks the specificity of other methods, it offers estimates that are not nearly
as sensitive to small differences in explanatory variables compared to more complex methods.
Therefore, these models can produce consistent estimates of average daily HOU for a given region,
using its specific distribution of bulbs by room and household type, and by the existing CFL saturation.
81
Rocky Mountain Power
Exhibit No. 5 Page 907 of 1365
Case No. PAC-E-14-07
Cadmus specified final models as cross-sectional, ANCOVA regressions for day type" fi), and bulb (i), as:
Average Daily HOU1,i
= Bo * P{FL Saturotioni } B2Kidsi * fuKitcheni * paBasementi * B5outdoori
* B5Bedroomi * BTBathroomi * psotheri
Where:
CFL Saturation
Kids
Kitchen
Basement
Outdoor
Bedroom
Bathroom
Other
The proportion of CFL bulbs in the home;
A dummy variable3o equal to one if children under 18 live in the
home, and zero otherwise;
A dummy variable equal to one if bulb is in kitchen, and zero
otherwise;
A dummy variable equal to one if bulb is in basement, and zero
otherwise;
A dummy variable equal to one if bulb is outdoors, and zero
otherwise;
A dummy variable equal to one if bulb is in bedroom, and zero
otherwise;
A dummy variable equal to one if bulb is in bathroom, and zero
otherwise; and
A dummy variable equal to one if bulb is in a low-use room (such as
a utility room, laundry room, or closet), and zero otherwise.
Cadmus tested the potential influences of other demographic and regional variables in model
specifications, such as: latitude, income, education, and home characteristics. These variables'
estimated coefficients did not differ significantly from zero or produced signs inconsistent with
expectations.
$i n*l Ssti m'rates *rs"rd Sxtrnp*$*ti*n
As shown in Table H-1, not all of the two models' estimated coefficients differed significantly from zero
for both day types, most likely due to differences in schedules between days. Nevertheless, Cadmus
included the same independent variables in each model for better cross comparability.
The two day-types for this analysis were weekend and weekday. Cadmus defined weekends as Saturday and
Sunday as well as the following federally recognized holidays: Christmas, Thanksgiving, Labor Day, Memorial
Day, New Year's Day, Fourth ofJuly, Presidents' Day, and Veterans' Day.
Dummy variables are binary, taking only values of either zero or one. Coefficients for these variables can be
interpreted as the difference in mean values between the two mutually exclusive groups.
82
2.38 <.0001
Roclly Mountain Power
Exhibit No. 5 Page 908 of 1 365
Case No. PAC-E-14-07
2.77
Tahle t{-1. HSt-f S$sd*l ANC*VA Sstin'rates
CFL Saturation
iie;
Kitchen
eaiementilia;;
Bil;;;;
e;ir',r;;
Other
-0.82
0.94
i.is
o.i3
i.ii
0.08
o.oi
o.oo
0.78
oi.iz
-0.34
r.)s
o.ri
-1.29
-0.0,
<.0001
o.l7
o.io
o.ti
o.oo
0.98
-1.06 0.00 -7.57 0.00
-0.85 0.05 o.92
-1.91
0.62
:.oooi-1.36 i 0.01
* P-values indicate the degree of confidence that the given coefficient equals zero. ln other words, it is the
probability that the effect of a given variable on HOU is random. Therefore, a lower p-value indicates a higher
degree of confidence in the estimated effect.
Cadmus used these model parameters to predict the average daily use of SYLR energy-savings kit bulbs
by taking the sum of the product of each coefficient shown in Table H-1, and its corresponding average
independent variable. Table H-2 shows the independent variables used for SYLR. Except for CFL
saturation, Cadmus estimated independent variables using 2011-2012 participant survey data. Due to a
lack of detailed CFL saturation data for Rocky Mountain Power's ldaho service area, Cadmus used
secondary data to estimate CFL saturations by room."
, CFL Saturation
. K!d:
, x!t9ne1
, Basemen!
, Outdoor
, Bedroom
, Balhroom
: Other t9o/o
Cadmus used an average CFL saturation from service areas with relatively new programs, taken from: Albee,
K., et al, "One Analysis to Rule Them AII and ln the Darkness Give Them CFLs." ln proceedings of the 2077
IEPEC Conference. lnternational Energy Program Evaluation Conference, Boston, Massachusetts, August 15-18,
2077.
28%
ii%
ii,%
4o/o
i,%
77%
iii/"
Tnh$* ${-R. \N*sls$sy ${$l$ $stirnati*n l*put VsIues
83
Roclq Mountain Power
Exhibit No. 5 Page 909 of 1 365
Case No. PAC-E-I4-07
Using these values, the following equation resulted in a 2.24 average weekday HOU:
Auerage Dai.ly HOU
= 2.377 + (0.28 x -0.816 +0.44*0.94+L.26 x 0.15 + 0.33 x 0.04 +7.267 x 0.05
+ -1.06 * 0.77 + -0.848 x 0.72 + -136 * 0.19) = 2.24
Using the same method, Cadmus calculated the weekend HOU using parameter estimates from the
weekend model. The weighted average of these two values then provided the average annual HOU
(Table H-3).
Weekday
w;6;a
-=;;ii.....
Precision calculations accounted for sampling errors in the model estimates and sample inputs, which
largely arose from participant surveys. The precision of individual HOU estimates can be impacted by the
precision of logger data model estimates and the accuracy of model inputs used for extrapolation.
Cadmus estimated the final relative precision for the CFL HOU in the SYLR Program as !4.2% with 90%
confidence.
Wms$s $Se*$ $mc$sr
The WHF is an adjustment representing the interactive effects of lighting measures on heating and
cooling equipment operation. For this evaluation, Cadmus applied the WHF adjustment to lighting
savings estimates that was recommended in the 2009-2010 evaluation report. Cadmus calculated the
WHF applied in this evaluation for the potential study conducted for Rocky Mountain Power ldaho in
2072.
Cadmus calculated SYLR's WHF using ASHRAE data on HDDs and CDDs in Rocky Mountain Power's ldaho
service territory. ln addition, Cadmus used the 2006 Energy Decisions Survey data32 to determine the
saturation of heating and cooling equipment types in ldaho.
To determine the portion of the year heating or cooling equipment operates, and therefore when
lighting would affect heating or cooling energy consumption, and to estimate the interaction for ENERGY
STAR lighting savings in the Sixth Regional Power Plan,33 Cadmus used the Northwest Power and
Conservation Council's workbook to estimate the interaction for ENERGY STAR lighting savings in the 5th
Regional Power Plan.
htlp;#_www.pa.cifig.otp.rory/e.p.lt_etudary{pe€lf"ig[qldq.q/.E.nglqy $ources/Deri].eld_Si*3 Management{
USM Volumel 2011.. Studv.pdf.
http;llwww.nwcouncil.orglenergv/nowerplan/6/supplvcurvns/reslEstarLishtine NewEY0grrl 0.xls.
l-s$l* $'{-S. ${St.S by'**y Type
84
Rocky Mountain Power
Exhibit No. 5 Page 910 of 1365
Case No. PAC-E-'14-07
This calculator estimates heating and cooling interactions based on building simulation models for a
variety of HVAC equipment and cities around the region. Cadmus estimated city savings for the ldaho
territory by using a weighted average of HDDs and CDDs from cities across the region that most closely
match the ldaho territory.
The Northwest Power and Conservation Council's calculator determined heating and cooling
interactions for zonal heating and heat pumps. To estimate interactions for electric forced air furnaces, a
heating system efficienry of 45% was included to account for duct losses. The cooling interaction from
heat pumps was used for all electric cooling systems, as shown in Table H-4.
Zonal 60%N/,A
Electric Furnace
Heat Pump
Cadmus then weighted these interactions by the market share of electric heating and cooling systems.
The heating interactlon calculation follows, where the summation is over the three electric heating
types:
Heating Interaction = -\{Vo Split Heattng Interoction * Market Share)i = 77.5o/o
The cooling interaction and WHF calculations are:
Cooltng Interaction = o/o Split Cooling lnteraction * Electrtc Cooling MarketShare
= -7.80/o
IndoorWHF = 7 - Heoting Interaction* Cooling lnteraction = t - 17.50/o* 1.Bo/o
= 84.30/o
The combined -L5% adjustment could be applied to electricity savings for all interior lighting measures
to account for a net increase in electric heating and cooling load due to more efficient lighting.
Weighting for the interior/exterior distribution estimated through participant surveys, Cadmus found
the final WHF to be85%:
WHF = L * (Heating Interaction * Cooling Interaction) * o/o lnterior Lighting
= 1 * (-175o/o * 7.80/o) * 960/o = 850/o
45%
i)it"
-53%iii
Tshls l"$-S^ $,$\JAC lntsr*etlsns
85
Rocky Mountain Power
Exhibit No. 5 Page 91 1 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
o rcffiouNrArN
Exhibit No. 5.1 I
Energy FinAnswer Evaluation 2009-20 1 1
Roclry Mountain Power
Exhibit No. 5 Page 912 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fruat EvetuATloli Rmonr FoIt lueno's ExgRGv
FmAruswr;ri Pnocn,+r,r (PY 2009-201 1 )
Prepared for:
N&\t'$T,\NT EMN
Navigant C)onsulting, lnc. Energ1" \4arket lnnovations, lnc.
1375 lValnut $treet 83 Coh"rmhia St
Suite ?00 Suite.l$$
Boulder, C() 80302 Seattle,l,tl\ 981414
303.728.2500 2il6-621-.1160
rtryvw'.navi{zant.com www.emiconsuitins.com
Fekrruary 15,2013
Rocky llfountain Power
RffiKYMOUFITILI]II
POWER
Prepared by:
Rocky Mountain Power
Exhibit No. 5 Page 913 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. HymasSAVI fiANT
1.Executive Summary .....,..............1
1.3.1 Key Program Findings..... ..........................2
1.3.2 Cost-Effectiveness......... .........2
1,.4.1, Overall Process Evaluation Findings..... .......................4
1.5 Program Evaluation Recommendations .............5
Energy FinAnswer Program Introduction............ ........................7
2.2 Program Changes from 2009 to 2011 ...................8
2.4 Program Theory and Logic Mode1......... ..............9
Evaluation Methodology .......... .................1,4
3.1 Impact Evaluation Methodo1ogy................... .......................... 14
3.1.1 Evaluation Approach... .......1,4
3.L.2 Project File Reviews................... ............... 15
3.1.3 Sampling Frame Development................... .................15
3.1.4 Gross Energy and Demand Realization Rate Calculation ............18
3.1.5 Net-to-Gross (NTG) Estimates.... ............18
3.1.6 Program Cost-Effectiveness ....................19
3.2 Notes on Validity and Reliability of Impact M&V Findingsa ..................21,
3.2.1. Reducing Uncertainty from Sample Selection 8ias.............. ..........21,
3.2.2 Reducing Uncertainty from Physical Measurement Error ...........22
3.2.3 Reducing Uncertainty from Engineering Analysis Error...... ........23
3.3.1 Overview of Steps in the Process Evaluation .................. ...............23
3.3.2 Process Evaluation Research Questions .....................24
3.3.3 Program Documentation Review ...........24
3.3.4 Logic Model Development............... .......24
3.3.5 Process Data Collection Activities................... ............25
3.3.5.1 Program Management Staff Interviews ............25
3.3.5.2 Participant Surveys...... ...................25
3.3.5.3 Near-Participant Interviews ............. ..................26
3.3.5.4 Non-Participant Surveys ................26
3.3.5.5 Energy Engineer Interviews ..........27
3.3.6 Process Data Analysis and Synthesis.... ......................27
Impact Evaluation Findings ......................28
4.1 Gross kW and k\A/h Savin9s................... .............28
4.1.1, Project Level Observations and Considerations for Energy FinAnswer .........31
4.2 Net kWh and kW Savings ..............31
4.3 Cost-Effectiveness Calibration and Ana1ysis................... ......32
)
J.
4.
lLvrrli:ai:iuri <:l ilor:itv h4ountain I\:.*el's lr.l*irg li.nr:l9.,, l:iiiri\.nsr,r'er lllr:grarrr (P\'2"00:l-:?iil.ii
rur\v$tANT
5. Process Evaluation Findings .....................34
5.1.1 Program Satisfaction ...........34
5.1,.2 Program Awareness and Motivation............... ...........35
5.1.3 Program Participation Process.... ............36
5.1.3.1 Pre-Installation ............... .................37
5|1..3.2 Installed Energy Efficiency Measures ...............37
5.1.3.3 Post-Installation.............. ................. 38
5.1..4 Program Influence.... ...........39
5.1.4.1 Influential factors .......39
5.1,.4.2 Free-ridership ................. ................. 40
5.1,.4.3 Spillover ......................41
5.1.5 Further Energy Efficiency Opportunities and Barriers .................42
Near Participant Findings................ ...................42
5.2.2 Program Satisfaction ...........43
5.2.3 Program Awareness and Motivation.................................... ...........43
5.2.4 Further Energy Efficiency Opportunities and Barriers .................44
Idaho Non-Participant Findings..... ....................44
5.3.1 Awareness of Rocky Mountain Power Programs ..........................46
5.3.2 Non-Participant Energy Efficiency Improvements.................. ......48
5.3.3 Further Energy Efficienry Opportunities and Barriers .................50
Energy Engineer Findings..... .........52
5-4.L Program Satisfaction ...........52
5.4.2 Program Awareness and Motivation............... ...........52
5.4.3 Training, Roles, and Communication...... ...................52
5.4.4 Energy Analysis Process....... ...................53
5.4.5 Quality Conhol Reviews .........................53
5.4.6 Measurement and Verification Process ......................54
5.4.7 Business Impact ...................54
Overall Process Findings..... ...........55
Roclq Mountain Power
Exhibit No. 5 Page 9'14 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
5.1
5.2
5.3
5.4
5.5
6. Program Evaluation Recommendations.... ................59
Appendix A: Glossary of Terms
Appendix B: Net Savings Methodology
Appendix C: Process Evaluation Survey Instruments
Appendix D: Process Evaluation Detailed Findings
ILvah.ration r.rf lior:i<v l\4.r.x.uriairr flo..ter's lriolro ll,nr:r;ir-, [;iirAnsra,,er Pi:i:1;rarn (PY ?"C09-2{l1i)
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Rocky Mountain Power
Exhibit No. 5 Page 9'15 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
This report provides findings and recommendations from the impact and process evaluation of Idaho's
Energy FinAnswer program for program years 2009 through 2011. These results serve to validate
reported savings and inform improvements anticipated for future program cycles.
L.1 ProgramBackgrounil
Rocky Mountain Powels Energy FinAnswer program offers custom incentives and engineering services
to commercial and industrial customers in Idaho for implementation of Energy Efficiency Measures
(EEMs).t The EEMs can include equipment installed as upgrades (i.e., retrofits) to existing equipment and
equipment installed as part of new construction projects. Commercial retrofit projects must cover a
minimum size of 20,000 square feet per electric meter to be eligible. Commercial new construction and all
industrial projects are eligible regardless of facility size. Rocky Mountain Power project managers and an
established network of energy engineering firms, under contract with Rocky Mountain Power, implement
the Energy FinAnswer program. The program offering includes:
> A vendor-neutral, investment-grade energy analysis to identify energy efficiency opportunities;
> Financial incentives equal to $0.12 per kWh annual energy savings plus $50 per kW average
monthly demand savings (up to 50 percent of project costs); and
> Design assistance, design team incentives, and a sliding scale incentive formula based on the
percentage by which a project exceeds the energy code.
7.2 Eaaluation Obiectiaes
This evaluation addressed the following objectives:
" To verify the annual and combined 2009 through 2011 gross and net energy and demand impacts
of Rocky Mountain Power's Energy FinAnswer program;2
, To review the effectiveness of program operations, highlighting achievements and identifying
opportunities for process improvement;
, To characterize participant and near-participant motivations;
" To perform cost effectiveness calculations on evaluated results for each year evaluated and in
total, and providing feedback on input assumptions; and
" To highlight Rocky Mountain Power's regulatory reporting compliance efforts while ensuring
accuracy.
1 Qualifying rate schedules are:6,6y'^,8,9,12,'1.9,23,23A,24,35 and 35A. Dairy barns on residential rates qualify as
commercial facilities per the Energy FinAnswer Tariff 125.1,, effective May 2008.
2The evaluation team planned for90110 by program and state; the final confidence/precision for Idaho's Energy
FinAnswer is 90/15.9. Industry standard is a minimum of 80120
[].r,ilir:niitrn <:l ilixirv h4.r.rtintain l\rrnrttr'.q lriah* Iiirr:r:g',, [iii:l.i\.nsrrtx Pri:g,r+rn G)Y 2ii{]$-Xl] i,:
uAv$t,qNT
Rocky Mountain Power
Exhibit No. 5 Page 916 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
7.3 Impact Evaluation
The impact evaluation of Rocky Mountain Power's Energy FinAnswer program quantified energy and
demand impacts for incented technologies, including:
" Quantifying the impacts of all measures and activities on annual gross energy consumption while
accounting for any interactions among technologies.
" Establishing post-implementation performance profiles for installed measures and activities.
" Explaining discrepancies between the results of this study and the reported savings estimates.
Evaluation metrics and parameters reported through this effort include:
, Gross and net et:aluatedprogram energy and demand savings estimates and realization rates for
completed projects.
> Energy usage profiles for commercial and industrial (C&I) technologies metered through on-site
Measurement & Verification (M&V) activities.
1.3"{ Key Prograrn Findings
A combination of in-depth project file reviews, interviews with facility staff, and on-site M&V activities
involving spot measurements and end-use metering of incented equipment informed the evaluated
savings estimates for each project sampled during the evaluation. Of the 32 projects that participated
during the 2009 through 2011 program years, 14 projects (representing 78 percent of reported savings)
were included in on-site verification activities.
The 2009 through 2011 gross program demand savings realization rate was 108 percent and the gross
program energy savings realization rate was 83 percent. Table 1 provides the program-leael reported and
evaluated kW and kWh realization rates:
Table l. Progra.m-L,evel (iross llealization ltates for lrlaho Energy FinAnswer
;jt:::!:!:!:!:!t!:!iiiiai!:::!:i:itiii:::itit:!:!iti!::iti:::!i:iiti:it:ii::i!:!:!:!:::!:!:!t!t!
iiii.ii.iii8,"4.isiiffi .iiXiiiiij ir
20.0 r7.9
't,494,547 7,226,453
::7"47fli;4-39::ii,i:t:ii,,iiiiiiiiiiiili;A$-9r58q,,,
487,927 358,182
62.0 67.6 109%
...faX*a:::iil* 16
90%
Atl 176.0 189.3 108%3,457,913 2,854,2t7 83%
The Evaluation Team calculated a Net-to-Gross (NTG) ratio of 0.89 for the Energy FinAnswer program/
for program years 2009 through 2011. The methodology used in this calculation is provided in detail in
Section 3.1.5.
{.3"2 Cost-Effectiveness
The evaluation team also calibrated and updated the cost-effectiveness models based on the impact
evaluation results. As
Table 5 indicates, the combined program results for the 2009 through 2011 program years were cost-
effective across all five standard cost tests. The Rate Payer Impact test did not pass the cost tests for
Rocky Mountain Power
Exhibit No.5 Page 917 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymasrx*s\v${-,\NT
program years 2009 and 2011. Detailed cost effectiveness tables for each program year are provided
below in Table 2 through Table 4 Details regarding cost-effectiveness calculation methodology can be
found in Section 3.L.6.
Total Resource Cost Test (PTRC)
Utility Cost Test (UCT)
{iBS.$
ffi Ei iIffi pAffi :ffi 1rtftiliv1}.iiiiiiii;i;;;i;;iiiiiiiiii;ii
1.,226,453
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1,226,453
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t,226,453
1,087,4r5
:rtffiri*ISirli:riil
1.,087,4t5
iiilrflEfr{[Siii:::::::i:::
1.,087,41,5
$s76,rs9
iiiiiiiiiiiiriirii$sr,6,,rssrrii
$3s8,426
iiiiiiiii.$ilffi.Frs
fi41.6,1.44 $884,439
1.81
ti:llt*
2.65
iiiiii.ii.iior'es
2.13"J.erlisie.ei't-S*Tl-I::l--€-gQ
Table 2. 200!) Idaho Ene FinAnswer Ilenefit-Cost ftatios
Table 3. 2010 ldaho Energv FinAnswer tsurnefit-Cost [datios
Total Resource Cost Test (PTRC)
,iii#bur,,n"*uiia,..cil+...N[;t,,rrncl i ii
ulilily Cost Tes! (UCI),,,,,,,,,,,,,,,
, ,RatelmpactTeeti(SSXI.....,....,.,,,,., ..,
Participant Cost Test (PCT)
r,269,582
':'iiffiiiira$ ...:-t,269,582
liixiiiii:l:li:riiiiil#g*5e2,1
1,269,582
1,125,555
tri*2$r($$liiiiii.i:':.:,:,:,:,|']:::,:,:,:,:,:,:,:,:,:,:,:,:,:,:,:,:,:':,:':
1,125,655
tfi*5i$ESii.i.X!
t;t25,555
$460,494
.:.:.$ 9,, iiiil
$369,1.86
$U0t3;roag::
$224,338
$r,1.62,030
:,*i;E6,**{:
$1,0s6,391
,;SX1CIsr.ia*!.:j
$833,821
2.52
j.frot ',
2.86
1;,l,::,:::;"::;:::.:lti :::
3.72
iiii..
Table 4.3{}11 Idaho En FinAnsu'er Berrefit-Cost
Total Resource Cost Test (PTRC)
y_!i]i!y corl [g;t (ucQ,..,
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Participant Cost Test (PCT)
$2t3,260
!$Bt$H60!ri
$1.54,356
isffidif 88iiiiiii iiii"iiiiitii, ,,,,,,,:,.,r.
$L1.4,846
358,182
,1fi98.;,1ffi
358,182
,;858;$EE
358,182
317,576
.4U..;,Attb.
317,576
3rfis76
317,576
,,$?,;ry,!]...?j
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Table 5. 2009-2S11 Combined Idaho Energy FinAnsr,t'er Benefil-L'ost Ral'ios
Roclry Mountain Power
Exhibit No. 5 Page 918 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
$2,5t9,r20 2.02
iiiiii+
2.50
,...ffw
2.62
Total Resource Cost Test (PTRC) 2,854,217
i.i.i.iilo ti.fiUs cU.i.trffiti.ifdsti eliri+Xliii.,..i 2iffi;tff
ulllity cgst T"t,t,(YC{)
,,.::::::::::,r:::::::::::i:i:::::::,:::::::.:.o,2!8.rnil,7
:ti::i:Raru:ilffifaffi:ffnet:i(Effili:lu*li:i:ittli:iii:::iti::i::ti::lti: r
Participant Cost Test (PCT) 2,854,217
2,530,646
zffis,6a6
2,530,646
$1,249,913
$2,290,r09
$r,979,908
7.4 Process Eaaluation
The process evaluation characterized the Energy FinAnswer program from the perspective of program
staff, participants, near participants, and energy engineers working with the program in order to identify
both existing strengths and areas for refinement that may better serve the Idaho C&I market in future
years. It also included consideration of the perspective of non-participants to identify the level of
program awareness and the barriers to actions to improve electric efficiency.
Between May and August 2012, the evaluation team surveyed or interviewed 55 customers: 12
participants, four near participants, and 50 non-participants.3 The evaluation team also conducted in-
depth telephone interviews with five energy engineers - active engineers who conduct analyses as part of
the program. These surveys and interviews provided data that were combined with information from
program staff interviews to create a comprehensive view of the Energy FinAnswer program from 2009 to
2011,.
1.4"1 Overall Process Evaluation Findings
The program is based on sound theory and design. The Energy FinAnswer program in Idaho seeks to
improve energy efficiency at commercial and industrial sites. The basic program theory is that providing
technical assistance will help overcome information gaps for customers and providing an incentive will
help the customers overcome cost barriers. The design is indicated in the program logic model in the
program overview. The program concept and design are based on sound theory and practice in line with
best practices for non-residential large comprehensive incentive program design.+ The program includes
a network of qualified engineers, inspections (site visits) before and after installatiory and commissioning
of mechanical equipment.
The program did not meet energy saoings goals in 2011.The program reported energy savings of 487,927
k\A/h in 2011; this is less than the energy savings goal of 3,598,1.84 kWh. No explicit energy savings,
demand savings, or participation goals were outlined for the Energy FinAnswer program for 2009 or
2010; however, the program reported savings of approximately 1.5 million k\Atrh in both years. The goal in
3 Near participants are those customers who began working with the program but did not complete their projects as
planned during the program years under study; these projects are identified as either cancelled or on hold. Non-
participants are industrial customers that did not work with any program during the program years under study.
a Quantum Consulting. 2004. National Energy Efficiency Best Practices Study Vol. NR-5 Non-Residential Large
Comprehensive Incentive Best Practices Report. Submitted to California Best Practices Project Advisory Committee.
ruE\v${"ANT
Rocky Mountain Power
Exhibit No. 5 Page 919 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
2011 was more than twice the reported savings from previous years, while reported savings were about
one third of previous reported savings. The cause of the decline in reported savings is not immediately
clear, as Energy FinAnswer projects tend to be large; delays or cancellations for a less than a handful of
proiects could dramatically alter savings during the course of a year. Participation was not dramatically
lower in 2011, but the cost-recovere-d projects had lower average savings.
The program is working as intended for participanfs. Both participants and energy engineers describe the
program as operating as would be expected from the logic model. AIso, two near participants did not
move forward with projects after the energy analysis because the savings based on their project scope
were not large enough to qualify for the program; this indicates that the energlt analysis nnd PM reoian are
workins to focus efforts towards oroiects with saainss. Customers who do besin workine with the orosram
mostly find out about it from vendors or directly from Rocky Mountain Power, as is expected from the
program logic model. Participants are influenced by saving money on energy bills, the program
incentive, and saving energy.
Participants are mostly satisfied, keeping their equipment in operation, anil achieoing expected enerry
sauings, When asked to rate their overall satisfaction with the program, 1.1. of 12 participants were
satisfied; the one other participant indicated "neither satisfied nor dissatisfied" due to the amount of
unexpected work involved in the commissioning process. The 12 surveyed respondents installed 17
measures, and they indicated satisfaction with all of these installed measures. The majority of
respondents indicated that the equipment was meeting energy savings expectations (15 out of 17
measures) and also providing other non-energy benefits (11 out of 17 measures). Non-energy benefits
included improved more reliable equipment, better control, and employee satisfaction.
The programhas lou free-riilership but no attributable spilloaer. Most measures installed are at least
partially influenced by the program. Participants indicated that just three of 17 measures would have
been installed at the same time without the program. There is no indication at this time of spillover from
the Energy FinAnswer program from participants or participating energy engineers.
Customers iilentify high uplront costs as a key barier to further action to reduce enery consumption
and demand. Participants, near participants, and non-participants who believed there were further
actions their firm could take to improve energy efficiency were asked what might prevent them taking
action. High upfront costs were most commonly cited as a barrier to further customer action to reduce
energy consumption and demand, by seven out of nine participants, two out of four near participants,
and seven out of 11 non-participants. Lack of access to capital, time constraints, long payback periods,
and internal communications difficulties were also noted as barriers. However, a large portion of non-
participants (78 percent) did not believe there were further actions that their firm could take to improve
efficiency. These responses indicated that one barrier might be that the eligible population truly does not
have additional energy efficiency actions or is not aware of possible additional actions. Given that they
believe there are no other opportunities, it may be a challenge to gain their attention and educate them
otherwise.
7.5 PrcgramEoaluationRecommendations
Based on the findings from this evaluation, the evaluation team has identified the following
recommendations to enhance the delivery efficiency and effectiveness of the Energy FinAnswer Program
in future program cycles:
, Recommendation 1: Consider revised marketing strategies to increase lead generation. More
than three-quarters of eligible industrial non-participants did not believe there were further
actions they could take to improve efficiency at their firm. Customers who do not believe there
Li,aiuatiuii r:i itocic. \4r:untain l)(r-,.rel's lriahi.r lLnr:r-{i. I;irt:\nsr.r'el Pliiirrafii (PY 20i]-.i-;?'iii .ii
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are actions that they can take may not respond to traditional approaches promoting energy
efficienry programs. Project managers, program muulagers, and energy engineers understand the
potential for cost-effective improvements across industries. Data from previous projects can be
used to identify cost savings and operational improvements from common efficienry efforts in
particular industries in order to interest more eligible customers. Increasing participation is
important to ensure continued program success.
Recommendation 2: Closely track project status. Closely tracking the status of projects should
alert the project and program managers when savings goals may not be met by existing projects.
The program staff could then determine alternative strategies to rneeting savings goals.
Depending on the projects in the pipeline at the time, the approach may be to seek out new
participants, to encourage project completiory or to encourage customers to take action on
measures identified in their EARs that were not currently being addressed. Ensuring that projects
are completed as expected decreases uncertainty and risk for projects where Rocky Mountain
Power has already invested time and resources.
Recommendation 3: Clarify baseline conditions, particularly for lighting proiects. There were
turo lighting projects in the Energy FinAnswer program impact evaluation sample which did not
include any description of baseline equipment. Project files simply stated that premium efficiency
T8s were being installed, and no calculations were provided. Without information on any
removed fixtures, or baseline assumptions in the case of new constructiory it is not possible to
accurately determine how savings were calculated for the projects.
Recommendation 4: Include energy and demand savings calculations in a spreadsheet format.
By providing this information in one consolidated locatiorL future evaluation efforts will be more
efficient and reduce the potential for comparing verified savings to incorrect or outdated project
assumptions.
o Although each project properly documented the reported energy and demand savings
estimates, the absence of savings calculations (particularly for demand savings) reduces
the transparenry of reported savings, along with the efficiency of evaluation efforts.
Providing both the input assumptions and savings calculation methodologies will ensure
the comparability and accuracy of reported and evaluated savings and will reduce
associated evaluation costs.
o Include the clearly identified final Energy Savings table in project files for the evaluation.
The data should include both baseline and current energy and demand usage as well as
savings estimates. Utilizing consistent formats based on the FINAL numbers is important
for all follow up activities, and will provide decision makers the key information needed
to quickly assess the situation and take appropriate action relative to the inspections
conducted. It is noted that the key elements are included in the documentation for each
project but it is often difficult to identify the final set of parameters used because the
project files capture multiple changes/revisions to the application process.
Rocky Mountain Power
Exhibit No. 5 Page 920 ot 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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ru,.u\v$ilANT
Rocky Mountain Power
Exhibit No. 5 Page 921 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
This chapter describes in detail the Energy FinAnswer program as delivered in Idaho from 2009 through
2011. Changes that have occurred over the last three years to the Idaho program are also explained in this
chapter. In additiory program theory and a logic model is discussed.
2.7 ProgramDesciption
The Energy FinAnswer program is intended to maximize the efficient use of electricity for new and
existing loads in commercial and industrial Facilities by promoting the installation of Energy Efficiency
Measures. In2011,, the program had an energy savings goal of 3,598,184 kWh; there were no program
savings goals in 2009 or201,0.
The Energy FinAnswer program offers custom incentives and engineering services to commercial and
industrial customers in Idaho for implementation of Energy Efficiency Measures (EEMs).s The EEMs can
include equipment installed as upgrades (i.e., retrofits) to existing equipment and equipment installed as
part of new construction projects. Commercial retrofit projects must cover a minimum size of 20,000
square feet per electric meter to be eligible. Commercial new construction and all industrial projects are
eligible regardless of facility size. Rocky Mountain Power project managers and an established network
of energy engineering firms implement the Energy FinAnswer program under contract with Rocky
Mountain Power. The program offering includes:
> A vendor-neutral, investment-grade energy analysis to identify energy efficiency opportunities
> Financial incentives equal to $0.12 per kWh annual energy savings plus $50 per kW average
monthly demand savings (up to 50 percent of project costs)
> Design assistance, design team incentives, and a sliding scale incentive formula based on the
percentage by which a project exceeds the energy code
Incentives offered through this program are subject to a cap that prevents the incentive from reducing the
payback period for a project below one year. Lighting energy savings projects per Energy FinAnswer
project are capped because lighting-only projects are handled through the FinAnswer Express program.
The FinAnswer Express program is a prescriptive incentive program offered by Rocky Mountain Power
to all non-residential customers. The Energy FinAnswer program includes a commissioning requirement
and post-installation verification to document the energy savings and measure costs for installed
measures. For comprehensive new construction and major renovation projects where the whole building
exceeds energy code by at least 10 percent, Energy FinAnswer includes design assistance, design team
incentives, and a sliding scale incentive formula based on the percentage that a project exceeds the energy
code.
The incentive structure for both the design assistance and the energy analysis is defined in the Tariff
Schedule 125.1. Detail on the program activities and a desired outcome is provided in the discussion of
the program logic model in Table 6.
5 Qualifying rate schedules are: 6, 6.4, 8, 9, 12, 19, 23,23A,24, 35 and 35A. Dairy bams on residential rates qualify as
commercial facilities per the Energy FinAnswer Tariff 125.1,, effective May 2008.
[].va]uati*n ot itor.*_v N4r.runiain Pt:.,rel's ltlaho lLnr:r9.,, Fini\.nsr.r,el l)rsg;rarit iI)Y:00-ti^:?01 il
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Rocky Mountain Power
Exhibit No. 5 Page 922 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Tabie 6. Incentive Structure for Energy FinAnsw-ero
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Qualifying
equipment must
exceed code
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iffithBsi;iEiffiir:iiii:iiiiiiiiiiiiii:irirl:lli:ii:iii:ii1:;....1i::aa::::iiiirffi
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Incentives lncentive
:r: :: : t:,,'::::::,:, ..:':.:.:.::::::::i::.::1..:::. EAt :: :r:::::::r:-::
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2.2 Program Changes from 2009 to 2077
No changes to the program were filed from 2009 to 2017.
2.3 Program Participation
From 2009 to201.'1,, there were 32Energy FinAnswer projects completed in Idaho: eight projects in 2009,
10 projects in 2010, and 14 projects in 2011. Due to some projects involving multiple measures, there were
50 total measures across the 32 Energy FinAnswer projects. Through 2011, the program reported
3,457,9L3 kWh in energy savings; TableT summarizes the projects present in the program by measure
category.
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Exhibit No. 5 Page 923 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table T.Idaho En FinAnsrver Frciect Details for program year 2009 through 2011"
HVAC
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4 1.36,820 2%
3,457,913 r00%50
2.4 Program Theory and Logic Moilel
Program logic models depict the primary program activities, the outputs that are expected to result from
each activity, and the expected short, mid and long-term outcomes of those activities. Program activities
depict the primary actions that are required to implement the program. This includes marketing,
participant recruitment, training, etc. The outputs depict the tangible "product" resulting from each
primary activity. For example, marketing materials, training documents, and databases of recruited
participants can all be outputs of primary program activities. Outputs are typically identified as "things"
that can be tracked and tallied. Outcomes represent the intended results of successful deployment of the
identified activities.
Developing a logic model that clearly provides the theory of action and change is an important step in
evaluation, allowing the evaluator and program actors to see inside the program'black box.'5 Program
Iogic models provide a framework for an evaluation because they highlight key linkages between
program activities and expected outcomes. The process and impact evaluations focused on these
linkages, particularly those on the critical path to achieving savings goals. The evaluation identified
which linkages in the program logic model are working properly and which linkage(s) may be weak or
broken. Thus, if the program falls short of achieving its intended short, mid, or long-term outcome(s), the
source of the shortfall can be pinpointed and remedied. Logic Models are often developed as a visual tool
to document the program theory. The creation of such a model serves to develop a common
understanding of program activities and intended outcomes among program staff, Rocky Mountain
Power, and the evaluator. With this foundation, the evaluation team can then make informed choices
related to the prioritization and focus of evaluation resources.
The underlying theory for the Energy FinAnswer Program is articulated in the Logic Model provided in
Figure 1. The evaluation team created the logic model based on a review of program documentation and
discussions with program management and implementers.
6 Funnell, Sue and Patricia Rogers. 2011. Purposeful Program Theorlz: Effective Use of Theories of Change and Logic
Models. fohn Wiley & Sons.
Rocky Mountain Power
Exhibit No. 5 Page 924 of I 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
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The Energy FinAnswer program is designed to overcome two commercial and industrial customer
barriers to imolementine enersv efficiencv proiects: Iack of trusted information and hieh upfront capital
costs. The program's primary intervention for overcoming these barriers is through the provision of
technical assistance and incentives. Incentives improve customer economics while technical assistance
helps to quantify opportunities in advance of customer investment. Linkages within the program logic
are described here with numbers related to those shown in the logic model figure.
1. Rocky Mountain Power coordinates marketing efforts with outreach through account
managers. By design, individual programs are not marketed to customers. Instead, Rocky
Mountain Power markets the portfolio of energy efficiency programs.
2. Customers become aware of the program through marketing and account managers.
3. Customers either directly submit Letters of Intent or express interest through the Rocky
Mountain Power efficiency program's phone number, online inquiry form, email to the
energy expert, or their customer or community manager. The majority of participants are
expected to express interest in energy efficiency or demand reduction projects without being
familiar with the Energy FinAnswer program by name.
4. Rocky Mountain Power Project Manager (PM) screens interested customers to identify
projects that are candidates for Energy FinAnswer and ensure program eligibility criteria are
met.
PM drafts Letter of Intent and provides it to the customer along with program information.
The customer submits signed Letter of Lrtent (LOI) to begin the program process. Rocky
Mountain Power receives and reviews applications. PM coordinates customer contacts with
account manager, asks project screening questions, and determines the general scope of the
project.
Rocky Mountain Power PM selects an appropriate energy engineer from a list of pre-
qualified engineering firms that support Rocky Mountain Power. The PM contracts with the
energy engineer to scope and analyze the project potential.
The energy engineer visits the customer's facility and identifies savings opportunities. The
engineer develops an Energy Analysis Report (EAR) that includes EEMs that could improve
efficiency as well as potential costs, savings, and any commissioning necessary to ensure
proper EEM operation and savings.T In many cases, the energy engineer visits the customer's
facility and submits an initial scoping report called an Initial Site Visit Report (ISVR) or
Preliminary Energy Analysis Report (PEAR), to the PM before conducting a detailed energy
analysis. PM discusses scoping with customer, conducts further screening, and decides to
move forward with energy analysis. Small or well-defined projects may go forward with a
PEAR to avoid unnecessary analysis expense; the PM will make the determination to go
ahead based on project timeline and size.
7 For some Energy FinAnswer projects, Rocky Mountain Power requires the customer to commission certain
measures. The EAR provides details regarding these requirements on a measure-specific basis. If the customer
chooses not to commission the project, when it is required, their incentive will be based on kWh savings and allowed
project costs that are reduced by 20 percent. Commissioning reports are submitted to Rocky Mountain Power along
with invoices and other documentation before the incentive is awarded to the customer.
Roclry Mountain Power
Exhibit No. 5 Page 925 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
E
6.
7.
8.
8..'aluatioii ol Rockv N'lountain l)(r,r,c.r''s ld;riro Eneigt FinAr.sro,,e.' Frograni iIry Sijt)!i-2{} i i )
9.
10.
13.
11.
12.
1,4.
15.
1,6.
N,qV}ilANT
As a quality control measure, Rocky Mountain Power requires that EARs be peer-reviewed
by a second energy engineering consultant before the report is delivered to the customer. The
EAR and peer review ensure that appropriate EEMs, along with costs and savings, are
identified.
The customer can rely on this information to make decisions, reducing information barriers.
Throughout the customer's participatiory Rocky Mountain Power provides technical support,
as needed, to ensure that implementation meets the intent and requirements of the program.
The EAR and Incentive Agreement, highlighting incentives and stipulations for
recommended measures/ are presented to the customer.
An agreement is reached between Rocky Mountain Power and the customer on which
measures to implement, and the customer signs the Incentive Agreement for agreed-upon
measures. Before purchasing or installing equipment, the customer is required to sign an
incentive agreement with Rocky Mountain Power based on the EAR estimates.
EEMs are implemented either by the customer or their contractor. Commissioning is
completed for those EEMs for which commissioning was prescribed in the EAR. The
customer notifies Rocky Mountain Power of project completion and the status of any
expected commissioning.
EEMs reduce energy consumption (and, in some cases, demand) at the facility.
Reduced energy consumption contributes to meeting annual program targets.
Customers experience reduced energy costs.
17. An energy engineer verifies proper installation of measures, reviews commissioning report
(if any) and obtains invoicing information.
18. A Final Inspection Report is submitted to Rocky Mountain Power. The Final Inspection
Report documents verification of energy savings; verification ensures that expected savings
occur.
19. Rocky Mountain Power processes incentives after final incentive calculation.
20. Incentives are mailed to the customer. Incentives reduce customer costs for the project.
As part of the program evaluation, the evaluation team assesses program outcomes and compares these
actual outcomes with the outcomes expected in the logic model. In order to make this comparison,
indicators for each expected outcome as well as sources of indicator data are identified. In some cases,
these indicators are directly observable from program tracking data or other archives; in other cases,
indicators can be assessed through data collection and analysis of survey or interview responses.
Table 8 identifies both key indicators and data sources for each of the Energy FinAnswer program
outcomes (short, medium, and long-term) shown in the logic model, above.
Roclq Mountain Power
Exhibit No. 5 Page 926 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E-.'aluralion oi l(,:lcky lv{ountain Pcr*'er's ldaho Energt, FinAnsvr,er l:}rograni iPY 2t}tl!i-201 i)l1
s'Arr${-ANT
Customer expresses interest in the
proSram
GUstomer,si.ffi..ffid,..* ms.L6l,,,..,,
Energy engineers selected for
project analysis and quality
control
Energy sav;ffi ..ffi Su*es; gosts,
innHiiihb fi*iiidffififfi,iii.iif:iir::i'i'''::':::i.i:i.':i'i.i::..':.ii':i
Measures installed and
commissioned as required
,.ffi tittatffi or**ru*a-i',.+#fiU,......,',.,
: :::: i: ::: , ., :,:, : .. , . : .:::::::::::::: . ,
Customers receive benefits and
have reduced first costs
Rocky Mountain Power
Exhibit No. 5 Page 927 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 8. Indicators and Dat'a Sources for Program Outcomes
r[$ffiipe attilf,rs$ils$ia$ orn€r
Program attracts interested
participants; participation
iiiit$li:tm,i.pfqi$t:iifils
Engineers identified for projects
unergr a tysi" r"pot,#*Uu#.,
meS$Urcs;,tssts and.benefits.,,',,,,,,,,,,,',,
Commissioning report in project
file; final inspection report;
invoices
Customer surveys; program
tracking data; non-participant
data
fnggramlracf.in6;*ata :'::'i
Program tracking data; energy
engineer interviews
i'ffiio"r'r+*,,*u*,U i;.;
engfreer,ihterviews ::;:i :iii:;: :i:i:i:iii:ii
Customer surveys; energy
engineer interviews
c*tffi.t i'*n* ....',....';.'.,',rxriii.efigineer,,infe,,ti-iiews ::
Program tracking data; Customer
surveys
rCustofiier
Customers observe energy cost
savings
I'6t8SSiii,,,,,,,,,,,,,,,,,,,,,,,,:,::::'.::'::a.laiii,:,:ttt:tttt::ttltl:,ttlilttttttttt:,:ttttt:t:tt:tl
Customers realize expected
savings
Customer surveys
[]r.'aIiiaiioii oi iiock-,ll i n i\nsr{,ci I.rOg la rii r rr.I: )iii]tl..2ti j i j\
ruAvltANT
The following subsections provide a detailed description of the evaluation methodologies used in the
impact evaluation of Idaho's Energy FinAnswer program.
3.L ImpactEvaluationMethoilology
This section summarizes the impact evaluation methods used to develop project- and program-level
realization rates for the Energy FinAnswer Program. Findings provide Rocky Mountain Power staff with
the feedback they need to increase program efficacy by providing an independent quantitative review of
program achievements.
Overall, the Impact Evaluation of Rocky Mountain Powels Energy FinAnswer Program aimed to
characterize program specific energy and demand impacts for commercial and industrial retrofit and new
construction measures. The impact evaluation of Rocky Mountain Power's Energy FinAnswer Program
aimed to characterize energy and demand impacts for completed projects in the 2009 through 2011
program years, including:
> Quantifying the impacts of all measures and activities on annual gross energy consumption while
accounting for any interactions among technologies.
" Establishing post-implementation performance profiles for installed measures and activities.
" Explaining discrepancies between the results of this study and the reported savings estimates.
Evaluation metrics and parameters reported through this study include:
, Gross program demand and energy savings estimates and realizations rates for completed
projects.
> Energy usage profiles for C&I technologies metered through on-site Measurement & Verification
(M&V) activities.
" Net program savings estimates and realization rates as a function of both spillover and free
ridership.
The impact evaluation methodology included the following steps:
" Evaluation Approach
" Project File Review
" Sampling Framework Development
, Gross Energy & Demand Realization Rate Calculation
" Net-to-GrossEstimates
" ProgramCost-EffectivenessCalculation
3.1.1 EvaluationApproach
The Energy FinAnswer programs include only custom projects. The most common evaluation method
employed for these projects involves International Performance and Measurement Verification Protocols
Roclry Mountain Po$rer
Exhibit No. 5 Page 928 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E.ralr-ration oi Rockr,:- N4ountain 1)(.r'r.rci''s ldaho Energv FinAnsr.r.,er Proeran-i iPY 2t10!i-201 lii 14
N&V}TANT
flPMVP) Option 88; through which the evaluation team either metered the individual equipment power
consumption or obtained facility data showing records of equipment operation. In cases where the
project affects a significant portion of energy use on a utility meter, such as with pumps in isolated
locations, the evaluation team employed IPMVP Option C for savings analysis, normalized by equipment
usage records from the facility. Occasionally IPMVP Option A may be used if the equipment operates at a
constant power level on a known schedule.
3.1.2 Project File Reviews
A thorough review of the Energy FinAnswer project files allowed the evaluation team to increase the
accuracy of calculated measure savings and demand reductions, thereby ensuring that they were
representative of installation conditions.
For each project file reviewed, the evaluation team characterized any data gaps, consistency issues, and
the accuracy of the information used to estimate project level savings. The evaluation team also assessed
the variability/uncertainty between Rocky Mountain Power's input assumptions and secondary studies
along with the relative impact on energy and demand savings. This type of sensitivity analysis was
crucial in prioritizing and aligning task resources. The results of this effort were used to develop
recommendations for input assumption revisions based on prior evaluation studies, upcoming policy
requirements, and geographic factors. Examples of secondary resources that were leveraged through this
task include:
o Regional Technical Forum (Rff;r
o Commercial and Institutional Building Energy Use Survey (CIBEUS)Io
Rocky Mountain Power
Exhibit No, 5 Page 929 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
t o Database for Energy-efficient Resources (DEER;,,
e Buildings Energy Data Book (BEO3;tz
. Commercial Buildings Energy Consumption Survey (CBECS)13
Figure 2 presents an example of the overview of parameters verified through the project file review
process. Overall, the evaluation team found the Energy FinAnswer project files and assumptions to be
sound and within industry standards.
8 For more information regarding IPMVP options and definitions, see http://www.evo-
world.org/index.php?option=com_content&view=article&id=272&Itemid=397&lanpen.
e Regional Technical Forum, RTF Unit Energy Savings (UES) Measures and Supporting Documentation,
http ://www.nwcouncil. org I ener gy I rtf I measures/Default.asp
10 Demand Policy and Analysis Division of the Office of Energy efficiency, Commercial and Institutional Building
Energy Use Detailed Statistical Report, December 2002
11 California Public Utilities Commission, Database for Energy-efficient Resources, 2008
12 U.S. Department of Energy, 2008 Buildings Energy Data Book, 2008
t3 Energy lnformation Administration, Commercial Buildings Energy Consumption Survey,2003
Eiralualior-r ol Rock,r" N4ouniain lLrLr'\,tri's ldal..o Energv lllnAnst'e.' Proeran. iPY ?iii,}9-201 i)lli
Rocky Mountain Power
Exhibit No. 5 Page 930 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
N&V $T.q NT
2. Parameters Verified throu iect File Reviert"s (Exam
Ene*g3r $inAnswer Proiect Sile Re:r,ienn
Frcier't Name
Custoaner Nrr:m
FsrictLNumt*r $Iss
Enugy $avings Clainr*d {kfttr}J.tJ,r,.r*r'.tJU
tlrriEed tners,"d $*rring$ Cl*ised {k&lh}l 5 L3Lr. I L{J _ /"tr
[ne1gq $-avi ngs eealizat]or,r &.nte 3{}3,.}i
Drnand S*vings Cta*ne$ {k!f}'t;! m
!"sri{iad. I}emand Sar.i*ss Claimed {&ltr}
Demand Sarriag R*xlixation ft*t*ll{ }b
[ot$ 8$i*rt (ust s rsi.$.33.$0
V"eri{ird Total fnsirtt Cost 5 336.516.$$
Re{x}rted Inmniir*$ 5"t ${5,8S
Vkri{ied }ncenlive $ o;i,*lt.t'\.
Notox
Continuing to understand and document the available data and considerations within each unique
project file allowed the evaluation team to make informed recommendations for future evaluation rycles
and custom calculation revisions.
3.1.3 $arnpling Frame Development
For the evaluation of the Energy FinAnswer program, the evaluation team adopted a Ratio Estimation
approach to sampling which achieved increased precision and reliability by taking advantage of a
relatively stable correlation between an auxiliary variable and the variable of interest (i.e., the ratio of
actual savings to program reported savings). This approach served to reduce the overall coefficient of
variation within the population.
As an example, consider two Energy FinAnswer projects where savings may range anywhere from3,709
kWh to 1,,628,571kWh based on the size of each participating facility and measures installed. Both the
average size and the average savings for this group of customers have very large coefficients of variatiory
thereby increasing the sample size required to achieve a specific confidence/precision threshold if the
evaluation aims to estimate the magnitude of program savings.
However, evaluation experience has demonstrated that a majority of customers have a ratio of actual
savings to program reported savings between 70 to 100 percent, regardless of the magnitude of each
individual project's energy savings. This ratio is lhe realization rate for gross evaluated savings and a
core objective of this impact evaluation. As such, the standard deviation of the realization rate is
generally much smaller than that of the magnitude of individual project savings. It follows that the
l\,'alr,ratior', ol liockv N{orrntain Por,ver's ldaho Iinerlgv llinAnsr.r'*r Prograr:r 1PY !ii0!i-201 i)'1 1-
N&V}TANT
sample sizes required to achieve a specific confidence/precision threshold may be greatly improved by
estimating the realization rate instead of total energy savings.
Per the 2004 California Evaluation Frameworkra, sample sizes developed using the Stratified Ratio
Estimation approach comply with the following equation:
Rocky Mountain Power
Exhibit No. 5 Page 931 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
(T)'
L+(+)'/N
Where:
n = Sample Size
Z = Z-Score for Desired Confidence Level
e = Assumed Error Ratiols
rp = Desired Relative Precision
N = Population Size
Moreover, the evaluation team proportionately stratified the sample by program reported savings. Under
this approach, the sample population was divided into subgroups by reported savings (i.e., strata). The
evaluation team selected projects proportionately within each stratum to ensure:
1.) The largest projects and contributors to program performance are evaluated, and;
2.) The medium and smaller projects receive fair representation in the evaluation. Collectively, these
projects also reflect a large percentage of program level savings.
The impact evaluation planned for 901L0 confidence and precision across the 2009 through 2011 program
years by energy GVVh) savingsr6. Table 9 provides an overview of the impact evaluation framework
representing 78 percent of the reported Energy FinAnswer Program savings for the 2009 through 2011
program years.
!a TecMarket Works, The California Eoaluation Framanork, June 2004
15 The evaluation team assumed a consentatioe error ratio of 0.4 for developing the sample framework. The error ratio
corresponds to the expected standard deviation of the realization rate for the program and was selected based on
previous PacifiCorp evaluations.
15 The evaluation team planned for 90/10 by program and state; the final confidence/precision for Idaho's Energy
FinAnswer is90ll5.9.Industry standard is a minimum of.80120.
Evah-ration ol i(ock-v Nlountain ljolt er's ldaho Energv Finirnslr,e.- Ilrogran-r i IrY ?tlil9-201 i )
N,qV $il; A N-*T
3,457,973 2,773,011
3.1.4 Gross Energy and Dennand Realization Rate Calculation
Gross energy and demand realization rates for each project in the impact evaluation sample were
combined to form program leoel realization rates for each program year. The evaluation team researched
the following technical issues in order to accurately determine gross program impacts and realization
rates:
> Determining the appropriateness of the pre-installation technology performance baseline via
project files and secondary literature review.
" Verifying installation and quantity of reported energy efficiency measures (EEMs).
" Verifying the baseline and measure performance characteristics of the measures installed,
and revising or computing performance variables (e.g., operating hours) as needed.
> Estimating the load shapes for the EEMs installed through the programs, including the
coincidence of each EEM with peak demand periods.
" Determining the demand savings (kW) and energy savings (kVVh) impacts of the EEMs
installed for projects sampled. This was accomplished by first calculating case weights for each
evaluated project; the case weight is the number of projects in the population in each stratum
divided by the number of projects in the final sample in the corresponding stratum.lT
Evaluated realization rate presents energy savings verified in a facility at the time of M&V. The program
level realization rate was then calculated as the ratio between the product of case weights and oerified
savings estimates and the product of case weights and reported savings estimates. This is illustrated in the
equation below:
Roclq Mountain Power
Exhibit No. 5 Page 932 of 1 365
Case No. PAC-E-1447
Wtness: Kathryn C. Hymas
Table 9. Clverr-iew of the I Evaluation Sam
74
Ft"ogrcrr.: S'ss iii..ss it:x Fstc. =
r.i:.l,j; I Cu-**' it,'ei5i J:t: x .1lreri.dl Es Ser,in$s Eslinl.cisi
3.{.5 Net-to-Gros$(NTC}Estimates
This section contains a brief overview of the Net-to-Gross (NTG). Using self-reported responses, the
evaluation team's estimation of net savings first attempted to assess the program's influence on the
participants' decision to implement an energy efficienry project and what would have occurred absent
program intervention. This estimation included an examination of the program's influence on three key
characteristics of the project: its timing, its level of efficiency, and its scope (i.e., the size of the project).
This estimate represents the amount of savings attributed to the program that would have occurred
without its intervention and is often referred to as "free-ridership."
17 The TecMarket Works Team, The California Evaluation Framework, Prepared for the California Public Utilities
Commission and the Project Advisory Group, June 2004.
Erialr-raliou ol Rockr.:- fr.'lountain Pcrwe-r's lciaho iinergv FinAnsrver I'rogran-, iPY ?iltl9-201 1)18
ruAr,$ilANT
The team's measurement of net savings then estimated program influence on the broader market as a
result of the indirect effects of the program's activities. This estimate often referred to as "spillooer,"
represents the amount of savings that occurred because of the program's intervention and influence but
that is not currently reported by the program. Spillover savings can be broken into two categories of
savings: "participant" spillover and "non-participant" spillover. Participant spillover savings occur
directly (i.e., program participants install additional energy efficient equipment), while non-participant
spillover savings occur indirectly (i.e., market allies install additional energy efficient equipment to
customers that choose not to participate as a result of the program).
A program's net savings are adjusted by both free-ridership and spillover savings at the measure level
and then extrapolated to the program. The net savings are the program-reported savings minus any free-
ridership savings plus any identified spillover savings, or:
Net Program Sarsings = Gross Program Saoings - Free-Ridership Saoings + Spillorser Saoings
Oftery this finding is described as a "net-to-gross ratio." This ratio is the net program savings divided by
the gross program savings, or:
Net-to-Gross Ratio (NTG) = Net Program Saaings I Gross Program Saoings
The findings of the NTG analysis are presented in Section 4.2.
For a more detailed explanation of NTG, see Appendix B.
3.1.6 Program Cost-Effectiveness
The cost-effectiveness of utility funded programs in the state is typically analyzed using tests prescribed
by the Califomia Standard Practice Manual.18 For the purposes of this evaluation, Rocky Mountain Power
specifically required the following cost-effectiveness tests:
> PacificCorp's Total Resource Cost Test (PTRC)
" Total Resource Cost Test (TRC)
" Utility Cost Test (UCT)
" Ratepayer Impact (RIM)
> Participant Cost Test (PCT)
With the exception of the P'IRC, all other tests are explained in the California Standard Practices Manual.
The evaluation team worked with Rocky Mountain Power to understand the PTRC and construct a tool
that calculates the PTRC at measure, program and portfolio level. Table 10 presents details of generally
accepted cost-effectiveness tests:
18 The California Standard Practice Manual is an industry accepted manual; it identifies the cost and benefit
components and cost-effectiveness calculation procedures. Definitions and methodologies for cost-effectiveness tests
can be found at htto:,',/w1a'rr'.enercv.ca.sor,/uleenlruildinc/dr:cuments.rhackerorrrrdi0T-
T CPUC STANDAITD PILACTICE }VIANUAL.PDF.
Roclq Mountain Power
Exhibit No. 5 Page 933 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Erralualion oi ltockv lr.4cuniain Poi,r'ei''s Idaho Ent:r'gr,' FinAnsr+'er lrroglam ilrY ?i109-201 i)
Roclry Mountain Power
Exhibit No. 5 Page 934 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
TN.s\\J$ilANT
Tahle 1CI. f)etails of Cost-Effectiveness Tests 1e
Participant cost test
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measure
Will the participants benefit over the
measure life?
,,Wiil ut$itv reye{lue::t::. r: ..1.i: : .:j. ; : :::::::::::::::::::::::::::::.11'mc,r.ease.l . ::r.:,rr:::::::::j::
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Will utility rates increase?
Will the total costs of energy in the
utility service territory decrease when
a proxy for benefits of conservation
resources is included?
Comparison of costs and benefits of
the customer installing the measure
;Ot:::t,f ulgif AtrIl::::::::::::::::r
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Comparison of program
administrator costs and utility bill
reductions to supply side resource
costs
Comparison of program
administrator and customer costs to
utility resource savings including
10% benefits adder.
The evaluation team spent considerable time initializing and validating the cost-effectiveness model used
for this evaluation. This model was calibrated by using prior inputs and outputs from the previous
evaluation cycle to ensure that similar inputs yielded similar outputs. The evaluation team worked
through a range of input assumptions pertaining to avoided cost data formats, financial assumptions
regarding discount and escalation rates, participant costs and benefits, and other input parameters.
For program years 2009 and 2010, the team used the 2008 IRP East System load shape decrement at $45
Carbon Stream to calculate avoided costs. For program year 2071., the evaluation team used the 2011 IRP
East System load shape decrement at Medium Carbon Stream to calculate avoided costs.
Cost-effectiveness inputs were provided by Company staff, including data obtained from the 2008 and
2011 IRP, and include program cost inputs, program savings by measure, and measure life. Table 11
provides an overview of cost-effectiveness input values used by the evaluation team in the cost-
effectiveness analysis:
te "Understanding Cost Effectiveness of Energy Efficiency Programs: Best Practices, Technical Methods, and
Emerging Issues for Policy - Makers" NAPEE, November 2008.
Itttt-.:,//u'rr;,,v.epa.go\;/'c!earlenerg', /documents,/sucairosi.-eiiectir,'eness.odf.
I\,'aliiaiioii ol. iiorkv S.{ountain l:i{!\\ii:ry's lr--iairo Iineig-rr FinAnsr.r.cr i}ieglaiii .il\ :titi(.}..:i,\! i,i 2ij
Rocky Mountain Power
Exhibit No. 5 Page 935 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
iN',d\V$ilANT
$0.0694
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Each measure's effective useful life (EUL) was derived from DEER (Database of Energy Efficiency
Resources), which is the source for deemed measure characteristics in California (as per the California
Public Utilities Commission).20 The evaluation team believes that this is a suitable source for calculating
measures installed in Idaho and is in line with Rocky Mountain Power's design values.
3.2 Notes onValidity and Reliability oflmpactMSV Findings
The evaluation team identified several sources of uncertainty associated with estimating the impacts of
the Energy FinAnswer program. Examples of such sources include:
" Sample selection bias.
> Physical measurement bias (e.g., meter bias, sensor placement, non-random selection of
equipment or circuits to monitor).
> Engineering analysis error (e.g., baseline construction, engineering model bias, modeler bias).
The evaluation team remained cognizant of these issues throughout the evaluation process and adopted
methods to reduce the uncertainty arising from these sources, thereby improving the validity and
reliability of study findings. Key uncertainty sources and mitigation strategies are discussed further
below.
3"2.1 Reducing Uncertainty from Sarnple Selectiom Sias
The problem that selection bias creates for program evaluation is recognized in the evaluation industry.
Although projects were chosen in the impact evaluation sample according to prescribed protocols, bias
may have been introduced if the selected projects did not choose to participate in the evaluation effort. In
an effort to minimize non-response bias, the evaluation team established and implemented the following
recruitment protocols:
20 More information on DEER can be found at hiip:/1rvi,r,'*t,.deeresources.ctur'.r/.
Tablar 11. Cost-Effectivrlness Evaluation In t Values
il.r,'aluatioi^, +l !(or,kv \,1si:niai* Ii(r.,.rii.r's iriairo iir-rr:r'gt lliiiAl..srr,r.v iticgrar:', ri)\ l(i(}(.i..'ji.\i i,i .)i
N&V I TA NT
> Notified participants as early as possible in the evaluation process.
> Accurately characterized M&V activities and the duration of the evaluation process.
> Maintained brief and frequent communication with participants and inform them of any
changes/additions to the evaluation effort.
The intent of these protocols was to give each participant ample time to prepare documentation and
secure the appropriate resources to support the evaluation effort. Brief and frequent contact with each
participant ensured the participant remained engaged.
In the event that a non-respondent was encountered, the evaluation team first identified the nature of the
project (i.e., measure type). Non-response for non-certainty projects was addressed by oversampling
projects within each of the original stratum. These "alternative" projects were substituted into the impact
sample in the event that a project did not respond to evaluation requests. Non-response for certainty
projects were generally addressed by choosing similar projects (i.e., measure technologies) with
equivalent, or larger savings. Collectively, this effort ensured that precision levels were met within the
overall impact evaluation sample.
3.2.2 Redurcing Uncentainty frorn Physical Measurement Hrror
There is inevitably some error associated with all physical measurement. For the impact evaluation of the
Energy FinAnswer program, a large measurement effort involved installing lighting/current/power
loggers to determine the operating characteristics of incented technologies across a broad range of
applications. Several steps were taken to minimize the uncertainty resulting from bias/error that may
have been introduced in this process:
> Back-up Loggers: Prior evaluation experience indicates that lighting loggers sometimes fail in the
field due to flickering or battery issues. To account for the possibility that some of these loggers
might fail in this evaluatiory the evaluation team deployed backup loggers for each site. This
ensured that the sample size requirements would be met even if a percentage of the loggers
failed.
> Logger Calibration: To minimize measurement error from improper calibration of the
lighting/current/power loggers, the evaluation team checked all loggers used in the field to
ensure that they were properly calibrated prior to being deployed. Field staff was also trained to
use consistent measurement intervals whenever possible, and to symchronize the logger
deployment activities (e.g., time delay). This ensured that the data could be compared across a
uniform time period.
> Logger Placemenfi To minimize biases arising because of improper placement of the loggers,
field staff was given a prescribed protocol for the placement and installation of loggers on circuits
(e.g., CT placement) and fixtures (e.g., uniform distance from the lamps).
> Logging Period: Usage patterns for retrofit measures may vary from month-to-month. Sampling
for a short duration could therefore introduce a degree of error into the overall results. To reduce
this type of error, loggers were typically deployed for a minimum of two weeks and
supplemented with available facility records (e.9., EMS trends, production logs, etc.). The logged
data was used to calibrate the facility records which spanned multiple months or years. These
extended logging intervals minimized the bias introduced from extrapolating short term
metering results to longer periods of time.
Roclry Mountain Power
Exhibit No. 5 Page 936 of 1 365
Case No. PAC-E-'I4-07
Wtness: Kathryn C. Hymas
Erralu"rtion oi ilockv trilountain ljcrur,er's ldaho Energv FinAnsr'cr Prograr:'r {Pt ?i}09-201 i)ZZ
rus\vttANT
> Logged Data Quality: Poor quality data can also be a significant source of error and uncertainty.
To minimize the potential impact of this problem, various quality assurance checks were applied
to the logger results. This included consistent spot measurements that could be compared against
logger data. Additionally, qualified analysts reviewed all logger files to ensure that the results
were representative of the technology being investigated:
o Lighting Ioggers were reviewed to identify inconsistencies in operating
characteristics and/or extended periods of inactivity. If a particular file was deemed
suspicious, the evaluation team followed up with field staff and facility managers to
ensure that the findings were reasonable. Inaccurate results were removed from the
analysis.
3.2.3 Reducing Uncertainty from Engineering Analysis Error
There are several opportunities for biases in engineering analyses that may compound the error and
uncertainty of. eaaluated savings estimates. The evaluation team adopted the following protocols to
minimize uncertainty from engineering analysis error in this study:
" All project analysis findings were peer reviewed to ensure that consistent methods and
assumptions were used throughout the impact evaluation.
, The evaluation team developed data collection protocols that yielded appropriate inputs into the
analysis models and reviewed all field observations with the evaluation team. Collectively, this
served to reduce potential modeling error in this study.
Roclq Mountain Power
Exhibit No. 5 Page 937 of 1 365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
t 33 ProcessMethoitology
This section describes the methodology used for the process evaluation of Idaho's Energy FinAnswer
program. First, the section provides a high-level overview of the steps taken to collect and analyze the
data for this evaluation. This is followed by a list of the research questions that guided the evaluation.
Next, a detailed description of the data collection activities is provided, and this section concludes by
describing methods used to analyze the process data.
3.3"1 Sverview of Steps in the Froeess Evaluation
To meet the objectives of this evaluatiory the evaluation team undertook the following activities:
> Process Evaluation Research Questions Development. Key evaluation questions were
established from the development of the 2009 - 2011 evaluation plan with Rocky Mountain Power
staff.
> Program Documentation Review. The evaluation team reviewed program documentation,
including regulatory filings, brochures, application forms, and the website.
" Logic Model Development. The evaluation team worked with program staff to define a logic
model for the program that described the intended program design, activities, outputs, and
outcomes.
> Process Data Collection Activities. The evaluation team collected process data through
interviews with program staff, energy engineers working with the program, and near
participants who did not finish projects with the program as well as telephone surveys with
participating customers and with non-participating customers.
Il.ialr-ratioi, ol Rock,v frilountain P{r-,rei's ida}ro Energv lrinAnsrccr I'rogran, iPY ?t}09-201 i)L-:t
.!lN \V${:.qNT
Process Data Analysis and Synthesis. The effectiveness of the program processes was assessed
by analyzing program tracking data, in-depth interview data, non-participant survey data, and
participant survey data.
3.3.2 Process Evaluation Research Questions
Discussions with program management staff and a review of the program theory and logic identified six
overarching research questions to guide the process evaluation.
1. What are the program goals, concept, and design? Are they based on sound theory and practice,
and, if not, where are the gaps?
2. Do program administrators and managers have the resources and capacity to implement the
program as planned, and if not, what is needed?
3. Is the program being delivered as planned, and if not, how and why?
4. Is the program reaching the intended target populatiory and if not, why? Specifically, are eligible
customers aware of the program, how are they becoming aware, and what is the program
influence on their actions?
5. What barriers are preventing customers from taking actions to reduce energy consumption and
demand, and which jeopardize program cost-effectiveness?
6. Are participants achieving desired outcomes, and if not, how and why?
These questions were explored through a mixed-methods approach. Table 12 shows the overarching
research questions and associated data collection activities used in the process evaluation. Data collection
activities were analyzed to identify findings, which were then used to answer the overarching research
questions.
Roclry Mountain Power
Exhibit No. 5 Page 938 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 12. A roaches to ,.Lnswer Research Questions
,
Proglarn $,,9Pm,,:lPtlon l-eYew
: ;:F} am::Otaff in s.WC , i:,:iiiiiiiiiiiiii:i:ii:
Participant su,f,Y9.,Y*?,,,,,,,,,,,,,,,,,,,,,,,,,.,,,,,,,,,,,,,.,,,,,,,,,,,,,,,,,,,,,,..,,,
.:Nmn::p-a*icip+hr;int+ffi e.i,itniiiiiiiiiiiiiiiiiiiiiii
. Non palti"clP,?,11,,1,',Y,1Y1Xi,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
::,Tfadst tniefviCws t;,;t:t:,:t:t,::t:t:t:t:t:,,t:t:t:t:t:t:t:t:t:t:t:t:::t:t
iiiiii:ii:irii;r::i:::i:i:ii:irii:ii:iiiiiii:iriiilrilnllri:::xx
v:t ::: ::tt:: .:!:tttvtt tlA:, ,:,,::::,:,, A,:''':':':':':.:':':':':':,:':':':':':':,:':,:':':n],]!, j:].1,::],]
X
:::::i:l:i::;:i:i::i:::::::i:::::i::::::::l:i:l::jl::i:,:,:j,:
:t::lii:i:i:i:tii:ti:l:i:i:ii:il:i:l::i:ti:itl: j::::;;i;::::l
XX
x,.....i...i..ii..iiii.iiiiii.
X
:::l::::tl:::l::l:::::ii::::il::1,: X
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3.3.3' Program Documentation Review
The evaluation team reviewed program regulatory filings, marketing materials, program website,
program manuals, application materials, annual reports, previous evaluations, and project tracking data.
This archival data review identified how the program is marketed, how engineers are supported, and
how the process works for enrollment, administratiory and tracking.
3.3.4 LeigicModelSev*loprnent
Based on the program documentation review and interviews with program administrators, the
evaluation team developed a program logic model. A logic model is a visual depiction of the program
theory. Logic models illustrate the flow of activities that create needed behavioral outputs, which in turn
achieve desired outcomes over the course of the program. Activities are actions taken by the program
administrators or contractors, as part of the program, such as reviewing applications, developing and
[.iair-rairoii oi. i(ockv \4t:urriaii.. l:'(rr.r,i],''s Iciaho linergrr .l;inA*sn er itroelani iy\' ltiil!i.'2i] i i)1,+
ruAv$ tANT
presenting reports to customers, or verifying installations. Outputs are measurable or verifiable tasks that
result directly from the program activities. Outcomes can be in the short, medium, or long-term, and they
are the result of the activities and outputs. The evaluation team reviewed and revised the logic model
through program administrative staff input (Figure 1).
3.3.5 Prqrcess Data Collection Activities
Program management staff interviews supported the development of the program overview and logic
model. And findings from the other four data collection activities were synthesized to draw overall
conclusions and recommendations for the program.
3.3.5.7 Program Management Staff Inurviews
The evaluation team interviewed two program management staff. These interviews informed the
development of the program logic model. The objectives of interviews with key program management
staff were to:
> Understand the design and goals of the program;
> Understand any program changes occurring during the 2009 through 2011 cycle;
> Identify program strengths from program staffperspective;
" Identify program weaknesses and opportunities for improvement from the program staff
perspective; and
" Identify other actionable ideas the program staff hoped to gain from the evaluation.
3.3.5.2 ParticipantSurveys
The evaluation team defined participants as commercial and industrial class customers who completed
an Energy FinAnswer project between 2009 and 2011. Surveys with participants specifically addressed
the following questions in support of the process evaluation objectives:
, How do customers come to participate in the program?
, How satisfied are customers overall with the program, including application materials,
inspections, and the incentive?
> What is the extent of program influence on customer actions, including free-ridership and
spillover?
> \Atrhat barriers are customers facing that prevent increasing energy efficiency?
> What kinds of commercial and industrial customers are participating?
The evaluation team defined the unit of analysis for Energy FinAnswer as a project. For each project, the
evaluation team examined all measures included in the project and focused the participant survey on the
two measures that were associated with the greatest energy savings in the tracking data. There were 32
Rocky Mountain Power
Exhibit No. 5 Page 939 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Er..aluation ol RockV L,lounlain ljcr.r'l:r,s ldaho Energv I; jnAnsn,e-r prograni iPy ?(,it]9_20] i )13
N&V $ TA NT
projects completed by 28 unique participants with the Idaho Energy FinAnswer program during program
years 2009 through 2011. In May and June of 2012, the evaluation team interviewed 12 participants.2l
3.3.5.3 Near-Participantlnterviews
The evaluation team defined near participants as commercial and industrial class customers who began
working on a project with the Energy FinAnswer program between 2009 and 2011 but had not completed
the project. Interviews with near participants specifically addressed the following questions in support of
process evaluation objectives:
, How do customers come to begin working with the program?
> What would they change in order to participate?
> What energy efficient projects are near participants installing (outside the program)?
> What barriers are customers facing that prevent increasing energy efficiency?
The evaluation team defined the unit of analysis for Energy FinAnswer near participants as a project at a
site. The evaluation team selected near participants from all projects for which the status was listed as "on
hold" with a last update date before |une of 2011; sites with multiple projects that met the criteria for
inclusion were only asked about one project that they did not complete. This focus on earlier projects
ensured that the evaluation team did not reach out to participants whose projects were still on track for
completion in2012. Near participant data did not contain information about potential project measures,
so the evaluation team was unable to prioritize any project over another with respect to potential savings.
In May of 20L2, the evaluation team completed interviews with four out of 11 near participants.
3.3.5.4 Non-Participant Surveys
The evaluation team defined non-participants as industrial customers in qualifying rate classes who did
not participate in any Rocky Mountain Power C&I demand side mtrnagement program during the 2009
through 2011 program years.z Non-participant surveys targeted C&I portfolio level considerations
through the following questions:
, Are non-participating customers aware of the programs?
,, Why are they not participating (if they are aware of the programs)?
" What energy efficient projects are non-participants installing (outside the programs)?
" What barriers are customers facing that prevent increasing energy efficienry?
There were 719 non-participant industrial customers identified, and 50 of them completed a suwey. At 90
percent confidence, this implies a precision of +l- 71,.3 percent. Some commercial class customers would
qualify for this programi however, non-participant customer data did not include building size, so
eligible commercial class customers could not be identified directly. Based on the most recent federal
21 The impact evaluation included 14 projects, as stated in Table 9. The process evaluation was conducted in parallel,
but separate from, the impact evaluation.
2 The non-participants included in the sample frame were drawn from a database of non-participating customers
provided by the Company as a subset of the population of non-participants; total non-participant counts are based on
the total number of customers per class (provided by the Company) minus the number of participants in all
programs in the state per class.
Rocky Mountain Power
Exhibit No. 5 Page 940 of 1 365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
E.iah-ration r:l Rockv N{ountarn Pcilr'i:r's Ir-iaho llnergv Fin;lnsl,i,ilr Prograni iIrY ?00!i-2i}1 i)lI)
N$\JX{-ANT
commercial building statistics, about 10 percent of buildings are 25,000 square feet or larger.23 Therefore,
it is possible that about 10 percent of the commercial customers, or 857 of 8,574 non-participating
commercial customers, would qualify for this program.
3.3.5.5 EnergyEngineerlnterviews
Energy Engineers are contracted by the Company to complete energy analyses for Energy FinAnswer
participants. Interviews with energy engineers specifically addressed the following questions in support
of process evaluation objectives:
, How are energy analyses completed (for simple and more complex projects requiring scoping)?
, FIow are savings measured, verified, and communicated?
, How is quality assured in measurement and verification?
> How does the energy-engineering peer review process work? Does this improve their
operations? Does it improve the quality of their work?
, How satisfied are these market actors with their role in the program?
, How does the Energy FinAnswer program affect their business?
> What would they do to improve the program?
The evaluation team identified active energy engineers working with the Company for the Energy
FinAnswer program using information from the program tracking database, program staff interviews,
and participant surveys. Senior evaluation staff, knowledgeable about the programs and appropriate
technologies, interviewed five active energy engineers via telephone in |uly and August of 2012.2a
3.3.6 Process Data Analysis and Synthesis
The process data collection activities included both quantitative and qualitative data. The evaluation team
used statistical software, specifically SPSSTM (originally, Statistical Package for the Social Sciences), to
analyze the survey responses from participants and non-participants. Interview responses from near
participants and energy engineers were analyzed directly as textual data. In both cases, the evaluation
team reviewed data for missing or erroneous entries. Analysis included recoding data in some instances
to disaggregate "other" responses or to combine similar responses into one category. Where appropriate,
the evaluation team tabulated frequencies of responses. After data from each data collection activity were
analyzed individually for findings, the evaluation team identified common process findings across
activities.
23 US ElA, Commercial Building Characteristics 2003, June 2006, Table 82.
2a The evaluation team offered a $50 gas card as an incentive to complete the interview.
Rocky Mountain Power
Exhibit No, 5 Page 941 of 1 365
Case No. PAC-E-I4-07
Wtness: Kathryn C. Hymas
E..,aluatior-. r:i. Rock-":- N.{ountain lj(r-r,i:r's lciaho Ent:rgv IiinAnsrver I'rogram iPY ?i}i}9.201 i)
L.x$V$il,s\,\T
Leveraging the evaluation strategies previously discussed for the Energy FinAnswer program, this
section summarizes the impact evaluation findings for each project included in the 2009 through 2011
evaluation sample.
The evaluation team characterized savings as "reported" and "evaluated." Reported savings present
project savings estimated at the time of measure installation. Evaluated savings present energy savings
verified in a facility at the time of evaluation. See Section 3.1.4 for details regarding the savings
calculation methodology.
4.7 Gross kW anil kWh Saoings
Of the 32 projects that participated in the 2009 through 2011 program years, 14 projects (representing 78
percent of reported savings) were included in on-site verification activities. The 2009 through 2011 gross
program demand savings realization rate was 108 percent, and the gross program energy savings
realization rate was 83 percent.
Table 13 provides program-level gross realization rates for the Energy FinAnswer program from 2009
through 2011.
r,226,453 82%
i rxx#68#B$iiiiiil;tr::l::l::tl:itltl:it:i:i::i:::::i:i::iiiiiiiiiiiiiiiEg%358,182 73%
Rocky Mountain Power
Exhibit No. 5 Page 942 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
13. Program-L.evel Gross Realization Rates for ldaho's Ene FinAnswer
2009
Z0ilHji;
2011.
::::::::::::'::,::,
iiii:i::ll:i:::.iliiiiiiili::i:iiiiiiis.4$lliiiii::ii.::i:i*i::ii.,ilr$sif
62.0
20.0
67.6
17.9
109%
*itfl%:iii:xfi:
90%
L,494,547
ti#I,Hl4,Es
487,927
83%All 176.0 189.3 108%3,457,9r3 2,854,2t7
Table 14 provides the sample-level gross realization rates for the Energy FinAnswer program from 2009
through 2011.
Table 14. Sample-level Gross Realization Rates fol ldaho's Errergy Finrdnswer lrrograrn
2009
ligsr{}
20L1.
62.0
$l:iEiffiX
11.0
67.6
nxxiliiil:ti:i8e
9.9
109%
a:ii1fiYi
90%
t,346,522
;;,,*jffi.8i?;\8,,1,,,,:,,:,,,;,
1.08,277
::a::!
82%
86$',"
1) O/
The realization rates reflect the difference between expected savings at the time of installation and
evaluated savings one to two years after project completion. However, customers often modified their
operating profiles during this time interval for a myriad of reasons that cannot always be attributed to
program influence. For example, the C&I sector is particularly sensitive to economic changes as
production throughput, occupancy, and operating schedules are driven by customer demand. Similarly,
changes in equipment usage also affect the efficiency of the baseline and replacement technologies
Iir,,'alr"iai'ion ol i{.+ckr.: N{ountain li$l,rirr!'"s liiairti Iinrlgr.' .llinAnsr,i'ei'i)rograr-i-i il}\' :(it}$..2i)! i)
1,104,981
79,485
1ii
Rocky Mountain Power
Exhibit No. 5 Page 943 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
!\ i s\ $ .< { s i\ t\ : si\r- \V tr\....N.s\i\ S
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incented through the Energy FinAnswer program. Throughout the impact evaluation, the evaluation
team remained cognizant of these factors which could influence project level savings. And though the
economic downturn did not significantly influence the projects in the impact evaluation sample, the
evaluation team emphasizes that program savings are continuously evolving due to a dynamic business
climate and that the aforementioned realization rates are a snapshot of program performance in time.
Table 15 provides project level demand savings for the 14 projects in the impact evaluation sample.
ii:ir:,::i:2fltit ?*,Oiect,,ff(}tdl,:r:r:r:r:r:,ir',,'':r:r:,:r:,:r:i::i'::r'.:.:, "'.' 0,0
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'['able 15. trc{ah* Energv ErinAnswer [}roject-Level $en'lanc{ tkX{} }teatrieatiun trdates
lt:i,ralr-raiior, ol. ii.ock_:,.' i.\{oultaur P{rwei's lci*lirr llnsl$r,' iiini\*si.r,rr l}roiil'an"i ilri
oo:
\I AV$T,ANT
Sites with N/A realization rates did not claim any demand savings. Table 16 details the energy savings
realization rate for all projects in the evaluation sample.
f'able 16. Idaha linergr. FinAnswer Proiect-Level Energy tkwh) Realizaticn llates
Rocky Mountain Power
Exhibit No. 5 Page 944 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
stffi iiii::::;;:::::i.;
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::r:j:l:i:l:i::i:::: j:::::l:ilrii:ll::::r::i l: :il
riii'.i...r.i...',,r.r,i.iiiSi*#
1-60,641-
i.xiiiiiiiiiiiiii*s*ss8r:iiiiii::ii:ii]
.-.. . .. 62,5.24-
4L,1.02
120,268
i',,.,,iit,I8 tg ,:i
ta )o?
31.,605
7s%
ii s"iiiiiiiiiiiiiiiiiiii:iii
37,621 1.06%
.t*tls4....,..i......,...........i'i.,fs%.ii.ir.rl.L1L,404 78%
::::::::i::::i ::.:. : I!:!:!:!:!:!:!:!:!:::!:!:!::'.i :::j:.:.::::::::::::::::::::::::::::::::': . . .
,15X,995.. .'',.,,,,,,,,.::, iiiiiiiiiii:i:i:it98o6,..,, iiiii
26!395
. -....P7:.0116-1
40,539
fl0.rflS",,,*i,,i
20,000
7.9."1"
110/// /o
,'.'.. 99%
1_27_"/"
84%
:::i:!iiiii',,fru%iiiii.iii::i:::::.:.:
110%HVAC 1.8,1.92tr* #d#il*ffiii,.#:.:.l.:.:.:.iif$.e;t ii.iiiiii.il.i.ii.i.iiili::.i:.ii.iii
,Mo!of-!_4:.[r]8uotio" ,,,,,,, 106,361
.,:';iiiiiiiii:;:iiii:,i::,trlldect;i[0td,,,,,,,,,,,,,,,,, ,;:,,,. , i6l#6:: :t.,.::::;:::,,::::,:;.::,::::.::
Motors 76,836
C9;mpres19d Air
Motors
Motors
... 224!007
L00!528_
260,651.
3L0,758
$$,Epii:::iiiiiiiiiiii:i:i
L:4:21L....
1.5,762
1..90:8i78
1.99,841
347,477
... LL1'."/:.
96%
iiiiiiines,$,l#:r::
220%
51:Y4iriririririririririri!::',
0%
... 100'/9
110/// /o
112%
11.4o/"
2.5"/_:.
100%
$i.r,diiil$,,1
i.:.r$itd:,*iliririirlriiiX#:i:::*6II
Reftigeration
iiiiii:i fl$iEffiitrotal ,i
. .Li-ght|yg
Motors
1;1;1#ffi r::,j;,],,::i:iiiiiiiiiiiiiiini*ffi #ii-il
. .. 1_6..-201
._--_.1.5,-029
11,855
The evaluation team notes the explanatory factors driving the lower (or higher) realization rates for
specific projects in the following subsection.
[r,.a]*aiioi^, ol i(or.k-y' \4tuniaur f'(rwc.r's ldairo Ei-:t:r'Bri llinArlsrq,er i:'rograt:-, 1u\']{i(}!t-2i,ii i)3$
rq,&v $il.,\ \il T
4.1.{ Proiect LevelObseruations and Considerations for Energy FinAnswer
Sites One, Two and Three: These three sites installed variable frequency drives (VFDs) on cooling
ventilation fans for potato storage cellars. Due to weather and loading variability, the preferred method
to analyze all of these projects would have been billing comparison. However, due to the location of
utility meters, some of which had additional loads, and the fact that some of the storage facilities were
new construction, billing comparison was only viable for Site One. Navigant obtained facility trend logs
for Site Three, and used these along with spot measurements to estimate savings for that project. For Site
Two, the fans were about to be shut off at the time of the audit, but Navigant logged them for the
remaining days of the storage season. Navigant used billing data to estimate typical run hours for this
facility and combined that with the logged data and spot measurements to estimate annual savings.
Site Five: Site Five was closed nine months after the two measures were installed, and the air compressor
has since been moved to another facility. Because of this, Navigant staff could not verify the EEM
installation and instead conducted a file review. The Final Inspection Report showed that the air
compressor's power usage was logged thoroughly, and compressor curves were applied accurately.
Therefore, the compressor's realization rate was deemed to be 100 percent for the measure's nine months
of service, resulting in the first year realization rate of 75 percent.
Site Six The realization rate for both HVAC control measures is lower than expected because the units
are operating a larger percentage of time than the application predicted. The lighting realization rate is
higher than expected because the gym is used more than the application predicted.
Site Seven: Navigant calculated a realization rate of 90 percent for demand reduction and 78 percent for
energy savings. The difference in energy savings may be due to a change in operation from the base case
to the efficient case. In the final inspection report, it was noted that facility personnel were shutting off
the new air compressor during non-operating hours. Since this is an operational improvement, the
associated energy savings cannot be included in the evaluated savings.
Site 12: Site 12 sequenced their air compressors and installed variable speed drives on three boiler feed
water pumps and three air makeup unit (AMU) fans. The affected compressor had failed since the
implementation of the project, and was replaced with a single unit making the sequencing obsolete.
Consequently, there are no longer any savings from the air compressor measure. Navigant logged the
boiler feed water pumps and AMU fans. The boiler was undergoing maintenance at the time of the site
visif so spot measurements were limited to fan operation and supply voltages. Based on observed
operations, Navigant estimated the pumps would operate only 8,400 hours per year, compared to the
8,760 reported in the project file, but operation averaged slightly lower power than seen at the time of
project verificatiory so savings are increased slightly compared to the reported values. Based on the
logged data, and the file baseline, the fans are somewhat more heavily used than during project
verification. Consequently, savings for the fan VFDs has decreased.
4.2 Net kWh and kW Saoings
The Evaluation Team calculated an average Net-to-Gross (NTG) ratio of 0.89 for the Energy FinAnswer
program across the evaluated period, for program years 2009 through 2011. Table 17 applies the NTG
ratio of 0.89 for program-level net realization rates for Idaho's Energy FinAnswer program.
Rocky Mountain Power
Exhibit No, 5 Page 945 of 1 365
Case No. PAC-E-14-07
Wtnessr Kathryn C. Hymas
Evah,iation ol iLock-; N4ouniain lLcr*,cr''s: Iciaho Entilgr,' liin:\nsrt'er I'rograni iIr\ ?ilil9.-201i).)|
Roclq Mountain Power
Exhibit No. 5 Page 946 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
TNJ\V$il;AN-I""
2009
za,!o.;1;111;$=1;i;
2011
Tahle 17. Progra,m-L,er.el Net fteialization Rates for lda]rn's En FinAns$r'er F
59.9
,fiifi ,1,;,:,:;;t::;::;:,:;:;l$:
1.5.9
r,494,547
X;rt75,439,
487,927
95"/"All L57.8 3,457,9't3 2,530,646
The program weighted NTG ratio was calculated by weighting a sample of project level NTG ratios by
their reported energy savings values. The methodology used in this calculation is provided in detail in
Section 3.1.5, Net kWh and kW Savings. The project level NTG ratios are presented in Table 18.
73%
EF000_000213
uH**s*ll{iil:l:t:.
EFSen_8416
inEFffi ffi r':i.iiii.iii'r,x
EF000_000136
,;*uffi #*'gi.i......l.r,........
EFSen_8952
ii.EFffi#+fl ffi i*lii.li....''..
EFSen_8269
rIEF$en #l 5
i....ii.ti.Xnxn
EFSen 8629
Motors
rii:,..!:r,i,.rr::.r...:,:,ll!i[1sffi sii. .:rr::.liririririririi.iil,:
Motors
; ;::: Kef s$Qffi fQff,;,;,;,;,;,,,
:t:::::::::::::::::::::j:;:i:::::::::::::::::::::::::::::::::::::::itii:;::::::t::::::li::ii:l
Motors
::::::ii:::::::i::!;::::irf{tr*Jf€i:ili::i:,:i:r:!:!ii:i;iiir
20t1
20ilr
2010
e0rH
2011
1.00
ri'iog
1.50
0.00
,riffi
i.isfi
CI',ii.ii'iiiiiix',.,i
2010
...frfl*fr...*ti..l..
2009
...a$CIs.:.....:...i.',iiii,rX
2010
Motors 1.00
Moit$ liishtiilg i,,.,,i.i,::,:,,,,: o9
HVAC 1.OO
4.3 Cost-Effectioeness CalibrationandAnalysis
Using PacifiCorp's model for calculating the program's benefit-cost ratios, the evaluation team calibrated
and updated cost-effectiveness models using five primary cost tests: PacifiCorp's Total Resource Cost test
(PTRC), Total Resource Cost test (TRC), Utility Cost Test (UCT), Rate Impact Measure test (RIM), and the
Participant Cost Test (PCT).
Table 19 through Table 22 illustrates the Costs, Benefits and Benefit/Cost Ratio for the cost-effectiveness
tests used in this evaluation. Impacts were evaluated for 2009,2010,2011, and for combined2009 -201,1,
program years. Individual program year results are for comparison purposes only; actual 9011,5.9
confidence and precision was achieved.
Details regarding cost-effectiveness calculation methodology can be found in Section 3.1.6.
Tahle 18. Idaho's Energv FinAnswer Project-Level Net-to-Gross (NTG) Ratios
I:rali-iaiir-ri', ot iiock'". lr,,louniirin l:'cr'vei-'s ldaiis linE-:ir',r.'.liin.Ansr,r,er lit,'ograni iyY ?i)t}!i.'2{11 i).lr
,:\N r .:$\ \ s I r'-\ * \ r.Yt{s..$.:\\sts}ti\ .""'\ \t $ \*-l ,.\ i\ N
Total Resource Cost Test (PTRC)
#6tuI!:fi esffi ffi $$$$t.:ffi ,$..'.iiXrll
Utility Cost Test (UCT)
rute,,lmpact rest,(B_[+Dl
iiiii;:i,: :iiiiiii
Participant Cost Test (PCT)
Rocky Mountain Power
Exhibit No. 5 Page 947 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Tahle tr9. 30(}9 ldaho Ene FinAnsw*r Benefit-Cost Ratios
1,226,453
.{lrs6i*fi31
L,226,453
{,;22614-53:
1,226,453
t,087,415
,*,iFF;?rl**:b,
1,,087,41.5
,I;08{#*5
't,087,415
$576,1.59
,ii$sf,6 $9.......i.,i'i
9358,426
$t!0ffi+rolllll
$41.6,1,44
$1.,044,553
":.$9A91fi9*,,,i,
$949,594
'..;SrfOi
*'
$884,439
1.81
1i6s
2.65
v|qa
2.13
T'ahile 30. 201{} Idah* Ene liin Ansrrer Ilenef it-Cosi ltatirls
Total Resource Cost Test (PTRC)
trffi.;R€ reoet,l.l eSt'.ffi$,....;
Utility Cost Test (UCT)
Rate,,,ntnpactT*i!,fftIM),',,,,,,,,,,','
Participant Cost Test (PCT)
1,269,582
xit6ei#8j!
1,269,582
r;
t,269,582
t,125,655
1,1*fs1655
1.,1.25,655
1tt2$n;6$,S
1,125,655
9460,494
i-4fl9 {e4:iii,
$369,186
;$1i013;o8$
$224,338
$1.,162,030
|;|:fiLtffi39L,
$1,056,391,
,r$1iCI 39trl
$833,821
2.52
Are9
2.85
.s.is4
3J2
Tatrle 2t^ 30.11 ldaho En Firulnswer Ilenefit-Cklst ltatios
Total Resource Cost Test (PTRC)
To l.ifl esCIsr€$Co$t.SlE$t
Utility Cost Test (UCT)
ie...E#f$ct,.- i..,t@...:*
Participant Cost Test (PCT)
358,182
3$S;.,1.82
358,182
35S.
358,182
31.7,576
*l:|7r;#7t6
317,576
311/;;*7rt
317,576
$2r3,260
$txai26CI
$1.54,366
$$ffi28E
$11.4,846
s312,537
ffi*;l,z*.:
$284,1.24
fi2Wt1!4it,
$26t,649
1..47
1,n;33
1.84
.,S;Ez
2.28
Tatrle 23. 3S09-3011 Comhinecl Idaho Energv FinA.nsrver Benefit-Cost Ratios
Total Resource Cost Test (PTRC)
:-:T,bral EsoufaE;:masrife::q1,,pJ]...]!i'':':
Utility Cost Test (UCT)
.iRa[e lrnpdet,iugt l[tllvl; i ,,ii:
Participant Cost Test (PCT)
2,854,2\7
i?jS5+"217
2,854,217
',,l,,1,?185*iZlv;1
2,854,217
2,530,646
2i53fl$
2,530,646
2;530j{4q
2,530,646
$L,249,913
$*249S13
$881,978
$r2#6%87rs;
$755,328
$2,51.9,r20
$2;2ftfl;'t.ffi"
$2,290,1.09
$ni?90.,ix109
$1,979,908
2.02
,,';tt1ilt?l**
2.60
iiiioff
2.62
E.,,'aiiiaiior-i oi iiock-; N'iountnin i:J{r,i,,o!"::.iciairt-. Iint:r'gl lirtri\nsrti:l"irrrrqruni iP\'liiiili..jilii)
Nf\VITANT
This section provides findings from the process evaluation effort, including the Energy FinAnswer
participant surveys, near participant interviews, Idaho non-participant surveys, and energy engineer
interviews. The findings provide a description of the sample and findings for each of the four data
collection methods. The evaluation team then synthesized findings from the four data collection methods
to inform findings and recommendations for Idaho's Energy FinAnswer program.
5.1, ParticipantFinilings
In May and June of 2012, the evaluation team surveyed 12 of 28 unique total participants in the Idaho
Energy FinAnswer program. These 12 respondents were small firms representing four industries. The
number of employees at each firm ranged from two to 350, with a mean of 56 employees. Respondents
represented the industries listed in Table 23.
Fin.Answer Su Respcndents
Dairy/Agricultural
,,!-99q,i Hi f $qp,$st{lg,i i i i,,
Educational Services
Total
In order to understand the value of electric efficiency to participants, the evaluation team asked
respondents to identify the portion of operating expenses represented by electricity costs. Electricity costs
account for a substantial portion of operating costs for responding firms. The respondents reported the
percentage of their operating costs represented by their electricity bills ranging from 5 percent to 33
percent with a mean of 17 percent.
5.1.1 ProgramSatisfaction
Most participants (11 out of 12) were satisfied with the Energy FinAnswer program. When asked to rate
their overall satisfaction with the program, seven respondents were "very satisfied," four were
"somewhat satisfied," and one was "neither satisfied nor dissatisfied," as shown in Figure 3. The
respondent who was "neither satisfied nor dissatisfied" indicated that it was "really hard to get
everything together." Later in the survey this respondent mentioned that they "didn t realize what was
involved in the commissioning process."
Roclry Mountain Po\fler
Exhibit No. 5 Page 948 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Iilralualion oi i{ockv lr{ountain Por.r,er's lciah<i Ilnergv .Finr\nsr.r''cr l"rograr:r {fY ?00!i-2i}i 1)i4
N'.d\V}ilANT
Figure 3. Partieipation Satisfaction with fnergv FinAnswer, ()verall
Neither ::atisfiecl
non dissatisfied, 1 "".
lzVhen asked what changes they would like to see in the Energy FinAnswer program, five respondents
offered the following suggestions:
> Higher incentives (identified by three respondents)
" A simpler and faster approval process (identified by one respondent)
> Better advertising of information on potential savings (identified by one respondent)
Eight of 12 respondents indicated they had contacted Rocky Mountain Power with questions or requests
for assistance at some point during their participation in the Energy FinAnswer program. Of these, all
reported the representatives they contacted were knowledgeable with respect to the program and its
requirements, and all but one respondent agreed that program representatives were timely in addressing
their questions.
5.1.2 Progran'l Awareness and Motivation
The primary sources of awareness of Energy FinAnswer are Rocky Mountain Power staff (account
representatives and others), and vendors or contractors, as shown in Figure 4.
Rocky Mountain Power
Exhibit No. 5 Page 949 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
E.ialualioi-, ol ltock-.r N,lountain .F'o-wci"s Idairo lintrigr.' liinAr.srq,er l:trograr:i (IrY :{}i}1i-2{.\1 i).i.:)
Rocky Mountain Power
Exhibit No. 5 Page 950 of 1 365
Case No. PAC-E-1447
Wtness: Kathryn C. Hymas
ru&vIfiANT
Figure 4. How Participants Leamed About Energy Fi.nA,nswer
Anorherft usinesscotieasuetttjiii.la\il}t--\=\^NitijX
i
. --. .- - l
f )!"eviorrsParticipntionrnRMilPrr:gramsSgtirri-\]N}u\\Nl+lii:
S:iN+\:i::.1.:.HrlitiirLLiiliiiiii+Iit\\{itHLiililllliilltLi\'.iN1r$rr i Nriow/ NiiT. sure iiliiiL\\:lt_i_l-iri.._l.i1tii:iririirillirliilfl\$Ii,l||furffillli\u\\-\t\l
;
i'i'rade Aily, Venrlor' or (.o$iiartof iiiiiilli"lil}iiiiiiHii+irlii..\\\riiiir:+iri'\:\il\\-\.tii,,-i-I,{ Xiiii riiiiii
Count of Respontients
When respondents were asked why their organizations decided to participate in the program, the most
frequently mentioned reason was to save money on electricity bills, followed by energy savings, see
Figure 5.
Figure 5. Motivation to I'articipate in Energy FinAnswer
RecommenEied by cr:nti'actsr
To inrprove value oi prope rty
To acquire ths latest tecilnoiogy
To im prsue operatisns, il!"odilctioil, *r' quality
'l'ci obtain an incentivr:
'Ir..l save energi'
T'o srve rnoney ofi eriei:tric !:rilis
i:iiiiiiir$:i.*+i,riii.\.rtiiriii-iliiiiiii.:iiiiiilllll:iiiii
.i$t1,\i1L\.\1:-$-\Ti.L}..iiii,: .ii]i
*\\lHfitii:lIixiflti.,ix*
i|ri:: Pi"irnary Response
I Secnndary Response
, Cnunt of Responrisnts
Multiple responses were allowed. Respondents who gave multiple answers were asked to identify their
primary reason.
5.1.3 ProgramParticipationProcess
Participant responses indicate that the Energy FinAnswer program is working well. Participation will be
discussed here in three steps: pre-installation, measure installation, and post-installation.
Evaluation o1 i(ockv lv{ountain Pcr*er's ldaho Energr' liinAnsn er l}rogram {PY ?00!i-201 i).ih
Nd\\r$tANT
5.7.3.7 Pre-Installation
Before participants install equipment with the Energy FinAnswer program, an energy engineer conducts
a site visit. Six of the 12 respondents recalled an initial site visit from an engineer contracted to Rocky
Mountain Power. When asked about this step, all six were satisfied with the energy engineer; five of the
six respondents reported they were "very satisfied."
The energy engineer then develops an EAR that Rocky Mountain Power shares with the participant. The
EAR includes suggested measures to install along with expected energy savings and costs. When asked
about the EAR provided by Rocky Mountain Power, 11. of 12 respondents (92 percent) said they found
the report valuable. The remaining individual was unsure. Two of the 12 respondents indicated they
decided not to install measures recommended in their EAR. Of these two, one recalled motion sensors
were suggested but not installed. The other respondent could not recall what type of measure had been
recommended and not installed. \Atrhen asked why they decided against installation of this equipment,
both indicated financial limitations. One stated that the measure's payback would be too long while the
other reported that his organization lacked the necessary funds.
5.7.3.2 Installed Energy Efficiency Measures
With the Energy FinAnswer program/ participants install measures identified in the EAR. Depending on
the project, there can be one to several measures. Among the 12 respondents, 17 energy efficiency
measures were installed with the program. These measures were:
> Pump motors
> HVAC, including controls, and an air handler upgrade
> VFDs, including with pumps and motors
> Plate cooler
> Lighting
> Refrigeration, including floating head pressure control
> Compressor sequencer
Installation of energy efficiency measures can include totally new installations or retrofits of existing
equipment. Of the L7 measures , 12 were totally new installations, and four of these 12 were part of new
construction projects. The other five measures replaced existing equipment. When those installing
replacement equipment were asked about the functionality of the equipment they replaced, they reported
that three of the five measures replaced items that were working with no problems, one was working
with some problems, the condition for the other could not be interpreted, see Figure 6.
Roclry Mountain Power
Exhibit No.5 Page 951 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E..ralualioi', ol .iock_v N4ountain Powe.r's idaho Entlrgv FinAnsr.r'cr I't'ogran-i iI'Y :ili,}$-201 l )
I .U $\J $ {..,\ N T
Figure ti. Frogram Hqtripment lnstallatian Status
,,,, New in::taliirtioir
r tlx i sl i i:$ e G i.r i t: i'rr rl ri\. r^,ro lx i i'is
witii 1,':r:hiesis
r l.{lstlns iiiiu i snient r,rrsr *ing
iru probienis
s l.xistirrg e,qi.iipiiieni --
i:r:n$ iiion i.r fi \ri$$., rl
Respondents were asked about the benefits of the energy efficiency measures that they installed with the
program, both expected energy benefits and other potential benefits. The majority of respondents
indicated that the equipment was meeting energy savings expectations and also providing other non-
energy benefits-15 of 17 measures reportedly met the energy savings expectations of respondents. For
the remaining two measures, respondents were unsure whether these savings expectations are being met.
When asked about additional non-energy savings benefits they expected from their installed measures
respondents named additional advantages to 11 of rhe 17 measures. For the remaining six measures,
respondents reported they either anticipated no further benefits or were unsure.
Rocky Mountain Power
Exhibit No. 5 Page 952 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Tahle 24. Non-energr. Benefits of lnstalled lVleasures
,,,.,,Ne*,rrrrffi#ffiffilloff#rsi. ilfe tt ii.a, tibnsftffitrots
Employee salisfaclion ::: :!,::Better lisht ' , :,:ir: ! ::::::: ,:, :.
j lfrxptu*ieaL pfoclucfiii$uefify, ::,:,:::;:::':':i : ::: 1 :::::::: : : : ': ' :':l
Pon;i r"o*lN"l;;;
3
',;..i 1,::,:,:::,,:,1,:
2
,x4.:.ii:...r..:,
1
i:.iiiiilriiiiiiiiiii
2
1.7
!:-a::=:::::::::::::::::::::::::::::::::::::.:::::a::::t:::::::::::,:
t:::l$ltiile::ir:::r:::r:::ri:i:::iri:::it,:r:ri :ii:rr i,t,ii ,tiliili i
Total
Respondents were asked about their satisfaction with the measures that they installed through the
program. The respondents are satisfied with the performance of all of their energy efficiency measures.
For 12 of the measures, respondents were "very satisfied." For the other five measures, respondents were
"somewhat satisfied."
5.1.3.3 Post-Installation
After installation, participants commission equipment in line with the recommendations in the EAR.
Eleven of 12 respondents stated that their projects were commissioned as recommended. The other
respondent did not recall if the project was commissioned.
Following commissioning, the participant notifies Rocky Mountain Power of project completiory and an
energy engineer goes out to the participant's site to conduct a post-installation inspection to verify proper
installation and operation of equipment. Ten of 12 respondents recalled post-installation inspections, and
[:i..air-raiioi-, oi i(orkv \{r:untain f'{r'.^.ir.'r's icillio iint..i.qv.liinAnsu,ri'Itrogran', ilY:i}0i]..2t11 i)
sNJ\\J$il,s\NT
they were mostly satisfied. While eight of these 10 respondents were "very satisfied" with the inspection
process, one was "neither satisfied nor dissatisfied," and one was "very dissatisfied." On follow up, the
respondent who was "neither satisfied nor dissatisfied" stated that he had "no opinion" about the
inspection process. The respondent who was "very dissatisfied" stated that "it took forever to get it
done," and later in the survey, he stated that the individual conducting the inspection "did a lousy job."
Figur* 7. Ilarticipant $atis{action *'ith Fost fnsta,Ilation Inspectinn
Very dissatisfied,
Neither satisfied
nor dissatisfied, 3
S.t "4 Prograrn lnfluer"rce
The evaluation team asked participants several questions about the program influence on the project that
they completed with the Energy FinAnswer program. These questions can be grouped into three general
areas of influence: Factors influencing the actual equipment installed as part of the project (Influential
factors), what would have happened in the absence of the program (Free-ridership), and the program
influence on future energy efficienry purchases (Spillover).
5.L.4.L Influentialfactors
Respondents were asked how influential seven factors were in their decision to purchase the actual
equipment installed through the Energy FinAnswer program. They were asked to rate the importance of
each factor on a scale of one to five, with one being "not at all important" and five being "extremely
important." All 12 respondents indicated that the incentive from Rocky Mountain Power was at least
somewhat important in their decision. Eleven out of 12 respondents indicated that the information
provided on the payback and a contractor recommendation was at least somewhat important in their
decision. Ten out of 12 indicated that the information provided by the energy analysis was at least
somewhat important in their decision. As shown in Figure 8, there were mixed responses for equipment
familiarity, previous participation, and corporate policies regarding energy reduction.
Rocky Mountain Power
Exhibit No. 5 Page 953 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
_ii)[].,,'aii-iaiior', ol Rock-., ir.{ouniain li(r-,i,,rr's lcial..o linr.:rg-v l;inAlrsu,rr l:trosran-i iPY:i}i.}$-.2ili i)
Rocky Mountain Power
Exhibit No. 5 Page 954 of 1 365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
N&VIil&NT
Figure 8. Factors lnfluencing Froject Decisions
Frcgrsrt lncentive
I nf or mati*n r--n Par*back
Vendor Recorr-r n.rend ati$n
EnergY Apslysts lnfi:r*iaiir:ri r:n Si*vings
famiiiariiv witlr Equiprnent
Previr:us Pa rtici petiE;n
C$ipo rate Pri I ! r:y fo r I ne r $1r R s6] u ci 1$ * iti$iiiii{Xiiiii:i.1H
lll: Don't Nnr:it,/itot Sure/tlefuser{ I i'i$t irniiertant At All
I Ner-:l;'al n SClnl€what llrportailt
Count of Respondents
I Somewhat U nimp{rrtant
x fxtre meiy lroponant
5,7.4.2 Free-ridership
In order to determine to what extent Energy FinAnswer's availability affected installation decisions, the
survey team asked respondents what would have been different about their installations were the
program not an option. When asked about each of the 17 measures installed, three of the measures would
have been installed at the same time while five would not have been installed at all. Two measures would
have been installed within 12 months, one at the same efficiency and the other at a lower efficiency. Five
measures would have been installed more than 12 months later. For two measures, the respondent wasn't
sure if they would have ended up installing any measure without the program.
All three respondents who indicated their measures would have been installed at the same time without
the program had previously stated that the Rocky Mountain Power incentive was important in their
decision to install this equipment. One of these respondents had also indicated that the energy analysis
information was important in the decision to install this equipment. They were further asked to identify
what influence the program actually had on the decision to install the measure. One respondent said that
the program impact was to "save power and have less wear on equipment," and another said that the
program impact was "previous experience with Rocky Mountain Power programs.'/ The respondent who
had said that the incentive and the energy information were important in the decision said that the
program had "no impact." Program influence on installations by measure is shown in Table 25.
Erralnati,on oi Rock,v N'lountain Por.r,cr's lciairo Eneig"r'IlinAnsrrrer l)rograni iI'Y ?i,}09..20I ii
Roclq Mountain Power
Exhibit No. 5 Page 955 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Ns\VXil-qNT
Table 25. Installations in the Ahsence nf Enei Fin.Answer lry S{easure
.....i,....i;,lii...........,..'.t.....iUll't,.'.'
3
.,i.t, : l,,.:^:.:.:.:.:.:.:r.:.:.:.:.:.:.:.:.:.:::.:*:::::::::i1,.:
1
iiiiiiii:iiii$iiiiiixi* i::::
5
:it!
Total Count of Measures t7
5.1.4.3 Spillover
There is evidence of the Energy FinAnswer program influencing some additional energy efficiency
installations. Two respondents indicated installing equipment after the Energy FinAnswer project
without assistance from any utility programi both respondents neither agreed nor disagreed that the
program influenced the decision to install additional high efficiency on his/her own. Additional detail on
both "like" and "unlike" measures installed by respondents after participating in the Energy FinAnswer
program is given below.
For two of the 17 measures installed, respondents installed additional "like," or similar measures of the
same type they installed through the program after their participation in Energy FinAnswer. These
measures were VFD motors and a pump. Respondents indicated that both of these were just as efficient
as equipment installed through the Energy FinAnswer program. The VFD motors were installed using
another Rocky Mountain Power program while the pump was installed without assistance. The one
measure that was installed without assistance represents potential quantifiable spillover. When prompted
with the statement "My experience with Rodcy Mountain Pozoer's FinAnswer Express program influenced me to
install high fficiency equipment on my o'10n," the respondent "neither agreed nor disagreed." Quantifiable
spillover from this project is included in the calculated net savings for the program.
Of the L2 survey respondents, four said they had made additional "unlike," or dissimilar energy
efficiency improvements since those they installed with the program. Three of these were lighting
measures (two at ENERGY STAR qualifying efficiency, one at lower efficiency but better than standard),
and the other was composed of standard efficiency pumps and irrigation equipment. Two of the lighting
measures and the pumps/irrigation measure received other incentives from Rocky Mountain Power
while the remaining lighting measure was not incentivized. The one measure that was installed without
assistance represents potential quantifiable spillover. When prompted with the statement "My experience
with Rocky Mountain Power's FinAnswer Express program influenced me to installhigh efficiency equipment on
tny o70n," the respondent "neither agreed nor disagreed." This measure indicates that non-quantifiable
"unlike" spillover is occurring due to program influence.
The two survey respondents who reported installing measures outside of the Energy FinAnswer program
but did not participate in a different incentive program were asked why they did not apply for an
incentive from Rocky Mountain Power. One indicated that his organization was not aware that the
incentive was available (but would have applied if they had been aware). The other did not apply
because of the "difficult paperwork" involved.
E.;air-rartion oj iiorkv N.4ilunlain j:'$r+r.ri's k:iaho l.nerg,r.' .lrinAnsrc*r |'rograr:-, ii'Y :{}i.t!j-2i)1 ii +i
ix-s\xr${:ANT
S.1.5 Further Energy Efficiency Opportunities and Barriers
When asked whether there were additional energy efficiency improvements their organizations could
make, nine of the 12 respondents affirmed there were. When asked what these improvements might be,
these nine respondents indicated the measures described in Table 26.
Rocky Mountain Power
Exhibit No. 5 Page 956 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 36, Potential Further Energy Efficiency lvleasures
VFDs
i.€.ffi.t*fl *.......i....:i.Xrt:.1; f ....l.ii..,....
!ea1
exchang€r
,: i ,i,l+tll{illr!:,,!:!:!:!:!:!:::!:!:!:!:!:!:,:',!',,:,., :' :i!:!:!:
ffi;iK";/N;i;;;;
4
:t:ts::::::i:lr::::
1
i:ii:*lii:iil:iii:iii
1
:::::i!::
3')10
:::::::::::::::i:i:i:l:i
$iffl6iir
8%
:,Ei&li
8%
i::.lri:
,:fi
Total 100"/"
Of these nine respondents, six said they had plans in place to make those changes to improve electric
efficiency. Five of these six respondents indicated that incentives from Rocky Mountain Power or another
organization were part of their plans.
When asked about factors preventing them from making these changes, respondents identified high
upfront costs (seven) and their lack of access to the necessary capital (one), and turnaround time (one).
5.2 Near Participant Findings
The evaluation team interviewed four Energy FinAnswer near participants in Idaho. Near participants
are those customers who are in the project tracking system with a project through the Energy FinAnswer
program during 2009 through 2011 but are identified as cancelled or on hold as of the end of 2011. In total
there were l.l. near participants in Idaho in the 2009 through 2011 period; however one was considered
ineligible for survey having also participated in Rocky Mountain Power's FinAnswer Express program
during the evaluation period.
The respondents represented four different industries. These were:
" Food processing
" Manufacturing
" Dairy/Agricultural
" PublicAdministration
Three of four respondents estimated that three to 5 percent of their operating costs were due to their
electricity bills. The remaining respondent provided a much higher estimate of 80 percent. Therefore,
electricity bills for an average near participant make up 23 percent of total operating costs. 25
Respondents report their organizations employ between five and 100 people with an average of 35
employees. 26
25 If this response is treated as an outlier, the average electricity percentage is 3.8 percent.
26 One respondent indicated these people are unpaid volunteers, not actual employees.
Il..ralr,iairoii oi iiockr.. Nrlouniair: i:t1i-..,ui.ri"s kinho Iint:rg-1.'.lrinAns\{'*i'Itrograri-, iPY:ili!!i..?-{}li)
Nf\V$TANT
5.2.1 Causes of Non-Completion
When asked about the current status of their Energy FinAnswer projects, one reported plans to complete
the project another said the project had already been completed without Energy FinAnswer, and the
remaining two indicated their projects had been cancelled (i.e. they are not completing the project at all).
Reasons for non-completion fell into two categories, as listed here:
, Customer could not move forward because of cost. Two projects that were cancelled because of
costs. One said that their firm wanted to avoid high up-front costs in a poor business
environment. The other stated that the payback proved to be longer than originally anticipated.
" The project did not qualify. For two projects, the energy analysis showed that savings from the
project would not allow the project to qualifii for incentives. One of the projects was completed
outside the program, and the other will be completed outside of the program because of other
benefits to the firm.
When asked what would need to change for respondents to participate in Energy FinAnswer, one
respondent provided a suggestion. This respondent said the information provided by Rocky Mountain
Power with respect to details about the project and incentives was "fairly limited." This respondent also
said that there was no follow up or contact from Rocky Mountain Power. More interaction and
information would be helpful in moving projects forward.
5.2.2 FrogramSatisfaetion
Three out of four respondents were "very satisfied" with the Energy FinAnswer overall; one was "neither
satisfied nor dissatisfied." When asked why he was "neither satisfied nor dissatisfied," the respondent
reported there was no contact from Rocky Mountain Power, only from some electricians. This lack of
follow-up gave the respondent the impression that the program wasn't worth his participation.
Near participants were asked if they reached out to Rocky Mountain Power during their program
involvement with questions in order to assess the customer service provided to them. None of the
respondents indicated that they had attempted to contact Rocky Mountain Power during their
participation.
S.?.3 Program A,warenesE and Motivation
Like participants, near participants were asked how they became aware of the program. Each of the
survey respondents leamed of Energy FinAnswer from a different source. These were:
, An account representative or other Rocky Mountain Power staff
" Rocky Mountain Powels printed materials and an online advertisement
" Respondent's own experience as an engineer
" A trade ally, vendor, or contractor
Near participants were also asked what motivated them to begin working with the Energy FinAnswer
program. The most common motivation for getting involved with Energy FinAnswer was to obtain an
incentive, as shown in Figure 9.
Rocky Mountain Power
Exhibit No. 5 Page 957 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Erraluation ol ii.ock'": \.louniain Pcr"r,c.r's ldaho iinergr,' Irin:\nsi.r,er Prograni iirY :t109-201 i )
Roclry Mountain Power
Exhibit No. 5 Page 958 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ruAvrtANr
Figure 9. Near Participant Reasons for Interest in Energy FinAnswer
RecommencJaticn by ccntractc,r .i...t.itiiii:ii,.:_:-: iiii,,,iiil],.tiiiiriiitiiil.: ,ll:l Prim.lry fi.espons*
t S*urndary Response
To obtain ts.chnicgl essistance
To save n:oney on eiectric bills
To obtain iln in;entive
Multiple responses "r;;; ;il,r*;e. R;;p;il;nts who gave multiple answers were asked to identify their
primary reason.
5.2.4 Further Energy Efficiency Opportunities and Barriers
When asked whether there were other changes their organizations might make to reduce electricity use,
all four respondents indicated "yes!'
They offered the following examples of further energy efficiency opportunities:
> Lightingreplacements,
" Motion sensors for lighting,
" Reduction of water use, and
" VFDs.
Two of the respondents said they had plans in place to make these changes, and one of these two
reported that his organization plans to use a Rocky Mountain Power incentive program.
Respondents were asked to identify factors that might prevent their organizations from making the
changes described. Two respondents indicated that high up-front costs could prevent them from moving
forward, and one responded indicated that long payback periods (more than two or three years) could
prevent them from moving forward. The other respondent indicated that the current system supports
multiple users, and there is no clear way to communicate to users about the electric costs of their
equipment use.
5.3 IdahoNon-ParticipantFinilings
In May and )une of 2012, the evaluation team surveyed 50 industrial class firms that did not participate in
any Rocky Mountain Power programs between 2009 and 2011, according to program tracking data. While
only industrial class non-participating customers are included in this section, the evaluation team notes
that some commercial class customers would qualify for the Energy FinAnswer program. However, they
are not included here because eligible commercial class customers could not be identified directly from
the non-participant data.
The majority of non-participant firms are small, based on number of employees, with 46 percent of
responding firms (23 of 50 respondents) employing fewer than three people; however eight firms were
Evah"iaiion o1 iLtxkl:- h4ountain Pcr"tcr's idaho Energv FinAnsr'r'er Program {I'Y ?009-201 :) 44
,.:iN.s\V$il4\*T"
either not sure or chose not to answer (shown in Table 27). Similarly, the majority of participating firms
had few employees, with a maximum of 129 employees reported by interviewed participants.
'tr'able 17. Size n{ Nmn-Participant }rims, b-v.. Number of Ielvees
46%
i:iiiliii::l:::i::i:i:l::i:liiii':i:lillll::llffi'y.i::::it::l:ili::ilii:iil:::i:ii:i:il:::ii::ii::i:il
20"/o
.'.:::::::::::::::.:::::::..:::::::::::.:.:::::.::.:::::::Ad". . . !:.:::::::::::::::::::':.:::.:::::::::::::::::::j::j:::::::::::::::::::::::::::::::::fjtr'!li.. :::::::::::::::::::j:.:
07o
,,,:i:i:i:i:i:::::i:'::: i:i:i:::i:':i:':ii::::::::,i:i:i*Ol:1q., : .'
'100"/"
Non-participant respondents represent diverse industries with the most common industry being "dairy
and agricultural." The second most common industries were "reta7l" and "real estate," with seven
responses each. Figure 10 shows the distribution of primary activities for the surveyed non-participants.
Figure 10. tr'rim*ry Activity for Non-Participrating Respondents
Roclry Mountaln Power
Exhibit No, 5 Page 959 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
23
lll.flrli
10
i's..i.i...i
0
C$ n si!"i.ri: tii:n
Reiigiou:i Ssrrvici::i;'Sr:,gi;ii Srlrvictl-rJNi:nirrofit
Fl;: l.r, ir.{ ii is t'i r,t i i;
i:.:cd ss.ivices
Ai:i:t-,iri irir-rii$ iii.r t;
Idi.icsi.ionai services
Rt:sidenc*
.{ rts, I ti ts: itii ! n $ s nt. a ii ii R r:i: r'tt,:i i ii: ti
Reirigersisii v.;ii ie h*usr.,
irtif*ssir.'noi. srieiiiitii:, airrj ir,:ririiii:;;i :;sr'!rii'.9-i
Don't kncir',t'ldot siirelRei'i.l:isri
i'itsilii r:*iii
\ I- -.-.4..,.a..-i-.-,:Yidr Iii: ni.l.iri l: i:::
iieai ss',aie
l-t ilto ii
iia i rv;'A.g ricii ltu la i
:i :i :i t:
Cr:i.: ni i:i l\ss$slidents
In order to understand the importance of reducing electricity use to non-participants, the evaluation team
asked respondents to identify the portion of operating expenses represented by electricity costs. Similar
to participating firms, non-participating firms had difficulty with this question; only 20 out of 50
respondents provided a response. For these 20, the range was 1 percent to 80 percent, with an average
response of 15 percent. About half of respondents (nine of 20) indicated that their firm's electric bills
comprised 7 percent or less of their total annual operating expenses, while the other 11 indicated that
their firm's electric bills comprised 10 percent or more. The range of electricity costs to operating
expenses is generally lower among these non-participant respondents compared to the participants
surveyed for this evaluation, who indicated a range of 10 percent to 50 percent.
Total 50
Ir:.-;aii.i;riioii oi ii..rckv Vliiirntairr l:'(!'ir.i$l-'s irial-,o lilltigr,' li iiiAnst cr" Itrogl'an, iIY :iii.}$.'2{,\ i i,\:i.l)
ruAvrtANT
5.3.1 Awareness of Rocky lt{ountain Power Prograrns
\A/hen asked if they were aware that Pacific Power offers incentives and technical assistance to help
consumers reduce electricity usage, about 28 percent of program non-participant customers (14 of 50)
affirmed they were, as shown in Figure 11.
Figure 11. Non-Participant Arvareness of Rocky Mountain Power Assistance
" Aware that fiocky N,lountain
Porr;er otfels Assist+ncs tc
lm pi r*r,,e $ ne rg-v lif f icierir:1,
r hii:i aware th+i liosky
lvlou niain Pourei ofiEr"s
,Assistance is lmprove [ne!"gy
Lffir:iency
Those respondents who were aware that Rocky Mountain Power offers incentives and technical
assistance aimed at helping customers reduce electricity usage were asked to identify what programs or
services Rocky Mountain Power offers customers. This was an open-ended questiory so customers were
not prompted with a list of programs but were instead allowed to name as many programs or services
that they could.
Of the 14 respondents who were aware that Rocky Mountain Power offers incentives and technical
assistance, six were not able to identify a particular Rocky Mountain Power program or service that is
available to them.27 For those that could identify specific programs or services, the most common
response, offered by six respondents, was "incentives for efficient equipment" (shown in Figure 12). The
second most common program identified, mentioned by three respondents, was the "Irrigation Load
Control" program. None of the respondents identified the Energy FinAnswer program or technical
assistance.
27 More than one response was allowed. The 8 respondents who gave examples provided a total of 4 examples of
programs or services.
Roclq Mountain Power
Exhibit No. 5 Page 960 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Evaluatioir ol l{ocky h{ountain P$r,r,e.r's ldal..cr llntrrgv llinAnsr,,,er l}rogram iPY 2009-201 i )46
N$\J$ili A\I T
Figure 12. Non-participanI Awareness of Prograrns and Sierrri.ces
. ,,:,:,:,:,lll:,lll:+:.1:1:,
[.1 ]iAt1Sw,: i r ]:pi.n5s iiiri:riiiiiitiiiir
I rri gir i.:i: ri I ite r gy S;:rrtr i s ii:iiii:liiitiii ilii;:"::
Ir:'isstiin load Control iiilillliiiir,i*i:1ffiliiiiii;:i;:Iiiiiiiiiiiiiiii+iii
:.:.:1:E:.:.1::+:,:,:,:,:,:,:.Nci :\ri i'sr' L.rs n t Nnilw iiiiiiiiilil::l+iitititii
?34::
Couiit uf Respurideni::
Of those who were aware that Rocky Mountain Power offers programs, the most common source of
program information identified by four of 14 respondents was through "word of mouth." The second
most common source referenced was through "Rocky Mountain Power printed materials" (three of 1.4).
Additional responses of how non-participants indicated hearing about the programs are displayed in
Figure 13.
Figure 1,3" Haw hlon-Participa.nts Heard about Itocky l\{ountain Porqer Programs
Word of ir-routi..
ol'Respcniisnts
Respondents were also asked how they would prefer to learn about Rocky Mountain Power programs, as
shown in Figure 14. The top two preferred methods were "Rocky Mountain Power printed materials" (L4
respondents) and "email" (13 respondents). Comparing the preferred methods to learn about programs
with actual methods that non-participants had heard about Rocky Mountain Power assistance suggests
that current marketing efforts through Rocky Mountain Power representatives, bill inserts, and
newsletters are effective means to reach customers. However, email is the second most preferred method
to learn about programs, suggesting that email communications could offer a cost-effective option to
reach out to customers in the Idaho territory that could increase awareness and potentially participation.
Rocky Mountain Power
Exhibit No. 5 Page 961 of 1 365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
'i'i;iiie alli, vensi:r, $i' {:iifttracisi
'iV ijdvertisinA
i\$ci{v l,.icuiltairr Fou.;el r-iewsiettsi'
$sn't xncw,/l.ici sure
i)r*irii:i..1s fiai'Lrcipaitisii in Fii:i:x,t- \4ci;irl:,tin Power irrsgi^ains
li {)ii i(v i\{ ii (j ilia i r p$r^,re i fi ii nti. ii rn ei.tr iia i s
11
Ci)unt
Il..,aluaiion cl ii+ck-,, \{or-rntain lirr.r,ri"'s iii.aho linergl' liinAnslr'er l:}rograni if\ ?i}i}9-2{)i i)47
NAv$ TANT
Figure 14. Preferred &{athods to tr,earn of Rocky klnuntain Power: Programs
!\oChy futoUritain Pi..wer nt'-\rsiijttei i,,,,iiiiiii,,,i'j,:ii.,,:,,f,,i,ii;i.,,,,,,ii,,,iiiiiiiii.ii,
:
UUi I L Ki iU \aja !ILi L 5L: ! C l:!i:!iiiii:!iiiliiilii.::11ii]H:::::::::::::::::l::::::::1i:j:::i::i::::11::i
tt,
si4$s10i:i4:16
Cnuni: of Resnondents
S.3"2 Non-PartieipantEnergyEfficiencylmprovements
Non-participants were asked a series of questions about energy efficienry actions or improvements that
they may have taken during the program years of 2009 to 2011. These questions were in regards to: high
efficient equipment purchases, load or demand reduction efforts, and systematic evaluations or energy
analyses of existing facilities.28 Two of the respondents indicated that their facilities were constructed
since 2009, so they were not asked about changes made to their facilities. Neither of the respondents with
new facilities were aware of their firm using high efficient equipment when constructing the facility.
Of the 48 industrial non-participants with existing facilities in2009, seven respondents indicated that
their firms installed high efficiency equipment between 2009 and 2011. Only two industrial class non-
participating customers indicated that they had assistance from Rocky Mountain Power when they
installed high efficiency equipment, as shown in Figure 15. The high efficiency equipment installed by
industrial non-participants included lighting, refrigeration, heating, and variable frequency drive
equipment.
28 Respondents were asked if they had received assistance from Rocky Mountain Power if they reported taking
energy efficiency actions or improvements. The evaluation team assumes that this assistance is not in the form of
program participation because the non-participant list was crosschecked with the participant tracking data by Rocky
Mountain Power.
Rocky Mountain Power
Exhibit No. 5 Page 962 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
[i.,'aliiaiioii ol iiock-r. Mount.rin l]o\.r,e.r's Ici"riro iint:rgr.,.lilnAnsrvc.r i:]rogram ryY ]tii]9..20i ii .is
ru,&lr It.& N T
Figure 15. Non-Participant High Efficicrncy Equipment Purchases in Existing Facilities
* Yes. t:urchnseri or iristaiied high effir:iency
equipnient be$";een 1S$9 arid 2*it without
rssistsncsj frorn Rocky lvloilntain Power
r Yeg, puliirased or inst;iiied hiei-r efficiencY
er;uiament beirveen il$Q? and ?$ii tritli
essistance fro,'n Rocky Mountai* Pcwer
r N*, eiid not purthase oi" instnil hlgh efficiency
equ!pmQt)t
* l*r.rl ilfiirlicahiil,/Netv facility
The majority of non-participants (aa of 50) reported that they did not implement load control strategies.
However, four respondents stated that load control strategies were implemented with assistance from
Rocky Mountain Power, as shown in Figure 16.
Figure 16. Non-Participant Higir t,oad Control Strategies in Hxisting Facilities
+ Yes, iinpiementeri ioaii c$ntrol
stistsfiies beii+een i03$ and
2Sli^ r.riiir assistance iruni Rockv
[4ountain l)ower
r \lo, dirl nr:t implernent l*+rJ
c$ntt$l strate!tr,ies
r Not apolicabiei iiet"' faciiit'y'
The majority of industrial non-participants also had not conducted a systematic evaluation of their
facilities between 2009 and 2011. Three industrial non-participants stated that they had completed a
systematic evaluation of their facility; one of these stated that they had assistance from Rocky Mountain
Power (Figure L7). These industrial non-participants had taken actions based on the systematic
evaluations to replace pumPs, install a VFD, and install a motion sensor.
Rocky Mountain Power
Exhibit No. 5 Page 963 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
B.ialuaiion ol Rock1..- N{ounlain l}<r,,,,rrr''s Idairo }inergr: li"inAnsrq.'er Program (l}Y Stli}9-2{}li l)
ruAvrtANT
Figure 17. Non-Participant S5'stem.atic Hvaluations of F,xisting Facilities
s, Yes, corrducted li systematii
evaiuation belrrreen ?$09 and
2{}ii withcut assiste nce trom
Racky ir4ountain Power
r Yes, conducte$ a syst!ffiatic
evaiuatiolr between ISQ$ and
2iJ1.i. with ;lssirtance frr.riri Rocky
N4auntain Fower
r No, did not cclnduct fi systemntic
evaiuati0n
r l\cti a ppiica irls,,'Nenr facility
Non-participants who indicated that their firms installed high efficienry equipment, implemented load
control strategies, or undertook systematic evaluations of existing facilities between 2009 and 2011 were
asked what motivated them to take that action. Across all three activities, the most common response was
"to save money on energy bills," as shown in Figure 18.
Figure 18. Non-Participant Motivations for Taking Efficient Actions
Sy$tema iic Lvolu;riion
Load Ccntroi
iilgir ffficlert F.ouipment iriiit.ii.i liii]iii:tttitt.ii.i riliirr
5.i:)
Courii of liespondenls
iii: l'ri save rn$[ir]v sil eier:trii: i:llis I'i'r: *!:la jri ;ln incentivsj
I Tt'r replacti olil, Lrroken, oi psi-:riy lvorking iiquipmeni s Ts save eilersy
I Recommeilded by contractsisriti"adcr eiiieslcolleague s To imnreve oirerelions, Frsdui:tion, cr quaiity
5.3.3 Further Energy Efficiency Opportunities and Barriers
About 20 percent of non-participants (11 of 50) stated that they believed there were further energy
efficiency opportunities, as shown in Figure 19. However,22 of 50 non-participants did not believe their
firms could take additional steps to increase electric efficiency, and 17 reported that they were not sure.
Roclry Mountain Power
Exhibit No. 5 Page 964 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Erlaturaiion oL l{ockv N{ountain Prr,t cr's }claho Entrrg-v FinAnsro'rer }'rograni. ifY ?00!)-21}1 i)lii)
ru,&v xt,{ N T
Figure 19, No1;Farticipa.n! Indication of Further Energy F.fficiency Oppotfulities
, Yes, couki rnake fiiiure
irngrrovements
: i\i:, r:r:t.rld not maker f,.riure:
in'lprr:vements
r Noi sur$ *r Refused
When asked for examples of measures that the responding firms could implement in order to increase
electric efficienry, nine respondents offered the following actions.2e
, Purchase more efficient equipment/appliances/lighting (six respondents)
, Make upgrades in efficienry of equipment parts (three respondents)
" Improve building envelope (one respondent)
These same 11 non-participants who indicated they believed their firms could take additional steps to
improve electric efficiency were also asked what might prevent them from implementing electric
efficiency improvements. The most common potential barrier, noted by seven respondents, was "high
upfront costs;" respondents also noted "lack of access to capital" and "time/convenience for schedule," as
shown in Table 28. The Energy FinAnswer program offers technical assistance and incentives, which
could overcome the high upfront costs barrier. In addition, providing engineering services and technical
assistance may reduce the time/convenience burden for some customers. Rocky Mountain Power
currently does not have programs to overcome the barrier of lack of access to capital; support for
financing could help with this barrier if Rocky Mountain Power seeks to address it.
Rocky Mountain Power
Exhibit No. 5 Page 965 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Tatrle 28" Earriers to lm Electric Effici
7
i:i:li]]iEi
1
ti
11
Lack of access to capital
,i,iitrimU/. ienoe. i*chuflul+,iii.,i.iii..i,.,,,.............il:r,......
Total
2e Two of the non-participants that thought there were additional opportunities did not have examples; one did not
answer and the other was not sure.
Erralualion o{ Rockv N4ounlain i}<rwer.'s ldaho lin<,irgv FinAusrn,e-r }'rograni {PY ?t}i}!i-z0l : )r.i
Nf\VITANT
5.4 Energy Engineer Eindings
In July and August of 2012, the evaluation team interviewed energy engineers from five out of twenty-
three Energy Engineering Firms who are contracted by the Company to conduct energy analyses
throughout the territory, including Rocky Mountain Power territory in Idaho. Engineers do not work in
only one state because they tend to be experts in particular industrial or equipment areas.
5.4.1 Program$atisfaction
All of the energy engineers interviewed indicated that they were satisfied with their experience with the
Energy FinAnswer program overall. They believe that the program is well designed and works well for
customers.
Three engineers indicated some dissatisfaction with their role in the program. These engineers expressed
concern with what they perceive is a shift away from their customer interactions towards working in the
background; all three noted that they used to have more interaction with customers and that customers
still reach out to them. They also note that they have been discouraged from seeking additional project
leads.
5.4.2 Frogram Awareness and Motivation
It is unclear how engineers become aware of the Energy FinAnswer program. All five engineers
interviewed indicated that they had been working with the program for so long, or their company had
started working with the program before they started working there, so they did not remember how they
initially became aware of the Energy FinAnswer program.
Engineers appear to be motivated to work with the program as they would for any customer. Two
engineers indicated that it was a good opportunity while one indicated that the Company was their first
customer. Two engineers did not recall what motivated them to work with the Energy FinAnswer
ProSram.
5.4.3 Training, Roles, and Cornmunication
None of the interviewed engineers indicated that they had formal training from the program. These
engineers either had internal training on the program (three) or did not recall training on the program
(two). One indicated that their firm puts quite a bit of effort into ensuring that their engineers understand
the program. Others indicated that they educated themselves about the program. All engineers indicated
that they understood the program and their role in the program.
Engineers noted that the Company holds an annual meeting for consultants that they attend. Three of five
engineers had comments on these meetings, in addition to stating that the information provided at the
meetings was useful. Two engineers suggested changing the format of the meeting, indicating that they
would prefer more dialogue. One engineer was particularly appreciative of the annual meeting and
indicated that they were "quite valuable."
Engineers communicate mostly with the project manager who is associated with the area in which their
project is located; communication is as needed throughout the project. Sometimes, engineers will
communicate with the program mimager. Two engineers indicated that they have noticed an increase in
the consistency of communications with project managers over time. Two engineers were satisfied with
their communications with the program contacts; one was not sure. Two engineers were neither satisfied
Rocky Mountain Power
Exhibit No. 5 Page 966 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Erraluation o1 i{ocky lv{ountain l}cwcr's lciahrr EnerBv FinAnsrnrer I'rogram tl'Y 2009-201 i)
NAV}T&NT
nor dissatisfied; these two indicated that the project managers were busy, and the engineers may have to
contact them more than once to get answers to questions. \A/hen they are able to reach the program
contact, the contact has been able to answer their questions.
5.4.4 Energy Analysis Frocess
Engineers indicate that the bulk of their time (at least half) with the Energy FinAnswer program is spent
doing contracted energy analyses, as opposed to quality control reviews of other engineering firm's work.
The interviewed engineers provided similar descriptions of the energy analysis process. They indicate
that a project manager contacts them with an interested customer's information. They are able to review
some information, depending on the project and customer, before going out to the customer's site. The
engineer will collect as much information as possible while on the customer's site; this includes noting
equipment and settings in place and talking with facilities personnel. After this initial site visit, the
engineer will draft up a report that provides a rough estimate of savings opportunities; the report is sent
to the project manager. The project manager and the customer will decide if they are moving forward
with the project, and, if so, the project manager will contact the engineer again.
At this point, the engineer will determine whether they can do the work within the time allotted by the
program without a proposal, or if the engineer will need more time.3o If the engineer needs more time, the
engineer submits a proposal to the project manager that details the required budget to complete the
analysis.
Engineers sometimes must retum to the site for the more detailed energy analysis, but sometimes they
can conduct this work based on data already collected and through contact with the site. When they have
completed the analysis, they prepare an EAR that they send to the project manager. The EAR is peer
reviewed for quality control, and the engineer revises as necessary and resubmits the EAR to the project
manager.
Two engineers noted that the EARs and associated quality control reviews were by far the most rigorous
that they had seen among different programs over time. Three engineers offered additional comments on
the EARs. One indicated that some projects might be better served with shorter, simpler reports. Projects
that could be candidates for simpler reports are those with straightforward EEMs. Two others indicated
that they were not clear on what level of detail should be included in reports; however, both of these
engineers noted that new templates had recently been provided, and they expressed optimism that the
new templates may relieve this confusion.
5.4.5 Quafiity Control Ftevlews
All five engineers that were interviewed also conducted quality control reviews of peer engineers' work.
One engineer suggested that his firm spends about half their time with Energy FinAnswer conducting
these reviews; the other five indicated less than 10 percent or less than 5 percent of their time working
with Energy FinAnswer is spent on quality control reviews.
These quality control reviews are completed on EARs that are submitted by other engineering firms. All
engineers believe that their peers provide them with constructive feedback most of the time. Reviews are
30 The program allowed 16 hours without a proposal in 2009 and 2010; in 2011, the program began allowing 24 hours
of work without a proposal.
Roclry Mountain Power
Exhibit No. 5 Page 967 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Il\ralr"ratio* oL Rockl. lo4oulrtain P<rwer's lcial..o Errerlgv liinAnst'er I'rosran', iPY :ii0i].-201 ir\::i.1
ruAvril&Nr
valuable because they provide a different viewpoint and they can improve the value of the work. One
engineer indicated that the quality control reviews had changed the way they work outside of the
program because it increased diligence. Others indicated that the reviews did not change the way they
did business; one noted that they always did internal quality control reviews.
All five engineers indicate that the time allotted for completion of quality control reviews is sufficient.
Two stated that it is sometimes difficult to turn their attention to quality control reviews when they are in
the middle of another project, but that they are able to work with the project managers to have more time
if necessary.
5.4.6 Measurement and Verification Process
Engineers indicate that they conduct measurement and verification both with the program (where their
work is funded by the Company) and as part of commissioning (where their work is funded by the
customer). Engineers state that, formally, they find out about project completion from the project
manager, who is notified by the customer. However, informally, they are in contact with the customer
either because they have previously been retained to complete the commissioning or because the project
manager asked them to keep up to date on the project's status. Engineers noted that customers sometimes
are challenged to manage the project and stay in touch with the program from the EAR through
commissioning.
Engineers believe the commissioning step, for equipment that benefits from commissioning, is valuable
because it provides four weeks of data with the equipment in operation as designed in the energy
analysis (or improved after installation by the engineer). When the engineers conduct both
commissioning and the final inspection on a project they can usually combine the visits and split the
costs between activities.
For verification, the engineers ensure that the equipment is installed and operating as designed in the
EAR. They may take pictures of the installed equipment, note serial numbers, review invoices, take
measurements, and speak to the site contact. If they did not conduct the commissioning, they will review
the commissioning reporf which includes information about actual operating energy use for four weeks.
The Final Inspection Report includes the engineer's estimate of annual energy savings based on the data
that they have available.
Engineers note that they usually have enough time to conduct measurement and verification, but that the
task is more difficult if the customer did not do commissioning. They are challenged to estimate savings
without commissioning data within the time allotted for measurement and verification.
5,4.7 Business lmpact
Engineers were asked how working with Energy FinAnswer had impacted their business. Engineers
provided mixed responses. Two engineers indicated that they started doing energy analyses with the
Company as their first customer. Two others noted that the program had no impact on their business
beyond the project work that they did. One engineer was not sure how to describe the impact of the
program on his business.
None of the five engineers we spoke with are doing the same kind of work for ostomers in the Rocky
Mountain Power territory who do not work with the Rocky Mountain Power programs. They indicate
that they would continue to offer the same kind of services, but they cannot foresee great demand for this
Rocky Mountain Power
Exhibit No. 5 Page 968 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Eriali:aiioi^, oL liockv lvllounlain f)cnrrev's ld;rho Entrrgl, liin1l.r".sr,r"ey l:)rogram iPY ?0t19-201 i )t:1
N$V}TANT
work. However, one engineer indicated the challenge at identifying the market's willingness to seek
energy analyses without the program because the utility has offered some form of assistance for so long.
5.5 Ooerall Process Findings
From May through August 2012, the evaluation team surveyed or interviewed 66 customers: L2
participants, four near participants, 50 industrial class non-participants. The evaluation team also
conducted in-depth interviews with five energy engineers. This section summarizes answers to the
research questions for this process evaluation.
What are the program goals, concept and design? Are they based on sound theory and practice,
and, if not, in what respects?
The Energy FinAnswer program in Idaho seeks to improve energy efficiency at commercial and
industrial sites. The basic program theory is that providing technical assistance will help overcome
information gaps for customers and providing an incentive will help the customers overcome cost
barriers. The design is indicated in the program logic model in the program overview. The program
concept and design are based on sound theory and practice in line with best practices for non-
residential large comprehensive incentive program design.31 No explicit energy savings, demand
savings, or participation goals were outlined for the Energy FinAnswer program for 2009 or 2010; in
2011, the program had an energy savings goal of 3,598,1.84 kWh. This goal was more than twice
average savings in the previous two years and was not met by program reported savings.
Do program managers have the resources and capacity to implement the program as planned?
Program managers indicated that they had the resources and capacity to implement the program as
planned. All eight participants who reported contacting Rocky Mountain Power with questions
indicated that the program representatives were knowledgeable in answering their questions, and all
but one out of those eight said that the representatives were timely. No near participants indicated
contacting Rocky Mountain Power; however, one of the near participants said that there was no
follow up from the program, and follow up would have been helpful to keep the project moving.
Energy engineers noted that there were some communications challenges and delays between the
customers and the program. Since the findings across data sources conflict, it is not clear if resource
and capacity constraints are hindering the program process.
31 Quantum Consulting. 2004. National Energy Efficiency Best Practices Study Vol. NR-5 Non-Residential Large
Comprehensive Incentive Best Practices Report. Submitted to California Best Practices Project Advisory Committee.
Roclg Mountain Power
Exhibit No. 5 Page 969 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
2.
E.;ali-iiriioii *l ltock_v N4ouniain lLo'lr'r:r's Iciaho Energv FinAnsr+ar Proprani iP\' :tlt.}9-201 i )
ruAvr tANT
Is the program being delivered as planned and if not, how and why?
In general, participants, near participants, and energy engineers describe the program operating as
expected from the logic model. Also, two near participants did not move forward with projects after
the energy analysis because the savings based on their project scope were not large enough to qualify
for the program; this indicates that the energy analysis and PM review is working to focus efforts
towards projects with savings.
Based on the evaluation findings, 10 of 12 of the program outcomes expected from the logic model
were positively affirmed. Table 29 lists the program outcomes indicated in the logic model along with
findings based on the key indicators and data sources reviewed in the process evaluation (refer to
Table 8 for key indicators and data sources). One of the outcomes indicated in the logic model,
"customers are aware of the program" was not clearly indicated through customer surveys; this is
addressed in the next question. The other outcome that was not affirmed is meeting energy savings
targets, as mentioned above.
Is the program reaching the intended target population, and if not, why? Specifically, are eligible
customers aware of the progr.rm, how are they becoming aware, and what is the program influence
on their actions?
All industrial customers and commercial customers with facilities greater than 20,000 square feet are
eligible for the Energy FinAnswer program. From 2009 to 201.1. there were 32 participating projects
from 28 unique customers and 11 nearly participating customers. This implies an estimated program
reach of 2.4 percent of eligible customers (39 of 1.,617).e
Are eligible customers aware of the program? To understand if eligible customers are aware of the
program, the evaluation team relies on non-participant responses. Of a representative sample of
industrial non-participants, 28 percent (14 out of 50) affirmed that they were aware that Rocky
Mountain Power offers incentives and technical assistance to customers in their class to help them
reduce electricity usage. When asked what programs or services were offered to customers in their
class, six non-participants identified incentives for efficient equipment and none identified technical
assistance. No industrial non-participants were specifically aware of Energy FinAnswer as a
program. The program is not expected to have high name recognition due to the intentional choice by
Rocky Mountain Power to market the non-residential programs as a portfolio and then match
customers with the program that best fits their needs. However, low awareness that Rocky Mountain
Power offers technical assistance and incentives may limit participation by eligible customers.
How are they becoming aware? Customers who do begin working with the program mostly find out
about it from vendors or directly from Rocky Mountain Power, as is expected from the program logic
model. However, the logic model also presumes that customers will learn about the program from
marketing campaigns which includes print and radio advertisements in addition to a customer
efficiency focused website. No participants indicated that they had heard about the program through
any of these channels. One near participant had learned about the program through print materials
and online advertisements. Some non-participants indicated these channels as well; one had learned
32 Eligible customers are estimated at 1,617 , the sum of: 28 participants, 11 near participants, 719 industrial class non-
participants, and 857 commercial class non-participants (see methodology for explanation).
Rocky Mountain Power
Exhibit No. 5 Page 970 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
3.
4.
Il..;alnat'ior, r:1 iR+ck,v lvtlountair"r Po'r,rrer's Iciaho li.nergv IiinAnsr,r,cr I'rogram il'Y ?{lt}!i-201 ii i'. ai.
NI &V XTE NT
about programs through TV advertising, and three recalled printed materials. Non-participants
indicated that they mostly prefer to learn about programs through printed materials, email, and mail.
What is the program influence on their actions? Participants are influenced by saving money on
energy bills, obtaining incentives, and saving energy. Most measures installed are at least partially
influenced by the program. Participants indicated that just four of 17 measures would have been
installed at the same time without the program, and five of 17 measures would not have been
installed at all without the program. The other eight measures would have been completed later or
would not have had as large of energy savings without the program. After adjusting for prior
experience and inconsistencies, two measures are assumed to be full free riders-that is measures
that would have been completed at the same time without the program. Another three are partial free
riders, while 12 measures are not free riders. There is some indication of spillover from this program;
one additional "like" project and one "unlike" project were completed with no incentives at least
partly due to the program influence.
What barriers are preventing customers from taking actions to reduce energy consumption and
demand, and which jeopardize program cost-effectiveness?
Customers who believed their firms could take additional action to reduce energy consumption and
demand were asked what might prevent them from moving forward. High upfront costs were most
commonly cited as a barrier to further customer action to reduce energy consumption and demand,
by seven out of nine participants, two out of four near participants, and seven out of 11 non-
participants. Lack of access to capital, time constraints, long payback periods, and internal
communications difficulties were also noted as barriers. However, a large portion of non-participants
(78 percent) did not believe there were further actions that their firm could take to improve efficiency.
These responses indicated that one barrier might be that the eligible population truly does not have
additional energy efficienry actions or is not aware of possible additional actions. Given that they
believe there are no other opportunities, it may be a challenge to gain their attention and educate
them otherwise.
Are participants achieving desired outcomes, and if not how and why?
For the most part, participants are achieving desired outcomes. Participants are mostly satisfied,
keeping their equipment in operation, and achieving energy savings as expected based on the
program logic model. Energy engineers were not doing similar work with eligible customers outside
of the program but participants indicate both repeat participation and some "like" and "unlike"
spillover.
Rocky Mountain Power
Exhibit No.5 Page 971 of 1365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
5-
6.
I
E..,air,iatioii ol RockV N{ounia:in Porq,ei.'s ld.rho llnelgl. IiinAnsn,er l,rograni iI,l ?i}illi-201 i)
rus\xsN*rANT
:,:i:i:i:i:i:i:i,: '':i:::i:i,: . .. ...,,..:::::::.''r"' .,,,i:i:i:r:r:r:r:::Ult ,
t,
,,.,,,,,,,,:' .:,::,:,::::l'' i"
Customer expresses
interest in the program
'ic"Ja, ims.,mu'':'
.
,, .eUmi,UOt f iiiii': iiiiiiiii'
::iii
Energy engineers selected
for project analysis and
oualitv control
......End$y sa*ing,rneeisu lpg,
,,,bqqtg;,and,, enefitSt,t,;,,,,,.,1' "
......1.aefitlliudi:'"' i,......,.iii':'
:iii,...........,'
Measures installed and
commissioned as required
, l*tairUiu"'ui,*.;sUr*r'i:ii,iiiiiiiit#trifiid ii..: ;i;iiii,i-,.,iiiiiiiiiiiii,,
Customers receive
benefits and have reduced
first costs
i i i:,*cni[n.: $Aik d and;.,
and,i:ens,tB/ use,redu ction,
Tahte 29" Prngrarn flutcomes and Findings
Rocky Mountain Power
Exhibit No. 5 Page 972 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Reduce kW and/or kWh at Yes, most participants indicate that energy savings are meeting exPectatlons.
customer facili
tatgb*,.,,1.i"''',,,,,,,,,,.....,', :' :::::::::::,:
Customers observe
energy cost savrngs
i\iirii-raiior', t:i iior:kir klor-tnfattr i:'1r,r,:rti"'s ft-iaho ll.tttii'.r,' l'!nAl1sl^rcr i:trogratii iirY ?iii!!i-2il:l :i
ru vr{,ANT
Based on the findings from this evaluatiory the evaluation team has identified the following
recommendations to enhance the delivery efficienry and effectiveness of the Energy FinAnswer Program
in future program cycles:
" Recommendation 1: Consider revised marketing strategies to increase lead generation. A
revised marketing strategy may be necessary to reach eligible customers who are not learning
about the program through existing marketing and outreach efforts; just L4 out of 50 non-
participants were aware that Rocky Mountain Power offers any assistance to improve energy
efficiency, and none were aware of the technical assistance offered by this program. Project
managers, program managers, and energy engineers understand the potential for cost-effective
improvements across industries. Data from previous projects can be used to identify cost savings
and operational improvements from common efficienry efforts in particular industries in order to
interest more eligible customers. Emphasis on non-energy benefits may motivate the portion of
ostomers (78 percent of surveyed non-participants) who do not believe there are actions that
they could take to improve efficiency. Customers who do not believe there are actions that they
can take may not respond to traditional approaches promoting energy efficiency programs.
Reaching out to customers on their terms helps increase awareness and participation in the
program. Increasing participation is important to ensure continued program success.
" Recommendation 2: Closely track proiect status. 1n2011., the program's reported savings did not
meet savings goals, and the reported savings in 2011 were about one-third of the reported
savings in 2009 and 2010. Over the period from 2009 to201.1., the program had 32 participants and
11 near participants (not including projects that are considered 'cancelled'). The four near
participants interviewed as part of this evaluation indicated that the project status of "on hold"
was not correct. Even though these near participants were listed as "on hold" with their project
status last updated on or before ]une of 2011, none of the near participants we interviewed had
plans to continue their projects with the program. Follow up with these customers to check on
their status could have informed the project manager that their true status was "cancelled."
Closely tracking the status of projects should alert the program manager when savings goals may
not be met by existing projects. The program mEmager could then determine alternative strategies
to meeting savings goals. Depending on the projects in the pipeline at the time, the approach may
be to seek out new participants, to encourage project completion, or to encourage customers to
take action on measures identified in their EARs that were not currently being addressed.
Ensuring that projects are completed as expected decreases uncertainty and risk for projects
where Rocky Mountain Power has already invested time and resources.
" Recommendation 3: Clarify baseline conditions, particularly for lighting projects. There were
two lighting projects in the Energy FinAnswer program impact evaluation sample which did not
include any description of baseline equipment. Project files simply stated that premium efficiency
T8s were being installed, and no calculations were provided. Without information on any
removed fixtures, or baseline assumptions in the case of new construction, it is not possible to
accurately determine how savings were calculated for the projects.
Roclry Mountain Po,er
Exhibit No. 5 Page 973 of l365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Er,'ah-iaiior", ol. i{r:*k-v }'loulrtain I'erre.r's lciaho Enetgv llinr\lurt'er Frograni iPY !i}0!i-201 i)
Rocky Mountain Power
Exhibit No. 5 Page 974 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
N&\I$il-ANT
Recommendation 4: Include energy and demand savings calculations in a spreadsheet fonnat.
By providing this information in one consolidated location, future evaluation efforts will be more
efficient and reduce the potential for comparing verified savings to incorrect or outdated project
assumptions.
Although each project properly documented the reported energy and demand savings
estimates, the absence of savings calculations (particularly for demand savings) reduces the
transparency of reported savings, along with the efficiency of evaluation efforts. Providing
both the input assumptions and savings calculation methodologies will ensure the
comparability and accuracy of reported and evaluated savings and will reduce associated
evaluation costs.
Include the clearly identified final Energy Savings table in project files for the evaluation. The
data should include both baseline and current energy and demand usage as well as savings
estimates. Utilizing consistent formats based on the FINAL numbers is important for all
follow up activities, and will provide decision makers the key information needed to quickly
assess the situation and take appropriate action relative to the inspections conducted. It is
noted that the key elements are included in the documentation for each project, but it is often
difficult to identify the final set of parameters used because the project files capture multiple
changes/revisions to the application process.
Bvaluurtion ol. Rock'l N,{ountain l}crwer's }ciairo li.nergv liinAnslver }\'ogran', {['Y ?0Lli-201 i )u\]
Roclq Mountain Power
Exhibit No. 5 Page 975 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Final Evaluation Report for ldaho's Energy FinAnswer
Program {PY 2009-2011)
AT}PENDICES
Prepared for:
Kocky Mountain Power
RSCKYMOUNTAIN
PmtfHn
Prepared by:
N$V $ t A N T Ins,artnersirip,vitlr ffiffiN
Narriliant (it.lnsulting. inc.
I375 }t'alnut Street
Suite 2tlt.l
R*ulder, CC) B{]302
303.728.250{i
rvr"-rt,.navisantconsu I ting.corn
F*rbruary 15.2i]13
Flni:r5lv N{arket Innorrations, I-nc.
ii3 Coiumbia St
Suite 4ilil
Seaitle, tr\,A 98104
?06-6?1-116i]
rvr,r,rt, .e mi r:o ns ultin {:. (:o m
N$\V$TAN]-
Appendix A. Glossary of Frequently-Used Evaluation Tenns... ..............A-1
Appendix B. Net Savings Methodology B-1
B.1 Measurement of Net Savings Memo - |anuary 27,2012....... ............B-1
8.2 Net Savings Scoring - June '18,2012 ........8-11
Appendix C. Process Evaluation Survey Instruments.............. .................C-1
C.1 Participant Survey Instrument .................. C-1
C.2 Near-Participant Survey Instrument................... ........ C-15
C.3 Non-Participant Survey Instrument. ......C-23
C.4 Energy Engineer Survey Instrument. ..... C-33
Roclry Mountain Power
Exhibit No. 5 Page 976 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
Appendix D. Process Evaluation Detailed Findings ............... D-l
Participant Results .................D-1
Near-Participant Results .......D-3
Non-Participant Results ........D-4
Con,{c'si,}tiai ar$ &aprieia,_"r,
idanc Energy FirAnswer Evaiualion Report
D.1
D.2
D.3
Page i
,n|\T-S\V$TANT
A.L Glossaryl
Adiustments: For M&V analyses, factors that modify baseline energy or demand values to account for
independent variable values (conditions) in the reporting period.
Allowances: Allowances represent the amount of a pollutant that a source is permitted to emit during a
specified time in the future under a cap and trade program. Allowances are often confused with credits
earned in the context of project-based or offset programs, in which sources trade with other facilities to
attain compliance with a conventional regulatory requirement. Cap and trade program basics are
discussed at the following EPA Web site: <http://www.epa.gov/ airmarkets/cap-trade/index.html>.
Assessment boundary: The boundary within which all the primary effects and significant secondary
effects associated with a project are evaluated.
Baseline: Conditions, including energy consumption and related emissions that would have occurred
without implementation of the subject project or program. Baseline conditions are sometimes referred to
as "business-as-usual" conditions. Baselines are defined as either project-specific baselines or
performance standard baselines.
Baseline period: The period of time selected as representative of facility operations before the energy
efficiency activity takes place.
Bias: The extent to which a measurement or a sampling or analytic method systematically
underestimates or overestimates a value.
Co-benefits: The impacts of an energy efficiency program other than energy and demand savings.
Coincident demand: The metered demand of a device, circuit, or building that occurs at the same time
as the peak demand of a utility's system load or at the same time as some other peak of interest, such as
building or facility peak demand. This should be expressed to indicate the peak of interest (e.g.,
"demand coincident with the utility system peak") Diversity factor is defined as the ratio of the sum of
the demands of a group of users to their coincident maximum demand. Therefore, diversity factors are
always equal to one or greater.
Comparison group: A group of consumers who did not participate in the evaluated program during
the program year and who share as many characteristics as possible with the participant group.
Confidence: An indication of how close a value is to the true value of the quantity in question.
Confidence is the likelihood that the evaluation has captured the true impacts of the program within a
certain range of values (i.e., precision).
1 Glossary definitions are provided to assist readers of this report, and are adapted from the Model Energy
Efficienry Program Impact Evaluation Guide, US Environmental Protection Agenry, November 2007
ionilcenir'si enri p,iprefsri Page A.- l
r$ann fnsr.gy- FirAnswsr Ivaiuation Report
Apnendir ii - Giosserry oi Fi"equentiv'Used Evaiuaiicn Ternis
Rocky Mountain Power
Exhibit No. 5 Page 977 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
NJ\VXTANT
Cost-effectiveness: An indicator of the relative performance or economic attractiveness of any energy
efficienry investment or practice. In the energy efficiency field, the present value of the estimated
benefits produced by an energy efficiency program is compared to the estimated total costs to determine
if the proposed investment or measure is desirable from a variety of perspectives (e.9., whether the
estimated benefits exceed the estimated costs from a societal perspective).
Database for Energy-Efficient Resources (DEER):
A Califomia database designed to provide well-documented estimates of energy and peak demand
savings values, measure costs, and effective useful life.
Demand Side Management (DSM): See "Energy efficiency."
Deemed savings: An estimate of an energy savings or energy-demand savings outcome (gross savings)
for a single unit of an installed energy efficienry measure that
(a) has been developed from data sources and analytical methods that are widely considered acceptable
for the measure and purpose and (b) is applicable to the situation being evaluated.
Demand: The time rate of energy flow. Demand usually refers to electric power measured in kW (equals
k\A/h/h) but can also refer to natural gas, usually as Btu/hr, kBtu/ hr, therms/day, etc.
Direct emissions: Direct emissions are changes in emissions at the site (controlled by the project sponsor
or owner) where the project takes place. Direct emissions are the source of avoided emissions for thermal
energy efficiency measures (e.g., avoided emissions from burning natural gas in a water heater).
Effective Useful Life (EUL): An estimate of the median number of years that the efficienry measures
installed under a program are still in place and operable.
Energy efficiency: The use of less energy to provide the same or an improved level of service to the
energy consumer in an economically efficient way; or using less energy to perform the same function.
"Energy conservation" is a term that has also been used, but it has the connotation of doing without a
service in order to save energy rather than using less energy to perform the same function. Demand Side
Management (DSM) is also frequently used to refer to actively-managed energy efficiency initiatives.
Energy Efficiency Measure (EEM): A permanently installed measure which can improve the efficiency
of the Customer's electric energy use.
Engineering model: Engineering equations used to calculate energy usage and savings. These models
are usually based on a quantitative description of physical processes that transform delivered energy
into useful work such as heat, lighting, or motor drive. In practice, these models may be reduced to
simple equations in spreadsheets that calculate energy usage or savings as a function of measurable
attributes of customers, facilities, or equipment (e.9. lighting use = watts x hours of use).
Error: Deviation of measurements from the true value.
Evaluation: The performance of studies and activities aimed at determining the effects of a program; any
of a wide range of assessment activities associated with understanding or documenting program
performance, assessing program or program-related markets and market operations; any of a wide range
of evaluative efforts including assessing program-induced changes in energy efficiency markets, levels of
demand or energy savings, and program cost-effectiveness.
tloniideniral anil Propr'elsry*
idai:n [.nergy FinAnsrter Ivaiuntion Rsprrt
Apcendix A - Giossory oi Frequenllv-Used Eva!u*iicri Tsrnts
Rocky Mountain Power
Exhibit No. 5 Page 978 of I 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
i'}age A-2
nNd\V$TANIT
Evaluatioru Measurement and Verification (EM&V): Data collection, monitoring, and analysis
associated with the calculation of gross and net energy and demand savings from individual sites or
projects which is performed in conjunction with a program or portfolio evaluation (see Evaluation).
Evaluated savings estimate: Savings estimates reported by an evaluator after the energy impact
evaluation has been completed. Often referred to as Ex Post Saaings (From the Latin for "from
something done afterward.")
Free driver: A non-participant who has adopted a particular efficiency measure or practice as a result of
the evaluated program.
Free rider: A program participant who would have implemented the program measure or practice in the
absence of the program. Free riders can be total, partial, or deferred.
Gross savings: The change in energy consumption and/or demand that results directly from
program-related actions taken by participants in an efficiency program, regardless of why they
participated.
Impact evaluation: An evaluation of the program-specific, directly induced changes (e.g., energy and/or
demand usage) attributable to an energy efficienry Program.
Independent variables: The factors that affect energy use and demand, but cannot be controlled (e.9.,
weather or occupancy).
Interactive factors: Applicable to IPMVP Options A and B; changes in energy use or demand occurring
beyond the measurement boundary of the M&V analysis.
Load shapes: Representations such as graphs, tables, and databases that describe energy consumption
rates as a function of another variable such as time or outdoor air temperature.
Market effect evaluation: An evaluation of the change in the structure or functioning of a market, or
the behavior of participants in a market, that results from one or more program efforts.. Typically, the
resultant market or behavior change Ieads to an increase in the adoption of energy-efficient products,
services, or practices.
Market transformation: A reduction in market barriers resulting from a market intervention, as
evidenced by a set of market effects, that lasts after the intervention has been withdrawn, reduced, or
changed.
Measurement A procedure for assigning a number to an observed object or event.
Measurement and Verification (M&V): Data collection, monitoring, and analysis associated with the
calculation of gross energy and demand savings from individual sites or projects. M&V can be a
subset of program impact evaluation.
Measurement boundary: The boundary of the analysis for determining direct energy and/or demand
savings.
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Roclry Mountain Power
Exhibit No. 5 Page 979 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page A.-3
N&\r$t&NT
Metering: The collection of energy consumption data over time through the use of meters. These meters
may collect information with respect to an end-use, a circuit, a piece of equipment, or a whole building
(or facility). Short-term metering generally refers to data collection for no more than a few weeks. End-
use metering refers specifically to separate data collection for one or more end-uses in a facility, such as
lighting, air conditioning or refrigeration. Spot metering is an instantaneous measurement (rather than
over time) to determine an energy consumption rate.
Monitoring: Gathering of relevant measurement data, including but not limited to energy consumption
data, over time to evaluate equipment or system performance,8.5., chiller electric demand, inlet
evaporator temperature and flow, outlet evaporator temperature, condenser inlet temperature, and
ambient dry-bulb temperature and relative humidity or wet-bulb temperature, for use in developing a
chiller performance map (e.g., kWton vs. cooling load and vs. condenser inlet temperature).
Net savings: The total change in load that is attributable to an energy efficiency program. This change
in load may include, implicitly or explicitly, the effects of free drivers, free riders, energy efficiency
standards, changes in the level of energy service, and other causes of changes in energy consumption or
demand.
Net-to-gross ratio (NTGR): A factor representing net program savings divided by gross program
savings that is applied to gross program impacts to convert them into net program load impacts.
Non-participanfi Any consumer who was eligible but did not participate in the subject efficiency
program, in a given program year. Each evaluation plan should provide a definition of a non-
participant as it applies to a specific evaluation.
Normalized annual consumption (NAC) analysis: A regression-based method that analyzes monthly
energy consumption data.
Participant A consumer that received a service offered through the subject efficienry program, in a
given program year. The term "service" is used in this definition to suggest that the service can be a
wide variety of services, including financial rebates, technical assistance, product installations, training,
energy efficiency information or other services, items, or conditions. Each evaluation plan should define
"participanf' as it applies to the specific evaluation.
Peak demand: The maximum level of metered demand during a specified period, such as a billing
month or a peak demand period.
Persistence study: A study to assess changes in program impacts over time (including retention and
degradation).
Portfolio: Either (a) a collection of similar programs addressing the same market (e.g., a portfolio of
residential programs), technology (e.9., motor efficiency programs), or mechanisms (e.g., loan programs)
or (b) the set of all programs conducted by one organization, such as a utility (and which could include
programs that cover multiple markets, technologies, etc.).
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Roclry Mountain Power
Exhibit No. 5 Page 980 of 1 365
Case No. PAC-E-14{7
\Mtness: Kathryn C. Hymas
Page A.-4
.\
N $V$ ilANT
Potential studies: Studies conducted to assess market baselines and savings potentials for different
technologies and customer markets. Potential is typically defined in terms of technical potential, market
potential, and economic potential.
Precision: The indication of the closeness of agreement among repeated measurements of the same
physical quantity.
Primary effects: Effects that the project or program are intended to achieve. For efficiency programs,
this is primarily a reduction in energy use per unit of output.
Process evaluation: A systematic assessment of an energy efficiency program for the purposes of
documenting program operations at the time of the examinatiory and identifying and recommending
improvements to increase the program's efficiency or effectiveness for acquiring energy resources while
maintaining high levels of participant satisfaction.
Program: A group of projects, with similar characteristics and installed in similar applications. Examples
could include a utility program to install energy-efficient lighting in commercial buildings, a developer's
program to build a subdivision of homes that have photovoltaic systems, or a state residential energy
efficienry code program.
Project An activity or course of action involving one or multiple energy efficiency measures, at a single
facility or site.
Rebound effect: A change in energy-using behavior that yields an increased level of service and occurs
as a result of taking an energy efficiency action.
Regression analysis: Analysis of the relationship between a dependent variable (response variable) to
specified independent variables (explanatory variables). The mathematical model of their relationship
is the regression equation.
Retiability: Refers to the likelihood that the observations can be replicated.
Remaining Useful Life GUL): An estimate of the remaining number of years that a technology being
replaced under an early retirement program would have remained in place and operable. Accurate
estimation of the RLIL is important in determining lifetime program savings and cost effectiveness.
Reported savings estimate: Forecasted savings used for program and portfolio planning purposes.
Often referred to as Ex Ante Sauings (From the Latin for "beforehand.")
Reporting period: The time following implementation of an energy efficiency activity during which
savings are to be determined.
Resource acquisition program: Programs designed to directly achieve energy and or demand savings,
and possibly avoided emissions
Retrofit isolation: The savings measurement approach defined in IPMVP Options A and B, and
ASHRAE Guideline 14, that determines energy or demand savings through the use of meters to isolate
the energy flows for the system(s) under consideration.
ilon,{deni,ei a,,tg pr"o6ri.sf€ry
i'iai:c Snsryy FinAnswsr Evaiuati.:n Report
Apcendix A - Gisssery of Siequeniiy"rjsed Evaiuaiicrn Teinrs
Rocky Mountain Power
Exhibit No, 5 Page 981 of 1365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
ilage i.-$
ruAv$tANt r
Rigon The level of expected confidence and precision. The higher the level of rigor, the more confident
one is that the results of the evaluation are both accurate and precise.
Spillover: Reductions in energy consumption and/or demand caused by the presence of the energy
efficiency program, beyond the program-related gross savings of the participants. There can be
participant and/or nonparticipant spillover.
Statistically adjusted engineering (SAE) models: A category of statistical analysis models that
incorporate the engineering estimate of savings as a dependent variable.
Stipulated values: See "deemed savings."
Takeback effect See "rebound effect."
Uncertainty: The range or interval of doubt surrounding a measured or calculated value within which
the true value is expected to fall within some degree of confidence.
Roclq Mountain Power
Exhibit No. 5 Page 982 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Co**cenL,a eric Fioprrefary
idahc In*rgy FinAnswer Evaluation Repait
Apnendir A - Gicsssry of Fi'equentiy-Used Evaiuaiion Teims
Page F.-$
Ng\\T$TANT
Rocky Mountain Power
Exhibit No. 5 Page 983 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
8.7
To:
From:
Date:
Subject:
Measurement of Net Saaings Memo - January 27,2072
Shawn Grant Esther Giezendanner, PacifiCorp
Kevin Cooney, Matt Haakenstad, and Mike Yim, Naviganf Ellen Steiner, ]ess
Chandler, and Jeremy Kraft, Energy Market Innovations,Inc
]anuary 27,2012
Measurement of Net Savings
o
This memorandum provides context and suggested approaches for estimating net savings so that the
team can decide whether to move forward with this approach or continue to make changes.
Estimation of net savings attempts first to assess program influence on the participants' decision to
implement an energy efficiency project. This estimation includes an examination of the program's
influence on three key characteristics of the decision related to the project: timing, scope, and extent.
Measurement of net savings then attempts to estimate program influence on the broader market with
respect to non-program actions (free-ridership and spillover). These two efforts are combined for an
overall estimate of net savings. First, the previous method is briefly described for context followed by
our proposed method moving forward.
Preoious method for tneasurement
The approach used in past evaluations for estimating program influence consisted of presenting
program participants a battery of six core questions, used in combination, to derive free-ridership scores
included in net-to-gross calculations. The six core questions were:
. Would the participant have installed the equipment without the program?
e Had the participant already ordered or installed the equipment before learning about the
program?
o Would the participant have installed the equipment to the same level efficienry without the
program incentive?
o Would the participant have installed the same quantity of equipment without the program?
o fu absence of the program, when would the participant have installed the equipment; were they
planning to install the equipment in the same year?
o Was the equipment included in the participant's most recent capital budget?
Responses to these survey questions were evaluated using a scoring matrix (for an example of this
matrix see Appendix G.1 in Final Evaluation Report For Wyoming's FinAnswer Express Program2) to
determine each participant's free-ridership score. Spillover was not quantitatively assessed in past
evaluations.
2 Navigant and EMI. Final Eoaluation Report For Wyoming's FinAnswer Express Program. Prepared for Rocky Mountain
Power. October 25, 2071.
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!Cai:c [.nergy FinAnsner E.",aiuation Repoil
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.tNd\V$TANT
Reasons for proposing a new method
Though a consistent net savings estimation technique across programs is desirable to ensure
comparability, our experience with the previous method provided several "lessons learned." Based on
this experience, we believe a more rigorous approach is advisable and that the benefits of improved
validity outweigh the benefits of a consistent methodology between program years.
The changes recommended result in a more granular and holistic approach to assessing program
influence. First, the previous method did not adjust the questions to get meaningful responses by
measure type from the participants. This absence was particularly apparent on large custom projects,
such as Energy FinAnswer. For Wyoming, the savings by measure could be accomplished only for
lighting, and for previous evaluations, no attempt was noted in the reports to attempt to describe net
savings by measure. Also, our methodology did not include any estimation of spillover savings
attributed to the program and only assessed free-ridership. The absence of spillover in our net savings
estimation results in a conservative estimate of program impacts.
Our recommended changes to the free-ridership battery are based on recent research conducted in
Massachusetts on best practices in free-ridership and spillover estimation techniques3. This research is
not only timely, but it has also been rigorously reviewed. The report was created by a team of
experienced evaluators (Tetra Tech, KEMA, and NMR) and reviewed by program staff at eight utilities
operating in Massachusetts including National Grid and NSTA& two of the largest investor-owned
utilities in New England both with long histories of energy efficiency programs. Members of the
PacifiCorp's evaluation team were integral to both the development and implementation of these
methodologies in2007,2009, and again in 2011. Implementing these recommendations provide the
following benefits to the evaluation:
. Targeted questions improve internal validity of free-ridership estimates.
. The methodology creates a calculated estimate of free-ridership savings compared with the
scored estimate previously used.
In addition to estimating program free-ridership, we also recommend that the evaluation quantitatively
assess participant spillover. As programs mature and transform their target market, quantifying
spillover allows for evaluators to recognize the programs' market effectsa. Spillover savings can be
classified into two categories based on measure types: "like" spillover and "unlike" spillover.
o "Like" spillover savings are the energy savings associated with additional high efficiency
equipment installed outside of the program of the same end-use as what that participant
installed through the program. For example, if the participant installed high-efficiency lighting
fixtures as part of the program, "like" spillover would be limited to any additional high
efficiency lighting installed without any assistance from PacifiCorp but influenced by program
activity. This type of spillover is quantifiable using program tracking savings as a proxy.
Historically, spillover results in a small portion of the overall program attribution (in the
Massachusetts studies cited above, it represented 8.8 percent of the overall attribution score).
3 Tetra Tech, KEMA, and NMR. Cross-Cutting C&l Free-Ridership and Spillooer Methodology Study Final Report.
Prepared for the Massachusetts Program Administrators. April 78,2011..
a Saxonis, William P. New York State Department of Public Service. Free-Ridership and Spillover: A Regulatory
Dilemma. IEPEC.2007
Rocky Mountain Power
Exhibit No. 5 Page 984 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Conideniai en* Pioor'eisry
i$nhr f n*rg,v FilAnswer Evaiuaiior Repsrt
Apcendrr B - Nei Savings Methoriciog.v
Page B-?
Nf\\1 $t,qNT
o "Unlike" spillover savings are the savings associated with any other high efficiency equipment
installed outside of the program that are not of the same end-use category as what installed
through the program. Continuing the example above, if the participant installed high efficiency
lighting through the program, the high efficiency HVAC equipment installed outside of the
program would be considered "unlike" spillover as it is not the same end-use.
Spillover savings can come from participants, who are influenced by their program participation to
conduct further energy efficiency improvements, known as "participant" spillover. Spillover questions
can be added to the participant surveys conducted for projects completed at least 6 months prior. Asking
participants who have just completed a project with the program about spillover from that program may
not be productive, since participants are unlikely to have the opportunity to install any spillover
measures.
Spillover savings can also come from non-participants. Non-participants may be influenced by program
advertisements or other program actions (like contractor training, upstream buy-downs, etc.) and make
energy efficienry improvements without assistance from any program. This is known as "non-
participant" spillover. Non-participant spillover can be most easily quantified by interviewing
participating vendors and other supply chain actors. During these interviews, the evaluation team can
assess the amount of measure adoption that occurred outside of the program compared to what
occurred through the program. Again, using program-tracking data as a proxy, we can estimate outside
sales. This estimate of outside sales will capture both "like" and "unlike" spillover savings. We will
remove "like" spillover estimates as reported by participants to avoid double-counting.
Limitations
There are limitations with our proposed changes (these limitations were also present in our previous
methodology). Our participant estimates are still limited to self-reported responses to a hypothetical
situation (i.e., what would have happened absent the program). However, we feel that proper survey
design and fielding protocols can mitigate the problems associated with self-reports,6In additiory
without detailed market level baseline data, the self-report methodology is still the most appropriate and
cost-effective way to estimate program influence at the detail needed to assist in program designT.
Likewise, our experience in Wyoming indicated that it was not fruitful or cost-effective to review project
file text for the purposes of enhancing the self-reported responses.
Figure 1 illustrates the adjustment steps taken when evaluating net savings. In contrast with the gross
savings, which usually can be directly measured with instrumentation, the adjustments made to reach
net savings are measured indirectly. This is important to keep in mind as the farther from the actual
measure we get, the less precise findings can be.
5 Keating, Kenneth M., PhD. Free-Ridership Borscht: Don't Salt the Soup. IEPEC. 2009
6 Megdal, Lori, Megdal & Associates, LLC, Yogesh Patil, Energy & Resource Solutions, Inc., Cherie Gregoire and
Jennifer Meissner, New York State Energy Research and Development Authority, and Kathryn Parlin, West Hill
Energy & Computing, Inc. Feasting at the Ultimate Enhanced Free-Ridership Salad Bar. IEPEC. 200
7 National Action Plan for Energy Efficiency (2007). Model Energy Efficiency Program Impact Evaluation Guide.
Prepared by Diane Munns and ]im Rogers. <www.epa.gov/eeactionplan
Conirdenii€i eaC,sio.arei*ry
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Rocky Mountain Power
Exhibit No.5 Page 985 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page ts-li
,.nN.s\VtrTANT
1. Savings Ac{justmentsE
For illustration purposes, consider a participant in the FinAnswer Express program:
A participant installs a variable frequency drive on a fan motor with the program and
gets an incentive. The program and evaluators can measure the energy consumed by the
new variable frequency drive either directly, depending on configuration, or based on
the hours it is observed to be operating and its features. This consumption is compared
to a baseline estimate of what would have been consumed by a direct drive in the same
case. There is high confidence that the savings are accurate.
Then, the evaluators ask the participant if they would have installed the same variable
frequency drive at the same time without the incentive; the participant can consider
whether the previous drive needed to be replaced at the same time and the relative costs
to decide what might have happened. Then, the evaluators ask the participant if they
installed any other variable frequency drives since participating in the program and
how much the program influenced their choice; the participant can consider the time
frame of installation and determine (probably more easily with this equipment type than
some others) if something similar was installed.
Exploring still further, the evaluators ask the participant if they installed any other
efficient equipment - now the participant has to think about the time frame and relative
efficiencies of any equipment purchased since the program involvement. When asked
how influential the program was on these purchases, the participant is expected to think
through many decisions.
As a thought exercise, we can imagine that gross savings for a program and measure type are estimated
to be 100 k\zVh. Based on participant responses, the free-ridership ratio is estimated tobe20o/o; the sample
was random and drawn to meet 90olo confidence and 10% precision, so the range of this estimate is 18%
ro 22"/". Of all the possible spillover, only "like" spillover can be quantitatively assessed, and it is
estimated to be 10% with the same confidence and precision leading to an estimate of 9"/" to 11%. The
unlike participant spillover questions revealed that participants are more likely to install efficient unlike
Roclry Mountain Power
Exhibit No. 5 Page 986 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Coniceriaj enC Pio.nroisry
iiiinc EnsrS.r FinAnsrver Eteluati0n Rep0it
Apcendix ts - Siet Savings [,telhorii;iagt'
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equipment than like equipment and attribute it to program influence, and market allies confirm that they
are seeing activity outside of the program.
These adjustments result in net savings of 90 k\4/h with a range of 87 kwh to 93 kWh. However, these
numbers cannot capture the other spillover that we can only qualitatively assess. We may say we think
is closer to the higher number because participant and market ally responses reflect additional program
influence, but this is a subjective assessment and may not be appropriate given the need for defensible
savings estimates. In some cases, we may find high free-ridership responses and not identify any
quantifiable "like" spillover even if much unquantifiable spillover can be described. In these cases,
reporting net savings may reflect poorly on the actual program influence.
Though this method provides net savings that are much less precisely estimated than the gross savings,
we feel that given the design of the PacifiCorp programs, it is the most cost-effective and consistent
method to assess program attribution.
Proposed method for measuretnent
This section includes brief recommendations for measuring free-ridership and spillover to get to a net
savings estimate.
Free-ridership
To improve the test of the counterfactual (i.e., what would have the participant done without the
assistance of the program), we recommend more targeted free-ridership questions. As a start, we
recommend refining the initial free-ridership question (Would the participant have installed the
equipment without the program?). This question would be altered to include "at the same time" to
clarify the timing component of the decision. It would also be preceded by a brief description of all the
assistance the customer received as part of their participation in the program (e.9., technical design
assistance, the amount of any monetary incentives, any program-subsidized financing). This description
would be customized by program and by project (as data are available). This description is intended to
remind the participant of all the ways the program may have influenced their decision to move forward
with a specific project.
Then, we recommend asking targeted questions about quantity and efficiency of equipment that would
have been installed (or actions that would have been taken) without the program while referencing what
the participant did with the program.
Including these revisions in the free-ridership battery will allow the evaluation team to use a calculation
approach to estimating the amount of energy savings that may have occurred without the program.
This approach is detailed in Figure 2 below.
Rocky Mountain Power
Exhibit No.5 Page 987 of 1365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
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Based on the participant's responses, the team can estimate the percentage of equipment that would
have been installed at the same time without the program (the quantity score) and the percentage of that
installed equipment that would have been high efficiency equipment (the efficiency score)8. The product
of these two estimates is the initial free-ridership ratio.
Free-Ridership Ratio = Quantity Score x Efficiency Score
For example, a participant that installed four high efficiency HVAC units through the program reports
that, without the program, they would have not installed the same measures at the same time. Following
up, the respondent states they would have installed some equipment and it would have been installed
within 12 months. When probed about the level of efficiency of the equipment that would have been
installed absent the program, the participant reports that they would have installed equipment that was
more efficient than baseline but not as efficient as the program-eligible equipment. Finally, they report
they only would have installed one unit (instead of four). Using the scoring above, this participant's
efficiency score would be set to 0.5 and the quantity score would be set to 0.25. Their initial, unadjusted
free-ridership score is then the producte of these two scores or 0.125. This figure indicates that 12.5
percent of the savings attributed to this project would have occurred absent the program.
8 Question text will be altered for projects where quantity is not applicable. For example, if a project consisted of the
installation of an EMS, the quantity question would be skipped.
e This multiplicative approach is appropriate as the score is the result of a product of the quantity installed and not a
product of probabilities (Keating. Eree-Ridership Borscht: Don't Salt the Soup.IEPEC.2009).
Ro_cky Mountain Power
Exhibit No. 5 Page 988 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Figur* 3. Enhancecl Free-ridership Calculation Appr*ach
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N$V$ilANT
This ratio can then be adjusted by the responses to other questions already referenced in the battery.
These include any reported changes in the timing of projects as a result of the program and the reported
influence of various factors on the decision to install the equipment. These adjustments are not detailed
in this document, as they will be tailored to individual program design. As part of these adjustments, we
recommend that the list of factors be expanded to include "other PacifiCorp program participation."
This addition will allow evaluators to adjust free-ridership based on PacifiCorp's portfolio level outreach
efforts. For example, if a participant received sequential incentives from two different PacifiCorp
programs, his or her participation in the first program may have increased their awareness of the
secondary program. In this situation, their responses to free-ridership questions regarding the secondary
program may present this participant as a free-rider. ln this situation, we can use the responses to the
influence questions to assess if the secondary project was influenced by PacifiCorp actions from another
program. If so, PacifiCorp should receive attribution for those savings and free-ridership would be
adjusted downward.
This methodology requires several adjustments when applied to programs that offer custom incentives
or to programs that utilize unique mechanisms to achieve savings. First, the self-report survey should
include complete and accurate descriptions of what measures were implemented as part of custom
projects. Also, as custom programs often work with participants to implement a variety of end-uses
under the "custom" umbrella, custom projects should be evaluated holistically and not at the end-use
level. Similarly, unique programs may require additional refinements to question wording. For example,
when assessing a recommissioning program, the interview may seek to assess the decision to conduct
the initial project study instead of the decision to implement the energy-saving opportunities identified.
Finally, for complex or large projects, the self-reported estimate can be verified by a review of project
documentation (if available) and follow-up interviews with the contractors associated with the project.
These additional steps can be costly and should only be considered when the savings of the project make
up a significant portion of the program's overall savings or contractor outreach is a significant part of the
program design.
As an example, we provide recommended free-ridership questions for the Energy FinAnswer program
in Figure 3.
Conildenirai anij Plo$rieliln'
idaht fn*6y FinAnswer fivaiuation Repttt
Apceildix B - I'iel Saviirgs Melhodai.:rgv
Rocky Mountain Power
Exhibit No. 5 Page 989 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Fnro Fi-i
N,d\V$TANT
Fieure 3. Free li.id frorn IiinAnswer su n"ev DRAli'I"lrr
...[READ: "With the Energy liinAnsn er program, Fltrilvl receiyeci technical assistance and financia]
incentives. FIRlvl insralled LIST_MEASIIR.ES with the prograrn."
REPEAT FOR EACH MEASI.}RE-TYPE-# I,ISTED UP TO 3.
READ: "iror these next questions, please focus on IUEASURH_:I'YPE..# rrhich includes
tvlEASURE_T'YPE_#_INS'I for vonr project. "l
FRl. \'l'ithout the program, meaning without either the technical assistance or the financial
inceutive, rvould you have stiil installed the exact sanie IvtEASUI{E...T'YPE..# at the sarre time?
ilF 1=YESI => REI']EAT fbr next I,{EASLJRE-TYPE or go on tD spillover
[F 1*N0] => go to 2
F'R3. Withou t the progranl, 'ut ottld },ou have installed anr, $'[EASURE-'I'YPE-# eqlipment?
[F Z=YESI=> go tir 3
IlF Z=Nt]l=> GO BACK T0 l. fkrr next h,IE.ASURE_TYPE (]r go on to spil]over
FR4. Wittrout the prograrn, would yeru have lnstaiied tiris *quipment rvithin 1? uronths of when
ynu did with the prrlgram?
[lF 3=1'ES]=> go t0 4
ilF' 3=NOl=> G0 BACK'f0 1 far next IVIEASURE-TYPE or go on to spillover
l'iF.APPL,ICABl,El FR5. Rel;rtive to the energy etTiciency of MEASI.IRE_TYPE_# installed through
the program, how would you ciraracterize the efficiencv of equipment you lr'ould have installed
rrr'ithout the program?
a. Just as eff1cient as inshlleti with the []r{)Srari
b. Lolrrer than installed through the proglam, l:ut hetter than the standard efficiencv
c. Standard efficiency
IlF APPI,ICABL,E] FR6. Woultl -you harre ir-rstal]ed the same amount of lviEASI.IRE_TYPE_#?a. Yes
b. No => FR(ra
FR6;1. N{ore or less?
Flt6b. liow much more or iess!'
fiO BACK T0 1 fon next I\{EASIJRE*TYPE or gD (}rl to consistencrv rir spilloi,en...
Rocky Mountain Power
Exhibit No. 5 Page 990 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
t0 Variables and notes to the interviewer are in ALL CAPS. The variable MEASURE-TYPE is grouped and worded
by measure types, such as "lighting equipment" or "HVAC equipment" with specific measures installed identified
for the respondent to be sure they understand what is meant.
il+nfrdeniiai siiri I r'0irtei$+,
iiahc [.ner.qy FirAnswer E.",eiuutior Report
A$reniiir * - I'iei Savings L4ethcc.;irgy
Pnge ts-$
Nd\V$ilAN'T
Spilloaer
We recommend asking participants about both "like" and "unlike" spillover with an understanding that
the "like" spillover can by quantitatively assessed and the "unlike" spillover will be characterized
qualitatively (though efforts will be made to use deemed estimates if possible). With "like" spillover, we
can use the gross savings estimates from the program tracking database as a proxy for the "like"
equipment. With no savings data to use as comparison, our ability to confidently assign savings to
reported "unlike" spillover projects is limited by the amount of data participants are able to provide. For
example, if a participant reports that they installed "some high efficiency lighting" but cannot recall how
much or what type, we can only qualitatively report that project as spillover. However, if the participant
is able to provide detailed specifications about the project (e.9., 40 T8s with ballasts), we can then use
deemed savings values as a reference for assigning savings. Savings for measures without deemed
values (e.9., recommissioning prol'ects, industrial process improvements) can only be verified via on-site
and our spillover assessments will be qualitative in nature.
We also recommend asking market allies about program-eligible sales outside of the programs. Market
ally responses and participant "unlike" spillover responses will allow a qualitative discussion about the
estimated magnitude of spillover relative to the "like" spillover that can be quantified. In addition,
interviews with market allies will provide an assessment of spillover across the entire program year. As
we are planning to interview participants quarterly regarding their projects, our estimates of participant-
reported spillover savings will under-represent annual savings as potential spillover projects completed
after that three month period will not be captured. However, market ally interviews will only be
conducted once per evaluation year and cover the entire program year, capturing all spillover projects in
the process. Likewise, the spillover reported by market allies will capture "unlike" spillover savings that
we were only able to qualitatively assess from the participant reports.
Similar to the free-ridership battery, question wording will be adjusted for unique programs (e.g.,
recommissioning) or for custom projects. The like spillover questions will be repeated for the same two
measure types as used for the free-ridership battery, as applicable.
The participant spillover questions recommended as part of the participant surveys and interviews are
listed below for both like an unlike spillover.
LIKE
o Since participating in this program/ have you purchased and installed any additional
Imeasures]?
o \Alhat did you purchase or install? How many did you purchase or install?
e Did you receive assistance from [utility] or another organization?
o On a scale from 1 to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you
"strongly agree" , please rate the following statement: My experience with futilityl's energy
fficiency program influenced my decision to install other high efficiency equipment on rny orr)n.
. VVhy did you not apply for an incentive from [utility] for this equipment?
Conijdeniia anij Fio$risiery
iiahl En*rgy FilAnsrser Evaluaiien Repoit
Aprendir D - l.,iet Savings l,4ethoriti,;g"v
Rocky Mountain Power
Exhibit No. 5 Page 991 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Pege ts-$
NJ\VITANT
UNLIKE
o Since participating in this program/ have you purchased on installed any OTHER energy
efficiency improvements?
o What did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
o How many did you purchase or install?
r Did you receive assistance from [utility] or another organization?
o I'm going to read a statement about the equipment that you purchased on your own. On a scale
from 1 to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you "strongly
agree" , please rate the following statement: My experience with futility)'s energy fficiency program
influenced my decision to install other high fficiency equipmmt on my own.
. Why did you not apply for an incentive from [utility] for this equipment?
The non-participant spillover questions recommended as part of market ally interviews are listed below.
. Approximately what percent of all [measure] sales in [state] last year would you estimate was
from program-eligible equipment?
. Approximately what percent of your [measure] sales in [state] last year was from program-
eligible equipment, that is [description of eligibility requirements]?
o Did you sell more program-eligible equipment last year?
o According to our records, you sold [quantity] [measure] as part of projects that received
program incentives. To the best of your knowledge did you complete any [measure] projects
with [utility] customers that did not receive program incentives? If so, how many?
o Do the [utilitvl Drosram incentives influence vour stockins/sellins of orosram-elieible
[measures]?
o Does the [utility] Pro8ram information influence your stocking/selling of program-eligible
Imeasures]?
Net saaings
Spillover savings can be combined with free-ridership savings to create a comprehensive picture of
program influence. This combination is often referred to as a net-to-gross ratio and is calculated by
adding the spillover ratio to the inverse of the free-ridership ratio or:
Net-to-Gross Ratio = 1-Free-Ridership Ratio) + Spillot:er Ratio
Gross savings are then multiplied by the resulting ratio to find net savings by measure type and
Program.
Rocky Mountain Power
Exhibit No. 5 Page 992 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Cor,.frdenlia *nij Pro$rreiary..
iCahc f n*rgy" FilAnswer Evaiuaticn Repo$
Apoendir B - N*t Savini;s l'4ethoCaiag"v
Page B- i 0
N $V $t.,\ N'T
8.2
To:
From:
Date:
Subject:
Rocky Mountain Power
Exhibit No. 5 Page 993 of 1365
Case No. PAC-E-14-07
Wltness: Kathryn C. Hymas
Net Saoings Scoing - June 78, 2072
Shawn Grant, Esther Giezendanner, PacifiCorp
Kevin Cooney, Matt Haakenstad, Mike Yim, and Jeff Erickson, Naviganf Ellen
Steiner, ]ess Chandler, and ]eremy Kraft, Energy Market Innovations, Inc
June1.8,2012
Net Savings Scoring
This memorandum provides a detailed description of how the evaluation team plans to estimate a net-
to-gross (NTG) ratio for the portfolio of the PacifiCorp energy efficienry programs. An NTG ratio is a
comprehensive picture of program influence and is the ratio of net savings to gross savings and is an
indication of the programs' influence on customers' decision-making regarding energy efficienry at their
facility.
Oaeruiew
Using self-reported responses, the evaluation team's estimation of net savings first attempts to assess the
program's influence on the participants' decision to implement an energy efficiency project and what
would have occurred absent the program's intervention. This estimation includes an examination of the
program's influence on three key characteristics of the project: its timing, its level of efficienry, and its
scope (i.e., the size of the project). This estimate represents the amount of savings attributed to the
program that would have occurred without its intervention and is often referred to as "free-ridership."
The team's measurement of net savings then attempts to estimate program influence on the broader
market as a result of the indirect effects of the program's activities. This estimate, often referred to as
"spillooer," represents the amount of savings that occurred because of the program's intervention and
influence but that is not currently claimed by the program. Spillover savings can be broken into two
categories of savings: "participant" spillover and "non-participant" spillover. Participant spillover
savings occur directly (i.e., program participants install additional energy efficient equipment), while
non-participant spillover savings occur indirectly (i.e., market allies install additional energy efficient
equipment to customers that choose not to participate as a result of the program).
A program's net savings are adjusted by both free-ridership and spillover savings at the measure level
and then extrapolated to the program. The net savings are the program-reported savings minus any free-
ridership savings plus any identified spillover savings, or:
Net Program Saaings: Gross Program Saaings - Free-Ridership Saz:ings + Spillooer Saoings
Oftery this finding is described as a "net-to-gross ratio." This ratio is the net program savings divided by
the gross program savings, or:
Net-to-Gross Ratio = Net Program Saoings / Gross Program Satsings
F ree-ridership C alculation
To determine free-ridership, the interview presents respondents with a series of questions regarding
their decision to install the equipment promoted by the program. The team then scores the responses to
these questions to determine the level of free-ridership. A score of 1.0 indicates the respondent is a
complete free-rider; they would have installed the exact same equipment at the same time and in the
Confideniial enr Pl6priefar!
idahc EIL,r$y FiriF*sr,r,er Hr,alueticn Rept{
Aprendix $ - liet iiavings N4etlixlningy
Sarrs tr-'i 1
ruAxr$tANi r
same quantity without the program's assistance. A score of 0.0 (zero) indicates the respondent is not a
free-rider; that is, without the program they either would not have installed any equipment within 12
months of when they did or they would have installed baseline efficient equipment.
As the first step in scoring, the evaluation team reviews the interview responses to determine if the exact
same project (in terms of scope and efficiency level) would have occurred at the same time without the
program. If so, the respondent is scored as a complete free-rider. If not, the evaluation team reviews the
responses to determine whether the project would have occurred at all within the same 12 month period.
If not, the respondent is scored as a non-free-rider. If the project would have occurred within the same 12
month period but altered in respect to its size or efficiency level, the respondent is scored as a partial
free-rider. To assess the level of partial free-ridership, the evaluation team uses the respondents'
estimates of the percentage of equipment that would have been installed within 12 months without the
program (the quantity score) and the percentage of the installed equipment that would have been high
efficiency equipment (the fficiency score)ll.If the project would have occurred with some changes absent
the program, the product of these two estimates is the initial free-ridership ratio or:
lnitial Free-Ridership Ratio = Quantity Score x Efficiency Score
After scoring the initial free-ridership ratio, a series of consistency check questions is reviewed. These
questions ask about the influence of the program's interventions (e.g. financial incentives, technical
assistance) and address the counter-factual (e.g., what would have happened without the program). For
example, if the respondent states that the financial incentive was extremely important to their decision
(FR1D = 5) but that they would have installed the exact same equipment at the same time without the
program (FR2 = 1), the interviewer asks them to describe in their own words what impact the program
had on their decision (FR7). During the scoring process, these responses are reviewed by analysts to
determine which scenario is correct and are scored accordingly to create an adjusted free-ridership score.
Finally, the free-ridership score is adjusted to account for prior program participation. Given
PacifiCorp's efforts to cross-promote their entire portfolio of energy efficiency programs, a respondent's
prior participation in a PacifiCorp program may have been influential in their decision to participate in
the current program. Ideally, this influence would be attributed to the prior program as spillover savings
since that program was responsible for the influence. However, given the portfolio-level marketing
approach that PacifiCorp implements, respondents are unlikely to be able to identify the prior program
by name. Therefore, the evaluation team will attribute the savings credit to the current program.
To calculate this credit, the team will review the respondents' rating of the influence of the prior
program. If the respondent rates their previous participation as a "4" or "5," lheir adjusted free-ridership
is reduced by either 50 percent or 75 percent respectively.
Figure 4 illustrates the series of questions asked to support this calculation while Table 1 provides
detailed scoring and descriptions of each question.
11 Question text will be altered for projects where quantity is not applicable. For example, if a project consisted of the
installation of an EMS, the quantity question would be skipped.
CclfiCeniral and Py6preis$
ii$!10 Ensr$y FinAnswsr [r,aiuation Rep:od
Aprcndix $ - I'iet Savings [..lethociciogy
Rocky Mountain Power
Exhibit No. 5 Page 994 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Paq* B-i ?
.t\i ,g\V\TAN.T
Rocky Mountain Power
Exhibit No. 5 Page 995 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
tr'able 1. Irree-ridership Calculation Approach
FRlB On a scale from 1 to 5, with 1 being not important at all
and 5 being extremely important, how important were
the following factors in deciding which equipment to
install: information provided by PacifiCorp on energy
incentive and technical assistance, would you have still
Would you have installed this equipment within 12
IMEASUREI?
Consistency Check
l:::tU:t:!::i:i!:!l!:!;i::itr|:t:t:::!i:
lii$,l,fH+
FR2
:l:a:*:
l1::1,:1.,i
;; i:; :::::::::::::.f:I{6Si.:::::
':iii:iiiiiiiiii$
FR7
illi::li:::lli::i:iiixi
i,i1.:::1:::;:::::1:1:;:;!;:ii!::i
FR4
Cc,*iici+riiai aii d Frr:1:t'i'etaq,
ittail+ [nergy Firir\nsiver Hvailration P.e;:iiri
Ap$t:ndix S - l.iet Savilgs l\'!eihod+ir":gv
ilrr:s S^ 1 i
N$\d$TANT
\. .'
iyes
t
,..ill'it,:,:iit:i::i:iFR4 tl:::,i
.,li,,,,,,,,,,,,,,,,,,1ttttthir f; l:::'\:;::::;;:ttlc0ltlh$?:t!:
\:i::::::i::,i:iii:, :.:::t;l
yes
Fi gure il. Fre*rid ership Calcul a ti on Approa ch
Rocky Mountain Power
Exhibit No. 5 Page 996 of l365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
,Fr,ee.{ideIs,r!F
ii:)----No. DK --------.--.-----------:
Ii::: _ _-"--_ """'i FR7 Consistedcv i}r: chsil i- --'---+
..i,iiri::i'r'\ ..
----$^1 EhlEl,tlB > 1!!.:.---No--
\il!::::::::::i:i:rlr
,,,,,,,,,,,,,,,,,,,$,,,,,,-,,,,t,,,I 'I]mi;;ssiii:=,1 i
yes
i::::8tr!4ry!py::,8!QiC::=::O:::::i ir,:SffiSpnn*,:,Eqe::=:ri5:ir:ii...rdri*.rrJ;.**..*.r.*Gl l.:.:r-.-***-......-.*...*-*l$+Standard
i
,,J'\ i
l/\:
)'
l
No, DK
' *l Ouantrty.:'Score '=::Fft60 i-
i
Yesx
$
r;:r:tn!tBmiffi,,,ii
\:, :,::r,E{fdiEintir?,'
,, !. Fn5 '.
)'..," o
tiiro"r *,i leyer ot- :;)--tn Beween, Dx-.' \emqency-/,'
No
(e.9., RCx Study)
For example, a participant that installed four high efficiency HVAC units through the program reports
that, without the program, they would have not installed the same measures at the same time. Following
up, the respondent states they would have installed some equipment and it would have been installed
within 12 months. When probed about the level of efficiency of the equipment that would have been
installed absent the program, the participant reports that they would have installed equipment that was
more efficient than baseline but not as efficient as the program-eligible equipment. Finally, they report
they only would have installed one unit (instead of four). Using the scoring above, this participant's
efficiency score would be set to 0.5 and the quantity score would be set to 0.25. Their initial, unadjusted
free-ridership score is then the productlz of these two scores or 0.125. Likewise, they state that the
incentive was important and that previous participation was not important. These responses indicate a
consistent installation scenario and no further adjustment is necessary.
r2 This multiplicative approach is appropriate as the score is the result of a product of the quantity installed and not
a product of probabilities (Keating. Free-Ridership Borscht: Don't Salt the Soup.IEPEC. 2009).
llorirC+ri,ei ari Frrrlrr's f a+,
iCa[+ Urisi$y FiiiAnsiver fivaliiirtiori Iispoii
Apnsndix Ll - li*t linvin$s N,hlhocinic,qy
Fagsr S-14
rus\xs$tANT
Spillooer Calculation
P arti cip ant-rep o rt e d Sp ill o a er
Similar to free-ridership, to determine spillover, the interviewer presents respondents with a series of
questions regarding their decision to implement projects outside of the program (i.e., projects that did
not receive any assistance from the program). These responses are then scored to determine the level of
spillover. The evaluation team will ask participants about both "like" and "unlike" spillover projects.
"Like" spillover is associated with equipment that is similar to the equipment incented by the program.
In comparison, "unlike" spillover is associated with equipment that is not similar to the equipment that
was incented by the program. Using the program-reported per-unit savings as a proxy, "like" spillover
savings can by quantitatively assessed. However, as it has no comparative program savings data,
"unlike" spillover can only be characterized qualitatively (though efforts will be made to use deemed
estimates if possible).
To assess "like" spillover, the evaluation team first reviews interview responses and determines whether
the respondent installed any additional equipment similar to what was incented through the program. If
additional equipment was installed, the team determines whether it was rebated through a PacifiCorp
program. If not, the team then estimates the amount of potential spilloaer saoings associated with the
project. This estimation is created by using the program-tracking savings as a proxy for per-unit savings
and adjusting for the amount of equipment installed. The team will also adjust for equipment similar to
that installed through the program but of a lower efficiency. If the respondent states that efficiency level
is lower than what was installed through the program but better than standard efficiency, the potential
spillover savings are reduced by half. Since the energy savings associated with the reduced efficiency
project will be less than the project incented by the program/ this adjustment credits the program with
some, but not all, of the savings.
In order to account for the program's influence on the spillover savings, the team then adjusts the
quantified spillover savings by the free-ridership rate identified earlier or:
Spilloaer Saoings = Potential Spillooer Saoings X Free-ridership Factor
As a consistency check, the team uses an additional question to check the evaluated free-ridership rate.
Respondents are asked to rate the level of influence from the program on their decision to purchase the
additional equipment. The team compares these responses to the identified free-ridership rate to identify
any contradictory responses (i.e., free-ridership factor of 1.0 but spillover influence is high or free-
ridership factor of zero but spillover influence is low). If the responses are contradictory, the potential
spillover savings are reduced by 50 percent. Without further evidence, the team cannot objectively
determine which statement of influence is correct. Adjusting the potential spillover savings by 50 percent
acknowledges this uncertainty without overly penalizing or rewarding the program.
Figure 5 illustrates the series of questions asked to support this calculation while Table 2 provides
detailed scoring and descriptions of each question.
Ccriicieni, a aird Fri.rptielary
idahc Inergy FiiiAnswer fivaluation Reporl
Apnendix $ * lict Savings Method"ri*gy
Rocky Mountain Power
Exhibit No. 5 Page 997 of 1 365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
$ar,s F- i i.sYv-.!'
N..-\V$ilANT
Rocky Mountain Power
Exhibit No. 5 Page 998 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
tr'able 2.IIover Calcutration
SP1
iii-*
SPlc
Since participating in this program, have you purchased If no, potential spillover savings
Relative to the energy efficiency of [MEASURE] installed If lower than program but
$P#H
SPlf
through the program, how would you characterize the
efficiency of this equipment?
higher than standard, reduce
potential spillover savings by
half.
If standard efficiency, potential
Consistencv CheckJ
"strongly disagree" and 5 indicating that you "strongly
agree" , please rate the following statement: My experience
with the PacifiCorp program influenced my decision to install
th' oaairl-g--r.gl*tig-t*9.ff.*,g.r.gy*g,r:prye4:ruvqrc - -
-**.--,,-
*.-.* *-.,,-..-.,.---
ilc*f,,rr*riirei eriii Fri:pdeiary
i$airc [irsrgy i:iriAnswer f vilii.ri:iiori R*g:oi't
Apren*ix ll - list liavings l\,leiilocicirgy
S,rr,s F.- ! ii
N'$V$ilANT
' $PItPvdiSavin{F = PoEltid ', j
Roclry Mountain Power
Exhibit No. 5 Page 999 of l365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
l'igure 5. Spilkrver Calculatian Approach
;''n, \ *
,..2r,,,,,,,,$Pt ll::r\.r
i',,,,{ny,addithnal .)--.---.--.--.--No, DK......-...\ {}gqlpmenri ..r
\ .,.\r'j
yes
iri.,/,,\ |
---'":r".tt. icorx \'io*ntil inlt"rnat.l .
./i
ril:::::ii
A similar process is used for "unlike" spillover. However, since the measure is not the same as the in-
program measure, the team has less information from which to calculate the measure's savings. Thus the
team's ability to confidently assign savings to reported "unlike" spillover projects is limited by the
amount of data participants are able to provide about the measure and its use. For example, if a
participant reports that they installed "some high efficiency lighting" but cannot recall how much or
what type, we cannot reliable assign any spillover savings to that project. However, if the participant is
able to provide detailed specifications about the project (e.g., 40 TSs with ballasts), we can then use
values based on savings from similar measures in the program-tracking database as a reference for
assigning potential spillover savings. Savings for measures without deemed values (e.9.,
recommissioning projects, industrial process improvements) can only be verified via on-site and our
spillover assessments will be qualitative in nature. If "unlike" spillover projects of significant magnitude
are identified, on-site visits may be cost-effective. In this situation, the team will discuss conducting
visits in order to quantify the savings.
Colilisre,riei +l $ Proprri6iary
iiieho i:r:sig.v Firi.A.n$wsi fviliLr$tion ileg:i:i'i
Apuenrlix li - liet iiaviirgs [,letiioci+ir:gv
rx-'S\V${:ANT
N onp arti cip ant S p ill oa er
To capture a comprehensive picture of spillover, the team also asks market allies about program-eligible
sales outside of the programs as part of our in-depth interviews with this group. By examining the
amount of program-eligible sales occurring outside of the program, the team can create high-level
estimates of nonparticipant spillover that can be added to the participant-reported spillover savings.
First, the team determines whether the market ally installed any program-eligible equipment that did
not receive incentives from the program. If so, the team compares the quantity of equipment installed
outside of the program to the quantity tracked through the program-tracking database. Using the
savings associated with that market ally in the program-tracking database, the team can then estimate
the amount of savings installed outside of the program. Note that market allies may have difficultly
reporting the amount of equipment that did not receive program assistance. As these "don't know"
response will not be used in analysis, our estimate will likely be conservative.
Finally, the team determines the influence of the program on these sales in order to attribute the
nonparticipant spillover savings to the program. The team examines responses to three questions
regarding the influence of the program incentive and information on the stocking and selling of
program-eligible equipment. Respondents are asked to rate the influence of the program on a scale of 1
to 5 where 1 is "no influence" and 5 is "a great deal of influence." If the average response is greater than
4, 100 percent of the savings installed outside of the program are attributed to the program. If the
average response is greater than 3 but less than or equal to 4,75percent of the savings are attributed to
the program. If the score is greater than 2 but less than or equal to 3, 50 percent of the savings are
attributed to the program. None of the savings associated with market allies with average influence
scores lower than 2 are attributed to the program.
Table 3 describes in detail the questions asked and their associated scoring.
Tahle 3. Non pant $pillover Catreulation roach
Rocky Mountain Power
Exhibit No. 5 Page 1 000 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
21,
!til
According to our records, you sold [NUMBER OF
PROIECTSI of [TYPE] as part of projects that received
program incentives. To the best of your knowledge did
you complete any [TYPE] projects [IF LIGHTING OR
HVAC: that would have been eligible for the programl
that did not receive program incentives? If so, how
.,,....m...t*UU og1iffi.i. elsiiiiiffitunnce.i.ffCI$r.$ffiing.,bf
.
:iiiii#ffigtri{ffiElt8tb,&:iffi1*i$tnffiiiif$riiifEY&"8:}?,::::::::: ,,,:,,;,;,:i,,: . :
,,
Do the program incentives influence your stocking of
:poqs tht:Br,o$f ,informaHon,influente,,,y;CIur,,.,rc1trin9,,$i
' . " -. .-. i +.:Jl:!::i:::::l::::::1.:." ":. .
(Projects outside of
program/Projects through
program) X program savings
associated with market ally:
potential nonparticipant
spillover
Avera ge,,prograr-n,,,,inf ltrerece,
scuf.g:::ii:i:i:i:i:i:::,::,i:i' .::::::::::::'::::::::i:::::i:i:::::i:::.:i::.:::::.':::i:i.:.:::i:i:i:::::i:::i:i:::::i:i:
23
i:.iiig4
Net-to-Gross Ratio
The evaluation team will determine measure-specific free-ridership and spillover rates. To determine
program-level rates, the team will weigh the rates by savings and for any disproportionate sampling.
C+itfi$+riiiai erio P1r;rpseiaty
iiluht Inrrg.y" F ri'iAnslvrir Hr,air.i:ltiori Rri:r{
Aplsndix il - liet iiavings \.,let$oci*i+gv
Nd\\I$TANT
This weighting ensures that the analysis is representative of the overall program both in terms of its
distribution of savings and its mix of measures. For example, projects that account for a larger
proportion of the program's overall savings will have more influence on the final programJevel rate. In
additiory if projects that are part of certain sub-groups within a program are intentionally selected more
frequently (i.e., over-sampled) as part of the sample design, those projects will have less influence on the
program-level rate.
Likewise, the team will apply similar weights to the market-ally reported nonparticipant spillover
savings to determine measure-level estimates. To avoid double-counting, participant-reported spillover
estimates will be subtracted from the market ally-reported estimates. If, at the measure level, the
participant-reported spillover estimate is less than the estimate reported by market allies, the team will
add the difference to the spillover rate. If the participant-reported estimate is greater than the estimate
identified by market allies, the team will not add any nonparticipant spillover savings to the overall
estimate.
The team will then create the final net-to-gross ratio. This ratio is the net program savings divided by the
gross program savings or:
Net-to-Gross Ratio = Net Program Satsings I Gross Program Saaings
The net program savings are the program-reported savings minus any free-ridership savings plus any
identified participant and nonparticipant spillover savings or:
Net Program Saoings = Gross Program Satsings - Free-Ridership Saaings + Participant Spilloaer Saoings +
N onp articip ant Spillooer Saoin gs
Note that as the nonparticipant spillover ratio is created for each market ally and not each participant
the final ratio is adjusted at an aggregated level.
Conf Cenirai a$i Fio;:rieta,-^,.
idsho fnsrsy FiriAnsrver Er,aiuatlon Report
Aprendix $ - \'et Savings lvletilmci*gy
Roclry Mountain Power
Exhibit No. 5 Page 1001 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Srng tr^ ! Q
Nd\V$SANT
C.7 Participant Suntey Instrument
Note: Energy FinAnswer Participants are those custorners who completed a project through the Energy
FinAnswer program during 2009-2011. Participants are questioned about up to two rrcasure subtypes
based on the largest kWr savings. Measure subtypes will be determined during sampling and will likely
be grouped by end-use (e.g., lighting equipnrent, HVAC equipnent).
Objectioes
These surveys are designed to meet the following list of objectives.o To describe how customers come to participate in the program
o To understand overall customer satisfaction with the program, including: incentive agreement,
report, inspections, customer service, and the incentive
To understand program influence on customer actions, including free-ridership and spillover
To understand barriers customers are facing that prevent increasing energy efficiency
To characterize participating firms
Vaiables
Confrdenlra efi s Prapr-teiery
itiahc fnergy FirAnswer Evaluation Repoit
Apcendir C - Prosbss Evaiuation Sirrvsy ln$irumsrits
Rocky Mountain Power
Exhibit No.5 Page 1002 of 1365
Case No. PAC-E-I4-07
Vwness: lcthryn C. Hymas
o
a
a
Variable Name Description Type
&CONTACT Respondent name Text
&FIRM Comoanv name Text
&PROGRAM Enersv FinAnswer Text
&SITE Address Text
&YEAR Year of oroiect comoletion YYYY
&PACIFICORP Rockv Mountain Power. Pacific Power Text
&PREINSPECTDATE Date of first inspection Date MMYYYY
&POSTINSPECTDATE Date of oost insoection Date MMYYYY
&INSTALLED MEASURES List of installed measures Text
&MEASURE-TYPE-1 Name of Measure I Text
&MEASURE TYPE 2 Name of Measure 2 Text
&INCENTIVE Value of incentive paid to particiDant Numeric
&NC Flas for New Construction oroiect BINARY
&EAFIRM Eneineerins Firm Text
Frage $- l
NS\V$fi,qNi T
Suroey lnstrument
Introduction and Screen
INTROI. Hello, this is INTERVIEWER, calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficiency programs. This is not a sales call. May I
please speak with &CONTACT?
1. YES, THAT IS ME ) SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU
3. NOT NOW
'
SCHEDULE APPT AND CALL BACK
4. NO/REFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficiency programs. This is not a sales call.
&PACIFICORP is evaluating its &PROGRAM program and would appreciate your input."
I'd like to let you know that this call may be monitored or recorded for quality assurance purposes. Also,
all of your responses will be kept confidential and will not be revealed to anyone outside of the research
team. Do you have a few minutes to answer questions about your experience with the program? [IF
I\-EEDED, READ: "This survey is for research purposes only and will take about 15 minutes."]
1. YES ) SKIP TO IS2
2, NOT NOW ) MAKE APPT. TO CALL BACK
3. NO/REFUSED ) TERMINATE
INTRO3. &PACIFICORP is evaluating its &PROGRAM program and would appreciate your input.I'd
like to let you know that this call may be monitored or recorded for quality insurance purposes. Also, all
of your responses will be kept confidential and will not be revealed to anyone outside of the research
team. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research purposes only and will take about 15 minutes."]4. YES
5. NOT NOW ) MAKE APPT. TO CALL BACK6. NO/REFUSED ) TERMINATE
[IF VERIFICATION IS NEEDED, TELL TIIEM TIIEY CAN CALL SHAWN GRANT AT 801-
220-41961.
IS2a. &PACIFICORP records indicate that your firm received an incentive from the &PROGRAM
program in &YEAR after installing &INSTALLED_MEASLIRES at &SITE, is this correct?1. YES ) SKIP TO APl2. NO, DID NOT PARTICIPATE
3. NO, ONE OR MORE MEASURES ARE INCORRECT ) SKIP TO IS2d4. NO, ADDRESS IS INCORRECT ) SKIP TO IS2C
88. DON'T KNOWNOT SURE
99. REFUSED
IS2b. Is there someone else that might be familiar with this project?
1. Yes2. No ) TERMINATE
88. Don't know ) TERMINATE
IS2c. May I speak with that person?
iloniideniral snt,si"oj:neiilq.,
ida!:c fn*6y FilAnsrv*i Ev*iurtion Report
Appendir C - Process Evaiuatir:n S*ivev lnstruments
Rocky Mountain Power
Exhibit No. 5 Page 1 003 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page C-i
N&V $T,& N T
1. Yes ) RETURN TO INTRO2
2. Not now) SCIIDULE CALLBACK3. No ) TERMINATE
IS2d. What measures were installed?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IS2e. What is the correct address?
1. [RECORD RESPONSE]
88. DON'T KNOWATOT SURE
99. REFUSED
IS3. Are you the person most familiar with &FIRM's decision to implement this project?
1. YES2. NO ) SKIP to IS2b
88. DON'T KNOWNOT SURE ) SKIP to IS2b
99. REFUSED ) SKIP to IS2b
Awareness & Participation
APl. How did you first become aware of &PROGRAM? [DO NOT READ RESPONSES; ALLOW
MULTIPLE RESPONSES]
1. ACCOUNT REPRESENTATTVE OR OTHER &PACIFICORP STAFF2, &PACIFICORP RADIO ADVERTISEMENT3. &PACIFICORP PRINT ADVERTISEMENT4. &PACIFICORP PRINTED MATERIALS/BROCHURE5. &PACIFICORP ONLINE ADVERTISEMENT
6. &PACIFICORP TV ADVERTISEMENT7, &PACIFICORP NEWSLETTER8. &PACIFICORP WEBSITE
9, PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
10. CONFERENCE, WORKSHOP, OR EVENT [SpECIFy: I
11. &PACIFICORP SPONSORED ENERGY AUDIT OR TECHNICAL ASSESSMENT
12. FROM TRADEALLY, VENDOR OR CONTRACTOR
13. ANOTHER BUSINESS COLLEAGIJE
14. FAMILY, FRIEND, OR NEIGHBOR
15. OTHER [SPECTFY]:
88. DON'T KNOWNOT SURE
99. REFUSE
AP2. Why did your firm decide to participate in the program? [DO NOT READ RESPONSES;
ALLOW MULTTPLE RESPONSESI
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
Con|.rsentla/ en ii Pioprr eiilq,'
!iian+ En*r.qy FinAnswer Evaiuati.:n Repoii
Apcendrr C - Process Evaiuatrori Si;i'.e1r Insy5xisrL
Rocky Mountrain Power
Exhibit No. 5 Page 1004 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page i:-3
ru..Arr$ileNT
10. To save energy
I 1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, production, or quality
15. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSE
[IF more than one response to LP2)
LP2a.
Of those reasons, which one was most inlluential in the decision to participate in the program?
[ALLOW ONLY ONE RESPONSE]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
1 I . Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, production, or quality
15. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
Pre-Installation
UF &PREINSPECTDATE>0] EEl. When you frst became involved with the &PACIFICORP
program, an energy engineer "Uf (IS NOT NULL(&EAFIRM)) "with &EAFIRM"I came out to your
facility to identifu potential savings opportunities. Using a scale of 1 to 5 where 1 indicates 'very
dissatisfied' and 5 indicates 'very satisfied', how satisfied were you with the energy engineer who came
out to your facility?
I. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITMR SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO BE3
5. VERY SATISFIED ) SKIP TO BE3
88. DON'T KNOWAIOT SURE ) SKIP TO EE3
99. REFUSED '
SKIP TO EE3
EE2. Why were you less than satisfied with the energy engineer?
1. TRECORD RESPONSE]
fjoni deniraj enrj ilro$nsisq.,
iiaitr [nsrgy FinAnsrrer Evaiuaticn Reporl
Aprendir C - Prr:sess Evaiuaiioii Sutr,ey lnsitunielts
Rocky Mountain Power
Exhibit No. 5 Page 1005 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Flagc C-4
ruAvr tA NT
88. DON'T KNOWNOT SURE
99. REFUSED
EE3. As part of the program, you received a report documenting the findings from the energy analysis
that included recommended equipment and changes. Did you find this report valuable? [NOTE: May
have received more than one version of the report; interested in the final version.]
1. YES
2. NO
3. DON'T RECALL RECETVTNG A REPORT ) SKIP TO IMl
88. DON'T KNOWA.IOT SURE
99. REFUSED
EE4. Were there recommendations in the report that you decided not to install?I. YES
2. NO ) SKIP TO IMl
88. DON'T KNOWNOT SURE ) SKIP TO IMl
99. REFUSED ) SKIP TO IMl
EE5a. What were they?
1. [RECORD RBSPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EEsb. Why did you decide against the recommendation(s)?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Installed Measures
READ: I'm going to ask a few questions about the equipment that you installed.
IREPEAT FOR EACH &MEASIIRE_TYPE UP TO TWO MEASURESI
[IF &NC=l, SKIP to IM3]IMl. Did the &MEASURE_TYPE# installed through the program replace
existing equipment or was it a new installation?
1. REPLACED EXISTING EQUIPMENT ) SKIP TO IM2
2. TOTALLY NEW INSTALLATION ) SKIP TO IM3
88. DON'T KNOWA{OT SI.IRE ) SKIP TO IM1A
99. REFUSED ) SKIP TO IM1A
IMIA. Could you please provide contact information for the person who would know about the
equipment that was installed with this project, and we can ask them specifically about equipment?
1. [COLLECT: IM_CONTACT_NAME, IM_CONTACT_PHONE, and
IM_CONTACT_EMAILI ) SKIP TO PIl
IM2. What was the operating condition of the equipment that the &MEASLIRE_TYPE# replaced?
1. EXISTING EQUIPMENT HAD FAILED
2. EXISTING EQUIPMENT WORKING BUT WITH PROBLEMS
3. EXISTING EQUIPMENT WORKING WITH NO PROBLEMS
4. OTHER [SPECMY]:
88. DON'T KNOWA{OT SURE
99. REFUSED
Confraeniiai an *,crolrief *ry*
i,Jaitl fnsrgy FilrAnsrver Evaluation Reprrl
Apiendix C - Process Evaiuaiion Survey lns$umei'ris
Rocky Mountain Power
Exhibit No. 5 Page 1 006 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fagc C*li
ru,s\vr $t,q N T
IM3. Have the energy savings related to this equipment met your expectations?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
IM4. What other benefits, if any, do you anticipate from the &MEASURE_TYPE#?
1. NONE
2. YES [RECORD RESPONSE]:
88. DON'T KNOWA{OT SURE
99. REFUSED
IM5. Using a scale of I to 5 where 1 indicates 'very dissatisfied' and 5 indicates 'very satisfied', overall,
how satisfied were you with the performance of the &MEASURE_TYPE#?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO PIl
5. VERY SATISFIED ) SKIP TO PIl
88. DON'T KNOWA{OT SURE ) SKIP TO PIl
99. REFUSED ) SKIP TO PIl
IM6. Why were you less than satisfied with the performance of the &MEASURE_TYPE#?
1. [RECORD RESPONSE]
88. DON'T KNOWA{OT SURE
99. REFUSED
Post-Installation
PI1. After you finished the installation, did you complete or contract to complete commissioning on your
new equipment per the guidance in the energy analysis?
1. YES ) SKIP TO PI3
2. NO, Opted out of commissioning
3. NO, Commissioning not recommended ) SKIP TO PI3
88. DON'T KNOWA{OT SURE ) SKIP TO PI3
99. REFUSED ) SKIP TO PI3
PI2. Why did you opt out of commissioning the equipment?
1. Too costly2. Don't have the expertise
3. Not cost-effective4. OTHER [SPECIFY:]
88. DON'T KNOWAIOT SURE
99. REFUSED
PI3. After you notified &PACIFICORP of your project completion, around &POSTINSPECTDATE, an
engineer came out to your facility to measure and verify savings from your installation. Using a scale of
I to 5 where I indicates 'very dissatisfied' and 5 indicates 'very satisfied', how satisfied were you with
the engineer's inspection?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
Conlideltiai enC,sropr,eio,y
illnh* [ne rgy FinAnsrver Evaiuation ReSori
Aprendix C - Pror*ss Evaiuaiicn Sui'vey lnstrunrents
Roclry Mountain Power
Exhibit No. 5 Page 1 007 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Fage $-$
ru&vI ilA NT
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO FRl
5. VERY SATISFIED ) SKIP TO FRl
88. DON'T KNOWNOT SURE ) SKIP TO FRl
99. REFUSED ) SKIP TO FRl
PI4. Why were you less than satisfied with the engineer's visit?
1. [RECORD RESPONSE]
88. DON'T KNOWA{OT SURE
99. REFUSED
Free Ridership
FRl. With the &PROGRAM program, &FIRM received technical assistance and financial incentives of
&INCENTIVE. &FIRM installed &INSTALLED_MEASURES with the program.
On a scale from 1 to 5, with 1 being not important at all and 5 being extremely important, how important
were the following factors in deciding which equipment to install.
A. RECOMMENDATION FROM CONTRACTOR OR VENDOR
B. INFORMATION PROVIDED BY THE &PACFICORP ENERGY ANALYSIS ON ENERGY
C.
D.
E.
F.
G.
SAVING OPPORTTINITIES
INFORMATION ON PAYBACK
THE &PACFICORP INCENTTVE
FAMILIARITY WITH THIS EQUIPMENT
PREVIOUS PARTICIPATION WITH A &PACIFICORP PROGRAM
CORPORATE POLICY REGARDING ENERGY REDUCTION
IREPEAT FR2-FR7 FOR EACH &MEASURE_TYPE# UP TO TWO_MEASURESI
[READ: "When answering these next questions, think specifically about &MEASURE-TYPE_#
installed through the program."l
FR2. Without the program, meaning without either the technical assistance or the financial incentive,
would you have still installed the exact same &MEASURE_TYPE_# at the same time?
1. YES ) SKIP TO FRTa
2. NO
88. DON'T KNOWA{OT SURE
99. REFUSED
FR3. Without the program, would you have installed any &MEASURE_TYPE_# equipment?
1, YES
2. NO ) SKIP TO FRTa
88. DON'T KNOWAJOT SURE
99. REFUSED
FR4. Without the program, would you have installed this equipment within 12 months of when you did
as part of the program?
1. YES
2. NO ) SKIP TO FRTa
88. DON'T KNOWATOT SURE
99. REFUSED
Coniiderirai en$ Proprisisiy
i$ant fnsrgy FirAnsrvei Eveiuation Repc{
Apien.Jir C - Frocess El'eiuation Suivel, l1si111p6i*r'1*
Roclry Mountain Power
Exhibit No. 5 Page 1008 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
irage C-7
N'f\\'$ilANT
FRS. Relative to the energy efficiency of &MEASURE_TYPE_# installed through the program, how
would you characteize the efficiency of equipment you would have installed without the program?
1. Just as efficient as installed with the program
2. Lower than installed through the program, but better than the standard efficiency
3. Standard efficiency
FR6a. Would you have installed the same amount of &MEASURE-TYPE-#?
1. YES ) START NEXT MEASURE
2. NO
88. DON'T KNOWNOT SURE ) START NEXT MBASURE
99. REFUSED ) START NEXT MEASURE
FR6b. Would you have installed more or less equipment?
1. MORE) How much more?
2. LESS) How much less?
88. DON'T KNOWAIOT SURE
99. REFUSED
IIFFR1D<3ANDFR3=21
FR7a. Previously, you said that the incentive was not important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would not have installed
any equipment. ln your own words, can you please describe what impact the program had on your
decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
UFFR1D<3ANDFR4=21
FR7b. Previously, you said that the incentive was not important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would not have installed
any eQuipment with 12 months of when you did. ln your own words, can you please describe what
impact the program had on your decision to install the equipment?
1. IRBCORD RESPONSE]
88. DON'T KNOWATOT SURE
99. REFUSED
IIFFR1D>3ANDFR2=11
FR7c. Previously, you said that the incentive was important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would have installed the
exact same equipment at the same time. In your own words, can you please describe what impact the
program had on your decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF FR1B < 3 AND FR3 = 2l
FR7d. Previously, you said that the technical assistance was not important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would not have installed
any equipment. ln your own words, can you please describe what impact the program had on your
decision to install the equipment?
1. [RE,CORD RESPONSE]
88. DON'T KNOWNOT SURE
Coniideni,'a en{r Fiopi:eis1,'
iiai:r Sn*6y FinAnswer Evaiuatior Repsit
Aprendir C - Frocess EvciLraiion Si.ii'vsy lnstrunterits
Roclry Mountain Power
Exhibit No. 5 Page 1009 of '1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pags C-8
ru &v$ ilA NT
99. REFUSED
UF FR1B < 3 AND FR4 = 2l
FR7e. Previously, you said that technical assistance was not important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would not have installed
any equipment with 12 months of when you did. In your own words, can you please describe what
impact the program had on your decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWATOT SURE
99. REFUSED
IIF FR1B > 3 AND FR2 = 1l
FR7f. Previously, you said that the technical assistance was important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would have installed the
exact same equipment at the same time. In your own words, can you please describe what impact the
program had on your decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWAIOT SURE
99. REFUSED
Spillover
REPEAT SPl for each &MEASURE_TYPE#
SP1. Since participating in this program, have you purchased on installed any additional
&MEASURE TYPE#?
Rocky Mountain Power
Exhibit No. 5 Page 1010 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
how
1. YES
2. NO ) START next measure or SKIP TO SP2
88. DON'T KNOWA{OT SURE ) START next measure or SKIP TO SP2
99. REFUSED ) START next measure or SKIP TO SP2
SPLa. What did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1. [RECORD RESPONSE]
88. DON'T KNOWAJOT SURE
99. REFUSED
SPlb. How many did you purchase or install?
1. [RECORD RESPONSE]
88, DON'T KNOWA{OT SURE
99. REFUSED
SPlc. Relative to the energy efficiency of &MEASURE_TYPE_# installed through the program,
would you characterize the efficiency of this equipment?
1. Just as efficient as installed with the program2. Lower than installed through the program, but better than the standard efficiency
3. Standard efficiency
SP1d. Did you receive an incentive from &PACIFICORP or another organization?
1. YES
Conf deniiai anC Pi'oprieiery
!$unc En*tg.u' FinAnswer Evaluation Repul
Apcentiir C - Frocess Evaiuation Suivey l151ss6i3*1*
Page C-$
ru&v $t.q N T
2. NO ) SKIP TO SPlf
88. DON'T KNOWNOT SURE ) SKIP TO SPlf
99. REFUSED ) SKIP TO SPlf
SPLe. What program or sponsor provided an incentive?
1. &PACtr'ICORP2. IRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SPLf. I'm going to read a statement about the additional &MEASURE_TYPE# that you purchased on
your own. On a scale from I to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you
"strongly agree", please rate the following statement:
My experience with &PACIFICORP's &PROGMM program influenced my decision to install
additional high efficiency equipment on my own.
Would you say you... [READ 1-5]
1. STRONGLY DISAGREE
2. SOMEWHAT DISAGREE
3. NEMHER AGREE OR DISAGREE
4. SOMEWHAT AGREE
5. STRONGLY AGREE
88. DON'T KNOWNOT SURE
99. REFUSED
[IF SPle not L] SPlg. Why did you not apply for an incentive from &PACIFICORP for this equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SP2. Since participating in this program, have you purchased on installed any OTHER energy
effi ciency improvements?
1. YES
2. NO ) SKIP TO 81
88. DON'T KNOWAiOT SURE ) SKIP TO 81
99. REFUSED ) SKIP TO 81
SP2a. What did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SP2b. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWAIOT SURE
99. REFUSED
SP2c. How would you characterize the efficiency of this equipment?
1. The most efficient or ENERGY STAR certified
iloniidentiai en*' P-l'o j)fi sia,y
i$anc fn*rgy FinAnswer Evaiuation Repo{
Apnendir C - Frocess [valuatiorr Suiley lnstrunter*s
Roclry Mountain Power
Exhibit No. 5 Page 10'1 1 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
Fagc C-10
N&V$ SANT
2. Lower than the most efficient, but better than the standard efficiency3. Standard efficiency
SP2d. Did you receive an incentive from &PACIFICORP or another organization?
1. YES
2, NO , SKIP TO SP2f
88. DON'T KNOWNOT SURE ) SKIP TO SP2f
99. REFUSED ) SKIP TO SP2f
SP2e. What program or sponsor provided an incentive?
1. &PACIFICORP2. [RECORD RESPONSE]
88. DON'T KNOWA{OT SURE
99. REFUSED
SP2f. I'm going to read a statement about the other equipment that you purchased on your own. On a
scale from I to 5, with I indicating that you "strongly disagree" and 5 indicating that you "strongly
agree", please rate the following statement:
My experience with &PACIFICOW's &PROGMM program influenced my decision to install other
high efficiency equipment on my own.
Would you say you...[READ 1-5]
1. STRONGLY DISAGREE
2. SOMEWHAT DISAGREE
3. NEITHER AGREE OR DISAGREE
4. SOMEWHAT AGREE
5. STRONGLY AGREE
88. DON'T KNOWA{OT SURE
99. REFUSED
[IF SP2e not 1] SP2g. Why did you not apply for an incentive from &PACIFICORP for this equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWA{OT SURE
99. REFUSED
Bariers
81. Do you think there are other changes that you could make to improve electric efficiency at &FIRM?
1. YES
2. NO ) SKIP TO ICl
88. DON'T KNOWAIOT SURE ) SKIP TO ICl
99. REFUSED ) SKIP TO ICl
82. Could you provide some examples of changes you think would improve electric efficiency at
&FIRM?
1. [RBCORD RESPONSE: PROBE FOR ADDITIONAL]
88, DON'T KNOWAIOT SURE
99. REFUSED
B3. Are plans in place to make any of those changes?
Confideniia anil Propr'eiary
i*ahc Sn*6y FinAnswer Evaiuaiion Repsil
Aprendir C - Fr,:cess Evaiuaiiorr Sui'vey lnstuments
Rocky Mountrain Power
Exhibit No. 5 Page 1012 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
l"'age S-1 1
ru.Art$ilANT
1. YES
2. NO ) SKIP TO 85
88. DON'T KNOWNOT SURE ) SKIP TO 85
99. REFUSED ) SKIP TO 85
84. Are incentives from &PACIFICORP or another organization part of those plans?
1. NO
2. YES
88. DON'T KNOWA{OT SURE
99. REFUSED
85. What factors could prevent &FIRM from making these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
1. HIGH TJPFRONT COSTS
2. LACKOFACCESS TO CAPITAL
3. LONG PAYBACK PERIOD; SLOW RATE OF RETURN
4. LOW PRIORITY/LACK OF INTEREST OF SEMOR MANAGEMENT IN ENERGY
EFFICIENCY
5. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
6. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAI]F
7, OTHER (SPECIFY
-)
88. DON'T KNOWAIOT SURE
99. REFUSED
IIF MORE THAN ONE RESPONSE TO B5l 86. Which of these do you think is the most challenging
factor?
1. HIGH IJPFRONT COSTS
2. LACK OFACCESS TO CAPITAL
3. LONG PAYBACK PERIOD; SLOW RATE OF RETURN4. LOW PRIORITY/LACK OF INTEREST OF SEMOR MANAGEMENT IN ENERGY
EFFICIENCY5. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
6. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
7. OTHER (SPECTFY _)
88. DON'T KNOWA{OT STIRE
99. REFUSED
Satisfaction
ICL. Using a scale of I to 5 where 1 indicates 'very dissatisfied' and 5 indicates 'very satisfied', how
satisfied were you overall with the program?
1. VERY SATSIFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO IC2
5. VERY SATISFIED ) SKIP TO IC2
88. DON'T KNOW,NOT SURE ) SKIP TO IC2
99. REFUSED ) SKIP TO IC2
ICIA. Why were you less than satisfied with the program overall?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
$onfldenlral .rnd Propnefary
idalir: fn*rgy FinAnswer Evaluaticn Report
Apcendir C - Froc*ss Evaiuatioii Suivev lnstiunt*nts
Roclry Mountain Power
Exhibit No. 5 Page 1013 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Fare 0-12
ru&v I TA NT
99. REFUSED
lcz.lt you could change anything about the &PROGRAM program, what would you change?
1. TRECORD RESPONSEI
88. DON'T KNOWNOT SURE
99. REFUSED
IC3. During your involvement with &PROGRAM did you ever contact &PACIFICORP with questions
or requests for assistance?
1. YES
2. NO ) SKIP TO FBl
88. DON'T KNOWA{OT SURE ) SKIP TO FBl
99. REFUSED ) SKIP TO FBl
IC4. Were &PACIFICORP and its representatives timely in addressing your questions in regards to the
program?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
ICS. Were &PACIFICORP and its representatives knowledgeable in regards to the program and the
program eligibility requirements?
1. YES
2. NO
88. DON'T KNOWAIOT SURE
99. REFUSED
Firrnographics
FBl INTRO.
Now I have a few final, general questions about your company for comparison purposes only.
FBl. Which of the following best describes your company's primary activities?
1. MANUFACTURING
2. RETAIL
3. DAIRY / AGRICULTURAL
4. FINANCE AND INSTIRANCE
5. FOOD PROCESSING
6. REFRIGERATED WAREHOUSE
7. PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES
8. EDUCATIONAL SERVICES
9. HEALTH CARE
1 O. PUBLIC ADMINISTRATION
I1. ARTS, ENTERTAINMENT, AND RECREATION
12. ACCOMMODATION
13. FOOD SERVICES
14. REAL ESTATE
15. MINING
16. OIL AND GAS
17. oTHER [SPECTFY]
Sonfl deniiai anri Proprreisry
ld*h* fn*rgy FinAnswer Evaiuation Repr$
Aprendir C - Frocess Evaiuation Sui'vey lns$umrnts
Rocky Mountain Power
Exhibit No.5 Page 1014 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C-l3
N$V$S,qi\l
88. DON'T KNOWNOT SURE
99. REFUSED
FB2. Approximately, what percent of your total annual operating costs does your electricity bill
represent?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
FB3. About how many people does your firm employ?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SI]RE
99. REFUSED
End
ENDI. Those are all of the questions that I have for you. Is there anything about your experiences with
&PACIFICOM's &PROGRAM program you'd like to mention that we did not talk about today?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
TTHANK RESPONDENT AND TERMINATE SURVEY]
Con irdeni, a j sns Froprieisry*
l$ahr: Energy FinAnswer Evaiuation Report
Apmndir C - Process Evaiuation Suivey lnstumerits
Roclry Mountain Power
Exhibit No. 5 Page 1015 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
f-lage 0-t4
ru r,,$tANT
C.2 Near-Participant Suntey lnstrument
Note: Energy FinAnswer and FinAnswer Express Near Participants are those customers who are in the project
tracking systun with aproject through the Energy FinAnswer or FinAnswer Express program during 2009-2011.
but are identified as cancelled or on hold as of the end of 20L7.
Objectioes
These surveys are designed to meet the following list of objectives.
. To describe how customers come to participate in the program
o To characterize the current status of projects identified as on hold or cancelled
o To understand overall customer satisfaction with the program, while participating
o To understand what it would take to motivate near participants to participate
o To understand barriers customers are facing that prevent increasing energy efficiency
o To characterize near-participant firms
Variables
Intentiew lnstrument
Introduction and Screen
INTROI.. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's &PROGRAM and would like to hear about your
experiences. This is not a sales call. May I please speak with &CONTACT?
1. YES, THAT IS ME ) SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU ) SKIP TO INTROz
3. NOT NOW ) SCHEDULE APPT AND CALL BACK
4. NO/REFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's &PROGRAM and would like to hear about your
experiences. This is not a sales call."
I'd like to let you know that this call may be monitored or recorded for quality assurance purposes. Also,
all of your responses will be kept confidential and will not be revealed to anyone outside of the research
team. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research purposes only and will take about 10 minutes."l
1. YES ) SKIP TO IS2a
2. NOT NOW + MAKE APPT. TO CAIL BACK
Conildentiai enri Fropriefery
i$ahc fn*6y FinAnswer Evaiuation Rep.rit
Apcen.Jir C - Frocess Evaiuatiori Sui^vsy instrumei'lts
Roclry Mountain Power
Exhibit No. 5 Page 1016 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Variable Name Description Tvpe
&CONTACT Respondent name Text
&FIRM Companv name Text
&PROGRAM Energy FinAnswer, FinAnswer Express Text
&SITE Address Text
&YEAR Year of oroiect start YTYY
&PACIFICORP Rocky Mountain Power, Pacific Power Text
Fla,:e C-1ii
ruAxr$tANT
3. NO/REFUSED ) TERMINATE
INTRO3. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research purposes only and will take about 10 minutes."l I'd like
to let you know that this call may be monitored or recorded for quality assurance purposes. Also, all of
your responses will be kept confidential and will not be revealed to anyone outside of the research team.
4. YES
5. NOTNOW ) MAKE APPT. TO CAIL BACK
6. NO/REFUSED
'
TERMINATE
[IF VERIFICATION IS NEEDED, TELL THEM THEY CAN CALL SHAWN GRANT AT 801.-220-
41961.
IS2a. &PACIFICORP records indicate that you were considering a project to improve efficiency at &SITE
with the &PROGRAM program in &YEAR but did not complete the project and get an incentive, is this
correct?
1. YES ) SKIP TO APl
2. NO, DID NOT PARTICIPATE
3. NO, COMPLETED PROIECT AND GOT INCENTIVE ) CONFIRM &TERMINATE
88. DON'T KNOWNOT SURE
99. REFUSED
IS2b. Is there someone else that might be familiar with this project?
1.. Yes
2. No ) TERMINATE
88. Don't know ) TERMINATE
IS2c. May I speak with that person?
1.. Yes ) RETURN TO INTRO2
2. Notnow)SCHEDULECALLBACK
3. No ) TERMINATE
IS3. Are you the person most familiar with &FIRM's decision to begin this project?
1,. YES
2. NO ) SKIP to IS2b
88. DON'T KNOWNOT SURE ) SKIP to IS2b
99. REFUSED ) SKIP to IS2b
Awareness & Participation
APl. How did you firstbecome aware of &PROGRAM? [DO NOT READ RESPONSES]
1,. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
2. &PACIFICORPRADIOADVERTISEMENT
3. &PACIFICORP PRINTADVERTISEMENT
4, &PACIFICORPPRINTEDMATERIALS/BROCHURE
5. &PACIFICORP ONLINE ADVERTISEMENT
6, &PACIFICORP TV ADVERTISEMENT
7. &PACIFICORPNEWSLETTER
8. &PACIFICORP WEBSITE
9. PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
C$srisrlntisi s$$ Pi"oprisiery
itiaiii: In*rgy FilAnswer Evaluntio.r Repo*
Apnendir: C - Frocess Evriiustioir Siri'v*v lnstiurnerits
Rocky Mountain Power
Exhibit No. 5 Page 1017 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
F age C-lS
Nd\VISENT
10. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY: ]
11. &PACIFICORP SPONSORED ENERGY AUDIT OR TECHNICAL ASSESSMENT
12. FROM TRADE ALLY, VENDOR OR CONTRACTOR
13. ANOTFIER BUSINESS COLLEAGUE
14. FAMILY, FRIEND, OR NEIGHBOR
15. OTHER [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSE
AP2. Why did you decide to participate in the program? [DO NOT READ RESPONSES; SELECT ALL
THAT APPLY]
L. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
1.3. Recommended by family, friend or neighbor
14. Recommended by &PACIFICORP staff
15. To improve operations, production, or quality
16. To improve value of property
17.To improve comfort
18. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSE
[IF more than one response to AP2]
AP2a. Of those reasons, which one was most influential in your decision to participate in the program?
IALLOW ONLY ONE RESPONSEI
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
1.2. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Recommended bv &PACIFICORP staff
ilonfi denfial en{i Fiolrefsry
ldaha En*rgy FinAnswer Evaiuatron Rep*il
Apcendix C - Prucess fvtsiuation Suivey lnstrumeilts
Rocky Mountain Power
Exhibit No.5 Page 1018 of l365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fagr-:0-1?
rus\ttsANT
15. To improve operations, productiory or quality
16. To improve value of property
17.To improve comfort
18. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
Near Participant
NPl. Thinking back to the project that you started under the &PROGRAM program at this site, how
would you characterize its status today? [IF NECESSARY, READ OPTIONS]
1. NOW DOING PROJECT
2, PLANNING TO DO PROJECT /PROJECT ON HOLD
3. COMPLETED PROIECT WITTIOUT PROGRAM ) SKIP TO NPs
4, NOTDOING PROIECT/PROJECTCANCELLED ) SKIPTO NP6
5. OTHER[SPECIFY---] ) SKIP TO NP7
88. DON'T KNOWNOT SURE ) SKIP TO NP7
99. REFUSED ) SKIP TO NP7
NP2. Why did you put the project on hold?
1. Not on hold
2. Needed to acquire capital funding
3. Delays from contractor
4. Other [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
NP3. Will th e project be completed under a &PACIFICORP program?
1. YES
2. NO ' SKIP TO NPs
88. DON'T KNOWNOT SURE ' SKIP TO NPs
99. REFUSED ) SKIP TO NPs
NP4. Which program will you complete the project under? [READ LIST]
1. SELF-DIRECTION CREDIT ) SKIP TO 81
2. ENERGY FINANSWER ) SKIP TO 81
3. FINANSWER EXPRESS) SKIP TO 81
4, OR SOMETHING ELSE (SPECIFY-) ) SKIP TO 81
88. DON'T KNOWNOT SURE ) SKIP TO 81
99. REFUSED ) SKIP TO 81
Coafrdenira an$ Ficpreiori,'
!dahc Encrg,v FlrAnswe r Evaiuatior Repo*
Apcent]rr C - Frocess Eveiuaiiott Survel, ilisgs6ist1"t
Roclry Mountain Power
Exhibit No. 5 Page '1019 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Flage 0-1$
ruAv$sANT
NPS. lA/hy did you decide do the project without participating in any programs?
1. [RECORD RESPONSE] ) SKrP TO NP7
88. DON'T KNOWAIOT SURE) SKIP TO NP7
99. REFUSED) SKIP TO NP7
NP5. Why did you decide not do to the project?
1. [RECORD RESPONSE] ) SKrP TO NP7
88. DON'T KNOWNOT SURE) SKIP TO NP7
99. REFUSED) SKIP TO NP7
NP7. What would need to change for you to participate in &PROGRAM or similar program?
i. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Barriers
8L. Do you think there are other changes that you could make to improve electric efficienry at &FIRM?
1. YES
2. NO ) SKIP TO ICl
88. DON'T KNOWAJOT SURE ) SKIP TO ICI.
99. REFUSED ) SKIP TO ICl
82. Could you provide some examples of changes you think would improve electric efficienry at
&FIRM?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
83. Are plans in place to make any of those changes?
1. YES
2. NO ) SKTP TO 85
88. DON'TKNOWNOTSURE ) SKIPTO 85
99.REFUSED
'
SKIPTO85
84. Are incentives from &PACIFICORP or another organization part of those plans?
1. NO
2. YES
88. DON'T KNOWNOT SURE
99. REFUSED
Confdenira an* Frorneiary
irianr fne6y FilAnsiver Evaluation R*poit
Apcendir C - Prcsess Evaiuatiorr Suiv*y hrstrr"imerits
Rocky Mountain Po\,er
Exhibit No. 5 Page 1020 of 1365
Case No. PAC-E-14-07
Witness: lGthryn C. Hymas
Fage C- i $
ru &tr $il,q N T
85. What factors could prevent &FIRM from making these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
1. HIGH UPFRONT COSTS
2. LACK OF ACCESS TO CAPITAL
3. LONG PAYBACK PERIOD; SLOW RATE OF RETURN
4. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
5. LACK OF INFORMATION ABOUT SAVINGS AND PERTORMANCE
6. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
7. OTHER (SPECIFY
-)
88. DON'T KNOWAJOT SURE
99. REFUSED
[IF MORE THAN ONE RESPONSE TO 85] 86. Which of these do you think is the most challenging
factor?
1. HIGH UPFRONT COSTS
2, LACK OF ACCESS TO CAPITAL
3. LONG PAYBACK PERIOD; SLOW RATE OF RETURN
4. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
5. LACK OF INFORMATION ABOI.]'TSAVINGS AND PERFORMANCE
6, LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
7. OTHER (SPECIFY-)
88. DON'T KNOWNOT SURE
99. REFUSED
Satisfaction
ICI.. Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5 indicates 'very satisfied', how
satisfied were you overall with the experience that you had with the program?
1. VERY DISSATSIFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWI{AT SATISFIED ) SKIP TO IC2
5. VERY SATISFIED ' SKIP TO IC2
88. DON'TKNOWI{OTSURE ) SKIPTO IC2
99. REFUSED ) SKIP TO IC2
ICLA. Why were you less than satisfied with the program overall?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IC2. During your involvement with &PROGRAM did you ever contact &PACIFICORP with questions or
requests for assistance?
1. YES
2. NO )SKIPTOFBI.
88. DON'T KNOWNOT SURE ) SKIP TO FBI.
99. REFUSED ) SKIP TO FBI.
Con;'.rdenir a er:C,ciopr'eisry
iCaIc En*6y FinAnsrver Evaiuaticn Repoit
Apcendir C - Fr*c*ss Evaiuation Siri'v$y li]:iiriimsr*s
Rocky Mountain Power
Exhibit No. 5 Page 1021 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Fastl 0-2ii
N.f\VITAi\T
IC3. Were &PACIFICORP and its representatives timely in addressing your questions in regards to the
program?
1. YES
2. NO
88. DON'T KNOWA{OTSURE
99. REFUSED
IC4. Were &PACIFICORP and its representatives knowledgeable in regards to the program and the
program eligibility requirements?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
Finnographics
FBl. Now I have a few final, general questions about your company for comparison purposes only.
\Alhich of the following best describes your company's primary activities?
1. MANUFACruRING
2. RETAIL
3. DAIRY / AGRICULTURAL
4. FINANCE AND INSURANCE
5. FOOD PROCESSING
6. REFRIGERATED WAREHOUSE
7. PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES
8. EDUCATIONAL SERVICES
9. HEALTH CARE
10. PUBLIC ADMINISTRATION
11. ARTS, ENTERTAINMENT, AND RECREATION
12. ACCOMMODATION
13. FOOD SERVICES
14. REAL ESTATE
15. MINING
16. OIL AND GAS
17. OTHER [SPECIFY]
88. DON'T KNOWNOT SURE
99. REFUSED
FB2. Approximately, what percent of your total annual operating costs does your electricity bill
represent?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
FB3. About how many people does your firm employ?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
C+nfide,ri:ei saii Prosr,eiory Fage 0-21
iCeht fnsrgy FirAnswer Evaiuation Repc$
irprentjrr C - Process Evaiuaiiorr Suir,ey lnstrumer*s
Roclq Mountain Power
Exhibit No. 5 Page 1022 of 1365
Case No. PAC-E-'I4-07
Wtness: Kathryn C. Hymas
Roclry Mountain Power
Exhibit No. 5 Page 1 023 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
End
END1. Those are all of the questions that I have for you. Is there anything about your experiences with
&PACIFICORP's &PROGRAM program you'd like to mention that we did not talk about today?
1. [RECORD RESPONSE]
88. DON'T KNOWNIOT SURE
99. REFUSED
[THANK RESPONDENT AND TERMINATE SURVEY]
Cr:n*dent,ei *n$ Pro.nrisiery
iiahc Energy FinAnsrver Evaiuati.ln Repurt
Aprendir C - Frqcess Evaiuatiorr Suryey lnstrunrents
Page 0-22
ruAv$ tANT
C.3 Non-Participant Suruey Instrument
Note: Non-participants are C&l customers who are not identified as haoing started participating in any
PacifiCorp programs befineen 2009 and 201.1..
Objectioes
These surveys are designed to meet the following list of objectives.
. To assess awareness of PacifiCorp programs among non-participants
r To identify non-participant efficient purchasing
o To understand barriers customers are facing that prevent increasing energy efficiency
o To characterize non-participant firms
Vartables
Suruey Instrument
Introduction and Screen
INTROI. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficienry programs so that they better suit the needs
of customers like you. This is not a sales call. May I please speak with the person who is responsible for
the $_CLASS electric account for $_FIRM?
1. YES, THAT IS ME ) SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU
3. NOT NOW ) SCHEDULE APPT AND CALL BACK
4. NO/REFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's efficiency programs so that they better suit the needs of
customers like you. This is not a sales call. Do you have a few minutes? [IF NEEDED, READ: "This
survey is for research purposes only and will take about 1.0 minutes."I
7. YES t SKIP TO IS2a
8. NOT NOW '
MAKE APPT. TO CALL BACK
9. NO/REFUSED ) TERMINATE
INTRO3. Great. I'd like to let you know that this call may be monitored or recorded for quality
assurance purposes. Also, all of your responses will be kept confidential and will not be revealed to
anyone outside of the research team.
[IF NEEDED, READ: "This survey is for research purposes only and will take about 10 minutes."]
1. CONTINUE WITH INTERVIEW
ilonf o'eliia enC Propr'ef .r4r
i$an* [nergy FinAnswer Evaiustisn Repsil
Aprendrr il ^ Frocess Evaiuation Sui'','ey lns$unierits
Rocky Mountain Power
Exhibit No. 5 Page 1024 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Variable Name Description Tvpe
&FIRM Companv name Text
&PHONE Phone number Numeric
&SITE Address Text
&PACIFICORP Rocky Mountain Power, Pacific Power Text
&CLASS Revenue Class Text
F age C-23
ru"'&V$tANT
2. NOT NOW ) MAKE APPT. TO CALL BACK
3. NO/REFUSED ) TERMINATE
[IF VERIFICATION IS NEEDED, TELL THEM THEY CAN CALL SHAWN GRANT AT 801..22&
41951.
VL. First, I'd like to verify my records. \l/hich utility company provides electricity at &SITE?
1. &PACIFICORP
2. OTHER ) TERMINATE
88. DON'T KNOWNOT SURE
99. REFUSE
[IF &_CLASS "COMMERCIAL" OR "INDUSTRIAL"]V2. Was this facility at &SITE constructed before or
after 2009?
1. BEFORE 2OO9
2.2OO9ORLATER
Awareness
A1. Are you aware that &PACIFICORP offers incentives and technical assistance to &CLASS customers
to help them reduce electricity usage?
1. YES
2. NO ) SKIP to A4
88. DON'T KNOWNOT SURE ) SKIP TO A4
99. REFUSED + SKIP TO A4
A2. How did you become aware that &PACIFICORP offers energy efficiency program(s)? [DO NOT
READ RESPONSES, SELECT ALL THAT APPLY]
16. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
17. &PACIFICORP RADIO ADVERTISEMENT
18. &PACIFICORP PRINT ADVERTISEMENT
19. &PACIFICORP PRINTED MATERIALS/BROCHURE
20. &PACIFICORP ONLINE ADVERTISEMENT
21. &PACIFICORP TV ADVERTISEMENT
22. &PACIFICORP NEWSLET'TER
23. &PACIFICORPWEBSITE
24. PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
25. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_]
26. &PACIFICORP SPONSORED ENERGY AUDIT OR TECHNICAL ASSESSMENT
27. FROM TRADE ALLY, VENDOR OR CONTRACTOR
28. ANOTHER BUSINESS COLLEAGUE
29. FAMILY, FRIEND, OR NEIGHBOR
30. OTHER ISPECIFY]:
89. DON'T KNOWNOT SURE
99. REFUSE
tonfidentrai entr Propriefs4,'
i$ahc En*r.gy FinAnswe r Evaiualion Repu$
Aprendir C - Froress Evaiuatiort Sui,rcy lnstunieiits
Roclry Mountain Power
Exhibit No. 5 Page 1025 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Faotl C-24
Nd\V$TANT
Rocky Mountain Power
Exhibit No. 5 Page 1 026 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
A3.I4/hich programs or services can you think of that &PACIFICORP offers to &CLASS customers? IDO
NOT READ RESPONSES, SELECT ALL THAT APPTYI
1. ENERGYFINANSWER
2. FINANSWER EXPRESS
3. SELF.DIRECTION CREDIT
4. RECOMMISSIONING
5. IRRIGATION LOAD CONTROL
6, IRRIGATION ENERGYSAVERS
7. INCENTTVES FOR EFFICIENT EQUIPMENT
8. TECHNICAL ASSISTANCE/ ENERGY ANALYSIS
9. DEMAND RESPONSE /LOAD CONTROL
10. Other ISPECIFY]:
88. DON'TKNOWAJOTSURE
99. REFUSED
A4. In the futurg what is the best for &PACFICORP to keep you informed about programs they offer
that could help your firm save energy?
1. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
2, RADIOADVERTISEMENT
3. PRINTADVERTISEMENT
4, PRINTED MATERIALS/BROCHURE
5. ONLINEADVERTISEMENT
6, TV ADVERTISEMENT
7, NEWSLETTER
8. WEBSITE
9. CONFERENCE, WORKSHOP, OR EVENT [SpECIFY:_]
10. TRADE ALLY, VENDOR OR CONTRACTOR
11. OTHER [SPECIFY]:
90. DON'T KNOWNOT SURE
99. REFUSE
Energy Efficient Actions by Non-Participants
llFV2=2, SKIPTO EE21.I
EEl. Between 2009 and 2011, did you have a systematic evaluation or audit of your facility, at &SITE, to
identify and implement operational improvements? [IF NEEDED: "this includes building and
equipment audits, system analyses, energy engineering analysis, other detailed studies."]
1. YES
2. NO ) SKIP TO EE8
88. DON'T KNOWNOT SURE ) SKIP TO EE8
99.REFUSED ) SKIPTOEEs
EE2. What factor or factors motivated you to have your facility undergo a systematic evaluation? [DO
NOT READ RESPONSES; ALLOW MULTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
Conildelirei an$ Propr,ef ary..
iSan* fns6y FinAnswer Evaiuation Repsit
Aprendir C - Process Ev$iuaiion Survey lns$uments
F-'age 0-?5
h} &V$TANT
5. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
L 1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, productiory or quality
15. To improve value of property
L6. To improve comfort
17. Other [SPECIFY]:
88. DON'TKNOWA{OTSURE
99. REFUSED
EE3. Did you receive assistance from &PACIFICORP or another organization? [IF NEEDED: assistance
may include technical assistance or incentives]
1. YES
2, NO ) SKIP TO EEs
88. DON'T KNOWNOT SURE ) SKIP TO EE5
99.REFUSED ) SKIPTOEEs
EE4. What program or sponsor provided assistance?
1. &PACIFICORP ) SKIPTO EE8
2. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EEs. What opportunities for improvement were identified? [PROBE FOR AS MUCH DETAIL AS
POSSTBLEI
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE5. What actions have you taken as a result of the study?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF EE4 not 1lEE7. Why did you not apply for assistance from &PACIFICORP?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE8a. Did you install any high efficiency equipment at this site between 2009 ar.d2011?
1. YES
2. NO
88, DON'T KNOWNOT SURE
Sonfrdenirai enC Proprrefe4,
idahr fn*rgy FinAnswer E,.,aiuetion Repoil
Apnenilir C - Process Evaiuatioii Suivey lnsiruniei'lts
Rocky Mountain Power
Exhibit No. 5 Page 1027 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Fage 0-2$
NAV$ TANT
99. REFUSED
EESb. Did you make any improvements to this site between 2009 and 2011tohelp conserve energy? I1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
[IF EE8a + 1 and EE8b + 1, SKIP TO EEL5]
EE9. What did you install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1. [RECORD RESPONSEI
88. DON'T KNOWNOT SURE
99. REFUSED
EELO. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWA.JOT SURE
99. REFUSED
EE1.L. What factor or factors motivated you to make these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPTE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
L2. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, production, or quality
L5. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EEL2. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2. NO ) SKIP TO EE1.4
88. DON'T KNOWNOT SURE ) SKIP TO EE14
99. REFUSED ) SKIP TO EE1.4
EE13. What program or sponsor provided assistance?
#on";identr fl i enri ProOneiary-
idahc fnerrcy- FirAnswer fvaiuati.:n Repo{
Aprendlr C - Prncess Evaiuaiiorr Slii'v$y ln$inim$iits
Roclq Mountain Po\ryer
Exhibit No. 5 Page 1028 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C-2i
Rocky Mountain Power
$,I\",d\V$TANT
3. &PACIFICORP ) SKIP TO EE15
4. IRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE1.4. \A/hy did you not apply for an incentive from &PACIFICORP for this equipment?
L. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EEL5. Since 2009, have you implemented any load control strategies at your facility?
1. YES
2. NO ) SKIP TO 81
88. DON'T KNOWNOT SURE ) SKIP TO 81
99. REFUSED ) SKIPTOBl
EEL6. What strategies have you implemented?
L. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE17. What factor or factors motivated you to make these changes? IDO NOT READ RESPONSES;
ATLOW MULTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
1 1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
L4. To improve operations, productiory or quality
15. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EE18. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2, NO ) SKIP TO EE2O
88. DON'T KNOWNOT SURE ) SKIP TO EE2O
99. REFUSED ) SKIPTO EE2O
Conf deniia en."r F),-opiieiary-
iiiai'rc In*rgir FinAnswer Evaluation Repu*
Aprentiir C - Prr.rcess Evaiuaiiort Survey lnst'uni*tts
Exhibit No, 5 Page I029 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fagtl C-2$
ruAvr tANT
EEL9. What program or sponsor provided assistance?
1. &PACIFICORP ) SKIP TO 81
2. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE20. Why did you not apply for an incentive from &PACIFICORP for these load control
improvements?
1. [RECORD RESPONSE]
88. DON'T KNOWI{OT SURE
99. REFUSED
[IF V2=2] EE21. When constructing this facility, did you install any high efficienry equipment?
1. YES
2. NO )SKIPTOBI
88. DON'T KNOWAJOT SURE ) SKIP TO B1.
99. REFUSED ) SKIP TO 81
EE,22. What high efficienry equipment did you install? (PROBE FOR AS MUCH DETAIL AS
POSSTBLE)
2. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE23. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE24. What factor or factors motivated you to make these changes? [DO NOT READ RESPONSES;
ALLOW MUTTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
5. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
1.3. Recommended by family, friend or neighbor
14. To improve operations, production, or quality
15. To improve value of property
16. To improve comfort
Conf, deri,a en$ Proprieiery-
iian* fn*ryy FirrAnswer Evaluation Repci"t
Apnendix C - Pr,)sess Eva:uati,)n Sr:rvsy llrstiuments
Rocky Mountain Power
Exhibit No. 5 Page 1 030 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Page C-2$
ruAxrs TANI T
Rocky Mountain Power
Exhibit No. 5 Page 1031 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EE25. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2. NO )SKIPTOEEZT
88. DON'T KNOWNOT SURE ) SKIP TO EE27
99. REFUSED ) SKIP TOEEZ7
EE26. \A/hat program or sponsor provided assistance?
5. &PACIFICORP ) SKIPTO 81
6. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE27. Why did you not apply for an incentive from &PACIFICORP for this equipment?
L. [RECORD RESPONSE]
88. DON',T KNOWATOT SURE
99. REFUSED
Barriers
BL. Do you think there are other changes that you could make to improve electric efficienry at &FIRM?
1. YES
2. NO ) SKIP TO FBI
88. DON',T KNOWNOT SURE ) SKIP TO FBL
99. REFUSED ) SKIPTOFBl
82. Could you provide some examples of what changes you think you could make?
1. [RECORD RESPONSE]
88, DON'T KNOWNOT SURE
99. REFUSED
83. Are plans in place to make any of those changes?
1. YES
2. NO ) SKIP TO 85
88. DON'T KNOWNOT SURE ) SKIP TO 85
99. REFUSED ) SKIPTO85
84. Are incentives from &PACIFICORP or another organization part of those plans?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
85. What factors could prevent &FIRM from making these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
8. HIGH UPFRONT COSTS
f; onfl denlrai an rj Froprr ei.lry-
iriai:* Sn*6y FinAnswer Evaiualinn Repmt
Apo*ndir C - Process Evaiuatiuti Survey lnsirunist,l*
F-'ase C-3(i
N&V$ TANT
9. LACKOF ACCESS TO CAPITAL
10. LONG PAYBACK PERIOD; SLOW RATE OF REruRN
11. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
12. LACK OF INFORMATION ABOUT SAVINGS AND PERTORMANCE
13. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
14. OTHER (SPECIFY-)
88. DON'T KNOWAJOT SURE
99. REFUSED
IIF MORE THAN ONE RESPONSE TO B5l 86. Which of these do you think is the most challenging
factor?
8. HIGH UPFRONT COSTS
9. LACK OF ACCESSTO CAPITAL
10. LONG PAYBACKPERIOD; SLOWRATE OF RETURN
11. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
12. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
13. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
14. OTHER (SPECIFY-)
88. DON'T KNOWNOT SURE
99. REFUSED
Firmographics
FBl. Now I have a few final, general questions about your company for comparison purposes only.
Could you describe your company's primary activities? (DO NOT READ LIST, CODE AND CONFIRIM
WITH RESPONDENT)
1. MANUFACTURING
2. RETAIL
3. DAIRY i AGRICULruRAL
4. FINANCE AND INSURANCE
5. FOOD PROCESSING
6. REFRIGERATED WAREHOUSE
7. PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES
8. EDUCATIONAL SERVICES
9. HEALTH CARE
10. PUBLIC ADMINISTRATION
1.1. ARTS, ENTERTAINMENT, AND RECREATION
12. ACCOMMODATION
13. FOOD SERVICES
14. REAL ESTATE
15. MINING
16. OIL AND GAS
17. OTHER [SPECIFY]
88. DON'T KNOWNOT SURE
99. REFUSED
Confidentiai anri P-ropnef ery..
itiahc In*rgy tinAnswer Evaiuation Repcrt
Aprendir C - Frocess Evaiuation Survslt lxsil,J61si!1*
Rocky Mountain Power
Exhibit No. 5 Page 1032 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pa.re 0--'l i
ruAv$ tANT
FB2. Approximately, what percent of your total annual operating costs does your electricity bill
represent? (IF NEEDED: An estimate is fine.)
1.. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
FB3. And about how many people does your firm employ at this facility?
L. IRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
End
END1. Those are all of the questions that I have for you. Is there anything about your experiences with
&PACIFICORP you'd Iike to mention that we did not talk about today?
I. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
[THANK RESPONDENT AND TERMINATE SURVEY]
tJonfdeniiei *n C Pra.c,ref ery*
i$onn Ine6y FinAnswer Evaluation Rep,;$
Apnendir fl - Frocess fivaiuation Suivey lnsgiinl$n1t
Roclry Mountain Power
Exhibit No. 5 Page 1 033 of 1 365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
F Aile t,-Jz
Nf\V$T*qNI T
C.4 Energy Engineer Suntry Instrument
Note: Potential respondents for the purposes of this interview are energy engineers supporting the RMP
and Pacific Power Energy who have completed at least one Energy FinAnswer project between 2009
and2017. Participant survey responses, tracking data, and suggestions from program staffwill be
considered before selecting allies to interview.
Objectioes
These interviews are designed to meet the following list of objectives.
e How are trade allies becoming aware of the program?
o How well does the trade ally participation agreement meet their needs?
o How are program operations communicated to trade allies? How is training provided? Is this
communication and training effective (do they understand the program)?
o How satisfied are trade allies with their role in the program? What would they do to improve
ir?
o Do trade allies who participate see value to their business? Can they describe the effect on
their operations?
Variables
Interaiew Guide
Hello, this is <INTERVIEWER NAME>, from Energy Market lnnovations. We are conducting an
independent evaluation of $_PACIFICORP's energy efficiency programs. This is not a sales call. May I
please speak with $_CONTACT.
I understand that $_FIRM conducts energy engineering in support of $_PACIFICORP's Energy
FinAnswer program. Your feedback can be used to improve the program.
A1. Are you the person that works most closely with $_PACIFICORP at your company?
a. Yes
b. No ) [ask to speak to person most familiar with the program]
Conildeniiai nnii Frooriefir4.,
idahc [.netgy FirAnswer Evaluation Repc$
Apcenciix C - Fr,:cess Evaluation Survsy lnstrunients
Roclry Mountain Power
Exhibit No. 5 Page 1 034 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Variable Description Type
$_CONTACT Name of contact Text
$_FIRM Name of vendor company Text
$_PACIFICORP Pacific Power /Rocky Mountain Power Text
$_PROJECTS Completed projects 2009 -201 |Number
$-STATE State(s) where active Text
Fage C-33
N&V$TANT
Rocky Mountain Power
Exhibit No. 5 Page I 035 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
I would like to discuss your experiences and perspectives regarding energy engineering with
$_PACIFICORP. This interuiew will take 15-30 minutes, and as a thank you for taking time to chat with
me, I would like to offer you a $50 gas card.
Is this a good time to talk or would you prefer to schedule a more convenient time?
[If no, scheduled callback time:]
-With your permission, I'd like to record this interview to ensure that I don't miss any important
information and for quality assurance. Your responses will be kept confidential.
A2. In one or two sentences, can you please tell me what $-FIRM does?
,A'3. What is your title/role at $-FIRM?
A3a. How long have you been in this position at your company?
Section L: Participation
1. How did you first hear about the program? (DO NOT READ, MARK ALL)
a. Advertising
b. PacifiCorp Representative
c. OtherContractorAy'endor
d. Customer
e. Other (SPECIFY
2. What motivated you to participate?
3. Our records show that your firm facilitated $_PROJECTS projects from 2009 to 2011 in
$_STATE in collaboration with $_PACIFICORP. (Repeat for each state firm is active in.)
a. How were you involved? (E.g. Did they influence the project or just write reports/do
QC/install loggers?)
Section 2: Training Roles, and Communication
4. What kind of training or information about the program were you provided when you first
became involved? [MAY HAVE HAD INTERNAL TRAINING.]
a. Have you had any follow up or continuing training?
b. Have you, or someone from $-FIRM attended an alliance workshop?
5. Did you feel like the program was clearly explained? What about your role in the program?
Confide,rilei an$ Pr-oplieisi"y
i.jahr: fn*rgy FiirAnswer Evaluati.lr Repoit
Apcenilir C - Frrlcess Evaiuatiott Suivey lns$uments
Fage 0-34
N&VISA i\T
6. How would you describe your communication with the program representatives?
Is there one key contact you communicate with about the program? Who?
What might initiate contact; is there a set frequency of contact or an action that would
trigger contact? Does he/she contact you or do you contact him/her? How often? Does
this meet your needs?
c. How would you rate your satisfaction with your contact, on a scale of 1 to 5 with I being
very dissatisfied and 5 being very satisfied?
d. Is he/she able to answer your questions or get you to someone who can?
7. How do you prefer to get information about the program? (DO NOT READ, MARK ALL
THAT ARE STATED)
e. Online, check site often
f. Email
Mail Newsletter
Phone Call
Section 3: Energy Analysis Process
8. Do you conduct Energy Analyses for the Energy FinAnswer Program?
[If no, skip to Q7] TENERGY ANALYSES ARE WHEN TI{EY GO OUT TO THE SITE, IDENTIFY
SAVINGS OPPORTUNITIES, AND DETERMINE PROJECT ELIGIBILITY]
9. Please tell me about your experience with the process of energy analysis for Energy FinAnswer
projects. First:
a. What does the process entail on your end? [PROBE FOR PARTICULARS: visit the
customer site, activities on site, reviewing baseline consumption, observing practices,
communications with line managersl
i. Probe for Initial Site Visit and Energy Analysis
ii. IPROBE FOR LEAD GENERATION] Do all of your Energy FinAnswer energy
analysis projects begin with contact from PacifiCorp, or do you bring projects to
the program?
b. Does the program allow enough time and resources to do this task well?
c. How are findings communicated with the customer? With $_PACIFICORP?
d. How are issues raised by the analysis resolved?
e. How long does this process take on average?
f. Do you have any concerns with the way that results are used?
Confidentra e$C Frcprief ary,'
i$ahc fnergy" FinAnsrver Evaiuation Reporl
Apoendir C - Process Evaiuation S,lrvey hsirumerrts
Rocky Mountain Power
Exhibit No.5 Page 1036 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
a.
b.
ob'
h.
Fage C-3{i
N$V $T,q N T
10. What percent of your time spent with the Energy FinAnswer program is performing Energy
Analysis? [CONDUCTING PRIMARY ENGINEERING ANALYSIS AND POST
INSPECTIONS AS OPPOSED TO REVIEWING OTHERS' WORK]
11. Do you conduct Quality Control Reviews for the Energy FinAnswer program?
[If no, skip to NEXT SECTION]
12. What percent of your contracts with the Energy FinAnswer program is performing quality
control? [REVIEWING OT]IER ENGINEERING WORK AS OPPOSED TO PERFORMING
ENGINEERING ANALYSIS AND POST INSPECTIONS]
Next, I'd like to get your thoughts on how the Quality Control Review works for you.
a. It is our understanding that quality reviews must be completed in 10 days. Is this enough
b. Do your peers provide you with constructive feedback in their quality reviews of your
work?
How do you think this built in quality control system affects the quality of your work?
Has this process changed the way you do business for other non-project related work? If
so, how?
Section 4: Measurement and Verification
14. Next, I have several questions asking about the project post-inspection process for the Energy
FinAnswer Program.
a. What does the process entail on your end (e.g., visit the customer site, activities on site,
reviewing baseline consumption, observing practices, communications with Iine managers)?
b. Does the program allow enough time and resources to do this task well?
c. How are findings communicated with the customer? With $_PACIFICORP?
d. How are disagreements resolved?
e. How long does this process take (generally)?
Section 5: Customer Involvement
15. Do you conduct similar energy engineering analysis for customers not working with the Energy
FinAnswer program? [IF NO, go to next question]
a. How about with customers not working with any utility program?
b. How does your interaction with customers as part of the Energy FinAnswer program
differ from those customers that aren't participating in any program?
ilon f, dentln j enri Proprief sry-
i$ah+ f n*rgy FiuAnswet Evaiuatior Rep.l$
Apoendir C - Frocess Evaiuation Suivsy lns$uniri'its
Rocky Mountain Power
Exhibit No. 5 Page 1037 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
c.
d.
fragc C-lii:
Nd\V$il,qNT
About how often do you conduct engineering analyses for projects not participating in
any progrilm that you think would qualify for the Energy FinAnswer program, based on
efficiency?
i. [PROBE TO GET PERCENT OF PROJECTS IN A YEAR]Thinking about just
2011, about what percent of energy analyses that would qualify for the Energy
FinAnswer program were completed without any program at all?
ii. Of those projects, how similar was the analysis in terms of the installed
measures and projected savings to the analysis performed as part of the Energy
FinAnswer program?
d. Why did those customers not participate in the Energy FinAnswer program?
16. What questions do customers typically have when you come in to do an analysis? Any concerns?
17. What challenges do you face in addressing customer questions or concerns towards the
programs?
Section 5: Business Impact
18. How has participation in this program impacted your business, if at all? [IF RESPONDENT
ALREADY ANSWERED THIS IN SECTION 5, DON'T ASK AGAIN.]
a. [PROBE] Does the program encourage additional engineering analysis, creating more
business that is not funded by &PACIFICORP?
b. [IF YES] Using a scale of one to five, please rate the influence of your participation in
the Energy FinAnswer progftrm on this additional engineering analysis,where one is no
influence at all and five is a driving force in your sales.
Would you continue to offer the same services to customers if the program no longer existed?
a. tIF YESI What percent of your current work do you think customers would still be
interested in receiving if the incentives were not available?
How does the Energy FinAnswer program differ from other similar programs that you may be
involved with at other utilities?
a. Is the amount of effort required on your part different?
b. What about the amount of paperwork?
c. How is it different for participants?
Rocky Mountain Power
Exhibit No, 5 Page 1038 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
r9.
20.
Section 7: Satisfaction with Program(s)
lNow, I HAVE JUST A FEW MORE QUESTIONS.I
21. Do you use the $-PACIFICORP vendor website?
a. [IF YES, follow up] How often do you visit the website?
iloafideniral an o Pinpr'ef sry
iiaha fnergy FinAnswer Evaiuation Repo(
Apoendix C - Frocess Evoiuaiion Suivey lns$iimei'its
Page 0-3i
N&\d${-ANT
b. [2"d follow up] What kind of information do you look for on the website?
22. On the whole, are you satisfied with your experience with the Energy FinAnswer program, on a
scale of 1 to 5 with 1 being very dissatisfied and 5 being very satisfied?
a. What would you change to make the initial site visit and energy analysis process work
better?
b. What would you change to make the Quality Control Reviews work better?
c. What would you change to make the post inspection process work better?
23. Is there anything else you'd like to tell us about your experience?
Section 8: Gas Card Offer/Closing
As a thank you for your participation in this interview, we'd like to offer you a $50 gas gift card. Would
you like to accept this offer?
(If yes) Which type of gas station would be most convenient for you?
INOTE: The following do not offer gift cards we can order: Loaf N'Jug, Kum & Go
The following companies DO offer gas cards: Exxon-Mobil, Sinclair, Conoco, Pilot-Flying J,
Shell, Valero (Diamond Shamrock), Phillips 66, Chevron-Texaco, Maverikl
To what address should we mail the gift card?
Thank you!
Con i,deni.rai erC F,rprefory
idahc Ensrgy FinAnsrrer El,aiuation Report
Aprendix C - Process Evaiuatiori Silivey lnsirumei*s
Roclq Mountain Power
Exhibit No, 5 Page 1039 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
Flage 0-3$
ss\u,${-Ax\T
Roclry Mountain Power
Exhibit No. 5 Page 1 040 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
D.1 Participant Results
Total
a
1
$atisfaction w'ith the E FinAnsner rarn Overall
L2
Table 5. Fartici
velY sa tisf ie*,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,.,.,,,,.,,,,,,,,,,,,.,
,,,SotttU,rw'hat,SU+i*1iffi,"',', '.' , .
Neither satisfied nor dissatisfied
::::::::::::::::::::::::::::::::::::::::::::::::l::::::::::.. ::::i::::::::::ii::::::::.:j::.j.. : : 1
,,,ffiffi#,d!$satiefied, ",,,,,,,,,,,,,,,,,,,,,,,,,,,,
Very dissatisfied
58%
:.,:::::::::::::r:iri:ir:rlllli:l:li:l:i:i::::i:::i:!:l:::::::::::::::::::l:::::::::::;:::::::::::::::::
8%
:iir:ii;lii::iiiiilffi i:;liliirlii:i:ii:iiiii:i::iixi$%:i:
7
: :il:1::!:::
1
,ttr,..;.&ii.o:li
0 0%
Total 72 100%
Table 4. Fri lndustry nf E FinAnsr.r'er Survey Respondents
Table 6. Partici Means of Learning About Energy FinAnswer
,Tlade AJlYrt,vgttdo'r9"-1.,.-c.,,9llot=1,,!.,1.,,91,.,,,,,,,,,,,,',,,,,',,,,,tt,,,,,,',,,,,,,t,,',,,,,,,,,
lA fifiti6j:rx.::siffil*!*lfl,fit*ti
4
*
2
ti
1Another Business Colleague
12 100.00%
Tatrle 7. Itre;rsons fnr Energ,v FinAnswer
ill ffi$Hiiffiffi.iiuniii a $
0onfiCsnf ,iai airo ilrrr*rieta,1.,
iria[u fnergy FiiiAnswrr Evaiuatiun ReFli't
Ap$erndi:< l-': - Proccss Hvaiuaii*n Ilstsiitlii i:in,Iings
r$iiu ii- i
N$\J$SANT
Roclry Mountain Power
Exhibit No. 5 Page 1041 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
2
1*,;i ;;.;.
1
,:l :,:,:::::::::::::::::::
77 100.00%
Table 6. Non-energ.v Benefits of Installed Measures
lnstallation Status
Tlable 10. tr'articipant Satisfaction u'ith the Po*t-Installatiun Inspection
Very sali;fied ..
'.ffi**f.tut*atisfi ;....................i.., ,.,,iiiiiiii.,.'.,',,i. i
Neither satisfied nor dissatisfied
,veil,"q,l,ejetitriediii.h[$fji k*
1
*..1j;.1.*1.:rU
1
tl:iriririririririt
Total 12 10Oo/"
Tahle 11. Firctors In{luencing Proiect Dc:cisio*s
Corporate Policy for
* ut"trrI,"l,I:t'T
r{e:rlcIIHiiili+alncrpmlpn
F;iiil;iiiliih
Program Incentive
2
T:::::.:.:.
1
iiii:::iiiiiiii
U:,:1i::,
0
::ii::-*::flii,
0
4
: . aatat::.t:: ::!:i:::!:
1
:liltii:ii:i:l:l
.iiii:i':I::':i
ilil:i :,i:,:,:'r'r
2
X$
J
1
*:::::l:::::.: l:
a
iiiiiiiiiiiiiiiii-
!t::::.:::..:
ttttttttil::::lni
1
:i:lii:s
0
J
::::::::
*i
4
0
: :.t t : l
iitiitiiiitt::!t;:;:ti:i:i;:!iriii!::::
0
0
:iii:.:t;::aiiiiii.i:j,.::li
i'*ffi
0
Cslii'Cs,,.1i,s j xlc,s,'oi:rieia,1,
isailo Irergy FiriAnsi.rer EvaiLratior Rep+{
Api:s:nilix $ ^ Procrlss Evaiuaiitn Dekiieir'iin,lirgs
N$V $fiA N T
Rocky Mountain Power
Exhibit No. 5 Page 1042 of l365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 12. Installations in the Absence of En FinAnsruer
Tahle 13" Fotential
VFDs
Don't Know/Not sure
4
:.::.:i.i:.::,:,:ri;r':,:,r':.:.rrrr:r:.tt:,;:i::rtsr:1.:.::I::::::.:::
1
J510
:,:,:,:,:i,:,:,:,:,:,:,:,:,:,:,:'1.].:.:,].]l:,:.1.::],:]n j:. j:]!
i:!i'f,i;l!:!:!:!::l:::: i::::::::::::: :::.::l::i
Iti!:!ZO!:!:!:,:!:! ..:::::.::j::...:..: :: i
8%
18%
Total 100o/o
elliiil
D.2
,,,,,,,J,--9,,1-,.?..y0,!-.,,T,,9,,,.1,9...;y--"9"19,,s.,Hi.
bllLr_,,,,i:r,:,,9,,::,:,,,,::._:,.,,,*,,:,,,:,:,:,,L,
iiiiiii#6,1,e,Effi1.i iitiiiffiiiiii.iiiiis
...Rssg:**-u..*{qtigl hv*.qg.1,t*-.1."o:......l**-- o-
N e ar - P arti cip ant Re sult s
'I'able 15. Near f'articipant Motivatinn for I'articipating in Ene
To save money on electric bills 0
,,,,nfo,:,ffi[*lin:;tffiitaniiiE$Ei$t ,,,,,,,,,,,,,,,,,,,,,,,,,,fj i :::::,,,:i]'
Recommendation by contractor 1
1
0
0
F'inAnsyrer
1. 17"/"
n:::::::::::::::::::::::::::::::::::::::i':lffi !l: r' !r l::::{::::::::::::::::::::::::::::::::::::::Il',::i6',:',:.:.::.r.',::i:jr::i,:,:,:,:,:,:,:,:,:,:,:,:,:,::,:,:,:,:,:,:,:,:,:,:,:,:i:,:::.:,:,:,:,:!,:,:1:::,:::,:::.:.:,
1 L7"/"
$onfic'sniiai ano Fnrpdelaq,
idail* ilrsrily FiiiAnslver Evaliietion Report
AFlrernrlix il ^ Prooess Hvniuation llet$iicd irinijincs
Table 14. Reasons for lnterest in Energy FinAnswer
Pege il-li
N$V$ilANT
D.3 N o n - P arti cip ant Re sult s
Rocky Mountain Power
Exhibit No. 5 Page 1 043 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
iifu"*+ffir*g, ,',:iiiiiiiiiiiii..,, : :.,,...,................... ,, ' ,,,........,...........,,
Health care
ibr"tiir."o#ffi"t *
"fu*ed,'*-11.,...i...,..,.'. ......iii......,,fX'.ii.iii
Professional, scientific, and technical services
.*er. iaa*a*ehffil',.ii.ii..i.....',,',..,i...........,,
Arts, Entertainment, and Recreation
..nr-la***iii:i;iiiiiiiiii: , r.ii:ii.i.i.:.. ,::,,,:,;i,;,-l.jiiiiiii,ii.i,i, .,,.iit:l.iiiiiiii
Educational services
,..,*"ia* Utfttio*',,,,,,,,,, '""':" ,,,. , '.',i:'.,i...................... t'l:..................,.,
Food services
7
':: -r::::::::::::::::::::.,
{il:]:::i
a
'l::r:r::::::::::::::: j:::::::l::::::::::i:::l:::
1
::.:::::::.lil:titit:,
1
iiii..1..:.
1
ii:r:r:
l:::111
:ii:::.]:::itI
Table 1E. Non*Partici t Avrareness Incentirres and Technical Assistance Customer Class
Aware that Rocky Mountain Power offers Assistance
100"/"
't'able'19. P nls anc{ Services Identified, by Custorner Class
Not Sure/Don't Know
..,1"c*rtireS..,tof nffiC6nt fquipmHt
I rrigation Load Control
- ... -':i:i:::::. - .:::i:i:i:ililiririri!.!::;. :'i.iii:i'iii:i:i:i::::ir.' "'Irflgaflon tsnergy,52YPr"$;;:;:;;;:;i::;:::i::;ir
6
:',::::'!:::!f)
J
:::::,=::
i,;,,i,,I
1FinAnswer Express
Total
Csitfr'criiriiai ar i F,",:riieia,';;
idai'lr:Ireri:-vFiiiAns.-,retEi,ailiati';tRei:i:{
$.1;$qn,iix i] ^ Ptccrlss Er,aiuaiitn DeLeiieii iin'lings
Table 16. Size of Non-Partici
Less than 3 23
10 to less than 100 10
!,tffiiioffp;ife ,,.'$f,c,.,.,.,.,.,.,i., ' .i:,.i.iiiiiiiiii...,,. ..,.,'i.ii.i;,i.iiib .i.iNii:i:i.iiiiiiii
Greater than 1000 0
h,v Numher ot Employees
Table 1,7. Printan, Activitv for Non-Parti .$irms, by Customer CIass
Total
Psse l-,i
Ns\tr$s,qNT
Tahle 20. How i{on-Participants Heard ahout Rockl,Ivfountain Porrer Programs, Overall
,,.P..,1,",,yil:-.p..3lli:ipul'gl*,R;9,,,9,.-\y,Mountain?9y*Dofllti:lfio# u1,suie :,,,,,, --,',,,,jiii,;.,:.'ii...i.i.i.i.ii.i
Rocky Mountaln Power
Exhibit No. 5 Page 1044 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Word of mouth
l."jlx '":llaln Powel newsletter: , , .. ,, ,, :,:rv-.il{v.sip.rr!$,,,.,, .,.r,,.,,,,,.irr.,,. ,,.i,rruri
Trade ally, ve.,Jor, o, contractor
Total L4
Tahle 21. Freferred Method to Learn ab*ut Frograms and Opportunities, ()verall
, ,,I,outuJr,,,'o'n!ain
Po-wer*printed m3,'t9,,1i"",.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,1,*ttt
Phone
Total 54
A<companyi"g bill:
Table ?2" Non-Partici rIi Efficienry Equi t Purchases in Existine Facilitieis
50 TOOo/"
Table 23.rticipant tr.oad Control Strategies in Existing Facilities
Yes, implemented load control strategies between 2009 and 2011 without assistance from Rocky 0
iiiiiiiiliriiriiliiriiiiii.iili-iiliiiii'iil i iiiiliiiii:
44
iiiiiiiil,:,,,1:rll:::::lii,lEi:,iiii:il:iii:!iri::,i
0%
:iiii::--iii
88Y"
!iriri*gc!:!
50 100%Total
Cciiijceriib j,rrs Frcr,prieiary
idai'* [rergy FiiiAnsitrer Evaiiiatiur Rep:i:ii
,a,$SE:n.dix i-i ^ ProCess [vaiuaii6i-r Deteiiei iindlngs
Psce D^ii
S-,s\tr$tANT
Rocky Mountain Power
Exhibit No. 5 Page 1045 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
4%
::!::::::::t:.:.1:::::::1it:.1::!+:1, lii lil:l:lllilll6tr::!
XXrtiiXr ,iri:
45 90%
X*iii jiii*i:i*#t
50 l00o/o
Tahle 24. lrlon-participant S),stematic Evaluations of Existing Facilities
Table 25. Non-Participant Ntctir.,ation for Fursuing Energy Ef lmprovements
2
;.il:r::r:::.r::,.:.ri:::;::i:.:rr.:r:.:,rii:::r:::r:::r.:::.:::r:r.:.::r:::::::::::::::::::rr:::::::rrrrrrrifi:::
1
iii$..
Recommended by contractors/trade 1 0 1
:fl*im*:",s*p"*nttffi pies
Table ?6. lrion-Trarticipant Indication of Further Energy Efficiency Opportunities
Yes, cguld mSke tuture implovemenls 11 2_Z%
Not sure or Refused ,,,.",,,,,",",, ,,,,,,,,,,,,,,,,,",",,,,,12,,,.,,,,,,,,,,,,,, ,,,,,," ."3.*7:,,,50 L00o/oTotal
Table 27. Non-I'}articipaurt Earriers to trmplementing Electric Efficienc-y lrnprovements
Lack of access to capital 1
r:**iiS::;+;;+S*i!S#$!!i!!!n#*S*i!!!!i;i!s!!iiri!$F$*iiii+S!;i.+SiSsii'!si..:iis;i++iS!!!i*!!!iii:.
Total 11
$itilfirillliiiai,lr o Frtrilr reiirry,
ician+ [irrrgy FinAnslver fvailirtioli Renrrt
ir.pll$ndix il - Process [vaiuaiirrn i]$iiirit]C i-indings
Pase l-0
Rocky Mountiain Power
Exhibit No. 5 Page 1046 of 1 365
Case No. PAC-E-14-07
\Alitness: Kathryn C. Hymas
reffiROCKYMOUNTAIN
HFoWERI A o{vrstoN oF PAcFrcoRP
Exhibit No. 5.12
FinAnswer Express Evaluation 2009-20I I
Rocky Mountain Power
Exhibit No. 5 Page 1047 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fnr;al H \iA[.uAT]]oN R p:t ottt' Fo]t Inar*o' s F tx A NS\, v" HR
Hxm*:ss Pn*cI{AM (PY ?009-2StX }
Prepared for:
Itocky Mountain Fower
$RffiI{Y MNI*INTAI${
$FTMilHR
Prepared by:
,*
N &\,f it.& NT
Navigant Consultin g, Irrc.
.1.,375 Walnut Street
Suite 200
Ilor"rlder, C() 803CI2
303.72S.250C
'*tw'lv.naviaant.com
N,farcil 4, i$i3
In p>artnership wit}'i silil$
Energ\r l\4arket lnnor.ations, Inc.
.q3 Coiurnbia St
SuiiE:40(}
Seattle. w-. 9S1U,1
20$.521.1i60
u'l','lv.emiconsu ltins.con'r
$d&\jiil&NT
Roclq Mountain Power
Exhibit No. 5 Page 1048 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
1,. Executive Summary
1.3.1 Key Program Findings..... ..........................2
1,.3.2 Cost-Effectiveness......... .........3
1,.4.1, Overall Process Evaluation Findings..... ................... j........................5
1.5 Program Evaluation Recommendations .............7
FinAnswer Express Program Introduction............ .......................8
2.1,.1, Trade Ally Coordination ...........................8
2.1,.2 Program Participation.................. ..............8
2.1".3 Program Changes from 2009 to 2011 ............................9
2.3 Program Theory and Logic Mode1......... ............10
Evaluation Methodology .......... .................17
3.1 Impact Evaluation Methodo1o9y................... .......................... 17
3.1.1 Evaluation Approach... .......17
3.1.2 Project File Reviews................... ...............18
3.1.3 Sampling Frame Development................... .................19
3.1,.4 Gross Energy and Demand Realization Rate Calculation ............21.
3.1.5 Net-to-Gross (NTG) Estimates.... ............22
3.1,.6 Program Cost-Effectiveness ....................23
3.2 Notes on Validity and Reliability of Impact M&V Findings ....................25
3.2.1, Reducing Uncertainty from Sample Selection 8ias.............. ..........25
3.2.2 Reducing Uncertainty from Physical Measurement Error ...........26
3.2.3 Reducing Uncertainty from Engineering Analysis Error...... ........26
3.3.1 Overview of Steps in the Process Evaluation .................. ........-......27
3.3.2 Process Evaluation Research Questions ..-......-...-.......27
3.3.3 Program Documentation Review ...........28
3.3.4 Logic Model Development............... .-.....28
3.3.5 Process Data Collection Activities................. ..............28
3.3.5.1 Program Staff Interviews ............. .......................29
3.3.5.2 Participant Surveys...... -....-.............29
3.3.5.3 Near-Participant Interviews ............. ..................29
3.3.5.4 Non-Participant Surveys................... .................. 30
3.3.5.5 Trade Ally Interviews.............. .......30
3.3.6 Process Data Analysis and Synthesis.... ......................31
Impact Evaluation Findings ......................32
4.1 Program-Level Gross Savings Results... ............32
4.2 On-Site Verification Results ...........33
2.
J.
4.
[].r.i:.luation r.rf itr>ci<y ]ttr.rttnia!n I\:i.\,e.r's !D FinAnsrvei Ll.>ipress I'rr.rgr;:s {i:ry ?i}09-?-0Iii
5.
r, .u s\r., $ A f-,i Y
Rocky Mountain Power
Exhibit No. 5 Page'1049 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
4.2.1. Demand Savings Results .........................33
4.2.2 Energy Savings Results........ ....................34
4.3 Program-Level Net Savings Results ..................37
4.4 Cost-Effectiveness Calibration and Ana1ysis................... ......38
Process Evaluation Findings .....................41
5.1.1 Program Satisfaction ...........41
5.1,.2 Program Awareness and Motivation............... ...........42
5.1.3 Program Participation Process........ ........43
5.1.3.1 Pre-Installation ............... .................44
5.1.3.2 Installed Energy Efficiency Measures ...............45
5.1.3.3 Post-Installation.............. .................46
5.1..4 Program Influence.... ...........46
5.1.4.1 Influential factors .......47
5.1..4.2 Free-ridership ................. .................47
5.1.4.3 Spillover ......................49
5.1.5 Further Energy Efficienry Opportunities and Barriers .................50
5.2 Near-Participant Findings..... .........50
5.3 Non-Participant Findings..... ..........51
5.3.1 Awareness of Rocky Mountain Power Programs ..........................53
5.3.2 Non-Participant Energy Efficiency Improvements............... .........56
5.3.3 Further Energy Efficienry Opportunities and Barriers .................59
5.4.1. Overall Satisfaction .............61
5.4.2 Program Awareness and Motivation............... ...........52
5.4.3 Training, Roles, and Communication.............. ...........62
5.4.5 Customer Invo1vement................... ......... 63
5.4.6 Effects of the Program............... ............... 63
5.5 Overall Process Findings..... ...........64
Program Evaluation Recommendations.. ..................69
Appendix A: Glossary of Terms
Appendix B: Net Savings Methodology
Appendix C: Process Evaluation Survey Instruments
Appendix D: Process Evaluation Detailed Findings
6.
ILveir:aiion r.r[ Roltv h4r:trniilin Pt)rr,rx'$ ll.) IrinAnsrvtir li:xpress l:]rr:grilnr (FY ?(:]09-.?-i]1 II
rr* fs$$AN$ T
Rocky Mountiain Power
Exhibit No. 5 Page 1050 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
This report provides findings and recommendations from the impact and process evaluation of Idaho's
FinAnswer Express program for program years 2009 through 2011. These results serve to validate
reported savings and inform improvements anticipated for future program rycles.
7.7 ProgramBackgrounil
Rocky Mountain Powe/s FinAnswer Express program offers prescriptive incentives to commercial and
industrial customers for the implementation of Energy Efficienry Measures (EEMs) resulting in improved
efficiencies to lighting, HVAC, and motors in existing facilities or new construction projects. The program
also includes a provision for custom incentives for EEMs that are not listed in the program's prescriptive
incentives tables.
Further information regarding Idaho's FinAnswer Express program, its program theory program
delivery methods, and program participation is addressed in Section 2: FinAnswer Express Program
Introduction.
7.2 Eoaluation Objectioes
The Impact and Process Evaluation of Idaho's FinAnswer Express program serve to validate reported
savings for program years 2009 through 2011 and inform improvements anticipated for future program
cycles. This evaluation addresses the following objectives:
" Verifying gross and net site-level savings for completed projects;t
, Reviewingand documentingprogramoperations/structure;
> Understanding motivations of participants and non-participants;
" Providing data to support program cost-effectiveness assessments; and
" Identifying market and customer barriers as well as areas for potential delivery improvements.
1-.3 lmpact Eoaluation
Evaluation metrics and parameters reported through this study include:
, Gross and Net eoaluated program demand and energy savings estimates and realization rates for
completed projects; and
" Energy usage profiles for Commercial and Industrial (C&I) technologies metered through on-site
Measurement and Verification (M&V) activities.
The evaluation team characterized savings as "reported" and "evaluated." Reported savings present
project savings estimated at the time of measure installation. Evaluated savings present energy savings
1 Site-level savings as opposed to generation-level, which takes into consideration transmission and distribution line
loss savings.
lLvaluetiun ol: Iiot:k_y N4i.runtain |b*..re1',c lD }rin.{nslvsr lirxl.rress l:)rr.r6uru: (l]Y ?0{}9-?0I I )
Rocky Mouniain Power
Exhibit No. 5 Page 1 051 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
verified in a facility at the time of this evaluation. Section 3.1: Impact Evaluation Methodology details the
savings calculation methodology.
1.3.'! Key Prograrn Findings
In aggregate, the Idaho FinAnswer Express program achieved lower demand (kW) and higher energy
(kwh) savings than is reported in the program tracking database.
The 2009 through 2011 gross program demand savings realization rate was 98 percent, and the gross
program energy savings realization rate was L01 percent. Table 1 details the demand (kW) and energy
(kVVh) realization rates for Idaho's FinAnswer Express program from 2009 through 2011. Realization rate
details can be found in Section 4.2: On-Site Verification Results.
Tahle 1.. ['rergrarn-L,evel Cross trlealization I{ates ft.lr trdaho FinAnswer Hxpress (2009-?011}
2009
i::20qfl
20t1.
22t.0 184.1
ffi fi$..,,.....'iiii,,iililr$u:ls
666.1, 702.0
83"/o
iiiiffiffil,aj.i
105"/"
i:i:i:iir:;:::i::iii:i::ijnt:t:r:ii:tlt!lt:tli:l:i,il::illirlii:::::i:::::::i::::i:le.,
ii.r,..i,..,..........riii..i..itnzy;2,314,312 1.04"/o
838,394
:3frrs#ffi3i
2,233,973
742,956 89%
1.,254.3 1,228.4 6,607,1t9 6,665,420 L01."/o
The Evaluation Team calculated a Net-to-Gross (NTG) ratio of 0.67 for the FinAnswer Express program,
for program years 2009 through 2011. The methodology used in this calculation is provided in detail in
Section 3.1.5: Net-to-Gross (NTG) Estimates. Table 2 provides energy and demand savings and realization
rates for Idaho's FinAnswer Express program from 2009 through 2011 with the Net-to-Gross Ratio
applied to gross savings and realization rates.
98"/"Alt
Table 2. Program-l.evel Net ltea]ization llates for kiaho FinAnsw,er Ex {3009-20i1 }
2009
ffin
2011.
:::l:::::i::
:
221.0
rlli:i,.$*illi
666.1
123.9
ffiS,4 :
iiii:i=:::i:::.lili..i:::i:
472.4
567o
6e%
n1 0/
838,394 500,016
i.=-3Es4jr6arrffil'121.*#5e;a:2,233,973 1,557,532
60%
re**..;ll
70"/"
t,254.3 826.7 66%6,607,1.19 4,486,501
Table 3 shows the distribution of reported energy savings across all measure categories, and the
realization rates for those measure types accounted for through this program's evaluation. An 'N/A'
indicates that the measure category was not part of the evaluation. These measures accounted for over 85
percent of all reported savings. These measure-level realization rates are illustrative and do not represent
statistically significant results; these measure level realization rates should not to be used for future
planning purposes.
68%A11
N $N $il,.\ \j "S
Table 3. Measure-Level ltealization ltates for ldaho FinA.nslver Ex
Rocky Mountain Power
Exhibit No. 5 Page 1 052 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
(2009-2ff1"1)
Lighting
tV.FD.,;,.,.,;,;,.,.,.,.,==
HVAC
ffi --.........i........i"i:::
Envelope
rrtrV[tl,t.i}li::::::::::::::::tt;ttt:rt:t:t ;i;i
3.480,828
i;@i;e
621,580
:::::is$it&::::
::::::::::::::a::::a::::::l)i:l::::::::a:::a::
79,754
iiiiiiiMis99.rir::::
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iiiiiiii:iiiiifiss%l
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ttiiii:iiiiiiiii:iiNA iill
NA
101ryo i
'!"3.4 Sost-Effectivsness
Using the Company's model for calculating the program's benefit-cost ratios, the evaluation team
calibrated and updated cost-effectiveness models using five primary cost tests: PacifiCorp's Total
Resource Cost test (PTRC), Total Resource Cost test (TRC), Utility Cost Test (UCT), Rate Impact Measure
test (RIM), and the Participant Cost Test (PCT).
As seen in Table 4 through TableT,Idaho's FinAnswer Express program was cost-effective by the UCT in
all years. In addition, the TRC did not pass in 2011 and the RIM did not pass any year. The TRC cost-
benefit ratio in 2011 is 0.91 due to high incremental costs and relatively low savings attributable to
measures installed. The incremental cost of measures installed in 2011 is approximately 160 percent of the
incremental cost of measures installed in 2010, while the net evaluated savings for 2011 is approximately
60 percent of the savings reported in 2010. It is rare for the RIM test result to have a cost-benefit ratio
greater than 1.0 for DSM programs as RIM tests measure the effect of DSM program implementation on
customer (average) rates, and DSM programs cause average customer rates to increase slightly. Details
regarding cost-effectiveness calculation methodology can be found in Section 3.1.5: Program Cost-
Effectiveness.
Tabie 4. 2ilt)!i ldaho FinAnrwer Ex Benefit-Cost Ratios
Total Resource Cost Test (PTRC)
, Tobal Resource,Cost Test:,{TRCI::r::::::,:: ::::
Utility Cost Test (UCT)
Participant Cost Test (PCT)
742,966
.:::.:.::.::..i..::74?,
j9ffi
742,966
:::::::aa:::::f$i5.$
742,966
497,787
....suil#sfl
497,787
7,;7AT
497,787
$337,048
lCI r;om
$255,104
ii$57?#98
$243,676
$436,403
$396rr38
$396,730
ffi 6:7,,3A,
$s62,505
r.29
.t.i.18
1.56
:O169
2.31.
Rocky Mountain Power
Exhibit No. 5 Page 1 053 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymasi
N $\J ${* A.N T
Tahle 5. 201S Idaho Fin-A"nsrver Express Benel:it-Cost Ratios
Total Resource Cost Test (PTRC)
f ota i Re$i eE.iiEustiifrest.iflB#},i iiiii. ..: -:::: ::::::::::::::::::::::::::::::::::::::::::::::::i:i:i:i:i:i:i:i::::,,.:::.:'..
Utility Cost Test (UCT)
Rare lffipaftiitresi..(8ffii,,,,,,,
Participant Cost Test (PCT)
$934,4M
fi620,490
2.75
u.iffi.ri.i*.ll
3.76
.sr*li..liili.i
3.30
Table 6.2011 Ldaho FinAnsrt'er Ex Benefit-Ccst Ratios
Total Resource Cost Test (PTRC) 2,31.4,312
r:;:.:^ii i;';:zeJ.[4t Jr.{
i,iis,iii
;ti$r$*1$rf
2,314,3t2
1,550,589
::i:iliiii!!!iitrS'50rffi::i:::::::::::::::::::::::::i::r,r::r::::::::::::::::::::::::::
1,550,589
.i.i.i.i.i.i.i.trS$gis8o:::::::l:::::::::::::::::::l:::ii:;::::::::::::::::::::::::::::
1,550,589
$1,505,332
;.i.i.iI.:i$I$SS,ffiE.iii.iili
l:l:l:l:l:l:l: :i.l.il:l:l:l:l:l:l:l:l:l:l:!.1:l:::::l:ll:l:l:l:l:l:l:i; ltl
$700,724
iirii iS26.;6s2iiili,:
$1.,733,334
$1,512,245
::::::::::::::::l:l::ltiil i::it:i:::i::::::i:i
$r,374,768
i.iil.iiitiiilsilbif,,&iffiifr.':i.i.iiiiiliiXi;.::i:il0i[il:iiii:ili:i:ii
$2,186,M0 1.26
#[utfr#s$$eiiiff$l+ii $ffi
Utility Cost Test (UCT)
Participant Cost Test (PCT)
Tatrle 7.2009-2t)L1 Combined ltlaho FinAnswer Express llenefit-Cost ILatios
6,666,420
r,{j,@t,t,ttt,t'
6,666,420
;;f,*&*U111.
6,666,420
4,466,502
i:::.::i:::r::ii{laf 6i$ffi
4,466,502
:::::+i:::l:*iffiffi
4,466,502
$2,776,824
::$zlrrrr;ga*.:.iitl
:::;::iii:t:::::!:!:::t:!::i::;:t:iii:iii:ij:::t::::i::iiiiiii:
$r,576,3r8
ig.A;e$.$j248.,.,,,i,
:::i:i:l ;,::::::i:::::::::::i:::i:::i:r::::::l::::::::i:i:ii :,1
$2,883,058
$4,51s,953
.li1ii$#tff Ej*$i$..iiii,l,i::::;::i:::ii:;,i:lj,:*:i::i:i:: j:i:l:i:::::i:::i:i:l:l
$4,105,411
.$4rff5,411
]:],],:],:,],],],:,:],],j,j,].]::'::':i]i':':':,i:':':':':':'
$s,741.,487
r.63
2.60
iiii.iili,,,ioiE3 ii*i
L.99
Rocky Mountain Power and the Idaho Office of Energy Resources (OER) have an Energy Efficiency
Incentive Agreement in place to maximize the impact of public school energy-efficiency projects.2 The
Agreement provides funding to promote the installation of additional cost-effective energy efficiency
measures in public schools within Rocky Mountain Power's service territory. As such, total energy
savings reported (and associated costs) for the Idaho FinAnswer Express program include measures not
incentivized by Rocky Mountain Power. To reflect cost-effectiveness that can be attributed solely to
Rocky Mountain Power, an alternate scenario was developed. In this scenario, all energy savings and
2 Rocky Mountain Power. 20L1 Energy Efficiency and Peak Reduction Annual Report - ldaho. August 3, 2072. Accessed
from
ill lterror'" Apoer..dix-od(.
lLvi-rh.iation <)i: i.lull.-.,i l\4.r.rr.rnioin [\-rwr.',r:'s ii-) I]inAns,.vur i:,ri:*:ss i:trr:6i;im iir\' :i.!09-?i)l'i i
iNc\\,r${:ANT
associated costs from public school energy-efficiency projects were removed to conduct the PTRC, TRC,
and PCT cost effectiveness tests.
Since public school projects completed through this Energy Efficiency Incentive Agreement occurred in
2011 only, this alternative scenario only affects cost-effectiveness results for program year 2011 and the
combined 2009 through 2011. As detailed in Table 8 and Table 9, respectively, the FinAnswer Express
program passes all the cost-effectiveness tests in this alternate scenario. The alternate scenario's benefit-
cost ratios are greater than those of the primary scenario/base-case scenario due to the higher costs (as
compared to associated energy savings) for the school projects that are not included in the alternate
scenario.
Table 8" 2011 ldaho FinAnswer rerss Benefit-Cost Ratios tAltennate $cenario)
Total Resource Cost Test (PTRC)$860,740
!iiiirri;riirSfltr
$u7,429
Rocky Mountain Power
Exhibit No. 5 Page 1054 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
$r,1.69,700 1.36
llffii241
2.00
1,771,778
ti#s;iI.e
::::::::::::::::::::::::::::::::::::I,:ii:
1,771,778
t,1.87,092
.illt87rr09g
::::::::i:::::::l::::::::::::::::::::::::::::::::
1.,1.87,092
I:.:.:.:.:.:.:.:.:.: :.:.:.:.: :.:.:t:r:: :.:.:::.:
9t,692,659
Table 9.2009-2t]L1 Ccrnbined tdaho IiinAnsw*r Ex s Eenefit-Cost fi.atios (Alternate Scenario)
Total Resource Cost Test (PTRC) 6,123,887 4,103,004
ti.:ti::tl::t:::,lii::::::i::::::::ii:::::::::::::::::,!:f llNiifflfi .ii.i.
4,703,004
$2,1.32,23L
iiffi,iilot#$tiitt*.i.i
fi1.,997,153
$4,173,408 1,.96
fis,247,707 2.63
7,4 Process Eaaluation
The process evaluation sought to characterize the FinAnswer Express program from the perspective of
program managers and administration staff, participants, near-participants, and trade allies in order to
identify both existing strengths and areas for refinement that may better serve the Idaho C&I market in
future years. It also included consideration of the perspective of non-participants to identify the level of
program awareness and the barriers experienced.
From May through August 2012, the evaluation team surveyed or interviewed 176 customers: 52
participants, one near-participant, and123 non-participants. The evaluation team also conducted in-
depth telephone interviews with 10 trade allies - active firms in the Energy Efficiency Alliance (EEA).
These surveys and interviews provided information that was combined with information from program
managers and administration staff interviews to create a comprehensive view of the FinAnswer Express
program from 2009 to 2011.
f .it.1 Gverall Procsss Evaluatlom Findings
The program is baseil on sound theory and design. The FinAnswer Express program in Idaho seeks to
improve energy efficiency at commercial, irrigation, and industrial sites. The concept is that providing a
quick, prescriptive incentive will help customers overcome cost barriers. The design is indicated in the
program logic model in the program overview. The program is in line with best practices for non-
[].r,ah:ai'ioii <ii Ri;r:i<v \4r.rilntain []i,;rnre.i:'s li] irinAnsivrir ii,xprr.rs.* !:'rr,ri:i:r.ur {irY ji)i}9-201 i'i 5
si .s\v $ il,& hl T
Rocky Mountain Power
Exhibit No. 5 Page 1 055 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
residential incentive programs. These practices include: establishing a trade ally network, making
incentive tables available, updating incentives with changes in markets and codes, and having quality
control measures in place.3
The program met or exceeded enery saoings targets and goals for progratn years (PY 2009 through 2077.
1n2011, the program introduced an overall energy savings goal of 1.,795,547 kWh; the program reported
savings of 2,233,973 k\Atrh in 2011 exceeding this goal. In 2009 and 2010, the program did not have overall
savings goals, but had contract targets with the third party administrator; overall third-party
administrator targets were met in 2009 and 2010.
Program administrators anil fitanagers haoe the resources and capacity to implement the program ns
planneil. Program administrators and managers indicated that they had the resources and capacity to
implement the program as planned. Program participants and the near-participant did not identify
communication delays that might indicate resource or capacity constraints. Participants who contacted
Rocky Mountain Power indicated that the representatives were knowledgeable and timely. Trade allies
indicated that they had a primary program contact to which they could reach out and receive prompt and
assistance.
The program is usorking as intended for participanfs. Both participants and trade allies describe the
program operating as expected from the logic model. Participants mostly find out about the program
from trade allies or directly from Rocky Mountain Power representatives. Participants are influenced by
Rocky Mountain Power incentives, saving energy, and saving money on energy bills.
Participants are mostly satisfied, keeping their equipment in operation, and achieaing expected enery
saoings. When asked to rate their overall satisfaction with the program, 92 percent of respondents were
satisfied. The majority of respondents indicated that the equipment was meeting energy savings
expectations (73 percent) and also providing other non-energy benefits (85 percent). The most commonly
cited non-energy benefit was improved lighting quality.
Customerc iilentify high costs and lack of access to capital as barriers to further action to rcduce enetgy
consumption and demazd. Customers (participants, near-participant, and non-participants) who thought
there were further actions that their firm could take to improve electric efficiency were asked what might
prevent them from moving forward:
" The most common barrier indicated by customers was high costs: 71 percent of responding
participants, the near-participant, and 63 percent of responding non-participants.
" The second most common barrier indicated by customers was a lack of access to capital:29
percent of responding participants and 5 percent of responding non-participants.
, In addition to these barriers, the near-participant identified long payback periods as a barrier;
non-participants also identified long payback periods, lack of interest of senior management, lack
of information on savings and performance, and time/convenience constraints.
, More telling is the portion of respondents who stated that there were no further actions that their
firm could take to improve efficiency: 48 percent of participants and 73 percent of non-
3 Quantum Consulting. 2004. National Energy Efficiency Best Practices Study Vol. NR-1 Non-Residential Lighting
Best Practices Report. Submitted to California Best Practices Project Advisory Committee.
ILr,aluotii:ril ol ilor:k.,i l\,Lr-rrirrio.in l\rlr,et's l l.) irin-Ansivtir i:r.x1.rress llrr-r;1ir*nr { FY :}i)09-?-i}l i }
Rocky Mountain Power
Exhibit No. 5 Page 1 056 of 'l 365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas}'I E\V E .il,q N T
participants. These responses indicate that one barrier might be that the eligible customer
population is not aware that measures can be taken to improve efficiency at their firm. Given that
they believe there are no other opportunities, it may be a challenge to gain their attention and
educate them otherwise.
7,5 ProgramEoaluaiionRecommendations
The evaluation team suggests the following to continue to enhance the efficienry and effectiveness of the
FinAnswer Express Program in future program cycles, as well as improve the experience for participants,
trade allies, and program staff:
, Recommendation L. Review marketing messages and channels to engage commercial and
industrial customers who are not aware of efficiency opportunities. Half of participants and
three-quarters of non-participants did not believe there are additional opportunities to improve
electric efficiency at their firm. Marketing collateral that educates and challenges customers to
reevaluate their position may be necessary to reach these customers. Reaching new customers is
essential to ensure long-term success of the program in cost-effectively meeting energy savings
goals.
> Recommendation 2. Continue to nurture and develop the trade ally network. Vendors are a
critical program delivery mechanism for post-purchase incentive programs, like FinAnswer
Express. Third-party program administrators, serving as Trade Ally Coordinators, should
continue their efforts to develop and nurture strong vendor relationships and to build additional
vendor relationships. Strong relationships encourage trade ally vendors to take the time to
market the program effectively.
[],vilh.r;rtion r.:f Ilortv Jvti.rtintain l\r,wer's !i) Irini\nsivsr ii:xprrr:ss l:rrr.rgi:nm {FY ?i109-?"01 1 )
jN$V$il,,\ $N T
Rocky Mountain Power
Exhibit No. 5 Page 1057 of 1365
Case No. PAC-E-14-07
Wtnessr Kathryn C. Hymas
This chapter describes in detail the FinAnswer Express program as delivered in Idaho from 2009 through
2011. Changes that have occurred over the last three years to the Idaho program are also explained in this
chapter. In addition, the different models for participation are described and then program theory and a
logic model are discussed.
2.L ProgramDestiption
Rocky Mountain Powels FinAnswer Express program offers prescriptive incentives to non-residential
customers for the implementation of Energy Efficiency Measures (EEMs) resulting in improved
efficiencies to lighting, HVAC, and motors in existing facilities or new construction projects. The
program also includes a provision for custom incentives for EEMs that are not listed in the program's
prescriptive incentives tables. Customers are eligible if served under Rocky Mountain Power's general
service rate schedul es 6, 6A, 7, 7 A, 9, 12, 19, 23, 234, 24, 35, and 35A.
2.1.1 Trade Ally Coordination
In both the pre-purchase incentive path and the post-purchase incentive pattr, the customer may work
with a trade ally. From 2009 through 2011, Nexant, Inc., and its subcontractor Evergreen Consulting,
provided trade ally coordination and application processing for the program as the program Trade Ally
Coordinator. The Trade Ally Coordinator recmits, trains, and maintains a network of trade ally vendors
and contractors, who submit a participation agreement to request to become an approved vendor. Upon
approval, trade allies can promote the program and are listed on the Rocky Mountain Power website as a
participating trade ally. Some trade allies will work with the program for multiple measures, such as
contractors that install both lighting and HVAC; other allies specialize in just one area, like shops that
conduct green motor rewinds. This trade ally network (known as the Energy Efficiency Alliance (EEA)),
along with Rocky Mountain Power project managers, functions as the primary channels for program
delivery.
2.1.?, Program Participation
The specific eligibility criteria and requirements for each type of equipment incentivized under this
program are provided through program brochures and tables. Incentives are paid upon completion of the
project and are capped so that simple payback is not less than one year. If incentives reduce simple
payback to less than one year, incentives are adjusted to a simple payback of one year.
Rocky Mountain Power project managers work directly with customers who need additional engineering
assistance; engineering consultants are contracted to support these projects and ensure that savings are
properly estimated. Rocky Mountain Power seeks to match customer projects with the most appropriate
program. Thus, these customers may have started projects within another program offered by Rocky
Mountain Power, but in the process, it was determined that the customer's project was a better fit with
the FinAnswer Express program.
Lighting retrofit and custom incentive projects must be completed through a pre-purchase path, where
the customer is involved with the program before purchasing equipment; other projects can be completed
through a post-purchase path, where the customer submits information for an incentive after purchasing
equipment.
ILvirluotii:r'i <.r{ itor:kv \,lr,rtrrriain l}tx.+er's li.) }rirtAnsivr,:r ii:xg.rrr.rss ltrr.r6ii;rirr (FY 2i)t}9-?-{11 .1i
i[:i $S. \. i $ $+'\ .S $. | "\*i\.i "+ \ \J i s - .i.,\ t\t Il\,+ \'tr I\*.$Jt'l\ $,
Rocky Mountain Power
Exhibit No.5 Page 1058 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
The majority of participants complete projects through the pre-purchase incentive path. These customers
often hear about the program through a vendor or contractor who is part of the EEA, but they can work
with another vendor. Trade allies, as part of the EEA, will work with a customer to specify a project and
prepare a Letter of Intent (LOD, which is a formal but non-binding indication of intent to go forward with
a qualifying project. The trade ally then works with the Trade AIly Coordinator to review cost, savings,
incentive estimates, and customer eligibility.
There are specific tools, such as a lighting calculator, developed and distributed by Rocky Mountain
Power, to enable the trade allies to accurately estimate savings and potential incentives to aid in customer
decision-making. If the estimated incentive exceeds a specified threshold, the project may be flagged for
pre-inspection. The pre-inspection serves as a baseline to ensure quality savings estimates by verifying
the number and operation of currently installed equipment. For example, a lighting project pre-inspection
would entail a walkthrough at the customer site to document the location and current lighting ballasts
and bulbs of all lights as well as operating hours. Both the customer and Rocky Mountain Power then
sign an Incentive Agreement and the customer completes the project. The customer or trade ally then
submits project documentation noting completion of the project to the Trade Ally Coordinator.
The post-purchase incentive path may be used for non-lighting retrofits or new construction equipment
purchased through trade allies or other vendors. For this project path, the customer makes an efficient
purchase that meets the program requirements and applies for an incentive through Rocky Mountain
Power after the purchase has been made. After purchase and installation, the customer or trade ally
submits project documentation noting completion of the project to the Trade Ally Coordinator.
Post-inspections are completed for any project that exceeds the inspection threshold. This post-inspection
verifies that incentivized equipment is installed and operating as proposed. All final project
documentation is reviewed and processed before a check for the incentive amount is sent to the customer.
2.1.3 Frogram ChanEes from 2009 to 2011
There were no changes to the program from 2009 to 2011.
2.2 Program Participation
From 2009 to20L1., there were 174 FinAnswer Express projects completed in Idaho: 56 projects in2009,46
projects in 2010 and72 projects in 2011. Through 2011, the program reported 6,607 Ill{Wh in energy
savings; Table 10 summarizes the number of measures installed through the 774 projects from 2009
through 2011.
Lighting
i::::::::::::::::::::::::::::::::::::::::::::
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Roclq Mountain Power
Exhibit No. 5 Page 1059 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
2.3 Program Theory and Logic Moilel
Program logic models depict the primary program activities, the outputs that are expected to result from
each activity, and the expected short-, mid- and long-term outcomes of those activities. Program actioities
depict the primary actions that are required to implement the program. This includes marketing,
participant recruitment, training, etc. The outputs depict the tangible "product'' resulting from each
primary activity. For example, marketing materials, training documents, and databases of recruited
participants can all be outputs of primary program activities. Outputs are typically identified as "things"
that can be tracked and tallied. Outcomes represent the intended results of successful deployment of the
identified activities.
Developing a logic model that clearly provides the theory of action and change is an important step in
evaluatiory allowing the evaluator and program actors to see inside the program'black box.'a Program
logic models provide a framework for an evaluation because they highlight key linkages between
program activities and expected outcomes. The process and impact evaluations focus on these linkages,
particularly those on the critical path to achieving savings goals. The evaluation identifies which linkages
in the program logic model are working properly and which linkage(s) may be weak or broken. Thus, if
the program falls short of achieving its intended short, mid, or long-term outcome(s), the source of the
shortfall can be pinpointed and remedied. Logic models are often developed as a visual tool to document
the program theory. The creation of such a model serves to develop a common understanding of program
activities and intended outcomes among Trade AIly Coordinator, Rocky Mountain Power, and the
evaluator. With this foundatiory the evaluation team can then make informed choices related to the
prioritization and focus of evaluation resources.
The underlying theory for the FinAnswer Express Program is articulated in the logic models provided in
Figure 1 and Figure 2. The evaluation team created these logic models based on a review of program
documentation and discussions with program management and implementers. These models present
differing logic for how the program will influence customers who participate pre- and post-purchase.
Participants who work directly with project m€rnagers are directed through the program as best suits
their project.
a Funnell, Sue and Patricia Rogers. 201 1. Purposeful Program Theor),: Effective Use of Theories of Change and Logic
Models. Iohn Wilev & Sons.
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Exhibit No. 5 Page 1060 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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Exhibit No. 5 Page 1061 of 1365
Case No. PAC-E-14-07
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The FinAnswer Express program pre-purchase path is designed to overcome three commercial and
industrial customer barriers to implementing energy efficiency projects: high upfront costs, long payback
periods, and lack of trusted information. The program's primary intervention for overcoming these
barriers is through the provision of technical assistance and incentives. Linkages within the program logic
are described here with numbers related to those shown in the pre-purchase path logic model figure
(Figure 1):
1. Rocky Mountain Power and the Trade Ally Coordinator reach out to trade allies to develop an
Energy Efficiency Alliance (EEA) that covers eligible energy efficiency measures (EEMs).
2. The EEA is armed with marketing materials, estimation software tools (lighting), and training on
the program. In addition, Rocky Mountain Power holds annual vendor meetings and workshops
to review the FinAnswer Express program and the support available for participating allies.s
Newsletters provide allies with program information between meetings and workshops.
3. The EEA promotes the program to customers.
4. The program, through increased awareness and participatiory and the EEA through increased
business benefit from the EEA promoting the program.
5. Trade ally success with the program encourages more EEA participation.
6. Rocky Mountain Power coordinates marketing efforts with the Trade Ally Coordinator and
outreach through account managers.
7. Customers become aware of the program or general energy efficiency assistance through
marketing and trade allies.
8. Aware customers express interest through the Rocky Mountain Power efficienry programs phone
number, online inquiry form, email to the energy expert, or through their customer or
community manager. Customer inquiries are processed to the appropriate manager or to the
third party Trade Ally Coordinator, as applicable.
9. Retrofit lighting and custom project customers are directed to submit an LOI to begin the
program process. New construction lighting projects and non-lighting projects start with the
Incentive Application; see Post-Purchase Logic Model.
10. The Trade Ally Coordinator and the Rocky Mountain Power Project Manager (PM) receive and
review submitted Letters of Intent; they coordinate to ensure project tracking by the appropriate
office. The Trade Ally Coordinator manages most projects.
11. If it is deemed necessary based on the project, an inspection of the customer facility is completed
before participation.
L2. The engineer conducts an inspection and submits an inspection report to the Trade Ally
Coordinator.
13. The pre-installation inspection reduces the risk of miscalculating energy savings by verifying
initial equipment and operating conditions.
14. If necessary for the project, energy analysis is performed to identify measures and estimate
associated energy savings and investment costs. For retrofit lighting projects, the trade ally
performs calculations using a lighting software tool. For custom, project manager-directed
projects, an engineer may perform an audit of the site.
15. Energy savings are identified and documented in the project file.
5 These events are held at least annually; vendors are not required to attend. The public is welcome at vendor events.
Rocky Mountain Power
Exhibit No. 5 Page 1 062 of 1 365
Case No, PAC-E-14-07
Witness: Kathryn C. Hymas
Erraluatior, o1 llock-v N.tlountain F)olver's II) IrinAnsr,r.'er Express Prog-r'a"rr iPY 2{)01i-:{}ii i t-f
il'd$\s$t&NT
J.
4.
5.
6.
account managers,
7. Customers become aware of the program or general energy efficiency assistance through
marketing and trade allies. Some customers, especially large customers working with a Rocky
Mountain Power customer account manager, may come into the program without working with
a trade ally and instead receive information about the program from a Rocky Mountain Power
PM.
6 These events are held at least annually; vendors are not required to attend. The public is welcome at vendor events.
Rocky Mountain Power and the Trade Ally Coordinator reach out to trade allies to develop an
Energy Efficiency Alliance (EEA) that includes allies for all eligible energy efficiency measures
(EEMs).
The EEA is armed with marketing materials, estimation software tools (lighting) and training on
the program. In addition, Rocky Mountain Power holds annual vendor meetings and workshops
to review the FinAnswer Express program and the support available for participating allies.6
Newsletters provide allies with program information between meetings and workshops.
The EEA promotes the program to customers.
The program, through increased awareness and participation, and the EEA through increased
business benefit from the EEA's promotion of the program.
Success with the program encourages more EEA participation.
Rocky Mountain Power coordinates marketing efforts with the third party administrator and
Rocky Mountain Power
Exhibit No. 5 Page 1063 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
16. Energy savings estimates are provided to the customer. The customer can rely on this
information to make decisions, reducing information barriers.
17. The Trade Ally Coordinator or Rocky Mountain Power PM creates an Incentive Agreement for
the customer. The customer signs the Incentive Agreement.
18. EEMs are purchased and/or installed by the customer or their contractor. Customers or trade
allies submit notification of project completion along with receipts/invoices.
19. EEMs reduce energy consumption (and in some cases, demand) at the facility.
20. Reduced energy consumption contributes to meeting annual program targets.
2L. Customers see reduced energy costs.
22- lf it is deemed necessary based on the project size, an inspection is completed to verify proper
installation of measures.
23. Verification ensures that expected savings occur.
24. Rocky Mountain Power processes incentives after the final incentive calculations, and incentive
checks are mailed.
25. The customer receives the incentive. Incentives reduce customer costs for the prol'ect and the
payback period.
26. Successful project completion encourages additional energy efficiency action on the part of the
customer.
The FinAnswer Express program post-purchase path is designed to use incentives to overcome
commercial and industrial customer barriers to implementing energy efficiency projects: high upfront
costs and long payback periods. Linkages within the program logic are described here with numbers
related to those shown in the logic model (Figure 2):
1.
Il-;alu.rtion ol Rock,v NIountaii.. F'(rr,vc!"'s II-) IiirrAnsr.ter li:xpress Progra:rn (llY 2il09-t{}ii )
N$V$TENT
8. Customers purchase and install (if required) qualifying EEMs.7 Qualifying EEMs are those listed
on Rocky Mountain Power/s prescriptive incentive tables.
9. EEMs reduce energy consumption (and in some cases, demand) at the facility.
10. Reduced energy consumptions contribute to meeting annual program targets.
11. Customers experience reduced energy costs.
12. Customers submit a completed Incentive Application (available on the web) and
receipts/invoices. Incentive Applications are processed.
13. The customer's project is added to program project tracking database, and the customer is
notified that the application has been received.
14. If it is deemed necessary based on the project size, an inspection verifies proper installation of
measures.
15. Verification ensures that expected savings occur.
16. Rocky Mountain Power processes incentives after the final incentive calculation, and incentive
checks are mailed.
17. The customer receives the incentive. Incentives reduce customer costs for the project.
18. Successful project completion encourages additional energy efficienry action on the part of the
customer.
As part of the program evaluatiory the evaluation team compares program outcomes in place with the
outcomes expected in the logic model. In order to make this comparison, indicators for each expected
outcome as well as sources of indicator data must be identified. In some cases, these indicators are
directly observable from program tracking data or other archives; in other cases, indicators can be
observed through analysis of survey or interview responses.
Table 11 identifies key indicators and data sources for FinAnswer Express program outcomes (short,
medium, and long-term) shown in the logic models, above.
7 Not all EEMs must be installed to qualify for incentives.
Rocky Mountain Power
Exhibit No. 5 Page 1 064 of I 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Ilrralnation oi itock,v lv{ounlain i:'{nq,c!''s 1I-} FinAnsi.ver Iixl:rtrss lrrog-r'am (PY 2009-2t}1i i 1 i'.
Roclry Mountain Power
Exhibit No. 5 Page 1 065 of 1 365
Case No. PAC-E-I4-07
Wtness: Kathryn C. Hymas
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Rocky Mountain Power
Exhibit No. 5 Page 1 066 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
tr".t A\JId\,t NI*rl'\ f 1 "r.* :* \*f J\ l\ $
The following subsections provide a detailed description of the evaluation methodologies used in the
impact evaluation of Idaho's FinAnswer Express program.
3.1 ImpactEoaluationMethoilology
This section summarizes the impact evaluation methods used to develop project and program level
realization rates for the FinAnswer Express Program for program years 2009 through 2011. The impact
evaluation of Idaho's FinAnswer Express Program aimed to achieve the following objectives:
> Quantifying the gross and ref impacts of the program through annual gross energy and demand
savings;
> Establishing post-implementation performance profiles for installed measures and activities; and
> Explaining discrepancies between the results of this study and the reported savings estimates.
Evaluation metrics and parameters reported through this study include:
, Gross and net eoaluated program demand and energy savings estimates and realizations rates for
completed projects; and
> Energy usage profiles for C&I technologies metered through on-site Measurement and
Verification (M&V) activities.
The impact evaluation methodology included the following steps:
" Evaluation Approach;
" Project File Review;
" Sampling Framework Development;
, Gross Energy & Demand Realization Rate Calculation;
> Net-to-Gross Estimates; and
" ProgramCost-EffectivenessCalculation.
3.1.1 EvaluationApproach
FinAnswer Express project evaluations were conducted using the International Performance
Measurement and Verification Protocols (IPMVP) Options A or B.8 The projects in the sample consisted of
motors, Variable Frequency Drive (VFD), and lighting measures.
Use of option A was limited to situations where the installed equipment operates at a fairly constant
power level, such as NEMA Premiumru efficiency motors. Specifically, for premium efficiency motor
measures, the evaluation team verified equipment purchase through the project file review process.
8 For more information regarding IPMVP options and definitions, see http:.//wwn'.evo-
vvorld.org,/inrlex.php?option=com conteni&viers=article&id=272&Itemid=397&lang=en.
E.,,aluatior^r ot l{ockv {ountain l}olr.'er's Ii) IinAn:l,ver Express Prograrn {PY 2009"?0ii t
itNJ\\i$*--qNT
Subsequent interviews with facility staff on-site confirmed that the motors were in place and operating.
Though the team could not always verify the exact location and loading factors for each motor, the
project file input assumptions were conseraatiae relative to secondary literature on prescriptive motor
performance.e Overall, any differences between the reported and evaluated savings estimates were
attributed to rounding differences.
The evaluation team also used IPMVP Option A to calculate realized savings from VFD measures. The
evaluation team verified at project sites VFD installations and VFD operating parameters such as
connected load and operating hours. This data was used to verify and update input used to calculate
energy savings.
The evaluation team used option B to estimate savings for lighting projects. The evaluation team verified
fixture counts and used logged data over a period of one to two weeks to verify operating hours.
No other measure categories were included in the sample. Details on the selection of the sample are
presented in Section 3.L.3: Sampling Frame Development.
3.1.2 Project File Reviews
A thorough review of the FinAnswer Express project files allowed the evaluation team to understand and
verify the accuracy of Rocky Mountain Power's energy savings calculation methodology and develop on-
site Measurement and Verification (M&V) plans for projects included in the on-site M&V sample.
For each project file reviewed, the evaluation team characterized any data gaps, inconsistencies, and
inaccuracies in estimating project level savings. The evaluation team also assessed the
variability/uncertainty between Rocky Mountain Powe/s input assumptions and those of secondary
studies, along with the relative impact on energy and demand savings. This type of sensitivity analysis
was crucial in prioritizing and aligning task resources. The results of this effort were used to develop
recommendations for input assumption revisions based on prior evaluation studies, upcoming policy
requirements, and geographic factors. Examples of secondary resources that were leveraged through this
task include:
,, Regional Technical Forum @tf;',0
, Commercial and Institutional Building Energy Use Survey (CIBEUS);I1
)). Database for Energy Efficient Resources (DEER);1,
> Buildings Energy Data Book (BEDB);I3 and
, Commercial Buildings Energy Consumption Survey (CBECS;.t+
e Motor loading factor was assumed to be 0.68. Source: "Quality Motor Rewinding an Energy Efficiency Measure." -
Green Motors Practices Group.
10 Regional Technical Forum, RTF Unit Energy Savings (UES) Measures and Supporting Documentation.
http ://www.nwcouncil.org I ener gy I rtf I measures/Def ault.asp,
11 Demand Policy and Analysis Division of the Office of Energy Efficiency, Commercial and Institutional Building
Energy Use Detailed Statistical Report December 2002.
12 California Public Utilities Commission, Database for Energy Efficient Resources, 2008.
13 U.S. Department of Energy,2008 Buildings Energy Data Book, 2008.
Rocky Mountain Power
Exhibit No. 5 Page 1 067 of 1 365
Case No, PAC-E-14-07
\Mtness: Kathryn C. Hymas
L\ralual.ior-i ol i{ock1' }'{ouniain Por.r'ei:'s II-} Iirr;\n:ivrrer H;xpress Progranr {PY 200S-?t}11i 18
hd &V $ilu.,q i\i T
Figure 3 presents an example of the overview of parameters verified through the project file review
Process.
Figure 3, Parameters Verified thruugh l'roiect Irile t{eviews {Exarn
Continuing to understand and document the available data and considerations within each unique
project file allowed the evaluation team to make informed recommendations for future evaluation cycles
and custom calculation revisions.
3.1.3 Sampling Frame Development
For the evaluation of the Idaho FinAnswer Express program, the evaluation team developed a sampling
framework that provides 90/10 confidence/precision level at the program level.ls The team adopted a
Ratio Estimation approach to sampling which achieved increased precision and reliability by taking
advantage of a relatively stable correlation between an auxiliary variable and the variable of interest (i.e.,
the ratio of actual savings to program reported savings). This approach served to reduce the overall
coefficient of variation within the population.
As an example, consider the FinAnswer Express program project savings that may range anywhere from
100 k\ /h to 250,000 k\A/h based on the size of each participating facility and measures installed. Both the
average size and the average savings for this group of customers have very large coefficients of variation,
thereby increasing the sample size required to achieve a specific confidence/precision threshold if the
ra Energy Information Administration, Commercial Buildings Energy Consumption Survey, 2003.
15 The evaluation team planned for 90/10 by program and state; the final confidence/precision for ID FX is 90/5.5.
Industry standard is a minimum of 80120.
Rocky Mouniain Power
Exhibit No. 5 Page 1068 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
FinAnswer Express Proiect File Review- Lighting
Proiect Name
Customer N.ame
Proiect Number 61.572
Enersy Savings Claimed (kWh)325,700.00
Verified Enersy Savinss ftWh)350,453.96
Energy Savings Realization Rate 108%
Demand Savings Claimed &W)64.40
Verified Dernand Savinss (kW)69.25
Demand Savine Realization Rate 108%
fotal Proiect Cost $ 183,046.00
Verified Total Proiect Cost $ 162,794.58
Reported Incentive $ 29,751-.00
Verified Incentive $ 26,865.00
Notes
iggffi shrued that tune at@s uqe 8760 oryating houn ra*tq
har he clnimed houn, catsing he highr uqgq r@liation rak.
ligha Dmand Ruliutim RaE k couscd by a our atimakl
lmand dionity foctrbeing .85 ruhq han fue claind -78
I:'.r,'ah-iaiioi^, ol iltrkt- I\4ountain P(ri.rrer's II-) FinAnsir.,er Express Illogionr (llY 20t)9-?tiii;
*fui s\ \,{ $ s"'" ..{ Ni *ri\r\v$\"*$f'\lv$
evaluation aims to estimate the magnitude of program savings. However, evaluation experience has
demonstrated that a majority of customers have a ratio of actual savings to program reported savings
between 70 - 100 percent regardless of the magnitude of each individual project's energy savings. This
ratio is the realization rate for gross verified savings and a core objective of this impact evaluation. As
such, the standard deviation of the realization rate is generally much smaller than that of the magnitude
of individual project savings. It follows that the sample sizes required to achieve a specific
confidence/precision threshold may be greatly improved by estimating the realization rate instead of total
energy savings.
The 2004 California Evaluation Framework provides industry accepted guidance on developing sample
size.16 Per this framework, sample sizes developed using the Stratified Ratio Estimation approach comply
with the following equation:
,"J'rl!
isriri=---:-
: + fffi irs
Il/here:
n = Sample Size
Z=Z-Score for Desired Confidence Level
e = Assumed Error Ratio (0.4 Based on Prior Evaluation Studies)
rp = Desired Relative Precision
N = Population Size
Moreover, the evaluation team proportionately stratified the sample by program reported savings. Under
this approach, the sample population was divided into subgroups by reported savings (i.e., strata). The
evaluation team selected projects proportionately within each stratum to ensure:
1. The largest projects and contributors to program performance are evaluated, and
2. The medium and smaller projects receive fair representation in the evaluation. (Collectively,
these projects also reflect a large percentage of program level savings.)
For Idaho's FinAnswer Express program, the evaluation team assumed a conservative error ratio of 0.4
for developing the sample framework. The error ratio corresponds to the expected standard deviation of
the realization rate for the program and was selected based on Navigant's experience with similar
commercial and industrial energy efficienry program evaluation results.
Additionally, the evaluation team took care to sample complete FinAnswer Express projects rather than
individual measures. As an example, if the unique project number IDL00028, was selected as part of the
evaluation sample, all measures installed through that project were evaluated.
16 TecMarket Works, The California Evaluation Framework, june 2004.
Rocky Mountain Power
Exhibit No. 5 Page I 069 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Erraluiriion ol l(ocky N,lountain Fc,r.r'er's II-) IrinAnswer li;xpress Prt:glam (llY 2il{)!r-?tli1}
rru Axr $il,q NI Y
The final impact evaluation sample achieved 90/5.5 confidence and precision across the 2009 through
2011 program years by energy savings (kVVh).Table 12 provides an overview of the impact evaluation
framework representing 58 percent (25) of the reported FinAnswer Express Program savings for the 2009
through 2011 program years. The 25 projects sampled included lT lighting, three motors, and five
variable frequency drive (VFD) proiects.
Tablct 1.2. Oven iew' of the IfJ Fin,Answer ress Impact Evaluaticn $arnrrli Frame
174 6,607,119 3,819,953 58%
3.1.4 Gross Energy and Demand Flealization Rate Calculation
Gross energy and demand realization rates for each project in the impact evaluation sample were
combined to form program leael realization rates for each program year. The evaluation team researched
the following technical issues in order to accurately determine gross program impacts and realization
rates:
Determining the appropriateness of the pre-installation technology performance baseline via
project file and secondary literature review.
Verifying installation and quantity of reported energy efficiency measures.
Verifying the baseline and measure performance characteristics of the measures installed, and
revising or computing performance variables as needed (e.9. operating hours were updated for
sites that the evaluation team installed lighting data loggers in).
Estimating the load shapes for the energy efficienry measures installed through the programs to
calculate maximum demand savings realized by the customer. For lighting projects, this included
calculating a diversity factor per site. This diversity factor was calculated by determining a
typical load shape, which was used to determine the diversity factor and the maximum demand
savings realized by a customer.
" Determining the demand savings (kW) and energy savings (kVVh) impacts of the energy
efficiency measures installed for projects sampled. This was accomplished by first calculating case
weights for each evaluated project; the case weight is simply the number of projects in the
population in each stratum divided by the number of projects in the final sample in the
corresponding stratum.lT
The program level realization rate was then calculated as the ratio between the product of case weights
and oerified savings estimates and the product of case weights and reported savings estimates. This is
illustrated in the equation below:
17 The TecMarket Works Team, The Califomia Evaluation Framework, Prepared for the California Public Utilities
Commission and the Project Advisory Group, June 2004.
Rocky Mountain Power
Exhibit No. 5 Page 1 070 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
25
I}raluatiou o,. l(ockv htlountain Por.rer's IL) iiir:Ansr,rrer lixi:ress Ilroglanr (PY 200!r":()1i i
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3.1.5 Net-to-Gross(NTGIEstirnates
Using self-reported responses, the evaluation team's estimation of net savings first attempted to assess
the program's influence on the participants' decision to implement an energy efficienry project and what
would have occurred absent program intervention. This estimation included an examination of the
program's influence on three key characteristics of the project: its timing, its level of efficiency, and its
scope (i.e. the size of the project). This estimate represents the amount of savings attributed to the
program that would have occurred without its intervention and is often referred to as "free-ridership."
The team's measurement of net savings then estimated program influence on the broader market as a
result of the indirect effects of the program's activities. This estimate, often referred to as " spilloaer,"
represents the amount of savings that occurred because of the program's intervention and influence but
that is not currently reported by the program. Spillover savings can be broken into two categories of
savings: "participant" spillover and "non-participanfl' spillover. Participant spillover savings occur
directly (i.e., program participants install additional energy efficient equipment), while non-participant
spillover savings occur indirectly (i.e., market allies install additional energy efficient equipment to
customers that choose not to participate as a result of the program).
A program's net savings are adjusted by both free-ridership and spillover savings at the measure level
and then extrapolated to the program. The net savings are the program-reported savings minus any free-
ridership savings plus any identified spillover savings, or:
Net Program Saoings = Gross Program Saaings - Free-Ridership Saaings + Spilloaer Saaings
OfterU this finding is described as a "net-to-gross ratio." This ratio is the net program savings divided by
the gross program savings, or:
Net-to-Gross (NTG) Ratio = Net Program Saoings / Gross Program Saaings
The Idaho FinAnswer Express NTG ratio was calculated using a different self-reported sample of 49
projects (three participants refused to answer self-report influence questions) as compared to the sample
of 25 projects used to calculate energy and demand realization rates or cost-effectiveness. These projects
represent close to 12 percent of reported savings. A more detailed explanation of net savings calculations
can be found in the appendices. The findings of the NTG analysis are presented in Section 4.3: Program-
Level Net Savings Results.
Rocky Mountain Power
Exhibit No. 5 Page 1071 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
I\ralr.ralion ol I{ock,v N,4ouniain Por'r,cr's It} };irri\nrir,ver Exirruss Progrilm (i}Y 20t)!r"?(ii I;t-1
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measure
3.1.6 PrograrnGost-Effectiveness
The evaluation team calculated cost-effectiveness using the methodology prescribed by the California
Standard Practice Manual.18 For the purposes of this evaluation, Rocky Mountain Power specifically
required the following cost-effectiveness tests:
" PacifiCorp's Total Resource Cost Test (PTRC)
" Total Resource Cost Test (TRC)
" Utility Cost Test (UCT)
" Ratepayer Impact (RIM)
" Participant Cost Test (PCT)
With the exception of the PTRC, all other tests are explained in the California Standard Practices Manual.
The evaluation team worked with Rocky Mountain Power to understand the PTRC and construct a tool
that calculates the PTRC at measure, program and portfolio level. Table 13 presents details of the cost-
effectiveness tests accepted by Rocky Mountain Power.
Will the participants benefit over the
measure life?
Rocky Mountain Power
Exhibit No. 5 Page 1 072 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Comparison of costs and benefits of
the customer installin g the.m-.9-a€ure .
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administrator costs and utility bill
reductions to supply side resource
costs
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:::::iil:j::ll:::::::::::!:::::::::l i:;::::::l:l:
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Will utility rates increase?
Table 13. Details of Cost-Effectiveness Testsl"
resources is included?percent benefits adder.
Cost-effectiveness inputs include program cost inputs, program savings by measure, measure effective
useful life, and utility-level inputs such as avoided costs and retail rates. The evaluation team worked
through a range of cost input assumptions pertaining to discount and escalation rates, avoided cost data
18 The California Standard Practice Manual is an industry accepted manual; it identifies the cost and benefit
components and cost-effectiveness calculation procedures. Definitions and methodologies for cost-effectiveness tests
can be found at http:/1rvr,r'rr'.erlsllg}.sa8s}::i[ireelr.[:ui].dirr!;i.lo<:rrrlrenisli.'r.:trlgt0fJ.Dsl/(17.:
I C!:UC. S'I i\NDA[tD ltrltAC] lCF |i{""\NUAL.PLIL.
le "Understanding Cost Effectiveness of Energy Efficiency Programs: Best Practices, Technical Methods, and
Emerging Issues for Policy - Makers" NAPEE, November 2008.
http;/lrry rt w.epa.govlcleanenerB),,i d,:cunrents/5uca,,co:rt^ef fectiveness.prlf .
Ilralr-iaiior^, ot lt,rcki lr.{rtitutai* I'$wc.r':i .ll-} }rinAn:ii.r,r:r ii.xprtrss {}rttgli;rm il}Y 20i)9.:0ii}2i
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formats, and participant costs and benefits Table 14 provides an overview of cost-effectiveness input
values used by the evaluation team in the cost-effectiveness analysis.
Rocky Mountain Power
Exhibit No. 5 Page 1073 of 1365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
7.32%
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Discount Rate
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Commercial Line Loss
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iiiiiiiiiiiii:i:iiilii:iiiliii::iiiiliiiiiii:jiir:lrittl::r:::riiiiiiliNl:::i
$0.0715
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To calculate avoided costs, the team used the 2008 IRP East System load shape decrement at $45 Carbon
Stream for program years 2009 and 2010. For program year 201.1., the evaluation team used the 2011 IRP
East System load shape decrement at Medium Carbon Stream to calculate avoided costs.
Each measure's effective useful life (EUL) was derived from the Database of Energy Efficiency Resources
(DEER;.zo
In addition, the team developed an alternate scenario for conducting cost-effectiveness tests for the Idaho
FinAnswer Express program due to the Energy Efficiency Incentive Agreement in place between Rocky
Mountain Power and the Idaho Office of Energy Resources (OEn;.,, The Agreement provides funding to
promote the installation of additional cost-effective energy efficiency measures in public schools within
Rocky Mountain Power's service territory. As such, total energy savings reported (and associated costs)
for the Idaho FinAnswer Express program include measures not incentivizedby Rocky Mountain Power.
To reflect cost-effectiveness that can be attributed solely to Rocky Mountain Power, an alternate scenario
was developed. In this scenario, all energy savings and associated costs from public school energy-
efficiency projects were removed to conduct the PTRC, TRC, and PCT cost effectiveness tests. Since
public school projects completed through this Energy Efficiency Incentive Agreement occurred in 2011
only, this alternative scenario only affects cost-effectiveness results for program year 2011 and the
20 DEER is the source for deemed measure characteristics in California (as per the California Public Utilities
Commission). More information on DEER can be found at http://www.deeresources.com/. The evaluation team
believes that this is a suitable source for calculating measures installed in Idaho and is in line with Rocky Mountain
Power's design values.
21 Rocky Mountain Power. 20L1 Energy Efficiency and Peak Reduction Annual Report - ldaho. August 3,2012. Accessed
from
hitP:ii,,l"'r,rt,.'.racificor!..con,.icontentldam/EracificcrpidociEnelBl,'SoirrceslDernanii Siile h{anagement/JD 2011 A^nu
al Repori Airlrenili>:.pdf.
24Ilvairiaiioii ol. ilolki. N{ouni.arri i]sr.r,ei's II-} Firr:\n:ii,vt:i ii.:<irlt:,-rs ltlilg,sni ii}Y 2i)i)!'.^ltii I l
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combined 2009 through 2011. Results for this alternate scenario are provided in Section 4.4: Cost-
Effectiveness Calibration and Analysis.
3.2 Notes onValidity anilReliability of lmpnctMSV Eindings
The evaluation team identified several sources of uncertainty associated with estimating the impacts of
the FinAnswer Express program. Examples of such sources include:
> Sample selection bias;
> Physical measurement bias (e.9., meter bias, sensor placement, non-random selection of
equipment or circuits to monitor); and
> Engineering analysis error (e.g., baseline constructiory engineering model bias, modeler bias).
The evaluation team remained cognizant of these issues throughout the evaluation process and adopted
methods to reduce the uncertainty arising from these sources, thereby improving the validity and
reliability of study findings. Key uncertainty sources and mitigation strategies are discussed further
below.
3.2.f Reducing [.lncertainty frorn Sample Selection Bias
The problem that selection bias creates for program evaluation is recognized in the evaluation industry.
Although projects were chosen in the impact evaluation sample according to prescribed protocols, bias
may have been introduced if the selected projects did not choose to participate in the evaluation effort. In
an effort to minimize non-response bias, the evaluation team established and implemented the following
recruitment protocols:
> Notified participants as early as possible in the evaluation process.
> Accurately characterized M&V activities and the duration of the evaluation process.
> Maintained brief and frequent communication with participants and inform them of any
changes/additions to the evaluation effort.
The intent of these protocols was to give each participant ample time to prepare documentation and
secure the appropriate resources to support the evaluation effort. Brief and frequent contact with each
participant ensured the participant remained engaged.
In the event that a non-respondent was encountered, the evaluation team first identified the nature of the
project (i.e., measure type).22 Non-response for non-certainty projects was addressed by oversampling
projects within each of the original stratum. These "alternative" projects were substituted into the impact
sample in the event that a project did not respond to evaluation requests. Non-response for certainty
projects were generally addressed by choosing similar projects (i.e., measure technologies) with
equivalent, or larger savings. Collectively, this effort ensured that precision levels were met within the
overall impact evaluation sample.
2 The impact evaluation encountered zero non-respondents in this study.
Rocky Mountain Power
Exhibit No. 5 Page I074 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Liialuialioi"i ol Rockv lr,{ountair"r Pcrwer's II-} };inAnswer H,xpress Progiarn (l}Y 20t)9-?ilii i LJ
,*rusu $t -q \$ T
3.2.2 Reducing Uncertainty frorn Physical Measurement Error
There is inevitably some error associated with all physical measurement. For the impact evaluation of the
FinAnswer Express program, a large measurement effort involved installing lighting/current/power
Ioggers to determine the operating characteristics of technologies across a broad range of applications.
Several steps were taken to minimize the uncertainty resulting from bias/error that may have been
introduced in this process:
> Back-up Loggers: Prior evaluation experience indicates that Iighting loggers sometimes fail in the
field due to flickering or battery issues. To account for the possibility that some of these loggers
might fail in this evaluation, the evaluation team deployed backup loggers for each site. This
ensured that the sample size requirements would be met even if a percentage of the loggers
failed.
> Logger Calibration: To minimize measurement error from improper calibration of the
lighting,/current/power loggers, the evaluation team checked all loggers used in the field to
ensure that they were properly calibrated prior to being deployed. Field staff was also trained to
use consistent measurement intervals whenever possible, and to synchronize the logger
deployment activities (e.g., time delay). This ensured that the data could be compared across a
uniform time period.
> Logger Placemenh To minimize biases arising because of improper placement of the loggers,
field staff was given a prescribed protocol for the placement and installation of loggers on circuits
(e.g., CT placement) and fixtures (e.g., uniform distance from the lamps).
> Logging Period: Usage patterns for retrofit measures may vary from month-to-month. Sampling
for a short duration could therefore introduce a degree of error into the overall results. To reduce
this type of error, Ioggers were typically deployed for a minimum of two weeks and
supplemented with available facility records (e.g., EMS trends, production logs, etc.). The logged
data was used to calibrate the facility records which spanned multiple months or years. These
extended logging intervals minimized the bias introduced from extrapolating short term
metering results to longer periods of time.
> Logged Data Quality: Poor quality data can also be a significant source of error and uncertainty.
To minimize the potential impact of this problem, various quality assurance checks were applied
to the logger results. This included consistent spot measurements that could be compared against
logger data. Additionally, qualified analysts reviewed all logger files to ensure that the results
were representative of the technology being investigated:
o Lighting loggers were reviewed to identify inconsistencies in operating
characteristics and/or extended periods of inactivity. If a particular file was deemed
suspicious, the evaluation team followed up with field staff and facility managers to
ensure that the findings were reasonable. Inaccurate results were removed from the
analysis.
3.2.3 Reducing tlncertainty fremr Engineering Analysts Error
There are several opportunities for biases in engineering analyses that may compound the error and
uncertainty of eoaluated savings estimates. The evaluation team adopted the following protocols to
minimize uncertainty from engineering analysis error in this study:
Rodry Mountain Power
Exhibit No. 5 Page 1 075 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E...alu.rtioi.. oi !{ock,v lvllountain Po'r\,ei"s Ii-} }ririAnsvr,-el li,xFrress Proglam (PY 2009-:i}ii i l.l:]
ruAviil.q NT
" All project analysis findings were peer reviewed to ensure that consistent methods and
assumptions were used throughout the impact evaluation.
" The evaluation team developed data collection protocols that yielded appropriate inputs into the
analysis models and reviewed all field observations with the evaluation team. Collectively, this
served to reduce potential modeling error in this study.
3.3 Process Methodology
This section describes the methodology used to complete the process evaluation. First, the section
describes a high-level overview of the steps taken to collect and analyze the data for this evaluation. This
is followed by a list of the research questions that guided the evaluation. Next, a detailed description of
the data collection activities is provided, and this section concludes by describing the methods used to
analyze the process data.
3.3.1 Overview of Steps in the Process Evaluation
To meet the objectives of this evaluatiory the evaluation team undertook the following activities:
> Process Evaluation Research Question Development. Key evaluation questions were established
from the development of the 2009 through 2011 evaluation plan with Rocky Mountain Power
staff.
" Program Documentation Review. The evaluation team reviewed program documentation,
including regulatory filings, brochures, application forms, and website.
" Logic Model Development. The evaluation team worked with program staff to define a logic
model for the program that describes the intended program design, activities, outputs, and
outcomes.
> Process Data Collection Activities. The evaluation team collected process data through
interviews with program staff, trade allies working with the program, and near-participants who
did not finish projects with the program, as well as telephone surveys with participating
customers and with non-participating customers.
" Process Data Analysis and Synthesis. The effectiveness of the program processes was assessed
by analyzing program tracking data, in-depth interview data, non-participant survey data, and
participant survey data.
3.3.2 Frocess Evaluation Research Questions
Discussions with program staff and a review of the program theory and logic identified six overarching
research questions to guide the process evaluation.
1.What are the program goals, concept, and design? Are they based on sound theory and practice,
and, if not, where are the gaps?
Do program administrators have the resources and capacity to implement the program as
planned, and if not, what is needed?
Is the program being delivered as planned and described in the program logic model, and if not
how and why?
Rocky Mountain Power
Exhibit No. 5 Page 1 076 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
2.
Erraluation oi ilockv N4ountain P(rirrii's II-) FinAnsvrrer !,xpress Program (P'1 2009-l0ii ,i 2:i
4. Is the program reaching the intended target population, and if not, why? Specifically, are eligible
customers aware of the program, how are they becoming aware, and what is the program
influence on their actions?
5. What barriers are preventing customers from taking actions to reduce energy consumption and
demand, and which jeopardize program cost-effectiveness?
6. Are participants achieving desired outcomes, and if not, how and why? Program outcomes and
key indicators are identified in Table 11.
These questions were explored through a mixed-methods approach. Table 15 shows the overarching
research questions and associated data collection activities. Data collection activities were analyzed to
identify findings, which were then used to answer the overarching research questions.
Table L5. A aches to Answer Research Questions (ttQ)
3.3.3 Program Doeumentation Review
The evaluation team reviewed program regulatory filings, marketing materials, program website,
program manuals, application materials, annual reports, previous evaluations, and project tracking data.
This archival data review identified how the program is marketed, how trade allies are supported, and
how the process works for enrollment, administration, and tracking.
3.3.4 l*ogicModeNDevelopment
Based on the program documentation review and interviews with program administrators, the
evaluation team developed a draft logic model, representing the program theory. The program theory
explains how it is designed to overcome the barriers that the program is targeting. Logic models illustrate
the flow of activities that create needed behavioral outputs, which in turn achieve desired outcomes over
the course of the program. Activities are actions taken by the program administrators or implementation
contractors, as part of the program, such as: reviewing applications, developing and presenting reports to
customers, or verifying installations. Outputs are measurable or verifiable tasks that result directly from
the program activities. Outcomes can be in the short, medium, or long-term, and they are the result of the
activities and outputs. The logic model was reviewed with the program manager and revised with
program manager input. The logic models are included in this report and are shown in Section 2.3:
Program Theory and Logic Model.
3"3.S Frocess Data Collection Activities
The process data collection activities are described in this section. Program staff interviews were used to
support development of the program overview and logic model. Findings from the other four data
collection activities are presented in the findings section and then slmthesized to draw overall
conclusions and recommendations for the program.
Rocky Mountain Power
Exhibit No. 5 Page 1 077 of I 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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3.3.5.7 ProgramStaffInterviews
The evaluation team interviewed two program managers and administrators. The objectives of interviews
with key program managers and administration staff were to:
> Understand the design and goals of the program to assist with development of the logic model;
" Understand any program changes that had been implemented going into the 2009 through 2011
rycle, as well as changes occurring during the current cycle;
" Identify program strengths from the perspective of program managers and administration staff;
" Identify program weaknesses and opportunities for improvement from the program managers
and administrative staff perspective; and
" Identify other actionable ideas the program managers and administrative staff hoped to gain
from the evaluation.
3.3.5.2 ParticipantSurveys
Participants are commercial and industrial class customers who completed a FinAnswer Express project
between 2009 and 20L1. Surveys with participants specifically addressed the following questions in
support of addressing the process evaluation research questions:
, How do customers come to participate in the program?
, How satisfied are customers overall with the program, including application materials,
inspections, and the incentive?
> What is the extent of program influence on customer actions, including free-ridership and
spillover?
> What barriers are customers facing that prevent increasing energy efficiency?
" What kinds of commercial and industrial customers are participating?
The evaluation team defined the unit of analysis for FinAnswer Express participants as a project. For each
projec! the evaluation team examined all measures included in the project and focused the participant
survey on the two measures that were associated with the greatest energy savings in the tracking data.
There were 174 projects completed by 99 unique participants with the Idaho FinAnswer Express program
during program years 2009 through 20L1. In May and June of 2012, the evaluation team surveyed 52
participants. At 90 percent confidence, this represents a precision of +/- 9.6 percent.
3.3.5.3 Near-Participant Interyiews
Near-participants are commercial and industrial class customers who began working on a project with
the FinAnswer Express program between 2009 and 2011 but had not completed the project. Interviews
with near-participants specifically addressed the following questions in support of addressing the process
evaluation research questions:
> How do customers come to begin working with the program?
" \A/hat would they change in order to participate?
\Atrhat energy efficient projects are near-participants installing (outside the program)?
What barriers are customers facing that prevent increasing energy efficienry?
Rocky Mountain Power
Exhibit No. 5 Page 1 078 of 1 365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
Erraittatior.. oi Rockv l\{ountain P$r.t,r:r's IL) FinAnsr,ver Exprcss lrregram (PY 2001}-?t}i1i ,,. t}
,N J\\o'$ {: A Ni T
The evaluation team defined the unit of analysis for FinAnswer Express near-participants as a project at a
site. The evaluation team selected near-participants from all projects for which the status was listed as
"on hold," with a last update date before June of 2011; sites with multiple projects that met the criteria for
inclusion were only asked about one project that they did not complete. This focus on earlier projects
ensured that the evaluation team did not reach out to participants whose projects were still on track for
completion in2012. Near-participant data did not contain information about potential project measures,
so the evaluation team was unable to prioritize any project over another with respect to potential savings;
all six project contacts were attempted with a goal of reaching five near-participants. In May of 2012, the
evaluation team completed an interview with one out of six near-participants.
3.3.5.4 Non-ParticipantSurveys
Non-participants are commercial and industrial (C&f customers in qualifying rate classes who did not
participate in any Rocky Mountain Power C&I demand side management program during the 2009
through 2011 program years. Non-participant surveys targeted C&I portfolio level considerations
through the following questions:
, Are non-participating customers aware of the programs?
" Why are they not participating (if they are aware of the programs)?
" What energy efficient projects are non-participants installing (outside the programs)?
" \Atrhat barriers are customers facing that prevent increasing energy efficiency?
The population of C&I non-participating customers was grouped into two strata by customer sector
(Commercial & industrial), and a target number of completes was set for each of the two sectors to allow
for results that are statistically valid at the 90 percent confidence level with +/-10 percent precision. As
shown in Table 16, these targets were met for commercial but not industrial class customers. This table
also shows the design weights, which are the relative population to sample size for each class; design
weights ensure that averages across the sample are representative of the population.23
Tahle 16. Non-Participant Population and Contacts
Commercial 8,574
Rocky Mountain Power
Exhibit No. 5 Page 1079 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
1.555
SrI*0
9.60%
IIi3ff%
196 9.60%1.555
3.3.5.5 Trade Ally Interviews
Trade allies are vendors, contractors, or distributors who have signed a participation agreement with the
Company to become part of the Energy Efficiency Alliance (EEA). Active trade allies are those in the EEA
who completed at least one FinAnswer Express project between 2009 and 2011. Interviews with active
23 The non-participants included in the sample frame were drawn from a database of non-participating customers
provided by the Company as a subset of the population of non-participants; design weights are based on the total
number of customers per class (provided by the Company) minus the number of participants per class.
!l.,,aluaiioi^, ol i\rxkr.' lr{ouniain l:;qr,r,riii':r ll,} }:irri\nsiver ixirtrss I}lugrant (j}Y l{}i)!,t-:i}i'i i
N$UI$T.ENT
trade allies specifically addressed the following questions in support of addressing process evaluation
research questions:
, How are trade allies becoming aware of the program?
> How well does the trade ally participation agreement meet their needs?
> How are program operations communicated to trade allies? How is training provided? Is this
communication and training effective (do they understand the program)?
, How satisfied are trade allies with their role in the program? What would they do to improve it?
, Do trade allies who participate see value to their business? Can they describe the effect on their
operations?
" What kind of energy efficient sales are they seeing outside of the program (spillover)?
The evaluation team identified active trade allies using information from the program tracking database,
program staff interviews, and participant surveys. Senior evaluation team staff members who were
knowledgeable about the program and appropriate technologies interviewed ten active trade allies
between |une and July of 2012.24
3.3.6 Process Data Analysis and Synthesis
The process data collection activities included both quantitative and qualitative data. The evaluation team
used statistical software, specifically SPSSTM (originally, Statistical Package for the Social Sciences), to
analyze the survey responses from participants and non-participants. Interview responses from near-
participants and energy engineers were analyzed directly as textual data. In both cases, the evaluation
team reviewed data for missing or erroneous entries. Analysis included recoding data in some instances
to disaggregate "other" responses or to combine similar responses into one category. Where appropriate,
the evaluation team tabulated frequencies of responses. After data from each data collection activity were
analyzed individually for findings, the evaluation team identified common process findings across
activities.
24 A $50 gift card incentive was offered to trade allies who agreed to participate in the interview.
Rocky Mountain Power
Exhibit No. 5 Page 1080 of 1365
Cese No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Evalii;riion ol itock,v N{ountain Pcxter's lL) FiriAnswer l-i,xpress Proglam (I}Y 20i)9-2ti1i t lt
Roclry Mountain Power
Exhibit No. 5 Page 1081 of l365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
N"-\V$t-&NI j-
2009
lztrtoji
20t1.
Leveraging the evaluation strategies previously discussed for the FinAnswer Express program, this
section summarizes the impact evaluation findings for each project included in the 2009 through 2011
evaluation sample.
The evaluation team distinguished savings into "gross" and "net." The methodology for calculating net
savings from gross savings is detailed in Section 3.1.5: Net-to-Gross (NTG) Estimates.
The evaluation team further characterized savings as "reported" and "evaluated." Reported savings
present project savings estimated at the time of measure installation. Evaluated savings present energy
savings verified in a facility at the time of evaluation. See Section 3.1.4: Gross Energy and Demand
Realization Rate Calculation for details regarding the savings calculation methodology.
4.1" Program-Leael Gross Saoings Results
In aggregate, the FinAnswer Express program achieved lower demand (kW) and higher energy (kVVh)
savings than is reported in the program tracking database.
The 2009 through 2011 gross program demand savings realization rate was 98 percent, and the gross
program energy savings realization rate was 101 percent. Table 17 details the demand and energy
realization rates for Idaho's FinAnswer Express program from 2009 through 2011.
'I'able 17. Ilrogram-Level Gross Itealization l{ates for ldaho FinAnswer Express (2009-2$1L}
742,966 89%
:.isrffi ffi
.,i...ii.ii,.ii.lll.lrdX$,S,,.i'4ii,i.,.,*..l.2,31.4,372 704%
83"/o
.iii.is,,,rc.*..l.
l05o/o
t,254.3 1.,228.4 98"/o 6,607,1.19 6,666,420 't01%
Table 18 shows the distribution of reported energy savings across all measure categories, and the
realization rates for those measure types accounted for in the stratified randomly-drawn sample. An
'N/A' indicates that the measure category was not part of the evaluation sample. These measure-level
realization rates are illustrative and do not represent statistically significant results; these measure level
realization rates should not to be used for future planning purposes.
All
Lighting
t#fi trJ,....lx...................'ii':;1!rt',,t:;:
HVAC
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3,480,828
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621.,580
97%
,iiiiiiiiii|iiillr:iiill$ffi lii:ilii
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i.......i..lt.lrlri..ffi fi ,lqll
NA
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E.,,alunt'ion of l(ocki- lr,louni.ain Ps'r,,,ei''s ii) firri\nrii,tei ixpress Ilrogii,rnr ii'Y :{}{).'r.r-liii I i 32
ru&VIil& Ni T
4.2 O n- Site V eifi c ati on Result s
Final realization rates for program-level demand (kW) and energy (kwh) savings were applied from on-
site field verification. The evaluation team visited 25 sites, representing 58 percent of the total reported
savings. The 25 projects sampled included lT lighting, three motor, and five variable frequency drive
(VFD) projects. Although realization rates were calculated for every project site visited, note that only
program-level, not measure-level, realization rates are statistically significant.
The 2009 through 2011 gross sample demand (kW) and energy (kwh) savings realization rates are
detailed in Table 19.
Table 19. Sample-l.evel Gross Realization Rates for Idaho FinAnswer F,}press {2$09-201.1)
Rocky Mountain Power
Exhibit No.5 Page 1082 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
89%
,,iliiiiiiiiiiifl{Ia,:*4H
']..04"/"
2009
+zlg1CI
2011 1.W.6 194.5
342,204
iiiiiiiiii*il8s..$$.,
889,285
83%
4.2.1 Demand $avings Results
Erialualion ol ltockv \{ountair:r Po'l.r,e.r's Ii..J }:irrAnsvr,ei Express Proglarn {F'1 2009-}0ii;.)-l
,$.N$V$il:-qNT
Table 20Table 20 provides projectJevel demand realization rates for the projects in the impact evaluation
sample that achieved an overall realization rate in 2009 of 83 percent in 2010 of 93 percent, and in 2011 of
105 percent.
Lighting projects' realization rates vary due to the difference between assumed and evaluated demand
diversity factors. Project files assumed average ASHRAE-recommended diversity factors to calculate
demand savings per project. The evaluation team replaced these average diversity factors with calculated
diversity factors for sites that the evaluation team installed loggers in.
Motor projects' realization rates do not vary greatly from 100 percenti Navigant verified that all
differences between reported and evaluated savings are due to rounding differences in calculations.
VFD projects' all achieved a 100 percent demand realization rate. Three VFD projects did not report any
demand savings to evaluate.
Roclq Mountain Pon/er
Exhibit No. 5 Page 1 083 of 1 365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
Errah"iation ol ilockv N{ouni'ain I'ou,er's It) }rinAnsw,er Express lrrograrn {PY 20i)9-?0i1;.14
Rocky Mountain Power
Exhibit No. 5 Page 1 084 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ru$V$TA, T
IDL00181
Tahle 20. Idaho FinA.ns$,'er Express Proiect-Level Demand (kW) Realization ltates
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,,,,i'i,ii,',,,,i,,,,,,,,,,,,.,1,,',,'i..irxj.ii..ili.liiiili.iiiiilliiiiiiiii.iiiiiiiiiii1DL00217 2010
IDL00250 2011
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;;..:l l1.;.......;.:...;.s6*si.....i.,,,ii.,i;..;i.:i;':'i.'tighffi;;,
2010 Lighting
2010 Lighting
" . : 'i:.,iit;l8ltrtl-Il8:'i:i:i
=ii.,.t
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:::i:,i:;Ii:i!::::t::t:t:::::,:i*:r::::::::i::::: :i,:::::ir::::::i:::::
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jrii.t:.::iii1i:::::i:1i::::i::::;;.:lii:iil:i::iiiil:lll:lll::!iriil:iiii
70%
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0.0
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4.2.2 Energy Savings Results
Table 21 details the energy savings realization rate for all projects in the evaluation sample that yielded
an overall realization rate in 2009 of 89 percent, in 2010 of 1.02 percent, and in 2017 of 104 percent.
Lighting projects' realization rates vary due to a difference in operating hours or a count of fixtures
installed. Details for each project that did not achieve a 100 percent realization rate are explained in Table
22.
The three motors projects reviewed did not vary greatly from 100 percent energy savings realization rate.
Four of the five VFD projects also yielded 100 percent energy realization rate based on installation
verification and a desk review of the project files. IDN00124 achieved 108 percent realization rate as it
Lighting
r::::u:llit:i:::::::::i*l::::
IDLo0164
IDN00111
hl.ialr-ialion ol iiock.v N{ountain lr$r,rrrii"'s II-} }iirrAniivver i]xi:r:rss Itrt.rgreinr ii)Y 20i)q.l$ii i -j:l
\.i d\ \ i t $"1 -..\ N"t Ti\f ]..\'N\*IJ\i\ $
was found, through field inspection, that the VFD in question was connected to a larger horsepower (HP)
Ioad than reported in the project file.
Rocky Mountain Power
Exhibit No. 5 Page 1085 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
T'able 2I. ldaho FinAnswer Ex Proiect-Level Ene (kl{,'h} lteal ization Rates
i€*{fl ws,,.r+.ii........i..,;,
IDN00111
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IDN00124
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Lighting
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Lighting
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76V"
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91.%
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to.a19;
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iv,f,iH
VFD
..Y.EBi
VFD
i;:::ilffiNoEl$ii
rDN00130
iili:::.tl
tl:l::::
The lighting project evaluation yielded significant differences between the reported and verified energy
savings estimates. Specifically, eight of the 17 lighting projects sampled yielded energy realization rates
above 100 percent and nine yielded realization rates below 100 percent. Table22lists the projects that
yielded energy realization rates above or below 100 percent with explanations as to whether the resulting
realization rates can be attributed to a verified fixture count or a difference in operating hours.
The table further explains whether the difference in operating hours is due to:
" Difference in Reported Operating Hours: The customer reported different operating hours to
the evaluation team than was reported on the original project file;
" Difference in Logged Operating Hours: The evaluation team's lighting data loggers captured
different annual operating hours than was originally reported in the project file; and/or
" Both.
Lighting
Lighting
l'.r:aiuatioi"i ol i(ockv \4ouniain I'or.,\'e!''s ll-) irinAnrr.rrel ii,ri:rr:ss Plcgram it-]Y 20t)9"!ilii;
nfS\Xs$il-\\l "I-
Tahle 23. Idaho Fin.Answer Ex
FESen_61844
ii.ffi1ilii
*..-*,,,i,*riffi--. ffi ..ffiffiffiIDL00075 91"/" Operating Hours Difference in Logged
Operating Hours
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IDL00100 52% Operating Hours Difference in Reported
Propram.s nith Realization Rates lanations
Rocky Mountain Power
Exhibit No. 5 Page 1 086 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Verified fewer occupancy sensors
than reported. Project file indicated
significantly different operating
hours compared to what customer
reported and Navigant logged,
especially in areas like the Waiting
.:.:.:.:oguagin$ ihqu$;ii.$#E€if,ic&[#,,iifi i.itl}Gii.i:iiii.
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Project file calculated the occupanry
sensor savings using a savings per
watt factor, while Navigant used a
20% reduction of operation hours to
calculate occrrpancy sensor savings,
Customert:repwted abgtit l 59o fewer
:: .:. . :: :::::i::::::::::::: : i . j " I ::::!:,:!.!.r.,.!. ;,i. .: . :, , : : ,'i . 1.:'::.,ooetatirrpiihoufs tf.rditli*iiitiallviri::i:.',:'.,:: .::;::!::..:::r:i:::::!:!:!:r!:!:!:!:::!l!:!:!i:':1. "'.'.': i.. , inti""""""""' ' "" ' ': :indictrgffiiiiih piojectfile;,,,,Lffi$er$,,1;,,
iii.riririi:wuruiiiiao}iih .ffiiiiffiie.init.t.is$.i,ir1ii
Customer reported and Navigant
logged fewer operating hours in all
Navigant logged fewer operating
h.orrrsnthantheprojegt.-f.il,5.1,1-oiT,,.9,,,"4.;,,,,,,,,,,,
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......''.i'''iiiri:'e,,H$f.$::at6ill'i'fE*::.eti ..ii....::
operating hours.saved more energy.
Project file claimed 8,760 annual
operating hours for both the
upstairs and downstairs areas.
However, downstairs logged 8,7 60
while upstairs logged only 1,336
Customer reported fewer hours of
operation during onsite visit than
project file claimed. Site contact did
not allow loggers to be placed.
rY"6'?......"'i."':
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Operating Hours
FESen_62083 76% Operating Hours
::::::i:::::::::::::::--; -.I:L :!.:::i:E.::: ::::::::r:::i::::::::::i:.il:::::il::.:::::::::::::::i:iiii:i:::::,,i:,:ilX.,.I:*.Yo,,'Opef.At*hs fJUUf
67% Operating Hours
and Logged Operating
Hours
and Logged Operating
Hours
:::::::::::::::::l:::l:;:::::i::::::::::::::,::::r::n:::ar:;:i: l:Ir.::!:i:::::::::::::::li:l:ilii:Eitr" Pnted:
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Difference in Reported
Operating Hours
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Rocky Mountain Power
Exhibit No. 5 Page 1 087 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ffiu ii U*ating
HoutS,.,thanigr,epct,:filU, Claim ,:,:$at
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Navigant logged fewer operating
hours than project file claimed,
,,,,,',',',',',',,,',,',,' ,,,,,,i?8if,r1al!y in the sh98n,,,,',,,,,,,,,,,,,*r,,,,,
,,. On atsraid,i.Narrib ,il6eied
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:i:i:.',.,::. . i:i:i:i:i:i:i:tl{:ei:iclittrIIlec1.....,,,::.i.:' :,:.
Customer reported greater
operating hours than project file
claimed. Navigant logged hours
similar to hours reported onsite, but
logged fewer than reported hours
for areas such as the office and
Customer reported greater
operating hours than project file
claimed.
In addition, the verified savings estimates and realization rates for lighting projects ate conseraatiae due
to:
Rocky Mountain Power does not credit energy and demand savings towards HVAC Interactive
Effects, which may be substantial.
Rocky Mountain Power assumes a conservative baseline of energy efficient lamps and magnetic
ballast combinations for rebated T-12 linear fluorescent lighting projects (except where the
existing equipment was already more efficient than this). In light of Energy Policy Act (EPACT)
and Energy Independence and Security Act (EISA) legislation increasing the minimum efficacy
(lumens per watt) standards of linear fluorescent lamps, the evaluation team accepted this
baseline while recognizing Rocky Mountain Power's efforts to lay the groundwork for future
changes in federal standards. However, the evaluation team also acknowledged that the verified
savings for projects involving the replacement of T-12 fixtures less efficient than the assumed
program baseline may be understated.
4.3 Program-LeoelNetSaoingsResults
The evaluation team calculated a Net-to-Gross (NTG) ratio of 0.67 for the FinAnswer Express program,
for program years 2009 through 2011. Table 23 provides evaluated program-level demand and energy
savings with the NTG ratio of 0.67 applied. With the application of the NTG ratio, overall realization rates
for the program fall below 70 percent.
.l:.]
{ru.$N$il.qNT
201,1,
221.0 r23.9
666.1. 472.4
Rocky Mountain Power
Exhibit No.5 Page 1088 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
70V"tL/o 2,233,973
Tabtre 33" P '[.evel Net Realization Rattrs for Idaho FinAnsr,t'er ress (2009-201.1)
s6%
t,5s7,532
t,254.3 825.7 667"6,607,1.19 4,486,501 687"
NTG ratios were calculated based on questions asked during participant surveys from 49 proiects that
contribute to approximately 15 percent of total reported savings.2s Of the 49 responders, ST (75 percent)
were reported as non free-riders. The program-weighted NTG ratio of 0.67 was calculated by weighting
the sample of project-level NTG ratios by their reported energy savings values. The evaluation team
found that only around 12 percent of projects qualified as full free-riders; details about responses can be
found in Section 5.1.4: Program Influence.
Further details regarding NTG ratio calculation methodology (and what makes a customer a free-rider)
can be found in Section 3.1.5: Net-to-Gross (NTG) Estimates. The appendices include a table that provides
projectJevel NTG ratios along with reported energy savings.
4.4 Cost-Effectioeness Calibration anil Analysis
Using the Company's model for calculating the program's benefit-cost ratios, the evaluation team
calibrated and updated cost-effectiveness models using five primary cost tests: PacifiCorp's Total
Resource Cost test (PTRC), Total Resource Cost test (TRC), Utility Cost Test (UCT), Rate Impact Measure
test (RIM), and the Participant Cost Test (PCT). Details regarding cost-effectiveness calculation
methodology can be found in Section 3.L.6: Program Cost-Effectiveness.
As seen in Table 24 through Table2T,Idaho's FinAnswer Express program was cost-effective by the UCT
in all years. In addition, the TRC did not pass in 20L1 and the RIM did not pass any year. It is rare for the
RIM test result to have a cost-benefit ratio greater than 1.0 for DSM programs as RIM tests measure the
effect of DSM program implementation on customer (average) rates, and DSM programs cause average
customer rates to increase slightly. The TRC cost-benefit ratio in 2011 is 0.91 due to high incremental cost
and relatively low savings attributable to measures installed. The incremental costs of measures installed
in 2011 are approximately 160 percent of the incremental costs of measures installed in 2010, while the net
evaluated savings for 2011 is approximately 60 percent of the savings reported in 2010.
25 Three respondents refused to answer influence questions.
All
Il..,alualion o1 iLockv lr{ountain For.r,cr's II-} }:irrAnsr..l..ei Lxprr:ss I}rogram (PY 2009-!{iii;
Roclq Mountain Power
Exhibit No. 5 Page 1 089 of 1 365
Case No. PAC-E-'14-07
Witness: Kathryn C. Hymas
i\ .*. .. ."ful "$\\JIid]"s\i .T'
{\r..r\' l\*..}J\I\. $
Total Resource Cost Test (PTRC)
;111f Uin-*.*Uffi ..,+ustgnen.,.,.,.
Utility Cost Test (UCT)
,,,.,.rcl* r"rp*i.#*t+ : ,,.,,.,i:.iiiiiiiiii..
Participant Cost Test (PCT)
742,966
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742,966
497,787 $337,048 $436,403
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9396,730
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:::::::::::::::l::li:ii:::::::::::::::::l:;:i:i:::
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1.56
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2.31.
Tatrk" 2il. 20il9 ldaho FinAnsrtrer Ex Benefit-Cost Ratios
Table 25. 201t} Idahn FinAnswer ress Benefit-Cost Ratios
Total Resource Cost Test (PTRC)
.....ffi!elii#e$hi*iEe$CI$'.itrE$tii ,.....ij,::::::::::::::::j::j::: 1 , :i:::::i ] :::::::::::::::::::::::::::::: :.' :
Utility Cost Test (UCT)
.....Raie..1mr;"t,r ...ffi*Ui..,., l,...............i.......
Participant Cost Test (PCT)
3,609,1.42,tiii*ffiiti
3,609,1.42
..i.........i..iri8'6E9triL48
3,509,142
2,418,125,ffiffi
2,418,125
$934,444
:,:::$9SA14lEt:ia*i::::iii:::i:iilltl:::lt:::::::::::::::::iii:::::ri:i il;;:i:;ljll
$620,490
,*2.-j4WiLl$:;,,tt,,,,,,
l:::l:i:i::::::::::::::::::::::::::::l:i:::::l:i:l::11,1:::::::::::::::
$906,048
$2,567,304
itlffit83&ersi.:il:r,:l::f i::rir::iri:i:i:::::::::t:r::::i:::i::::::::::::
$2,333,91.3
iiiiii$.l; $i.
i::,1::,::::::::::i:l:i; i:i:::::::::::::::::;:::i:::::::::::::::::
$2,992,542
2.75
3.76
oiE6iii.ii.i.i
3.302,41.8;t25
Tahle 26. 1011 ldaho FinA.nswer Hxpress llenefit-Cost trlatios
Total Resource Cost Test (PTRC)
.tr e iiisost.ifi€stii ii,Xi
Utility Cost Test (UCT)
,Rate,ffigct,,iFert,(Rt-.rQ,;;:t:t:t:t:t:t:t:t:t:,:t:t:::t:;, :
Participant Cost Test (PCT)
$1,s05,332
:::::i.i:;rr:r::r:::r:::::i:::::a::::::r:::::::::::r::::,::::::::::::i:ri:iiairit::
....i,*,;,,,,9*:?t$ sgllliiiii
$1.,733,334
$1.,512,245 1.00
,,,$tr;374'7,,68 :,:::',iiii;i:'ii0tgf ':': :::.:::.:::":.:::.. ::::::':$1.,374,768 1..96
$1,1374768 :1 , 0.71
92,1.86,440 1..26
2,314,312
.i.iiiia#r*p*eii.....
2,3r4,3't2
ni;niz$r.4Etzlii.i.ii
2,3r4,312
1,550,589
I.i55flifi89.
i:t:tlilt::i:t;;:ti::l::::::::::i::::::::::::::
1,550,589
rr550jss$
:::::::::::i:::i:l::::j:::::::::::l:::::::::::::
1,550,589
:ii:;r::r
;,i:;:i;
I'able 27" 2009-30'11 Conrbined ldaho finAnsrver Express Benefit-Cost ltatieis
Total Resource Cost Test (PTRC)4,466,502
i;.i;iiiiliiiiiiiii,4i$,ffi H.Biii;Xiiiiii
4,466,502
i:ri,:;#ffi isaz,',.'i,r
4,466,502
$4,515,953 1.53
iiWilo5i lt"ll.s............'.';...,ri$ lifit$4,r05,4'tr 2.60
,.$4,f0s,41,n,,,,,,",:,',',:,';':',',':";
i 0:*B :' ;:
$5,74t,487 1.99
6,666,420
:ffi661480
6,666,420
,r*,6ffi#6
6,666,420
$2,776,824
#ffibt4:ii-
$t,s76,3L8
$4r$k?#48iil:i.:l:i:li
:::::::: i::: l::::::::::::::::::::::::::::::::: i:::::::: i : I I, ,;::
$2,883,058
Evah-iaiioii +l Rock_r Nrlor:ntail'r f'$r'r,E:.r's Ii-) IrinAnsr.vei i:.:<irrirss i'i:sgieim iilY.10{}tt-:i}i1)
N I .i$\''\ ,r t tr'\ ,$ [ I \*i\-$\N$t"*S\l\ $
Rocky Mountain Power and the Idaho Office of Energy Resources (OER) have an Energy Efficiency
Incentive Agreement in place to maximize the impact of public school energy-efficiency projects.26 The
Agreement provides funding to promote the installation of additional cost-effective energy efficiency
measures in public schools within Rocky Mountain Power's service territory. As such, total energy
savings reported (and associated costs) for the Idaho FinAnswer Express program include measures not
incentivized by Rocky Mountain Power. To reflect cost-effectiveness that can be attributed solely to
Rocky Mountain Power, an alternate scenario was developed. In this scenario, all energy savings and
associated costs from public school energy-efficiency projects were removed to conduct the PTRC, TRC,
and PCT cost effectiveness tests.
Since public school projects completed through this Energy Efficiency Incentive Agreement occurred in
2011 only, this alternative scenario only affects cost-effectiveness results for program year 2011 and the
combined 2009 through 2011. As detailed in Table 28 and Table29, respectively, the FinAnswer Express
program passes all the cost-effectiveness tests in this altemate scenario. The alternate scenario's benefit-
cost ratios are greater than those of the primary scenario/base-case scenario due to the higher costs (as
compared to associated energy savings) for the school projects that are not included in the alternate
scenario.
Rocky Mountain Power
Exhibit No. 5 Page 1 090 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table ?8. 2011 Idaho FinAnsrver Express Eeinefit-Cost Ratios (Altemate Scenario)
Total Resource Cost Test (PTRC)
i..i;+ t;mU €os+ftut,,ffi,,,,,
Participant Cost Test (PCT)
1,,77't,778
.I .*f iiii:iiiii'iii'ii
1,771,,778
L,1,87,092
,.iitltsrffii
t,1.87,092
$860,740
$ff$lffisi....i
$u7,429
$7,169,700
Table ?9.2009-201'1 Combined Idaho FinAnswer Ex Benefit-Cost Ratios (Alternate Scenario)
Participant Cost Test (PCT)
Total Resource Cost Test (PTRC)6,1.23,887
6jxa$j$82;
6,723,887
4,L03,004
*iiilffi$ffi
4,103,004
$2,1.32,231.
$sifisEffir
$1,997,153
94,173,408
$3jr..:.,#l0sx,iiii::::i:::
fis,247,707
1..96
;:[lffii:l:i:l:iii
2.63
ft'taI
26 Rocky Mountain Power. 20L1. Energy Efficiency and Peak Reduction Annual Report - ldaho. August 3,201,2. Accessed
from
httP:iir,,,'rtrni.pacificorF..comicc,ntent,/damr/pacificorl./dociEnerB)'Sor.rrces,/Demanrl Sir-le N{anagement,/ID 2011 Annu
al Repori,{plrendix.pdf.
F.-;aiiiaiioi'i ot !iock'; lt{ountau'r f'o\q,ci-'s .ii-} }:inAnsi,.r,-er i:rpless Irrogra,r (l}Y 20i)!r-}i}1ii
\+ .N \i t s-": -s \r Yi\*.$ r,N i\I..r\l\ \
This section describes the findings from the process evaluation data collection activities. These activities
include the FinAnswer Express participant surveys, near-participant interviews, Idaho non-participant
surveys, and trade ally interviews. For each data collection activity, this report provides a description of
the sample followed by findings from that activity. At the end of this section, findings from these four
data collection activities are synthesized into key process findings and recommendations for the
FinAnswer Express program in Idaho.
5.7 Participant Findings
In May through August of 2012, the evaluation team surveyed respondents representing 52 of 174 total
projects in the Idaho FinAnswer Express program from 2009 to 2011.
Participating firms represented retail, educational services, service and repair, manufacturing, and other
industries, as listed in Table 30. The respondents indicated that their companies employed between three
and 3,500 people with a mean of 121 employees.
Table 30. Primary lndustr,r.6f FinAnswer Express Survey I{espondents
Educational Services
ffiImc€ iul#,::ltBpaxf i
-*Q-=S-:.r-(hls=e..-s-ls*Hsl:€*-g-l*s..ll'....-s"TP*"-"-..-.*"?..-..-Total 52
In order to understand the value of electric efficiency to participants, the evaluation team asked
respondents to identify the portion of operating expenses represented by electricity costs. Electricity
represented a substantial cost for some participants, although only 25 of the 52 respondents were able to
estimate the percentage of total annual operating costs attributable to electricity. These estimates ranged
from 0.5 percent to 50 percent, with a mean of 13 percent.
5.f .t Program Satisfaction
When asked to rate their overall satisfaction with the FinAnswer Express program, 71 percent of
respondents (37) were "very satisfied,"21. percent (11 respondents) were "somewhat satisfied," and 8
percent (four respondents) were "neither satisfied nor dissatisfied," as shown in Figure 4. No respondents
indicated dissatisfaction with the program.
Rocky Mountain Power
Exhibit No. 5 Page 1 091 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Retail
4
*
!:l..,air-ialioii oi ilock-_,'lvloiiniain I'o-'r,ei''s li) irini\n:;i,rer i:,xFrtr:is irroEieun iPY:l{}il9'.}tiii}4?
&l s\\..*l$'*,t \i*I-i\il C \ \.r $ l r i't. l\i lt \i .. $ .i \--i i \ i'+ I
Figure 4. Participant Satisfaction with the FinAnswclr B,xpresri Program Oveirall
Neither
satisfied nor
dissatisfied,
8o/o
Two of the four respondents who were "neither satisfied nor dissatisfied" with the program provided an
explanation for their rating. One cited the time it took to complete the paperwork while the other said
that starting the project required "quite a communication process" and the project took too much time to
complete.
When asked what changes they would like to see in the FinAnswer Express program, 65 percent of
respondents (34 respondents) did not respond. Four respondents had suggestions not applicable to the
FinAnswer Express program/ such as: concerns about a rate increase, disinterest in surveys, desires for
publicity, and requests for a focus on education. The other 14 respondents offered the following
suggestions:
, Decrease paperwork (four respondents)
, Increase incentives (four respondents)
, Increase responsiveness of customer service (two respondents)
, More communication (two respondents)
" Improve quality of products (one respondent)
" Quicker tumaround of incentive payment (one respondent)
Eleven respondents reported contacting Rocky Mountain Power with questions or requests for assistance
at some point during their participation in the program. Ten out of these 11 respondents found Rocky
Mountain Power staff/representatives knowledgeable about program requirements and timely in
addressing their questions.
5.1.2 Program Awareness and [tlotivation
Participants found out about the FinAnswer Express program mostly from trade allies; online
advertisements, program representatives, word of moutlr, and Rocky Mountain Power brochures and
newsletters were also noted as sources of awareness (see Table 33).
Rocky Mountain Power
Exhibit No. 5 Page 1092 of '1365
Case No. PAC-E-I4-07
Wtness: Kathryn C, Hymas
Ii.iah-ririion ol Rockv l\4ountain Pcr,r,i:r's IL) IririAnsiver Express Program (PY 20t)9-?t)1i.;
:i{. i i!\ \. ,{ t $.$ { \. i *Y*+ r+ !\. :: t
i+;a:l-i*\tlRJ'$I
Tlade allyr, vend'on o1c3,.tl3,!l;9L,,,,,,,,,,,,,,,,,,,,,,,',,,,',,,,,,,,'r,,,,,,,,,,,,,,,,,,,,,,,,,,
Rft ki M6$htain rP,+wer snline advffi sernent
R-,g,*yYollle=i".r.,9,,y9t
l,:,p1u",,0r,,.!,,,1t11iys,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
Family, friend, or neighb,oi i':,:.: " , '
:,,;,
Another business colleague
_\, ""f l:y lXg1"!4n roy 3r n ew sletter
ri:$;ip*ffi $uffi $dffi iiiini.fiffi 11ffi ffi I*#ffi Eft iiiffi #i
Table 31. Horq Farticipants Became Awartt ot the FinAnswer E,x
Rocky Mountain Power
Exhibit No. 5 Page 1 093 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
62%
,,,r6s1,, -,,, ,:,,,:,,, ,,,:, ,,,
O10.:: ,:,: ,,i : ii i:,:
ii.',: iiii::iiiiiii!!!i!!:!:,i!,:.!: ! t:%., :..
,o/
:l:tltltltlt:tltltilt:tl:::l!lt;;:,1::::::l'rytr::::::::i::.::: ::i::j'. . .: ::a::la::::::::::::::.a.':.. - -... -:
to/L/O
il:::::i:::::::::::::::::l:::i:Il :: :iii:l ::fi#:::::::.::i:i : :: .::E:::I6':,::,::::':' -: ::
i::::::::::::::::::::::::::::;:iiii:: lii i:: I i i:::
8%
sP
JZ
lil::i:::::::::::
:::tlti:'{iii
J
:::::::::::::|:|:
',i.,*t'
2
i;1t...
1
iiii.xj.ii
4
i:rlrlrlrl
D on' t kn ow/N "t r".e/ry.9..*.:..p...9-[1:
Total '1000/"
Participants reported a variety of motivations for their involvement with the FinAnswer Express
program, as indicated in Figure 5. Multiple responses were allowed; and respondents who gave multiple
answers were asked to identify their primary reason. The most common motivators were: saving money
on electric bills, replacing old or poorly working equipment, and saving energy.
Ir"rgure 5. h,trotivatir>n to .f]articipate in Fin.Answer [ixpress
To save money on electric bills
To replace old or poorly working equipment
-t
To obtain an incentive m
I
To improve operations, production, or quality il]
To save energy ffi;j
_I* i i : nprimary
Toreducemaintenancecosts ffi : i i USecondary
'_'j
To protect the environment ffi
-i
To replace broken equipment ffi
'iother'ffi i i i ! i+** ****-i.*............**..s-....*-......*.i**. --+^*-*-* - --i.* .*---*-{
051015202530
Count of Respondents
$.1.3 ProgranrParticipationFrocess
The majority of surveyed participants (46 out of 52) had completed lighting retrofit projects with the
program, going through the pre-purchase path. Three had completed non-lighting retrofits, and three
had completed new construction projects (two lighting, one non-lighting); these six participants went
through the post-purchase incentive path.
ss.i.&.uana--.* s.i*r*:r'*. I $'I \I X a ra+ i\n ti\r 1N $L"rf\i\. $
Participant responses indicate that the FinAnswer Express program functioned smoothly, and this is
described in more detail below. Participation will be discussed here in three logical steps: pre-installatiory
measure installation, and post-installation.
5.1.3.L Pre-Installation
Before participants install equipment with the FinAnswer Express program in Idaho, they may work with
a Rocky Mountain Power program manager or a vendor (who can be a trade ally vendor), depending on
the project. Although 36 of the lT4projects completed between 2009 and 2011 were completed with a
project manager, none of the surveyed participants had worked with a program manager on their project.
Forty respondents worked with a trade ally from the Rocky Mountain Power EEA on their project. This
includes 37 of the 46lighting retrofit projects, one non-lighting retrofit project, and two new construction
lighting proiects. As shown in Figure 6, respondents were asked to rate their satisfaction with the EEA
ally with whom they worked. Most respondents (83 percent, or 33 out of 40 respondents) were satisfied
with the trade ally, but 8 percent (three out of 40 respondents) were "neither satisfied nor dissatisfied,"
and 3 percent (one out of 40 respondents) was "somewhat dissatisfied." When asked why they were less
than satisfied, the respondents who were "neither satisfied nor dissatisfied" explained that they did not
save money, while the "somewhat dissatisfied" respondent said that the project took longer than desired
to complete because the vendor had run out of equipment.
Figure 6. Participr;rnt Satisfaction with their EEA Ally
Don't know/ Not
sure, 3%,Refused,
5%
Somewhat
dissatisfied, 3%
Neither satisfied
nor dissatisfied,
8o/o
\Arhen requested by the program administrators, an inspector conducts a pre-installation inspection. This
inspection is intended to document the equipment that will be replaced to ensure that savings are
calculated appropriately. Twelve percent of six respondents (six out of 52) recalled an inspector's visit to
their site before installatiory and all six were somewhat or very satisfied with the inspector conducting
the visit.
Roclry Mountain Power
Exhibit No. 5 Page 1094 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E.,'aluirtion oi Rock-v lr{ounlain Poure.''s li-} }ririi\nsn-ei Exirrerss Progiarn iPY 20{)9.?{}ii }45
Rocky Mountain Power
Exhibit No. 5 Page 1095 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
r\ i s\ \.. L$"* ..* \:: *T*:\ i +"]. \ .! s t r\i\,.".,, *L,N\-"$ s.\i\ I
5.L.3.2 Installed Energy Elficiency Measures
Installation of energy efficiency measures can include new installations or retrofits of existing equipment.
The majority of project measures (79 percent or 41 out of 52) replaced existing equipment. Another 13
percent of measures (seven out of 52) discussed with respondents involved new installations. The other 8
percent (four respondents) were unsure whether the measures replaced existing equipment. For the
projects that replaced existing equipment, the majority of equipment was working with no problems, as
shown in Figure 7.
Figure 7. ,$tatu.s ot Proiect Equip:ment InstaLlations
Don't
Know/Not
Sure/Refused
lYo
Existing
Equipment
Failed
2o/o
Existing
Equipment
Working, With
Problems
12o/o
:i
Respondents were asked about the benefits of the energy efficiency measures that they installed with the
program, both expected energy benefits and other potential (non-energy) benefits. The majority of
respondents indicated that the equipment was meeting energy savings expectations and was also
providing other non-energy benefits. The project equipment met the energy savings expectations for most
(38 out ot52, or 73 percent) respondents, while two respondents indicated the equipment was not
meeting energy savings expectations. Seven respondents did not know and four refused to answer this
question.
Forty-eight respondents (92 percent) indicated that the equipment was providing other benefits besides
energy savings; however, four of these respondents indicated energy savings when asked what the
benefit was. As shown in Table 32, 64 percent (28 of the 44 respondents) of the respondents with non-
energy benefits indicated higher quality of lighting as a benefit. Six respondents mentioned the quicker
turn-on time of the new lights, six respondents described less frequent replacement of lamps, and three
respondents indicated that they were saving money on energy costs.
Ii..,ralrraiioii ol iiork-", iVtouni,ain ir(r'r.r,u:i's il-] I:inAn:iwer i:.r;rles..; Irlog-.rirm ii*i ;:i)ili,t-")ijl i i
Tatrle 33" Non-Energy Benerfits of FinAnsrt'er
i( r i\ t ,. l c'* s \. i -rj: Ll )l t t-t d I r s.{ i \! It c..r i \ s \-.rs \l \ t
,luBi1jl |,1sntit8,,,9'
uli w,,,r,,,,,:ri,i,r,i,:,i,i,i,i,i,
:,i::,,,, i$nts.ii#Si .Ort iillt0rGl$urE&,|,,trf iiiiii: :iii jiiii
,,,f;oi'**"t..,1*",,P*l'.tt**1.......'r........iiift#iifigitinn 11li!ffriti€r,i idust$i::,:
lecleased,leat iouillut
Total 100"/"
Respondents were asked about their satisfaction with the measures that they installed through the
program. Nearly 80 percent (41 out of 52) of respondents indicated that they were very satisfied; 10
respondents were somewhat satisfied, and one respondent did not know, as shown in Figure 8. No
respondents reported that they were less than satisfied with the performance of the measure.
figure 8. Participant liatisfaction with Installed Measures
Not
sure/Don't
know,2o/o
Somewhat
satisfied,
19%
5.L.3.3 Post-Installation
After the measures are installed through the program, the program administrator may send a
representative to verify the installation. Fifteen of the surveyed projects had post-installation inspections.
When asked about the post-installation inspection, 47 percent of respondents (seven of 15 respondents)
were "very satisfied," 33 percent (five of 15 respondents) were "somewhat satisfied," and 20 percent
(three of 15 respondents) were not sure.
5.1.4 Frograrnlnfluence
The evaluation team asked participants several questions about the program's influence on the project
that they completed with the FinAnswer Express program. These questions can be grouped into three
general areas of influence: factors influencing the actual equipment installed as part of the project
(Influential factors), what would have happened in the absence of the program (Free-ridership), and the
program influence on future energy efficiency purchases (Spillover).
Roclq Mountain Power
Exhibit No. 5 Page 1 096 of I 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
64"/"
',:.!.i, : :r:', :t.:::::,':'::.i:,::':,t::::.:l:::iif[$ji:iiiiiiiiiiiiiiiiiiiiiiiiiiiii:ii::.i. .- .l'
,,,,,::,:,:,:,:,:,:,:,:,:,:,,:,::,:,:,::,,:]11::,:,
I:l.ialr-iation +i iiock-r. lr'tlountain F'(r..\,t'i's II-) IrinAnsir..ei ii,tl:ltrss lrrtrqri-rrn (llY 2009-:il1i j
si &v$teNT
5.7.4.7 Influentialfactors
Respondents were asked how influential seven factors were in their decision to purchase the equipment
installed through the FinAnswer Express program. They were asked to rate the importance of each factor
on a scale of one to five, with one being "not at all important" and five being "extremely important." As
shown in Figure 9, the Rocky Mountain Power incentive, contractor recommendations, and information
provided on payback were the most common influences on customer decisions to select the equipment
that they installed through the program. Corporate policies on energy savings and previous participation
in Rocky Mountain Power programs appeared to be least influential on the decision of which equipment
to purchase.
Figure 9. Iractors Influencing Preiject l)ecisions
5.L.4.2 Free-ridership
In order to determine to what extent the FinAnswer Express program affected installation decisions, the
survey team asked respondents what would have been different about their installations were the
program not an option. All participant responses are shown in Table 33.
When asked directly,lT percent of respondents (nine out of 52 respondents) stated that projects would
have been installed at the same efficienry and scope within the same year, while 37 percent of projects (19
out of 52) would not have been installed at all. Another 37 percent of projects (19 out of 52) would have
occurred, but they would have been either installed more than 12 months later, the measures chosen
would have been less efficient, or the project would have been reduced in scope. For the remaining 10
percent (five projects), participants were unable to characterize what would have occurred without the
program.
Rocky Mountain Power
Exhibit No. 5 Page 1 097 of 1 365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
Rocky Mountain Power lncentive
Contractor Recommendation
Familiarity with this Equipment
lnformation Provided on Payback
lnformation on Energy Savings
Previous Participation In a Roclry Mountain Power program
Corporate Policy for Energy Reduction
0510152025303540
Count of Respondents
i:i Don't KnoWNot Sure/Refused I Not at All
s Somewhat Unimportant i'j Neutral
tliSomewhat lmportant sExtremely lmportant
45
Evalr-ration ul i(ockr., N4ountain P(r*,er's ll-) Fini\nswer Er1:ress lrrsgla,rt iIlY 20i)9-:il1i i 48
rru $VXil-q NT
Yes
::ili;i:lli:r[lillliilll:llillltr#i:'.*iii
No
i:':' :,::ii:iii:iiiiiii:ii;:;:i.No[.:b"r.s#,:::.:::,::
,,rl.,.i..,r'. XUfused......:....:.',.
,..xJ'ffi,::na#ti.ffi. .,,;,.:. A*rd ,.,:.:::::::
No, Standard
.... at s*#m+ffiu....
-*$$**ffi****
Yes 2
,i . "i''il b*.nair, i............r.., r,,i
Rocky Mountain Power
Exhibit No.5 Page 1098 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. HYmas
7
r,.5 ,,i:i:::::: '
11
i$ii,iliiiii::i
Table 33. Froject Instaltrations in Atrsence n{ Fin-Arrs}t:-!*Ij1glll:
:: ::::' ilXeq
Yes
xxltt'+$ffi
i.;i .iltffi ii.,.i i .ilillil** lil{Il
Yes Lower, Half
ltltl::ti!:::::::::::
t!:iiilr:ii',il
.i.i.ii.iii.iH$.i,,,i,
Yes
'::. lSS:,,,'!l
l'ffiiii::l:iii::iix
No
:i:ii::::
l::i:i:i:
:ii:lli
:::lr:il
ii:i:::]l::i:lri:r:::iii:i:iii:iiii:if iiii::]irlri:ii:ii:i::iiiiiiiiii:iii
t7
'::::: .::ii.1:::::i:t,:::i:::i:i:i:i:i:i:i:::i:
:: .:::::::::::::::::: }:j:::::::l::::
5
Participants' statements about what they would have done in absence of the program were compared to
their statements about factors influencing their project. ln six cases, participants indicated that they found
the program incentive or assistance important in their decision, but then went on to say they would have
installed the same project at the same time. The evaluation team considered these responses to be
inconsistencies, and requested participants to explain the program's influence on their project in their
own words. Two of the six participants with inconsistent responses provided a description that indicated
that the program influenced the project. One of these two referred to the program as "the tipping point
that justified the installation." The other said the incentive allowed the project to increase in scope. Based
on these responses, these two participants are considered partial free-riders rather than full free-riders.
Based on participant responses and after adjusting for inconsistencies and prior Program experience, the
evaluation team determined that the majority of respondents were non free-riders, as shown in Figure
1.0.28
27 " Any project" refers to any similar project. For example, the customer would still have replaced an HVAC unit or
lighting.
28 This chart shows responses for 52 participants, including three who refused to answer influence questions. Note
that one participant's project contained two measures; this participant was asked about both measures. The
participant's responses indicate that the participant was a full free-rider for both measures. This breakdown does not
reflect overall program net savings, which are weighted for the savings of measures discussed with respondents.
il.;alri.:iion ol i(orki,' lr4or"inia:in .l:'(r,.r,!ri's Ii) IiirrAui:r.'vtti Ii,xi:ltrss Illogiam i|Y 20i)fl-liiil;t(i
Figure 1i). Idaho FinAnswer Express Frere-Riderstr.ip
5.L.4.3 Spillover
There is evidence of limited spillover from this program. One respondent indicated quantifiable "like"
spillover, and four indicated non-quantifiable "unlike" spillover. More detail on spillover is provided
here.
Eight respondents have completed "llke," or similar, projects since the project discussed in the survey.
Five of these eight had assistance from Rocky Mountain Power for their more recent projects; these
responses indicate that the program is attracting rePeat participation.
Three respondents completed a similar project since the one discussed in the survey without assistance
from Rocky Mountain Power or any other entity. Two respondents said the project was of the same
efficiency and one declined to respond. When prompted with the statement " My experience with Rocky
Mountain Power's FinAnswer Express program influenced me to install high fficiency equipment on my own,"
two respondents "neither agreed nor disagreed" and one "somewhat agreed" with the statement. The
one respondent who "somewhat agreed" with the statement after installing equipment without
assistance represents quantifiable program spillover.
Ten respondents had completed "unlikg" or dissimilar, projects since the project discussed in the survey.
Half of these (five respondents) had assistance for these projects, three of them from Rocky Mountain
Power; these responses indicate that the program is attracting repeat program participation. The other
five did not have assistance. When prompted with the statement " My experience with Rocky Mountain
Power's FinAnswer Express program influenced me to install high efficiency equipment on my own," two
respondents "completely agreed," two respondents "somewhat agreed," and one respondent "somewhat
disagreed." The four respondents who "somewhat" or "completely" agreed with the statement after
installing equipment without assistance represent non-quantifiable "unlike" program spillover. These
respondents installed motion sensors, and HVAC equipment. When asked why they did not seek
assistance from Rocky Mountain Power, they provided the following reasons:
" It took less time to do the project without the program;
Roclry Mountain Power
Exhibit No. 5 Page 1 099 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Il.r,'ah-iatior-, cL ilockv lvCounlair.. P*lr,rt,''s ll-) IrirrAn:ti,trtr ii,ri:ltss l'rttgtir:rn i.PY 2ilt)li'liliii ilr
\hr.s\\,'$ils \l T
Didn't think about the incentive;
Heard the incentive was minimal; and
Was not aware incentives were available for the measure.
5.1.5 Further Energy Efficiency CIpportunities and Earriers
To assess additional energy efficiency opportunities with the surveyed customers, respondents were
asked if they thought there were additional energy efficiency improvements their organizations could
make. Twenty respondents (39 percent) affirmed there were additional energy efficiency opportunities.
When asked what these improvements might be, 16 respondents indicated the 19 measures listed in Table
34 (three respondents were not sure and one declined to respond; multiple responses were allowed).
Respondents most commonly mentioned additional lighting improvements or lighting controls. Twenty-
five respondents (48 percent) stated that there were no further energy efficiency opportunities for their
firms, and seven (13 percent) were not sure or refused to answer.
Roclry Mountain Power
Exhibit No. 5 Page 1 1 00 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Tatrle 34. Potential Furth*r EnergS, Efficienc.v S{easures
Additional Lighting
Ei$htingGontrols ,,,,,,
Motors
ffi$erior,Lighting i:,,:,,ii::
Building Shell (Insulation & Windows)
5
ii.i::i.:i::i..:.i:::.:.:.:.:.i.:.li'::.:::il:1,i4::l:":::',:':':,:::,',,,:,;,:i::Nl:,:,::
3
':'::':':':':':':':':'::::::il:1,::.]1i::i:':i:j,]::,
a
26%
i.i.gti%,iiur,i..'rli,
16%
.iXti{fl's'.] iji;.:r:::
t1%
i.::15, ;;::;i:iiirrr:::rr:r:
Ist**19 lOO"/"
Of the 16 respondents who identified additional energy efficiency improvements, six indicated that plans
were in place to make these changes. Of these six, three said that incentives from Rocky Mountain Power
were part of their plans. When asked about factors preventing them from making these changes, two
respondents did not identify any barriers. The other 14 respondents identified high upfront costs (10
respondents) and their lack of access to the necessary capital (four respondents) as barriers.
5.2 Near-ParticipantFindings
The evaluation team interviewed one FinAnswer Express near-participant in Idaho. Near-participants are
those customers with a project in the project tracking system for the FinAnswer Express program during
2009 through 2011, but the project is identified as cancelled or on hold as of the end of 2011. In total there
were six near-participants in Idaho in the 2009 through 2011 period; however, only three of these were
considered eligible for the survey because they had not completed any other projects with either
FinAnswer Express or Energy FinAnswer. Of the three eligible near-participants, an interview was
completed with one near-participant; the other two near-participants were not available to be
interviewed.
The respondent categorized her organization's activity as public administration. The organization
employs 10 people, and its electricity bills account for approximately 10 percent of operating costs. This
respondent learned about the program from Rocky Mountain Power staff and decided to participate to
save money on electric bills.
I:.t llli"iiioi, i:i ii,:l.il i'.ltr:niairi i-J{}."r,,::!"s ii.) }:iii,\n,irr,r'i i:.\irrt{,s i'ilriilrnr (l)'i .ii)i]9.:i)l i i :r!
N .-\V Xi:.\ \'T
The respondent reported that the project has been "on hold," but the organization plans to complete the
lighting project it started with FinAnswer Express using either FinAnswer Express or Energy FinAnswer.
The project was placed on hold because "at the time it wouldn't pay out, but now it seems like it will."
Overall, the respondent has had mixed satisfaction with the program so far. The respondent reported she
was "neither satisfied nor dissatisfied" with the FinAnswer Express program, but was "very satisfied"
with the program representative who visited the municipal facility. Lack of satisfaction with the program
was reportedly due to the amount of time it required. She mentioned having to escort the person
conducting the site inspection to each individual light fixture. On the positive side, she reported
contacting Rocky Mountain Power with questions and/or requests for assistance during participation in
the FinAnswer Express program and found the contacts to be both knowledgeable about the program
and timely in their responses. She also commented that Rocky Mountain Power's account representative
attends city council meetings once or twice per year and is very helpful.
The respondent reported that high up-front costs and long paybacks hinder work on potential energy
efficiency projects. She indicated there were additional steps her organization could take to improve
electric efficienry, including, perhaps, pumps and streetlights, but she was unsure whether any plans
were in place to make such changes
5.3 Non-Pafticipant Findings
In May and ]une of 2012, the evaluation team surveyed 123 program eligible Idaho firms that did not
participate in any Rocky Mountain Power programs between 2009 and 2011. Recall from the
methodology that generalizations to all non-participants are weighted because the distribution of
commercial and industrial survey respondents is not the same as the distribution of all quali$ring non-
participating customers.
All of these firms were in qualifying rate schedules for the program. Table 35 shows that most
respondents were under schedule 23.
Roclry Mountain Power
Exhibit No. 5 Page 1 101 of 'l 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Tatrle 35. Count of Non-Farticipant Respondents by Qualifying l{at'e Scheclule
6
iliiii:6'A::;i:i]l::::::i:iiiliiiil:::i::.ii:::i
7
iiiiiiir#ii::iiirl:::::::;i:::iiii::::iiiiiirllii::i
9
.i.).:,,,:' : ....iii
: i: i: i: i:: :: i:: ,:: i:;::: i: l: l::::::::::: i . : :::: i: i :,1: i: i
t9
i!:::::23l]:i!iiiii i:]::.i::::i:l:::::::.:;:]::
23r'.
iiiiiiif4i:ii:|:iiiilil]::::::::i:iii.;]::iiiiii]]]]i:
35
tr,P-*Po ",ru,u.uffiTotal
55
i:i::i:ii:
11
!t;,iu,;|
1
:::l:l:|]
50 1iCI3
11
Iiiiiiiiiiiii
1
50/3 123
In order to understand the value of electric efficiency to non-participants, the evaluation team asked
respondents to identify the portion of operating expenses represented by electricity costs. Less than half
(59 out ot123) of Idaho non-participating firms was able to provide indications of the extent to which
i:.,;aiiiaiioi"r ol. i{ockv \{*lrniaili l:'c'n,i.'i':: iil i::lrrAni;i..r,ei i:..r.i:lt-s:: Irrt:!..tuni iP i'' I0t}9.iiii i i
Rocky Mountain Power
Exhibit No. 5 Page 1 1 02 of 1 365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
R r,u[ *,. . a'* .{ s. i -"**
i\l j +. ti S \ \ t{ j\: sl \ .J,, $- .i \^.-l i \ t \. $
their electric bills made up their total annual operating expenses. In total, these proportions ranged from
0 - 100 percent. Approximately 80 percent of respondents had bills that accounted for 20 percent or less of
their firms' annual operating expenses. The mean portion of operating costs represented by electricity for
non-participants was 10 percent, which is not significantly different from the portion identified for
participants (13 percent).
The majority of responding non-participants represent small firms. As seen in Table 36, 43 percent of non-
participant firms employed fewer than three people. Only two firms had 100 or more employees.
Iahle 36. Siz* nf Nnn-Participant Firrns, by Numb*r of Hmployees
Less than 3
**tffi.'.**-i............................i.i...i..ii-......i......
10 to less than 100
ffiiiffi1iffi9Tl:::::::+l =.
:.:.:,ll.l.
Greater than 1000
,,,Siot,,sure#Bonlt rrcb*vffi *ffi sEd
31
-..i.ii.ii.i.ii.ii.iiiiiii.-*i
12
23
,,:::::,,,:,,::,:!.,,,,,:, :1.,:,i..!q!,!:
iiiiiiiii:ii:iii:xiixffi ::lii
10
ri i.
0
::::::::::::::::::i-+, j:::::::::::::::::::::::::::::::i::tl
U:rc':i.rtr''::::::::::::::"': :
i.i.i.i.i.i.i.iiririti:.l.i.i.i.l.l.l.l.,i,ri:iii
Total 100%
Non-participant respondents represent diverse industries with the most common responses being
agriculture, retail, and professional services. A small portion of respondents (a weighted 3 percent,
overall commercial and industrial respondents) indicated that they were not representing a firm, but a
household; these respondents may have non-residential meters because of wells or shops on their
property. Figure 11 shows the distribution of primary activities for the surveyed non-participant firms.
[;igure 11. Primary Act"rr.itr- for Non-.f'articipating ll.esponclents, by Custumer Class
50/3
Weighted Total (n=123)
lndustrial (n=50)
Commercial (n=73)
!I
I
+*.-
0o/o
x Dairy/Agricultural
s Professional, scientific, and technical services
s Food services/food processing
'n Manufacturing
t Other(S or fewer respondents each)
40o/o 50Yo 60%
Percent of Respondents
s Retail
* Real estate
30o/o20%1lYo 70o/o 80o/o 90o/o 100Yo
s Arts, Entertainment, and Recreation
u Residence
'-'Not sure
li...alr-r"rIioii *i. iiolrv N{ouniatn l:i(r.,r'i]v':: I'i.) }:tr''Ani;ir'tti ii.rirrtss {)ii}giiri-\t ii)Y ?i){)t'.:ii1 I j -1.-'J
& I :t\ I .. ,tr $:'a ,{ N f -t*i\:i .tr- '1 t.r+ $ t . dj\ l\i i{\,"i:$I\.I+\l\$
S.3"1 Awareness of Rocky Mountain Fower Frogranrs
\A/hen asked if they were aware that Rocky Mountain Power offers incentives and technical assistance to
help consumers reduce electricity usage, 41 percent of non-participating respondents affirmed they were.
Three respondents indicated that they did not know or were not sure if they were aware of any Rocky
Mountain Power programs. These have been included in the count of respondents who said they were
not aware of programs. As seen in Figure 12, awareness was significantly higher for the Commercial class
respondents (at 43 percent) than the Industrial class respondents (at 28 percent).
Figure 12. Non-Farticipant Awareness of Rocky Mountain Porver Programs and Services
41% i
Commercial All Non-Participants
r Aware that Rocky Mountain Power offers Assistance to lmprove Energy Efficiency
B Not aware that Rocky Mountain Power offers Assistance to lmprove Energy Efficiency
Those respondents who were aware ihat Rocky Mountain Power offers incentives and technical
assistance aimed at helping customers reduce electricity usage were asked to identify what programs or
services Rocky Mountain Power offers customers in their class. This was an open-ended question;
customers were not prompted with a list of programs and were allowed to name as many programs or
services that they could. Over half (26 out of 45) who were aware that Rocky Mountain Power offers
incentives and technical assistance were not able to identify a particular Rocky Mountain Power program
or service that would be available to them. The remaining respondents who were aware of programs
provided 23 responses; about half of those responses (12 out of 23) indicated awareness of incentives for
efficient equipment, as shown in Figure 13. One respondent identified the FinAnswer Express program
directly.
Figure 13. Non-participant An'areness ol: Prograrns and Services, by Custorner Class
Appliance/Equipment Pick Up and Disposal
I
NCommercial
E! lndustrialFinAnswer Express
Renewable Energy Programs
lrrigation Energy Savers
Demand Response/Load Control
lrrigation Load Control
lncentives for Efficient Equipment
Not Sure/Don't Know
l Count of Respondents
Rocky Mountain Power
Exhibit No. 5 Page 1 103 of 1365
Case No, PAC-E-14-07
VMtness: Kathryn C. Hymas
i***--
I
Ii.r! -f,'!,!
i l,.':!:!I I.i.l 1,,;:i\i
i
N
^i"..Nffi
N:l::fNit*3
kwW
30
E.ialuaiion ol. Rock'.; N4ounla:in Pfr.r,r,.'ei"S Ii-) I:inAnsiver Express l)roBra.rn iPY 200 -:0ii i
,\*" ] Jq \ ,r N s"'* A h. i'\*
When these responses are weighted to represent the population of non-respondents, it is clear that only
small percentages of non-participants are aware of any specific programs, as shown in Figure 14.
FinAnswer Express makes up less than 1 percent of responses and is included in "Other." More than half
of all non-participants (61 percent) who were aware that Rocky Mountain Power provides some
assistance for improving customer efficiency were not sure of any specific examples.
Figure 14. JNnn-participant Arvareness of Programs and Services, flverall
Renewable
Energy
Programs-60/o \
lrrigation
Energy
Savers
3o/o
lrrigation
Load Control
4o/o
Roclry Mountain Power
Exhibit No. 5 Page 1 1 04 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ta:ttiil;:
Figure 15 shows how non-participants, who were aware that Rocky Mountain Power offers programs,
indicated hearing about the programs (multiple responses were allowed). The most common source of
program information (29 percent) was from Rocky Mountain Power printed materials - forms or
brochures. The next most common response (15 percent) indicated learning about programs directly from
Rocky Mountain Power staff or program representatives.
liialr-i"-ri'ioii i:ll !{ock',' Ntlountain l:tgr'.a:g;"5 li) }:inAnsi.vei il.rirlr,-qs; l)rogianr il}Y:0i.\!;Lliliiii
,N $V $il* s\ NI T
Figure 15. How Non-Participants Htrard ahout Rocky Mountain Power Programs, Clverall
Trade ally, vendor, or contractor
ln the news
Public official
Print advertising
General knowledge/personal research
Online advertising
Don't know/Not sure
Rocky Mountain Power website
IV advertising
ts*
lPrevious participation in Rocky Mountain Power programs
Accompanying billing
Rocky Mountain Power newsletter
Word of mouth
Rocky Mountain Power representative
Rocky Mountain Power printed materials/broch ures
Respondents were also asked how they would prefer to learn about Rocky Mountain Power programs.
Figure 16 shows the methods through which respondents prefer to learn about Rocky Mountain Power
programs. Email accounted for the largest percent of responses (27 percent). The next most commonly
preferred methods were program advertisements in mail (15 percent) and printed materials/brochures (15
percent). Another 11 percent prefer to hear about program opportunities over the phone.
Figure 16" Preferrecl Methods to Learn about Frngxams and Opportunities, Clveraltr
TV advertisement
Print advertisement
Rocky Mountain Power website
Rocky Mountain Power representative
Accompanying bills
Rocky Mountain Power newsletter
Don't knoMNot sure
Phone
Rocky Mountain Power printed materials/brochure
Mail
Email
10o/o 20Yo 30ok 40o/o 50o/o 600/o 70Yo 80o/o
Weighted Percent of Respondents
The evaluation team compared how non-participants who are aware of Rocky Mountain Power
opportunities to the communication methods preferred by non-participants. Figure 17 shows both the
way that non-participants became aware of programs and services and the way that non-participants
prefer to hear for all the ways that non-participants prefer to hear about programs and services. There is a
disparity between the two, with no respondents indicating that they heard about the program through
ii.ialu"rtior.. ol iiockv N4oulriain Pe\r,ei's II-) Iini\nsr..r'er Iixi:ress llrtrgram (ilY 20{}9-?i}ili
Roclry Mountain Power
Exhibit No. 5 Page 1 1 05 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
0% 10Yo 20Yo 30% 40Yo 50% 60% 70o/o 80o/o 90%100Yo
Weighted Percent of Respondents
***-****--*-!
ii!ii:
IJll
:jri!ii:iliiii
il!:iilriiti
ii:iiriiili
ii!il!
ii:iii
*..|"ry{:
!90o/o 100o/o !
i'.4_
tui $kr.{:$d'*.6. \i-$'::'\.t $':R P.+ I * iA t\l ti \ .,t'':r $ $ \*S,r \ i \ .i.
email or mail, the most preferred methods. Three methods have about equal representation from both
groups: accompanying bills, print advertisement, and the website. It appears that printed materials are
effective means of communication when they are noticed by these non-participants.
fiE;ure 17. Preferrecl versus Actual lvlethods of Program Arvareness
Rocky Mountain Power
Exhibit No. 5 Page 1 106 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mou ntain Power printed materia lsi/broch u re
Rocky Mountain Power representative
Rocky Mountain Power newsletter
TV advertisement
Print advertisement
Rocky Mountain Power website
Accompanying bills
Phone
Mail
Email
0o/o
ItHow Non-Participants Prefer to Hear (n=123)
10o/o 20Vo 30Yo 40o/o 50o/o 600/o 70o/o 80Yo 90yo 100%
Weighted Percent of Responses
il How Aware Non-Participants Found Out (n=43)
5.3.2 Non-ParticipantEnergyEfficiency!mprovements
Non-participants were asked a series of questions about energy efficienry actions or improvements that
they may have taken during the program years of 2OO9 ro 2011. These questions were in regards to: high
efficient equipment purchases, load or demand reduction efforts, and systematic evaluations or energy
analyses of existing facilities.2e
Five respondents (three commercial and two industrial) indicated that their facilities were constructed
since 2009; these respondents were the only ones asked about efficient new constructiory and they were
not asked about other improvements. Of these five respondents whose facilities were constructed since
2009, two (both commercial class) had installed high efficiency equipment when constructing the new
facility.
Of the 117 non-participants with existing facilities in 2009, 16 percent indicated that their firms installed
high efficiency equipment between 2009 and 201.1, as shown in Figure L8. The high efficient equipment
installed by non-participants included lighting, appliances, HVAC, and VFDs (variable frequency drives.
2e Respondents who reported taking energy efficiency actions or improvements were asked if they had received
assistance from Rocky Mountain Power. The evaluation team assumes that this assistance is not in the form of
program participation because the non-participant list was crosschecked with the participant tracking data by Rocky
Mountain Power.
E..raluation ol Rocky lvlouniain Pcrwei"s ll-) FinAnsvr.,er iJxirress Program (PY 2009-:0ii,}
Rocky Mountain Power
Exhibit No. 5 Page 1 1 07 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C, Hymas
Commbrcial
rYes, purchased or installed high efficiency equipment between 2009 and 2011 without assistance from Rocky Mountain Power
slYes, purchased or installed high efficiency equipment between 2009 and 2011 with assistance from Rocky Mountain Power
tr No, did not purchase or install high efficiency equipment
N Not applicable/New facility
A weighted average of 6 percent of non-participants indicated that they implemented load control
strategies for their facilities. One-third of these (2 percent overall) indicated having assistance from Rocky
Mountain Power, as shown in Figure 19. Participant responses did not clearly identify strategies to
reduce load during peak periods.
Figure 19. Non-part'icipant I"oad Control Strategies in Existing Facilities
All Non-Participants
rYes, implemented load control strategies between 2009 and 2011 without assistance from Rocky Mountain Power
NYes, implemented load control strategies between 2009 and 2011 with assistance from Rocky Mountain Power
El No, did not implement load control strategies
N Not applicable/New facility
About 4 percent of non-participants indicated that they conducted a systematic evaluation of their facility
in order to identify chances to improve energy efficiency. Three-quarters of these (3 percent overall)
indicated that they received assistance from Rocky Mountain Power to conduct the evaluation, as shown
in Figure 20.
Alt
4o/o4o/o
\
I
I
I
Figure 18. Non-Participant Fligh Efficierncy Equipment Furcha.ses in Existing Facilities
Commercial
ll.:alr-ratioii ol l(ockv \4ouniain l)(rr.r,$i's Il-) I:irrAn,;rvr:r'i:ri:rr-rss ilrog-iam iP'r'2ilt,\!r-:{1ii j
Rocky Mountain Power
Exhibit No. 5 Page 1 108 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
:T$L.l S\\,,'{s"* A NI}:i\,,3 \\'$\*J".'\l\ $
Figure 20. Non-participant Systematic Hvaluations of Existing Facilities
All Non-Participants
rYes, conducted a systematic evaluation between 2009 and 2011
ElYes, conducted a systematic evaluation between 2009 and 201'l
E! No, did not conduct a systematic evaluation
N Not applicable/New facility
Non-participants who indicated that their firms installed high efficiency equipment, implemented load
control strategies, or undertook systematic evaluations of existing facilities between 2009 and 2011 were
asked what motivated them to take that action. Figure 21 shows the motivations respondents indicated
for each action and the weighted overall responses. The three most frequently cited reasons for making
efficiency improvements were "to save rron€/,", "to replace old or poorly working equipment " and "to
save energy'' which represented 32 percent, Z2percent, and 18 percent of responses overall, respectively.
Figure 21. Non Pa.rticigrant lvlotivations for Pursuing Efficienry Improvements
Overall
Systematic Evaluation
Load Control
High Efficient Equipment
0% 10Yo 20% 30o/o 4Oo/o 5Oo/o 600/0 70% 80Yo 90Yo 100Yo
Weighted Percent of Respondents
without assistance from Rocky Mountain Power
with assistance from Rocky Mountain Power
ETo save money on electric bills
ETo save energy
eTo protect the environment
rRocky Mountain Power initiated iUjust did it
gTo obtain an incentive
aTo replace old, broken, or poorly working equipment
ITo acquire the latest technology
trTo improve operations, production, or quality
ETo improve security
E Recommended bv contractors/trade a
Those respondents who had installed energy efficient equipment or conducted a systematic evaluatiory
but did not apply for assistance from Rocky Mountain Power, were asked why they had not. While this
evaluation focuses specifically on the FinAnswer Express program, Rocky Mountain Power also offers
the Energy FinAnswer program to eligible customers in Idaho. Both of these programs offer assistance for
systematic evaluations and high efficient equipment. Reasons for not applying for load control strategies
in Idaho are not relevant because Rocky Mountain Power does not offer load control programs for
commercial and industrial class customers in Idaho (but does for irrigation class customers). Figure 22
shows the reasons that respondents indicated for not applying for each action and the weighted overall
responses. The most common response overall (45 percent of respondents) was that they were not aware
that assistance was available. The next most common response (27 percent of respondents) was that the
[iraluatior', ot Rock,v N{ountain l}o'n,c!''s IL} FiriAnsr,r.,er i:,xirrt.ss l}rogram ii}Y 20t)9-3i}1i.t
Rocky Mountain Power
Exhibit No.5 Page 1109 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
{:\ i,,i\ \ .t \ s-"' .i \ i *\*'
respondent did not know or was not sure why they had not applied. Others indicated that they would
not qualify, did not think it would be worthwhile, did not think they would qualify, or forgot about it.
Iiigur* 32. l{h-r Die{n't Non-[]articipants Applv fcr Assistance from ltockv N{ourntain P*wer
Systematic Evaluation i:!
;*-,-.-.-,.-.-,.-.--,.,.,-.;,.,.-.-.-.-.-.,-.*--.riq.a,.r.,-.o,.-,a-,-i - i -:'
High Efficient
Equipment
i------------i------------i--------iii
100Yo
S"3"3 Further Emergy Hfficiency CIpportunities amd Barriers
About 27 percent of the non-participating respondents indicated that they believed their firms could take
additional steps in order to increase electric efficiency. |ust over half (51 percent) stated that they did not
think their firm could make additional energy efficiency improvements. The rest (22 percent) were not
sure, as shown Figure 23.
Figure 23. Non-Participant lndication of Further Energv Eificienq,-Opportunities
All Non-Participants
When asked for examples of measures respondents' firms could implement in order to increase electric
efficiency, "purchasing more efficient appliances, equipment and lighting" was offered by 13 percent of
non-participants, as seen in Table 37.
20% 40Yo 60Yo
Weighted Percent of Respondents
ENot sure/No response Nwould
not worth it sl Didn't think about iUforgot o Didn't
80Yo
not qualify
know if qualifled
Purchase more efficient equipment/appliances/lighling
ba;[. "$#n*dbr
j";ffiiilh[y li:uquip*entpags ,.', ,"...,.,.'.,'....,.,,.,',
Ins!111 "dislribuled
generatiorr/smalJ;scaJe renewable en"tgy,,,=
Technical assessment/energy analysis
tJglitiit Kngw.fftgtilD-ure . ..',ii.,':l:. . . :.,:.: .':'::,',:,: :::::'::::' '.: :':
1.3%
i.3%i..
J10
1,$,?/a,,,
1.%
:,,*:Ya,:,
""-N-9."1=np-.t"Ys*T...e.=lsTotal
Commercial lndustrial
Ta b le 37" Fotenti al lll ectri c F,f f ici ency kn6: rovem.ents
11..,'* I r-r l t ioii t i iior kv \'{ riu n i'a i ir ir{rr'r' i: r-' s
100%
ir*o."^-'*Rd:.*::\ I $1 \ ,' \ f, i:\ \.: tii \:l "s \ \..i $ i . r.\ :\: $i\:J i\.t\N,i\l\ t
As shown in Figure 24,66 percent of respondents across all classes who indicated that they believed their
firms could take additional steps to improve electric efficiency did not have plans in place at their firms to
implement such projects. Respondents with plans in place were split on whether they intended to
implement proiects with Rocky Mountain Power assistance; 5 percent reported having plans in place and
intended to apply for assistance from Rocky Mountain Power, while 19 percent had plans in place but did
not intend to apply for assistance from Rocky Mountain Power.
Respondents who believed their firms could take additional steps to improve electric efficiency were
asked what might prevent them from implementing electric efficiency improvements. The most common
potential barrier, more than half (63 percent) of all responses, was "high upfront costs." Non-participants'
next most common potential barrier was a "lack of access to capital" with 10 percent of responses. Table
38 shows barriers identified by Idaho non-participants.
Rocky Mountain Power
Exhibit No. 5 Page 1 1 10 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Figure 24. Indicaticn of Plans to lmplement Electric Efficiency Proiects for Non*l'articipants
E$Yes, plans in place to implement projects - with Rocky
Mountain Power assistance
EIYes, plans in place to implement projects - without Rocky
Mountain Power Assistance
B No, plans not in place
nDon't Know/Not Sure
Table 38. Rarriers to Inplementing Elertric E.fficiency lurprovements
High upfront costs
Long payback period; slow rate of return
....,{"ow
p-o - tack of..in[errest,,of senior man$,[*enttUn1,1A1ng:ow*i
Lack of information about savings and performance
Don't know/Not sure
63"/"
::U./01:.'.. r'. :: :
tlll:llltl:lt:t:ll::t:t:t:tl:lt:t:!:l:i:
5%
.SB6f r t,.
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r'5Pl' l.ii..,i.l
1.0%
Total '1,00"/"
I\,'aliiation oi i{oc,kv N4ourrtain P+'ln'r:.r's il-J i:iiri.\nr;r.rr:i i:ri:rt.:.;s: i)rt;*iam ii}Y 2i}i)li.li}ii;
Pd $\t' til.q N T
O 5.4 Traile Ally Findings
In july and August of.201,2, the evaluation team interviewed ten vendors and contractors who had signed
up to be part of the Company's Energy Efficiency Alliance, including two that performed work in Rocky
Mountain Power territory in Idaho.30
In the program tracking data,25 vendors are identified as trade allies and pafiners on projects in Idaho.
About 64 percent of these trade allies completed just one project, as shown in Figure 25. The data also
show that three of the trade allies completed projects during all three years, two completed projects in
two years, and 20 completed projects during just one of the three years. In total, five trade allies
completed projects in 201.1., compared to 16 in 2010 and 12 in2009 .
Figure 25. Trade Ally Activity hy Vendor {20t}9-3011}
60
C'
Ssooo$l>40o.
E
E.o
CL
E
920I
.1roo
o-
0
i:n2011
N201 0
r2009
7 8 9't0 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Trade Ally identified in Program Tracking Data
5.4.1 OveraNlSatisfaction
Nine of the trade allies interviewed reported being satisfied (three were very satisfied) with their
experience with the program and the remaining trade ally was neither satisfied nor dissatisfied.
Trade allies see the program as an opportunity to help customers and have a favorable view of their role
in the program. Three trade allies had suggestions for improving the program. These included being
more discerning on including firms in the alliance, providing special advantages for allies over other
vendors, and providing more frequent contact between program staff and trade allies.
Most trade allies were not able to identify similar programs to compare their experience between
FinAnswer Express and others. One trade ally who works with FinAnswer Express and also incentive
programs for public utility districts noted that the FinAnswer Express program was, "always the cleanest,
simplest, and most straightforward."
30 Additional trade allies were not interviewed in Idaho because data saturation was reached, and findings did not
vary geographically.
Rocky Mountain Power
Exhibit No.5 Page 1111 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E}ralualion ol Rock-v N.tlr:runlain P(rr't $r's Ii-) IririAnsr.t'er hixpr:ess lrroglam ilrY 2009":0i1)ni
*ru,qvxil-qNT
5.4.2 Frogram Awareness and Motivation
Trade allies are finding out about the program through several avenues; no particular avenue appears to
be the most effective. Two leamed directly from the Company, two learned through a customer, three
found out about it through word of mouth, and one searched for it. Two trade allies did not remember
how they first became aware of the program.
Trade allies are motivated to work with the program because they see it as an opportunity to provide
value to their customers. About half of the trade allies described their motivation as a win for all parties:
themselves, the customer, and the Company.
5.4.3 Training, RoJes, and Cornmunlcatisn
About half of the trade allies interviewed had some kind of training from the Company when they first
started working with the alliance. Others had on the job training. Most allies (six of 10) attend annual
workshops, while two indicated that other people in their shop attend. All trade allies indicate that they
understand their role in the program.
All trade allies noted that they had a primary contact with the program and they prefer email
communications - which they get from their trade ally coordinator contacts. Eight trade allies described
communications as good or very good, while two described contact as minimal and would prefer more
contact from the program representatives. All ten of the trade allies agreed that their contact could
answer questions that they had or get them to someone who could do so. When asked to rate their
satisfaction with their primary contact, six trade allies were "very satisfied" and the other four trade allies
were "somewhat satisfied."
5.4.4 Marketing
Trade allies use the program to market their services to customers. Mostly, this is in the form of letting
customers know about the program and associated incentives when discussing project options. The
program eligible equipment is often more expensive than the standard equipment, and the incentive can
influence customer's purchasing decision. Trade allies were asked how the program helped their sales.
Six trade allies said that the program helped customers choose to buy more premium equipment; one
stated that it was hard to tell what drove customer decision-making, and three trade allies said they did
not know.
All but one of the trade allies indicated having program-marketing materials, either brochures or other
printed materials. Five trade allies indicated that they use these marketing materials to highlight the
incentives available on higher efficienry equipment; the other half did not use the marketing materials.
Two offered suggestions to improve the program marketing: one noted that marketing materials had a
competitor on them, so he/she did not like the materials; the other would appreciate inclusion of local
trade ally names in radio marketing.
The lighting trade allies all agreed that they, or others at their firm, use the FinAnswer Express lighting
tool when selling projects. Most lighting trade allies used the lighting tool to show customers the
potential savings from participating in the program, but one trade ally noted that he/she would only use
the lighting tool for customers who were interested in the program. The lighting tool output summary
helps them sell projects because it is essential to the application for the incentive, but also because it
identifies the estimated energy savings and incentive. All but one of the lighting trade allies is happy
with the performance of the tool. The trade ally that was not happy with the performance of the lighting
Roclry Mountain Power
Exhibit No. 5 Page 11 12 of 1365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
Erialu;rtioii oJ RtNkt' Nlounlain P(rlver's Ii-] I;inAnsir,,er E:xi:ress Illogram iPY 2009-ti)1i l
,I$tr) riB\sr.fh s \1.*t-i\$*r\t$Lr.s\i\ $
tool prefers to use another spreadsheet tool that he/she used before working with the FinAnswer Express
Program.
5.4"5 Customerlnvolvement
The trade allies state that customers typically find out about the program from them, with about 10
percent to 50 percent of customers have some idea about incentives being available for efficient
equipment before they engage the trade ally. Most projects start with the customer contacting the trade
ally; however, trade allies note that customers, especially for lighting projects, do not have complete
projects in mind. Half of the trade allies indicated that they are able to suggest changes to proiects to
increase the efficienry of what the customer envisioned. Some technologies do not have a range of
efficiencies with which to adjust, such as: automatic milker takeoffs, green motor rewinds, and variable
speed pumps.
Trade allies do not identify any differences in their work with customers working with the program and
those not working with the program outside of explaining program specific details. Trade allies describe
similar sales strategies and customer service actions for both groups. For customers working with the
program, trade allies often need to explain the program steps to the participant. Customers mostly ask
trade allies about the size of the incentive and how long it will take to get the incentives. Most trade allies
also fill out the incentive forms for the customer, so that the customer only needs to add identifying
information and sign the form. Only one trade ally identified having challenges in addressing customer
concerns towards the program; this trade ally stated that customers find delamping difficult to
understand, so he/she will often have to demonstrate the idea by delamping a portion of their facility.
5.4.6 Effects of the Frogram
Trade allies were able to describe the program influence on their activities, as shown in Figure 26.Trade
allies find the program incentives influential, and seven trade allies agreed that the program incentives
had influenced their selling of program-eligible equipment. For the eight trade allies who stock
equipment, four indicated that the program incentives had influenced their stocking practices. Trade
allies do not attribute much influence to program information; seven of ten trade allies said that the
information provided to them by the program did not influence their sales of program-eligible equipment
at all.
Figure 25. Program Influence on Trade hlly Sales and Stocking
i Pr*$r*rn *ffis$ilrm* inff{s$n*s
stsiltln$ sf Srogfn$r *ti$iblsi e,qulsf$8nt
Rocky Mountain Power
Exhibit No. 5 Page 1113 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
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When asked how their sales of program-eligible equipment would change if the FinAnswer Express
program did not exist, eight trade allies indicated that sales would decline and two were not sure. Four of
Il.ialr-iatioii ol i(ockv \.{ountain Per.ti:.r's II-) I:inAni;r.r'er Ex1:ress I'rtgiam iPY z{li.!lr-:{,ii1j
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the eight indicated that their sales would be dramatically lower, with two of these indicating that their
business would be severely diminished or no longer in existence.
The majority of trade allies (seven of 10) indicated that they did not sell any program-eligible equipment
in 2011 outside of the program. The three that indicated that they did sell some program-eligible
equipment without incentives stated that they were small projects; two trade allies reasoned that
customers did not participate because the incentive was not worth the effort of the paperwork while the
other did not identify a reason.
Four trade allies noted more program-eligible equipment sold in 2011 than in previous years; one stated
that this was due to a large project and another said that their business was growing. When asked about
trends over time related to the efficiency of purchases, half of the trade allies indicated greater awareness
of energy efficient options, such as LED lighting and variable speed drives. One trade ally summed up
the sentiment, "We have two different kinds of customers: Those that want the cheapest product, and
those that want the most efficient; we [are] seeing more of the latter now due to increasing efficient
options." The other half had not noticed any trends in purchases.
5.5 Ooerall Process Finilings
From May through August 2012,t}l.e evaluation team surveyed or interviewed 176 customers:52
participants, one near-participant, and 123 non-participants. The team also interviewed 10 trade allies.
This section first summarizes answers to the research questions for this process evaluation and then
highlights the key findings across the process evaluatiory with recommendations where applicable.
The evaluation team sought to answer six process evaluation research questions. These questions are
listed here along with short summary answers.
1. What are the program goals, concept and design? Are they based on sound theory and practice,
and, if not, in what respects?
The FinAnswer Express program in Idaho seeks to improve energy efficienry at commercial,
irrigation, and industrial sites. The concept is that providing a quick, prescriptive incentive will help
customers overcome cost barriers. The design is indicated in the program logic model in the program
overview. The program concept and design are based on sound theory and practice in line with best
practices for non-residential incentive program design. These practices include: establishing a trade
ally network, making incentive tables available, updating incentives with changes in markets and
codes, and having quality control measures in place.sr
Energy savings targets were set for the third party administrators under contract to deliver the
program in2009,2010, and 2011. The program also had overall energy savings goals in 2011. These
annual savings targets were met in all years.
2. Do program managers and administrators have the resources and capacity to implement the
program as planned, and if not, what is needed?
31 Quantum Consulting. 2004. National Energy Efficiency Best Practices Study Vol. NR-1 Non-Residential Lighting
Best Practices Report. Submitted to California Best Practices Project Advisory Committee.
Rocky Mountain Power
Exhibit No. 5 Page 1 1 14 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E.;a.h-rali.on ol Rockv l''lountain llo-cc.-'s Ii-) FinAnslver i:.rprerss l)rcgrarn iirY 2il09-30ii;65
ru$VX ilANT
Yes. Program m.magers and administrators indicated that they had the resources and capacity to
implement the program as planned. Program participants and the near-participant did not identify
communication delays that might indicate resource or capacity constraints. Participants who
contacted Rocky Mountain Power indicated that the representatives were knowledgeable and timely.
Also, trade allies indicated that they had a primary program contact to which they could reach out
and receive prompt and knowledgeable assistance.
3. Is the program being delivered as planned and if not, how and why?
Mostly, both participants and trade allies describe the program operating as expected from the logic
model, and 13 of 16 outcomes from the logic model were positively affirmed during this evaluation.
Table 39 lists the program outcomes indicated in the logic model along with findings based on the
key indicators and data sources reviewed in the process evaluation (refer to Table 11 for key
indicators and data sources).
One outcome from the logic model could not be fully evaluated: "Customers sign and return the
LOl."32 One outcome that was not positively affirmed was "Trade ally network grows to include
more active providers;" the number of active providers is not growing over time, although a few
trade allies are very active. However, more trade allies are signing up to be associated with the
program; at the end of 2009,28 trade allies were listed in the EEA, and at the end of.20LL,84 trade
allies were listed.33 The other outcome that was not positively affirmed was "customers are aware of
programf' this is addressed in the next question.
4. Is the program reaching the intended target population, and if not, why? Specifically, are
eligible customers aware of the progr:rm, how are they becoming aware, and what is the
program influence on their actions?
From 2009 to20L1, there were lT4participating projects from 99 unique customers and six near-
participant customers from a base of approximately 9,425 eligible customers. This implies an
estimated program reach of 1.1 percent of eligible customers (105 out of 9,425).The174 participating
projects from 2009 to 2011 represent less participation than the program had during the previous
cycle,2006-2008, when there were 293 participating projects.3a While decreased participation may
cause concem, it is important to note that the Energy FinAnswer program, which offers custom
incentives, became available to Idaho customers in the middle of 2008. Some customers who might
have participated in the FinAnswer Express program may have been better served under the Energy
32 The program tracking data included LOI dates for the project manager projects, but not for other projects, through
the pre-purchase incentive path, that would be expected to have LOI.
33 According to Rocky Mountain Power annual reports for 2009 and 2011. Retrieved from:
s Cadmus. 2010. PacifiCorp FinAnswer Express 2006-2008Idaho Program Evaluation. Prepared for PacifiCorp.
Retrieved from:
http:i/!vurrr.rracif icorn.com,/contentldamirracificorrri dociEneluv Sources.Dernand Side lr,lanagementi ID FinAns,,ver'
Express Reuort.odf.
Roclry Mountiain Power
Exhibit No.5 Page 1 115 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
i\raluatioii ol itock,v L4cuntain Po.*,e.''s II-) i:inAnsr.ver Expless Frogranr iPY 2009t"lilii;
rud\HIT"&\I T
FinAnswer program. Since the program is meeting energy savings goals, declining participation does
not appear to be a concem at this time.
Are eligible customers aware of the program? To understand if eligible customers are aware of the
program, the evaluation team relies on non-participant responses. Of a representative sample of C&I
non-participants, 4L percent affirmed that they were aware that Rocky Mountain Power offers
incentives and technical assistance to customers in their class to help them reduce electricity usage.
Awareness was significantly higher for the Commercial class respondents (at 43 percent) than the
Industrial class respondents (at 28 percent).
\A/hen asked what programs or services were offered to customers in their class, 20 percent of non-
participants who were aware of programs (8 percent overall) indicated incentives for high efficient
equipment, and one non-participant (<1 percent of non-participants) was specifically aware of
FinAnswer Express. The program is not expected to have high name recognition due to the
intentional choice by Rocky Mountain Power to market the programs as a portfolio and then match
customers with the program that best fits thefu needs. However, low awareness that Rocky Mountain
Power offers incentives for high efficient equipment may limit participation by eligible customers.
Several non-participants (n=12) who took efficient actions between 2009 and 201L indicated that they
did not seek Rocky Mountain Power assistance because they were not aware of programs.
How are they becoming aware? Customers who do begin working with the program mostly find out
about it from trade allies, as is expected from the program logic model. The logic model also
presumes that customers will learn about the program from marketing efforts, including print radio,
and online advertisements in addition to a customer efficiency focused website. Four participants (8
percent) heard about the program through an online advertisement, but other advertisement media
were not identified by participants. Non-participants who were aware of programs and services
indicated that they had heard through these marketing channels: online advertisements (3 percent),
website (3 percent), TV advertisements (3 percent), and print advertisements (3 percent). Non-
participants indicated preference for email (27 percent), mail (15 percent), and printed materials (15
percent) as ways that they prefer to learn about programs. Mailings and print materials are already
used to reach out to the customer base, but email is not currently used.
What is the program influence on their actions? Participants are influenced by Rocky Mountain
Power incentives, saving energy, and saving money on energy bills. There is some indication of
program influence on participant purchases with the program. Based on participant self-report 17
percent of projects would have been completed within the same year without the program, 37 percent
would not have been completed at all. The other 46 percent would have been completed later or
would not have had as large of energy savings without the program. After adjusting for prior
experience and inconsistencies, 12 percent of projects are assumed to be full free-riders-that is
projects that would have been completed at the same time without the program. Another 13 percent
are partial free-riders, while 75 percent are not free-riders. There is some indication of spillover from
this program; one additional "like" project and four "unlike" projects were completed with no
incentives at least partly due to the program influence.
5. What barriers are preventing customers from taking actions to reduce energy consumption and
demand, and which jeopardize program cost-effectiveness?
Rocky Mountain Power
Exhibit No. 5 Page 1 1 16 of 1 355
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E.;ah-iation oi i(ockv N{ounlain Pon,e,r's Ii-) }:inAnsw.ei Lxt:ress Irroglam {i}Y 2009-:tlii i 6',!
ru&v$ileNT
High costs and lack of access to capital are barriers to further customer action to reduce energy
consumption and demand. The FinAnswer Express program is designed to help customers overcome
the high cost barrier by providing incentives for efficient purchases. There are no programs in place
to help customers overcome lack of access to capital.
More telling is the portion of respondents who stated that there were not further actions that their
firm could take to improve efficiency: half of participants and three-quarters of non-participants.
These responses indicated that one barrier might be that the intended target population truly does
not have additional energy efficiency actions or is not aware of possible additional actions. Given that
they believe there are no other opportunities, it may be a challenge to gain their attention and educate
them otherwise.
6. Are participants achieving desired outcomes, and if not how and why?
Participants are achieving desired outcomes. Participants are mostly satisfied, keeping their
equipment in operatiory and achieving energy savings as expected based on the program logic
model. Trade allies reported very little program-eligible equipment being sold outside of the
program, but participants indicate both repeat participation and some "like" and "unlike" spillover.
Rocky Mountain Power
Exhibit No.5 Page 1117 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Erraluatioi-, of Rockv S.Iouniain lr(r*,er's III FinAnswer Express Progranr iPY 2009-?il1i i {i8
ru $v*il,q Nr-
Short-term Outcomes
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Customers choose to do more
projects to increase energy
efficiency
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Customers observe energy cost
Yes, program-tracking data indicate repeat participation. Participant resPonses
indicate some potential spillover.
No, five trade allies completed projects in 2011, compared to 16 in 2010 and 12 in
2009. However, more trade allies are approaching the Program; at the end of
2009,28 trade allies were listed in the EEA, and 84 trade allies were listed at the
end of 2011.35
,,ves1,,,Th"program,:mer ov**ru...#Ur[y ruvi :t"og
...r*, urrratpX+v i iiiiiiiiiiiiiiii..:iiiiii:;i;i.,. '..:
, *ffiiotf1lfl,.fl,..u...uii'5aiaii,. ;' e prgryam metiirlvciin inergy saYin$s goals in
Yes, most customers indicate that energy savings are meeting expectations.
Tahte 39. Frogram Outcomes and Findings
Rocky Mountain Power
Exhibit No. 5 Page 1 1 18 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Yes, customers who worked with a trade ally were satisfied. Trade allies provide
1:iiiii:i
information about costs and savings.
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35 According to Rocky Mountain Power annual reports for 2009 and 2011. Retrieved from:
http:,//1,u,',v.pacificorp.corrrlconteniidam/pacificorp/doc/Er-rerg),. SourcesiDemand SiCe l\ilanaBerneni/.
[:'...,aliiaiioi^, oi !(ockV ir"li;r:niain P(rii,ri]i'!t .ill Iini\nti.r,ei i:.xprt:ss I]rogitm (IY 20t]l)-]i]ii;
ru$,vr$t"qNT
The evaluation team suggests the following to continue to enhance the efficiency and effectiveness of the
FinAnswer Express Program in future program cycles, as well as improve the experience for participants,
trade allies, and program staff:
" Recommendation 1. Review marketing messages and channels to engage commercial and
industrial customers who are not aware of efficiency opportunities. Half of participants and
three-quarters of non-participants did not believe there are additional opportunities to improve
electric efficiency at their firm. Marketing collateral that educates and challenges customers to
reevaluate their position may be necessary to reach these customers. Reaching new customers is
essential to ensure long-term success of the program in cost-effectively meeting energy savings
goals.
Non-participants indicated that their three most preferred methods of learning about programs
and opportunities from Rocky Mountain Power were: email, mail, and Rocky Mountain Power
printed materials and brochures. However, of these, only printed material and brochures was
identified as a common way that non-participants who were aware of Rocky Mountain Power
program offerings became aware of these programs. Extending the campaign to customer email
may provide an additional avenue to generate program participation leads. This may also be the
most cost-effective method of reaching out to the rural Idaho territory. The previous evaluation
of this program, covering 2006-2008 also found low awareness among non-participants;
expanded communications or marketing of the program was recommended.
, Recommendation 2. Continue to nurture and develop the trade ally network. The program
logic indicates that one long-term outcome is expansion of active vendors and contractors in the
trade ally network. The program has been able to include more vendors and contractors over
time: 28 trade allies were listed in the EEA at the end of 2009, and 84 trade allies were listed at the
end of 201L. Vendors are a critical program delivery mechanism for post-purchase incentive
programs, like FinAnswer Express. Such growth suggests that the effort to recruit new trade
allies has been successful and the challenge will be in keeping these trade allies supported and
active with the program. Third-party program administrators, serving as Trade Ally
Coordinators, should continue their efforts to develop and nurture strong vendor relationships.
Strong relationships encourage trade ally vendors to take the time to market the program
effectively.
Rocky Mountain Power
Exhibit No. 5 Page 1119 of 1365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
E..,ah-iation ol i{ock'l Ntlountain Polrer's lI-) }inAnsw,er Exprcss Prosra.rn iPY 2009-ttl1i i
Rocky Mountain Po,er
Exhibit No. 5 Page 1 120 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Final Evaluation Report for Idaho's FinAnswer Express
Program (PY 2009-2011)
APPENDICES
Prepared for:
Rocky Mountain Power
WRffiKYMCIUNTAIH
reffiltER
Prepared b.v:
h* &\t' $ {* ,& hl T rn partnersrdp *'itir Ettilffi
Navigant Consultins, lnc.
1375 Walnut Strelet
Srrite 20tl
Boulder, CO i10302
303.728.?500
wwrar.navi san tconsrrl tin g.corll
NCarch 4, 2-013
Energy S'iarket Innovations, lnc.
83 Colrrmbia St
$uitqi 40i]
Seattle,l\rA 9tJ10,{
206.521.1150
w14,r,.emiconsultins.com
$-*s\vtffi&NT
Appendix A. Glossary of Frequently-Used Evaluation Tenns... ..............A'1
Appendix B. Net Savings Methodology....... ............8-1
8.1 Measurement of Net Savings Memo -January 27,2012....... ............8-L
8.2 Net Savings Scoring - June 18,2012 ........8-11
Appendix C. Process Evaluation Survey Instruments.............. .................C-1
C.1 Participant Survey Instrument .................. C-1
C.2 Near-Participant Interview Instrument ................ ...... C-16
C.3 Non-Participant Survey Instrument. ......C-24
C.4 Trade Ally Interview Instrument................. ................ C-34
Appendix D. Process Evaluation Detailed Findings ............... D-L
D.1 Participant Results .................D-1
D.2 Non-Participant Results ........D-5
D.3 Project-Level Net-to-Gross Results.... ..... D-10
f, on,tdeltjal and Pior:rieiery,
ldai.'o Finfu rswe r Expi'ess Ivai *atirrn Re$ori
Rocky Mountain Power
Exhibit No. 5 Page '1121 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fen,r i
ruAv$ ilANT
A.7 Glossaryl
Adiustments: For M&V analyses, factors that modify baseline energy or demand values to account for
independent variable values (conditions) in the reporting period.
Allowances: Allowances represent the amount of a pollutant that a source is permitted to emit during a
specified time in the future under a cap and trade program. Allowances are often confused with credits
earned in the context of project-based or offset programs, in which sources trade with other facilities to
attain compliance with a conventional regulatory requirement. Cap and trade program basics are
discussed at the following EPA Web site: <http://www.epa.gov/ air markets/cap-trade/index.html>.
Assessment boundary: The boundary within which all the primary effects and significant secondary
effects associated with a project are evaluated.
Baseline: Conditions, including energy consumption and related emissions, which would have occurred
without implementation of the subject project or program. Baseline conditions are sometimes referred to
as "business-as-usual" conditions. Baselines are defined as either project-specific baselines or
performance standard baselines.
Baseline period: The period of time selected as representative of facility operations before the energy
efficiency activity takes place.
Bias: The extent to which a measurement or a sampling or analytic method systematically
underestimates or overestimates a value.
Co-benefits: The impacts of an energy efficienry program other than energy and demand savings.
Coincident demand: The metered demand of a device, circuit, or building that occurs at the same time
as the peak demand of a utili!/s system load or at the same time as some other peak of interest such as
building or facility peak demand. This should be expressed so as to indicate the peak of interest (e.g.,
"demand coincident with the utility system peak") Diversity factor is defined as the ratio of the sum of
the demands of a group of users to their coincident maximum demand. Therefore, diversity factors are
always equal to one or greater.
Comparison group: A group of consumers who did not participate in the evaluated program during
the program year and who share as many characteristics as possible with the participant group.
Confidence: An indication of how close a value is to the true value of the quantity in question.
Confidence is the likelihood that the evaluation has captured the true impacts of the program within a
certain range of values (i.e., precision).
1 Glossary definitions are provided to assist readers of this report, and are adapted from the Model Energy
Efficiency Program Impact Evaluation Guide, US Environmental Protection Agency, November 2007
Conr-lde,lirai ano Proprrefary Page A-l
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Case No. PAC-E-14-07
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Cost-effectiveness: An indicator of the relative performance or economic attractiveness of any energy
efficiency investment or practice. In the energy efficiency field, the present value of the estimated
benefits produced by an energy efficiency program is compared to the estimated total costs to determine
if the proposed investment or measure is desirable from a variety of perspectives (e.g., whether the
estimated benefits exceed the estimated costs from a societal perspective).
Database for Energy-Efficient Resources (DEER):
A Califomia database designed to provide well-documented estimates of energy and peak demand
savings values, measure costs, and effective useful life.
Demand Side Management (DSM): See "Energy efficiency."
Deemed savings: An estimate of an energy savings or energy-demand savings outcome (gross savings)
for a single unit of an installed energy efficiency measure that
(a) has been developed from data sources and analytical methods that are widely considered acceptable
for the measure and purpose and (b) is applicable to the situation being evaluated.
Demand: The time rate of energy flow. Demand usually refers to electric power measured in kW (equals
k\ /h/h) but can also refer to natural gas, usually as Btufu, kBtu/ hr, therms/day, etc.
Direct emissions: Direct emissions are changes in emissions at the site (controlled by the project sponsor
or owner) where the project takes place. Direct emissions are the source of avoided emissions for thermal
energy efficienry measures (e.g., avoided emissions from burning natural gas in a water heater).
Effective Useful Life (EUL): An estimate of the median number of years that the efficiency measures
installed under a program are still in place and operable.
Energy efficiency: The use of less energy to provide the same or an improved level of service to the
energy consumer in an economically efficient way; or using less energy to perform the same function.
"Energy conservation" is a tetm that has also been used, but it has the connotation of doing without a
service in order to save energy rather than using less energy to perform the same function. Demand Side
Management (DSM) is also frequently used to refer to actively-managed energy efficienry initiatives.
Energy Efficiency Measure (EEM): A permanently installed measure which can improve the efficiency
of the Customer's electric energy use.
Engineering model: Engineering equations used to calculate energy usage and savings. These models
are usually based on a quantitative description of physical processes that transform delivered energy
into useful work such as heat, lighting, or motor drive. In practice, these models may be reduced to
simple equations in spreadsheets that calculate energy usage or savings as a function of measurable
attributes of customers, facilities, or equipment (e.9" lighting use = watts , hours of use).
Error: Deviation of measurements from the true value.
Evaluatioru The performance of studies and activities aimed at determining the effects of a program; any
of a wide range of assessment activities associated with understanding or documenting program
performance, assessing program or program-related markets and market operations; any of a wide range
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Case No. PAC-E-14-07
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of evaluative efforts including assessing program-induced changes in energy efficiency markets, levels of' demand or energy savings, and program cost-effectiveness.
Evaluation, Measurement and Verification (EM&V): Data collectiory monitoring, and analysis
associated with the calculation of gross and net energy and demand savings from individual sites or
projects which is performed in conjunction with a program or portfolio evaluation (see Evaluation).
Evaluated savings estimate: Savings estimates reported by an evaluator after the energy impact
evaluation has been completed. Often referred to as Ex Post Saaings (From the Latin for "from
something done afterward.")
Free driver: A non-participant who has adopted a particular efficiency measure or practice as a result of
the evaluated program.
Free rider: A program participant who would have implemented the program measure or practice in the
absence of the program. Free riders can be total, partial, or deferred.
Gross savings: The change in energy consumption and/or demand that results directly from
program-related actions taken by participants in an efficiency program, regardless of why they
participated.
Impact evaluation: An evaluation of the program-specific, directly induced changes (e.g., energy and/or
demand usage) attributable to an energy efficiency program.
Independent variables: The factors that affect energy use and demand, but cannot be controlled (e.g"
weather or occupanry).
Interactive factors: Applicable to IPMVP Options A and B; changes in energy use or demand occurring
beyond the measurement boundary of the M&V analysis.
Load shapes: Representations such as graphs, tables, and databases that describe energy consumption
rates as a function of another variable such as time or outdoor air temperature.
Market effect evaluation: An evaluation of the change in the structure or functioning of a market, or
the behavior of participants in a market, that results from one or more program efforts. Typically the
resultant market or behavior change leads to an increase in the adoption of energy-efficient products,
services, or practices.
Market transformation: A reduction in market barriers resulting from a market intervention, as
evidenced by a set of market effects, that lasts after the intervention has been withdrawry reduced, or
changed.
Measurement A procedure for assigning a number to an observed object or event.
Measurement and Verification (M&V): Data collection, monitoring, and analysis associated with the
calculation of gross energy and demand savings from individual sites or projects. M&V can be a
subset of program impact evaluation.
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Case No. PAC-E-14-07
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Case No. PAC-E-14-07
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Measurement boundary: The boundary of the analysis for determining direct energy and/or demand
savings.
Metering: The collection of energy consumption data over time through the use of meters. These meters
may collect information with respect to an end-use, a circuif a piece of equipment, or a whole building
(or facility). Short-term metering generally refers to data collection for no more than a few weeks. End-
use metering refers specifically to separate data collection for one or more end-uses in a facility, such as
lighting, air conditioning or refrigeration. Spot metering is an instantaneous measurement (rather than
over time) to determine an energy consumption rate.
Monitoring: Gathering of relevant measurement data, including but not limited to energy consumption
data, over time to evaluate equipment or system performance, p.gr chiller electric demand, inlet
evaporator temperature and flow, outlet evaporator temperature, condenser inlet temperature, and
ambient dry-bulb temperature and relative humidity or wet-bulb temperature, for use in developing a
chiller performance map (e.g., kW/ton vs. cooling load and vs. condenser inlet temperature).
Net savings: The total change in load that is attributable to an energy efficiency program. This change
in load may includg implicitly or explicitly, the effects of free drivers, free riders, energy efficiency
standards, changes in the level of energy service, and other causes of changes in energy consumption or
demand.
Net-to-gross ratio (NTGR): A factor representing net program savings divided by gross program
savings that is applied to gross program impacts to convert them into net program load impacts.
Non-participant Any consumer who was eligible but did not participate in the subject efficiency
program, in a given program year. Each evaluation plan should provide a definition of a non-
participant as it applies to a specific evaluation.
Normalized annual consumption (NAC) analysis: A regression-based method that analyzes monthly
energy consumption data.
Participanh A consumer that received a service offered through the subject efficienry program, in a
given program year. The term "service" is used in this definition to suggest that the service can be a
wide variety of services, including financial rebates, technical assistance, product installations, training,
energy efficiency information or other services, items, or conditions. Each evaluation plan should define
"participant" as it applies to the specific evaluation.
Peak demand: The maximum level of metered demand during a specified period, such as a billing
month or a peak demand period.
Persistence study: A study to assess changes in program impacts over time (including retention and
degradation).
Portfolio: Either (a) a collection of similar programs addressing the same market (e.g. a portfolio of
residential programs), technology (e.g., motor efficiency programs), or mechanisms (e.g., loan programs)
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or (b) the set of all programs conducted by one organizatiory such as a utility (and which could include
programs that cover multiple markets, technologies, etc.).
Potential sfudies: Studies conducted to assess market baselines and savings potentials for different
technologies and customer markets. Potential is typically defined in terms of technical potential, market
potential, and economic potential.
Precision: The indication of the closeness of agreement among repeated measurements of the same
physical quantity.
Primary effects: Effects that the project or program are intended to achieve. For efficiency programs,
this is primarily a reduction in energy use per unit of output.
Process evaluation: A systematic assessment of an energy efficiency program for the purposes of
documenting program operations at the time of the examination, and identifying and recommending
improvements to increase the program's efficienry or effectiveness for acquiring energy resources while
maintaining high levels of participant satisfaction.
Program: A group of projects, with similar characteristics and installed in similar applications. Examples
could include a utility program to install energy-efficient lighting in commercial buildings, a developer's
program to build a subdivision of homes that have photovoltaic systems, or a state residential energy
efficiency code program.
Projecfi An activity or course of action involving one or multiple energy efficienry measures, at a single
facility or site.
Rebound effect: A change in energy-using behavior that yields an increased level of service and occurs
as a result of taking an energy efficiency action.
Regression analysis: Analysis of the relationship between a dependent variable (response variable) to
specified independent variables (explanatory variables). The mathematical model of their relationship
is the regression equation.
Reliability: Refers to the likelihood that the observations can be replicated.
Remaining Useful Life (RUL): An estimate of the remaining number of years that a technology being
replaced under an early retirement program would have remained in place and operable. Accurate
estimation of the RUL is important in determining lifetime program savings and cost effectiveness.
Reported savings estimate: Forecasted savings used for program and portfolio planning purposes.
Often referred to as Ex Ante Saoings (From the Latin for "beforehand.")
Reporting period: The time following implementation of an energy efficiency activity during which
savings are to be determined.
Resource acquisition program: Programs designed to directly achieve energy and or demand savings,
and possibly avoided emissions
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Exhibit No.5 Page 1 126 of 1365
Case No. PAC-E-'14{7
Wtness: Kathryn C. Hymas
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Retrofit isolation: The savings measurement approach defined in IPMVP Options A and B, and
ASHRAE Guideline 14, that determines energy or demand savings through the use of meters to isolate
the energy flows for the system(s) under consideration.
Rigor: The level of expected confidence and precision. The higher the level of rigor, the more confident
one is that the results of the evaluation are both accurate and precise.
Spillover: Reductions in energy consumption and/or demand caused by the presence of the energy
efficienry program, beyond the program-related gross savings of the participants. There can be
participant and/or nonparticipant spillover.
Statistically adiusted engineering (SAE) models: A category of statistical analysis models that
incorporate the engineering estimate of savings as a dependent variable.
Stipulated values: See "deemed savings."
Takeback effect See "rebound effect."
Uncertainty: The range or interval of doubt surrounding a measured or calculated value within which
the true value is expected to fall within some degree of confidence.
Rocky Mountain Power
Exhibit No. 5 Page 1 127 of I 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Conriderirai and Pi oprrei"'ry
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Exhibit No. 5 Page 1 128 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
8,7 Measurement of Net Saaings Memo -lanuary 27,2072
To:
From:
Date:
Subject:
Shawn Granf Esther Giezendanner, PacifiCorp
Kevin Cooney, Matt Haakenstad, and Mike Yim, Navigan! Ellen Steiner, ]ess
Chandler, and Jeremy Kraft, Energy Market Innovations, Inc
]anuary 27,2012
Measurement of Net Savings
This memorandum provides context and suggested approaches for estimating net savings so that the
team can decide whether to move forward with this approach or continue to make changes.
Estimation of net savings attempts first to assess program influence on the participants' decision to
implement an energy efficiency project. This estimation includes an examination of the program's
influence on three key characteristics of the decision related to the project timing scope, and extent.
Measurement of net savings then attempts to estimate program influence on the broader market with
respect to non-program actions (free-ridership and spillover). These two efforts are combined for an
overall estimate of net savings. First, the previous method is briefly described for context followed by
our proposed method moving forr.rrard.
Preoious method for tneasuretnent
The approach used in past evaluations for estimating program influence consisted of presenting
program participants a battery of six core questions, used in combinatiory to derive free-ridership scores
included in net-to-gross calculations. The six core questions were:
. Would the participant have installed the equipment without the program?
o Had the participant already ordered or installed the equipment before leaming about the
program?
o Would the participant have installed the equipment to the same level efficienry without the
program incentive?
o Would the participant have installed the same quantity of equipment without the program?
r In absence of the program, when would the participant have installed the equipment; were they
planning to install the equipment in the same year?
o Was the equipment included in the participant's most recent capital budget?
Responses to these survey questions were evaluated using a scoring matrix (for an example of this
matrix see Appendix G.1 in Final Evaluation Report For Wyoming's FinAnswer Express Program2) to
2 Navigant and EMI. Final Eoaluation Report ForWyoming's FinAnswer Express Program. Prepared for Rocky Mountain
Power. October 25, 2011.
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Page B-!
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determine each participant's free-ridership score. Spillover was not quantitatively assessed in past
gvaluations.
Reasons for proposing a new method
Though a consistent net savings estimation technique across programs is desirable to ensure
comparabilif, our experience with the previous method provided several "lessons learned." Based on
this experience, we believe a more rigorous approach is advisable and that the benefits of improved
validity outweigh the benefits of a consistent methodology between program years.
The changes recommended result in a more granular and holistic approach to assessing program
influence. First, the previous method did not adjust the questions to get meaningful responses by
measure type from the participants. This absence was particularly apparent on large custom projects,
such as Energy FinAnswer. For Wyoming, the savings by measure could be accomplished only for
lighting, and for previous evaluations, no attempt was noted in the reports to attempt to describe net
savings by measure. Also, our methodology did not include any estimation of spillover savings
attributed to the program and only assessed free-ridership. The absence of spillover in our net savings
estimation results in a conservative estimate of program impacts.
Our recommended changes to the free-ridership battery are based on recent research conducted in
Massachusetts on best practices in free-ridership and spillover estimation techniques3. This research is
not only timely, but it has also been rigorously reviewed. The report was created by a team of
experienced evaluators (Tetra Tech, KEMA, and NMR) and reviewed by program staff at eight utilities
operating in Massachusetts including National Grid and NSTA& two of the largest investor-owned
utilities in New England both with long histories of energy efficienry programs. Members of the
PacifiCorp's evaluation team were integral to both the development and implementation of these
methodologies in2007,2009, and again in 2011. Implementing these recommendations provide the
following benefits to the evaluation:
o Targeted questions improve internal validity of free-ridership estimates.
o The methodology creates a calculated estimate of free-ridership savings compared with the
scored estimate previously used.
In addition to estimating program free-ridership, we also recommend that the evaluation quantitatively
assess participant spillover. As programs mature and transform their target market, quantifying
spillover allows for evaluators to recognize the programs' market effectsa. Spillover savings can be
classified into two categories based on measure types: "like" spillover and "unlike" spillover.
o "Like" spillover savings are the energy savings associated with additional high efficiency
equipment installed outside of the program of the same end-use as what that participant
installed through the program. For example, if the participant installed high-efficiency lighting
fixtures as part of the program, "like" spillover would be limited to any additional high
efficiency lighting installed without any assistance from PacifiCorp but influenced by program
activity. This type of spillover is quantifiable using program tracking savings as a proxy.
3 Tetra Tech, KEMA, and NMR. Cross-Cutting C&I Free-Ridership and Spillooer Methodology Study Final Report.
Prepared for the Massachusetts Program Administrators. April 18,2011.
a Saxonis, William P. New York State Department of Public Service. Free-Ridership and Spillover: A Regulatory
Dilemma. IEPEC.2007
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Exhibit No. 5 Page 1 129 of 1 365
Case No. PAC-E-14-07
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Historically, spillover results in a small portion of the overall program attribution (in the
Massachusetts studies cited above, it represented 8.8 percent of the overall attribution score).
o "Unlike" spillover savings are the savings associated with any other high efficienry equipment
installed outside of the program that are not of the same end-use category as what installed
through the program. Continuing the example above, if the participant installed high efficiency
lighting through the program, the high efficiency HVAC equipment installed outside of the
program would be considered "unlike" spillover as it is not the same end-use.
Spillover savings can come from participants, who are influenced by their program participation to
conduct further energy efficiency improvements, known as "participant" spillover. Spillover questions
can be added to the participant surveys conducted for projects completed at least 6 months prior. Asking
participants who have just completed a project with the program about spillover from that program may
not be productive, since participants are unlikely to have the opportunity to install any spillover
measures.
Spillover savings can also come from non-participants. Non-participants may be influenced by program
advertisements or other program actions (like contractor training, upstream buy-downs, etc.) and make
energy efficiency improvements without assistance from any program. This is known as "non-
participant" spillover. Non-participant spillover can be most easily quantified by interviewing
participating vendors and other supply chain actors. During these interviews, the evaluation team can
assess the amount of measure adoption that occurred outside of the program compared to what
occurred through the program. Again, using program-tracking data as a proxy, we can estimate outside
sales. This estimate of outside sales will capure both "like" and "unlike" spillover savings. We will
remove "like" spillover estimates as reported by participants to avoid double-counting.
Limitations
There are limitations with our proposed changes (these limitations were also present in our previous
methodology). Our participant estimates are still limited to self-reported responses to a hypothetical
situation (i.e., what would have happened absent the program). However, we feel that proper survey
design and fielding protocols can mitigate the problems associated with self-reports,5 In addition,
without detailed market level baseline data, the self-report methodology is still the most appropriate and
cost-effective way to estimate program influence at the detail needed to assist in program designT.
Likewise, our experience in Wyoming indicated that it was not fruitful or cost-effective to review project
file text for the purposes of enhancing the self-reported responses.
Figure L illustrates the adjustment steps taken when evaluating net savings. In contrast with the gross
savings, which usually can be directly measured with instrumentatiory the adjustments made to reach
net savings are measured indirectly. This is important to keep in mind as the farther from the actual
measure we get, the less precise findings can be.
5 Keating, Kenneth M., PhD. Free-Ridership Borschu Don't Salt the Soup. IEPEC. 2009
6 Megdaf Lori, Megdal & Associates, LLC, Yogesh Patil, Energy & Resource Solutions, Inc., Cherie Gregoire and
Jennifer Meissner, New York State Energy Research and Development Authority, and Kathryn Parlin, West Hill
Energy & Computing, Inc. Feasting at the Ultimate Enhanced Free-Ridership Salad Bar. IEPEC.200
7 National Action Plan for Energy Efficiency (2007). Model Energy Efficiency Program Impact Evaluation Guide.
Prepared by Diane Munns and Jim Rogers. <www.epa.gov/eeactionplan
Cr.rnideriiai and,nroprefary
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For illustration purposes, consider a participant in the FinAnswer Express program:
A participant installs a variable frequenry drive on a fan motor with the program and
gets an incentive. The program and evaluators can measure the energy consumed by the
new variable frequency drive either directly, depending on configuration, or based on
the hours it is observed to be operating and its features. This consumption is compared
to a baseline estimate of what would have been consumed by a direct drive in the same
case. There is high confidence that the savings are accurate.
Then, the evaluators ask the participant if they would have installed the same variable
frequency drive at the same time without the incentive; the participant can consider
whether the previous drive needed to be replaced at the same time and the relative costs
to decide what might have happened. Thery the evaluators ask the participant if they
installed any other variable frequency drives since participating in the program and
how much the program influenced their choice; the participant can consider the time
frame of installation and determine (probably more easily with this equipment type than
some others) if something similar was installed.
Exploring still further, the evaluators ask the participant if they installed any other
efficient equipment - now the participant has to think about the time frame and relative
efficiencies of any equipment purchased since the program involvement. When asked
how influential the program was on these purchases, the participant is expected to think
through many decisions.
As a thought exercise, we can imagine that gross savings for a program and measure type are estimated
to be 100 kWh. Based on participant responses, the free-ridership ratio is estimated to be 20"/"; the sample
was random and drawn to meet 90% confidence and 10% precision, so the range of this estimate is 18%
to 22"h. Of all the possible spillover, only "like" spillover can be quantitatively assessed, and it is
estimated to be 10% with the same confidence and precision leading to an estimate of 9"h to 11%. The
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unlike participant spillover questions revealed that participants are more likely to install efficient unlike
equipment than like equipment and attribute it to program influence, and market allies confirm that they
are seeing activity outside of the program.
These adjustments result in net savings of 90 kWh with a range of 87 kwh to 93 kWh. However, these
numbers cannot capture the other spillover that we can only qualitatively assess. We may say we think it
is closer to the higher number because participant and market ally responses reflect additional program
influence, but this is a subjective assessment and may not be appropriate given the need for defensible
savings estimates. In some cases, we may find high free-ridership responses and not identify any
quantifiable "like" spillover even if much unquantifiable spillover can be described. Lr these cases,
reporting net savings may reflect poorly on the actual program influence.
Though this method provides net savings that are much less precisely estimated than the gross savings,
we feel that, given the design of the PacifiCorp programs, it is the most cost-effective and consistent
method to assess program attribution.
Proposed method for measurement
This section includes brief recommendations for measuring free-ridership and spillover to get to a net
savings estimate.
Free-idership
To improve the test of the counterfactual (i.e., what would have the participant done without the
assistance of the program), we recommend more targeted free-ridership questions. As a start, we
recommend refining the initial free-ridership question (Would the participant have installed the
equipment without the program?). This question would be altered to include "at the same time" to
clarify the timing component of the decision. It would also be preceded by a brief description of all the
assistance the customer received as part of their participation in the program (e.g., technical design
assistance, the amount of any monetary incentives, any program-subsidized financing). This description
would be customized by program and by project (as data are available). This description is intended to
remind the participant of all the ways the program may have influenced their decision to move forward
with a specific project.
Thery we recommend asking targeted questions about quantity and efficiency of equipment that would
have been installed (or actions that would have been taken) without the program while referencing what
the participant did with the program.
Including these revisions in the free-ridership battery will allow the evaluation team to use a calculation
approach to estimating the amount of energy savings that may have occurred without the program.
This approach is detailed in Figure 2 below.
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Based on the participanfs responses, the team can estimate the percentage of equipment that would
have been installed at the same time without the program (the quantity score) and the percentage of that
installed equipment that would have been high efficiency equipment (the efficiency score)8. The product
of these two estimates is the initial free-ridership ratio.
Free-Ridership Ratio = Quantity Score x Efficiency Score
For example, a participant that installed four high efficiency HVAC units through the program reports
that, without the program, they would have not installed the same measures at the same time. Following
up, the respondent states they would have installed some equipment and it would have been installed
within 12 months. When probed about the level of efficiency of the equipment that would have been
installed absent the program, the participant reports that they would have installed equipment that was
more efficient than baseline but not as efficient as the program-eligible equipment. Finally, they report
they only would have installed one unit (instead of four). Using the scoring above, this participant's
efficiency score would be set to 0.5 and the quantity score would be set to 0.25. Their initial, unadjusted
8 Question text will be altered for projects where quantity is not applicable. For example, if a project consisted of the
installation of an EMS, the quantity question would be skipped.
[grr ijaje I i.r$,i Sii C rsi-r.r1:rr.ref Ary
liehc F inAnsr,*'er EliSi'$ss Svaiuriicn i\enl.ii
Apuendrx S * l,iet Savirlls lr,'ieihrdtirgi,
i]+,rs R..il
ru,&qs $t.e sd r
free-ridership score is then the products of these two scores or 0.125. This figure indicates that 12.5
percent of the savings attributed to this project would have occurred absent the program.
This ratio can then be adjusted by the responses to other questions already referenced in the battery.
These include any reported changes in the timing of projects as a result of the program and the reported
influence of various factors on the decision to install the equipment. These adjustments are not detailed
in this document, as they will be tailored to individual program design. As part of these adjustments, we
recommend that the list of factors be expanded to include "other PacifiCorp program participation."
This addition will allow evaluators to adjust free-ridership based on PacifiCorp's portfolio level outreach
efforts. For example, if a participant received sequential incentives from two different PacifiCorp
programs, his or her participation in the first program may have increased their awareness of the
secondary program. In this situation, their responses to free-ridership questions regarding the secondary
program may present this participant as a free-rider. In this situation, we can use the responses to the
influence questions to assess if the secondary project was influenced by PacifiCorp actions from another
program. If so, PacifiCorp should receive attribution for those savings and free-ridership would be
adjusted downward.
This methodology requires several adjustments when applied to programs that offer custom incentives
or to programs that utilize unique mechanisms to achieve savings. First, the self-report survey should
include complete and accurate descriptions of what measures were implemented as part of custom
projects. Also, as custom programs often work with participants to implement a variety of end-uses
under the "custom" umbrella, custom proiects should be evaluated holistically and not at the end-use
level. Similarly, unique programs may require additional refinements to question wording. For example,
when assessing a recommissioning program, the interview may seek to assess the decision to conduct
the initial project study instead of the decision to implement the energy-saving opportunities identified.
Finally, for complex or large projects, the self-reported estimate can be verified by a review of project
documentation (if available) and follow-up interviews with the contractors associated with the project.
These additional steps can be costly and should only be considered when the savings of the project make
up a significant portion of the program's overall savings or contractor outreach is a significant part of the
program design.
As an example, we provide recommended free-ridership questions for the Energy FinAnswer program
in Figure 3.
e This multiplicative approach is appropriate as the score is the result of a product of the quantity installed and not a
product of probabilities (Keating. Free-Ridership Borscht: Don't Salt the Soup.IEPEC. 2009).
Conirdenirai *nd,sroprief$ry
irlahc FinAnswel Hxplsss Ivaiuation Reps*
Ap*endix S - Net Savirgs lr,teihacli:lcgy
Rocky Mountain Power
Exhibit No. 5 Page 1 1 34 of 1 365
Case No. PAC-E-14-07
Wtnessi Kathryn C. Hymas
Pace E-i
*
N d\N N {-u.,\ i\ T
Rocky Mountain Power
Exhibit No. 5 Page I 1 35 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
t0 Variables and notes to the interviewer are in ALL CAPS. The variable MEASURE_TYPE is grouped and worded
by measure types, such as "lighting equipment" or "HVAC equipment" with specific measures installed identified
for the respondent to be sure they understand what is meant.
ilon rlSerirai SriiJ Firrp,..ef Ory
i.j$h0 FrnAns'r.",ei' Hli"nisss Svaiuation iiepa*
Aprcndix $ - l'let l\arirgs lr,leihurhicg:.'
Figure 3" Free li.idership Battery F.lxtraet frorn tlnergy lrinAnswer Suruey UiA$T10
...[ftEAD: "With the Energy FinAnsrver prograrn, FIRM rr:ceived technical assistance and I'inancial
in<:entirres^ FI RM in stalled l,l ST-I{E ASl.l ttES w'ith th e pro gra m."
REPEAT FOR EACH MEASURE-TYPE-# LISTED UP TO '.IIEAD: "For these next questions, please ftrcus on i\,{EASURE-TYPE*# which inciudes
h{EASIJRE_TYPE_#_ll{ST fkrr -riour proj ect."'l
FRZ. Without the program, meaning u,ithollt either the technical assistance or the financial
incentive, r.'/ould you ha,,,e still installed the eract same IvIEASIIRE-TYPE-# at the sanre tlrne'i
f iF 1=YES] => REPEAT for next IUEASLIRE-TYPE or go orl to spillover
[F 1-NO] => g0 t0 2
FR3. Without t;he prograrn, rvould you h;rve installed an.v MEASI.IRE_TYPE-# equiprnent?
[lF Z=YESI=> gu tti 3
[F 2=NO]=> CO IIACI{ T0 1 tbr next MEASURE..TYPE or go on to spil}over
FIl4. Without the prngrarn, would -you have installed t.his equipmenl within 1? months of when
you did rvith the program?
[F:3=YES]=:> go to 4
FF l3=N0l=> G0 EACK T0 1 for next I\4EASIJRE-TYPE (lr go orl to spillover
Ii: itPPLICAIiLE] F'1t5. Relatirre to t]re energ-v efficiency of MEASURIl..TYPE..# installed through
the pragrarn, hor,v would you characterize the efliciency of equipment yru u,'ould have ins[alled
u,i [h out the progr;rnl?
a. f ust as efficient as instalied vr,ith the progranr
b. Lower than inslalled through the proglam, llut better than the standard efliciency
c. Standard el'ficiency
[iII APPLICABLII] irR6. lVonld you have instaliL.d the same amourlt of FIEASURE...TYPE..#?a. Yes
b. No -> FR6it
FRfia. Ivtore or lessi'
FRtib. Horv rnuch more or le)-)-:'
GO BACI\ TO 1. fkrr next h'IEASURE*TYPE or go $n to consis^tenr:y or spillover...
ilr:.o R..1,
ru &\s $il- -q Nj T
Spilloaer
We recommend asking participants about both "like" and "unlike" spillover with an understanding that
the "like" spillover can by quantitatively assessed and the "unlike" spillover will be characterized
qualitatively (though efforts will be made to use deemed estimates if possible). With "like" spillover, we
can use the gross savings estimates from the program tracking database as a proxy for the "like"
equipment. With no savings data to use as comparison, our ability to confidently assign savings to
reported "unlike" spillover projects is limited by the amount of data participants are able to provide. For
example, if a participant reports that they installed "some high efficiency lighting" but cannot recall how
much or what type, we can only qualitatively report that project as spillover. However, if the participant
is able to provide detailed specifications about the project (e.9., 40 T8s with ballasts), we can then use
deemed savings values as a reference for assigning savings. Savings for measures without deemed
values (e.g., recommissioning projects, industrial process improvements) can only be verified via on-site
and our spillover assessments will be qualitative in nature.
We also recommend asking market allies about program-eligible sales outside of the programs. Market
ally responses and participant "unlike" spillover responses will allow a qualitative discussion about the
estimated magnitude of spillover relative to the "like" spillover that can be quantified. ln addition,
interviews with market allies will provide an assessment of spillover across the entire program year. As
we are planning to interview participants quarterly regarding their projects, our estimates of participant-
reported spillover savings will under-represent annual savings as potential spillover projects completed
after that three month period will not be captured. However, market ally interviews will only be
conducted once per evaluation year and cover the entire program year, capturing all spillover projects in
the process. Likewise, the spillover reported by market allies will capture "unlike" spillover savings that
we were only able to qualitatively assess from the participant reports.
Similar to the free-ridership battery, question wording will be adjusted for unique programs (e.g.,
recommissioning) or for custom projects. The like spillover questions will be repeated for the same two
measure types as used for the free-ridership battery, as applicable.
The participant spillover questions recommended as part of the participant surveys and interviews are
listed below for both like an unlike spillover.
LIKE
o Since participating in this program, have you purchased and installed any additional
Imeasures]?
r What did you purchase or install? How many did you purchase or install?
r Did you receive assistance from [utility] or another organization?
. On a scale from L to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you
"strongly agree" , please rate the following statement: My experience with [utility)'s mergy
fficiency program influenced my decision to install other high fficiency equipment on my own.
. Why did you not apply for an incentive from [utility] for this equipment?
COn,-1lr'eniiai *,'iil F,'Opref ary
i$eho iinAnswer Ix0ress Ivaiuation iiepa*
Aprendix $ * I'iet Savirgs lvleihcilaiagv
Rocky Mountain Power
Exhibit No. 5 Page 1 136 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page B-S
fl{$\d $t,q N T
UNLIKE
o Since participating in this program/ have you purchased on installed any OTHER energy
ef ficiency improvements?
o What did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
o How many did you purchase or install?
o Did you receive assistance from [utility] or another organization?
o I'm going to read a statement about the equipment that you purchased on your own. On a scale
from 1 to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you "strongly
agree", please rate the following statement: My expnience with futility)'s energy fficiency program
influmced my decision to install other high efficirncy equipmutt on my own.
. \ /hy did you not apply for an incentive from [utility] for this equipment?
The non-participant spillover questions recommended as part of market ally interviews are listed below.
. Approximately what percent of all [measure] sales in [state] Iast year would you estimate was
from program-eligible equipment?
. Approximately what percent of your [measure] sales in [state] last year was from program-
eligible equipment, that is [description of eligibility requirements]?
o Did you sell more program-eligible equipment last year?
o According to our records, you sold [quantity] [measure] as part of projects that received
program incentives. To the best of your knowledge, did you complete any [measure] projects
with [utility] customers that did not receive program incentives? If so, how many?
r Do the [utilitvl Drosram incentives influence vour stockins/sellins of orosram-elisible
Imeasures]?
r Does the [utility] program information influence your stocking/selling of program-eligible
[measures]?
Net saaings
Spillover savings can be combined with free-ridership savings to create a comprehensive picture of
program influence. This combination is often referred to as a net-to-gross ratio and is calculated by
adding the spillover ratio to the inverse of the free-ridership ratio or:
Net-to-Gross Ratio = (1-Free-Ridership Ratio) + Spilloaer Ratio
Gross savings are then multiplied by the resulting ratio to find net savings by measure type and
program.
Conijcre* jrai end,D,'r..priais,y
iC.?nc f inAnswer Ixsiess Svaiuation iiepa(
Aplendix $ - liet Savirgs lr,leihllttaio.;v
Roclry Mounhin Power
Exhibit No. 5 Page 1 137 of 1 365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
Srns Q- i ii
ru v ${.ANi -$-
8.2
To:
From:
Date:
Subject:
Rocky Mountain Power
Exhibit No. 5 Page 1 138 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Net Saoings Scoring - June 78,201-2
Shawn Grant Esther Giezendanner, PacifiCorp
Kevin Cooney, Matt Haakenstad, Mike Yim, and ]eff Erickson, Naviganf Ellen
Steiner, Jess Chandler, and Jeremy Kraft, Energy Market Innovations,Inc
]une 18,20L2
Net Savings Scoring
This memorandum provides a detailed description of how the evaluation team plans to estimate a net-
to-gross (NTG) ratio for the portfolio of the PacifiCorp energy efficiency programs. An NTG ratio is a
comprehensive picture of program influence and is the ratio of net savings to gross savings and is an
indication of the programs' influence on customers' decision-making regarding energy efficiency at their
facility.
Ooeruiew
Using self-reported responses, the evaluation team's estimation of net savings first attempts to assess the
program's influence on the participants' decision to implement an energy efficienry project and what
would have occurred absent the program's intervention. This estimation includes an examination of the
program's influence on three key characteristics of the project its timing, its level of efficienry, and its
scope (i.e., the size of the project). This estimate represents the amount of savings attributed to the
program that would have occurred without its intervention and is often referred to as "free-ridership."
The team's measurement of net savings then attempts to estimate program influence on the broader
market as a result of the indirect effects of the program's activities. This estimate, often referred to as
"spillooer," represents the amount of savings that occurred because of the program's intervention and
influence but that is not currently claimed by the program. Spillover savings can be broken into two
categories of savings: "participant" spillover and "non-participant" spillover. Participant spillover
savings occur directly (i.e., program participants install additional energy efficient equipment), while
non-participant spillover savings occur indirectly (i.e., market allies install additional energy efficient
equipment to customers that choose not to participate as a result of the program).
A program's net savings are adjusted by both free-ridership and spillover savings at the measure level
and then extrapolated to the program. The net savings are the program-reported savings minus any free-
ridership savings plus any identified spillover savings, or:
Net Program Saoings = Gross Program Saoings - Free-Ridership Saoings + Spillooer Saoings
Ofteru this finding is described as a "net-to-gross ratio." This ratio is the net program savings divided by
the gross program savings, or:
Net-to-Gross Ratio = Net Program Saoings I Gross Program Saoings
Ccniideniial ana' F*pretary
itiaho f rnAns'f,ier Ix]ress Ivaiuation Repori
Aplendix S - l.iet Savings lt!eth+dciogy-
Pa$e B-'i i
Roclq Mountain Pot/ver
Exhibit No. 5 Page 1 1 39 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymasru A-qs $t.,q N T
Er ee-ridership C alcul ation
To determine free-ridership, the interview presents respondents with a series of questions regarding
their decision to install the equipment promoted by the program. The team then scores the responses to
these questions to determine the level of free-ridership. A score of 1.0 indicates the respondent is a
complete free-rider; they would have installed the exact same equipment at the same time and in the
same quantity without the program's assistance. A score of 0.0 (zero) indicates the respondent is not a
free-rider; that is, without the program they either would not have installed any equipment within 12
months of when they did or they would have installed baseline efficient equipment.
As the first step in scoring, the evaluation team reviews the interview responses to determine if the exact
same project (in terms of scope and efficiency level) would have occurred at the same time without the
program. If so, the respondent is scored as a complete free-rider. If not, the evaluation team reviews the
responses to determine whether the project would have occurred at all within the same 12 month period.
If not, the respondent is scored as a non-free-rider. If the project would have occurred within the same 12
month period but altered in respect to its size or efficiency level, the respondent is scored as a partial
free-rider. To assess the level of partial free-ridership, the evaluation team uses the respondents'
estimates of the percentage of equipment that would have been installed within 12 months without the
program (the quantity score) and the percentage of the installed equipment that would have been high
efficiency equipment (the efficiency score)11.If the project would have occurred with some changes absent
the program, the product of these two estimates is the initial free-ridership ratio or:
lnitial Free-Ridership Ratio = Quantity Score x Efficiency Score
After scoring the initial free-ridership ratio, a series of consistency check questions is reviewed. These
questions ask about the influence of the program's interventions (e.9., financial incentives, technical
assistance) and address the counter-factual (e.g., what would have happened without the program). For
example, if the respondent states that the financial incentive was extremely important to their decision
(FR1D = 5) but that they would have installed the exact same equipment at the same time without the
program (FR2 = 1), the interviewer asks them to describe in their own words what impact the program
had on their decision (FR7). During the scoring process, these responses are reviewed by analysts to
determine which scenario is correct and are scored accordingly to create an adjusted free-ridership score.
Finally, the free-ridership score is adjusted to account for prior program participation. Given
PacifiCorp's efforts to cross-promote their entire portfolio of energy efficiency programs, a respondent's
prior participation in a PacifiCorp program may have been influential in their decision to participate in
the current program. Ideally, this influence would be attributed to the prior program as spillover savings
since that program was responsible for the influence. However, given the portfolio-level marketing
approach that PacifiCorp implements, respondents are unlikely to be able to identify the prior program
by name. Therefore, the evaluation team will attribute the savings credit to the current program.
To calculate this credit, the team will review the respondents' rating of the influence of the prior
program. If the respondent rates their previous participation as a " 4" or "5," their adjusted free-ridership
is reduced by either 50 percent or 75 percent respectively.
11 Question text will be altered for projects where quantity is not applicable. For example, if a project consisted of the
installation of an EMS, the quantity question would be skipped.
Con,idelirA aii$ Fropnefaiy
i{i€ilc FinAnswer Express Hvaiuation fiep.,.ri
Apuendix S - I'iet Savilgs lr,leth+doicgy
Orac Q--{ i
ruAxs$il:ANT
Figure 4 illustrates the series of questions asked to support this calculation while Table 1 provides
detailed scoring and descriptions of each question.
Roclq Mountain Power
Exhibit No. 5 Page 1 140 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Tahle 1". Free-ridership Calculafion Approach
FRlB Consistencv Check
i.' : ii.*Ul1,fee-riaei$Hlp,.=;..0.
.i.....,.,,.,:,,r,i.i.i.i.i.iii.iiiiiii.i.i..,.'.,:i..,...,.......r:,.i""",'.,"'.'.;'',","
If no, free-ridership = 6
-$$$
ii
FR4
ffi
FR6a
FR7
.EftliFi,li.ii*.**
If between high efficiency and
baseline, efficiency score = 0.5
If yes, quantity score = 1
tJ+nirsi+riiai *rij Frrl:rcf "+ty!dsi'i+ iinAnslrel [>r"nii+ss Hvair:nlian $iepofi
Aprcnciix $ - l.iei Sa",ings lvlein.rcitinrrv
$.\' .s\v $ {l A Ni l-
..Li.r rrL\*
u'' FR2 l,. same nopcr' \ ,Same'l-ime?,
I
No, DK
+
Yes
,aro-,,,,,,,,,,t,,,,,.,a=aaoaa
i::i.{iminssoor€= t I::--:------------------ - :
i
Yes
s,l:.\
-,,rlincemi*tror.'i:::+Etrnienet? .. J
't'.'
i
No
(e.9., RCx Study)
Rocky Mountain Power
Exhibit No. 5 Page 1 141 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
F igure ;1. F ree-ri dership Cal culation ^tXpproach
\ iiii:::i:iiiiii:iii::::
_).......---Yes- r"1.;;;;Fn=t i - -
:' l-i11i.....-..-*.]
'i*,,;il$ " ^,rl.t----'o'"*
J-FR;iP:f-j
\!'::i:::i:!i::::::::::::::::::::::::::::l:::rli:ir A\'::\ ... i
tl--- ----'------i r"" -'-- - -"'l\
-S, -'.j .:: -.-'-'-' i.-...-....--..--la: Free4ialsi$hirt :
Yes
t
trr : I iFtt+:::::::::::::::,:\,,.y$thin 12 _)..........No. DK ...--.
ii iltMontha?,::::::'::::::.
,Jl ]]::]] :]]::]:::::::::::': :::lil:}
\ Aua1ll$rrtri: r r:> No l
i:ffi : ?'iming Scdie i
--s" x Elfidiency Scdfe i
i,,,,*"9,----'-
A
:
i tll,cEfiuv ticofe. r o : i EltcBttol scor€.! .5
---"**^'4 "----" *'---[-------
Standard i
..'.:.
FR5 .. :
,- - ti^t,^^..*<' Levelof )-..1n Between, oK:(e.9.. FtvAU) \ \efficiehcy?.\::::: -"'
\,J
--- 1,1*;,r,1. 1 S, ',, .,,, , , ,I vs irGiiiEttv Scarc.*..!l Is !"..:::.::... - r.-,,\ A
'' ees" t. .(.srm nmount?'l---Yes-
'\ ::::::;::::r-'\:l;i'
iNo. DK
Same Level
$
For example, a participant that installed four high efficiency HVAC units through the program reports
that, without the program, they would have not installed the same measures at the same time. Following
up, the respondent states they would have installed some equipment and it would have been installed
within 12 months. \rVhen probed about the level of efficiency of the equipment that would have been
installed absent the program, the participant reports that they would have installed equipment that was
more efficient than baseline but not as efficient as the program-eligible equipment. Finally, they report
they only would have installed one unit (instead of four). Using the scoring above, this participant's
efficiency score would be set to 0.5 and the quantity score would be set to 0.25. Their initial, unadjusted
free-ridership score is then the productr2 of these two scores or 0.125. Likewise, they state that the
incentive was important and that previous participation was not important. These responses indicate a
consistent installation scenario and no further adjustment is necessary.
12 This multiplicative approach is appropriate as the score is the result of a product of the quantity installed and not
a product of probabilities (Keating. Free-Ridership Borscht: Don't Salt the Soup.IEPEC.2009).
il+n i$ie,"liei snC Fiul:,,.eis,.y
iiieiio FinAnsvrei [)isress ilvaiuEtion ii*pr:ri
Aplendii * - I'iet i\avngs \,ieili.ldricSv
Pe$e ts- i 4
ru,&v$t".qNT
Spillover Calculation
P articip ant- rep orted Spill oo er
Similar to free-ridership, to determine spillover, the interviewer presents respondents with a series of
questions regarding their decision to implement projects outside of the program (i.e., projects that did
not receive any assistance from the program). These responses are then scored to determine the level of
spillover. The evaluation team will ask participants about both "like" and "unlike" spillover proiects.
"Like" spillover is associated with equipment that is similar to the equipment incented by the program.
In comparisory "unlike" spillover is associated with equipment that is not similar to the equipment that
was incented by the program. Using the program-reported per-unit savings as a proxy, "like" spillover
savings can by quantitatively assessed. However, as it has no comparative program savings data,
"unlike" spillover can only be characterized qualitatively (though efforts will be made to use deemed
estimates if possible).
To assess "like" spillover, the evaluation team first reviews interview responses and determines whether
the respondent installed any additional equipment similar to what was incented through the program. If
additional equipment was installed, the team determines whether it was rebated through a PacifiCorp
program. If not, the team then estimates the amount of potential spillooer saaings associated with the
project. This estimation is created by using the program-tracking savings as a proxy for per-unit savings
and adjusting for the amount of equipment installed. The team will also adjust for equipment similar to
that installed through the program but of a lower efficienry. If the respondent states that efficiency level
is lower than what was installed through the program but better than standard efficiency, the potential
spillover savings are reduced by half. Since the energy savings associated with the reduced efficienry
project will be less than the project incented by the program, this adjustment credits the program with
some, but not all, of the savings.
In order to account for the program's influence on the spillover savings, the team then adjusts the
quantified spillover savings by the free-ridership rate identified earlier or:
Spillooer Saoings = Potential Spilloaer Saaings X Free-ridership Factor
As a consistency check, the team uses an additional question to check the evaluated free-ridership rate.
Respondents are asked to rate the level of influence from the program on their decision to purchase the
additional equipment. The team compares these responses to the identified free-ridership rate to identify
any contradictory responses (i.e., free-ridership factor of 1.0 but spillover influence is high or free-
ridership factor of zero but spillover influence is low). If the responses are contradictory, the potential
spillover savings are reduced by 50 percent. Without further evidence, the team cannot objectively
determine which statement of influence is correct. Adjusting the potential spillover savings by 50 percent
acknowledges this uncertainty without overly penalizing or rewarding the program.
Figure 5 illustrates the series of questions asked to support this calculation while Table 2 provides
detailed scoring and descriptions of each question.
Con ijcrerirai aii.J,srapr'eiary
i$ai-':o irnAnsvier Ex$ress Hvaiuaticn Repoii
Apwndix * - l,iet Savirgs lr,lethoddogv
Rocky Mountain Power
Exhibit No. 5 Pase 1 142 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Page 8-15
hl $\'$ -{:s..q \l T
Rocky Mountain Power
Exhibit No. 5 Page 1 143 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Table 2. Spillover Calculatinn Approach
SP1
ffi
SPlc If lower than program but
higher than standard, reduce
potential spillover savings by
half.
lf standard efficiency, potential
SPfi.diiiiiiiiiiiii.ii..i:, ,,.,.:Did:,you r€be,i.ye an incer,rtive:ftom FacifiCorp or another
SPlf On a scale from 1 to 5, with f. indicating that you
"strongly disagree" and 5 indicating that you "strongly
agree", please rate the following statement: My experience
with the PacifiCorp program influenced my decision to install
,,,,.,i,P"'o-urt.:",.,r",,,,,t1,t",I.rg
Consistency Check
Since participating in this program/ have you purchased If no, potential spillover savings
on installed any additional [MEASURE]?
i11.1ilE#.ihil#utar.1.1*ru;
; t*uHtu.,,:.:,
Relative to the energy efficiency of [MEASURE] installed
through the program, how would you characterize the
efficiency of this equipment?
t
i+ni,'iieniiai $iiii r$,.01:trciiiy
iiJ.qi'l+ FinAnsi';er H >rsiess iluaiuation liei.rr:ti
Afrl;ensi,< ii * liei Savi:tgs ir,teiiilrcioitrtr
Snns R- i G
rou $\J $ .,q Sd T
Rocky Mountain Power
Exhibit No. 5 Page 1 144 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Figure 5. Spillover Calculaticn Approach
.'''f"tLx\'i\'o'''lil sP{iiiiii:'::":':'t'
<,.:: Arilfpqiiiiinel .;>-*-..*-..-.----No, DK-----.
\ r;ir
iyes ii,i
'4'r :/: ""\ :--r \. isPtb ),* i'\Quantl-t!, ilnEldled,?,i/ i
.Y-.................................. .
1nffierryv-'no*..+..ffix. l*;.1
i: i ::,:i:,iii€port€d fiefilt!:llt!:Sr*vlrgq!:,i!:!:!:i.!ii!,,:!:!l
i' ' . ,,,,!::,::!,!:!:!:!,!:!:!: ,!:!: ' :::.. ::: :::!:!:!:!:!:!::: ::i:r ,': :':!: : :::,, : :,: , :., :j
A
-.:i:tl::t!:i:::::::\
,,4....-Pi;...'^'t "l-------.'(,.,.:.:.:.:.:.:.:.:EffaiqIs}.,,il lt.)--i \:::::::::::::::lnatglldd : iii:l,rr_.: . \(,,,,,,,,,,,,;,,,,,,,,,,,,,,,1,,,,;,;,".
Medium Efficiency, DK -<:::::::!::::,:iiii;:r
Yrii:rlrt::i:n.ri:-,:i.i :r:::::::
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i
High Efficiency
t
i 'NoaryIsonem. i
t
..,1:::i:i:::::i i\
,rlii.,,,.;se1.o "-{ :li::!:liri!:liriririRacgirc \,-Yes-
\. r.':lfieEhilvE? ,.
'\:::::::::!:::::::i::.:. : i:r/
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.-- ,- -.-:".'"'tr-' .-.1'l
,.:i r ; :FpifQ!{+t,,SaVlngqr:E Fo{Qt!q*.1:i!:!i!:::!:t
i Sillor/er Saviflgts:x Free{idenihipr::::'.{i. Factor 'i' " i.'.'i
A similar process is used for "unlike" spillover. However, since the measure is not the same as the in-
program measure, the team has less information from which to calculate the measure's savings. Thus the
team's ability to confidently assign savings to reported "unlike" spillover projects is limited by the
amount of data participants are able to provide about the measure and its use. For example, if a
participant reports that they installed "some high efficiency lighting" but cannot recall how much or
what type, we cannot reliable assign any spillover savings to that project. However, if the participant is
able to provide detailed specifications about the project (e.g.,40 T8s with ballasts), we can then use
values based on savings from similar measures in the program-tracking database as a reference for
assigning potential spillover savings. Savings for measures without deemed values (e.9.,
recommissioning projects, industrial process improvements) can only be verified via on-site and our
spillover assessments will be qualitative in nature. If "unlike" spillover projects of significant magnitude
Con,.rderi.ui *iiii Frol::r"ieiory
iti.rilo iinAnswel Ixpr+ss ilvaiuaiicn Reni-.it
Aptendix * - I'iet Savi:rs$ l.Jeihu$oiogi,
Faqe S- i ?
N s\\s $ {1 .,\ Nd T
:::::::::::::::::::::::::::::::::l::::::i:::::::
......................itt!lr:-: :,:,:,:,:,:,:':,:,:,:!i.:::,]:]1:::: j:l : ]:.: ::':':
aa
::::::il;::::::::i:::aiii:::::ilit,i:irt ::i:::ilil:li:::l . i :r :. ':
iiiiiiiiiiiiiiiiiiiiliu
ilor,rrce,'ri,ai s$ij Fiopneiary
i$r\c FinAns'r.;er [>rpress ir.vaiuaticn ilei:stt
Aplen.Iir S - l(el Savircs N,ieih#riog.s
are identified, on-site visits may be cost-effective. In this situation, the team will discuss conducting
visits in order to quantify the savings.
N onp arti cip ant S p ill oo er
To capture a comprehensive picture of spillover, the team also asks market allies about program-eligible
sales outside of the programs as part of our in-depth interviews with this group. By examining the
amount of program-eligible sales occurring outside of the program, the team can create high-level
estimates of nonparticipant spillover that can be added to the participant-reported spillover savings.
First, the team determines whether the market ally installed any program-eligible equipment that did
not receive incentives from the program. If so, the team compares the quantity of equipment installed
outside of the program to the quantity tracked through the program-tracking database. Using the
savings associated with that market ally in the program-tracking database, the team can then estimate
the amount of savings installed outside of the program. Note that market allies may have difficultly
reporting the amount of equipment that did not receive program assistance. As these "don't know"
response will not be used in analysis, our estimate will likely be conservative.
Finally, the team determines the influence of the program on these sales in order to attribute the
nonparticipant spillover savings to the program. The team examines responses to three questions
regarding the influence of the program incentive and information on the stocking and selling of
program-eligible equipment. Respondents are asked to rate the influence of the program on a scale of 1
to 5 where 1 is "no influence" and 5 is "a great deal of influence." If the average response is greater than
4, 100 percent of the savings installed outside of the program are attributed to the program. If the
average response is greater than 3 but less than or equal to 4,75percent of the savings are attributed to
the program. If the score is greater than 2 but less than or equal to 3, 50 percent of the savings are
attributed to the program. None of the savings associated with market allies with average influence
scores lower than 2 are attributed to the program.
Table 3 describes in detail the questions asked and their associated scoring.
Table 3. )Vonparticipant Spiilover Calculation Apprnach
i.:n lt:lir t
l-ralds H.-: n
According to our records, you sold [NUMBER OF
PROIECTSI of [TYPE] as part of projects that received
program incentives. To the best of your knowledge, did
you complete any [TYPE] projects IIF LIGHTING OR
HVAC: that would have been eligible for the programl
that did not receive program incentives? If so, how
Do...the..ipioglarn, incentives;,,influence,your seffi.,.uf
pro$ -eligi-bleequipm*ilor,,.1*Wtlt :iii::ii: :iiii:i:':,:i'i
Do the program incentives influence your stocking of
Rocky Mountain Power
Exhibit No. 5 Page 1 145 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Projects outside of
program/Projects through
program) X program savings
associated with market ally =
potential nonparticipant
spillover
ru &v$fi&lsT
Net-to-Gross Ratio
The evaluation team will determine measure-specific free-ridership and spillover rates. To determine
program-level rates, the team will weigh the rates by savings and for any disproportionate sampling.
This weighting ensures that the analysis is representative of the overall program both in terms of its
distribution of savings and its mix of measures. For example, projects that account for a larger
proportion of the program's overall savings will have more influence on the final program-level rate. In
addition, if projects that are part of certain sub-groups within a program are intentionally selected more
frequently (i.e., over-sampled) as part of the sample design, those projects will have less influence on the
program-level rate.
Likewise, the team will apply similar weights to the market-ally reported nonparticipant spillover
savings to determine measure-level estimates. To avoid double-counting, participant-reported spillover
estimates will be subtracted from the market ally-reported estimates. Il at the measure level, the
participant-reported spillover estimate is less than the estimate reported by market allies, the team will
add the difference to the spillover rate. If the participant-reported estimate is greater than the estimate
identified by market allies, the team will not add any nonparticipant spillover savings to the overall
estimate.
The team will then create the final net-to-gross ratio. This ratio is the net program savings divided by the
gross program savings or:
Net-to-Gross Ratio = Net Program Saoings I Gross Program Saoings
The net program savings are the program-reported savings minus any free-ridership savings plus any
identified participant and nonparticipant spillover savings or:
Net Program Saaings = Grotss Program Saaings - Free-Ridership Sauings + Participant Spillooer Saaings +
N onp articip ant Spilloaer S aoings
Note that as the nonparticipant spillover ratio is created for each market ally and not each participant,
the final ratio is adjusted at an aggregated level.
Conirde,"iiai ans Frnpr'etary
irisiro FinAnswer Exprsss Svaiuation Repr:ri
Aptendix B - l(et Savings l\.{ethdoiogy
Rocky Mountain Power
Exhibit No. 5 Page 1 146 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
ra$e $- : Y
s,,$ &v'$il & Nd T
C,L Participant Suntey Instrument
Note: FinAnswer Express Participants are those customers who completed a project through the FinAnswer
Express program during 2009-201.L. Participants are questioned about up to tuto measure subtypes based on the
largest ktNh saoings. Measure subtypes will be determined duing sampling and will likely be grouped by end-use
( e. g., lightin g equipment, HVAC equipment).
Objectioes
These surveys are designed to meet the following list of objectives.
o To describe how customers come to participate in the program
. To understand overall customer satisfaction with the program, including application materials,
inspections, and the incentive
o To understand program influence on customer actions, including free-ridership and spillover
o To understand barriers customers are facing that prevent increasing energ:y efficiency
. To characterize participating firms
Variables
Corideriiai and Fropr'eier,y
itJehc "r-rnAnswer Expi'ess Ivaiuat!cn iiepa*
Aprcndix C - Process Evalr.:ation Sur,-ey- lnsti'u,nents
Roclq Mountain Power
Exhibit No, 5 Page 1 147 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Variable Name Description Tvpe
&CONTACT Respondent name Text
&FIRM Comoanv name Text
&PROGRAM FinAnswer Express Text
&SITE Address Text
&YEAR Year of oroiect completion YYYY
&PACIFICORP Rocky Mountain Power, Pacific Power Text
&PREINSPECTDATE Date of first inspection Date MMYYYY
&POSTINSPECTDATE Date of post inspection Date MMYYYY
&INSTALLED MEASURES List of installed measures Text
&MEASURE TYPE 1 Name of Measure 1 Text
&MEASURE TYPE 2 Name of Measure 2 Text
&Vendor Vendor that completed the proiect Text
&INCENTIVE Amount oaid for oarticioation Numeric
&PM Flae for PM delivered proiect BINARY
&NC Flae for New construction proiect BINARY
Fags C-l
N&V$t,,qS{T
Suruey lnstrument
Introduction and Screen
INTROL. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficiency programs. This is not a sales call. May I
please speak with &CONTACT?
1. YES, TFIAT IS ME ) SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU
3. NOT NOW ' SCHEDULE APPT AND CALL BACK
4. NO/REFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficiency programs. This is not a sales call.
&PACIFICORP is evaluating its program and would appreciate your input."
I'd like to let you know that this call may be monitored or recorded for quality assurance purposes. Also,
all of your responses will be kept confidential and will not be revealed to anyone outside of the research
team. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research pu{poses only and will take about 15 minutes."I
1. YES ) SKIP TO IS2
2. NOT NOW ) MAKE APPT. TO CALL BACK
3. NO/REFUSED ) TERMINATE
INTRO3. &PACIFICORP is evaluating its &PROGRAM program and would appreciate your input. I'd
like to let you know that this call may be monitored or recorded for quality insurance purposes. Also, all
of your responses will be kept confidential and will not be revealed to anyone outside of the research
team. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research purposes only and will take about 15 minutes."I
4, YES
5. NOT NOW ) MAKE APPT. TO CALL BACK
5, NO/REFUSED ) TERMINATE
INTROL. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficienry programs. This is not a sales call. May I
please speak with &CONTACT?
1. YES, TFIAT IS ME ) SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU
3. NOT NOW
'
SCHEDULE APPT AND CALL BACK
4. NOiREFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER, calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficiency programs. This is not a sales call.
&PACIFICORP is evaluating its &PROGRAM program and would appreciate your input."
I'd like to let you know that this call may be monitored or recorded for quality assurance purposes. Also,
all of your responses will be kept confidential and will not be revealed to anyone outside of the research
Ccnirderirai om Fropiiefory
iCshc irnAnswel Exsress $.vaiuaiicn Renafi
Apriendix C - Prccess Ei,aluaiitir Su,*-ey l|rslrr.rnitnts
Rocky Mountain Power
Exhibit No. 5 Page 1 148 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fate C-2
Roclry Mountain Power
Exhibit No. 5 Page 1 149 of 1 365
Case No. PAC-E-14-07
Vvitness: Kathryn C. HymasN&\s$il$"NT
team. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research purposes only and will take about 15 minutes."I
7. YES ) SKIP TO IS2
8. NOT NOW ) MAKE APPT. TO CALL BACK
9. NO/REFUSED ) TERMINATE
INTRO3. &PACIFICORP is evaluating its &PROGRAM program and would appreciate your input. I'd
like to let you know that this call may be monitored or recorded for quality insurance purposes. Also, all
of your responses will be kept confidential and will not be revealed to anyone outside of the research
team. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research purposes only and will take about 15 minutes."I
10. YES
11. NOT NOW ' MAKE APPT. TO CAIL BACK
12. NO/REFUSED ) TERMINATE
13.
[IF VERIFICATION IS NEEDED, TELL THEM THEY CAN CALL SHAWN GRANT AT 801-220.
41961.
IS2a. &PACIFICORP records indicate that your firm received an incentive from the &PROGRAM
program in &YEAR after installing &INSTALLED_MEASURES at &SITE, is this correct?
1,. YES ) SKIP TO IS3
2, NO, DID NOTPARTICIPATE
3. NO, ONE OR MORE MEASURES ARE INCORRECT ) SKIP TO IS2d
4. NO, ADDRESS IS INCORRECT ) SKIP TO IS2C
88. DON'T KNOWNOT SURE) TERMINATE
99. REFUSED
IS2b. Is there someone else that might be familiar with this project?
1.Yes
2. No ) TERMINATE
88. Don't know ) TERMINATE
IS2c. May I speak with that person?
1.Yes ) RETURN TO INTRO2
2. Not now) SCHEDULE CALLBACK
3. No ) TERMINATE
IS2d. What measures were installed?
1. IRECORD RESPONSE]
88. DON'T KNOWNIOT SURE
99. REFUSED
IS2e. \AIhat is the correct address?
L. [RECORD RESPONSE]
88. DON'T KNOWAJOT SURE
99. REFUSED
Corirciendrai ;ritii F,"optisiary
itjano F r nAns'r-,el S >rpress Sr,aiiration llepo*
Aprendix C - Piocess Evaiuatiur Suruey irstrum*nis
Fage C-3
ru&v$ileNT
IS3. Are you the person most familiar with &FIRM's decision to implement this project?
1. YES
2. NO ) SKIP to IS2b
88. DON'T KNOWNOT SURE ) SKIP to IS2b
99. REFUSED ) SKIP to IS2b
Awareness & Participation
APL. How did you first become aware of &PROGRAM? IDO NOT READ RESPONSES; ALLOW
MULTIPLE RESPONSES]
1. ACCOUNT REPRESENTATIVE OR OTFIER &PACIFICORP STAFF
2, &PACIFICORP RADIO ADVERTISEMENT
3. &PACIFICORPPRINTADVERTISEMENT
4. &PACIFICORPPRINTEDMATERIALS/BROCHURE
5. &PACIFICORPONLINE ADVERTISEMENT
6. &PACIFICORP TV ADVERTISEMENT
7. &PACIFICORPNEWSLETTER
8. &PACIFICORP WEBSITE
9, PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
10. CONFERENCE, WORKSHOP, OR EVENT [SpECIFy:_]
11. &PACIFICORP SPONSORED ENERGY ALIDIT OR TECHNICAL ASSESSMENT
12. FROM TRADE ALLY, VENDOR OR CONTRACTOR
13. ANOTHER BUSINESS COLLEAGUE
14. FAMILY, FRIEND, OR NEIGHBOR
15. OTFIER [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSE
AP2. Why did your firm decide to participate in the program? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
1 1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, production, or quality
15. To improve value of property
15. To improve comfort
17. Other [SPECIFY]:
Ccrr.lde;lira,r enrt Propristary
iCai:c FinAnswer Exoress Ivaiuaticn Rena*
Apwndix C - Pi'ocess fvaluaii+n Suruey iirsirumenis
Rocky Mountain Power
Exhibit No. 5 Page '1 150 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pags C-4
ru Aur $il.\ Nr r
88. DON'T KNOWNOT SURE
99. REFUSE
[IF more than one response to AP2]
AP2a.
Of those reasons, which one was most influential in the decision to participate in the program?
[AILOW ONLY ONE RESPONSE]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, production, or quality
15. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
Pre-Installation Section
IIF &PREINSPECTDATb0I EEL. When you first became involved with the &PACIFICORP program,
an energy engineer came out to your facility to inspect existing equipment. Using a scale of L to 5 where
1 indicates'very dissatisfied' and 5 indicates 'very satisfied', how satisfied were you with the energy
engineer who came out to your facility?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHATSATISFIED, SKIP TO EE3
5. VERY SATISFIED ) SKIP TO EE3
88. DON'TKNOWNOTSURE ) SKIPTO EE3
gg.REFUSED )SKIPTOEE3
EE2. Why were you Iess than satisfied with the energy engineer?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Conirdeni, ar elij,sropr'eiary
i$aho SinA.nswer Hxlr+ss Ivaiuaticn Rena*
Apendix C - Piccess [vaiuatri]t Sui*,e:,'irtstrunt*nts
Rocky Mountain Power
Exhibit No. 5 Page 1 151 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fa*e C-5
*h*,s\\t'$ileNJ'T
[IF &VENDOR>0] EE3. The records we received show that you worked with &VENDOR on this project.
Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5 indicates 'very satisfied', how satisfied
were you with &VENDOR?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO IMl
5. VERY SATISFIED ) SKIP TO IMl
88. DON'T KNOWNOT SURE ) SKIP TO IMl
99. REFUSED ) SKIP TO IMl
EEa. Why were you less than satisfied with the &VENDOR?
1-. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
[IF &PM=1] EE5. As part of the program, you received a report documenting the findings from the
energy analysis that included recommended equipment and changes. Did you find this report valuable?
1. YES ) SKIP TO IMl
2. NO
3. DON'T RECALL RECEIVING A REPORT ' SKIP TO IM1
88. DON'T KNOWNOT SURE ) SKIP TO IMl
99. REFUSED ) SKIP TO IMI.
EE5. \Atrhy not?
1. [RECORD RESPONSE]
88. DON'T KNOWNIOT SURE
99. REFUSED
Installed Measures
READ: I'm going to ask a few questions about the equipment that you installed.
[REPEAT FOR EACH &MEASURE-TYPE UP TO TWO MEASURESI
IIF &NC=l, SKIP to IM3l IML. Did the &MEASURE_TYPE# installed through the program replace
existing equipment or was it a new installation?
1. REPLACED EXISTING EQUIPMENT) SKIP TO IM2
2. TOTALLY NEW INSTALLATION ) SKIP TO IM3
88. DON'T KNOWNOT SURE ) SKIP TO IM1A
99. REFUSED ) SKIPTO IMI.A
IMIA. Could you please provide contact information for the person who would know about the
equipment that was installed with this projec! and we can ask them specifically about equipment?
1. [COLLECT: IM_CONTACT_NAME, IM_CONTACT_PHONE, and IM_CONTACT_EMAIL]
) SKIP TO PIl
IM2. What was the operating condition of the equipment that the &MEASURE_TYPE# replaced?
1. EXISTING EQUIPMENTHAD FAILED
i?,rnirderrlni al ri Fropi"reiary
idehc FrrAnswer Exprsss Ivaiuaticn Repr:ri
Aprendix C * Process Evaluati+n Sur,'ey irrstrumrnts
Roclq Mountain Power
Exhibit No. 5 Page I 152 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page C-S
N$V$il,qNT
2. EXISTING EQLIIPMENT WORKING BUT WITH PROBLEMS
3. EXISTING EQLIIPMENT WORKING WITTI NO PROBLEMS
4. OTFIER [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
IM3. Have the energy savings related to this equipment met your expectations?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
IM4. What other benefits, if any, have you observed from the &MEASURE-TYPE#?
1. NONE
2. YES [RECORD RESPONSE]:
88. DON'T KNOWNOT SURE
99. REFUSED
IMS. Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5 indicates'very satisfied', overall,
how satisfied were you with the performance of the &MEASURE_TYPE#?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO PIl
5. VERY SATISFIED ) SKIP TO PII.
88. DON'TKNOWNIOTSURE ) SKIPTO PI1
99. REFUSED ) SKIP TO PIl.
IM5. Why were you less than satisfied with the performance of the &MEASURE_TYPE#?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Post-Installation
IIF &POSTINSPECTDATE>0] PIl. After your project was installed, around &POSTINSPECTDATE, a
program representative came out to your facility to verify your installation. Using a scale of 1 to 5 where
1 indicates'very dissatisfied' and 5 indicates'very satisfied', how satisfied were you with the
inspection?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHATSATISFIED ) SKIP TO FRl.
5. VERY SATISFIED ) SKIP TO FR1
88. DON'TKNOWA{OTSURE ) SKIPTO FRl
99.REFUSED )SKIPTOFRl
Coniidefl liai nnd Froprlefary
idaho f inAns'wel Sxprsss Ivaiuation Repoit
Aprendix C - Process fvaluation Suruey- lnstrunents
Rocky Mountain Power
Exhibit No. 5 Page 1 153 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pagt i-I
.!*
hi $V$TANI T
C.
D.
E.
F.
G.
PI2. Why were you less than satisfied with the inspection?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Free Ridership
FRL. With the &PROGRAM program, &FIRM received [IF &PM=], add "technical assistance identifying
energy saving opportunities and"l financial incentives of &INCENTIVE for installing
&INSTALLED_MEASURES with the program.
On a scale from 1 to 5, with 1 being not important at all and 5 being extremely important how important
were the following factors in deciding which equipment to install.
A. RECOMMENDATION FROM CONTRACTOR OR VENDOR [if &VENDOR >0, replace
"Contractor or vendor" with &VENDORI _
B. INFORMATION PROVIDED BY &PACFICORP ON ENERGY SAVING OPPORTUNITIES
Rocky Mountain Power
Exhibit No. 5 Page 1 '154 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
INFORMATION ON PAYBACK
THE &PACFICORP INCENTTVE
FAMILIARITY WITH THIS EQUIPMENT
PREVIOUS PARTICIPATION WITH A &PACIFICORP PROGRAM
CORPORATE POLICY REGARDING ENERGY REDUCTION
[REPEAT FR2-FR7 FOR EACH &MEASURE TYPE# UP TO TWO MEASURES]
[READ: "When answering these next questions, think specifically about &MEASURE_TYPb#
installed through the program."l
FR2. Without the program, meaning without the financial incentive [IF &PM=1, add "and technical
assistance"], would you have still installed the exact same &MEASURE_TYPE_# at the same time?
1. YES ) SKIP TO FRTa
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
FR3. Without the program, would you have installed any &MEASURE_TYPE_# equipment?
1. YES
2. NO ) SKIP TO FRTa
88. DON'T KNOWNOT SURE
99. REFUSED
FR4. Would you have installed this equipment within 12 months of when you did with the program?
1. YES
2. NO ) SKIP TO FRTa
88. DON'T KNOWNOT SURE ) START NEXT MEASURE
99. REFUSED ) START NEXT MEASURE
Conircrenlrai and Proprreisry
itj.rlro FinAns'r,'lel Ixpress Ivaiuatian iiepi:ri
Ap;:endix C - Process [vaiuatlsn Suiuey irrstiunmnts
Fugr'l-8
:*
N $\.J $il],q N T
FRS. Relative to the energy efficiency of &MEASURE_TYPE_# installed through the program, how
would you characterize the efficiency of equipment you would have installed without the program?
1. ]ust as efficient as installed with the program
2. Lower than installed through the program, but better than the standard efficiency
3. Standard efficiency
FR6a. Would you have installed the same amount of &MEASURE_TYPE-#?
1. YES ) START NEXT MEASURE
2. NO
88. DON'T KNOWNOT SURE ) START NEXT MEASURE
99. REFUSED ) START NEXT MEASURE
FR5b. Would you have installed more or less equipment?
1. MORE) How much more?
2. LESS) How much less?
88. DON'T KNOWNOT SURE
99. REFUSED
uF FR1D < 3 AND FR3 = 2l
FR7a. Previously, you said that the incentive was not important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would not have installed
any equipment. In your own words, can you please describe what impact the program had on your
decision to install the equipment?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF FR1D < 3 AND FR4 = 2l
FR7b. Previously, you said that the incentive was not important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would not have installed
any equipment with 12 months of when you did. In your own words, can you please describe what
impact the program had on your decision to install the equipment?
L. IRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
lrF FR1D > 3 AND FR2 = U
FR7c. Previously, you said that the incentive was important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would have installed the
exact same equipment at the same time. In your own words, can you please describe what impact the
program had on your decision to install the equipment?
L. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
lrF FR1B < 3 AND FR3 = 2l
*nr,rderirai en*' P,'opriaf ary
iCono FinAns'rrei Exlis*<s Ivaiua{icn iiepa*
Apuendix C - Prccess Evah.iatlon Sui"-e,v lttstiunenis
Rocky Mountain Power
Exhibit No. 5 Page 1 1 55 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page C-S
N$V$il&NY
FR7d. Previously, you said that the technical assistance was not important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would not have installed
any equipment. In your own words, can you please describe what impact the program had on your
decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWI{OT SURE
99. REFUSED
IIF FR1B < 3 AND FR4 = 2l
FR7e. Previously, you said that technical assistance was not important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would not have installed
any equipment with 12 months of when you did. In your own words, can you please describe what
impact the program had on your decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF FR1B > 3 AND FR2 = 1l
FR7f. Previously, you said that the technical assistance was important in your decision to install the
&MEASURE_TYPE#. However, you also said that without the program, you would have installed the
exact same equipment at the same time. In your own words, can you please describe what impact the
program had on your decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Spillover
REPEAT SPl for each &MEASURE_TYPE#
SPL. Since participating in this program, have you purchased on installed any additional
&MEASURE_TYPE#?
1. YES
2. NO ) START next measure or SKIP TO SP2
88. DON'T KNOWNOT SURE ) START next measure or SKIP TO SP2
99. REFUSED ) START next measure or SKIP TO SP2
SPLa. \Atrhat did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SPlb. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
th iienirai ariii Pioi",risiory
i$sno Frn-a.nsiriel Ixpiess Ir,aiuaiicn Repo*
Aprcndix C - Prccess Evalualicr Suney irstii-ii^+enis
Roclry Mountain Power
Exhibit No, 5 Page 1 1 56 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fai:e C-10
ru &v$teNi T
SP1c. Relative to the energy efficiency of &MEASURE_TYPE_# installed through the program, how
would you characterize the efficiency of this equipment?
1. Just as efficient as installed with the program
2. Lower than installed through the program, but better than the standard efficienry
3. Standard efficiency
SPld. Did you receive an incentive from &PACIFICORP or another organization?
1. YES
2. NO ) SKIP TO SPl.f
88. DON'T KNOWNOT SURE ) SKTP TO SPl.f
99. REFUSED ) SKIP TO SPlf
SPle. \A/hat program or sponsor provided an incentive?
1.. &PACIFICORP
2. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
SP1f.I'm going to read a statement about the additional &MEASURE_TYPE# that you purchased on
your own. On a scale from 1 to 5, with 1 indicating that you "strongly disagree" and 5 indicating that
you "strongly agree", please rate the following statement:
My experience with SPACIFICORP's &PROGRAM program influenced my decision to install additional high
fficiency equipment on my own.
Would you say you...[READ 1-51
1. STRONGLY DISAGREE
2. SOMEWHATDISAGREE
3. NEITHER AGREE OR DISAGREE
4. SOMEWHATAGREE
5. STRONGLY AGREE
88. DON'T KNOWNOT SURE
99. REFUSED
IIF SPle not Ll SPlg.Why did you not apply for an incentive from &PACIFICORP for this equipment?
1.. [RECORD RESPONSE]
88. DON'TKNOW/NOTSURE
99. REFUSED
SP2. Since participating in this program, have you purchased on installed any OTHER energy
ef f iciency improvements?
1. YES
2. NO ) SKIP TO 81.
88. DON'T KNOWNOT SURE ) SKIP TO 81
99. REFUSED ) SKIP TO 81.
SP2a. \A/hat did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1". [RECORD RESPONSE]
Con*derirai en d Fru.g;ref ary
ldaho FinAnswer [>rsi'ess Evaiuation Repolt
Aplendix C - Pi'tcess f.vali.iatisit Suruey irstrr;menis
Rocky Mountain Power
Exhibit No. 5 Page 1 '157 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
Fage C- i i
ru Avtrt,qNT
88. DON'T KNOWNOT SURE
99. REFUSED
SP2b. How many did you purchase or install?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SP2c. How would you characterize the efficiency of this equipment?
1. The most efficient or ENERGY STAR certified
2. Lower than the most efficient, but better than the standard efficiency
3. Standard efficiency
SP2d. Did you receive an incentive from &PACIFICORP or another organization?
1. YES
2. NO ) SKIP TO SP2f
88. DON'T KNOWNOTSURE ) SKIP TO SP2f
99.REFUSED ) SKIPTO SP2f
SP2e. What program or sponsor provided an incentive?
1. &PACIFICORP
2. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SP2f. I'm going to read a statement about the other equipment that you purchased on your own. On a
scale from 1 to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you "strongly
agree" , please rate the following statement:
My experience with SPACIFICORP's €TPROGRAM program influenced my decision to install other high
efficiency equipment on my own.
Would you say you...[READ 1"-5]
1. STRONGLY DISAGREE
2. SOMEWHATDISAGREE
3. NEITHER AGREE OR DISAGREE
4. SOMEWHAT AGREE
5. STRONGLY AGREE
88, DON'T KNOWNOT SURE
99. REFUSED
IIF SP2e not 1l SP2g. Why did you not apply for an incentive from &PACIFICORP for this equipment?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Bariers
ConrlCenirai arliJ Fropr'efory*
itieho FinAnswer Express Ivaiuation fiecort
Aplendix C - Piocess Evaluati*n Sur*ey instru,renis
Rocky Mountain Power
Exhibit No. 5 Page 1 1 58 of 1365
Case No. PAC-E-14-07. \Mlness: Kathryn C. Hymas
Page C-13
S,i $\s $t.q i\! T
81. Do you think there are other changes that you could make to improve electric efficiency at &FIRM?
1. YES
2, NO )SKIPTOICI
88. DON'T KNOWNIOT SURE ) SKIP TO ICl
99. REFUSED ) SKIP TO ICl
82. Could you provide some examples of changes you think would improve electric efficienry at
&FIRM?
1.. [RECORD RESPONSE: PROBE FORADDITIONAL]
88. DON'TKNOWA{OTSURE
99. REFUSED
83. Are plans in place to make any of those changes?
].. YES
2, NO )SKIPTOBs
88. DON',T KNOWNOT SURE ) SKIP TO Bs
gg.REFUSED ) SKIPTO85
84. Are incentives from &PACIFICORP or another organization part of those plans?
1. NO
2. YES
88. DON'T KNOWNOT SURE
99. REFUSED
85. \,1/hat factors could prevent &FIRM from making these changes? [DO NOT READ RESPONSES;
AttOW MULTIPLE RESPONSES]
1. HIGH UPFRONT COSTS
2. LACK OF ACCESS TO CAPITAL
3. LONG PAYBACK PERIOD; SLOW RATE OF REruRN
4. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
5. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
6. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
7. OTHER (SPECIFY-)
88. DON'T KNOWNOT SURE
99. REFUSED
IIF MORE TIIAN ONE RESPONSE TO B5l 86. Which of these do you think is the most challenging
factor?
1. HIGH UPFRONT COSTS
2. LACK OF ACCESS TO CAPITAL
3. LONG PAYBACK PERIOD; SLOW RATE OF RETURN
4. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
5. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
6. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
7. OTHER(SPECIFY_)
Conirde,llrai anil Fio;:iiefary
iCaiic irnAnsiriel [>.Dress Ivaiuation ileoo*
Ap*endix C - Pi'ccess Evaluatisil Suire! irrstiunients
Rocl(y Mountain Po\ryer
Exhibit No. 5 Page 1 159 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C-13
ros v tt,q N T
88. DON'T KNOWNOT SURE
99. REFUSED
Satisfaction
ICl. Using a scale of 1 to 5 where 1 indicates 'very dissatisfied' and 5 indicates'very satisfied', how
satisfied were you overall with the program?
1. VERY SATSIFIED
2. SOMEWHAT DISSATISFIED
3. NEMHER SATISFIED OR DISSATISFIED
4. SOMEWHATSATISFIED ) SKIP TO IC2
5. VERY SATISFIED
'
SKIP TO IC2
88. DON'T KNOWA{OT SURE ) SKIP TO IC2
99. REFUSED
'
SKIP TO IC2
ICIA. Why were you less than satisfied with the program overall?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IC2. If you could change anything about the &PROGRAM program, what would you change?
I. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IC3. During your involvement with &PROGRAM did you ever contact &PACIFICORP with questions or
requests for assistance?
1. YES
2. NO ) SKIP TO FBl
88. DON'T KNOWNOT SURE ) SKIP TO FBl
99.REFUSED ) SKIPTO FBl
IC4. Were &PACIFICORP and its representatives timely in addressing your questions in regards to the
program?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
IC5. Were &PACIFICORP and its representatives knowledgeable in regards to the program and the
program eligibility requirements?
1. YES
2. NO
88. DON'T KNOWA{OT SURE
99. REFUSED
Coniidenlred,BneJ Froi:rciary
iiJaho FinA.nswer [xprsss Evaiuaticn iie*o*
Aplendix C - Piorcss Evaliiatirn Survey instrumenis
Rocky Mountain Power
Exhibit No.5 Page 1160 of'1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C^i4
N&V$T-qNT
Finnographics
FBl INTRO.
Now I have a few final, general questions about your comp:rny for comparison purposes only.
FBl. Which of the following best describes your company's primary activities?
1. MANUFACTURING
2. RETAIL
3. DAIRY / AGRICULruRAL
4. FINANCE AND INSURANCE
5. FOOD PROCESSING
6. REFRIGERATED WAREHOUSE
7. PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES
8. EDUCATIONAL SERVICES
9. HEALTH CARE
10. PUBLIC ADMINISTRATION
1].. ARTS, ENTERTAINMENT, AND RECREATION
12. ACCOMMODATION
13. FOOD SERVICES
14. REAL ESTATE
15. MINING
1.6. OIL AND GAS
1.7. OTHER ISPECIFY]
88. DON'T KNOWI{OT SURE
99. REFUSED
FB2. Approximately, what percent of your total annual operating costs does your electricity bill
represent?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
FB3. About how many people does your firm employ?
1. IRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
End
ENDL. Those are all of the questions that I have for you. Is there anything about your experiences with
&PACIFICORP's &PROGRAM program you'd like to mention that we did not talk about today?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
[THANK RESPONDENT AND TERMINATE SURVEY]
Conrldenirai an a' Propreiary*
irjslro FinAns',ver Ixpress Ir'aiuation Repari
Aprcndix C * Process Evaluaticn Suruey instrunents
Rocky Mountain Power
Exhibit No. 5 Pdge 1 161 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C- 1 5
Rocky Mountain Power
Exhibit No. 5 Page 1 162 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. HymasN&\$${:&MT
C.2 Near-Participant lntentiew Instrument
Note: Energy FinAnswer and FinAnswer Express Near Pmticipants are those customers who are in the project
tracking systnn with aproject through the Energy FinAnswn or FinAnswer Express program during 2009-20L7
but are identified as cancelled or onhold ns of the end of20L1..
Objectioes
These surveys are designed to meet the following list of objectives.
o To describe how customers come to participate in the program
o To characterize the current status of projects identified as on hold or cancelled
o To understand overall customer satisfaction with the program, while participating
r To understand what it would take to motivate near participants to participate
o To understand barriers customers are facing that prevent increasing energy efficiency
o To characterize near-participant firms
Variables
lnteroiew Instrament
Introduction and Screen
INTROI.. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's &PROGRAM and would like to hear about your
experiences. This is not a sales call. May I please speak with &CONTACT?
1. YES, THAT IS ME ) SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU ) SKIP TO INTRO2
3. NOT NOW ) SCHEDULE APPT AND CALL BACK
4. NO/REFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's &PROGRAM and would like to hear about your
experiences. This is not a sales call."
I'd like to let you know that this call may be monitored or recorded for quality assurance purposes. Also,
all of your responses will be kept confidential and will not be revealed to anyone outside of the research
team. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research purposes only and will take about 10 minutes."I
Ccnideni,ai ortf Froptefsty
iiohc FinAnstrer Hxpress Ivaiuai!on Rept"r*
Aprcndix C - Process [vaiuati.sn Sui"'ey instiumentE
Variable Name Description Tvpe
&CONTACT Respondent name Text
&FIRM ComDanv name Text
&PROGRAM Energy FinAnswer, FinAnswer Express Text
&SITE Address Text
&YEAR Year of proiect start YYYY
&PACIFICORP Rocky Mountain Power, Pacific Power Text
Face C-l 6
,.l[,N&V$TAruT
14. YES ) SKIP TO IS2a
15. NOT NOW ) MAKE APPT. TO CALL BACK
16. NO/REFUSED ) TERMINATE
INTRO3. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research purposes only and will take about L0 minutes."l I'd like
to let you know that this call may be monitored or recorded for quality assurance purposes. Also, all of
your responses will be kept confidential and will not be revealed to anyone outside of the research team.
17. YES
18. NOT NOW ) MAKE APPT. TO CALL BACK
19. NO/REFUSED ) TERMINATE
[IF VERIFICATION IS NEEDED, TELL THEM THEY CAN CALL SHAWN GRANT AT 801.-220-
41961.
IS2a. &PACIFICORP records indicate that you were considering a project to improve efficiency at &SITE
with the &PROGRAM program in &YEAR but did not complete the project and get an incentive, is this
correct?
5. YES
'
SKIP TO APl
6, NO, DID NOT PARTICIPATE
7. NO, COMPLETED PROIECT AND GOT INCENTIVE ) CONFIRM &TERMINATE
89. DON'T KNOWNOT SURE
99. REFUSED
IS2b. Is there someone else that might be familiar with this project?
1. Yes
2. No ) TERMINATE
88. Don't know ) TERMINATE
IS2c. May I speak with that person?
1. Yes ) RETURN TO INTRO2
2. Not now) SCHEDUTE CALLBACK
3. No ) TERMINATE
IS3. Are you the person most familiar with &FIRM's decision to begin this project?
1.. YES
2. NO ) SKIP to IS2b
88. DON'TKNOWNOTSURE ) SKIPto IS2b
99. REFUSED ) SKIP to IS2b
Awareness & Participation
APl. How did you firstbecome aware of &PROGRAM? [DO NOT READ RESPONSES]
16. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
17. &PACIFICORP RADIO ADVERTISEMENT
18. &PACIFICORP PRINT ADVERTISEMENT
19. &PACIFICORP PRINTED MATERIALSEROCHURE
Ccniide,,riraj orii Pio.nref*ry
Itlsirc FinAnsi,rei [>lDress Ivaiuation llepu*
Aprcndix C * Process Eval*ati.w Suivey instrumenis
Roclry Mountain Power
Exhibit No. 5 Page 1163 of '1365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
Fage C-l?
,{
N d\V $ t,q $-d T
20. &PACIFICORP ONLINE ADVERTISEMENT
21. &PACIFICORP TV ADVERTISEMENT
22. &PACIFICORP NEWSLETIER
23. &PACIFICORPWEBSITE
24. PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
25. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_]
26. &PACIFICORP SPONSORED ENERGY AUDIT OR TECHNICAL ASSESSMENT
27. FROM TRADE ALLY, VENDOR OR CONTRACTOR
28. ANOTHER BUSINESS COLLEAGUE
29. FAMILY, FRIEND, ORNEIGHBOR
30. OTHER [SPECIFY]:
89. DON'T KNOWNOT SURE
99. REFUSE
AP2. Why did you decide to participate in the program? [DO NOT READ RESPONSES; SELECT ALL
THAT APPLY]
1.. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
1 1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Recommended by &PACIFICORP staff
15. To improve operations, production, or quality
16. To improve value of property
17.To improve comfort
18. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSE
[IF more than one response to AP2]
AP2a. Of those reasons, which one was most influential in your decision to participate in the program?
IALLOW ONLY ONE RESPONSEI
1.. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
Rocky Mountain Power
Exhibit No. 5 Page 1 164 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
DOnr'ideniiaj end pl6rpriefOry
idoho FinAns'*er Expi"sss Svalunlion ilepo*
Appendix C - Pt'ocess fvaluati*n Suivey iitsiti;nisnls
Fage C-lS
N$V$TAruT
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Recommended by &PACIFICORP staff
15. To improve operations, productiory or quality
16. To improve value of property
17.To improve comfort
18. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
Near Participant
NPL. Thinking back to the project that you started under the &PROGRAM program at this site, how
would you characterize its status today? [IF NECESSARY, READ OPTIONS]
1. NOW DOING PROIECT
2. PLANNING TO DO PROIECT /PROJECT ON HOLD
3. COMPLETED PROIECT WITHOUT PROGRAM ) SKIP TO NPs
4. NOT DOING PROJECT/ PROJECT CANCELLED ) SKIP TO NP5
5. OTHER[SPECIFY-] ) SKIP TO NP7
88. DON'T KNOWNIOT SURE ) SKIP TO NP7
99. REFUSED ) SKIP TO NP7
NP2. \A/hy did you put the project on hold?
1. Not on hold
2. Needed to acquire capital funding
3. Delays from contractor
4. Other [RECORD RESPONSE]
88. DON'T KNOWI{OT SURE
99. REFUSED
NP3. Will th e project be completed under a &PACIFICORP program?
1. YES
2. NO ) SKIP TO NPs
88. DON'T KNOWI{OT SURE ) SKIP TO NP5
99, REFUSED ) SKIP TO NPs
NP4. Which program will you complete the project under? [READ LIST]
1.. SELF-DIRECTION CREDIT ) SKIP TO 81.
2, ENERGY FINANSWER ) SKIP TO B1
3. FINANSWER EXPRESS) SKIP TO 81
4, OR SOMETHING ELSE (SPECIFY-) ' SKIP TO 81
88. DON'T KNOWNOT SURE ) SKIP TO 81.
99. REFUSED ) SKIP TO B1
Roclry Mountain Power
Exhibit No. 5 Page 1 165 of 'l 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Conririeri,ei aird Fropr'efary
iiianc FinAns'rrer Exprsss Svaiuation iieno*
Apsendix C - Process Evaiuatim Suivey iitstr,;nenis
Fage C-i$
Nd\k"$t&NT
NPS.IA/hy did you decide do the project without participating in any programs?
1. [RECORD RESPONSE] ) SKrP TO NP7
88. DON'T KNOWNOT SURE) SKIP TO NP7
99, REFUSED' SKIP TO NP7
NP6. Why did you decide not do to the project?
1. [RECORD RESPONSE] ) SKrP TO NP7
88. DON'T KNOWT{OT SURE) SKIP TO NP7
99. REFUSED) SKIP TO NP7
NP7. What would need to change for you to participate in &PROGRAM or similar program?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Barriers
81. Do you think there are other changes that you could make to improve electric efficiency at &FIRM?
1. YES
2. NO ) SKIP TO ICl
88. DON'T KNOWAIOT SURE ) SKIP TO ICl.
99. REFUSED ) SKIP TO ICI.
82. Could you provide some examples of changes you think would improve electric efficienry at
&FIRM?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
83. Are plans in place to make any of those changes?
1. YES
2. NO +SKIPTOBs
88. DON'T KNOWNIOT SURE ) SKIP TO 85
99.REFUSED ) SKIPTOBs
B4. Are incentives from &PACIFICORP or another organization part of those plans?
1. NO
2. YES
88. DON'T KNOWNOT SURE
99. REFUSED
Ccnr-Sderlrai enC Froprreiory*
idsnc FrnAnsv,ier Hxpress Evaiuaticn Reno$
Aprendix C - Prscess Evaluatisn Suireli irrstru, enis
Rocky Mountain Power
Exhibit No.5 Page 1166 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C-2S
Rocky Mountain Power
Exhibit No. 5 Page 1'167 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
,,:*
N,.s\\d $ ill A hj T
85. What factors could prevent &FIRM from making these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPTE RESPONSES]
8. HIGH UPFRONT COSTS
9, LACKOF ACCESSTO CAPITAL
10. LONG PAYBACK PERIOD; SLOW RATE OF REruRN
11. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
12. LACK OF INFORMATION ABOUT SAVINGS AND PERIORMANCE
13. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
14. OTHER (SPECIFY
-)
88. DON'T KNOWNOT SURE
99. REFUSED
IIF MORE THAN ONE RESPONSE TO B5l 86. Which of these do you think is the most challenging
factor?
8, HIGH UPFRONT COSTS
9. LACK OF ACCESS TO CAPITAL
10. LONG PAYBACK PERIOD; SLOW RATE OF REruRN
11. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
12. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
13. LACK OF RESPONSTBLE/ACCOUNTABLE ENERGY STAFF
14. OTHER (SPECIFY-)
88. DON'T KNOWNOT SURE
99. REFUSED
Satisfaction
ICL. Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5 indicates 'very satisfied', how
satisfied were you overall with the experience that you had with the program?
1. VERY DISSATSIFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO IC2
5. VERY SATISFIED ) SKIP TO IC2
88. DON'T KNOWNOT SURE ) SKIP TO IC2
99. REFUSED
'
SKIP TO IC2
ICIA. Why were you less than satisfied with the program overall?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IC2. During your involvement with &PROGRAM did you ever contact &PACIFICORP with questions or
requests for assistance?
1. YES
2. NO ' SKTP TO FB1
CrnricJeri,ai +nir Fropreiery
i$ei:o FinA.nsvier [xpress $vaiuation fiepr:rt
Apuendix C - Pi'scess fvaluatlrn Sui*'e--v hsti.lnents
Fage C-21
ru&v$ffilq.N.T
88. DON'T KNOWNOT SURE ) SKIP TO FBl
99. REFUSED ) SKIP TO FBl.
IC3. Were &PACIFICORP and its representatives timely in addressing your questions in regards to the
program?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
IC4. Were &PACIFICORP and its representatives knowledgeable in regards to the program and the
program eligibility requirements?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
Firmographics
FBl. Now I have a few final, general questions about your company for comparison purposes only.
\Atrhich of the following best describes your company's primary activities?
1. MANUFACruRING
2. RETAIL
3. DAIRY/AGRICULTURAL
4. FINANCE AND INSURANCE
5. FOOD PROCESSING
6. REFRIGERATED WAREHOUSE
7. PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES
8. EDUCATIONAL SERVICES
9. HEALTH CARE
10. PLTBLIC ADMINISTRATION
11. ARTS, ENTERTAINMENT, AND RECREATION
12. ACCOMMODATION
13. FOOD SERVICES
14. REAL ESTATE
15. MINING
15. O[ AND GAS
17. OTHER TSPECITY]
88. DON'T KNOWNOT SURE
99. REFUSED
FB2. Approximately, what percent of your total annual operating costs does your electricity bin
represent?
1. [RECORD RESPONSE]
88. DON'T KNOWI{OT SURE
99. REFUSED
FB3. About how many people does your firm employ?
Conirderiia;rnii Froprefary Fage C-22
i i siic F r n.{.n sirie i E x
"n
i'sss Evai u ati cn iiepu.rt
Aplendix C * Piccess fvaluatrcn Survey irstr:;nienis
Roclry Mountain Power
Exhibit No. 5 Page '1 168 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
Rocky Mountain Power
Exhibit No. 5 Page 1 169 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymasru,&v$t,& ruT
L. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
End
ENDI. Those are all of the questions that I have for you. Is there anything about your experiences with
&PACIFICORP's &PROGRAM program you'd like to mention that we did not talk about today?
1,. [RECORD RESPONSEI
88. DON'T KNOWAJOT SURE
99. REFUSED
TTHANK RESPONDENT AND TERMINATE SURVEY]
Conr5tleni,a ald Froprciary
itiailo FinAnswer Express Ivaiuaiion ileps*
Apliendix C - Process Evaluatisn Sur*'eY lnstiumenis
Fage C-23
.t*
ru &v$il,qNT
C.3 Non-Participant Survq Instrument
Note: Non-participants are C€d customers who are not idrntified as haoing started participating in any
PacifiCorp programs between 2009 and 20LL.
Objectioes
These surveys are designed to meet the following list of objectives.
o To assess awareness of PacifiCorp programs among non-participants
o To identify non-participant efficient purchasing
o To understand barriers customers are facing that prevent increasing energy efficiency
. To characterize non-participant firms
Variables
Suruey lnstrument
Introduction and Screen
INTROI". Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficiency programs so that they better suit the needs
of customers like you. This is not a sales call. May I please speak with the person who is responsible for
the $_CLASS electric account for $_FIRM?
1. YES, THAT IS ME ) SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU
3. NOT NOW
'
SCHEDULE APPT AND CALL BACK
4. NO/REFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's efficienry programs so that they better suit the needs of
customers like you. This is not a sales call. Do you have a few minutes? [IF NEEDED, READ: "This
survey is for research purposes only and will take about 10 minutes."I
20. YES ) SKIP TO IS2a
21. NOT NOW ' MAKE APPT. TO CALL BACK
22. NO/REFUSED ) TERMINATE
INTRO3. Great. I'd like to let you know that this call may be monitored or recorded for quality
assurance purposes. Also, all of your responses will be kept confidential and will not be revealed to
anyone outside of the research team.
Conf, dential enC P,'L1.siisi6r.y..
!*ai.ic $inA.nsy"tei Exniess Evaiuation,Qepori
AprenCrr C * Process [valuatlon Suivey lnsirunelts
Rocky Mountain Power
Exhibit No. 5 Page 1 1 70 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Variable Name Description Type
&FIRM Comnanv name Text
&PHONE Phone number Numeric
&SITE Address Text
&PACIFICORP Rocky Mountain Power, Pacific Power Text
&CLASS Revenue Class Text
Fage 0-24
ru$\.d$ilA}\dT
[IF NEEDED, READ: "This survey is for research purposes only and will take about 1.0 minutes."]
1. CONTINUE WITH INTERVIEW
2. NOT NOW ) MAKE APPT. TO CALI BACK
3. NO/REFUSED ) TERMINATE
[IF VERIFICATION IS NEEDED, TELL THEM THEY CAN CALL SHAWN GRANT AT 801.220.
41951.
VL. First, I'd like to verif my records. \Atrhich utility company provides electricity at &SITE?
1. &PACIFICORP
2. OTHER ) TERMINATE
88. DON'T KNOWNOT SURE
99. REFUSE
[IF &-CLASS "COMMERCIAL" OR "INDUSTRIAL"]V2. Was this facility at &SITE constructed before or
after 2009?
1. BEFORE2OO9
2. 2OO9ORLATER
Awareness
A1. Are you aware that &PACIFICORP offers incentives and technical assistance to &CLASS customers
to help them reduce electricity usage?
1. YES
2. NO ) SKIP to A4
88. DON'T KNOWNOT SURE ) SKIP TO A4
99. REFUSED ) SKIP TO A4
A2. How did you become aware that &PACIFICORP offers energy efficiency program(s)? IDO NOT
READ RESPONSES, SELECT Att THAT APPLY]
31. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
32. &PACIFICORP RADIO ADVERTISEMENT
33. &PACIFICORP PRINT ADVERTISEMENT
34. &PACIFICORP PRINTED MATERIALS/BROCHURE
35. &PACIFICORP ONLINE ADVERTISEMENT
36. &PACIFICORP TV ADVERTISEMENT
37. &PACIFICORP NEWSLETTER
38. &PACIFICORPWEBSITE
39. PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
40. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_]
41. &PACIFICORP SPONSORED ENERGY AUDIT OR TECHNICAL ASSESSMENT
42. FROM TRADE ALLY, VENDOR OR CONTRACTOR
43. ANOTHER BUSINESS COLLEAGUE
44. FAMILY, FRIEND, OR NEIGHBOR
45. OTHER [SPECIFY]:
90. DON'T KNOWNOT SURE
i'onf d*ntrai anci Propreiery,'
iCahc FinAnswei Expi'sss Evaiiration Relsri
Apcendir C - Pi'ocess [vaiuation Surve;r lnstrunrents
Rocky Mountain Power
Exhibit No. 5 Page 1 1 71 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
f'1age 0-2$
r*,&v $il "q N T
99. REFUSE
A3. Which programs or services can you think of that &PACIFICORP offers to &CLASS customers? [DO
NOT READ RESPONSES, SELECT ALL THAT APPLY]
1. ENERGY FINANSWER
2, FINANSWER EXPRESS
3. SELF-DIRECTIONCREDIT
4. RECOMMISSIONING
5. IRRIGATION LOAD CONTROL
6. IRRIGATION ENERGY SAVERS
7, INCENTIVES FOR EFFICIENT EQUIPMENT
8. TECHNICAL ASSISTANCE/ ENERGY ANALYSIS
9. DEMAND RESPONSE / LOAD CONTROL
10. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
A4. In the future, what is the best for &PACFICORP to keep you informed about programs they offer
that could help your firm save energy?
1. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
2. RADIOADVERTISEMENT
3. PRINTADVERTISEMENT
4. PRINTEDMATERIALS/BROCHURE
5. ONLINEADVERTISEMENT
6, TVADVERTISEMENT
7, NEWSLETTER
8. WEBSITE
9. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_]
10. TRADE ALLY, VENDOR OR CONTRACTOR
11. OTHER [SPECIFY]:
91.. DON'T KNOWNOT SURE
99. REFUSE
Energy Efficient Actions by Non-Participants
llF Y2=2, SKIP TO EE2Ll
EEL. Between 2009 and 2011, did you have a systematic evaluation or audit of your facility, at &SITE, to
identify and implement operational improvements? [IF NEEDED: "this includes building and
equipment audits, system analyses, energy engineering analysis, other detailed studies."]
1. YES
2. NO )SKIPTOEE8
88. DON'T KNOWAJOT SURE ) SKIP TO EE8
99.REFUSED ) SKIPTOEE8
EE2. What factor or factors motivated you to have your facility undergo a systematic evaluation? [DO
NOT READ RESPONSES; AttOW MULTIPLE RESPONSESI
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
Con*de$liei e,,id Proprieiary*
i$ahc FinAnsu;ei Exprsss Evaluation Repori
Apoendir C - Process [valuation Surveir lnstiunients
Rocky Mountain Power
Exhibit No. 5 Page 1 172 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
l'1age C-26
ru&v$t,qN! T
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
L0. To save energy
1 1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, productiory or quality
1.5. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EE3. Did you receive assistance from &PACIFICORP or another organization? [IF NEEDED: assistance
may include technical assistance or incentives]
1. YES
2. NO ) SKIP TO EEs
88. DON'T KNOWAIOT SURE ' SKIP TO EEs
99. REFUSED ) SKIPTOEEs
EE4. What program or sponsor provided assistance?
3. &PACIFICORP ) SKIPTO EE8
4. [RECORD RESPONSE]
88. DON'T KNOWAJOT SURE
99. REFUSED
EEs. What opportunities for improvement were identified? [PROBE FOR AS MUCH DETAIL AS
POSSTBLEI
1". [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE6. \Alhat actions have you taken as a result of the study?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF EE4 not 1lEE7. \AIhy did you not apply for assistance from &PACIFICORP?
I. [RECORD RESPONSE]
88. DON'T KNOWA{OTSURE
99. REFUSED
EE8a. Did you install any high efficiency equipment at this site between 2009 and201.1?
1. YES
Confl dentiai ana Propfi efs+,'
iriuhc tinAnswei' Exni*ss f vaiuaticrn Rei:ort
Aprendir C - Frocess Evaluation Suivey lnstru,renis
Roclry Mountain Power
Exhibit No. 5 Page 1 1 73 of 1 365. Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fag,n 0-2I
ru $\d $t,q N T
2. NO
88. DON'T KNOWNIOT SURE
99. REFUSED
EE8b. Did you make any improvements to this site between 2009 and 2011 to help conserve energy?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
[IF EE8a * 1 and EESb + 1, SKIP TO EEls]
EE9. lAlhat did you install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1.. [RECORD RESPONSE]
88. DON',T KNOWI{OT SURE
99. REFUSED
EE10. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EELL. What factor or factors motivated you to make these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
1.. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
1 1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, productiory or quality
15. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EEL2. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2. NO
'
SKIP TO EE14
88. DON'T KNOWNOT SURE ) SKIP TO EE1.4
99.REFUSED > SKIPTOEEl4
Sonfidential enn Fropriefo4,'
idahn FinAnslvei Exnress fvaluation R*puri
Apcendir C - Process Ei,aluation Suruey lns$ui'nerrls
Roclry Mountain Power
Exhibit No. 5 Page I174 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C"2S
:$
hj d\$ $il,q N T
EEL3. What program or sponsor provided assistance?
5. &PACIFICORP ) SKIPTO EE1.5
6. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
EE14. Why did you not apply for an incentive from &PACIFICORP for this equipment?
L. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EEL5. Since 2009, have you implemented any load control strategies at your facility?
1. YES
2. NO ) SKIP TO 81
88. DON'T KNOWNOT SURE ) SKIP TO 81
99. REFUSED ) SKIP TO 81
EE15. What strategies have you implemented?
1. IRECORD RESPONSE]
88. DON'T KNOWNOT STIRE
99. REFUSED
EE17. What factor or factors motivated you to make these changes? IDO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP' 8. Previous experience with &PACIFICORP
9. To protect the environment.
L0. To save energy
L l.. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, productior; or quality
15. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EEL8. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2. NO ) SKIP TO EE2O
Confidentiai and Prnpnefsy
itjah* FinAnsvrei Expr*ss fvaluation Repsfi
Apcen,Jix C * Process fvaluation Suruey instrui'rrents
Rocky Mountain Power
Exhibit No. 5 Page 1 '175 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C-2$
h$ ,&\--"$teNT
88. DON'T KNOWNOT SURE ) SKIP TO EE2O
99.REFUSED ) SKIPTOEE2O
EE1.9. What program or sponsor provided assistance?
1. &PACIFICORP ) SKIPTO 81
2. IRECORD RESPONSE]
88. DON'T KNOWT{OT SURE
99. REFUSED
8E20. Why did you not apply for an incentive from &PACIFICORP for these load control
improvements?
1. IRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
[IF V2=2] EE2L. When constructing this facility, did you install any high efficiency equipment?
1. YES
2. NO ) SKIP TO 81
88. DON'T KNOWNOT SURE ) SKIP TO B1.
99. REFUSED ) SKIP TO 81
E822. What high efficienry equipment did you install? (PROBE FOR AS MUCH DETAIL AS
POSSTBLE)
2. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
E823, How many did you purchase or install?
r. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE24. What factor or factors motivated you to make these changes?
ALLOW MULTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
L4. To improve operations, productiory or quality
Confidentr'a ana Pr'oprreia4..
i$ahc FinA.nswei Expi'*ss Evaluation S.epari
Apnendir C - Process Evaluaticrr Survei,' hrstrurnerits
[DO NOT READ RESPONSES;
Roclry Mountain Power
Exhibit No. 5 Page 1 176 of '1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
l"age 0-3(i
ruflv$t-qNT
L5. To improve value of property
L5. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EE25. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2. NO )SKIPTOEEZT
88. DON'T KNOWNOT SURE ) SKIP TO EE27
99. REFUSED ) SKIPTOEEZT
EE26. What program or sponsor provided assistance?
7. &PACIFICORP ' SKIP TO B1
8. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE27. $/hy did you not apply for an incentive from &PACIFICORP for this equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
Barriers
81. Do you think there are other changes that you could make to improve electric efficienry at &FIRM?
1. YES
2. NO ) SKIP TO FBl
88. DON'T KNOWNOTSURE ) SKIP TO FBl
99.REFUSED
'
SKIPTOFBl
82. Could you provide some examples of what changes you think you could make?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
83. Are plans in place to make any of those changes?
1. YES
2. NO ) SKIP TO 85
88. DON'TKNOWNOTSURE
'
SKIP TO 85
99. REFUSED ) SKIPTO 85
84. Are incentives from &PACIFICORP or another organization part of those plans?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
Confrde,rira enC Froer-r'eisry
i$ah* FinA.nswer Exniess ivaiuation R*i:ori
Apuendir: C * Process [i,aluation Survey- lnstrurnents
Rocky Mountain Power
Exhibit No. 5 Page 'l 1 77 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 0-31
it
ru sv$t-&Nr T
B5. What factors could prevent &FIRM from making these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSESI
15. HIGHUPFRONTCOSTS
16. LACK OF ACCESS TO CAPITAL
17. LONG PAYBACK PERIOD; SLOW RATE OF RETURN
18. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
19, LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
20. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
21. OTHER (SPECIFY
-)
88. DON'T KNOWNOT SURE
99. REFUSED
IIF MORE THAN ONE RESPONSE TO B5l 85. \l/hich of these do you think is the most challenging
factor?
15. HIGH UPFRONT COSTS
15. LACK OF ACCESS TO CAPITAL
17. LONG PAYBACK PERIOD; SLOW RATE OF RETURN
18. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
19. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
20. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
21, OTHER (SPECIFY-)
88. DON'T KNOWNOT SURE
99. REFUSED
Firmographics
F81.. Now I have a few final, general questions about your company for comparison purposes only.
Could you describe your company's primary activities? (DO NOT READ LIST, CODE AND CONFIRIM
WITH RESPONDENT)
1. MANUFACTURING
2. RETAIL
3. DAIRY / AGRICULruRAL
4. FINANCE AND INSURANCE
5. FOOD PROCESSING
6. REFRIGERATED WAREHOUSE
7. PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES
8. EDUCATIONAL SERVICES
9. HEALTH CARE
10. PLIBLIC ADMINISTRATION
].].. ARTS, ENTERTAINMENT, AND RECREATION
12. ACCOMMODATION
13. FOOD SERVICES
14. REAL ESTATE
15. MINING
16. OILANDGAS
17. OTHER TSPECIFY]
Confrdenirai en*' Fropn*iery
idnno FinAnswer Expr*ss [vaii;ation Repa*
Apneniiir C - Process fi,aiuaticn Suruey hrstlunierts
Rocky Mountain Power
Exhibit No. 5 Page 1 178 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Faot:0-32
ru&\$$tANT
88. DON'T KNOWNOT SURE
99. REFUSED
FB2. Approximately, what percent of your total annual operating costs does your electricity bill
represent? (IF NEEDED: An estimate is fine.)
1. [RECORD RESPONSE]
88. DON'T KNOWAIOT SURE
99. REFUSED
FB3. And about how many people does your firm employ at this facility?
1.. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
End
ENDL. Those are all of the questions that I have for you. Is there anything about your experiences with
&PACIFICORP you'd like to mention that we did not talk about today?
1. [RECORD RESPONSE]
88. DON'T KNOWAJOT SURE
99. REFUSED
[THANK RESPONDENT AND TERMINATE SURVEY]
Confidenlra anrl Proo,:eisq,
!iai:c FinAnsyrer fxni*ss fvaiuation Re-rort
Apren.Jir C - Process lvalualion Suruey lnstlunients
Rocky Mountain Power
Exhibit No. 5 Page 1179 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage C-33
*.
h$ $v $t.,8 ]s T
C.4 Trade Ally Intentiew Instrument
Note: Potmtial respondents for the purposes of this interoiew are contractors in the kMP and Pacifc Power
Energy Efficiency Alliance who haae completed at least one FinAnswer Express project betutem 2009 and 20L1..
Participant sun)ey responses, tracking data, and suggestions from program staffwillbe consideredbefore selecting
allies to interuiao.
Objectioes
These interviews are designed to meet the following list of objectives.
o How are trade allies becoming aware of the program?
o How well does the trade ally pariicipation agreement meet their needs?
o How are program operations communicated to trade allies? How is training provided? Is
this communication and training effective (do they understand the program)?
o How satisfied are trade allies with their role in the program? What would they do to
improve it?
o Do trade allies who participate see value to their business? Can they describe the effect on
their operations?
o What kind of energy efficient sales are they seeing outside of the program? (Spillover)
Variables
Confidentiai anrj irotiief0,1,'
i$ah+ FinAnsul*i f xpr'*ss Evaiuatinn R*i:cri
Apnendir C - Frocess Evaluation Sutrei- ln;iiurnents
Rocky Mountain Power
Exhibit No. 5 Page 1 180 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Variable Description TyP"
$-CONTACT Name of contact Text
$-FIRM Name of vendor company Text
$-PACIFICORP Pacific Power /Rocky Mountain Power Text
$_PROIECTS Completed projects 2009 -2011 Number
$_TYPE Based on "UtilityMeasureType" and "UtilityMeasureSubtype."
Includes:
o Lighting equipmentr HVAC equipment (non VFD)o VFD
Text
$_ENROLL_DATE When they are listed as EEA Date
$-STATE State(s) where active Text
Fage 0-3,1
Roclq Mountain Power
Exhibit No. 5 Page 1181 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymasru &V$ TANT
lntentiew Guide
Hello, this is <INTERVIEWER NAME>, from Energy Market Innovations. We are conducting an
independent evaluation of $_PACIFICORP's energy efficienry programs. This is not a sales call. May I
please speak with $_CONTACT.
I understand that $_FIRM is part of $_PACIFICORP's Energy Efficiency Alliance. Your feedback can be
used to improve Alliance support and the FinAnswer Express program.
A1. Are you the person that works most closely with the Energy Efficienry Alliance at your company?
a. Yes
b. No ) [ask to speak to person most familiar with the program]
I would like to discuss your experiences and perspectives regarding the Energy Efficiency Alliance. This
interview will take 30-45 minutes, and as a thank you for taking time to chat with me, I would like to
offer you a $50 gas card.
Is this a good time to talk or would you prefer to schedule a more convenient time?
[If no, scheduled callback time:]
With your permissiory I'd like to record this interview to ensure that I don't miss any important
information and for quality assurance. Your responses will be kept confidential.
A2. In one or two sentences/ can you please tell me what $_FIRM does?
A3. What is your title/role at $_FIRM?
A3a. How long have you been in this position at your company?
Section L: Participation
1. Our records show that your firm joined the Energy Efficiency Alliance for $_TYPE in
$_ENROLL_DATE? Is this your understanding as well?
2. How did you first hear about the program? (DO NOT READ, MARK ALL)
Advertising
PacifiCorp Representative
Other Contractor/Vendor
d. Customer
e. Other (SPECIFY
3. lvVhat motivated you to participate?
Confldenfiai anci Prnprlnfa4i
i$ai:a FinAnswei Expiuss Ivaiuation R*puti
Apcendir C - Prccess Evaluation Surue'y' lnstriiineiits
a.
b.
c.
F',Aile L-Ji)
t'* &\d $t e $d r
4. Our records show that your firm facilitated $*PROIECTS $_TYPE projects from 2009 to 2011 in
$-STATE as part of $_PACIFICORP's Energy Efficienry Alliance. (Repeat for each state firm is
active in.)
a. How were you involved? (E.g. Did they influence the project or just take orders?)
Section 2: Training Roles, and Communication
5. What kind of training or information about the program were you provided when you first
became involved? [MAY HAVE HAD INTERNAL TRAINING.]
a) Have you had any follow up or continuing training?
b) Have you, or someone from $_FIRM attended an alliance workshop?
Did you feel like the program was clearly explained? What about your role in the program?
How would you describe your communication with the program representatives?
a. Is there one key contact you communicate with about the program? Who?
b. \Mhat might initiate contact?
i. Is there a set frequency of contact or an action that would trigger contact?
ii. Does he/she contact you or do you contact him/her?
c. How often is the contact?
i. Does this meet your needs?
d. How would you rate your satisfaction with your contact, on a scale of 1 to 5 with 1 being
very dissatisfied and 5 being very satisfied?
e. Is he/she able to answer your questions or get you to someone who can?
How do you prefer to get information about the program? (DO NOT READ, MARK ALL THAT
ARE STATED)
6.
7.
Rocky Mountain Power
Exhibit No. 5 Page 1 182 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
8.
a) Online, check site often
b) Email
c) Mail Newsletter
d) Phone Call
9. [IF $_TYPE = Lighting only] Do you use the program's lighting software tool?
a. If so, how does the lighting tool help you?
i. [FOLLOW UP] Does the tool output summary help you sell projects?
b. If you could change one thing about the lighting tool, what would it be?
Section 3: Marketing
10. Do you use the program as part of your marketing to potential customers?
a) [IF YES] how?
b) [2"d FOLLOW UP]Has it had any effect on your sales?
Conirdenirai anrj $.oilrr$i$t,
i$ahc FinAnsu;ei Expi*ss Evaiuation Repor
Apcendir C - Process Evaluation Surve.,r instiurnenis
Fagt: C-3{.t
t
i\{ d\$ $t & Ni T
11. Did the program provide your firm with any marketing materials, such as brochures, flyers, or
forms to help promote and explain the program offerings?
a) Brochures
b) Forms
12. Are there changes you would like to see in the marketing materials?
a) If yes, what?
Section 4: Customer lnvolvement
13. Is your interaction with customers that are participating in the program different than those that
are not part of the program? How?
14. Are you able to help customers fill out applications for incentives for equipment purchased
through the program?
a) Any difficulties?
b) Do customers need assistance with the application? How much?
15. What questions do customers typically have when you talk to them about the programs? Any
concerns?
16. What challenges do you face in addressing customer questions or concerns towards the
programs?
17. How do customers typically find out about the program? [INTERESTED IF CUSTOMERS
KNOW ABOUT THE PROGRAM AND BRING IDEA TO THE ALLY OR IF THE ALLY E
ACTIVELY SELLING/ADVERTISINGTHE PROGRAM; PROBE TO DETERMINE ONE OR THE
oTHER.l
a) For the projects you completed between 2009 and 2011, what percent were initiated
by you contacting the customer to propose the project as compared to the customer
contacting you with a project in mind?
b) When customers come to you with a project in mind, how often are you able to
suggest changes to increase the energy efficiency of what they initially envisioned?
18. How many projects do you know of that were started but were not completed (i.e. not installed
by anyone to the best of your knowledge)?
a) How does that compare, portion wise, to the completed projects?
b) What do you see as the primary reasons these projects were not completed? (TIE
ANSWERS TO BARRIERS LIST USED IN PARTICIPANT SURVEY: HIGH
UPFRONT COSTS, LACK OF ACCESS TO CAPITAL, LONG PAYBACK PERIOD;
SLOW RATE OF REruRN, LOW PRIORITY/LACK OF INTEREST OF SENIOR
MANAGEMENT IN ENERGY EFFICIENCY, LACK OF INFORMATION ABOUT
SAVINGS AND PERFORMANCE, LACK OF RESPONSIBLE/ACCOUNTABLE
ENERGY STAFF)?
Confi deniiai anu iT oi:reiory,'
idahn FinA.nswei' f xpr*ss Evaiuation .Repari
AscentJir C - Process Evaiiration Suive'/ hsturnents
Rocky Mountain Power
Exhibit No. 5 Page 1 1 83 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
l,aqe O-lii
ruAv$teldT
Section 5: Effects of the Program
For the next few questions, please consider just 2011, if you can.
19. [IF LIGHTING OR HVAC OR MOTORS] Approximately what percent of @I $_TYPE
sales in $-STATE last year was from program-eligible equipment, (IF NEEDED: that is
[DESCRIPTION OF ELIGIBILITY REQUIREMENTS, WILL VARY BY TYPE]X
[If $_TYPE=VFD], Approximately what percent of drives sold in $_STATE were variable
frequency?l
a. [PROBE FOR MORE THAN ONE TYPE IF APPROPRIATE. WE ARE TRYING TO
UNDERSTAND PORTION OF SALES THATARE OF EFFICIENT-ENOUGH
EQUIPMENT TO QUALIFY FOR THE PROGRAM.]
b. To the best of your knowledge, did you complete any $_TYPE projects in 2011 [IF
LIGHTING OR HVAC: that would have been eligible for the program andl that did not
receive program incentives?
i. [IF YES - FOLLOW UP] Thinking of just 2011, about how many projects do you
think would oualifv that did not receive Drosram incentives? [OR. could vou
relate the volume of eligible equipment with the volume that you do with the
program?l
ii. [SECOND FOLLOW UP]Why did those customers not participate in the
program?
20. [IF LIGHTING OR HVAC] Did you sell more program-eligible $_TYPE last year, than in
previous years?
[IF VFD] Did you sell more VFD's last year than in previous years?
[PROBE TO FOCUS ON THE SALES- SHARE OF ENERGY STAR OR OTHER HIGHLY
EFFICIENT EQUIPMENT]
a. Have you noticed any other trends over time, related to the efficiency of purchases?
21. Do the $_PACIFICORP program incentives influence your selling of program-eligible
equipment for $_TYPE? [THIS QUESTION APPLIES TO SERVICES AS WELL AS WIDGETS; IT
IS A YES/NO, BUT INTERVIEWER SHOULD PROBE TO FIND OUT WHAT THAT MEANS TO
THEM.I
a. [IF YES] Please rate the influence on a scale of one to five, where one is no influence at
all and five is a driving force in your sales.
22. (IF APPLICABLE) Do the $_PACIFICORP program incentives influence your stocking of
program-eligible equipment for $_TYPE? [THIS QUESTION APPLIES TO WIDGETS; IT IS A
YES/NO, BUT INTERVIEWER SHOULD PROBE TO FIND OUT WHAT THAT MEANS TO
THEM.I
a. [IF YES] Please rate the influence on a scale of one to five, where one is no influence at
all and five is a driving force in your stocking practices.
23. Does the $_PACIFICORP program information influence your selling of program-eligible
equipment for $_TYPE? UNTERVIEWER MAY NEED TO CLARIFY THAT WE ARE
DISCUSSING IUST THE INFORMATION PROVIDED TO THEM; PERHAPS AT
WORKSHOPS/WEBSITE/ETC.]
a. [IF YES] Please rate the influence on a scale of one to five, where one is no influence at
all and five is a driving force in your sales.
24. If the FinAnswer Express program did not exist, can you estimate how your sales of this efficient
$_TYPE equipment would be different? (PROBE FOR PERCENTAGE CHANGE)
Confrdgnilai sn$ Propr.r'eii?O,'
i$ah* FinA.nswer Er.pi'*ss Evaiiration Repc$
Aprentjir C -. Pi'ccess Evaluation Suivey hsllui'*eirts
Roclry Mountain Power
Exhibit No. 5 Page 'l 1 84 of 1 365
Case No. PAC-E-I4-07
Wtness: Kathryn C. Hymas
Fage O-li$
:t
h$ $v $t.q N T
Section 6: Business Impact
25. Are there any other ways that participation in this program impacted your business, if at all? [IF
RESPONDENT ALREADY ANSWERED THIS IN SECTION 5, DON,T ASK AGAIN. LoOKiNg
for qualitative here - already asked ratel
26. How does the FinAnswer Express program differ from other similar programs that you may be
involved with at other utilities? (BE SURE TO FOCUS PROBES ON: Is the amount of effort
required on your part different? What about the amount of paperwork? The program offer to
participants?)
Section 7: Satisfaction with Program(s)
[NOW, I HAVE IUST A FEW MORE QUESTIONS.]
27. On the whole, are you satisfied with your experience in the Energy Efficiency Alliance, on a
scale of 1 to 5 with 1 being very dissatisfied and 5 being very satisfied?
28. Do you use the $-PACIFICORP vendor website?
a. IIF YES, follow up] How often do you visit the website?
[2.d follow up] What kind of information do you look for on the website?
[IF NO] Did you know that upcoming events as well as archives of alliance newsletters
are available on the website?
i. How do you find out about events and newsletters?
29. \Alhen you joined the Energy Efficiency Alliance, you signed a trade ally participation
agreement. Do you remember this agreement?
a. [IF RECALLS AGREEMENT] Is there anything you would have liked to change about
this agreement?
30. Is there anything else you'd like to tell us about your experience?
Section 8: Gas Card Offer/Closing
As a thank you for your participation in this interview, we'd like to offer you a $50 gas gift card. Would
you like to accept this offer?
(If yes) Which type of gas station would be most convenient for you?
[NOTE: The following do not offer gift cards we can order: Loaf N'Jug, Kum & Go
The following companies DO offer gas cards: Exxon-Mobil, Sinclair, Conoco, Pilot-Flying J,
Shell, Valero (Diamond Shamrock), Phillips 55, Chevron-Texaco, Maverik]
To what address should we mail the gift card?
Thank you!
Confl o'enLaj eii$ Piopreiory
i$ahc FinAnsy,rer Exnrsss Evaiilatinn *.epuii
Apuenifu C * Prucsss fi,al*etion Suii'ey instturtients
Rocky Mountain Power
Exhibit No. 5 Page 1 185 of 1 365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
b.
C.
Fagtr O-lJli
rs v*ff*NT
List of Traile Allies Intentiewed for EinAnswer Express Eoaluation
All-Seasons
Carrier
Commercial tighting Supply
Cralux Lighting
D & S Electrical
ESCO
Gunthers
H & N Electric
Orange Dairy
Whipple Electric
Confidentiai and Propietary
ldaho FinAnswer Express Evaluation Report
Appendix C - Process Evaluation Suruey lnstruments
Rocky Mountain Pover
Exhibit No. 5 Page 1 1 86 of 1 365
Case No. PAC-E-14-07
Wh€3s: l(afiryn C. Hyrnas
Page C40
,NN',s\vsileldT
Rocky Mountain Power
Exhibit No. 5 Page 1 187 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
D.1 Participant Results
Retail
.lffi ffi iruiiiiiiiiiiiillil 1l.i*:.11l
Educational Services
Dairy/Agricultural
::::::::.1::::::::::::::::::::i:. 1i::::::::::: jl ::::::::::::::::::::::::::::::: .:' : j:'t!::i:,! t ,i!,:::i::
:.i:.. '.'i'.ii;,i.,' ::.::. . .: :::: :.:., i:
Ia
ii,iiii.li,ii,,i,i,iii,,,,,iiiiiiiii$,,liiiiiiiii:iiiliiiiiilii:l:iii:liiiiiiiiiffiil:ii:liiiiii*:.{i.lrfiiii:i:i:i:i:ix{i :llt*
o
77
ii!:!:!{}..,.!.!:!'!i!.!irl.!i
iii;ii:riiilrirliiji
6
Table 4. Primar-1, Industry of FinAnswer Express Survey Respondents
Total 52
Table 5. Or.erall T'artici t Satisfartion with the -Fin.Answer
{loniideniiai snC i:,roprioisn
i$gi-.n FinAnsv,r*i [xprsss Ivaiuation Repr:ti
Apiendir D - Ficrsss [valiratiol Deiaiitc Fiittlittgs
Fa,:s $- i
{
fN,-&\d $ il,q r\l T
Rocky Mountain Power
Exhibit No. 5 Page 'l 188 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Table 6. Hnw Partici nts Became Aware of the Fin"Answer
Trade Ally, Vendor, or Contractor
Don't Know/Not Sure/No Response
:::.::.:.:::.:.:,:t:1lN:::,:,:,:i,:-:-i:::-ii:::it*+::::::1:::::::::::::::::::::::::::::i:::::::::fr:::::j:::::::::::::::::::i::::r6G:::::::r:i
Rocky Mountain Power Representative
Total 52 '100"/"
Tatrle 7" Motir,'ation to Particioate in FinAnswer
Other
,,,tffi,rgplace,.,bi ..:eqeip.merl+,,
To protect the environment
4L5 8"/"
!:!:!:!:!:!:!:!:!:!:!:ijir;!|!:!:!:!:!:!:!:!:!:!:iiir:iiiti !,:::,Ii::,:::4:rc::,::,::,,:1,,,,,,r,:
i:::::::::::::::::::::::::::::::::::1:::i::i:::::::j:I:::+i:i:::::::ao/L/O
To improve operations, production, or
::::::::i::i::::::::::::i::i::::i:::i:1]1]]:1]1::1,::
.:.:::::,:,---,,|,:,,,,,,,,,,,,,,,:,:,:,:,:,:,:,:,:,:,:,:g:,*w]]::i.:'j:r: ::::::::::::j.::.:::::::::::::::::::::::::::::::::::::::::::::::i:l:1::::::::::i::;i:::::::::::::::
a 10/Z J/O
quality
To save energy 2 I 1,3%
Total
48"/"
25 27 60 1,0070
Confl d*nfnl anr Piupriein4,
iriuhc FinAnsl'*'e:' Exnress Ivaluatian Rsi:cri
Apcen.Jir: D - Frocess Evaluation Detailec Fiiitiirigs
Flaue rl-l
N: $\j ${-l A N T"
Rocky Mountain Power
Exhibit No. 5 Page 1 189 of '1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ress Trade AIlvTable 8. Partici nt Satisfaction nith FinAnsrver
Very satisfied
.. urhatiidissdtis-f,i i..i..,. .,,,..,,rt
Very dissatisfied
25
ii:i..+rs.....,i
J
fjiiii.i.iii.iiiiiliii..'iii
0
, ,,,.,,.,'1.'.,
2
i,.t,::t:,
l-Ii...
::::::::=i::
48%
t
it;:::*
ffi
:::i::::::::;t:
iixiii'
t:::tt::::t:r;atl,
jYo
,,!rdl.:,.::. .:.;1.:::: .1::: :.i
::i::|ir;:::::::i;11:-::ii.li::lir:1:i,r.:.:=iii;iti:
4o/"
Total 40 1,00%
Table 9. Farticipant Satisfactisn with their lnstalled Measures
Very satisfied
,riffiffs tiiiffiiibtfiffiiXii..li.i.i.i.'iiii.liiii;iii1i,i,.,,,,,,iiiiiiiiiiiii.ii,.., .::::::::::.:::::::':::::::::::::::::::::::::::: ...j1..i::i:i:i:::::':.. ': .::::::::i:i:i:i:i:i
Neither satisfied nor dissatisfied
Total
41.
*{,;$,l
0
79%
Ii9Y#
0%
.iS$6ii.i
0%
i:rihr :. i::L:t!tb..l
s.::li:i:ii:iiiiiiiiiiiiilii:iil:iiiiiillii:::iiiiix
0
52 1,007"
Tahle 1t]. StatuLs of Pr*ject Equiprnent lnstallations
Existing Equipment Failed
Existing Equipment Working, No Problems
Wiffiiiifrffi$te
':,::t'tmeW"'tnstallffti'orli.ii:iiiiiiiiiiiiiiiiiiiiii.'li:,,,,,,,,,,,,,,,,,,,,,,,,,,.,',,,,,,,,,,,,
Don't Know/Not Sure/Refu sed
34
I i I i::tltltli: li::;:il:i::::::ii:::::;::::t:t;t:;::;: I lti::ti:;:il::::::i:i:::::::::i:ii::
t:ilil:ljtl:ultai::t:iii:::i:i:::::::il::i;il:;;iti:r:ii:i::::i:ili::i::iiilt:]l::;
1
.:::l::.:.i:.::...::::::i:i:i:i:i:::i:: ; ,.i,::ii:::i:::i:,:i:i:i'i:r,:,.1.. i
lI
Better lighting quality
I-i$hts,turn on.r.nbre,,.,quicXty........,..,,''
:, ,,i'i:,,:i:,:,,i, ::i . . :::.:'i:: :.:.::i:::i:: :'r:':::::::::::::::::::::::::.::,.,., :. ..::::.::.
Less frequent replacement
#+i*[,.*une$...u **## adbb,,,,.,,,,..,,............,,,:,,
Decreased heat output
74%
I ttttttttt I I cot . : :,::' 'l ti. . : i
ir#i1::i1t:rti,:fi i:ilaiiaj:i'Ii:..i::,j:.:.i'.i::i:i:i:;ii:1iiri:i:i:i:ilit
ao/L/O
28
::::ti:',t::
6
,:.,} i
1
Total
Table 11. Non-F.nerp.' $enefits of lrinAnsvr,er Fixpress Proiects
il,n lid*nliiii 6[ ij,':']'0irr'$i$,],'
i$iiim $inAnslvei' Ixpi'*ss Il'aiiiation Rcpari
Apnenilrr; D -' Piu,;ess [valuaticn Deiaiied Firii:ttgs
t-\^.-- i\':
ru s\xr $ il,e r-j T
Rocky Mountain Power
Exhibit No. 5 Page 1 190 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ii1:::::::::::::::::a::aajl
it:i1i::i:i:ii::ti:::i:::::i::i:!:ti:
a
8
iiffi*
17
:::::::::::::!::::::::i::::i:::a::::::::*
li;,liii::i:i:i:iiiiiiiii:iiii;l
34
10
4
!ii:!:!:!:!i::!l!:!:t::l!:tltllliii:ti::i:t:l;i::ii:::::::1,:r,,:]r,]:,,] ]64 ]:l: j:,:,:,-,,.,,,:,,:,:r, ]] &v ::,:,,,:,tffii'.'ffiiiiiii
27
1 12
Tahle 12. Factors lnfluenci Proiect Decisions
Full Free Riders 6
::' r .+:::::::::::::::::::::::i:1:':::::::::::': ::b. : :::..-:':i':::1-
.::' .ri :irijiiii::iii:::::::::::::::::::::::,::.,. . . ,: ,. . ,:, ,,.., :,:::,:,:i:,:,:::,,:::i j.l
Non-Free Riders 37
::r:trtrirtr:;t:::rt::::::::::::::::::::::::iii:::::j:::i:i:1i!:::!i;iti:::i::::i:iti;tl::::iiit::
i:P, al.iFi#,ffir.q
Table 14. Potential Further Efficienc5, Ildeasures
l;'+niiderira j en ij,5]"!.rr oi$t
iiiili Fli]A.nsvisi Exprvts IvaiiLatinn Rtnuii
Api*rujir D - Process Ei,aliratiort Deiaileu Finil:ngs
Flagc l)-{
N
N &V $L].q N'}-
D,2 N on -P articip ant Re sult s
Rocl(y Mountain Power
Exhibit No. 5 Page 1 1 91 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
43"/"
ffrffi.i.l.i.X'fXffi
10
Sii
Table 15" Size of lrion-Pa ant Firms, by Number of
Table 16. Prim Activity for Non-Farti cipating Respondents,
i:i i iiii:ii:i:i::
14
ffifl,ffi
9
Total
Aware 31 43% 1,4 28%
;isii!!R{\E!s$+!i!!!!!i:$!!Sii+:+i*i!..+:[::i{i:i+:+:i:ia:!!!i:i:ii:i::-r:-- !Sii!iri+si{+.i:S!lriii!i!]i-!ii..:..:.i.i.i:.:
Total 73 100"/" 50 7007"
ijonfldeliial,rnil S,roSri$iTD,'
!Cahir Iin;r.nsv-'er Ixni'ess Evaiuatitn Repu$
Apcendir D - Frocess Eval';ation Deiaii*d Fittcittgs
Flage i)-ii
ru$v${:,qNT
Table 18. Rockv Nfountain Fower
Not Sure/Don't Know
Irrigation Load Control
Not Sure/Don't Know
::::::::::.::::::::::.:::::.:t.: - :::: :::::::::::.::::::::: ::.::. :.:. :. _::--:::::::t:,:,:..:ij .::::::
:::::::::::::::::::::::::::::::j..j.-1.::::::i::::::::::::::::::::::::::::::::::1:i'I:ii:::::::::::::::ilrr:i::i::::::10
::::'::::::l:::j::.:.::..i:r ;.1:::::::::::.:.:.:.:::.:j:1:::':::':..1:-jj: :.jj::::::j::::l:j.fr:::iil::l:::::::::::::::::
:':,... , :.:.::jj:iit::::.:1,. ..-:r:::. ii t:10
: ::: . .r . : :l ::::::::::::::::::::: :.:::::.: :.: :.'1 : l- : - :j: ::::i :::::i::::::::::'l:'i::::::::::::::::::::::::10
+.i'.. d:..:..::..::..:::.
.::':i. .. ':r:::::::::::::: : .:::.::':::::::::::::-::':::::::::::::::::::::::::01
Roclry Mountain Power
Exhibit No. 5 Page 1 1 92 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Custorner Classand Services ldentified,
20
tlorlf,tr{}l
:iiiil{o€ftI{Iiiili.{tlrlne$i:itr:tr.ellnsXetterriiiiiiiiii:,iii:,,ii::,i:i:,! ',,::!'!
,l
Accompanying billing
i}",'::!i:lttt:tiittirtl:,
2
:::i:I1:::::ii::i{i; ji+il
i::aiiii:::::::i:*:tii:t::::
0
rlPi,iHtrihdv,erti$ine,,,,, ::::i:::::j:::i::::::i::::::i:::r::ii::i:::ii:iii
Public official
Trade ally, vendor, or contractor
Table 19" Non-participant Aw'areness uf Pr.rgrarns and Sen ices, ()r,erall
lrrigation Load Control
TV advertising
fjonildeniLai enr Pro.ririeiiiry'
i$aht FinAnswcr Exnrciss Ivali:ation ,tepi:ri
Apcentiir D - Ficc*ss fvaluetlon Deiail*c FinCings
PaUs i-)-S
Iq .s\\i $ il,q $i \-
Rocky Mountain Power
Exhibit No. 5 Page 1193 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
....:::::::::::::::::::... -"...' .: ::::::::::::::::::::::::::::::::::l':. ' ' :: : ::::::::::::::j::::
75
i..........iXlXi......lll.''.il!1,..,,,,..,..,w'i..'ri...ii..i.+..'....riiii...i....:ifI,0.i..iiiiiiiiiiii..iiii.iiii:i20
, .......,..:.i:.,.,i:::iririririririririi,, ..,f.::,. ,,:,: . ::..::i:i:i:i::::::- : ,::::::::::::
10
'tr'abte 21. Ilreferrecl Method to Learn about I'rograms ancl Opportunities. Overall
Total 5073
Table 22. Freferred and Actual .h,tethods of nt Aw-areines$
Email
:,,#*lii.::.
Phone
0%
::::iiiiiiffiii:iiiiii
0%
l,:.::::,::5,i;o/O'::::::
C10
iiitl;;t:::;::::::::::::::;::i;ii lti
xx.ii..iits%rX
3%
l:ll+::ro ::::l
15%
ir:::::::::::::::i:i:l
27o/"
,i,ii iiiiiii ii i i,;*'*; ::i t::H
1,1,o/"
. !!: ::::::::::: ::ll {a :::: ::,:|::::: : ::::::::::::::!:::
,i,l,l,:::::l:::!::t:t:tl::::il:i::ili:tiiitiiliiii:li;:::::::::i:::::::::iit;r:lt:::::j:::l:l:l
3%
ll::ltlttr,i:i,sm::l+:,::llllllll'i:.=.:....=.
1."/"
, !iri89fl . :
:ltttL)1):::,iii,:i:
no/
]iiit::r::::::::::::::::i::::::Dllolr ltlt:tlt:t:tlt;:l:::;tit::ltiili
Table ?,3. Non-Farticipant Hi ment Pu,rchases in Existing Facilitiuts
Yes, without assistance from Rocky Mountain
Power
Y"i,,#iffi assi*iinp *ffi.,..n".ky uo.u"-"il::ii.iiiiiiiiiiiiiiiiiiiiiii...i.i
No
6ffinfiuil$#ffi6#:.:i#Ai#
707"
:::.;:: .l : ,{tJ. */o
ii::lliii::i,ii"'ffiii
82%
::: : :l :!l :,1!:,:r!{i,t:!:!l!:!:!:!:!:!:
':.::::::!:!:!:!:::.ri!/r0:!:::!:!'i::
$oriijde n rin j iln i.i Pro$ri$iitr.v-
r*ri$ ti.,rAnsr*'ei f xnivss [iaiu*tion Rti:uti
;\psen.jrr $ - Prcress [",aiuetioti $eiaiiti iilttiittgs
Fa,:s l)-li
N $\r $ ill -\ i-{* T
0%
iii-.iiiii:i[$'
88%
Table 25. N rticipant Systematir Hvaluations of [xisti facilities
Yes, without assistance from Rocky Mountain
Power
No 92% 90V"
Tahle 26. Why Didn't lrtron-Farticipants A for Assistance frorn ltocky lvtountain Porver
Rocky Mountain Power
Exhibit No. 5 Page 1 I 94 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 24" Non-participant Load Control Str ies in Existing Facilities
47"
AO/lo/"
Wasn't aware
,:, Nbt S U,,,fesp$$e i,,,: .,:,.
Would not qualify
ss%
i:ri;iiass;
nol
54%
i.itii.firr,iifig
i:i:ijiriii*:i:i:i::::r::t:i:i:i:i:i:i:i:i:i:i
17%
460/"
!:!:!:!,,'A!,tEii.:., . r,. ri-.-:-!!:L',r-:-:ta. .
i:i:i:ir::::::iiiiiii::::ii::ii:iiiiltiiiiliii
9o/"
Confi#+nini anlJ Pio$,"rsi$.l
!$eiiil FinAnsv,,ei fxnrsss Ivaiuatirn Firpuri
Apnendir $ .. Pio*ss li,aluutiurrr '\eiail*d Finriinils
f'agc I-8
Table 27" Non'Parti nt l\ltotivation for Pursui
i
N: $\j ${:l A i\'i T
To save money on electric bills
To save energy
::::::::::::::,:::lj::]::r,,,::,:j ,,. ,,::,:,.:::,:::::::::,,,:r, :::::::::::::i , :::i:::,:.: :: : ::
troii*beuire. ffie,latest tedifidl oBY
::!.::!:!:!:!:!:!:!:!::.::!i.!:!:!:!i!:!:!:!:!:!:,:::!:i!:!:!:!:!:!:!:!:!:!:!: ::.' .'::::::::::r
To protect the environment
did it
Teiii.iffi pfbv:e.sec-urlty,,.,
To obtain an incentive
Efr:I
'I"able 28. Nun-.[]articipant Ine{ication of Further Ene Effici encv $pptrrtunities
Yes, could make future improvements
ffif,,1ffi,*$+iiffiiai
Not sure or Refused
iiiiiiiiiiiiiiiiiiiiiiiiiiiiir-iiiiiiiii*,i,..liliiiiiiffi-i-iiiiiiiiiiiiitffi.i1i.g.,.'|rtllr1ffil*jllliii36% 8% 1.8%
:n!:::::::::::iili:iij::i::::i:::::::Eril:',, ,':'.i;.:l .-.J.rt. ', :: .,' t:;:
//o
::::::::::::::::;:|:::::::::::::::|:::..:|.1:..::*,,t,iD):: .t: a:'':t 7.s.,, .. ::
iiiiiiii:iiiiiiiiiiiii:iii::i::i:ffi
4%
.iii..#%...i...i..r=:aa
1%
Rocky Mountain Power
Exhibit No. 5 Page 1 1 95 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
43% 1,6%32%30%
*4996
74%
*,,.w":#
10%
,...i,,.iiii,...,.
,,,,.,.,..,,......,..i ,,,.i ,
t,',.',lii.ii..iiii.i.ii.,.i
0o/"
,,,,, ] i- .,,,:,:,:,,,:,
,:,i.',:,:,:,:,:,:,:,:,:,:,:,i,,:,:,:,:,:,,,,,,,,..,':'.,,,:,.:' iii::liiii
,, : .:iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii ,. .. . .. ::. : .i::,,,i : '::
67%
227o
i#urn
:il :tl:l:l::::iii:ii:i;i:ii
34o/"
Tatrie 29. trnetication of Flans to Impiernent Electric Efficiency []rojects for Non-Farticipants w'ho
21%
br"lieve their Firrn has Further Efficiency Opportunities
Yes, plans in place to implement projects - with Rocky
Mountain Power assistance
Y+$;,.;.pla ;lnplace.;.to,ryemt*t;.pgfri9ffi$ttiii:. n tiiiiiiii.i.ill
ffiE*+M;u*iii*iifA*ei.,,nsslsHnte ,'''.,i.,iii.i.i.i.i.i.i.':.,..'.'
No, plans not in place
Total
.,L
'
.li.....ll'.illl'.
*,l,,ll-i..li...iii..i.
22
5%
-i-.ii:::::iiiii
660/o
JJ 100'/o
C+liic*riiai sri ii ii o$seiir:r,'
iriri* FiilA.ns'r,r*i Exniess ltiaiiiation R.ei:**ti
Apnen,jir D - iri'oiess li,aii^iatior Dei*iled Finriings
!'agc Li-$
N$V$ilA}{. T
Rocky Mountain Power
Exhibit No. 5 Page 1 1 96 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
637"
. t :t:,:,t:::t:t:t:t:t:t:t:t:t:t:t:t:tH. 4:ti+:t:t:t:t:t:t:t:t:t:t:it
ait:iiijii:::i;::::::::::::::::::j::::::::::il:iiiiti::::j:1::::::::::::i:::::
co/J/O
:Ii!itiiii:i:!:!:!:!:!:!:!:!:!:!:!:!:!:::!:itl::t:!i::li::alit:!i::t::i::t:!:!:
:::'iir:i-.,!.::!:!:!:!:!'!:!i:::!:El}y'r!,. :i,.,,,::,:,1 j:,,,,r,,,,,:r:,:,:,::,s,rc , . : ,,,,
ffi,xiiii'iii.i.i.i.i..ii'i.i1
5%
:iffi li::::ii:$ediiiiiiiiiiillXiii+
1.0%
:i:::i::ir;irt:
j,l::::::::i::ii:i:
Table 3$. Barrieirs to l.mplementing flectric Efficienqv lm
Total 1007o
D,3 Project-LeoelNet-to-Gross Results
Table 31. Idaho FinAnswer Express Project-Level Net-to-Gross Idatios
IDL00101
:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::i.::i::::::::::::::::::::::::::::::::::::::::::::::ja:l:
:iilEf+$flilit#x,r.:.:i.:.i:iii.:,:.i;iiiiiiiiiiiiiiiiii:iiiii;:,.i:;,,
IDLO0153
IDf{OoSo,] ' ,,,,,,,
IDL00087
'':::::':''::':':':''':'''::;"^';;l
.,.,.... :.,,;iIir;ltl.,l
:t::tllt:t!:i::tr:r:::t:tt:t::i:i:::ri:::i::::i::iii::iiii::iiiiii;::;
139,035
' :.:: , 4itl..,-?fl. :
?q 10,
ffi ffi .fr, ift ,Hil.ll.............'i....'.....1.......iiliiil,.i ll
2,347 1
:iii:iiiiii:iiiiii:iriii..:t:tr::t:;::::::::::::::
:::l::::i:::i:::::::l#4*0
6,748
IDL00027
t.'.lHEffi ffiuXt,r'....i....i...+li
IDL00138
iiffi.itffi .xj$6ffi i':i.,.,.,.,.,.,.,.,.,.,.
rDL00077
rrrIDf fl $lfirsj:*i ii:::::::
IDN00145
'i,i..nHHEgg*r;jiii
i::
rDL00229
,i.i.llllffis.
IDL00056
trx'
9,334
4'Affii
L4,9L3
.Ii8ffi.
1,2,61.3
17,81.5
:::::.i: ::i::i}jh7:I::: . :i:::::.: .:
:i:ti;:1.iii;ti;iititltiuii:lriii:iririii::r!!l::!;:::ii:irlr:!::::!ji::::i::itiii:::ii::l:i
4,795
0.75
liri:iririririririririrlrririririri!:!::':i:.!:,i:!:!',::l
li!i!i!i!i!i!i:i!i!i:i!i!i!:li!i!i:i:l:i:::1]:::::::i:::::i:j:
0.5
,,::i:,:,:,i:r:iii0ffi :i:iii:iriii::i:i:iiii
1.
llliillllls.:lllffi
0
::iiiii;i:i;::iii:iiiii:iiiii:iliiiii!::li:i:t;:l::::::::::
:iirii::iti:ii::t:::::::i:i:i:i:i:::r:ri::::i::::i:i:i:i:i:
0
:::::::::::::::::I::::::::::::: : ::::: :
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii:,,.:rIil:li:
1
1
ii:irt::iii:ri:ii:i:i:ii:i:i:i:i:i:i:i:i:iii:i::
1
i0:5 ::.::::i
::::::::::::::::::::::::::::i:::i:::::,::::::::::
1
i..uis...iii'lffi
0
IDL00097
iiffi.,'ffi #.......,.............;.i,.
IDL00105
ii..iiiIEnsl00'192:
':ii.,....lrDL00225
r:,,,:,I8il0t}I50:,,::I:ii::::i:iiii::iliii.,....::]]]i:i::
::::::L::!j::i:::::!:i:::::i::::::::itiii:iiii:j:l;:::ri:;::l:::::::::::iifffi ii:i:ii:iiiiiiiiiiii:iiiiiiiEffi ii:iiiiii'
4,41,8
!iniii:iiiiiiiiiiiiiiiiiriii;iiii;iriii':
lonijd*niiai onij,crocriefs,T
iglhc Fin.a.nsir*ei lixnr*ss ili aiualirrn Seils$
ApmnCix D * Prccess Evaluation Deiaiisi Fiirrtirrils
Face D-iii
ruAv$il.e r'j T
i,rnNo0l3ilii,, ,,..,........,
rDL00278
u- i1....................,,,
...6,Suo....'i............itu ,,,,iiiiii......*.................i .,,,,,...5,953 1
Roclq Mountain Power
Exhibit No. 5 Page 1 1 97 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
IDL00130
IDL00059
1,39,980
3,912
1.
i::i: .1:;,:: iri!:iii''i
1IDL00146
. f,,pfg.n:t$*.ir' r ::,,,,i!,liririririririiiiiiiii;i,ii'
j'i'liiiiiiiiiiii
:', ,;,,, '',,, ,,,, ,,, ,,, ,:,::,:,:::::::::::::::::::::::::::: ::: : ::,:,! :,,::::::::::::::::i:::::.,:
rDL00120
.'..ffi fi ffi .*r*, i itiiiiiiiiiiiiiii..i.,,,,- .irttt',,,,,,.i
iffi.111.ritJ+,t+ffi
17,923
1,5,723
,,
t 1:::.,ii::i:i:::.""." ;"i.i.+j4.. r*a.....:.i
7,725
tuffi $E$u'''ili:.iIffi liii'
tr+1.i.'...''.un***:11',X-*.,i.,1,,''',',i.-#,-il.,...','''
,l'oniideni,'ar' e$$ pio.nrr sisrf
idallr F i nAnsi'.'+i Ixni*ss ['r.aiuaticn Renuri
Aprendir D - Piocss; [i,aiuation Deiaiie$ Firrtiings
12,414
Rocky Mountain Poiler
Exhibit No. 5 Page 1 1 98 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
YffiROCKYMOUNTAIN
rcFoWER\ AuvrgroiloFPA0rE0RP
Exhibit No. 5.13
Irrigation Energy Savers Evaluation 2009-201 1
Rocky Mountain Power
Exhibit No. 5 Page 1 1 99 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Final Evaluation Report for ldaho's Irrigation Energ),
Savers Program {PY 2009-2011)
Frepared for:
Rocky Mountain Fower
reffiR0cKYMOUNTATN*€POWER
x A, plvlsroN oF PAClFlcoBt!
Prepared h1':
M &V I t A N T hrp;rrincrshipi,r,ith €MN
Navigant (ionsulting, Inr:.
1375 Walnut Str:eet
Suite 200
Boulder, ClO 8030?
303.728.2s00
w ww'.naviqantc<lnsulting.com
lr{ay 10, ?013
Energy \4arket Lnnovations, lnc.
83 Colurnhia St
Suite 303
Seattle,l,YA 981i.]4
206-6?1..:1160
w wrt'.enriconsu I tins.com
rus\vrrANT
Impact Methodo1ogy................... .................. 16
3.1.1 project Fl" R;;;..:........:.::.:::....:..:............... .......................... 17
3.1,.2 Sampling Framework Development................... ..-.........-.-....17
3.1.3 Evaluation Approach .....................18
3.1,.4 Gross Energy Realization Rate Calculation. ..........................23
3.1.5 Net-to-Gross Estimates. ..................23
3.1,.6 Program Cost-Effectiveness......... .......................24
Notes on Validity and Reliability of Impact M&V Findings .............24
3.2.1, Reducing Uncertainty from Sample Selection Bias............. ......................25
3.2.2 Reducing Uncertainty of Physical Measurement Error...... ......................25
3.2.3 Reducing Uncertainty of Site Visit Analysis Error....... ........25
Process Methodo1ogy................... .................25
3.3.1 Overview of steps in the process eva1uation.................. .......26
3.3.2 Process Evaluation Research Questions... .........26
3.3.3 Program Documentation Review .............-........27
3.3.4 Logic Model Development............... ..................27
3.3.5 Process Data Collection Activities................. .-................-.....-27
3.3.6 Process Data Analysis and Synthesis ................29
Rocky Mountain Power
Exhibit No. 5 Page 1200 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
3.1
3.2
3.3
Nal,iLlant hrrpai:i &. Iln'icr,:ss livahrotii;n of
I{oi:k\, \4 o un ta i n i:\:r,v er's I rli gati t:n kirer:gv 5a r, ers Frogranl
4 Impact Findings
4.1, Analysis Gross kWh Savings....... ................ 30
4.1.1. Results from the Site Visit Analysis..... ..............30
4.1,.2 Results from the Billing Data Analysis ................ .................31
30
Pags: i
sr Av !rA NT
4.1,.3 Merger of Results from Two Analysis Methods into Final Evaluated Savings..........35
4.1,.4 Overview of Statistical Validity, Confidence and Precision .........................................35
4.1.5 Evaluated Results at the Measure Group Level .......... .........36
4.2 NetkWhSavings....... ...............37
4.3 Cost Effectiveness Calibration and Analysis ..................38
Process Findings. ...................49
Participant Findings..... ............49
5.1.1 Program Satisfaction. ......................51
5.1,.2 Program Awareness and Motivation............... ......................52
5.1.3 Program Process and Satisfaction.............. ........53
5.1,.4 Program Influence ..........-...............57
5.1.5 Further Energy Efficiency Opportunities and Barriers....... ......................61
Idaho Non-Participant Findings...... ............64
5.2.1, Awareness of Rocky Mountain Power Programs.... ............. 65
5.2.2 Non-Participant Energy Efficiency Improvements............... ....................67
5.2.3 Motivations for Pursuing Efficiency Improvements............... ..................69
5.2.4 Further Energy Efficiency Opportunities and Barriers....... ......................70
Trade Ally Findings................... ...................71.
5.3.1 Satisfaction. .................71.
5.3.2 Program Awareness and Motivation............... ......................7'1.
5.3.3 Training, Roles and Communication............. ........................72
5.3.4 Marketing.. ..................72
5.3.5 Customer Invo1vement................... ..................... zr
5.3.5 Effects of the Program............... ..........................74
Overall Process Findings..... .........................75
5.4.1 Process Research Findings ............75
Program Evaluation Recommendations ...............80
Rocky Mountain Power
Exhibit No. 5 Page 1201 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
5.1
5.2
5.3
5.4
.l,iovitlont inr}:ai':i & Ilroct:rss [],i aiuotiun of
l\or:k-v \,lountoin J:lor,rrer's .lrrigatit:rn li.nergv Sar,ers I'togt:ar:t l:'agtl ii
Rocky Mountain Power
Exhibit No. 5 Page 1202 of 1365
Case No, PAC-E-14-07
Witness: Kathryn C. Hymas.t*Nd\V${--&NT
This report describes the Impact and Process Evaluation of Rocky Mountain Power's Irrigation Energy
Savers program (IES) offered in Idaho for 2009 through 2011, and includes findings and
recommendations. These evaluation results provide feedback that can improve program delivery and
cost effectiveness in future program cycles.
1..1 Program Ooeraieat
The Irrigation Energy Savers program offers Idaho irrigation customers (rate Schedule 10) the
opportunity to increase the efficiency of their agricultural irrigation systems through implementation of
energy-efficiency measures and education. The measures and services incentivized through the Rocky
Mountain Power program are intended to improve irrigation system efficiency either through upgrades
to individual components (e.9. tuning center pivots by replacing nozzles to evenly distribute the water
being applied), through the addition of control devices such as Variable Frequency Drives (VFDs), or
through the reduction of total water pumped (e.g. replacing worn gaskets and drains to reduce leaks).
Specifically, the program offers the following incentives and services:
Pivot/Linear Upgrade Pressure Regulators Replace worn parts to reduce pressure at nozzle, to reduce
Equipment Exchange
a::::::.:.:.::!*:
i:i:i:i:iii:::::iiiii;
c xuv iii '.F.#*t*S"*v"il,,f,,Fi
.d;Iil fioni,ffiiffi#fri;##ffis,' ,use
l,'ii
:::::::::::iI::::::::;:::ij:::::::::i:::::::::::::::
Cl,1€r.8#iir-Ise
.: : ::::::::::: l:::i!:iii:iii:ii:::: : lll'::::::::i::::::j:':'iiij ::::::1:i li lii':':::
,,;;,,,,,:.:,:.. .,G#kets-,,.,,,
Drains Reduces pumping flow rate during same run time for
energy savings, additional savings if run time is reduced
...i.:.l ...,;,;.,,., . :.,'.,' .,.::. ,,', .. ',,',
:::i:i:i:i:ilil,ilf;f:[If,::. '',. i:,:':i::i:,i:i:i:,i,ii:,:i,,:i::i:i:ii,::i::::,:::'::.,: .ii:,:::,iii:iii:
Pump Upgrades
,,,,.,,,,,i,, G v,*r$Is{t,,ffi!i84f,$ty :,,!,,,
:!:!:!:!:!'!:!.irll:,:!:::::!:l:!:!:!:,:!:!:!:::,:i!.!:!:::!:!:::::!:!:,,!:!:!:!:!:!:!:!:!:!:!:!:!:::!:!:!:!:,:!:!:!:!tri:,t!:!,!:!
:i,:i:i:i:ii:iiiji:$iilt$ilElll:,:,i:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::rr;i:.:::::::::::::
oih;;it;; R;J;;6;
iiiiiiiiiiiiii:::.:i.i$.y,.$tem:iifr -Ilitty,:$t$iite..l$le€
for,iffii$ottf EIIlg+i i i nnf$lf ,io-t
$ite fff
A more detailed description on the Irrigation Energy Savers program can be found in Section 2.2
1.2 Eaaluation Objectiztes
Rocky Mountain Power requested an evaluation of the Irrigation Energy Savers program in Idaho. This
evaluation addresses the following objectives:
idor, i$ari i Itrip;: t-i &. I)ltit:i:ss []. i,a]u o ti uii oi:
Iloi:ii,_r, \,ir:uni:ain l:\nr,er's lrrigi:rtir:n L,ner:5v $3ypys !:llqgranr
C;;il ili;;;;;;; i;p.ovements to irrigation system
T'able'1" Ilrogram [ncentives and Serviees
Ilerptr I
ru,.,&rr$tANT
To verify the annual and combined2009-201L gross and net energy impactsl of Rocky Mountain
Power's Irrigation Energy Savers Program
To review the effectiveness of program operations, document achievements and identify
opportunities for process improvements
" To characterize participant and non-participant motivations in upgrading their irrigation system
To perform program cost effectiveness calculations for each of the three years evaluated as well
as for the 2009-2011. program cycle as a whole, and provide feedback on input assumptions
To provide Rocky Mountain Power findings for regulatory reporting
1.3 Program lmpact Eztaluation
The impact evaluation of Rocky Mountain Power's Irrigation Energy Savers includes:
" Establishing post-implementation performance for installed measures and activities
" Quantifying the impacts of incentivized measures and activities on annual gross energy
consumption while accounting for any interactions among technologies
" Explaining discrepancies between the results of this study and the reported savings estimates.
Evaluation metrics and parameters reported by this effort include:
, Gross program, project, and measure level energy savings estimates and realization rates.
" Energy usage profiles for irrigation pump stations obtained through on-site Measurement &
Verification (M&V) activities
> Net program savings estimates and realization rates as a function of both spillover and free
ridership
1.3.{ Key lrnpact Evaluation Findings
There is reason to doubt that the progr.rm is providing expected energy savings.
The Evaluation Team utilized both a Site Visit Analysis (based on data collected during visits to
participant sites) as well as a comprehensive Billing Data Analysis which included billing data from all
program participants. The Site Visit Analysis combines the International Performance Measurement and
Verification Protocol (IPMVP), options B & C by collecting temporary trend data on-site and leveraging
historical billing records; the Billing Data Analysis utilizes billing records and complies with IPMVP
option C. Both evaluation methods yielded a high degree of uncertainty regarding program energy
savings, and indicated the program may not be providing significant savings.
The high deviations between reported and evaluated energy savings could be due to a combination of the
following factors:
1 Demand impacts (kW) are not calculated due to uncertainty of project level savings and the program's emphasis on
energy (k\Atrh) savings.
2 Refer to Appendices for detailed description of IPMVP options.
Nstigoni irnpaci & Pri'ii:t':ss ll.vaiuotiun oi
l{oi:kl. \4 oun ta i n I\:w' er's l rri gntit:n lrlerii-\,' Sa v e rs i:'iograst
Rocky Mountain Power
Exhibit No. 5 Page 1203 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
I)i+ge ?
sr s\vrtANT
1.Reported energy savings for the majority of the energy efficiency measures are based on deemed
values3, either directly or through a quasi-custom approach. Since the reported impacts for
deemed measures are not calibrated or confirmed via measurement the evaluators are unable to
establish a reliable baseline for a bottom-up engineering analysis of energy impacts (i.e. the
leakage rates from prior to installing the measure could not be gauged after the fact).
Farmers may opt to participate in the program in anticipation of future increases in watering
requirements. This results in a self-selection bias in the billing analysis as a net increase in kWh
energy use (even though specific measures may actually be yielding positive energy savings
impacts).
"Measure mobili{/' was observed; non-center-pivot and non-pump-specific measures (e.g.
measures installed on handlines) are generally gathered to a single location at the end of a
growing season. Changes in location can reduce the applicability of a retrospective billing
analysis because energy impacts occur across multiple meters. This issue does not manifest with
smaller farms or farms with limited mobile irrigation lines. Given the lack of baseline data,
Navigant attempted to assess savings from these measures using both the Site Visit Analysis
(with reduced sample size) and the Billing Analysis (with all participant sites included). To
further refine the savings from these measures will require site specific data on a large sample of
participant projects, ideally with temporary pre/post- install data monitoring.
Lack of good data on crop planting history or participants' expansion efforts introduce
uncertainty regarding kWh consumptiory due to differences in watering requirements for various
crops - both on a daily and seasonal basis.
Growers often bring acreage in and out of production, with subsequent impacts on water use and
kWh consumption.
Lack of information on soil characteristics for various participants impeded efforts to understand
moisture retention at participant sites, and subsequent impacts on watering requirements.
Growers often install multiple measures in the same season. The resulting interactions between
installed measures further complicate the analysis beyond the approved sampling methodology.
The lack of baseline data combined with unknowns regarding the relative magnitude of the
varying measures increases uncertainty.
Suggested modifications intended to increase the certainty of Program savings are included under
Recommendations in this section.
1.3.2 RealizationRates
The 2009-2011 gross program energy savings realization rate is 22 percent, indicating realized savings are
substantially below reported. The system redesign measure group provided more savings than expected;
pivot/linear upgrade and equipment exchange measures provided fewer savings than expected. Table 2
provides the program-leael reported and net evaluated kWh, realization rates, and the evaluation's
confidence interval.
3 During the evaluation process, it was determined that the deemed savings for irrigation measures in the Northwest
are considered out of compliance by the RTF. Given the ongoing review of these measures at the regional level, the
evaluation team did not investigate the assumptions or methodology behind the reported deemed values.
Nsri.gont lrrip;rri & Plu:ess [].vair:oiiul oi'
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Rocky Mountain Power
Exhibit No. 5 Page 1204 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
4.
5.
6.
7.
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Rocky Mountain Power
Exhibit No. 5 Page 1205 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. HymasN.-\N$ilAN"tr
Pivot/Linear Upgrade
!8ffi iF,rnsr,rt.!ifx ffiei1ii
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n1 0/-2,29t,288
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The realization rates shown in Table 2 suggest that some of the projects are leading to increased energy
use. Research performed by others has also identified potential issues and concerns regarding water (and
thus energy) savings due to irrigation efficiency programs. The US Department of Agriculture (USDA)
and the National Center for Appropriate Technology (NCAT) have reported that "promotion of more
efficient irrigation technologies can unintentionally increase.irrigated crop consumptive water use."s If
irrigators do not make management changes that reduce total operating hours, "energy consumption
often stays the same or even increases."6
The evaluation team calculated a Net-to-Gross (NTG) ratio of 0.75 tor the Idaho Irrigation Energy Saver's
program for program years2009 through 2011. The methodology used in this calculation is provided in
Sections 3 and 4.
Measure specific findings include:
" VFDs appear to be performing well; they provide greater savings than expected.
" Pivot/Linear system retrofits appear to result in increased energy use.
, As a Measure Group, the impacts from Equipment Exchange measures (Drains, Gaskets &
Nozzles) have significantly more variance than normal. Assessing the impacts from these
measures to a confidence/precision interval of 80120 will require much larger sample sizes than
typically required for this size program.
The evaluated energy savings for gaskets and drains are statistically indistinguishable
from zero. Therefore, the energy impact for these measures is assumed tobe zero.7
,, Zero is a conservative estimate given that the majority of the high to low savings
range was less than zero.
- The only measure from the Equipment Exchange measure group that provides
statistically valid, net positive impacts is Drains; with 90% confidence, the precision
interval for Drains at an individual measure level is +l- 79"/".
a See Section 4.1.4 Overview of Statistical Validity, Confidence and Precision
3 Water Conseruation in lnigated Agriculture: Trends and Challenges in the Face of Emerging DemandslElB-99, Economic
Research Service, USDA" September 2012.
6 EnergV Saoings Tips for lrigators (2006),IP278, rcf.. Pump Up: lmprooing Plant Efficiency Does Not Always Saae Energy
by Blaine Hanson (2002)
7 See Section 4.1.4 Overview of Statistical Validity, Confidence and Precision
idil'r,'ir:ont Iinpni:i 8* I)lr.rt:ess [],i,;i]r:e iil-rii oir
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ruAxsr{-ANT
Rocky Mountain Power
Exhibit No. 5 Page 1206 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
1.3.3 Gost-Effectiveness
Using PacifiCorp's model for calculating the program's benefit-cost ratios, the evaluation team calibrated
and updated cost-effectiveness models using five primary cost tests as shown in Table 3 through Table 6
below. These cost benefit tests include:
" PacifiCorp's Total Resource Cost test (PTRC),
" Total Resource Cost test (TRC),
,, Utility Cost Test (UCT),
> Rate Impact Measure test (RIM), and the
" Participant Cost Test (PCT)8
As Table 3 through Table 6 show, the program is generally not cost effective.
T'abtre 3. 2009 Evaluated llenefit Cost ltatios
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8 Tests are consistent with the California Standard Practice Manual,
PTRC refer to table 19 on page ?.
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]\ot:L.rr \,it,-untiiii-r l\rr.ter'i: lrrigatitln lirer:;ir,'5aveys i:tl'{}tlyalTr
$r,474,808
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with the exception of the PTRC(for definition of
730,977
,iiif:SEj9IFiiii
Table 4. 2010 Evaluated Benefit Cost Ratios
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426,424
Rocky Mountain Power
Exhibit No. 5 Page 1207 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
0.55
Tahle 6. Comhined 2009 through 2011 Evaluated Benefit Cost Ratios
1,984,864 $3,072,U0
#*tU.,W.ffi9
$2,102,729
$3;$s2if29
0.68
I"09: ,:,,
1-.4 Process Eaaluation
The process evaluation characterizes the Irrigation Energy Savers program from the perspective of
program staff, participants, and trade allies in order to identify both existing strengths and areas for
refinement that will better serve the Idaho irrigation market in future years. It also includes consideration
of the perspective of non-participants to identify the level of program awareness and barriers to
participation.
From May through August 2012, the evaluation team surveyed or interviewed:
- 139 customers:
- 66 Irrigation Energy Savers participants and
- 73 program-eligible non-participants.
The evaluation team also conducted in-depth telephone interviews with six trade allies - active firms in
the Irrigation Energy Efficiency Alliance. These surveys and interviews provided data that are combined
with information from program staff interviews and project file reviews to create a comprehensive view
of the Irrigation Energy Savers program from 2009 to 2011.
I)erg.e {:r
N$V}TANJ T
Rocky Mountain Power
Exhibit No. 5 Page 1208 of'1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
',.4.1 Overall Process Evaluation Findings
There is no current scheme or metric established to rank the importance of specific findings. Therefore,
the following are provided in an order based on logical progression, not priority or importance.
Program administrators haoe the resources anil copacity to implement the progratn as planneil. Program
administrators indicated that they had the resources and capacity to implement the program as planned.
Program participants did not identify communication delays that might indicate resource or capacity
constraints. Participants and trade allies who contacted Rocky Mountain Power indicated that the
representatives were knowledgeable and timely. Trade allies indicated that they had a primary program
contact to which they could reach out and receive prompt and knowledgeable assistance; only one trade
ally indicated any communication delays.
The program f,ppef,rs to be reaching the intended target population.The program appears to have high
reach into the irrigation customer population. Program documentation provided at the time of the
process evaluation indicates that there were 85L projects completed at 528 unique sites by 369 unique
customerse. There were S22irrigation customers who had not participated in any program. In addition,
three-quarters of irrigation non-participants are aware that Rocky Mountain Power offers assistance to
improve efficienry.
Participants are mooing through the program as expected from the logic moilel. Both participants and
trade allies described the program operations as expected from the logic model. The program is
influencing actions of participants, particularly those who participate through system analysis and
redesign. Participants indicated that the program influenced additional similar purchases, and trade allies
indicated that program-qualifying equipment was similar to that purchased outside of the program.
Rocky Mountain Power needs to consider whether program benefits to customers meet other company
goals, or whether they will need to reconsider measure eligibility until verified deemed savings values
can be predicted and achieved.
The program materials arc oaeily complex and should be simplified. Participants and trade allies noted
that there could be improvements in the application paperwork, especially for equipment exchange and
pivot and linear upgrades. Current applications for equipment exchange and pivot and linear upgrades
are three pages long and include program information and legal disclaimers in the text of application;
these program details are also included in the program print brochure and manual. Trade allies compare
these applications to the single page applications from another utility, which do not include program
detail. Trade allies noted that customers may not return applications or may not want to wait for the ally
to fill out the application. A few participants also indicated a desire for greater clarity of program
expectations; the program brochure covers all four subprograms and may be confusing.
Customers idenffi high costs and lack of access to capital as barrierc to further action to reduce enerry
consumption and ilemand. Customers (47 participants and 18 non-participants) who thought there were
additional actions they could take to reduce energy consumption and demand were asked what might
e Program documentation provided to the evaluation team was updated at several points during the evaluation. Final
impacts and cost effectiveness reflect a comprehensive list of all known projects; however, the process evaluation was
completed prior to the final true-up of participant lists. Therefore, the sample framework and survey results were not
retroactively adjusted. This is acceptable because carry-over from the process evaluation into the final results is
primarily in the form of the unitless Net to Gross Ratio. As this is valid for the slightly smaller subset of projects, it is
applicable to the larger population with minimal impact on overall precision.
ldorri$ani igrpai:i & Ilri'ril-qs lLvah:stiun oi
Iiorl'.1r ltvi,luntilin l\'lr,ver's lrlig;rtitln F,irer:gl'5ar,ers !:irogiarjl i'erpre 7
Nd\V$TANY
Roclry Mountain Power
Exhibit No. 5 Page 1209 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
prevent them from doing so. The most common potential barrier, identified by 72 percent of responding
participants and 67 percent of responding non-participants, was "high upfront costs." The next most
common potential barrier was a "lack of access to capital" with 15 percent of responding participants and
11 percent of responding non-participants indicating that was a barrier for them. Among other barriers to
further customer action to reduce energy consumption and demand were lack of time and lack of
information. The Irrigation Energy Savers program is designed to overcome high upfront costs and lack
of information. Program designs like equipment exchange overcome capital constraints for low-cost
equipment; however, as noted in the impact section of this report, measures in the equipment exchange
program are subject to a high degree of uncertainty. No programs are currently in place at Rocky
Mountain Power to overcome the barrier of "lack of access to capital" for projects requiring larger capital
investment. Access to capital is particularly important for retrofit projects with high upfront costs, such as
VFDs, system redesigns, and center pivot tuning projects.
The program claimed 99 percent of its 2077 enery saoings goals. ln 2009 and 2010, the program did not
have overall savings goals, but had contract targets with the third party administrator. The third party
administrator exceeded savings targets in both years based on reported savings. 1n201,1,, the program
introduced an overall energy savings goal of 2,389,790 kWh; reported savings of 2,360,391. kWh are 99
percent of this goal.
L.5 Program Eoaluation Recommendations
The evaluation team recommends that Rocky Mountain Power consider undertaking the following steps
to improve the program for future cycles. There is no current scheme or metric established to rank the
importance of specific recommendations. Therefore, the following are provided in an order based on
logical progressiorl not priority or importance.
See Section 6 for details of recommendations.
The program needs modifications that will increase the likelihood of savings occurring as expected.
Some measures are successfully providing positive energy impacts, while others are not. This program
should not continue in its present form unless steps are implemented to confirm that the impacts of each
type of measure included in the program are net positive. Suggested modifications include:
1. If the program is to continue, it should be considered as being in a test period.
2. Increase program focus on Variable Frequency Drive (VFD) applications. This measure has
positive impacts and an 80122 confidence/precision interval.
3. Modify the program such that mobile measures (i.e. non-center pivot, non-pump specific) are
temporarily delivered via a direct install participant track. The intent of this recommendation
is to allow for pre/post monitoring that can immediately assess measure savings with
interactive impacts. This change will increase the cost of implementing what would
otherwise be very low cost measures and may limit the number of these measures
incentivized, but the benefit is that a direct install model allows for better data to be collected
in order to confirm positive measure impacts before further program moneys are spent on
measures with little or potentially negative, impacts.
4. Establish protocols to ensure that installation dates are accurately captured.
5. Revise the program to encourage and incent only those measures which are determined to
consistently reduce energy usage, and remove other measures from the program.
Na'i,iqsni iripalt &. Pr:ocr-:ss {l,va}rioiii.rr-. o{
ilodtr \,it:untain !l'ur.,uer's lrrigatit:n [i,i-.ei:gr.'Savers i]rogranr I'iigre I
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Roclry Mountain Power
Exhibit No. 5 Page 1210 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Determination of which measures remain in the program should consider waiting until after
further data collection while the program is in test period status or, until additional
performance based data is available to justify measure inclusion.
The program should be considered to be in a test period and regularlo follow-up evaluations should be
conducted until the program shows reliable, cost effective savings. The evaluation team has the
following recommendations for reducing uncertainty in the next program evaluation:
1.Until the regionally deemed savings are back in compliance, treat all measures that are part
of the program as custom (as opposed to prescriptive).
Determine baseline energy use for implemented measures. This will necessitate primary data
collection prior to measure installation. Data collection will need to include in-situ flow rates,
power spot readings and, possibly, temporary data monitoring of pump power that can be
correlated with measured flow data. This step is particularly critical for measures that can
migrate between pumping stations, as they cannot be accurately verified after the fact.
Utilize additional survey tools to assess participant tendencies toward self-selecting into the
program in anticipation of increased crop watering plans for the coming year. The expanded
survey needs to also verify if total irrigation system capacity changed at the time of
participation. Additional documentation of changes in system design can then be used to
construct an improved counterfactual baseline across all program measures.
Consider performing a Randomized Control Trial (further described in Section 3 of this report)
to address potential selection bias, in conjunction with the next program evaluation.
There are additional recommendations that could help reduce customer barriers and increase
participation.ll If the program continues following the test period and implementation of the actions
previously described, the Evaluation Team has the following additional, second fler recommendations:
1. Simplify the application process and provide clear guidance.
2. Approach Sprinkler Packs as a fully custom measure.
3. As opposed to the current offer to retune center pivot systems back to original design specs,
investigate options for system redesigns that promote incremental improvements in system
efficacy beyond current standard practice.l2
4. Explore options to make financing available to customers for projects requiring capital
investment.
r0 Annual evaluations may be advisable during the test period, but decisions regarding the most appropriate
evaluation schedule are left to the Company.
11 Short recommendations are included here. For context and more detail, see Section 6 Program Evaluation
Recommendations
12 Changes of this nature may be most effective if conducted and evaluated under a market transformation model.
Nilrr.i.gant inrpai:t & I)i:i'it:ess ILvah:oiion oi'
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2.
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.!ilNd\VI{:ANT
Rodry Mountiain Power
Exhibit No. 5 Page 1211 of 1365
Case No. PAC-E-14-07
Wtnessi Kathryn C. Hymas
This section provides a description of the Irrigation Energy Savers program and a discussion of the
underlying program theory and logic model, which depicts the activities, outputs and desired outcomes
of the program.
2.7 Eoaluation Objectioes
The Impact and Process Evaluation of Idaho's Irrigation Energy Savers program accomplishes the
following objectives in support of Rocky Mountain Power's targets for energy efficiency achievements in
Idaho:
" Verifies the annual and combined 2009 through 2011 gross and net energy impacts of Rocky
Mountain Power's Irrigation Energy Savers Program
> Reviews the effectiveness of program operations, highlighting achievements and identifying
opportunities for process improvement
> Characterizes participant and non-participantmotivations
, Performs cost effectiveness calculations on evaluated results for each year evaluated and in total,
and provides feedback on input assumptions
" Provides Rocky Mountain Power findings required for regulatory reporting
The following report provides context on evaluation findings and incorporates feedback from Rocky
Mountain Power program staff.
2.2 Program Desciption
The Irrigation Energy Savers program offers Idaho irrigation customers (rate Schedule 10) the
opportunity to increase the efficiency of their agricultural irrigation systems through implementation of
energy-efficiency measures and education. In 201L, the program sought to achieve energy savings of
2,389,790 k\Atrh. In 2009 and 2010 there were no overall savings goals, but the third-party administrator
had savings targets. The program offers the following incentives and services:
Nsti$gnt intpari &. Prcress lLvi*iuntir:,"r oi'
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Roclry Mountain Power
Exhibit No. 5 Page '1212 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Replace worn parts to reduce pressure at nozzle, to reduce
flow
Replacing worn nozzles to improve water distribution and
reduce nozzle flow rate
Reduces pumping flow rate during same run time for
energy savings, additional savings if run time is reduced
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The equipment exchange option is for customers with hand lines, wheel lines, and solid set sprinkler
systems. Participants exchange their worn nozzles, gaskets, or drains for equivalent new equipment (at
no cost to the customer) through program allied vendors. The pivot and linear system upgrade option is
available for customers with center pivot and linear move systems and provides incentives for the
replacement of existing equipment with new low pressure drains, sprinkler pressure regulators, or
sprinkler packages.
The program provides customers with technical assistance in the form of system consultations and pump
tests to help them determine the pumping efficienry of their system and to suggest efficiency
improvements. Customers who are adding capacity, changing their water source, or replacing all or part
of their system qualify for an in-depth system analysis. Customers who implement recommended
changes may qualify for incentives for site-specific projects that save energy as determined by the
program administrator.
Customers interested in participating in the program can choose from a list of participating vendors in
Rocky Mountain Powe/s service territory or contact the program administrator to identify a participating
vendor. A list of participating vendors is available on the Company's web site. A third-party
administrator primarily administered the program from 2009 to2017.
2.3 Program Changes from 2009 to 20L1-
The method for estimating energy savings from pivot retrofits was updated mid-year in 20L0. With this
update, claimed savings transitioned away from a prescriptive, per system estimate, to a semi-
customized approach that includes several system specific inputs which inform a customized version of
deemed savings. In 2010, the energy savings value for Sprinkler Pressure Regulators was also changed
No:'iqoni itri1:ari ci l)l:cicers lLi,i'iluatioii oi'
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Rocky Mountain Power
Exhibit No. 5 Page 1213 of 1365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
from a deemed value, to one that can be calculated using a quasi-custom approach that combines deemed
savings with system specific inputs.
2.4 ProgramParticipation
Detailed program documentation from 2009 to 2011, indicate that there were 851 projects completed at
528 unique sites by 369 unique customers.
2.5 ProgramTheory anil Logic Model
Program logic models depict the primary program activities, the outputs that are expected to result from
each activity, and the expected short-, mid- and long-term outcomes of those activities. Program actiuities
depict the primary actions that are required to implement the program. This includes marketing,
participant recruitment, training, etc. The outputs depict the tangible "product" resulting from each
primary activity. For example, marketing materials, training documents, and databases of recruited
participants can all be outputs of primary program activities. Outputs are typically identified as "things"
that can be tracked and tallied. Outcomes represent the intended results of successful deployment of the
identified activities.
Developing a logic model that clearly provides the theory of action and change is an important step in
evaluation, allowing the evaluator and program actors to see inside the program "black box."13 Program
logic models provide a framework for an evaluation because they highlight key linkages between
program activities and expected outcomes. The process and impact evaluations focus on these linkages,
particularly those on the critical path to achieving savings goals. The evaluation identifies which linkages
in the program logic model are working properly and which linkage(s) may be weak or broken. Thus, if
the program falls short of achieving its intended short, mid, or long-term outcome(s), the source of the
shortfall can be pinpointed and remedied. Logic models are often developed as a visual tool to document
the program theory. The creation of such a model serves to develop a common understanding of program
activities and intended outcomes among third-party program implementation staff, Rocky Mountain
Power, and the evaluator. With this foundatiory the evaluation team can then make informed choices
related to the prioritization and focus of evaluation resources.
The underlying theory for the Irrigation Energy Savers Program is articulated in the logic model
provided in Figure 1. The evaluation team created the logic model based on a review of program
documentation and discussions with program management and implementers.
13 Funnell, Sue and Patricia Rogers. 2011. Purposeful Program Theory: Effective Use of Theories of Change and Logic
Models. Iohn Wilev & Sons.
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Rocky Mountain Power
Exhibit No. 5 Page 1214 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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Exhibit No. 5 Page 1215 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
The Irrigation Energy Savers program is designed to overcome two customer barriers to implementing
energy efficiency projects: lack of trusted information and high upfront costs for some irrigation
equipment. The program provides some equipment at no cost, provides incentives for other equipment,
and offers technical assistance. Linkages within the program logic are described here with numbers
related to those shown in the logic model figure.
1. The third-party program administrator led an effort to reach out to irrigation product dealers to
develop an Irrigation Efficienry Alliance (IEA) that covers eligible energy efficiency measures
(EEMs) - nozzles, drains, gaskets, sprinkler pressure regulators, and sprinkler packages.
2. The IEA is armed with marketing materials, application materials, and training on the program.
3. IEA promotes the program, both equipment exchange and pivot and linear equipment upgrades,
to customers.
4. Rocky Mountain Power coordinates marketing and outreach efforts with the third-party program
administrator, and irrigation account managers.
5. Customers become aware of the program through marketing and dealers in the IEA.
6. Customers return used nozzles, gaskets, and drains from hand lines, wheel lines, and solid set
sprinkler systems to dealers. (Equipment Exchange)
7. For center pivot sprinklers and linear move sprinklers, IEA dealers help customers select
qualifying equipment to replace worn equipment. (Pivot and Linear Equipment Upgrade)
8. IEA dealers help customers submit equipment exchange applications, if exchanging equipment,
or pivot and linear equipment upgrade applications, if upgrading worn pivot and linear
equipment.
9. The third-party program administrator receives, processes, and documents applications for
Equipment Exchange and Pivot and Linear Equipment Upgrades.
10. Equipment Exchange and Pivot and Linear Upgrade customers install the new equipment.
11. New equipment reduces demand and/or energy consumption at the irrigation site.
12. Customers may request individualized system consultation to evaluate: irrigation scheduling,
system integrity, pressure and flow, pumping lift, or opportunities for a system redesign.
13. The program administrator determines what kind of analysis to perform for the irrigation
customer. In some cases, scoping may require a visit to the customer site. Based on the
individualized consultation parameters, pump tests may be performed or detailed project
analysis may be conducted at the irrigation site.
14. Based on an irrigation site visit and individual parameters, a system consultation report and/or
an irrigation project analysis report, documenting recommendations for energy improvements is
prepared by the third-party program administrator.
15. The report recommendations are presented to the customer. Both reports include
recommendations for system improvements. An irrigation project analysis report will also
include an estimated incentive offer.
16. If customers are going forward with system redesign, they submit a signed incentive agreement.
17. Customers install recommended equipment and implement recommended strategies or controls.
18. New equipment or control strategies reduce energy consumption (and, in some cases, demand) at
the irrigation site.
19. Reduced energy consumption contributes to meeting annual program targets for Rocky
Mountain Power; note that overall program savings targets were put into place in 2011.
20. Customers see reduced energy costs and potentially reduced water costs.
21,. If it is deemed necessary based on the project, the program administrator verifies proper
installation of measures.
22. Yerification is documented and ensures that expected savings occur.
Norri$ilnt irnpai':i 8x l)nrr:ti$s li:l'i:iluoti*n oi
]iockv \4t:untilin iiror.rrer's .lrrigi:rtit:n Lir-rer:g.i Sar,ers l:'rrtttarri Fugr 14
ru.&xrlsANT
The program administrator informs Rocky Mountain Power of project completion and processes
incentives for equipment exchange, pivot and linear system upgrades, and system redesign.
Incentive checks are mailed to the appropriate recipient. Dealers receive equipment exchange
incentives (no cost to customer); customers receive incentives for pivot and linear system
upgrades or system redesign. Incentives reduce customer costs for the project.
Program outcomes can be evaluated by reviewing key indicators. Table 8 identifies key indicators and
data sources for Irrigation Energy Savers program outcomes noted in the logic model.
Tahle L lndicators and Data Sources for Process Er.aluration
Rocky Mountain Power
Exhibit No. 5 Page 1216 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
23.
24.
Dealers identify pivot and linear
system upgrades
liirs$Eii'6f,iii isalidfi{,,1ffislr:l lsn.i.i,.,....,.,.,lt
.......ideffit+a'.,..,,:,:.:: ,.,..,....,.,.,.,.-..,i.,,,...........,t1':i:i'iiiiii:, ',ii
Energy saving measures, costs, and
benefits identified
,1**#*li"stalled,iiiiiiiiiiiiiiii,,i.ii' ,'iiiiiii. .,,.,,,.....................,..
Installation of measures verified
Program tracking data; customer
surveys; trade ally interviews
Customer surveys
::::::::::::::::::,,::::,, . ] :::]:]]]:!:!:::::|:: :: ::i:::]::i:::i::l:l:::j:1,::l
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l\gi;iiy \.ii.v1;1-rfain i:tor+ei'-s lrr:ig;rtii:n {it'rergr. Sai tlrs i:'ttt:triett:n.,,a,\ 1 q
rus\rsxt&NT
Roclq Mountain Power
Exhibit No. 5 Page 1217 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
The following section provides a detailed description of the evaluation methodologies used in the impact
evaluation of ldaho's Irrigation Energy Savers program.
3.L Impact Methodology
This section summarizes the Impact Evaluation methods used to develop project- and program-level
realization rates for the Irrigation Energy Savers (IES) program. Findings provide Rocky Mountain Power
staff with the feedback they need to improve the program and to meet the objectives of Idaho's Public
Service Commission by providing an independent quantitative review of program achievements.
The goal of the impact study was to:
> Quantify the impacts of all measures and activities on annual gross energy consumption while
accounting for any interactions among technologies
" Establish post-implementation performance profiles for installed measures and activities;
" Explain discrepancies between the results of this study and the reported savings estimates.
Evaluation metrics and parameters reported through this study include:
, Gross program energy savings estimates;
" Realizations rates for projects and energy savings by measure types;
" Energy usage profiles for variable flow irrigation technologies obtained through on-site
Measurement & Verification (M&V) activities; and
" Net program savings estimates and realization rates as a function of both spillover and free
ridership.
The impact evaluation methodology is outlined as follows:
" Evaluation Approach
" Project File Review
" Sampling Framework Development
, Gross Energy & Demand Realization Rate Calculation
" Net-to-GrossEstimates
" Program Cost-Effectiveness Calculation
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ruAvltANT
Rocky Mountain Power
Exhibit No. 5 Page 1218 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
3.1.1 Project File Review
A review of the Irrigation Energy Savers project files allowed the evaluation team to understand the
nature of the energy savings treatment and develop on-site Measurement and Verification (M&V) plans
for projects included in the on-site M&V sample.
The project application and verification report for VFDs was more detailed than the other measures and
allowed the evaluation team to confirm input assumptions and trace a greater portion of the measure
impact calculations.
3.1.2 Sampling FramerryorkDevelopment
The team adopted a Ratio Estimation approach to sample design which relies on the relatively stable
correlation between an auxiliary variable and the variable of interest. The ratio of actual savings to
program reported savings is generally seen as a reliable source for this correlation; this ratio is known as
the realization rate for gross verified savings and is also a core objective of this impact evaluation.
Further, the standard deviation of the realization rate is generally much smaller than that of the
magnitude of individual project savings. However, as seen with this program, the Ratio Estimation
method can underestimate the sample size required if claimed savings deviate dramatically from actual
measure impacts (i.e., when the realization rate is consistently much larger or much smaller than 1.0).
It follows that the sample sizes required to achieve a specific confidence/precision threshold may be
greatly improved by estimating the realization rate instead of total energy savings. Industry standard for
confidence/precision is a minimum of 80120; however, the evaluation was designed to achieve 90/L0 at the
program level.
Per the 2004 California Evaluation Framework,la sample sizes developed using the Stratified Ratio
Estimation approach comply with the following equation:
IA/here:
n = Sample Size
Z = Z-Score for Desired Confidence Level
e = Assumed Error Ratio (0.5 Based on Prior Evaluation Studies)
rP = Desired Relative Precision
N = Population Size
Moreover, the evaluation team proportionately stratified the sample by program reported savings. Under
this approach, the sample population was divided into subgroups (strata) by claimed savings. The
evaluation team selected projects proportionately within each stratum to ensure:
1. The largest projects and contributors to program performance are evaluated, and
2. The medium and smaller projects receive fair representation in the evaluation. (Collectively,
these projects also reflect a large percentage of program level savings.)
la TecMarket Works, The Califomia Evaluation Framework, June 2004
Navi$ont Im1:ai:t & Pr:ut:ess ll,r,;ih:oti*n of
I{.ocky \4 a u n ta in lti:lr.t er's l rri gi,ltit:r: Ii,nei:gri Sa vers .l}r+grarn
il-t
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:,!::-l .:t:
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Roclry Mountain Power
Exhibit No. 5 Page 1219 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 9 provides an overview of the impact evaluation framework representing the reported Irrigation
Energy Savers Program savings for the 2009-2011. program years. The sample framework was established
using an initial version of program documentation provided by Rocky Mountain Power that included 728
projects.
8,869,898 1.,007,5U 110/0
3.1.3 EvaluationApproach
This evaluation applied two rigorous, industry-accepted methods and both provided strong reason to
doubt that some measures included in the program are providing savings that are either positive or
statistically significant. The Evaluation Team utilized both a Site Visit Analysis (based on data collected
during visits to participant sites) as well as a comprehensive Billing Data Analysis which included billing
data from all program participants. The Site Visit Analysis combines the International Performance
Measurement and Verification Protocol (IPMVP) options B & C; the Billing Data Analysis complies with
IPMVP option C.
Both evaluation methods indicate a high degree of uncertainty regarding energy impacts related to
certain measures, and indicated that other measures included in the program may be causing a net
negative impact on electrical energy use.
Irrigation Energy Savers projects involve the following measures:
15 Program documentation provided to the evaluation team was updated at several points during the evaluation.
Final impacts and cost effectiveness reflect a comprehensive list of all known projects; however, the evaluation
sample was completed as one of the very first steps, prior to the final true-up of participant lists. As noted in the
following footnote, this has minimal impact on overall precision since the final sample size was ultimately
expanded.
16 Original sample size expanded from 54 projects when it became apparent that homogeneity of savings would be a
challenge. A total of 89 projects were reviewed via on-site data collection at 57 sites,
l\iir,igilnI hnpai:t & Ilruct:ss ll,villuotion oi'
I{oi:}t;1, \,tou.n1ain l:ti:nl,er's irrigatir:n li,riergv 5a'r,ei:s .l:}rograni
Tahle 9, Overvier,r'of the ldaho Irrigation Energy Savers Impact Evaluation Sampling Frarne
Fage 1$
N$V $T,q NT
Drains
Sprinkler Package
!iri!:$y,$IH#l::i+Sgf,+$I$tt$ii:,:,:,:,, :,,,:,i.:.:,i.:.:.i.:.:.:.:.:.|,i.|.:,:.:,:,:,|,|,:,:,:,|,:,:,;,;,:'|,:,:1!:,:!,:,:.:,:,:,:,:,:,:,:,:,:,:,ll::,:,:,:,:,:,::':,:::
VFD
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On-site data collection also included: a visual verification of installed IES measures, electrical spot
measurements, installation of temporary data loggers, measurement of discharge pressure and system
flow rates.
17 A single participant may have had multiple projects, potentially all connected to the same pumping station.
Therefore, this metric is determined by the number of unique project IDs that were covered.
t27
2go 44'693 4,085 45.17"
:::iijri:::iii::::i
f,}:il: i .:: ..::::
:iaiai:iii:ii:i::li
37 9,820 1,083
23,908
Rocky Mountain Power
Exhibit No. 5 Page 1220 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
* Measure Count based on units proaided in Table 7.
3.1..3.1 On-Sites lnspections anil Site Visit based Analysis
Between June and September 2012, the evaluation team visited 89 Irrigation Energy Savers project sitesrT
to conduct M&V activities. The purpose of these onsite visits was to verify that incentivized energy
efficiency measures were installed and operating as reported. The evaluation team also used onsite
collected data to verify realization rates, and to calculate demand and energy savings.
The evaluation team recruited program participants for on-site project review and data collection using a
stratified-random sample. Each recruited participant was interviewed to obtain data concerning the
operation of their farm. This interview based data collection included, in part, the following data points:
" Irrigation water sources
> Irrigation acreage
Irrigation equipment counts and technologies in use
Irrigation hours of use, watering strategies
Irrigation records for past years
Field acreage, crop planting and harvesting schedules
Field crop rotation for past four years
Narrirlilni irn;rai:l & I)lut:riss ll,r,ah:iltiun ol'
l'lot:i,;\, ili,tt tr n ta i lr ll'ow er's l rri gi:iti tln Li rrrtE:i Sa t ers .i:'rt:,qram
I'able 10" Irrigation Energy Savers lleported Savings by Measure
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Roclry Mountain Power
Exhibit No. 5 Page 1221 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
The spot-readings confirmed the operational parameters of the irrigation system while operation
continued at a normal level. These primary data collection measurements included:
, Measurement of operational parameters while system was operating
o Water flow rates and pressures
o Electrical spot measurements
o Recording of manufacturer's name plate information
o Metering of electrical usage on VFDs
> Documentation of any changes to system or system operations post implementation
Site specific data (meter number, crop type, irrigated acres, etc.) was correlated to billed energy use and
normalized to estimated water use. Cumulative pumping volume is rarely monitored at agricultural
sites; therefore water use is estimated using a calculated evapotranspiration rate. The evapotranspiration
(ET) rate is a metric of estimated plant water use that factors in the crop type and weather factors such as:
solar gains, wind, temperature, humidity and precipitation. This provides a crop specific, localized
estimate of a plant's ideal water needs. This method does not account for grower decision processes or
other external influences, beyond weather, on field level water use.
VFDs projects included in the sample were monitored for a period of one to three months using Onset
HOBO data loggers. Logger trends are combined with spot power readings, which allows the VFD part-
loading to be determined. Energy impacts are then calculated using the variance between evaluated
pump full speed demand and the part load demands recorded by the data logger. The daily energy
impacts are then extrapolated using seasonal use profiles and the baseline is calibrated using the average
of the site's previous five years of annual billing data. The final result is an annual energy impact per
VFD that is normalized using motor horsepower.
3.1.3.2 Eoaluation Approach for Billing Analysis
A program level billing analysis was conducted as part of the impact evaluation so as to improve overall
confidence. The sample of projects used for the Site Visit Analysis represented 12 percent of reported
savings Table 5; the Billing Data Analysis included inputs for all program participants from the
evaluation years of 2009-2011.. The Site Visit Analysis incorporates a greater level of site specific details
but the Billing Data Analysis leverages a larger sample size.
Billing records showing the actual amount of electricity used by a customer over a given billing cycle are
combined with data from the program tracking database to estimate the average electricity savings
generated by program participation. The main methodological issue for the impact evaluation is to
estimate the counterfactual enerry use by sites that installed irrigation measures as part of the IES program
- that is, the energy that sites would haoe used in the absence of the program measures. Using billing records to
compare energy use after measure installation to the counterfactual energy use indicates the energy
savings due to measures installed through the IES program.
Simply comparing the rate of energy use after measure installation to energy use before installation is not
sufficient for estimating savings, because other factors affecting energy use - weather, economic
conditions, crop rotations, and other variables - also affect the change in energy use over time. To the
extent that these factors are observable, they can be included in a statistical analysis in an attempt to
l,:' il l.i$an I ir:r }:a i: t & Procr-:ss iL v al r.r a ti.r.;rr oi
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N,&VXTANT
Rocky Mountain Power
Exhibit No. 5 Page 1222 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
isolate the effects of the IES program. But despite great diligence to include such variables, there is a
strong possibility that some factors are unobservable and will not be adequately represented in the
analysis, causing the estimated impact of the measures calculated in this way to be biased.
One approach to account for these other factors is to include in the analysis a set of control sites to
provide an estimate of the counterfactual energy use of program participants. The ideal method for
determining the counterfactual is the construction of a randomized control trial (RCT) approach. In
practice, constructing an RCT control group can pose significant design and recruiting constraints. Using
an RCT approach allows the analysis to account for any possible selection bias that may be present in the
data otherwise. Selection bias may be present if there is some non-random factor that influences when a
site chooses to install measures as part of the IES program. The presence of such a bias may influence the
amount of energy used for irrigation pre- and post-installation independently of the irrigation technology
utilized. Such factors could include one or more macro- or micro-level influences, including crop prices,
site-level crop rotations, the age of existing irrigation equipment, expectations of near- and medium-term
irrigation requirements, or other non-observable characteristics.
In the absence of an RCT to establish a baseline, a quasi-experimental method called the variation in
adoption (VIA) approach is appropriate. The fundamental insight of the approach is that both late
enrollees and early enrollees reveal an important commonality and similar motivations by virtue of their
similar decision to participate in the program. It follows that a good estimate of the "counterfactual"
energy consumption is available via sites already enrolled in the program - that is, the energy
consumption these sites would haoe used in the absence of the Irrigation Energy Savers program - is the
energy consumption of future enrollees not yet in the program during the same billing period. The VIA
approach is classified as a good estimate of the counterfactual because while it does help to ensure that
sites contributing to the baseline analysis demonstrate a similar level of enthusiasm for installing
irrigation measures as those sites that have already been treated, it does not completely compensate for
the selection bias that may influence when a site chooses to participate in the program and the relative
level of energy use that may result.
The version of the VIA approach utilized for this analysis uses a fairly simple, but flexible, linear fixed
effects regression model of energy consumption by activated participants. The model casts daily
electricity consumption as a function of participant-specific fixed effects, month-specific fixed effects, and
the basket of measures installed at each participant site. Using this "two-way'' fixed effects model
estimates the impact of all time-invariant variables that are directly modeled into the equation. The
participant-specific fixed effects account for all time-invariant characteristics of a single farm, such as its
locatiory microclimate, and other aspects. The month-specific fixed effects estimate the impact of all site-
invariant temporal factors that affect all customers, such as regional weather, crop prices, economic
conditions, and seasonal conditions. Stated formally, we have the following model structure:
5s1i61ilnt Im;:ari rs Pi:t;ctriss ll,r,al.r.iotiun o1'
I{oi:hrr \4 o u n ia i n }:\rrrr er's .l rri gati t:n [,ne'rg.". 5a vers l:'rtlqrarn Fage ii
where,
sl,,
Model l
ADII1 = ok * br+y,Dt*, + eu,
Average daily energy use by site k in month f;
Site-specific constant (fixed effect);
Month/year specific constant for growing season (fixed effect);
A 0/1 indicator variable, taking a value of 1 if measurei is installed in month t at site k.
Evaluated coefficient on the indicator variable Dfr;
Model error term for site k in month f.
Model2
ADII1 = ox * br+y1str, + e6
A variable representing the deemed kWh savings in month f at site k from measureT.
This variable takes a value of 0 in months prior to measure installatiory and the deemed
savings value as represented in the program tracking database after measure
installation. For unit consistency, this value is adjusted to a daily amount.
All other terms in Model 2 are defined the same as in Model 1. )ust as before, the residuals are clustered
at the site level to account for any serial correlation. Once again, yi is the variable of interest, but in this
model specification it represents the estimated realization rate on measure-level savings.
iiiolillont irrrpai":t 8e Prr:csrs ll,l'trIuiliir:n si'
I{oi:l;rr \.li:r-rntain I\:wer's lrrigatit:n Li*er:g.",Savers l:'ri:gr;irr
ru Axr $il,e N T
where,
ADUkt
Oy
bt
D,u,
fi
€tt
In Model 1, y; is the ultimate variable of interest as it represents the estimated daily kWh savings for each
measure installed through the IES program. The error terms, epr, in the above model are clustered at the
site-level. If the electricity use at a specific site trends above what the baseline predicts the site would use
for a series of back-to-back months, it is likely that this "over use" of electricity relative to the baseline is
correlated rather than due to random chance. Said another way, if a site is using more electricity than
predicted in one month, there is a better than random chance that it will also use more electricity than the
baseline predicts in the following month. By clustering errors at the site level, the model allows the
calculated standard errors on the coefficient estimates to account for any serial correlation among the
amount of monthly electricity used at each participating site.
As a robustness check, a second billing analysis model, known as a statistically-adjusted engineering
(SAE) model, was also used as an alternative method of determining measure-level savings. This model
incorporates the deemed gross savings amounts for measures installed at a given sites as an independent
variable in the regression equation. These ex ante savings values come from the program tracking
database. In the regression, the estimated coefficient on these deemed savings values can be interpreted
as measure-level realization rates for all installed measures incented by the program. This method of
analysis can be beneficial when program participants and the level of expected savings per participant
are relatively heterogeneous. Formally, the secondary model is constructed as follows:
Roclry Mountain Power
Exhibit No. 5 Page 1223 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage Xl
Rocky Mountain Power
Exhibit No, 5 Page 1224 of 1365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
The models described above are not appropriate analytical tools for estimating demand savings that
result from participation in the Irrigation Energy Savers program. By its nature, a program level billing
analysis uses monthly billing data to analyze customer energy use over an extended period of time. The
parameters and fixed-effects in the above models are calibrated to measure program impacts over this
longer-term time scale rather than short-term demand. In order to properly determine demand savings
using this method, customer billing data would be needed at the hourly level to differentiate levels of
demand throughout a daily period.
3.1.4 Gross Energy Realization Rate Calculatiein
Gross energy and demand realization rates for each project in the impact evaluation sample were
combined to form program-leoel realization rates for each program year. The evaluation team researched
the following technical issues in order to accurately determine gross program impacts and realization
rates:
" Installation and quantity of reported measures.
" Baseline and measure performance characteristics of the measures installed, and revision of
performance variables (e.g., operating hours) as needed.
" Energy savings (kwh) impacts of the measures installed for projects sampled. This was
accomplished by first calculating case weights for each evaluated project; the case weight is simply
the number of projects in the population in each stratum divided by the number of projects in the
final sample in the corresponding stratum.ls
The program-level realization rate was then calculated as the ratio between the product of case weights
and aerified savings estimates and the product of case weights and reported savings estimates. This is
illustrated in the equation below:
F,*e$,-flrtr R.=crt5sii+ar Ssie' =
rrrIi:=, if*sE itretg,t.t1 x i'rsrifi:Bd Ss.u'ix5fs Esfir-nsfe:
r*Ii=1 fn".r". lfe.$ht, x .tsportecl Ssr,'i.?i$s- E-siinls.lsr
3.1.5 Net-to-GrossEstimates
This section contains a brief overview of the Net-to-Gross (NTG); a more detailed explanation is provided
in the appendices.le Using self-reported responses, the evaluation team's estimation of net savings first
attempted to assess the program's influence on the participants' decision to implement an energy
efficienry project and what would have occurred absent program intervention. This estimation included
an examination of the program's influence on three key characteristics of the project its timing, its level of
efficienry, and its scope (i.e., the size of the project). This estimate represents the amount of savings
attributed to the program that would have occurred without its intervention and is often referred to as
"free-ridership."
The team's measurement of net savings then estimated program influence on the broader market as a
result of the indirect effects of the program's activities. This estimate often referred to as "spillotser,"
rB The TecMarket Works Team, The California Evaluation Framework, Prepared for the California Public Utilities
Commission and the Project Advisory Group, June 2004
le Appendices contain a chapter dedicated to Net Savings methodology.
Nar.,igont irnl:ai:t {e Pi:ocr,-ss [:,va]r:atirxr oi
lloi:krr \4r:untain l:ror.r,,er's lrrigatit:n [ir:rerg.;.Sai,ers i:'r'ogram Page 13
represents the amount of savings that occurred because of the program's intervention and influence but
that is not currently claimed by the program. Spillover savings can be broken into two categories of
savings: "participant" spillover and "non-participant" spillover. Participant spillover savings occur
directly (i.e., program participants install additional energy efficient equipment), while non-participant
spillover savings occur indirectly (i.e., market allies install additional energy efficient equipment to
customers that choose not to participate as a result of the program).
A program's net savings are adjusted by both free-ridership and spillover savings at the measure level
and then extrapolated to the program level. The net savings are the program-reported savings minus any
free-ridership savings plus any identified spillover savings, or:
Net Program Saaings = Gross Program Satsings - Free-Ridership Saoings + Spilloaer Saoings
Oftery this finding is described as a "net-to-gross ratio." This ratio is the net program savings divided by
the gross program savings, or:
Net-to-Gross Ratio = Net Program Saoings I Gross Program Saoings
The findings of the NTG analysis are presented in Section 4.2.
3.{.6 ProgramCost-Effectiveness
Program and measure group cost-effectiveness calculations were performed using the same cost-
effectiveness models and assumptions developed within the PacifiCorp planning department. The
evaluation team worked closely with PacifiCorp to discuss the implications of evaluated measure savings
on cost-effectiveness test results along with other additional cost-effectiveness inputs (beyond measure
incremental costs, Effective Useful Life (EUL), Remaining Useful Life (RUL), and the validity of measure
savings) reviewed as part of this exercise.2o
The evaluation team ran the cost-effectiveness tests with updated evaluation findings, including:
1. Gross Program Savings Estimates
Gross Program Realization Rates
Net-to-Gross Ratios
Program Costs (Administrative and Incentive)
Measure End-Use Load Shapes as provided by PacifiCorp
NS\V$ilANI T
3.2 Nofes on Validity and Reliability of lmpact MUV Findings
Nnr.i$ont itrtpai':t &. Ilri.rt:ess ll,r,aluili.i*n of
i{or:k-v \4or"rn{:ain l]or+'er's lrrigation Lirrerg.,'Saters l:'rotrain
)
J.
4.
5.
Roclry Mountain Power
Exhibit No. 5 Page 1225 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
The evaluation team identified several sources of uncertainty associated with estimating the impacts of
the Irrigation Energy Savings program. Examples of such sources include:
, Sample selection bias (participant decision and motivation)
> Physical measurement bias (e.g., meter bias, sensor placement)
20 The evaluation team found the measure life input assumptions to be within range of industry standards and
similar programs offered in other jurisdictions (e.9., The Database for Energy Efficient Resources (DEER),
itll.i/Ag.:"*rr'.er:ei:g]'.ca,Bgv&feer/). The evaluation team expects to monitor and refine these input assumptions in future
evaluation cycles based on primary data collection activities.
Fage 14
hI&V}TANT
Rocky Mountain Power
Exhibit No.5 Page 1226 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
> Analysis assumptions (e.g., weather and microclimates that differ from conditions reported at the
weather statiory farmer behavior )
The evaluation team remained cognizant of these issues throughout the evaluation process and adopted
methods to reduce the uncertainty arising from these sources, thereby improving the validity and
reliability of study findings. Key uncertainty sources and mitigation strategies are discussed further
below.
3.2.1 Reducing Uncertainty from Sample Selection Bias
The problem that selection bias creates for program evaluation is recognized by evaluators. Although
projects were chosen in the impact evaluation sample according to prescribed protocols, bias may have
been introduced if the selected projects did not choose to participate in the evaluation effort. In an effort
to minimize non-response bias, the evaluation team established and implemented the following
recruitment protocols:
> Notified participants as early as possible in the evaluation process.
> Accurately characterized M&V activities and the duration of the evaluation process.
> Expanded analysis to include entire participant population.
The intent of these protocols was to ensure that the impact of sample bias is mitigated to the degree
possible and that the sample accurately reflects the participant population.
3.2.2 Redueing Uncertainty of Physical Measurement Error
There is inevitably some error associated with all physical measurement. For the impact evaluation of the
Irrigation Energy Savers program, electrical spot readings were collected using a Fluke Power meter.
These measurements were repeated across each input phase to allow for multiple measurements per site.
In rare situations a power measurement seemed out of the expected range, in these situations another
measurement was taken. Systems operating with a high-leg were measured using a three-phase power
reading.
HOBO logger data files were manually reviewed to ensure data consistency and reasonableness.
Flow readings were collected with a highly sensitive ultrasonic flow meter that was recently calibrated.
3.2.3 Reducing Uncertainty ot Site Visit Analy$is Error
There are several opportunities for biases in Site Visit Analyses that may compound the error and
uncertainty of eaaluated savings estimates. The evaluation team adopted the following protocols to
minimize uncertainty from engineering analysis error in this study:
" All project analysis findings were peer reviewed to ensure that consistent methods and
assumptions were used throughout the impact evaluation.
" The evaluation team developed data collection protocols that yielded appropriate inputs into the
analysis models and reviewed all field observations with the evaluation team. Collectively, this
served to reduce potential modeling error in this study.
3.3 ProcessMethoilology
This section describes the methodology used to complete the process evaluation. First, the section
describes a high-level overview of the steps taken to collect and analyze the data for this evaluation. This
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Roclry Mountain Power
Exhibit No. 5 Page 1227 ot 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
is followed by a list of the research questions that guided the evaluation. Next, the section provides a
detailed description of the data collection activities, and concludes by describing the methods used to
analyze the process data.
3.3.'l Overview of $tsps in the proce$s evaluatlon
To meet the objectives of this evaluatiory the evaluation team undertook the following activities:
Process Evaluation Research Question Development. Key evaluation questions were established
from the development of the 2009 - 2011. evaluation plan with Rocky Mountain Power staff.
Program Documentation Review. The evaluation team reviewed program documentatiory
including regulatory filings, brochures, application forms, and the program website.
Logic Model Development. The evaluation team worked with program staff to define a logic
model for the program that describes the intended program design, activities, outputs, and
outcomes.
Process Data Collection Activities. The evaluation team collected primary data through
interviews with program staff and vendors working with the program, as well as telephone
surveys with participating customers and with non-participating customers.
Process Data Analysis and Synthesis. The effectiveness of the program processes was assessed
by analyzing program tracking data, in-depth interview data, non-participant survey data, and
participant survey data.
3.3.2 Frocess Evaluatlein Research Questions
Discussions with program staff and a review of the program theory and logic identified six overarching
research questions to guide the process evaluation.
1. \A/hat are the program goals, concept, and design? Are they based on sound theory and practice,
and, if not where are the gaps?
2. Do program memagers and administrators have the resources and capacity to implement the
program as planned, and if not, what is needed?
3. Is the program being delivered as planned and described in the program logic model, and if not,
how and why? Program outcomes and key indicators are identified in Table 8.
Is the program reaching the intended target population, and if not, why? Specifically, are eligible
customers aware of the program, how are they becoming aware, and what is the program's
influence on their actions?
\z\rhat barriers are preventing customers from taking actions to reduce energy consumption and
demand, and which jeopardize program cost-effectiveness?
Are participants achieving desired outcomes, and if not, how and why?
These questions were explored through a mixed-methods approach. Table 11 shows the overarching
research questions and associated data collection activities. Data collection activities were analyzed to
identify findings, which were then used to answer the overarching research questions.
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Exhibit No. 5 Page 1228 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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Program Documentation Review
3.3.3 ProgramDocumentationReview
The evaluation team reviewed program marketing materials, program manuals, training and
communication manuals, annual reports, previous evaluations, and project tracking data. This archival
data review identified how the program is marketed, how trade allies are supported, and how the
process for enrollment, administration, and tracking works.
3.3.4 LogicModelDevelopment
Based on the program documentation review and interviews with program administrators, the
evaluation team developed a draft logic model. The program logic explains how the program is designed
to overcome the barriers that the utility is targeting. Logic models illustrate the flow of activities that
create needed behavioral outputs, which in turn achieve desired outcomes over the course of the
program. Activities are actions taken by the program administrators or contractors, as part of the
program, such as: reviewing applications, developing and presenting reports to customers, or verifying
installations. Outputs are measurable or verifiable tasks that result directly from the program activities.
Outcomes can be short, medium, or long-term, and they are the result of the activities and outputs. The
logic model was reviewed with program administrative staff and revised with program staff input. The
logic model is included in this report as Figure 1, in Section 2.5.
3.3.5 Process Data Collection Activities
The process data collection activities are described in this section. Program staff interviews were used to
support development of the program overview and logic model. Findings from the other three data
collection activities are presented in the findings section and then symthesized to draw overall
conclusions and recommendations for the program.
3.3,5.1. Program Management and Ailministratioe Stalf lnteraiews
The evaluation team interviewed a program manager and the third-party program administrators. These
interviews were used in the development of the program logic model. The objectives of interviews with
key program staff were to:
> Understand the design and goals of the program;
" Understand any program changes that were implemented going into the 2009-2011. cycle, and
any changes that occurred during this cycle;
" Identify program strengths from the program staff perspective;
> Identify program weaknesses and opportunities for improvement from the program staff
perspective; and
" Identify other actionable ideas the program staff hoped to gain from the evaluation.
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Rocky Mountain Power
Exhibit No. 5 Page 1229 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
3.3.5.2 Participant Sunteys
Participants are irrigation class customers who completed an Irrigation Energy Savers project between
2009 and 2011. Surveys with participants specifically addressed the following questions in support of
addressing the process evaluation research questions:
" How do customers come to participate in the program?
, How satisfied are customers overall with the program, including application materials,
inspections, and the incentive?
" What is the extent of program influence on customer actions, including free-ridership and
spillover?
> \A/hat barriers are customers facing that prevent increasing energy efficiency?
" What kinds of commercial and industrial customers are participating?
The evaluation team defined the unit of analysis for Irrigation Energy Savers as a project at a site. Projects
were sorted by subprogram in which the customer participated, from the subprogram with the fewest
participants (system redesign) to the subprogram with the most participants (equipment exchange). For
each site, the evaluation team focused the participant survey based on this hierarchy. For example, if a
participant completed a system redesign, purchased pivot and linear upgrades, and exchanged
equipment with the program, that participant would be asked about system redesign; participants were
asked about equipment exchange if that was the only way that their site participated. There were 851
completed projects at 528 sites during program years2009-2011. In May and June of 2012, the evaluation
team surveyed 66 participants. At 90 percent confidence, this represents a precision of +/- 9.8 percent.
3.3.5.3 Non-participant Suroeys
Non-participants are irrigation customers on rate schedule 10 who did not participate in any Rocky
Mountain Power demand side management program during the 2009-2011 program years. Non-
participant surveys targeted non-residential portfolio level considerations through the following
questions:
, Are non-participating customers aware of the programs?
,, Why are they not participating (if they are aware of the programs)?
> What energy efficient projects are non-participants installing (outside the programs)?
" What barriers are customers facing that prevent increasing energy efficiency?
There were 4,413 non-participating irrigation customers in Idaho.2l In May of 2012, the evaluation team
surveyed 73 of these customers, and all 73 were eligible for this program. At 90 percent confidence, this
represents a precision of +l- 9.6 percent.
3.3.5.4 Trude Ally lnteraiews
Trade allies are vendors, contractors, or distributors who have signed a participation agreement with
Rocky Mountain Power to become part of the IEA. The evaluation team defined active trade allies as
those in the IEA who had completed at least one Irrigation Energy Savers project between 2009 and 2011.
Interviews with active trade allies specifically addressed the following questions in support of addressing
process evaluation research questions:
21 The count of non-participating customers - precision is based on total counts of irrigation class customers, provided
by the Company, minus program participants. The non-participant sample was drawn from a data set of contact
information for a subset of non-participating customers, also provided by the Company.
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Rocky Mountain Power
Exhibit No.5 Page'1230 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
, How are trade allies becoming aware of the program?
> How well does the trade ally participation agreement meet their needs?
, How are program operations communicated to trade allies? How is training provided? Is this
communication and training effective (do they understand the program)?
> How satisfied are trade allies with their role in the program? What would they do to improve it?
> Do trade allies who participate see value to their business? Can they describe the effect on their
operations?
" What kind of energy efficient sales are they seeing outside of the program (spillover)?
The evaluation team identified active trade allies using information from the program tracking database,
program staff interviews, and participant surveys. Senior evaluation team staff who are knowledgeable
about the program and appropriate technologies, interviewed six out of 11 active trade allies in June and
|uly of 2012.22
3.3.6 Process Data Analy$i$ and $ynthesis
The process data collection activities included both quantitative and qualitative data. The evaluation team
used statistical software, specifically SPSSTM (formerly Statistical Package for the Social Sciences)
to analyze the survey responses from participants and non-participants. Interview responses from trade
allies were analyzed directly as textual data. In both cases, the evaluation team reviewed data for missing
or erroneous entries. Analysis included recoding data in some instances to disaggregate "othe1'
responses or to combine similar responses into one category. Where appropriate, the evaluation team
tabulated frequencies of responses. After data from each data collection activity were analyzed
individually for findings, the evaluation team identified common findings to synthesize the process
findings across data collection activities.
22 The evaluation team offered a $50 gift card as an incentive to complete the interview.
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This section summarizes the Impact Evaluation findings for each prol'ect included in the 2009-2011
evaluation sampling framework. The Project-level savings estimates informed the overall Program-level
realization rates for energy savings. These findings provide Rocky Mountain Power staff with the
feedback they need to improve the program and to meet the objectives of the Idaho Public Service
Commission by providing an independent quantitative review of program achievements.
This section summarizes the two methods of Impact Evaluation findings. First is the summary of the Site
Visit Analysis findings for each project included in the 2009-2011 evaluation sampling framework. A
summary of the measure level Billing Data Analysis is provided second.
Due to this measure's sensitivity to environmental and operational factors, the result's precision levels are
outside the normal range of 10 to 20 percent. Therefore, this program is unique in that a combination of
both the Project-Level Site Visit Analysis and the Measure-level Billing Analysis are blended into the
Eoaluated program-level savings. The final savings values are selected based on whichever of the two
analysis methods provided the best statistical precision for a given measure. These final, evaluated results
are outlined in Section 4.1.3.
The Evaluated findings provide Rocky Mountain Power staff with the feedback they need to improve the
program and to meet the objectives of the Idaho Public Service Commission by providing an independent
quantitative review of program achievements.
4.L Analysis Gross kWh Saoings
This evaluation applied two rigorous, industry-accepted methods. The Evaluation Team utilized both a
SiteVisit Analysis (based on data collected during actual participant site visits) as well as a more
comprehensive Billing Data Analysis which included billing data from all program participants. The Site
Visit Analysis combines IPMVP options B & C; the Billing Data Analysis complies with IPMVP option C.
Bofh methods indicated a high degree of uncertainty regarding program energy savings.
4.1.1 Results from the $ite Visit Analys!*
Of the projects that participated in the 2009-2011 program years, 58 projects (representing LL.5 percent of
reported savings) were included in on-site verification activities.
The following table presents energy impacts and realization rates by measure group. These results are
based on the Site Visit Analysis and provide both realization rate and analysis precision interval.
Rodry Mountain Power
Exhibit No. 5 Page 1231 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
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Roclq Mountain Power
Exhibit No. 5 Page 1232 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Equipment Exchange
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Evaluated realization rates are provided at the Measure-level and are outlined in Section 4.1.3.
4.'|..2 Results frorm the Billing Data Analysis
In total, billing and measure installation data was available for 527 sites that participated in the IES
Program. The billing data provided for the analysis spanned the period from ]anuary 2008 until
September of 2012 and included the k\AIh charged to each site and meter during each billing cycle.
According to the program tracking database, the earliest measure was installed in April of 2009, while the
latest measures were installed in December of 201.1.. This means that for all program participants in the
model for which there is uninterrupted billing data, the analysis contains at least one full growing season
of billing data prior to measure installation and almost an entire growing season of data after measure
installation.
As part of the billing analysis, months during which sites used little or no electricity for irrigation were
deleted from the data pool. The analysis showed that over the 57 month period for which billing data was
available, the robustness of the model could be improved by eliminating billing periods from November
through April during which energy use for irrigation was almost unanimously zero. Figure 2 below
shows the average daily k$/h use across all sites by calendar month according to the billing data.
Figure 2. Average Dail"v kWh by Billing Month
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The billing data provided to the evaluation team was cleaned in other ways to prepare it for inclusion in
the billing analysis. Transition months were noted in the dataset, which flagged billing cycles that
spanned the period of time during which a measure was installed at a particular site according to the
tracking database. These billing cycles were removed from the analysis because they contain a mix of pre-
and post-installation data that cannot be properly separated in the analysis. As Figure 3 shows, the
majority of measure installations happen during the growing seasory which further necessitates the
removal of these months from the analysis. Additionally, it is possible that measure installation during
the growing season may delay the time it takes for a farmer to fully adjust their farming and irrigation
practices to the newly installed measures.
Figure 3. Number of S{easure Installations by ,\{onth
200
150
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Rocky Mountain Power
Exhibit No. 5 Page 1233 of 1365
Case No, PAC-E-I4-07
\Mtness: Kathryn C. Hymas
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Additionally, the amount of electricity used at a site over the course of a billing cycle was converted to an
average daily electricity use to compensate for variations in the length of billing cycles across months and
across sites. For this reason, the first billing cycle for each site was removed from the analysis because the
number of days in the cycle could not be confirmed. Similarly, annual deemed savings values were
converted to daily savings rates based on the number of days in the irrigation season as described above.
The results of the Billing Data Analysis using annual energy use as the variable of interest (Model L) are
presented in Table 13 below.
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In total, the billing analysis found statistical significant impacts for five out of the ten groups of measures,
and seven out of ten measure groups when measured deemed savings were incorporated into a
statistically-adjusted engineering (SAE) regression model. Most significantly, both analysis models
estimate electricity savings for drains, sites associated with gravity system conversion, and other system
redesigns in excess of 80 percent confidence, often higher. Sprinkler packages and gaskets also produced
results that were consistently significant. However, the billing analysis revealed a tendency for the
installation of new sprinklers and gaskets to produce an increase in average electricity use per site. This
increase in electricity usage may be due to a selection bias as previously discussed or some other
confounding factor, such as a high coincidence of installation between two or more measure types that
makes it more difficult to distinguish impacts from one measure over the other (discussed below).
There are several explanations for why the billing analysis was unable to achieve statistically significant
results for all measure groups. The first reason is the lack of a distinct control group to use as a
mechanism for constructing an energy baseline that is comparable in aggregate to the treatment sites in
all ways except for measure installation. When a randomized control trial (RCT) is not possible, the
variation in adoption (VIA) approach used in this analysis can be a reasonable substitute for constructing
a baseline. However, this approach works only to the extent that late adopters are comparable to early
adopters in all ways except for the time of measure installation. With the inherent heterogeneity among
customers in the agricultural sector, this assumption of comparability is less likely to hold. Differences
could also be compounded by any selection bias present in the data that influences the time during which
a farmer chooses to get measures installed. This may further make program participants less comparable
from one year to the next. Future billing analyses would likely benefit from the construction of a separate
control group, perhaps using matched control sites, as a baseline for calculating measure savings.
The relatively small number of installations of some measure types is also a factor contributing to the
levels of significance on estimated savings and realization rates. Figure 4 below shows the number of
measures installed over the three year program period. Measures that tended to yield less significant
energy savings estimates were often those with the lowest installation counts (pressure regulators, pump
upgrades, VFD and pump upgrades). Though a large number of measure installations is not necessary to
achieve significant impact results (as evidenced by the results for sites participating in gravity system
conversion or other system redesigns), more occurrences of installation does decrease the magnitude of
impacts required to achieve statistically significant results and helps to offset the negative influence of
site heterogeneity and noise in the data that can lead to insignificant results.
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Rocky Mountain Power
Exhibit No. 5 Page 1234 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C, Hymas
Page 33
N$VITANT
Figure 4. Number of Sites rrith Measures Installed
Nozzles
Gaskets
Drains
Sprinkler Packages
Pressure Regulators
Gravity System Conversion
VFD
Pump Upgrade
VFD and Pump Upgrade
Other System Redesign
s0 100 150 200 250 300 3s0
Number of Sites with Measure lnstallation
Source: Program Tracking Database and IES System redesign breakout.xlsx
A billing analysis relies upon variation in the data to parse out the influence of each independent variable
on the variable of interest, program savings. When two measures are frequently installed in combination
with each other, it can become more difficult for the model to differentiate between the impact of one
measure and the impact of the other. This was most true for the measure pair of nozzles and gaskets,
which had correlation of installation of 0.53. In addition to a possible selection bias, this may be an
explanation for the negative savings estimated for gasket installations.
Additional pieces of data related to irrigation practices and energy usage would also benefit any future
billing analysis performed for the IES Program. The fixed-effect model used in the billing analysis
estimates the impact of variables that are not modeled in the equation but impact energy usage. The site-
specific fixed-effect should take account of the characteristics of specific farms and microclimates,
whereas the month-specific fixed-effects should account for monthly/seasonal weather conditions and
economic conditions across all farms. An effort was made early on in our analysis to compare the use of
fixed effects for modeling weather versus modeling weather directly. There was no appreciable
difference in our test results and using the fixed effects increased the models efficienry and degrees of
freedom, so the analysis used that approach.
The lack of crop data in the analysis is a greater concern. Crop plantings are neither time-invariant nor
site-invariant, so they are not accounted for by the fixed-effects. An attempt was made to incorporate
such data into this billing analysis, but crop data was only available for a small fraction of the farms in the
billing analysis and only for a subset of the years being analyzed. Thus, it was not possible to account for
this in the model. Since crop data was only available for a small fraction of the farms in the billing
analysis and only for a portion of the years being analyzed the baseline year of 2008 was not present.
Since one of the most significant factors influencing the amount of irrigation performed on a farm is the
crop that is being grown, data representing the crops grown at each site in each year of the billing
analysis would likely increase the robustness of the model and its impact results. Other data points that
may be of value include soil moisture levels or tracking data showing farmer participation in the IES
program prior to the years being analyzed. It is possible that the inclusion of these or other pieces of data
Rocky Mountain Power
Exhibit No. 5 Page 1235 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
|'iavi$an| irnpai'.l & Plucuss ll,valuntii.rn of
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would help to achieve more statistically significant impact results even without a corresponding increase
in the number of participating sites.
4.1.3 Merger of Results from Two Analysis Methods into Final Evaluated $avings
The final evaluated savings and cost effectiveness are determined using the measure level results with the
best precision. Table 14 provides the measure level precision obtained by both the Billing Analysis and
Site Visit Analysis.
In some instances, the site-visit analysis results were deemed particularly unreliable, as noted by "--" irt
Table 14. This assessment was made using a series of quality control filters that removed projects based
on logical constrains (e.g. a filter is used to remove any project that impacted less than 15 percent of the
total irrigated acreage on a given meter from the sample.)
If the Quality Control (QC) process added to the Site-Visit Analysis results in too few of a given measure
to produce results, the evaluated savings for that measure is based on the billing analysis. The analysis
method used for each measure and associated precision are specified in Table 14.
Per Drain 79% Billing Analysis
Per Nozzle 198"/o Billing Analysis
28%Site Visit Analysis
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4.1.4 Overview of $tatistiqalValidity, Confidence and Frecision
When the evaluation team reviewed the program level results, it was noted that the realization rates for
the IES projects had significantly more variation than found in a typical program evaluation. During the
evaluation it became clear that the precision of the Site Visit Analysis might not achieve the required
confidence/precision intervals of 80120, thus the decision was made to include ALL sites in the evaluation
through a Billing Analysis approach. The measure level results were then assessed using a combination
of approaches that leveraged the benefits of the detail oriented Site Visit Analysis and the ability to
include the largest possible sample size via a Billing Analysis approach. This two-prong approach to
analysis complicates the determination of final precision intervals. Therefore, to assess precision bounds
Ner,igilnt ltrlg:,';:lt & I)lur:gss !!,r,u}uotiun of
lloi*y iylsgnlilin !:ti:i,ver's lrrigi:rtior: Iinerg_r.Savr:rs l:'rr:grari
Rocky Mountain Power
Exhibit No. 5 Page 1236 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
T'able 14. Measure Level l'recisian for llilling Analysis and Site Visit Analysis
Gravity Project 66% 25%
Note, nozzle and gasket measures were often installed as part of a single project.
!:)rrur li{
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at the measure level, the measure group level, and the program level, the team performed a Monte Carlo
simulation. Precision at the measure level and the measure group level are provided as appropriate in
other sections of this repor| however, in summary, statistical review of the program level results found
that with 90% confidence, these results are determined to have an 89'/o precision interval.23
The system redesigns measures are the only projects that pass the statistical validity test, exceeding the
minimum standard of 80120 with 80% confidence that the precision of the results is within +l-17"/o of the
actual impact. VFD projects and the gravity fed, community-scale system redesigns nearly pass the
industry minimum confidence /precision requirements with confidence/precision interval of 80122 and
80/20, respectively.
While the precision intervals for the remaining measure level results are not in compliance with industry
minimum guidelines, the general trends remain valid and several insights into program effectiveness and
recommendations can be drawn to aid in program refinement.
4.1.5 Evaluated Results at the Measure Group Level
The gross valuated savings by measure group are presented in Table 15. The negative realization rate for
Pivot/Linear Upgrades reflects increases in energy use after project implementation that is consistent
across the majority of these projects. Weather and crop factors are accounted for in the analysis but not
details related to participant motivation (selection bias). The precision range for these results does not
meet the objective for results at the 90/10 level. However, the conclusions are statistically valid in that
they are clearly distinguishable from zero and consistent across both analysis approaches.
Savings from the Equipment Exchange measure group are zero because the results appear to be negative
but the statistical precision bounds include a range that spans both positive and negative final impacts.
System Redesigns are providing consistently positive and statistically viable results. The realization rate
for the overall program is twenty-two percent (22"/.)
Tahle 15. Flvaluateei Gr*ss Energ,r, $avings and f.{ealization Rates {ktrlv-h)
Rocky Mountain Power
Exhibit No. 5 Page 1237 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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2a See Section 4.1.5 Evaluated Results at the Measure Group Level
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tr'*ble 15, it is ,qhorvn that System l{.edesigns af.e reliably achieving gireater savings than expected.
t{ow'ev*r, proiects focused on Pivot ancl Linear uBrgrades 4re.not provic{ing statistically significant
savings. All'hough counter intrritive, the post-retrct:it increase in energv use suggested by
Table 15 is supported by secondary research. The USDA2S states "Improved technology alone may not be
enough. Producer adoption of more efficient irrigation technology may increase agricultural water
consumption in several ways.
1.More efficient irrigation systems allow the producer to reduce the quantity of water applied
to a field, often through improved uniformity of field-water distribution and timing of water
applications to meet crop growth-stage requirements. These improvements may also result in
higher crop yields, which generally increase crop consumptive water use.
In the absence of defined "conserved" water rights, water savings from irrigation efficiency
improvements on one field may be applied to additional crop acreage under irrigation.
Unless restricted, "water spreading" over an expanded acreage base generally increases
aggregate agricultural water consumption.
Improved irrigation technologies can alter the economics of irrigation enough to entice
producers to adjust traditional cropping patterns, potentially shifting to more water-intensive
irrigated crops. In the High Plains, for example, higher yields and reduced irrigation
pumping costs with improved irrigation efficiency have prompted a shift from irrigated
wheat and sorghum production to increased acreage in irrigated corn. These types of
cropping pattern adjustments may increase aggregate crop consumptive water use".
4.2 Net kWh Saoings
The evaluation team calculated an average Net-to-Gross (NTG) ratio for the Irrigation Energy Savers
program across the evaluated period, for program years 2009 through 201L. The program weighted NTG
ratio was calculated by weighting a sample of project-level NTGRs by their claimed energy savings
values. The methodology used in this calculation is provided in detail in Section 3.1.5, Net-to-Gross
Estimates. The project level NTGRS are presented in the appendix.
Table 16 lists the weighted Net-to-gross ratios by measure group.
Roclry Mountain Power
Exhibit No. 5 Page '1238 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
2.
J.
Table 16. tdaho lrrigation Hnergy Savers l,Veighted Measure (iroup Net-tn-Gross Ratios
Redesign
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25 Water Conseraation in lrrigated Agriculture:
Research Service, USDA' September 2012.
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Itoi:il, \'t o u.i-: ta i n l:rt:'i.t ei's I i'ri qat i t:n !.ne rgr,'
Trends and Challenges in the Face of Emerging DemandslElB-99, Economic
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Rocky Mountain Power
Exhibit No. 5 Page 1239 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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The realization rates shown above reflect the difference between savings reported at the time of
installation and evaluated savings 1-3 years after project completion. However, customers often modified
their operating profiles during this time interval and, therefore, impacts statistically different from zero
cannot always be attributed to program influence. For example, the agricultural sector is sensitive to
economic changes that influence food prices. Similarly, irrigation equipment functions in an environment
where catastrophic failure is part of the routine. Also, "on the fly" operational changes affect the
reliability of both the baseline and in-situ energy use.
Throughout the impact evaluatiory the evaluation team remained cognizant of these factors which could
influence projectJevel savings. And though the economic downturn did not appear to significantly
influence the projects in the impact evaluation sample, the evaluation team emphasizes that program
savings are continuously evolving due to a dynamic business climate and that the aforementioned
realization rates are a snapshot of program performance in time.
4.3 Cost Effectioeness Calibration and Analysis
The cost-effectiveness of utility-funded programs in the state are typically analyzed using cost-
effectiveness tests prescribed by the Commission.26 For the purposes of this evaluation, Rocky Mountain
Power specifically required the following cost-effectiveness tests:
" PacifiCorp Total Resource Cost Test (PTRC)
> Total Resource Cost Test (TRC)
,, Utiliry Cost Test (UCT)
> Ratepayer Impact (RIM)
,, Participant Cost Test (PCT)
The evaluation team worked with PacifiCorp to understand the PTRC and construct a tool that calculates
the PTRC at measure, program and portfolio level. Table 18 presents descriptions of generally accepted
cost-effectiveness tests.
26 The California Standard Practice Manual is an industry accepted manual; it identifies the cost and benefit
components and cost-effectiveness calculation procedures from five major perspectives: Participant, Ratepayer
Impact Measure (RIM), and Total Resource Cost (TRC). Definitions and methodologies of these cost-effectiveness
tests can be found at httr::/lrr,irrv.enert\,.(.'4.,:()r'lureenlruiiriintlclrx.:urnerrtsibi'rr.'ktlouncii0T-
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T'able 17. Evaluated Net Energy Savings and l{ealization Itates (kWh}
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Rocky Mountain Power
Exhibit No. 5 Page 1240 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Comparison of costs and benefits of
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resources is included?
The evaluation team spent considerable time initializing and validating the cost-effectiveness model used
for this evaluation. This model was calibrated by using prior inputs and outputs from the previous
evaluation cycle to ensure that similar inputs yielded similar outputs. The evaluation team worked
through a range of input assumptions pertaining to avoided cost data formats, financial assumptions
regarding discount and escalation rates, participant costs and benefits, and other input parameters.
Cost-effectiveness inputs were provided by PacifiCorp staff and include program cost inputs, program
savings by measure, and measure life. Table 19 provides an overview of cost-effectiveness input values
used by the evaluation team in the cost-effectiveness analysis:
27 "Understanding Cost-ffictioeness of Energy fficiency Programs: Best Practices, Technical Methods, and Emerging lssues for
Policy - Makers" NAPEE, November 2008. h.ltnlg +,:lf
28 The RIM test is a measure of the difference between the change in total revenues paid to a utility and the change in
total costs to a utility resulting from an energy efficiency program. If retail rates are higher than marginal costs, few
programs that significantly reduce energy consumption will pass this test.
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Inflation Rate
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Rocky Mountain Power
Exhibit No. 5 Page 1241 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C, Hymas
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The following tables illustrate the Costs, Benefits and Benefit/Cost Ratio for the cost-effectiveness tests
used in this evaluation. Impacts were evaluated for 2009,20L0,2011, and for combined 2009-2011 over
four different scenarios: Reported, Evaluated, High and Low scenarios.
Table 20 through Table 23 outline the Evaluated scenario. The tables for the other three scenarios are
included in the report Appendix.
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Roclry Mountain Power
Exhibit No. 5 Page 1242 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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Exhibit No. 5 Page 1246 of 1365
Case No. PAC-E-14-07
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Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
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Exhibit No, 5 Page 1248 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
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Exhibit No. 5 Page 1249 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
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N&VITANT
This section describes the findings from the process evaluation data collection activities. These activities
include the Irrigation Energy Savers participant surveys, Idaho non-participant surveys, and trade ally
interviews. For each data collection activity, this report provides a description of the sample followed by
findings from that activity. At the end of this sectiory findings from these three data collection activities
are synthesized into key process findings and recommendations for the Irrigation Energy Savers program
in Idaho.
5.L Participant Findings
In May of.2012, the evaluation team surveyed 66 participants the Idaho Irrigation Energy Savers
program. Irrigation Energy Savers includes four subprograms: System Analysis and Redesign, System
Consultation and Pump Test, Pivot and Linear Upgrade, and Equipment Exchange.
Customers could participate in as many subprograms as they wished, though each respondent was only
asked about participation in one of them to minimize respondent fatigue. The survey design prioritized
inquiring about participation in the System Analysis and Redesign subprogram. Next, priority was given
to investigating participation in the System Consultation and Pump Test program. If the participant did
not partake in either of these but conducted a Pivot and Linear Upgrade, the questions were tailored to
survey this experience. Finally, if participants only conducted an Equipment Exchange, the survey asked
about this experience instead.
No participants in the program tracking data had completed a System Consultation and Pump Test
without going on to complete a System Analysis and Redesigry therefore, no participants were asked
about the System Consultation and Pump Test portion of the program.2e Note that no program savings
are claimed from the system consultations or pump tests. Figure 5 shows the breakdown of participants
surveyed, by subprogram.
2e The program administrator tracks customers who are interested in System Consultation and Pump Tests separately
from the program-tracking database. No program energy savings are reported from this part of the program, which
offers information to customers.
Novitlcrnt irnpai:t & I)ttictlss ll,vtrlrriltiun of
Roi:k-r, i\4 t: u n til i n libwer's l rri gati on Li nerg.,, Sav evs lLrogram
Rocky Mountain Power
Exhibit No. 5 Page 1250 of 1365
Case No. PAC-E-'14-07
Wtness: Kathryn C. Hymas
Page 4$
\\ i .n\\ \ .,' S rs"-\ A,\ i *$*
sxst\},x\
Roclq Mountain Power
Exhibit No. 5 Page 1251 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
I:igure 5. Breakdown of Par:ticipants $urve1,ed, try Subprogram
System
Analysis and
Redesign
13
Equipment -Exchange \,1,
24
*t*i
*un"
Pivot and
Linear
Upgrade
29
Participating irrigator survey respondents represent small firms, with 24 percent employing fewer than
three individuals during the growing season (as opposed to the harvesting season when employment
may spike temporarily). Only 26 percent employ 10 or more individuals during the growing season, as
shown in Table 24. The mean number of growing season employees is seven for these participants.
Tahle 24. Farticipant Siee {Numlrer of Gr*ra,ing Season Employeesi
Less than 3
11*..luss...tna*{tu.......................iiir.
10 to less than 100
ifl il,.#''.#$s.i$H uuN,,,.r
Greater than 1000
Nd.s* ffi ffi u*AuHffi
.i...'.=
Total
16
29
17
,1tffi,,,
0
66
^to/z+ /o
:::::::::::::::::::::::::::.:a:::::::::::::::::::::::::::::|::::.::iial]!::j:::::: :::j: : :: ]::::]:::::]:]::: ]:::]:: : ] ::::]:]::::::::: :::::::: l::::i!l::::l:i::::::::: :: : llr *dI'!::i:.!i ': l'l::!:*AL-/b !l:::' l-
::::i:!:!:!::i:i:::i!:i::i::::::::::::::!:!::i:::::!::::a:f.ii::.ii;iiariil::i::l::l:::l::l:::,::l::l:::::l:::
26%
i:,: :-O%,,:::ii::
,,:,i:::i,;;:,;:
0%
iiiii"'t:..,.i.r;ry1't':'::':,::,;,:;::::::::::w:::':::'::::::::::::'::::::::::::::,
700%
t:,1:::::::l::i::::::
::.::t:.tt::ttt:tttttt:
Both water and electricity are important operating expenses for participating irrigators. As seen in Figure
6, about one-third of respondents reported that they have water bills that represent 10 percent or more of
their annual operating costs, and more than half of respondents have electric bills that represent 10
percent or more of annual operating costs. Water makes up 21 percent of operating costs for these
participants while electricity makes up about 14 percent of operating costs, on average.
l',i :r v lils ii i I;ri 1,,ra i: i' i\ i) li.rt.'ri:'s lL viii i.i rl i.i r.rtt r-.i'
]lorlr,;r. \4ouni:oin l:'u,r,ei's iii'igtrtliir: l:,rlel'il...Siai,$r's i:'r'r)ii;l*r Fagt 5"1
kt $\t$.s\.+. Nt*s*i\rs\,N$Ls.,'\l\ $
Don't
KnoWNot
Figure 6. Self-Ii.eported Percent of Annual Operating Costs l\lade up by Water and Electric Bills
Sure
12
Sy$ern Analysis and
Reebsiryr
Pivotand Unmr
Upgnath
0
Don't
Know/Not
Sure
15
Equipment
Exclnnge
0
%
Rocky Mountain Power
Exhibit No. 5 Page 1252 of 1 365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Total i
Electric
5.1.'! ProgramSatisfaction
As shown in Figure 7, about two-thirds of participants (44 of 66 participants) were "very satisfied" with
their experience with the Irrigation Energy Savers programi another third (20 participants overall) were
"somewhat satisfied." The two other participants indicated that they were "neither satisfied nor
dissatisfied;" both of these participants had worked with the System Analysis and Redesign offering of
the program.
Figure 7. lrrigation Energy Savers Participant $atisfaction
When asked what changes they would like to see in the Irrigation Energy Savers program, nearly three-
quarters of participants had no suggestions for changes. Those participants who did have suggested
changes for the program offered the following:
" Offer larger incentives (identified by eight participants),
" Reduce paperwork/bureaucracy (identified by three participants),
> Increase clarity about deadlines/expectations (identified by three participants),
" Shorten program timeline (identified by two participants), and
o Increase kinds of incentives offered (identified by one participant).
Less than half of participants (44 percent) indicated they had contacted Rocky Mountain Power with
questions or requests for assistance at some point during their participation in the Irrigation Energy
Nati$ont ltril:ai,i & Ilri.rt:e$s l:,i ah:stiun oi
Itoi:lt-\, ir4t:untsin Itor,.r.,er's lrrigi:itiru !,nerg..,5aveis l:'rDgrari
25%
16
I Very Saiisfed ASomewhal Satisfbd Elierther Satisfied or Dissatisf!€d
Fage 51
Savers program. AII of the participants who contacted Rocky Mountain Power indicated that the
representatives they contacted were knowledgeable with respect to the program and its requirements and
were timely in addressing questions.
5"1.2 Frogranr Awareness and Motivation
Nearly 30 percent of participants learned about the Irrigation Energy Savers program from trade allies,
and another 18 percent learned about it directly from program administrators, as shown in Figure 8.
Figure 8. Hon* Farticiptrnts Heard ahotrt lrrigation Encrrgy- Savers
Rocky Mountain Power
Exhibit No. 5 Page 1253 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Rocky Mountain Power printed materials
Roctcy Mountain Power website
Previous participation in Rocky Mountain Power programs
Other (single response each)
Don't knoWNot sure
Word of mouth
Rocky Mountain Power representative
Trade ally, vendor, or contractor
0To 10o/o 20Yo 30o/o 40o/o 50o/o 600/o 70o/o 80o/o
Percent of Respondents
90Yo 100o/o
I \44ren respondents were asked why
frequently mentioned reason was to
on electricity bills Table 25.
their organizations decided to participate in the program, the most
replace old or poorly working equipment, followed by saving money
To replace old or poorly working
',,10 uu"[.,,#*.51 on electric bills
To obtain an incentive
:::,:,,,:::::
To acquire the latest technology
:',r,,,1.O,6&V€.,l4IiI't€f '::::::j:: :::::.'. .... : .. :', ,i,,,,:,:r, :. ::::::::i::::::::::i:i:i::::.::.:.:j::..:.:.. :i::::::i
Other (single response each)
Dodl:Kn;;1Nilil;,,,;,,,:iii:ii;,i:iii:,,,
equrpment
.ia:ttlri i.,,,.,.,,,,,,,,i,,iii
48%
iiiiiiiiiii]iiii!:iiiiiiiii2e,v*:i:iiiiiiiii
72%
::,,,:,:i:,,:1d+s,,:,:,:,:,:,
: "!:ii'::::'le::E:!:!:!:!
ll:ti:i:l:i::iiiititiiiiitit:ltiti:::i:i:iiiiiiiii:iii:ii;:
5"h
:l:]::]:::::::::::::lii.l$vt:i|iliii:]:
6%
=€-=Total
30 Multiple responses were allowed. The percent of respondents indicates the percent of respondents who identified
the motivation listed as a reason for participating
I"l o v i$il ri t Lx p ;.: i': i 8i ltr:i.rt-lr.-ss iir v a h.i o ti ui-r r,.i
]ioi.il.' ir4out.'toin !:ttr,vei's iriiHatitln l;.tre.,':11.,.Sai,t1r-ii i:trit;';ri:iiti
Table 25. Rr.ason for Irrigation Energy Savers Prograrn Participationstl
ili:iit $l
N,&V$TATST
5.1.3 Proqrann Process and $atisfaction
Participant responses indicate that the Irrigation Energy Savers program is working well. Each
subprogram relies on a different process, and these are discussed separately here.
5.1..3.7 System Analysis and Redesign
A project may qualify for System Analysis and Redesign if it includes adding capacity, changing the
water source, or replacing part or all of the irrigation system. The evaluation team focused surveys on
system analysis and redesign for 13 participants. About half (six) of these participants indicated that they
qualified because they were replacing part or all of their irrigation system; four were changing the water
source; and two were adding capacity. The other one did not provide a specific qualifying reason.
With this portion of the program, an irrigation specialist goes out to the participant's site to complete a
comprehensive project analysis and then provides a written report at no cost to the participant. All 13
participants were satisfied with this visit. All 13 respondents found the report that documented findings
from the project analysis and recommended efficiency improvements to be valuable. All 13 respondents
that participated in the System Analysis and Redesign program indicated that they received their reports
from the analysis in time to inform their energy efficiency improvement decisions.
Participants were asked if they had taken all of the actions indicated by the report. A large proportion of
respondents (11 of the 13) made all of the recommendations present in the report provided as a result of
participation in the System Analysis and Redesign. Two did not make all of the recommendations. All 13
respondents were satisfied with the overall performance of their redesigned system--10 were "very
satisfied," and three were "somewhat satisfied."
Ten of the 13 respondents who were surveyed about the system analysis and redesign portion of the
program recalled a post-installation inspection to verify their installation. Nine of these participants were
"very satisfied" with the post-installation inspection, and one was "somewhat satisfied."
5.1.3.2 Pioot and Linear Upgraile
Rocky Mountain Power provides cash incentives to participants for upgrades of worn pressure
regulators, low pressure drains, and sprinkler packages on pivot and linear systems. The evaluation team
focused the survey on pivot and linear upgrades tor 29 participants. From the participant perspective, the
program includes working with a vendor, installing equipment, and notifying the program administrator
of the completed project, as shown in Figure 9.
Rocky Mountain Potr/er
Exhibit No. 5 Page 1254 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Nari.i:ant imy:nci & Illr;urss ll,valuati*n of
Roi:i.'.y \4r:untoin ll\1.r,er's Irrigirtitln liirer:glr 5avers l:'ri:gratn Fage 53
NJ\V$IAI\T
Rocky Mountain Power
Exhibit No. 5 Page 1255 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
liigure 9. Flow Chart af Pivot and Linear Upgrade Proeess
Eliglbte
Curtomere
P*ticlpettng
Deelers
Frogarn
Admlttl*reoor
Source: Rocky Mountain Power Irrigation Energy Savers Manual
\A/hen asked, 27 of 29 participants who completed pivot and linear upgrades indicated that their vendor
had been helpful; the other two were not sure. All29 participants indicated that they had installed the
pivot and linear equipment, and the installed equipment is still in place.
Nearly two-thirds of the participants (18 of 29) who were surveyed regarding pivot and linear upgrades
recalled a post-installation inspection to verify installation. All 18 of these respondents were satisfied
with the post-installation inspection; 10 were "very satisfied" and eight were "somewhat satisfied."
5.7.3.3 EquipmentExchange
The evaluation team focused the survey on equipment exchange for 24participants. From the participant
perspective, equipment exchange involves bringing old or worn equipment to a participating dealer,
completing an applicatiory and installing new equipment that is provided at no cost to the participanf as
shown in Figure 10.
.Novi$ilnI impai':i & I)locilss lllvaii:otilrrt oi'
i{or:kr, \4r:untilin l:tc:rver's lrrig;rtir:n li.nrrg*,, Sai'ets l:'rr:grarrt iruge 54
NI AV}TANT
Figure 10. Florr Chart of the Equipment Exchange Process
Eli$ble Pertlclpatlng PrcgnrnCuetomers Dedere Admlnlstnrtor
Source: Rocky Mountain Power Irrigation Energy Savers Manual
Participants were asked if they found their vendor to be knowledgeable about the program; all 24
participants agreed that they did.
Participants can exchangenozzles, gaskets, and drains through this program. For the participants
surveyed, most had exchanged only gaskets, as shown in Table 26. Eighteen participants had exchanged
gaskets; 10 had exchanged nozzles; and four had exchanged drains.
N sr,itlon t lv1 1:nr'. I 6i l)nir:rlss ll, r'aiu a ii on oi:
Iloi:I.::-rr \4ountilin l;toi,ver's lri'igation Liner:g',, Sarreis i:irt)?rarl
Roclq Mountain Power
Exhibit No. 5 Page 1256 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage 55
\
N AV $ilA N-}-
Roclry Mountain Power
Exhibit No. 5 Page'1257 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Gaskets & Nozzles
Total
Every respondent except one said that they installed the more efficient nozzles, drains, or gaskets they
received the same year the exchange took place, as shown in Table 27.The one respondent who did not
install all of the drains in the same year stated that not all of them were working. All24 respondents
indicated that at the time of the survey, the program equipment was still installed and functional.
Yes, installed equipment in the same year as equipment exchange 10
Total
As shown in Figure 11, nearly all participants are "very satisfied" with the equipment. One respondent
was "very dissatisfied" with the nozzles received through the program; however, this respondent
declined to explain this rating.
Figure 11. Satisfaction vrith Nen' F.lxchanged liquipment
Drains (n=4)Gaskets (n=18)
2
r Very Satisfied
e Neither Satisfied nor Dissatisfied
ESomewhat Satisfied
N Somewhat Dissatisfied
trDon't KnoWNot Suresl Verv Dissatisfied
N o r, iliil n t irrr pa i:i $i ]>rt;criss ll: r, a].r.i a ii r:r': oi'
iioi:i;:-v \4 ou n to i n i:\nrrer's l rri gati t:n L;,n e1lri Sa v ers l:')rogral-\
24
18
1810
'l'atrle 26. Equipment Exchanged through the Program
Table 27. Irrstallation of Exehanged Equipment
Page 5S
N$VI TANT
Less than half of the participants (10 of 24) who completed an equipment exchange recalled a post-
installation inspection to verify installation. All ten were "very satisfied" with the inspection.
5.1.4 Programlnfluence
The evaluation team asked participants several questions about the program influence on the project that
they completed with the Irrigation Energy Savers program. These questions can be grouped into three
general areas of influence: factors influencing the actual equipment installed as part of the project
(Influential factors), what would have happened in the absence of the program (Free-ridership), and the
program's influence on future energy efficiency purchases (Spillover).
5.7.4.7 lnfluentialfactors
Respondents were asked how influential eight factors were in their decision to exchange equipment,
purchase and install new equipment, or make improvements after a system analysis with the Irrigation
Energy Savers program. They were asked to rate the importance of each factor on a scale of one to five,
with one being "not at all important" and five being "extremely important." The factors of familiarity
with equipment and the program incentive or equipment provided at no cost were both "extremely
important" for more than half of respondents. As shown in Figure 12, there were mixed responses for
most factors.
Figure 1.2. Factors lnfluencing Proiect Decisions3t
Rocky Mountain Power
Exhibit No. 5 Page 1258 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
i
Familiarity with Equipment
Program lncentive/No Cost
Previous Participation
lA/ater Saving lnformation
Vendor Recommendation
Corporate Policy for Energy Reduction
Energy Savings lnformation
lnformation on Payback
0 5'10 15 20 25 30 35 40 45 50 55 60 65 70
Count of Respondents
i:: Not Asked
mNot lmportantAtAllfi NeutralNExtremelv lmoortant
il Don't KnoWNot Sure/RefusedsSomewhat UnimportantllSomewhat lmportant
5.1..4.2 Free-iilership
In order to determine to what extent the Irrigation Energy Savers program affected installation decisions,
the survey team asked respondents what would have been different about their installations were the
program not an option. Nearly half of the projects (31 out of 66) would have been completed with the
31 Importance of Water Saving Information was asked of participants surveyed regarding Equipment Exchange and
Pivot and Linear Upgrades (53 respondents). Importance of Information on Payback was asked of participants
surveyed regarding System Analysis and Redesign (13 respondents).
N trr ita n i itri 1:a i', i -* Pi:lrcr-rss l:, rrtr l i.i s ii.lrn oi
]tor:l':v \4i:untain i::sr.r;er's .[rrigirlii:n {inerg.,.5ar,ers .l]rr:rgrarn Page 5?
xAxltilArl'*T
same efficiency and to the same extent within the same year. Another 17 percent (1"L out of 66) would
have completed the project in the same year but to a lesser extent or at a lower efficiency level. About 13
percent of projects would not have happened at all without the program. Details of how participants
described what they would have done if the Irrigation Energy Savers program had not been available are
provided in Table 28.
Rocky Mountain Power
Exhibit No. 5 Page 1259 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table ?6" Projects in Ahsence of lrrigatiun lrnergy Savers
Yes
iiiiiN*
No
ffiii
::l::lll lr
i:;t'itl:
No.;:; :;,;;:;,;,;1,,,,,i: ::i:iii;
. :' :.:. ::::: ::::: : :jj : : :!: :::!:
No
ili:''. .. Yes:ri:iriririr::i:: r
:t:itrt:t:t:ttt:::::t::i;;t:tt::::t:::l*i:l::ji:::i:i:i:::i;i:iLi:ti
Yes
:::: lil I :: :,. l^;ll: .:::i::ili. iii:::;': .r. . .,: :'I€Sririr:rl ,,:::,:
:i:ii;i;::::::::::ii:ltlt::::::::::::::::::::::::::::::::::::::l:i::I::::i:!
Yes
ii:ii:. : Y.€S:::,r:r:ririri:r:r
:::t::::::::::::t ::::::::.1.:jt::.t:i::t:t:t:t:t:t:::: ::t:::
Yes
, :, ., .. ::,:: '.';;::':1': :
tltlt:tl'tltltltltltl:lt::lt:tltltltltl:ltltltltl::tl:ltltlt:tltllt:ttt:t::,:lli.:;::a,:lt:::::
Yes
,. ::.:.r ,ygs
iial:a:i!::i!!:triiiiiii iiiiilii:i:,!iiiiiili;ii'j:it=:::::::::::::
Yes
**,L.#t
....
Yes
$ffi hfia*ra;...,.,...,.........
Standard
i:i:,r :::i:i!:!:!:!:!,
!:{e.*.:!:!:!:!:!:!:!:!:!: :!:l
iiiiiirr:::::i:iiiiiiiiiiiiiiii:ii:rrri:
No, Less
[!€S:!:!:!:!:!:!:!:,,,. !:!:!:
il]lii::tiiiiiiiiiiiiiiiiiiiiiiiiiiliiiiii
No, LessNo
hIrl
No
:::::::::::::::i::.:::::::::::::::::::::::::::::]::]:::
l........[lo................::i.]li.:
Not Sure/
Refused
t:ii:tn:i:::,,:,:ii:::it:ittt:t:ttttttttttttttlN6..ri*.i:..........i.t
Not Sure/
Refused
Total
In some cases, participants provided inconsistent responses between their stated influential factors and
what they would have done without the program. For example, if the respondent stated that the financial
incentive was extremely important to their decision but that they would have installed the exact same
equipment at the same time without the program, the interviewer asked them to describe in their own
words what impact the program had on their decision. These responses were used to adjust self-reported
free ridership scores.
In addition, the program free-ridership was adjusted to account for prior program participation. Given
Rocky Mountain Powels efforts to cross-promote the entire portfolio of energy efficiency programs, a
respondent's prior participation in a Rocky Mountain Power program may have been influential in their
decision to participate in the current program. Ideally, this influence would be attributed to the prior
program as spillover savings since that program was responsible for the influence. However, given the
portfolio-level marketing approach that Rocky Mountain Power implements, respondents are unlikely to
be able to identify the prior program by name. Therefore, the evaluation team will attribute the savings
credit to the current program. This is done by reducing free-ridership scores by 50 percent for those who
say that the previous participation was "extremely important" and by 25 percent for those who say that
the previous participation was "somewhat important" in their decision.
After adjusting for inconsistencies and previous participatiory about 17 percent of participants (11 of 66)
were classified as full free riders. These participants would have completed the same project within the
same year without the program as they did with the program. About 42 percent of the participants are
partial free riders; they might have achieved some savings without the program, but they would not have
achieved the same level of savings as with the program. Another 41 percent of the participants are not
i"i o v ii.:ari i Itri i:,';: i. t rk l)r:t.rcess iL v r li.r o ti i:n oi
l\or:lir,.' lr,iouiitain i:'or.r,er's iiriR;ition ll,lrt.lri1:. Saveir:.: i:tfrlill'iirnr
66
Fugr 5$
free riders - they would not have achieved any savings without the program. A breakdown of free
ridership classifications is given in Figure 13. Note that there are only 11 projects that would have been
completed in the same manner without the program, compared to 29 projects for which the respondent
initially stated that they would have completed the same project without the program; this is due to
adjustments made for inconsistencies and previous participation influence.
Figure 13. Program Free Riders, try .lrrigation Energy Sirvers Suhprogra-rn:'2
Rocky Mountain Power
Exhibit No. 5 Page 1260 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Full Free
Riders
Full Free
Riders
E
Non Free
Riders
5
4
Partial Free
Riders
14
Equipment Exchange (n=24)Pivot and Linear Upgrades (n=29)
Non Free
RidersI
Partial Free
Riders
2
System Analysis and Redesign (n=13)All Participants (n=66)
5.1-.4.3 Spillooer
There is some evidence that the Irrigation Energy Savers program is influencing additional energy
efficiency irrigation installations. Additional detail on both "like" and "unlike" measures installed by
respondents after participating in the Irrigation Energy Savers program is provided below.
Half of the respondents who completed additional projects had received assistance from Rocky Mountain
Power or another organization; therefore, their savings are not considered influenced by the Irrigation
Energy Savers program. The other half, were asked the extent to which they agreed with the statement
" My experience with Rocky Mountain Power's lrrigation Energy Saaers program influenced my decision to install
additional high efficiency equipment on my ou)n." The majority of these participants agreed that the program
influenced their decision, as shown in Figure 14.
32 Graphs are shown for all three sub-programs discussed in surveys; however, sampling and statistical significance
are for all participants in the program. Due to different responses, it may make sense to conduct a larger survey with
sufficient sample at the subprogram level in the next evaluation.
|i 3',r lgiin i lrr: p;l i:t dr l)r:t:r:rss ll, r'al r.r o ti on r:i'
iior:i,.y \'it:ri-rniirin lltulvei:'s Irri:Ii.rtir:rn linergr. Sar,€i:s l:'ri)giarr-r iirnp 59t
,:kNd\V$ilAI\\LJ-
Rocky Mountain Power
Exhibit No.5 Page 1261 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
I4. lrrigation Unergy Savers Program lnfluence on .Addititrnatr "Like" l'rojects
Strongly
Disagree
1
Neither
Strongly
Agree
7
Agree or
Disagree
2
Somewhat
Agree
6
Nearly half (32 of 66) of the Irrigation Energy Savers participants indicated that they had completed other
"unlike" projects after participating with the project discussed during the survey. Installed equipment
included variable frequenry drives for pumps, pivots, efficient pumps, sprinklers, and others shown in
Table29.
::::::::r::r:i:j::::i:r5i::j::i:i::it::::i:::::::::::::::::::::::::::::::::::i:::::::::::::::::::::::::::::::::::::::::iii.i.. msffisuYffi,.,.
New bulbs on equipment
:::::::::::::::::::::::::::::i,,lr, , ::i,:, ,r,,, ,l j :1i:1::: ::,:, :,]::r:::i:::::: r r$rffi+t i:,lXil'liUlllllilllti. : :iiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
Gaskets
1
::::::::i::::i!:l:::::::::::i::li:il:::::::::l::i:::::::::::::::::l:::i::::i:i::i:::::
1
:::::ji,:jj:.i::::::::i:ilii::::i:::;:i;ilti;l:.t:tt::i:ii:t:i::1::::,::::
ll]=::::::::::iifit::::!:;:l:i:il:l::t:::tl:t:tlt:i:tllii:it:il::i::t:ti
1
, .!,r,i:!:!:::.,::!
34
]ust over one-third of respondents (12 out of 32) who had completed additional "unlike" projects received
assistance from Rocky Mountain Power or another organization; therefore, their savings are not
considered influenced by the program. The other 19 respondents were asked the extent to which they
agreed with the statement " My experience with Rocky Mountain Power's lrrigation Energy Sauers program
33 More than one response was allowed.
.1,:' al, illirni Irrr pa i':i & I)riu+ss lLl'+ir.i il ti trr t-ri:
I{oc},.v \.'lounte in iltr:r..uei's .irriglitiotr l-;,r'rexg_rr 5a\,$rs l:rrL}r';riiir)l
'Iable 29. $lfficient "Unlike" Equipment Installed After f'rngrarn Participatione""
New Heads
Fage $0
ii\,J\V$il4}'{T
influmced my decision to install additionalhigh efficiency equipmmt on my outn." The majority of these
participants did not indicate that the program influenced their decision, as shown in Figure 15.
Figure 1.5. Irrigation Energy Savers Prcgra.m lnfluence on Additional "Unlike" Projects trl=19)
Strongly
Agree
4
Strongly
Disagree
2
Somewhat
Disagree
3
Neither
Agree or
Disagree
9
Lr sum, the program appears to be influencing additional efficient actions with program participants;
however, the influence is mostly limited to "like" projects. fust one-quarter of participants who took
"unlike" actions (five out of 19) believed the program to have been influential in their decision; this is
compared to more than three-quarters of participants who took "like" actions (13 out of 16) who believed
the program to have been influential in their decision.
S.1.5 Further Energy Efficiency Opportunities and Barriers
When asked whether there were additional energy efficiency improvements their organizations could
make, 71 percent of all respondents affirmed there were, as shown in Figure 16. The distribution of
responses across sub-programs is similar, indicating that Irrigation Energy Savers participants generally
believe that there are additional improvements that they can make, regardless of the kinds of
improvements made with the program.
lYo
ffi.
Rocky Mountain Power
Exhibit No, 5 Page 1262 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
hy $uh-Program
8o/o i
%.i
Total
i .Y"., could make
t-*--..*...-_-.*-
future improvements El No, could not make future improvements tr Not sure or Refused ii
The 47 respondents that indicated a belief in the ability of their firms to improve electric or water
efficiency were further asked to provide examples of what actions they could take. Potential further
efficiency measures indicated by respondents are shown in Table 30.
.N' alritlon t ini }:n i': t 6x ]lttrt:rss [r, v i:il.li s ti t.rn oi:
System Redesign Pivot and Linear
Upgrades
Equipment
Figure 16. Participant Indication of Further Hnergy Hfficiency Opportunities,
1lYo
I{or1ry i\4 t:un toin i::r:wer's lrri gaiit:n Ii ner:gy Savers l:'rt)1;ra$i Page 51
N$V$TANT
Installing VFDs on equipment 43'/o
illl:iii:lii*u*'iii
Ll"/o
6%
4%
$:Xii iiliiiiiii:::i:x*ffii
:.1::i:laa,i::::::::::::::::::.:::.i:::lii::fi:d:,,:,.,:, .aj,:j,:,:,:,j:,:,. ::,,,:.L,:/d
$.i;lttlll;1liilffi.
Remove hands lines 2%
,ffiii*n**"'-:lii:.:..:,'iliiii:iiii.i:iiiiil:iiiii::i:::ii.iiii.:',,.i.::..ii.: .i::.::i::::::ii:i:i:.:
ao/zlo
Don't know/Not sure L5%
34 Multiple responses were allowed. The percent of respondents indicates the percent who identified the specific
example and does not sum to 100 percent. One respondent identified "more incentives" as an example. This
respondent is included in the count of "Don't Know/Not Sure."
N ol ifi on i tr*iirni':i & I)li.rcuss lilvr:rii.i ati r:r': +i:
itoci,;r, \4r:trtrl'ilin lllt:r.ver's .lriifiatitln li,rlels*,i Sat r:rs l:'lutrnsi
Roclry Mountain Power
Exhibit No. 5 Page 1263 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Tahle 3*. Fotential Further Efficiency- Meaguress{
Fegr'jt
\ l .,-\ \,.' l s'*'' .\ N i ^t*i\i\,\r\\...sr\i\ i
As shown in Figure 17, 40 percent of respondents who indicated that they believed their firms could take
additional steps to improve electric efficiency beyond what they completed with the Irrigation Energy
Savers program did not have plans in place at their firms to implement such projects. Most respondents
with plans in place intended to implement projects with Rocky Mountain Power assistance;43 percent
reported having plans in place and intended to apply for assistance from Rocky Mountain Power, while
13 percent had plans in place but did not intend to apply for assistance from Rocky Mountain Power.
Figure 17. Indication of Plans tt-l [rnplen:rent Electric Efficiency []rojects for Farticipant.g who believe
their Firm has Further Efficiency Clpportunities
N$Yes, plans in place to implement projects - with
Rocky Mountain Power assistance
HlYes, plans in place to implement projects -
without Rocky Mountain Power Assistance
E No, plans not in place
II Don't Know/Not Sure
i
-.,lThese respondents were asked what might prevent them from implementing electric efficienry
improvements. The most common potential barrier, identified by 72 percent of all respondents, was "high
upfront costs." The next most common potential barrier was a "lack of access to capital" with 15 percent
of respondents indicating that was a barrier for them. Table 31 shows barriers identified by Idaho
Irrigation Energy Savers participants.
High upfront costs
iiiiiiiLin$r$-1fr f ttf s(€s$]::tsi:€fFitail
Lack of time
fiael(.of.i otfiatiimji,ffiiiba$in$i8ffirij,pEtrfff,nlanhei,iii,ii. :, :
i
Timing or coordination difficulties
,tbng palthaik pqiiod; slo$, i;ti:of iahrrn , .
Conflicting f inancial obligations
35 Multiple responses were allowed. The percent of respondents indicates the percent who identified the specific
barrier and does not sum to 100 percent.
Roclq Mountain Power
Exhibit No. 5 Page 1264 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 3L. Participant Barriers tu Further Efficienc_v lmprnvernentsss
a10/
rtlii:ii:iiiii:iriiirl:l::::::::i:i::::::i::.;t:::::
i:.ii.iii1,' ,. r::.:.:.:.:::i:iii::iitr;:
6o/"
,]:,:,:,:,:,:,:,:,:,:,:':'':].],:.:,:,:,:,:,:,:,:,:,:,1:':':i'].
:::,:::::t,y€,,,:::::::::::,:, ]
,::::::i:i:::l:::i:l:::::l:,i1,::i:::::::::::::::::i:;:::i
f( nl irlsit t iili 1:..;l i:i $.1 ])r. ct':uss ll,r,i iii: lii un oi'
i{oi*:r. ir"it:tiitioin }:!ttr,ver's irrigi:ititln lirrerg-rr Sar,ors l:'rt)i1ta$r
4%
dnt .:i': .: : ''.1
::ii:iii::i:tii:r:::::::::t::;:!il:ii::jiiif,ijl::;::;::tiir::iiiiiiljliti:ti::::
2%
Fugr ii3
:I\ i ,.{\ \ i I -$** A .\ t ^'r*i\i ."'\ \,t $ S .i\ l\i il\.' \N S\--^{"r\i\ S
5.2 Idaho N on-P articip ant Eindings
In May and |une of 2012, the evaluation team surveyed T3Idaho firms on rate schedule 10 that did
participate in any Rocky Mountain Power programs between 2009 and 2011.
The majority of responding non-participants represent small firms. As seen in Table 32, more than half of
non-participant firms (52 percent) employed fewer than three people. Only one firm had 100 or more
employees.
Rocky Mountain Power
Exhibit No. 5 Page 1265 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
not
Less than 3
'.4.,to.,,1*rsimau..it$ii.iiii.ii.ii:,,ii,i.i
10 to less than 100
.....iii10CI iine5$.,,ihilnii.li0ffi
38
:::::::l:i:::i:i::,:l,l,l,:::,:::::::l
:ifi ilii:tlii:iiiiil:i;iiiii:i
J
:r:iri:::iili;iiiiiiiiiiiiiiii:iii:liiii
iiiiiiiiiiiiiiiiiiiiiii:liiiiiiiiiiiii
0
:::::::::ti:::::i:::i:::::i::::::,:il:,:!:tl:!:!:,:!l . i
:::::::i::::i:l:::li:ililii:tiii:,r::
73
52"/"
i:ii:iagss%
4V"
iiiiiiiiiiiiiiii:iiiiiiiiiiiii##iiiiiiiiii:
0%
i!i:i:i:!r!i!i!i!i!i!i!i!iii!i{tTi!i!iii!i!::,::,::::::,,:,::::::::Iz::/G::::::::
:i:::iii:i:ii::iii:i:iiiiiiiiiiiii:iiiililiiiliiiiiiiiiiii-too%
C."",". than 1000
I$$is otlifii$Il f* sE
Total
Non-participant respondents mostly identify with the dairy/agriculture industry. A handful of
respondents indicated that they were aligned with other industries or not representing a firm, but a
household; these "residence" respondents may have irrigation rate schedules because of wells or pumps
on their property. Figure 18 shows the distribution of primary activities for the surveyed non-participant
firms.
Figure 18. Iirimarv itrctivit1, for Non-Participating llespcndents
'I alrle 33" Size of Non-l'articipant liirms, by Nurnher of [nTplovees
Manufacturing
Professional, scientific, and technical services
Accomodation
Finand and insurance
Construction
lrrigation
Residence
Refused
$
Ni
N
\\.t.
\\
.:
N
NN
Dairy/Agricultural
Oo/o 10o/o 20%30% 40oh 50o/o 600/0 70% 80% 90Yo 100Yo
P-erg _e-rl 9f Resp-o_n g-enF
In order to understand the value of electric efficiency to non-participants, the evaluation team asked
respondents to identify the portion of operating expenses represented by electricity costs. |ust over half
(41 out of 73) of Idaho non-participating firms were able to provide indications of the extent to which
their electric bills made up their total annual operating expenses. In total, these proportions ranged from
i.i' o r, i*lil ii i irri p ;,: i: i rti ir irl)t.'vis il, r'l l i.i a ti r;r-. r..i'
i.loi:lr.-rr \ior-rrrtoin ]:tlrr,r,qi's lyi'iqirlit:n [,rlcr'S.,, Si;.t'r'r,ti:.r l:'rsilutrr-r Fa'ge iiA
ruAv$il,,qruT
0 - 100 percent. The mean portion of operating costs represented by electricity for non-participants was 26
percent, which is higher than the portion identified for participants (L4 percent).
5.2.1 Av*areness of Rocky Mountain Fower Programs
Three-quarters of non-participants indicated awareness of Rocky Mountain Power programs and services
aimed at helping consumers reduce electricity usage/ as shown in Figure 19.
Figure 19. Non-Participant Ar,r,areness of Rocky h,Iountain Power Programs and Sen ices
tAware that Rocky Mountain Power offers assistance to
improve energy efficiency
trNot aware that Rocky Mountain Power offers assistance to
improve energy efficiency ii#i i
Those respondents who were aware that Rocky Mountain Power offers incentives and technical
assistance aimed at helping customers reduce electricity usage were asked to identify what programs or
services Rocky Mountain Power offers customers in their class. This was an open-ended question;
customers were not prompted with a list of programs and were allowed to name as many programs or
services that they could. Several non-participants (26 out of 55) who were aware that Rocky Mountain
Power offers incentives and technical assistance were not able to identify a particular Rocky Mountain
Power program or service that would be available to them. The remaining 29 respondents who were
aware of programs provided 39 responses. Respondents were most aware of Irrigation Load Control and
incentives for efficient equipment as shown in Figure 20. Four respondents (5 percent) identified the
Irrigation Energy Savers program directly.
Figure 20. Non-participant Avvareness of Programs and Sen ices
Self-Direction Credit
Technical assistance/Energy analysis
lrrigation Energy Savers
Demand response/Load control
lncentives for efiicient equipment
lnigation Load Control
Not aware of programs
Not Sure/Don't Know
0o/o 10o/o 20o/o 30o/o 40o/o 50o/o 600/o 70o/o
Percent of Respondents
8oo/o g1oh lO0oA
Figure 21 shows how non-participants, who were aware that Rocky Mountain Power offers programs,
indicated hearing about the programs. The most common source of program information (36 percent)
was from Rocky Mountain Power printed materials - forms or brochures. The next most common
Nar,igant irnpact & Pntcess l],r'aiuiltiun of
Ror:h-r, \4t:r-rni:ain l:\:i.ver's .lrrigatit:n !-:'nergrr 5avers .l:'rogratrr
Roclry Mountain Power
Exhibit No. 5 Page 1266 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
N
Fage 55
rus\vlrANi-
response (17 percent) indicated leaming about programs from the Rocky Mountain Power Newsletter.
Another L2 percent had leamed of programs directly from Rocky Mountain Power representatives.
Figr.rre 21. Hnw Non-Iiarticipants Heard ahout Rocky Mountain Power Prograrnssr
Roclry Mountain Power
Exhibit No. 5 Page 1267 of 1365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
Rocky Mountain Power presentation/meeting
General knowledge/personal research
Online advertising
Accompanying billing
Trade ally, vendor, or contractor
Don't knodNot sure
Rocky Mountain Power website
Word of mouth
iPrevious participation in Rocky Mountain Power programs
Rocky Mountain Power representative
Rocky Mountain Power newsletter
Rocky Mou ntain Power printed materials/brochures
10Yo 20Yo 30o/o 40o/o 50% 60To 70Yo 80To
Percent of Respondents
Respondents were also asked how they would prefer to leam about Rocky Mountain Power programs.
Figure 22 shows the methods through which respondents prefer to learn about Rocky Mountain Power
programs. Non-participants mostly prefer to leam about programs through mail (27 percent), printed
materials (23 percent), newsletters (16 percent), email (15 percent), and phone (11 percent). Other
methods were mentioned by less than 10 percent of non-participants.
lrigure 22. Pre{erred }Vfethod to Leam abont Prcgrams and Opportunities, Overall
t
x
T
TilIh.mIm
Rocky Mountain Power presentation/meetings/workshops
Print advertisement
Don't knoWNot sure
Rocky Mountain Power website
Accompanying bills
Rocky Mountain Power representative
Phone
Email
Rocky Mountain Power newsletter
Rocky Mountain Power printed materials/brochure
Mail -$-*.t-. ! i-i**&{.*+,.*..+
20o/o 30o/o 40o/o 50o/o 60Yo 70o/o 80o/o 90o/o 1O0o/o
Percent of Respondents
36 Multiple responses were allowed. \l/hile 2 of 55 respondents did not recall, the remaining 53 offered 57 sources.
Narri.gont irnpai:i & I)roccss l],va]uaiiun oi'
llor:ky \4 oun ta i n i:\:llrer's l rri f, ;rtion Li,r-rergrr Sav t:rs l:'rograrn
10o/o
Fagr 50
lq,,S.vltAld"r
5.2.2 Non-Participant Energy Efficiency Improvements
Non-participants were asked a series of questions about energy efficiency actions or improvements that
they may have taken during the program years of 2009 to 2011. These questions were in regards to: high
efficient equipment purchases, load or demand reduction efforts, and systematic evaluations or energy
analyses of existing facilities.3T
Of the 73 non-participants, 22 percent indicated that their firms installed high efficienry equipment
between 2009 and 201,1,;3 percent had assistance from Rocky Mountain Power, as shown in Figure 23. The
high efficient equipment installed by non-participants included pumps, gaskets, nozzles, sprinkler
packages, appliances, lighting, and VFDs (variable frequenry drives).
Figure 23. Non-Participant F1igh Efficiency Equipment Purchases in Existing Facilities
lYes, purchased or installed high efficiency equipment between 2009 and 2011
without assistance from Rocky Mountain Power
NYes, purchased or installed high efficiency equipment between 2009 and 2011
with assistance from Rocky Mountain Power
tr No, did not purchase or install high efficiency equipment
About one-third of non-participants indicated that they implemented load control strategies for their
facilities. About two-thirds of these indicated having assistance from Rocky Mountain Power to
implement load control strategies, as shown in Figure 24. Specifically, the 16 respondents (22 percent)
who indicated that they had assistance from Rocky Mountain Power either identified the Irrigation Load
Control program directly or said that they had pumps that could be shut off by Rocky Mountain Power.
The other respondents (11 percent) who implemented load control strategies without Rocky Mountain
Power assistance identified timers on pumps (two), interruptible power (one), drains (one), pivots (one),
and variable speed drive pumps (one). Depending on how timers and other equipment are operated, the
effect may not control load at peak but may offer some other control benefit to the customer.
37 Respondents who reported taking energy efficiency actions or improvements were asked if they had received
assistance from Rocky Mountain Power. The evaluation team assumes that this assistance is not in the form of
program participation because the non-participant list was crosschecked with the participant tracking data by Rocky
Mountain Power.
N orr i. tlil n i lrri 1>a i': i dr Pli.rct iss [ii viiiu o i.i un r:i'
i{oi.:k-r,' ill ou.n ta i n ilbr,r, er's .l rri gat i on Lilner:g*,' Sa v tlrs l:}ir:rtrn rrl
Rocky Mountain Power
Exhibit No. 5 Page 1268 of 1365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
Fage $7
N$VNilAN"S-
trrigure 24" Nun-Participant Load Ccntrol Strategie* in Exi;ting Facitritie*
f Yes, implemented load control strategies between 2009 and2011
without assistance from Roct<y Mountain Power
scYes, implemented load control strategies between 2009 and 2011
with assistance from Rocky Mountain Power
trNo, did not implement load control strategies
About 4 percent of non-participants indicated that they conducted a systematic evaluation of their facility
in order to identify chances to improve energy efficiency. |ust 1 percent indicated that they received
assistance from Rocky Mountain Power to conduct the evaluatiory as shown in Figure 25. One
respondent provided an example of action taken in response to the systematic evaluation; this respondent
had used pivots instead of pumps.
Figure 35. Non-participant Systematic Evaluations of Existing Facilities
Rocky Mountain Power
Exhibit No. 5 Page 1269 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
1104
3o/oI
I
IYes, conducted a systematic evaluation between 2009 and 2011
without assistance from Rocky Mountain Power
ElYes, conducted a systematic evaluation between 2009 and 2011
with assistance from Rocky Mountain Power
ElNo, did not conduct a systematic evaluation
Those respondents who implemented energy efficient equipment load control strategies, or systematic
evaluations, but did not apply for assistance from Rocky Mountain Power, were asked why they had not.
This evaluation is focused specifically on Irrigation Energy Savers, which incentivizes some efficient
equipment and early replacement as well as providing technical assistance for systematic evaluation.
However, Rocky Mountain Power offers other programs that provide incentives for high efficient
equipment (FinAnswer Express and Energy FinAnswer), implement load control (Irrigation Load
Control), and support systematic evaluation (Energy FinAnswer). 3a Figure 26 shows the reasons that
respondents indicated for not applying for each action and the weighted overall responses.3e The most
common response (49 percent of respondents) was that they were not sure. The next most common
response (23 percent of respondents) was that they were not aware that assistance was available. Others
indicated that they did not think they would qualify, did not think it would be worthwhile, did not think
about it or forgot, or knew they would not qualify.
38 Schedule 10 customers do not qualify for Energy FinAnswer or FinAnswer Express in Idaho, but some of these
customers may have more than one rate schedule for different areas of business.
3e Weighting is by the portion of non-participants responding to each question, by fype of action.
Nsr,i*:e rii irri1.:ali 6< I)nri:l:ss ll,i;iii:iliir;l i>i:
lioi:ii-r,' \iour.'i'sin !:tr:r,r,er's iriiqatir:tr l:.i're.r:qri Siai:cis !:rit::qri:iil-r ilagr ii$
N$V $TA N"\-
Systematic Evaluation
High Efficient Equipment
0o/o 10% 20Yo
!'Not sure/No response
I Small project size, not worth it
rWasn't aware
B Didn't think about iUforgot
30Yo 40% 50o/o 60%o 70% 80o/o 90%
Percent of Respondents
Roclry Mountain Power
Exhibit No. 5 Page '1270 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
100o/o
Figure 26. tthy Didn't Non-Participants Apply for Assistance f,rom Rocky Mountain Povver
NWould not qualiff
trDidn't know if qualified
5.2.3 Motivations for Pursuing E?ficiency lmprovements
Non-participants who indicated that their firms installed high efficiency equipment, implemented load
control strategies, or undertook systematic evaluations of existing facilities between 2009 and 2011 were
asked what motivated them to take that action. Figure 27 shows the motivations respondents indicated
for each action and the weighted overall responses.ao By far, the most common response was "to save
money on electric bills."
Figure 27. Non-Participant Motivation {or Prrrsuing Energv Efficienc_v Improvement's
Overall
Systematic Evaluation
Load Control
High Efficient Equipment
Oo/o 20o/o 3Oo/o
ETo save money on electric bills
NTo replace old, broken, or poorly working equipment
trTo improve comfort
lTo save water
ElTo protect the environment
40% 50Yo 60% 7Oo/o 8Oo/o 9Oo/o
Percent of Respondents
E To obtain an incentive
rTo save energy
trTo improve operations, production, or quality
BTo acquire the latest technology
1OY.lOOo/o
a
II
i
a0 Weighting is by the portion of non-participants responding to each question, by type of action.
N*rriqani hnpari & I)locsss [,r,;ili:oiir:l o1:
I{ock;-r: \.lr:ui-rtoin l:}orar'er's lrrigation {.r,nergr. Savers i:!t'r}gr;rr}-\Fage t-+
ruAxrltAN-i-
5.2.4 Further Energy Efficiency Opportunities and Barrierc
About 25 percent of the non-participating respondents indicated that they believed their firms could take
additional steps in order to increase electric efficiency. More than one-third (38 percent) stated that they
did not think their firm could make additional energy efficiency improvements. Another quarter (37
percent) were not sure, as shown in Figure 28.
The 18 respondents who believed their firms could take additional steps to improve electric efficiency
were asked for examples of measures that their firms could implement in order to increase electric
efficiency. The most common response, by six non-participants was to "make upgrades to efficiency of
equipment;" two non-participants each mentioned "purchase more efficient appliances, equipment, and
lighting," "conduct technical analysis," and "make building envelope improvements."
The 18 respondents who believed their firms could take additional steps to improve electric efficiency
were also asked if they had plans in place to move forward. As shown in Figure 29,56 percent did not
have plans in place at their firms to implement such projects. Respondents with plans in place were split
on whether they intended to implement projects with Rocky Mountain Power assistance; 22 percent
reported having plans in place and intended to apply for assistance from Rocky Mountain Power, while
17 percent had plans in place but did not intend to apply for assistance from Rocky Mountain Power.
Figure 29. lndication of Plans to Implement Hleetric Efficiency Proiects for Non-Participants
slYes, plans in place to implement projects - with Rocky Mountain Power assistance
HYes, plans in place to implement projects - without Rocky Mountain Power assistance
uNo, plans not in place
IDon't KnoWNot Sure
Respondents who believed their firms could take additional steps to improve electric efficiency were
further asked what might prevent them from implementing electric efficiency improvements. Table 33
shows barriers identified by Idaho non-participants. The most common potential barrier was "high
upfront costs," followed by "lack of access to capital," "lack of information on savings and performance,"
and "nothing."
\31rigo*t Inii:a*l & Pn:t:r'rss ll,i,'air:otiun oi
llotliy \t 6uI! ;o in llor,rr er's l rrigati t:n [,nerg\r Savers l]ritgrani
Roclq Mountain Power
Exhibit No. 5 Page 1271 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
I:'igure 28" Non"participant Indication nf llurrther Energy E{ficiency Opportunities
rYes, could make future improvements
NNo,could not make future improvements
tr Not sure or Refused
Fage 70
V$ilAh'T
High upfront costs
Lack of information about savings and performance
Don't know/Not sure
Roclry Mountain Power
Exhibit No. 5 Page 1272 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
67%
iiiiiiiiii..iii...Iire''
67o
li:::::i:::::::::::::i::6E;
1,t%
:t:t:t:t:t:tI0Hi&6
5.3 Trade Ally Findings
In July and August of 2012, the evaluation team interviewed six out of 11 active vendors in the Irrigation
Energy Efficiency Alliance. Interviewees were well versed in irrigation equipment and the market; they
included sales managers, district managers, and product managers with 12 to 15 years of experience in
their position.
S.3."t Satlsfaetion
Most of the interviewed trade allies reported satisfaction with the program. Two were very satisfied and
three were somewhat satisfied. One was somewhat dissatisfied with the program; this trade ally noted
that dissatisfaction stemmed from the time it takes to communicate back and forth with the program
administrator. This trade ally rated the program contact, the program administrator, as "good" and said
that the customer project driven communication "met their needs," but also indicated that it takes a long
time to "get stuff done" for customers through the program. Therefore, this dissatisfaction is with timing
for customer projects and not with communication.
Three of the trade allies also worked with other similar programs. They suggested that the Irrigation
Energy Savers program could improve by being more streamlined or providing incentives for additional
equipment. One trade ally suggested that there had been a problem in the past when the program was
suspended for a few months that hurt one of his customers; however, the program was not suspended
between 2009 and 2011, so this response does not make sense for the program and indicates some
confusion. No other concerns about program continuity and availability were raised.
5.3"? Frograrm Awareness and Motivation
Four of the trade allies indicated that they leamed about the program from the program administrator.
One learned about the program directly from Rocky Mountain Power, and one leamed about the
program from customers.
\Atrhen asked about why they decided to get involved with the Irrigation Energy Savers program, trade
allies responded that they were motivated to get involved in order to help their customers. Trade allies
agreed that the program is good for irrigators, and they would like to see the program remain available
consistently.
.N ol itan t ii::i 1:;.:i:i $r I)ll.rt:uss l:, r,i rii.i ili.i r:n oi
iioi:i.;-r, \4ountein !:iura,rril':l lri'igiition li,*cr:i1ri Si;rver:; i:'Lt.lf.rii,r:-:
'I"atrle 33" Sarriers to Implementing Electric Efficiency lmprovements
Puqr Ti
NI ,$\V$TANT
5.3.3 Training, Roles and Communication
Five of the six interviewed trade allies indicated having an in-person meeting with the program
administrator to discuss the program offerings. Two of the six trade allies indicated that they had follow-
up training; one of these considered a seminar offered by Rocky Mountain Power that included allies and
customers as follow-up training.
All trade allies reported that they have information on the program and believe that their role in the
program has been clearly explained. One trade ally who had not had follow-up training indicated a
desire for additional communication and information about the program.
Trade allies communicate directly with the program administrator. All trade allies described this
communication in positive terms. They indicated that they can always reach out to the program
administrator with questions, knowing that they will be able to reach someone who can help.
Communication is largely driven by customer needs. Trade allies will contact the program administrator
when they have new applications or when customers need more technical assistance with the program.
The majority of interviewed trade allies stated that they prefer email as a primary communication
channel, but other means were mentioned. Four prefer email communicatiory and two of these would
also like phone or mail communication as back up to the emails. One trade ally stays up to date with the
website and prefers communications online, directly on the site. One trade ally prefers newsletters.
5.3.4 Marketing
More than half of the trade allies (four of the six) interviewed indicated that they use the program to
market their services to customers. Mostly, this is in the form of letting customers know about the
program and associated incentives when discussing project options. Trade allies reported that the
incentive can influence customer purchasing decisions, and knowing that they can get some equipment at
no cost can lead to replacements that would not otherwise occur. Trade allies were asked how the
program helped their sales. Three indicated that they believe the program has led to increased sales of
efficient equipment. They specifically mentioned increased sales of variable frequency drives, gaskets,
and nozzles.
Trade allies would prefer to receive more marketing materials. Three interviewees offered suggestions to
improve the program marketing materials; all three suggested providing simple brochures with expected
costs and program incentives. One trade ally's response is representative: "A little brochure would be
perfect, so you could hand to people if they are curious. [The brochure would] have in there exactly what
it costs, what it takes to do it. [That way] a guy can just take it when he's busy and read it when he has a
few minutes. Sometimes, they come in and out of here, they are in a pretty good hurry, and so you don't
have a whole lot of time to explain to them what is going on." The evaluation team notes that there is a
brochure for the program that describes program steps Figure 30. This brochure explains all of the
program offerings, but it does not describe costs. Perhaps separate brochures by program component
could provide greater detail without becoming too complex.
Novitlarit ii:rpai:i & Pitrt:r.irs lLvaiuaiir,rr of
)toi:iiy \,iouniein lltor,rrer's .lrrigatir:n l,;.netg',r S*r,crs l:'rogra*r
Rocky Mountain Power
Exhibit No. 5 Page 1273 of '1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage 7?
N &V $TA N"}-
$.3.5 Customerlnvolvement
The interviewed trade allies stated that about half of customers find out about the program from them,
whereas other customers know about the programs from their neighbors or other irrigators. Projects start
with either the customer contacting the trade ally or with the trade ally making suggestions to the
customer who may not have considered the program before contacting the trade ally. Relative
proportions varied across allies from a 50/50 split to 10/90 for one proactive trade ally.
Roclq Mountain Power
Exhibit No. 5 Page 1274 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
N c r, itlil rr t lrri p ;: i: i i:r I)r:i-rctiss L, i.' al u s ti or-r oil
Iloi':i.ry \4ouni'oin l:)uwer's lrrigarir:n li.r-ret:qir Sa'r,e,":s .i:'r'r.;giiln-r
Figure 30. Ilarriers to knplementing Electric Efficiency Improvements
Page T3
s$tv*tAI{T
Trade allies did not identify any differences in their work with customers working with the program and
those not working with the program, except that the trade allies explain the program to those customers
working with the program. Trade allies described similar sales strategies and customer service actions for
both groups.
\A/hen asked about projects that were not completed, trade allies stated that few projects would likely not
be completed. Rarely, with larger projects, the customer may not go forward, if the incentive turned out
to not be enough to reduce high costs of equipment, to a level with which they were comfortable. Trade
allies noted that incompletion is not a concem at all with the equipment exchange portion of the program.
However, trade allies suggested that the application process could be streamlined. One specifically
mentioned time constraints involved with printing applications from the website and then filling them
out by hand. The trade ally does not mind doing this work, but the customer does not always want to
wait for the forms to be filled out. The trade ally would prefer to be able to print partially filled forms, or
to have simpler application forms. Another trade ally noted that the applications are a challenge for the
customers to fill out at home, and the customers do not always return the completed forms. These trade
allies are referring to the three page applications for the equipment exchange and pivot and linear
upgrade portions of the program. These applications include program details and legal disclaimers. For
equipment exchange, the incentive is sent to the dealer based on the actual cost of the make and size of
the equipmenU this requires the dealer to write in additional information besides the count of equipment
of each type exchanged. Trade allies are familiar with another utility program in the state with a single
page application and prescriptive incentives by equipment typei the other application is simpler and
faster for them to fill out.
5.3.6 Effects of the Program
Trade allies were asked about the relative efficienry of the equipment that went through the program and
equipment that is not incentivized through the program. For both equipment exchange and the pivot and
linear upgrade equipment, trade allies stated that the program equipment is the same efficienry as what
people would purchase without the program. One trade ally noted that nozzles can be conventional or
low flow, and low flow nozzles (flow control nozzles) are more efficient. al This ally stated that the
conventional nozzles are 30 cents, compared to two dollars for low flow, and the program currently does
not incentivize them to convert conventionalnozzles to low flow nozzles, but moving customers to low
flow nozzles would improve efficiency. The program manual indicates that the program will not cover
the cost of replacement low flow nozzles, "Please note that the full cost for replacement of flow control
nozzles will not be paid by the program. The program will pay the cost of standard nozzles toward the
replacement of flow control nozzles."42
A couple (two of the six) trade allies could identify program-qualifying sales in 20LL that did not go
through the program. Both of these trade allies stated that there had been four or five pivot and linear
upgrades completed in the last year that would have qualified for the program but did not get processed
through the program. One trade ally said that the customers did not go through the program because
they did not want to take the time to deal with the application. The other trade ally indicated that these
ar Low flow nozzles are not more efficient in all cases. They can reduce pressure variations across the system.
a2 Idaho Irrigation Energy Savers Program Manual. Page 5. Retrieved from
http://www.rockymountainpower.net/content/dam/rocky_mountain_power/doc/Business/Save_Energy_Mon ey I Agrt
cultural_L.pdf
Navi(itnt irnpari 8r I)r:r;cuss lLva)i.istii.:;t o{'
iloi:ii\, \4t:untain l:\:i..r,er's lrrigi,rtit:n {:,1r'rqr, Sai,cis l:'r*qram
Rocky Mountain Power
Exhibit No. 5 Page 1275 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage 74
N V${-ANT
upgrades did not go through the program because the trade ally or the customer did not get the
application filled out.
Trade allies were asked to describe the program influence on their activities, as shown in Table 34.a3
While the reported influence of the program on sales was mixed, trade allies generally reported that the
program incentives were somewhat influential in their stocking practices.
Program incentives influence sales of program-eligible equipment 2
iiiiiiiiiiil:iiiiiiiiliii
itri!:!i!:!:!ii:1:
When asked how their sales of program-eligible equipment would change if the Irrigation Energy Savers
program did not exist, three trade allies indicated that sales would decline and two were not sure (one
does not directly sell any equipment but only provides irrigation assistance). Trade allies expect that
without the program, customers would not replace equipment until it was broken, and they may install
cheaper direct drives rather than variable frequency drives for pumps.
5.4 Oaedl Process Findings
From May through August 2012, the evaluation team surveyed or interviewed 66 participants, 73 non-
participants, and six trade allies. This section summarizes answers to the research questions for this
process evaluation.
5.4.1 Process Research Findings
The evaluation team sought to answer six process evaluation research questions. These questions are
listed here along with short summary answers.
L. What are the program goals, concept and design? Are they based on sound theory and practice,
and, if not in what respects?
The Irrigation Energy Savers program in Idaho seeks to improve energy efficiency for irrigation sites.
The basic program theory is that providing technical assistance will help overcome information gaps
for customers and providing an incentive (or no cost equipment) will help overcome customer cost
a3 One interviewed trade ally coordinates between customers and vendors and does not directly stock or sell
equipment. One other trade ally did not stock equipment.
N o r, i$iln t Irri J:a i':| & I)rt'rcess ll,r'ii)r.i ai.isi-r ol:
]ior:!:r, \'iuurttilin ll\lr,r,ei''s Irligatir:n i],n*rtl*,r Sia'r,er:s i:'ro11Li:uri
Rocky Mountain Power
Exhibit No.5 Page 1276 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 34. Program Influence on Trade Ally Sales and Stncking
Fuge T$
iNJ\V$ilANT
barriers. Customers will replace wom equipment earlier with equipment exchange and pivot and
linear upgrades, and customers will run more efficient systems with help from the system analysis
and redesign; better equipment and irrigation practices will reduce water pumping and, therefore,
electricity use. More information on the design is indicated in the program logic model in the
program overview. Energy savings targets were set for the third party administrator under contract
to deliver the program in2009 and 2010. The program set overall energy savings goals in 2011.
Savings targets were exceeded based on reported savings in 2009 and 2010, and 99 percent of savings
targets were reported in 2011.
2. Do program administrators have the resources and capacity to implement the program as
planned?
Yes. Program administrators indicated that they had the resources and capacity to implement the
program as planned. Program participants did not identify communication delays that might indicate
resource or capacity constraints. Participants and trade allies who contacted Rocky Mountain Power
indicated that the representatives were knowledgeable and timely. Trade allies indicated that they
had a primary program contact to which they could reach out and receive prompt and
knowledgeable assistance; only one trade ally indicated any communication delays.
3. Is the program being delivered as planned, and if not, how and why?
Yes, the program is being delivered as planned. Both participants and trade allies described the
program operations as expected from the logic model , and \2 of 13 program outcomes were
positively affirmed in this evaluation. A few participants and trade allies noted that there could be
improvements in the application paperwork as well as in clarity of program expectations.
Table 8 lists the program outcomes indicated in the logic model along with findings based on the key
indicators and data sources reviewed in the process evaluation (refer to Table 8 for key indicators and
data sources). Only one outcome from the logic model was not affirmed in this evaluation, "Achieve
peak demand and energy use reduction targets." The reported savings in 2011 (2,360,391. k\A/h) were
99 percent of the program target of 2,398,790 kWh. The impact analysis also indicates that the
program may not be achieving the reported savings.
4. Is the program reaching the intended target population, and if not, why? Specifically, are
eligible customers aware of the program, how are they becoming aware, and what is the
program's influence on their actions?
All irrigation rate schedule 10 customers in Idaho are eligible for the Irrigation Energy Savers
program, although sub-programs have different requirements. From 2009 to 2011, there were 851
participating projects from 528 sites and 369 unique from a base of approximately 4,782 customers.
This implies an estimated program reach of 7.7 percent of eligible customers (369 out of 4,782).
Are eligible customers aware of the program? To understand if eligible customers are aware of
the program, the evaluation team relies on non-participant responses. Of a representative sample
of non-participants, 75 percent affirmed that they were aware that Rocky Mountain Power offers
incentives and technical assistance to customers in their class to help them reduce electricity
usage. When asked what programs or services were offered to customers in their class, 14 percent
.Ni a l igil n t hri 1':;r i': [ & ])*rr:r.:ss ll, v i:i i u il ti t;n ol:
I{oiinr \4outrtoin ll\:r.r,er's lrri{atitllr l-i,nergrr Sav*rs i:'rop;rar-:
Roclq Mountain Power
Exhibit No. 5 Page 1277 of I 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fagr 70
rur\vltANT
of non-participants indicated incentives for high efficient equipmenf and 5 percent were
specifically aware of Irrigation Energy Savers.
How are they becoming aware? Customers who do begin working with the program mostly find
out about it from trade allies (29 percent) or Rocky Mountain Power representatives (18 percent),
as is expected from the program logic model. Participants also indicate knowing about the
program because of colleagues and friends, previous participatiory the Rocky Mountain Power
website, and printed materials/brochures. Non-participants who were aware of programs learned
about them through printed materials/brochures (36 percent), newsletters (17 percent), and
Rocky Mountain Power representatives (12 percent). Non-participants indicated preference for
mail (27 percent), printed materials (23 percent), newsletters (15 percent), and email (15 percent)
as ways that they prefer to learn about programs. Mailings, printed materials, and newsletters are
already used to reach out to the customer base, but email is not currently used.
What is the program influence on their actions? Participants are influenced to participate in
order to replace old or poorly working equipment (48 percent), save money on electricity bills (29
percent), obtain Rocky Mountain Power incentives (12 percent), and save energy (12 percent).
There is some indication of program influence on participant purchases with the program. Based
on participant self-report, 45 percent of projects would have been completed within the same
year without the program while 14 percent would not have been completed at all. The other
projects would have been completed later or would not have had as large of energy savings
without the program. After adjusting for prior experience and inconsistencies, 17 percent of
participants are assumed to be full free riders-who would have done their projects without the
program, and 42 percent were partial free riders; the remaining 41 percent were non free riders.
Free ridership varied over subprograms and was highest for equipment exchange. There is some
indication of spillover from this program, both like and unlike projects were completed with no
incentives at least partly due to the program influence.
5. What barriers.ue preventing customers from taking actions to reduce energy consumption and
demand and which ieopardize progr.rm cost-effectiveness?
Customers who thought there were additional actions they could take to reduce energy consumption
and demand werd asked what might prevent them from doing so. The most common potential
barrier, identified by 72 percent of responding participants and 57 percent of responding non-
participants, was "high upfront costs." The next most common potential barrier was a "lack of access
to capital" with 15 percent of responding participants and 11 percent of responding non-participants
indicating that was a barrier for them. Among other barriers to further customer action to reduce
energy consumption and demand were lack of time and lack of information.
6. Are participants achieving desired outcomes, and if not, how and why?
For the most part, participants are achieving desired outcomes. Participants are mostly satisfied and
installing and keeping their equipment in operation as expected based on the program logic model.
Participants indicated that the program influenced spillover, and trade allies indicated that
program-qualifying equipment was similar to that purchased outside of the program.
.N*r,iblilni lmpai.':i & Ili:ricr:rss Lvi'rluiltion of
I{oili:v \4 o u n ta i n i:'or.ver's l rri gati on l:,neirgy 5a t,iii"s l:'rogra*i
Rocky Mountain Power
Exhibit No. 5 Page 1278 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fage 7?
.tN&VI TANT
7. Additional process feedback from on-site customer interview:
Several participants interviewed mentioned that the paperwork was submitted by the equipment
distributer or was delayed until after the measure was already installed. These discrepancies impact
the evaluator's ability to delineate between pre and post periods when reviewing billing records
Natitant Impai':t & I)r:i:cess [],irair:aii*n of
I{ockr, \4r:untain l}or,r,er's lrrigatit:n Energri Savers l)rr:, rati
Roclry Mountain Pourer
Exhibit No. 5 Page 1279 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page 78
N&V}TAI\T
Dealers identify pivot and linear system
upgrades
Energy saving measures/ costs, and
benefits identified
Reduce kW and/or kWh at customer
facility
::rr{ll8s.$Ifitif:,[e-mail]::ii:.iiiiiiiiiiiii:iiiiii::iiiii:i::iiiiiiiiiiiiiiiii::,,iii::iiiii:::iiiiii:i:iii
Achieve peak demand and energy use
Nalitlont ir:lrpai':i S,r l)ttt:r.iss L','alr:at!sn +i
iioi':k-r. i\4 i: u tr t.r i n llil'iu t:t's l r ri gat i t:n l:,ne rgr.' 5a r,r:r$ l:'rt:gram
Roclry Mountain Power
Exhibit No. 5 Page 1280 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
75% of irrigation non-participants were aware of any programs; 5%
identified Irrigation Energy Savers by name, and 14% knew of
incentives for efficient equipment.
Trade allies assisted customers; participants and trade allies described
pivot and linear system upgrades in line with program design.
Reports include information on measures, costs, and savings;
customers find these valuable.
T'able 35. Program flutcomes and lrinclings
Mid-term Outcomes
reduction targets
ruAxsltANT
Based on the findings from this evaluation, the evaluation team has identified recommendations for the
Irrigation Energy Savers program. These recommendations will help the program meet energy savings
targets by validating measure performance and facilitating participation. There is no current scheme or
metric established to rank the importance of specific recommendations. Therefore. the following are not
ranked accordins to prioritv or importance.
Continuation of the program would require modifications that will increase the likelihood of savings
occurring as expected. Some measures are successfully providing positive energy impacts, while others
are not. This program should not continue in its present form unless steps are implemented to confirm
that the impacts of each type of measure included in the program are net positive. If the program is to
continue, it should be considered as being in a test period.
Suggested modifications include, in no particular order:
1. If the program is to continue, it should be considered as being in a test peiod.
Increase program focus on Variable Frequency Drive (VFD) applications. This measure has
positive impacts and an 80122 confidence/precision interval. The upfront capital required for
VFDs reduces the potential for free-ridership. Also, growers cite the added flexibility is the
primary driver for adoption. Finally, the measure is in a fixed location, which aids M&V.
To reduce the potential for free ridership and aid data collection, the Company should
modify the program so that measures which readily transition between pumping stations
(i.e. non-center pivot non-pump specific measures) are incentivized via a direct install
mechanism. Measurement and Verification (M&V) of savings from mobile measures using a
billing analysis approach is not advisable because these measures readily diffuse across
multiple utility meters. Also, the impact from these measures can be lost in the "noise" of
billing data. (i.e. billing analysis is ineffective for non-meter specific measures due to the
order of magnitude of these measures' impacts relative to the overall metered energy use,
compounded with irregular operational schedules and a high probability for un-incentivized
maintenance or system redesigns to obscure the measure impact.) M&V using a bottom-up
engineering approach requires baseline information that cannot be collected after the fact. A
direct install delivery mechanism will reduce free-ridership and allow for the collection of
baseline operational data. The intent of this recommendation is to allow for pre/post
monitoring that can immediately assess measure savings with interactive impacts. This
change will increase the cost of implementing what would otherwise be very low cost
measures and may limit the number of these measures incentivized, but the benefit is that a
direct install model allows for better data to be collected in order to confirm positive measure
impacts before further program moneys are spent on measures with littlg or potentially
negative, impacts.
Establish protocols to ensure that installation dates are accurately captured. Some
applications were not submitted until well after the measure was already installed. This
Rocky Mountain Power
Exhibit No. 5 Page 1281 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
4.
Novifiilnt irnpari & ]]nrce,.s ll,r,aiuoi.ii:n of
i{oi:l::r,' \4ountein I\:u..'er's lrrigatii>n {,i,trer:g-'ri Savcrs l:'ri:?rarn Fage $0
ru&v$ tA NT
makes billing analysis very difficult because it is difficult to ensure that the pre/post data
points are properly separated without losing a significant portion of the potential data points.
5. Revise the program to encourage and incent only those measures which are determined to
consistently reduce energy usage, remove other measures from the program.
Determination of which measures remain in the program should consider waiting until after
further data collection while the program is in test period status or, until additional
performance based data is available to justify measure inclusion.
The program should be considered to be in a test period and regular follow-up evaluations should be
conducted until the program shows reliable, cost effective savings. The evaluation team has the
following recommendations for reducing uncertainty in the next program evaluation, in no particular
order:
Until the regionally deemed savings are considered in compliance, treat all measures that
are part of the progr.rm as custom and collect the data needed to verify savings at the time
of implementation.
Determine baseline energy use for implemented measures. This will require primary data
collection prior to measure installation. Data collection will need to include in-situ flow rates,
and either power spot readings or temporary energy use trends acquired using data
monitoring of pump power correlated to measured flow data. This step is particularly
critical for measures that can migrate between pumping stations, as they cannot be accurately
verified after the fact and without a site specific baseline. If the data required to quantify leak
reduction and system performance impacts can be collected without jeopardizing
participation or cost effectiveness, then this step should be maintained beyond the test
period.
Utilize additional survey tools to assess participant tendencies toward self-selecting into
the program due to anticipation of increased irrigation requirements. The expanded survey
needs to also verify if total irrigation system capacity changed at the time of participation.
Additional documentation of changes in system design can then be used to construct an
improved counterfactual baseline across all program measures.
Consider perfonning a Ranilomized Control Trial (further described in Section 3 of this
report) to address potential selection bias, in conjunction with the next program evaluation.
There are additional recommendations that could help reduce customer barriers and increase
participation.s If the program continues following the test period and implementation of the actions
previously described, the Evaluation Team suggests the following additional, second tier
recommendations, in no particular order:
1. Simplify the application process and provide clear guidance. The program manual
provides clear steps to participatiory but customers may be confused by the multiple ways to
e Short recommendations are included here. For context and more detail, see Section 6 Program Evaluation
Recommendations
L.
)
J.
4.
Roclq Mountain Power
Exhibit No, 5 Page 1282 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Nar,i$onl impai:t & Ilroct-:ss l],r,iiiuiltior: o{:
Ilocl';-v \4ountain l:\-l+er's.lrrigiltion l-;,r'relg-ri Savers l:'rogram Fage $i
N&V}TA I\T
Roclry Mountain Power
Exhibit No. 5 Page 1283 of'1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
3.
4.
5.
participate. Current applications are three pages long and require trade allies to fill in the
make and brand information for equipment exchanged. Removing program detail from
applications could shorten the application length. To reduce the time required to fill out
equipment exchange applications, a form-type application where the trade ally could store
commonly exchanged equipment "make" information would need to be developed. In
additiory trade allies noted that customers who do not want to wait for trade allies to fill out
applications by hand might take them home but then not return the application. Streamlined
applications could reduce the burden on trade allies and customers to participate in the
program. If the application cannot be modified, simplified program explanatory brochures,
by sub-program, could make the program more accessible to customers. Clarifying and
simplifying application materials can increase participation and may encourage trade allies to
be more proactive with the program.
Shift focus toward measures that offer an improvement above the standard efficiency
baseline. One example is low-flow-high-precision center pivot nozzles. Variable rate
irrigation, computerized control, and emerging technologies provide additional alternative
measures. The program currently covers the cost of conventional nozzles to replace wom
nozzles exchanged through the program. Low-flow-high-precision nozzles offer an
opportunity to decrease water application and pumping needed to cover the same area. If the
program is able to move customers to more efficient technology, the program can capture
greater energy savings and meet energy savings goals.
Approach Sprinkler Packs as a fully custom measure. The impacts from center-pivot tuning
and maintenance are too variable to apply a fixed savings rate. Also, a protocol is needed to
verify in-situ baseline system performance so as to facilitate an engineering approach to
M&V.
As opposed to the current offer to retune center pivot systems back to original design specs,
investigate options for system redesigns that promote incremental improvements in
system efficacy beyond current standard practice.as
Explore options to make financing available to customers for projects requiring capital
investment. While the program is designed to overcome the high upfront cost barrier
identified by participants and non-participants alike, there are no programs to help
customers overcome their lack of access to capital. Helping customers access financing, either
through direct financing, on-bill financing, or partnerships with other institutions can
overcome this barrier. Accessible financing makes larger investments more attractive and can
drive additional savings. The most common potential barrier, identified by 72 percent of
responding participants and 67 percent of responding non-participants, was "high upfront
costs." The next most common potential barrier was a "lack of access to capital" with 15
percent of responding participants and 11 percent of responding non-participants indicating
that was a barrier for them.
a5 Changes of this nature may need to be conducted and evaluated under a market transformation model.
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Exhibit No. 5 Page 1284 of 1365
Case No. PAC-E-1447
Wtness: Kathryn C. HymasruA,v rtA NT
Final Evaluation Repo:rt tcrr ldaho's lrrigation Ener$y
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Appendix A. Glossary of Frequently-Used Evaluation Tenns... ..............A-1,
Appendix B. Net Savings Methodology....... ............B-L
8.1 Measurement of Net Savings Memo -]anuary 27,2012....... ............8-1
8.2 Net Savings Scoring - June 1.8,2012 ........B-11
Appendix C. Impact Evaluation............... ................C-21.
Appendix D. Process Evaluation Survey Instruments.............. ................. E-1
D.1 IES EEA Interview Guide.......... ..................E-1
1..1..2 Section 1: Participation............... ........................E-2
1.1.3 Section 2: Training, Roles, and Communication....... ...........E-3
1..1.4 Section 3: Marketing ......................E-3
1.1.5 Section 4: Customer InvoIvement................... .......................E-4
L|1,.6 Section 5: Effects of the Program .............. ........E-5
1..1..7 Section 6: Business Impact........ .........................8-6
1.1,8 Section 8: Satisfaction with Program(s). ...........E-6
1,.L.9 Section 9: Gas Card Offer/C1osing.......... ..........E-6
C.2 IES Participant Survey Instrument ............8-7
C.3 IES Non-Participant Survey Instrument ......................E-37
Rocky Mountain Power
Exhibit No. 5 Page 1285 of 1365
Case No. PAC-E-14{7
Wtness: Kathryn C. Hymas
idahc irrigation Ensrgy Sai,ings Hvaiuaiiori Re$ori
Fana i
N&V$ TENT
A.7 Glossaryl
Adiustments: For M&V analyses, factors that modify baseline energy or demand values to account for
independent variable values (conditions) in the reporting period.
Allowances: Allowances represent the amount of a pollutant that a source is permitted to emit during a
specified time in the future under a cap and trade program. Allowances are often confused with credits
earned in the context of project-based or offset programs, in which sources trade with other facilities to
attain compliance with a conventional regulatory requirement. Cap and trade program basics are
discussed at the following EPA Web site: <http://www.epa.govlairmarkets/cap-trade/index.html>.
Assessment boundary: The boundary within which all the primary effects and significant secondary
effects associated with a project are evaluated.
Baseline: Conditions, including energy consumption and related emissions that would have occurred
without implementation of the subject project or program. Baseline conditions are sometimes referred to
as "business-as-usual" conditions. Baselines are defined as either project-specific baselines or
performance standard baselines.
Baseline period: The period of time selected as representative of facility operations before the energy
efficienry activity takes place.
Bias: The extent to which a measurement or a sampling or analytic method systematically
underestimates or overestimates a value.
Co-benefits: The impacts of an energy efficiency program other than energy and demand savings.
Coincident demand: The metered demand of a device, circuit, or building that occurs at the same time
as the peak demand of a utilit5/s system load or at the same time as some other peak of interest, such as
building or facility peak demand. This should be expressed to indicate the peak of interest (e.9.,
"demand coincident with the utility system peak") Diversity factor is defined as the ratio of the sum of
the demands of a group of users to their coincident maximum demand. Therefore, diversity factors are
always equal to one or greater.
Comparison group: A group of consumers who did not participate in the evaluated program during
the program year and who share as many characteristics as possible with the participant group.
Confidence: An indication of how close a value is to the true value of the quantity in question.
Confidence is the likelihood that the evaluation has captured the true impacts of the program within a
certain range of values (i.e., precision).
1 Glossary definitions are provided to assist readers of this report and are adapted from the Model Energy
Efficienry Program Impact Evaluation Guide US Environmental Protection Agenry, November 2007
i.jai':c lrtigaticn Energy Savirgs Evaiuaiicn Repo(
Apnendir A - Ci';ssary o{ Frequenliv-Useti Eva!uaiion Teims
Rocky Mountain Power
Exhibit No. 5 Page 1286 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Page A.-1
N,$\V$TANT
Cost-effectiveness: An indicator of the relative performance or economic attractiveness of any energy
efficienry investment or practice. In the energy efficienry field, the present value of the estimated
benefits produced by an energy efficienry program is compared to the estimated total costs to determine
if the proposed investment or measure is desirable from a variety of perspectives (e.g., whether the
estimated benefits exceed the estimated costs from a societal perspective).
Database for Energy-Efficient Resources (DEER):
A Califomia database designed to provide well-documented estimates of energy and peak demand
savings values, measure costs, and effective useful life.
Demand Side Management (DSM): See "Energy efficiency."
Deemed savings: An estimate of an energy savings or energy-demand savings outcome (gross savings)
for a single unit of an installed energy efficiency measure that
(a) has been developed from data sources and analytical methods that are widely considered acceptable
for the measure and purpose and (b) is applicable to the situation being evaluated.
Demand: The time rate of energy flow. Demand usually refers to electric power measured in kW (equals
kwh/h) but can also refer to natural gas, usually as Btu/hr, kBtu/ hr, therms/day, etc.
Direct emissions: Direct emissions are changes in emissions at the site (controlled by the project sponsor
or owner) where the project takes place. Direct emissions are the source of avoided emissions for thermal
energy efficiency measures (e.g., avoided emissions from burning natural gas in a water heater).
Effective Useful Life (EUL): An estimate of the median number of years that the efficiency measures
installed under a program are still in place and operable.
Energy efficiency: The use of less energy to provide the same or an improved level of service to the
energy consumer in an economically efficient way; or using less energy to perform the same function.
"Energy conservation" is a term that has also been used, but it has the connotation of doing without a
service in order to save energy rather than using less energy to perform the same function. Demand Side
Management (DSM) is also frequently used to refer to actively-managed energy efficienry initiatives.
Energy Efficiency Measure (EEM): A permanently installed measure which can improve the efficiency
of the Customer's electric energy use.
Engineering model Engineering equations used to calculate energy usage and savings. These models
are usually based on a quantitative description of physical processes that transform delivered energy
into useful work such as heat, lighting, or motor drive. In practice, these models may be reduced to
simple equations in spreadsheets that calculate energy usage or savings as a function of measurable
attributes of customers, facilities, or equipment (e.9" lighting use = watts x hours of use).
Error: Deviation of measurements from the true value.
Evaluation: The performance of studies and activities aimed at determining the effects of a program; any
of a wide range of assessment activities associated with understanding or documenting program
performance, assessing program or program-related markets and market operations; any of a wide range
of evaluative efforts including assessing program-induced changes in energy efficiency markets, levels of
demand or energy savings, and program cost-effectiveness.
idah* lnigati*n Inergy Savirgs Evniuaticn Repon
Apnenilx li - Siessery of Ftequenliy'Uss$ Evuiuaiiitrt Teims
Rocky Mountain Power
Exhibit No. 5 Page 1287 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Nd\V$ilANT
Evaluatioru Measurement and Verification (EM&V): Data collectiory monitoring and analysis
associated with the calculation of gross and net energy and demand savings from individual sites or
projects which is performed in conjunction with a program or portfolio evaluation (see Evaluation).
Evaluated savings estimate: Savings estimates reported by an evaluator after the energy impact
evaluation has been completed. Often referred to as Ex Post Saoings (From the Latin for "from
something done afterward.")
Free driver: A non-participant who has adopted a particular efficienry measure or practice as a result of
the evaluated program.
Free rider: A program participant who would have implemented the program measure or practice in the
absence of the program. Free riders can be total, partial, or deferred.
Gross savings: The change in energy consumption and/or demand that results directly from
program-related actions taken by participants in an efficiency program, regardless of why they
participated.
Impact evaluation: An evaluation of the program-specific, directly induced changes (e.g., energy and/or
demand usage) attributable to an energy efficiency program.
Independent variables: The factors that affect energy use and demand, but cannot be controlled (e.g-
weather or occupancy).
Interactive factors: Applicable to IPMVP Options A and B; changes in energy use or demand occurring
beyond the measurement boundary of the M&V analysis.
Load shapes: Representations such as graphs, tables, and databases that describe energy consumption
rates as a function of another variable such as time or outdoor air temperature.
Market effect evaluation: An evaluation of the change in the structure or functioning of a market, or
the behavior of participants in a market, that results from one or more program efforts. Typically, the
resultant market or behavior change leads to an increase in the adoption of energy-efficient products,
services, or practices.
Market transformation: A reduction in market barriers resulting from a market interventiory as
evidenced by a set of market effects, that lasts after the intervention has been withdrawry reduced, or
changed.
Measuremenh A procedure for assigning a number to an observed object or event.
Measurement and Verification (M&V): Data collection, monitoring, and analysis associated with the
calculation of gross energy and demand savings from individual sites or projects. M&V can be a
subset of program impact evaluation.
Measurement boundary: The boundary of the analysis for determining direct energy and/or demand
savings.
iCaha lrrigaticr Energy Savings EvaiLiaiion Reiron
Apcendir A - Gi,;ssary ol Fcqu*ntiy-Used fivaiuaiiun Teinrs
Roclq Mountain Power
Exhibit No. 5 Page 1288 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
Pag* A-3
Nf\V$TANT
Metering: The collection of energy consumption data over time through the use of meters. These meters
may collect information with respect to an end-use, a circuit, a piece of equipment, or a whole building
(or facility). Short-term metering generally refers to data collection for no more than a few weeks. End-
use metering refers specifically to separate data collection for one or more end-uses in a facility, such as
lighting, air conditioning or refrigeration. Spot metering is an instantaneous measurement (rather than
over time) to determine an energy consumption rate.
Monitoring: Gathering of relevant measurement data, including but not limited to energy consumption
data, over time to evaluate equipment or system performancel p.g.r chiller electric demand, inlet
evaporator temperature and flow, outlet evaporator temperature, condenser inlet temperature, and
ambient dry-bulb temperature and relative humidity or wet-bulb temperature, for use in developing a
chiller performance map (e.g., kWton vs. cooling load and vs. condenser inlet temperature).
Net savings: The total change in load that is attributable to an energy efficiency program. This change
in load may include, implicitly or explicitly, the effects of free drivers, free riders, energy efficiency
standards, changes in the level of energy service, and other causes of changes in energy consumption or
demand.
Net-to-gross ratio (NTGR): A factor representing net program savings divided by gross program
savings that is applied to gross program impacts to convert them into net program load impacts.
Non-participant Any consumer who was eligible but did not participate in the subject efficiency
program, in a given program year. Each evaluation plan should provide a definition of a non-
participant as it applies to a specific evaluation.
Nonnalized annual consumption (NAC) analysis: A regression-based method that analyzes monthly
energy consumption data.
Participanh A consumer that received a service offered through the subject efficienry program, in a
given program year. The term "service" is used in this definition to suggest that the service can be a
wide variety of services, including financial rebates, technical assistance, product installations, training,
energy efficiency information or other services, items, or conditions. Each evaluation plan should define
"participant" as it applies to the specific evaluation.
Peak demand: The maximum level of metered demand during a specified period, such as a billing
month or a peak demand period.
Persistence study: A study to assess changes in program impacts over time (including retention and
degradation).
Portfolio: Either (a) a collection of similar programs addressing the same market (e.g. a portfolio of
residential programs), technology (e.9., motor efficiency programs), or mechanisms (e.g., loan programs)
or (b) the set of all programs conducted by one organization, such as a utility (and which could include
programs that cover multiple markets, technologies, etc.).
iriuhn lrfigat!crr Energy Savings Ivaiuaiicn R*po(
Apnendir A " Siossary oi Frequently-Usetl [vaiuaiiun Tetns
Rocky Mountain Power
Exhibit No. 5 Page 1289 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
ilage,r.4
r{d\V$TANT
Potential studies: Studies conducted to assess market baselines and savings potentials for different
technologies and customer markets. Potential is typically defined in terms of technical potential, market
potential, and economic potential.
Precision: The indication of the closeness of agreement among repeated measurements of the same
physical quantity.
Primary effects: Effects that the project or program are intended to achieve. For efficienry programs/
this is primarily a reduction in energy use per unit of output.
Process evaluation: A systematic assessment of an energy efficiency program for the purposes of
documenting program operations at the time of the examinatiory and identifying and recommending
improvements to increase the program's efficiency or effectiveness for acquiring energy resources while
maintaining high levels of participant satisfaction.
Program: A group of projects, with similar characteristics and installed in similar applications. Examples
could include a utility program to install energy-efficient lighting in commercial buildings, a developer's
program to build a subdivision of homes that have photovoltaic systems, or a state residential energy
efficiency code program.
Proiech An activity or course of action involving one or multiple energy efficienry measures, at a single
facility or site.
Rebound effech A change in energy-using behavior that yields an increased level of service and occurs
as a result of taking an energy efficienry action.
Regression analysis: Analysis of the relationship between a dependent variable (response variable) to
specified independent variables (explanatory variables). The mathematical model of their relationship
is the regression equation.
Reliability: Refers to the likelihood that the observations can be replicated.
Remaining Useful Life (RUL): An estimate of the remaining number of years that a technology being
replaced under an early retirement program would have remained in place and operable. Accurate
estimation of the RUL is important in determining lifetime program savings and cost effectiveness.
Reported savings estimate: Forecasted savings used for program and portfolio planning purposes.
Often referred to as Ex Ante Saoings (From the Latin for "beforehand.")
Reporting period: The time following implementation of an energy efficienry activity during which
savings are to be determined.
Resource acquisition program: Programs designed to directly achieve energy and or demand savings,
and possibly avoided emissions
Retrofit isolation: The savings measurement approach defined in IPMVP Options A and B, and
ASHRAE Guideline 1,4, lhat determines energy or demand savings through the use of meters to isolate
the energy flows for the system(s) under consideration.
i$a[* inigatrurr Energy Savi:rgs Evaiuation fiepart
Aprendir A - Siassary of Ftequentiy-Use$ Evaiualion Trims
Rocky Mountain Power
Exhibit No.5 Page 1290 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Poge A.-ii
h\r&V$tANT
Rigon The level of expected confidence and precision. The higher the level of rigor, the more confident
one is that the results of the evaluation are both accurate and precise.
Spillover: Reductions in energy consumption and/or demand caused by the presence of the energy
efficiency program, beyond the program-related gross savings of the participants. There can be
participant and/or nonparticipant spillover.
Statistically adjusted engineering (SAE) models: A category of statistical analysis models that
incorporate the engineering estimate of savings as a dependent variable.
Stipulated values: See "deemed savings."
Takeback effec* See "rebound effect."
Uncertainty: The range or interval of doubt surrounding a measured or calculated value within which
the true value is expected to fall within some degree of confidence.
idah* lrrigatr*n Energy Savings Evaiuaiicn Repofi
Apnrnuiir A - Gisssary uf Frcquentiy'Used Ivaiuaiion Tsrms
Rocky Mountain Power
Exhibit No. 5 Page 1291 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page i.-S
ru&v$t&NT
Rocky Mountain Power
Exhibit No. 5 Page 1292 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
8.1
To:
From:
Date:
Subject:
Measurement of Net Saztings Memo - January 27,2072
Shawn Grant Esther Giezendanner, PacifiCorp
Kevin Cooney, Matt Haakenstad, and Mike Yim, Navigan! Ellen Steiner, ]ess
Chandler, and |eremy Kraft, Energy Market Innovations, Inc
|anuary 27,2012
Measurement of Net Savings
This memorandum provides context and suggested approaches for estimating net savings so that the
team can decide whether to move forward with this approach or continue to make changes.
Estimation of net savings attempts first to assess program influence on the participants' decision to
implement an energy efficiency project. This estimation includes an examination of the program's
influence on three key characteristics of the decision related to the project: timing, scope, and extent.
Measurement of net savings then attempts to estimate program influence on the broader market with
respect to non-program actions (free-ridership and spillover). These two efforts are combined for an
overall estimate of net savings. First, the previous method is briefly described for context followed by
our proposed method moving forward.
Preoious method for measurement
The approach used in past evaluations for estimating program influence consisted of presenting
program participants a battery of six core questions, used in combinatiory to derive free-ridership scores
included in net-to-gross calculations. The six core questions were:
. Would the participant have installed the equipment without the program?
o Had the participant already ordered or installed the equipment before learning about the
program?
. Would the participant have installed the equipment to the same level efficiency without the
program incentive?
. Would the participant have installed the same quantity of equipment without the program?
. In absence of the program, when would the participant have installed the equipment; were they
planning to install the equipment in the same year?
r Was the equipment included in the participant's most recent capital budget?
Responses to these survey questions were evaluated using a scoring matrix (for an example of this
matrix see Appendix G.L in Final Evaluation Report For Wyoming's FinAnswer Express Program2) to
determine each participant's free-ridership score. Spillover was not quantitatively assessed in past
evaluations.
2 Navigant and EMI. Final ktaluation Report For Wyoming's FinAnswer Express Program. Prepared for Rocky Mountain
Power. October 25, 2011.
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ApreniJix S - Nel Savings [4ethod.;itgy-
PaSe B-1
N$VXT,{NT
Reasons for proposing a fleu) method
Though a consistent net savings estimation technique across programs is desirable to ensure
comparability, our experience with the previous method provided several "lessons learned." Based on
this experience, we believe a more rigorous approach is advisable and that the benefits of improved
validity outweigh the benefits of a consistent methodology between program years.
The changes recommended result in a more granular and holistic approach to assessing program
influence. First, the previous method did not adjust the questions to get meaningful responses by
measure type from the participants. This absence was particularly apparent on large custom projects,
such as Energy FinAnswer. For Wyoming, the savings by measure could be accomplished only for
lighting, and for previous evaluations, no attempt was noted in the reports to attempt to describe net
savings by measure. Also, our methodology did not include any estimation of spillover savings
attributed to the program and only assessed free-ridership. The absence of spillover in our net savings
estimation results in a conservative estimate of program impacts.
Our recommended changes to the free-ridership battery are based on recent research conducted in
Massachusetts on best practices in free-ridership and spillover estimation techniques3. This research is
not only timely, but it has also been rigorously reviewed. The report was created by a team of
experienced evaluators (Tetra Tech, KEMA, and NMR) and reviewed by program staff at eight utilities
operating in Massachusetts including National Grid and NSTAR, two of the largest investor-owned
utilities in New England both with long histories of energy efficiency programs. Members of the
PacifiCorp's evaluation team were integral to both the development and implementation of these
methodologies in 2007, 2009, and again in 2011. Implementing these recommendations provide the
following benefits to the evaluation:
o Targeted questions improve internal validity of free-ridership estimates.
o The methodology creates a calculated estimate of free-ridership savings compared with the
scored estimate previously used.
In addition to estimating program free-ridership, we also recommend that the evaluation quantitatively
assess participant spillover. As programs mature and transform their target market, quantifying
spillover allows for evaluators to recognize the programs' market effectsa. Spillover savings can be
classified into two categories based on measure types: "like" spillover and "unlike" spillover.
o "Like" spillover savings are the energy savings associated with additional high efficiency
equipment installed outside of the program of the same end-use as what that participant
installed through the program. For example, if the participant installed high-efficiency lighting
fixtures as part of the program, "like" spillover would be limited to any additional high
efficienry lighting installed without any assistance from PacifiCorp but influenced by program
activity. This type of spillover is quantifiable using program tracking savings as a proxy.
Historically, spillover results in a small portion of the overall program attribution (in the
Massachusetts studies cited above, it represented 8.8 percent of the overall attribution score).
3 Tetra Tech, KEMA, and NMR. Cross-Cutting C9I Free-Ridership and Spillot:er Methodology Study Final Report.
Prepared for the Massachusetts Program Administrators. April 1,8,201,1,.
a Saxonis, William P. New York State Department of Public Service. Free-Ridership and Spillover: A Regulatory
Dilemma. IEPEC. 2007
iCah* irrioati* Ensrg.v Savirgs Evaiuaiion ftepori
Apueni}r B - Siel +cavinss ,\4elhoc,;icgy
Rocky Mountain Power
Exhibit No. 5 Page 1293 of l365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
Pege ts-2
r-*Av${.&NT
o "Unlike" spillover savings are the savings associated with any other high efficiency equipment
installed outside of the program that are not of the same end-use category as what installed
through the program. Continuing the example above, if the participant installed high efficienry
lighting through the program, the high efficiency HVAC equipment installed outside of the
program would be considered "unlike" spillover as it is not the same end-use.
Spillover savings can come from participants, who are influenced by their program participation to
conduct further energy efficiency improvements, known as "participant" spillover. Spillover questions
can be added to the participant surveys conducted for projects completed at least 6 months prior. Asking
participants who have just completed a project with the program about spillover from that program may
not be productive, since participants are unlikely to have the opportunity to install any spillover
measures.
Spillover savings can also come from non-participants. Non-participants may be influenced by program
advertisements or other program actions (like contractor training, upstream buy-downs, etc.) and make
energy efficienry improvements without assistance from any program. This is known as "non-
participan/' spillover. Non-participant spillover can be most easily quantified by interviewing
participating vendors and other supply chain actors. During these interviews, the evaluation team can
assess the amount of measure adoption that occurred outside of the program compared to what
occurred through the program. Agair; using program-tracking data as a proxy, we can estimate outside
sales. This estimate of outside sales will capture both "like" and "unlike" spillover savings. We will
remove "like" spillover estimates as reported by participants to avoid double-counting.
Limitations
There are limitations with our proposed changes (these limitations were also present in our previous
methodology). Our participant estimates are still limited to self-reported responses to a hypothetical
situation (i.e., what would have happened absent the program). However, we feel that proper survey
design and fielding protocols can mitigate the problems associated with self-reports,6 In addition,
without detailed market level baseline data, the self-report methodology is still the most appropriate and
cost-effective way to estimate program influence at the detail needed to assist in program designT.
Likewise, our experience in Wyoming indicated that it was not fruitful or cost-effective to review project
file text for the purposes of enhancing the self-reported responses.
Figure 1 illustrates the adjustment steps taken when evaluating net savings. In contrast with the gross
savings, which usually can be directly measured with instrumentation, the adjustments made to reach
net savings are measured indirectly. This is important to keep in mind as the farther from the actual
measure we get, the less precise findings can be.
s Keating, Kenneth M., PhD. Free-Ridership Borscht Don't Salt the Soup. IEPEC.2009
5 Megdal, Lori, Megdal & Associates, LLC, Yogesh Patil, Energy & Resource Solutions, Inc., Cherie Gregoire and
Jennifer Meissner, New York State Energy Research and Development Authority, and Kathryn Parlin, West Hill
Energy & Computing, lnc. Feasting at the Ultimate Enhanced Free-Ridership Salad Bar. IEPEC. 200
7 National Action Plan for Energy Efficiency (2007). Model Energy Efficienry Program Impact Evaluation Guide.
Prepared by Diane Munns and Jim Rogers. <www.epa.gov/eeactionplan
!$ah* lrilgatrcn Energy Savings Evaiuaticn Rei:ori
Apcendir B - Net Savings tr4ethocaiagy-
Roclq Mountain Power
Exhibit No. 5 Page 1294 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page B-3
N&V$TAN]'
For illustration purposes, consider a participant in the FinAnswer Express program:
A participant installs a variable frequency drive on a fan motor with the program and
gets an incentive. The program and evaluators can measure the energy consumed by the
new variable frequenry drive either directly, depending on configuratiory or based on
the hours it is observed to be operating and its features. This consumption is compared
to a baseline estimate of what would have been consumed by a direct drive in the same
case. There is high confidence that the savings are accurate.
Then, the evaluators ask the participant if they would have installed the same variable
frequency drive at the same time without the incentive; the participant can consider
whether the previous drive needed to be replaced at the same time and the relative costs
to decide what might have happened. Thery the evaluators ask the participant if they
installed any other variable frequency drives since participating in the program and
how much the program influenced their choice; the participant can consider the time
frame of installation and determine (probably more easily with this equipment type than
some others) if something similar was installed.
Exploring still further, the evaluators ask the participant if they installed any other
efficient equipment - now the participant has to think about the time frame and relative
efficiencies of any equipment purchased since the program involvement. When asked
how influential the program was on these purchases, the participant is expected to think
through many decisions.
As a thought exercise, we can imagine that gross savings for a program and measure type are estimated
to be 100 k\A/h. Based on participant responses, the free-ridership ratio is estimated tobe20/"; the sample
was random and drawn to meet 90% confidence and 10% precisiory so the range of this estimate is 18%
to22"h. Of all the possible spillover, only "like" spillover can be quantitatively assessed, and it is
estimated to be 10% with the same confidence and precision leading to an estimate of 9V" to 11%. The
unlike participant spillover questions revealed that participants are more likely to install efficient unlike
idahc irrigatiolr f nargy Savings Evaiuaiion Renan
Apnendir B - I't'et Saviqs l,4elnodi:ii;Ev
Rocky Mountain Power
Exhibit No, 5 Page 1295 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
PaS* ts-{
N&V$ TANT
equipment than like equipment and attribute it to program influence, and market allies confirm that they
are seeing activity outside of the program.
These adjustments result in net savings of 90 kWh with a range of 87 kwh to 93 kWh. However, these
numbers cannot capture the other spillover that we can only qualitatively assess. We may say we think it
is closer to the higher number because participant and market ally responses reflect additional program
influence, but this is a subjective assessment and may not be appropriate given the need for defensible
savings estimates. In some cases, we may find high free-ridership responses and not identify any
quantifiable "like" spillover even if much unquantifiable spillover can be described. In these cases,
reporting net savings may reflect poorly on the actual program influence.
Though this method provides net savings that are much less precisely estimated than the gross savings,
we feel that, given the design of the PacifiCorp programs, it is the most cost-effective and consistent
method to assess program attribution.
Proposed method for tneasurement
This section includes brief recommendations for measuring free-ridership and spillover to get to a net
savings estimate.
Free-ridership
To improve the test of the counterfactual (i.e., what would have the participant done without the
assistance of the program), we recommend more targeted free-ridership questions. As a start, we
recommend refining the initial free-ridership question (Would the participant have installed the
equipment without the program?). This question would be altered to include "at the same time" to
clarify the timing component of the decision. It would also be preceded by a brief description of all the
assistance the customer received as part of their participation in the program (e.g., technical design
assistance, the amount of any monetary incentives, any program-subsidized financing). This description
would be customized by program and by project (as data are available). This description is intended to
remind the participant of all the ways the program may have influenced their decision to move forward
with a specific project.
Thery we recommend asking targeted questions about quantity and efficiency of equipment that would
have been installed (or actions that would have been taken) without the program while referencing what
the participant did with the program.
Including these revisions in the free-ridership battery will allow the evaluation team to use a calculation
approach to estimating the amount of energy savings that may have occurred without the program.
This approach is detailed in Figure 2 below.
idahn in'i$att+n Enetgy Savings Evaiuaticn ,tepart
Apcen,Jix B " Nel Savings l,4elhorx*i';gv
Roclq Mountain Power
Exhibit No.5 Page 1296 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pag* S-{i
r+s\xs$tANT
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Ijigure 3. Enhancecl
Rocky Mountain Power
Exhibit No. 5 Page 1297 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
f:ree-ridership Calculation Appruach
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Based on the participant's responses, the team can estimate the percentage of equipment that would
have been installed at the same time without the program (the quantity score) and the percentage of that
installed equipment that would have been high efficiency equipment (the efficiency score)8. The product
of these two estimates is the initial free-ridership ratio.
Free-Ridership Ratio = Quantity Score x Efficiency Score
For example, a participant that installed four high efficienry HVAC units through the program reports
that, without the program, they would have not installed the same measures at the same time. Following
up, the respondent states they would have installed some equipment and it would have been installed
within 12 months. When probed about the level of efficiency of the equipment that would have been
installed absent the program, the participant reports that they would have installed equipment that was
more efficient than baseline but not as efficient as the program-eligible equipment. Finally, they report
they only would have installed one unit (instead of four). Using the scoring above, this participant's
efficiency score would be set to 0.5 and the quantity score would be set to 0.25. Their initial, unadjusted
free-ridership score is then the producte of these two scores or 0.125. This figure indicates that 12.5
percent of the savings attributed to this project would have occurred absent the program.
8 Question text will be altered for projects where quantity is not applicable. For example, if a project consisted of the
installation of an EMS, the quantity question would be skipped.
e This multiplicative approach is appropriate as the score is the result of a product of the quantity installed and not a
product of probabilities (Keating. Free-Ridership Borscht: Don't Salt the Soup.IEPEC. 2009).
i,iai:+ lrigaticrr Inergy Savirgs Evairiaiioii F.eni-.-ri
irpntnd:r B - I'irl Savirils l,4etilcrciit3v
!:t-^.^ [ I
NC\V$TANT
This ratio can then be adjusted by the responses to other questions already referenced in the battery.
These include any reported changes in the timing of projects as a result of the program and the reported
influence of various factors on the decision to install the equipment. These adjustments are not detailed
in this document, as they will be tailored to individual program design. As part of these adjustments, we
recommend that the list of factors be expanded to include "other PacifiCorp program participation."
This addition will allow evaluators to adjust free-ridership based on PacifiCorp's portfolio level outreach
efforts. For example, if a participant received sequential incentives from two different PacifiCorp
programs, his or her participation in the first program may have increased their awareness of the
secondary program. In this situation, their responses to free-ridership questions regarding the secondary
program may present this participant as a free-rider. In this situatiory we can use the responses to the
influence questions to assess if the secondary project was influenced by PacifiCorp actions from another
program. If so, PacifiCorp should receive attribution for those savings and free-ridership would be
adjusted downward.
This methodology requires several adjustments when applied to programs that offer custom incentives
or to programs that utilize unique mechanisms to achieve savings. First, the self-report survey should
include complete and accurate descriptions of what measures were implemented as part of custom
projects. Also, as custom programs often work with participants to implement a variety of end-uses
under the "custom" umbrella, custom projects should be evaluated holistically and not at the end-use
level. Similarly, unique programs may require additional refinements to question wording. For example,
when assessing a recommissioning program, the interview may seek to assess the decision to conduct
the initial project study instead of the decision to implement the energy-saving opportunities identified.
Finally, for complex or large projects, the self-reported estimate can be verified by a review of project
documentation (if available) and follow-up interviews with the contractors associated with the project.
These additional steps can be costly and should only be considered when the savings of the project make
up a significant portion of the program's overall savings or contractor outreach is a significant part of the
program design.
As an example, we provide recommended free-ridership questions for the Energy FinAnswer program
in Figure 3.
idahc lrrigaticn Energy Savirgs Evaiualion Rei:an
Apr*ndix B - l.,iel Savings l,4Bthodcii,$v
Rocky Mountain Power
Exhibit No, 5 Page 1298 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pasn [i-i
*u,.\\s$ilANT
Fi 3. [:ree l{.idershin I}a Extract frorn Ene FinAn sv"'er Su rv"e v DI{AIrTlo
...[READ: "With the Energy liinAnsrver program, [:lRl,l receivi:rd teclurical assistance and financial
ince ntives. FI R.lr'l in stalled l,i$T-M E.ASLI RE S u'i th th e i:rograur."
REPEAT FC}R EACH MEASTIRE-TYPE_# I,ISTED UF TO ].
IIEAD: "iior these next questio*s, please focus on MEASLIitE..l'YPE...# rvhich includes
tulEAS UIi.E-T'YPE-#-lll $T for your proj ect. "l
FRl. \trrithr:ut the program, meaning without either the technical assistance or the financiai
incentive, n ould you ha,,,e still installed the exact same &1EASURE...T'YPE..# at tire same tirne?
[lF" 1=YES] => REPEAT for next I\,IEASI"JRE-TYPE or g(] on to spillover
llF 1=N0J => g0 t0 2
F'R3. Without the plogt'ant, nould you have installect anlr MEASURE-]'YPE-# equipmr:nt?
IlF Z-YES l*> go til 3
[F Z=NC]l=> GO BACH TO I fbr next h{E.4SURE_TYPE or go or1 to spi}}orrer
FR4. Wittrout the prograln. would you have installed this r,,quipment rvilhin 13 months ol n hen
ynu did n ith the program?
llF 3=YESJ--> go to 4
ilF: 3=N0l=> GO EACK'f0 I for next II4EASURE_'|1'PE or lio on to spillover
llF .APF'l.,lCABt,El FR5. Relative to the energy etlir:iency of MEASLIRE_TYPE_# installed through
the program, how would you cltaracterize the efficiencS.z of equipment you n ould har,e installed
wilhriut the program?
a. Just as efJicient;rs inslalleri with the prosrarn
b. Lol.rer than installed through the program, but better than the standard efficienc,v
c. Standard efficiency
[F APPI,ICABL,EI FR5. Wou]d you have insfirlied the same ;rmount of N{EASI.IIIE_TYPE_#?a. Yes
b. No => FR{:a
FRtia. Nfrire cr less?
IrR6b. l{ow rnuch more or lessi'
G0 EACK T0 1 for next h{EASIJRE*TYPE or go on ro conb-isterlcy or spillnver...
10 Variables and notes to the interviewer are in ALL CAPS. The variable MEASURE_TYPE is grouped and worded
by measure types, such as "lighting equipment" or "HVAC equipment" with specific measures installed identified
for the respondent to be sure they understand what is meant.
idaht irricaii*ir Enrrgy Savugr Fvaiuation Rtpori
Api*ndir. 3 - liiel Savin$s l-{ethcij$is$y
Rocky Mountain Power
Exhibit No. 5 Page 1299 of I 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page ts-$
,,nl{ l\\j x t,{ N T
Spillooer
We recommend asking participants about both "like" and "unlike" spillover with an understanding that
the "like" spillover can by quantitatively assessed and the "unlike" spillover will be characterized
qualitatively (though efforts will be made to use deemed estimates if possible). With "like" spillover, we
c:u1 use the gross savings estimates from the program tracking database as a proxy for the "like"
equipment. With no savings data to use as comparisory our ability to confidently assign savings to
reported "unlike" spillover projects is limited by the amount of data participants are able to provide. For
example, if a participant reports that they installed "some high efficiency lighting" but cannot recall how
much or what type, we can oniy qualitatively report that project as spillover. However, if the participant
is able to provide detailed specifications about the project (e.g., 40 T8s with ballasts), we can then use
deemed savings values as a reference for assigning savings. Savings for measures without deemed
values (e.g., recommissioning projects, industrial process improvements) can only be verified via on-site
and our spillover assessments will be qualitative in nature.
We also recommend asking market allies about program-eligible sales outside of the programs. Market
ally responses and participant "unlike" spillover responses will allow a qualitative discussion about the
estimated magnitude of spillover relative to the "like" spillover that can be quantified.In addition,
interviews with market allies will provide an assessment of spillover across the entire program year. As
we are planning to interview participants quarterly regarding their projects, our estimates of participant-
reported spillover savings will under-represent annual savings as potential spillover projects completed
after that three month period will not be captured. However, market ally interviews will only be
conducted once per evaluation year and cover the entire program year, capturing all spillover projects in
the process. Likewise, the spillover reported by market allies will capture "unlike" spillover savings that
we were only able to qualitatively assess from the participant reports.
Similar to the free-ridership battery, question wording will be adjusted for unique programs (e.g.,
recommissioning) or for custom projects. The like spillover questions will be repeated for the same two
measure types as used for the free-ridership battery, as applicable.
The participant spillover questions recommended as part of the participant surveys and interviews are
listed below for both like an unlike spillover.
LIKE
o Since participating in this program, have you purchased and installed any additional
Imeasures]?
o What did you purchase or install? How many did you purchase or install?
o Did you receive assistance from [utility] or another organization?
. On a scale from 1 to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you
"strongly agree" , please rate the following statement: My experience with lutility)'s energy
fficiency program influenced my decision to install other high fficiency equipment on my own.
. Why did you not apply for an incentive from [utility] for this equipment?
idahc lrigaticir Energy Savings Evaiuation Repa(
Aprendir B - Net Savings [4ethocoiogi,-
Rocky Mountain Power
Exhibit No.5 Page 1300 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
vaa8 s-lj
tsf\xr$ilANr"
UNLIKE
o Since participating in this program/ have you purchased on installed any OTHER energy
efficienry improvements?
What did you purchase or install? (PROBE FORAS MUCH DETAIL AS POSSIBLE)
How many did you purchase or install?
Did you receive assistance from [utility] or another organization?
I'm going to read a statement about the equipment that you purchased on your own. On a scale
from L to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you "strongly
agree" , please rate the following statement: My experience with lutilityl's energy fficiency program
influenced my decision to install other high fficiency equipment on my oun.
Why did you not apply for an incentive from [utility] for this equipment?
The non-participant spillover questions recommended as part of market ally interviews are listed below.
. Approximately what percent of all [measure] sales in [state] last year would you estimate was
from program-eligible equipment?
Approximately what percent of your [measure] sales in [state] Iast year was from program-
eligible equipment, that is [description of eligibility requirements]?
Did you sell more program-eligible equipment last year?
According to our records, you sold [quantity] [measure] as part of projects that received
program incentives. To the best of your knowledge did you complete any [measure] projects
with [utility] customers that did not receive program incentives? If so, how many?
Do the tutilitvl Drosram incentives influence vour stockine/selline of prosram-elieible
Imeasures]?
Does the [utility] plgglalqjde4qatiql influence your stocking/selling of program-eligible
Imeasures]?
Net saaings
Spillover savings can be combined with free-ridership savings to create a comprehensive picture of
program influence. This combination is often referred to as a net-to-gross ratio and is calculated by
adding the spillover ratio to the inverse of the free-ridership ratio or:
Net-to-Gross Ratio = (7-Free-Ridership Ratio) + Spillooer Ratio
Gross savings are then multiplied by the resulting ratio to find net savings by measure type and
Program.
iCahc lrrigaiicn Energy Savir:gs Evaiuaiion Reilr:ri
Apcendir B - Net Savings l'4ethocoi,.:gy
Rocky Mountain Power
Exhibit No. 5 Page 1301 of 1365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
a
a
Page B-1ii
tl*&V$tANT
8,2
To:
From:
Date:
Subject:
Roclq Mountain Power
Exhibit No. 5 Page 1302 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Net Saoings Scoring - June 78, 20L2
Shawn Grant Esther Giezendanner, PacifiCorp
Kevin Cooney, Matt Haakenstad, Mike Yim, and Jeff Erickson, Navigan! Ellen
Steiner, ]ess Chandler, and ]eremy Kraft, Energy Market Innovationt Lrc
June 18,2012
Net Savings Scoring
This memorandum provides a detailed description of how the evaluation team plans to estimate a net-
to-gross (NTG) ratio for the portfolio of the PacifiCorp energy efficienry programs. An NTG ratio is a
comprehensive picture of program influence and is the ratio of net savings to gross savings and is an
indication of the programs' influence on customers' decision-making regarding energy efficiency at their
facility.
Ooeroiew
Using self-reported responses, the evaluation team's estimation of net savings first attempts to assess the
program's influence on the participants' decision to implement an energy efficienry project and what
would have occurred absent the program's intervention. This estimation includes an examination of the
program's influence on three key characteristics of the project: its timing, its level of efficienry, and its
scope (i.e., the size of the project). This estimate represents the amount of savings attributed to the
program that would have occurred without its intervention and is often referred to as "free-ridership."
The team's measurement of net savings then attempts to estimate program influence on the broader
market as a result of the indirect effects of the program's activities. This estimate, often referred to as
"spillooer," represents the amount of savings that occurred because of the program's intervention and
influence but that is not currently claimed by the program. Spillover savings can be broken into two
categories of savings: "participant" spillover and "non-participant" spillover. Participant spillover
savings occur directly (i.e., program participants install additional energy efficient equipment), while
non-participant spillover savings occur indirectly (i.e., market allies install additional energy efficient
equipment to customers that choose not to participate as a result of the program).
A program's net savings are adjusted by both free-ridership and spillover savings at the measure level
and then extrapolated to the program. The net savings are the program-reported savings minus any free-
ridership savings plus any identified spillover savings, or:
Net Program Saoings = Gross Program Saoings - Free-Ridership Sat:ings + Spillooer Saaings
Often, this finding is described as a "net-to-gross ratio." This ratio is the net program savings divided by
the gross program savings, or:
Net-to-Gross Ratio = Net Program Saaings I Gross Program Saoings
Fre e -ridership C alculation
To determine free-ridership, the interview presents respondents with a series of questions regarding
their decision to install the equipment promoted by the program. The team then scores the responses to
these questions to determine the level of free-ridership. A score of 1.0 indicates the respondent is a
idailo lrigati$ir Inergy Sauings Evaiuaiitn Rsmfi
Apuendix [1 - I'let Savings !\,letho<i*ingy
Fag* S-i l
Ns\v$fi.&NT
complete free-rider; they would have installed the exact same equipment at the same time and in the
same quantity without the program's assistance. A score of 0.0 (zero) indicates the respondent is not a
free-rider; that is, without the program they either would not have installed any equipment within 12
months of when they did or they would have installed baseline efficient equipment.
As the first step in scoring, the evaluation team reviews the interview responses to determine if the exact
same project (in terms of scope and efficiency level) would have occurred at the same time without the
program. If so, the respondent is scored as a complete free-rider. If not, the evaluation team reviews the
responses to determine whether the project would have occurred at all within the same 12 month period.
If not, the respondent is scored as a non-free-rider. If the project would have occurred within the same 12
month period but altered in respect to its size or efficiency level, the respondent is scored as a partial
free-rider. To assess the level of partial free-ridership, the evaluation team uses the respondents'
estimates of the percentage of equipment that would have been installed within 12 months without the
program (the quantity score) and the percentage of the installed equipment that would have been high
efficiency equipment (the efficiency score)ll.If the project would have occurred with some changes absent
the program, the product of these two estimates is the initial free-ridership ratio or:
lnitial Free-Ridership Ratio = Quantity Score x Efficiency Score
After scoring the initial free-ridership ratio, a series of consistency check questions is reviewed. These
questions ask about the influence of the program's interventions (e.9., financial incentives, technical
assistance) and address the counter-factual (e.g., what would have happened without the program). For
example, if the respondent states that the financial incentive was extremely important to their decision
(FR1D = 5) but that they would have installed the exact same equipment at the same time without the
program (FR2 = 1), the interviewer asks them to describe in their own words what impact the program
had on their decision (FR7). During the scoring process, these responses are reviewed by analysts to
determine which scenario is correct and are scored accordingly to create an adjusted free-ridership score.
Finally, the free-ridership score is adjusted to account for prior program participation. Given
PacifiCorp's efforts to cross-promote their entire portfolio of energy efficiency programs, a respondent's
prior participation in a PacifiCorp program may have been influential in their decision to participate in
the current program. Ideally, this influence would be attributed to the prior program as spillover savings
since that program was responsible for the influence. However, given the portfolioJevel marketing
approach that PacifiCorp implements, respondents are unlikely to be able to identify the prior program
by name. Therefore, the evaluation team will attribute the savings credit to the current program.
To calculate this credit, the team will review the respondents' rating of the influence of the prior
program. If the respondent rates their previous participation as a "4" or "5," their adjusted free-ridership
is reduced by either 50 percent or 75 percent respectively.
li Question text will be altered for projects where quantity is not applicable. For example, if a project consisted of the
installation of an EMS, the quantity question would be skipped.
iCaIc lrigaticn Energy Savings Evaiuaiian li:eno(
Appendix S - |tet Saviirgs li,lethacicirgv
Rocky Mountain Power
Exhibit No. 5 Page 1303 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Page ts^i ?
ro-r,&vttANT
Figure 4 illustrates the series of questions asked to support this calculation while Table 1 provides
detailed scoring and descriptions of eadr question.
ldaho lrigation Energy Savings Evaiuation Report
Appendix fi ' Net Savings Methodoiogy
Rocky Mountain Pofler
Exhibit No. 5 Page 1304 of 1365
Case No. PAC-E-14-07
Whess: l(ethryn C. Hymas
Page B-i 3
\!t\.V $T A N-T
Rocky Mountain Power
Exhibit No. 5 Page 1 305 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
'tr'able 1. Irree-rid ership Calcul ati on Approa ch
FRlB
FR2
FR7
i:..is'&l"F
Consistency Check
:$ffiiiiiffi#ffiffiiwffi
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ii:ii:iiiii:ii:lilioIl8.l8tErlclI.iistrtEG,l(i:iiiiiiiiiii:iiii:iiiiiiiiii:i:i:::::'::::::::::::::::::::::::: :::
If yes, free-ridership = 1
H&g...'iii.iii:i.iii
.!,!:!:!:!+!;:!j::,:!-,,.:'!.;;r:!:!,!:l::,!:!:!:!,,,,:,,!:::!:::!:!:!
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If between high efficienry and
If yes, quantity score = 1
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free-ridership = Q
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t
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Yes
Rocky Mountain Power
Exhibit No. 5 Page 1306 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Figure 4" Fre*rid*rship Calculation Approach
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For example, a participant that installed four high efficiency HVAC units through the program reports
that, without the program, they would have not installed the same measures at the same time. Following
up, the respondent states they would have installed some equipment and it would have been installed
within 12 months. When probed about the level of efficiency of the equipment that would have been
installed absent the program, the participant reports that they would have installed equipment that was
more efficient than baseline but not as efficient as the program-eligible equipment. Finally, they report
they only would have installed one unit (instead of four). Using the scoring above, this participant's
efficiency score would be set to 0.5 and the quantity score would be set to 0.25. Their initial, unadjusted
free-ridership score is then the productl2 of these two scores or 0.125. Likewise, they state that the
incentive was important and that previous participation was not important. These responses indicate a
consistent installation scenario and no further adjustment is necessary.
12 This multiplicative approach is appropriate as the score is the result of a product of the quantity installed and not
a product of probabilities (Keating. Free-Ridership Borscht: Don't Salt the Soup.IEPEC. 2009).
idiilo lil'ii1ati{in Eneqy Savngs Evaiuairiin R*iori
Ai:uendir [: - li*t Sevings \.'ltti-rrci+i+.lv
F-d d\v $t..{ N T
Spillooer Calculation
P arti cip ant -rep ort e d Spill o a er
Similar to free-ridership, to determine spillover, the interviewer presents respondents with a series of
questions regarding their decision to implement projects outside of the program (i.e., projects that did
not receive any assistance from the program). These responses are then scored to determine the level of
spillover. The evaluation team will ask participants about both "like" and "unlike" spillover projects.
"Like" spillover is associated with equipment that is similar to the equipment incented by the program.
In comparisory "unlike" spillover is associated with equipment that is not similar to the equipment that
was incented by the program. Using the program-reported per-unit savings as a proxy, "like" spillover
savings can by quantitatively assessed. However, as it has no comparative program savings data,
"unlike" spillover can only be characterized qualitatively (though efforts will be made to use deemed
estimates if possible).
To assess "like" spillover, the evaluation team first reviews interview responses and determines whether
the respondent installed any additional equipment similar to what was incented through the program. If
additional equipment was installed, the team determines whether it was rebated through a PacifiCorp
program. If not, the team then estimates the amount of potential spillooer saoings associated with the
project. This estimation is created by using the program-tracking savings as a proxy for per-unit savings
and adjusting for the amount of equipment installed. The team will also adjust for equipment similar to
that installed through the program but of a lower efficiency. If the respondent states that efficiency level
is lower than what was installed through the program but better than standard efficiency, the potential
spillover savings are reduced by half. Since the energy savings associated with the reduced efficiency
project will be less than the project incented by the program, this adjustment credits the program with
some, but not all, of the savings.
In order to account for the program's influence on the spillover savings, the team then adjusts the
quantified spillover savings by the free-ridership rate identified earlier or:
Spillozter Saaings = Potential Spilloaer Saaings X Free-ridership Factor
As a consistency check, the team uses an additional question to check the evaluated free-ridership rate.
Respondents are asked to rate the level of influence from the program on their decision to purchase the
additional equipment. The team compares these responses to the identified free-ridership rate to identify
any contradictory responses (i.e., free-ridership factor of 1.0 but spillover influence is high or free-
ridership factor of zero but spillover influence is low). If the responses are contradictory, the potential
spillover savings are reduced by 50 percent. Without further evidence, the team cannot objectively
determine which statement of influence is correct. Adjusting the potential spillover savings by 50 percent
acknowledges this uncertainty without overly penalizing or rewarding the program.
Figure 5 illustrates the series of questions asked to support this calculation while Table 2 provides
detailed scoring and descriptions of each question.
i,jaho lnigaticri Energy Savirgs Evaiuairsn Ren,:fi
F,puendix $ - l.ist Savings N,,leiiraccicgv
Rocky Mountain Power
Exhibit No. 5 Page 1307 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Sarr* F.-i R
Nr\\J$TANT
Rocky Mountain Power
Exhibit No. 5 Page 1308 of 1365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
If no, potential spillover savings
=0.
If lower than program but
higher than standard, reduce
potential spillover savings by
half.
lf standard efficiency, potential
..s{.td. l11, nid,tggu.., tnrufi#i,#am.,iFu m*ffi.lt..yr rffiru i*..,u iBo+er ,j,:,.iii:..,..,,,,,
,..iiii...'
SPlf On a scale from 1 to 5, with 1 indicating that you Consistency Check
"strongly disagree" and 5 indicating that you "strongly
agree" , please rate the following statement: My experience
with the PacifiCorp program influenced my decision to install
!daho h'ilgat:cri Energv Savirgs Evaiuaiion h:eno(
Aprendix $ - I'iet Savings [{ethodaicgy
illover Calculation A
Pa.g+ S-i?
rus\v$tANT
Rocky Mountain Power
Exhibit No. 5 Page 1309 of '1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
,}--------Yes
A similar process is used for "unlike" spillover. However, since the measure is not the same as the in-
program measure, the team has less information from which to calculate the measure's savings. Thus the
team's ability to confidently assign savings to reported "unlike" spillover projects is limited by the
amount of data participants are able to provide about the measure and its use. For example, if a
participant reports that they installed "some high efficiency lighting" but cannot recall how much or
what type, we cannot reliable assign any spillover savings to that project. However, if the participant is
able to provide detailed specifications about the project (e.9.,40 T8s with ballasts), we can then use
values based on savings from similar measures in the program-tracking database as a reference for
assigning potential spillover savings. Savings for measures without deemed values (e.g.,
recommissioning projects, industrial process improvements) can only be verified via on-site and our
spillover assessments will be qualitative in nature. If "unlike" spillover projects of significant magnitude
are identified, on-site visits may be cost-effective. In this situation, the team will discuss conducting
visits in order to quantify the savings.
i,Jahc lriqaticr Energy Saviiigs [vaiuaiitn iier.r$
Aprendix B - liet Savings l\{ethodoingy
N$V$ TANT
N o np articip ant Spill o o er
To capture a comprehensive picture of spillover, the team also asks market allies about program-eligible
sales outside of the programs as part of our in-depth interviews with this group. By examining the
amount of program-eligible sales occurring outside of the program, the team can create high-level
estimates of nonparticipant spillover that can be added to the participant-reported spillover savings.
First, the team determines whether the market ally installed any program-eligible equipment that did
not receive incentives from the program. If so, the team compares the quantity of equipment installed
outside of the program to the quantity tracked through the program-tracking database. Using the
savings associated with that market ally in the program-tracking database, the team can then estimate
the amount of savings installed outside of the program. Note that market allies may have difficultly
reporting the amount of equipment that did not receive program assistance. As these "don't know"
response will not be used in analysis, our estimate will likely be conservative.
Finally, the team determines the influence of the program on these sales in order to attribute the
nonparticipant spillover savings to the program. The team examines responses to three questions
regarding the influence of the program incentive and information on the stocking and selling of
program-eligible equipment. Respondents are asked to rate the influence of the program on a scale of 1
to 5 where 1 is "no influence" and 5 is "a great deal of influence." If the average response is greater than
4, 100 percent of the savings installed outside of the program are attributed to the program. If the
average response is greater than 3 but less than or equal to 4, 75 percent of the savings are attributed to
the program. If the score is greater than 2 but less than or equal to 3, 50 percent of the savings are
attributed to the program. None of the savings associated with market allies with average influence
scores lower than 2 are attributed to the program.
Table 3 describes in detail the questions asked and their associated scoring.
Table 3. N rtici t Spillover Caleulation ch
Rocky Mountain Power
Exhibit No. 5 Page 1 31 0 of 1 365
Case No. PAC-E-I4-07
Wtness: Kathryn C. Hymas
27 According to our records, you sold [NUMBER OF
PROJECTSI of [TYPE] as part of projects that received
program incentives. To the best of your knowledge, did
you complete any [TYPE] projects [IF LIGHTING OR
HVAC: that would have been eligible for the programl
that did not receive program incentives? If so, how
(Projects outside of
program/?rojects through
program) X program savings
associated with market ally =
potential nonparticipant
spillover
Net-to-Gross Ratio
The evaluation team will determine measure-specific free-ridership and spillover rates. To determine
program-level rates, the team will weigh the rates by savings and for any disproportionate sampling.
Pelo S.- i Q
i$eho lrtigallar Energy Savings Evaruaiicn Reno(
Apiendix S - li*t Savings l\{eihodring-r,
N$V$TANT
This weighting ensures that the analysis is representative of the overall program both in terms of its
distribution of savings and its mix of measures. For example, projects that account for a larger
proportion of the program's overall savings will have more influence on the final program-level rate. In
addition, if projects that are part of certain sub-groups within a program are intentionally selected more
frequently (i.e., over-sampled) as part of the sample design, those projects will have less influence on the
program-level rate.
Likewise, the team will apply similar weights to the market-ally reported nonparticipant spillover
savings to determine measure-level estimates. To avoid double-counting, participant-reported spillover
estimates will be subtracted from the market ally-reported estimates. If, at the measure level, the
participant-reported spillover estimate is less than the estimate reported by market allies, the team will
add the difference to the spillover rate. If the participant-reported estimate is greater than the estimate
identified by market allies, the team will not add any nonparticipant spillover savings to the overall
estimate.
The team will then create the final net-to'gross ratio. This ratio is the net program savings divided by the
gross program savings or:
Net-to-Gross Ratio: Net Program Satsings I Gross Program Saoings
The net program savings are the program-reported savings minus any free-ridership savings plus any
identified participant and nonparticipant spillover savings or:
Net Program Saaings = Gross Program Saoings - Free-Ridership Saaings + Participant Spilloaer Saaings +
N onp articip ant Sp illoo er S aa in gs
Note that as the nonparticipant spillover ratio is created for each market ally and not each participant
the final ratio is adjusted at an aggregated level.
The final, weighted Net-to-Gross Ratios for each Measure Group are provided in Table 4.
Table 4, Idaho IES Weighted S{easure Group Net-to-Gross Ratios
Measure Group NTG
Redesien o.927
Pivot/Linear Upgrade 0.570
Eouioment Exchanse 0.572
Program Weighted o.745
lCahc lrigahcn Energy $avirgs Evaiuaiisn Ren**
Aprcndix S - l,lst Savings Methoc*icgt
Roclry Mountain Power
Exhibit No. 5 Page 1311 of 1365
Case No. PAC-E-I4-07
Wtness: Kathryn C. Hymas
Fai;e ts-?0
h'$v$t..\NT
Rocky Mountain Power
Exhibit No. 5 Page 1312 of I365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table 5" Measure Grourr Grass for Idaho IES (1009-20111
PligltlHnaeti:tl;eg1p:dt:;:::, ::,;:;:,,;,,:
vEquipment Exchange -3,739,106
iiiEi7,,$.- 080
-26L,707
u,iji$l,{*siW
-3,739,LO6
ii...iii:i:iii+,{$6iH},fi
-4,172,7L9
L,sLt,982
*ffii8s*"
8,869,898Program Total
'tr'able 6. Measure Group Er.aluated Net Ilealization ftates for ldaho IES (2009-30'11]
ilIE*lri:Xi$:drili|tqff
Equipment Exchange 00
;iiliiis.$,tt'*,,o4, iiiiirilii* i
2,998,636 -73t,882
L,5LL,982 0%
:tiii*i::*i,,......4*iffi *.....i...i.i'tii.. +si
8,869,898 a8%
00
;i jiiliii$f;$-s,ffi ...;iiiiiiiiiii jl;l $ tltnf,
1,478,t58 .1,133,377
iiii:i:iiiiirtii:i::::::::::::::::i:i;::::::::i:::::::iii:i:iili:iiri:.:.ri:r::i:::i:i::::iii:i:
$srlHint,:l$euf sii$'*$:.i.i.:'iliili
Program Total
x.
fr
::::::r
Table 7. Measure Level Energy Impacts per Unih Calculated, Iligh, Lon, ane{ Evaluated
21.6"k
iiiiiiiiiiiiiiiiiiif''9?8iiiiiii:iiiiiii
97"/"
..:rrirrrr;r..:.:$,#Srii:i..:;.iil
153%
:L:1;;1li;45!4,tt;;1,;;;.t;;;.
44"k
i;liiiii'2ff-8",,ii,,,i,i
| -"107 -3
i.irr.iii.iiiiiiirilii.iiii.ii$siii.i.iixi.i......iilXiriiiii.i''1P,*.i.iliil, -ZZ 38
iiiiiiiiiiiiiiiiiixix.l.: P, liiiiilfi iii:iilnniii iiiiii| 67,993 | 97,742
:-:: : :.1 -.an:::.: : ::: : : : : : tt: : :ttt:t::t:t :..u,.:.:.:.:.:.: :.:.:2U1 : ::.::.: :::ll:::36*
-zt"l i o*
i.ii:iii*.i1:1:l;l;:;i;:i:iii:ii;-'1rt;i:w:iiiiiiiii:t:ti1r-'182 : 0*
iiiilto,,'$xn.ii.iiii'.iiiii::i::..i'' .... i.38,243 | 67,993
i:i?.0r.1::*..:r.:.:.:.:l.:.::;l.,?[1,*r:ir:.t:
" Eztaluated results for Drains and Gaskets zeroed because the impact is minor relatioe to total use and is lost in the
noise of a billing analysis; an engineering analysis cannot be used due to a lack of baseline data; deemed saaings are
out of compliance.
"" Eaaluated results for Nozzles and Pressure Regulators zeroed because results are not statistically differrnt from
zero.
""" System Redesign results summarized on a per project basis; howeaer, the normalizing units used for the
analysis depends on the specific type of system redesign.
i,Jahrl lrigatrcrr Eneqy Savir*cs E,,raiuaiiirn Renofi
Apl:ondix $ - liet llavings l\{etliociri*iiv
Frye C-21
ru&v$tANT
Rocky Mountrin Power
Exhibit No- 5 Page 1 31 3 of 1 365
Case No. PAC-E-14-07
Vvitness: Kathryn C. Hymas
ldaho lrigatran Energy $avings Evaiuation Repuft
Aprendix S - I'lst Savings Methociningy
Fuge C^21
Ns\\T$TANT
Rocky Mountain Power
Exhibit No.5 Page 1314 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Table .9. Cost-Effectiveness Evaluation Input Values
Inflation Rate '1.87"/"
eilTn8i%iiiiii .i
0.68
iii.lr!i!i!i!i!i!i!i!tiiSg
Industrial Line Loss 1.0.399
Industrial Retail Rate $0.05
iEfeBsti!fiUr$t$ffi€t,i€o$$,iiiiiiiiiiiii,,,i,,,i,,ii,ii,il.,,,. .. , ,ii;i$.1,55$j:7..S6iiii
Program Costs $807,238
,#€ffiifii$trative ,i, .' .i,ii.ii..iliiiiiii.iiiiiiiiii. ,, .,:i.iiiiiiii=rTi*Irliiiil
$191,303
Iable 9. Cornbined 2009 throush 3011 Evaluated Benefit Cost l{atias
::ri:li:r:i::::l::::il:l:!rl:::lii:l:ir::i:l::ri:i:l:i:i:l:i:i::i:l;i::::::::::::::;i:lI:S .r,$$$tii.tHIffiel
ir':l:::
l$ail* lrigalcn Energy 531,11nu Evaiuaiion iieroii
Ap*ondix $ - ii*t S*vings Meiho$rilgy
Paue D-i*t
5d$V${:AN'T
Rocky Mountain Power
Exhibit No.5 Page 1315 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
T'abtre 'i0" 20t]9 Evaiuated trienefit Cost tr{aiios
'Talrle 10. :CI10 Eyaluated Benefit Cnst llatics
im4iffi
Total Resource Cost Test (TRC) 430,712 320,758 $804,489 $293,41'6 0'35
-il. il;;.;i"'i'rninal 430,212 s2o,7s8 $786,624 92e3,416 o.s7
,,,,, Particfu :ant,,,€ost',ff€$:t,'lI' *.Jll***1***.J*lr;;-;;i;***,,.,.,.,,i..:*'illri('-{*
572,600bw
572,600
iriz82Or,f,$E...-f
*sa a
426,424
4r6,43u
426,424
,i.iii.ffi.I$6
$687,1.55
rffiOffll
$694,611,
S$4I7is:0riiiiiiiii.ii.i...
fi379,188
$ere,rsffi:N1
$379,1.88
....r$ .iiRtsCIiu1rn.$p=5'..f*t...rye1...,.
Total Resource Cost Test (TRC)
..:::::::::::::::: :' .' rl':,,,, : .::Utilily,CostTest (UCI) , ,. l
Rate Impact Test (RIM)
,.,;',fmiciP6fi 1...ffi ffi l ,,,(HCfr)
Table 11.2t)11 Evaluated Bemefit Cnst l{atiers
iriillt lriiilili:i:ii iineigy l\aviitqs Evaiunii$n S*ilil
i.i;l:sri,jii ilt - i'i$i :-\evii-lg: l,isiiilc+iirrr-
F+ue ti"i4
\.$V$ilANT
Rocky Mountain Power
Exhibit No. 5 Page 13'16 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
T'able 12. Combined 2009 2011. [,Ieasure Level Evaluated llenefit Cost ldatios
iiiiiiiiiiiriiiriliii
0!S0l
!ititititititititiii!ttitiiitititititiiitiitii!ttiiitititititititllr:.i.-iiiiiitii
i',{p-rl,iiq$q,!:!.::!iri!:!::iri :!iri i!:!iri!:!:!iririririri
;iiiirir;riri:i::ri:iilfiiiiiiiiiiriiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii
$257,666
#i1i6i7A9.
-3,076,729
ii::1ii:1;:i:ti:trr.:;:;tf :ii::::ititii:;:::::::a:i::!i;ti:
r+*Uiw:tr-;Ar*;X;.ffi r..
-3,076,729
5,061.,593
l:i:r:,:,1:::::l:::l:::::i::::::::::::::::::::::::::::: iliiii:
.i...$*lH*uji*l
-2,291,288
i:::::::::::::::::::::i::i:::::::::::::::::::::::::::::::::
#lE*XX+ffiii.ii
-2,29L,288
\\:rr r \,'r \.-- _.
ii:i...i''' iiiiiiiiiiii.iixiiiiiiixiiixi '*xii
:i:ii i,,,,,,,,,,,',iiiiiX,,,,rii:XiXiii:iriXi].:':ii.::i.l.!i
$7r2,677
[:i:i:::::::::::::::::::::::::::::::::::::::::::::::
XXS'?#,8i54+S
$1,859,904
!ileh* lrilEatian Hnelgi,- $avirgs Evaiuaiisn Rrnu*
Apr;endix ll - l.iet Savings lvlelhodnicgrr'
Fage ti^25
rxr.S\Vr$tANI
iiiffiiiH#
't'able 13. 2t)09-2011 Eyaluated Benefit Cost Ratios by Measure'tr'
I$lf,,I,i"I flil
(2,291.,288)
Pize'11,7,p;
(2,291.,288)
Rocky Mountain Power
Exhibit No. 5 Page 1317 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
,::I:!i:::!::!:!:!:!:!:!:!:!:!:!:!:!:!:!:::,:!:::!:,.:, i I ., : l
illq,+,1p.##:::i:.:,:i:i:,:::i ,:. lti.r \ii.ii.irj.i . ,, . .'L,O*.
:::::..:::::::::::::::::::::::::::::::::::::::::::::::::::::.:.:rr ::.::::: ::j::.::: :: .. ::. r..j...
%3.164 | i,tl:,.,.,,ti,ir -12.20
:$iil.:.i:.iiii:ffi 6etiir:iii:::::i:.:t:at;,
:.:.:.:.:.
- $64,698 i $0
:i.ii:., $49;$13 :.,.i:i:i:ii::i:::;:i$0ii::i:i:i:i
::::::::::::i:iijii:,:,::::::::::::::::::::::::i:ijil:::j#:::::::::::::::::::::::::::::::::::::::::::::::- $49,s13 I $0
:+:::::::::rjrl#0;*ati:iriiixi:iiiiiiiiiiiiS14pe$
- $754,724 , $0
itiiiiiiiilr:ii$1.*u#$flffi .ii....i...i.iisE ii..i
- 5777732 i $0
0.00
i0ffi
0.00
!Hl$7i
i0Jfroi
0.00
::::l:iffi €6$tle;*l:!"8'-$r::
ii:iiiRate Impact Test (RIM)
r,nCJ,fbtalR*sofiei.Co*i,tCst::(F
Total Resource Cost Test (TRC)
j.i::::::::::::::r::::l::i:::t:t:it:iit!a:t::i:!i:!:iti:::j:::::::::::::::::::::::::i::::
:r Rate Impact Test (RIM)
Total Resource Cost Test (TRC)
2'7ffi {siiiiii,,,,iiiiiiiiS uru,
2,753,403 2,057,949
::::::: i ,::::::::::::::i:::::li:: : lli
irXPffirffi
2,057,949
:::r!:lilRTrqilg
iriil:r.i;Iiririiri!:!iiriri.t;:ri:irl!r.*,i::;Ii'!iii:it i.,f :ii;:;1.!iri!'::,:
iiii&iibll.f{*j.iiiiiiiiiiiiiiiiiiils.+i{f,.s..,}+*i:i.':=,:.i..,,,,,:5;*u,,:i::r',
$7,062,993 | $1,468,542 1.38
$a4$#99
ztTi#iffi
2,763,403
:la,.altl:.,tltl,tl:ltltl:L:,1:l:l:::!::i:l:i:*'*;7ffiiffi::,,i
- (1Rr rql
'::;nr!::.r.:.:.r.:.:r:r': t:::.i::.::.::::.::.. :. ! :. ta. :. :.. :. : :. I : :b*:6n.:uha
s136,720 $0 0.00
idsi\o llri$ati$ii Inelgv Sil""irgs Evaiuaiiiin Ren,:$
Ai:len,lix $ - liet iiavirgs ir.'letlrocici+1;y
Frue $-2$
y*'s\vlilANT
T'abtr e'14. 2009-201 1 ltenef 'rt C*st ltatios bv Measu re't'
ii-r'PlR,:.:.:rl.::.:.c,,,:,,,;,:,.,1:: jI*tl
lJtiHty CffiTest ({:163 : : ':: ':'
:i Rate Impa ct Test GIfvI)
::iij:::::;:::;:::::::::::::::iiaii:ir:i:rr;iii:ii:::::ii:i:i;i;::::ir:;:iliii{..*!rttti$din}:i€l}$tr:ft *i:i
iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii:iliiiiii:iiiiiiiiiiiiiiiiii'*i:ii:iiiiiiiiiiii'"1'1o",:,,,,:,,X:",-,:":.:'$tl
P.rU:tqffieiii&egffitor,,,,,,,,,,,,,,, ,r:qs:tT+,qit;:(Il.S.i;I):;::i:::;i:;:;:i:;:;:;:i:i:ii:::::::::::
ili::iiiriii:iii::i:iiiiiiiiii:iiiiii:iiii::::iiiiiii::i:iiiiiiiiiiiiiiiiiiiiiiiii::ii:iiiiii:i:iiRate Impact Test (RIM)
2,479,869: 1,U6,797
,?-479,M:9.,Ai9*6i7,97i i
::::::i:::::i:i:iiin:il,l::l:,::i,::::::::::i::i:i1:l,l::,1:::i:::::i:i:i:i:::::::::::::l:::!:l:::;:;::::r:i::
2,479,869: 7,U6,797
:iiins iiiiiiiiiiixllii.l.:':8s*#8iliii:':i:i:iii.''ii$3,Iffi
$31,396
:$34;ls$
$233,263
:.r#sre.fi::::::::::::llll:::i:l{ffii$6fiiiiiiiiiiiii:i$561ffi:ii:::i:i:::i;:;::::*ti#,7 frii e,tsl
2,345,818: 1,,746,967 $567,674 : $r,352,596 2.41.
ss4sitsunE:,'.riii;,iiiiiiii!.iiiliTc6l$6fri'iiiiiiiiiii$4frsiff,ntliii.irii.$+#,5e#6ii:ii:ii:ii:.,,.q#:
2,U5,878 1,746,967 $1.1s5.313 $7.352.596 7.77
A.JI
Rocky Mountain Power
Exhibit No.5 Page 1318 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
r llound of Evalualee{ Savings
i?$&m$IJ
(1.,2s3,820)
i{l12$t:aae)
(1,253,820)
sriis.liilii'ri............i
97,31-t I
srristlili',irii......,....i.
97,377
72,469 W,698 : $20,761
i?*l{6e iii,se.5l*,,,,,.i.iiiii::.iiiii.iiiiiita"0,;Ir1:.r;.,
72,469 W,998 | $20,761.
!*!::I:l:{tnts.i
:!:!:!:!:!:!:!: :::l
0.32
lft:ilr::
:::::::::::::::tlt:i
0,32
foulistf ba:1+xcd$il.Ts$i::t
Toial Resource Cost Test (TRC)
,::i:ii:iii:::;,::::::i:::l:::iiIii:::ili::i:lii:i:::::i:::::i:i:i::::ii:r::::::,:,:,i:11,:
:...:....{jB$F1lr$iffi I,I;l{lr,, D:,ri;
Rate lmpact Test (RIlvI)
:YduIf*a*$uf ceii:cu$$ii.Tffi :;{Hffi l
$43,354
ii$r.q ...'.....:.
$467,703
i!$.143.*Siririririri!
SSP.a:i*r#
$528,3s0
:::::ii:::::i:::ta:i:t:::::.:i:.:=
ii$6rsiry"=
$628,3s0
iiiiiiiil::i:i::[oB*.n€r{tit'c'...€e$I,,nbis'tig$S
:i:;:::;liii:Total Resource Cost Test (TRC)
i'li::I{'. :,SfEt:r"5$i{ri,,,.SrP::::.:
:i;illRate tmpact Test (RIM)
irliliir> lirigalirn Hnergy Saviircs Evaiuaiisn iienlit
Aplr:n,lix ii - ii*t iievings \{eil-rcslnipg-\'
Fage lt i?
rus\rs$t&NT
:::::::::::::;tliii:t:::i:i:::::::::::::::::::;:;:::::!::::;:::::::::::i::::::
.SftSltdtl;+.faffi
Table 15. 2009-2i|LL Benefit Cost ltatios Measure - Lorver Bourrd of Evaluated Savi
€os"t:f-e$i
Rocky Mountain Power
Exhibit No. 5 Page 1319 of I 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
.!r.'.,:!.!:!,!i,\!i\.-\:r:*\:\.\ri::!:l
ililris.iiri \r
riiiriiii:iri$ii$r'ir l
iili:iiiiiTotal Resource Cost Test (TRC)
,.,: *ifii+.[*rie;j,lu[r+i:iiiiiiii:i:: :
:si+$ld_E;iii
Hg,iI)
Total Resource Cost Test (TRC)
Rate Impact Test (RIM)
Total Resource Cost Test (TRC)
CoEtilS'Et
Total Resource Cost Test (TRC)
Total Resource Cost Test (TRC)
(463,763)t (345,371)
it*$S.;.? iiiiiiiiiiiiii:iiiiiiiii(e{git?X}
:{*0:2re6;:,:.:.;.:.11:.,{,+ $;9t2i
(1.0,277,648)
tftttil7.,l|t;1#
(1.0,277,tr.9)
(7,653,922): $154,724 i (i;,,i,.r'r:.i.i;:i4: -17.73
It;653i9g2Jri!'! ;.::$tT];V'fr, r i$).),;'':i:ii\ii,:'lii .1,5,45:',i:::
(7,653,922) i:11.':i1!r,.iril) (i;.i,]+:l.iiii4) 0.00
---*...'.i
il-"--]iii.,,i'
,ffi
liii:riii:::::t:tl:llt:t::::i::
i(i0PBfi .8J ,.' ,,,[+6Sar ,,,1,,,,,,,,$9S,.r1.,$3 i,,,,' ,, ]ti$i l.*r*lttl.,;!, -ii,6
j4i+0,i
3.72
t],tiliivCb*tf;extii{:IIcfi iii:,i ' ,
Rate Impact Test (RIM)
$43,354
$56r,674
:s430.
$774,754
r$SA&BZq'
)6W,
::in::::::::::::::::::::::::::::::::::::
$72r,679
;ffiffi..',..
$389,349
'r$EI*i4$t[::i:ii
r5il,5 :,
::l:::::: :.. :l:l:l:::l:: :rl:l:l:
-4.77
fr..6,,"*i:i'::":;':;
0.00
.u.30
::::::::::::::::i:
0.48
!*iOtl:::::l:l:l:l:l:l:
0.89
iili4t
Rate Impact Test (RIM)
utilitv,fuEt,ire8t,iflJen ::,.. r.:,, , , ::'.'r:
Rate lmpact Test (RlM)
!l!:!:!:!:::!:!:!:!l!:!::l:l::!::;:;i::iailiiiiiiii,tll:lt:i!::i:ii,€uxli:ifgrg,trr#r$fi
:! t::!:!:!:!.:: :::::::::.!ijr:::::::::::::::::::::::: : . ..... :.::
: 1:i:i:i:i{]}rill{ii:fittiiiirfiiiifllcr} ., ',:i:.: : :i::::::i:i: r{:::::' ::::::::::::::::::::::i:: :: \: : :.: :r . ::::
iirilliriiRate Impact Test (RlM)
i:ilniiii#iffi iliiH$:il:t;:i:i;illffi
,, -,r*,ult,nupou+e:CoEi.faui 1,,
ii:iai.r:!ilR":'"::e,co11 relt jrnc]' trlili{,f,,t;;t t*,ll {Ucfi}
:::,,t,:iiril na te Impact Test (Rl M)
,,,.,,,,',":f *rt*lpa"t,G"iliiTe,s,iii
i9IZiffif;iri:,
917,827
iarr1m,,.rg:
977,827
:rT*7"8eI,rr
,i,iiiii6$"5f0
683,520
,;.jil.6ffiii52CI
683,520
li,,,:,,,,frSAj520
''tii....ue$ir,*3..'369,742
..iil.iififire..
369,742
rrlrrrrrrrfi 6$jf-,,Cfi rl:
$-l*!t$6::;ti,
$529,2'18
ssH#18
9529,2-18
$49{iae
:::::::
$345,699
:]:]::i#;i',.,.fP
s345,699
:::::::s&E$i+:4iI
(607,593)
gtrrt
Total Resource Cost Test (TRC)
t+illdt'tt 1$r82,
$182,294
::$:136'r, 8
i;$lts 4n:
:::::::l:::::::!:l:i:,1:i:::i:::::::l::::
t::::l:i::::::::::::i:iii;i:ti:::::::
tls:N
1.lil.:.1,
-'1.6't
ra:it:.:rr.: ::
:,:,:ll:],::ii:il:l:li::::::l:::
0.00
(491,,677):
;ii:{*.t1. ,.
(491,,677)
'{491;$f.?i ',
(660,222)
(660,222\
F+ge $-2S
ii:li..o lriilat:aii Inergv Savirgs Euaiuaiiiin Renu(
Appendix l3 - list iiavings ltlethod*ingr
Rocky Mountain Power
Exhibit No. 5 Page 1 320 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
E.7 IESEEAlnteruiew Guide
Note: Potential respondents for the purposes of this interoiew are contractors in the KMP lruigation Energy
Efficiency Alliance who haoe completed at least one lrrigation Energy Saoers project in Idaho between 2009 and
2011. Alliance aendors may be conducting equipment exchange and receioing direct reimbursement f-rom kMP. A
census of aandors will be attempted.
Objectives
These interviews are designed to meet the following list of objectives.
> Understand how trade allies come to be involved in the program alliance;> Understand overall ally satisfaction with the program, including application materials, training,
roles, and communications;
" Characterize how they would improve the program for themselves and for customers;
" Characterize the value allies see in participatingi
" Determine the level of programJike activity occurring without the program support (spillover).
This includes assessing how different program sales are from typical sales and how efficiency of
products is changing.
" Understand what drives allies to stop participating or to not complete any projects.
> Determine if allies are receiving their incentives for equipment exchange in a manner consistent
with their needs?
Variables
Variable Description TyPe
$_CONTACT Name of contact Text
$-ALLY Business name Text
$-PACIFICORP Rocky Mountain Power Text
$_PROIECTS Completed projects 2009 -201,L Number
$ SUB_TYPE Equipment Exchange, Pivot and Linear Text
$_ENROLL_DATE When they are listed as IEEA Date
$_2009_FLAG Flag for IEEA no longer active Binary
lnterview Guide
Hello, this is <INTERVIEWER NAME>, from Energy Market Innovations. We are conducting an
independent evaluation of $-PACIFICORP's energy efficienry programs. This is not a sales call. May I
please speak with $_CONTACT.
I understand that $_FIRM is part of $-PACIFICORP's Irrigation Energy Efficienry Alliance. Your
feedback in can be used to improve Alliance support and the Irrigation Energy Savers program.
,{1. Are you the person that works most closely with the Irrigation Energy Efficiency Alliance at your
company?
ldan+ lvi$aticn Ir*qy Savinqs Evaiuaiian Remil
$.f:pendix C - Prcces-q [valuahsir Suruey inshurnenis
Pags H-i
Roclry Mountain Power
Exhibit No. 5 Page 1 321 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
a. Yes
b. No ) [ask to speak to person most familiar with the program]
I would like to discuss your experiences and perspectives regarding the Irrigation Energy Efficiency
Alliance. This interview will take 30-45 minutes, and as a thank you for taking time to chat with me, I
would like to give you a $50 gas card.
Is this a good time to talk or would you prefer to schedule a more convenient time?
[If no, scheduled callback time:]
With your permission, I'd like to record this interview to ensure that I don't miss any important notes
and for quality assurance. Your responses will be kept confidential.
A2. In one or two sentences/ can you please tell me what $_FIRM does?
,A.3. What is your title/role at $-FIRM?
A3a. How long have you been in this position at your company?
lJl..z Section L: Participation
1. Our records show that your firm joined the Irrigation Energy Efficiency Alliance in
$_ENROLL_DATE? Is this your understanding as well?
2. How did you first hear about the program? (DO NOT READ, MARK ALL)
a. Advertising
b. RMP Representative
c. OtherContractor/Vendor
d. Customer
e. Other (SPECIFY
3. What motivated $_ALLY to participatei
4. Our records show that your firm facilitated $_PROIECTS $_SLIB_TYPE projects from 2009 to
201.1..
a. How were you involved? (8.9. did they influence the project or just take orders)
5. [IF $_2009FLAG=1] Our records show that $_FIRM did not facilitate any projects since 2009. Can
you describe the challenges that you face with the program?
a. Have you been involved with the program more recently, in2012?
b. [IF YES TO A] What changed to allow you to participate in2012?
ilrnc, S^')
i$ali* lirigati$n Enelgv $airings fvaiuaiion R*uot't
A.p$endix C - Process Evaiuaiicn $uruey lnslrunenis
Rocky Mountain Power
Exhibit No. 5 Page 1 322 of 1 365
*,,,!3ilA?;ii?1i,i;31
1.1.3 Section 2: Training Roles, and Communication
6. What kind of training or information about the program were you provided when you first
became involved? [MAY HAVE HAD INTERNAL TRAINING.]
a. Have you or someone at $_FIRM had any follow up or continuing training?
Did you feel like the program and your role were clearly explained?
How would you describe the quality of one-on-one communication with the program
representatives?
a. Is there one key contact you communicate with about the program? Who?
b. \,Vhat might initiate contacti
i. Is there a set frequency of contact or an action that would trigger contact?
ii. Does he/she contact you or do you contact him/her?
c. How often is the contact?
i. Does this meet your needs?
d. How would you rate your satisfaction with your contact?
e. Is he/she able to answer your questions or get you to someone who can?
How do you prefer to get information about the program? (DO NOT READ, MARK ALL)
a. Online, check site often
b. Email
Mail Newsletter
Phone Call
1.1.4 Section 3: Marketing
10. Do you use the program as part of your marketing to potential customers?
a. [IF YES] how?
b. [2"d FOLLOW UP]Has it had any effect on your sales?
11. Did the program provide your firm with any marketing materials, such as brochures, flyers, or
forms to help promote and explain the program offerings?
a. Brochures
ldahc lrriqaticn Energy $avings Evaiualion Rsnoii
Af:pendix C .. Procnss Hv.llualicn Suryey inslrumenis
8.
9.
c.
d.
Roclry Mountain Power
Exhibit No. 5 Page 1323 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
b. Forms
12. Is there anything you would change about the existing material?
a. If yes, what?
1.1..5 Section 4: Customer Involvement
13. Is your interaction with customers that are participating in the program different than those that
are not part of the program? How?
a. [IF $_SUB_TYPE=PIV/LIN] As part of the program, customers are expected to work
with you to determine the appropriate new pivot and linear equipment to purchase. Is
this kind of consultation typical for all purchases?
14. [IF $_SUB_TYPE=EQUIP EXCH] Have you had any difficulties fiIling out applications for
rebates for equipment exchanged through the program?
15. [IF $_SUB_TYPE=PIViLIN] Are you able to help customers fill out applications for rebates for
equipment purchased through the program?
a. Any difficulties?
b. Do customers need assistance with the application? How much?
16. How do customers typically find out about the program? UNTERESTED IF CUSTOMERS
KNOW ABOUT THE PROGRAM AND BRING IDEA TO THE ALLY OR IF THE ALLY IS
ACTTVELY SELLING/ADVERTISINGTHE PROGRAM; PROBE TO DETERMINE ONE OR THE
oTHER.l
c. For the projects you completed between 2009 and 201.1, about what percent started as
you contacting the customer to propose the project versus the customer contacting you
with a project in mind?
d. For those with a project in mind, about what percentage did you sell/install as they
envisioned versus those where you suggested changes to increase the efficiency of the
project?
17. For each project that was completed from 2009 and 2011, about how many others started in but
were cancelled (i.e. not installed by anyone to the best of your knowledge)?
e. What do you see as the primary reasons these projects did not complete (TIE ANSWERS
TO BARRIERS LIST USED IN PARTICIPANT SURVEY: HIGH UPFRONT COSTS,
LACK OF ACCESS TO CAPITAL, LONG PAYBACK PERIOD; SLOW RATE OF
RETURN, LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN
ENERGY EFFICIENCY, LACK OF INFORMATION ABOUT SAVINGS AND
PERTORMANCE, LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF)
icaho li"rigaticn Ensqv Savings Evaiuaiion Relori
,a.prcndix C -.Fii:cess fivaliial.ion $ur;ey iiisiiuments
i)asc. li-rl
Rocky Mountain Power
Exhibit No.5 Page 1324 of'1365
*,"!3IAi;if?:';l,#i
1.1.6 Section 5: Effects of the Program
18. UF $-SUB_TYPE=EQUIP EXCHI Are the nozzles, drains and gaskets exchanged with the
program similar to equipment purchased by irrigators not involved with the program? (IF
NEEDED "UNDERSTANDABLY, THE EFFICIENCY IMPROVEMENTS ARE LARGELY
FOCUSED ON WATER APPLICATION. ARE PROGRAM NOZZLES, DRAINS, AND GASKETS
SIMILAR TO EQUIPMENT PURCHASED BY IRRIGATORS NOT INVOLVED IN TFIE
PROGRAM?")
To the best of your knowledge, did you complete any $_SUB_TYPE projects that would
have been eligible for the program in 2011 that did not receive program incentives?
[IF YES] Thinking of just 2011, about how many projects do you think would qualify?
[OR, could you relate the volume of eligible equipment with the volume that you do
with the program?l
c. Why did customers not participate in the program?
UF $-SUB-TYPE=PIV/LIN] Are the pressure regulators, low pressure drains, and sprinkler
packages for pivot and linear systems purchased with the program similar to equipment
purchased by irrigators not involved with the program? (IF NEEDED "UNDERSTANDABLY,
THE EFFICIENCY IMPROVEMENTS ARE LARGELY FOCUSED ON WATER APPLICATION.
ARE PROGRAM PIVOT AND LINEAR NOZZLES AND SYSTEMS SIMILAR TO OTFIER NON-
PROGRAM PURCHASES?")
a. To the best of your knowledge, did you complete any $_SLIB_TYPE projects that would
have been eligible for the program in 2011 that did not receive program incentives?
b. [IF YES] Thinking of just 2011, about how many projects do you think would qualify?
[OR, could you relate the volume of eligible equipment with the volume that you do
with the program?l
c. \A/hy did customers not participate in the program?
Do the $_PACIFICORP program incentives influence your selling of program-eligible
equipment for irrigators [THIS QUESION APPLIES TO SERVICES AS WELL AS WIDGETS; IT
IS A YES/NO, BUT INTERVIEWER SHOULD PROBE TO FIND OUT WHAT THAT MEANS TO
THEM.I
a. [IF YES] Please rate the influence on a scale of one to five, where one is no influence at
all and five is a driving force in your sales.
(IF APPLICABLE) Do the $_PACIFICORP program incentives influence your stocking of
program-eligible equipment for irrigators [THIS QUESTION APPLIES TO WIDGETS; IT IS A
YES/NO, BUT INTERVIEWER SHOULD PROBE TO FIND OUT WHAT THAT MEANS TO
THEM.I
a. [IF YES] Please rate the influence on a scale of one to five, where one is no influence at
all and five is a driving force in your stocking practices.
idah.; lrigation Eriergv Savinqs E.",aiuaiion Reloft
A.pptndix C - Fi'ocess Evaluaticn Sur;ey insiiu,nenis
t9.
20.
2L.
Dens F^rr
23.
1.7.7
24.
L.1..8
lNow,
26.
27.
Rocky Mountain Power
Exhibit No. 5 Page 1 325 of 1 365
*,"!3iiA?;ii?ffi31
22. Does the $_PACIFICORP program information influence your selling of program-eligible
equipment for irrigators [INTERVIEWER MAY NEED TO CLARIFY THAT WE ARE
DISCUSSING IUST THE INFORMATION PROVIDED TO THEM; PERHAPS AT
WORKSHOPS/VVEBSITE/ETC.]
a. IIF YES] Please rate the influence on a scale of one to five, where one is no influence at
all and five is a driving force in your sales.
If the Irrigation Energy Savers did not exist, can you estimate how your sales of this efficient
irrigation equipment would be different? (PROBE FOR PERCENTAGE)
Section 6: Business Impact
Are there any other ways that participation in this program impacted your business, if at all? [IF
RESPONDENT ALREADY ANSWERED THIS IN SECTION 5, DON'T ASK AGAIN - looking
for qualitative here. Already asked them to rate.l
How does the program differ from other similar programs that you may be involved with at
other utilities? (BE SURE TO FOCUS PROBES ON: Is the amount of effort required on your part
different? What about the amount of paperwork? The program offer to participants?)
Section 8: Satisfaction with Program(s)
I HAVE IUST A FEW MORE QUESTIONS.]
On the whole, are you satisfied with your experience in the Energy Efficienry Alliance, on a
scale of 1 to 5 with 1 being very dissatisfied and 5 being very satisfied?
Do you use the $_PACIFICORP vendor website?
a. [IF YES, follow up] How often do you visit the website?
25.
I
[2.d follow up] What kind of information do you look for on the website?
[IF NO] Did you know that upcoming events as well as archives of alliance newsletters
are available on the website?
i. How do you find out about events and newsletters?
28. When you joined the Irrigation Energy Efficiency Alliance, you signed a trade ally
agreement. Do you remember this agreement?
d. [IF RECALLS AGREEMENT]Is there anything you would have liked to change about
this agreement?
29. Is there anything else you'd like to tell us about your experience?
1.1.9 Section 9: Gas Card Offer/Closing
As a thank you for your participation in this interview, we'd like to offer you a $50 gas gift card. Would
you like to accept this offer?
(If yes) Which type of gas station would be most convenient for you?
!dahu lirigati*n Eneri3y $avinqs Evaiuaiion Remii
Ap|tenrjix C .. Pi"ccess [valuation l]ui"s-ey ir:stiitt',':enis
b.
c.
Roclq Mountain Power
Exhibit No. 5 Page 1326 of 1365
*,,331i,1?; il?*;i,fr 3l
[NOTE: The following do not offer gift cards we can order: Loaf N'Jug, Kum & Go
The following companies DO offer gas cards: Exxon-Mobil, Sinclair, Conoco, Pilot-Flying J,
Shell, Valero (Diamond Shamrock), Phillips 66, Chevron-Texaco, Maverikl
To what address should we mail the gift card?
Thank you!
C.2 IES Participant Suruey lnstrument
Note: lrrigation Energy Saoers Participants are those customers who exchanged equipment, upgraded equipment,
or had any irrigation system consultation through lrrigation Energy Saaers program during 2009-2011-. This
sun)ey is designed with four distinct tracks, respondmts are directed to the tracks by the logic at the beginning of
the section with priority in this order: Systnn Analysis €t Redesign, System Consultation, Pitsot and Linear
Equipment Upgrades, and Equipment Exchange. lf a respondent participated in more than one track, the logic at
the beginning of the section of the first track that is appropriate for that respondent will let thern know that the
sunley is only focusing on that part.
Objectives
These surveys are designed to meet the following list of objectives.o To describe how customers come to participate in the different aspects of the program
o To understand overall customer satisfaction with the program, including satisfaction with
vendors (where applicable), equipment (where applicable), inspections (where applicable), and
reports and recommendations (where applicable)
o To understand dealer influence on equipment exchanged and upgraded and participant
perspective of dealer knowledge about programo To understand program influence on customer actions, including free-ridership and spillover
o To understand barriers customers are facing that prevent increasing energy efficiency
o To characterize participating firms
idahu lirig;aticn Energy Savinqs Evaiuuiion R*,;:rit
AFilenrlix S - Frocess fivalualion $urvey insliunrnis
Variables
Variable Name Description Tvpe
&CONTACT Respondent name Text
&FIRM Companv narne Text
&PROGRAM Irrigation Enerqy Savers Text
&SITE Address Text
&YEAR Year of proiect completion YYYY
&PACIFICORP Rocky Mountain Power Text
&PART TYPE List of participation types (e.g.
Equipment Exchange, System
Consultation)
Text
&EQUIP_EXCHANGE Participated in Equipment Exchange BINARY
&PIVLIN UPGRADE Participated in Pivot/Linear Upsrade BINARY
Fa$s E^7
&PIVLIN-EQUIP Equipment installed through program Text
&SYS CONSULT Participated in System Consultation BINARY
&SYS REDESIGN Participated in System Redesign BINARY
&PUMP TEST Had a pump test BINARY
&NOZZLE-COUNT Count of nozzles exchanged Numeric
&GASKET COUNT Count of gaskets exchanged Numeric
&DRAIN_COUNT Count of drains exchaneed Numeric
&VENDOR Vendor that completed the proiect Text
&POSTINSPECTDATE Date of post inspection MMYYYY
&INCENTIVE Amount of financial incentive Numeric
&MEASURECOST Amount of measure cost Numeric
&VFD FIag if measure was VFD BINARY
Roclry Mountain Power
Exhibit No. 5 Page 1327 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Survey Instrument
I ntroduction and Screen
INTROL. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's Irrigation Energy Savers program. This is not a sales call.
May I please speak with &CONTACT?
1. YES, THAT IS ME
'
SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU
3. NOT NOW ' SCHEDULE APPT AND CAIL BACK
4. NO/REFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's Irrigation Energy Savers program. This is not a sales call
and would appreciate your input."
I'd like to let you know that this call may be monitored or recorded for quality assurance purposes. Also,
all of your responses will be kept confidential and will not be revealed to anyone outside of the research
team. Do you have a few minutes to answer questions about your experience with the program? [IF
NEEDED, READ: "This survey is for research pu{poses only and will take about 15 minutes."I
1,. YES ) SKIP TO IS2
2. NOT NOW ) MAKE APPT. TO CALL BACK
3. NO/REFUSED ) TERMINATE
INTRO3. I'd like to let you know that this call may be monitored or recorded for quality insurance
purposes. Also, all of your responses will be kept confidential and will not be revealed to anyone outside
of the research team. Do you have a few minutes to answer questions about your experience with the
program? [IF NEEDED, READ: "This survey is for research purposes only and will take about 15
minutes."]
4, YES
5. NOT NOW '
MAKE APPT. TO CAIL BACK
idal'l+ luig;atirn Ener6y Savinqs fvuiuaiian R*iro$
Apil$ndix 0 - Process Evalualion iiur;ey Insirumeris
ffrns. F:^*
R@ky Mountain Power
Exhibit No. 5 Page 1 328 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
6. NO/REFUSED ) TERMINATE
[IF VERIFICATION IS NEEDED, TELL THEM THEY CAN CALL SHAWN GRANT AT 801-220-
41961.
IS2a. &PACIFICORP records indicate that your firm participated in the &PROGRAM program in
&YEAR through &PART_TYPE at &SITE, is this correct?
1. YES ) SKIP TO SRl
2, NO, DID NOTPARTICTPATE
3. NO, ONE OR MORE SUBPROGRAMSARE INCORRECT ) SKIP TO IS2d
4. NO, ADDRESS IS INCORRECT ) SKIP TO IS2C
88. DON'T KNOWNOT SURE
99. REFUSED
IS2b. Is there someone else that might be familiar with this project?
1. Yes
2. No ) TERMINATE
88. Don't know ) TERMINATE
IS2c. May I speak with that person?
1. Yes ) RETURN TO INTRO2
2. Notnow) SCHEDULECALLBACK
3. No ) TERMINATE
IS2d. What activities did you participate in with the &PROGRAM?
1. [RECORD RESPONSE and update &EQUIP_EXCHANGE, &PMIN_UPGRADE,
&SYS_CONSULT, &SYS-REDESIGN] ) SKIPTO SRI.
88. DON'T KNOWNOT SURE) SKIP TO SRl
99. REFUSED ) SKIP TO SRl
IS2e. What is the correct address?
1. [RECORD RESPONSE]
'
SKIP TO SR1
88. DON'T KNOWNOT SURE ) SKIP TO SRl
99. REFUSED ) SKIP TO SRl
Sysfem Analysis & Redesrgn
lif &SYS_REDESIGN=0, skip to next sectionl
lif &SYS_CONSULT=1 OR &PMIN-UPGRADE=1 OR &EQUIP-EXHANGE=L, read "For this
survey, we would like to focus on just the customized system analysis that you had through the
program."]
SRL. How did you first become aware of the opportunity to have a customized irrigation system
analysis through the &PROGRAM program? [DO NOT READ RESPONSES; ALLOI{ MULTIPLE
RESPONSES]
1. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
2, &PACIFICORP RADIO ADVERTISEMENT
3, &PACIFICORP PRINTADVERTISEMENT
idsli* liri1,1ati0il Eriergy Savings Evaiuaiion R*cori
Appendix C - Process Hvaluali*n ;\ur-,ey lnsiruments
Srn* tr-Q
Rocky Mountain Power
Exhibit No. 5 Page 1329 of 1365
*,"!3li*?; ii?*,1,i,31
4, &PACIFICORPPRINTED MATERIALS/BROCHURE
5. &PACIFICORPONLINE ADVERTISEMENT
6, &PACIFICORP TV ADVERTISEMENT
7. &PACIFICORPNEWSLETTER
8. &PACIFICORP WEBSITE
9, PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
10. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_]
11. &PACIFICORP SPONSORED ENERGY AUDIT OR TECHNICAL ASSESSMENT
12. FROM TRADE ALLY, VENDOR OR CONTRACTOR
13. ANOTHER BUSINESS COLLEAGUE
14. FAMILY, FRIEND, OR NEIGHBOR
15. OTHER [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSE
SR2. When you started the process to do a customized system analysis, was it because you were adding
capacity, changing water source planning to replace all or part of your system, or something else?
1. ADDING CAPACITY
2. CHANGING WATER SOURCE
3. REPLACEALL ORPARTOF SYSTEM
4. SOMETHING ELSE (SPECIFY)
88. DON'T KNOWNOT SURE
99. REFUSE
SR3. Why did you decide to do a customized system analysis with &PACIFICORP? DO NOT READ
RESPONSES; ATLOW MULTIPLE RESPONSESI
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Other [SPECIFY]:
15. To save water
88. DON'T KNOWNOT SURE
99. REFUSE
[IF more than one response to SR3] SR3a. Of those reasons, which one was most influential in your
decision to participate in the program? [ALLOW ONLY ONE RESPONSE]
1. To save money on electric bills.
2. To obtain an incentive.
i.danu lrigaticn Ineigy Savings Evaluaiicn R*iori
Aii$$ndir( C -. Process Evaluatisn Sur;e--v iiisiiuitenis
Sens F-'i ti
Rocky Mountain Power
Exhibit No. 5 Page 1330 of I365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
L0. To save energy
1 1. Recommendation by contractors/trade allies
1.2. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Other [SPECIFY]:
L5. To save water
88. DON',T KNOWA{OTSURE
99. REFUSED
SR4. A program representative came out to your facility to inspect existing equipment and determine
ways to improve your irrigation system. Using a scale of L to 5 where 1 indicates'very dissatisfied' and 5
indicates'very satisfied', how satisfied were you with the representative who came out to your facility?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHATSATISFIED ) SKIP TO SR6
5. VERY SATISFIED ) SKIP TO SR6
88. DON'T KNOWNOT SURE ) SKIP TO SR6
99. REFUSED ) SKIP TO SR5
SR5. Why were you less than satisfied with the iepresentative?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SR6. As part of the program, you received a report documenting the findings from the energy analysis
that included recommended equipment and changes to improve the efficienry of your irrigation system.
Did you find this report valuable?
1. YES
2. NO
3. DO NOT RECALL REPORT ) SKIP TO SR1.1.
88. DON'T KNOWNOT SURE
99. REFUSED
SR7. Did you receive the report in time to inform your decisions?
1. YES ) SKIP TO SR8
2. NO
88. DON'T KNOWNOT SURE ) SKIP TO SR8
99. REFUSED ) SKIP TO SR8
SR7a. Can you describe what happened?
idalu lrigaticn Eneqy $avings Evaiuaiion R*mft
A.psendix C .. Pr"*cess Evalilaticn S.ui,,e.v iirsii'unenis
treng F^'! 'i
Rocky Mountain Power
Exhibit No. 5 Page 1331 of 1365
*,,!3liA?;ii?',1,fr3i
1. [RECORD RESPONSE]
88. DON,T KNOWA\iOT SURE
99. REFUSED
SRS.Were there recommendations in the report that you decided not to install?
1. YES
2. NO
'
SKIPTO SRll
88. DON'TKNOWA{OTSURE ) SKIPTO SRll
99. REFUSED ) SKIP TO SRl.1
SR9. What were they?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SR10. Why did you decide against the recommendation(s)?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SRll. Using a scale of 1 to 5 where 1 indicates 'very dissatisfied' and 5 indicates 'very satisfied', overall,
how satisfied were you with the performance of the redesigned system?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO SR1.2
5. VERY SATISFIED ) SKIP TO SR1.2
88. DON'TKNOWNOTSURE ) SKIPTO SR12
99, REFUSED ) SKIP TO SR1.2
SRLLA. lzVhy were you less than satisfied with the performance of the redesigned system?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SR12. With the &PROGRAM program, &FIRM received a no-cost customized system analysis and
&INCENTIVE worth of financial incentives. As part of this program, &FIRM installed
&INSTALLED_MEASURES.
On a scale from 1 to 5, with 1 being not important at all and 5 being extremely important, how important
were the following factors in deciding which equipment to install.
A. RECOMMENDATION FROM CONTRACTOR OR VENDOR
B. INFORMATION PROVIDED BY THE &PACFICORP SYSTEM ANALYSIS ON POTENTIAL
SAVINGS
INFORMATION ON PAYBACK
THE &PACFICORP INCENTIVE
FAMILIARITY WITH THIS EQUIPMENT
PREVIOUS PARTICIPATION WITH A &PACIFICORP PROGRAM
ltaht; lriitraticn En*rgy $avings E';aiuaiion Rerci'i
Aprlenrjix $ .. Process [valualisn liuruey instrumenis
C.
D.
E.
F.
Fags [^i l?
Roclq Mountain Power
Exhibit No. 5 Page 1 332 of 1 365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
G. CORPORATE POLICY REGARDING ENERGY REDUCTION
SR13. Without the program, meaning without either the system analysis or the financial incentive,
would you have still installed the same equipment at the same time?
1. YES ' SKIP TO SR1.8A
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
SRL4. Without the program, would you have installed any new equipment?
1. YES
2. NO ) SKIP TO SRl8a
88. DON'T KNOWNOT SURE
99. REFUSED
SR15. Would you have installed this equipment within 12 months of when you did with the program?
1. YES
2. NO ) SKIP TO SRL8a
88. DON'T KNOWAJOT SURE ) SKIP TO SR18A
99. REFUSED ) SKIP TO SR18a
[IF &VFD=0]SRL6a. Relative to the energy efficienry of equipment installed through the program, how
would you characterize the efficiency of equipment you would have installed without the program?
1.. Just as efficient as installed with the program
2. Lower than installed through the program, but better than the standard efficiency
3. Standard efficienry
[IF &VFD=l] SR16b. Would you still have installed variable frequency drives on your pumps without
the program?
1.. YES
2. NO ) SKIP TO SR18a
88. DON'T KNOWNOT SURE ) SKIP TO SR1.8A
99. REFUSED ) SKIP TO SRL8a
SRL7a. Would you have installed the equipment to the same extent as you did with the program?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
SR17b. Would you have installed more or less equipment?
1. MORE) How much more?
2. LESS) How much less?
88. DON'T KNOWNOT SURE
99. REFUSED
UF SR12D < 3 AND SR14 = 2l
ldaiiu luii;aticn Energy $avings Evaiuaiion Reuoft
App*ndix C .. Process [valuali*n $uruey instruments
Fags [-1 3
.*,0n'' "lT[',]5i :iui i]fJ
*,"!31i,[?; il?.';1fr 31
SRL8a. Previously, you said that the incentive was not important in your decision to redesign your
irrigation system. However, you also said that without the program, you would not have redesigned
your system. In your own words, can you please describe what impact the program had on your
decision to redesign your system?.1,. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF SR12D < 3 AND SRls = 2I
SR18b. Previously, you said that the incentive was not important in your decision to redesign your
irrigation system. However, you also said that without the program, you would not have redesigned
your system with 12 months of when you did. In your own words, can you please describe what impact
the program had on your decision to redesign your system?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
lrF sR12D > 3 AND SR13 = 1l
SRL8c. Previously, you said that the incentive was important in your decision to redesign your irrigation
system. However, you also said that without the program, you would have installed the exact same
equipment at the same time. In your own words, can you please describe what impact the program had
on your decision to redesign your system?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF SR12B < 3 AND SR14 = 2l
SR19a. Previously, you said that the system analysis was not important in your decision to redesign
your irrigation system. However, you also said that without the program, you would not have
redesigned your system. In your own words, can you please describe what impact the program had on
your decision to redesign your system?
1.. [RECORD RESPONSE]
88. DON'T KNOWI{OT SURE
99. REFUSED
IIF SR12B < 3 AND SR15 = 2l
SR19b. Previously, you said that the system analysis was not important in your decision to redesign
your irrigation system. However, you also said that without the program, you would not have
redesigned your system with 12 months of when you did. In your own words, can you please describe
what impact the program had on your decision to redesign your system?
I. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF SR12B > 3 AND SR13 = 1l
SRL9c. Previously, you said that the system analysis was important in your decision to redesign your
irrigation system. However, you also said that without the program, you would have installed the exact
idaht lrii;aticn Energv $avinqs Evaiuaiion Reiofi
F.ppendix $.- Frccess tvaluaticn *.irr-'ev lnsiiunenis
trne:, F-'!i.
E,hibit N o TfYaHlSS:iiY."J
*,,!3ll*i;ii?*;i,i;3i
same equipment at the same time. Lr your own words, can you please describe what impact the program
had on your decision to redesign your system?
1.. [RECORD RESPONSE]
88. DON'T KNOWA.JOT SURE
99. REFUSED
SR20. Since participating in this program, have you conducted or contracted for additional system
analysis and redesign on the same irrigation system or another?
1. YES
2. NO
'
SKIP TO PI1
88. DON'T KNOWNOT SURE ) SKIP TO PII.
99. REFUSED ) SKIP TO PIl.
SR2la. Was the scope of this analysis the about the same as the analysis completed with the
program?
I. YES
2. NO, MORE EXTENSIVE, LARGER SCOPE
3. NO, LESS EXTENSIVE, SMALLER SCOPE
88. DON'T KNOWNOT SURE
99. REFUSED
SR2Lb. Did &PACIFICORP or another organization cover the cost of the analyis?
1. YES
2. NO t SKIP TO SR2l.e
88. DON'T KNOWNOT SURE ) SKIP TO SR21f
99.REFUSED ) SKIPTO SR21f
SR21d. \Alhat program or sponsor covered the cost?
1.. &PACIFICORP) SKIPTO SR21.f
2, [RECORD RESPONSE]
88. DON'T KNOWNOT SURE ) SKIP TO SR21f
99. REFUSED) SKIP TO SR21f
SR2le. Why did you not apply for assistance from &PACIFICORP for this additional analysis?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SR2Lf. I'm going to read a statement about the equipment that you purchased on your own. On a scale
from 1 to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you "strongly agred' ,
please rate the following statement:
My experience with SPACIFICORP's APROGRAM program influrnced my decision to conduct additional
system analysis and redesign on my own.
Would you say you...[READ L-51
1. STRONGLY DISAGREE' SKIP TO PIl.
2. SOMEWHAT DISAGREE) SKIP TO PI1
3. NEITHER AGREE OR DISAGREE ) SKIP TO PIl
idahc lrigaticn Energy $3v;395 Evaiuaiioi'l Reioil
Ap$r;ndix C - Process Evaiuaticn Sui'"'ey irsliumenis
Fens tr-i i
Roclry Mountain Power
Exhibit No. 5 Page 1335 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
4. SOMEWHAT AGREE' SKIP TO PIl
5. STRONGLY AGREE' SKIP TO PIl
88. DON'T KNOWNOT SURE+ SKIP TO PIl
99, REFUSED) SKIP TO PI1
System Consultation and Pump Tesf
Iif &SYS_CONSULT=0, skip to next sectionl
lif &PIVLIN_UPGRADE=1 OR &EQUIP_EXHANGE=L, read "For this survey, we would like to focus
on iust the System Consultation that you had through the progran."l
SCL. How did you first become aware of the opportunity to have a customized irrigation system
analysis through the &PROGRAM program? [DO NOT READ RESPONSES; ALLOW MULTIPLE
RESPONSES]
1. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
2, &PACIFICORPRADIOADVERTISEMENT
3. &PACIFICORPPRINTADVERTISEMENT
4. &PACIFICORPPRINTEDMATERIALSIBROCHURE
5. &PACIFICORPONLINEADVERTISEMENT
6, &PACIFICORP TV ADVERTISEMENT
7. &PACIFICORPNEWSLETTER
8. &PACIFICORP WEBSITE
9. PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
10. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_I
&PACIFICORP SPONSORED ENERGY AUDIT OR TECHNICAL ASSESSMENT
FROM TRADE ALLY, VENDOR OR CONTRACTOR
ANOTHER BUSINESS COLLEAGUE
FAMILY, FRIEND, OR NEIGHBOR
OTHER ISPECIFY]:
DON'T KNOWNOT SURE
REFUSE
SC2. \afhy did you decide to do a customized system analysis with &PACIFICORP? IDO NOT READ
RESPONSES; ALLOW MULTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
1L. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Other [SPECIFY]:
15. To save water
88. DON'T KNOWNOT SURE
ida[r lrigaticr Eneigt Savirgs E';aluaiisii Repcft
A.p$sndi;< C - Prccess Evaiuailsri Sur;e--v lnsirunenis
11.
12.
13.
1,4.
15.
89.
99.
Ser:.: i---i t^l
Rocky Mountein Power
Exhibit No. 5 Page 1336 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
99. REFUSE
[IF more than one response to SC2] SC2a. Of those reasons, which one was most influential in your
decision to participate in the program? [ALLOW ONLY ONE RESPONSE.]
1.. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
L4. Other [SPECIFY]:
15. To save water
88. DON'T KNOWNOT SURE
99. REFUSED
SC3. A representative came out to your facility to inspect existing equipment and determine ways to
improve your irrigation system. Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5
indicates'very satisfied', how satisfied were you with the representative who came out to your facility?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO SCs
5. VERY SATISFIED ) SKIP TO SCs
88. DON'T KNOWNOT SURE ) SKIP TO SCs
99. REFUSED ) SKIP TO SCs
SCa. Why were you less than satisfied with the representative?
1. [RECORD RESPONSE]
88. DON'T KNOWNIOT SURE
99. REFUSED
SC5. After the inspectiory you received a report detailing recommendations to improve your system.
Using a scale of 1 to 5 where 1 indicates 'very dissatisfied' and 5 indicates 'very satisfied', how satisfied
were you with the report?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO SC7
5. VERY SATISFIED ) SKIP TO SC7
88. DON'T KNOWAIOT SURE ) SKIP TO SC7
99.REFUSED )SKIPTOSCT
idalrc irigaticr Energy Savinqs Evaiuaiion Reloft
A.ppendix C .. Prccess tvalualien Su*ey lnstru,renis
Fagc E-17
SC6. \Alhy were you less than satisfied with the report?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SC7. \A/hat action did you take following the report? [ALLOW MULTIPLE RESPONSES]
1. PUMP TEST ) SKIP TO SCTa
2. SYSTEMANALYSIS ) SKIPTO SPI.
3. NONE) SKIP TO SPI.
4. Other [SPECIFY]:) SKIP TO SP1
88. DON'T KNOWNOT SURE ) SKIP TO SPl.
99.REFUSED ) SKIPTOSPl
SC7a. What action did you take following the pump test?
1. REPLACE OR REPAIR PUMP MOTORS' SKIP TO SPI.
2, REPLACE ORREPAIR PUMP IMPELLER' SKIP TO SP1
3. REPLACE OR REPAIR PUMP BOWL ) SKIP TO SPl
4. PUMP ADIUSTMENT ) SKIP TO SP1
5. IMPELLER TRIMMING ) SKIP TO SPl
6. CHANGE TO VARIABLE SPEED/FREQUENCY DRIVE (VSD/VFD) SKIP TO SPl
7. SYSTEM ANALYSE ) SKIP TO SPl
8. NONE) SKIP TO SP1
9. Other [SPECIFY]:) SKIP TO SPl
88. DON'T KNOWNOT SURE) SKIP TO SPl.
99. REFUSED) SKIP TO SPl
Roclry Mountain Power
Exhibit No. 5 Page 1337 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Pivot and Linear Upgrade
lif &PMIN_UPGRADE=0, skip to next sectionl
lif &EQUIP-EXHANGE=L, read "For this survey, we would like to focus on just the Pivot or Linear
Sprinkler Equipment that you upgraded through the program."l
PLl. How did you first become aware of incentives offered to upgrade pivot and linear equipment
through the &PROGRAM program? [DO NOT READ RESPONSES; ALLOW MULTIPLE
RESPONSES]
1. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
2. &PACIFICORPRADIOADVERTISEMENT
3. &PACIFICORPPRINTADVERTISEMENT
4. &PACIFICORPPRTNTED MATERIALS/BROCHURE
5. &PACIFICORPONLINEADVERTISEMENT
6. &PACIFICORP TV ADVERTISEMENT
7. &PACIFICORPNEWSLETTER
8. &PACIFICORP WEBSITE
9, PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
10. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_]
11. &PACIFICORP SPONSORED ENERGY ALiDIT OR TECHNICAL ASSESSMENT
12. FROM TRADE ALLY, VENDOR OR CONTRACTOR
13. ANOTHER BUSINESS COLLEAGUE
isans liri$ati$l Energ,v Savirys Evaiuaii'3il ReDori
App*ndix C -'Piccess Lvaluatisn *\ur;e.v lnsi*menis
Fens, l--^'i R
Rocky Mountain Power
Exhibit No. 5 Page I338 of 1365
Case No. PAC-E-14{7
\Mtness: Kathryn C. Hymas
14. FAMILY, FRIEND, ORNEIGHBOR
15. OTHER [SPECIFY]:
90. DON'T KNOWNOT SURE
99. REFUSE
PL2. \A/hy did you decide to upgrade your equipment with the program? IDO NOT READ
RESPONSES; ALLOW MULTIPTE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
L0. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Other [SPECIFY]:
15. To save water
88. DON'T KNOWNOT SURE
99. REFUSE
[IF more than one response to PL2]
PL2a. Of those reasons, which one was most influential in your decision to participate in the program?
IALLOW ONLY ONE RESPONSEI
1.. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
l. 1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Other [SPECIFY]:
15. To save water
88. DON'T KNOWNOT SURE
99. REFUSED
PL3. Our records show that you worked with &VENDOR to purchase new equipment. Were they able to
answer all of your questions about the program?
idanu lrigaticn Enurgy Sar,ings E.;aiuaiion Remii
$.ppen,Jix C .. Process Evaluation Survey insiiumenis
Pans ij--'{ Q
.*n, on *olT9"HlliiliiffJ
*,.!3liA?; ii?';i,i;31
1. YES ) SKIP TO PLs
2. NO
88. DON'T KNOWNOTSURE ) SKIP TO PLs
99. REFUSED ) SKIP TO PLs
PL4. What could &VENDOR not explain or describe to your satisfaction?
'1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
PLS. Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5 indicates'very satisfied', overall,
how satisfied were you with the performance of the new &PryLIN-EQUIP?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED ) SKIP TO PL7
4. SOMEWHAT SATISFIED ) SKIP TO PL7
5. VERY SATISFIED ) SKIP TO PL7
88. DON'T KNOWNOT SURE ) SKIP TO PL7
99. REFUSED ) SKIP TO PL7
PL5. \A/hy were you less than satisfied with the performance of the &PIVLIN_EQUIP?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
PL7.Is all of the equipment installed through the program in &YEAR still installed?
1. YES ) SKIP TO PL8
2. NO
88. DON'T KNOWNOT SURE ) SKIP TO PL8
99. REFUSED ) SKIPTOPLs
PL7a. What has been removed?
1. Nozzles
2. Pressure regulators
3. Sprinkler packages
4. OTHER [RECORD RESPONSE ]
88. DON',TKNOWA{OTSURE
99. REFUSED
PL7b. Why have they been removed?
.1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
PL8. With the &PROGRAM program, &FIRM received &INCENTIVE in financial incentives for
installing &P[VLIN_EQUIP.
ldahc lrii;atir:n Eneigy $sv;ig5 Evaiuation Repon
Appendix C - Prccess Evaluation hlurue.v insiiumenis
Fenr- F^?i'\
Roclq Mountain Power
Exhibit No. 5 Page 1340 of 1365
*,.:3::,*fif?-'"Ifr:l
On a scale from 1 to 5, with 1 being not important at all and 5 being extremely important, how important
were the following factors in deciding which equipment to install.
A. RECOMMENDATION FROM CONTRACTOR OR VENDOR [if &VENDOR TSNOTNULL,
replace "Contractor or vendor" with &VENDOR] _B. INFORMATION ON ENERGYSAVINGS
C. INFORMATION ON WATER SAVINGS
D. &PACIFICORP INCENTTVE
-
E. FAMILIARITY WITH THIS EQUIPMENT
F. PREVIOUS PARTICIPATION WITH A &PACIFICORP PROGRAM
G. CORPORATE POLICY REGARDING ENERGY REDUCTION
PL9. Without the program, meaning without the financial incentive, would you have still installed the
exact same &PIVLIN_EQUIP at the same time?
1. YES ' PL15
2. NO
88. DON',T KNOWAiOT SURE
99. REFUSED
PL10. Without the program, would you have installed any &PIVLIN_EQUIP?
1. YES
2. NO ) SKIP TO PL15
88. DON'TKNOWA{OTSURE
99. REFUSED
PLll. Would you have installed this equipment within 12 months of when you did with the program? O1. YES
2. NO ) SKIP TO PL15
88. DON'T KNOWI{OT SURE ) SKIP TO PL15
99. REFUSED ) SKIP TO PL15
PL12. Relative to the energy efficiency of equipment installed through the program, how would you
characterize the efficiency of equipment you would have installed without the program?
1,. ]ust as efficient as installed with the program
2. Lower than installed through the program, but better than the standard efficiency
3. Standard efficiency
88, DON'T KNOWNOT SURE
99. REFUSED
PL1.3. Would you have installed the same amount of &PIVLIN_EQUIP?
1. YES ) SKIP TO PL15
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
PL14. Would you have installed more or less equipment?
1. MORE) How much more?
2. LESS) How much less?
idah+ lrigaticn Ensr6y Savinqs Evaiuaiian Repc*
A.ppendix C .. Process Evalualisn Sul;ey insiruments
Fags [-?i
,"n.on*"lTf'"HilfliiY#
*,"!3li*?;il?11,i,31
88. DON'T KNOWNOT SURE
99. REFUSED
lrF PLSD < 3 AND PL1(F 2I
PL15a. Previously, you said that the financial incentive was not important in your decision to install the
equipment. However, you also said that without the program, you would not have installed any
equipment. In your own words, can you please describe what impact the program had on your decision
to install the equipment?
t. [RECORD RESPONSE]
88. DON'T KNOWAJOT SURE
99. REFUSED
IIF PL8D < 3 AND PL10 = 2l
PL15b. Previously, you said that financial incentive was not important in your decision to install the
equipment. However, you also said that without the program, you would not have installed any
equipment with 12 months of when you did. In your own words, can you please describe what impact
the program had on your decision to install the equipment?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF PL8D > 3 AND PL10 = 1l
PL15c. Previously, you said that the incentive was important in your decision to install the equipment.
However, you also said that without the program, you would have installed the exact same equipment
at the same time. In your own words, can you please describe what impact the program had on your
decision to install the equipment?
1.. [RECORD RESPONSEI
88. DON'T KNOWNOT SURE
99. REFUSED
PL15. Since participating in this program/ have you purchased or installed any additional
&PIVLIN_EQUIP ?
1. YES
2, NO ) SKIP TO PI1
88. DON'T KNOWNOT SURE ) SKIP to PI1
99. REFUSED t SKIP to PIL
PL16a. What did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
PL16b. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
PL15c. Did you receive assistance from &PACIFICORP or another organization?
idahu lrrigaticn En*rgy Saviags Evaiuaiion R*m$
,a.ppenriix C .. Fli"gc,rss fivalualicn S.i.ti".i*y Instrl;nenis
F*E* ii^?:?
Rocky Mountain Power
Exhibit No. 5 Page 1342 of 1 365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
1. YES
2. NO t SKIP TO PLL8e
88. DON'T KNOWA\rOT SURE ) SKIP TO PLl8e
99.REFUSED ) SKIPTOPLIse
PL15d. What program or sponsor provided assistance?
1. &PACIFICORP
2. IRECORD RESPONSEI
88. DON'T KNOWNOT SURE
99. REFUSED
PL16e. I'm going to read a statement about the equipment that you purchased on your own. On a scale
from 1 to 5, with f. indicating that you "strongly disagree" and 5 indicating that you "strongly agred',
please rate the following statement:
My experience with SPACIEICORP's &PROGRM program influenced my decision to install other high fficiency
equipment on my ou)n.
Would you say you...[READ 1.-5]
1. STRONGLY DISAGREE
2. SOMEWF{AT DISAGREE
3. NEITHER AGREE OR DISAGREE
4. SOMEWHAT AGREE
5. STRONGLYAGREE
88. DON'T KNOWAJOT SURE
99. REFUSED
IIF PL15d >1; ELSE SKIP TO PIll PL18f. \l/hy did you not apply for an incentive from &PACIFICORP
for this equipment?
1. [RECORD RESPONSE] ) SKIP TO PIl
88. DON'T KNOWNOT SURE' SKIP TO PIl
99. REFUSED) SKIP TO PIl.
Equipment Exchange
tif &EQUIP_EXCHANGE=0, skip to next sectionl
EXl. How did you first become aware of the opportunity to exchange wom equipment through the
&PROGRAM program? tDO NOT READ RESPONSES; ALLOW MULTIPLE RESPONSESI
1. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
2. &PACIFICORP RADIO ADVERTISEMENT
3. &PACIFICORP PRINTADVERTISEMENT
4. &PACIFICORP PRINTED MATERIALS/BROCHURE
5. &PACIFICORPONLINEADVERTISEMENT
6. &PACIFICORP TV ADVERTISEMENT
7. &PACIFICORPNEWSLETTER
8. &PACIFICORP WEBSITE
9. PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
10. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_]
11. &PACIFICORP SPONSORED ENERGY AUDIT OR TECHNICAL ASSESSMENT
12. FROM TRADE ALLY, VENDOR OR CONTRACTOR
idahc ltrigtraticn Energv $avinqs Evaiuaii$n R*Dsrt
A.pperndix (l - Prscess fi.valuaticn Sur'iey lnsliuinelis
Fagu [^?3
Rocky Mountain Power
Exhibit No. 5 Page 'l 343 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
13. ANOTHER BUSINESS COLLEAGUE
14. FAMILY, FRIEND, OR NEIGHBOR
15. OTHER [SPECIFY]:
91.. DON'T KNOWNOT SURE
99. REFUSE
EX2. Why did you decide to exchange equipment with the program? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
1.3. Recommended by family, friend or neighbor
14. Other [SPECIFY]:
15. To save water
88. DON'T KNOWNOT SURE
99. REFUSE
[IF more than one response to EX2]
EX2a. Of those reasons, which one was most influential in your decision to participate in the program?
IALLOW ONLY ONE RESPONSEI
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
11. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14. Other [SPECIFY]:
15. To save water
88. DON'T KNOWNIOT SURE
99. REFUSED
i$hc lir"igaticn Enelgy Savings Evaiuaiion Renofi
,r.ppendix C * Fri:c,ess tvaluaticn S.ul;ey insirunenis
PaEs H^?4
Rocky Mountain Power
Exhibit No. 5 Page 1344 of 1 365
*,.!3li*i;ii?*ffi
EX3. Our records show that you exchanged equipment through &VENDOR. Were they able to answer
all of your questions about the program?
1. YES )SKIPTOEXs
2. NO
88. DON'T KNOWA{OT SURE ' SKIP TO EXs
99. REFUSED ) SKIP TO EXs
EX4. What could &VENDOR not explain or describe to your satisfaction?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
lif &NOZZLE_COUNT>0, ELSE SKIP TO EX6l EXs. Our records show that you exchanged
&NOZZLE_COUNT nozzles; did you install all of the nozzles in &YEAR?
1. YES ) SKIP TO EXsb
2. NO
88. DON'T KNOWNOT SURE ) SKIP TO EXsb
99. REFUSED ) SKIPTO EXsb
EXSa. \A/hy did you not install them the same year of exchange?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EXsb. Are all of the nozzles still installed?
1. YES ) SKIP TO EXsd
2. NO
88. DON',T KNOWA{OT SURE ) SKIP TO EXsd
99. REFUSED ) SKIPTO EXsd
EXSc. \Atrhy have they been removed?
I. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EXsd. Using a scale of 1 to 5 where 1 indicates 'very dissatisfied' and 5 indicates'very satisfied', overall,
how satisfied were you with the performance of the new nozzles?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED ) SKIP TO EX6
4. SOMEWHATSATISFIED ) SKIP TO EX5
5. VERY SATISFIED ) SKIP TO EX5
88. DON'T KNOWNOT SURE ) SKIP TO EX5
99. REFUSED ) SKIP TO EX6
EXSe. \Alhy were you less than satisfied with the performance of the nozzles?
1.. [RECORD RESPONSE]
idanc lxii;ation Energv Savinqs E',,aiuaiion R*pori
Appendix 0 -.Frccess Evaiuatisn Sui"re--r" inslrumenis
Fage [-?5
Rocky Mountain Power
Exhibit No. 5 Page 1345 of 1 365
*,"!3ll*?;il?*;i,fr3i
88. DON'T KNOWNOT SURE
99. REFUSED
lif &DRAIN_COUNT>0, ELSE SKIP TO EXT] EX6. Our records show that you exchanged
&DRAIN_COUNT drains; did you install all of the drains in &YEAR?
1. YES ) SKIP TO EX6b
2. NO
88. DON',T KNOWNOT SURE t SKIP TO EX6b
99.REFUSED ) SKIPTO EX6b
EX6a. \Atrhy did you not install them the same year of exchange?
1.. IRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EX6b. Are all of the drains still installed?
1. YES )SKIPTOEX5d
2. NO
88. DON'TKNOWNOTSURE ' SKIPTO EX6d
99. REFUSED ) SKIP TO EX6d
EX5c. Why have they been removed?
1.. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
EX6d. Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5 indicates'very satisfied', overall,
how satisfied were you with the performance of the new drains?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED ) SKIP TO EX7
4. SOMEWHAT SATISFIED ) SKIP TO EX7
5. VERY SATISFIED ) SKIP TO EX7
88. DON'TKNOWNOTSURE ) SKIPTO EX7
99. REFUSED ) SKIP TO EX7
EX6e. Why were you less than satisfied with the performance of the drains?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
[if &GASKET_COUNT>0, ELSE SKIP TO EX8] EX7. Our records show that you exchanged
&GASKET_COUNT gaskets; did you install all of the gaskets in &YEAR?
1. YES ) SKIP TO EXTb
2. NO
88. DON'T KNOWNOT SURE ) SKIP TO EXTb
99. REFUSED ) SKIP TO EXTb
Fags ll-iit)
i$aii* lxigaticn f nergv Savings Evuiuaiion Reion
,a,psendix l: - Ficcess Evalualicn Liur;ey issliu,trnis
Rocky Mountain Power
Exhibit No. 5 Page 1 346 of 1 365
*,"!3iiA?;if?.ffii
EX7a. Why did you not install them the same year of exchange?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EX7b. Are all of the gaskets still installed?
1. YES ) SKIP TO EXTd
2. NO
88. DON'T KNOWNOT SURE ) SKIP TO EXTd
99. REFUSED ) SKIP TO EXTd
EX7c. \A/hy have they been removed?
1.. [RECORD RESPONSE]
88. DON'T KNOWA\IOT SURE
99. REFUSED
EX7d,. Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5 indicates'very satisfied', overall,
how satisfied were you with the performance of the new gaskets?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED ) SKIP TO EX8
4. SOMEWHAT SATISFIED ) SKIP TO EX8
5. VERY SATISFIED ) SKIP TO EX8
88. DON'T KNOWNOT SURE ) SKIP TO EX8
99.REFUSED )SKIPTOEXs
EX7e. Why were you less than satisfied with the performance of the gaskets?
1. [RECORD RESPONSE]
88. DON'T KNOWAJOT SURE
99. REFUSED
EX8. With the &PROGRAM program, &FIRM received &MEASURECOST worth of new nozzles,
gaskets, and/or drains at for free.
On a scale from 1 to 5, with 1 being not important at all and 5 being extremely important, how important
were the following factors in deciding which equipment to install.
A. RECOMMENDATION FROM CONTRACTOR OR VENDOR [if &VENDOR ISNOTNULL,
replace "Contractor or vendor" with &VENDOR] _B. INFORMATION ON ENERGYSAVINGS
C. INFORMATION ON WATER SAVINGS
D. FREE EQUIPMENT
E. FAMILIARITY WITH TFIIS EQUIPMENT
F. PREVIOUS PARTICIPATION WITH A &PACIFICORP PROGRAM
G. CORPORATE POLICY REGARDING ENERY REDUCTION
lda.\c lrigaticn Enetgv Savinqs Evaiuaiion Reptfi
A.psendlx C * Frocess Evaiualion Suruey lnsti"uments
Pags i-i7
Rocky Mountain Power
Exhibit No. 5 Page 1347 of 1365
*,"!3ii*?;if?*,1i,31
[if &NOZZLE_COUNT{] EX9a. When answering these next questions, think specifically about
nozzles installed through the program. Without the program, meaning without equipment at no cost to
you, would you have still installed the exact same &NOZZLE_COUNT nozzles at the same time?
1. YES ) SKIP TO EX9g
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
EX9b. Without the program, would you have installed any nozzles?
1. YES
2, NO ) SKIP TO 99
88. DON'T KNOWNOT SURE
99. REFUSED
EX9c. Would you have installed these nozzles within 12 months of when you did with the program?
1. YES
2. NO ) SKIP TO EXeg
88. DON'T KNOWNOTSURE ) SKIP TO EX9g
99. REFUSED ) SKIP TO EX9g
EX9d Relative to the flow rate of nozzles installed through the program, how would you characterize the
flow rate of nozzles you would have installed without the program? fsize of nozzles affects flow rate, if
the respondent needs additional guidance, ask about water efficienry rather than energy efficiency]
1. The same as installed with the program
2. Higher flow rate than installed through the program, but using less water than standard
3. Standard flow rate
EX9e. Would you have installed the same amount, &NOZZLE_COUNT, of nozzles?
1. YES)EXeg
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
EX9f. Would you have installed more or less equipment?
1. MORE) How much more?
2. LESS) How much less?
88. DON'T KNOWNOT SURE
99. REFUSED
IIF EXSD < 3 AND EX9b=21
EX9g. Previously, you said that the no cost equipment was not important in your decision to install the
nozzles. However, you also said that without the program, you would not have installed any equipment.
In your own words, can you please describe what impact the program had on your decision to install the
equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
irisll$ lili$aticn Eneigy $avings E$aiuaii0ri Re$0ri
A.pr:endix C - Prccess [valuaticn Suruey insiruments
Fags.: [^llB
.*' on * o*T!'"I".ilfl iil,,g
*,.33ii4?;ii?11,i;31
UF EXBD < 3 AND EX9c = 2l
EX9h. Previously, you said that the no cost equipment was not important in your decision to install the
nozzles. However, you also said that without the program, you would not have installed any nozzles
with 12 months of when you did. In your own words, can you please describe what impact the program
had on your decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'TKNOWATOTSURE
99. REFUSED
IIF EXSD > 3 AND EX9b = 1l
EX9i. Previously, you said that the no cost equipment was important in your decision to install the
nozzles. However, you also said that without the program, you would have installed the exact same
equipment at the same time. In your own words, can you please describe what impact the program had
on your decision to install the nozzles?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
[if &DRAIN-COUNT>0] EX10a. \Atrhen answering these next questions, think specifically about drains
installed through the program. Without the program, meaning without equipment at no cost to you,
would you have still installed the exact same &DRAIN_COUNT drains at the same time?
1. YES
' SKIP TO EXl.Of
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
EX10b. Without the program, would you have installed any drains?
1. YES
2. NO ) SKIP TO EXIOf
88. DON'T KNOWNOT SURE
99, REFUSED
EX10c. Would you have installed these drains within 12 months of when you did with the program?
1.. YES
2. NO ) SKIP TO EXL0f
88. DON'T KNOWNOT SURE ) SKIP TO EXIOf
99, REFUSED ) SKIP TO EXIOf
EX10d. Would you have installed the same amount, &DRAIN_COUNT, of drains?
1. YES t EX10f
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
EX10e. Would you have installed more or less equipment?
1. MORE) How much more?
2. LESS) How much less?
88. DON'T KNOWNOT SURE
ldaha lrriqaticn Eneryy Savings Evaruaiion ReuoR
Aprendix C - Prccess Evaiualion hluryey |nstrumenis
$en* S:-?Q
E,h i bit N"lTEvaHl llili iyg
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
99. REFUSED
uF EXSD < 3 AND EX10b = 2l
EXL0f. Previously, you said that the no cost equipment was not important in your decision to install the
drains. However, you also said that without the program, you would not have installed any equipment.
In your own words, can you please describe what impact the program had on your decision to install the
equipment?
I. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF EX8D < 3 AND EX10c =21
EX10g. Previously, you said that the no cost equipment was not important in your decision to install the
drains. However, you also said that without the program, you would not have installed any drains with
12 months of when you did. In your own words, can you please describe what impact the program had
on your decision to install the equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
uF EX8D > 3 AND EX10b = 1l
EX10h. Previously, you said that the no cost equipment was important in your decision to install the
drains. However, you also said that without the program, you would have installed the exact same
equipment at the same time. In your own words, can you please describe what impact the program had
on your decision to install the drains?
1.. TRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
[if &GASKET_COUNT>0] EXlla. When answering these next questions, think specifically about
gaskets installed through the program. Without the program, meaning without equipment at no cost to
you, would you have still installed the exact same &GASKET_COUNT gaskets at the same time?
1. YES ) SKIP TO EXllg
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
Exllb. Without the program, would you have installed any gaskets?
1. YES
2. NO ) SKIP TO EXllg
88. DON'T KNOWNOT SURE
99. REFUSED
EXllc. Would you have installed these gaskets within 12 months of when you
1. YES
2. NO ) SKIP TO EXLLg
88. DON',T KNOWNOT SURE ) SKIP TO EXLLg
99. REFUSED ) SKIP TO EX1lg
iri*tr* ilrigaticn Energl. Sa""ings Evaiuaiion Renoli
,a.i:sen,li;< C - Prscess iralualio;r *\ur;e--v insirumeris
did with the program?
$nns. F^llt'l
Rocky Mountain Porver
Exhibit No.5 Page 1350 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
EX1Ld. Would you have installed the same amount, &GASKET_COUNT, of gaskets?
1. YES ) EXI.lg
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
EXLLe. Would you have installed more or less equipment?
L. MORE) Howmuchmore?
2. LESS) How much less?
88. DON'T KNOWNOT SURE
99. REFUSED
UF EXSD < 3 AND EX11b = 2l
EXLLf. Previously, you said that the no cost equipment was not important in your decision to install the
gaskets. However, you also said that without the program, you would not have installed any equipment.
In your own words, can you please describe what impact the program had on your decision to install the
equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF EX8D < 3 AND EX11c = 2l
EXllg. Previously, you said that the no cost equipment was not important in your decision to install the
gaskets. However, you also said that without the program, you would not have installed any gaskets
with 12 months of when you did. In your own words, can you please describe what impact the program
had on your decision to install the equipment?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF EXSD > 3 AND EX11b = 1l
EXL1.h. Previously, you said that the no cost equipment was important in your decision to install the
gaskets. However, you also said that without the program, you would have installed the exact same
equipment at the same time. In your own words, can you please describe what impact the program had
on your decision to install the gaskets?
1. [RECORD RESPONSE]
88, DON'T KNOWNOT SURE
99. REFUSED
8X12. Since participating in this program, have you purchased or installed any additional efficient
nozzles, gaskets or drains?
1, YES
2. NO ) SKIP TO EX1"6
88. DON'T KNOWNOT SURE ) SKIP to EXL6
99. REFUSED ) SKIP to EXL5
idano lri1;ation Energy Savings Evaiuaiion Repoft
A.psendix C - Prscess Evaluahon Suruey insirirmenis
Fags E-3'i
Roclry Mountain Power
Exhibit No. 5 Page 1 351 of 1 365
Case No. PAC-E-14-07
VMtness: Kathryn C. Hymas
EX13. What did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1.. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
8X14. How many did you purchase or install?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EXL5. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2. NO ) SKIP TO EXL5e
88. DON'T KNOWNOT SURE ) SKIP TO EX1.5f
99. REFUSED ) SKIPTOEXI5f
EX15d. What program or sponsor provided assistance?
1.. &PACIFICORP) SKIPTO Exlsf
2. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE ) SKIP TO EX1.5f
99. REFUSED' SKIP TO EXI.5f
EX15e. Why did you not apply for an incentive from &PACIFICORP for this equipment?
].. IRECORD RESPONSE]
88. DON'T KNOWATOT SURE
99. REFUSED
EXL5f. I'm going to read a statement about the equipment that you purchased on your own. On a scale
from 1 to 5, with f. indicating that you "strongly disagree" and 5 indicating that you "strongly agree",
please rate the following statement:
My experience with €TPACIFICORP's &PROGRAM program influenced my decision to install additional
fficient nozzles, gaskets or drains on my own.
Would you say you...[READ 1.-51
1. STRONGLY DISAGREE
2. SOMEWHATDISAGREE
3. NEITHER AGREE OR DISAGREE
4. SOMEWHATAGREE
5. STRONGLY AGREE
88. DON'T KNOWNOT SURE
99. REFUSED
Post-l nstallation
[if &POSTINSPECTDATE{] PIl". After you installed the new equipment, a program representative
came out to your site to inspect the installation, around &POSTINSPECTDATE. Do you recall this visit?
1. YES
2. NO ) SKIP TO SPl
idail* ilrigaticn Enslgy Savings Evuiuaiion R*uot't
AppE:n,lix C - Frccess Evaiualisn ;lurue--t" insirumenis
Fnn* tr-i?
Rocky Mountain Power
Exhibit No, 5 Page 1 352 of 1 365
*"!3X,"*?;ift'*,i.,31
88. DON'T KNOWNOT SURE ' SKIP TO SPl
99.REFUSED ) SKIPTO SPl
PI2. Using a scale of 1 to 5 where 1 indicates'very dissatisfied' and 5 indicates'very satisfied', overall,
how satisfied were you with the inspection?
1. VERY DISSATISFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED ) SKIP TO SPl
4. SOMEWHATSATISFIED ) SKIP TO SP1
5. VERY SATISFIED ' SKIP TO SPl
88. DON'T KNOWA{OT SURE ) SKIP TO SPl
99. REFUSED ) SKIP TO SPl
PL2a. Why were you less than satisfied with the inspection to verify your installation?
1. [RECORD RESPONSE] ) SKIP TO SPl
88. DON'T KNOWNOT SURE) SKIP TO SPl
99. REFUSED) SKIP TO SPI.
Unlike Spillover
SPL. Since participating in this program, have you purchased or installed any irrigation equipment that
would improve electric efficiency or water pumping efficienry, [IF PL16=1 OR EX12=1, add "besides
what we already discussed."]?
1. YES
2. NO ) SKIP TO 81
88. DON'T KNOWNIOT SURE ) SKIP to B1
99. REFUSED ) SKIP to 8L
SP2a. \Atrhat did you purchase or install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SP2b. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SP2c. Did you receive an incentive from &PACIFICORP or another organization?
1. YES
2, NO ' SKIP TO SP2C
88. DON'T KNOWNOT SURE ) SKIP TO SP2f
99.REFUSED ) SKIPTO SP2f
SP2d. What program or sponsor provided an incentive?
I. &PACIFICORP) SKIP TO SP2f
2. [RECORD RESPONSE]
88. DON'T KNOWNOTSURE ) SKIP TO SP2f
99. REFUSED) SKIP TO SP2f
idano lrillaticn Energv $avinqs fvaiuaiion Reion
Appendix C .' Pracess Evaiuation Surusy h.<iruments
Se,:s F^?i
Rocky Mountain Power
Exhibit No. 5 Page 1353 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
SP2e. Why did you not apply for an incentive from &PACIFICORP for this equipment?
1. TRECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
SP2f. I'm going to read a statement about the equipment that you purchased on your own. On a scale
from 1 to 5, with 1 indicating that you "strongly disagree" and 5 indicating that you "strongly agred',
please rate the following statement:
My experience with APACIFICORP's &PROGRAM program influenced my decision to install other high
fficiency equipment on my own.
Would you say you...[READ L-51
1. STRONGLY DISAGREE) SKIP TO 81.
2. SOMEWHATDISAGREE) SKIP TO 81
3. NEITHER AGREE OR DISAGREE ) SKIP TO 81.
4. SOMEWHATAGREE) SKIP TO B1.
5. STRONGLY AGREE) SKIP TO B1.
88. DON'T KNOWNOT SURE) SKIP TO 81
99. REFUSED) SKIP TO 81
Barriers
B1. Do you think there are other changes that you could make to improve electric efficienry or water
pumping efficiency?
1. YES
2. NO ) SKIP TO ICl
88. DON'T KNOWNOT SURE ) SKIP TO ICl.
99. REFUSED '
SKIP TO ICl.
82. Could you provide some examples of changes you think would improve electric efficiency or water
pumping efficiency? [PROBE FOR ADDITIONAL]
L. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
83. Are plans in place to make any of those changes?
1. YES
2. NO ) SKIP TO 85
88. DON'T KNOWAJOT SURE ' SKIP TO 85
99. REFUSED ) SKIP TO 85
B4. Are incentives from &PACIFICORP or another organization part of those plans?
1. NO
2. YES
88. DON'T KNOWNOT SURE
99. REFUSED
iiiah* lirigaticn Energy $avings Evu!ualion Rer,:R
Ap$ernrlix C .. Process Hvoluaticn tur'lsy instiumentn
Fags [^34
Rocky Mountain Power
Exhibit No. 5 Page 1354 of '1365
Case No, PAC-E-14-07
Wtness: Kathryn C. Hymas
85. What factors could prevent &FIRM from making these changes? IDO NOT READ RESPONSES;
ALTOW MUITIPIE RESPONSES]
1. HIGH UPFRONT COSTS
2. LACK OF ACCESS TO CAPITAL
3. LONG PAYBACK PERIOD; SLOW RATE OF RETURN
4. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
5. LACK OF INFORMATION ABOUT SAVINGS AND PERI'ORMANCE
6. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
7. OTHER (SPECIFY
-)
88. DON'T KNOWNOT SURE
99. REFUSED
IIF MORE THAN ONE RESPONSE TO B5l 85. Which of these do you think is the most challenging
factor?
1. HIGH UPFRONT COSTS
2. LACK OF ACCESS TO CAPITAL
3. LONG PAYBACK PERIOD; SLOW RATE OF REruRN
4. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
5. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
6. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
7. OTHER (SPECIFY
-)
88. DON'T KNOWAIOT SURE
99. REFUSED
Satisfaction
ICL. Using a scale of L to 5 where 1 indicates'very dissatisfied' and 5 indicates'very satisfied', how
satisfied were you overall with the program?
1. VERY DISSATSIFIED
2. SOMEWHAT DISSATISFIED
3. NEITHER SATISFIED OR DISSATISFIED
4. SOMEWHAT SATISFIED ) SKIP TO IC2
5. VERY SATISFIED ) SKIP TO IC2
88. DON',T KNOWNOT SURE ) SKIP TO rC2
99. REFUSED ) SKIP TO IC2
ICIA. Why were you less than satisfied with the program overall?
L. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
lcz.If you could change anything about the &PROGRAM program, what would you change?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
ldaho lrrii;ation Ensi'gy $avings Evaiuaiisn Reroft
Appendix C -.Process fivaluati+n Suruey instn.rnenis
Fags [-35
Rocky Mountain Power
Exhibit No. 5 Page 1355 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
99. REFUSED
IC3. During your involvement with &PROGRAM did you ever contact &PACIFICORP with questions or
requests for assistance?
1. YES
2. NO ) SKIP TO FBl
88. DON'T KNOWNOT SURE ) SKIP TO FB1
99. REFUSED ) SKIP TO FBl
IC4. Were &PACIFICORP and its representatives timely in addressing your questions in regards to the
program?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
IC5. Were &PACIFICORP and its representatives knowledgeable in regards to the program and the
program eligibility requirements?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
Firmographics
FBl INTRO.
Now I have a few final, general questions about your company for comparison purposes only.
FBl. Approximately, what percent of your total annual operating costs does your water bill represent?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
FB2. Approximately, what percent of your total annual operating costs does your electricity bill
represent?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
FB3. About how many people do you employ during the growing season?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
End
ENDL. Those are all of the questions that I have for you. Is there anything about your experiences with
&PACIFICORP's &PROGRAM program you'd like to mention that we did not talk about today?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
ifiari+ lilig;athn Eneigy Sauings Evaiuuiion R+mil
Ap$endix C - Pxrcess Evalualicn !-lulvey insiiltnenis
Fen* F:^'lfi
Roclry Mountain Power
Exhibit No. 5 Page 1356 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
99. REFUSED
[THANK RESPONDENT AND TERMINATE SURVEY]
C.3 IES Non-Participant Suntey Instrument
Note: Non-participants are CbI customers who are not identified as haoing started participating in any
PacifiCorp programs betutem 2009 and 2011-.
Objectives
These surveys are designed to meet the following list of objectives.o To assess awareness of PacifiCorp programs among non-participants
o To identify non-participant efficient purchasing. To understand barriers customers are facing that prevent increasing energy efficiency
o To characterize non-participant firms
Survey lnstrument
I ntroduction and Screen
INTROI.. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's energy efficiency programs so that they better suit the needs
of customers like you. This is not a sales call. May I please speak with the person who is responsible for
the $_CLASS electric account for $_FIRM?
1. YES, THAT IS ME ) SKIP TO INTRO3
2. YES, LET ME TRANSFER YOU
3. NOT NOW ) SCHEDULE APPT AND CALL BACK
4. NO/REFUSED ) TERMINATE
INTRO2. Hello, this is INTERVIEWER. calling on behalf of &PACIFICORP. We are conducting an
independent evaluation of &PACIFICORP's efficiency programs so that they better suit the needs of
customers like you. This is not a sales call. Do you have a few minutes? [IF NEEDED, READ: "This
survey is for research purposes only and will take about L0 minutes."I
7. YES ) SKIP TO IS2a
8. NOT NOW ) MAKE APPT. TO CALL BACK
9, NO/REFUSED ) TERMINATE
ldalio lrrigatim Energy $ar,ings Evaiuuiion R*;roft
Ai:oendix C - Process Evalualicn $uruey lnsir*ments
Variables
Variable Name Description Tvpe
&FIRM Comoanv name Text
&PHONE Phone number Numeric
&SITE Address Text
&PACIFICORP Rocky Mountain Power, Pacific Power Text
&CLASS Revenue Class Text
$er* i:^li?
Roclry Mountain Power
Exhibit No. 5 Page 1357 of '1365
*,.!31i,*;ii?*;1,fr31
INTRO3. Great. I d like to let you know that this call may be monitored or recorded for quality
assurance purposes. Also, all of your responses will be kept confidential and will not be revealed to
anyone outside of the research team.
[tF NEEDED, READ: "This survey is for research purposes only and will take about 10 minutes."]
1. CONTINUE WITH INTERVIEW
2. NOT NOW ) MAKE APPT. TO CALL BACK
3, NO/REFUSED ) TERMINATE
[IF VERIFICATION IS NEEDED, TELL THEM THEY CAN CALL SHAWN GRANT AT 801.-220-
41961.
Vl. First, I'd like to verify my records. Which utility company provides electricity at &SITE?
1. &PACIFICORP
2. OTHER ) TERMINATE
88. DON'T KNOWNOT SURE
99. REFUSE
[IF &_CLASS "COMMERCIAL" OR "INDUSTRIAL"]V2. Was this facility at &SITE constructed before or
after 2009?
1. BEFORE 2OO9
2, 2OO9ORLATER
Awareness
AL. Are you aware that &PACIFICORP offers incentives and technical assistance to &CLASS customers
to help them reduce electricity usage?
1. YES
2. NO ) SKIP to A4
88. DON'T KNOWNOT SURE ) SKIP TO A4
99. REFUSED ) SKIP TO A4
A2. How did you become aware that &PACIFICORP offers energy efficienry program(s)? [DO NOT
READ RESPONSES, SELECT ALL THAT APPLY]
16. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
17. &PACIFICORP RADIO ADVERTISEMENT
18. &PACIFICORP PRINT ADVERTISEMENT
19. &PACIFICORP PRINTED MATERIALS/BROCHURE
20. &PACIFICORP ONLINE ADVERTISEMENT
21. &PACIFICORP TV ADVERTISEMENT
22. &PACIFICORP NEWSLETTER
23. &PACIFICORP WEBSITE
24. PREVIOUS PARTICIPATION IN &PACIFICORP PROGRAMS
25. CONFERENCE, WORKSHOP, OR EVENT [SpECIFy:_]
26. &PACIFICORP SPONSORED ENERGY ALIDIT OR TECHNICAL ASSESSMENT
27. FROM TRADE ALLY, VENDOR OR CONTRACTOR
28. ANOTHER BUSINESS COLLEAGUE
29. FAMILY, FRIEND, OR NEIGHBOR
idahtl lrigaticn Ener5,cy Sauini;s Evaiualion R*pori
Apnc,ndix C - Flrccess Evaluation liuLrey lnstrunents
Sen* F-1R
Rodry Mountain Power
Exhibit No. 5 Page 1 358 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C, Hymas
30. OTHER [SPECIFYI:
92. DON'T KNOWNOT SURE
99. REFUSE
A3. \A/hich programs or services can you think of that &PACIFICORP offers to &CLASS customers? [DO
NOT READ RESPONSES, SELECT ALL THAT APPTY]
1. ENERGYFINANSWER
2. FINANSWER EXPRESS
3. SELF-DIRECTION CREDIT
4, RECOMMISSIONING
5. IRRIGATION LOAD CONTROL
6. IRRIGATION ENERGY SAVERS
7. INCENTIVES FOR EFFICIENT EQUIPMENT
8. TECHNICAL ASSISTANCE/ ENERGY ANALYSIS
9. DEMAND RESPONSE / LOAD CONTROL
10. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
A4. In the future, what is the best for &PACFICORP to keep you informed about programs they offer
that could help your firm save energy?
1. ACCOUNT REPRESENTATIVE OR OTHER &PACIFICORP STAFF
2. RADIO ADVERTISEMENT
3. PRINTADVERTISEMENT
4, PRINTEDMATERIALS/BROCHURE
5. ONLINEADVERTISEMENT
6, TVADVERTISEMENT
7, NEWSLETTER
8. WEBSITE
9. CONFERENCE, WORKSHOP, OR EVENT [SPECIFY:_]
10. TRADE ALLY, VENDOR OR CONTRACTOR
11. OTHER [SPECIFY]:
93. DON'T KNOWNOT SURE
99. REFUSE
Energy Efficient Actions by Non-Participants
UF Y2=2, SKIP TO EE21l
EEL. Between 2009 and2011,, did you have a systematic evaluation or audit of your facility, at &SITE, to
identify and implement operational improvements? IIF NEEDED: "this includes building and
equipment audits, system analyses, energy engineering analysis, other detailed studies."]
1. YES
2. NO ) SKIP TO EE8
88. DON'T KNOWNOT SURE ) SKIP TO EE8
99. REFUSED ) SKIP TO EE8
EE2. \A/hat factor or factors motivated you to have your facility undergo a systematic evaluation? [DO
NOT READ RESPONSES; ALLOW MULTIPLE RESPONSESI
1. To save money on electric bills.
2. To obtain an incentive.
idah* lrii.laticn Energy fuv;1gu Evaiualian Re*ol^t
A$sendix C - Prccess [reluatisn Sul+ev instiunents
Fags [-3$
Rocky Mountain Power
Exhibit No. 5 Page 1359 of 1365
Case No. PAC-E-14-07
Witness: Kathryn C. Hymas
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
5. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
L 1. Recommendation by contractors/trade allies
1.2. Recommended by colleague
13. Recommended by family, friend or neighbor
14. To improve operations, production, or quality
15. To improve value of property
15. To improve comfort
L7. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EE3. Did you receive assistance from &PACIFICORP or another organization? UF NEEDED: assistance
may include technical assistance or incentives]
1. YES
2. NO ) SKIP TO EE5
88. DON',TKNOWA{OTSURE ) SKIPTO EEs
99. REFUSED ) SKIP TO EEs
EE4. What program or sponsor provided assistance?
3. &PACIFICORP ) SKIPTO EE8
4. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EEs. What opportunities for improvement were identified? [PROBE FOR AS MUCH DETAIL AS
POSSTBLEI
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE6. What actions have you taken as a result of the study?
L. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF EE4 not 1]EE7. Why did you not apply for assistance from &PACIFICORP?'t. [RECORDRESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
idaha lrrigatir:rn En*rgy Savings Evaiuaii0ri R*$0r't
Appernrlix $ - Process Lvaluallon *ulvey insiruments
Frr:e i:-r!.i'l
Rocky Mountain Power
Exhibit No. 5 Page 1360 of 1365
*,,!3liA?; il?'=;i,fr 3l
EE8a. Did you install any high efficienry equipment at this site between 2009 and2011?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
EE8b. Did you make any improvements to this site between 2009 and 2011 to help conserve energy?
1. YES
2. NO
88. DON'T KNOWNOT SURE
99. REFUSED
[IF EE8a 'a 1 and EE8b + 1, SKIP TO EE1.5]
EE9. \Atrhat did you install? (PROBE FOR AS MUCH DETAIL AS POSSIBLE)
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
8E10. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EEll. What factor or factors motivated you to make these changes? [DO NOT READ RESPONSES;
ATLOW MULTIPTE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
1 1.. Recommendation by contractors/trade allies
L2. Recommended by colleague
13. Recommended by family, friend or neighbor
L4. To improve operations, production, or quality
15. To improve value of property
16. To improve comfort
L7. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EE12. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2. NO ) SKTP TO EE1.4
!ffahc lrigatim Energy Savings Evaruaiion Reuon
A.ppendix C .. Process fivoluati*n lluruey hsir"irmenis
Prnr F^4'1
88. DON'T KNOWNIOT SURE
'
SKIP TO EE1.4
99. REFUSED ' SKIPTO EE14
EE13. What program or sponsor provided assistance?
5. &PACIFICORP ) SKIP TO EE15
6. [RECORD RESPONSE]
88. DON'T KNOWNIOT SURE
99. REFUSED
EE14. \A/hy did you not apply for an incentive from &PACIFICORP for this equipment?
1.. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE15. Since 2009, have you implemented any load control strategies at your facility?
1. YES
2. NO
'
SKIP TO 81.
88. DON'T KNOWNOT SURE ) SKIP TO 81
99.REFUSED ) SKIPTOBl
EE15. \A/hat strategies have you implemented?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EEL7. \A/hat factor or factors motivated you to make these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
L1. Recommendation by contractors/trade allies
12. Recommended by colleague
13. Recommended by family, friend or neighbor
14.To improve operations, production, or quality
15. To improve value of property
16. To improve comfort
17. Other [SPECIFY]:
88. DON'T KNOWNOT SURE
99. REFUSED
EE18. Did you receive assistance from &PACIFICORP or another organization?
idah.; lrrigaticn Eneigy $3v1pgs fvaiuaiion ReioI
Apnsrndix C - Process fivalualion $uruey lnstiirmenis
Rocky Mountain Power
Exhibit No. 5 Page 1361 of 1365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
Fags i^43
Rocky Mountain Powdr
Exhibit No. 5 Page I 362 of 1365
Case No. PAC-Ej4-07
Wtness: Kathryn C. Hymas
1. YES
2. NO )SKIPTOEE2O
88. DON'T KNOWNOT SURE ) SKIP TO EE2O
99.REFUSED ) SKIPTO EE2O
EE19. What program or sponsor provided assistance?
1. &PACIFICORP ) SKIP TO 81
2. [RECORD RESPONSE]
88. DON'TKNOWA{OTSURE
99. REFUSED
EE20. Why did you not apply for an incentive from &PACIFICORP for these load control
improvements?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
IIF V2=2] EE21. When constructing this facility, did you install any high efficiency equipment?
1. YES
2. NO ) SKIP TO 81
88. DON'T KNOWNOT SURE ) SKIP TO B1.
99.REFUSED ) SKIPTOBl
E822. \A/hat high efficiency equipment did you install? (PROBE FOR AS MUCH DETAIL AS
POSSTBLE)
2. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE23. How many did you purchase or install?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE24. What factor or factors motivated you to make these changes? [DO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSESI
1. To save money on electric bills.
2. To obtain an incentive.
3. To replace old or poorly working equipment.
4. To replace broken equipment.
5. To acquire the latest technology.
6. To reduce maintenance costs.
7. Because the program was sponsored by &PACIFICORP
8. Previous experience with &PACIFICORP
9. To protect the environment.
10. To save energy
Ll.. Recommendation by contractors/trade allies
12. Recommended by colleague
Fag* E-43
idahu lrigaticn Eneqy Savings Evaiuaiion R*rori
Ai:pendix C -. Frocess Evaiuaticn .\ul",iey inst'u,tenis
Rocky Mountain Power
Exhibit No. 5 Page 1 363 of 1 365
Case No. PAC-E-14-07
\Mtness: Kathryn C. Hymas
13. Recommended by family, friend or neighbor
14. To improve operations, productiory or quality
15. To improve value of property
16. To improve comfort
17. Other ISPECIFY]:
88. DON'T KNOWAJOT SURE
99. REFUSED
EE25. Did you receive assistance from &PACIFICORP or another organization?
1. YES
2. NO )SKIPTOEEZT
88. DON'T KNOWNOT SURE + SKIP TO EE27
99. REFUSED ) SKIPTOEE2T
EE26. What program or sponsor provided assistance?
7. &PACIFICORP ) SKIP TO 81
8. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
EE27.Why did you not apply for an incentive from &PACIFICORP for this equipment?
1. [RECORD RESPONSE]
88. DON'T KNOWNOT SURE
99. REFUSED
t Barriers
B1. Do you think there are other changes that you could make to improve electric efficiency at &FIRM?
1. YES
2. NO ) SKIP TO FBl
88. DON'T KNOryNOT SURE ) SKIP TO FB1
99. REFUSED ) SKIP TO FBI.
B2. Could you provide some examples of what changes you think you could make?
1. [RECORD RESPONSEI
88. DON'T KNOWNOT SURE
99. REFUSED
83. Are plans in place to make any of those changes?
1. YES
2. NO ) SKIP TO 85
88. DON'T KNOWNOT SURE ) SKIP TO 85
99. REFUSED ' SKIP TO 85
84. Are incentives from &PACIFICORP or another organization part of those plans?
1. YES
2. NO
88. DON'T KNOWNOT SURE
idan0 h"rigetion Ensqv Savings Evaiuaiion Resort
Appendix C .. Proc*ss fivaiualjcn $uruey lnstiu,tenis
Snr* tr-d.d
Roclry Mountiain Power
Exhibit No. 5 Page 1 364 of 1 365
Case No. PAC-E-1447
Wtness: Kathryn C. Hymas
99. REFUSED
85. What factors could prevent &FIRM from making these changes? IDO NOT READ RESPONSES;
ALLOW MULTIPLE RESPONSES]
8. HIGH UPFRONT COSTS
9. LACKOF ACCESSTO CAPITAL
10. LONG PAYBACKPERIOD; SLOWRATE OF RETURN
11. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
12. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
13. LACK OF RESPONSIBLE/ACCOUNTABLE ENERGY STAFF
14. OTHER (SPECIFY
-)
88. DON'T KNOWNOT SURE
99. REFUSED
IIF MORE THAN ONE RESPONSE TO B5l 85. \A/hich of these do you think is the most challenging
factor?
8. HIGH UPFRONT COSTS
9. LACKOF ACCESSTO CAPITAL
10. LONG PAYBACK PERIOD; SLOW RATE OF RETURN
11. LOW PRIORITY/LACK OF INTEREST OF SENIOR MANAGEMENT IN ENERGY
EFFICIENCY
12. LACK OF INFORMATION ABOUT SAVINGS AND PERFORMANCE
13. LACK OF RESPONSELE/ACCOUNTABLE ENERGY STAFF
14. OTHER (SPECTFY
88. DON'T KNOWNIOT SURE
99. REFUSED
Firmographics
FBl. Now I have a few final, general questions about your company for comparison purposes only.
Could you describe your company's primary activities? (DO NOT READ LIST, CODE AND CONFIRIM
WITH RESPONDENT)
1. MANUFACruRING
2. RETAIL
3. DAIRY/AGRICULTURAL
4. FINANCE AND INSURANCE
5. FOOD PROCESSING
6. REFRIGERATED WAREHOUSE
7. PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES
8. EDUCATIONAL SERVICES
9. HEALTH CARE
10. PUBLIC ADMINISTRATION
11. ARTS, ENTERTAINMENT, AND RECREATION
12. ACCOMMODATION
13. FOOD SERVICES
14. REAL ESTATE
15. MINING
ldahc lrigaticn Energy $avinqs Evaiuaiion Rsrrit
A,ppenrJix C .. Process fivaiuatisn ]ur*ey lrisii^umenis
Oenc F-rLi
Roclry Mountain Po rer
Exhibit No. 5 Page 1365 of 1 365
Case No. PAC-E-14-07
Wtness: Kathryn C. Hymas
16. OIL AND GAS
].7. OTHER ISPECIFYI
88. DON'T KNOWT{OT SURE
99. REFUSED
FB2. Approximately, what percent of your total annual operating costs does your electricity bill
represent? (IF NEEDED: An estimate is fine.)
1. [RECORD RESPONSE]
88. DON'T KNOWI{OT STIRE
99. REFUSED
FB3. And about how many people does your firm employ at this facility?
1. [RECORD RESPONSE]
88. DON'T KNOWAIOT SURE
99. REFUSED
End
END1. Those are all of the questions that I have for you. Is there anything about your experiences with
&PACIFICORP you'd like to mention that we did not talk about today?
1. IRECORD RESPONSE]
88. DON'T KNOWAIOT SURE
99. REFUSED
[THANK RESPONDENT AND TERMINATE SURVEY]
ldahc lrigation Energy $avings Evaiuaiion Recoft
Af;penrJix C - Process Evalual.ion $ur'iey lnsirumenis
Fnns F-dA