20220801Exhibit 1 2020 ID EE ACR FINAL.pdf

2020 Idaho Annual Conservation Report
July 30, 2021
All product and company names contained within this document are either trademarks (TM) or registered (®) trademarks of their respective holders. Use of them does not
imply any affiliation with or endorsement by them. All specifications are subject to change without notice.
All forward-looking statements contained in this document are based on underlying assumptions (many of which are based, in turn, upon further assumptions). These
statements are subject to a variety of risks, uncertainties, and other factors. Most of these factors are beyond our control and may have a significant effect on our
operations, results of operations, financial condition, or cash flows, which could cause actual results to differ materially from those anticipated in our statements.
Such risks, uncertainties, and other factors include, among others, those in our most recent Annual Report on Form 10-K, or Quarterly Report on Form 10-Q, filed with
the Securities and Exchange Commission. Those reports are available on our website at avistacorp.com.
St. Joe River, Idaho
2020 Idaho Annual Conservation Report
TABLE OF CONTENTS
Introduction ........................................................................................................................................................1
Tariff Rider Balances ...............................................................................................................................................2
Idaho Achievements ...............................................................................................................................................2
Program Impacts .................................................................................................................................................3
COVID-19 .....................................................................................................................................................3
COVID-19 Emergency Operating Plan Stages and Response ....................................................................3
Program Modifications during COVID-19 ................................................................................................4
Portfolio Trends ...................................................................................................................................................5
Verified Savings ...................................................................................................................................................8
Expenditures .......................................................................................................................................................9
Evaluation Approach ............................................................................................................................................10
Evaluation Methodology and Activities ..............................................................................................................11
Impact Evaluation Results, Portfolio ...................................................................................................................13
Cost-Effectiveness .................................................................................................................................................13
Commercial/Industrial Sector ...............................................................................................................................14
Overview ......................................................................................................................................................15
Marketing ......................................................................................................................................................16
Business Partner Program ..................................................................................................................................19
Customer Satisfaction .......................................................................................................................................20
Key Findings ...............................................................................................................................................21
Recommendations ......................................................................................................................................22
Impact Evaluation..............................................................................................................................................22
Performance and Savings Goals ..................................................................................................................22
Impact Evaluation Methodology ..................................................................................................................23
Sample Design......................................................................................................................................23
Document Review ................................................................................................................................25
Remote Verification ..............................................................................................................................26
Recommendations ......................................................................................................................................26
Cost-Effectiveness .............................................................................................................................................27
2020 Idaho Annual Conservation Report
Program-by-Program Summaries .......................................................................................................................28
Commercial/Industrial Site-Specific Program ................................................................................................28
Description ...........................................................................................................................................28
Program Activities .................................................................................................................................29
Program Changes .................................................................................................................................29
Customer Satisfaction ...........................................................................................................................30
Impact Evaluation .................................................................................................................................32
Recommendations ................................................................................................................................34
Plans for 2021 ......................................................................................................................................34
Commercial/Industrial Multifamily Natural Gas Market Transformation ........................................................35
Description ...........................................................................................................................................35
Program Activities .................................................................................................................................35
Program Marketing ..............................................................................................................................36
Customer Satisfaction ...........................................................................................................................36
Impact Evaluation .................................................................................................................................37
Recommendations ................................................................................................................................38
Plans for 2021 ......................................................................................................................................38
Commercial/Industrial Prescriptive Lighting Programs ..................................................................................39
Description ...........................................................................................................................................39
Program Activities .................................................................................................................................39
Program Changes .................................................................................................................................42
Program Marketing ..............................................................................................................................44
Impact Evaluation .................................................................................................................................44
Plans for 2021 ......................................................................................................................................45
Commercial/Industrial Prescriptive Non-Lighting Programs ...........................................................................46
Description ...........................................................................................................................................46
Program Activities .................................................................................................................................48
Program Changes .................................................................................................................................49
Program Marketing ..............................................................................................................................49
Customer Satisfaction ...........................................................................................................................50
Impact Evaluation .................................................................................................................................52
Recommendations ................................................................................................................................53
Plans for 2021 ......................................................................................................................................54
Residential Sector .................................................................................................................................................56
Overview ......................................................................................................................................................57
Marketing ......................................................................................................................................................58
Avista Kids ..................................................................................................................................................65
Impact Evaluation..............................................................................................................................................66
Performance and Savings Goals ..................................................................................................................66
Impact Evaluation Methodology ..................................................................................................................67
Document-Based Verification ................................................................................................................69
Survey-Based Verification ......................................................................................................................70
Recommendations ......................................................................................................................................71
2020 Idaho Annual Conservation Report
Cost-Effectiveness .............................................................................................................................................72
Program-by-Program Summaries .......................................................................................................................73
Residential HVAC Program ..........................................................................................................................73
Description ...........................................................................................................................................73
Program Activities .................................................................................................................................74
Impact Evaluation .................................................................................................................................75
Recommendations ................................................................................................................................76
Program Marketing ..............................................................................................................................76
Plans for 2021 ......................................................................................................................................76
Residential Shell Program ............................................................................................................................77
Description ...........................................................................................................................................77
Program Activities .................................................................................................................................78
Impact Evaluation .................................................................................................................................78
Recommendations ................................................................................................................................79
Program Marketing ..............................................................................................................................79
Plans for 2021 ......................................................................................................................................79
Residential Water Heating Program .............................................................................................................80
Description ...........................................................................................................................................80
Program Activities .................................................................................................................................80
Program Changes .................................................................................................................................80
Impact Evaluation .................................................................................................................................81
Recommendations ................................................................................................................................81
Program Marketing ..............................................................................................................................81
Plans for 2021 ......................................................................................................................................82
Residential ENERGY STAR® Homes Program ................................................................................................82
Description ...........................................................................................................................................82
Program Activities .................................................................................................................................83
Impact Evaluation .................................................................................................................................83
Recommendations ................................................................................................................................83
Program Marketing ..............................................................................................................................84
Plans for 2021 ......................................................................................................................................84
Residential Fuel Efficiency Program ..............................................................................................................84
Description ...........................................................................................................................................84
Program Activities .................................................................................................................................85
Program Changes .................................................................................................................................85
Impact Evaluation .................................................................................................................................85
Recommendations ................................................................................................................................85
Program Marketing ..............................................................................................................................85
Plans for 2021 ......................................................................................................................................86
2020 Idaho Annual Conservation Report
Residential Simple Steps, Smart Savings™ Program ......................................................................................86
Description ...........................................................................................................................................86
Program Activities .................................................................................................................................87
Program Changes .................................................................................................................................89
Program Marketing ..............................................................................................................................90
Customer Satisfaction ...........................................................................................................................90
Impact Evaluation .................................................................................................................................91
Plans for 2021 ......................................................................................................................................92
Residential Multifamily Direct Install Program and Supplemental Lighting ....................................................93
Description ...........................................................................................................................................93
Program Activities .................................................................................................................................93
Program Changes .................................................................................................................................93
Program Marketing ..............................................................................................................................94
Customer Satisfaction ...........................................................................................................................94
Impact Evaluation .................................................................................................................................95
Recommendations ................................................................................................................................96
Plans for 2021 ......................................................................................................................................96
Residential Home Energy Audit Pilot Program ..............................................................................................97
Description ...........................................................................................................................................97
Program Activities .................................................................................................................................97
Plans for 2021 ......................................................................................................................................97
Low-Income Sector ...............................................................................................................................................98
Program-by-Program Summaries .......................................................................................................................99
Low-Income Program (Including Community Energy Efficiency Program Projects) .........................................99
Description ...........................................................................................................................................99
Program Activities ...............................................................................................................................100
Program Changes ...............................................................................................................................101
Customer Outreach ............................................................................................................................101
Program Marketing ............................................................................................................................104
Impact Evaluation ...............................................................................................................................107
Impact Evaluation Methodology ...................................................................................................108
Cost-Effectiveness ..............................................................................................................................109
Plans for 2021 ....................................................................................................................................110
Regional Market Transformation .......................................................................................................................112
Electric Energy Savings Share ...........................................................................................................................113
Natural Gas Energy Savings Share ...................................................................................................................113
Glossary of Terms ................................................................................................................................................114
Appendices and Supplements ............................................................................................................................128
2020 Idaho Annual Conservation Report
LIST OF TABLES
Table 1 – Tariff Rider Activity ......................................................................................................................................2
Table 2 – Avista COVID-19 Emergency Operating Plan Stages .....................................................................................3
Table 3 – Energy Efficiency Savings by Sector – Electric ...............................................................................................8
Table 4 – Energy Efficiency Savings by Sector – Natural Gas ........................................................................................8
Table 5 – Annual Conservation Plan Budget to Actual Expenditures Comparison ........................................................9
Table 6 – Programs with Highest Impact on Expenditure Variance ...............................................................................9
Table 7 – Program Evaluation Activities (Electric Program Evaluation Activities by Cadmus) .......................................11
Table 8 – ADM Impact Evaluation Activities by Program and Sector ..........................................................................11
Table 9 – Program Evaluation Activities (Natural Gas Program Evaluation Activities by Cadmus) ................................11
Table 10 – ADM Impact Evaluation Activities by Program and Sector ........................................................................12
Table 11 – Process Evaluations for Idaho Programs ...................................................................................................12
Table 12 – Electric Portfolio Cost-Effectiveness Results ..............................................................................................13
Table 13 – Natural Gas Portfolio Cost-Effectiveness Results .......................................................................................13
Table 14 – Commercial/Industrial Verified Savings by Program ..................................................................................15
Table 15 – Commercial/Industrial Prescriptive Electric Evaluation Sample ...................................................................24
Table 16 – Commercial/Industrial Site-Specific Electric Evaluation Sample .................................................................25
Table 17 – Commercial/Industrial Prescriptive Natural Gas Evaluation Sample ............................................................25
Table 18 – Commercial/Industrial Site-Specific Natural Gas Evaluation Sample ..........................................................25
Table 19 – Commercial/Industrial Electric Cost-Effectiveness Results ..........................................................................27
Table 20 – Commercial/Industrial Natural Gas Cost-Effectiveness Results ..................................................................27
Table 21 – Commercial/Industrial Site-Specific Program Metrics ................................................................................28
Table 22 – Commercial/Industrial Site-Specific Program Participation Challenges .......................................................31
Table 23 – Commercial/Industrial Site-Specific Electric Impact Findings .....................................................................32
Table 24 – Commercial/Industrial Site-Specific Evaluation Summary of Discrepancies ................................................33
Table 25 – Commercial/Industrial Site-Specific Natural Gas Impact Findings ..............................................................33
Table 26 – Commercial/Industrial Multifamily Natural Gas Market Transformation Program Metrics ..........................35
Table 27 – Commercial/Industrial Fuel Efficiency Impact Findings ..............................................................................37
Table 28 – Commercial/Industrial Prescriptive Lighting Programs Metrics ...................................................................39
Table 29 – Commercial/Industrial Prescriptive Lighting Program Changes ..................................................................42
Table 30 – Commercial/Industrial Prescriptive Electric Impact Findings .......................................................................44
Table 31 – Commercial/Industrial Prescriptive Evaluation Summary of Discrepancies ..................................................45
Table 32 – Commercial/Industrial Prescriptive Non-Lighting Program Metrics ............................................................46
Table 33 – Commercial/Industrial Prescriptive Non-Lighting Program Rebate Changes, Insulation ..............................49
Table 34 – Commercial/Industrial Prescriptive Programs Aspects Working Well ..........................................................51
Table 35 – Commercial/Industrial Prescriptive Programs Improvement Suggestions ...................................................52
Table 36 – Commercial/Industrial Prescriptive Electric Impact Findings (Non-Lighting) ................................................52
Table 37 – Commercial/Industrial Prescriptive Natural Gas Impact Findings ................................................................53
Table 38 – Commercial/Industrial Prescriptive Evaluation Summary of Discrepancies ..................................................53
Table 39 – Residential Savings by Program ................................................................................................................57
Table 40 – Residential Programs Reported Electric Savings ........................................................................................66
Table 41 – Residential Programs Reported Natural Gas Savings .................................................................................67
2020 Idaho Annual Conservation Report
Table 42 – Residential Programs Document-Based Verification Samples and Precision by Program .............................70
Table 43 – Residential Programs Survey-Based Verification Sample and Precision by Program ....................................70
Table 44 – Residential Electric Cost-Effectiveness Results ..........................................................................................72
Table 45 – Residential Natural Gas Cost-Effectiveness Results ...................................................................................72
Table 46 – Residential HVAC Program Metrics ..........................................................................................................73
Table 47 – Residential Shell Program Metrics ............................................................................................................77
Table 48 – Residential Water Heating Program Metrics .............................................................................................80
Table 49 – Residential ENERGY STAR Homes Program Metrics ..................................................................................82
Table 50 – Residential Fuel-Efficiency Metrics ............................................................................................................84
Table 51 – Residential Simple Steps, Smart Savings Program Metrics .........................................................................86
Table 52 – Residential Simple Steps, Smart Savings Program Incentives Changes ......................................................89
Table 53 – Residential Simple Steps, Smart Savings Program Marketing Activities .....................................................90
Table 54 – Residential Simple Steps, Smart Savings Program Phase-Out ....................................................................92
Table 55 – Residential Multifamily Direct Install Program and Supplemental Lighting Program Metrics ......................93
Table 56 – Residential Multifamily Direct Install Programs Electric Impact Findings .....................................................95
Table 57 – Low-Income Program Metrics ..................................................................................................................99
Table 58 – Low-Income Reported Savings ...............................................................................................................100
Table 59 – Low-Income Program Approved Measure List ........................................................................................100
Table 60 – Low-Income Program Qualified Rebate Measure List ..............................................................................101
Table 61 – Low-Income Outreach Event and LED Bulb Distribution Summary ..........................................................103
Table 62 – Low-Income Impact Findings – Electric Savings ......................................................................................107
Table 63 – Low-Income Impact Findings – Natural Gas Savings ...............................................................................108
Table 64 – Low-Income Program Measure Savings .................................................................................................109
Table 65 – Low-Income Electric Cost-Effectiveness Results ......................................................................................109
Table 66 – Low-Income Natural Gas Cost-Effectiveness Results ...............................................................................110
Table 67 – Actual Savings and Associated Costs for Avista Idaho ............................................................................113
2020 Idaho Annual Conservation Report
LIST OF FIGURES
Figure 1 – Electric and Natural Gas Service Areas ........................................................................................................2
Figure 2 – Electric Energy Savings (2019–2020) ..........................................................................................................5
Figure 3 – Natural Gas Energy Savings (2019–2020) ...................................................................................................6
Figure 4 – Electric Savings Portfolio ............................................................................................................................7
Figure 5 – Natural Gas Savings Portfolio .....................................................................................................................7
Figure 6 – Commercial/Industrial HVAC System Changes Q&A in Response to COVID-19 Flyer .................................16
Figure 7 – Commercial/Industrial Building Shutdown Checklist .................................................................................17
Figure 8 – Commercial/Industrial Tips to Save Energy when Shutting Down Commercial Buildings Flyer ....................17
Figure 9 – Commercial/Industrial Preparations for Workforce Re-Entry Checklist .......................................................18
Figure 10 – Commercial/Industrial Support for Small Businesses During the COVID-19 Crisis Flyer ............................18
Figure 11 – Commercial/Industrial Business Partner Program Newsletter ...................................................................20
Figure 12 – Commercial/Industrial Site-Specific Incentive Dollars by Measure ............................................................29
Figure 13 – Commercial/Industrial Respondent Satisfaction with Site-Specific Program Components ........................30
Figure 14 – Commercial/Industrial Site-Specific Program Successes ...........................................................................31
Figure 15 – Commercial/Industrial Important Criteria for Making Energy-Efficiency Improvements ............................32
Figure 16 – Commercial/Industrial Multifamily Natural Gas Incentive Program Flyer ..................................................36
Figure 17 – Commercial/Industrial Prescriptive Lighting Program Savings by Month ..................................................40
Figure 18 – Commercial/Industrial Prescriptive Interior Lighting kWh Savings by Measure .........................................40
Figure 19 – Commercial/Industrial Prescriptive Exterior Lighting kWh Savings by Measure .........................................41
Figure 20 – Commercial/Industrial Prescriptive Incentive Dollars by Measure – Electric ...............................................48
Figure 21 – Commercial/Industrial Prescriptive Incentive Dollars by Measure – Natural Gas........................................48
Figure 22 – Commercial/Industrial Satisfaction with Prescriptive Program Components .............................................50
Figure 23 – Commercial/Industrial Participation Challenges ......................................................................................51
Figure 24 – Residential Rebates Contractor Meeting .................................................................................................58
Figure 25 – Residential “Way to Save” Television Commercials .................................................................................59
Figure 26 – Residential Energy Savings Tips While at Home Flyer ..............................................................................60
Figure 27 – Residential Energy Use and Savings Guide for Residential Customers .....................................................61
Figure 28 – Residential “Way to Save” Digital Ads ....................................................................................................62
Figure 29 – Residential “Way to Save” Social Media .................................................................................................63
Figure 30 – Residential “Smart Winter” Brochure .....................................................................................................64
Figure 31 – Residential Kids Can Save Energy Too Coloring and Activity Book ...........................................................65
Figure 32 – Residential Impact Process......................................................................................................................68
Figure 33 – Equation 2-1 Sample Size for Infinite Sample Size ..................................................................................68
Figure 34 – Equation 2-2 Sample Size for Finite Population Size ...............................................................................68
Figure 35 – Residential HVAC Incentive Dollars by Measure – Electric ........................................................................74
Figure 36 – Residential HVAC Incentive Dollars by Measure – Natural Gas ................................................................74
Figure 37 – Residential Simple Steps, Smart Savings Program – Lighting kWh Savings ...............................................88
Figure 38 – Residential Simple Steps, Smart Savings Program – Showerheads Savings ...............................................88
Figure 39 – Residential Simple Steps, Smart Savings Program – Clothes Washers kWh Savings .................................89
Figure 40 – Residential Multifamily Direct Install Program Flyer .................................................................................94
2020 Idaho Annual Conservation Report
Figure 41 – Low-Income Home Energy Savings Kit Direct Mail ................................................................................103
Figure 42 – Low-Income Home Energy Savings Kit Brochure ...................................................................................104
Figure 43 – Low-Income Energy Bill Assistance Bill Insert ........................................................................................105
Figure 44 – Low-Income Energy Bill Assistance Flyer ...............................................................................................105
Figure 45 – Low-Income Energy Bill Assistance Print Ad ..........................................................................................106
2020 Idaho Annual Conservation Report
LIST OF APPENDICES AND SUPPLEMENTS
Appendix A – 2020 Idaho Electric Impact Evaluation Report – Commercial/Industrial
Appendix B – 2020 Idaho Natural Gas Evaluation Report – Commercial/Industrial
Appendix C – 2020 Idaho Electric Impact Evaluation Report – Residential and Low-Income
Appendix D – 2020 Idaho Natural Gas Evaluation Report – Residential and Low-Income
Appendix E – 2020 Process Evaluation Report
Appendix F – 2020 Expenditures by Program
Appendix G – 2020 Program Activity
Appendix H – 2020 Idaho Cost-Effectiveness Tables 
Appendix I – 2020 UES Measure List
Appendix J – 2020-2021 Evaluation Work Plans
INTRODUCTION
Snake River, Lewiston, Idaho (left) and Clarkston, Washington (right)
2020 Idaho Annual Conservation Report Pg 1
INTRODUCTION
Avista has spent more than four decades developing responsible and cost‐effective energy-efficiency programs. This
2020 Annual Conservation Report provides a synopsis of those efforts for the company’s electric and natural gas
customers in the state of Idaho – efforts that are designed not only to provide a least-cost resource, but also to help
these customers conserve energy, save money, and live more comfortably – and delivers the results of third-party
assessments of Avista’s efficiency program portfolio performance.
Recommendations from these assessments, as well as the application of lessons learned through each program year,
are incorporated into Avista’s annual business planning process to further refine program design and improve their
chances of success.
Customers continued to be the focus of Avista’s Energy-Efficiency Program in 2020, though unanticipated impacts
of COVID-19 caused the company to look for new avenues to reach them while also maintaining social distancing
for the safety of customers, business partners, and employees. While Avista made significant efforts to maintain the
program participation of a typical year, overall conservation achievements were affected by lower participation rates in
2020. Nevertheless, the company modified its outreach efforts, took steps to ensure customers stayed connected, and
continued on its path of keeping power both affordable and reliable – efforts that are discussed in more detail in this
report.
In addition to offering a mix of programs implemented both by the company and by third-party contractors, Avista
funds the regional market transformation effort through the Northwest Energy Efficiency Alliance (NEEA). Reported
electric energy savings, cost-effectiveness, and other related data, however, are specific to local programs unless
otherwise noted.
Note that the electric and natural gas savings conveyed in this report are provided as gross values based on all
program participants.
FIGURE 1 – ELECTRIC AND NATURAL GAS SERVICE AREAS
2020 Idaho Annual Conservation Report Pg 2
TARIFF RIDER BALANCES
At the start of 2020, the Idaho electric and natural gas (aggregate) tariff rider balances were underfunded by $4.3
million, due primarily to the high level of conservation achieved during the 2016-17 program years. During 2020,
$11.7 million in tariff rider revenue was collected to fund energy efficiency, while $8.9 million was expended to
operate energy-efficiency programs. The $2.7 million excess of collections over expenditures contributed to the
decrease in the underfunded balance of the tariff riders, resulting in an underfunded balance of $1.6 million by year
end.
Table 1 illustrates the 2020 tariff rider activity by fuel type.
TABLE 1 – TARIFF RIDER ACTIVITY
Electric Natural Gas Total
Beginning Balance (Underfunded)/Overfunded $ (4,375,287)$ 78,073 $ (4,297,214)
Energy-efficiency funding $ 10,273,434 $ 1,382,684 $ 11,656,119
Net funding of operations $ 5,898,147 $ 1,460,757 $ 7,358,905
Energy-efficiency expenditures $ 6,472,333 $ 2,482,258 $ 8,954,591
Ending Balances (Underfunded)/Overfunded $ (574,186)$ (1,021,500)$ (1,595,686)
IDAHO ACHIEVEMENTS
◆Electric Conservation: 16,710,969 kWh from local programs.
◆Natural Gas Conservation: 352,548 therms from local programs.
◆NEEA Conservation: An additional 3,578,000 kWh were achieved through the NEEA program, resulting in
a total of 20,288,969 kWh for Avista’s electric program. Moreover, the natural gas NEEA program achieved
an additional 5,641 therms, resulting in an overall conservation savings of 358,189. Note that the Annual
Conservation Report is intended to provide information on Avista’s local programs; it will therefore refer to
the local achievement of 16,710,969 kWh for electric and 352,548 therms for natural gas.
2020 Idaho Annual Conservation Report Pg 3
Program Impacts
COVID-19
COVID-19 created multiple and far-reaching impacts to Avista’s customers. While the Energy-Efficiency Program saw a
decline in participation, the impact was much more profound within the communities served. Many small businesses
suffered financial losses, with more than 100 in the company’s service territory closing permanently. Many people lost
their jobs. Avista adapted its Energy-Efficiency Program to provide needed support to help customers through this
unprecedented event.
COVID-19 Emergency Operating Plan Stages and Response
Early in 2020, Avista operated at the “Monitoring and Precautions” stage of its Emergency Operating Plan (EOP), with
additional precautions put in place to protect the safety of employees and customers. At the beginning of March, the
company had moved into the “Preventative” stage, which increased restrictions and limited customer interactions.
By the middle of the month, Avista had skipped the “Responsive” stage and moved to “Critical,” which places the
highest restrictions on meetings, public interactions, travel, and customer-related work. In addition, all non-essential
employees moved to a work-from-home model.
Table 2 illustrates the four stages of the COVID-19 EOP.
TABLE 2 – AVISTA COVID-19 EMERGENCY OPERATING PLAN STAGES
Stage Monitoring and
Precautions Preventative Responsive Critical
Description A regional health or safety
threat exists with potential
impact to Avista operations
and/or employees. Avista is
monitoring and preparing to
take necessary actions.
Regional organizations and/
or public health officials
begin recommending
preventative actions. Avista
is mitigating risks to ensure
it can continue to provide
essential services to its
customers.
Either the threat has
affected employees or
service territory directly or an
impact is clearly imminent.
Avista is actively responding
to protect employees,
customers, and essential
services.
The threat to essential
services is severe. Avista
is taking critical measures
to protect employees and
essential services.
Public interactions Precautions Additional precautions Limited Critical only
Meetings Normal Large postponed, virtual
encouraged
Virtual only Virtual only
Travel Discretionary/limit high-risk Limit non-essential Essential only Emergency only
DSM staff desk
work
Remote work voluntary Remote work recommended Remote work mandatory Remote work mandatory
DSM customer
site work
Call ahead to check with
customer.
Ask permission to work on
customer site. Go to campus
only for instruments.
Ask customer for essential
work only. Plan trips to
Avista campus for supplies
to avoid others. Meet with
two or fewer people at the
customer site and maintain
social distance.
Request through account
executive that customer
send information necessary
for projects. No trips to
Avista campus or customer
without permission from
manager.
2020 Idaho Annual Conservation Report Pg 4
Program Modifications during COVID-19
Installation Verification: Avista temporarily modified its approach to installation verification. For projects normally
requiring on-site verification, the company allowed customers to submit photographs of installations. For some
projects, photo submissions were supplemented with live video chats, enabling Avista to virtually walk through the
facility and verify equipment installation. This approach met Avista’s verification standard while maintaining safe
working conditions for employees and customers.
Multifamily Direct Install Pilot: The Multifamily Direct Install (MFDI) program has historically been a high-touch
approach to reducing customer energy use. The program uses a direct-installation process for LED lighting, faucet
aerators, low-flow showerheads, and other low-cost energy-saving measures. In March, Avista’s EOP response
restricted staff and contractors from any work done in close proximity with customers; the program was therefore
put on hold for the remainder of the year. In its place, the company worked with its implementer to develop a pilot
process in which customers could drop off their old equipment, pick up energy-efficient items, and install them. This
pilot is discussed in more detail later in the report.
Account Executives: Avista’s account executive (AE) team is responsible for maintaining working relationships with
commercial/industrial customers. COVID-19 presented challenges for the AE team, because Avista’s EOP “Critical”
phase significantly limited face-to-face meetings; many business customers had similar restrictions. The impact of
these restrictions was significant, because customers regularly report that direct contact and communication with
Avista representatives is often their preferred channel to learn about incentives. Impacts ranged from customers
closing operations for months, operating under reduced hours and workforce, or closing businesses permanently.
Some businesses, however, experienced increased demand for products and services. Avista’s commercial/industrial
project pipeline became unpredictable as customers re-evaluated funding and scheduling for energy-efficiency
projects. In response, the AE team pursued every opportunity to continue to engage with customers while adhering
to the restrictions. The team’s new Business Concierge program pivoted to pandemic response in the spring of 2020,
helping connect business customers to critical resources related to COVID-19.
Customer Outreach: Energy fairs and outreach events were canceled, leaving a significant hole in Avista’s ability to
connect with the communities it serves. The company developed outreach kits that contained low-cost, energy-saving
items, and partnered with Meals on Wheels to help distribute them. The kits included window plastic, LED lamps,
nightlights, energy-saving tips, and information on assistance programs.
2020 Idaho Annual Conservation Report Pg 5
Portfolio Trends
As shown in Figure 2, Avista’s energy savings in 2020 were lower than in 2019 (16,710,969 kWh vs. 25,230,990
kWh). The reduction, seen in both residential and commercial/industrial programs, is mainly attributed to COVID-19
and the discontinuation of the Simple Steps, Smart Savings program. Savings acquired through the company’s
residential program decreased 34 percent between 2019 and 2020, while commercial/industrial programs decreased
33 percent.
FIGURE 2 – ELECTRIC ENERGY SAVINGS (2019–2020)
Customer Segment 2019 2020
Residential (inclusive of low-income programs)8,487,490 5,497,847
Commercial/Industrial 16,743,500 11,213,122
Total 25,230,990 16,710,969
El
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y

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v
i
n
g
s

(
k
W
h
)
Residential Commercial/Industrial Total
30,000,000
2019 2020
25,000,000
15,000,000
10,000,000
5,000,000
0
20,000,000
25,230,990
16,710,969
2020 Idaho Annual Conservation Report Pg 6
As shown in Figure 3, Avista’s natural gas portfolio had an increase in savings in 2020 compared to the prior year.
Residential programs experienced a savings increase while the commercial/industrial programs saw a modest decrease.
Savings acquired through the company’s residential programs increased from 183,691 therms in 2019 to 323,044 in
2020, or 176 percent. Much of the change is attributed to a higher participation rate for residential HVAC programs,
which include Avista’s highest participation measures. Savings acquired through the company’s commercial/industrial
programs decreased 11 percent from 33,271 therms in 2019 to 29,503 in 2020. Overall natural gas portfolio savings
increased by 63 percent.
FIGURE 3 – NATURAL GAS ENERGY SAVINGS (2019–2020)
Customer Segment 2019 2020
Residential (inclusive of low-income programs) 183,691 323,044
Commercial/Industrial 33,271 29,503
Total 216,962 352,548
Na
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G
a
s

S
a
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g
s

(
t
h
e
r
m
s
)
Residential Commercial/Industrial Total
400,000
2019 2020
300,000
200,000
100,000
50,000
0
216,962
352,548
350,000
250,000
150,000
2020 Idaho Annual Conservation Report Pg 7
Of Avista’s overall electric portfolio in 2020, the commercial/industrial prescriptive lighting and site-specific programs
obtained 64 percent of the savings. All other programs combined achieved the remaining 36 percent (see Figure 4).
FIGURE 4 – ELECTRIC SAVINGS PORTFOLIO
Of Avista’s overall natural gas savings portfolio, residential HVAC programs obtained 76 percent of the savings in
2020. The residential water heater, shell, and commercial/industrial programs combined achieved 24 percent of the
overall savings for 2020. (see Figure 5).
FIGURE 5 – NATURAL GAS SAVINGS PORTFOLIO
1% Low-Income
27% Residential
4% Multifamily Direct Install
25% Site-Specic
39% Commercial/Industrial Lighting
3% Multifamily Market Transformation
1% Commercial/Industrial other
2% Low-Income
14% Residential Other
76% Residential HVAC
0% Site-Specic
8% Commercial/Industrial
2020 Idaho Annual Conservation Report Pg 8
Verified Savings
Avista’s targets are set through the Integrated Resource Plan (IRP) process. Targets for 2020 were 15,387 MWh and
421,270 therms.
For the 2020 electric target, Avista chose to use the Conservation Potential Assessment (CPA) obtained from its
2017 electric IRP as the basis for its Annual Conservation Plan (ACP) savings goals and targets. The company’s 2020
conservation acquisition target identified in its IRP was 15,387 MWh of qualifying energy efficiency in Idaho.
The 2020 natural gas target of 421,270 therms was identified in the 2018 natural gas IRP and was used to establish
the targets for each program in the natural gas portfolio.
In 2020, the electric energy-efficiency portfolio achieved first-year annual energy savings of 16,711 MWh and natural
gas savings of 352,548 therms. Based on the target established in the electric and natural gas IRPs, Avista achieved
109 percent of the electric savings target and 84 percent of the natural gas savings target. Table 3 shows 2020
savings by fuel and sector.
The Idaho electric portfolio achieved an overall 89 percent realization rate.
TABLE 3 – ENERGY EFFICIENCY SAVINGS BY SECTOR – ELECTRIC
Sector Reported Savings
(kWh)
Evaluated Savings
(kWh)Realization Rate
Commercial/Industrial 13,194,720 11,213,122 85%
Residential 5,428,913 5,282,547 97%
Low-Income 195,603 215,300 110%
Total 18,819,236 16,710,969 89%
The Idaho natural gas portfolio achieved an overall realization rate of 119 percent as shown in Table 4.
TABLE 4 – ENERGY EFFICIENCY SAVINGS BY SECTOR – NATURAL GAS
Sector Reported Savings
(therms)
Gross Evaluated
Savings (therms)Realization Rate
Commercial/Industrial 29,315 29,503 101%
Residential 263,167 317,550 121%
Low-Income 5,009 5,495 110%
Total 297,491 352,548 119%
2020 Idaho Annual Conservation Report Pg 9
Expenditures
The 2020 Annual Conservation Plan provided an expectation for operational planning, with Avista pursuing all
cost-effective measures under Tariff Schedules 90 and 190. Since customer incentives are the largest component of
expenditures, customer demand can easily affect the funding level of the tariff riders. Table 5 provides a detailed
comparison of budgeted to actual energy-efficiency expenditures by fuel type.
TABLE 5 – ANNUAL CONSERVATION PLAN BUDGET TO ACTUAL EXPENDITURES COMPARISON
Electric Natural Gas
Projected 2020 Expenditures
Incentives budget $ 4,605,923 $ 2,278,095
Non-incentives and labor $ 1,828,069 $ 261,606
Market transformation, CPA, EM&V $ 1,279,500 $ 133,500
Total Budgeted Expenditures $ 7,713,492 $ 2,673,201
Actual 2020 Expenditures
Incentives $ 3,625,202 $ 2,005,738
Non-incentives and labor $ 2,049,757 $ 297,365
Market transformation, CPA, EM&V $ 797,374 $ 179,155
Total Actual Expenditures $ 6,472,333 $ 2,482,258
Variance $ (1,241,159)$ (190,943)
Table 6 illustrates the top five programs with the highest impact on the expenditure variance.
TABLE 6 – PROGRAMS WITH HIGHEST IMPACT ON EXPENDITURE VARIANCE
Program Planned Actual Variance Variance Percentage
Site-Specific $ 1,682,774 $ 922,158 $ 760,616 45%
Residential Conversions $ 962,370 $ 340,785 $ 621,585 65%
Low-Income (electric)$ 246,592 $ 637,629 $ (391,038)(159)%
Commercial/Industrial Lighting Exterior $ 647,545 $ 962,080 $ (314,535)(49)%
Residential Prescriptive (natural gas)$ 1,737,762 $ 1,426,403 $ 311,359 18%
2020 Idaho Annual Conservation Report Pg 10
EVALUATION APPROACH
Because evaluation is a critical component of any successful energy conservation program, Avista employs Evaluation,
Measurement and Verification (EM&V) protocols to validate and report verified energy savings related to its energy-
efficiency measures and programs. Those protocols represent the comprehensive analyses and assessments necessary
to supply useful information to both management and stakeholders. (EM&V includes impact and process, and,
taken as a whole, are analogous with industry standard terms such as portfolio evaluation or program evaluation.)
Avista also incorporates recommendations to improve program performance, enact changes to programs, and make
decisions to phase out programs and measures.
Program evaluations are generally conducted by third-party EM&V firms, selected on a biennial basis through a
competitive bidding process managed by Avista’s supply chain management group. Scope of work for selected
evaluators is defined and managed by the company’s planning and analytics team. Third-party evaluators provide
recommendations pertaining to specific programs and related processes in impact and process evaluation report
outputs; Avista tracks those recommendations and uses them as inputs for the annual business planning process.
For 2020, Avista retained two separate firms to conduct impact and process evaluations of electric and natural
gas programs in the utility’s Idaho program portfolio. Cadmus conducted impact evaluations of the commercial/
industrial program portfolio and process evaluations for most programs in the program portfolio; ADM performed
impact evaluations of residential and low-income programs. Evaluations took a portfolio-wide evaluation approach
to provide a benchmark to compare against future years. Impact and process evaluations for most programs were
also completed at the program level, so that customer experience could be better delineated and realization rates
understood.
Several guiding EM&V documents are maintained and published to support planning and reporting requirements.
These include the Avista EM&V framework, an annual EM&V plan, and EM&V contributions within other DSM and
Avista corporate publications. Program-specific EM&V plans are created to inform and benefit the DSM activities.
These documents are reviewed and updated as necessary to improve the processes and protocols for energy-efficiency
measurement, evaluation, and verification.
EM&V efforts are also used to evaluate emerging technologies and applications in consideration of their inclusion
in Avista’s energy-efficiency portfolio. In its electric portfolio, Avista may spend up to 10 percent of its conservation
budget on programs whose savings impacts have not yet been measured if the overall conservation portfolio passes
the applicable cost-effectiveness test. These programs may include educational, behavioral change, and other
investigatory projects. Specific activities can include product and application document reviews, development of
formal evaluation plans, field studies, data collection, statistical analysis, and solicitation of user feedback.
Both Avista and its customers benefit from activities and resources related to energy efficiency and conservation. To
contribute to regional efforts, one Avista employee has a voting role and a second a corresponding member role
on the Regional Technical Forum (RTF) – the advisory committee to the Northwest Power and Conservation Council
and a primary source of information regarding the standardization of energy savings and measurement processes
for electric applications in the Pacific Northwest. This knowledge base provides Avista with energy efficiency data,
metrics, non-energy benefits, and references for inclusion in the company’s Technical Reference Manual (TRM) relating
to acquisition planning and reporting. Avista also works with other northwest utilities and NEEA in a number of pilot
projects and subcommittee evaluations; portions of the energy-efficiency savings acquired through the latter’s regional
programs are attributable to Avista’s portfolio.
2020 Idaho Annual Conservation Report Pg 11
Evaluation Methodology and Activities
The 2020 Idaho electric portfolio impact evaluation took advantage of a variety of methodology approaches. Cadmus
evaluated commercial, industrial, and multifamily programs using the following evaluation methods:
TABLE 7 – PROGRAM EVALUATION ACTIVITIES (ELECTRIC PROGRAM EVALUATION ACTIVITIES BY CADMUS)
Sector Program Document/Database
Review
Verification/Metering
Site Visits
Commercial/Industrial
Prescriptive (multiple)✔✔
Site-Specific ✔✔
Multifamily
Multifamily Direct Install ✔--
Supplemental Lighting ✔--
Fuel Efficiency Multifamily Market Transformation ✔--
ADM evaluated programs in the residential electric portfolio with the following methods:
TABLE 8 – ADM IMPACT EVALUATION ACTIVITIES BY PROGRAM AND SECTOR
Sector Program Database
Review
Survey
Verification Impact Methodology
Residential
Water Heat ✔✔RTF UES
HVAC ✔✔RTF UES/Billing analysis with
comparison group
Shell ✔RTF UES
Fuel Efficiency ✔✔Avista TRM/Billing analysis with
comparison group
ENERGY STAR Homes ✔RTF UES
Simple Steps, Smart Savings ✔RTF UES
Low-Income Low-Income ✔Avista TRM
More details about sample design for each sector are included later in this report and in Appendices A and C.
Each evaluator also chose a tailored approach for program evaluation in the gas portfolio. Table 9 lays out evaluation
activities by Cadmus.
TABLE 9 – PROGRAM EVALUATION ACTIVITIES (NATURAL GAS PROGRAM EVALUATION ACTIVITIES BY CADMUS)
Sector Program Document/Database
Review
Verification/Virtual
Site Visit
Commercial/Industrial
Prescriptive (multiple)✔✔
Site-Specific ✔✔
Fuel Efficiency Site-Specific (Commercial/Industrial)✔--
2020 Idaho Annual Conservation Report Pg 12
ADM evaluated the following programs in the residential gas portfolio:
TABLE 10 – ADM IMPACT EVALUATION ACTIVITIES BY PROGRAM AND SECTOR
Sector Program Database
Review
Survey
Verification Impact Methodology
Residential
Water Heat ✔✔Avista TRM
HVAC ✔✔Avista TRM/IPMVP Option A
Shell ✔Avista TRM/Billing analysis with
comparison group
Fuel Efficiency ✔✔Avista TRM/Billing analysis with
comparison group
ENERGY STAR Homes ✔Avista TRM
Simple Steps, Smart Savings ✔RTF UES
Low-Income Low-Income ✔Avista TRM
Cadmus was also contracted in 2020 to conduct process evaluation activities. The process evaluation focused on three
fundamental objectives:
◆Assess participant and market actor program journeys, including motivation for participation, barriers to
participation, and satisfaction.
◆Assess Avista and implementer staff experiences, including organizational structure, communication, and
program processes.
◆Document areas of success, challenges, and changes to the program.
Table 11 outlines the process evaluation activities that were completed in Idaho in 2020:
TABLE 11 – 2020 PROCESS EVALUATIONS FOR IDAHO PROGRAMS
Program
Commercial/Industrial Programs
Site-Specific
Prescriptive a
Multifamily Programs
Multifamily Direct Install
Multifamily Market Transformation
Residential
ENERGY STAR Homes
Simple Steps, Smart Savings
a) Includes Lighting, Food Service Equipment, Green Motors Rewind, Commercial HVAC, Insulation, HVAC Motor Controls, Grocer, Fleet Heat, and AirGuardian
Compressed Air.
Residential HVAC, Water Heat, and Shell/Window programs in Idaho will be evaluated following the 2021 program
year.
2020 Idaho Annual Conservation Report Pg 13
Process evaluation findings are included in this report for each sector and, where relevant, at the program level under
“Customer Satisfaction” headings.
Impact Evaluation Results, Portfolio
As a result of the impact evaluation performed, the following realization rates were achieved in the Idaho program
portfolio:
◆Electric: 89 percent realization rate and 16,710,969 kWh in annual verified savings.
◆Natural Gas: 119 percent realization rate and 352,548 therms in annual gross savings.
The evaluators collected Avista’s reported savings through database extracts from its customer care and billing
(residential) and Infor CRM and iEnergy (commercial/industrial) databases, and from data provided by third-party
implementers to determine evaluated savings.
COST-EFFECTIVENESS
Before implementing any new program, Avista conducts analyses to determine whether that program is cost-effective
both from the company’s and from customers’ perspectives. Avista uses four metrics to evaluate cost-effectiveness:
the Utility Cost Test (UCT), the Total Resource Cost (TRC), the Participant Cost Test (PCT), and the Ratepayer Impact
Test (RIM). For Idaho programs, the UCT is the most important. Avista’s cost-effectiveness goal for both the electric
and natural gas program portfolios is to have a UCT above 1.00, which indicates that the benefits to the utility exceed
the costs of implementing the program. In 2020, the UCT benefit/cost ratios were 2.09 for electric and 1.64 for
natural gas.
TABLE 12 – ELECTRIC PORTFOLIO COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 12,280,877 $ 5,886,868 2.09
Total Resource Cost (TRC)$ 13,576,343 $ 9,852,524 1.38
Participant Cost Test (PCT)$ 19,406,684 $ 7,712,680 2.52
Ratepayer Impact (RIM)$ 12,280,877 $ 25,099,813 0.49
TABLE 13 – NATURAL GAS PORTFOLIO COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 3,751,762 $ 2,285,360 1.64
Total Resource Cost (TRC)$ 4,220,253 $ 4,475,939 0.94
Participant Cost Test (PCT)$ 5,638,507 $ 4,196,316 1.34
Ratepayer Impact (RIM)$ 3,751,762 $ 12,999,595 0.29
COMMERCIAL/INDUSTRIAL SECTOR
University of Idaho, Moscow, Idaho
2020 Idaho Annual Conservation Report Pg 15
COMMERCIAL/INDUSTRIAL SECTOR
Overview
The commercial/industrial energy-efficiency market is served through a combination of prescriptive and site-specific
programs. Any savings measure not offered through the Prescriptive program – and/or that does not meet its
parameters – is automatically eligible for treatment through the Site-Specific program, subject to the criteria for
participation in that program.
The Prescriptive program path is selected for simple, straightforward equipment installations that generally have
similar operating characteristics (such as lighting, simple HVAC systems, food service equipment, and variable
frequency drives).
The Site-Specific program path is reserved for more unique or complex projects that require custom savings
calculations and technical assistance from Avista’s energy engineers (such as compressed air, process equipment and
controls, and comprehensive lighting retrofits). In certain instances, a performance basis approach is used.
◆1,020 commercial/industrial electric measures in 2020: Total savings of 11,213 MWh.
◆65 commercial/industrial natural gas measures in 2020: Total savings of 29,503 therms in 2020.
TABLE 14 – COMMERCIAL/INDUSTRIAL VERIFIED SAVINGS BY PROGRAM
Commercial/Industrial Program Type Electric Savings
(kWh)
Natural Gas Savings
(Therms)
Exterior Lighting
Prescriptive
2,552,295 -
Food Services 13,761 13,597
Green Motors 52,038 -
Grocer 45,938 -
Interior Lighting 3,944,956 -
Shell 1,341 1,821
HVAC - 13,992
SS Multifamily Market Transformation
Site-Specific
489,597 -
C&I Process 7,575 -
Compressed Air 32,412 -
Other 683,552 -
Shell Windows 4,916 94
Exterior Lighting 571,249 -
Interior Lighting 2,813,492 -
Total Commercial/Industrial 11,213,122 kWh 29,503 therms

2020 Idaho Annual Conservation Report Pg 16
Marketing
To assist commercial customers during the coronavirus pandemic, Avista developed communications materials that
included tip sheets – e.g. “HVAC System Changes Q&A” – plus checklists for saving energy when shutting buildings
down and when re-entering. To support small businesses, a flyer was created identifying sources of local, state, and
federal help available in Idaho. Electronic newsletters containing information on Avista’s energy-efficiency programs
and related content were also sent to commercial and small business customers. Vendors were mailed updates about
program information. New email templates were created for Avista’s account executives, providing a customizable
tool that could be used to promote various rebate programs to their customers.
Ongoing updates to Avista’s website regarding energy-efficiency programs, as well as COVID-19 information,
continued throughout the year.
FIGURE 6 – COMMERCIAL/INDUSTRIAL HVAC SYSTEM CHANGES Q&A IN RESPONSE TO COVID-19 FLYER
HVAC System Changes Q&A
in Response to COVID-19
What is the required percentage of outside air supply (OSA) according
to code?
Minimum OSA rates are based on type of usage and square footage; however,
outside air rates are not limited to 10% above design airflow. As COVID-19 is
a special case, facility operators could choose to take emergency measures for
the safety of staff.
If you choose to increase outside air rates, we recommend that you ensure
the equipment and building are operating properly. All equipment should be
operating within their respective design envelopes, and building pressure is to
be maintained by an equal amount of exhaust/relief air leaving the building.
Special pressurization and operating conditions also must be maintained for
labs, hospitals, restrooms, workspaces, etc.
Will increasing the flow of outside air improve the air quality in office
settings?
Yes, increasing the OSA rate will improve air quality, and we would encourage
increased outside air flow if possible. Air flow should only be increased to the
level that the HVAC equipment is rated. Increasing outside air flow beyond
the equipment limits can cause insufficient building heating/cooling, as well as
damage to HVAC equipment and possibly the building. Outside temperatures
can also dip below freezing, so you need to guard against the possibility of
freeze damage from cold outside air.
Fan speeds should not be increased above rated speeds or fan bearings may
be damaged. We do not recommend adjusting individual room diffusers, since
that could cause balance issues in the overall building. Building pressure should
be maintained by an equal amount of exhaust/relief air exiting the building.
What would be the impact to our utility costs if we set the outside
air-flow at 100%?
Utility costs would increase based on additional fan use and natural gas
usage to heat OSA to room temperature. Based on an average outside air
temperature of 40°F, we estimate natural gas use could double.
Please use this information
to answer customer questions regarding HVAC systems changes to reduce
viral possibilities. We give
special thanks to Coffman Engineers for their
expertise in this matter.
HVAC System Changes Q&A in Response to COVID-19
What recommendations do you have to ease concerns of staff about supply air?
The supply and ventilation air rates of commercial HVAC systems are designed to mitigate the
transmission of cold and flu viruses, but there is no way to completely eliminate the risk. Air humidity
plays a large role in stopping the transmission of bacteria and viruses through the air.
As shown in the graph above, there is a sweet spot around 55-60% humidity that reduces viruses and
respiratory infections while still keeping other agents, such as fungi, in check. We encourage increasing
building humidification or having employees keep a humidifier in their work area.
Avista recommends following the CDC guidelines for businesses:
cdc.gov/coronavirus/2019-ncov/community/guidance-business-response.html
Should we install a special HEPA filter on RTUs/AHUs?
Increased filtering on the return/supply air can improve air quality and safety (more filtering on
the outside air will not help). High efficiency filters, like HEPA filters, would increase the pressure
drop in air ducting which could impede air flow. Poor airflow could defeat the purpose of
providing fresh ventilation and could also damage natural gas heating elements in the
HVAC equipment. We recommend that you improve filtering if possible but follow
the equipment manufacturers’ filter guidelines.
Bacteria
Viruses
Fungi
Mites
Respiratory Infections
Allergic Rhinitis & Asthma
Chemical Interactions
Ozone Productions
Too Dry Healthy Zone Too Moist
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OPTIMUM RELATIVE HUMIDITY RANGE FOR HUMAN COMFORT AND HEALTH(A decrease in bar height indicates a decrease in effect for each of the items.)
2020 Idaho Annual Conservation Report Pg 17
FIGURE 7 – COMMERCIAL/INDUSTRIAL BUILDING SHUTDOWN CHECKLIST
FIGURE 8 – COMMERCIAL/INDUSTRIAL TIPS TO SAVE ENERGY WHEN SHUTTING DOWN COMMERCIAL BUILDINGS FLYER
Building Shutdown
Checklist
GENERAL BEST PRACTICES
Review this checklist one week prior to shutdown to ensure all arrangements are made to complete a successful shutdown of
each building.
Check that all windows and doors to the outside are closed and
locked.
Cooling Season: Lower and close all blinds to prevent solar heat gain.
Heating Season: Open blinds to allow for warming (unless this
creates a security issue).*
Make a quick walkthrough of your building at the end of the last day of operation to see how you’re doing and identify any potential problems. Listen/feel for any
equipment that is running.
Consolidate building activities during shutdown period and
instruct occupants on set-back procedures.
*This is at the building owner’s discretion (providing safety allows).
WATER
Check all drinking fountains, faucets, showers and toilets for
water leaks.
Turn off any automatic flushing systems.
Check water meters to verify there
is not use (movement of the meter) due to water leaks.
Turn off all water heaters that will not be needed.
If possible, turn off or unplug
drinking fountains containing individual refrigeration units.
LIGHTING
Check that timers are working and set correctly for exterior lights that will be in operation during the break.
Turn off all display-case lighting.
Wherever possible, turn off all
interior lights except exit/security lighting.
Where lighting controls exist, adjust scheduling to be in accordance
with new operation schedules.
HVAC
Heating Season: Set temperatures
to 45-50 degrees in all parts of the building.
Cooling Season: Set temperatures
to 80-85 degrees in all parts of the building or just shut off AC system.
Ensure that all HVAC equipment is set to “auto,” not “on.” If
individual rooms have working HVAC controls, check each room.
Adjust your HVAC timers according
to required schedules; review building automation system to
ensure that schedules are updated for unoccupied period.
Ensure that nothing is stacked on supplies or returns.
Turn off all automatic and manual
exhaust fans.
Review the need for building ventilation and shut down all unnecessary ventilation fans.

ELECTRICITY
Check to make sure that all unnecessary electrical appliances are turned off and unplugged. This includes copiers, computers,
printers, televisions, fax machines, radios, water coolers, sound
systems and task lighting.*
For schools, check that all electrical appliances in the teachers’ lounge are turned off and unplugged.
Unplug vending machines (be sure
to inform the vendor).
Check computer rooms. Turn off and unplug computers, monitors,
speakers, projectors and printers.
Turn off intercom and conference room systems.
KITCHENS & WORKSHOPS
Confirm that all kitchen equipment, both gas and electric, is turned off.
Consolidate items from multiple
refrigerators into one and clean out, open and unplug others.*
Milk coolers not in use should be
turned off.*
Turn off electric water heaters at
circuit box.
Turn off any hot water boosters for kitchen dishwashers.
Turn off domestic hot water circulating pumps, if feasible.
Check to see that all compressors
used in facilities or other shops are turned off.
*Send e-mail to appropriate staff
requesting they take these steps prior to leaving.
Save energy when shutting
down commercial buildings
Leaving Lights On
If you are concerned about security,
it’s smart to leave at least one light
on to deter burglars (or to put a few
lights on an automatic timer). If you
do leave any lights on, just make
sure they are all LEDs, which use the
least amount of energy. Businesses
with a security fence should turn off
all their lighting. Just make sure to
close and lock your fence.
Unplug Energy-Nabbing Devices
Few people realize it, but electronics
and appliances use energy even
when they are off. These “parasitic
load” devices include printers,
scanners, personal entertainment
systems, personal computers and
other at-the-ready equipment that
may be located throughout your
offices. Unplugging these devices
before you leave will save energy
while you’re temporarily away.
Curtains and Blinds
Save on heating and cooling by
making sure all the windows of your
building are closed and locked and
that curtains and blinds are shut. This
helps heat from coming in during
the summer and prevents heat loss
in the winter.
Refrigeration
A refrigerator can use up to $80 a
year in electricity—even if it’s not
opened. To save energy, empty the
contents of all refrigerators, unplug
them, and open the doors (block
them so they stay open). The same
goes for any miniature refrigerators
as well, and be sure to turn off lights
in walk-in refrigerators. Also check
to see if you have other types of
refrigeration systems that can be
shut off. You’ll save money by pulling
the plug on water coolers not being
used, as well. If your business uses
air compressors, shut them all off if
there is not work occurring in the
building. Although air compressors
may not sound as if they’re running,
they will come on every time there
is a slight drop in pressure. Last but
not least, as you turn devices off,
put sticky notes on them to remind
people that they should be off (and
as a reminder for you to turn them
back on when you return).
HVAC Systems
If you must shorten the occupancy
hours of your building, also
shorten the operating time of
your HVAC system and automated
lighting systems by changing the
programming in your EMS system,
programmable thermostats, or
manual thermostats. If your building
will be unoccupied for several
weeks, consider lowering your
HVAC heating set point to 45°F.
This will create a noticeable drop in
HVAC usage and should not pose a
problem to the building, as long as
you monitor for extended periods of
freezing temperatures.
Water Heater
Save electricity or natural gas by
turning down your water heater
when you leave. A water heater
consumes 25% of its energy to keep
the tank of water warm—even if
hot water is not being used. When
lowering the water temperature,
set it above 115°F or below 75°F
to prevent the growth of Legionella
bacteria, which can cause illness.
If you think you’ll be away for an
extended period, shut off your water
heater completely. Make sure your
circulation pumps are off, as well.
Save energy when
leaving a building unoccupied. Just follow these simple energy-saving
tips from Avista. The larger your facility, the more you can save.
2020 Idaho Annual Conservation Report Pg 18
FIGURE 9 – COMMERCIAL/INDUSTRIAL PREPARATIONS FOR WORKFORCE RE-ENTRY CHECKLIST
FIGURE 10 – COMMERCIAL/INDUSTRIAL SUPPORT FOR SMALL BUSINESSES DURING THE COVID-19 CRISIS FLYER
Preparations for
Workforce Re-Entry
GENERAL BEST PRACTICES
Begin completing these checklist
tasks a week early for a successful reopening.
Restart larger or hastily closed buildings earlier as they take more time to recommission.
Send emails to educate building occupants about restarting
procedures.
Restart systems and equipment backward from shutdown order to avoid damage.
Complete a complete facility
inspection a day before reopening.
ELECTRICITY AND GAS
Check all circuit breakers/fuses to
ensure they are not tripped/blown.
Ensure natural gas valves are open and that fittings do not leak.
Plug in all office equipment, such as copiers, computers, printers, sound systems, task lighting, breakroom appliances, etc.
Turn on intercom and conference
room systems.
Inspect and plug in refrigerated water fountains and water coolers.
Plug in vending machines (be sure to inform the vendor).
Ensure all gas appliances have relit
pilot lights and are operational.
Test the building security system.
LIGHTING
Check all lighting controls and
adjust settings to new operational schedules.
Ensure exit and security lights are working.
Turn on all display-case lighting.
WATER
Flush water through all lines, especially drinking and potable
sources, before use.
Make sure all water fountain, faucet, toilet and shower valves are
open and do not leak.
Turn on all automatic flushing systems.
Turn on water heaters and set temperatures at or above 120° F
to meet safety requirements.
Ensure hot-water recirculating pumps are turned on and operational.
Turn on any hot water boosters for
kitchen dishwashers.
Ensure facility and shop compressors are turned on.
HEATING & AC/REFRIGERATION
Inspect ductwork for holes/leaks
as well as rodent or other animal nests.
Replace dirty filters with higher-efficiency filters that are sealed properly.
Ensure required vents are open.
Turn on all necessary ventilation fans.
Test economizers to ensure they are not stuck open or closed.
Ensure all HVAC equipment and
timers, including programmable thermostats, are operating
properly. (Remember to check rooms with individual HVAC
controls.)
Gradually adjust temperature
settings to suit occupancy levels (adjust a few degrees each day
over a week).
Maximize the introduction of outside air (per CDC guidelines)
to dilute airborne contaminants/viruses while maintaining indoor comfort.
Aim for 40-60% relative humidity,
which is considered ideal for containing the virus.
Apply additional ASHRAE
measures, including those for high-risk situations, found at ashrae.org/technical-resources/commercial
Check equipment refrigerant levels to ensure there are no leaks. (Turn
on milk coolers, if applicable.)
TRAFFIC EFFORT/SIGNAGE
Place signs on all entrance doors reminding occupants not to enter
if they have COVID-19 symptoms. Encourage personal health
monitoring for employees as well.
Suggest (or require) face masks for all occupants, visitors and maintenance personnel as part of entrance-sign messaging.
Install signs listing CDC guidelines for COVID-19 in breakrooms
and other highly used rooms.See “Print Resources” at cdc.
gov/coronavirus/2019-ncov/communication
Install signs that encourage safe physical distancing and respiratory
etiquette (cover sneezes) in high-traffic and confined areas.
Install signs that urge 20-second
handwashing in common areas and restrooms.
Consider 6-foot physical-distance markings on floors.
POINTS OF CONTACT/TOUCH
Limit elevator capacity where possible.
Provide open access to stairwells
where security requirements allow.
Prop open interior doors that do not pose a security or safety risk in order to provide hands-free traffic.
Remove some tables and seating
in breakrooms/conference areas for added physical distancing, and
keep disinfectant wipes nearby to clean tables, handles and other
equipment after each use.
Consider staggering employee breaks so fewer people are in breakroom areas at the same time.
Consider installing automated
faucets, soap dispensers and towel dispensers in bathrooms.
Consider installing ultraviolet disinfection lighting to create sterile environments.
JANITORIAL/MAINTENANCE
Focus on cleaning and disinfecting high-touch surfaces using EPA-
recommended products which eliminate SARS-CoV-2, the virus
that causes COVID-19.
Install stations with alcohol-based (70%) hand sanitizer in common areas with high-touch surfaces such as elevator buttons and door handles.
Supply additional soap and paper
towels in breakrooms.
Frequently clean and disinfect breakroom refrigerator, microwave, coffee station, etc.
Close blinds during cooling season
to prevent solar heat gain. Open blinds during heating season to do
the opposite.
Perform building inspections/non-urgent repairs when rooms and offices are least crowded. Instruct nearby staff to wear masks when appropriate.
Support for small businesses
during the COVID-19 crisis
Small businesses are the backbone of our country. It’s why Avista is dedicated to supporting you in these challenging times. We want to empower small business owners like you by providing advice and services to help, including:
• Making payment arrangements
• Applying security deposits to existing account balances (if applicable)
• Providing references to existing resources in Idaho and the federal
programs available from the $2 Trillion Coronavirus Aid, Relief, and Economic Security Act, (CARES Act)
Let our dedicated support team help with your business.
Please call 509-495-4717 or 800-936-6629
(Monday thru Friday, 7:00 a.m. to 5:00 p.m.) or email [e-mail]
(See additional information on back)
COVID-19 Small Business Resources for Idaho
U.S. Senate Committee on Small Business
& Entrepreneurship:
A small business owner’s guide to the CARES Act.
sbc.senate.gov/public/index.cfm/guide-to-the-cares-act
home.treasury.gov/policy-issues/cares/ assistance-for-small-businesses
SBA COVID-19 Small Business
Guidance & Loan Resources:Long-term, low-interest SBA loans due to COVID-19
for eligible small business owners.
sba.gov/page/coronavirus-covid-19-small- business-guidance-loan-resources
SBA Economic Injury Disaster Loan Program:
Working-capital loans of up to $2 million to help
small businesses overcome temporary revenue loss.
disasterloan.sba.gov/ela
Paycheck Protection Program (PPP)
information Sheet – Borrowers:
Borrowers information fact sheet.
home.treasury.gov/system/files/136/PPP--Fact-Sheet.pdf
Coronavirus Emergency Loans Guide
and Checklist for Small Businesses:
uschamberfoundation.org/reports/coronavirus- emergency-loans-guide-and-checklist-small-businesses -and-nonprofits
Business & Industry Loan Guarantees
Offers loan guarantees to rural businesses.
rd.usda.gov/programs-services/business-industry- loan-guarantees
Avista’s COVID-19 Response and Resources:Energy-saving tips for closing buildings, suggested
HVAC system changes, FAQs and more.
myavista.com/safety/covid-19-response
Innovia Foundation:
Two COVID-19 Response and Recovery Funds for
community-based organizations working at the
frontlines of the outbreak in Eastern Washington and North Idaho.
innovia.org/covid19
Joint Business Service Providers
cdaedc.org/covid19
Idaho Small Business Development Center:COVID-19 resources for North Idaho.
idahosbdc.org/covid-19-resources
Idaho Community Foundation Response and Recovery Fund for Idaho, which will
provide grants to trusted organizations that support
and serve low-income Idahoans.
idahocf.org/covid-19
United Way of North Idaho
Coeur d’Alene Coronavirus Relief Fund
unitedwayofnorthidaho.org/coronavirus-relief-fund
Where to find business relief assistance due to COVID-19
Avista is committed to a strong future for small businesses. Below are some sources of local, state and federal help that may be available to your small business.
Federal Resources
Idaho Resources
©️ 2020 AVISTA CORPORATION. ALL RIGHTS RESERVED.
2020 Idaho Annual Conservation Report Pg 19
Business Partner Program
The Business Partner Program (BPP) began in fall 2019 as an outreach effort designed to target small business
customers in Avista’s rural service territories. Initiated with an introductory letter followed by a site visit, it was
updated in March 2020 to a mail campaign due to the COVID-19 pandemic. The BPP brings awareness of Avista’s
services to rural small business customers in Idaho and Washington, and includes information on energy audits,
budget billing plans, energy-efficiency rebates, and, most recently, information about COVID-19.
By the end of 2020, the BPP had reached 1,926 small businesses in 15 Idaho rural service territories. Outreach
communication included mail, email, phone calls, and some initial site visits. Seven audits were performed, and 53
incandescent lamps were replaced with LEDs for a savings of 6,464 kWh.
In April of 2020, Avista introduced a Trade Ally Bid program, in which the company arranges for various vendors (e.g.
lighting, HVAC, window, and insulation) to provide cost estimates to customers for energy-efficiency upgrades to their
facilities. This service also helps to educate and empower business owners and their employees to use less energy.
Avista has collaborated with trade ally partners to help customers identify energy conservation projects by performing
audits, walking through the efficiency incentive process, and helping customers obtain bids for projects. The Trade Ally
Bid program has enabled Avista to reach small business customers who may not have the time, budget, or access to
contractors to make efficiency improvements. By the end of 2020, the program provided cost estimates to eight small
business customers in Idaho.
In response to the pandemic, Avista also pivoted its Business Concierge program to focus on COVID-19 resources.
Avista customer service representatives contacted more than 2,600 business customers by phone to share
information on resources available during the shutdown, including efficiency assistance, flexible repayment options,
and information on Avista’s shutoff suspension policy. This program helped connect business customers to critical
resources, and also helped inform the company’s ongoing response to the COVID-19 pandemic.
2020 Idaho Annual Conservation Report Pg 20
The outreach forecast for 2021 includes communication with 43 Idaho communities reaching 3,554 small business
customers.
FIGURE 11 – COMMERCIAL/INDUSTRIAL BUSINESS PARTNER PROGRAM NEWSLETTER
Customer Satisfaction
Cadmus conducted process evaluations of the Site-Specific and Prescriptive programs for the 2020 program year.
The methodology consisted of interviews with program staff at Avista as well as online surveys with trade allies and
program participants.
Interviews with Avista program staff focused on the following program topics:
◆Program roles and responsibilities
◆Program goals and objectives
◆Program design and implementation
◆Data tracking
◆Program participation
◆Marketing and outreach
◆Program successes
◆Market barriers
◆Program impact on the market
◆Future program changes including redesign
Business Partner Program
Avista’s COVID-19 Response
To learn more please visit: myavista.com/safety/covid-19-response
COVID-19 Programs and Assistance for Small Business:
Innovia Foundation – COVID-19 Community Response and Recovery Funds
Local philanthropic, government and business partners have joined to create two COVID-19 Response and Recovery Funds, both of which will be rapidly deployed to community-based organizations working at
the frontlines of the COVID-19 outbreak in Eastern Washington and North Idaho. Funds are intended to
complement the work of public health officials, medical providers, businesses and governments and expand
their capacity of to more effectively address the regional outbreak. For details, visit: innovia.org/covid19
SBA – COVID-19 Small Business Guidance & Loan Resources
Small business owners in all U.S. states, Washington D.C. and U.S. territories are eligible to apply for a long-term, low-interest loan from The Small Business Association (SBA) due to COVID-19. The SBA will work directly
with state governors to target this vital economic support toward small businesses and non-profits severely
impacted by the virus.
Visit: sba.gov/page/coronavirus-covid-19-small-business-guidance-loan-resources
SBA – Economic Injury Disaster Loan Program The Economic Injury Disaster Loan program provides working-capital loans of up to $2 million to help small
businesses overcome temporary revenue loss. For details, visit:
Disaster Loan Assistance Application: disasterloan.sba.gov/ela
Access to local assistance: disasterloan.sba.gov/ela
Avista’s new Business Partner Program is an outreach effort aimed at rural small-
business customers in Washington and Idaho to create awareness of utility programs
and services related to the recent spread of COVID-19. The situation has caused all of
us to make changes in how we operate our business.
Here is what you should know:
Best of success,
Lorri Kirstein – Program Manager
Avista’s Business Partner Program [e-mail]
2020 Idaho Annual Conservation Report Pg 21
Cadmus completed 81 online surveys in 2020 with commercial/industrial program participants in Idaho and
Washington. Cadmus relied on site visits and telephone reminder calls to increase survey participation. The participant
survey guides gathered critical insights into participants’ program journey, covering the following topics:
◆Program awareness
◆How respondents learned about the program
◆General program participation
◆Reasons for participation
◆Program benefits
◆Program delivery experience
◆Overall program satisfaction
◆Satisfaction with Avista
◆Current energy-efficient behaviors and purchases
◆Suggestions for program improvements
Key Findings
The impact of COVID-19 on project scope was minimal, but there may be slight reductions in the number
or scope of energy-efficiency projects due to budget or staff constraints. Ten of 13 Site-Specific respondents
and 88 percent of Prescriptive participants (n=59) said COVID-19 did not create any obstacles to their 2020 project;
most respondents who reported obstacles said the obstacles were minor. Four of 13 Site-Specific respondents and
24 percent of Prescriptive respondents expected reductions to budget or staff availability to support energy-efficiency
upgrades in 2021.
Although contractors drive a significant portion of participation, continued Avista outreach and messaging
is important to support contractor sales. Eight of 15 Site-Specific participants and 70 percent of Prescriptive
participants (n=63) reported first hearing about the Avista program from a contractor, vendor, or retailer. Twelve
of 15 Site-Specific participants and 55 percent of Prescriptive participants (n=64) thought the best way to learn
about rebates and incentives was through Avista emails or direct mail, or communication from an Avista account
representative.
Despite some process issues in 2020, participants are satisfied with the application process and the
program overall. Site-Specific satisfaction was lowest for process-related aspects, including submitting the rebate
application (75 percent satisfied, n=15) and the time to process the application (87 percent satisfied), but 100 percent
of respondents were satisfied with the program overall. Though 14 percent of Prescriptive participants mentioned the
application paperwork was burdensome, and 9 percent had some difficulty understanding requirements, 100 percent
of participants were satisfied with the program overall, and several respondents mentioned the easy and fast process
as an aspect of the program that worked well. Suggestions for process improvements were related to potential
enhancements (such as a searchable database of eligible products, or chat feature for application support) rather than
suggestions to correct significant problems.
2020 Idaho Annual Conservation Report Pg 22
Recommendations
Cadmus offered the following recommendations to improve customer satisfaction for Avista’s commercial/industrial
programs:
◆Develop tools to help participants sort through options and scope eligible projects more quickly.
For example, although the Avista website currently directs customers to search for eligible lighting on the
ENERGY STAR Product Finder database or Design Lights Consortium websites, both of which have advanced
search functionality, the search results can be overwhelming. A resource such as an “Energy Efficiency Buying
Guide” for specific products could help customers with less technical background navigate their options or
evaluate and understand proposals they receive from contractors.
◆If not already doing so, use email blasts, bill inserts, and other promotional tools that are direct
from Avista to its customers, and use Avista branding to promote commercial/industrial programs
and incentives. Participants were more likely to want communication directly from Avista than through
their contractor or vendor. These marketing efforts will enhance any contractor and vendor marketing or
advertising and give sales representatives better credibility, enabling them to make more sales through the
program.
Program-specific customer satisfaction recommendations, as well as Avista’s plans to improve this customer
experience, are described in more detail in the program-by-program summaries (see pages 28-54).
Impact Evaluation
Although some individual project results varied, particularly within the Prescriptive exterior lighting program,
the overall commercial/industrial sector performed strongly in 2020 relative to reported savings. Most projects
that Cadmus sampled for the evaluation were well-documented and matched findings from the remote project
verifications. Savings realization rates were as follows:
◆Electric: Total verified savings of 10,723.5 MWh (excludes fuel conversions) in 2020 with a realization rate of
85 percent.
◆Natural Gas: Total verified savings of 29,503 therms with a combined realization rate of 101 percent.
Performance and Savings Goals
The commercial/industrial sector did not meet the combined Prescriptive and Site-Specific program paths’ electric
goal of 15,020 MWh, with the programs achieving 71 percent of the overall goal. For natural gas programs, the
commercial/industrial sector also fell short of the annual therm savings goal for combined Prescriptive and Site-Specific
programs, achieving 29,503 therms (36 percent of the combined Prescriptive and Site-Specific program paths’ natural
gas savings goal of 82,680 therms).
2020 Idaho Annual Conservation Report Pg 23
Impact Evaluation Methodology
As the first step in evaluating electric and natural gas savings for the commercial/industrial sector, Cadmus explored
the following documents and data records to gain an understanding of the programs and measures slated for
evaluation:
◆Avista’s annual business plans, detailing processes and energy savings justifications
◆Project documents from external sources (such as customers, program consultants, or implementation
contractors)
◆Avista’s iEnergy tracking system
Based on the initial review, Cadmus checked the distribution of program contributions with the overall program
portfolio. The review provided insight into the sources for unit energy savings (UES) claimed for each measure offered
in the programs, along with sources for energy-savings algorithms, internal quality assurance, and quality control
processes for large commercial/industrial sector projects.
Following this review, Cadmus designed a sample strategy for impact evaluation activities and performed the
following evaluation activities in two waves:
◆Selected evaluation sample and requested project documentation from Avista
◆Reviewed project documentation
◆Prepared virtual site-visit measurement & verification (M&V) plans
◆Performed virtual site visits using the Streem platform and collected on-site data (such as trend data, photos,
and operating schedules)1
◆Used virtual site-visit findings to calculate evaluated savings by measure
◆Applied realization rates to the total reported savings population to determine overall evaluated savings
Sample Design
Cadmus created two sample waves for 2020. Sample 1 included program data from January through June; sample
2 included program data from July through December. As a guideline, Cadmus used the proposed overall 2019
commercial/industrial sample sizes by subprogram in the measurement and verification plan, seeking to complete
approximately half of the sample in each wave.
Cadmus initially estimated the total annual population size by reviewing the wave 1 population data and comparing
it to 2018-19 population data. Cadmus developed initial sample size targets to achieve 90 percent confidence at ±10
percent precision (90/10) for the estimated annual population for 2020, with a target of 90/20 by program. After
receiving the wave 2 population data, Cadmus revised the annual sample size targets for the full year and selected the
wave 2 sample to complete the revised target within each program.
Avista advised Cadmus not to evaluate certain programs with low participation and historically consistent realization
rates every year. Since the Green Motors program has shown a 100 percent realization rate in every prior evaluation,
Cadmus did not evaluate the program in 2020, and does not plan to evaluate it in 2021. Cadmus plans to evaluate
the Food Services program only in 2020, and the Energy Smart Grocer and Prescriptive Shell programs only in 2021.
1) For more information on Streem: https://www.streem.com/platform-streem#platform-remote-video
2020 Idaho Annual Conservation Report Pg 24
Cadmus evaluated all other commercial/industrial programs that had participation in 2020.
For each activity wave, Cadmus developed a stratified random sample of applications by program (such as Site-
Specific other, Site-Specific lighting, Prescriptive interior lighting, or Prescriptive motor controls). In programs where
individual projects represented a significant portion of the total savings in the program, the team selected the highest-
savings applications with certainty. Within programs with a wide variance in savings, the team further stratified
non-certainty applications by reported savings magnitude into small and medium strata, each with approximately 50
percent of the total non-certainty program savings. The team assigned random numbers within each stratum to select
a random sample of non-certainty sites. In some cases, Cadmus selected additional applications at the same location
as a previously selected application to evaluate as a convenience selection if the team could assess both applications in
a single virtual visit.
Cadmus encountered some challenges contacting customers to evaluate the wave 1 sample, primarily due to changes
in business operations as a result of the COVID-19 pandemic. The team pulled an additional backup sample for the
wave 2 sample using random sampling, and recruited participants from the backup sample when participants from
the initial random sample were unreachable.
The team pooled results from the randomly selected sites to calculate a realization rate by stratum and applied that
realization rate to projects in the population in that stratum. Cadmus applied the project-specific evaluated savings for
every project that was in the sample, regardless of whether it was a random, certainty, or convenience selection.
Table 15 summarizes the Idaho commercial/industrial Prescriptive program path evaluation sample. Cadmus sampled
41 Prescriptive applications at 32 unique sites. Of the sampled applications, the team selected five for certainty review
based on the scale of savings, selected the 29 randomly, and selected seven additional convenience projects based on
location. There was no participation in the AirGuardian, Fleet Heat, and Motor Control programs in 2020.
TABLE 15 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE ELECTRIC EVALUATION SAMPLE
Program Type Applications
Sampled a
Sampled Savings
(kWh)
Percentage of
Reported Savings
Interior Lighting 19 1,589,327 42%
Exterior Lighting 22 947,468 20%
Shell Measure 0 0 N/A
Green Motors 0 0 N/A
Food Service Equipment 2 13,761 100%
AirGuardian 0 0 N/A
Energy Smart Grocer 1 3,060 7%
Commercial/Industrial Prescriptive 41 2,553,616 29%
a) Three applications included measures in the interior lighting and exterior lighting programs, but each measure is only counted once in the total.
2020 Idaho Annual Conservation Report Pg 25
Table 16 summarizes the Site-Specific program path’s evaluation sample, where Cadmus sampled 12 Site-Specific
applications at 12 unique sites overall. Of the sampled applications, the team selected three for certainty review based
on the savings scale and selected the remaining nine applications randomly.
TABLE 16 – COMMERCIAL/INDUSTRIAL SITE-SPECIFIC ELECTRIC EVALUATION SAMPLE
Program Path Applications
Sampled
Sampled Savings
(kWh)
Percentage of
Reported Savings
Site-Specific 12 2,366,694 59%
Table 17 summarizes the Idaho Commercial/Industrial Prescriptive program path natural gas evaluation sample.
Overall, Cadmus sampled 14 Prescriptive applications at 14 unique sites, selecting all applications randomly. The team
did not select any applications for certainty review.
TABLE 17 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE NATURAL GAS EVALUATION SAMPLE
Program Type Applications
Sampled
Sampled Savings
(therms)
Percentage of
Reported Savings
HVAC 7 3,553 26%
Shell 0 0 0%
Food Service Equipment 7 4,490 33%
Commercial/Industrial Prescriptive 14 8,043 28%
Note: Totals may not sum due to rounding.
Table 18 summarizes the Idaho Commercial/Industrial Site-Specific program path’s natural gas evaluation sample.
Cadmus sampled one Site-Specific application at one unique site. The team selected the sampled application with
certainty as it was the only gas participant in the Site-Specific program.
TABLE 18 – COMMERCIAL/INDUSTRIAL SITE-SPECIFIC NATURAL GAS EVALUATION SAMPLE
Program Applications
Sampled
Sampled Savings
(therms)
Percentage of
Reported Savings
Site-Specific 1 94 100%
Document Review
Cadmus requested and reviewed project documentation for each sampled application and prepared M&V plans
to guide the site visits. Typically, project documentation included data entered into the iEnergy system, incentive
application forms, calculation workbooks, invoices, equipment specification sheets, and Avista installation verification
(IV) reports.
2020 Idaho Annual Conservation Report Pg 26
Remote Verification
Cadmus performed virtual site visits and verification calls at 36 unique commercial/industrial locations to assess
electric savings for 102 unique Prescriptive and Site-Specific measures (not including fuel efficiency measures) from
44 different applications. To assess natural gas savings, Cadmus performed verifications at 14 unique commercial/
industrial locations in Idaho to assess natural gas energy savings for 17 unique Prescriptive and Site-Specific measures
(not including fuel efficiency measures). Cadmus evaluated the remaining applications through desk reviews that did
not require participant outreach, or through verification calls, which involved a brief discussion by phone or video to
confirm key details and any information that was missing in the project documentation. Cadmus typically conducted
video calls using the Streem platform that records video and audio. The team conducted some verifications using
Microsoft Teams meetings if customers were unable to access Streem or preferred using Teams due to prior familiarity.
Cadmus used the project documentation review and on-site findings to adjust the reported savings calculations where
necessary.
Recommendations
Cadmus offers the following conclusions and recommendations to improve the commercial/industrial sector’s energy
savings:
◆Avista’s new iEnergy system has the capability to automatically calculate more detailed energy savings
estimates since it records additional detailed inputs on some prescriptive measures that were not previously
tracked in Infor CRM. Some of these inputs are not currently used in the savings calculations.
Recommendation: Review deemed savings values for prescriptive measures and consider opportunities
to take advantage of the additional data now collected in iEnergy to calculate more accurate savings
for each participant project. For example, food service measures can use the reported pounds of food
cooked per day and cooking hours per day values collected in iEnergy to automatically calculate more
precise savings.
◆The iEnergy system introduced variance of up to 2 percent between reported and evaluated savings by
rounding intermediate wattage calculation values.
Recommendation: Review iEnergy calculations to ensure that rounding is only applied on final displayed
values and not to any intermediate values.
◆Customer uncertainty on where program equipment was installed created challenges for verifying installed
quantities and may have contributed to reduced realization rates for projects where verified quantities were
less than reported.
Recommendation: Update all application forms to include space for location notes for each installed
measure and encourage contractors installing equipment at very large facilities to include installation
location with equipment invoices.
2020 Idaho Annual Conservation Report Pg 27
◆Variations in the level of detail in Avista IV reports introduced additional complexity in evaluating accurate
measure counts, types, and operating parameters.
Recommendation: Provide more consistent documentation with IV reports. Cadmus recommends that
all IV reports include basic information to explicitly state the quantity and type of equipment found. For
lighting projects, this would include confirmed fixture types, quantities, installation locations, controls,
and estimated HOU. For most other equipment, this would include nameplates, model numbers, and
quantities.
Avista will consider these recommendations and identify new ways to take advantage of iEnergy to improve the
accuracy of calculations. Avista is also planning to overhaul and streamline the installation verification process, which
will result in a standardized template for installation verification reports.
Cost-Effectiveness
Tables 19 and 20 show the commercial/industrial sector cost-effectiveness results by fuel type.
TABLE 19 – COMMERCIAL/INDUSTRIAL ELECTRIC COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 6,434,778 $ 3,207,038 2.01
Total Resource Cost (TRC)$ 7,078,256 $ 5,975,711 1.18
Participant Cost Test (PCT)$ 11,301,365 $ 5,238,461 2.16
Ratepayer Impact (RIM)$ 6,434,778 $ 12,020,967 0.54
TABLE 20 – COMMERCIAL/INDUSTRIAL NATURAL GAS COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 181,083 $ 196,443 0.92
Total Resource Cost (TRC)$ 199,192 $ 370,999 0.54
Participant Cost Test (PCT)$ 219,873 $ 250,818 0.88
Ratepayer Impact (RIM)$ 181,083 $ 340,054 0.53
As noted in Table 20, the UCT benefit to cost ratio for the commercial/industrial sector was 0.92 in 2020. While
Avista always strives to ensure programs are cost-effective, the commercial/industrial natural gas program is very cost-
sensitive due to its low participation rates. As compared to 2019, the 2020 program had a decrease in therm savings
of approximately 4,000, which was enough to move the program from a 1.04 UCT to a 0.92 UCT.
2020 Idaho Annual Conservation Report Pg 28
Program-by-Program Summaries
Commercial/Industrial Site-Specific Program
TABLE 21 – COMMERCIAL/INDUSTRIAL SITE-SPECIFIC PROGRAM METRICS
Site-Specific Program Summary – Electric 2020
Participation, Savings, and Costs
Conservation projects 108
Overall kWh savings 4,113,196
Incentive spend $ 679,152
Non-incentive utility costs $ 243,006
Idaho energy-efficiency rider spend $ 922,158
Site-Specific Program Summary – Natural Gas 2020
Participation, Savings, and Costs
Conservation projects 1
Overall therm savings 94
Incentive spend $ 282
Non-incentive utility costs $ 922
Idaho energy-efficiency rider spend $ 1,204
Description
The commercial/industrial energy-efficiency market is delivered through a combination of prescriptive and site-specific
offerings. Any measure not offered through a Prescriptive program is automatically eligible for treatment through the
Site-Specific program, subject to the criteria for participation in that program. Avista’s account executives work with
commercial/industrial customers to provide assistance in identifying energy-efficiency opportunities. Customers receive
technical assistance in determining potential energy and cost savings as well as identifying and estimating incentives
for participation. Site-specific projects include appliances, compressed air, HVAC, industrial process, motors (non‐
prescriptive), shell, and lighting, with the majority being HVAC, lighting, and shell.
2020 Idaho Annual Conservation Report Pg 29
Program Activities
◆Electric: Savings of 4,113,196 kWh, or 25 percent of the overall electric savings. The largest percentage of
incentives went to interior lighting projects (68 percent) followed by exterior lighting (14 percent).
◆Natural Gas: Savings of 94 therms in 2020, or 1 percent of the overall natural gas savings. All therm savings
in the program came from shell measures.
Incentives by measure are listed in Figure 12.
FIGURE 12 – COMMERCIAL/INDUSTRIAL SITE-SPECIFIC INCENTIVE DOLLARS BY MEASURE
Program Changes
In 2020, Avista did not make any changes to the Site-Specific program. Incentives for any qualifying electric or natural
gas energy-saving improvements with a 15-year simple payback or less continue to be offered.
$ 531,197 Site-Specic Lighting – Interior
$ 100,772 Site-Specic Lighting – Exterior
$ 47,183 all other measures
2020 Idaho Annual Conservation Report Pg 30
Customer Satisfaction
Cadmus evaluated the Site-Specific program in its 2020 Process Evaluation. Figure 13 compares the percentage of
2020 respondents rating themselves very satisfied or somewhat satisfied with different aspects of the Site-Specific
program with responses from 2019. While overall satisfaction is very high, respondents were less likely to be satisfied
with several components in 2020 than in 2019, in particular with the procedure to submit the application and the
time it took to process it. In comments explaining their satisfaction levels, one respondent had difficulty understanding
the paperwork, another experienced delays after their Avista representative retired, and a third reported this was their
first energy-efficiency project, and they were unsure how to proceed.
FIGURE 13 – COMMERCIAL/INDUSTRIAL RESPONDENT SATISFACTION WITH SITE-SPECIFIC PROGRAM COMPONENTS

Source: 2020 and 2019 Site-Specific survey question E1: “In terms of the Site-Specific program, how satisfied were you with the following aspects? Please think
about each item individually as you select your answer.” Showing only respondents that indicated they were very satisfied or somewhat satisfied.
100%
100%
Project contract process
Time it took to process
your application
Submitting the application
Rebate amount
Communication with youraccount executive
The program overall
Percentage of Respondents
10%20%30%40%50%60%70%80%
3
5
0%100%90%
100%
75%
Post-project inspection
The equipment that was installed
Pre-project inspection
Technical assistance receivedfrom Avista staff
Communication with program
contractors/vendors
100%
87%
100%
92%
100%
93%
100%
93%
100%
93%
94%
100%
100%
100%
100%
100%
100%
100%
Satised, 2020 (n=12, Avg)Satised, 2019 (n=18, Avg)
2020 Idaho Annual Conservation Report Pg 31
As shown in Table 22, 10 of 15 2020 respondents reported experiencing program participation challenges. Another
respondent reported having no challenges, while four others did not respond. In 2020, the most common challenge
reported by participants was just learning about the program. Another two respondents reported internal challenges,
related to getting approval to pursue the project and for the up-front capital expense.
TABLE 22 – COMMERCIAL/INDUSTRIAL 2020 PARTICIPATION CHALLENGES
Challenge 2020 (n=10)
Discovering the program 3
Getting internal interest and approval 2
Finding eligible equipment 1
Understanding what equipment is eligible 1
Slow communication from Avista 1
Delay in receiving the rebate check 1
Finding a contractor willing to work with the program 1
Source: Site-Specific survey question E3: “What do you see as the biggest challenges to participating in Avista’s Site-Specific program?”
Despite these issues, 11 respondents identified aspects of the program that they viewed as working well. For example,
one Site-Specific participant said, “It is great that Avista is working with business[es] and residents to reduce the
electrical demand with new tech.” Figure 14 shows the full breakdown of responses.
FIGURE 14 – COMMERCIAL/INDUSTRIAL SITE-SPECIFIC PROGRAM SUCCESSES
Source: Site-Specific survey question E5: “What would you say is working particularly well with Avista’s Site-Specific program?” Multiple responses allowed.
When responding to questions about their motivation to pursue energy-efficiency projects, 12 of 15 respondents said
the rebate provided by Avista was very important in their decision to complete their project. Another two said it was
somewhat important and one said the rebate was not too important in their decision. All respondents said energy
efficiency was very or somewhat important when making capital upgrades or improvements.
Program helps customers save
money and reduce their energy usage
Avista representatives are helpful
Rebate amounts are fair
Smooth and easy process
Number of Respondents
1 2 3 4
1
2
4
4
(n=11)
2020 Idaho Annual Conservation Report Pg 32
As shown in Figure 15, respondents most commonly selected the project’s return on investment and energy or
operating costs as the most important criteria in their decision to complete their project, followed closely by rebate or
outside funding availability. These responses are similar to those from 2019.
FIGURE 15 – COMMERCIAL/INDUSTRIAL IMPORTANT CRITERIA FOR MAKING ENERGY-EFFICIENCY IMPROVEMENTS
Source: Site-Specific survey question F5: “Which of the following criteria are important in deciding whether your company makes energy-efficiency improvements?”
Multiple responses allowed.
Impact Evaluation
Table 23 shows reported and evaluated electric energy savings for Avista’s commercial/industrial Site-Specific program
path for the program year. The overall Site-Specific program path had a 103 percent electric realization rate. The
table does not include reported and evaluated electric savings for measures in the Multifamily Market Transformation
program which, for the purposes of the Cadmus Impact Evaluation Report, were included as a Site-Specific program
(see Site-Specific Multifamily).
TABLE 23 – COMMERCIAL/INDUSTRIAL SITE-SPECIFIC ELECTRIC IMPACT FINDINGS
Program Path Reported Savings
(kWh)
Evaluated Savings
(kWh)Realization Rate
Site-Specific 3,993,803 4,113,196 103%
Maintenance costs
Information from contractor,
vendor, or retailer
Information from Avista
account executive
Directive from senior leadership
Number of Respondents
4 8 12
3
5
6
9
(n=15)
2 6 100 14
12
12
13
13Return on investment (ROI)
Energy or operating costs
Availability of rebates, other
outside co-funding
Initial cost of the equipment
11Payback period
2020 Idaho Annual Conservation Report Pg 33
Of 12 evaluated applications, Cadmus identified discrepancies in six, based on virtual site visits and project
documentation review. Table 24 summarizes the reasons for discrepancies between reported and evaluated savings.
TABLE 24 – COMMERCIAL/INDUSTRIAL SITE-SPECIFIC EVALUATION SUMMARY OF DISCREPANCIES
Project Type Number of
Occurrences Savings Impact Reason(s) for Discrepancy
Interior Lighting 2 
Cadmus found increased savings for one project that added new lighting
controls which had not been accounted for in the reported savings. The
lighting controls reduced the installed fixture wattage by dimming the lights
throughout the space.
Cadmus zeroed out negative savings for one line item – which should not
have been approved – in which the installed wattage was higher than
the existing wattage. This measure did not receive an incentive but was
erroneously included in the reported savings.
Motor Control (VFD)1 
The original analysis for a paper mill wastewater pump variable frequency
drive (VFD) project assumed a constant output voltage based on a single
spot measurement and a 0.95 power factor from the VFD. Cadmus updated
the analysis to estimate the energy use with the VFD with a 0.88 power
factor based on the motor specifications and using the metered output
voltage via the industrial control system trends, which showed the voltage
varied significantly.
Exterior Lighting 1 
Cadmus determined that the HOU for one sign lighting project was higher
than reported through interviews with on-site staff. Unlike the prescriptive
sign lighting projects, this project did not apply a deemed savings value to
determine reported savings.
Compressed Air 1 
Air compressor VFD power data were rounded in the original analysis files.
Cadmus did not round any intermediate numbers, which resulted in slightly
lower evaluated savings.
Refrigeration 1 
Cadmus found that the original analysis included unrelated equipment in
the baseline energy use. The project removed two self-contained freezers
that were not replaced with energy-efficient equipment. Cadmus confirmed
that the two freezers were removed because the site no longer sold frozen
products. Cadmus updated the analysis to exclude unrelated freezer
equipment in the baseline energy use calculation, decreasing baseline
energy use and decreasing savings.
Table 25 shows reported and evaluated natural gas energy savings for Avista’s 2020 commercial/industrial Site-Specific
program path. The overall Site-Specific program path natural gas realization rate was 100 percent. The table does not
include reported and evaluated natural gas penalties for measures in the fuel efficiency path.
TABLE 25 – COMMERCIAL/INDUSTRIAL SITE-SPECIFIC NATURAL GAS IMPACT FINDINGS
Program Reported Savings
(therms)
Evaluated Savings
(therms)Realization Rate
Site-Specific 94 94 100%
2020 Idaho Annual Conservation Report Pg 34
Recommendations
◆The evaluated lighting HOU assumptions for interior and exterior lighting projects did not always align with
reported values.
Recommendation: Review HOU estimates when processing applications and conducting installation
verifications. When entering average weekly HOU, confirm how many weeks per year that schedule
applies. In particular, Avista should apply additional scrutiny to applications claiming 8,760 hours per year.
◆Discrepancies between reported fixture quantities and invoice quantities added complexity and uncertainty in
evaluating the Site-Specific lighting program. It is often impractical for Avista staff conducting IV inspections
or evaluators conducting verification visits to count every fixture for large lighting projects, necessitating a
greater reliance on project documentation.
Recommendation: Include more detailed documentation for Site-Specific lighting projects. Lighting
drawings should be provided whenever possible, and if any other notes, spreadsheets, or other
documentation are used to determine eligible quantities, these should be included with the application
records. Any difference between invoice quantities and rebated quantities should be clearly explained.
◆Avista may rely on spot measurements for values that vary during typical operation. The submitted analysis
for a Site-Specific industrial process motor project assumed a fixed output voltage from the VFD based on
a single spot measurement, but the plant’s industrial control system was capable of recording voltage trend
data. Cadmus worked with the customer to add a voltage trend and determined that the VFD voltage output
actually varied significantly in daily operation.
Recommendation: Assume that amperage and voltage output from a VFD may fluctuate significantly.
Whenever possible, configure trend data collection for both values. If a voltage trend is unavailable,
take multiple spot voltage readings at various VFD speeds or consider installing a temporary power data
logger.
Plans for 2021
Avista plans to continue to offer the Site-Specific program in Idaho for both electric and natural gas customers in
2020. Avista will assess the current measurement and verification process and develop a standardized installation
verification report. Avista will also employ a process change to more closely assess HOU assumptions in lighting
calculations.
2020 Idaho Annual Conservation Report Pg 35
Commercial/Industrial Multifamily Natural Gas Market Transformation
TABLE 26 – COMMERCIAL/INDUSTRIAL MULTIFAMILY NATURAL GAS MARKET TRANSFORMATION PROGRAM METRICS
Multifamily Natural Gas Market Transformation Program Summary 2020
Participation, Savings, and Costs
Conservation projects 4
Overall kWh savings 489,597
Incentive spend $ 444,000
Non-incentive utility costs $ 48,967
Idaho energy-efficiency rider spend $ 492,967
Description
The Site-Specific program path also includes a market transformation initiative intended to encourage natural gas
space and water heating in multifamily residential developments. The focus is on new-construction multifamily
residential rental buildings with five or more units. The goal of the program is to address the split incentive issue
where developers are focused on low development costs, which can drive low-efficiency heating choices and place
a higher cost burden on building tenants. The program intends to create developer confidence in natural gas as a
heating option for multifamily construction, while also helping developers and building owners understand the added
long-term value of natural gas space and water heating systems. Avista offers program incentives of $3,000 per unit
for converting to natural gas by installing standard-efficiency space heat and water heaters.
Program Activities
In 2020, Idaho program performance was consistent with prior years. Four projects with a total of 132 units
were constructed. Savings totaled 489,597 kWh and $492,967 in total tariff rider spend. The multifamily market
transformation program accounted for approximately 20 percent of fuel efficiency savings in 2020.
2020 Idaho Annual Conservation Report Pg 36
Program Marketing
Avista’s account executive team focused on creating relationships with regional builders, including one-on-one
conversations with contractors and developers. The team also engaged in regular informal check-ins to provide
education about offered programs, benefits, savings, and payoffs in installing natural gas – from environmental,
comfort, and cost-saving standpoints.
FIGURE 16 – COMMERCIAL/INDUSTRIAL MULTIFAMILY NATURAL GAS INCENTIVE PROGRAM FLYER
Customer Satisfaction
Overall, the Multifamily Natural Gas Market Transformation (MFMT) program was successful in meeting
the energy savings goal and achieving high program satisfaction.
◆The program surpassed its electric savings goal of 476 MWh per year for 2020.
◆Builders have told Avista staff that they appreciate the incentive because it allows them to install natural gas
appliances which provides a competitive advantage, since they say natural gas appliances are more attractive
and can help increase the value of units.
◆The builder who completed a survey said they were very satisfied with the program and planned to
participate to a greater extent in 2021.
As we continue to look for ways to increase energy efficiency, natural gas has emerged as not only efficient,
but also one of the cleanest energy resources available. And while natural gas can be burned in combustion
turbines to generate electricity, using it directly in homes for heating and cooking is the most efficient use
of this natural resource.
Because direct use is the best use, Avista is offering incentives to assist developers in bringing this
convenient, plentiful, and versatile fuel into multifamily projects. This program is available exclusively
for Avista electric customers.
Eligibility
The Multifamily Natural Gas Incentive Program is available
for new construction in Avista’s electric and natural
gas service territory (five or more units per building).
Participants must sign a contract by December 1, 2020
and complete their projects within two years.
Funding
Avista incentives pay up to $3,000 per unit for installation
of either space heating or hot water – or a combination
of both.*
And once the project has natural gas heat, adding
a natural gas range, dryer, or fireplace is easy and
economical. Plus, installing high-efficiency natural gas
appliances can help make your property more attractive.
*Capped at 100% of the incremental cost to install
natural gas. Program subject to change.
Natural gas too costly to
install? Think again.
For more information or to apply, contact:
Jamie HowardAvista Account Executive208.769.1871
[e-mail]
728 Sherman, Coeur d’Alene
Idaho
2020 Idaho Annual Conservation Report Pg 37
The MFMT program has had success working with HVAC installers to help market the program – though
more can be done to increase marketing efforts and participation.
◆Avista reported success working with HVAC installers to help promote the program. Staff said this is a
beneficial relationship as the HVAC installers are provided with additional work and the program with more
participants.
◆Avista reported that there used to be a flyer handed out as promotional material for the program, though it is
no longer used. Staff also said there is no current way in which they monitor effectiveness of their marketing
efforts and do not cross-promote the MFMT program with other Avista programs.
Impact Evaluation
Cadmus followed the same impact evaluation methodology for fuel-efficiency measures as outlined in the Impact
Evaluation Methodology section on page 23. Two MFMT applications were sampled. Of the sampled applications, the
team selected one for certainty review based on the savings scale and selected one randomly.
TABLE 27 – COMMERCIAL/INDUSTRIAL FUEL EFFICIENCY IMPACT FINDINGS
Fuel Efficiency Measure Reported Savings
(kWh)
Evaluated Savings
(kWh)Realization Rate
Multifamily Market Transformation 528,727 489,597 93%
Total 528,727 489,597 93%
Cadmus identified discrepancies for one high-rise residential tower project that installed a central boiler and chiller
system. Avista used the typical deemed savings values for MFMT HVAC measures. Avista developed these savings
values through an internal engineering study using building simulation modeling. The savings values are based on the
number of apartment units and the rated efficiency of natural gas furnaces replacing electric resistance heaters, and
assume a three-story building with a ground, middle, and top floor.
This building had 16 middle floors of residential units, while the ground and top floors did not have residential units.
Although this project was eligible per the program criteria, the deemed savings values were not designed to account
for this type of installation due to the building layout and because it installed boilers instead of furnaces. Cadmus
adjusted the analysis to use the deemed savings value for middle floor units only and to account for additional energy
consumption required for the boiler circulation pumps. These adjustments reduced energy savings because the
middle-floor units experience less heat loss relative to the ground- and top-floor units, and because pump energy is
not required with gas furnace heating.
2020 Idaho Annual Conservation Report Pg 38
Recommendations
Cadmus offers the following conclusions and recommendations to improve Avista’s MFMT measures:
◆Avista’s deemed savings values for MFMT HVAC measures are intended for natural gas furnaces and do not
accurately estimate savings for central boiler systems because they have additional energy consumption from
pumps, experience heat loss in the piping system between the boiler and the conditioned space, and have
substantially different equipment sizing, heat transfer properties, and fuel consumption.
Recommendation: Only use deemed savings in this program for standard forced air gas furnaces that
directly heat residential spaces. Analyze eligible projects with any other type of equipment using a site-
specific approach, which may require a custom energy model for that particular building.
◆Avista’s deemed savings values for MFMT HVAC measures overestimate savings for buildings with more than
one middle floor, because they assume a three-story building with a ground, middle, and top floor.
Recommendation: Include a place for MFMT HVAC applications to confirm the number of floors in the
building and should apply a weighted average of the deemed savings for ground, middle, and top floors
when a building does not have the standard three-story layout.
Cadmus offers the following process improvement recommendations to improve customer satisfaction:
◆Develop marketing materials which can be used by HVAC contractors to help promote the MFMT program.
Due to the strengthening relationships between program staff and HVAC contractors, promotional materials
could be greatly beneficial to provide information about the program in instances where the contractors may
encounter potential participants.
◆Develop strategies to evaluate the effectiveness of marketing efforts and cross-promotion with other Avista
programs. In order to understand if marketing efforts are successful, evaluation standards or goals should be
set to better understand what the primary forces are that drive participation to the program. Cross-promotion
is also a simple and effective way to increase visibility of the program and garner interest from potential
participants.
Plans for 2021
The program will continue in the Idaho service area. Avista will also assess project documentation for this program
and determine if process improvements need to be made or if incentive levels need to be adjusted. Avista will also
consider an increase in marketing efforts for this program, in alignment with the marketing recommendations offered
by Cadmus.
2020 Idaho Annual Conservation Report Pg 39
Commercial/Industrial Prescriptive Lighting Programs
TABLE 28 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE LIGHTING PROGRAMS METRICS
Prescriptive Lighting Program Summary 2020
Participation, Savings, and Costs
Conservation projects 888
Overall kWh savings 6,497,251
Incentive spend $ 1,207,030
Non-Incentive Utility Costs $ 385,746
Idaho Energy Efficiency Rider spend $ 1,592,776
Description
This program is intended to prompt commercial/industrial electric customers to increase the energy efficiency of their
lighting equipment through direct financial incentives. It indirectly supports the infrastructure and inventory necessary
to ensure that the installation of high-efficiency equipment is a viable option for the customer.
There is opportunity for lighting improvements in commercial facilities – and, to streamline the process and make
it easier for customers and vendors to participate, Avista developed a prescriptive approach in 2004. This program
provides for many common retrofits to receive a predetermined incentive amount, which is calculated using a baseline
average for existing wattages and the average replacement wattages from the previous year’s project data. Claimed
energy savings is calculated based on actual customer run times and qualified product lighting data.
This streamlined approach makes program participation easier, especially for smaller customers and vendors. The
measures included in the prescriptive lighting program include fluorescent lamps and fixtures, HID, MR16, and
incandescent can fixture retrofits to more energy-efficient LED light sources and controls.
Program Activities
Savings for prescriptive lighting were 6,497,251 kWh, or 58 percent of commercial/industrial electric savings, a
substantial increase in savings compared to 2019 and exceeding the goal of 6,078,000 by 7 percent.
As the continued shift toward more prescriptive exterior lighting measures occurred in 2019 and 2020, the four-foot
T12/T8 lamp replacement measure fell second to the sign lighting measure as the most popular measure, which also
achieved the highest kWh savings in 2020.
2020 Idaho Annual Conservation Report Pg 40
As seen in Figure 17, lighting throughput was not affected by COVID-19 in 2020. There was a noticeable shift toward
exterior lighting projects throughout the year, which may have been a result of social distancing measures. However,
apart from June and September, monthly goals were met and annual savings targets were not affected.
FIGURE 17 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE LIGHTING PROGRAM SAVINGS BY MONTH
FIGURE 18 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE INTERIOR LIGHTING KWH SAVINGS BY MEASURE
1,600,000
1,200,000
800,000
400,000
Jan
2019 2020
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Interior Exterior
0
1,400,000
1,000,000
600,000
200,000
Occupancy Sensor Controls
1000W HID Fixture to 400W or less LED Fixture
400W HID Fixture to 175W or less LED Fixture
250W HID Fixture to 140W or less LED Fixture
75-100W Incandescent Can to 12-20W LED Fixture
40-100W Incandescent to 6-20W LED Fixture
2-Lamp T12/T8 Fixture to LED 2x2 Fixture
20-50W MR16 to 2-9W LED MR16
2, 3, 4-Lamp T12/T8 Fixture to LED 2x4 Fixture
T12/T8 Eight-Foot to T8 TLED
T12/T8 Four-Foot to T8 TLED
250,000 500,000 1,000,000 1,500,000
T5HO Lamp to 1-Lamp T5 TLED
T12/T8 U-Bend to T8 TLED
750,000 1,250,000
2020 Idaho Annual Conservation Report Pg 41
FIGURE 19 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE EXTERIOR LIGHTING KWH SAVINGS BY MEASURE
500,000 1,000,000 1,500,000 2,000,000
Sign Lighting (SQ.FT.)
1000W HID Fixture to 400W or less LED
400W HID Fixture to 175W or less LED
320-400W HID Fixture to 160W or less LED
320W HID Fixture to 160W or less LED
250W HID Fixture to 140W or less LED (Ext, NC)
175W HID Fixture to 100W or less LED (Ext, NC)
250W HID Fixture to 140W or less LED
175W HID Fixture to 100W or less LED
150W HID Fixture to 50W or less LED
90-100W HID Fixture to 30W or less LED
70-89W HID Fixture to 25W or less LED
2,500,000
750W HID Fixture to 300W or less LED
2020 Idaho Annual Conservation Report Pg 42
Program Changes
Avista made the following changes to the program in 2020:
TABLE 29 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE LIGHTING PROGRAM CHANGES
2020 Changes to Commercial Exterior Lighting Rebates 2019 2020 Notes
Exterior Lighting
Replacement HID Lighting (Pole, Wallpack, or Cano) – Requires at Least 4,288 Hours of Use per Year – Must Be DLC-Rated
*Eligible only if ballast and all other existing electrical components are removed.
70-89W HID fixture to ≤ 25W LED fixture, retrofit kit, or lamp $ 60 $ 65 Incentive Increase
90-100W HID fixture to ≤ 30W LED fixture, retrofit kit, or lamp $ 80 $ 85 Incentive Increase
150W HID fixture to ≤ 50W LED fixture, retrofit kit, or lamp $ 125 $ 130 Incentive Increase
175W HID fixture to ≤ 100W LED fixture, retrofit kit, or lamp $ 130 $ 130
250W HID fixture to ≤ 140W LED fixture, retrofit kit, or lamp $ 140 $ 160 Incentive Increase
320W HID fixture to ≤ 160W LED fixture, retrofit kit, or lamp $ 180 $ 195 Incentive Increase
400W HID fixture to ≤ 175W LED fixture, retrofit kit, or lamp $ 255 $ 280 Incentive Increase
750W HID fixture to ≤ 300W LED fixture, retrofit kit, or lamp $ 450 $ 490 Incentive Increase
1000W HID fixture to ≤ 400W LED fixture, retrofit kit, or lamp $ 610 $ 610
New Construction Fixtures HID Lighting – Requires at Least 4,288 Hours of Use per Year – Must Be DLC-Rated
175W code HID fixture to ≤ 100W LED fixture $ 130 $ 130
250W code HID fixture to ≤ 140W LED fixture $ 140 $ 160 Incentive Increase
320W code HID fixture to ≤ 160W LED fixture $ 250 $ 195 Incentive Decrease
Sign Lighting Retrofit – Requires at Least 4,288 Hours of Use per Year
T12 to LED sign lighting $ 17/SQFT $ 22/SQFT Incentive Increase
2020 Idaho Annual Conservation Report Pg 43
2020 Changes to Commercial Interior Lighting Rebates 2019 2020 Notes
Interior Lighting
Fluorescent Tubular Lamps – Must Be DLC-Rated
T5HO four-foot TLED $ 15.00 $ 12.50 Incentive Decrease
T8 four-foot TLED $ 6.50 $ 6.50
U-bend LED $ 8.00 $ 10.00 Incentive Increase
T8 eight-foot TLED $ 13.00 $ 11.50 Incentive Decrease
Fluorescent Fixtures – Must Be DLC-Rated
2, 3, or 4-Lamp T12/T8 fixture to LED-qualified 2x4 fixture $ 40.00 $ 28.00 Incentive Decrease
2-Lamp T12/T8 fixture to LED-qualified 2x2 fixture $ 30.00 $ 20.00 Incentive Decrease
HID Lighting – Must Be DLC-Rated
*Eligible only if ballast and all other existing electrical components are removed.
250W HID fixture to ≤ 140W LED fixture or lamp $ 155.00 $ 125.00
Incentive Decrease
Removed Hourly
Requirement
400W HID fixture to ≤ 175W LED fixture or lamp $ 205.00 $ 185.00
Incentive Decrease
Removed Hourly
Requirement
1000W HID fixture to ≤ 400W LED fixture or lamp $ 460.00 $ 270.00
Incentive Decrease
Removed Hourly
Requirement
Incandescent Replacement Lamps
6-20W LED lamp $ 8.00 $ 0.00 Measure Discounted
50-60W LED fixture $ 55.00 $ 0.00 Measure Discounted
MR16 (GU10 Base) – Must Be ENERGY STAR-Rated
2-9W MR16 lamp $ 10.00 $ 5.50 Incentive Decrease
Can Light Kit – Must Be ENERGY STAR-Rated
12-20W LED fixture retrofit $ 20.00 $ 20.00
Controls
Occupancy sensor controls with built-in relays $ 40.00 $ 25.00
Incentive Decrease
(must control at least
170W)
DLC-qualified LLLC fixture Site-Specific $ 35.00
New Measure (must
control at least 300W,
must be DLC qualified)
2020 Idaho Annual Conservation Report Pg 44
Program Marketing
Key to the success of the Prescriptive lighting program is clear communication to lighting supply houses, distributors,
electricians, and customers on incentive requirements and forms. The Avista website is also a channel to communicate
program requirements and highlight opportunities for customers. In addition, the company’s regionally based
account executives are an integral component of delivering the prescriptive lighting program to commercial/
industrial customers. Any changes to the program typically include advance notice of 90 days to submit under the old
requirements and/or incentive levels. This usually includes – at a minimum – direct email communication to trade allies
as well as website updates.
Impact Evaluation
The program had a strong realization rate for interior lighting but a relatively low realization rate for exterior lighting.
This was due primarily to the sign lighting adjustment, which is described in Table 30.
TABLE 30 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE ELECTRIC IMPACT FINDINGS
Program Type Reported Savings
(kWh)
Evaluated Savings
(kWh)Realization Rate
Interior Lighting 3,816,812 3,944,956 103%
Exterior Lighting 4,742,300 2,552,295 54%
Cadmus notified Avista in January 2021 of systematic savings discrepancies in sign lighting measures within the
Prescriptive exterior lighting program. The team observed a significant increase in sign lighting measures in 2020 and
found consistently low realization rates on the sign lighting measures evaluated. Avista applied deemed savings of
107.2 kWh per square foot of signage replaced, based on a 2014 internal engineering review that assumed eight-
foot T12 high-output fluorescent lamps as the baseline for all sign lighting. Cadmus evaluated sign lighting projects
by verifying the quantity, wattages, and HOU for the baseline and installed lamps in each sign by visual confirmation
through video or by reviewing invoices and IV report photos. In cases where documentation was insufficient and
customers were unable to access the sign, Cadmus estimated lamp quantities and lengths based on the shape and
size of the sign. Cadmus calculated savings as the difference in energy use between the actual baseline and installed
lighting equipment it verified. In every case, this evaluation methodology resulted in a lower evaluated savings, and
Cadmus found an average realization rate of 26 percent across the evaluated sign lighting measures. The team did
not find any systematic discrepancies with other exterior lighting measures. The realization rate for non-sign lighting
exterior lighting measures was 96 percent.
2020 Idaho Annual Conservation Report Pg 45
Of 41 evaluated applications, Cadmus identified discrepancies for 36, based on virtual site visits, verification calls, and
project documentation review. Table 31 summarizes the reasons for discrepancies between reported and evaluated
savings.
TABLE 31 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE EVALUATION SUMMARY OF DISCREPANCIES
Project Type Number of
Occurrences Savings Impact Reason(s) for Discrepancy
Interior Lighting
7 
Cadmus found that two projects were inaccurately categorized as interior
lighting projects rather than exterior. Evaluated savings for these projects
were removed from the interior lighting program and added to the exterior.
Cadmus determined that the HOU for four projects was lower than reported
on the applications after interviewing on-site staff.
Cadmus verified that one project had installed fewer LED lamps than
reported. Several linear LED lamps were found in storage and not yet
installed in some fixtures throughout the facility, lowering the evaluated
savings.
5 Cadmus determined that the HOU for five projects was higher than reported
on the applications after interviewing on-site staff.
Exterior Lighting
17 
Cadmus found that the installed fixtures for two projects had a higher
wattage than reported on the application.
Cadmus found one project that was categorized as a new construction
measure but involved removing five existing higher-wattage LED wall pack
fixtures and installing three LED flood lights in their place. Cadmus adjusted
savings to include an estimated baseline wattage for the removed LED wall
packs.
Cadmus evaluated 14 sign lighting projects by calculating the difference in
energy use between the baseline and installed lamps, rather than applying
a deemed value per square footage of the sign. Cadmus determined the
deemed values overestimated savings.
2 
Cadmus found that two projects were inaccurately categorized as interior
lighting projects rather than exterior. Evaluated savings for these projects
were removed from the interior lighting program and added to the exterior.
5 
Cadmus found that some projects had discrepancies due to rounding
differences. iEnergy rounds the kilowatt savings to two decimal places in the
middle of the calculation, causing a loss of accuracy in the final savings. This
correction resulted in a decrease in savings for two projects and an increase
for three.
Plans for 2021
In its third year of having more sophisticated measure level detail in iEnergy, Avista has been able to update interior
and exterior lighting measures annually to reflect market conditions. The company does not anticipate significant
changes to the program in 2021, but will be more flexible in making mid-year changes as needed. Avista has
also been able to use the more refined data from the Site-Specific program to add three new measures into the
prescriptive offerings. The company plans to dive deeper into networked lighting controls and increase the prescriptive
incentive amount for Luminaire Level Lighting Controls (LLLC) to encourage more participation and garner more data.
Avista planned to implement changes to the sign lighting measure effective April 15, 2021, to address these concerns.
2020 Idaho Annual Conservation Report Pg 46
Commercial/Industrial Prescriptive Non-Lighting Programs
TABLE 32 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE NON-LIGHTING PROGRAM METRICS
Prescriptive Non-Lighting Program Summary – Electric 2020
Participation, Savings, and Costs
Conservation projects 23
Overall kWh savings 113,078
Incentive spend $ 17,783
Non-Incentive Utility Costs $ 4,876
Idaho Energy Efficiency Rider spend $ 22,659
Prescriptive Non-Lighting Program Summary – Natural Gas 2020
Participation, Savings, and Costs
Conservation projects 64
Overall Therm savings 29,409
Incentive spend $ 75,981
Non-Incentive Utility Costs $ 119,258
Idaho Energy Efficiency Rider spend $ 195,239
Description
Commercial Food Service Equipment Program – The Commercial Food Service Equipment program helps
encourage customers to purchase energy-efficient equipment. If Avista provides the fuel type of the equipment
installed, customers are eligible when equipment meets the efficiency requirement. For equipment that requires hot
water heat, Avista must provide that heat source for eligibility. This program offers a variety of electric and natural
gas food service equipment. Customers who meet the requirements must submit rebate paperwork within 90 days of
project completion. Incentives are disbursed after receipt of documentation and verification of equipment eligibility.
Commercial Insulation Program – The Commercial Insulation program is a retrofit program to encourage customers
to increase the insulation in an existing building. It addresses three building areas – wall, attic, and roof – and is
available to Avista commercial customers who have an annual heating footprint of at least 340 therms or 8,000 kWh.
Insulation must be installed by a licensed contractor and meet the eligibility guidelines for existing and new R-values.
Customers who meet the requirements must submit rebate paperwork with accompanying insulation certificate and
invoice within 90 days of project completion. Incentives are disbursed after receipt of documentation and verification
of eligibility.
AirGuardian – The AirGuardian program was developed to offer a prescriptive path for Avista electric customers with
a 15 HP or greater rotary screw compressor. It offers a free walk-through audit to identify energy-saving opportunities
and the direct installation of a compressed air leak reduction device. Energy savings are generated by reducing the
impact of compressed air leaks during off-hour periods. The program is currently delivered by 4Sight Energy Group,
LLC. Savings are determined on an individual basis with pre- and post-logging. After logging is complete, a site report
is presented with detailed project data and an invoice for kWh savings payment to 4Sight Energy Group, LLC.
2020 Idaho Annual Conservation Report Pg 47
Commercial Natural Gas HVAC Program – The Commercial Natural Gas HVAC program encourages Avista
commercial natural gas customers to save energy by choosing to install energy-efficient natural gas furnaces and
boilers. It offers six different equipment types that customers may select from to best fit their business needs and
save energy dollars. Incentives are paid by the input kBtu and the efficiency of the equipment selected. Customers
must submit rebate forms with proof of purchase invoices and AHRI certificates within 90 days of project completion.
Incentives are disbursed after receipt of documentation and verification of eligibility.
Green Motors Rewind – The Green Motors Rewind program offers Avista commercial electric customers an instant
rebate on their service center invoice for a green rewind of an existing motor. Qualifying motors must fall between 15
and 5,000 horsepower and be used in an industrial capacity. The program pays $1 per HP to the service center and
another $1 per HP off the invoice for the customer. Green Motors Practices Group is the third party that manages
this program for the region and is paid an administrative fee of $.05 per kWh savings per customer rewind. Program
participation is presented monthly by Green Motors Practices Group in the form of an invoice accompanied by
detailed service center information per project.
Fleet Heat – The Fleet Heat program is provided to Avista commercial electric customers who use uncontrolled block
heaters to keep fleet engines warm when their vehicles are not running during colder months – typically from the end
of October to the end of March. This program offers a product that provides an engine-mounted remote thermostat
with an ambient temperature thermostat in a Twinstat cord to maximize energy efficiency. Upon receiving the rebate
form, Avista will order the cords for customers from Hotstart according to the information provided on the form.
Avista delivers the cords to the customer. The customer is responsible for the installation of the cords and the initial
payment to Hotstart. After installation verification, Avista refunds the customer’s Twinstat cord costs.
Commercial Grocer – The Commercial Grocer program provides Avista commercial electric customers with a range
of retrofit energy savings measures associated with commercial refrigeration. The incentives within this program offer
specific measures that can be installed and applied for after project completion. Customers may install any of the
eligible measures from display case lighting, motors, controls, strip curtains, or gaskets and apply for an incentive by
submitting a rebate form with associated invoicing and providing proof of purchase and installation. Incentives are
disbursed after receipt of documentation and verification of eligibility.
Commercial VFD Retrofit – The Commercial HVAC Variable Frequency Drive program is an incentive for Avista
commercial electric customers to increase the energy efficiency of their HVAC fan or pump applications with a
variable frequency drive. Installing a VFD on an existing unit of equipment enables that equipment to be more energy-
efficient. The incentive is calculated at $130 per HP of the motor the VFD is installed on. Post-installation verification
is required before payment is issued for all VFD projects. Customers may apply for this incentive after they install a
VFD on an existing piece of eligible equipment and submit required documentation. Incentive disbursement will be
processed after an installation inspection has occurred.
2020 Idaho Annual Conservation Report Pg 48
Program Activities
◆Electric: Savings of 113,078 kWh – a decrease of 42 percent compared to 194,978 kWh in 2019. The
majority of electric savings came from the Green Motors Rewind program.
◆Natural Gas: Savings of 29,409 therms in 2020, an increase of 13 percent in comparison to 26,120 therms
in 2019. Commercial HVAC comprised 55 percent of the program’s therm savings, while food service
measures accounted for 36 percent.
FIGURE 20 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE INCENTIVE DOLLARS BY MEASURE – ELECTRIC
FIGURE 21 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE INCENTIVE DOLLARS BY MEASURE – NATURAL GAS
$ 9,334 Green Motors Rewind
$ 1,800 Food Service
$ 240 Insulation
$ 6,410 Grocer
$ 41,507 Commercial HVAC
$ 26,750 Food Service
$ 7,724 Insulation
2020 Idaho Annual Conservation Report Pg 49
Program Changes
Several commercial insulation measures were modified from 2019 to 2020. The wall R11 to R18 was decreased to .35
from .40 per square foot. The attic up to R44 was increased from .20 to .50 and R45 or greater from .25 to .60. Roof
insulation was increased from .25 to .40 per square foot.
There were no other changes to commercial/industrial non-lighting prescriptive programs in 2020.
TABLE 33 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE NON-LIGHTING PROGRAM REBATE CHANGES, INSULATION
Commercial Insulation Program 2019 2020 Notes
Insulation Retrofit
Less than R11 Attic Insulation to R30-R44 Attic Insulation 0.20 0.50 Incentive Increase
Less than R11 Attic Insulation to R45+ Attic Insulation 0.25 0.60 Incentive Increase
Less than R11 Roof Insulation to R30+ Roof Insulation 0.25 0.40 Incentive Increase
Less than R4 Wall Insulation to R11-R18 Wall Insulation 0.40 0.35 Incentive Decrease
Program Marketing
Avista account executives market this program, which is also featured on the Avista efficiency website and used by
trade allies as a marketing tool.
2020 Idaho Annual Conservation Report Pg 50
Customer Satisfaction
According to Cadmus’ process evaluation, 2020 respondents were nearly all somewhat satisfied or very satisfied with
all aspects of the program, as shown in Figure 22. Two respondents reported being not too satisfied with aspects of
the program. One of these explained that the contractor had been difficult to work with and the process difficult to
understand. The other respondent did not provide additional detail on their rating.
FIGURE 22 – COMMERCIAL/INDUSTRIAL SATISFACTION WITH PRESCRIPTIVE PROGRAM COMPONENTS
Source: Prescriptive survey questions H1: “In terms of the [PROGRAM], how satisfied were you with the following aspects? Please think about each item individually
as you select your answer.”
Time to process the
application (n=60)
Submitting the
application materials (n=25)
Rebate amount (n=62)
Program overall (n=63)
Post-project inspection (n=19)
Pre-project inspection (n=17)
Equipment installed (n=61)
Communications with trade allies (n=44)
Communications with
account executive (n=47)
Percentage of Respondents
Very Satised
25%75%100%50%
Somewhat Satised Not too Satised Not at all Satised
80%
76%
79%
89%
88%
74%
92%
84%
79%
20%
24%
21%
11%
12%
26%
7%
14%
19%
2020 Idaho Annual Conservation Report Pg 51
When asked what challenges the program presented, 35 percent provided no response and 27 percent took the
opportunity to report there were no problems, or to compliment the program. Excessive paperwork was the most
common challenge reported, mentioned by 14 percent of respondents.
FIGURE 23 – COMMERCIAL/INDUSTRIAL PARTICIPATION CHALLENGES
Source: Prescriptive survey question H9: “What do so see as the biggest challenges to participating in Avista’s [PROGRAM_NAME]?”
Respondents called out several program aspects that they viewed as working well. As shown in Table 34, respondents
most commonly mentioned the fast or easy application process, followed by the opportunity to save energy and
money on utility bills. Several respondents who mentioned the fast process also mentioned good customer support.
For example, one respondent stated, “Great customer service and fast rebate turnaround.”
TABLE 34 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE PROGRAMS ASPECTS WORKING WELL
Program Aspects Number of
Respondents
Easy/fast process 11
Saving energy and money on utility bills 10
Overall program works well 7
Access to better lighting 5
Good customer service 5
Rebate amount 5
Contractor support 2
Access to quality products 1
Source: Prescriptive survey question H11: “What would you say is working particularly well with Avista’s program?” (Multiple responses allowed; n=39)
Difculty understanding requirements
Lack of awareness
Upfront costs
No challenges/compliment
Excessive or confusing paperwork
Other
Percentage of Respondents
5%10%15%20%25%30%35%
3
5
2%
6%
8%
9%
14%
27%
(n=66)
No response 35%
2020 Idaho Annual Conservation Report Pg 52
As shown in Table 35, 16 participants provided suggestions for program improvements. The most common suggestion
was to provide more information about program requirements, or better customer support. For example, one
respondent suggested having a chat function for customer support, instead of just phone and email. Another person
requested a searchable database for eligible products.
TABLE 35 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE PROGRAMS IMPROVEMENT SUGGESTIONS
Suggestion Number of
Respondents
More information/better customer support 7
More marketing 5
Bigger rebates 3
Outreach to contractors 1
Source: Prescriptive survey question H10: “What recommendations, if any, would you make to improve the program?” (n=16)
Impact Evaluation
Electric: Table 36 shows reported and evaluated electric energy savings for Avista’s commercial/industrial Prescriptive
program path (non-lighting) as well as the realization rates between the evaluated and reported savings for 2020. The
overall commercial/industrial Prescriptive program path achieved a 76 percent electric realization rate.
TABLE 36 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE ELECTRIC IMPACT FINDINGS (NON-LIGHTING)
Program Type Reported Savings
(kWh)
Evaluated Savings
(kWh)Realization Rate
Shell Measure 1,341 1,341 100%
Green Motors 52,038 52,038 100%
Food Service Equipment 13,761 13,761 100%
AirGuardian 0 0 NA
Energy Smart Grocer 45,938 45,938 100%
Commercial/Industrial Prescriptive 113,078 113,078 100%
2020 Idaho Annual Conservation Report Pg 53
Natural Gas: Table 37 shows the reported and evaluated natural gas energy savings for Avista’s commercial/industrial
Prescriptive program path as well as realization rates between the evaluated and reported savings for 2020. The
overall commercial/industrial Prescriptive program path achieved a 101 percent natural gas realization rate.
TABLE 37 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE NATURAL GAS IMPACT FINDINGS
Program Type Reported Savings
(therms)
Evaluated Savings
(therms)Realization Rate
HVAC 13,803 13,992 101%
Shell 1,821 1,821 100%
Food Service Equipment 13,597 13,597 100%
Commercial/Industrial Prescriptive 29,221 29,409 101%
Of 14 evaluated applications, Cadmus identified discrepancies for one based on the verification and project
documentation review. Table 38 summarizes the reasons for discrepancies between reported and evaluated savings.
TABLE 38 – COMMERCIAL/INDUSTRIAL PRESCRIPTIVE EVALUATION SUMMARY OF DISCREPANCIES
Project Type Number of
Occurrences Savings Impact Reason(s) for Discrepancy
HVAC 1 
Cadmus found that the installed furnaces for one project were multistage
based on the model number and specifications rather than single-stage as
reported, which increased the evaluated savings.
Recommendations
Cadmus offered the following recommendations to improve realization rates for prescriptive programs:
◆Review deemed savings values for prescriptive measures and consider opportunities to leverage the additional
data now collected in iEnergy to calculate more accurate savings for each participant project. For example,
food service measures can use the reported pounds of food cooked per day and cooking hours per day values
collected in iEnergy to automatically calculate more precise savings.
◆Review iEnergy calculations to ensure that rounding is only applied on final displayed values and not to any
intermediate values.
◆Update all application forms to include space for location notes for each installed measure and encourage
contractors installing equipment at very large facilities to include installation location with equipment
invoices.
2020 Idaho Annual Conservation Report Pg 54
Plans for 2021
Avista is considering increasing incentive levels to encourage more participation in the Commercial/Industrial Insulation
and VFD programs. A new measure in the Commercial/Industrial HVAC program for 92 percent AFUE natural gas unit
heaters is under consideration. The current AirGuardian program will end in 2021; it will be renamed and relaunched
as the Commercial/Industrial Compressed Air Line Isolation program.
Avista will continue to improve and refine calculations in iEnergy for prescriptive rebates in line with Cadmus’
recommendations, and will consider updating application forms to capture more accurate location data for installed
measures.
Avista will also consider increasing outreach to customers for commercial/industrial programs, and will consider ways
to help participants sort through equipment options more efficiently.
2020 Idaho Annual Conservation Report Pg 55
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RESIDENTIAL SECTOR
Memorial Bridge, Lewiston, Idaho
2020 Idaho Annual Conservation Report Pg 57
RESIDENTIAL SECTOR
Overview
Avista’s residential sector portfolio is composed of several approaches that encourage customers to consider energy-
efficiency improvements within their homes. Prescriptive rebate programs are the main component of the portfolio
and are augmented by a variety of additional interventions, including upstream buy-down of low-cost lighting
and water-saving measures, select distribution of low-cost lighting and weatherization materials, direct-installation
programs, and a multifaceted, multichannel outreach and customer engagement effort.
Nearly $2.3 million in rebates and direct customer benefits were provided to Idaho residential customers to offset the
cost of implementing these energy-efficiency measures in 2020. All programs within the residential sector portfolio
combined contributed 5,283 MWh and 317,550 therms to the annual energy savings.
TABLE 39 – RESIDENTIAL SAVINGS BY PROGRAM
Residential Program Electric Savings
(kWh)
Natural Gas Savings
(therms)
ENERGY STAR Homes 50,705 401.94
Fuel Efficiency 635,962 0
Multifamily Direct Install 747,227 0
Residential HVAC 508,131 266,939
Residential Water Heat 12,986 37,976
Residential Shell 358,972 12,000
Simple Steps, Smart Savings 2,968,563 233.56
Total Residential 5,282,546 317,550
2020 Idaho Annual Conservation Report Pg 58
To help educate contractors on Avista’s new residential rebates, a webinar was conducted – as well as a meeting in
Spokane – to present information and provide a forum for questions.
FIGURE 24 – RESIDENTIAL REBATES CONTRACTOR MEETING
Marketing
The spring “Way to Save” advertising campaign included TV, digital, search engine marketing, and social media. It
began March 7 and was scheduled to continue through May 3. The campaign was pulled on March 16, however,
because the majority of Avista’s rebates require professional installation, and many HVAC contractors and vendors
were not working due to the stay-at-home order.
Even though the campaign was cut short, it was very effective in driving website traffic while it was running. Average
page views on Avista’s Idaho rebates page went from 90 per day to 572 per day – an increase of 536 percent.
Residential Rebate Contractor Meeting
Please join us to learn about our 2020 energy-efficient rebates for residential customers, including:
• New incentives and requirements
• Invoice examples and AHRI certificate requirements• Our new online rebate submittal process for contractors
• The benefits of natural gas heating for your customers• Idaho natural gas conversion incentives
• Avista Trade Ally Participation
Coeur d’Alene: Spokane:March 3 – 9:30am to 11am March 5 – 8am to 10:30am
Avista Office Spokane County Water Reclamation Center(Lunchroom) (Conference Room)
1735 N. 15th St. 1004 N. Freya St.
Webinar Option:March 4 – 9am to 10am
You must be an Avista Trade Ally Network member (or become a member) to be a guest. Please RSVP to attend an event in person or to participate via webinar.
(Webinar call-in instructions will be sent by email one day prior to the event.)
To RSVP for a meeting: Go to avistatradeallynetwork.force.com/tradeally and look for the EVENTS tab. If you have not yet created your account (or wish to
join our network), request a personal registration code and instructions by email at [e-mail].
AvistaP.O. Box 3727 MSC-15
Spokane, WA 99220-3727
Learn about Avista’s new residental rebates.
2020 Idaho Annual Conservation Report Pg 59
FIGURE 25 – RESIDENTIAL “WAY TO SAVE” TELEVISION COMMERCIALS
2020 Idaho Annual Conservation Report Pg 60
To help customers during the coronavirus pandemic, additional communications were developed that included
website updates and energy-efficiency tips for residential customers.
FIGURE 26 – RESIDENTIAL ENERGY SAVINGS TIPS WHILE AT HOME FLYER
Energy-saving tips while at home
Set your fridge temperature between 37 and 40 degrees. Keep the freezer section at 5 degrees. Also vacuum exposed coils located on the back or underneath the appliance. Regular cleaning can improve efficiency up to 15% or more.
Set your stand-alone freezer to 0 degrees. A full freezer also retains cold better than an empty one.
Don’t put warm foods directly into the refrigerator. Allow hot foods to cool, then refrigerate. Cooked meats, however, should be refrigerated immediately.
Add humidity to your home if it has under 30% relative humidity. Keeping your home’s humidity between 40% and 50% will make you feel warmer and reduce the chance of viral spread. If you don’t own a device that displays the humidity level inside your home, here are ways to increase humidity indoors as well as how to assess your relative humidity.
How to increase humidity. You can increase humidity indoors using a humidifier. If you don’t own one or prefer to save energy, however, you can place water-filled vases on sunny windowsills. The sunshine will slowly evaporate the water, releasing moisture into the air. Hang your clothes to dry inside your home to take advantage of incidental moisture release. A steamy kettle on the stove beats using a microwave.
Set your water heater temperature to 120 degrees. That’s plenty hot and won’t scald. Do not set the water temperature below 115 degrees to prevent Legionnaires’ disease.
Take short showers. You’ll use less hot water than a bath.
Fix leaky faucets. A small drip can waste a bathtub full of hot water each month.
Always use a sink stopper or dishpan. Washing or rinsing dishes under running hot water wastes energy.
Run a full dishwasher. If your dishwasher has an automatic energy-savings/cool-dry cycle, use that setting. Otherwise, turn it off after the final rinse and let dishes air dry.
THE ICE CUBE HUMIDITY TEST
1. Place two or three ice cubes into a glass, add tap water and stir.
2. Wait three to four minutes and then observe the glass.
3. Examine the outside of the glass. If moisture does not form, the air is too dry. If the outside of the glass shows a fog of water vapor, the relative humidity is correct. If water has condensed on the outside of the glass with drops rolling down, the relative humidity is high.
NOTE: Conduct this test in any room where humidity is a concern except the kitchen, as cooking vapors may produce inaccurate results.
Wash only full loads of clothes. Wash full loads using the proper water levels. Some experts also advise washing clothes in hot water to reduce the chance of virus strands clinging to your clothes (this may increase your energy consumption).
Clean your dryer’s lint filter after every load. Clogged filters increase drying time.
Don’t overload your dryer. Clothes will take longer to dry.
Kitchen
Humidity Level
Water Heating Laundry
Energy-saving tips while at home
Concerned about the virus in your home? During this time of uncertainty, you can help keep your air cleaner by cracking windows or opening the fresh-air damper on your furnace intake to let in more outside air. Also, continuously run your furnace fan at a low speed and change furnace filters often.
Set your thermostat no higher than 68 degrees. Also lower it an extra five degrees at night unless you have a heat pump.
Keep heat registers free of obstructions. Drapes, furniture and plants can all block air flow.
Close doors to unoccupied rooms if you have zoned heat like baseboards. You’ll save space-heating costs. Do not shut off registers or block returns with a forced air system. It will increase fan energy usage and may cause damage to your equipment.
Turn off TVs and other electronics after use. They may continue to consume power even when appearing off. Also, plug your home electronics into a single power strip so you can switch it off and cut power to all of them at once.
Turn off unnecessary lights. Use sunlight during the daytime if possible. Make sure your exterior lights are off during the day.
Let the sun warm your home. Open your drapes/ blinds on south-facing windows to let in sunlight. Close them in rooms that receive no sun to insulate against cold drafts. At night, close coverings to retain heat.
Clean or replace your furnace filters. If you do not have filters on hand, it’s still possible to order them for pick-up from local stores. Or, enroll in Avista’s Furnace Filter Program to receive reminders, get valuable coupons and have new filters delivered right to your door. Go to myavista.com/changemyfilter
Make sure your fireplace is used properly. If you are using another heat source for your home, close off the damper on your fireplace to avoid energy loss up the flue.
Activate power-saving settings on your game console. Adjusting these settings on your console, and using power strips, can address the phantom loads associated with standby modes. Also, some game consoles use more energy than other dedicated devices to stream HD movies. Check the manufacturer’s website for more information.
To help prevent the spread of COVID-19, government officials have issued a stay-at-home order throughout our region. People working from home—as well as
students of all ages in the house—can mean an increase in energy use. You can help
take charge of your energy use with these simple home energy-efficiency tips.
Living Spaces
Electronics
2020 Idaho Annual Conservation Report Pg 61
FIGURE 27 – RESIDENTIAL ENERGY USE AND SAVINGS GUIDE FOR RESIDENTIAL CUSTOMERS
Page 4 Energy Use and Savings Guide
Typical Energy Use in Your Home
The energy bill for a typical U.S. single family home averages $2,200 per year . Where does all this money go?
The cost of heating and cooling your home can represent 40%
to 60% of your total energy bill . The chart to the right shows
the breakdown of energy use by category and starts to give
you a sense of where savings can be found . Reducing energy
consumption by just 15% could save you over $300 a year in
energy costs .
Managing Your Energy Budget
Having a budget is always a good
idea . Developing a budget starts with
understanding your resource needs .
Each month, you need food, clothing,
transportation and energy to run your
home . Understanding your energy usage
is the first step to creating that portion of your budget . Inside this booklet, you’ll find many energy saving tips to help you manage your resources .
This booklet contains ideas and suggestions on how you can monitor— and better control—your energy consumption . You may already be familiar with some of our energy savings suggestions,
though some may surprise you .
Individual lifestyle and energy use habits,
number and age of occupants, as well
as the size, design, levels of insulation
and heating system in your home,
all combine to determine how much
energy you will use for heating .
The statistics in this booklet are based on national averages . The wattage or energy usage and efficiencies of your appliances, your own use habits, as well as the size of your family will vary . Keep this in mind when you’re reviewing your own energy use .
Page 5
Understanding This Guide
Listed below are terms and definitions that will be used throughout this guide .
All numbers and costs included are a representation based on national average use
with average Avista rates .
Kilowatt Hours (kWh): We measure electrical energy in watt hours . One kilowatt hour equals 1,000 watt hours . The kilowatt hours on your bill equals the rate or speed of use (kilowatts) x the length of time electricity was used . Running a 5,000-watt (5 kilowatt) clothes dryer for 1 hour uses 5 kilowatt hours of electricity . Burning a 100-watt light bulb for 10 hours uses 1 kilowatt hour .
Therms: Your gas energy use is measured
in a unit called therms . Therms identify the
heating value provided by gas . One therm
equals the heating capacity of approximately
100,000 wooden kitchen matches .
Approximate Watts: The wattage is the consumption rate of electricity a device exhibits while operating . This energy consumption may occur when a computer is turned on, when a kitchen mixer is in use or when light bulbs are turned on in a light fixture .
Monthly kWh Usage: The monthly
kWh usage for each device is based on
an assumed typical month of operation,
estimating the hours the device is
operating in conjunction with its power
consumption as noted in the watt rating .
Estimated Monthly Cost: The estimated monthly cost is based on the energy consumption at $0 .10 per kilowatt hour for electricity or $0 .80 per natural gas therm which are typical for Avista residential customers .
Heating & Cooling – 46%
Water Heating – 14%
Lighting – 12%
Appliances – 13% (Includes refrigerator, dishwasher, clothes washer and dryer)
Electronics – 4% (Includes computer, monitor, TV and DVD player)
Other – 11% (Includes external power adapters, set-top boxes, ceiling fans, vent fans and home audio)
46%
14%
12%
13%
4%
11%
Energy Use
and Savings Guide
For Residential Customers
Page 8
Energy Use and Savings Guide
Heating and Cooling
On sunny winter
days, open your draperies to get full benefi t of sun
shining through
the windows . In
summer, close the
draperies to help
keep out unwanted
heat .Fireplace dampers should be kept closed when you’re not using the fi replace .

A
chimney can draw off as much as 25%
of the heated air in your house if the
damper is left open . Safely block off unused fi replaces when possible .
Turn down the heat in winter . Keep your thermostat at or below 68° F; setting your thermostat three degrees lower in th
e

w
i
n
t
e
r
can reduce your bill by about 10% .
Heating and Cooling Energy Sav
i
n
g

T
i
p
s
8.5
17.0
8.5
17.0
8.5
17.0
8.5
17.0
8.5
17.0
When selecting a heat pump, check its Heating Seasonal Performance Fa
c
t
o
r

(HSPF) . The HSPF indicates a hea
t

p
u
m
p
’
s

relative annual heating effi cienc
y

.

A

HSPF of 8 .5 and above will provi
d
e

l
o
w
e
r

operating costs for heating .
When selecting an air conditioning unit, both room or central, check its
Seasonal Energy Effi ciency Ratio (SE
E
R
)

.
The SEER indicates a unit’s relative en
e
r
g
y
effi ciency . Most units are tagged w
i
t
h
this information, or your dealer can
h
e
l
p
you determine the SEER . The highe
r

t
h
e
SEER, the better . A SEER of 13 or a
b
o
v
e

i
s
preferred, 18 or above is exceptiona
l

.
Page 9
Heating and Cooling
Energy Saving Checklist
Block drafts. Check caulking and weather stripping around windows

a
n
d
doors . If you see cracks, light, or f
e
e
l

a
draft, make repairs where needed .
Seal leaks. Ductwork exposed to outside air or in unconditioned spaces sh
o
u
l
d

b
e

sealed using mastic paste and wr
a
p
p
e
d

securely with insulation; insulatio
n

j
o
i
n
t
s

should be sealed with insulation
t
a
p
e

.
Check furnace fi lter. Check fi lters at least once a month; clean or replace them when dirty .
Bring in a professional. A qualifi ed serviceman should check heating an
d
cooling equipment at the beginning

o
f
each season to ensure effi cient op
e
r
a
t
i
o
n

.
Use drapes or shades. Window coverings are one of the easiest w
a
y
s

to help insulate your house . Kee
p

t
h
e
m

closed on cold days and open on
s
u
n
n
y

ones .
Use fans in the summer. Try using fans in the summer before switching on

t
h
e
air conditioning . Old A/C equipm
e
n
t

c
a
n

be equivalent to using 30 or more

f
a
n
s

.

If you must use your air conditione
r
,

s
e
t

it at 78° F; each degree over 78° in

t
h
e

summer will save you approximate
l
y

3
%

on your cooling bill .
Program your thermostat. Adjust temperature settings according to a preset schedule . This way you can warm up or cool down your rooms when you know you’ll be awake or at home . Consider a Wi-Fi enabled smar
t
thermostat that learns your settings .
Visit myavista.com/readyourmeter to learn more about how to read you
r

m
e
t
e
r

.
Reading Your Meter
Electric and natural gas meters ar
e

n
o
t

d
i
f
f
i

c
u
l
t

t
o

read and they can provide you w
i
t
h

i
n
f
o
r
m
a
t
i
o
n

about your energy consumption .
Page 12 Energy Use and Savings Guide
Water Heating
If you do not have access to natural gas,
consider a heat pump water heater to
save energy .
Showers generally take less hot water
than baths and dishwashers generally
take less water than hand washing .
Buy
ENERGY STAR
appliances .
If you don’t have hard water or you
do have a water softener, consider a
tankless natural gas water heater
that reduces standby losses .
Water Heating Energy Saving Tips
102
Page 13
Water Heating
Energy Saving Checklist
Keep showers short. Try to keep your shower to no longer than fi ve minutes .
Adjust your temperature settings. Set your water heater at 120° F .
Replace washers on faucets that drip. A leaky faucet can waste 2,500 gallons of hot
water per year at a rate of one drip per second .
Install a low-fl ow shower head. It can reduce your home water consumption as much as 50%, and reduce your energy cost of heating the water also by as much as 50% . When purchasing a new shower head you should look for shower heads that use no more than 1 .5 gallons per minute (water consumption) and preferably no more than 0 .6 gallons per minute .
Energy Use Guide–Electric
Water heater, 50-gallon heat pump 182 .9 $18 .29
Water heater, 50-gallon high-effi ciency 385 .2 $38 .52
Water heater, 50-gallon standard-effi ciency 404 .8 $40 .48
Assuming 25 gallons per day
Energy Use Guide–Natural Gas
Water heater, 50-gallon 20 $16 .00
Water heater, 40-gallon 17 .5 $14 .00
Instantaneous water heater 11 .5 $9 .20
2020 Idaho Annual Conservation Report Pg 62
As businesses opened up in the summer, Avista placed its “Way to Save” digital advertising campaign to help increase
awareness of the company’s rebates. The advertising included social media, search engine marketing, and online
banner ads. It ran June 22-August 31 and proved successful in driving customer engagement. When looking at the
weeks prior to the campaign (i.e., May 1-June 21), page views on Avista’s Idaho rebates page totaled 2,140. During
the campaign and including the two weeks following the advertising (June 22-September 14), page views totaled
29,248 – an increase of 1,267 percent.
FIGURE 28 – RESIDENTIAL “WAY TO SAVE” DIGITAL ADS
2020 Idaho Annual Conservation Report Pg 63
FIGURE 29 – RESIDENTIAL “WAY TO SAVE” SOCIAL MEDIA
2020 Idaho Annual Conservation Report Pg 64
As cold weather moved in, Avista’s “Smart Winter Giveaway” campaign was implemented to remind customers of
energy-saving tips for the heating season. Communication tactics included the Connections newsletter, emails, a bill
insert, the website, and social media. The campaign proved successful in driving customer engagement, with more
than 43,000 entrants.
FIGURE 30 – RESIDENTIAL “SMART WINTER” BROCHURE
Hot Water14%
Heat50%or more
A 1/4” gap at the bottom of a door is equivalent to a softball-sized hole in the wall.
Install a door sweep to stop drafts.
Hot Water14%
Heat50%or more
A 1/4” gap at the bottom of a door is equivalent to a softball-sized hole in the wall.
Install a door sweep to stop drafts.
Hot Water14%
Heat50%or more
A 1/4” gap at the bottom of a door is equivalent to a softball-sized hole in the wall.
Install a door sweep to stop drafts.
Hot Water14%
Heat50%or more
A 1/4” gap at the bottom of a door is equivalent to a softball-sized hole in the wall.
Install a door sweep to stop drafts.
Hot Water14%
Heat50%or more
A 1/4” gap at the bottom of a door is equivalent to a softball-sized hole in the wall.
Install a door sweep to stop drafts.
Hot Water14%
Heat50%or more
A 1/4” gap at the bottom of a door is equivalent to a softball-sized hole in the wall.
Install a door sweep to stop drafts.
2020 Idaho Annual Conservation Report Pg 65
Avista Kids
With more children at home due to the pandemic, it was a good time to develop new material to help educate this
younger audience about energy efficiency. A complete creative refresh was done to existing materials, with new
lessons designed to teach kids how to conserve energy while having fun at the same time. They included pictures to
color and activities such as puzzles, word searches, mazes, and fun science experiments – all designed to build energy-
saving habits for life. The printable coloring pages and activities content can be found on the website at
myavista.com/kids, categorized for ages 4-8 and 9-12. In addition, customers can request a free Kids Activities Kit,
which includes a printed version of the activities book along with crayons and pencils. The kit offer is promoted on
Avista’s website, in the Connections newsletter, and through social media channels.
FIGURE 31 – RESIDENTIAL KIDS CAN SAVE ENERGY TOO COLORING AND ACTIVITY BOOK
K I D S C A N
C o l o r i n g a n d A c t i v i t i e s

B

o

o

k
SAVE
ENERGY,
TOO!
SAVE ENERGY
Find the difference between the two pictures in each row. Then circle the picture that shows how to save energy and color it!
ANSWERS
1) B. The TV is turned off to save electricity. 2) A. The refrigerator is shut to keep in cold air. 3) B. Fans use less energy than air conditioners.
HINT: Turn this off when no one is watching.1
HINT: Shut this fast to keep in cold air.2
HINT: Use thisinstead to keepyourself cool.3
A
A
A
B
B
B
Word Search
ELECTRICITYENERGY
FANREFRIGERATOR
FURNACENATURAL GASHOT WATER
LIGHT SWITCHSWEATER
TELEVISION VIDEO GAME
WATT
F Y D D C Y E W H P S Y E K Q
Z N A T U R A L G A S B X Y V
T S R V T V C W I Y O I S A I
E H E L B C J G Q A S R O Y D
L O F L I A H F M K Q N X C E
E T R R E G O N N V M F J Z O
V W I U S C H E Z J D A X S G
I A G F W A T T J O Z E U X A
S T E U E U D R S L B P J Q M
I E R R A N E E I W N E V W E
O R A N T C F N G C I K T N S
N A T A E I A E L Q I T M W H
K N O C R C N R R O Q T C H T
B S R E S G Q G B W F T Y H N
J J P R N F A Y S U K A L H E
Saving energy is as easy as turning things off when you’re done, wearing a sweater when you’re cold, taking short showers to save hot water and more.
TIP
FIND THEWORDSLISTEDBELOW
myavista.com/kids
UNFOLDING
ENERGY
SAVINGS
ANSWERS
1 2 3 4
5 6 7 8
Circle the blocks that can be made
from this example once it is folded.
ENERGY SAVING REMINDER
S
Use LED bulbs, take shorter showers,
turn off games, clean the dryer vent,
shut the refrigerator door quickly an
d

wash only full loads.
2 and 8
Turning off lights when you leave a room

i
s

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way to save energy. But not everyo
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.
ANSWER Josh left first, followed by Jayden, Aaron
and Terrell. Amber was the last to leave
and forgot to turn off the lights.
LIGHTS ON
DETECTIVE
myavista.com/kids
Don’t keep the refrigerato
ropen for too long.
Turn off the TV and video g
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myavista.com/kids
2020 Idaho Annual Conservation Report Pg 66
Impact Evaluation
While some individual programs varied, the residential sector performed strongly overall in 2020. Savings realization
rates were as follows:
◆Electric: Total verified savings of 5,282,546 kWh with a realization rate of 97 percent.
◆Natural Gas: Evaluated natural gas savings show a realization rate of 121 percent on savings of 317,550
therms.
Complete impact evaluations for electric and natural gas are included in Appendices A and D.
Performance and Savings Goals
The electric program portfolio achieved 115 percent of the 2020 savings goal, the result of high program participation
(134 percent) and a strong overall realization rate for the residential sector.
Lighting measures accounted for 70 percent of the total residential sector savings. The following shows the
percentage of residential evaluated savings provided by each program:
◆Simple Steps, Smart Savings provided 56 percent, mostly through lighting measures.
◆Multifamily Direct Install (MFDI) provided 14 percent, again mostly through lighting measures.
◆The residential HVAC program accounted for 10 percent of evaluated savings.
◆The Shell and ENERGY STAR Homes programs accounted for a combined 8 percent.
Table 40 shows savings goals assigned to Avista’s residential sector programs for 2020, as well as reported savings and
the goal portion achieved in 2020. All programs except ENERGY STAR Homes and residential HVAC exceeded savings
goals based on reported savings.
TABLE 40 – RESIDENTIAL PROGRAMS REPORTED ELECTRIC SAVINGS
Program Savings Goals
(kWh)
Savings Reported
(kWh)Percentage of Goal
Simple Steps, Smart Savings 661,531 2,968,563 449%
HVAC 560,367 508,131 91%
Residential Appliances 4,220 0 0%
Shell 252,475 358,972 142%
Fuel Efficiency 1,798,470 635,962 35%
ENERGY STAR Homes 6,630 50,705 765%
Water Heat 16,324 12,986 80%
Multifamily Direct Install 1,288,412 747,227 58%
Residential Total 4,588,429 5,282,546 115%
The natural gas segment of the portfolio achieved 93 percent of the goal for 2020.
2020 Idaho Annual Conservation Report Pg 67
The following shows the percentage of residential evaluated savings provided by each program:
◆The HVAC program accounted for 84 percent, and was the only program to meet its savings goal.
◆The Water Heating program accounted for 12 percent.
◆The Shell program accounted for 3.8 percent of residential gas savings.
◆Simple Steps, Smart Savings and ENERGY STAR Homes combined accounted for less than 1 percent.
Table 41 shows savings goals assigned to Avista’s residential sector programs for 2020, as well as reported savings and
percentage of goal achieved in 2020. Note that as part of Avista’s planning process, no estimates were made for the
Simple Steps, Smart Savings program; thus, no goal was established for the program year.
TABLE 41 – RESIDENTIAL PROGRAMS REPORTED NATURAL GAS SAVINGS
Program Savings Goals
(therms)
Savings Reported
(therms)Percentage of Goal
Simple Steps, Smart Savings 0 234 N/A
HVAC 258,170 266,939 103%
Shell 42,334 12,000 28%
ENERGY STAR Homes 670 402 60%
Water Heat 39,436 37,976 96%
Multifamily Direct Install 236 0 0%
Residential Total 340,846 317,550 93%
Impact Evaluation Methodology
The evaluators employed the following approach to complete impact evaluation activities for the programs. The
evaluators define two major approaches to determining net savings for Avista’s programs:
◆A deemed savings approach involves using stipulated savings for energy conservation measures for which
savings values are well-known and documented. These prescriptive savings may also include an adjustment
for certain measures, such as lighting, in which site operating hours may differ from RTF values.
◆A billing analysis approach involves estimating energy savings by applying a linear regression to measured
participant energy consumption utility meter billing data. Billing analyses included billing data from
nonparticipant customers. This approach does not require on-site data collection for model calibration. This
approach aligns with the IPMVP Option C.
The evaluators accomplished the following quantitative goals as part of the impact evaluation:
◆Verify savings with 10 percent precision at the 90 percent confidence level;
◆where appropriate, apply the RTF to verify measure impacts; and
◆where available data exists, conduct billing analysis with a suitable comparison group to estimate measure
savings.
2020 Idaho Annual Conservation Report Pg 68
For each program, the evaluators calculated adjusted savings for each measure based on the Avista TRM and results
from the database review. They calculated verified savings for each measure based on the RTF UES, Avista TRM, or
billing analysis in combination with the results from document review. For the HVAC, Water Heat, and Fuel Efficiency
programs, the evaluators also applied in-service rates (ISRs) from verification surveys.
FIGURE 32 – RESIDENTIAL IMPACT PROCESS
The evaluators assigned methodological rigor levels for each measure and program based on its contribution to the
portfolio savings and availability of data.
They analyzed billing data for all electric measure participants in the HVAC and Low-Income programs, and applied
billing analysis results to determine evaluated savings only for measures where savings could be isolated (that
is, where a sufficient number of participants could be identified who installed only that measure). Program-level
realization rates for the HVAC, Water Heat, and Fuel Efficiency programs incorporate billing analysis results for some
measures.
The evaluators verified a sample of participating households for detailed review of the installed measure
documentation and development of verified savings. They verified tracking data by reviewing invoices and surveying a
sample of participant customer households. They also conducted a verification survey for program participants.
The evaluators used the following equations to estimate sample size requirements for each program and fuel type:
FIGURE 33 – EQUATION 2-1 SAMPLE SIZE FOR INFINITE SAMPLE SIZE
FIGURE 34 – EQUATION 2-2 SAMPLE SIZE FOR FINITE POPULATION SIZE
Adjusted
Savings
Document
Review
Interim
Veried
Savings
Reported
Savings
Database
Review
n =()Z x CV
d
2
n0 =n
1 +n
N()
2020 Idaho Annual Conservation Report Pg 69
Where,
◆n = Sample size
◆Z = Z-value for a two-tailed distribution at the assigned confidence level.
◆CV = Coefficient of variation
◆d = Precision level
◆N = Population
For a sample that provides 90/10 precision, Z = 1.645 (the critical value for 90 percent confidence) and d = 0.10 (or
10 percent precision). The remaining parameter is CV, or the expected coefficient of variation of measures for which
the claimed savings may be accepted. A CV of .5 was assumed for residential programs due to the homogeneity
of participation,1 which yields a sample size of 68 for an infinite population. Sample sizes were adjusted for smaller
populations via the method detailed in Equation 2-2.
The following sections describe the evaluators’ methodology for conducting document-based verification and survey-
based verification.
Document-Based Verification
The evaluators requested rebate documentation for a subset of participating customers. These documents included
invoices, rebate applications, pictures, and AHRI certifications for the following programs:
◆Water Heat
◆HVAC
◆Shell
◆Fuel Efficiency
◆ENERGY STAR Homes
◆Simple Steps, Smart Savings
◆Low-Income
This sample of documents was used to cross-verify tracking data inputs. In the case the evaluators found any
deviations between the tracking data and application values, they reported and summarized those differences in the
database review sections presented for each program in Sections 3.3 and 4.1 of the electric and natural gas impact
evaluations (Appendices C and D).
The evaluators developed a sampling plan that achieves a precision of ±10 percent at 90 percent statistical confidence
– or “90/10 precision” – to estimate the percentage of projects for which the claimed savings are verified or require
some adjustment.
The evaluators developed the following samples for each program’s document review using Equation 2-1 and
Equation 2-2, and ensured representation in each state and fuel type for each measure.
1) Assumption based on California Evaluation Framework: https://www.cpuc.ca.gov/uploadedFiles/CPUC_Public_Website/Content/Utilities_and_Industries/Energy/Ener-
gy_Programs/Demand_Side_Management/EE_and_Energy_Savings_Assist/CAEvaluationFramework.pdf
2020 Idaho Annual Conservation Report Pg 70
Table 42 represents the number of rebates in both Idaho and Washington territories. The evaluators ensured
representation of state and fuel type in the sampled rebates for document verification. Please note that number of
rebates is not equivalent to number of customers, because some customers receive multiple rebates.
TABLE 42 – RESIDENTIAL DOCUMENT-BASED VERIFICATION SAMPLES AND PRECISION BY PROGRAM
Sector Program Gas Population
Sample (with
Finite Population
Adjustment)*
Precision at 90% CI
Residential
Water Heat 957 65 ±9.85%
HVAC 7,401 69 ±9.86%
Shell 1,337 68 ±9.72%
Fuel Efficiency N/A N/A N/A
ENERGY STAR Homes 6 6 ±0.00%
Simple Steps, Smart Savings N/A N/A N/A
Low-Income Low-Income 550 66 ±9.50%
* Assumes sample size of 68 for an infinite population, based on CV (coefficient of variation) = 0.5, d (precision) = 10 percent, Z (critical value for 90 percent
confidence) = 1.645.
Survey-Based Verification
The evaluators conducted survey-based verification for the Water Heat and HVAC programs. The primary purpose
of conducting a verification survey is to confirm that the measure was installed and is still currently operational and
whether the measure was early retirement or replace-on-burnout.
The evaluators summarize the final sample sizes shown in Table 43 for the Water Heat and HVAC for the Idaho Gas
Avista projects. The evaluators developed a sampling plan that achieved a sampling precision of ±4.24 percent at 90
percent statistical confidence for ISR estimates at the measure-level during web-based survey verification.
TABLE 43 – RESIDENTIAL SURVEY-BASED VERIFICATION SAMPLE AND PRECISION BY PROGRAM
Sector Program Population Respondents Precision at 90% CI
Residential
Water Heat 957 115 ±7.20%
HVAC 7,401 246 ±5.16%
Fuel Efficiency N/A N/A N/A
Total 8,358 361 ±4.24%
The evaluators implemented a web-based survey to complete the verification surveys. They supplemented with
phone interviews to reach the 90/10 precision goal. The findings from these activities served to estimate ISRs for each
measure surveyed. These ISRs were applied to verification sample desk review rebates towards verified savings, which
were then applied to the population of rebates. The measure-level ISRs resulting from the survey-based verification are
summarized in Section 3.1 of the residential impact evaluations (Appendices A and C).
2020 Idaho Annual Conservation Report Pg 71
Recommendations
ADM offered the following recommendations for Avista’s residential programs:
◆The evaluators recommend Avista work to improve methods for collecting mail-in rebate application
information to reconcile the Customer Care & Billing (CC&B) database. The values found in the project
documentation should accurately reflect the values represented in the CC&B database.
◆A number of rebates were not accompanied by AHRI certification. In order to acquire accurate equipment
efficiencies and tank sizes, AHRI certifications are recommended to be required and submitted with the
rebate application, with an invoice that matches the model number found in the AHRI certification.
◆The evaluators note that a number of rebate applications did not contain values associated with whether
the home is existing or was new construction. This field is an input to apply correct RTF UES values. The
evaluators recommend requiring this field be completed in rebate applications, both mail-in and web-based.
◆The evaluators cross-referenced the billing data to verify whether customers demonstrated the required
heating season electricity usage of 8,000 kWh and natural gas usage of less than 340 therms, as defined
in the program requirements. The evaluators found many customers used less than 8,000 kWh or 340
therms annually. In addition, some customers had insufficient pre-period data to determine annual usage.
The evaluators recommend Avista verify whether customers meet the requirements prior to completing the
rebate.
◆The evaluators also recommend collecting information on single-family/multi-family/manufactured in the
web rebate form. This allows the evaluators to accurately assign RTF values. The mail-in rebates collect this
information; it does not seem to be currently required to complete the rebate, however; many rebates are
missing this information.
◆The evaluators note several instances in which the web-based rebate data indicates the household has
electric space heating, but all other sources (project data and document verification) indicate natural gas
space heating, and vice versa. The evaluators recommend updating data collection standards in order that all
sources of information reflect the same values as the project documentation.
2020 Idaho Annual Conservation Report Pg 72
Cost-Effectiveness
Tables 44 and 45 show the residential sector cost-effectiveness results by fuel type. Note that these values are inclusive
of both the prescriptive programs and the multifamily direct install programs.
TABLE 44 – RESIDENTIAL ELECTRIC COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 5,573,921 $ 2,133,107 2.61
Total Resource Cost (TRC)$ 6,131,313 $ 3,271,662 1.87
Participant Cost Test (PCT)$ 7,417,708 $ 2,019,940 3.67
Ratepayer Impact (RIM)$ 5,573,921 $ 12,060,227 0.46
Table 7 shows residential cost-effectiveness results for electric.
TABLE 45 – RESIDENTIAL NATURAL GAS COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 3,502,394 $ 1,426,403 2.46
Total Resource Cost (TRC)$ 3,852,633 $ 3,466,442 1.11
Participant Cost Test (PCT)$ 4,821,706 $ 3,422,171 1.41
Ratepayer Impact (RIM)$ 3,502,394 $ 11,836,441 0.30

2020 Idaho Annual Conservation Report Pg 73
Program-by-Program Summaries
Residential HVAC Program
TABLE 46 – RESIDENTIAL HVAC PROGRAM METRICS
HVAC Program Summary – Electric 2020
Participation, Savings, and Costs
Conservation projects 198
Overall kWh savings 508,131
Incentive spend $ 75,613
Non-Incentive Utility Costs $ 59,607
Idaho Energy Efficiency Rider spend $ 135,219
HVAC Program Summary – Natural Gas 2020
Participation, Savings, and Costs
Conservation projects 3,229
Overall Therm savings 266,939
Incentive spend $ 1,028,366
Non-Incentive Utility Costs $ 35,073
Idaho Energy Efficiency Rider spend $ 1,063,439
Description
Through the HVAC program, Avista encourages residential customers to select a high-efficiency solution when making
energy upgrades to their homes.
Idaho residential electric customers (Schedule 1) who heat their homes with Avista electricity are eligible for rebates
for converting their electric straight-resistance space heating to an air-source heat pump or ductless heat pump
system. Customers must demonstrate electricity usage of 8,000 kWh and natural gas usage of less than 340 therms
for replacement of electric straight-resistance to air-source heat pumps or ductless heat pumps. Ductless heat pumps
are required to demonstrate a 9.0 HSPF or greater.
There was a significant drop in electric conservation projects and savings due to the variable speed motor program
being discontinued at the end of 2019 due to it becoming standard equipment on natural gas forced air furnaces.
There were also impacts to savings because of the COVID-19 shutdown. The 2020 goal for 300 projected projects to
be completed was not met; 199 projects were completed.
Idaho natural gas customers (Schedule 101) who heat their homes with Avista natural gas are eligible for high-
efficiency natural gas forced air or wall furnaces or boilers with an energy efficiency of 90 percent AFUE or greater.
The supporting documentation required for participation includes copies of project invoices and an Air Conditioning,
Heating, and Refrigeration Institute (AHRI) certification. The prescriptive rebate approach issues payment to the
customer after the measure has been installed by a licensed contractor.
2020 Idaho Annual Conservation Report Pg 74
In 2020, the rebate was increased from $300 to $450 to promote replacement of inefficient natural gas heating
systems. This increase in incentives motivated many customers to replace their inefficient HVAC systems. Even with
the COVID-19 shutdown, furnaces were replaced at the same rate as in 2019. In the 2020 TRM, Avista had to lower
the savings for the natural gas furnace measure to 71 therms. The company will continue to encourage installations
of high-efficiency natural gas furnaces as well as smart thermostats.
Smart thermostat rebates will continue in 2020. The thermostats can be contractor- or self-installed. The thermostats
are required to be connected to the Internet and available to control from a cell phone.
Program Activities
◆Electric: Savings of 508,131 kWh in 2020, 10 percent of the overall savings achieved in Avista’s residential
portfolio. The program achieved 91 percent of its savings goal of 560,367 kWh.
◆Natural Gas: Savings of 266,939 therms in 2020 – 84 percent of the overall residential savings. The program
slightly surpassed its savings goal of 258,170 therms (103 percent of goal).
FIGURE 35 – RESIDENTIAL HVAC INCENTIVE DOLLARS BY MEASURE – ELECTRIC
For the electric HVAC program, electric furnaces to air source heat pumps comprised approximately 46 percent of
residential HVAC electric incentives. Ductless heat pumps experienced a rise in use, accounting for almost double the
incentives over 2019.
FIGURE 36 – RESIDENTIAL HVAC INCENTIVE DOLLARS BY MEASURE – NATURAL GAS
$ 37,100 Electric to Air-Source Heat Pump
$ 31,000 Electric to Ductless Heat Pump
$ 1,573 Smart Thermostat DIY with Electric Heat
$ 4,900 Smart Thermostat Paid-Install with Electric Heat
$ 1,040 Variable Speed Motor
$ 8,100 Natural Gas Boiler
$ 904,950 Natural Gas Furnace
$ 0 Natural Gas Wall Heater
$ 14,316 Smart Thermostat DIY with Natural Gas Heat
$ 101,000 Smart Thermostat Paid-Install with Natural Gas Heat
2020 Idaho Annual Conservation Report Pg 75
High-efficiency natural gas furnaces continued to provide the largest portion of natural gas savings in the residential
sector portfolio, comprising approximately 88 percent of Avista’s 2020 residential HVAC incentives. Smart thermostats
continued to be popular, with 1,269 installed in the Idaho service territory (1,199 for natural gas HVAC systems, 70
for electric HVAC systems).
Energy-efficiency marketing efforts build considerable awareness of opportunities in the home and drive customers to
the website for rebate information. Vendors generate participation using the rebate as a sales tool for their services.
Additional communication methods that encourage program participation are utility website promotion, vendor
training, retail location visits, and presentations at various customer events throughout the year.
In 2020, Avista program managers kept in regular contact with trade allies via topical, focused email blasts. These
blasts notified trade allies of upcoming program changes and deadlines. Avista program managers also held two trade
ally engagement events – in person and via webinars – to review program changes, encourage participation, and
answer trade ally questions. Trade ally engagement continues to be a core marketing strategy for this program.
The program was included on the “Way to Save” advertising campaign to increase awareness and drive program
participation. See pages 58-63.
Impact Evaluation
The ADM impact evaluation team found a 101 percent realization rate for the electric HVAC program and a 131
percent realization rate for the natural gas HVAC program in 2020.
The evaluators applied the results of the billing analysis to each electric variable speed motor measure. They reviewed
the Avista TRM values along with verified tracking data to estimate net program adjusted savings for measures not
evaluated through billing analysis. In addition, the evaluators reviewed and applied the current RTF UES values for the
electric measures along with verified tracking data to estimate net program verified savings for this measure.
The electric smart thermostat DIY with electric heat realization rate is low because the Avista TRM uses an average of
retail and direct installation savings values as well as an average across heating types, while the evaluators assigned
the appropriate RTF UES value for each installation type and heating zone. The appropriate categories in the RTF led
to a lower-than-expected savings for the retail rebates and a higher-than-expected savings for the direct installation
rebates for this measure. In addition, the 93.33 percent ISR was applied to the electric smart thermostat with electric
heat measure, further decreasing the realization rate for the measure.
The electric to ductless heat pump rebates have high realization rates because the expected savings value used a value
differing from the RTF values. The value in the TRM for this measure most likely represents an average of the RTF
savings values for a combination of heating zones. The electric variable speed motor program has a high realization
rate due to the relatively higher unit-level energy savings from the billing analysis as opposed to the Avista TRM.
2020 Idaho Annual Conservation Report Pg 76
Recommendations
ADM offered the following recommendations for Avista’s residential HVAC programs, in addition to the overall
recommendations for the residential sector listed on page 71:
◆The evaluators conducted a billing analysis for the electric variable speed motor measure in the HVAC
program. The estimated savings value from the billing analysis was roughly 124 percent of the value reflected
in the Avista TRM. The evaluators recommend updating the savings value for this measure in the Avista TRM
to reflect observed savings more closely in the territory.
◆The natural gas furnace measure in the HVAC has a high realization rate because the billing analysis resulted
in a savings value that was 137.45 percent of the value previously used in the Avista TRM. The evaluators
recommend adjusting the Avista TRM to reflect the observed savings values from all billing analyses from this
impact evaluation.
Program Marketing
The program was included in the “Way to Save” advertising campaign to increase awareness and drive program
participation. See pages 58-63.
Plans for 2021
Air-source heat pumps will have an energy efficiency requirement of 9.0 HSPF and ductless heat pumps will have a
requirement of 10.0 HSPF.
Smart thermostat rebates will be promoted through an increased incentive. Contractor-installed thermostats will
increase from $100 to $150. Self-installed thermostats will increase from $75 to $125. In 2021, the new multifamily
rebate program will be offering a $20 rebate for line voltage digital and smart thermostats.
Avista will consider updating savings values for the natural gas furnace measure, per ADM’s recommendation. The
variable speed motor measure will be discontinued from Avista’s offerings in 2021, due to energy code changes.
Avista will also examine the rebate process and seek ways to improve accuracy and completeness of submitted
information.
2020 Idaho Annual Conservation Report Pg 77
Residential Shell Program
TABLE 47 – RESIDENTIAL SHELL PROGRAM METRICS
Shell Program Summary – Electric 2020
Participation, Savings, and Costs
Conservation projects 119
Overall kWh savings 358,972
Incentive spend $ 78,703
Non-Incentive Utility Costs $ 113,867
Idaho Energy Efficiency Rider spend $ 192,570
Shell Program Summary – Natural Gas 2020
Participation, Savings, and Costs
Conservation projects 285
Overall Therm savings 12,000
Incentive spend $ 156,016
Non-Incentive Utility Costs $ 4,148
Idaho Energy Efficiency Rider spend $ 160,163
Description
Through the shell program, Avista encourages residential customers to improve their home’s shell or exterior by
upgrading insulation, windows, and storm windows. This prescriptive rebate approach issues payment to the
customer after the measure has been installed. Energy-efficiency marketing efforts build considerable awareness of
opportunities in the home and drive customers to the website for rebate information. Vendors generate participation
using the rebate as a sales tool for their services. Additional communication methods that encourage program
participation include utility website promotion, vendor training, and presentations at customer events.
Idaho residential electric customers (Schedule 1) who heat their homes with Avista electric are eligible to apply, as
are Idaho residential natural gas customers (Schedule 101) who heat their homes with natural gas. Avista will review
energy usage as part of the program eligibility requirements. In Idaho, Avista fuel-heated primary residences with
electric- heated homes must demonstrate a heating season usage of 8,000 kWh; those with natural gas-heated
homes must demonstrate a heating season usage of 340 therms. Windows and insulation are required to be installed
by licensed contractors. The rebate is calculated by square feet of windows or insulation.
Windows must have a U-factor rating of 0.30 or lower (encourages .29 or less U-factor). Storm windows (interior/
exterior) must be new, the same size as the existing window, and not be in direct contact with the existing window;
exterior window low-e coating must be facing the interior of the home. Glazing material emissivity must be less than
0.22 with a solar transmittance greater than 0.55.
2020 Idaho Annual Conservation Report Pg 78
Avista provides rebates for insulation of attics, walls, and floors that are between conditioned and unconditioned
primary living space. Attic rebates require an existing R-value of R-11 or less and brought up R-49 or greater. Wall
insulation requires no existing insulation and brought up to R-11 or greater. Floor insulation requires no existing
insulation and brought up to R-19 or greater.
Program Activities
◆Electric: Savings of 358,972 kWh in 2020 (7 percent of the overall residential savings), a 223 percent increase
over the 160,507 kWh achieved in 2019. The program achieved 142 percent of its goal of 252,475 kWh.
◆Natural Gas: Savings of 12,000 therms in 2020, or 4 percent of the overall residential savings. The program
had a 31 percent decrease in savings relative to the of 17,458 therms achieved in 2019, achieving 28 percent
of its goal of 42,334 therms.
The savings derived from the Residential Shell program for both natural gas and electric homes are primarily attributed
to single-pane window replacements.
Shell program participants have generally been inclined to replace existing windows with regular windows rather than
with storm windows.
Impact Evaluation
ADM arrived at a 174 percent realization rate of savings for prescriptive shell rebate measures in electric homes and
59 percent for rebate measures in homes with natural gas.
The realization rate for the electric savings in the Shell program deviates from 100 percent due to the differences
between the categories applied in the Avista TRM prescriptive savings values and the more detailed categories present
with unique RTF UES values.
The realization rate for gas savings in the Shell program had significant deviation from 100 percent because of low
realization rates for two measures: window replacement and attic insulation. Both of these measures had a statistically
significant difference between the billing analysis done by ADM and the RTF values the program used to calculate
savings.
The evaluators found no duplicate rebates in the project data and therefore did not remove any rebates from verified
savings. However, ADM’s document review did illuminate some discrepancies for residential shell projects:
◆In one instance, square footage quantity in the rebate application did not match the values presented in the
project data for attic insulation.
◆Two rebates showed R-values that did not align with TRM or RTF values related to the measure.
◆For one floor insulation rebate, the new R-value did not match TRM or RTF values.
◆In several instances, web-based rebate data indicated electric space heating, but other sources (project data
and document verification) indicated natural gas space heating, and vice versa.
◆In one instance, R-values for a window were assigned incorrectly. Evaluators reassigned window insulation on
this project from an insulation of R0 to R49 to an insulation of R11 to R49.
2020 Idaho Annual Conservation Report Pg 79
Recommendations
In addition to the recommendations offered in the overall residential impact evaluation (noted on page 71), ADM
offered the following recommendations for the Residential Shell program:
◆The evaluators found rebates in which the R-values did not align with TRM or RTF values (R38 and R64). They
recommend collecting information in a standardized manner.
◆The evaluators recommend collecting information on single/double-pane windows of the baseline windows
and class of the efficient windows in order to correctly assign RTF UES values.
◆The evaluators also recommend collecting information on single-family/multi-family/manufactured in the web
rebate form. This allows them to accurately assign RTF values. The mail-in rebates collect this information;
it does not seem to be required to complete the rebate, however, since many rebates are missing this
information.
◆The evaluators recommend verifying the household space heating type prior to completing the rebate.
Program Marketing
The program was included in the “Way to Save” advertising campaign to increase awareness and drive program
participation. See pages 58-63.
Plans for 2021
Avista plans to adjust the U-factor requirement to 0.29 or lower, following the RTF required efficiency revision. In
2021, the new multifamily rebate program will be offering insulation, storm windows, and windows with the same
requirements as the residential program but without a usage requirement. Small homes can use this multifamily
program as well. There may be changes mid-2021, such as adding measures and adjusting savings and incentives.
Avista will also examine the rebate process and seek ways to improve accuracy and the completeness of submitted
information.
2020 Idaho Annual Conservation Report Pg 80
Residential Water Heating Program
TABLE 48 – RESIDENTIAL WATER HEATING PROGRAM METRICS
Water Heating Program Summary – Electric 2020
Participation, Savings, and Costs
Conservation projects 10
Overall kWh savings 12,986
Incentive spend $ 2,365
Non-Incentive Utility Costs $ 1,002
Idaho Energy Efficiency Rider spend $ 3,367
Water Heating Program Summary – Natural Gas 2020
Participation, Savings, and Costs
Conservation projects 507
Overall Therm savings 37,976
Incentive spend $ 195,800
Non-Incentive Utility Costs $ 4,982
Idaho Energy Efficiency Rider spend $ 200,782
Description
Idaho electric customers (Schedule 1) who heat their homes with Avista electric or natural gas may be eligible for a
rebate for the installation of a high-efficiency electric heat pump water heater (≥1.8 UEF) , natural gas tankless water
heater (≥ 0.82 UEF), or natural gas high-efficiency 55-gallon or less water heater (≥0.65 UEF). Efficiencies for space-
and water-heating equipment are verified according to the contractor invoice or the Air-Conditioning, Heating, and
Refrigeration Institute (AHRI).
Program Activities
◆Electric: Savings were 12,986 kWh in 2020, a 12 percent decrease over the 14,763 kWh of savings achieved
in 2019. Savings accounted for less than 1 percent of the residential portfolio.
◆Natural Gas: Overall therm savings were 37,976, an increase of 121 percent over savings of 17,131 therms
in 2019. Savings accounted for 12 percent of the residential portfolio and the program achieved 96 percent
of its savings goal of 39,436 therms.
Program Changes
There were no program changes for 2020.
2020 Idaho Annual Conservation Report Pg 81
Impact Evaluation
ADM arrived at a realization rate of 111 percent for the residential electric water heating program and 100 percent
for the natural gas program.
The realization rate for the electric savings in the Water Heat program deviates from 100 percent due to the Avista
TRM prescriptive savings value. The Avista TRM assigns a combination of the values the RTF assigns for Tier 2 and Tier
3 heat pump water heaters. However, among document verification, the evaluators found a majority of water heaters
to be Tier 3 or higher, which the RTF UES assigns a higher savings value.
The evaluators found all Water Heat program rebates to have completed rebate applications with the associated water
heater model number and efficiency values filled in either the CC&B web rebate data or mail-in rebate applications.
The evaluators also found that all sampled rebate equipment met or exceeded the measure efficiency requirements
for the Water Heat program.
The evaluators did note the following discrepancies:
◆In some instances, the CC&B web rebate data does not reflect the same values found in the mail-in rebate
applications and/or invoices or AHRI certification documents submitted with the rebate application. For
example, 10 of the 111 sampled rebates were not found in the CC&B dataset. A number of the sampled
rebates were found to have discrepancies in model numbers between the CC&B data and the mail-in rebate
applications and/or invoices.
◆Not all rebates were accompanied with AHRI certification.
◆The evaluators found one rebate that indicated a quantity of two, but expected savings assigned to the
rebate aligned with a quantity of one. The evaluators applied the sampled realization rate to the expected
savings value; therefore, the rebate was assigned the savings of one unit of equipment.
Recommendations
◆The evaluators recommend that Avista work to improve methods for collecting mail-in rebate application
information to reconcile the CC&B database.
◆In order to acquire accurate equipment efficiencies and tank sizes, AHRI certifications are recommended to be
required and submitted with the rebate application, with an invoice that matches the model number found in
the AHRI certification.
◆The evaluators recommend correcting for instances where quantity is greater than one and savings is
equivalent to one measure.
Program Marketing
The program was included in the “Way to Save” advertising campaign to increase awareness and drive program
participation. See pages 58-63.
2020 Idaho Annual Conservation Report Pg 82
Plans for 2021
Avista plans to continue offering water heater rebates in 2021. Avista will also examine the rebate process and seek
ways to improve accuracy and the completeness of submitted information.
Residential ENERGY STAR Homes Program
TABLE 49 – RESIDENTIAL ENERGY STAR HOMES PROGRAM METRICS
ENERGY STAR Homes Program Summary – Electric 2020
Participation, Savings, and Costs
Conservation projects 16
Overall kWh savings 50,705
Incentive spend $ 6,500
Non-Incentive Utility Costs $ 7,052
Idaho Energy Efficiency Rider spend $ 13,552
ENERGY STAR Homes Program Summary – Natural Gas 2020
Participation, Savings, and Costs
Conservation projects 3
Overall Therm savings 402
Incentive spend $ 1,950
Non-Incentive Utility Costs $ 69
Idaho Energy Efficiency Rider spend $ 2,019
Description
The ENERGY STAR Manufactured Homes program takes advantage of the regional and national effort surrounding
the U.S. Department of Energy and U.S. Environmental Protection Agency’s ENERGY STAR label. Avista and partnering
member utilities of NEEA have committed significant resources to develop and implement this program to set
standards, train contractors, and provide third-party verification of qualifying homes. NEEA, in effect, administers the
program and Avista pays the rebates for homes that successfully complete the process and are labeled ENERGY STAR.
In addition, after the launch of NEEA’s regional effort, the manufactured homes industry established manufacturing
standards and a labeling program to obtain ENERGY STAR-certified manufactured homes. While the two approaches
are unique, they both offer 15-25 percent savings versus the baseline.
The ENERGY STAR Manufactured Homes program promotes a sustainable, low operating cost, environmentally
friendly structure as an alternative to traditional manufactured home construction. In Idaho, Avista offers both electric
and natural gas energy-efficiency programs, and, as a result, has structured the program to account for homes where
either a single fuel or both fuels are used for space and water heating needs. Avista continues to support the regional
program to encourage sustainable building practices.
2020 Idaho Annual Conservation Report Pg 83
Idaho residential electric customers (Schedule 1) with a certified ENERGY STAR home or ENERGY STAR/ECO-rated all-
electric manufactured home are eligible. Idaho residential electric customers (Schedule 1) with a NEEM-certified home
that has Avista electric and Avista residential natural gas (Schedule 101) for space and water heating are eligible.
A certified ENERGY STAR manufactured home with Avista electric or natural gas only or both Avista electric and
natural gas service provides energy savings beyond code requirements for space heating, water heating, shell
measures, lighting, and appliances. Space-heating equipment can be either electric forced air or electric heat pump,
or a natural gas furnace. This rebate may not be combined with other Avista individual measure rebate offers (such as
high-efficiency water heaters).
Program Activities
◆Electric: Savings were 50,705 kWh in 2020, far surpassing the program’s goal of 6,630 kwh. Still, the
program accounted for 1 percent of the residential electric savings portfolio.
◆Natural Gas: Savings were 402 therms in 2020, with three projects overall (one natural gas, two natural gas
and electric combined), less than 1 percent of the residential gas savings portfolio.
The 2020 incentive for ENERGY STAR manufactured homes was $650 per unit for electric only (and natural gas and
electric customers). The gas-only customer rebate was $400 in 2020.
Impact Evaluation
Evaluators arrived at a realization rate of 102 percent for the electric ENERGY STAR Homes Program and 100 percent
for the natural gas program.
The realization rate for the electric program deviated slightly from 100 percent due to the categorical differences
between the applied Avista TRM prescriptive savings value and the more detailed RTF UES categories. The Avista TRM
applies RTF savings values from heating zone 2 to all rebates. In addition, the Avista TRM does not take into account
cooling zone, which also affects savings assigned in the RTF. The evaluators applied the appropriate RTF savings values
for the heating zone and cooling zone for each rebated household. This change led to low realization rates for some
rebates and high realization rates for others within the same Avista ENERGY STAR Home – Manufactured Furnace
measure category. The overall effect this change had on the measure is an upward adjustment on savings.
The evaluators found no significant or notable discrepancies in the project data and rebate documentation for the
rebates in the Idaho electric service territory.
Recommendations
The evaluators note that the realization for the ENERGY STAR Home – Manufactured, Natural Gas & Electric measure
is low because the Avista TRM savings was employed using an additive methodology between a gas-heated home
and an electric-heated home for the electric savings. However, the evaluators reviewed the RTF and determined
manufactured home electric savings for a fully natural gas-heated home would be closer to the savings a gas-heated
home with electricity would save. The evaluators recommend adjusting Avista TRM electric savings for this measure to
reflect the RTF values associated with a fully natural gas-heated home at 43 kWh saved per year.
2020 Idaho Annual Conservation Report Pg 84
Program Marketing
The program was included in the “Way to Save” advertising campaign to increase awareness and drive program
participation. See pages 58-63.
Plans for 2021
Avista plans to continue to offer the ENERGY STAR Homes program in 2021. The 2021 incentive for ENERGY
STAR manufactured homes will be increased to $1,000 per unit for both electric only and natural gas and electric
customers. The gas-only customer rebate will be increased to $600 in 2021. Avista also plans to update the RTF value
for ENERGY STAR homes measures in the TRM per ADM’s recommendation.
Residential Fuel-Efficiency Program
TABLE 50 – RESIDENTIAL FUEL-EFFICIENCY METRICS
Fuel-Efficiency Program Summary – Fuel Efficiency 2020
Participation, Savings, and Costs
Conservation projects 95
Overall kWh savings 635,962
Incentive spend $ 225,600
Non-Incentive Utility Costs $ 115,185
Idaho Energy Efficiency Rider spend $ 340,785
Description
The Fuel-Efficiency program rebate encourages customers to consider converting their resistive electric space and
water heating to natural gas. The direct use of natural gas continues to be the most efficient fuel choice when
available, and, over time, offers the most economic value in terms of the operating costs of the equipment. Since the
early 1990s, Avista has offered a conversion rebate. While natural gas prices have risen slowly in recent years, the cost
of infrastructure continues to rise at a faster pace, both for the utility and for customers’ installation costs for these
conversions. Avista provides incentives for customers switching from electric resistance heat to a natural gas forced air
furnace – or a combination conversion rebate for water heater and natural gas furnaces.
The company pays this prescriptive rebate upon the measure installation and receipt of all relevant documentation.
Customers’ minimum qualifications include using Avista electricity for electric straight-resistance heating or water
heating, which is verified by evaluating their energy use. Residential electric customers (Schedule 1) in Idaho who
heat their home or water with Avista electricity may be eligible for a rebate for converting to natural gas. The home’s
electric baseboard or furnace heat consumption must indicate a use of 8,000 kWh or more during the previous
heating season (and less than 340 therms).
In 2020, the conversion for electric heat to natural gas forced air or boiler heat was $2,100. The conversion from
electric heat to natural gas forced air heat and water heat combination was $2,850.
2020 Idaho Annual Conservation Report Pg 85
Program Activities
The Fuel-Efficiency program obtained 635,962 kWh of savings in 2020, which is a decrease of 46 percent from the
1,181,596 kWh achieved in 2019. Savings from this program accounted for 12 percent of the residential electric
savings portfolio.
Fifty-nine of 95 customers used the electric furnace to natural gas furnace measure, with the remaining 36 using
the combination measure (natural gas furnace and water heat). The decline in savings was due in part to a lower
realization rate than in previous years.
Program Changes
TRM values for this program were changed in accordance with Cadmus recommendations.
Impact Evaluation
ADM arrived at a realization rate of 82 percent for the residential Fuel-Efficiency program. Evaluation methods for
this program included a database review and document verification, verification surveys, and a billing analysis. The
realization rate for the electric savings deviate from 100 percent due to the differences between the applied Avista
TRM prescriptive savings value and the billing analysis and true Avista TRM value. The evaluators found one rebate
was duplicated in the project data for the electric to natural gas furnace measure. ADM removed this instance from
the verified savings for the program. In addition, the 93.33 percent survey in-service rate applied to the combination
conversion measure further decreased the realization rate for the measure and program overall.
Recommendations
In addition to the recommendations in the residential programs section on page 71, ADM offered the following
recommendations for the Fuel-Efficiency program:
◆Evaluators recommend Avista collect efficiency values on the rebate application for conversion measures,
not just HVAC measures. Customers can get rebates for a conversion but also not apply for an HVAC rebate
(HVAC rebates do ask for the efficiency on the application).
◆The evaluators found the CC&B data does not contain manufacturer information. The evaluators recommend
this as an input in the CC&B data. The electric to natural gas furnace & water heat measure CC&B data
does not detail both the furnace and the water heater model number and manufacturer details. Instead,
it contains only the furnace or only the water heater equipment. The evaluators recommend collecting
equipment manufacturer, model number, and efficiency for the combination measures.
Program Marketing
Energy-efficiency marketing efforts build considerable awareness of opportunities in the home and drive customers to
the website for rebate information. Vendors generate participation using the rebate as a sales tool for their services.
Additional communication methods that encourage program participation and utility website promotion include
vendor training, retail location visits, and presentations at various customer events throughout the year.
2020 Idaho Annual Conservation Report Pg 86
The program also took advantage of the “Way to Save” advertising campaign to increase awareness and drive
program participation. See pages 58-63.
Plans for 2021
There were no changes made for the program in 2021. Avista will consider ADM’s recommendations to expand
information collected on the rebate form to include efficiency values and manufacturer information.
Residential Simple Steps, Smart Savings Program
TABLE 51 – RESIDENTIAL SIMPLE STEPS, SMART SAVINGS PROGRAM METRICS
Simple Steps, Smart Savings Program Summary – Electric 2020
Participation, Savings, and Costs
Conservation measures 235,575
Overall kWh savings 2,968,563
Incentive spend $ 214,050
Non-Incentive Utility Costs $ 262,550
Idaho Energy Efficiency Rider spend $ 476,600
Simple Steps, Smart Savings Program Summary – Natural Gas 2020
Participation, Savings, and Costs
Conservation measures 1,129
Overall Therm savings 234
Incentive spend $ 0
Non-Incentive Utility Costs $ 0
Idaho Energy Efficiency Rider spend $ 0
Description
Avista collaborates with BPA on Simple Steps, Smart Savings, a regional program designed to increase the adoption
of energy-efficient residential products. To achieve energy savings, residential consumers are encouraged to purchase
and install high-quality LEDs, light fixtures, energy-saving showerheads, and ENERGY STAR appliances. Lighting and
showerhead programs are offered only in Idaho.
Simple Steps, Smart Savings continues to provide the region’s best opportunity to collectively influence both retail
stocking practices and consumer purchasing. There continue to be opportunities for efficient lighting improvements
in customer residences, as many residential lighting sockets are still occupied by inefficient bulbs. Incentives also
encourage customers to increase efficiency before burn-out of the existing less-efficient lighting. Energy savings
claimed are based on BPA deemed savings values.
2020 Idaho Annual Conservation Report Pg 87
Program Activities
◆Electric: Savings were 2,968,563 kWh in 2020, far surpassing the program’s goal of 661,531 kWh. Savings
accounted for 56 percent of all residential electric savings.
◆Natural Gas: Savings were 234 therms in 2020, less than 1 percent of the residential gas savings portfolio.
The key to delivering on the objectives of this program are the incentives to encourage customers’ interest
and marketing efforts to drive them to using the program. The model used for lighting and showerheads uses
manufacturer partnership to buy down costs of products and allow for greater flexibility on how money is used
(markdowns and/or marketing).
CLEAResult is contracted by Avista to provide the manufacturer and retail coordination. They are responsible for
coordinating program marketing efforts, performing outreach to retailers, ensuring that the proper program tracking
is in place, and coordinating all implementation aspects of the program. Big-box retailers, in addition to select regional
and national mass-market chains, are the primary recipient of the product and typically offer a variety of the Simple
Steps, Smart Savings products at their locations. These products are clearly identified with point-of-purchase tags.
Lighting product savings decreased slightly in 2020 over 2019 as demand for LEDs reached its peak and the program
was terminated at the end of Q3. The lowest lumen (250-1049) general purpose LED lamp continued to yield the
largest savings for Avista. Savings for showerhead products increased drastically from 2019 while savings for clothes
washers was nearly nonexistent.
While the pandemic continued to have a significant impact on the economy and consumer trends, the Simple Steps,
Smart Savings lighting and showerhead programs saw a quick rebound in sales at home improvement stores likely
because of an uptick in DIY projects while Avista’s customers were home. Clothes washers, on the other hand, were
affected dramatically as one of the two retail participants closed its doors permanently and the other offered curbside
pickup services only throughout most of 2020.
2020 Idaho Annual Conservation Report Pg 88
FIGURE 37 – RESIDENTIAL SIMPLE STEPS, SMART SAVINGS PROGRAM – LIGHTING KWH SAVINGS

FIGURE 38 – RESIDENTIAL SIMPLE STEPS, SMART SAVINGS PROGRAM – SHOWERHEADS SAVINGS
600,000
500,000
400,000
200,000
Jan
2019 2020
Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
300,000
100,000
Li
g
h
t
i
n
g

k
W
h

S
a
v
i
n
g
s
0
El
e
c
t
r
i
c
i
t
y

S
a
v
i
n
g
s

(
k
W
h
)
kWh Therms
1,200
2018 2020
1,100
600
300
200
100
0
2019
Sh
o
w
e
r
h
e
a
d
s
20,000
14,000
10,000
8,000
6,000
4,000
2,000
0
900
400
700
500
16,000
12,000
18,000
Units
1,000
800
2020 Idaho Annual Conservation Report Pg 89
FIGURE 39 – RESIDENTIAL SIMPLE STEPS, SMART SAVINGS PROGRAM – CLOTHES WASHERS KWH SAVINGS
Program Changes
Incentives and savings decreased in 2020 for lighting and showerhead products and remained stable for clothes
washers.
TABLE 52 – RESIDENTIAL SIMPLE STEPS, SMART SAVINGS PROGRAM INCENTIVES CHANGES
Product Category Incentive Per Unit
2020 2020
LED Bulb $ 0.50-3.00 $ 0.50-2.00
LED Fixture $ 0.50-4.00 $ 0.50-2.00
Showerhead $ 2.00-6.00 $ 2.00
Clothes Washer $ 25.00 $ 25.00
Ele
c
t
r
i
c
i
t
y

S
a
v
i
n
g
s

(
k
W
h
)
kWh Units
120
2018 2020
60
40
20
0
2019
Cl
o
t
h
e
s

W
a
s
h
e
r
s
14,000
8,000
4,000
2,000
0
80
100
10,000
6,000
12,000
2020 Idaho Annual Conservation Report Pg 90
Program Marketing
Table 93 is a monthly chart of Simple Steps, Smart Savings program marketing and field activities indicating when the
activity was deployed or took place.
TABLE 53 – RESIDENTIAL SIMPLE STEPS, SMART SAVINGS PROGRAM MARKETING ACTIVITIES
Deliverable JAN FEB MAR APR MAY JUN JUL AUG SEP OCT
Program Activities
Annual report ✔✔
Paid placement ✔
Shelf survey ✔
Final program report ✔✔
Marketing Activities
Partner promotions ✔✔✔✔✔
EFX conference ✔
Brand awareness ✔✔✔✔
Retail collateral ✔✔✔✔✔✔✔✔✔
Field Activities
Lighting events ✔✔✔✔✔✔✔
Appliance events ✔✔✔✔
Shelf survey data collection ✔
Customer Satisfaction
As the Simple Steps, Smart Savings field representatives sunsetted each store toward the end of Q3, they collected
comments and feedback from store associates. Those interviewed mentioned that the program worked well in driving
customers to LEDs and the customers really appreciated the lighting discounts. The associates also noted they will miss
having the program in place as it was beneficial to their overall sales.
The implementer responded to the COVID-19 pandemic thoughtfully, which enabled the program
to continue to perform well despite the circumstances until its termination in September 2020. The
implementer let retailers permit or deny store visits from implementation field staff, allowed field staff the flexibility to
reschedule store visits, and conducted virtual store visits to educate store associates about the program and products
(such as LEDs) like it typically would. Avista and the implementer also scaled back marketing and outreach efforts and
allowed each retail location to tailor marketing, including point-of-purchase materials provided by the implementer, to
their individual needs.
2020 Idaho Annual Conservation Report Pg 91
Avista observed unexpectedly low throughput for clothes washers, which the implementer attributed
to the challenge it faced when recruiting retail locations to participate. Despite showing a willingness to
participate, some retail locations for franchised and individually owned stores like Ace Hardware could not offer
program rebates because of a lack of communication/direction from their corporate offices. Thus, fewer retailers
offered buy-down for clothes washers, and fewer customers obtained clothes washer rebates. This is useful feedback
for Avista as it considers potential midstream appliance programs in the future.
Cadmus’ process evaluation found that retailers were generally appreciative of their opportunity to participate in
Simple Steps, Smart Savings and saddened to learn of the program’s discontinuation. Per the implementer, retailers
complimented the program as a “selling tool” and “a good way to get customers looking at more-efficient products.”
Impact Evaluation
The Simple Steps, Smart Savings program had a realization rate of 94 percent for electric measures, accounting for 56
percent of residential evaluated savings. The realization rate for gas measures in the program was 100 percent.
2020 Idaho Annual Conservation Report Pg 92
Plans for 2021
For 10 years, Simple Steps, Smart Savings has been a source of significant savings for Avista. In 2019 it became clear
that the lighting market has transformed drastically over the years in part to retail incentive programs. Where once
only inefficient products lined the shelves, energy-efficient products now account for 75 percent of lighting on shelves
in the Northwest. As a result of this transformation, the Simple Steps, Smart Savings program was terminated on
September 30, 2020 per the following activity schedule:
TABLE 54 – RESIDENTIAL SIMPLE STEPS, SMART SAVINGS PROGRAM PHASE-OUT
August September October
Program
Utility communication – program ending + next
steps ✔✔
Partner communication ≠ program ending +
submission deadline ✔✔
Final monthly invoices and program reports to
utilities and BPA ✔
Final annual program report to BPA ✔
Life of program report – 1st draft to BPA ✔
Life of program report – 2nd draft to BPA ✔
Life of program report – final to BPA ✔
Final annual NPS reports to BPA ✔
Historical program date and files to BPA ✔✔✔
Field
Store Communication – program ending +
remove POP – Tier 3 ✔✔
Store Communication – program ending +
remove POP – Tier 2 ✔✔
Store Communication – program ending +
remove POP – Tier 1 ✔
Marketing
Website disabled ✔
Temporary website messaging displayed ✔✔✔✔
2020 Idaho Annual Conservation Report Pg 93
Residential Multifamily Direct Install Program and Supplemental Lighting
TABLE 55 – RESIDENTIAL MULTIFAMILY DIRECT INSTALL PROGRAM AND SUPPLEMENTAL LIGHTING PROGRAM METRICS
Multifamily Direct Install Program Summary – Electric 2020
Participation, Savings, and Costs
Measures installed 16,925
Overall kWh savings 747,227
Incentive spend $ 278,555
Non-Incentive Utility Costs $ 167,397
Idaho Energy Efficiency Rider spend $ 445,952
a) The MFDI has been tracked by total measures installed which include LED lamps, faucet aerators, showerheads, smart strips, pipe wrap, and other measures.
Description
The MFDI program is designed to help hard-to-reach customers save energy. Field installers coordinate with property
managers of multifamily complexes of five units or more to directly install small energy savers in tenant units such as
LED lamps, faucet aerators, showerheads, and smart power strips, as well as vending misers in common areas. During
the first site visit with properties, installers audit the complex not only for tenant needs, but also for any eligible
common area lighting, which would include stairwell lighting used 24/7, exterior lamps and fixtures on a daylight
sensor, and conversions from interior fluorescent T12s and T8s to LED used 24/7. Direct installations are completed
at the complex and the supplemental lighting information is passed on to lighting contractors contracted to work in
various areas. Lighting contractors communicate with the property managers to audit and put together project data
that is sent to SBW and Avista to ensure the project is cost-effective, after which the project is completed.
Program Activities
◆Electric: Savings were 747,227 kWh in 2020, achieving 58 percent of the program’s goal of 1,289,000 kWh.
Savings accounted for 58 percent of all residential electric savings.
During 2020, the response to the COVID-19 pandemic caused disruption to the MFDI program’s direct-installation
design, forcing the third-party implementer to temporarily halt program processes. In late August 2020, supplemental
lighting contractors were allowed to complete projects with exterior lighting measures only. The program also
experimented with a couple of non-contact or low-contact delivery methods, including a tote drop-off method,
in which tote bags including predetermined numbers of lamps, showerheads and aerators, as well as program
information, were delivered to residents in multifamily communities. A second method used on-site facility managers
that were willing to help tenants install these products. Despite employing these innovative approaches, the MFDI and
MFDI supplemental lighting programs did not meet savings goals, with reported savings achieving 55 percent of the
savings goal for MFDI programs.
Program Changes
The program did not have any measure changes in 2020.
2020 Idaho Annual Conservation Report Pg 94
Program Marketing
This program is marketed by Avista and SBW, and by property managers through word-of-mouth. Avista tries to
manage the program pipeline to provide a timely scheduling process.
FIGURE 40 – RESIDENTIAL MULTIFAMILY DIRECT INSTALL PROGRAM FLYER
Customer Satisfaction
Cadmus evaluated MFDI processes and shared the following findings with Avista:
Collaborative relationships between Avista and the program implementer allowed new delivery
methods and future implementation techniques to be conceptualized quickly in response to COVID-19.
Open communication between the implementer and property managers ensured the quick dissemination of new
implementation information to maintenance staff and tenants allowing the program to continue in 2020 despite
challenges due to the pandemic.
◆In response to continued COVID-19 restrictions, Avista and implementer staff developed a contactless delivery
method.
◆Due to low uptake in the first post-COVID-19 implementation phase, Avista and the implementer adjusted
the program to increase participation and measure installation by limiting measures and working with
property managers.
How?
Replacing Light Bulbs
1) turn off the light at the switch
2) remove only old compact fluorescent or incandescent light bulbs
3) place new LED light bulb into the socket
4) gently turn clockwise until it stops
5) turn on the light at the switch
Replacing Showerheads
1) turning counterclockwise, remove the old showerhead (use an adjustable wrench if necessary)
2) remove the old gaskets
3) clean the pipe threads and wrap clockwise with the provided Teflon tape
4) make sure the new showerhead has a gasket inside
5) install the new shower head by turning clockwise, carefully tightening by hand
6) turn the shower on and check for leaks
Replacing Faucet Aerators
1) turning counterclockwise, remove the old faucet aerator (use an adjustable wrench if necessary)
2) remove the old gaskets
3) if the spout has inside threads, use both included gaskets (thin gasket closest to the aerator,
thick gasket on top)
4) if the spout has outside threads, use the thin gasket only
5) install new aerator by turning clockwise, carefully tightening by hand
6) turn the faucet on and check for leaks
What should I do with my old products?
We’ve included a black plastic return bag in your tote. Please place your old light bulbs, showerheads, and
faucet aerators in that bag. If you didn’t install all the products provided, please place the unused products in
the return bag.
The return bag will be picked up by your Avista representative on: _______________________________2020
If you have any questions, please contact us. We’ve attached your representative’s business card to this form.
Thank you for participating in this Avista Energy Efficiency Program!
FREE Energy Conservation Products for Multifamily Units
Why?
Your property management team is participating in the Avista Multifamily Direct Install Program – which means
Avista is providing you with free energy-saving equipment that can help you lower your utility bills.
What?
This program is an equipment exchange program. Replacing your incandescent light
bulbs with LEDs is quick and easy – not to mention smart. LEDs use about 90 percent less
electricity than incandescent light bulbs. And while incandescents lose much of their energy
to heat – leading to increased fire risk – LEDs are cool to the touch. LEDs can also last up to
50 times longer than incandescents and compact fluorescents. If you already have an LED,
please don’t replace it. Just return the new one with your replaced items.
Another great way to save energy is to start in your shower. A few years ago, showerheads delivered about
3-5 gallons of water per minute (GPM). Today’s low-flow, energy-efficient showerheads use only 2.5 GPM or
less – while maintaining water pressure. If you already have a showerhead with a flow rate below 1.75 GPM,
please don’t replace it. Just return the new one with your replaced items.
Faucet aerators in bathroom and kitchen sinks can also save both water and energy. We’ve provided a 1.5 GPM
swivel aerator for your kitchen and 1.0 GPM fixed aerator for your bathroom.
Turn the page for more information!
Replace these light bulbs
2020 Idaho Annual Conservation Report Pg 95
Property managers were satisfied with the program but suggested some tenants were not satisfied with
all the measures included in the program. Additionally, some tenants did not install measures that were difficult to
install or for which they did not have appropriate tools.
◆Four of five property managers were very satisfied with their MFDI program experience overall.
◆Two property managers reported tenants were not satisfied with faucet aerators and kitchen aerators due to
low water pressure and appearance while three property managers reported tenants were dissatisfied with
showerheads due to restricted water flow.
◆One property manager reported that tenants participating in Phase 1 were not at all satisfied with installation
and educational materials provided by Avista.
The reliance of current data tracking on tenants’ willingness to return uninstalled or unused equipment,
together with low recovery rates, may be a contributing factor to minor inconsistencies in measure-level
data.
◆The drop-off delivery phases relied heavily on documentation filled out by maintenance staff and tenants
detailing the location and type and quantity of both installed and removed measures. The implementer noted
during the drop-off phases difficulty in tracking measure installation locations in tenants’ units without the
presence of a field technician to document measure implementation.
Cadmus made the following recommendations to improve processes and customer satisfaction for the program:
◆If the MFDI program continues to request that tenants install measures directly, consider offering an
additional incentive such as an entry in a drawing for returning measures that are not installed and for
providing information on installed measures and their location.
◆If the MFDI program continues to operate using the drop-off delivery method which requires tenants to install
measures directly, continue focusing on simple and easy-to-install measures like LEDs. Provide easy-to-follow
installation instructions and remind tenants of the benefits of installation in the program materials.
Impact Evaluation
Overall, Cadmus found that the MFDI program is an efficient, effective mechanism for installing high-efficiency
lighting and aerators in multifamily units.
TABLE 56 – RESIDENTIAL MULTIFAMILY DIRECT INSTALL PROGRAMS ELECTRIC IMPACT FINDINGS
Program Reported Electric
Savings (kWh)
Adjusted Electric
Savings (kWh)Realization Rates
Multifamily Direct Install 510,265 542,451 106%
Multifamily Direct Install Supplemental Lighting 200,474 204,776 102%
MFDI Programs Total 710,740 747,227 105%
2020 Idaho Annual Conservation Report Pg 96
The discrepancies between evaluated and reported savings for the MFDI program were a result of reported savings
calculations using UES values for non-lighting measures (aerators and showerheads) that were lower than the UES
values provided by the most recent RTF workbooks. Specifically, reported savings for showerheads used UES values
from Avista’s most recent TRM that did not reflect the most recent RTF UES values. The implementer confirmed it
used UES values from the most recent TRM to calculate reported savings for showerheads, but not the most recent
RTF revision. Cadmus evaluated reported savings using the RTF’s most recent 2019 RTF UES value for showerheads.
Reported savings for aerators used a conservative weighted average UES value that would allow for some aerators
with heat pump water heaters. However, Cadmus determined that the aerator UES value for electric resistance water
heater types is more appropriate for the building stock served by the MFDI program. The implementer accepted this
recommendation, and Cadmus evaluated savings using the 2019 RTF UES value for aerators with electric resistance
water heater types.
Cadmus also identified instances where evaluated realization rates were low for lighting measures because the
implementer did not properly account for electric heating interaction effects in common area spaces. In addition,
Cadmus found reported savings calculations for lighting measures that did not account for the savings that come
from cooling interaction effects in interior spaces. However, the evaluated savings that resulted in fully realized or
higher realization rates for lighting and non-lighting measures in the MFDI program outweighed those with low
realization rates.
The discrepancies between evaluated and reported savings for the MFDI supplemental lighting program resulted
from contractors’ use of undefined annual HOU in the reported savings calculations instead of those hours consistent
with the savings calculations methodology and site data provided. Cases with undefined HOU exceeded 100 percent
realization since these hours were lower than those documented in the calculation methodology and site data
provided. In addition, Cadmus could not verify the interior or exterior lighting HOU for some of these spaces because
the assigned identification numbers could not be found in the accompanying audit data.
Recommendations
Cadmus offered the following recommendations for the MFDI program:
◆Continue to focus on replacing high-use, low-efficiency lamps where practical to maximize program cost-
effectiveness and maintain high savings.
◆Use the most current RTF UES values that are appropriate for the MFDI program’s building stock to calculate
reported savings. Ensure that the TRM provides values and cites sources for all measures. Review the TRM
annually and check if updated values are available for any TRM measures using RTF workbooks as a source.
◆Ensure methodology documentation and reported savings inputs are accurate and provided for all site data.
Plans for 2021
This program is currently scheduled to run through 2021 and will be run as originally planned as COVID-19 restrictions
are lifted. Avista will consider short-term changes to drop-off and tenant installation methods of delivery, but those
considerations will depend on the timeline for COVID-19 restrictions being lifted.
For 2021, Avista has updated its TRM to the most recently available RTF at that time. Note that UES values are
updated at the beginning of the planning cycle and are locked in for the year.
2020 Idaho Annual Conservation Report Pg 97
Residential Home Energy Audit Pilot Program
Description
Taking advantage of previous home energy audit program experience and aligning with industry best practices,
Avista launched a pilot Home Energy Audit program in 2019. Eligible participants included residential customers who
use Avista energy as their primary heating source and are located in Kootenai County, Idaho or in Spokane County,
Washington. The program was implemented by Avista using a contract auditor.
The contract auditor conducted in-person energy audits in customer homes. Audit findings and energy-efficiency
recommendations were discussed with the customer and documented in an audit report, which was later sent by
both email and postal mail to customers. Customers were also given low-cost efficiency items if needed. Where
applicable/feasible, items were directly installed by the auditor at the time of the audit. Energy savings were captured
for LED lamps, power strips, low-flow showerheads, and low-flow faucet aerators. Other low-cost efficiency items
were left behind for the customer to self-install if warranted. These items included rope caulk, plastic window film
kits, foam outlet and switch-plate gaskets, door sweeps, and weather stripping. Customers were then interviewed for
feedback on the program.
In early 2020 Avista gained approval from the Energy Efficiency Advisory Group and commission staff for both
Idaho and Washington to move the program from pilot to full program status. Modifications to program marketing
materials and agreement forms were underway when pandemic restrictions began, effectively suspending the Home
Energy Audit program. As a result, no audits were conducted in 2020.
Program Activities
Due to COVID-19 related restrictions, all program activities were suspended and will resume when these restrictions
are lifted.
Plans for 2021
As intended for 2020, the Home Energy Audit pilot program will be scaled up and offered across the utility’s entire
Idaho and Washington service territory. Based on pilot program participation, Avista estimates that 200 audits will
be conducted between the two states per year. Customer education about energy efficiency and cross-program
awareness will be key focus areas. Avista will also continue to work closely with our community agency partners to
serve vulnerable populations with this program offering.
Qualifying customers are residential customers using an Avista fuel for space heating. Single family homes, multifamily
homes up to a four-plex, and condominium homes are eligible to participate. Multifamily homes with five or more
units will be considered on a case-by-case basis.
LOW-INCOME SECTOR
Clearwater River, Orofino, Idaho
2020 Idaho Annual Conservation Report Pg 99
LOW-INCOME SECTOR
Program-by-Program Summaries
Low-Income Program (Including Community Energy Efficiency Program Projects)
TABLE 57 – LOW-INCOME PROGRAM METRICS
Low-Income Program Summary – Electric 2020
Participation, Savings, and Costs
Conservation projects 146*
Overall kWh savings 215,300
Incentive spend $ 395,025
Non-Incentive Utility Costs $ 241,779
Idaho Energy Efficiency Rider spend $ 637,629
Low-Income Program Summary – Natural Gas 2020
Participation, Savings, and Costs
Conservation projects 149*
Overall Therm savings 5,495
Incentive spend $ 547,343
Non-Incentive Utility Costs $ 115,171
Idaho Energy Efficiency Rider spend $ 662,514
* Many homes served in Idaho last year were dual-fuel and may be counted on both the electric and the natural gas program totals.
Description
Avista works with a Community Action Partnership (CAP) agency to deliver low-income energy-efficiency programs in
nine Idaho counties within the company’s service territory. The CAP has the infrastructure in place to income-qualify
customers and provides access to a variety of funding sources to make energy-efficiency improvements to their
homes. The agency serving Avista’s Idaho territory receives an annual funding amount of $875,000.
The agency may spend its contract amount at its discretion on either electric or natural gas efficiency measures.
Improvements to the home’s shell (e.g. insulation, windows) or conversions from electric heat to heat pump or from
electric heat to natural gas furnaces require that the home demonstrates a minimum level of annual energy use of
either Avista electricity or natural gas for space heating purposes. Within the annual funding allocation is a 15 percent
reimbursement for administrative costs. The agency may also choose to use up to 15 percent of its annual allocation
for home repair as well as other health and safety improvements.
To guide the agencies toward projects that are most beneficial to Avista’s energy-efficiency efforts, the company
provides an approved list of measures that are cost-effective and allow for full reimbursement of the installation.
2020 Idaho Annual Conservation Report Pg 100
A qualified list of measures allows for partial reimbursement of efficiency improvements that may not be cost-
effective from a utility perspective but may be vital for the home’s functionality. These measures are compensated
with an amount that is equal to the utility’s avoided cost of the energy savings associated with the energy efficiency
improvement.
Program Activities
For 2020, the program achieved 215,300 kWh of reported electric savings in Idaho.
Table 58 shows Avista savings goals for the low-income sector for 2020, as well as reported savings and goal portions
achieved in 2019. The program achieved 5,495 of reported therm savings.
TABLE 58 – LOW-INCOME REPORTED SAVINGS
Program Savings Goals (kWh)Reported Savings
(kWh)Percentage of Goal
Low-Income 101,876 195,603 192%
Low-Income – Total 101,876 195,603 192%
Avista continued to reimburse the agencies for 100 percent of the cost for installing most energy-efficiency measures
defined on the approved measure list (see Table 59). Avista deemed these measures as cost-effective during the 2020
Annual Conservation Plan development.
TABLE 59 – LOW-INCOME PROGRAM APPROVED MEASURE LIST
Electric Measures Natural Gas Measures
◆Air infiltration
◆Doors – ENERGY STAR rated
◆Duct insulation
◆Duct sealing
◆Floor insulation
◆LED lamps
◆Refrigerator – ENERGY STAR rated
◆Wall insulation
◆Boiler – 96%
◆Doors – ENERGY STAR rated – .30 U-factor
◆Furnace (90% AFUE)
◆Natural gas water heater (0.65 for storage)
◆Natural gas water heater (.82 tankless)
◆Windows – ENERGY STAR rated
Fuel Conversion Measures
◆Electric to natural gas furnace
◆Electric to natural gas water heater
◆Electric to air-source heat pump (8.5 HSPF)
Measures that did not meet the utility cost-effectiveness test are found on the qualified rebate list. The agency is
eligible to receive a partial reimbursement for the installation. The reimbursement amount is equal to the avoided
cost-energy value of the improvement. This approach focuses the agency toward installing measures that had the
greatest cost-effectiveness from the utility’s perspective. To allow for additional flexibility, the agency may use the
health and safety dollars to fully fund the cost of the measures on the qualified rebate list.
2020 Idaho Annual Conservation Report Pg 101
TABLE 60 – LOW-INCOME PROGRAM QUALIFIED REBATE MEASURE LIST
Electric Measures Natural Gas Measures
◆Air source heat pump replacement (9.0 HSPF)
◆Attic insulation
◆Electric to ductless heat pump (9.0 HSPF)
◆Heat pump water heater (Tier 2-3 any size)
◆Windows – ENERGY STAR rated – .30 U-factor
◆Air infiltration
◆Attic insulation
◆Duct insulation
◆Duct sealing
◆Floor insulation
◆Wall insulation
Program Changes
The agency started the year with a funding allocation of $875,000 for energy-efficiency measures; this was a $50,000
increase from the previous year contract as per Order No. 34499 of IPUC Case No. AVU-E-19-04. Other program
changes include the yearly update of measures eligible for the approved or qualified rebate lists. This is based on
the company’s annual business plan process that is completed in Q4 2019. The eligible measures for 2020 are
summarized in Tables 59 and 60.
While not a change to the program, the COVID-19 pandemic certainly had an effect on homes. When Idaho stay-at-
home orders were announced in late March, agencies paused installation of weatherization services until early July
2021. The CAP agency operating in Idaho also serves Avista customers in a small neighboring county in Washington
state. For consistency purposes, the same Safe Start protocols that were developed in Washington were also applied
to the Idaho service territory. This plan included personal protection and contact tracing initiatives. While it was
anticipated that the agency would not be able to spend much of its Avista contract amount due to losing three
months of time in the field, it was able to spend the full amount of the Avista contract along with an additional
$200,000 to assist with serving a growing list of customers who were heading into the winter with homes in need
of weatherization and heating system upgrades. Part of the reason for the quick spend of Avista dollars during the
pandemic was the lack of federal dollars that were expected but did not materialize. Utility dollars were the primary
funding source available when the agency was able to re-enter customer’s homes; the original amount of the Avista
contract was fully allocated by September.
Customer Outreach
Customers who participate in the low-income weatherization program are often referred through the agency’s
energy assistance program. In a usual year, Avista provides a handful of referrals each year from a variety of internal
departments including energy efficiency and customer service, as well as Avista’s Customer Assistance Referral and
Evaluation Services (CARES) program. CARES provides support for disabled, elderly, and low-income customers,
or customers experiencing hardships related to employment, health, or finances. In 2020 the company expanded
this process to include a hardship referral for customers who contacted Avista’s call center and expressed economic
distress. The hardship referral includes a customer call transfer along with a daily report of the previous days’
referrals to CAP to ensure customers are connected to helpful bill assistance programs and ultimately weatherization
opportunities once the agency was able to re-enter customer homes.
2020 Idaho Annual Conservation Report Pg 102
Other referrals are a result of various outreach events Avista hosts or is invited to attend. In partnership with the
company’s energy-efficiency efforts, its community and economic vitality department conducts conservation education
and outreach for low-income customers, seniors, individuals living with disability, and veterans. Avista reaches this
target population through workshops, energy fairs, and mobile and general outreach. Each includes demonstrations
and distribution of low‐ and no‐cost materials with a focus on energy efficiency, conservation tips and measures, and
information regarding energy assistance that may be available through agencies. One low-income and senior outreach
goal is to increase awareness of energy assistance programs such as the Low-Income Home Energy Assistance
program (LIHEAP) and Project Share.
Avista recognizes several educational strategies as being efficient and effective activities for delivering energy
efficiency and conservation outreach:
◆Energy conservation workshops for groups of Avista customers where the primary target audience is senior
and low-income participants.
◆Energy fairs where attendees can receive information about low- and no-cost methods to weatherize their
homes through demonstrations and energy-saving products. In addition, fair attendees can learn about bill
assistance and watch demonstrations of the online account and energy management tools. Community-
based organizations that provide services to low-income populations and support to increase personal
self-sufficiency are invited, at no cost, to host a booth and provide information about their services and
accessibility.
◆Mobile outreach is conducted through the Avista Energy Resource Van, where visitors can learn about
effective tips to manage their energy use, bill payment options, and community assistance resources.
◆Through general outreach, Avista provides energy management information and resources at events (such as
resource fairs) and partnerships that reach the target populations. General outreach also includes outlining
bill payment options and assistance resources in senior and low-income publications.
In 2020, to safeguard public and staff health and well-being, Avista suspended outreach activities for several months
and used the time to determine how to safely connect with customers to provide energy saving information and
resources. For public and staff safety, company-hosted energy fairs and workshops were not conducted in 2020;
rather, the outreach team distributed items to local food banks to give out in food boxes and participated in food
bank drive-through events. In the fall, kits were provided to North Idaho HeadStart, Meals on Wheels, and Panhandle
Health’s Senior Companion programs for distribution to their clients. Business reply cards were sent to customers with
past due balances to return for a free home energy kit that includes draft-stopping items such as weather stripping
and electrical outlet gaskets, as well as LED bulbs. The outreach team conducted and participated in 39 events that
included mobile outreach and general outreach (via partnerships and events) that reached 2,147 individuals in Idaho.
Table 61 shows an overview of the different activities.
2020 Idaho Annual Conservation Report Pg 103
TABLE 61 – LOW-INCOME OUTREACH EVENT AND LED BULB DISTRIBUTION SUMMARY
Description Number of Events/
Activities Contacts LEDs
Energy fairs 0 0 0
General outreach 38 1,922 8,451
Mobile outreach 1 225 450
Workshops 0 0 0
Total 39 2,147 8,901
In addition to the company’s outreach and education activities, Avista partners with CAP for the employment of a
full-time conservation education specialist. CAP also uses the funds to enable energy assistance intake specialists in
their 10 offices to conduct conservation education activities with clients and in their communities. The conservation
specialist conducts activities similar to and in parallel with Avista, and also provides one-on-one education to
individuals seeking energy assistance and while weatherization projects are underway. Furthermore, the conservation
specialist supports each CAP office’s energy staff in their local conservation efforts.
In some situations, the conservation specialist partners with Avista’s outreach personnel. These collaborations provide
an opportunity for the specialist to learn Avista outreach practices and messaging. During the events where both
the company and agency staff are present, the specialist focuses on promoting CAP services and programs. Due to
COVID and similar to Avista’s outreach program, CAP suspended participation at community events in 2020 and
sought to connect with clients through mailed kits, 972 of which were mailed to households who had received energy
assistance in the past year. The kits included a deluxe window kit, gasket covers, V-Seal weather stripping, LED bulbs,
a nightlight, energy saving tips, and an information sheet about bill/payment options and assistance programs. A
business reply card was also included, in which customers could request a Home Energy Use guide and/or a Kids
Activity book.
Figure 41 includes snapshots of the business reply card, along with the instruction sheet that was included in home
energy kits distributed to customers who responded to the card and through community partners to their clients:
FIGURE 41 – LOW-INCOME HOME ENERGY SAVINGS KIT DIRECT MAIL
START SAVING NOW!
Start Saving Energy By
Ordering your FREE Energy Savings Kit
STARTSAVINGTODAY!
AV
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G
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S
A
V
I
N
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S

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Inside Panel 1
Bleed 18.25 x 5.5
Inside Panel 2
Final Size 18 x 5.25
7 inches 7 inches
Inside Panel 1
Bleed 18.25 x 5.5
Inside Panel 2
Final Size 18 x 5.25
7 inches 7 inches
Inside Panel 1
Bleed 18.25 x 5.5
Inside Panel 2
Final Size 18 x 5.25
7 inches 7 inches
!Please respond no later than
November 13, 2020.
2020 Idaho Annual Conservation Report Pg 104
FIGURE 42 – LOW-INCOME HOME ENERGY SAVINGS KIT BROCHURE
Program Marketing
Multiple communication channels were used to increase awareness of Avista’s energy fairs. Tactics included news
releases, direct mail, email, flyers, community calendars, social media, signage, and print advertising.
CAP categorizes their activities in three different approaches: low-, medium-, and high-impact. Low-impact activities
are designed to heighten awareness but have the least probability of resulting in behavior change, e.g. brochures or
flyers on the wall in the office waiting room. Medium-impact activities help to heighten awareness, are educational
in nature, and have a moderate probability of resulting in behavior changes. They include workshops and/or
informational booths at community events. Finally, high-impact activities are conducted one-on-one with individuals
and have the highest probability of inspiring behavior change. High-impact activities are conducted during energy
assistance intake appointments and/or while weatherization projects are underway.
Your 2020 AvistaHome Energy Kit
If you have questions about your Home Energy Kit, please contact Avista Outreach by email at [e-mail] 509-495-8500.
More energy-saving tips
Open curtains on south-facing windows to let in warm sunlight during the winter. Keep window coverings closed in rooms that do not receive direct
sunlight to insulate from cold window drafts.
Close all curtains at night to retain heat.
Clean or replace your furnace filters monthly throughout the heating season and every three
months during the cooling season. Also put in a clean filter at the start of the fire season to improve air quality and replace as outside air conditions deem necessary. Sign up for a free email reminder
myavista.com/changemyfilter.
Take quick showers and use low-flow showerheads. Short showers use less hot water than a bath.
Practice zone heating when using baseboard or space heaters by turning down the heat and closing doors in unused rooms (a good temperature is
55°F). Keep both clear from obstructions such as
furniture and drapes that block heat. Anything that touches these devices can be a fire hazard.
See a complete list of energy-saving tips at
myavista.com/DIY.
Window Plastic
Covering your windows with plastic insulation is a simple solution to save energy. The film seals out cold air and keeps in warm air, plus it’s clear so you can still see outside.
To Install:
1. Clean and dry edge of window.
2. Apply double-sided mounting tape around window edge.
3. Unfold film and cut it to the width of the window, adding an extra 2” on all sides.
4. Press film in place starting at the top of the window, then sides and bottom.
5. Shrink film to remove wrinkles using a hair dryer ¼ inch or so away from the film.
LED Lightbulbs
Compared to standard incandescent lightbulbs, LEDs last 15 times longer (providing up to 25,000 hours of light) and use up to 90% less energy. The four energy-efficient LED bulbs in your kit are also dimmable.
Nightlight
A low-watt nightlight is perfect for when you have to get up at night and saves on electricity. The one in your kit has a light sensor for nighttime use only.
Blanket
A cozy blanket lets you lower your thermostat and still stay warm and comfy in winter. Save energy by setting your thermostat at 68°F. Also lower it another 5 degrees at night or when away from home for an hour or more.
V-Seal Weather Strip
V-Seal weather strip blocks narrow gaps around doors or windows. The two sides of its V shape are squeezed together for a tight seal when you close your door or window.
To Install:
1. Apply when temperature is above 20°F.
2. Cut to the required length.
3. Fold along the pre-scored center line to form a “V” with the adhesive on the outside.
4. Peel off the backing strip and press into place, positioning it
so the “V” compresses as the door or window is closed.
Doors:
1. Apply across and down the latch side of the doorstop molding.
2. Apply to the hinge side, next to doorframe molding.
Windows:
1. Apply to frame above the window.
2. Apply to sill under the window.
3. Apply across the lock rail.
Reusable Tote
We’ve also included a handy reusable tote to carry whenever you shop.
See how to install these products with our do-it-yourself
videos at myavista.com/DIY.
Your 2020 AvistaHome Energy Kit
If you have questions about your Home Energy Kit, please contact Avista Outreach by email at [e-mail] or by phone at 509-495-8500.
More energy-saving tips
• Open curtains on south-facing windows to let in warm sunlight during the winter. Keep window coverings closed in rooms that do not receive direct
sunlight to insulate from cold window drafts.
Close all curtains at night to retain heat.
• Clean or replace your furnace filters monthly throughout the heating season and every three
months during the cooling season. Also put in a clean filter at the start of the fire season to improve air quality and replace as outside air conditions deem necessary. Sign up for a free email reminder
at myavista.com/changemyfilter.
• Take quick showers and use low-flow showerheads. Short showers use less hot water than a bath.
• Practice zone heating when using baseboard or space heaters by turning down the heat and closing doors in unused rooms (a good temperature is
55°F). Keep both clear from obstructions such as
furniture and drapes that block heat. Anything that touches these devices can be a fire hazard.
• See a complete list of energy-saving tips at
myavista.com/DIY.
2020 Idaho Annual Conservation Report Pg 105
FIGURE 43 – LOW-INCOME ENERGY BILL ASSISTANCE BILL INSERT
FIGURE 44 – LOW-INCOME ENERGY BILL ASSISTANCE FLYER
Looking for energy
bill assistance?
We have options.
AVA411i
• Energy Assistance Grants are available through local
community agencies for income-qualified residential customers. To find an agency near you, call Avista at
1-800-227-9187 or visit myavista.com/assistance.
• Comfort Level Billing divides yearly energy costs into
12 equal and predictable monthly payments.
• Preferred Due Date helps align your bill’s due date with payday.
• Payment Arrangements can be made on an
individual basis for those in need.
Avista partners with community agencies to
provide financial assistance, plus we offer other services
to help you manage and pay your bill.
For more ways we can help, please call 1-800-227-9187
or visit myavista.com/covid-19.
BILLING OPTIONSComfort Level Billing smooths out the seasonal highs and lows of energy bills bydividing yearly usage into 12 equal monthlypayments. Your account must be in goodstanding with at least 12 months of usagehistory to qualify for this program.
Preferred Due Date can help alignthe billing due date with payday. We maybe able to adjust the payment due date,depending on account status and specificsituation (some restrictions apply).
Paperless Billing lets you receive your bills via e-mail and set due-date reminders and other notifications.
PAYMENT OPTIONS
Payment Arrangements can be made
on an individual basis for those in need.
Give us a call or login to our website at
myavista.com to make payment
arrangements online.
Auto Pay automatically withdraws your
Avista payment from your checking
or savings account each month or
charges your debit or credit card.
FINANCIAL HELP
Energy Assistance Grants, such as Project
Share, are available to residential customers
who meet the eligibility guidelines. These
funds are distributed to qualifying customers
through local community agencies.
Visit myavista.com/assistance to find
your local Community Action office.
Looking for energy bill assistance?We have options.
Avista has a variety of ways to help you with your bill. One of those options is
bill assistance for income-qualified customers and those experiencing financial
hardship. Please call us at 800-227-9187 to discuss how we may be able to help.
(See additional information on back.)
Online Energy-Management Tools
can make accessing billing and energy
information fast and simple. Online
customers have a variety of tools at their
fingertips and it’s easy to sign up. Sign into
your online account at myavista.com.
Bill and Usage Insights provides energy-
saving tips and helps explain what could
be impacting your most recent bill – find
it on the Compare Your Bills page.
Energy and Savings Profile takes it one
step further for a more comprehensive
energy analysis and a complete list of ways
to save energy. By completing the Energy
Profile, you’ll see a more precise breakdown
of how your energy is being used. Sign into
your online account at myavista.com.
Bill Comparison shows any bill compared
to previous bills and identifies how bills
are impacted by weather and the number
of days in the billing period. Sign into
your online account at myavista.com.
© 2020 AVISTA CORPORATION. ALL RIGHTS RESERVED.09/20
Energy Efficiency is an important part of
managing energy costs for both the short
and long terms. Avista offers energy-
efficiency tips, rebates and information
on making homes as efficient as
possible at myavista.com/waytosave.
Avista Outreach includes our Energy
Resource Van that travels to areas
throughout Washington and Idaho
distributing energy-conservation materials.
Visit myavista.com/outreach
to see if there is an event near you.
OTHER WAYS TO HELP MANAGE YOUR ENERGY BILL
2020 Idaho Annual Conservation Report Pg 106
FIGURE 45 – LOW-INCOME ENERGY BILL ASSISTANCE PRINT AD
Avista partners with community agencies to provide financial assistance,
plus we offer other services to help you manage and pay your bill.
• Energy Assistance Grants are available for income-qualified residential customers. Funds are distributed to qualifying
customers through local community agencies — please call us
at 1-800-227-9187 to find your local community agency or visit
myavista.com/assistance.
• Comfort Level Billing divides yearly energy costs into 12 equal and predictable monthly payments.
• Preferred Due Date helps align your bill’s due date with payday.
• Payment Arrangements can be made on an individual basis for
those in need.
For more ways we can help, please call 1-800-227-9187.
Looking for energy bill assistance?
We have options.
2020 Idaho Annual Conservation Report Pg 107
Impact Evaluation
With a realization rate of 110 percent for both electricity and gas savings, the low-income program achieved savings
of 215,300 kWh in 2020 and 5,495 therms in gas savings.
The realization rates for the program deviate from 100 percent due to differences between the Avista TRM values
and the appropriately assigned RTF UES values. For the Low-Income program, the evaluators applied a realization rate
from a sample of rebates after verifying documentation for quantity and efficiency of measures.
TABLE 62 – LOW-INCOME IMPACT FINDINGS – ELECTRIC SAVINGS
Measure 2020
Participation
Expected Savings
(kWh)
Adjusted Savings
(kWh)
Verified Savings
(kWh)Realization Rate
Duct sealing 1 689 689 689 100.00%
Ductless heat pump 0 0 0 0
Air infiltration 18 15,345 15,345 18,018 117.42%
ENERGY STAR doors 9 1,304 1,682 1,682 128.94%
ENERGY STAR refrigerator 1 27 39 39 144.44%
ENERGY STAR windows 12 1,372 1,371 1,661 121.12%
High efficiency air heat pump 1 1,493 2,054 2,054 137.54%
Insulation – attic 5 3,507 3,497 1,825 52.05%
Insulation – duct 2 653 619 653 100.00%
Insulation – floor 9 7,298 8,794 9,563 131.04%
Electric to natural gas furnace and
water heater 4 19,660 36,300 36,300 184.64%
Electric to natural gas furnace
conversion 13 63,862 59,432 45,448 71.17%
Electric to natural gas H20 conversion 5 13,004 9,516 7,930 60.98%
Electric to heat pump conversion 15 62,338 87,980 87,980 141.13%
Health and safety 24 0 0 0 -
LED bulbs 27 1,339 1,337 1,458 108.89%
Total 146 195,603 228,654 215,300 110.07%
2020 Idaho Annual Conservation Report Pg 108
TABLE 63 – LOW-INCOME IMPACT FINDINGS – NATURAL GAS SAVINGS
Measure 2020
Participation
Expected Savings
(Therms)
Adjusted Savings
(Therms)
Verified Savings
(Therms)
Verified
Realization Rate
Air infiltration 18 218.91 220.14 220.14 100.56%
Duct sealing 1 20.17 20.17 20.17 100.00%
ENERGY STAR doors 7 66.96 67.62 67.62 100.99%
ENERGY STAR windows 17 369.48 368.25 376.70 101.95%
High efficiency furnace 49 3,342.84 3,049.76 3,796.64 113.58%
High efficiency water heater 50G 25 174.10 176.28 176.28 101.25%
Insulation – attic 3 370.98 370.98 383.35 103.33%
Insulation – duct 0 0.00 0.00 0.00
Insulation – floor 4 296.76 296.76 310.18 104.52%
Insulation – wall 2 82.62 82.62 77.11 93.33%
Health and safety 22 0.00 0.00 0.00
Tankless water heater 1 66.50 66.50 66.50 100.00%
Total 149 5,009.32 4,719.08 5,494.69 109.69%
Impact Evaluation Methodology
ADM conducted a database review for the Low-Income program by selecting a subset of rebate applications to cross-
verify tracking data inputs. Project documentation provided by Avista was reviewed, and billing data was used to
check against household-level annual usage in the database.
The evaluators attempted to estimate measure-level Low-Income program energy savings through billing analysis
regression with a counterfactual group selected via propensity score matching. The evaluators attempted to isolate
each unique measure; however, there were inadequate numbers of participants in the Low-Income program with
isolated measures, and therefore the evaluators were unable to estimate measure-level savings through billing
analysis.
The evaluators instead conducted a whole-home billing analysis for all the electric measures combined, in order to
estimate savings for the average household participating in the program, across all measures. A matched cohort
for electric measure households was created, with customers matched on ZIP code (exact match) and their average
pre-period seasonal usage, including summer, fall, winter, and spring for each control and treatment household.
The evaluators were provided a considerable pool of control customers to draw upon, and used nearest-neighbor
matching with a 5:1 matching ratio. Therefore, each treatment customer was matched to five similar control
customers.
Table 64 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the final model for
the Low-Income program as it provided the highest adjusted R-squared among the regression models. Savings are
statistically significant at the 90 percent level for all measures and the adjusted R-squared shows the model provided
an excellent fit for the data (adjusted R-squared > 0.90).
2020 Idaho Annual Conservation Report Pg 109
TABLE 64 – LOW-INCOME PROGRAM MEASURE SAVINGS
Measure Treatment
Customers
Control
Customers
Annual Savings
per Customer
(kWh)
90% Lower CI 90% Upper CI Adjusted
R-Squared Model
All electric
measures 77 364 1,693 1145 2624 0.73 Model 2: PPR
The evaluators applied these regression savings estimates to the program as a whole, by the number of unique
households in the program, and found a realization rate of 129.86 percent for all electric measures in the program.
Further details of the billing analysis can be found in Appendix A.
ADM provided the following recommendations for Avista’s Low-Income program:
◆The evaluators note that most deviations from 100 percent realization rate are due to differences between
the limited measure category options in Avista’s TRM and the more detailed categories for heating zone,
cooling zone, heating type, and bulb type present in the RTF. The evaluators recommend that Avista refer to
the more detailed RTF measures when calculating expected savings for the programs.
◆The evaluators reviewed the project documentation provided by Avista and identified conflicting square
footage or number of units between the aggregated project data from the CC&B and the rebate project
documentation provided in the data request for document verification. In addition, the unit type, in terms
of square footage or number of measures (windows, doors, etc.,) was not documented consistently
and therefore savings values were applied inaccurately. The evaluators recommend updating CC&B
documentation standards to more accurately reflect values present on the rebate applications.
◆The evaluators found discrepancies between the 20 percent annual consumption cap and the claimed energy
savings. The evaluators recommend checking each project against billing data prior to reporting energy
savings for the project, as well as documenting each household’s usage and the date range used to calculate
the household consumption estimate.
Cost-Effectiveness
Tables 65 and 66 show the low-income sector cost-effectiveness results by fuel type.
TABLE 65 – LOW-INCOME ELECTRIC COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 272,178 $ 546,723 0.50
Total Resource Cost (TRC)$ 366,774 $ 605,151 0.61
Participant Cost Test (PCT)$ 687,611 $ 454,279 1.51
Ratepayer Impact (RIM)$ 272,178 $ 1,018,619 0.27
2020 Idaho Annual Conservation Report Pg 110
Table 9 shows residential cost-effectiveness results for electric.
TABLE 66 – LOW-INCOME NATURAL GAS COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 68,285 $ 662,514 0.10
Total Resource Cost (TRC)$ 168,428 $ 638,498 0.26
Participant Cost Test (PCT)$ 596,928 $ 523,327 1.14
Ratepayer Impact (RIM)$ 68,285 $ 823,100 0.08
Plans for 2021
The measures available for full reimbursement will be the same as 2020 and will now include window replacement
for electric heated homes. Homes that heat with electricity will receive partial funding for replacement of: existing air
source heat pumps with high-efficiency models, converting electric water heaters to natural gas, and the installation
of heat pump water heaters. Homes that heat with natural gas continue to receive partial funding for all insulation
measures.
As a dual-fuel utility, Avista does not impose requirements to annually serve a set number of electric or natural gas
heated homes. The CAP is provided with the flexibility to serve the home of a qualified customer identified during a
program year. As mentioned previously, the measures that appear on the approved and qualified list may fluctuate
annually based on utility cost-effectiveness tests. The flexibility given to the health, safety, and repair allocation does
allow for non-cost-effective measures on the qualified list to be fully funded. The agency has demonstrated the ability
to fully spend its utility allocation each year and exceeded that expectation in 2020.
In a separate but related issue, the agency has been awarded $250,000 from the company’s Energy Efficiency
Assistance Fund (EEAF) that was developed as part of Idaho Settlement Agreement AVU-E-19-4. In conjunction with
the EEAF advisory group these funds are distributed for projects that are not typically eligible for traditional energy
efficiency funding. The agency will use this amount toward health, safety, and repair work on homes that have not
been able to receive energy efficiency services due to extenuating circumstances. The agency will make necessary
improvements, which may range from fixing electrical issues to asbestos removal. Once the issue has been resolved,
the agency will be able to provide a comprehensive energy efficiency offering using funds from Avista’s low- income
energy efficiency contract.
As part of Avista’s annual business planning, UES measure values will continue to be reviewed and updated; however,
when applicable, Avista will continue to use evaluated savings instead of UES values, because evaluated savings are
generally more accurate. In addition, Avista will re-evaluate the units used to set program participation goals for the
year. Per ADM’s recommendations, Avista will also revisit quality control/ accuracy issues in the CC&B tracking system
as well as documentation related to the 20 percent savings cap currently used. Lastly, Avista will ensure that the TRM
is updated to reflect any UES adjustments.
2020 Idaho Annual Conservation Report Pg 111
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REGIONAL MARKET TRANSFORMATION
Downtown Wallace, Idaho
2020 Idaho Annual Conservation Report Pg 113
REGIONAL MARKET TRANSFORMATION
Avista’s local energy-efficiency portfolio consists of programs and supporting infrastructure designed to enhance and
accelerate the saturation of energy-efficiency measures throughout its service territory through a combination of
financial incentives, technical assistance, program outreach, and education.
It is not feasible for Avista to independently have a meaningful impact on regional or national markets. Consequently,
utilities within the Northwest have cooperatively worked together through NEEA to address opportunities that are
beyond the ability or reach of individual utilities. Avista has been participating in and funding NEEA since it was
founded in 1997.
Table 67 shows the 2020 NEEA actual savings and the associated costs for Idaho. The 2020 electric costs of $651,035
are inclusive of $645,907 paid directly to NEEA and $5,128 for Avista’s participation in committees. For natural gas,
$137,615 was paid directly to NEEA and an additional $1,593 originated from Avista’s participation in committees.
TABLE 67 – ACTUAL SAVINGS AND ASSOCIATED COSTS FOR AVISTA IDAHO
Fuel Type
2020 NEEA Final
Reported Energy
Savings
2020 Costs
(Avista Financials)
Avista Idaho Current
Funding Share
(2020-2024)
Electric 3,578 MWh
(0.41 aMW)$ 651,035 1.69%
Natural gas 5,641 $ 139,208 3.55%
Electric Energy Savings Share
All the values provided in this report represent the amounts that are allocated to Avista’s service territory, which is a
combination of site-based energy savings data (where available) or is an allocation of savings based on funding share.
Using the funding share allocation approach, the funding share for Avista is split between 30 percent for Avista Idaho
and 70 percent for Avista Washington. The funding share for Avista varies by funding cycle and within each cycle if
the funding composition changes.
Natural Gas Energy Savings Share
NEEA’s costs include all expenditures for operations and value delivery: energy savings initiatives; investments in
market training and infrastructure; stock assessments, evaluations, data collection, and other regional and program
research; emerging technology research and development; and all administrative costs.
Avista’s criteria for funding NEEA’s electric market transformation portfolio calls for the portfolio to deliver
incrementally cost‐effective resources beyond what could be acquired through Avista’s local portfolio alone. Avista
has historically communicated with NEEA the importance of NEEA delivering cost‐effective resources to the company’s
service territory. Avista believes that NEEA will continue to offer cost‐effective electric market transformation in the
foreseeable future. Avista will continue to be active in the organizational oversight of NEEA, a critical step in ensuring
geographic equity, cost‐effectiveness, and resource acquisition.
GLOSSARY OF TERMS
Palouse wheat field, Idaho
2020 Idaho Annual Conservation Report Pg 115
GLOSSARY OF TERMS
advisory group: Avista’s group of external stakeholders who comment about the company’s energy efficiency
activities.
Active Energy Management (AEM): The implementation of continuous building monitoring to improve building
performance in real time.
Adjusted Market Baseline (AMB): Based on the RTF guidelines, represents a measurement between the energy-
efficient measure and the standard efficiency case that is characterized by current market practice or the minimum
requirements of applicable codes or standards, whichever is more efficient. When applying an Adjusted Market
Baseline, no net-to-gross factor would be applied since the resultant unit energy savings amount would represent the
applicable savings to the grid.
Advanced Metering Infrastructure (AMI): Systems that measure, collect and analyze energy usage, from advanced
devices such as electricity meters, natural gas meters and/or water meters through various communication media on
request or on a predetermined schedule.
AHRI Certificates (Air-Conditioning, Heating and Refrigeration Institute) – a certification widely recognized
through the industry as a standard certification for HVAC/ refrigeration efficiency.
Air-Conditioning, Heating, and Refrigeration Institute (AHRI): The trade association representing manufacturers
of HVACR and water heating equipment within the global industry.
aMW: The amount of energy that would be generated by one megawatt of capacity operating continuously for one
full year. Equals 8,760 MWhs of energy.
American National Standards Institute (ANSI): A source for information on national, regional, and international
standards and conformity assessment issues.
American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE): Devoted to the
advancement of indoor-environment-control technology in the heating, ventilation, and air conditioning (HVAC)
industry, ASHRAE’s mission is “to advance technology to serve humanity and promote a sustainable world.”
Annual Conservation Plan (ACP): An Avista-prepared resource document that outlines Avista’s conservation
offerings, its approach to energy efficiency, and details on verifying and reporting savings.
Annual Conservation Report (ACR): An Avista-prepared resource document that summarizes its annual energy
efficiency achievements.
Annual Fuel Utilization Efficiency (AFUE): A measurement on how efficiently a furnace or boiler uses its fuel.
2020 Idaho Annual Conservation Report Pg 116
avoided cost: An investment guideline, describing the value of conservation and generation resource investments in
terms of the cost of more expensive resources that would otherwise have to be acquired.
baseline: Conditions, including energy consumption, which would have occurred without implementation of the
subject energy efficiency activity. Baseline conditions are sometimes referred to as “business-as-usual” conditions.
baseline efficiency: The energy use of the baseline equipment, process, or practice that is being replaced by a more
efficient approach to providing the same energy service. It is used to determine the energy savings obtained by the
more efficient approach.
baseline period: The period of time selected as representative of facility operations before the energy efficiency
activity takes place.
BPA: Bonneville Power Administration
Building Owners & Managers Association (BOMA): An international federation of U.S. local associations and
global affiliates that represents the owners, managers, service providers, and other property professionals of all
commercial building types.
Business Partner Program (BPP): An outreach effort designed to raise awareness of utility programs and services
that can assist rural small business customers in managing their energy bills.
British Thermal Unit (Btu): The amount of heat energy necessary to raise the temperature of one pound of water
one degree Fahrenheit (3,413 BTUs are equal to one kilowatt-hour).
busbar: The physical electrical connection between the generator and transmission system. Typically, load on the
system is measured at busbar.
capacity: The maximum power that a machine or system can produce or carry under specified conditions. The
capacity of generating equipment is generally expressed in kilowatts or megawatts. In terms of transmission lines,
capacity refers to the maximum load a line is capable of carrying under specified conditions.
Coefficient of Performance (COP): A ratio of useful heating or cooling provided to work (energy) required for heat
pumps, refrigerators or air conditioning systems. Higher COPs equate to more efficient systems and lower operating
costs.
Community Action Partnership (CAP): General term for Community Action Programs, Community Action
Agencies, and Community Action Centers that provide services such as low-income weatherization through federal
and state and other funding sources (e.g. utility constitutions).
conservation: According to the Northwest Power Act, any reduction in electric power consumption as a result of
increases in the efficiency of energy use, production or distribution.
2020 Idaho Annual Conservation Report Pg 117
Conservation Potential Assessment (CPA): An analysis of the amount of conservation available in a defined area.
Provides savings amounts associated with energy efficiency measures to input into the Company’s Integrated Resource
Planning (IRP) process.
cooling degree days: A measure of how hot the temperature was on a given day or during a period of days. A day
with a mean temperature of 80°F has 15 cooling degree days, assuming a base of 65 degrees Fahrenheit. If the next
day has a mean temperature of 83°F, it has 18 cooling degree days.
cost-effective: According to the Northwest Power Act, a cost-effective measure or resource must be forecast to be
reliable and available within the time it is needed, and to meet or reduce electrical power demand of consumers at an
estimated incremental system cost no greater than that of the least-costly, similarly reliable and available alternative or
combination of alternatives.
curtailment: An externally imposed reduction of energy consumption due to a shortage of resources.
customer/customer classes: A category(ies) of customer(s) defined by provisions found in tariff(s) published by the
entity providing service, approved by the PUC. Examples of customer classes are residential, commercial, industrial,
agricultural, local distribution company, core and non-core.
decoupling: In conventional utility regulation, utilities make money based on how much energy they sell. A utility’s
rates are set based largely on an estimation of costs of providing service over a certain set time period, with an
allowed profit margin, divided by a forecasted amount of unit sales over the same time period. If the actual sales turn
out to be as forecasted, the utility will recover all of its fixed costs and its set profit margin. If the actual sales exceed
the forecast, the utility will earn extra profit.
deemed savings: Primarily referenced as unit energy savings, an estimate of an energy 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 load that is drawn from the source of supply over a specified interval of time (in kilowatts, kilovolt-
amperes, or amperes). Also, the rate at which natural gas is delivered to or by a system, part of a system or piece of
equipment, expressed in cubic feet, therms, BTUs or multiples thereof, for a designated period of time such as during
a 24-hour day.
Demand Response (DR): A voluntary and temporary change in consumers’ use of electricity when the power system
is stressed.
Demand Side Management (DSM): The process of helping customers use energy more efficiently. Used
interchangeably with Energy Efficiency and Conservation although conservation technically means using less while
DSM and energy efficiency means using less while still having the same useful output of function.
2020 Idaho Annual Conservation Report Pg 118
Direct Load Control (DLC): The means by which a utility can signal a customer’s appliance to stop operations in
order to reduce the demand for electricity. Such rationing generally involves a financial incentive for the affected
customer.
discount rate: The rate used in a formula to convert future costs or benefits to their present value.
distribution: The transfer of electricity from the transmission network to the consumer. Distribution systems generally
include the equipment to transfer power from the substation to the customer’s meter.
Distributed Generation (DG): An approach that employs a variety of small-scale technologies to both produce and
store electricity close to the end users of power.
Effective Useful Life (EUL): Sometimes referred to as measure life and often used to describe persistence. EUL is an
estimate of the duration of savings from a measure.
Emergency Operating Plan (EOP): A plan that assigns responsibility to organizations and individuals for carrying
out specific actions to respond to an emergency. An EOP sets forth lines of authority, lays out organizational roles
and responsibilities during an emergency, and illustrates how actions will be coordinated. An EOP also describes how
people and property will be be protected in emergencies and natural disasters, and identifies personnel, equipment,
facilities and supplies to use during recovery operations.
end-use: A term referring to the final use of energy; it often refers to the specific energy services (for example, space
heating), or the type of energy-consuming equipment (for example, motors).
energy assistance advisory group: An ongoing energy assistance program advisory group to monitor and explore
ways to improve Avista’s Low-Income Rate Assistance Program (LIRAP).
Energy Efficiency Advisory Group (EEAG): A group which advises investor-owned utilities on the development of
integrated resource plans and conservation programs.
energy-efficiency measure: Refers to either an individual project conducted or technology implemented to reduce
the consumption of energy at the same or an improved level of service. Often referred to as simply a “measure.”
Energy Independence Act (EIA): Requires electric utilities serving at least 25,000 retail customers to use renewable
energy and energy conservation.
Energy Use Intensity (EUI): A metric – energy per square foot per year – that expresses a building’s energy use as a
function of its size or other characteristics.
2020 Idaho Annual Conservation Report Pg 119
evaluation: The performance of a wide range of assessment studies and activities aimed at determining the effects
of a program (and/or portfolio) and understanding or documenting program performance, program or program-
related markets and market operations, program-induced changes in energy efficiency markets, levels of demand or
energy savings, or program cost-effectiveness. Market assessment, monitoring and evaluation, and verification are
aspects of evaluation.
Evaluation, Measurement and Verification (EM&V): Catch-all term for evaluation activities at the measure,
project, program and/or portfolio level; can include impact, process, market and/or planning activities. EM&V is
distinguishable from Measurement and Verification (M&V) defined below.
ex-ante savings estimate: Forecasted savings value used for program planning or savings estimates for a measure;
Latin for “beforehand.”
ex-post evaluated estimated savings: Savings estimates reported by an independent, third-party evaluator after
the energy impact evaluation has been completed. If only the term “ex-post savings” is used, it will be assumed that
it is referring to the ex-post evaluation estimate, the most common usage; from Latin for “from something done
afterward.”
external evaluators (AKA third party evaluators): Independent professional efficiency person or entity retained
to conduct EM&V activities. Consideration will be made for those who are Certified Measurement and Verification
Professionals (CMVPs) through the Association of Energy Engineers (AEE) and the Efficiency Evaluation Organization
(EVO).
free rider: A common term in the energy efficiency industry meaning a program participant who would have
installed the efficient product or changed a behavior regardless of any program incentive or education received. Free
riders can be total, partial, or deferred.
generation: The act or process of producing electricity from other forms of energy.
Green Motors Practices Group (GMPG): A nonprofit corporation governed by electric motor service center
executives and advisors whose goal is the continual improvement of the electric motor repair industry.
gross savings: The change in energy consumption and/or demand that results from energy efficiency programs,
codes and standards, and naturally-occurring adoption which have a long-lasting savings effect, regardless of why
they were enacted.
heating degree days: A measure of the amount of heat needed in a building over a fixed period of time, usually a
year. Heating degree days per day are calculated by subtracting from a fixed temperature the average temperature
over the day. Historically, the fixed temperature has been set at 65 degrees Fahrenheit, the outdoor temperature
below which heat was typically needed. As an example, a day with an average temperature of 45 degrees Fahrenheit
would have 20 heating degree days, assuming a base of 65 degrees Fahrenheit.
2020 Idaho Annual Conservation Report Pg 120
Heating Seasonal Performance Factor (HSPF): Defined as the ratio of heat output over the heating season to the
amount of electricity used in air source or ductless heat pump equipment.
Heating, Ventilation, and Air Conditioning (HVAC): Sometimes referred to as climate control, the HVAC
is particularly important in the design of medium to large industrial and office buildings where humidity and
temperature must all be closely regulated whilst maintaining safe and healthy conditions within.
High Intensity Discharge (HID) fixture: A fixture that is bright and powerful enough to throw a large number of
lumens an extremely long distance; often used in very large spaces such as manufacturing facilities or sports stadiums.
Hours of Use (HOU): an annual estimation of lighting or HVAC equipment operation hours).
Idaho Public Utilities Commission (IPUC): Regulators of investor-owned or privatively owned utilities that provide
gas, water, electricity or some telephone services for profit.
impact evaluation: Determination of the program-specific, directly or indirectly induced changes (e.g., energy and/or
demand usage) attributable to an energy efficiency program.
implementer: Avista employees whose responsibilities are directly related to operations and administration of energy
efficiency programs and activities, and who may have energy savings targets as part of their employee goals or
incentives.
incremental cost: The difference between the cost of baseline equipment or services and the cost of alternative
energy-efficient equipment or services.
installation verification (IV) report: A detailed report documenting installed conservation measures on a site-
specific project.
Integrated Resource Plan (IRP): An IRP is a comprehensive evaluation of future electric or natural gas resource
plans. The IRP must evaluate the full range of resource alternatives to provide adequate and reliable service to a
customer’s needs at the lowest possible risk-adjusted system cost. These plans are filed with the state public utility
commissions on a periodic basis.
Integrated Resource Plan Technical Advisory Committee (IRP TAC): Advisory committee for the IRP process that
includes internal and external stakeholders.
International Performance Measurement and Verification Protocol (IPMVP): A guidance document with a
framework and definitions describing the four M&V approaches; a product of the Energy Valuation Organization
(www.evo-world.org).
Investor-owned utility (IOU): A utility that is organized under state law as a corporation to provide electric power
service and earn a profit for its stockholders.
2020 Idaho Annual Conservation Report Pg 121
Kilowatt (kW): The electrical unit of power that equals 1,000 watts.
Kilowatt-hour (kWh): A basic unit of electrical energy that equals one kilowatt of power applied for one hour.
Kilo British Thermal Unit (kBtu): Btu, which stands for British thermal units, measures heat energy. Each Btu equals
the amount of heat needed to raise one pound of water one degree Fahrenheit; the prefix kilo- stands for 1,000,
which means that a kBtu equals 1,000 Btu.
Levelized Cost of Energy (LCOE): The present value of a resource’s cost (including capital, financing, and operating
costs) converted into a stream of equal annual payments. This stream of payments can be converted to a unit cost of
energy by dividing them by the number of kilowatt-hours produced or saved by the resource in associated years. By
levelizing costs, resources with different lifetimes and generating capabilities can be compared.
line losses: The amount of electricity lost or assumed lost when transmitting over transmission or distribution lines.
This is the difference between the quantity of electricity generated and the quantity delivered at some point in the
electric system.
Low-Income Home Energy Assistance Program (LIHEAP): Federal energy assistance program, available to
qualifying households based on income, usually distributed by community action agencies or partnerships.
Low-Income Rate Assistance Program (LIRAP): LIRAP provides funding (collected from Avista’s tariff rider) to CAP
agencies for distribution to Avista customers who are least able to afford their utility bill.
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.
measure (also Energy Efficiency Measure or “EEM”): Installation of a single piece of equipment, subsystem or
system, or single modification of equipment, subsystem, system, or operation at an end-use energy consumer facility,
for the purpose of reducing energy and/or demand (and, hence, energy and/or demand costs) at a comparable level
of service.
measure life: See Effective Useful Life (EUL).
Measurement and Verification (M&V): A subset of program impact evaluation that is associated with the
documentation of energy savings at individual sites or projects, using one or more methods that can involve
measurements, engineering calculations, statistical analyses, and/or computer simulation modeling. M&V approaches
are defined in the International Performance Measurement and Verification Protocol (IPMVP available at
www.evo-world.org).
Megawatt (MW): The electrical unit of power that equals one million watts or one thousand kilowatts.
2020 Idaho Annual Conservation Report Pg 122
Megawatt-hour (MWh): A basic unit of electrical energy that equals one megawatt of power applied for one hour.
net savings: The change in energy consumption and/or demand that is attributable to an energy efficiency program.
This change in energy use and/or demand may include, implicitly or explicitly, consideration of factors such as free
drivers, non-net participants (free riders), participant and non-participant spillover, and induced market effects. These
factors may be considered in how a baseline is defined and/or in adjustments to gross savings values.
Non-Energy Benefit/Non-Energy Impact (NEB/NEI): The quantifiable non-energy impacts associated with program
implementation or participation; also referred to as non-energy benefits (NEBs) or co-benefits. Examples of NEIs
include water savings, non-energy consumables and other quantifiable effects. The value is most often positive, but
may also be negative (e.g., the cost of additional maintenance associated with a sophisticated, energy-efficient control
system).
Northwest Energy Efficiency Alliance (NEEA): A nonprofit organization that works to accelerate energy efficiency
in the Pacific Northwest through the adoption of energy-efficient products, services, and practices.
Northwest Power and Conservation Council (NWPCC): An organization that develops and maintains both a
regional power plan and a fish and wildlife program to balance the environmental and energy needs of the Pacific
Northwest.
Outside Air Temperature (OAT): Refers to the temperature of the air around an object, but unaffected by the
object.
On-Bill Repayment/Financing (OBR): A financing option in which a utility or private lender supplies capital to
a customer to fund energy efficiency, renewable energy, or other generation projects. It’s repaid through regular
payments on an existing utility bill.
portfolio: Collection of all programs conducted by an organization. In the case of Avista, portfolio includes electric
and natural gas programs in all customer segments. Portfolio can also be used to refer to a collection of similar
programs addressing the market. In this sense of the definition, Avista has an electric portfolio and a natural gas
portfolio with programs addressing the various customer segments.
prescriptive: A prescriptive program is a standard offer for incentives for the installation of an energy efficiency
measure. Prescriptive programs are generally applied when the measures are employed in relatively similar
applications.
process evaluation: A systematic assessment of an energy efficiency program or program component for
the purposes of documenting operations at the time of the examination, and identifying and recommending
improvements to increase the program’s efficiency or effectiveness for acquiring energy resources while maintaining
high levels of participant satisfaction.
2020 Idaho Annual Conservation Report Pg 123
program: An activity, strategy or course of action undertaken by an implementer. Each program is defined by a
unique combination of program strategy, market segment, marketing approach and energy efficiency measure(s)
included. Examples are a program to install energy-efficient lighting in commercial buildings and residential
weatherization programs.
project: An activity or course of action involving one or multiple energy efficiency measures at a single facility or site.
Ratepayer Impact (RIM) Test: An economic test used to compare administrator costs and utility bill reductions to
costs of supply side resources.
Regional Technical Forum of the Northwest Power and Conservation Council (RTF): A technical advisory
committee to the Northwest Power and Conservation Council established in 1999 to develop standards to verify and
evaluate energy efficiency savings.
Realization Rate (RR): Ratio of ex-ante reported savings to ex-post evaluated estimated savings. When realization
rates are reported, they are labeled to indicate whether they refer to comparisons of 1) ex-ante gross reported savings
to ex-post gross evaluated savings, or 2) ex-ante net reported savings to ex-post net evaluated savings.
reliability: When used in energy efficiency evaluation, the quality of a measurement process that would produce
similar results on (a) repeated observations of the same condition or event, or (b) multiple observations of the same
condition or event by different observers. Reliability refers to the likelihood that the observations can be replicated.
reported savings: Savings estimates reported by Avista for an annual (calendar) period. These savings will be based
on best available information.
Request for Proposal (RFP): Business document that announces and provides details about a project, as well as
solicits bids from potential contractors.
retrofit: To modify an existing generating plant, structure, or process. The modifications are done to improve energy
efficiency, reduce environmental impacts, or to otherwise improve the facility.
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, i.e., reliable.
R-value or R-factor (resistance transfer factor): Measures how well a barrier, such as insulation, resists the
conductive flow of heat.
schedules 90 and 190: Rate schedules that show energy efficiency programs.
schedules 91 and 191: Rate schedules that are used to fund energy efficiency programs.
sector(s): The economy is divided into four sectors for energy planning. These are the residential, commercial (e.g.,
retail stores, office and institutional buildings), industrial, and agriculture (e.g. dairy farms, irrigation) sectors.
2020 Idaho Annual Conservation Report Pg 124
Strategic Energy Management (SEM): Overall processes implemented in a building or portfolio to manage and
continuously improve energy performance.
service territory: The areas in Idaho, Washington, and Oregon served by Avista to provide either gas or electric
service (or both).
site-specific: A non-residential program offering individualized calculations for incentives upon any electric or natural
gas efficiency measure not incorporated into a prescriptive program.
simple payback: The time required before savings from a particular investment offset costs, calculated by investment
cost divided by value of savings (in dollars). For example, an investment costing $100 and resulting in a savings of
$25 each year would be said to have a simple payback of four years. Simple paybacks do not account for future cost
escalation, nor other investment opportunities.
spillover: Reductions in energy consumption and/or demand caused by the presence of an energy efficiency
program, beyond the program-related gross savings of the participants and without direct financial or technical
assistance from the program. There can be participant and/or nonparticipant spillover (sometimes referred to as “Free
Drivers”). Participant spillover is the additional energy savings that occur as a result of the program’s influence when a
program participant independently installs incremental energy efficiency measures or applies energy-saving practices
after having participated in the energy efficiency program. Non-participant spillover refers to energy savings that occur
when a program non-participant installs energy efficiency measures or applies energy savings practices as a result of a
program’s influence.
Technical Reference Manual (TRM): An Avista-prepared resource document that contains Avista’s (ex-ante) savings
estimates, assumptions, sources for those assumptions, guidelines, and relevant supporting documentation for its
natural gas and electricity energy efficiency prescriptive measures. This document is populated and vetted by the RTF
and 3rd party evaluators.
Total Resource Cost (TRC) test: A cost-effectiveness test that assesses the impacts of a portfolio of energy-efficiency
initiatives regardless of who pays the costs or who receives the benefits. The test compares the present value of costs
of efficiency for all members of society (including all costs to participants and program administrators) compared to
the present value of all quantifiable benefits, including avoided energy supply and demand costs and non-energy
impacts.
trade ally: Contractors and service providers who partner with utility efficiency programs to deliver energy efficiency
projects, products, and services.
trade ally bid: A bid for an energy-efficiency project, product, or service from a trade ally.
transmission: The act or process of long-distance transport of electric energy, generally accomplished by elevating
the electric current to high voltages. In the Pacific Northwest, Bonneville operates a majority of the high-voltage, long-
distance transmission lines.
2020 Idaho Annual Conservation Report Pg 125
Uniform Energy Factor (UEF): A measurement on how efficiently a water heater utilizes its fuel.
Unit Estimated Savings (UES): Defines the first year kWh savings value for an energy efficiency measure.
U-value or U-factor: The measure of a material’s ability to conduct heat, numerically equal to 1 divided by the
value of the material. Used to measure the rate of heat transfer in windows. The lower the u-factor, the better the
window insulates
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.
Utility Cost Test (UCT): One of the four standard practice tests commonly used to evaluate the cost-effectiveness
of DSM programs. The UCT evaluates the cost-effectiveness based upon a program’s ability to minimize overall utility
costs. The primary benefits are the avoided cost of energy in comparison to the incentive and non-incentive utility
costs.
Variable Frequency Drive (VFD): A type of motor drive used in electro-mechanical drive systems to control AC
motor speed and torque by varying motor input frequency and voltage.
verification: An assessment that the program or project has been implemented per the program design. For example,
the objectives of measure installation verification are to confirm (a) the installation rate, (b) that the installation meets
reasonable quality standards, and (c) that the measures are operating correctly and have the potential to generate
the predicted savings. Verification activities are generally conducted during on-site surveys of a sample of projects.
Project site inspections, participant phone and mail surveys, and/or implementer and consumer documentation
review are typical activities association with verification. Verification may include one-time or multiple activities over
the estimated life of the measures. It may include review of commissioning or retro-commissioning documentation.
Verification can also include review and confirmation of evaluation methods used, samples drawn, and calculations
used to estimate program savings. Project verification may be performed by the implementation team, but program
verification is a function of the 3rd party evaluator.
weather normalized: This is an adjustment that is made to actual energy usage, stream-flows, etc., which would
have happened if “normal” weather conditions would have taken place.
Weighted Average Cost of Capital (WACC): A calculation of a firm’s cost of capital in which each category of
capital is proportionately weighted. All sources of capital, including common stock, preferred stock, bonds, and any
other long-term debt, are included in a WACC calculation.
8760: Total number of hours in a year.
APPENDICES AND SUPPLEMENTS
Grangeville, Idaho
2020 Idaho Annual Conservation Report Appendices
APPENDIX A – 2020 IDAHO ELECTRIC IMPACT EVALUATION REPORT –
COMMERCIAL/INDUSTRIAL

PY 2020 Idaho Electric
Impact Evaluation Report
April 16, 2021
Prepared for:
Avista Corporation
1411 East Mission Avenue
Spokane, WA 99202

i
Table of Contents
Portfolio Executive Summary ................................................................................................................ 1
Evaluation Methodology and Activities ................................................................................................. 1
Summary of Impact Evaluation Results ................................................................................................. 1
Conclusions and Recommendations ...................................................................................................... 2
Nonresidential Impact Evaluation ......................................................................................................... 6
Program Summary ................................................................................................................................. 6
Program Participation Summary ............................................................................................................ 6
Nonresidential Impact Evaluation Methodology ................................................................................... 8
Nonresidential Impact Evaluation Findings ......................................................................................... 11
Nonresidential Conclusions and Recommendations ........................................................................... 14
Multifamily Direct Install (MFDI) Impact Evaluation ............................................................................ 17
Program Summary ............................................................................................................................... 17
Program Participation Summary .......................................................................................................... 17
Multifamily Direct Install Impact Evaluation Methodology ................................................................. 18
Multifamily Direct Install Impact Evaluation Results ........................................................................... 18
Multifamily Direct Install Conclusions and Recommendations ........................................................... 19
Fuel Efficiency Impact Evaluation ........................................................................................................ 20
Program Summary ............................................................................................................................... 20
Program Participation Summary .......................................................................................................... 20
Fuel Efficiency Impact Evaluation Methodology .................................................................................. 20
Fuel Efficiency Impact Evaluation Results ............................................................................................ 21
Fuel Efficiency Conclusions and Recommendations ............................................................................ 21

Tables
Table 1. Electric Program Evaluation Activities ............................................................................................ 1
Table 2. Reported and Evaluated Energy Efficiency Electric Savings ............................................................ 2
Table 3. Nonresidential Prescriptive Electric Savings ................................................................................... 7
Table 4. Nonresidential Prescriptive Participation by Project ...................................................................... 7
Table 5. Nonresidential Site Specific Electric Savings ................................................................................... 7
Table 6. Nonresidential Site Specific Participation by Project ...................................................................... 8

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Table 7. Idaho Nonresidential Prescriptive Electric Evaluation Sample ..................................................... 10
Table 8. Idaho Nonresidential Site Specific Electric Evaluation Sample ..................................................... 10
Table 9. Nonresidential Prescriptive Electric Impact Findings ................................................................... 12
Table 10. Nonresidential Prescriptive Evaluation Summary of Discrepancies ........................................... 12
Table 11. Nonresidential Site Specific Electric Impact Findings ................................................................. 13
Table 12. Nonresidential Site Specific Evaluation Summary of Discrepancies ........................................... 14
Table 13. MFDI Programs Reported Electric Savings .................................................................................. 17
Table 14. MFDI Programs Participation ...................................................................................................... 18
Table 15. MFDI Programs Electric Impact Findings .................................................................................... 18
Table 16. Avista Portfolio Fuel Efficiency Reported Electric Savings .......................................................... 20
Table 17. Avista Portfolio Fuel Efficiency Reported Participation .............................................................. 20
Table 18. Nonresidential Fuel Efficiency Electric Impact Findings ............................................................. 21

1
Portfolio Executive Summary
For several decades, Avista Corporation (Avista) has administered demand-side management (DSM)
programs to reduce the electricity and natural gas energy use by its customer portfolio. While Avista has
implemented most of these programs in-house, external vendors have fulfilled some of them.
Avista contracted with Cadmus to complete process and impact evaluations of its program year
(PY) 2020 electric DSM Nonresidential and multifamily Residential programs in Idaho. This report
presents the electric impact evaluation findings for PY 2020. Cadmus did not apply net-to-gross (NTG)
adjustments to savings values, except where deemed energy savings values already incorporated NTG as
a function of the market baseline.
Evaluation Methodology and Activities
Cadmus conducted the Idaho portfolio evaluation using the methods and activities shown in Table 1.
Table 1. Electric Program Evaluation Activities
Sector Program Document/Database
Review
Verification/Metering Site
Visits
Nonresidential Prescriptive (Multiple) ü ü
Site Specific ü ü
Multifamily Multifamily Direct Install ü --
Supplemental Lighting ü --
Fuel Efficiency Multifamily Market Transformation ü --

Summary of Impact Evaluation Results
The Nonresidential and Multifamily Idaho electric energy efficiency programs achieved an 86%
realization rate and acquired 11,960,349 kWh in evaluated savings, as shown in Table 2. Cadmus
collected Avista’s reported savings through database extracts drawn from Avista’s iEnergy database
(Nonresidential) and from data provided by the third-party implementor for the Multifamily Direct
Install (MFDI) program.
Despite the COVID-19 pandemic reducing participation in both the Nonresidential and Multifamily
sectors, most programs Cadmus evaluated performed strongly relative to reported savings in PY 2020.

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Table 2. Reported and Evaluated Energy Efficiency Electric Savings
Sector Reported Savings (kWh) Evaluated Savings (kWh) Realization Rate
Nonresidential 12,665,993 10,723,525 85%
Multifamily Direct Install 710,740 747,227 105%
Fuel Efficiency 528,727 489,597 93%
Total 13,905,460 11,960,349 86%
Note: totals may not sum due to rounding.
Conclusions and Recommendations
During the PY 202019 evaluation, Cadmus identified several areas for improvement, outlined below by
sector.
Nonresidential Conclusions and Recommendations
The Nonresidential sector achieved total evaluated electric energy savings of 10,724 MWh in PY 2020,
with a combined realization rate of 85%. The Nonresidential sector did not meet the combined
Prescriptive and Site Specific program paths’ electric goal of 15,020 MWh, with the program achieving
71% of its goal.
Although some individual project results varied, particularly within the Prescriptive exterior lighting
program, the overall Nonresidential sector performed strongly in PY 2020 relative to reported savings.
Most projects that Cadmus sampled for the evaluation were well documented and matched findings
from the remote project verifications.
Cadmus offers the following conclusions and recommendations to improve the Nonresidential sector’s
energy savings:
• Avista’s new iEnergy system has the capability to automatically calculate more detailed energy
savings estimates since it records additional detailed inputs on some prescriptive measures that
were not previously tracked in InforCRM. Some of these inputs are not currently used in the
savings calculations.
§ Recommendation: Review deemed savings values for prescriptive measures and consider
opportunities to leverage the additional data now collected in iEnergy to calculate more
accurate savings for each participant project. For example, food service measures can use
the reported pounds of food cooked per day and cooking hours per day values collected in
iEnergy to automatically calculate more precise savings.
• The iEnergy system introduced variance of up to 2% between reported and evaluated savings by
rounding intermediate wattage calculation values.
§ Recommendation: Review iEnergy calculations to ensure that rounding is only applied on
final displayed values and not to any intermediate values.
• Customer uncertainty on where program equipment was installed created challenges for
verifying installed quantities and may have contributed to reduced realization rates for projects
where verified quantities were less than reported.

3
§ Recommendation: Update all application forms to include space for location notes for each
installed measure and encourage contractors installing equipment at very large facilities to
include installation location with equipment invoices.
• Variations in the level of detail in Avista installation verification (IV) reports introduced
additional complexity in evaluating accurate measure counts, types, and operating parameters.
§ Recommendation: Provide more consistent documentation with IV reports. Cadmus
recommends that all IV reports include basic information to explicitly state the quantity and
type of equipment found. For lighting projects, this would include confirmed fixture types,
quantities, installation locations, controls, and estimated hours of use (HOU). For most other
equipment, this would include nameplates, model numbers, and quantities.
• The evaluated lighting HOU for interior and exterior lighting projects did not always align with
reported values.
§ Recommendation: Review HOU estimates when processing applications and conducting
installation verifications. When entering average weekly HOU, confirm how many weeks per
year that schedule applies. In particular, Avista should apply additional scrutiny to
applications claiming 8,760 hours per year.
• Discrepancies between reported fixture quantities and invoice quantities added complexity and
uncertainty in evaluating the Site Specific lighting program. It is often impractical for Avista staff
conducting IV inspections or evaluators conducting verification visits to count every fixture for
large lighting projects, necessitating a greater reliance on project documentation.
§ Recommendation: Include more detailed documentation for Site Specific lighting projects.
Lighting drawings should be provided whenever possible, and if any other notes,
spreadsheets, or other documentation are used to determine eligible quantities, these
should be included with the application records. Any difference between invoice quantities
and rebated quantities should be clearly explained.
• Avista may rely on spot measurements for values that vary during typical operation. The
submitted analysis for a Site Specific industrial process motor project assumed a fixed output
voltage from the variable frequency drive (VFD) based on a single spot measurement, but the
plant’s industrial control system was capable of recording voltage trend data. Cadmus worked
with the customer to add a voltage trend and determined that the VFD voltage output actually
varied significantly in daily operation.
§ Recommendation: Assume that amperage and voltage output from a VFD may fluctuate
significantly. Whenever possible, configure trend data collection for both values. If a voltage
trend is unavailable, take multiple spot voltage readings at various VFD speeds or consider
installing a temporary power data logger.
Multifamily Direct Install Conclusions and Recommendations
Evaluated electricity savings show a 105% realization rate on evaluated savings of 747,227 kWh for MFDI
programs, representing 58% of the savings goal for the year.

4
Cadmus offers the following conclusions and recommendations to improve Avista’s MFDI electric
programs:
• The MFDI program is an efficient, effective mechanism for installing high-efficiency lighting and
aerators in multifamily units.
§ Recommendation: Continue to focus on replacing high-use, low-efficiency lamps where
practical to maximize program cost-effectiveness and maintain high savings.
• The MFDI program used outdated Regional Technical Forum (RTF) UES values for showerhead
measures and RTF UES values for aerator measures that were not appropriate for MFDI’s
building stock.
§ Recommendation: Use the most current RTF UES values that are appropriate for the MFDI
program’s building stock to calculate reported savings. Ensure that the TRM provides values
and cites sources for all measures. Review the TRM annually and check if updated values are
available for any TRM measures using RTF workbooks as a source.
• All supplemental lighting program savings calculations had undefined HOU values and some
were missing space identifiers in the provided audit data which complicated verification.
§ Recommendation: Ensure methodology documentation and reported savings inputs are
accurate and provided for all site data.
Fuel Efficiency Conclusions and Recommendations
Multifamily Market Transformation (MFMT) Fuel Efficiency measures achieved evaluated savings of
489,597 kWh, yielding a 93% realization rate, and achieved 103% of the electric energy savings goal of
476,000 kWh.
Cadmus offers the following conclusions and recommendations to improve Avista’s Fuel Efficiency
measures:
• Avista’s deemed savings values for MFMT HVAC measures are intended for natural gas furnaces
and do not accurately estimate savings for central boiler systems because they have additional
energy consumption from pumps; experience heat loss in the piping system between the boiler
and the conditioned space; and have substantially different equipment sizing, heat transfer
properties, and fuel consumption.
§ Recommendation: Only use deemed savings in this program for standard forced air gas
furnaces that directly heat residential spaces. Analyze eligible projects with any other type
of equipment using a Site Specific approach, which may require a custom energy model for
that particular building.
• Avista’s deemed savings values for MFMT HVAC measures overestimate savings for buildings
with more than one middle floor, because they assume a three-story building with a ground,
middle, and top floor.
§ Recommendation: Include a place for MFMT HVAC applications to confirm the number of
floors in the building and should apply a weighted average of the deemed savings for

5
ground, middle, and top floors when a building does not have the standard three-story
layout.

6
Nonresidential Impact Evaluation
Through its Nonresidential portfolio of programs, Avista promotes the purchase of high-efficiency
equipment to commercial and industrial utility customers. Avista provides rebates to partially offset the
difference in cost between high-efficiency equipment and standard equipment. Cadmus conducted
Nonresidential impact evaluation activities to determine evaluated savings for most programs; the team
conducted measurement and verification (M&V) of Prescriptive and Site Specific projects across the full
sample.
Program Summary
Avista completed and provided incentives for 1,011 Nonresidential electric measures in Idaho during
PY 2020 and reported total electric energy savings of 12,665,993 kWh. Through the Nonresidential
sector, Avista offers incentives for high-efficiency equipment and controls through three program paths:
Prescriptive, Site Specific, and Multifamily Market Transformation.
The Prescriptive program path applies to smaller, straightforward equipment installations that generally
have similar operating characteristics (such as lighting, simple HVAC systems, food service equipment,
and VFD). The Site Specific program path applies to more unique projects that require custom savings
calculations and technical assistance from Avista’s account executives (such as compressed air, process
equipment and controls, and comprehensive lighting retrofits).
Multifamily Market Transformation, a Site Specific program, prompts building owners and developers to
consider natural gas as the fuel of choice when constructing new multifamily housing. These measures,
represented by a combination of electric savings and natural gas penalties, typically involve replacing
electric space-heating or water-heating systems with natural gas equipment. See the Fuel Efficiency
Impact Evaluation section for a discussion of the evaluation methodology and results for the
Nonresidential Fuel Efficiency measures.
Program Participation Summary
This section summarizes Nonresidential sector participation and progress toward PY 2020 goals through
the Prescriptive and Site Specific program paths.
Nonresidential Prescriptive Program Path
Table 3 shows electric energy savings goals assigned to Avista’s Nonresidential Prescriptive program
path for PY 2020 as well as reported savings and a comparison between reported savings and goals.
Avista’s Nonresidential Prescriptive programs reported 128% of their collective savings goal in PY 2020.

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Table 3. Nonresidential Prescriptive Electric Savings
Program Name Savings Goals (kWh) Savings Reported
(kWh) Percentage of Goal
Interior Lighting 3,390,000 3,816,812 113%
Exterior Lighting 2,688,000 4,742,300 176%
Shell Measure 18,000 1,341 7%
Green Motors 41,000 52,038 127%
Motor Control (VFD) 76,000 0 0%
Fleet Heat 8,000 0 0%
Food Service Equipment 32,000 13,761 43%
AirGuardian 6,000 0 0%
Energy Smart Grocer 512,000 45,938 9%
Total 6,771,000 8,672,190 128%

Table 4 summarizes actual program participation.
Table 4. Nonresidential Prescriptive Participation by Project
Program Type Number of Applications Number of Measures
Interior Lighting 216 333
Exterior Lighting 306 553
Shell Measure 3 4
Green Motors 11 11
Motor Control (VFD) 0 0
Fleet Heat 0 0
Food Service Equipment 2 3
AirGuardian 0 0
Energy Smart Grocer 4 5
Totala 542 909
a Total participants. A single application may contain measures from multiple programs.

Nonresidential Site Specific Program Path
Table 5 shows electric savings goals assigned to the Site Specific program path in Avista’s Nonresidential
sector for PY 2020, reported savings, and the percent of goal achieved. The table does not include
reported electric savings for the Fuel Efficiency sector, such as those associated with the Multifamily
Market Transformation program. The Site Specific program reported 51% of its PY 2020 savings goal,
with participation reduced likely due to the COVID-19 pandemic.
Table 5. Nonresidential Site Specific Electric Savings
Program Path Savings Goals (kWh) Savings Reported (kWh) Percentage of Goal
Site Specific 7,773,000 3,993,803 51%

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Table 6 summarizes actual program participation for the Site Specific program.
Table 6. Nonresidential Site Specific Participation by Project
Program Number of Applications Number of Measures
Site Specific Lighting 29 95
Site Specific Other 7 7
Total 36 102

Nonresidential Impact Evaluation Methodology
As the first step in evaluating savings for the Nonresidential sector, Cadmus reviewed the following
documents and data records to gain an understanding of the programs and measures slated for
evaluation:
• Avista’s annual business plans, processes, and energy savings justifications
• Project documents from external sources (such as customers, program consultants, or
implementation contractors)
• Avista’s iEnergy tracking system for Nonresidential programs
Based on the initial review, Cadmus checked the distribution of program contributions with the overall
program portfolio. The review provided insight into the sources for unit energy savings (UES) claimed for
each measure offered in the programs, along with sources for energy-savings algorithms, internal
quality assurance, and quality control processes for large Nonresidential sector projects.
Following this review, Cadmus designed a sample strategy for impact evaluation activities and
performed the following evaluation activities in two waves:
• Selected evaluation sample and requested project documentation from Avista
• Reviewed project documentation
• Prepared virtual site-visit M&V plans
• Performed virtual site visits using the Streem platform and collected on-site data (such as trend
data, photos, and operating schedules)1
• Used virtual site-visit findings to calculate evaluated savings by measure
• Applied realization rates to the total reported savings population to determine overall evaluated
savings

1 For more information on Streem: https://www.streem.com/platform-streem#platform-remote-video

9
Sample Design
Cadmus created two sample waves for PY 2020:
• Sample 1 included program data from January 2020 through June 2020.
• Sample 2 included program data from July 2020 through December 2020.
Cadmus initially estimated the total annual population size by reviewing the wave 1 population data and
comparing it to 2018-2019 population data. Cadmus developed initial sample size targets to achieve
90% confidence at ±10% precision (90/10) for the estimated annual population for 2020, with a target of
90/20 by program. After receiving the wave 2 population data, Cadmus revised the annual sample size
targets for the full year and selected the wave 2 sample to complete the revised target within each
program.
Avista advised Cadmus not to evaluate certain programs with low participation and historically
consistent realization rates every year. Since the Green Motors Program has shown a 100% realization
rate in every prior evaluation, Cadmus did not evaluate the program in PY 2020 and does not plan to
evaluate the program in PY 2021. Cadmus plans to evaluate the food services program only in PY 2020,
and the energy smart grocer and prescriptive shell programs only in PY 2021. Cadmus evaluated all
other Nonresidential programs that had participation in PY 2020.
For each activity wave, Cadmus developed a stratified random sample of applications by program (such
as Site Specific other, Site Specific lighting, Prescriptive interior lighting, or Prescriptive motor controls).
In programs where individual projects represented a significant portion of the total savings in the
program, the team selected the highest-savings applications with certainty. Within programs with a
wide variance in savings, the team further stratified non-certainty applications by reported savings
magnitude into small and medium strata, each with approximately 50% of the total non-certainty
program savings. The team assigned random numbers within each stratum to select a random sample of
non-certainty sites. In some cases, Cadmus selected additional applications at the same location as a
previously selected application to evaluate as a convenience selection if the team could assess both
applications in a single virtual visit.
Cadmus encountered some challenges contacting customers to evaluate the wave 1 sample, primarily
due to changes in business operations as a result of the COVID-19 pandemic. The team pulled an
additional backup sample for the wave 2 sample using random sampling and recruited participants from
the backup sample when participants from the initial random sample were unreachable.
The team pooled results from the randomly selected sites to calculate a realization rate by stratum and
applied that realization rate to projects in the population in that stratum. Cadmus applied the project-
specific evaluated savings for every project that was in the sample, regardless of whether it was a
random, certainty, or convenience selection.
Table 7 summarizes the Idaho Nonresidential Prescriptive program path evaluation sample. Cadmus
sampled 41 Prescriptive applications at 32 unique sites. Of the sampled applications, the team selected
five for certainty review based on the scale of savings, selected the 29 randomly, and selected seven

10
additional convenience projects based on location. There was no participation in the AirGuardian, fleet
heat, and motor control programs in PY 2020 as shown in Table 4. Table 7 shows the total number of
unique application IDs sampled in each program, including three applications containing measures from
more than one program.
Table 7. Idaho Nonresidential Prescriptive Electric Evaluation Sample
Program Type Applications Sampleda Sampled Savings (kWh) Percentage of Reported Savings
Interior Lighting 19 1,589,327 42%
Exterior Lighting 22 947,468 20%
Shell Measure 0 0 N/A
Green Motors 0 0 N/A
Food Service Equipment 2 13,761 100%
AirGuardian 0 0 N/A
Energy Smart Grocer 1 3,060 7%
Nonresidential Prescriptive 41 2,553,616 29%
a Three applications included measures in the interior lighting and exterior lighting programs, but each measure is only
counted once in the total.

Table 8 summarizes the Idaho Nonresidential Site Specific program path’s evaluation sample, where
Cadmus sampled 12 Site Specific applications at 12 unique sites overall. Of the sampled applications, the
team selected three for certainty review based on the savings scale and selected the remaining nine
applications randomly.
Table 8. Idaho Nonresidential Site Specific Electric Evaluation Sample
Program Path Applications Sampled Sampled Savings (kWh) Percentage of Reported Savings
Site Specific 12 2,366,694 59%

Document Review
Cadmus requested and reviewed project documentation for each sampled application and prepared
M&V plans to guide its site visits. Typically, each set of project documentation included data entered
into the iEnergy system, incentive application forms, calculation workbooks, invoices, equipment
specification sheets, and IV reports.
Remote Verification
Cadmus performed virtual site visits and verification calls at 36 unique Nonresidential locations and
verifications at 36 unique Nonresidential locations to assess electric savings for 102 unique Prescriptive
and Site Specific measures (not including Fuel Efficiency measures) from 44 different applications.
Cadmus evaluated the remaining nine applications through desk reviews that did not require participant
outreach. The team typically conducted virtual site visits using the Streem platform that records video
and audio. The visits involved a detailed walkthrough to verify installed equipment types, make and
model numbers, operating schedules, and set points, as applicable. The team conducted some virtual
visits using Microsoft Teams meetings if customers were unable to access Streem or preferred using
Teams due to prior familiarity. Verification calls involved a brief phone or video call to confirm key

11
details and any information missing from the project documentation. Cadmus used the project
documentation review and on-site findings to adjust reported savings calculations, where necessary.
Nonresidential Impact Evaluation Findings
This section summarizes electric impact evaluation findings for the Nonresidential Prescriptive and Site
Specific program paths in PY 2020.
Prior to this program year, Avista completed a transition from its previous InforCRM system to the new
iEnergy system to track Nonresidential energy efficiency applications and measures. Cadmus found that
the additional detail provided by the iEnergy system facilitated conducting a detailed and
comprehensive evaluation. For example, the iEnergy system reports detailed information about each
lighting measure, including existing and installed model number, wattage, quantity, and HOU. This
facilitated Cadmus’ evaluation and allowed it to partially automate the generation of M&V plans and
some analysis tables.
The team did encounter some challenges with inconsistent data in report extracts from iEnergy
(i.e., reports with duplicated records) and developed additional quality control processes to identify
such issues, working with Avista’s technical staff to resolve them. In addition, Cadmus found variation of
up to 2% between reported and evaluated savings on Prescriptive lighting projects due to iEnergy
rounding an intermediate value in kilowatt units to two decimal places. The level of variance is
equivalent to rounding the lighting wattage to the nearest 10 watts. Avista continues to work with the
iEnergy vendor to improve the system and integrate feedback.
Cadmus had difficulty verifying exact quantities of installed equipment for some projects at larger
facilities where customers often did not know where program equipment was installed or could not
recall which equipment was installed during which project if they had completed multiple applications
over the course of the year. As such, Cadmus assumed quantities based on invoices in some cases and
was not able to definitively verify the installation. This could lead to lower evaluated savings in the
future if only a portion of the installed equipment is located during a site visit.
In addition, Cadmus found that the level of detail varied in IV reports. Many IV reports only mentioned
that “equipment and quantities were verified,” and sometimes the photos only showed the equipment
from a distance. One IV report showed photos of lamps submitted under the interior lighting program
installed in an exterior location. These issues made it more difficult to determine accurate measure
details on various projects.
Nonresidential Prescriptive Programs
Table 9 shows reported and evaluated electric energy savings for Avista’s Nonresidential Prescriptive
program path as well as the realization rates between the evaluated and reported savings for PY 2020.
The overall Nonresidential Prescriptive program path achieved a 76% electric realization rate.

12
Table 9. Nonresidential Prescriptive Electric Impact Findings
Program Type Reported Savings (kWh) Evaluated Savings (kWh) Realization Rate
Interior Lighting 3,816,812 3,944,956 103%
Exterior Lighting 4,742,300 2,552,295 54%
Shell Measure 1,341 1,341 100%
Green Motors 52,038 52,038 100%
Food Service Equipment 13,761 13,761 100%
AirGuardian 0 0 N/A
Energy Smart Grocer 45,938 45,938 100%
Nonresidential Prescriptive 8,672,190 6,610,329 76%

Of 41 evaluated applications, Cadmus identified discrepancies for 36, based on virtual site visits,
verification calls, and project documentation review. Table 10 summarizes the reasons for discrepancies
between reported and evaluated savings.
Table 10. Nonresidential Prescriptive Evaluation Summary of Discrepancies
Project Type Number of
Occurrences Savings Impact Reason(s) for Discrepancy
Interior Lighting
7 ↓
• Cadmus found that two projects were inaccurately categorized as
Interior lighting projects rather than exterior lighting projects.
Evaluated savings for these projects were removed from the
Interior lighting program and added to the exterior lighting
program.
• Cadmus determined that the HOU for four projects were lower
than reported on the applications after interviewing on-site staff.
• Cadmus verified that one project had installed fewer LED lamps
than reported. Several linear LED lamps were found in storage
and not yet installed in some fixtures throughout the facility,
lowering the evaluated savings.
5 ↑ • Cadmus determined that the HOU for five projects were higher
than reported on the applications after interviewing on-site staff.
Exterior Lighting
17 ↓
• Cadmus found that the installed fixtures for two projects had a
higher wattage than reported on the application.
• Cadmus found one project that was categorized as a new
construction measure but involved removing five existing higher
wattage LED wall pack fixtures and installing three LED flood
lights in their place. Cadmus adjusted savings to include an
estimated baseline wattage for the removed LED wall packs.
• Cadmus evaluated 14 sign lighting projects by calculating the
difference in energy use between the baseline and installed
lamps, rather than applying a deemed value per square footage
of the sign. Cadmus determined the deemed values
overestimated savings.
2 ↑
• Cadmus found that two projects were inaccurately categorized as
interior lighting projects rather than exterior lighting projects.
Evaluated savings for these projects were removed from the
interior lighting program and added to the exterior lighting
program.

13
Project Type Number of
Occurrences Savings Impact Reason(s) for Discrepancy
5 ↓↑
• Cadmus found that some projects had discrepancies due to
rounding differences. iEnergy rounds the kilowatt savings to two
decimal places in the middle of the calculation, causing a loss of
accuracy in the final savings. This correction resulted in a
decrease in savings for two projects and an increase in savings for
three.

Cadmus found that verified lighting HOU varied from reported HOU in some interior and exterior
lighting projects. Several projects reported correct weekly HOU but did not operate the lights every
week of the year. Other projects had different weekly or daily operating hours than reported.
Cadmus notified Avista in January 2021 of systematic savings discrepancies in sign lighting measures
within the Prescriptive exterior lighting program. The team observed a significant increase in sign
lighting measures in PY 2020 and found consistently low realization rates on the sign lighting measures
evaluated. Avista applied deemed savings of 107.2 kWh per square foot of signage replaced, based on a
2014 internal engineering review that assumed 8-foot T12 high-output fluorescent lamps as the baseline
for all sign lighting. Cadmus evaluated sign lighting projects by verifying the quantity, wattages, and HOU
for the baseline and installed lamps in each sign by visual confirmation through video or by reviewing
invoices and IV report photos. In cases where documentation was insufficient and customers were
unable to access the sign, Cadmus estimated lamp quantities and lengths based on the shape and size of
the sign. Cadmus calculated savings as the difference in energy use between the actual baseline and
installed lighting equipment it verified. In every case, this evaluation methodology resulted in a lower
evaluated savings, and Cadmus found an average realization rate of 26% across the evaluated sign
lighting measures. Avista planned to implement changes to the sign lighting measure effective April 15,
2021, to address these concerns. The team did not find any systematic discrepancies with other exterior
lighting measures. The realization rate for non-sign lighting exterior lighting measures was 96%.
Nonresidential Site Specific Program
Table 11 shows reported and evaluated electric energy savings for Avista’s Nonresidential sector Site
Specific program path for the program year. The overall Site Specific program path had a 103% electric
realization rate. The table does not include reported and evaluated electric savings for measures in the
Fuel Efficiency path.
Table 11. Nonresidential Site Specific Electric Impact Findings
Program Path Reported Savings (kWh) Evaluated Savings (kWh) Realization Rate
Site Specific 3,993,803 4,113,196 103%

Of 12 evaluated applications, Cadmus identified discrepancies in six, based on virtual site visits and
project documentation review. Table 12 summarizes the reasons for discrepancies between reported
and evaluated savings.

14
Table 12. Nonresidential Site Specific Evaluation Summary of Discrepancies
Project Type Number of
Occurrences
Savings
Impact Reason(s) for Discrepancy
Interior Lighting 2 ↑
• Cadmus found increased savings for one project that added new
lighting controls, which had not been accounted for in the reported
savings. The lighting controls reduced the installed fixture wattage by
dimming the lights throughout the space.
• Cadmus zeroed out negative savings for one line item, which should not
have been approved, where the installed wattage was higher than the
existing wattage. This measure did not receive an incentive but was
erroneously included in the reported savings.
Motor Control
(VFD) 1 ↑
• The original analysis for a paper mill wastewater pump VFD project
assumed a constant output voltage based on a single spot
measurement and a 0.95 power factor from the variable frequency
drive (VFD). Cadmus updated the analysis to estimate the energy use
with the VFD with a 0.88 power factor based on the motor
specifications and using the metered output voltage via the industrial
control system trends, which showed the voltage varied significantly.
Exterior Lighting 1 ↑
• Cadmus determined that the HOU for one sign lighting project was
higher than reported through interviews with on-site staff. Unlike the
prescriptive sign lighting projects, this project did not apply a deemed
savings value to determine reported savings.
Compressed Air 1 ↓
• Air compressor VFD power data were rounded in the original analysis
files. Cadmus did not round any intermediate numbers, which resulted
in slightly lower evaluated savings.
Refrigeration 1 ↓
• Cadmus found that the original analysis included unrelated equipment
in the baseline energy use. The project removed two self-contained
freezers that were not replaced with energy-efficient equipment.
Cadmus confirmed that the two freezers were removed because the
site no longer sold frozen products. Cadmus updated the analysis to
exclude unrelated freezer equipment in the baseline energy use
calculation, decreasing baseline energy use and decreasing savings.

Cadmus found that reported fixture quantities for Site Specific lighting projects often did not match
invoice quantities, and applications often lacked detailed notes explaining these differences. Cadmus
also noted that many M&V plans, pre-installation verifications, and IV reports relied on customer-
provided photos and data because Avista staff could not safely visit the site due to the COVID-19
pandemic. It is likely that some of the discrepancies identified above may have been avoided had Avista
been able to conduct thorough in-person inspections before and after the project to verify the baseline
and installed equipment.
Nonresidential Conclusions and Recommendations
The Nonresidential sector achieved total evaluated electric energy savings of 10,724 MWh in PY 2020,
with a combined realization rate of 85%. The Nonresidential sector did not meet the combined
Prescriptive and Site Specific program paths’ electric goal of 15,020 MWh, with the program achieving
71% of its goal.

15
Although some individual project results varied, particularly within the Prescriptive exterior lighting
program, the overall Nonresidential sector performed strongly in PY 2020 relative to reported savings.
Most projects that Cadmus sampled for the evaluation were well documented and matched findings
from the remote project verifications.
Cadmus offers the following conclusions and recommendations to improve the Nonresidential sector’s
energy savings:
• Avista’s new iEnergy system has the capability to automatically calculate more detailed energy
savings estimates since it records additional detailed inputs on some prescriptive measures that
were not previously tracked in InforCRM. Some of these inputs are not currently used in the
savings calculations.
§ Recommendation: Review deemed savings values for prescriptive measures and consider
opportunities to leverage the additional data now collected in iEnergy to calculate more
accurate savings for each participant project. For example, food service measures can use
the reported pounds of food cooked per day and cooking hours per day values collected in
iEnergy to automatically calculate more precise savings.
• The iEnergy system introduced variance of up to 2% between reported and evaluated savings by
rounding intermediate wattage calculation values.
§ Recommendation: Review iEnergy calculations to ensure that rounding is only applied on
final displayed values and not to any intermediate values.
• Customer uncertainty on where program equipment was installed created challenges for
verifying installed quantities and may have contributed to reduced realization rates for projects
where verified quantities were less than reported.
§ Recommendation: Update all application forms to include space for location notes for each
installed measure and encourage contractors installing equipment at very large facilities to
include installation location with equipment invoices.
• Variations in the level of detail in Avista IV reports introduced additional complexity in
evaluating accurate measure counts, types, and operating parameters.
§ Recommendation: Provide more consistent documentation with IV reports. Cadmus
recommends that all IV reports include basic information to explicitly state the quantity and
type of equipment found. For lighting projects, this would include confirmed fixture types,
quantities, installation locations, controls, and estimated HOU. For most other equipment,
this would include nameplates, model numbers, and quantities.
• The evaluated lighting HOU for interior and exterior lighting projects did not always align with
reported values.
§ Recommendation: Review HOU estimates when processing applications and conducting
installation verifications. When entering average weekly HOU, confirm how many weeks per
year that schedule applies. In particular, Avista should apply additional scrutiny to
applications claiming 8,760 hours per year.

16
• Discrepancies between reported fixture quantities and invoice quantities added complexity and
uncertainty in evaluating the Site Specific lighting program. It is often impractical for Avista staff
conducting IV inspections or evaluators conducting verification visits to count every fixture for
large lighting projects, necessitating a greater reliance on project documentation.
§ Recommendation: Include more detailed documentation for Site Specific lighting projects.
Lighting drawings should be provided whenever possible, and if any other notes,
spreadsheets, or other documentation are used to determine eligible quantities, these
should be included with the application records. Any difference between invoice quantities
and rebated quantities should be clearly explained.
• Avista may rely on spot measurements for values that vary during typical operation. The
submitted analysis for a Site Specific industrial process motor project assumed a fixed output
voltage from the VFD based on a single spot measurement, but the plant’s industrial control
system was capable of recording voltage trend data. Cadmus worked with the customer to add a
voltage trend and determined that the VFD voltage output actually varied significantly in daily
operation.
§ Recommendation: Assume that amperage and voltage output from a VFD may fluctuate
significantly. Whenever possible, configure trend data collection for both values. If a voltage
trend is unavailable, take multiple spot voltage readings at various VFD speeds or consider
installing a temporary power data logger.

17
Multifamily Direct Install (MFDI) Impact Evaluation
Cadmus designed the MFDI program’s impact evaluation to verify reported program participation and
energy savings. Since the 2018-2019 evaluation showed that billing analysis did not provide meaningful
evaluation results, Cadmus found that a database review was the most appropriate evaluation
approach. The team used data collected and reported in the tracking database, online application forms,
and Avista’s TRM and RTF values to evaluate savings. This approach provided a reasonable estimate of
achieved savings practical for each program, given its delivery method, magnitude of savings, and
number of participants.
Program Summary
In PY 2020, Avista completed and provided incentives for 1,001 living units, common areas, or installed
lighting fixtures in Idaho and reported total electric energy savings of 710,740 kWh. Participation is
defined as installed lighting fixtures for the MFDI supplemental lighting program and common areas or
living units served for the MFDI program.
The MFDI program includes two delivery channels:
• MFDI, which provides free direct-install measures to multifamily residences (five units or more)
and common areas.
• MFDI supplemental lighting, which revisits multifamily properties participating in the MFDI
program to install additional common area lighting.
Program Participation Summary
Table 13 shows savings goals assigned to Avista’s MFDI programs for PY 2020, in addition to reported
savings. During PY 2020, the response to the COVID-19 pandemic caused disruption to the MFDI
program’s direct-install design, forcing the third-party implementer to temporarily halt program
processes and implement changes that adapt to pandemic restrictions. As a result, the MFDI and MFDI
supplemental lighting programs did not meet savings goals, with reported savings achieving 55% of the
savings goal for MFDI programs.
Table 13. MFDI Programs Reported Electric Savings
Program Savings Goals (kWh) Savings Reported (kWh) Percentage of Goal
Multifamily Direct Install 595,000 510,265 86%
Multifamily Direct Install Supplemental Lighting 694,000 200,474 29%
MFDI Programs Total 1,289,000 710,740 55%

Table 14 summarizes reported participation in the MFDI programs for PY 2020.

18
Table 14. MFDI Programs Participation
Program Participation Reported
Multifamily Direct Installa 767
Multifamily Direct Install Supplemental Lightingb 234
MFDI Programs Total 1,001
a Participation is defined as the number of living units and common areas served.
b Participation is defined as the number of installed units.

Lighting measures accounted for 79% of the total MFDI programs’ electricity savings. The following
shows the percentage of MFDI reported savings provided by each program:
• MFDI lighting measures provided 51% of reported savings.
• MFDI non-lighting measures provided 21% of reported savings.
• MFDI supplemental lighting program provided 28% of reported savings.
Multifamily Direct Install Impact Evaluation Methodology
To determine the MFDI program’s evaluated savings for PY 2020, Cadmus employed a database review.
For the impact evaluation database review, Cadmus applied UES values provided in the TRM and by the
RTF to calculate savings for measures reported in the measure tracking database. Such impact activity
may help identify incorrect UES values used to calculate reported savings. For this evaluation, Cadmus
applied 2020 Avista TRM values to PY 2020 measures.
Multifamily Direct Install Impact Evaluation Results
Cadmus used the results of the database review to evaluate savings for each measure. The analysis then
rolled up measure-level evaluated savings to calculate evaluated savings and a realization rate for each
program. Table 15 shows the resulting evaluated savings and realization rates.
Table 15. MFDI Programs Electric Impact Findings
Program Reported Electric
Savings (kWh)
Adjusted Electric
Savings (kWh)
Realization
Rates
Multifamily Direct Install 510,265 542,451 106%
Multifamily Direct Install Supplemental Lighting 200,474 204,776 102%
MFDI Programs Total 710,740 747,227 105%

The discrepancies between evaluated and reported savings for the MFDI program were a result of
reported savings calculations using UES values for non-lighting measures (aerators and showerheads)
that were lower than the UES values provided by the most recent RTF workbooks. Specifically, reported
savings for showerheads used UES values from Avista’s most recent TRM that did not reflect the most
recent RTF UES values. The implementer confirmed it used UES values from the most recent TRM to
calculate reported savings for showerheads, but not the most recent RTF revision. Cadmus evaluated
reported savings using the RTF’s most recent 2019 RTF UES value for showerheads. Reported savings for
aerators used a conservative weighted average UES value that would allow for some aerators with heat
pump water heaters. However, Cadmus determined that the aerator UES value for electric resistance

19
water heater types is more appropriate for the building stock served by the MFDI program. The
implementer accepted this recommendation, and Cadmus evaluated savings using the 2019 RTF UES
value for aerators with electric resistance water heater types.
Cadmus also identified instances where evaluated realization rates were low for lighting measures
because the implementer did not properly account for electric heating interaction effects in common
area spaces. In addition, Cadmus found reported savings calculations for lighting measures that did not
account for the savings that come from cooling interaction effects in interior spaces. However, the
evaluated savings that resulted in fully realized or higher realization rates for lighting and non-lighting
measures in the MFDI program outweighed those with low realization rates.
The discrepancies between evaluated and reported savings for the MFDI supplemental lighting program
resulted from the contractors’ use of undefined annual HOU in the reported savings calculations instead
of those hours consistent with the savings calculations methodology and site data provided. Cases with
undefined HOU exceeded 100% realization since these hours were lower than those documented in the
calculation methodology and site data provided. In addition, Cadmus could not verify the interior or
exterior lighting HOU for some of these spaces because the assigned identification numbers could not
be found in the accompanying audit data.
Multifamily Direct Install Conclusions and Recommendations
Evaluated electricity savings show a 105% realization rate on evaluated savings of 747,227 kWh for MFDI
programs, representing 58% of the savings goal for the year.
Cadmus offers the following conclusions and recommendations to improve Avista’s MFDI electric
programs:
• The MFDI program is an efficient, effective mechanism for installing high-efficiency lighting and
aerators in multifamily units.
§ Recommendation: Continue to focus on replacing high-use, low-efficiency lamps where
practical to maximize program cost-effectiveness and maintain high savings.
• The MFDI program used outdated RTF UES values for showerhead measures and RTF UES values
for aerator measures that were not appropriate for MFDI’s building stock.
§ Recommendation: Use the most current RTF UES values that are appropriate for the MFDI
program’s building stock to calculate reported savings. Ensure that the TRM provides values
and cites sources for all measures. Review the TRM annually and check if updated values are
available for any TRM measures using RTF workbooks as a source.
• All Supplemental Lighting Program savings calculations had undefined HOU values and some
were missing space identifiers in the provided audit data which complicated verification.
§ Recommendation: Ensure methodology documentation and reported savings inputs are
accurate and provided for all site data.

20
Fuel Efficiency Impact Evaluation
Cadmus designed the Fuel Efficiency sector impact evaluation to verify reported program participation
and energy savings. Evaluation methods included a database review and document review.
Program Summary
Fuel Efficiency measures replace electric space heating or water heating systems with equipment using
natural gas. These measures are offered within the Nonresidential Site Specific program path, which
includes MFMT measures. From this program, Avista reported electric energy savings of 528,727 kWh
for four Fuel Efficiency measures.
Fuel Efficiency measures provide positive electricity savings and negative natural gas savings, reflecting
negative avoided costs. Cadmus incorporated these negative avoided costs in the electric cost-
effectiveness calculations and reported the negative natural gas consumption impacts in the PY 2020
Idaho Natural Gas Impact Evaluation Report.
Program Participation Summary
This section summarizes Fuel Efficiency sector participation and progress toward PY 2020 goals for the
MFMT path.
Table 16 shows savings goals, reported savings, and percentage of goal for the MFMT path. Avista did
not set savings goals for the Site Specific Fuel Efficiency measures outside of the MFMT path.
Table 16. Avista Portfolio Fuel Efficiency Reported Electric Savings
Program Savings Goals (kWh) Reported Savings (kWh) Percentage of Goal
Multifamily Market Transformation 476,000 528,727 111%

Table 17 shows Avista’s PY 2020 reported participation for the MFMT measures. Avista did not set
participation goals for Site Specific Fuel Efficiency measures. There were four MFMT participants in
PY 2020.
Table 17. Avista Portfolio Fuel Efficiency Reported Participation
Fuel Efficiency Measure Participation Reported
Multifamily Market Transformation 4
Fuel Efficiency Impact Evaluation Methodology
The impact methodology for Fuel Efficiency measures is outlined below for the Nonresidential Site
Specific program path.
Nonresidential Site Specific Fuel Efficiency Impact Methodology
Cadmus followed the same impact evaluation methodology for Fuel Efficiency measures as outlined in
the Nonresidential Impact Evaluation Methodology section. Cadmus sampled two MFMT applications.
Of the sampled applications, the team selected one for certainty review based on the savings scale and
selected one randomly.

21
Fuel Efficiency Impact Evaluation Results
The following section summarizes findings for the Nonresidential Site Specific program path. All Fuel
Efficiency measures provide positive electricity savings and negative natural gas consumption impacts
because these measures replace electric space heating or water heating systems with equipment that
uses natural gas. Negative natural gas consumption impacts reflect negative avoided costs and are
incorporated in the electric cost-effectiveness calculations. The team also report these negative natural
gas consumption impacts in the PY 2020 Idaho Natural Gas Impact Evaluation Report.
Nonresidential Fuel Efficiency Impact Findings
Table 18 shows reported and evaluated electric energy savings for Avista’s Nonresidential Fuel Efficiency
measures, along with realization rates, through PY 2020.
Table 18. Nonresidential Fuel Efficiency Electric Impact Findings
Fuel Efficiency Measure Reported Savings (kWh) Evaluated Savings (kWh) Realization Rate
Multifamily Market Transformation 528,727 489,597 93%
Total 528,727 489,597 93%

Cadmus identified discrepancies for one high-rise residential tower project that installed a central boiler
and chiller system. Avista used the typical deemed savings values for MFMT HVAC measures. Avista
developed these savings values through an internal engineering study using building simulation
modeling. The savings values are based on the number of apartment units and the rated efficiency of
natural gas furnaces replacing electric resistance heaters, and assume a three-story building with a
ground, middle, and top floor. This building had 16 middle floors of residential units, while the ground
and top floors did not have residential units. Although this project was eligible per the program criteria,
the deemed savings values were not designed to account for this type of installation because of the
building layout and because it installed boilers instead of furnaces. Cadmus adjusted the analysis to use
the deemed savings value for middle floor units only and to account for additional energy consumption
required for the boiler circulation pumps. These adjustments reduced energy savings because the
middle-floor units experience less heat loss relative to the ground- and top-floor units and because
pump energy is not required with gas furnace heating.
Fuel Efficiency Conclusions and Recommendations
MFMT Fuel Efficiency measures achieved evaluated savings of 489,597 kWh, yielding a 93% realization
rate, and achieved 103% of the electric energy savings goal of 476,000 kWh.
Cadmus offers the following conclusions and recommendations to improve Avista’s Fuel Efficiency
measures:
• Avista’s deemed savings values for MFMT HVAC measures are intended for natural gas furnaces
and do not accurately estimate savings for central boiler systems because they have additional
energy consumption from pumps; experience heat loss in the piping system between the boiler
and the conditioned space; and have substantially different equipment sizing, heat transfer
properties, and fuel consumption.

22
§ Recommendation: Only use deemed savings in this program for standard forced air gas
furnaces that directly heat residential spaces. Analyze eligible projects with any other type
of equipment using a Site Specific approach, which may require a custom energy model for
that particular building.
• Avista’s deemed savings values for MFMT HVAC measures overestimate savings for buildings
with more than one middle floor, because they assume a three-story building with a ground,
middle, and top floor.
§ Recommendation: Include a place for MFMT HVAC applications to confirm the number of
floors in the building and should apply a weighted average of the deemed savings for
ground, middle, and top floors when a building does not have the standard three-story
layout.
2020 Idaho Annual Conservation Report Appendices
APPENDIX B – 2020 IDAHO NATURAL GAS EVALUATION REPORT –
COMMERCIAL/INDUSTRIAL

PY 2020 Idaho Natural Gas
Impact Evaluation Report
April 16, 2020
Prepared for:
Avista Corporation
1411 East Mission Avenue
Spokane, WA 99202

i
Table of Contents
Portfolio Executive Summary ................................................................................................................ 1
Evaluation Methodology and Activities ................................................................................................. 1
Summary of Impact Evaluation Results ................................................................................................. 1
Conclusions and Recommendations ...................................................................................................... 1
Nonresidential Impact Evaluation ......................................................................................................... 3
Program Summary ................................................................................................................................. 3
Program Participation Summary ............................................................................................................ 3
Nonresidential Impact Evaluation Methodology ................................................................................... 4
Nonresidential Impact Evaluation Findings ........................................................................................... 7
Nonresidential Conclusions and Recommendations ............................................................................. 8
Fuel Efficiency Impact Evaluation .......................................................................................................... 9
Program Summary ................................................................................................................................. 9
Program Participation Summary ............................................................................................................ 9
Fuel Efficiency Impact Evaluation Methodology .................................................................................... 9
Fuel Efficiency Impact Evaluation Results .............................................................................................. 9
Fuel Efficiency Conclusions and Recommendations ............................................................................ 10

Tables
Table 1. Annual Natural Gas Program Evaluation Activities ......................................................................... 1
Table 2. PY 2020 Reported and Gross Evaluated Natural Gas Savings ......................................................... 1
Table 3. Nonresidential Prescriptive Natural Gas Savings ............................................................................ 4
Table 4. Nonresidential Prescriptive Participation by Project ...................................................................... 4
Table 5. Nonresidential Site Specific Natural Gas Savings ............................................................................ 4
Table 6. Nonresidential Site Specific Participation by Project ...................................................................... 4
Table 7. Idaho Nonresidential Prescriptive Natural Gas Evaluation Sample ................................................ 6
Table 8. Idaho Nonresidential Site Specific Natural Gas Evaluation Sample ................................................ 6
Table 9. Nonresidential Prescriptive Natural Gas Impact Findings .............................................................. 7
Table 10. Nonresidential Prescriptive Evaluation Summary of Discrepancies ............................................. 7
Table 11. Nonresidential Site Specific Natural Gas Impact Findings ............................................................ 8
Table 12. Avista Portfolio Fuel Efficiency Participation ................................................................................ 9

ii
Table 13. Nonresidential Fuel Efficiency Natural Gas Findings .................................................................. 10

1
Portfolio Executive Summary
For several decades, Avista Corporation (Avista) has administered demand-side management (DSM)
programs to reduce electricity and natural gas energy use by its customer portfolio. While most of these
programs have been implemented in house, a few have had external implementers.
Avista contracted with Cadmus to complete process and impact evaluations of its program year (PY) 2020
natural gas DSM Nonresidential and multifamily Residential programs in Idaho. This report presents the
natural gas impact evaluation findings. Cadmus did not apply net-to-gross (NTG) adjustments to savings
values, except where deemed energy savings values already incorporated NTG as a function of the market
baseline.
Evaluation Methodology and Activities
Cadmus used a variety of methods and activities to conduct the Idaho natural gas portfolio evaluation,
shown in Table 1.
Table 1. Annual Natural Gas Program Evaluation Activities
Sector Program Document/
Database Review
Verification/ Virtual Site
Visit
Nonresidential Prescriptive (Multiple) ü ü
Site Specific ü ü
Fuel Efficiency Site Specific (Nonresidential) ü --

Summary of Impact Evaluation Results
Overall, the Idaho portfolio achieved a 101% realization rate on savings from natural gas measures,
acquiring 29,503 therms in annual gross savings, as shown in Table 2. Cadmus collected Avista-reported
savings through database extracts, drawn from Avista’s iEnergy database.
Table 2. PY 2020 Reported and Gross Evaluated Natural Gas Savings
Sector Reported Savings (therms) Gross Evaluated Savings (therms) Realization Rate
Nonresidential 29,315 29,503 101%
Total 29,315 29,503 101%

Conclusions and Recommendations
During the course of the annual evaluation, Cadmus identified the areas addressed below for
improvements by sector.
Nonresidential Conclusions and Recommendations
The Nonresidential sector achieved total evaluated natural gas energy savings of 29,503 therms in
PY 2020, with a combined realization rate of 101%. The Nonresidential sector did not meet the
combined Prescriptive and Site Specific program paths’ natural gas savings goal of 82,680 therms, with
the program achieving 36% of its goal.

2
The Nonresidential gas sector performed strongly in PY 2020 relative to reported savings. Most projects
that Cadmus sampled for the evaluation were well documented and matched findings from the remote
project verifications.
Cadmus offers the following conclusion and recommendation to improve the Nonresidential sector’s
natural gas savings:
Avista’s new iEnergy system has the capability to automatically calculate more detailed energy savings
estimates since it records additional detailed inputs on some prescriptive measures that were not
previously tracked in InforCRM. Some of these inputs are not currently used in the savings
calculations.
Recommendation: Review deemed savings values for prescriptive measures and consider opportunities
to leverage the additional data now collected in iEnergy to calculate more accurate savings for
each participant project. For example, HVAC furnace measures can use the exact AHRI efficiency
rating collected in iEnergy instead of a typical average to automatically calculate more precise
savings.
Fuel Efficiency Conclusions and Recommendations
Nonresidential Site Specific and Multifamily Market Transformation (MFMT) Fuel Efficiency measures
resulted in evaluated natural gas penalties of 21,948 therms, yielding a 94% realization rate.

3
Nonresidential Impact Evaluation
Through its Nonresidential program portfolio, Avista promotes purchases of high-efficiency equipment
for commercial and industrial utility customers. By providing rebates, Avista partially offsets cost
differences between high-efficiency and standard equipment. Cadmus conducted Nonresidential impact
evaluation activities to determine evaluated savings for most programs; the team also conducted
measurement and verification (M&V) of Prescriptive and Site Specific projects across the full sample.
Program Summary
In PY 2020, Avista completed and provided incentives for 66 Nonresidential natural gas projects in
Idaho, reporting total natural gas energy savings of 29,315 therms. Through the Nonresidential sector,
Avista offers incentives for high-efficiency equipment and controls through three program paths:
Prescriptive, Site Specific, and Fuel Efficiency.
The Prescriptive program path serves smaller, straightforward equipment installations that generally
include similar operating characteristics (such as simple HVAC systems, food service equipment, and
envelope upgrades). The Site Specific program path serves more unique projects requiring custom
savings calculations and technical assistance from Avista’s account executives (such as process
equipment, controls, and comprehensive HVAC retrofits).
Multifamily Market Transformation measures involve a combination of electric savings and natural gas
penalties. Typically, these measures include replacing electric space-heating or water-heating systems
with natural gas equipment. The Fuel Efficiency Impact Evaluation section provides a discussion of the
evaluation methodology and the results for Multifamily Market Transformation measures.
Program Participation Summary
This section summarizes Nonresidential sector participation and progress toward PY 2020 goals through
the Prescriptive and Site Specific program paths.
Nonresidential Prescriptive Programs
Table 3 shows natural gas energy savings goals assigned to Avista’s Nonresidential Prescriptive programs
for PY 2020 as well as reported savings and a comparison between reported savings and goals. Avista’s
Nonresidential Prescriptive programs achieved 40% of their collective savings goal in PY 2020. The lower
participation is likely due to effects from the COVID-19 pandemic, which forced many businesses to
reduce their operations or close entirely. For those businesses that remained open, facility and
maintenance staff had to prioritize planning for health and safety impacts above energy efficiency
concerns.

4
Table 3. Nonresidential Prescriptive Natural Gas Savings
Program Type Savings Goals (therms) Savings Reported (therms) Percentage of Goal
HVAC 28,605 13,803 48%
Shell 26,000 1,821 7%
Food Service Equipment 18,075 13,597 75%
Total 72,680 29,221 40%

Table 4 summarizes actual program participation by unique application numbers.
Table 4. Nonresidential Prescriptive Participation by Project
Program Type Number of Applications Number of Measures
HVAC 33 40
Shell 4 5
Food Service Equipment 19 20
Totala 56 65
a Total participants. A single application may contain measures from multiple programs.

Nonresidential Site Specific Program
Table 5 shows natural gas savings goals assigned to the Site Specific program path for Avista’s
Nonresidential sector for PY 2020, reported savings, and the percent of goal achieved. The Site Specific
program achieved 1% of its savings goal, with participation likely reduced due to the effects of the
COVID-19 pandemic. The table does not include reported natural gas penalties for the Fuel Efficiency
sector, such as those associated with the Multifamily Market Transformation program.
Table 5. Nonresidential Site Specific Natural Gas Savings
Program Savings Goals (therms) Savings Reported (therms) Percentage of Goal
Site Specific 10,000 94 1%

Table 6 summarizes actual program participation for the Site Specific program.
Table 6. Nonresidential Site Specific Participation by Project
Program Type Number of Applications Number of Measures
Site Specific Other 1 1
Total 1 1

Nonresidential Impact Evaluation Methodology
As the first step in evaluating annual savings for the Nonresidential sector, Cadmus explored the
following documents and data records to gain an understanding of programs and measures slated
for evaluation:
Avista’s annual business plans, detailing processes and energy savings justifications
Project documents from external sources (such as customers, program consultants, or implementation
contractors)
Avista’s iEnergy tracking system for Nonresidential programs

5
Based on the initial review, Cadmus checked the distribution of program contributions with the overall
program portfolio. The review provided insight into the sources for unit energy savings (UES) claimed for
each measure offered in the programs, along with sources for energy-savings algorithms, internal
quality assurance, and quality control processes for large Nonresidential sector projects.
Following this review, Cadmus designed a sample strategy for impact evaluation activities and
performed the following evaluation activities in two waves:
Selected evaluation sample and requested project documentation from Avista
Reviewed project documentation
Prepared virtual site-visit M&V plans
Performed virtual site visits using the Streem platform and collected on-site data (such as trend data,
photos, and operating schedules)1
Used virtual site-visit findings to calculate evaluated savings by measure
Applied realization rates to total reported savings population to determine overall evaluated savings
Sample Design
Cadmus created two sample waves for PY 2020:
Sample 1 included program data from January 2020 through June 2020.
Sample 2 included program data from July 2020 through December 2020.
Cadmus initially estimated the total annual population size by reviewing the wave 1 population data and
comparing it to 2018-2019 population data. The team developed initial sample size targets to achieve
90% confidence at ±10% precision (90/10) for the estimated annual population for 2020, with a target of
90/20 by program. The team pulled the first sample wave to meet one-half of the total target for each
program. After receiving the wave 2 population data, Cadmus revised the annual sample size targets and
pulled the wave 2 sample to make up the revised target within each program.
Avista advised Cadmus not to evaluate certain prescriptive programs with low participation and
historically consistent realization rates every year. Cadmus plans to evaluate the food services and HVAC
programs in PY 2020 only, and the shell program in PY 2021 only. Cadmus evaluated all other
Nonresidential programs that had participation in PY 2020.
For each activity wave, Cadmus developed a stratified random sample of applications by program path
(such as Site Specific other, shell measure, or Prescriptive HVAC). In the programs where individual
projects represented a significant portion of the total savings in a program, the team selected the
highest-savings applications with certainty. For non-certainty applications, Cadmus assigned random
numbers and developed a random sample.

1 For more information about Streem: https://www.streem.com/platform-streem#platform-remote-video

6
Cadmus encountered some challenges contacting customers to evaluate the wave 1 sample, primarily
due to changes in business operations as a result of the COVID-19 pandemic. The team pulled an
additional backup sample for the wave 2 sample using random sampling and recruited participants from
the backup sample when participants from the initial random sample were unreachable.
The team pooled results from the randomly selected sites to calculate a realization rate by stratum and
applied that realization rate to projects in the population in that stratum. Cadmus applied the project-
specific evaluated savings for every project that was in the sample, regardless of whether it was a
random, certainty, or convenience selection.
Table 7 summarizes the Idaho Nonresidential Prescriptive program path natural gas evaluation sample.
Overall, Cadmus sampled 14 Prescriptive applications at 14 unique sites, selecting all applications
randomly. The team did not select any applications for certainty review.
Table 7. Idaho Nonresidential Prescriptive Natural Gas Evaluation Sample
Program Type Applications Sampled Sampled Savings (therms) Percentage of Reported Savings
HVAC 7 3,553 26%
Shell 0 0 0%
Food Service Equipment 7 4,490 33%
Nonresidential Prescriptive 14 8,043 28%
Note: totals may not sum due to rounding.

Table 8 summarizes the Idaho Nonresidential Site Specific program path’s natural gas evaluation sample.
Cadmus sampled one Site Specific application at one unique site. The team selected the sampled
application with certainty as it was the only gas participant in the Site Specific program.
Table 8. Idaho Nonresidential Site Specific Natural Gas Evaluation Sample
Program Applications Sampled Sampled Savings (therms) Percentage of Reported Savings
Site Specific 1 94 100%

Document Review
Cadmus requested and reviewed project documentation for each sampled application and prepared
M&V plans to guide the site visits. Typically, project documentation included data entered into the
iEnergy system, incentive application forms, calculation workbooks, invoices, equipment specification
sheets, and Avista installation verification (IV) reports.
Remote Verification
Cadmus performed verifications at 14 unique Nonresidential locations in Idaho to assess natural gas
energy savings for 17 unique Prescriptive and Site Specific measures (not including Fuel Efficiency
measures). Cadmus evaluated the remaining application through a desk review that did not require
participant outreach. Verification calls involved a brief phone call or video call to confirm key details and
any information that was missing in the project documentation. Cadmus typically conducted video calls
using the Streem platform that records video and audio. The team conducted some verifications using

7
Microsoft Teams meetings if customers were unable to access Streem or preferred using Teams due to
prior familiarity. Cadmus used the project documentation review and on-site findings to adjust the
reported savings calculations where necessary.
Nonresidential Impact Evaluation Findings
This section summarizes the Nonresidential Prescriptive and Site Specific program paths’ natural gas
impact evaluation results for PY 2020.
Prior to this program year, Avista completed a transition from its previous InforCRM system to the new
iEnergy system to track Nonresidential energy efficiency applications and measures. Cadmus found that
the additional detail provided by the iEnergy system facilitated conducting a detailed and
comprehensive evaluation. For example, the iEnergy system reports detailed information about each
HVAC measure, including furnace model number and rated capacity. This facilitated Cadmus’ evaluation
and allowed it to partially automate the generation of M&V plans and some analysis tables.
The team did encounter some challenges with inconsistent data in report extracts from iEnergy
(i.e., reports with duplicated records) and developed additional quality control processes to identify
such issues, working with Avista’s technical staff to resolve them. Avista continues to work with the
iEnergy vendor to improve the system and integrate feedback.
Nonresidential Prescriptive Programs
Table 9 shows the reported and evaluated natural gas energy savings for Avista’s Nonresidential
Prescriptive program path as well as realization rates between the evaluated and reported savings for
PY 2020. The overall Nonresidential Prescriptive program path achieved a 101% natural gas realization
rate.
Table 9. Nonresidential Prescriptive Natural Gas Impact Findings
Program Type Reported Savings (therms) Evaluated Savings (therms) Realization Rate
HVAC 13,803 13,992 101%
Shell 1,821 1,821 100%
Food Service Equipment 13,597 13,597 100%
Nonresidential Prescriptive 29,221 29,409 101%

Of 14 evaluated applications, Cadmus identified discrepancies for one based on the verification and
project documentation review. Table 10 summarizes the reasons for discrepancies between reported
and evaluated savings.
Table 10. Nonresidential Prescriptive Evaluation Summary of Discrepancies
Project Type Number of
Occurrences
Savings
Impact Reason(s) for Discrepancy
HVAC 1 ↑
• Cadmus found that the installed furnaces for one project were
multistage based on the model number and specifications rather than
single-stage as reported, which increased the evaluated savings.

8
Nonresidential Site Specific Program
Table 11 shows reported and evaluated natural gas energy savings for Avista’s Nonresidential Site
Specific program path for the program year. The overall Site Specific program path achieved a 100%
natural gas realization rate. The table does not include reported and evaluated natural gas penalties for
measures in the Fuel Efficiency path. Cadmus did not identify any discrepancies in the evaluated
application.
Table 11. Nonresidential Site Specific Natural Gas Impact Findings
Program Reported Savings (therms) Evaluated Savings (therms) Realization Rate
Site Specific 94 94 100%

Nonresidential Conclusions and Recommendations
The Nonresidential sector achieved total evaluated natural gas energy savings of 29,503 therms in
PY 2020, with a combined realization rate of 101%. The Nonresidential sector did not meet the
combined Prescriptive and Site Specific program paths’ natural gas savings goal of 82,680 therms, with
the program achieving 36% of its goal.
The Nonresidential gas sector performed strongly in PY 2020 relative to reported savings. Most projects
that Cadmus sampled for the evaluation were well documented and matched findings from the remote
project verifications.
Cadmus offers the following conclusion and recommendation to improve the Nonresidential sector’s
natural gas savings:
Avista’s new iEnergy system has the capability to automatically calculate more detailed energy savings
estimates since it records additional detailed inputs on some prescriptive measures that were not
previously tracked in InforCRM. Some of these inputs are not currently used in the savings
calculations.
Recommendation: Review deemed savings values for prescriptive measures and consider opportunities
to leverage the additional data now collected in iEnergy to calculate more accurate savings for
each participant project. For example, HVAC furnace measures can use the exact AHRI efficiency
rating collected in iEnergy instead of a typical average to automatically calculate more precise
savings.

9
Fuel Efficiency Impact Evaluation
Cadmus designed the Fuel Efficiency sector impact evaluation to verify reported program participation
and natural gas consumption impacts. Evaluation methods included a database review and document
review.
Program Summary
Fuel Efficiency measures replace electric space heating or water heating systems with equipment using
natural gas. These measures are offered within the Nonresidential Site Specific program path, which
includes MFMT measures. From this program, Avista reported a natural gas energy penalty of 23,338
therms for four Fuel Efficiency measures.
Fuel Efficiency measures provide positive electricity savings and negative natural gas consumption
impacts, reflecting negative avoided costs. Cadmus reported the electric energy savings in the PY 2020
Idaho Electric Impact Evaluation Report.
Program Participation Summary
This section summarizes Fuel Efficiency sector impact in PY 2020 for the MFMT path.
Table 12 shows Avista’s PY 2020 reported participation for MFMT Fuel Efficiency measures. Avista did
not set participation goals for Site Specific Fuel Efficiency measures. There were four MFMT participants
in PY 2020.
Table 12. Avista Portfolio Fuel Efficiency Participation
Program Participation Reported
Multifamily Market Transformation 4

Fuel Efficiency Impact Evaluation Methodology
The impact methodology for Fuel Efficiency measures is outlined below for the Nonresidential Site
Specific program path.
Nonresidential Site Specific Fuel Efficiency Impact Methodology
Cadmus followed the same impact evaluation methodology for Fuel Efficiency measures as outlined in
the Nonresidential Impact Evaluation Methodology section. The team sampled two MFMT applications.
Of the sampled applications, the team selected one for certainty review based on the savings scale and
selected one randomly.
Fuel Efficiency Impact Evaluation Results
The following section summarizes findings for the Nonresidential Site Specific program path. All Fuel
Efficiency measures provide positive electricity savings and negative natural gas consumption impacts
because these measures replace electric space-heating or water-heating systems with equipment that
uses natural gas. Negative natural gas consumption impacts reflect negative avoided costs and are

10
incorporated in the electric cost-effectiveness calculations. The team also report these positive electric
savings in the PY 2020 Idaho Electric Impact Evaluation Report.
Nonresidential Site Specific Fuel Efficiency Impact Findings
Table 13 shows reported and evaluated natural gas penalties for Avista’s Nonresidential Fuel Efficiency
measures, along with realization rates, through PY 2020.
Table 13. Nonresidential Fuel Efficiency Natural Gas Findings
Fuel Efficiency Measure Reported Consumption
Impacts (therms)
Evaluated Consumption
Impacts (therms) Realization Rate
Multifamily Market Transformation (23,338) (21,948) 94%
Total (23,338) (21,948) 94%

Cadmus identified discrepancies for one project, where Avista reported higher natural gas consumption
for the ground- and top-floor units due to heat loss. Cadmus found that all units were mid floor and
removed the ground- and top-floor natural gas consumption impacts. The electric impact evaluation
report discusses the causes and solutions for this issue in more detail. This project achieved a realization
rate of 92%.
Fuel Efficiency Conclusions and Recommendations
Nonresidential Site Specific and MFMT Fuel Efficiency measures resulted in evaluated natural gas
penalties of 21,948 therms, yielding a 94% realization rate.
2020 Idaho Annual Conservation Report Appendices
APPENDIX C – 2020 IDAHO ELECTRIC IMPACT EVALUATION REPORT –
RESIDENTIAL AND LOW-INCOME

Evaluation, Measurement and Verification
(EM&V) of Avista Idaho Electric PY2020
Residential and Low-Income Energy Efficiency
Programs
Prepared for:

Avista Corporation

Delivered on:
June 7, 2021

Prepared by:

ADM Associates, Inc.
3239 Ramos Circle
Sacramento, CA 95827
916.363.8383

In Partnership with:
Cadeo Group
107 SE Washington St, Suite 450
Portland, OR 97214

Tables of Contents and Tables ii
Table of Contents
1. Executive Summary ............................................................................................................................. 6
1.1 Savings & Cost-Effectiveness Results ......................................................................................................... 6
1.2 Conclusions and Recommendations .......................................................................................................... 7
2. General Methodology ........................................................................................................................ 13
2.1 Glossary of Terminology .......................................................................................................................... 13
2.2 Summary of Approach ............................................................................................................................. 14
3. Residential Impact Evaluation Results ............................................................................................... 27
3.1 Simple Verification Results ....................................................................................................................... 27
3.2 Impacts of COVID-19 Pandemic ............................................................................................................... 29
3.3 Program-Level Impact Evaluation Results ................................................................................................ 30
3.4 Conclusions and Recommendations ........................................................................................................ 49
4. Low-Income Impact Evaluation Results ............................................................................................. 53
4.1 Program-Level Impact Evaluation Results ................................................................................................ 53
4.2 Conclusions and Recommendations ........................................................................................................ 58
5. Appendix A: Billing Analysis Results ................................................................................................... 60
5.1 HVAC Program ......................................................................................................................................... 60
5.2 Fuel Efficiency Program ............................................................................................................................ 65
5.3 Low-Income Program ............................................................................................................................... 70
6. Appendix B: Summary of Survey Respondents .................................................................................. 74
7. Appendix C: Cost Benefit Analysis Results ......................................................................................... 76
7.1 Approach .................................................................................................................................................. 76
7.2 Non-Energy Benefits ................................................................................................................................ 78
7.3 Economic Inputs for Cost Effectiveness Analysis ..................................................................................... 79
7.4 Results ...................................................................................................................................................... 79

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List of Tables
Table 1-1: Residential Verified Impact Savings by Program ......................................................................... 6
Table 1-2: Low-Income Verified Impact Savings by Program ....................................................................... 6
Table 1-3: Cost-Effectiveness Summary ....................................................................................................... 7
Table 1-4: Impact Evaluation Activities by Program and Sector ................................................................... 7
Table 2-1: Document-based Verification Samples and Precision by Program ........................................... 18
Table 2-2: Survey-Based Verification Sample and Precision by Program ................................................... 18
Table 3-1: Residential Verified Impact Savings by Program ....................................................................... 27
Table 3-2: Residential Portfolio Cost-Effectiveness Summary ................................................................... 27
Table 3-3: Summary of Survey Response Rate ........................................................................................... 28
Table 3-4: Simple Verification Precision by Program ................................................................................. 28
Table 3-5: Water Heat Program ISRs by Measure ...................................................................................... 28
Table 3-6: HVAC Program ISRs by Measure ................................................................................................ 29
Table 3-7: Fuel Efficiency Program ISRs by Measure .................................................................................. 29
Table 3-8: Water Heat Program Measures ................................................................................................. 31
Table 3-9 Water Heat Program Verified Electric Savings ........................................................................... 31
Table 3-10 Water Heat Program Costs by Measure ................................................................................... 31
Table 3-11: Water Heat Verification Survey ISR Results ............................................................................ 32
Table 3-12: HVAC Program Measures ........................................................................................................ 34
Table 3-13: HVAC Program Verified Electric Savings .................................................................................. 34
Table 3-14: HVAC Program Costs by Measure ........................................................................................... 34
Table 3-15: HVAC Verification Survey ISR Results ...................................................................................... 36
Table 3-16: Measures Considered for Billing Analysis, HVAC Program ...................................................... 36
Table 3-17: Measure Savings, HVAC Program ............................................................................................ 37
Table 3-18: Shell Program Measures .......................................................................................................... 38
Table 3-19: Shell Program Verified Electric Savings ................................................................................... 38
Table 3-20: Shell Program Costs by Measure ............................................................................................. 39
Table 3-21: Fuel Efficiency Program Measures .......................................................................................... 41
Table 3-22: Fuel Efficiency Program Verified Electric Savings .................................................................... 41
Table 3-23: Fuel Efficiency Program Costs by Measure ............................................................................. 42

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Table 3-24: Fuel Efficiency Verification Survey ISR Results ........................................................................ 43
Table 3-25: Measures Considered for Billing Analysis, Fuel Efficiency Program ........................................ 44
Table 3-26: Measure Savings, Fuel Efficiency Program .............................................................................. 44
Table 3-27: ENERGY STAR® Homes Program Measures ............................................................................. 45
Table 3-28: ENERGY STAR® Homes Program Verified Electric Savings ....................................................... 45
Table 3-29: ENERGY STAR® Homes Program Costs by Measure ................................................................ 46
Table 3-30: Simple Steps, Smart Savings Program Measures .................................................................... 48
Table 3-31: Simple Steps, Smart Savings Program Verified Electric Savings .............................................. 48
Table 3-32: Simple Steps, Smart Savings Program Costs by Measure ........................................................ 48
Table 4-1: Low-Income Verified Impact Savings by Program ..................................................................... 53
Table 4-2: Low-Income Portfolio Cost-Effectiveness Summary ................................................................. 53
Table 4-3: Low-Income Program Measures ............................................................................................... 54
Table 4-4: Low-Income Program Verified Electric Savings ......................................................................... 54
Table 4-5: Low-Income Program Costs by Measure ................................................................................... 55
Table 4-6: Measures Considered for Billing Analysis, Low-Income Program ............................................. 57
Table 4-7: Measure Savings, Low-Income Program ................................................................................... 57
Table 5-1: Measures Considered for Billing Analysis, HVAC Program ........................................................ 60
Table 5-2: Cohort Restrictions, HVAC Program .......................................................................................... 60
Table 5-3: Pre-period Usage T-test for Electric Variable Speed Motor, HVAC Program ............................ 63
Table 5-4: TMY Weather, HVAC Program ................................................................................................... 63
Table 5-5: Measure Savings, HVAC Program .............................................................................................. 64
Table 5-6: Measure Savings for All Regression Models, HVAC Program .................................................... 65
Table 5-7: Measures Considered for Billing Analysis, Fuel Efficiency Program .......................................... 65
Table 5-8: Cohort Restrictions, Fuel Efficiency Program ............................................................................ 66
Table 5-9: Pre-period Usage T-test for Electric to Gas Furnace, Fuel Conversion Program ....................... 68
Table 5-10: TMY Weather, Fuel Efficiency Program ................................................................................... 68
Table 5-11: Measure Savings, Fuel Efficiency Program .............................................................................. 69
Table 5-12: Measure Savings for All Regression Models, Fuel Efficiency Program .................................... 70
Table 5-13: Cohort Restrictions, Low-Income Program ............................................................................. 71
Table 5-14: Pre-period Usage T-test for Electric Measures, Low-Income Program ................................... 72

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Table 5-15: TMY Weather, Low-Income Program ...................................................................................... 73
Table 5-16: Household Savings for All Regression Models, Low-Income Program .................................... 73
Table 6-1: Type and Number of Measures Received by Respondents ....................................................... 74
Table 6-2: Survey Respondent Home Characteristics ................................................................................ 75
Table 7-1: Cost-effectiveness Results ......................................................................................................... 76
Table 7-2: Questions Addressed by the Various Cost Tests ....................................................................... 77
Table 7-3: Benefits and Costs Included in Each Cost-Effectiveness Test .................................................... 78
Table 7-4: Cost-Effectiveness Results by Sector ......................................................................................... 79
Table 7-5: Cost-Effectiveness Benefits by Sector ....................................................................................... 80
Table 7-6: Cost-Effectiveness Costs by Sector ............................................................................................ 80
Table 7-7: Cost-Effectiveness Net Benefits by Sector ................................................................................ 80

Tables of Contents and Tables 6
1. Executive Summary
This report is a summary of the Residential and Low-Income Electric Evaluation, Measurement, and
Verification (EM&V) effort of the 2020 program year (PY2020) portfolio of programs for Avista
Corporation (Avista) in the Idaho service territory. The evaluation was administered by ADM
Associates, Inc. and Cadeo Group, LLC (herein referred to as the “Evaluators”).
1.1 Savings & Cost-Effectiveness Results
The Evaluators conducted an impact evaluation for Avista’s Residential and Low-Income programs for
PY2020. The Residential portfolio savings amounted to 4,535,320 kWh with a 96.12% realization rate.
The Low-Income portfolio savings amounted to 215,300 kWh with a 110.07% realization rate. The
Evaluators summarize the Residential portfolio verified savings in Table 1-1 and the Low-Income
portfolio verified savings in Table 1-2 below.
The Residential portfolio reflects a TRC value of 2.08 and a UCT value of 3.01. The Low-Income portfolio
reflects a TRC value of 0.61 and a UCT value of 0.45, leading to a total Residential and Low-Income TRC
of 1.81 and a UCT of 2.33. Table 1-3 summarizes the evaluated TRC and UCT values with each the
Residential and Low-Income portfolios.
Table 1-1: Residential Verified Impact Savings by Program
Program
Expected
Savings
(kWh)
Verified
Savings
(kWh)
Verified
Realization
Rate
Total Costs
Water Heat 11,660 12,986 111.37% $3,366.77
HVAC 503,411 508,131 100.94% $135,247.55
Shell 206,012 358,972 174.25% $192,358.60
Fuel Efficiency 780,424 635,962 81.49% $340,839.76
ENERGY STAR Homes 49,687 50,705 102.05% $13,555.77
Simple Steps, Smart
Savings 3,166,980 2,968,563 93.73% $476,724.59
Total Res 4,718,173 4,535,320 96.12% $1,162,093.04

Table 1-2: Low-Income Verified Impact Savings by Program
Program
Expected
Savings
(kWh)
Verified
Savings
(kWh)
Verified
Realization
Rate
Total Costs
Low-Income 195,603 215,300 110.07% $637,629.48
Total Low-Income 195,603 215,300 110.07% $637,629.48

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Table 1-3: Cost-Effectiveness Summary
Sector TRC UCT
Benefits Costs B/C Ratio Benefits Costs B/C Ratio
Residential $5,579,452 $2,681,641 2.08 $5,072,229 $1,687,155 3.01
Low Income $366,774 $605,151 0.61 $272,178 $546,723 0.50
Total $5,946,226 $3,286,792 1.81 $5,344,407 $2,233,878 2.39
Table 1-4 summarizes the electric programs offered to residential and low-income customers in the
Idaho Avista service territory in PY2020 as well as the Evaluators’ evaluation tasks and impact
methodology for each program.
Table 1-4: Impact Evaluation Activities by Program and Sector
Sector Program Database
Review
Survey
Verification Impact Methodology
Residential Water Heat ü ü RTF UES
Residential HVAC ü ü RTF UES/Billing analysis with
comparison group
Residential Shell ü RTF UES
Residential Fuel Efficiency ü ü Avista TRM/Billing Analysis with
comparison group
Residential ENERGY STAR®
Homes ü RTF UES
Residential Simple Steps, Smart
Savings ü RTF UES
Low-Income Low-Income ü Avista TRM
1.2 Conclusions and Recommendations
The following section details the Evaluators’ conclusions and recommendations for each the Residential
Portfolio and Low-Income Portfolio program evaluations.
1.2.1 Conclusions
The following section details the Evaluator’s findings resulting from the program evaluations for each
the Residential Portfolio and Low-Income Portfolio.
1.2.1.1 Residential Programs
The Evaluators provide the following conclusions regarding Avista’s Residential electric programs:
n The Evaluators found the Residential portfolio to demonstrate a total of 4,535,320 kWh with a
realization rate of 96.12%. The Evaluators also conducted a cost-benefit analysis in order to
estimate the Residential portfolio’s cost-effectiveness. The resulting TRC value for this sector is
2.08 while the UCT value is 3.01. Further details on cost-effectiveness methodology can be
found in Appendix C.
n The Residential Portfolio impact evaluation resulted in a realization rate of 96.12% due to slight
differences between the Avista TRM categories and the appropriately assigned RTF UES
categories for each measure as well as billing analysis results. The Evaluators note several

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instances in which the Avista TRM value reflects an average of a range of RTF UES values for the
electric measures offered in the Idaho electric service territory. The values had been averaged
across heating zones, water heater storage tank sizes, equipment efficiency values, and fuel
types. The Evaluators, instead of applying these averages, verified the appropriate RTF UES
values for each rebate for a sample of rebates in each program and applied the resulting
realization rates to the population of rebates for each program. This led to a higher realization
rate, as some rebates reflected RTF savings values higher than the average for that measure.
n The Simple Steps, Smart Savings Program, which contributes 65.45% of the expected savings,
resulted in a realization rate of 93.73% whereas each of the other programs resulted in a
combined 101.00% realization rate. The Shell Program contributed to a 5% decrease in the
overall residential sector, which displayed a realization rate of 96.12%.
n The Evaluators conducted a billing analysis to estimate observed, verified savings for the E
Variable Speed Motor measure. The Evaluators found the resulting savings to be 513 kWh per
year, roughly 124% of the current Avista TRM value for the measure. This savings value was
applied to all rebates completed in PY2020.
n The Evaluators also conducted a billing analysis to estimate observed, verified savings for the E
Electric to Natural Gas Furnace measure in the Fuel Efficiency Program. The Evaluators found
the resulting savings to be 5,068 kWh per year, roughly 72.73% of the current Avista TRM value
for the measure. This savings value was applied to all rebates completed in PY2020.
n In the HVAC Program, the E Smart Thermostat DIY with Electric Heat realization rate is low
because the Avista TRM uses an average of retail and direct install savings values as well as an
average across heating types, while the Evaluators assigned the appropriate RTF UES value for
each installation type and heating zone. The appropriate categories in the RTF led to a lower-
than-expected savings for the retail rebates and a higher-than-expected savings for the direct
install rebates for this measure.
n The Evaluators note that the RTF version used to evaluate the Simple Steps, Smart Savings
Program represents the residential lighting workbook active at the time the Bonneville Power
Administration (BPA) planning for this program was established (October 1, 2019). The values
present in this version of the RTF workbook do not reflect the current savings values present in
the Avista TRM. Therefore, the adjusted savings displayed is significantly lower than the verified
savings. This is because the savings for the lighting measures decreased as the baseline
efficiencies have been updated and increased.
1.2.1.2 Low-Income Programs
The Evaluators provide the following conclusions regarding Avista’s Residential electric programs:
n The Evaluators found the Residential portfolio to demonstrate a total of 215,300 kWh with a
realization rate of 110.07%. The Evaluators also conducted a cost-benefit analysis in order to
estimate the Residential portfolio’s cost-effectiveness. The resulting TRC value for this sector is
0.61 while the UCT value is 0.50. These values are expected, as the Low-Income portfolio is not
expected to meet cost-effectiveness but are implemented in order to provide energy efficiency
benefits to low-income customers. Further details on cost-effectiveness methodology can be
found in Appendix C.

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n The Low-Income Portfolio impact evaluation resulted in a 110.07% realization rate. The
realization rates for each program deviate from 100% due to differences between the Avista
TRM values and the appropriately assigned RTF UES values. For the Low-Income Program, the
Evaluators applied a realization rate from a sample of rebates after verifying documentation for
quantity and efficiency of measures.
n The Evaluators attempted to estimate measure-level Low-Income Program energy savings
through billing analysis regression with a counterfactual group selected via propensity score
matching. The Evaluators attempted to isolate each unique measure. However, participation for
the Low-Income program resulted in a small number of customers with isolated measures and
therefore the Evaluators conducted a whole-home billing analysis for all the electric measures
combined in the Low-Income in order to estimate savings for the average household
participating in the program, across all measures. The Evaluators found a realization rate of
130% for all electric measures in the program, which supported the realization rate of 115%
from the desk review.
n Some rebates included in the Low-Income Program indicate that savings had been capped at 20%
of consumption. The provided project data do not include adequate information to determine
when savings values are being appropriately capped. The Evaluators recommend that annual
consumption be provided for each measure in the tracking data, if practical, so that evaluation
can include verifying that savings are being capped at 20% consumption for application measures.
1.2.2 Recommendations
The following section details the Evaluator’s recommendations resulting from the program evaluations
for each the Residential Portfolio and Low-Income Portfolio.
1.2.2.1 Residential Programs
The Evaluators offer the following recommendations regarding Avista’s Residential electric programs:
n The Evaluators recommend Avista work to improve methods for collecting mail-in rebate
application information to reconcile the CC&B database. The values found in the project
documentation should accurately reflect the values represented in the CC&B database.
n A number of rebates were not accompanied with AHRI certification. In order to acquire accurate
equipment efficiencies and tank sizes, AHRI certifications are recommended to be required and
submitted with the rebate application, with an invoice that matches the model number found in
the AHRI certification.
n The realization rate for the electric savings in the Water Heat Program deviate from 100% due to
the methodology in which the Avista TRM prescriptive savings value was applied. The Avista
TRM assigns a combination of the values the RTF assigns for Tier 2 and Tier 3 heat pump water
heaters. However, among document verification, the Evaluators found a majority of water
heaters to be Tier 3 or Tier 4, which the RTF UES assigns a higher savings value. The Evaluators
recommend splitting the Avista TRM value for Tier 2, Tier 3, and Tier 4 water heaters into
separate values in order to accurately reflect expected savings for the electric water heater
measure.

admenergy.com | 3239 Ramos Circle, Sacramento, CA 95827| 916.363.8383 10
n The Avista TRM assigns the savings values for water heaters of any size. During document
review, the Evaluators found most of the water heaters to have a storage tank under 55 gallons,
which has a higher savings value in the RTF than water heaters with unknown tank sizes (larger
systems have a more stringent code baseline). The Evaluators applied the RTF UES value for the
associated tank size and tier found for each model number in the sampled rebates. These
changes led to the high realization rate for the E Heat Pump Water Heater measure in the Water
Heat Program. The Evaluators recommend updating the Avista TRM value for this measure
based on actual tank size, in addition to collecting information on the tank size of the measure in
the rebate applications.
n The Evaluators note that some of the model numbers for the rebated equipment were
incomplete and the Evaluators were unable to identify a single AHRI certification that matched
the description in the rebate application. In order to acquire accurate equipment efficiencies,
AHRI certifications are recommended to be required and submitted with the rebate application,
with an invoice that matches the manufacturer and model number found in the AHRI
certification.
n The Evaluators note that a number of rebate applications did not contain values associated with
whether the home is existing or was a new construction home. This field is an input to apply
correct RTF UES values. The Evaluators recommend requiring this field be completed in rebate
applications, both mail-in and web-based.
n The Evaluators cross-referenced the billing data to verify if customers demonstrated the
required heating season electricity usage of 8,000 kWh and natural gas usage of less than 340
Therms, as defined in the program requirements. The Evaluators found many customers used
less than 8,000 kWh or 340 Therms annually. In addition, some customers had insufficient pre-
period data to determine annual usage. The Evaluators recommend Avista verify if customers
meet the requirements prior to completing the rebate.
n The Evaluators conducted a billing analysis for the E Variable Speed Motor measure in the HVAC
Program. The estimated savings value from the billing analysis was roughly 124% of the value
reflected in the Avista TRM. The Evaluators recommend updating the savings value for this
measure in the Avista TRM to reflect observed savings more closely in the territory.
n For the Shell Program, the Evaluators found rebates in which the R-values did not align with
TRM or RTF values (R38 and R64). The Evaluators recommend collecting information in a
standardized manner.
n The Evaluators recommend collecting information on single/double pane windows of the
baseline windows and class of the efficient windows in order to correctly assign RTF UES values.
n The Evaluators also recommend collecting information on single-family/multi-
family/manufactured in the web rebate form. This allows the Evaluators to accurately assign RTF
values. The mail-in rebates collect this information; however, it does not seem to be currently
required to complete the rebate. Therefore many rebates are missing this information.
n The Evaluators note several instances in which the web-based rebate data indicates the
household has electric space heating, but all other sources (project data and document
verification) indicate natural gas space heating, and vice versa. The Evaluators recommend
updating data collection standards in order for all sources of information to reflect the same
values as the project documentation.

admenergy.com | 3239 Ramos Circle, Sacramento, CA 95827| 916.363.8383 11
n The Evaluators note that the realization for the E ENERGY STAR® Home – Manufactured, Gas &
Electric measure is low because the Avista TRM savings was employed using an additive
methodology between a gas-heated home and an electric-heated home for the electric savings.
However, the Evaluators reviewed the RTF and determined manufactured home electric savings
for a fully natural gas heated home would be closer to the savings a gas heated home with
electricity would save. The Evaluators recommend adjusting Avista TRM electric savings for this
measure to reflect the RTF values associated with a fully natural gas-heated home at 43 kWh
saved per year.
n The Evaluators recommend the Avista TRM reflect the savings values in effect for the Simple
Steps, Smart Savings Program. The Avista TRM currently uses RTF values in effect on November
1, 2019 for the Simple Steps, Smart Savings whereas the expected savings for this program are
calculated using the RTF-approved BPA workbook in effect on October 1, 2019.

Work Plan 12
1.2.2.2 Low-Income Programs
The Evaluators offer the following recommendations regarding Avista’s Low-Income electric programs:
n The Evaluators note that most deviations from 100% realization rate is due to differences
between the limited measure category options Avista TRM values and the more detailed
categories referencing heating zone, cooling zone, heating type, and bulb types present in the
RTF. The Evaluators recommend that Avista reference the more detailed RTF measures when
calculating expected savings for the programs.
n The Evaluators reviewed the project documentation provided by Avista and identified conflicting
square footage or number of units between the aggregated project data from the CC&B and the
rebate project documentation provided in the data request for document verification. In
addition, the unit type, in terms of square footage or number of measures (windows, doors, etc)
was not documented consistently and therefore savings values were applied inaccurately. The
Evaluators recommend updating CC&B documentation standards to more accurately reflect
values present on the rebate applications.
n The Evaluators found discrepancies between the 20% annual consumption cap and the claimed
energy savings. The Evaluators recommend checking each project against billing data prior to
reporting energy savings for the project, as well as documenting each household’s usage as well
as the date range used to calculate the household consumption estimate.

Work Plan 13
2. General Methodology
The Evaluators performed an impact evaluation on each of the programs summarized in Table 1-4. The
Evaluators used the following approaches to calculate energy impact defined by the International
Performance Measurement and Verification Protocols (IPMVP)1 and the Uniform Methods Project
(UMP)2:
n Simple verification (web-based surveys supplemented with phone surveys)
n Document verification (review project documentation)
n Deemed savings (RTF UES and Avista TRM values)
n Whole facility billing analysis (IPMVP Option C)
The Evaluators completed the above impact tasks for each the electric impacts and the natural gas
impacts for projects completed in the Idaho Avista service territory.
The M&V methodologies are program-specific and determined by previous Avista evaluation
methodologies as well as the relative contribution of a given program to the overall energy efficiency
impacts. Besides drawing on IPMVP, the Evaluators also reviewed relevant information on
infrastructure, framework, and guidelines set out for EM&V work in several guidebook documents that
have been published over the past several years. These include the following:
n Northwest Regional Technical Forum (RTF)3
n National Renewable Energy Laboratory (NREL), United States Department of Energy (DOE) The
Uniform Methods Project (UMP): Methods for Determining Energy Efficiency Savings for Specific
Measures, April 20134
n International Performance Measurement and Verification Protocol (IPMVP) maintained by the
Efficiency Valuation Organization (EVO) with sponsorship by the U.S. Department of Energy (DOE)5
The Evaluators kept data collection instruments, calculation spreadsheets, and monitored/survey data
available for Avista records.
2.1 Glossary of Terminology
As a first step to detailing the evaluation methodologies, the Evaluators have provided a glossary of
terms to follow:

1 https://www.nrel.gov/docs/fy02osti/31505.pdf
2 https://www.nrel.gov/docs/fy18osti/70472.pdf
3 https://rtf.nwcouncil.org/measures
4 Notably, The Uniform Methods Project (UMP) includes the following chapters authored by ADM. Chapter 9 (Metering Cross-
Cutting Protocols) was authored by Dan Mort and Chapter 15 (Commercial New Construction Protocol) was Authored by Steven
Keates.
5 Core Concepts: International Measurement and Verification Protocol. EVO 100000 – 1:2016, October 2016.

Evaluation Report 14
n Deemed Savings – An estimate of an energy savings outcome (gross savings) for a single unit of
an installed energy efficiency measure. This estimate (a) has been developed from data sources
and analytical methods that are widely accepted for the measure and purpose and (b) are
applicable to the situation being evaluated.
n Expected Savings – Calculated savings used for program and portfolio planning purposes.
n Adjusted Savings – Savings estimates after database review and document verification has been
completed using deemed unit-level savings provided in the Avista TRM. It adjusts for such factors
as data errors and installation rates.
n Verified Savings – Savings estimates after the unit-level savings values have been updated and
energy impact evaluation has been completed, integrating results from billing analyses and
appropriate RTF UES and Avista TRM values.
n Gross Savings – The change in energy consumption directly resulting from program-related
actions taken by participants in an efficiency program, regardless of why they participated.
n Free Rider – A program participant who would have implemented the program measure or
practice in absence of the program.
n Net-To-Gross – 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.
n Net Savings – The change in energy consumption directly resulting from program-related actions
taken by participants in an efficiency program, with adjustments to remove savings due to free
ridership.
n Non-Energy Benefits – Quantifiable impacts produced by program measures outside of energy
savings (comfort, health and safety, reduced alternative fuel, etc).
n Non-Energy Impacts – Quantifiable impacts in energy efficiency beyond the energy savings gained
from installing energy efficient measures (reduced cost for operation and maintenance of
equipment, reduced environmental and safety costs, etc).
2.2 Summary of Approach
This section presents our general cross-cutting approach to accomplishing the impact evaluation of
Avista’s Residential and Low-Income programs listed in Table 1-4. The Evaluators start by presenting our
general evaluation approach. This chapter is organized by general task due to several overlap across
programs. Section 3.3 describes the Evaluators’ program-specific residential impact evaluation methods
and results in further detail and Section 4.1 describes the Evaluator’s program-specific low-income
impact evaluation methods and results.
The Evaluators outline the approach to verifying, measuring, and reporting the residential portfolio
impacts as well as cost-effectiveness and summarizing potential program and portfolio improvements.
The primary objective of the impact evaluation is to determine ex-post verified net energy savings. On-
site verification and equipment monitoring was not conducted during this impact evaluation due to stay-
at-home orders due to the COVID19 pandemic.
Our general approach for this evaluation considers the cyclical feedback loop among program design,
implementation, and impact evaluation. Our activities during the evaluation estimate and verify annual
energy savings and identify whether a program is meeting its goals. These activities are aimed to provide

Evaluation Report 15
guidance for continuous program improvement and increased cost effectiveness for the 2020 and 2021
program years.
The Evaluators employed the following approach to complete impact evaluation activities for the
programs. The Evaluators define two major approaches to determining net savings for Avista’s
programs:
n A Deemed Savings approach involves using stipulated savings for energy conservation measures
for which savings values are well-known and documented. These prescriptive savings may also
include an adjustment for certain measures, such as lighting measures in which site operating
hours may differ from RTF values.
n A Billing Analysis approach involves estimating energy savings by applying a linear regression to
measured participant energy consumption utility meter billing data. Billing analyses included
billing data from nonparticipant customers. This approach does not require on-site data collection
for model calibration. This approach aligns with the IPMVP Option C.
The Evaluators accomplished the following quantitative goals as part of the impact evaluation:
n Verify savings with 10% precision at the 90% confidence level;
n Where appropriate, apply the RTF to verify measure impacts; and
n Where available data exists, conduct billing analysis with a suitable comparison group to estimate
measure savings.
For each program, the Evaluators calculated adjusted savings for each measure based on the Avista TRM
and results from the database review. The Evaluators calculated verified savings for each measure based
on the RTF UES, Avista TRM, or billing analysis in combination with the results from document review.
For the HVAC, Water Heat, and Fuel Efficiency programs, the Evaluators also applied in-service rates
(ISRs) from verification surveys.

The Evaluators assigned methodological rigor level for each measure and program based on its
contribution to the portfolio savings and availability of data.
The Evaluators analyzed billing data for all electric measure participants in the HVAC and Low-Income
programs. The Evaluators applied billing analysis results to determine evaluated savings only for
measures where savings could be isolated (that is, where a sufficient number of participants could be
identified who installed only that measure). Program-level realization rates for the HVAC, Water Heat,
and Fuel Efficiency programs incorporate billing analysis results for some measures.
Reported
Savings
Database
Review
Adjusted
savings
Document
Review
Evaluated
Savings

Evaluation Report 16
2.2.1 Database Review
At the outset of the evaluation, the Evaluators reviewed the databases to ensure that each program
tracking database conforms to industry standards and adequately tracks key data required for
evaluation.
Measure-level net savings were evaluated primarily by reviewing measure algorithms and values in the
tracking system to assure that they are appropriately applied using the Avista TRM. The Evaluators then
aggregated and cross-check program and measure totals.
The Evaluators reviewed program application documents for a sample of incented measures to verify
the tracking data accurately represents the program documents. The Evaluators ensured the home
installed measures that meet or exceed program efficiency standards.
2.2.2 Verification Methodology
The Evaluators verified a sample of participating households for detailed review of the installed measure
documentation and development of verified savings. The Evaluators verified tracking data by reviewing
invoices and surveying a sample of participant customer households. The Evaluators also conducted a
verification survey for program participants.
The Evaluators used the following equations to estimate sample size requirements for each program and
fuel type. Required sample sizes were estimated as follows:
Equation 2-1: Sample Size for Infinite Sample Size
𝑛= $𝑍× 𝐶𝑉
𝑑*
!

Equation 2-2: Sample Size for Finite Population Size
𝑛"= 𝑛
1 +-𝑛𝑁/
Where,
n n = Sample size
n 𝑍 = Z-value for a two-tailed distribution at the assigned confidence level.
n 𝐶𝑉 = Coefficient of variation
n 𝑑 = Precision level
n 𝑁 = Population
For a sample that provides 90/10 precision, Z = 1.645 (the critical value for 90% confidence) and d = 0.10
(or 10% precision). The remaining parameter is CV, or the expected coefficient of variation of measures
for which the claimed savings may be accepted. A CV of .5 was assumed for residential programs due to

Evaluation Report 17
the homogeneity of participation6, which yields a sample size of 68 for an infinite population. Sample
sizes were adjusted for smaller populations via the method detailed in Equation 2-2.
The following sections describe the Evaluator’s methodology for conducting document-based
verification and survey-based verification.
2.2.2.1 Document-Based Verification
The Evaluators requested rebate documentation for a subset of participating customers. These
documents included invoices, rebate applications, pictures, and AHRI certifications for the following
programs.
n Water Heat Program
n HVAC Program
n Shell Program
n Fuel Efficiency Program
n ENERGY STAR® Homes
n Simple Steps, Smart Savings
n Low-Income Program
This sample of documents was used to cross-verify tracking data inputs. In the case the Evaluators found
any deviations between the tracking data and application values, the Evaluators reported and
summarized those differences in the Database Review sections presented for each program in Section
3.3 and Section 4.1.
The Evaluators developed a sampling plan that achieves a sampling precision of ±10% at 90% statistical
confidence – or “90/10 precision” – to estimate the percentage of projects for which the claimed savings
are verified or require some adjustment.
The Evaluators developed the following samples for each program’s document review using Equation
2-1 and Equation 2-2. The Evaluators ensured representation in each state and fuel type for each
measure.

6 Assumption based off California Evaluation Framework:
https://www.cpuc.ca.gov/uploadedFiles/CPUC_Public_Website/Content/Utilities_and_Industries/Energy/Energy_Programs/De
mand_Side_Management/EE_and_Energy_Savings_Assist/CAEvaluationFramework.pdf

Evaluation Report 18
Table 2-1: Document-based Verification Samples and Precision by Program
Sector Program

Electric
Population
Sample
(With Finite
Population
Adjustment) *
Precision at
90% CI
Residential Water Heat 127 45 ±10.0%
Residential HVAC 419 62 ±9.7%
Residential Shell 379 63 ±9.5%
Residential Fuel Efficiency 95 41 ±9.6
Residential ENERGY STAR® Homes 44 28 ±9.8%
Residential Simple Steps, Smart Savings N/A N/A N/A
Low-Income Low-Income 386 65 ±9.4%
*Assumes sample size of 68 for an infinite population, based on CV (coefficient of variation) = 0.5, d (precision) = 10%, Z (critical
value for 90% confidence) = 1.645.
The table above represents the number of rebates in both Washington and Idaho territories. The
Evaluators ensured representation of state and fuel type in the sampled rebates for document
verification.
2.2.2.2 Survey-Based Verification
The Evaluators conducted survey-based verification for the Water Heat Program and HVAC Program.
The primary purpose of conducting a verification survey is to confirm that the measure was installed and
is still currently operational and whether the measure was early retirement or replace-on-burnout.
The Evaluators summarize the final sample sizes shown in Table 2-2 for the Water Heat and HVAC for
the Idaho Electric Avista projects. The Evaluators developed a sampling plan that achieved a sampling
precision of ±5.5% at 90% statistical confidence for ISRs estimates at the measure-level during web-
based survey verification.
Table 2-2: Survey-Based Verification Sample and Precision by Program
Sector Program Population Respondents Precision
at 90% CI
Residential Water Heat 59 32 ±9.8%
Residential HVAC 419 88 ±7.9%
Residential Fuel Efficiency 95 42 ±9.5%
Total 573 162 ±5.5%

The Evaluators implemented a web-based survey to complete the verification surveys. The Evaluators
supplemented with phone interviews to reach the 90/10 precision goal. The findings from these
activities served to estimate ISRs for each measure surveyed. These ISRs were applied to verification
sample desk review rebates towards verified savings, which were then applied to the population of
rebates. The measure-level ISRs resulting from the survey-based verification are summarized in Section
3.1.

Evaluation Report 19
2.2.3 Impact Evaluation Methodology
The Evaluators employed the following approach to complete impact evaluation activities for the
programs. The Evaluators define two major approaches to determining net savings for Avista’s
programs:
n Deemed Savings
n Billing Analysis (IPMVP Option C)
In the following sections, the Evaluators summarize the general guidelines and activities followed to
conduct each of the above analyses.
2.2.3.1 Deemed Savings
This section summarizes the deemed savings analysis method the Evaluators employed for the
evaluation of a subset of measures for each program. The Evaluators completed the validation for
specific measures across each program using the RTF unit energy savings (UES) values, where available.
The Evaluators ensured the proper measure unit savings were recorded and used in the calculation of
Avista’s ex-ante measure savings. The Evaluators requested and used the technical reference manual
Avista employed during calculation of ex-ante measure savings (Avista TRM). The Evaluators
documented any cases where recommend values differed from the specific unit energy savings
workbooks used by Avista.
In cases where the RTF has existing unit energy savings (UES) applicable to Avista’s measures, the
Evaluators verified the quantity and quality of installations and apply the RTF’s UES to determine
verified savings.
2.2.3.2 Billing Analysis
This section describes the billing analysis methodology employed by the Evaluators as part of the impact
evaluation and measurement of energy savings for measures with sufficient participation. The Evaluators
performed billing analyses with a matched control group and utilized a quasi-experimental method of
producing a post-hoc control group. In program designs where treatment and control customers are not
randomly selected at the outset, such as for downstream rebate programs, quasi-experimental designs
are required.
For the purposes of this analysis, a household is considered a treatment household if it has received a
program incentive. Additionally, a household is considered a control household if the household has not
received a program incentive. To isolate measure impacts, treatment households are eligible to be
included in the billing analysis if they installed only one measure during the 2019 and 2020 program
years. Isolation of individual measures are necessary to provide valid measure-level savings. Households
that installed more than one measure may display interactive energy savings effects across multiple
measures that are not feasibly identifiable. Therefore, instances where households installed isolated
measures are used in the billing analyses. In addition, the pre-period identifies the period prior to
measure installation while the post-period refers to the period following measure installation.
The Evaluators utilized propensity score matching (PSM) to match nonparticipants to similar participants
using pre-period billing data. PSM allows the evaluators to find the most similar household based on the
customers’ billed consumption trends in the pre-period and verified with statistical difference testing.

Evaluation Report 20
After matching based on these variables, the billing data for treatment and control groups are
compared, as detailed in IPMVP Option C. The Evaluators fit regression models to estimate weather-
dependent daily consumption differences between participating customer and nonparticipating
customer households.
Cohort Creation
The PSM approach estimates a propensity score for treatment and control customers using a logistic
regression model. A propensity score is a metric that summarizes several dimensions of household
characteristics into a single metric that can be used to group similar households. The Evaluators created
a post-hoc control group by compiling billing data from a subset of nonparticipants in the Avista territory
to compare against treatment households using quasi-experimental methods. This allowed the
Evaluators to select from a large group of similar households that have not installed an incented
measure. With this information, the Evaluators created statistically valid matched control groups for
each measure via seasonal pre-period usage. The Evaluators matched customers in the control group to
customers in the treatment group based on nearest seasonal pre-period usage (e.g., summer, spring,
fall, and winter) and exact 3-digit zip code matching (the first three digits of the five-digit zip code). After
matching, the Evaluators conducted a t-test for each month in the pre-period to help determine the
success of PSM.
While it is not possible to guarantee the creation of a sufficiently matched control group, this method is
preferred because it is likely to have more meaningful results than a treatment-only analysis. Some
examples of outside variables that a control group can sufficiently control for are changes in economies
and markets, large-scale social changes, or impacts from weather-related anomalies such as flooding or
hurricanes. This is particularly relevant in 2020 due to COVID-19 related lockdowns and restrictions.
After PSM, the Evaluators ran the following regression models for each measure:
n Fixed effect Difference-in-Difference (D-n-D) regression model (recommended in UMP protocols)7
n Random effects post-program regression model (PPR) (recommended in UMP protocols)
n Gross billing analysis (treatment only)
The second model listed above (PPR) was selected because it had the best fit for the data, identified
using the adjusted R-squared. Further details on regression model specifications can be found below.
Data Collected
The following lists the data collected for the billing analysis:
1. Monthly billing data for program participants (treatment customers)
2. Monthly billing data for a group of non-program participants (control customers)
3. Program tracking data, including customer identifiers, address, and date of measure installation
4. National Oceanic and Atmospheric Administration (NOAA) weather data between January 1, 2018
and December 31, 2020)
5. Typical Meteorological Year (TMY3) data

7 National Renewable Energy Laboratory (NREL) Uniform Methods Project (UMP) Chapter 17 Section 4.4.7.

Evaluation Report 21
Billing and weather data were obtained for program years 2019 and 2020 and for one year prior to
measure install dates (2018).
Weather data was obtained from the nearest weather station with complete data during the analysis
years for each customer by mapping the weather station location with the customer zip code.
TMY weather stations were assigned to NOAA weather stations by geocoding the minimum distance
between each set of latitude and longitude points. This data is used for extrapolating savings to long-
run, 30-year average weather.
Data Preparation
The following steps were taken to prepare the billing data:
1. Gathered billing data for homes that participated in the program.
2. Excluded participant homes that also participated in the other programs, if either program
disqualifies the combination of any other rebate or participation.
3. Gathered billing data for similar customers that did not participate in the program in evaluation.
4. Excluded bills missing address information (0.1% of bills).
5. Removed bills missing fuel type/Unit of Measure (UOM) (0.1% of bills).
6. Removed bills missing usage, billing start date, or billing end date (0.17% of bills).
7. Remove bills with outlier durations (<9 days or >60 days).
8. Excluded bills with consumption indicated to be outliers.
9. Calendarized bills (recalculates bills, usage, and total billed such that bills begin and end at the
start and end of each month).
10. Obtained weather data from nearest NOAA weather station using 5-digit zip code per household.
11. Computed Heating Degree Days (HDD) and Cooling Degree Days (CDD) for a range of setpoints.
The Evaluators assigned a setpoint of 65°F for both HDD and CDD. The Evaluators tested and
selected the optimal temperature base for HDDs and CDDs based on model R-squared values.
12. Selected treatment customers with only one type of measure installation during the analysis years
and combined customer min/max install dates with billing data (to define pre- and post-periods).
13. Restricted to treatment customers with install dates in specified range (typically January 1, 2019
through June 30, 2020) to allow for sufficient post-period billing data.
14. Restricted to control customers with usage less than or equal to two times the maximum observed
treatment group usage. This has the effect of removing control customers with incomparable
usage relative to the treatment group.
15. Removed customers with incomplete post-period bills (<4 months).
16. Removed customers with incomplete pre-period bills.

Evaluation Report 22
17. Restricted control customers to those with usage that was comparable with the treatment group
usage.
18. Created a matched control group using PSM and matching on pre-period seasonal usage and zip
code.
Regression Models
The Evaluators ran the following models for matched treatment and control customers for each
measure with sufficient participation. For net savings, the Evaluators selected either Model 1 or Model
2. The model with the best fit (highest adjusted R-squared) was selected. The Evaluators utilized Model
3 to estimate gross energy savings.
Model 1: Fixed Effects Difference-in-Difference Regression Model
The following equation displays the first model specification to estimate the average daily savings due to
the measure.
Equation 2-3: Fixed Effects Difference-in-Difference (D-n-D) Model Specification
𝐴𝐷𝐶#$=𝛼"+𝛽%(𝑃𝑜𝑠𝑡)#$+𝛽!(𝑃𝑜𝑠𝑡× 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡)#$+𝛽&(𝐻𝐷𝐷)#$+𝛽'(𝐶𝐷𝐷)#$+𝛽((𝑃𝑜𝑠𝑡× 𝐻𝐷𝐷)#$+𝛽)(𝑃𝑜𝑠𝑡× 𝐶𝐷𝐷)#$+𝛽*(𝑃𝑜𝑠𝑡× 𝐻𝐷𝐷× 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡)#$
+𝛽+(𝑃𝑜𝑠𝑡× 𝐶𝐷𝐷× 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡)#$+𝛽,(𝑀𝑜𝑛𝑡ℎ)$+𝛽%"(𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦)#+𝜀#$
Where,
n i = the ith household
n t = the first, second, third, etc. month of the post-treatment period
n 𝐴𝐷𝐶#$ = Average daily usage reading t for household i during the post-treatment period
n 𝑃𝑜𝑠𝑡#$ = A dummy variable indicating pre- or post-period designation during period t
at home i
n 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡# = A dummy variable indicating treatment status of home i
n 𝐻𝐷𝐷#$ = Average heating degree days (base with optimal Degrees Fahrenheit) during
period t at home i
n 𝐶𝐷𝐷#$ = Average cooling degree days (base with optimal Degrees Fahrenheit) during period t
at home i (if electric usage)
n 𝑀𝑜𝑛𝑡ℎ$= A set of dummy variables indicating the month during period t
n 𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦# = a customer-specific dummy variable isolating individual household
effects
n 𝜀#$ = The error term
n 𝛼"= The model intercept
n 𝛽%-%" = Coefficients determined via regression
The Average Daily Consumption (ADC) is calculated as the total monthly billed usage divided by the
duration of the bill month. 𝛽! represents the average change in daily baseload in the post-period
between the treatment and control group and 𝛽* and 𝛽+ represent the change in weather-related daily
consumption in the post-period between the groups. Typical monthly and annual savings were
estimated by extrapolating the 𝛽* and 𝛽+ coefficients with Typical Meteorological Year (TMY) HDD and

Evaluation Report 23
CDD data. However, in the case of gas usage, only the coefficient for HDD is utilized because CDDs were
not included in the regression model.
The equation below displays how savings were extrapolated for a full year utilizing the coefficients in the
regression model and TMY data. TMY data is weighted by the number of households assigned to each
weather station.
Equation 2-4: Savings Extrapolation
𝐴𝑛𝑛𝑢𝑎𝑙 𝑆𝑎𝑣𝑖𝑛𝑔𝑠= 𝛽!∗365.25 +𝛽*∗𝑇𝑀𝑌 𝐻𝐷𝐷+𝛽+∗𝑇𝑀𝑌 𝐶𝐷𝐷
Model 2: Random Effects Post-Program Regression Model
The following equation displays the second model specification to estimate the average daily savings
due to the measure. The post-program regression (PPR) model combines both cross-sectional and time
series data in a panel dataset. This model uses only the post-program data, with lagged energy use for
the same calendar month of the pre-program period acting as a control for any small systematic
differences between the treatment and control customers; in particular, energy use in calendar month t
of the post-program period is framed as a function of both the participant variable and energy use in the
same calendar month of the pre-program period. The underlying logic is that systematic differences
between treatment and control customers will be reflected in the differences in their past energy use,
which is highly correlated with their current energy use. These interaction terms allow pre-program
usage to have a different effect on post-program usage in each calendar month.
The model specification is as follows:
Equation 2-5: Post-Program Regression (PPR) Model Specification
𝐴𝐷𝐶#$=𝛼"+𝛽%(𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡)#+𝛽! (𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒)#+𝛽& (𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟)#+𝛽'(𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟)#+𝛽((𝑀𝑜𝑛𝑡ℎ)$+𝛽)(𝑀𝑜𝑛𝑡ℎ× 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒)#$+𝛽*(𝑀𝑜𝑛𝑡ℎ× 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟)#$+𝛽+(𝑀𝑜𝑛𝑡ℎ× 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟)#$
+𝛽,(𝐻𝐷𝐷)#$+𝛽%"(𝐶𝐷𝐷)#$+𝛽%%(𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡× 𝐻𝐷𝐷)#$+𝛽%!(𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡× 𝐶𝐷𝐷)#$+𝜀#$
Where,
n i = the ith household
n t = the first, second, third, etc. month of the post-treatment period
n 𝐴𝐷𝐶#$ = Average daily usage for reading t for household i during the post-treatment period
n 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡# = A dummy variable indicating treatment status of home i
n 𝑀𝑜𝑛𝑡ℎ$ = Dummy variable indicating month of month t
n 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒# = Average daily usage across household i’s available pre-treatment billing reads
n 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟# = Average daily usage in the summer months across household i’s
available pretreatment billing reads
n 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟# = Average daily usage in the winter months across household i’s available
pre-treatment billing reads
n 𝐻𝐷𝐷#$ = Average heating degree days (base with optimal Degrees Fahrenheit) during
period t at home i

Evaluation Report 24
n 𝐶𝐷𝐷#$ = Average cooling degree days (base with optimal Degrees Fahrenheit) during period t
at home i (if electric usage)
n 𝜀#$ = Customer-level random error
n 𝛼"= The model intercept for home i
n 𝛽%-%! = Coefficients determined via regression
The coefficient 𝛽% represents the average change in consumption between the pre-period and post-
period for the treatment group and 𝛽%% and 𝛽%! represent the change in weather-related daily
consumption in the post-period between the groups. Typical monthly and annual savings were
estimated by extrapolating the 𝛽%% and 𝛽%! coefficients with Typical Meteorological Year (TMY) HDD and
CDD data.
The equation below displays how savings were extrapolated for a full year utilizing the coefficients in the
regression model and TMY data.
Equation 2-6: Savings Extrapolation
𝐴𝑛𝑛𝑢𝑎𝑙 𝑆𝑎𝑣𝑖𝑛𝑔𝑠= 𝛽%∗365.25 +𝛽%%∗𝑇𝑀𝑌 𝐻𝐷𝐷+𝛽%!∗𝑇𝑀𝑌 𝐶𝐷𝐷
Model 3: Gross Billing Analysis, Treatment-Only Regression Model
The sections above detail the Evaluator’s methodology for estimating net energy savings for each
measure. The results from the above methodology report net savings due to the inclusion of the
counterfactual comparison group. However, for planning purposes, it is useful to estimate gross savings
for each measure. To estimate gross savings, the Evaluators employed a similar regression model;
however, only including participant customer billing data. This analysis does not include control group
billing data and therefore models energy reductions between the pre-period and post-period for the
measure participants (treatment customers).
To calculate the impacts of each measure, the Evaluators applied linear fixed effects regression using
participant billing data with weather controls in the form of Heating Degree Days (HDD) and Cooling
Degree Days (CDD). The following equation displays the model specification to estimate the average
daily savings due to the measure.
Equation 2-7: Treatment-Only Fixed Effects Weather Model Specification
𝐴𝐷𝐶#$=𝛼"+𝛽%(𝑃𝑜𝑠𝑡)#$+𝛽!(𝐻𝐷𝐷)#$+𝛽&(𝐶𝐷𝐷)#$+𝛽'(𝑃𝑜𝑠𝑡× 𝐻𝐷𝐷)#$+𝛽((𝑃𝑜𝑠𝑡× 𝐶𝐷𝐷)#$
+𝛽)(𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦)#+𝛽*(𝑀𝑜𝑛𝑡ℎ)$+𝜀#$
Where,
n i = the ith household
n t = the first, second, third, etc. month of the post-treatment period
n 𝐴𝐷𝐶#$ = Average daily usage for reading t for household i during the post-treatment period
n 𝐻𝐷𝐷#$ = Average heating degree days (base with optimal Degrees Fahrenheit) during
period t at home i
n 𝐶𝐷𝐷#$ = Average cooling degree days (base with optimal Degrees Fahrenheit) during period t
at home i (if electric usage)

Evaluation Report 25
n 𝑃𝑜𝑠𝑡#$ = A dummy variable indicating pre- or post-period designation during period t at
home i
n 𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦# = a customer-specific dummy variable isolating individual household
effects
n 𝜀#$ = Customer-level random error
n 𝛼"= The model intercept for home i
n 𝛽%-) = Coefficients determined via regression
The results of the treatment-only regression models are gross savings estimates. The gross savings
estimates are useful to compare against the net savings estimates. However, the treatment-only models
are unable to separate the effects of the COVID19 pandemic. The post-period for PY2020 and perhaps
also PY2021 are affected by the stay-at-home orders that had taken effect starting March 2020 in Idaho.
The stay-at-home orders most likely affect the post-period household usage. Because there is
insufficient post-period data before the shelter-in-place orders, the Evaluators were unable to separate
the effects on consumption due to the orders and the effects on consumption due to the measure
installation. Therefore, the results from this additional gross savings analysis are unable to reflect actual
typical year savings. However, for planning purposes, these estimates may be useful.
2.2.4 Net-To-Gross
The Northwest RTF UES measures do not require NTG adjustments as they are built into the deemed
savings estimates. In addition, billing analyses with counterfactual control groups, as proposed in our
impact methodology, does not require a NTG adjustment, as the counterfactual represents the
efficiency level at current market (i.e. the efficiency level the customer would have installed had they
not participated in the program).
2.2.5 Cost-Effectiveness Tests
The Evaluators calculated each program’s cost-effectiveness, avoided energy costs, and implementation
costs. The Evaluators used our company-developed cost-effectiveness tool to provide cost-effectiveness
assessments for the Residential Portfolio by program, fuel type, program year, and measure, for each
state.
As specified in this solicitation, the Evaluators determined the economic performance with the following
cost-effectiveness tests:
n Total Resource Cost (TRC) test;
n Utility Cost Test (UCT);
n Participant Cost Test (PCT); and
n Rate Impact Measure (RIM).
2.2.6 Non-Energy Benefits
The Evaluators used the Regional Technical Forum (RTF) to quantify non-energy benefits (NEBs) for
residential measures with established RTF values where available. Measures with quantified NEBs
include residential insulation, high efficiency windows, air source heat pumps, and ductless heat pumps.

Evaluation Report 26
In addition to the residential NEBs, the Evaluators applied the end-use non-energy benefit and health
and human safety non-energy benefit to the Low-Income Program. The Evaluators understand that the
two major non-energy benefits referenced above are uniquely applicable to the Low-Income Program.
The Evaluators applied those benefits to the program impacts as well as additional non-energy benefits
associated with individual measures included in the program. The Evaluators incorporated additional
NEBs to the impact evaluation, as applicable. Additional details on the non-energy benefits applied can
be found in Section 7.2.

Work Plan 27
3. Residential Impact Evaluation Results
The Evaluators completed an impact evaluation on Avista’s Residential portfolio to verify program-level
and measure-level energy savings for PY2020. The following sections summarize findings for each
electric impact evaluation in the Residential Portfolio in the Idaho service territory. The Evaluators used
data collected and reported in the tracking database, online application forms, Avista TRM, RTF, and
billing analysis of participants and nonparticipants to evaluate savings. This approach provided the
strongest estimate of achieved savings practical for each program, given its delivery method, magnitude
of savings, number of participants, and availability of data. Table 3-1 summarizes the Residential verified
impact savings by program. Table 3-2 summarizes the Residential portfolio’s cost-effectiveness.
Table 3-1: Residential Verified Impact Savings by Program
Program Expected
Savings (kWh)
Verified
Savings
(kWh)
Verified
Realization
Rate
Total Costs
Water Heat 11,660 12,986 111.37% $3,366.77
HVAC 503,411 508,131 100.94% $135,247.55
Shell 206,012 358,972 174.25% $192,358.60
Fuel Efficiency 780,424 635,962 81.49% $340,839.76
ENERGY STAR Homes 49,687 50,705 102.05% $13,555.77
Simple Steps, Smart Savings 3,166,980 2,968,563 93.73% $476,724.59
Total Res 4,718,173 4,535,320 96.12% $1,162,093.04
Table 3-2: Residential Portfolio Cost-Effectiveness Summary
Sector TRC UCT
Benefits Costs B/C Ratio Benefits Costs B/C Ratio
Residential $5,579,452 $2,681,641 2.08 $5,072,229 $1,687,155 3.01

In PY2020, Avista completed and provided incentives for residential electric measures in Idaho and
reported total electric energy savings of 4,535,320 kWh. All programs except the Fuel Efficiency Program
and ENERGY STAR® Homes Program exceeded savings goals based on reported savings, leading to an
overall achievement of 96.12% of the expected savings for the residential programs. The Evaluators
estimated the TRC value for the Residential portfolio is 2.08 while the UCT value is 3.01. Further details
of the impact evaluation results by program are provided in the sections following.
3.1 Simple Verification Results
The Evaluators surveyed 261 unique customers that participated in Avista’s residential energy efficiency
program in February and March 2021 using a mixed mode approach (phone/email). Customers with a
valid email were sent the survey via an email invitation. Fifty-three did not have email addresses in
program records and were invited to take the survey by the Evaluators’ in-house survey administration
team. The Evaluators also conducted targeted follow-up outreach to customers for certain measures.
The Evaluators surveyed customers that received rebates for HVAC, Water Heater, and Fuel Efficiency
Programs.

Evaluation Report 28
Table 3-3: Summary of Survey Response Rate
Population Respondents
Initial email contact list 959
Invalid email addresses 3
Bounced email 43
Undeliverable email 27
Invalid email (%) 8%
Email invitations sent (unique valid) 886
Email completions 208
Email response rate (%) 23%
Initial phone list 190
Phone numbers w/ email addresses 138
Phone numbers w/ no email address 52
Disconnected/wrong number 20
Invalid phone (%) 11%
Phone calls (unique valid) 170
Phone completions 54
Phone response rate (%) 32%
Total invites (unique) 938
Total completions 262
Response rate (%) 28%
Initial email contact list 959
Invalid email addresses 3

3.1.1 In-Service Rates
The Evaluators calculated in-service rates of installed measures from simple verification surveys
deployed to program participants for the Water Heat and HVAC Programs. The Evaluators asked
participants if the rebated equipment is currently installed and working, in addition to questions about
the new equipment fuel type. The Evaluators achieved 6.50% precision across the programs surveyed
for the electric measures in Avista’s service territory, summarized in Table 3-4.
Table 3-4: Simple Verification Precision by Program
Sector Program Population Respondents Precision
at 90% CI
Residential Water Heat 59 32 ±9.8%
Residential HVAC 419 88 ±7.9%
Residential Fuel Efficiency 95 41 ±9.5%
Total 573 120 ±5.5%

The measure-level ISRs determined from the verification survey for each program in which simple
verification was conducted is presented in Table 3-5, Table 3-6, and Table 3-7.
Table 3-5: Water Heat Program ISRs by Measure
Measure Respondents ISR
E Heat Pump Water Heater 32 100%

Evaluation Report 29
Table 3-6: HVAC Program ISRs by Measure
Measure Respondents ISR
E Electric To Air Source Heat Pump 21 100.00%
E Electric to Ductless Heat Pump 21 100.00%
E Smart Thermostat DIY with Electric
Heat 15 93.33%
E Smart Thermostat Paid Install with
Electric Heat 27 100.00%
E Variable Speed Motor 4 100.00%

Table 3-7: Fuel Efficiency Program ISRs by Measure
Measure Respondents ISR
E Electric To Natural Gas Furnace 26 100.00%
E Electric To Natural Gas Furnace &
Water Heat 16 93.33%

These ISR values were utilized in the desk reviews for the Water Heat and HVAC Programs in order to
calculate verified savings. Additional insights from the survey responses are summarized in Appendix B.
3.2 Impacts of COVID-19 Pandemic
On average, about three people lived at the residence that had the rebated equipment installed and
about 60% of respondents said that two or fewer lived at the residence that had the rebated equipment
installed.
About two-thirds of respondents (66%) observed that the pandemic had not changed the number of
people in their household that worked or went to school remotely.8 Twenty-two percent of respondents
said that more members of their household were attending school remotely or working from home
since the COVID-19 pandemic began. Twelve percent of respondents indicated that more members of
their household had gone to work or school remotely before the COVID-19 pandemic.
Three-quarters of respondents said that the amount of time they spend at home has increased since the
COVID-19 pandemic began. A much smaller portion of respondents indicated that other members of
their household were spending more time at home, as displayed in Figure 3-1. About half of
respondents indicated that their utility bill had increased, as displayed in Figure 3-2.

8 n=257

Evaluation Report 30
Figure 3-1: Change in amount of time spent at home

Figure 3-2: Change in electricity bill since COVID19 pandemic began

3.3 Program-Level Impact Evaluation Results
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Residential sector in the section below.

Evaluation Report 31
3.3.1 Water Heat Program
The Water Heat Program encourages customers to replace their existing electric or natural gas water
heater with high efficiency equipment. Customers receive incentives after installation and after
submitting a completed rebate form. Table 3-8 summarizes the measures offered under this program.
Table 3-8: Water Heat Program Measures
Measure Description
Impact
Analysis
Methodology
E Heat Pump Water Heater Electric water heater (0.94 EF or higher) RTF UES
The following table summarizes the verified electric energy savings for the Water Heat Program impact
evaluation.
Table 3-9 Water Heat Program Verified Electric Savings
Measure PY2020
Participation
Expected
Savings
Adjusted
Savings
Verified
Savings
Realization
Rate
E Heat Pump Water Heater 10 11,660 12,826 12,986 111.37%
Total 10 11,660 12,826 12,986 111.37%
The Water Heat Program displayed verified savings of 12,986 kWh with a realization rate of 111.37%
against the expected savings for the program. The following table summarizes the incentive and non-
incentive costs associated with the program.
Table 3-10 Water Heat Program Costs by Measure
Measure Incentive
Costs
Non-
Incentive
Costs
Total Costs
E Heat Pump Water Heater $2,365.00 $1,001.77 $3,366.77
Total $2,365.00 $1,001.77 $3,366.77
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Water Heat Program in the section below.
3.3.1.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Water Heat Program.
3.3.1.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the Water Heat
Program. The Evaluators selected a subset of rebate applications to cross-verify tracking data inputs,
summarized in Section 2.2.2.1.
The Evaluators found all Water Heat Program rebates to have completed rebate applications with the
associated water heater model number and efficiency values filled in either the Customer Care & Billing
(CC&B) web rebate data or mail-in rebate applications.

Evaluation Report 32
However, the Evaluators note that the CC&B web rebate data does not reflect the same values found in
the mail-in rebate applications and/or invoices or AHRI certification documents submitted with the
rebate application. The Evaluators recommend Avista work to improve methods for collecting mail-in
rebate application information to reconcile the CC&B database. For example, ten of the 111 sampled
rebates were not found in the CC&B dataset. A number of the sampled rebates were found to have
discrepancies in model numbers between the CC&B data and the mail-in rebate applications and/or
invoices.
In addition, not all rebates were accompanied with AHRI certification. In order to acquire accurate
equipment efficiencies and tank sizes, AHRI certifications are recommended to be required and
submitted with the rebate application, with an invoice that matches the model number found in the
AHRI certification.
The Evaluators found all sampled rebate equipment met or exceeded the measure efficiency
requirements for the Water Heat Program. The Evaluators found one rebate which indicated a quantity
of two, but expected savings assigned to the rebate aligned with a quantity of one. The Evaluators
applied the sampled realization rate to the expected savings value; therefore, the rebate was assigned
the savings of one unit of equipment. The Evaluators recommend correcting for instances where
quantity is greater than one and savings is equivalent to one measure.
3.3.1.3 Verification Surveys
The Evaluators randomly selected a subset of participant customers to survey for simple verification of
installed measure. The Evaluators included questions such as:
n Was this water heater a new construction, or did it replace another water heater?
n Was the previous water heater functional?
n Is the newly installed water heater still properly functioning?
In addition, the Evaluators asked participants how the COVID19 pandemic stay-at-home orders have
affected their household’s energy consumption. The responses to this verification survey were used to
calculate ISRs for the measures offered in the Water Heat Program.
Table 3-11 displays the ISRs for each of the Water Heat measures for Idaho and Washington territory
combined.
Table 3-11: Water Heat Verification Survey ISR Results
Measure Number of
Rebates
Number of
Survey
Completes
Program-Level
Precision at 90%
Confidence
In-Service Rate
E Heat Pump Water Heater 117 32 9.84%* 100%
*Heat Pump Water Heater measure precision calculated at the participant-level, not the project-level, as most participants
were builders.
All survey respondents for each water heater measure described equipment to be currently functioning,
leading to a 100% ISR. The Evaluators applied these ISRs to each rebate to quantify verified savings for
each measure.

Evaluation Report 33
3.3.1.4 Impact Analysis
This section summarizes the verified savings results for the Water Heat Program. The Evaluators
calculated verified savings for the E Heat Pump Water Heater measure using the RTF workbook in place
at the time the savings goals for the program was finalized The UES value associated with this measure
was applied to a random sample of participants, with verification of project documents such as rebate
applications to verify installation, quantity, and efficiency of the equipment.
3.3.1.5 Billing Analysis
The Evaluators did not conduct a billing analysis for the electric measures in the Water Heat Program.
3.3.1.6 Verified Savings
The Evaluators reviewed and applied the current RTF UES values for the E Heat Pump Water Heater
measure along with verified tracking data to estimate net program savings for this measure. The verified
savings for the program is 12,986 kWh with a realization rate of 111.37%, as displayed in Table 3-9.
The realization rate for the electric savings in the Water Heat Program deviate from 100% due to the
Avista TRM prescriptive savings value. The Avista TRM assigns a combination of the values the RTF
assigns for Tier 2 and Tier 3 heat pump water heaters. However, among document verification, the
Evaluators found a majority of water heaters to be Tier 3 or higher, which the RTF UES assigns a higher
savings value.
In addition, the Avista TRM assigns the savings values for water heaters of any size. During document
review, the Evaluators found most of the water heaters to have a storage tank under 55 gallons, which
has a higher savings value in the RTF than water heaters with unknown tank sizes. The Evaluators
applied the RTF UES value for the associated tank size and tier found for each model number in the
sampled rebates. These changes led to the high realization rate for the E Heat Pump Water Heater
measure in the Water Heat Program. The ISRs for each of the measures in the Water Heat Program was
100% and therefore did not affect the verified savings realization rates.
3.3.2 HVAC Program
The HVAC program encourages installation of high efficiency HVAC equipment and smart thermostats
through customer incentives. The program is available to residential electric or natural gas customers
with a winter heating season usage of 4,000 or more kWh, or at least 160 Therms of space heating in the
prior year. Existing or new construction homes are eligible to participate in the program. Table 3-8
summarizes the measures offered under this program.

Evaluation Report 34
Table 3-12: HVAC Program Measures
Measure Description Impact Analysis
Methodology
E Electric To Air Source Heat
Pump
Electric forced air furnace replacement
with air source heat pump RTF UES
E Electric to Ductless Heat Pump Electric forced air furnace replacement
with ductless heat pump RTF UES
E Smart Thermostat DIY with
Electric Heat
Self-installed connected thermostats in
electrically heated home RTF UES
E Smart Thermostat Paid Install
with Electric Heat
Professionally installed connected
thermostats in electrically heated home RTF UES
E Variable Speed Motor Variable speed motor in electrically
heated home Billing Analysis
The following table summarizes the verified electric energy savings for the HVAC Program impact
evaluation.
Table 3-13: HVAC Program Verified Electric Savings
Measure PY2020
Participation
Expected
Savings
(kWh)
Adjusted
Savings
(kWh)
Verified
Savings
(kWh)
Verified
Realization
Rate
E Electric To Air Source Heat
Pump 53 301,463 304,997 292,375 96.99%
E Electric to Ductless Heat Pump 62 144,136 145,576 158,685 110.09%
E Smart Thermostat DIY with
Electric Heat 21 15,729 15,719 11,237 71.44%
E Smart Thermostat Paid Install
with Electric Heat 49 36,701 36,677 39,165 106.71%
E Variable Speed Motor 13 5,382 5,382 6,669 123.92%
Total 198 503,411 508,350 508,131 100.94%
The HVAC Program displayed verified savings of 508,131 kWh with a realization rate of 100.94% against
the expected savings for the program.
Table 3-14: HVAC Program Costs by Measure
Measure Incentive
Costs
Non-Incentive
Costs Total Costs
E Electric To Air Source Heat Pump $37,100.00 $32,277.56 $69,377.56
E Electric to Ductless Heat Pump $31,000.00 $21,149.76 $52,149.76
E Smart Thermostat DIY with Electric
Heat $1,572.61 $1,265.74 $2,838.35
E Smart Thermostat Paid Install with
Electric Heat $4,900.00 $4,411.44 $9,311.44
E Variable Speed Motor $1,040.00 $502.21 $1,542.21
Total $75,612.61 $59,606.71 $135,219.32
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the HVAC Program in the section below.

Evaluation Report 35
3.3.2.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the HVAC Program.
3.3.2.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the HVAC
Program. The Evaluators selected a random subset of rebate applications to cross-verify tracking data
inputs, summarized in in Section 2.2.2.1.
The Evaluators found all HVAC Program rebates to have project documentation with the associated
HVAC model number and efficiency values in either the CC&B web rebate data or mail-in rebate
applications. However, the Evaluators note that some of the model numbers were incomplete and the
Evaluators were unable to identify a single AHRI certification that matched the description in the rebate
application. In order to acquire accurate equipment efficiencies, AHRI certifications are recommended
to be required and submitted with the rebate application, with an invoice that matches the
manufacturer and model number found in the AHRI certification.
The Evaluators note that not all rebate applications contained existing/new construction field. This field
is an input to apply correct RTF UES values. The Evaluators recommend requiring this field be completed
in rebate applications, both mail-in and web-based.
The Evaluators cross-referenced the billing data to verify if customers that received a rebate for E
Electric To Air Source Heat Pump or E Electric To Ductless Heat Pump demonstrate a heating season
electricity usage of 8,000 kWh and natural gas usage of less than 340 Therms, as defined in the program
requirements. The Evaluators found many customers used less than 8,000 kWh or 340 Therms annually
(not just heating months). In addition, some customers had insufficient pre-period data to determine
annual usage. The Evaluators recommend Avista verify if customers meet the requirements prior to
completing the rebate.
The Evaluators found one E Electric to Air Source Heat Pump rebate was duplicated in the project data
after confirming with Avista. The Evaluators removed this instance from the verified savings for the
program. The Evaluators found all sampled rebate equipment met or exceeded the measure efficiency
requirements for the HVAC Program.
3.3.2.3 Verification Surveys
The Evaluators randomly selected a subset of participant customers to survey for simple verification of
installed measure described in Section 2.2.2.2. The Evaluators included questions such as:
n What type of thermostat did this thermostat replace?
n Is your home heating with electricity, natural gas, or another fuel?
n Was the previous equipment functional?
Is the newly installed equipment still properly functioning?
The responses to this verification survey were used to calculate ISRs for the measures offered in the
HVAC Program. In addition, the Evaluators asked participants how the COVID19 pandemic stay-at-home

Evaluation Report 36
orders have affected their household’s energy consumption. The responses to these additional
questions can be found in Appendix B.
Table 3-15 displays the ISRs for each of the HVAC measures for Idaho and Washington electric territory
combined. The ISRs resulted in 7.90% precision at the 90% confidence interval for the program.
Table 3-15: HVAC Verification Survey ISR Results
Measure
Number
of
Rebates
Number of
Survey
Completes
Precision
at 90%
Confidence
In-Service
Rate
E Electric To Air Source Heat Pump 53 21
7.90%
100.00%
E Electric to Ductless Heat Pump 41 21 100.00%
E Smart Thermostat DIY with Electric Heat 63 15 93.33%
E Smart Thermostat Paid Install with Electric Heat 61 27 100.00%
E Variable Speed Motor 3 4 100.00%
Survey respondents described equipment to be currently functioning, leading to a 100% ISR for all
measures except the E Smart Thermostat DIY with Electric Heat. Although less than 100%, the ISR for the
E Smart Thermostat DIY with Electric Heat measure still exceeded ISRs of 90%. The Evaluators applied
the ISRs listed in Table 3-15 to each rebate to quantify verified savings for each measure.
3.3.2.4 Impact Analysis
This section summarizes the verified savings results for the HVAC Program. The Evaluators conducted a
billing analysis for measures where participation allowed. The Evaluators calculated verified savings for
the remaining measures using the RTF workbook in place at the time the savings goals for the program
was finalized These UES values were applied to a random sample of participants, with verification of
project documents such as rebate applications to verify installation, quantity, and efficiency of the
equipment.
3.3.2.5 Billing Analysis
The results of the billing analysis for the HVAC program are provided in this section. The methodology
for the billing analysis is provided in Section 2.2.3.2.
Table 3-16 displays customer counts for customers considered for billing analysis (i.e. customer with
single-measure installations) and identifies measures that met the requirements for a billing analysis.
Table 3-16: Measures Considered for Billing Analysis, HVAC Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation
for Billing
Analysis
E Electric To Air Source Heat Pump N/A N/A
E Electric to Ductless Heat Pump N/A N/A
E Smart Thermostat DIY with Electric Heat N/A N/A
E Smart Thermostat Paid Install with Electric Heat N/A N/A
E Variable Speed Motor ü 206 ü

Evaluation Report 37
The Evaluators were provided a considerable pool of control customers to draw upon. The Evaluators
used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each treatment customer was
matched to 5 similar control customers. The final number of customers in each the treatment and
control group are listed in Table 3-17.
The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for each measure and the Evaluators conducted a linear
regression using the matched participant and nonparticipant monthly billing data. Further details
regarding the billing analysis methodology can be found in Appendix A.
Table 3-17 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the HVAC Program as it provided the highest adjusted R-squared among the regression
models. Savings are statistically significant at the 90% level for E Variable Speed Motor The adjusted R-
squared (0.88) shows the model provided an excellent fit for the data.
Table 3-17: Measure Savings, HVAC Program
Measure Treatment
Customers
Control
Customers
Annual
Savings
per
Customer
(kWh)
90%
Lower
CI
90%
Upper
CI
Relative
Precision
(90% CI)
Adjusted
R-
Squared
Model
E Variable
Speed Motor 126 630 513 126 900 75.4% 0.88 Model
2: PPR
The Evaluators determined the savings estimate for E Variable Speed Motors in PY2020 to be 513 kWh,
which represents a value 124% of that demonstrated in the Avista TRM. The Evaluators applied this
value to all rebates in the PY2020 project data.
3.3.2.6 Verified Savings
The HVAC Program in total displays a realization rate of 100.94% with 508,131 kWh verified electric
energy savings in the Idaho service territory, as displayed in Table 3-13. The realization rate for the
electric savings in the HVAC Program deviate from 100% due to the differences between the applied
Avista TRM prescriptive savings value and the true Avista TRM or appropriate RTF UES value.
The Evaluators applied the results of the billing analysis to each E Variable Speed Motor measure. The
Evaluators reviewed the Avista TRM values along with verified tracking data to estimate net program
adjusted savings for measures not evaluated through billing analysis. In addition, the Evaluators
reviewed and applied the current RTF UES values for the electric measures along with verified tracking
data to estimate net program verified savings for this measure.
The E Smart Thermostat DIY with Electric Heat realization rate is low because the Avista TRM uses an
average of retail and direct install savings values as well as an average across heating types, while the
Evaluators assigned the appropriate RTF UES value for each installation type and heating zone. The

Evaluation Report 38
appropriate categories in the RTF led to a lower-than-expected savings for the retail rebates and a
higher-than-expected savings for the direct install rebates for this measure. In addition, the 93.33% ISR
was applied to the E Smart Thermostat with Electric Heat measure, further decreasing the realization
rate for the measure.
The E Electric to Ductless Heat Pump rebates have high realization rates because the expected savings
value used a value differing from the RTF values. The value in the TRM for this measure most likely
represents an average of the RTF savings values for a combination of heating zones. The E Variable
Speed Motor has a high realization rate due to the relatively higher unit-level energy savings from the
billing analysis as opposed to the Avista TRM.
3.3.3 Shell Program
The Shell Program provides incentives to customers for improving the integrity of the home’s envelope
with upgrades to windows and storm windows. Rebates are issued after the measure has been installed
for insulation and window measures. Participating homes must have electric or natural gas heating and
itemized invoices including measure details such as insulation levels, window values, and square
footage. In order to be eligible for incentive, the single-family households, including fourplex or less,
must demonstrate an annual electricity usage of at least 8,000 kWh or an annual gas usage of at least
340 Therms. Multifamily homes have no usage requirement. This program includes free manufactured
home duct sealing implemented by UCONS. Table 3-8 summarizes the measures offered under this
program.
Table 3-18: Shell Program Measures
Measure Description Impact Analysis
Methodology
E Attic Insulation with Electric Heat Attic insulation for homes heated with electricity RTF UES
E Floor Insulation with Electric Heat Floor insulation for homes heated with
electricity RTF UES
E Storm Window with Electric Heat High-efficiency storm window replacement for
homes heated with electricity RTF UES
E Wall Insulation with Electric Heat Wall insulation for homes heated with electricity RTF UES
E Window Replc from Double Pane
W Electric Heat
High-efficiency double pane window
replacement for homes heated with electricity RTF UES
E Window Replc from Single Pane W
Electric Heat
High-efficiency single pane window replacement
for homes heated with electricity RTF UES
The following table summarizes the adjusted and verified electric energy savings for the Shell Program
impact evaluation.
Table 3-19: Shell Program Verified Electric Savings
Measure PY2020
Participation
Expected
Savings
(kWh)
Adjusted
Savings
(kWh)
Verified
Savings
(kWh)
Verified
Realization
Rate
E Attic Insulation with Electric Heat 19 44,595 44,728 87,731 196.73%
E Floor Insulation with Electric Heat 4 4,525 5,204 5,185 114.58%
E Storm Window with Electric Heat 1 1,342 1,342 821 61.19%
E Wall Insulation with Electric Heat 8 15,294 13,868 22,667 148.21%

Evaluation Report 39
E Window Replc from Double Pane W
Electric Heat 1 1,414 1,397 1,143 80.89%
E Window Replc from Single Pane W
Electric Heat 86 138,842 136,598 241,425 173.88%
Total 119 206,012 203,137 358,972 174.25%
The Shell Program displayed verified savings of 358,972 kWh with a realization rate of 174.25% against
the expected savings for the program. The following table summarizes the incentive and non-incentive
costs associated with the program.
Table 3-20: Shell Program Costs by Measure
Measure Incentive Costs Non-Incentive
Costs Total Costs
E Attic Insulation with Electric Heat $19,112.25 $27,862.25 $46,974.50
E Floor Insulation with Electric Heat $3,309.00 $1,646.58 $4,955.58
E Storm Window with Electric Heat $366.00 $123.21 $489.21
E Wall Insulation with Electric Heat $5,735.25 $7,198.83 $12,934.08
E Window Replc from Double Pane W
Electric Heat $508.00 $363.10 $871.10
E Window Replc from Single Pane W
Electric Heat $49,672.00 $76,673.10 $126,345.10
Total $78,702.50 $113,867.08 $192,569.58
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Shell Program in the section below.
3.3.3.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Shell Program.
3.3.3.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the Shell
Program. The Evaluators selected a random subset of rebate applications to cross-verify tracking data
inputs, summarized in Section 2.2.2.1.
The Evaluators reviewed each measure number of units, square footage, and insulation where available.
The Evaluators found one instance in which square footage quantity in the rebate application does not
match the values presented in the project data attic insulation. Two rebates showed R-values that did
not align with TRM or RTF values related to the measure (R38 and R64). The Evaluators recommend
collecting information in a standardized manner. The Evaluators assumed insulation levels closest to
those presented for those two instances.
The Evaluators found the square footage for the floor insulation, wall insulation, and storm windows to
be equivalent between the project data and the rebate applications, where available. However, the
Evaluators found one floor insulation rebate in which the new R-value did not match TRM or RTF values
(R21). The Evaluators recommend collecting this information in a standardized manner in addition to the
R-values, detailed above.

Evaluation Report 40
The Evaluators recommend collecting information on single/double pane windows of the baseline
windows and class of the efficient windows in order to correctly assign RTF UES values.
The Evaluators also recommend collecting information on single-family/multi-family/manufactured in
the web rebate form. This allows the Evaluators to accurately assign RTF values. The mail-in rebates
collect this information; however, it does not seem to be required to complete the rebate and therefore
many rebates are missing this information.
The Evaluators note several instances in which the web-based rebate data indicates the household has
electric space heating, but all other sources (project data and document verification) indicate natural gas
space heating, and vice versa. The Evaluators recommend verifying the household space heating type
prior to completing the rebate.
The Evaluators also note one instance in which the R-values for a window was assigned incorrectly. The
Evaluators reassigned this window from an insulation of R0 to R49 to an insulation of R11 to R49.
The Evaluators cross-referenced the billing data to verify if customers demonstrate a heating season
electricity usage of 8,000 kWh and natural gas usage of less than 340 Therms, as defined in the program
requirements. The Evaluators found many customers used less than 8,000 kWh or 340 Therms annually
(not just heating months). In addition, some customers had insufficient pre-period data to determine
annual usage. The Evaluators recommend Avista verify if customers meet the requirements prior to
completing the rebate.
The Evaluators found no duplicate rebates in the project data and therefore did not remove any rebates
from verified savings.
3.3.3.3 Verification Surveys
The Evaluators did not conduct verification surveys for the Shell Program. Weatherization measures
historically have high verification rates.
3.3.3.4 Impact Analysis
This section summarizes the verified savings results for the Shell Program. The Evaluators calculated
verified savings for the electric measures using the RTF workbook in place at the time the savings goals
for the program was finalized. The Evaluators calculated adjusted savings for each measure using the
active Avista TRM values and verified tracking data. These UES values were applied to a random sample
of participants, with verification of project documents such as rebate applications to verify installation,
quantity, and efficiency of the equipment.
3.3.3.5 Billing Analysis
The Evaluators did not conduct a billing analysis for the electric Shell measures, as the RTF provides valid
UES savings for all measures incented through the program.
3.3.3.6 Verified Savings
The Shell Program in total displays a realization rate of 174.25% with 358,972 kWh verified electric
energy savings in the Idaho service territory, as displayed in Table 3-19. The realization rate for the

Evaluation Report 41
electric savings in the Shell Program deviate from 100% due to the differences between the categories
applied in the Avista TRM prescriptive savings values and the more detailed categories present with
unique RTF UES values.
The Evaluators did not conduct a verification survey for the Shell Program and therefore did not adjust
verified savings with an ISR.
3.3.4 Fuel Efficiency Program
The Residential Fuel Efficiency Program encourages customers to consider converting their resistive
electric space and water heating equipment to natural gas. This program is offered to residential
customers in the Idaho service territory. Customers must use Avista electricity for electric straight-
resistance heating or water heating in order to qualify for the rebate, which is verified by evaluating
their energy use. The home’s electric baseboard or furnace heat consumption must indicate at least
8,000 kWh during the previous heating season. Customers receive incentives after installation and after
submitting a completed rebate form. Table 3-8 summarizes the measures offered under this program.
Table 3-21: Fuel Efficiency Program Measures
Measure Description Impact Analysis
Methodology
E Electric to Air Source Heat Pump
Electric central ducted forced
air furnace to air source heat
pump (9.0 HFSP or greater)
RTF UES
E Electric To Natural Gas Furnace
Electric baseboard or forced air
furnace heat to natural gas
forced air furnace
Billing Analysis
E Electric To Natural Gas Furnace & Water Heat Electric to natural gas furnace
and water heat combo Avista TRM
The following table summarizes the verified electric energy savings for the Fuel Efficiency Program
impact evaluation.
Table 3-22: Fuel Efficiency Program Verified Electric Savings
Measure PY2020
Participation
Expected
Savings
Adjusted
Savings
Verified
Savings
Verified
Realization
Rate
E Electric to Air Source Heat Pump* 0 N/A N/A N/A N/A
E Electric To Natural Gas Furnace 59 422,068 435,656 306,966 72.73%
E Electric To Natural Gas Furnace &
Water Heat 36 358,356 352,404 328,996 91.81%
Total 95 780,424 780,424 635,962 81.49%
*The E Electric to Air Source Heat Pump measure had 0 rebates completed in PY2020

The Fuel Efficiency Program displayed verified savings of 635,962 kWh with a realization rate of 81.49%
against the expected savings for the program. The following table summarizes the incentive and non-
incentive costs associated with the program.

Evaluation Report 42
Table 3-23: Fuel Efficiency Program Costs by Measure
Measure Incentive
Costs
Non-Incentive
Costs Total Costs
E Electric to Air Source Heat Pump* N/A N/A $0.00
E Electric To Natural Gas Furnace $123,000.00 $55,597.63 $178,597.63
E Electric To Natural Gas Furnace &
Water Heat $102,600.00 $59,587.57 $162,187.57
Total $225,600.00 $115,185.19 $340,785.19
*The E Electric to Air Source Heat Pump measure had 0 rebates completed in PY2020
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Fuel Efficiency Program in the section below.
3.3.4.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Fuel Efficiency Program.
3.3.4.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the Fuel
Efficiency Program. The Evaluators selected a random subset of rebate applications to cross-verify
tracking data inputs, summarized in in Section 2.2.2.1.
The Evaluators note that some of the model numbers were incomplete and the Evaluators were unable
to identify a single AHRI certification that matched the description in the rebate application. In order to
acquire accurate equipment efficiencies, AHRI certifications are recommended to be required and
submitted with the rebate application, with an invoice that matches the manufacturer and model
number found in the AHRI certification.
The Evaluators recommend collecting rebate documentation data in a standardized format. For
example, equipment efficiency was entered in either a numeric format, percentage format, or character
format. A unified format would allow for more accurate estimation of savings.
The Evaluators found one rebate was duplicated in the project data for the E Electric to Natural Gas
Furnace measure. ADM removed this instance from the verified savings for the program.
The Evaluators noted several instances where efficiency in documentation does not match that of the
database. Therefore, the Evaluators recommend improving methods for transferring information from
paper rebate applications to CC&B database.
Evaluators recommend Avista collect efficiency values on the rebate application for conversion
measures, not just HVAC measures. Customers can get rebated for a conversion but also not apply for
an HVAC rebate (HVAC rebates do ask for the efficiency on the application)
The Evaluators found the CC&B data does not contain manufacturer information. The Evaluators
recommend this as an input in the CC&B data. The E Electric to Natural Gas Furnace & Water Heat
measure CC&B data does not detail both the furnace and the water heater model number and
manufacturer details. Instead, it contains only the furnace or only the water heater equipment, but not

Evaluation Report 43
both. The Evaluators recommend collecting both equipment manufacturer, model number, and
efficiency for the combination measures.
ADM cross-referenced the billing data to verify if customers that received a rebate demonstrate a
heating season electricity usage of 8,000 kWh and natural gas usage of less than 340 Therms, as defined
in the program requirements. The Evaluators found many customers used less than 8,000 kWh or 340
Therms annually (not just heating months). In addition, some customers had insufficient pre-period data
to determine annual usage. ADM recommends Avista verify if customers meet the requirements prior to
completing the rebate.

3.3.4.3 Verification Surveys
The Evaluators randomly selected a subset of participant customers to survey for simple verification of
installed measure, as described in Section 2.2.2.2. The Evaluators included questions such as:
n Is your home heating with electricity, natural gas, or another fuel?
n Was the previous equipment functional?
n Is the newly installed equipment still properly functioning?
The responses to this verification survey were used to calculate in-service rates (ISRs) for the measures
offered in the Fuel Efficiency Program. In addition, the Evaluators asked participants how the COVID19
pandemic stay-at-home orders have affected their household’s energy consumption. The responses to
these additional questions can be found in Appendix B.
Table 3-11 displays the ISRs for each of the Fuel Efficiency measures for Idaho territory. The ISRs
exceeded 10% precision at the 90% confidence interval for the program.
Table 3-24: Fuel Efficiency Verification Survey ISR Results
Measure
Number
of
Rebates
Number of
Survey
Completes
Precision
at 90%
Confidence
In-Service
Rate
E Electric To Natural Gas Furnace 59 26 9.48% 100.00%
E Electric To Natural Gas Furnace & Water Heat 36 16 93.33%
Survey respondents described equipment to be currently functioning for the E Electric to Natural Gas
Furnace measure, leading to a 100% in-service rate. The E Electric To Natural Gas Furnace & Water Heat
combination measure displayed an in-service rate of 93.33% due to one of the respondents specifying
that they do not know if the equipment is currently installed and working. The Evaluators applied these
ISRs to each rebate to quantify verified savings for each measure.
3.3.4.4 Impact Analysis
This section summarizes the verified savings results for the Fuel Efficiency Program. The Evaluators
explored billing analyses for measure-level energy savings estimates. In the case participation was low
or billing analysis results did not achieve statistical significance, a desk review was conducted. The
Evaluators calculated verified savings for the electric measures using the most recent RTF workbook for

Evaluation Report 44
the Fuel Efficiency measures. The Evaluators calculated verified savings for the gas measures using the
active Avista TRM values. These UES values were applied to a random sample of participants, with
verification of project documents such as rebate applications to verify installation, quantity, and
efficiency of the equipment.
The following sections summarize the results of the billing analysis and the desk review, with a summary
of the verified savings for the Fuel Efficiency Program.
3.3.4.5 Billing Analysis
The results of the billing analysis for the Fuel Efficiency Program are provided in this section. The
methodology for the billing analysis is provided in Section 2.2.3.2.
Table 3-25 displays customer counts for customers considered for billing analysis (i.e. customer with
single-measure installations) and identifies measures that met the requirements for a billing analysis.
Table 3-25: Measures Considered for Billing Analysis, Fuel Efficiency Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation
for Billing
Analysis
E Electric To Natural Gas Furnace ü 186 ü
E Electric To Natural Gas Furnace &
Water Heat ü 33

The Evaluators were provided a considerable pool of control customers to draw upon. The Evaluators
used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each treatment customer was
matched to 5 similar control customers. The final number of customers in each the treatment and
control group are listed in Table 3-17.
The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for each measure and the Evaluators conducted a linear
regression using the matched participant and nonparticipant monthly billing data. Further details
regarding the billing analysis methodology can be found in Appendix A.
Table 3-26 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the Fuel Conversion Program as it provided the highest adjusted R-squared among the
regression models. Savings are statistically significant at the 90% level for all measures and the adjusted
R-squared shows the model provided an excellent fit for the data.
Table 3-26: Measure Savings, Fuel Efficiency Program
Measure Treatment
Customers
Control
Customers
Annual
Savings per
90%
Lower
CI
90%
Upper
CI
Relative
Precision
(90% CI)
Adjusted
R-
Squared
Model

Evaluation Report 45
Customer
(kWh)
E Electric to Natural
Gas Furnace 85 421 5,068 4,384 5,7512 0.13 0.73 Model 2:
PPR
The Evaluators determined the savings estimate for E Electric to Natural Gas Furnace in PY2020 to be
5,068 kWh, which represents a value 72.73% of that demonstrated in the Avista TRM. The Evaluators
applied this value to all rebates in the PY2020 project data.
3.3.4.6 Verified Savings
The HVAC Program in total displays a realization rate of 81.49% with 635,962 kWh verified electric
energy savings in the Idaho service territory, as displayed in Table 3-13. The realization rate for the
electric savings in the HVAC Program deviate from 100% due to the differences between the applied
Avista TRM prescriptive savings value and the billing analysis and true Avista TRM value. In addition, the
93.33% survey in-service rate applied to the combination conversion measure further decreased the
realization rate for the measure and program overall.
The Evaluators applied the results of the billing analysis to each E Electric to Natural Gas Furnace
measure. The Evaluators reviewed the Avista TRM values along with verified tracking data to estimate
net program adjusted savings for measures not evaluated through billing analysis. In addition, the
Evaluators reviewed and applied the current Avista TRM values for the electric measures along with
verified tracking data to estimate net program verified savings for this measure.
3.3.5 ENERGY STAR® Homes Program
The ENERGY STAR® Homes Program provides rebates for homes within Avista’s service territory that
attain an ENERGY STAR® certification. This program incentivizes for ENERGY STAR® Eco-rated homes.
Table 3-8 summarizes the measures offered under this program.
Table 3-27: ENERGY STAR® Homes Program Measures
Measure Description Impact Analysis
Methodology
E ENERGY STAR Home -
Manufactured, Furnace
ENERGY STAR-rated manufactured
home with electric furnace RTF UES
G ENERGY STAR Home -
Manufactured, Natural Gas
ENERGY STAR-rated manufactured
home with natural gas heating RTF UES
G ENERGY STAR Home -
Manufactured, Gas & Electric
ENERGY STAR-rated manufactured
home with gas and electric RTF UES
The following table summarizes the verified electric energy savings for the ENERGY STAR® Homes
Program impact evaluation.
Table 3-28: ENERGY STAR® Homes Program Verified Electric Savings
Measure PY2020
Participation
Expected
Savings
(kWh)
Adjusted
Savings
(kWh)
Verified
Savings
(kWh)
Verified
Realization
Rate

Evaluation Report 46
E ENERGY STAR Home - Manufactured,
Furnace 13 43,095 43,095 50,619 117.46%
G ENERGY STAR Home - Manufactured,
Natural Gas 1 0 0 0 -
G ENERGY STAR Home - Manufactured,
Gas & Electric 2 6,592 6,630 86 1.30%
Total 16 49,687 49,725 50,705 102.05%
The ENERGY STAR® Homes Program displayed verified savings of 50,705 kWh with a realization rate of
102.05% against the expected savings for the program. The following table summarizes the incentive
and non-incentive costs associated with the program.
Table 3-29: ENERGY STAR® Homes Program Costs by Measure
Measure Incentive
Costs
Non-
Incentive
Costs
Total Costs
G ENERGY STAR Home - Manufactured,
Gas & Electric* N/A N/A $0.00
E ENERGY STAR Home - Manufactured,
Furnace $6,500.00 $7,052.43 $13,552.43
E ENERGY STAR Home - Manufactured,
Gas & Electric N/A N/A $0.00
Total $6,500.00 $7,052.43 $13,552.43
*The costs associated with this measure are claimed in the Idaho Gas Impact Evaluation Report
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the ENERGY STAR® Homes Program in the section below.
3.3.5.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the ENERGY STAR® Homes Program.
3.3.5.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the ENERGY
STAR® Homes Program. The Evaluators selected a random subset of rebate applications to cross-verify
tracking data inputs, summarized in Section 2.2.2.1.
The Evaluators found no significant or notable discrepancies in the project data and rebate
documentation for the rebates in the Idaho electric service territory.
3.3.5.3 Verification Surveys
The Evaluators did not conduct verification surveys for the ENERGY STAR® Homes Program.
3.3.5.4 Impact Analysis
This section summarizes the verified savings results for the ENERGY STAR® Homes Program. The
Evaluators calculated verified savings for the electric measures using the RTF workbook in place at the
time the savings goals for the program was finalized. These RTF UES values were applied to a random

Evaluation Report 47
sample of participants, with verification of project documents such as rebate applications to verify
installation, quantity, and efficiency of the equipment.
3.3.5.5 Verified Savings
The Evaluators reviewed the Avista TRM values along with verified tracking data to estimate adjusted
program savings for each of the ENERGY STAR® Homes measures. In addition, the Evaluators reviewed
and applied the current RTF UES values for each measure along with verified tracking data to estimate
net program savings.
The ENERGY STAR® Homes Program in total displays a realization rate of 102.05% with 50,705 kWh
verified electric energy savings in the Idaho service territory, as displayed in Table 3-28. The realization
rate for the electric savings in the ENERGY STAR® Homes Program deviate from 100% due to the
categorical differences between the applied Avista TRM prescriptive savings value and the more detailed
RTF UES categories.
The Avista TRM applies RTF savings values from heating zone 2 to all rebates. In addition, the Avista TRM
does not take into account cooling zone, which also affects savings assigned in the RTF. The Evaluators
applied the appropriate RTF savings values for the heating zone and cooling zone for each rebated
household. This change led to low realization rates for some rebates and high realization rates for others
within the same Avista E ENERGY STAR® Home – Manufactured Furnace measure category. The overall
effect this change had on the measure is an upward adjustment on savings.
The realization for the E ENERGY STAR® Home – Manufactured, Gas & Electric measure is low because
the expected savings employed an additive methodology between a gas-heated home and an electric-
heated home for the electric savings. However, the Evaluators reviewed the RTF and determined
manufactured home electric savings for a fully natural gas heated home would be closer to the savings a
gas heated home with electricity would save. Therefore, the Evaluators assigned electric savings from
the RTF associated with a fully natural gas-heated home at 43 kWh saved per year.
The Evaluators did not conduct a verification survey for the ENERGY STAR® Homes Program and
therefore did not adjust verified savings with an ISR.
3.3.6 Simple Steps, Smart Savings Program
The Simple Steps, Smart Savings Program is a midstream lighting and appliance program which
encourages consumer to purchase and install high-quality LEDs, light fixtures, energy-efficient
showerheads, and energy-efficient clothes washers by marking down retail prices in the Idaho service
territory.
This section summarizes the impact results of the evaluation results for the Simple Steps, Smart Savings
Program. Table 3-30 summarizes the measures offered under this program.

Evaluation Report 48
Table 3-30: Simple Steps, Smart Savings Program Measures
Measure Description
Impact
Analysis
Methodology
Lighting General purpose and specialty bulbs and fixtures RTF UES
Showerhead 2.0 GPM showerheads RTF UES
Appliance High efficiency clothes washers RTF UES
The following table summarizes the verified electric energy savings for the Simple Steps, Smart Savings
Program impact evaluation.
Table 3-31: Simple Steps, Smart Savings Program Verified Electric Savings
Measure PY2020
Units
Expected
Savings
(kWh)
Adjusted
Savings
(kWh)
Verified
Savings
(kWh)
Realization
Rate
Lighting 234,446 3,144,312 988,339 2,961,197 94.18%
Showerhead 1,128 22,515 22,515 7,224 32.09%
Appliances 1 153 109 142 93.12%
Total 235,575 3,166,980 1,010,962 2,968,563 93.73%
The Simple Steps, Smart Savings Program displayed verified savings of 2,968,563 kWh with a realization
rate of 93.73% against the expected savings for the program. The following table summarizes the
incentive and non-incentive costs associated with the program.
Table 3-32: Simple Steps, Smart Savings Program Costs by Measure
Measure Incentive
Costs
Non-
Incentive
Costs
Total Costs
Lighting $210,589.08 $262,105.78 $472,694.87
Showerhead $3,436.00 $435.06 $3,871.06
Appliances $25.00 $9.29 $34.29
Total $214,050.08 $262,550.14 $476,600.22
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for Simple Steps, Smart Savings Program in the section below.
3.3.6.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Simple Steps, Smart Savings Program.
3.3.6.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for Simple Steps,
Smart Savings Program. The Evaluators requested the monthly invoices for each month in PY2020 for
the Simple Steps, Smart Savings Program from Avista.
The Evaluators collected and reviewed product-level quantity and pricing on each invoice. The
Evaluators found no discrepancies between the invoiced amounts and quantities and the project data
provided by Avista.

Evaluation Report 49
3.3.6.3 Verification Surveys
The Evaluators did not conduct verification surveys for the Simple Steps, Smart Savings Program.
3.3.6.4 Impact Analysis
This section summarizes the verified savings results for the Simple Steps, Smart Savings Program. The
Evaluators calculated verified savings for the electric measures using the RTF workbook in place at the
time the savings goals for the program was finalized.
3.3.6.5 Verified Savings
The Evaluators reviewed the Avista TRM values along with verified tracking data to estimate net
adjusted program savings for those measures. Final verified savings were estimated using the closest
RTF UES lighting category value associated with each measure. Simple Steps, Smart Savings Program
displayed 93.73% realization with 2,968,563 kWh saved, as displayed in Table 3-31.
The Evaluators note that the RTF version used to evaluate this program represents the residential
lighting workbook active at the time the Bonneville Power Administration (BPA) planning for this
program was established (October 1, 2019). The values present in this version of the RTF workbook do
not reflect the current savings values present in the Avista TRM. Therefore, the adjusted savings
displayed is significantly lower than the verified savings. This is because the savings for the lighting
measures decreased as the baseline efficiencies have been updated and increased.
3.4 Conclusions and Recommendations
The Evaluators provide the following conclusions and recommendations for Avista’s Residential Portfolio
program implementation.
3.4.1 Conclusions
The Evaluators provide the following conclusions regarding Avista’s Residential electric programs:
n The Evaluators found the Residential portfolio to demonstrate a total of 4,535,320 kWh with a
realization rate of 96.12%. The Evaluators also conducted a cost-benefit analysis in order to
estimate the Residential portfolio’s cost-effectiveness. The resulting TRC value for this sector is
2.08 while the UCT value is 3.01. Further details on cost-effectiveness methodology can be
found in Appendix C.
n The Residential Portfolio impact evaluation resulted in a realization rate of 96.12% due to slight
differences between the Avista TRM categories and the appropriately assigned RTF UES
categories for each measure as well as billing analysis results. The Evaluators note several
instances in which the Avista TRM value reflects an average of a range of RTF UES values for the
electric measures offered in the Idaho electric service territory. The values had been averaged
across heating zones, water heater storage tank sizes, equipment efficiency values, and fuel
types. The Evaluators, instead of applying these averages, verified the appropriate RTF UES
values for each rebate for a sample of rebates in each program and applied the resulting

Evaluation Report 50
realization rates to the population of rebates for each program. This led to a higher realization
rate, as some rebates reflected RTF savings values higher than the average for that measure.
n The Simple Steps, Smart Savings Program, which contributes 65.45% of the expected savings,
resulted in a realization rate of 93.73% whereas each of the other programs resulted in a
combined 101.00% realization rate. The Shell Program contributed to a 5% decrease in the
overall residential sector, which displayed a realization rate of 96.12%.
n The Evaluators conducted a billing analysis to estimate observed, verified savings for the E
Variable Speed Motor measure. The Evaluators found the resulting savings to be 513 kWh per
year, roughly 124% of the current Avista TRM value for the measure. This savings value was
applied to all rebates completed in PY2020.
n The Evaluators also conducted a billing analysis to estimate observed, verified savings for the E
Electric to Natural Gas Furnace measure in the Fuel Efficiency Program. The Evaluators found
the resulting savings to be 5,068 kWh per year, roughly 72.73% of the current Avista TRM value
for the measure. This savings value was applied to all rebates completed in PY2020.
n In the HVAC Program, the E Smart Thermostat DIY with Electric Heat realization rate is low
because the Avista TRM uses an average of retail and direct install savings values as well as an
average across heating types, while the Evaluators assigned the appropriate RTF UES value for
each installation type and heating zone. The appropriate categories in the RTF led to a lower-
than-expected savings for the retail rebates and a higher-than-expected savings for the direct
install rebates for this measure.
n The Evaluators note that the RTF version used to evaluate the Simple Steps, Smart Savings
Program represents the residential lighting workbook active at the time the Bonneville Power
Administration (BPA) planning for this program was established (October 1, 2019). The values
present in this version of the RTF workbook do not reflect the current savings values present in
the Avista TRM. Therefore, the adjusted savings displayed is significantly lower than the verified
savings. This is because the savings for the lighting measures decreased as the baseline
efficiencies have been updated and increased.
3.4.2 Recommendations
The Evaluators offer the following recommendations regarding Avista’s Residential electric programs:
n The Evaluators recommend Avista work to improve methods for collecting mail-in rebate
application information to reconcile the CC&B database. The values found in the project
documentation should accurately reflect the values represented in the CC&B database.
n A number of rebates were not accompanied with AHRI certification. In order to acquire accurate
equipment efficiencies and tank sizes, AHRI certifications are recommended to be required and
submitted with the rebate application, with an invoice that matches the model number found in
the AHRI certification.
n The realization rate for the electric savings in the Water Heat Program deviate from 100% due to
the methodology in which the Avista TRM prescriptive savings value was applied. The Avista
TRM assigns a combination of the values the RTF assigns for Tier 2 and Tier 3 heat pump water
heaters. However, among document verification, the Evaluators found a majority of water
heaters to be Tier 3 or Tier 4, which the RTF UES assigns a higher savings value. The Evaluators

Evaluation Report 51
recommend splitting the Avista TRM value for Tier 2, Tier 3, and Tier 4 water heaters into
separate values in order to accurately reflect expected savings for the electric water heater
measure.
n The Avista TRM assigns the savings values for water heaters of any size. During document
review, the Evaluators found most of the water heaters to have a storage tank under 55 gallons,
which has a higher savings value in the RTF than water heaters with unknown tank sizes (larger
systems have a more stringent code baseline). The Evaluators applied the RTF UES value for the
associated tank size and tier found for each model number in the sampled rebates. These
changes led to the high realization rate for the E Heat Pump Water Heater measure in the Water
Heat Program. The Evaluators recommend updating the Avista TRM value for this measure
based on actual tank size, in addition to collecting information on the tank size of the measure in
the rebate applications.
n The Evaluators note that some of the model numbers for the rebated equipment were
incomplete and the Evaluators were unable to identify a single AHRI certification that matched
the description in the rebate application. In order to acquire accurate equipment efficiencies,
AHRI certifications are recommended to be required and submitted with the rebate application,
with an invoice that matches the manufacturer and model number found in the AHRI
certification.
n The Evaluators note that a number of rebate applications did not contain values associated with
whether the home is existing or was a new construction home. This field is an input to apply
correct RTF UES values. The Evaluators recommend requiring this field be completed in rebate
applications, both mail-in and web-based.
n The Evaluators cross-referenced the billing data to verify if customers demonstrated the
required heating season electricity usage of 8,000 kWh and natural gas usage of less than 340
Therms, as defined in the program requirements. The Evaluators found many customers used
less than 8,000 kWh or 340 Therms annually. In addition, some customers had insufficient pre-
period data to determine annual usage. The Evaluators recommend Avista verify if customers
meet the requirements prior to completing the rebate.
n The Evaluators conducted a billing analysis for the E Variable Speed Motor measure in the HVAC
Program. The estimated savings value from the billing analysis was roughly 124% of the value
reflected in the Avista TRM. The Evaluators recommend updating the savings value for this
measure in the Avista TRM to reflect observed savings more closely in the territory.
n For the Shell Program, the Evaluators found rebates in which the R-values did not align with
TRM or RTF values (R38 and R64). The Evaluators recommend collecting information in a
standardized manner.
n The Evaluators recommend collecting information on single/double pane windows of the
baseline windows and class of the efficient windows in order to correctly assign RTF UES values.
n The Evaluators also recommend collecting information on single-family/multi-
family/manufactured in the web rebate form. This allows the Evaluators to accurately assign RTF
values. The mail-in rebates collect this information; however, it does not seem to be currently
required to complete the rebate. Therefore many rebates are missing this information.
n The Evaluators note several instances in which the web-based rebate data indicates the
household has electric space heating, but all other sources (project data and document
verification) indicate natural gas space heating, and vice versa. The Evaluators recommend

Evaluation Report 52
updating data collection standards in order for all sources of information to reflect the same
values as the project documentation.
n The Evaluators note that the realization for the E ENERGY STAR® Home – Manufactured, Gas &
Electric measure is low because the Avista TRM savings was employed using an additive
methodology between a gas-heated home and an electric-heated home for the electric savings.
However, the Evaluators reviewed the RTF and determined manufactured home electric savings
for a fully natural gas heated home would be closer to the savings a gas heated home with
electricity would save. The Evaluators recommend adjusting Avista TRM electric savings for this
measure to reflect the RTF values associated with a fully natural gas-heated home at 43 kWh
saved per year.
n The Evaluators recommend the Avista TRM reflect the savings values in effect for the Simple
Steps, Smart Savings Program. The Avista TRM currently uses RTF values in effect on November
1, 2019 for the Simple Steps, Smart Savings whereas the expected savings for this program are
calculated using the RTF-approved BPA workbook in effect on October 1, 2019.

Work Plan 53
4. Low-Income Impact Evaluation Results
The Low-Income Program delivers energy efficiency measures to low-income residential customers in its
Idaho service territory with a partnership with five network Community Action Agencies (“Agencies”)
and one tribal weatherization organization. The Agencies qualify income to prioritize and treat
households based on several characteristics. In-house or contract crews install approved program
measures. In addition, the Agencies have access to other monetary resources which allow them to
weatherize a home or install additional energy efficiency measures.
The Evaluators completed an impact evaluation on Avista’s Low-Income portfolio to verify program-level
and measure-level energy savings for PY2020. The following sections summarize findings for each
electric impact evaluation in the Low-Income Portfolio in the Idaho service territory. The Evaluators used
data collected and reported in the tracking database, online application forms, Avista TRM, and RTF
values to evaluate verified savings. This approach provided the strongest estimate of achieved savings
practical for each program, given its delivery method, magnitude of savings, number of participants, and
availability of data. Table 4-1 summarizes the Low-Income verified impact savings by program. Table 4-2
summarizes the Low-Income portfolio cost-effectiveness results.
Table 4-1: Low-Income Verified Impact Savings by Program
Program Expected
Savings (kWh)
Verified
Savings
(kWh)
Verified
Realization
Rate
Total Costs
Low-Income 195,603 215,300 110.07% $637,629.48
Total Low-Income 195,603 215,300 110.07% $637,629.48
Table 4-2: Low-Income Portfolio Cost-Effectiveness Summary
Sector TRC UCT
Benefits Costs B/C Ratio Benefits Costs B/C Ratio
Low Income $366,774 $605,151 0.61 $272,178 $546,723 0.50
In PY2020, Avista completed and provided incentives for low-income electric measures in Idaho and
achieved total electric energy savings of 215,300 kWh. The Low-Income Program exceeded savings
expectations based on reported savings. The Low-Income sector had achieved 110.07% of the savings
expectations. The Evaluators estimated the TRC value for the Low-Income portfolio is 0.61 while the UCT
value is 0.50. Further details of the impact evaluation results by program are provided in the sections
following.
4.1 Program-Level Impact Evaluation Results
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Low-Income sector in the section below.
4.1.1 Low-Income Program
The Low-Income Program delivers energy efficiency measures to low-income residential customers in its
Idaho service territory with a partnership with five network Community Action Agencies (“Agencies”)

Evaluation Report 54
and one tribal weatherization organization. The Agencies qualify income to prioritize and treat
households based on several characteristics. In-house or contract crews install approved program
measures. In addition, the Agencies have access to other monetary resources which allow them to
weatherize a home or install additional energy efficiency measures.
Avista provides CAP agencies with the following approved measure list, which are reimbursed in full by
Avista. Avista also provides a rebate list of additional energy saving measures the CAP agencies are able
to utilize which are partially reimbursed. The following table summarizes the measures offered under
this program.
Table 4-3 summarizes the measures offered under this program.
Table 4-3: Low-Income Program Measures
Measure Impact Analysis Methodology
Air Infiltration
Avista TRM
Air source heat pump
Attic insulation
Duct insulation
Duct sealing
Electric to air source heat pump
Electric to ductless heat pump
ENERGY STAR® door
ENERGY STAR® refrigerator
ENERGY STAR® window
Floor insulation
Heat pump water heater
LED lighting
Wall insulation
High efficiency furnace
High efficiency tankless natural
gas water heater
Natural gas boiler
Table 4-4 summarizes the verified electric energy savings for the Low-Income Program impact
evaluation.
Table 4-4: Low-Income Program Verified Electric Savings
Measure PY2020
Participation
Expected
Savings
(kWh)
Adjusted
Savings
(kWh)
Verified
Savings
(kWh)
Realization
Rate
E Duct Sealing 1 689 689 689 100.00%
E Ductless Heat Pump 0 0 0 0
E Air Infiltration 18 15,345 15,345 18,018 117.42%
E Energy Star Doors 9 1,304 1,682 1,682 128.94%

Evaluation Report 55
E Energy Star Refrigerator 1 27 39 39 144.44%
E Energy Star Windows 12 1,372 1,371 1,661 121.12%
E HE Air Heat Pump 1 1,493 2,054 2,054 137.54%
E INS - Attic 5 3,507 3,497 1,825 52.05%
E INS - Duct 2 653 619 653 100.00%
E INS - Floor 9 7,298 8,794 9,563 131.04%
E to G Furnace and Water Heater 4 19,660 36,300 36,300 184.64%
E To G Furnace Conversion 13 63,862 59,432 45,448 71.17%
E To G H20 Conversion 5 13,004 9,516 7,930 60.98%
E To Heat Pump Conversion 15 62,338 87,980 87,980 141.13%
Health And Safety 24 0 0 0 -
LED Bulbs 27 1,339 1,337 1,458 108.89%
Total 146 195,603 228,654 215,300 110.07%
The Low-Income Program displayed verified savings of 215,300 kWh with a realization rate of 110.07%
against the expected savings for the program. The following table summarizes the incentive and non-
incentive costs associated with the program.
Table 4-5: Low-Income Program Costs by Measure
Measure Incentive
Costs
Non-
Incentive
Costs
Total Costs
E Duct Sealing $517.80 $832.81 $1,350.61
E Ductless Heat Pump N/A N/A $0.00
E Air Infiltration $21,705.21 $16,350.71 $38,055.92
E Energy Star Doors $11,435.67 $3,801.49 $15,237.16
E Energy Star Refrigerator $749.00 $32.94 $781.94
E Energy Star Windows $3,919.34 $4,250.72 $8,170.06
E HE Air Heat Pump $1,885.18 $1,826.43 $3,711.61
E INS - Attic $4,289.63 $4,670.17 $8,959.80
E INS - Duct $1,110.19 $1,669.51 $2,779.70
E INS - Floor $12,489.19 $24,468.92 $36,958.11
E to G Furnace and Water Heater $38,426.38 $43,876.60 $82,302.98
E To G Furnace Conversion $76,367.48 $54,933.99 $131,301.47
E To G H20 Conversion $10,442.31 $5,773.23 $16,215.54
E To Heat Pump Conversion $152,547.26 $78,251.43 $230,798.69
Health And Safety $59,415.41 $0.00 $59,415.41
LED Bulbs $550.78 $1,039.72 $1,590.50
Total $395,850.83 $241,778.65 $637,629.48
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for Low-Income Program in the section below.
4.1.1.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Low-Income Program.

Evaluation Report 56
4.1.1.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the Low-Income
Program. The Evaluators selected a subset of rebate applications to cross-verify tracking data inputs,
summarized in Section 2.2.2.1.
The Evaluators reviewed the project documentation provided by Avista and identified conflicting square
footage or number of units between the aggregated project data from the CC&B and the rebate project
documentation provided in the data request for document verification. The Evaluators, updated
quantity based on project documentation.
The Evaluators note that some project data account numbers do not match the account numbers
referenced in the project documentation. In addition, the Evaluators found conflicting information in the
project documentation on a number of homes’ heating type. The Evaluators recommend confirming and
documenting all rebate applications for completed and accurate heating type details.
The Evaluators also note that project documentation contains additional equipment included in some
invoices. These additional equipment contribute to the total project cost. The Evaluators identified and
removed three duplicated rebates. These rebates seem to have been duplicated due to rebate
administration corrections.
The Evaluators also utilized the delivered billing data to check the household-level annual usage. The
Low-Income Program requires a 20% annual energy usage cap on claimed energy savings. The
Evaluators found some discrepancies between the 20% annual consumption cap and the claimed energy
savings. The Evaluators recommend checking each project against billing data prior to reporting energy
savings for the project, as well as documenting each household’s usage as well as the date range used to
calculate the household consumption estimate.
4.1.1.3 Verification Surveys
The Evaluators did not conduct verification surveys for the Low-Income Program.
4.1.1.4 Impact Analysis
This section summarizes the verified savings results for the Low-Income Program. The Evaluators
calculated verified savings for Low-Income Program measures using the Avista TRM. However, a whole
building billing analysis was completed to supplement the findings from the desk review.
4.1.1.5 Billing Analysis
The results of the billing analysis for the Low-Income Program are provided below. Table 4-6 displays
customer counts for customers considered for billing analysis (i.e. customer with single-measure
installations) and identifies measures that met the requirements for a billing analysis.
The Evaluators attempted to estimate measure-level Low-Income Program energy savings through
billing analysis regression with a counterfactual group selected via propensity score matching. The
Evaluators attempted to isolated each unique measure. In doing so, the Evaluators also isolate the
measure effects using the customer’s consumption billing data. However, participation for the Low-

Evaluation Report 57
Income program resulted in a small number of customers with isolated measures, as displayed in Table
4-6 and therefore the Evaluators were unable to estimate measure-level savings through billing analysis.
Table 4-6: Measures Considered for Billing Analysis, Low-Income Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation for
Billing Analysis*
Electric to air source heat pump ü 24
Electric to ductless heat pump ü 9
Air source heat pump ü 1
ENERGY STAR® door ü 0
ENERGY STAR® refrigerator ü 8
ENERGY STAR® window ü 0
Air Infiltration ü 0
Duct sealing ü 0
Attic Insulation ü 2
Duct insulation ü 0
Wall insulation ü 0
Floor insulation ü 4
LED lighting ü 20
*No measures had sufficient participation of isolated measures
The Evaluators instead conducted a whole-home billing analysis for all the electric measures combined
in order to estimate savings for the average household participating in the program, across all measures.
The Evaluators successfully created a matched cohort for the electric measure households. Customers
were matched on zip code (exact match) and their average pre-period seasonal usage, including
summer, fall, winter, and spring for each control and treatment household. The Evaluators were
provided a considerable pool of control customers to draw upon. The Evaluators used nearest neighbor
matching with a 5 to 1 matching ratio. Therefore, each treatment customer was matched to 5 similar
control customers.
Table 4-7 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the Low-Income Program as it provided the highest adjusted R-squared among the
regression models. Savings are statistically significant at the 90% level for all measures and the adjusted
R-squared shows the model provided an excellent fit for the data (adjusted R-squared > 0.90).
Table 4-7: Measure Savings, Low-Income Program
Measure Treatment
Customers
Control
Customers
Annual Savings
per Customer
(kWh)
90%
Lower
CI
90%
Upper
CI
Adjusted
R-
Squared
Model
All Electric Measures 77 364 1,693 1145 2624 0.73 Model 2: PPR

The Evaluators applied these regression savings estimates to the program as a whole, by the number of
unique households in the program and found a realization rate of 129.86% for all electric measures in
the program. Further details of the billing analysis can be found in Appendix A.

Evaluation Report 58
4.1.1.6 Verified Savings
Due to insufficient participation to conduct measure-level billing analyses, the Evaluators reviewed the
Avista TRM values along with verified tracking data to estimate net program savings for those measures.
Adjusted savings were estimated using the Avista TRM. The Low-Income Program in total displays a
realization rate of 110.07% with 215,300 kWh verified electric energy savings in the Idaho service
territory, as displayed in Table 4-4. The billing analysis supports this estimate, with the billing analysis
estimating a 129.86% realization. Due to requirements for measure-level verified savings for cost-
effectiveness testing, the Evaluators designated the adjusted savings as final.
The Evaluators note that the majority of deviations from 100% realization rate is due to the change in
square footage or number of units verified in the project documentation. The Evaluators updated the
quantity based on new project data.
4.2 Conclusions and Recommendations
The Evaluators provide the following conclusions and recommendations for Avista’s Low-Income
Portfolio program implementation.
4.2.1 Conclusions
The Evaluators provide the following conclusions regarding Avista’s Low-Income electric programs:
n The Evaluators found the Residential portfolio to demonstrate a total of 215,300 kWh with a
realization rate of 110.07%. The Evaluators also conducted a cost-benefit analysis in order to
estimate the Residential portfolio’s cost-effectiveness. The resulting TRC value for this sector is
0.61 while the UCT value is 0.50. These values are expected, as the Low-Income portfolio is not
expected to meet cost-effectiveness but are implemented in order to provide energy efficiency
benefits to low-income customers. Further details on cost-effectiveness methodology can be
found in Appendix C.
n The Low-Income Portfolio impact evaluation resulted in a 110.07% realization rate. The
realization rates for each program deviate from 100% due to differences between the Avista
TRM values and the appropriately assigned RTF UES values. For the Low-Income Program, the
Evaluators applied a realization rate from a sample of rebates after verifying documentation for
quantity and efficiency of measures.
n The Evaluators attempted to estimate measure-level Low-Income Program energy savings
through billing analysis regression with a counterfactual group selected via propensity score
matching. The Evaluators attempted to isolate each unique measure. However, participation for
the Low-Income program resulted in a small number of customers with isolated measures and
therefore the Evaluators conducted a whole-home billing analysis for all the electric measures
combined in the Low-Income in order to estimate savings for the average household
participating in the program, across all measures. The Evaluators found a realization rate of
130% for all electric measures in the program, which supported the realization rate of 115%
from the desk review.
n Some rebates included in the Low-Income Program indicate that savings had been capped at 20%
of consumption. The provided project data do not include adequate information to determine

Evaluation Report 59
when savings values are being appropriately capped. The Evaluators recommend that annual
consumption be provided for each measure in the tracking data, if practical, so that evaluation
can include verifying that savings are being capped at 20% consumption for application measures.
4.2.2 Recommendations
The Evaluators offer the following recommendations regarding Avista’s Low-Income electric programs:
n The Evaluators note that most deviations from 100% realization rate is due to differences
between the limited measure category options Avista TRM values and the more detailed
categories referencing heating zone, cooling zone, heating type, and bulb types present in the
RTF. The Evaluators recommend that Avista reference the more detailed RTF measures when
calculating expected savings for the programs.
n The Evaluators reviewed the project documentation provided by Avista and identified conflicting
square footage or number of units between the aggregated project data from the CC&B and the
rebate project documentation provided in the data request for document verification. In
addition, the unit type, in terms of square footage or number of measures (windows, doors, etc)
was not documented consistently and therefore savings values were applied inaccurately. The
Evaluators recommend updating CC&B documentation standards to more accurately reflect
values present on the rebate applications.
n The Evaluators found discrepancies between the 20% annual consumption cap and the claimed
energy savings. The Evaluators recommend checking each project against billing data prior to
reporting energy savings for the project, as well as documenting each household’s usage as well
as the date range used to calculate the household consumption estimate.

Evaluation Report 60
5. Appendix A: Billing Analysis Results
This appendix provides additional details on the billing analyses conducted for each program.
5.1 HVAC Program
The results of the billing analysis for the HVAC program are provided in this section. The methodology
for the billing analysis is provided in Section 2.2.3.2. Table 5-1 displays customer counts for customers
considered for billing analysis (i.e. customer with single-measure installations) and identifies measures
that met the requirements for a billing analysis.
The Evaluators attempted to estimate measure-level HVAC Program energy savings through billing
analysis regression with a counterfactual group selected via propensity score matching. The Evaluators
attempted to isolated each unique measure. In doing so, the Evaluators also isolate the measure effects
using the customer’s consumption billing data.
A billing analysis was completed for measures that had at least 75 customers with single-measure
installations. This ensured that measures would have a sufficient sample size after applying PSM data
restrictions (e.g. sufficient pre- and post-period data). The billing analysis included participants in both
PY2019 and PY2020 in order to acquire the maximum number of customers possible. However, results
from billing analyses are only extrapolated to PY2020 participants.
Table 5-1: Measures Considered for Billing Analysis, HVAC Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation
for Billing
Analysis
E Electric To Air Source Heat Pump N/A N/A
E Electric to Ductless Heat Pump N/A N/A
E Smart Thermostat DIY with Electric
Heat N/A N/A
E Smart Thermostat Paid Install with
Electric Heat N/A N/A
E Variable Speed Motor ü 206 ü

The Evaluators were provided a considerable pool of control customers to draw upon, as shown in Table
5-2. The Evaluators used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each
treatment customer was matched to 5 similar control customers. Also shown in Table 5-2, are the
impact of various restrictions on the number of treatment and control customers that were included in
the final regression model. The “Starting Count” displays the beginning number of customers available
prior to applying the data restrictions, while the “Ending Count” displays the number of customers after
applying data restrictions and final matching.
Table 5-2: Cohort Restrictions, HVAC Program
Measure Data Restriction Treatment
Customers
Control
Customers

Evaluation Report 61
E Variable Speed
Motor
Starting Count 206 132,725
Install Date Range: 2019-01-01 to 2020-06-30 206 132,725
Control Group Usage Outlier (>2X max treatment usage) 206 132,675
Incomplete Post-Period Bills (<24 months) 147 78,645
Incomplete Pre-Period Bills 126 72,062
Ending Count (Matched by PSM) 126 630
Figure 5-1 and Figure 5-2 display the density of each variable employed in propensity score matching for
the E Variable Speed Motor measure, before and after conducting matching. The figures following display
the density of each variable employed in propensity score matching for the other billing analysis
measures, before and after matching.
The distributions prior to matching appear to be less similar in summer, with control customers averaging
higher usage. However, after matching, the pre-period usage distribution in summer is more similar
between the groups. The remaining pre-period seasons (winter, summer, fall), closely overlap before and

Evaluation Report 62
after matching, indicating little differences exist on average between the groups prior to matching and
validating the initial selection of control customers.
Figure 5-1: Covariate Balance Before Matching, Electric Variable Speed Motor

Figure 5-2: Covariate Balance After Matching, Electric Variable Speed Motor

The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for the measure. T-tests of monthly pre period usage can
yield a statistically significant difference 40% of the time for one to two months out of 12. Thus, the
Evaluators set a tolerance band allowing two months out of 12 to vary in pre-period usage at the 95%
confidence level. All groups passed this threshold. In addition, the chi-squared test returned a p-value
well over 0.05 for all measures, indicating that pre-period usage was balanced between the groups.
Lastly, the standardized difference test returned values well under the recommended cutoff of 25,
typically falling under 10, further indicating the groups were well matched on all included covariates.

Evaluation Report 63
Table 5-3 provides results for the t-test on pre-period usage between the treatment and control groups
after matching for the HVAC program. The Evaluators placed a threshold of two rejects for each
measure as there is a 40% likelihood that one or two months may show statistical variance due to
chance. The variable speed motor measure did not exceed this threshold.
Table 5-3: Pre-period Usage T-test for Electric Variable Speed Motor, HVAC Program
Month
Average Daily
Usage (kWh),
Control
Average Daily
Usage (kWh),
Treatment
T Statistic Std
Error P-Value Reject
Null?
Jan 29.52 35.01 -1.57 3.49 0.118 No
Feb 28.54 32.01 -1.27 2.74 0.206 No
Mar 25.57 29.30 -1.65 2.25 0.101 No
Apr 22.68 25.32 -1.51 1.75 0.133 No
May 22.25 24.29 -1.30 1.57 0.195 No
Jun 24.46 26.32 -1.06 1.76 0.289 No
Jul 30.72 35.06 -2.04 2.13 0.043 Yes
Aug 28.76 32.84 -2.19 1.86 0.030 Yes
Sep 23.53 24.68 -0.57 2.01 0.566 No
Oct 22.95 25.43 -1.35 1.84 0.177 No
Nov 27.34 30.29 -1.28 2.30 0.201 No
Dec 30.83 34.59 -1.32 2.84 0.187 No

Table 5-4 provides customer counts for customers in the final regression model by assigned weather
station ID for each measure. In addition, TMY HDD and CDD from the nearest available TMY weather
station is provided as well as the weighted HDD/CDD for each measure. The HDD and CDD was weighted
by the number of treatment customers assigned to a weather station.
Table 5-4: TMY Weather, HVAC Program
Measure USAF Station
ID
Treatment
Customers
TMY
USAF ID
TMY
HDD
TMY
CDD
Weighted
TMY HDD
Weighted
TMY CDD
E Variable Speed Motor 720322 1 727834 6,915 376 6,527 475
E Variable Speed Motor 726817 1 727834 6,915 376 6,527 475
E Variable Speed Motor 727827 1 727827 5,428 731 6,527 475
E Variable Speed Motor 727830 5 727830 5,511 907 6,527 475
E Variable Speed Motor 727834 43 727834 6,915 376 6,527 475
E Variable Speed Motor 727850 3 727850 6,707 379 6,527 475
E Variable Speed Motor 727855 5 727855 7,360 439 6,527 475
E Variable Speed Motor 727856 57 727856 6,246 519 6,527 475

Evaluation Report 64
Table 3-17 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the HVAC Program as it provided the highest adjusted R-squared among the regression
models. Savings are statistically significant at the 90% level for E Variable Speed Motor The adjusted R-
squared shows the model provided an excellent fit for the data.
Table 5-5: Measure Savings, HVAC Program
Measure Treatment
Customers
Control
Customers
Annual
kWh
Savings per
Customer
90%
Lower
CI
90%
Upper
CI
Relative
Precision
(90% CI)
Adjusted
R-
Squared
Model
E Variable
Speed Motor 126 630 513 126 900 75.4% 0.88 Model
2: PPR

Figure 5-3 provides the monthly verified savings per customer for the variable speed motor measure.
Figure 5-3: Electric Variable Speed Motor Monthly Savings, HVAC Program

In addition to the net savings value represented above, the Evaluators also conducted a treatment-only
regression model for each of the measures described above. Table 5-6 provides annual
savings/customer for the HVAC program for each measure and regression model. The PPR model was
selected for ex-post net savings because it provided the best fit for the data (highest adjusted R-
squared). The treatment-only model represents estimated gross savings for this measure. However, the
Evaluators were unable to estimate a statistically significant value.

Evaluation Report 65
Table 5-6: Measure Savings for All Regression Models, HVAC Program
Measure Model Treatment
Customers
Control
Customers
Annual
Savings per
Customer
(kWh)
90%
Lower
CI
90%
Upper CI
Relative
Precision
(90% CI)
Adjusted
R-
Squared
E Variable
Speed Motor Diff-in-diff 126 630 687* -821 2,195 220% 0.02
E Variable
Speed Motor PPR 126 630 513 126 900 75% 0.88
E Variable
Speed Motor
Treatment
Only (Gross) 126 N/A 256* -316 829 223% 0.76
*Not statistically significant
5.2 Fuel Efficiency Program
The results of the billing analysis for the Fuel Conversion program are provided in this section. The
methodology for the billing analysis is provided in Section 2.2.3.2. Table 5-7 displays customer counts for
customers considered for billing analysis (i.e. customer with single-measure installations) and identifies
measures that met the requirements for a billing analysis.
The Evaluators attempted to estimate measure-level Fuel Efficiency Program energy savings through
billing analysis regression with a counterfactual group selected via propensity score matching. The
Evaluators attempted to isolated each unique measure. In doing so, the Evaluators also isolate the
measure effects using the customer’s consumption billing data.
A billing analysis was completed for measures that had at least 75 customers with single-measure
installations. This ensured that measures would have a sufficient sample size after applying PSM data
restrictions (e.g. sufficient pre- and post-period data). The billing analysis included participants in both
PY2019 and PY2020 in order to acquire the maximum number of customers possible. However, results
from billing analyses are only extrapolated to PY2020 participants.
Table 5-7: Measures Considered for Billing Analysis, Fuel Efficiency Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation
for Billing
Analysis
E Electric To Natural Gas Furnace ü 186 ü
E Electric To Natural Gas Furnace &
Water Heat ü 33

The Evaluators were successful in creating a matched cohort for each of the measures with sufficient
participation. Customers were matched on zip code (exact match) and their average pre-period seasonal
usage, including summer, fall, winter, and spring for each control and treatment household.
The Evaluators were provided a considerable pool of control customers to draw upon, as shown in Table
5-8. The Evaluators used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each
treatment customer was matched to 5 similar control customers. Also shown in Table 5-8, are the
impact of various restrictions on the number of treatment and control customers that were included in

Evaluation Report 66
the final regression model. The “Starting Count” displays the beginning number of customers available
prior to applying the data restrictions, while the “Ending Count” displays the number of customers after
applying data restrictions and final matching.
Table 5-8: Cohort Restrictions, Fuel Efficiency Program
Measure Data Restriction
# of
Treatment
Customers
# of
Control
Customers
E Electric To Natural Gas Furnace Starting Count 186 132,725
E Electric To Natural Gas Furnace Install Date Range: January 1, 2019 to June 30,
2020 162 132,725
E Electric To Natural Gas Furnace Control Group Usage Comparable to Treatment
Group 158 132,654
E Electric To Natural Gas Furnace Incomplete Post-Period Bills (<4 months) 132 89,361
E Electric To Natural Gas Furnace Incomplete Pre-Period Bills (<10 months) 85 69,413
E Electric To Natural Gas Furnace Restrict to Controls w/ Probable Electric
Resistance9 85 10,412
E Electric To Natural Gas Furnace Ending Count (Matched by PSM) 85 421
Figure 5-4 and Figure 5-5 display the density of each variable employed in propensity score matching for
the E Electric to Natural Gas Furnace measure, before and after conducting matching.
The distributions prior to matching appear to be less similar, with control customers averaging lower
usage. However, after matching, the pre-period usage distribution is more similar between the groups.
The pre-period usage in the winter before and after matching averages a more spread distribution for the
treatment group, however, the average usage between groups appears the same after matching (verified
with t-test on pre-usage).

9 The Evaluators restricted to controls with pre-period winter usage higher than the 85th percentile (i.e. top 15%) as these
customers are more likely to have electric resistance heating.

Evaluation Report 67
Figure 5-4: Covariate Balance Before Matching, E Electric to Natural Gas Furnace

Figure 5-5: Covariate Balance After Matching, E Electric to Natural Gas Furnace

The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for the measure. The t-test displayed no statistically
significant differences at the 95% level in average daily consumption between the treatment and control
groups for any month in the pre-period. In addition, the chi-squared test returned a p-value well over
0.05 for all measures, indicating that pre-period usage was balanced between the groups. Lastly, the
standardized difference test returned values well under the recommended cutoff of 25, and always
falling under 10, further indicating the groups were well matched on all included covariates.

Evaluation Report 68
Table 5-9 provides the results for the t-test on pre-period usage between the treatment and control
groups after matching for the Fuel Efficiency Program. The P-Value is over 0.05 for each month, meaning
pre-period usage between treatment and control groups is similar at the 95% confidence level.
Table 5-9: Pre-period Usage T-test for Electric to Gas Furnace, Fuel Conversion Program
Month
Average Daily
Usage (kWh),
Control
Average Daily
Usage (kWh),
Treatment
T Stat Std Error P-Value Reject Null?
Jan 72.502 69.978 0.699 3.613 0.486 No
Feb 69.808 67.655 0.611 3.522 0.542 No
Mar 59.063 60.098 -0.344 3.006 0.731 No
Apr 43.331 43.494 -0.077 2.133 0.939 No
May 30.497 29.155 0.915 1.466 0.362 No
Jun 29.164 27.861 0.802 1.624 0.423 No
Jul 34.092 33.291 0.364 2.198 0.716 No
Aug 33.202 32.844 0.175 2.050 0.862 No
Sep 30.944 30.174 0.435 1.766 0.664 No
Oct 41.417 41.816 -0.156 2.567 0.877 No
Nov 59.142 60.794 -0.389 4.246 0.698 No
Dec 69.305 69.601 -0.072 4.086 0.942 No

Table 5-10 provides customer counts for customers in the final regression model by assigned weather
station ID for each measure. In addition, TMY HDD and CDD from the nearest available TMY weather
station is provided as well as the weighted HDD/CDD for each measure. The HDD and CDD was weighted
by the number of treatment customers assigned to a weather station.
Table 5-10: TMY Weather, Fuel Efficiency Program
Measure
USAF
Station
ID
# of
Treatment
Customers
TMY USAF
ID TMY HDD TMY
CDD
Weighted
TMY HDD
Weighted
TMY CDD
E Electric to Natural Gas Furnace 720322 3 727834 6,915 376 6,333 517
E Electric to Natural Gas Furnace 726817 3 727834 6,915 376 6,333 517
E Electric to Natural Gas Furnace 727827 4 727827 5,428 731 6,333 517
E Electric to Natural Gas Furnace 727830 7 727830 5,511 907 6,333 517
E Electric to Natural Gas Furnace 727834 13 727834 6,915 376 6,333 517
E Electric to Natural Gas Furnace 727855 2 727855 7,360 439 6,333 517
E Electric to Natural Gas Furnace 727856 47 727856 6,246 519 6,333 517
E Electric to Natural Gas Furnace 727857 4 727857 6,467 299 6,333 517
E Electric to Natural Gas Furnace 727870 2 727856 6,246 519 6,333 517

Evaluation Report 69
Table 5-11 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the Fuel Efficiency Program as it provided the highest adjusted R-squared among the
regression models. Savings are statistically significant at the 90% level for all measures and the adjusted
R-squared shows the model provided an excellent fit for the data.
Table 5-11: Measure Savings, Fuel Efficiency Program
Measure
# of
Treatment
Customers
# of
Control
Customers
Annual
Savings/Customer
(kWh)
90%
Lower
CI
90%
Upper
CI
90%
Relative
Precision
Adjusted
R-
Squared
Model
E Electric to Natural
Gas Furnace 85 421 5,068 4,384 5,7512 0.13 0.73 Model 2:
PPR

Figure 5-6 provides monthly TMY savings per customer for the Fuel Conversion program. As expected,
the greatest savings occur during the winter months.
Figure 5-6: E Electric to Gas Furnace Monthly Savings, Fuel Conversion Program

The Evaluators found the E Electric To Natural Gas Furnace measure to display 5,068 kWh savings per
year. This estimate was statistically significant at the 90% confidence interval with precision of 13%. The
Evaluators estimate the Therms penalty for this measure with the following equation:
Equation 5-1: Furnace Conversion Heating Load
𝐻𝑒𝑎𝑡𝑖𝑛𝑔 𝐿𝑜𝑎𝑑=𝐴𝑛𝑛𝑢𝑎𝑙 𝑘𝑊ℎ 𝑆𝑎𝑣𝑖𝑛𝑔𝑠∗𝐶𝑂𝑃/012$3#2 ∗3,412 𝑘𝑊ℎ
𝐵𝑇𝑈100,000 𝑇ℎ𝑒𝑟𝑚𝑠
𝐵𝑇𝑈

Equation 5-2 Furnace Conversion Therms Penalty
𝑇ℎ𝑒𝑟𝑚𝑠 𝑃𝑒𝑛𝑎𝑙𝑡𝑦=𝐻𝑒𝑎𝑡𝑖𝑛𝑔 𝐿𝑜𝑎𝑑
0.80 𝐵𝑎𝑠𝑒 𝐴𝐹𝑈𝐸
919.0
769.1 722.3
385.4
281.9
21.6
-98.6 -103.4
76.1
464.9
716.4
913.5
-200.0
0.0
200.0
400.0
600.0
800.0
1000.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Mo
n
t
h
l
y

S
a
v
i
n
g
s
/
C
u
s
t
o
m
e
r

(
T
h
e
r
m
s
)
Month

Evaluation Report 70
Where,
n 𝐻𝑒𝑎𝑡𝑖𝑛𝑔 𝐿𝑜𝑎𝑑 = The number of full load hours required for heating the home per year
n 𝐴𝑛𝑛𝑢𝑎𝑙 𝑘𝑊ℎ 𝑆𝑎𝑣𝑖𝑛𝑔𝑠 = measure saving result from linear regression (5,068 kWh/year)
n 𝐶𝑂𝑃/012$3#2 = Coefficient of performance (equal to 1, assuming electric resistance baseline)
The Therms penalty for the E Electric to Natural Gas Furnace measure is 216.15 Therms. This penalty is
applied in the Idaho Gas Impact Evaluation Report.
Due to the insufficient isolated measure participation for the E Electric To Natural Gas Furnace & Water
Heater measure, the Evaluators assigned savings for this measure using the Avista TRM value of 9,789
kWh and -565 Therms savings per year.
Evaluators also conducted a treatment-only regression model for each of the measures described above.
This analysis was completed at the request of Avista in order to help with program planning. Table 5-12
provides annual savings/customer for the Fuel Conversion program for each measure and regression
model. The PPR model was selected for ex post savings because it provided the best fit for the data
(highest adjusted R-squared). The treatment-only model represents estimated gross savings for this
measure at 5,430 Therms saved per year.
Table 5-12: Measure Savings for All Regression Models, Fuel Efficiency Program
Measure Model
# of
Treatment
Customers
# of
Control
Customers
Annual
Savings/Customer
(kWh)
90%
Lower
CI
90%
Upper
CI
90%
Relative
Precision
Adjusted
R-
Squared
Electric to Natural
Gas Furnace Diff-in-diff 85 421 5,267.69 3,572.27 6,963.10 0.32 0.26
Electric to Natural
Gas Furnace PPR 85 421 5,068.03 4,384.25 5,751.80 0.13 0.73
Electric to Natural
Gas Furnace
Treatment
Only (Gross) 85 N/A 5,430.42 4,625.74 6,235.10 0.15 0.70

5.3 Low-Income Program
The Evaluators conducted a whole-home billing analysis for all the electric measures combined in order
to estimate savings for the average household participating in the program, across all measures. The
Evaluators successfully created a matched cohort for the electric measure households. Customers were
matched on zip code (exact match) and their average pre-period seasonal usage, including summer, fall,
winter, and spring for each control and treatment household.
The Evaluators were provided a considerable pool of control customers to draw upon, as shown in Table
5-13. The Evaluators used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each
treatment customer was matched to 5 similar control customers. Also shown in Table 5-13, are the
impact of various restrictions on the number of treatment and control customers that were included in
the final regression model. The “Starting Count” displays the beginning number of customers available
prior to applying the data restrictions, while the “Ending Count” displays the number of customers after
applying data restrictions and final matching.

Evaluation Report 71
Table 5-13: Cohort Restrictions, Low-Income Program
Measure Data Restriction
# of
Treatment
Customers
# of
Control
Customers
Whole home electric

Starting Count 147 2,632
Install Date Range: January 1, 2019 to June 30, 2020 90 2,632
Control Group Usage Outlier (>2X max treatment usage) 90 2,630
Incomplete Post-Period Bills (<4 months) 83 2,172
Incomplete Pre-Period Bills (<10 months) 77 1,932
Ending Count (Matched by PSM) 77 364
Figure 5-7 and Figure 5-8 display the density of each variable employed in propensity score matching for
the combined electric measures before and after conducting matching.
The distributions prior to matching appear to be less similar in summer, with control customers averaging
higher usage. However, after matching, the pre-period usage distribution in summer is more similar
between the groups. The remaining pre-period seasons (winter, summer, fall), closely overlap before and
after matching, indicating little differences exist on average between the groups prior to matching and
validating the initial selection of control customers.
Figure 5-7: Covariate Balance Before Matching, Low-Income Electric Measures

Evaluation Report 72
Figure 5-8: Covariate Balance After Matching, Low-Income Electric Measures

The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for each measure. The t-test displayed no statistically
significant differences at the 95% level in average daily consumption between the treatment and control
groups for any month in the pre-period. In addition, the chi-squared test returned a p-value well over
0.05 for all measures, indicating that pre-period usage was balanced between the groups. Lastly, the
standardized difference test returned values were under 10 (well under the recommended cutoff of 25),
further indicating the groups were well matched on all included covariates.
Table 5-14 provides results for the t-test on pre-period usage between the treatment and control groups
after matching for the Low-Income program. The P-Value is over 0.05 for each month, meaning pre-
period usage between treatment and control groups is similar at the 95% confidence level.
Table 5-14: Pre-period Usage T-test for Electric Measures, Low-Income Program
Month
Average Daily
Usage
(Therms),
Control
Average Daily
Usage
(Therms),
Treatment
T Statistic Std Error P-Value Reject
Null?
Jan 69.94 70.41 -0.130 3.608 0.897 No
Feb 53.51 56.83 -1.235 2.687 0.217 No
Mar 63.85 66.38 -0.778 3.255 0.437 No
Apr 40.20 43.70 -1.692 2.068 0.091 No
May 35.14 37.91 -1.529 1.814 0.127 No
Jun 22.69 24.73 -1.337 1.523 0.182 No
Jul 22.56 24.08 -0.990 1.528 0.322 No
Aug 28.73 28.07 0.228 2.869 0.819 No

Evaluation Report 73
Sep 22.87 25.08 -1.383 1.597 0.167 No
Oct 24.97 28.61 -2.192 1.661 0.029 No
Nov 52.77 57.49 -1.637 2.884 0.102 No
Dec 60.34 64.69 -1.355 3.206 0.176 No

Table 5-15 provides customer counts for customers in the final regression model by assigned weather
station ID for each measure. In addition, TMY HDD and CDD from the nearest available TMY weather
station is provided as well as the weighted HDD/CDD for each measure. The HDD and CDD was weighted
by the number of treatment customers assigned to a weather station.
Table 5-15: TMY Weather, Low-Income Program
Measure USAF
Station ID
# of
Treatment
Customers
TMY USAF ID TMY
HDD
TMY
CDD
Weighted
TMY HDD
Weighted
TMY CDD
All Electric Measures 727827 9 727827 5,428 731 6,171 550
All Electric Measures 727830 18 727830 5,510 906 6,171 550
All Electric Measures 727834 4 727834 6,915 376 6,171 550
All Electric Measures 727850 3 727850 6,246 519 6,171 550
All Electric Measures 727855 3 727855 7,360 439 6,171 550
All Electric Measures 727856 94 727856 6,246 519 6,171 550
All Electric Measures 727857 16 727857 6,467 299 6,171 550
In addition to the net savings value represented above, the Evaluators also conducted a treatment-only
regression model for each of the measures described above. Table 5-16 provides annual
savings/customer for the Low-Income program for all electric measures and regression model. The PPR
model was selected for ex-post net savings because it provided the best fit for the data (highest
adjusted R-squared). The treatment-only model represents estimated gross savings for this measure.
The Evaluators estimate gross savings for each Low-Income participant is 1,404 kWh per year.
Table 5-16: Household Savings for All Regression Models, Low-Income Program
Measure Model
# of
Treatment
Customers
# of
Control
Customers
Annual
Savings/Customer
90%
Lower
CI
90%
Upper
CI
Adjusted
R-Squared
All Electric
Measures Diff-in-diff 77 364 2,097* 0 4,340 0.34
All Electric
Measures PPR 77 364 1,693 1,146 2,624 0.73
All Electric
Measures
Treatment
Only (Gross) 555 64 1,404 0 4,049 0.69
*Not statistically significant

Evaluation Report 74
6. Appendix B: Summary of Survey Respondents
This section summarizes additional insights gathered from the simple verification surveys deployed by
the Evaluators for the impact evaluation of Avista’s Residential and Low-Income Programs.
Survey respondents confirmed installing between one and three measures that were rebated by Avista,
displayed in Table 6-1.
Table 6-1: Type and Number of Measures Received by Respondents
Measure Category Total Percent
One Measure 161 61%
Two Measures 69 26%
Three Measures 32 12%
HVAC 140 53%
Water Heater 138 53%
Smart Thermostat 113 43%
Variable Speed Motors 4 2%
The Evaluators asked respondents to provide information regarding their home, as displayed in Table
6-2. Most respondents noted owning a single-family home between 1,000-3,000 square feet with
central air conditioning.

Evaluation Report 75
Table 6-2: Survey Respondent Home Characteristics10

10 Four contractors or construction companies were not asked these questions.
Question Response Percent (n=258)
Own 97%
Rent 3%
Single-family house detached from any
other house 89%
Single-family house attached to one or
more other houses (e.g., duplex,
condominium, townhouse)
4%
Mobile or manufactured home 6%
Apartment with 2 or 3 units 1%
Garage/outbuilding 1%
Don’t Know 1%
Window air conditioning / a room AC unit 12%
Central air conditioning 73%
Neither 14%
Don’t Know 1%
Less than 1,000 square feet 6%
1,000-1,999 square feet 38%
2,000-2,999 square feet 35%
3,000-3,999 square feet 14%
4,000 or more square feet 6%
Don’t know 1%
Before 1960 21%
1960 to 1969 5%
1970 to 1979 17%
1980 to 1989 12%
1990 to 1999 12%
2000 to 2009 16%
2010 to 2018 15%
Don’t know 1%
Do you rent or your home?
Which of the following best
describe your home?
Does your home have central air
conditioning, window air
conditioning, or neither?
About how many square feet is
your home?
When was your home built?

Evaluation Report 76
7. Appendix C: Cost Benefit Analysis Results
The Evaluators estimated the cost-effectiveness for the Avista Residential and Low-Income Programs
using evaluated savings results, economic inputs provided by Avista, and incremental costs and non-
energy impacts from the RTF. The table below presents the cost-effectiveness results for the PY2020
portfolio.
Table 7-1: Cost-effectiveness Results
Program TRC UCT RIM PCT TRC Net
Benefits
Residential 2.08 3.01 0.47 3.96 $2,897,811
Low Income 0.61 0.50 0.27 N/A* ($238,377)
Total 1.81 2.39 0.45 N/A* $2,659,434
*Low Income is offered at no cost to participants; PCT is not calculable.

7.1 Approach
The California Standard Practice Model was used as a guideline for the calculations. The cost-
effectiveness analysis methods that were used in this analysis are among the set of standard methods
used in this industry and include the Utility Cost Test (UCT)11, Total Resource Cost Test (TRC), Ratepayer
Impact Measure Test (RIM), and Participant Cost Test (PCT). All tests weigh monetized benefits against
costs. These monetized amounts are presented as NPV evaluated over the lifespan of the measure. The
benefits and costs differ for each test based on the perspective of the test. The definitions below are
taken from the California Standard Practice Manual.
n The TRC measures the net costs of a demand-side management program as a resource option
based on the total costs of the program, including both the participants' and the utility's costs.
n The UCT measures the net costs of a demand-side management program as a resource option
based on the costs incurred by the program administrator (including incentive costs) and
excluding any net costs incurred by the participant. The benefits are similar to the TRC benefits.
Costs are defined more narrowly.
n The PCT is the measure of the quantifiable benefits and costs to the customer due to
participation in a program. Since many customers do not base their decision to participate in a
program entirely on quantifiable variables, this test cannot be a complete measure of the
benefits and costs of a program to a customer.
n The RIM test measures what happens to customer bills or rates due to changes in utility
revenues and operating costs caused by the program. Rates will go down if the change in
revenues from the program is greater than the change in utility costs. Conversely, rates or bills
will go up if revenues collected after program implementation is less than the total costs

11 The UCT is also referred to as the Program Administrator Cost Test (PACT).

Evaluation Report 77

incurred by the utility in implementing the program. This test indicates the direction and
magnitude of the expected change in customer bills or rate levels.
A common misperception is that there is a single best perspective for evaluation of cost-effectiveness.
Each test is useful and accurate, but the results of each test are intended to answer a different set of
questions. The questions to be addressed by each cost test are shown in the table below.12
Table 7-2: Questions Addressed by the Various Cost Tests
Cost Test Questions Addressed
Participant Cost Test (PCT)
n Is it worth it to the customer to install energy efficiency?
n Is it likely that the customer wants to participate in a utility program that
promotes energy efficiency?
Ratepayer Impact Measure (RIM)
n What is the impact of the energy efficiency project on the utility’s
operating margin?
n Would the project require an increase in rates to reach the same
operating margin?
Utility Cost Test (UCT)
n Do total utility costs increase or decrease?
n What is the change in total customer bills required to keep the utility
whole?
Total Resource Cost Test (TRC)
n What is the regional benefit of the energy efficiency project (including
the net costs and benefits to the utility and its customers)?
n Are all of the benefits greater than all of the costs (regardless of who
pays the costs and who receives the benefits)?
n Is more or less money required by the region to pay for energy needs?

Overall, the results of all four cost-effectiveness tests provide a more comprehensive picture than the
use of any one test alone. The TRC cost test addresses whether energy efficiency is cost-effective
overall. The PCT, UCT, and RIM address whether the selection of measures and design of the program
are balanced from the perspective of the participants, utilities, and non-participants. The scope of the
benefit and cost components included in each test are summarized in the table below.13

12 http://www.epa.gov/cleanenergy/documents/suca/cost-effectiveness.pdf
13 Ibid.

Evaluation Report 78

Table 7-3: Benefits and Costs Included in Each Cost-Effectiveness Test
Test Benefits Costs
PCT (Benefits and costs from
the perspective of the
customer installing the
measure)
n Incentive payments
n Bill Savings
n Applicable tax credits or
incentives
n Incremental equipment
costs

n Incremental installation
costs
UCT (Perspective of utility,
government agency, or third
party implementing the
program
n Energy-related costs avoided by
the utility
n Capacity-related costs avoided by
the utility, including generation,
transmission, and distribution
n Program overhead costs

n Utility/program
administrator incentive
costs
TRC (Benefits and costs from
the perspective of all utility
customers in the utility service
territory)
n Energy-related costs avoided by
the utility
n Capacity-related costs avoided by
the utility, including generation,
transmission, and distribution
n Additional resource savings
n Monetized non-energy benefits
n Program overhead costs

n Program installation costs

n Incremental measure costs
RIM (Impact of efficiency
measure on non-participating
ratepayers overall)
n Energy-related costs avoided by
the utility

n Capacity-related costs avoided by
the utility, including generation,
transmission, and distribution
n Program overhead costs

n Lost revenue due to
reduced energy bills

n Utility/program
administrator installation
costs

7.2 Non-Energy Benefits
Non-energy Benefits (NEBs) were sourced from the RTF workbook in place at the time the savings goals
for the program was finalized. NEBs included wood fuel credits, increased comfort, and reductions in PM
2.5 emissions.
n Residential measures with NEBs included air source heat pumps, ductless heat pumps, windows,
and insulation measures.
n Low Income NEBs included the NEBs described for Residential as well as a dollar-for-dollar benefit
adder for health and safety spending.

Evaluation Report 79

7.3 Economic Inputs for Cost Effectiveness Analysis
The Evaluators used the economic inputs provided by Avista for the cost benefit analysis. Avista
provided the Evaluators with avoided costs on the following basis:
n Hourly avoided commodity costs
n Modifications for the Clean Premium
n Avoided capacity costs
n Avoided transmission
n 10% Conservation Adder
n Line losses
n Discount rate (after tax Weighted Average Cost of Capital)
The values were aggregated to provide a single benefit multiplier on a kWh basis for every hour of the
year (8,760). Savings by measure were then parsed out to the following load shapes provided by Avista:
n Residential Space Heating
n Residential Air Conditioning
n Residential Lighting
n Residential Refrigeration
n Residential Water Heating
n Residential Dishwasher
n Residential Washer/Dryer
n Residential Furnace Fan
n Residential Miscellaneous
The Evaluators in addition created a Residential Heat Pump load shape by weighting the relative
magnitude of cooling versus heating savings from a heat pump and assigning these to weight the
Residential Space Heating and Residential Air Conditioning load shapes.
7.4 Results
The tables below outline the results for each test, for both the programs and the portfolio as a whole.
Summations may differ by $1 due to rounding.
Table 7-4: Cost-Effectiveness Results by Sector
Sector TRC UCT RIM PCT
Residential 2.08 3.01 0.47 3.96
Low Income 0.61 0.50 0.27 N/A*
Total 1.81 2.39 0.45 N/A*
*Low Income is offered at no cost to participants; PCT is not calculable.

Evaluation Report 80

Table 7-5: Cost-Effectiveness Benefits by Sector
Program TRC Benefits UCT Benefits RIM Benefits PCT Benefits
Residential $5,579,452 $5,072,229 $5,072,229 $6,330,037
Low Income $366,774 $272,178 $272,178 $687,611
Total $5,946,226 $5,344,407 $5,344,407 $7,017,649

Table 7-6: Cost-Effectiveness Costs by Sector
Program TRC Costs UCT Costs RIM Costs PCT Costs
Residential $2,681,641 $1,687,155 $10,805,160 $1,597,316
Low Income $605,151 $546,723 $1,018,619 $454,279
Total $3,286,792 $2,233,878 $11,823,780 $2,051,595

Table 7-7: Cost-Effectiveness Net Benefits by Sector
Program TRC Net Benefits UCT Net Benefits RIM Net Benefits PCT Net Benefits
Residential $2,897,811 $3,385,074 ($5,732,931) $4,732,722
Low Income ($238,377) ($274,545) ($746,441) $233,332
Total $2,659,434 $3,110,529 ($6,479,373) $4,966,054

2020 Idaho Annual Conservation Report Appendices
APPENDIX D – 2020 IDAHO NATURAL GAS EVALUATION REPORT –
RESIDENTIAL AND LOW-INCOME

Evaluation, Measurement and Verification
(EM&V) of Avista Idaho Gas PY2020
Residential and Low-Income Energy Efficiency
Programs
Prepared for:

Avista Corporation

Delivered on:
June 7, 2021

Prepared by:

ADM Associates, Inc.
3239 Ramos Circle
Sacramento, CA 95827
916.363.8383

In Partnership with:
Cadeo Group
107 SE Washington St, Suite 450
Portland, OR 97214

Tables of Contents and Tables ii
Table of Contents
1. Executive Summary ............................................................................................................................. 6
1.1 Savings & Cost-Effectiveness Results ......................................................................................................... 6
1.2 Conclusions and Recommendations .......................................................................................................... 7
2. General Methodology ........................................................................................................................ 12
2.1 Glossary of Terminology .......................................................................................................................... 12
2.2 Summary of Approach ............................................................................................................................. 13
3. Residential Impact Evaluation Results ............................................................................................... 26
3.1 Simple Verification Results ....................................................................................................................... 26
3.2 Impacts of COVID-19 Pandemic ............................................................................................................... 28
3.3 Program-Level Impact Evaluation Results ................................................................................................ 29
3.4 Conclusions and Recommendations ........................................................................................................ 46
4. Low-Income Impact Evaluation Results ............................................................................................. 49
4.1 Program-Level Impact Evaluation Results ................................................................................................ 50
4.2 Conclusions and Recommendations ........................................................................................................ 54
5. Appendix A: Billing Analysis Results ................................................................................................... 56
5.1 Water Heat Program ................................................................................................................................ 56
5.2 HVAC Program ......................................................................................................................................... 60
5.3 Shell Program ........................................................................................................................................... 67
5.4 Fuel Efficiency Program ............................................................................................................................ 74
5.5 Low-Income Program ............................................................................................................................... 79
6. Appendix B: Summary of Survey Respondents .................................................................................. 82
7. Appendix C: Cost Benefit Analysis Results ......................................................................................... 85
7.1 Approach .................................................................................................................................................. 85
7.2 Non-Energy Benefits ................................................................................................................................ 87
7.3 Economic Inputs for Cost Effectiveness Analysis ..................................................................................... 88
7.4 Results ...................................................................................................................................................... 88

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List of Tables
Table 1-1: Residential Verified Impact Savings by Program ......................................................................... 6
Table 1-2: Low-Income Verified Impact Savings by Program ....................................................................... 6
Table 1-3: Cost-Effectiveness Summary ....................................................................................................... 7
Table 1-4: Impact Evaluation Activities by Program and Sector ................................................................... 7
Table 2-1: Document-based Verification Samples and Precision by Program ........................................... 17
Table 2-2: Survey-Based Verification Sample and Precision by Program ................................................... 17
Table 3-1: Residential Verified Impact Savings by Program ....................................................................... 26
Table 3-2: Residential Portfolio Cost-Effectiveness Summary ................................................................... 26
Table 3-3: Summary of Survey Response Rate ........................................................................................... 27
Table 3-4: Simple Verification Precision by Program ................................................................................. 27
Table 3-5: Water Heat Program ISRs by Measure ...................................................................................... 28
Table 3-6: HVAC Program ISRs by Measure ................................................................................................ 28
Table 3-7: Water Heat Program Measures ................................................................................................. 30
Table 3-8: Water Heat Program Verified Natural Gas Savings ................................................................... 30
Table 3-9: Water Heat Program Costs ........................................................................................................ 30
Table 3-10: Water Heat Verification Survey ISR Results ............................................................................ 31
Table 3-11: HVAC Program Measures ........................................................................................................ 32
Table 3-12: HVAC Program Verified Natural Gas Savings ........................................................................... 33
Table 3-13: HVAC Program Costs ............................................................................................................... 33
Table 3-14: HVAC Verification Survey ISR Results ...................................................................................... 34
Table 3-15: Measures Considered for Billing Analysis, HVAC Program ...................................................... 35
Table 3-16: Measure Savings, HVAC Program ............................................................................................ 36
Table 3-17: Customer Counts for Natural Gas Furnaces, HVAC Program .................................................. 36
Table 3-18: Measure Savings for Natural Gas Furnaces, HVAC Program ................................................... 37
Table 3-19: Shell Program Measures .......................................................................................................... 38
Table 3-20: Shell Program Verified Natural Gas Savings ............................................................................ 38
Table 3-21: Shell Program Costs ................................................................................................................. 39
Table 3-22: Measures Considered for Billing Analysis, HVAC Program ...................................................... 41
Table 3-23: Measure Savings, HVAC Program ............................................................................................ 41

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Table 3-24: Fuel Efficiency Program Measures .......................................................................................... 42
Table 3-25: Fuel Efficiency Program Verified Natural Gas Penalty ............................................................. 42
Table 3-26: ENERGY STAR® Homes Program Measures ............................................................................. 43
Table 3-27: ENERGY STAR® Homes Program Verified Natural Gas Savings ................................................ 43
Table 3-28: ENERGY STAR® Homes Program Costs .................................................................................... 43
Table 3-29: Simple Steps, Smart Savings Program Measures .................................................................... 45
Table 3-30: Simple Steps, Smart Savings Program Verified Natural Gas Savings ....................................... 45
Table 4-1: Low-Income Verified Impact Savings by Program ..................................................................... 49
Table 4-2: Low-Income Portfolio Cost-Effectiveness Summary ................................................................. 50
Table 4-3: Low-Income Program Measures ............................................................................................... 50
Table 4-4: Low-Income Program Verified Natural Gas Savings .................................................................. 51
Table 4-5: Low-Income Program Costs ....................................................................................................... 51
Table 4-6: Measures Considered for Billing Analysis, Low-Income Program ............................................. 53
Table 4-7: Measure Savings, Low-Income Program ................................................................................... 54
Table 5-1: Measures Considered for Billing Analysis, HVAC Program ........................................................ 56
Table 5-2: Cohort Restrictions, HVAC Program .......................................................................................... 56
Table 5-3: TMY Weather, HVAC Program ................................................................................................... 59
Table 5-4: Measure Savings for All Regression Models, HVAC Program .................................................... 59
Table 5-5: Pre-period Usage T-test for Tankless Gas Water Heater, Water Heater Program .................... 59
Table 5-6: Measures Considered for Billing Analysis, HVAC Program ........................................................ 60
Table 5-7: Cohort Restrictions, HVAC Program .......................................................................................... 61
Table 5-8: Pre-period Usage T-test for Smart Thermostat DIY with Natural Gas Heat, HVAC Program ..... 64
Table 5-9: Pre-period Usage T-test for Smart Thermostat Paid Install with Natural gas Heat, HVAC Program
........................................................................................................................................................... 64
Table 5-10: TMY Weather, HVAC Program ................................................................................................. 65
Table 5-11: Measure Savings, HVAC Program ............................................................................................ 65
Table 5-12: Measures Considered for Billing Analysis, Shell Program ....................................................... 67
Table 5-13: Cohort Restrictions, Shell Program ......................................................................................... 67
Table 5-14: Pre-period Usage T-test for Attic Insulation, Shell Program .................................................... 71
Table 5-15: Pre-period Usage T-test for Window Replacement, Shell Program ........................................ 71
Table 5-16: TMY Weather, Shell Program .................................................................................................. 72

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Table 5-17: Measure Savings for All Regression Models, Shell Program ................................................... 72
Table 5-18: Measure Savings, Shell Program ............................................................................................. 73
Table 5-19: Measures Considered for Billing Analysis, Fuel Efficiency Program ........................................ 74
Table 5-20: Cohort Restrictions, Fuel Efficiency Program .......................................................................... 75
Table 5-21: Pre-period Usage T-test for Electric to Gas Furnace, Fuel Conversion Program ..................... 77
Table 5-22: TMY Weather, Fuel Efficiency Program ................................................................................... 77
Table 5-23: Measure Savings, Fuel Efficiency Program .............................................................................. 78
Table 5-24: Measure Savings for All Regression Models, Fuel Efficiency Program .................................... 79
Table 5-25: Cohort Restrictions, Low-Income Program ............................................................................. 79
Table 5-26: TMY Weather, Low-Income Program ...................................................................................... 81
Table 5-27: Measure Savings for All Regression Models, Low-Income Program ....................................... 81
Table 5-28: Pre-period Usage T-test for Natural Gas Measures, Low-Income Program ............................ 82
Table 6-1: Type and Number of Measures Received by Respondents ....................................................... 83
Table 6-2: Survey Respondent Home Characteristics ................................................................................ 84
Table 7-1: Cost-effectiveness Results ......................................................................................................... 85
Table 7-2: Questions Addressed by the Various Cost Tests ....................................................................... 86
Table 7-3: Benefits and Costs Included in Each Cost-Effectiveness Test .................................................... 87
Table 7-4: Cost-Effectiveness Results by Sector ......................................................................................... 88
Table 7-5: Cost-Effectiveness Benefits by Sector ....................................................................................... 89
Table 7-6: Cost-Effectiveness Costs by Sector ............................................................................................ 89
Table 7-7: Cost-Effectiveness Net Benefits by Sector ................................................................................ 89

Work Plan 6
1. Executive Summary
This report is a summary of the Residential and Low-Income Gas Evaluation, Measurement, and
Verification (EM&V) effort of the 2020 program year (PY2020) portfolio of programs for Avista
Corporation (Avista) in the Idaho service territory. The evaluation was administered by ADM
Associates, Inc. and Cadeo Group, LLC (herein referred to as the “Evaluators”).
1.1 Savings & Cost-Effectiveness Results
The Evaluators conducted an impact evaluation for Avista’s Residential and Low-Income programs for
PY2020. The Residential portfolio savings amounted to 317,549.63 Therms with a 120.66% realization
rate. The Low-Income portfolio savings amounted to 5,494.69 Therms with a 109.69% realization rate.
The Evaluators summarize the Residential portfolio verified savings in Table 1-1and the Low-Income
portfolio verified savings in Table 1-2 below.
The Residential portfolio reflects a TRC value of 1.11 and a UCT value of 2.46. The Low-Income portfolio
reflects a TRC value of 0.27 and a UCT value of 0.10, leading to a total Residential and Low-Income TRC
of 0.89 and a UCT of 1.66. Table 1-3 summarizes the evaluated TRC and UCT values with each the
Residential and Low-Income portfolios.
Table 1-1: Residential Verified Impact Savings by Program
Program
Expected
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
Total Costs
Water Heat 38,131.80 37,975.80 99.59% $200,782.21
HVAC 204,211.46 266,938.58 130.72% $1,063,438.94
Shell 20,121.75 11,999.75 59.64% $160,163.25
Fuel Efficiency1 0.00 0.00 -
ENERGY STAR Homes 402.00 401.94 99.99% $2,018.87
Simple Steps, Smart Savings2 299.69 233.56 77.93% $0.03
Total Res 263,166.70 317,549.63 120.66% $1,426,403.31

Table 1-2: Low-Income Verified Impact Savings by Program
Program
Expected
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
Total Costs
Low-Income3 5,009.32 5,494.69 109.69% $662,513.76
Total Low-Income 5,009.32 5,494.69 109.69% $662,513.76

1 The Fuel Efficiency Program displayed a verified Therms penalty of 32,378.27 Therms due to fuel conversion measures. For the
purposes of this report, this penalty is not included in the overall metrics of natural gas-saving energy efficiency measures.
2 The Simple Steps, Smart Savings Program displayed a verified Therms penalty of 22,604.26 Therms due to lighting measures.
3 The Low-Income Program displayed a verified Therms penalty of 3,759.50 Therms due to fuel conversion measures.

Evaluation Report 7
Table 1-3: Cost-Effectiveness Summary
Sector TRC UCT
Benefits Costs B/C Ratio Benefits Costs B/C Ratio
Residential $3,852,633 $3,466,442 1.11 $3,502,394 $1,426,403 2.46
Low Income $168,428 $638,498 0.26 $68,285 $662,514 0.10
Total $4,021,822 $4,105,041 0.98 $3,570,679 $2,089,019 1.71

Table 1-4 summarizes the gas programs offered to residential and low-income customers in the Idaho
Avista service territory in PY2020 as well as the Evaluators’ evaluation tasks and impact methodology for
each program.
Table 1-4: Impact Evaluation Activities by Program and Sector
Sector Program Database
Review
Survey
Verification Impact Methodology
Residential Water Heat ü ü Avista TRM
Residential HVAC ü ü Avista TRM/IPMVP Option A
Residential Shell ü Avista TRM/Billing analysis with
comparison group
Residential Fuel Efficiency ü ü Avista TRM/Billing analysis with
comparison group
Residential ENERGY STAR®
Homes ü Avista TRM
Residential Simple Steps, Smart
Savings ü RTF UES
Low-Income Low-Income ü Avista TRM
1.2 Conclusions and Recommendations
The following section details the Evaluators’ conclusions and recommendations for each the Residential
Portfolio and Low-Income Portfolio program evaluations.
1.2.1 Conclusions
The following section details the Evaluator’s findings resulting from the program evaluations for each
the Residential Portfolio and Low-Income Portfolio.
1.2.1.1 Residential Programs
The Evaluators provide the following conclusions regarding Avista’s Residential gas programs:
n The Evaluators found the Residential portfolio to demonstrate a total of 317,549.63 Therms with
a realization rate of 120.66%. The Evaluators also conducted a cost-benefit analysis in order to
estimate the Residential portfolio’s cost-effectiveness. The resulting TRC value for this sector is
1.11 while the UCT value is 2.46. Further details on cost-effectiveness methodology can be
found in Appendix C.
n The Residential Portfolio impact evaluation resulted in a realization rate of 120.66% due to slight
differences between the applied Avista TRM values and the most active Avista TRM value for

Evaluation Report 8
each measure in addition to the difference in savings values between the results from billing
analyses and the Avista TRM.
n The HVAC Program, which contributes 78% of the expected savings, resulted in a realization rate
of 130.72% whereas each of the other programs resulted in a combined 74% realization rate.
The Shell Program contributed to a 35% increase in the overall residential sector, which
displayed a realization rate of 120.66%.
n The Evaluators conducted verification surveys via web survey and phone calls to collect
information from customers who participated in the Water Heat and HVAC Programs. A total of
261 unique customers were surveyed between February and March 2021. The Evaluators
collected information including the functionality of the efficient equipment, the functionality of
the replaced equipment, and information on how the COVID19 stay-at-home orders have
affected the household energy usage. The Evaluators calculated in-service rates for the
measures within these two programs in order to apply findings to the verified savings results for
each program.
n The realization rate for the natural gas savings in the Water Heat Program was 99.59%. This
program deviated from 100% realization because two rebates were duplicates. Therefore, the
Evaluators removed these rebates from savings, lowering the realization rate for the program.
n The Evaluators explored a billing analysis for the natural gas water heater measures within the
Water Heat Program. However, the G 50 Gallon Natural gas Water Heater lacked sufficient
participation to estimate savings and the G Tankless Gas Water Heater measure resulted in
savings that were not statistically significant. Therefore, the Evaluators elected to use Avista
TRM values to estimate verified savings. The Evaluators will explore further billing analyses for
these measures during the next program year.
n The HVAC Program in total displays a realization rate of 130.72% with 266,938.58 Therms
verified natural gas savings in the Idaho service territory. The realization rate for the natural gas
savings in the HVAC Program deviate from 100% due to the differences between the applied
Avista TRM prescriptive savings value and the updated Avista TRM or updated RTF UES value.
The smart thermostat measures’ realization rates are low because an outdated Avista TRM
value was applied to the project data to calculate expected savings. The furnace measure has a
high realization rate because the billing analysis resulted in a savings value that was 137% of the
value previously used in the Avista TRM.
n The Evaluators attempted to estimate smart thermostat measure savings values for the HVAC
Program. However, because the results from the billing analyses for smart thermostats were
contradicting and/or inconclusive, the Evaluators elected to utilize Avista TRM values to
estimate verified savings for these measures. The findings from the PY2020 billing analyses for
these measures may have been impacted by the COVID19 pandemic. The Evaluators will explore
additional billing analyses for these measures during program year 2021.
n The Shell Program displayed verified savings of 11,999.75 Therms with a realization rate of
59.64% against the expected savings for the program. The realization rate for the natural gas
savings in the Shell Program deviate from 100% due to the differences between the billing
analysis results and the Avista TRM prescriptive savings values as well as outdated Avista TRM
values being applied in the expected savings calculations.

Evaluation Report 9
n For the Shell Program, the Evaluators conducted a billing analysis for two measures that had
sufficient participation. The Evaluators found the G Attic Insulation With Natural Gas Heat
measure to display a statistically significant verified savings value of 55.56 Therms per year. In
addition, the Evaluators found statistically significant savings of 36.78 Therms per year for the G
Window Replacement with Natural Gas Heat measure. The Evaluators used these savings
estimates towards calculating verified savings for the program.
n Final verified savings for the Simple Steps, Smart Savings Program were estimated using the RTF
UES values associated with each measure. Simple Steps, Smart Savings Program displayed
77.93% realization with 233.56 Therms saved. The discrepancy between expected and verified
Therms for the measures in this program are due to the differences between the BPA values
assigned and the appropriately applied RTF values the Evaluators assigned.
1.2.1.2 Low-Income Programs
The Evaluators provide the following conclusions regarding Avista’s Low-Income natural gas programs:
n The Evaluators found the Low-Income portfolio to demonstrate a total of 5,494.69 Therms with
a realization rate of 109.69%. The Low-Income Portfolio impact evaluation resulted in verified
savings that exceeded expected savings.
n The Evaluators conducted a cost-benefit analysis in order to estimate the Low-Income
portfolio’s cost-effectiveness. The resulting TRC value for this sector is 0.26 while the UCT value
is 0.10. These values are expected, as the Low-Income portfolio is not expected to meet cost-
effectiveness but are implemented in order to provide energy efficiency benefits to low-income
customers. Further details on cost-effectiveness methodology can be found in Appendix C.
n The Evaluators attempted to estimate measure-level Low-Income Program energy savings
through billing analysis regression with a counterfactual group selected via propensity score
matching. The Evaluators attempted to isolate each unique measure. However, participation for
the Low-Income program resulted in a small number of customers with isolated measures and
therefore the Evaluators conducted a whole-home billing analysis for all the natural gas
measures combined in the Low-Income in order to estimate savings for the average household
participating in the program, across all measures. The Evaluators found a realization rate of
139% for all natural gas measures in the program, which supported the realization rate of 110%
from the desk review.
n The Evaluators note that the majority of deviations from 100% realization rate is due to the
change in square footage or number of units verified in the project documentation.
1.2.2 Recommendations
The following section details the Evaluator’s recommendations resulting from the program evaluations
for each the Residential Portfolio and Low-Income Portfolio.
1.2.2.1 Residential Programs
The Evaluators offer the following recommendations regarding Avista’s Residential natural gas
programs:

Evaluation Report 10
n The Evaluators recommend Avista work to improve methods for collecting mail-in rebate
application information to reconcile the CC&B database. The values found in the project
documentation should accurately reflect the values represented in the CC&B database.
n A number of rebates were not accompanied with AHRI certification. In order to acquire accurate
equipment efficiencies and tank sizes, AHRI certifications are recommended to be required and
submitted with the rebate application, with an invoice that matches the model number found in
the AHRI certification.
n The Evaluators note that some of the model numbers for the rebated equipment were
incomplete and the Evaluators were unable to identify a single AHRI certification that matched
the description in the rebate application. In order to acquire accurate equipment efficiencies,
AHRI certifications are recommended to be required and submitted with the rebate application,
with an invoice that matches the manufacturer and model number found in the AHRI
certification.
n The Evaluators cross-referenced the billing data to verify if customers demonstrated the
required heating season electricity usage of 8,000 kWh and natural gas usage of less than 340
Therms, as defined in the program requirements. The Evaluators found many customers used
less than 8,000 kWh or 340 Therms annually. In addition, some customers had insufficient pre-
period data to determine annual usage. The Evaluators recommend Avista verify if customers
meet the requirements prior to completing the rebate.
n For the Shell Program, the Evaluators found rebates in which the R-values did not align with
TRM or RTF values (R38 and R64). The Evaluators recommend collecting information in a
standardized manner.
n The Evaluators recommend collecting information on single/double pane windows of the
baseline windows and class of the efficient windows in order to correctly assign RTF UES values.
n The Evaluators note several instances in which the web-based rebate data indicates the
household has electric space heating, but all other sources (project data and document
verification) indicate natural gas space heating, and vice versa. The Evaluators recommend
updating data collection standards in order for all sources of information to reflect the same
values as the project documentation.
n The natural gas furnace measure in the HVAC has a high realization rate because the billing
analysis resulted in a savings value that was 137.45% of the value previously used in the Avista
TRM. The Evaluators recommend adjusting the Avista TRM to reflect the observed savings
values from all billing analyses from this impact evaluation.
n The Evaluators recommend adjusting expected savings calculations in the Simple Steps, Smart
Savings Program to include Therms penalty for the measures offered, in order to more
accurately reflect the approved RTF savings values.
1.2.2.2 Low-Income Programs
The Evaluators offer the following recommendations regarding Avista’s Low-Income natural gas
programs:
n The Evaluators note that the majority of deviations from 100% realization rate is due to the
change in square footage or number of units verified in the project documentation. The
Evaluators reviewed the project documentation provided by Avista and identified conflicting

Evaluation Report 11
square footage or number of units between the aggregated project data from the CC&B and the
rebate project documentation provided in the data request for document verification. In
addition, the unit type, in terms of square footage or number of measures (windows, doors, etc)
was not documented consistently and therefore savings values were applied inaccurately. The
Evaluators recommend updating CC&B documentation standards to more accurately reflect
values present on the rebate applications.
n The Evaluators found discrepancies between the 20% annual consumption cap and the claimed
energy savings. The Evaluators recommend checking each project against billing data prior to
reporting energy savings for the project, as well as documenting each household’s usage as well
as the date range used to calculate the household consumption estimate.

Work Plan 12
2. General Methodology
The Evaluators performed an impact evaluation on each of the programs summarized in Table 1-4. The
Evaluators used the following approaches to calculate energy impact defined by the International
Performance Measurement and Verification Protocols (IPMVP)4 and the Uniform Methods Project
(UMP)5:
n Simple verification (web-based surveys supplemented with phone surveys)
n Document verification (review project documentation)
n Deemed savings (RTF UES and Avista TRM values)
n Whole facility billing analysis (IPMVP Option C)
The Evaluators completed the above impact tasks for each the electric impacts and the natural gas
impacts for projects completed in the Idaho Avista service territory.
The M&V methodologies are program-specific and determined by previous Avista evaluation
methodologies as well as the relative contribution of a given program to the overall energy efficiency
impacts. Besides drawing on IPMVP, the Evaluators also reviewed relevant information on
infrastructure, framework, and guidelines set out for EM&V work in several guidebook documents that
have been published over the past several years. These include the following:
n Northwest Regional Technical Forum (RTF)6
n National Renewable Energy Laboratory (NREL), United States Department of Energy (DOE) The
Uniform Methods Project (UMP): Methods for Determining Energy Efficiency Savings for Specific
Measures, April 20137
n International Performance Measurement and Verification Protocol (IPMVP) maintained by the
Efficiency Valuation Organization (EVO) with sponsorship by the U.S. Department of Energy (DOE)8
The Evaluators kept data collection instruments, calculation spreadsheets, and monitored/survey data
available for Avista records.
2.1 Glossary of Terminology
As a first step to detailing the evaluation methodologies, the Evaluators have provided a glossary of
terms to follow:

4 https://www.nrel.gov/docs/fy02osti/31505.pdf
5 https://www.nrel.gov/docs/fy18osti/70472.pdf
6 https://rtf.nwcouncil.org/measures
7 Notably, The Uniform Methods Project (UMP) includes the following chapters authored by ADM. Chapter 9 (Metering Cross-
Cutting Protocols) was authored by Dan Mort and Chapter 15 (Commercial New Construction Protocol) was Authored by Steven
Keates.
8 Core Concepts: International Measurement and Verification Protocol. EVO 100000 – 1:2016, October 2016.

Evaluation Report 13
n Deemed Savings – An estimate of an energy savings outcome (gross savings) for a single unit of
an installed energy efficiency measure. This estimate (a) has been developed from data sources
and analytical methods that are widely accepted for the measure and purpose and (b) are
applicable to the situation being evaluated.
n Expected Savings – Calculated savings used for program and portfolio planning purposes.
n Adjusted Savings – Savings estimates after database review and document verification has been
completed using deemed unit-level savings provided in the Avista TRM. It adjusts for such factors
as data errors and installation rates.
n Verified Savings – Savings estimates after the updated unit-level savings values have been
updated and energy impact evaluation has been completed, integrating results from billing
analyses and appropriate RTF UES and Avista TRM values.
n Gross Savings – The change in energy consumption directly resulting from program-related
actions taken by participants in an efficiency program, regardless of why they participated.
n Free Rider – A program participant who would have implemented the program measure or
practice in absence of the program.
n Net-To-Gross – 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.
n Net Savings – The change in energy consumption directly resulting from program-related actions
taken by participants in an efficiency program, with adjustments to remove savings due to free
ridership.
n Non-Energy Benefits – Quantifiable impacts produced by program measures outside of energy
savings (comfort, health and safety, reduced alternative fuel, etc).
n Non-Energy Impacts – Quantifiable impacts in energy efficiency beyond the energy savings gained
from installing energy efficient measures (reduced cost for operation and maintenance of
equipment, reduced environmental and safety costs, etc).
2.2 Summary of Approach
This section presents our general cross-cutting approach to accomplishing the impact evaluation of
Avista’s Residential and Low-Income programs listed in Table 1-4. The Evaluators start by presenting our
general evaluation approach. This chapter is organized by general task due to several overlap across
programs. Section 3.3 describes the Evaluators’ program-specific residential impact evaluation methods
and results in further detail and Section 4.1 describes the Evaluator’s program-specific low-income
impact evaluation methods and results.
The Evaluators outline the approach to verifying, measuring, and reporting the residential portfolio
impacts as well as cost-effectiveness and summarizing potential program and portfolio improvements.
The primary objective of the impact evaluation is to determine ex-post verified net energy savings. On-
site verification and equipment monitoring was not conducted during this impact evaluation due to stay-
at-home orders due to the COVID19 pandemic.
Our general approach for this evaluation considers the cyclical feedback loop among program design,
implementation, and impact evaluation. Our activities during the evaluation estimate and verify annual
energy savings and identify whether a program is meeting its goals. These activities are aimed to provide

Evaluation Report 14
guidance for continuous program improvement and increased cost effectiveness for the 2020 and 2021
program years.
The Evaluators employed the following approach to complete impact evaluation activities for the
programs. The Evaluators define two major approaches to determining net savings for Avista’s
programs:
n A Deemed Savings approach involves using stipulated savings for energy conservation measures
for which savings values are well-known and documented. These prescriptive savings may also
include an adjustment for certain measures, such as lighting measures in which site operating
hours may differ from RTF values.
n A Billing Analysis approach involves estimating energy savings by applying a linear regression to
measured participant energy consumption utility meter billing data. Billing analyses included
billing data from nonparticipant customers. This approach does not require on-site data collection
for model calibration. This approach aligns with the IPMVP Option C.
The Evaluators accomplished the following quantitative goals as part of the impact evaluation:
n Verify savings with 10% precision at the 90% confidence level;
n Where appropriate, apply the RTF to verify measure impacts; and
n Where available data exists, conduct billing analysis with a suitable comparison group to estimate
measure savings.
For each program, the Evaluators calculated adjusted savings for each measure based on the Avista TRM
and results from the database review. The Evaluators calculated verified savings for each measure based
on the RTF UES, Avista TRM, or billing analysis in combination with the results from document review.
For the HVAC, Water Heat, and Fuel Efficiency programs, the Evaluators also applied in-service rates
(ISRs) from verification surveys.

The Evaluators assigned methodological rigor level for each measure and program based on its
contribution to the portfolio savings and availability of data.
The Evaluators analyzed billing data for all natural gas measure participants in the HVAC and Low-
Income programs. The Evaluators applied billing analysis results to determine evaluated savings only for
measures where savings could be isolated (that is, where a sufficient number of participants could be
identified who installed only that measure). Program-level realization rates for the HVAC, Water Heat,
and Fuel Efficiency programs incorporate billing analysis results for some measures.
Reported
Savings
Database
Review
Adjusted
savings
Document
Review
Evaluated
Savings

Evaluation Report 15
2.2.1 Database Review
At the outset of the evaluation, the Evaluators reviewed the databases to ensure that each program
tracking database conforms to industry standards and adequately tracks key data required for
evaluation.
Measure-level net savings were evaluated primarily by reviewing measure algorithms and values in the
tracking system to assure that they are appropriately applied using the Avista TRM. The Evaluators then
aggregated and cross-check program and measure totals.
The Evaluators reviewed program application documents for a sample of incented measures to verify
the tracking data accurately represents the program documents. The Evaluators ensured the home
installed measures that meet or exceed program efficiency standards.
2.2.2 Verification Methodology
The Evaluators verified a sample of participating households for detailed review of the installed measure
documentation and development of verified savings. The Evaluators verified tracking data by reviewing
invoices and surveying a sample of participant customer households. The Evaluators also conducted a
verification survey for program participants.
The Evaluators used the following equations to estimate sample size requirements for each program and
fuel type. Required sample sizes were estimated as follows:
Equation 2-1 Sample Size for Infinite Sample Size
𝑛= $𝑍× 𝐶𝑉
𝑑*
!

Equation 2-2 Sample Size for Finite Population Size
𝑛"= 𝑛
1 +-𝑛𝑁/
Where,
n n = Sample size
n 𝑍 = Z-value for a two-tailed distribution at the assigned confidence level.
n 𝐶𝑉 = Coefficient of variation
n 𝑑 = Precision level
n 𝑁 = Population
For a sample that provides 90/10 precision, Z = 1.645 (the critical value for 90% confidence) and d = 0.10
(or 10% precision). The remaining parameter is CV, or the expected coefficient of variation of measures
for which the claimed savings may be accepted. A CV of .5 was assumed for residential programs due to

Evaluation Report 16
the homogeneity of participation9, which yields a sample size of 68 for an infinite population. Sample
sizes were adjusted for smaller populations via the method detailed in Equation 2-2.
The following sections describe the Evaluator’s methodology for conducting document-based
verification and survey-based verification.
2.2.2.1 Document-Based Verification
The Evaluators requested rebate documentation for a subset of participating customers. These
documents included invoices, rebate applications, pictures, and AHRI certifications for the following
programs:
n Water Heat Program
n HVAC Program
n Shell Program
n Fuel Efficiency Program
n ENERGY STAR® Homes Program
n Simple Steps, Smart Savings Program
n Low-Income Program
This sample of documents was used to cross-verify tracking data inputs. In the case the Evaluators found
any deviations between the tracking data and application values, the Evaluators reported and
summarized those differences in the Database Review sections presented for each program in Section
3.3 and Section 4.1.
The Evaluators developed a sampling plan that achieves a sampling precision of ±10% at 90% statistical
confidence – or “90/10 precision” – to estimate the percentage of projects for which the claimed savings
are verified or require some adjustment.
The Evaluators developed the following samples for each program’s document review using Equation
2-1 and Equation 2-2. The Evaluators ensured representation in each state and fuel type for each
measure.

9 Assumption based off California Evaluation Framework:
https://www.cpuc.ca.gov/uploadedFiles/CPUC_Public_Website/Content/Utilities_and_Industries/Energy/Energy_Programs/De
mand_Side_Management/EE_and_Energy_Savings_Assist/CAEvaluationFramework.pdf

Evaluation Report 17
Table 2-1: Document-based Verification Samples and Precision by Program
Sector Program Gas
Population
Sample
(With Finite
Population
Adjustment)*
Precision at
90% CI
Residential Water Heat 957 65 ±9.85%
Residential HVAC 7,401 69 ±9.86%
Residential Shell 1,337 68 ±9.72%
Residential Fuel Efficiency N/A N/A N/A
Residential ENERGY STAR® Homes 6 6 ±0.00%
Residential Simple Steps, Smart Savings N/A N/A N/A
Low-Income Low-Income 550 66 ±9.50%
*Assumes sample size of 68 for an infinite population, based on CV (coefficient of variation) = 0.5, d (precision) = 10%, Z (critical
value for 90% confidence) = 1.645.
The table above represents the number of rebates in both Washington and Idaho territories. The
Evaluators ensured representation of state and fuel type in the sampled rebates for document
verification.
2.2.2.2 Survey-Based Verification
The Evaluators conducted survey-based verification for the Water Heat Program and HVAC Program.
The primary purpose of conducting a verification survey is to confirm that the measure was installed and
is still currently operational and whether the measure was early retirement or replace-on-burnout.
The Evaluators summarize the final sample sizes shown in Table 2-2 for the Water Heat and HVAC for
the Idaho Gas Avista projects. The Evaluators developed a sampling plan that achieved a sampling
precision of ±4.24% at 90% statistical confidence for ISRs estimates at the measure-level during web-
based survey verification.
Table 2-2: Survey-Based Verification Sample and Precision by Program
Sector Program Population Respondents Precision
at 90% CI
Residential Water Heat 957 115 ±7.20%
Residential HVAC 7,401 246 ±5.16%
Residential Fuel Efficiency N/A N/A N/A
Total 8,358 361 ±4.24%

The Evaluators implemented a web-based survey to complete the verification surveys. The Evaluators
supplemented with phone interviews to reach the 90/10 precision goal. The findings from these
activities served to estimate ISRs for each measure surveyed. These ISRs were applied to verification
sample desk review rebates towards verified savings, which were then applied to the population of
rebates. The measure-level ISRs resulting from the survey-based verification are summarized in Section
3.1.

Evaluation Report 18
2.2.3 Impact Evaluation Methodology
The Evaluators employed the following approach to complete impact evaluation activities for the
programs. The Evaluators define two major approaches to determining net savings for Avista’s
programs:
n Deemed Savings
n Billing Analysis (IPMVP Option C)
In the following sections, the Evaluators summarize the general guidelines and activities followed to
conduct each of the above analyses.
2.2.3.1 Deemed Savings
This section summarizes the deemed savings analysis method the Evaluators employed for the
evaluation of a subset of measures for each program. The Evaluators completed the validation for
specific measures across each program using the RTF unit energy savings (UES) values, where available.
The Evaluators ensured the proper measure unit savings were recorded and used in the calculation of
Avista’s ex-ante measure savings. The Evaluators requested and used the technical reference manual
Avista employed during calculation of ex-ante measure savings (Avista TRM). The Evaluators
documented any cases where recommend values differed from the specific unit energy savings
workbooks used by Avista.
In cases where the RTF has existing unit energy savings (UES) applicable to Avista’s measures, the
Evaluators verified the quantity and quality of installations and apply the RTF’s UES to determine
verified savings.
2.2.3.2 Billing Analysis
This section describes the billing analysis methodology employed by the Evaluators as part of the impact
evaluation and measurement of energy savings for measures with sufficient participation. The Evaluators
performed billing analyses with a matched control group and utilized a quasi-experimental method of
producing a post-hoc control group. In program designs where treatment and control customers are not
randomly selected at the outset, such as for downstream rebate programs, quasi-experimental designs
are required.
For the purposes of this analysis, a household is considered a treatment household if it has received a
program incentive. Additionally, a household is considered a control household if the household has not
received a program incentive. To isolate measure impacts, treatment households are eligible to be
included in the billing analysis if they installed only one measure during the 2019 and 2020 program
years. Isolation of individual measures are necessary to provide valid measure-level savings. Households
that installed more than one measure may display interactive energy savings effects across multiple
measures that are not feasibly identifiable. Therefore, instances where households installed isolated
measures are used in the billing analyses. In addition, the pre-period identifies the period prior to
measure installation while the post-period refers to the period following measure installation.
The Evaluators utilized propensity score matching (PSM) to match nonparticipants to similar participants
using pre-period billing data. PSM allows the evaluators to find the most similar household based on the
customers’ billed consumption trends in the pre-period and verified with statistical difference testing.

Evaluation Report 19
After matching based on these variables, the billing data for treatment and control groups are
compared, as detailed in IPMVP Option C. The Evaluators fit regression models to estimate weather-
dependent daily consumption differences between participating customer and nonparticipating
customer households.
Cohort Creation
The PSM approach estimates a propensity score for treatment and control customers using a logistic
regression model. A propensity score is a metric that summarizes several dimensions of household
characteristics into a single metric that can be used to group similar households. The Evaluators created
a post-hoc control group by compiling billing data from a subset of nonparticipants in the Avista territory
to compare against treatment households using quasi-experimental methods. This allowed the
Evaluators to select from a large group of similar households that have not installed an incented
measure. With this information, the Evaluators created statistically valid matched control groups for
each measure via seasonal pre-period usage. The Evaluators matched customers in the control group to
customers in the treatment group based on nearest seasonal pre-period usage (e.g., summer, spring,
fall, and winter) and exact 3-digit zip code matching (the first three digits of the five-digit zip code). After
matching, the Evaluators conducted a t-test for each month in the pre-period to help determine the
success of PSM.
While it is not possible to guarantee the creation of a sufficiently matched control group, this method is
preferred because it is likely to have more meaningful results than a treatment-only analysis. Some
examples of outside variables that a control group can sufficiently control for are changes in economies
and markets, large-scale social changes, or impacts from weather-related anomalies such as flooding or
hurricanes. This is particularly relevant in 2020 due to COVID-19 related lockdowns and restrictions.
After PSM, the Evaluators ran the following regression models for each measure:
n Fixed effect Difference-in-Difference (D-n-D) regression model (recommended in UMP
protocols)10
n Random effects post-program regression model (PPR) (recommended in UMP protocols)
n Gross billing analysis (treatment only)
The second model listed above (PPR) was selected because it had the best fit for the data, identified
using the adjusted R-squared. Further details on regression model specifications can be found below.
Data Collected
The following lists the data collected for the billing analysis:
1. Monthly billing data for program participants (treatment customers)
2. Monthly billing data for a group of non-program participants (control customers)
3. Program tracking data, including customer identifiers, address, and date of measure installation
4. National Oceanic and Atmospheric Administration (NOAA) weather data between January 1, 2018
and December 31, 2020)

10 National Renewable Energy Laboratory (NREL) Uniform Methods Project (UMP) Chapter 17 Section 4.4.7.

Evaluation Report 20
5. Typical Meteorological Year (TMY3) data
Billing and weather data were obtained for program years 2019 and 2020 and for one year prior to
measure install dates (2018).
Weather data was obtained from the nearest weather station with complete data during the analysis
years for each customer by mapping the weather station location with the customer zip code.
TMY weather stations were assigned to NOAA weather stations by geocoding the minimum distance
between each set of latitude and longitude points. This data is used for extrapolating savings to long-
run, 30-year average weather.
Data Preparation
The following steps were taken to prepare the billing data:
1. Gathered billing data for homes that participated in the program.
2. Excluded participant homes that also participated in the other programs, if either program
disqualifies the combination of any other rebate or participation.
3. Gathered billing data for similar customers that did not participate in the program in evaluation.
4. Excluded bills missing address information (0.1% of bills).
5. Removed bills missing fuel type/Unit of Measure (UOM) (0.1% of bills).
6. Removed bills missing usage, billing start date, or billing end date (0.17% of bills).
7. Remove bills with outlier durations (<9 days or >60 days).
8. Excluded bills with consumption indicated to be outliers.
9. Calendarized bills (recalculates bills, usage, and total billed such that bills begin and end at the
start and end of each month).
10. Obtained weather data from nearest NOAA weather station using 5-digit zip code per household.
11. Computed Heating Degree Days (HDD) and Cooling Degree Days (CDD) for a range of setpoints.
The Evaluators assigned a setpoint of 65°F for both HDD and CDD. The Evaluators tested and
selected the optimal temperature base for HDDs and CDDs based on model R-squared values.
12. Selected treatment customers with only one type of measure installation during the analysis years
and combined customer min/max install dates with billing data (to define pre- and post-periods).
13. Restricted to treatment customers with install dates in specified range (typically January 1, 2019
through June 30, 2020) to allow for sufficient post-period billing data.
14. Restricted to control customers with usage less than or equal to two times the maximum observed
treatment group usage. This has the effect of removing control customers with incomparable
usage relative to the treatment group.
15. Removed customers with incomplete post-period bills (<4 months).
16. Removed customers with incomplete pre-period bills.

Evaluation Report 21
17. Restricted control customers to those with usage that was comparable with the treatment group
usage.
18. Created a matched control group using PSM and matching on pre-period seasonal usage and zip
code.
Regression Models
The Evaluators ran the following models for matched treatment and control customers for each
measure with sufficient participation. For net savings, the Evaluators selected either Model 1 or Model
2. The model with the best fit (highest adjusted R-squared) was selected. The Evaluators utilized Model
3 to estimate gross energy savings.
Model 1: Fixed Effects Difference-in-Difference Regression Model
The following equation displays the first model specification to estimate the average daily savings due to
the measure.
Equation 2-3: Fixed Effects Difference-in-Difference (D-n-D) Model Specification
𝐴𝐷𝐶#$=𝛼"+𝛽%(𝑃𝑜𝑠𝑡)#$+𝛽!(𝑃𝑜𝑠𝑡× 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡)#$+𝛽&(𝐻𝐷𝐷)#$+𝛽'(𝐶𝐷𝐷)#$+𝛽((𝑃𝑜𝑠𝑡× 𝐻𝐷𝐷)#$+𝛽)(𝑃𝑜𝑠𝑡× 𝐶𝐷𝐷)#$+𝛽*(𝑃𝑜𝑠𝑡× 𝐻𝐷𝐷× 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡)#$
+𝛽+(𝑃𝑜𝑠𝑡× 𝐶𝐷𝐷× 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡)#$+𝛽,(𝑀𝑜𝑛𝑡ℎ)$+𝛽%"(𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦)#+𝜀#$
Where,
n i = the ith household
n t = the first, second, third, etc. month of the post-treatment period
n 𝐴𝐷𝐶#$ = Average daily usage reading t for household i during the post-treatment period
n 𝑃𝑜𝑠𝑡#$ = A dummy variable indicating pre- or post-period designation during period t
at home i
n 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡# = A dummy variable indicating treatment status of home i
n 𝐻𝐷𝐷#$ = Average heating degree days (base with optimal Degrees Fahrenheit) during
period t at home i
n 𝐶𝐷𝐷#$ = Average cooling degree days (base with optimal Degrees Fahrenheit) during period t
at home i (if electric usage)
n 𝑀𝑜𝑛𝑡ℎ$= A set of dummy variables indicating the month during period t
n 𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦# = a customer-specific dummy variable isolating individual household
effects
n 𝜀#$ = The error term
n 𝛼"= The model intercept
n 𝛽%-%" = Coefficients determined via regression
The Average Daily Consumption (ADC) is calculated as the total monthly billed usage divided by the
duration of the bill month. 𝛽! represents the average change in daily baseload in the post-period
between the treatment and control group and 𝛽* and 𝛽+ represent the change in weather-related daily
consumption in the post-period between the groups. Typical monthly and annual savings were
estimated by extrapolating the 𝛽* and 𝛽+ coefficients with Typical Meteorological Year (TMY) HDD and

Evaluation Report 22
CDD data. However, in the case of gas usage, only the coefficient for HDD is utilized because CDDs were
not included in the regression model.
The equation below displays how savings were extrapolated for a full year utilizing the coefficients in the
regression model and TMY data. TMY data is weighted by the number of households assigned to each
weather station.
Equation 2-4: Savings Extrapolation
𝐴𝑛𝑛𝑢𝑎𝑙 𝑆𝑎𝑣𝑖𝑛𝑔𝑠= 𝛽!∗365.25 +𝛽*∗𝑇𝑀𝑌 𝐻𝐷𝐷+𝛽+∗𝑇𝑀𝑌 𝐶𝐷𝐷
Model 2: Random Effects Post-Program Regression Model
The following equation displays the second model specification to estimate the average daily savings
due to the measure. The post-program regression (PPR) model combines both cross-sectional and time
series data in a panel dataset. This model uses only the post-program data, with lagged energy use for
the same calendar month of the pre-program period acting as a control for any small systematic
differences between the treatment and control customers; in particular, energy use in calendar month t
of the post-program period is framed as a function of both the participant variable and energy use in the
same calendar month of the pre-program period. The underlying logic is that systematic differences
between treatment and control customers will be reflected in the differences in their past energy use,
which is highly correlated with their current energy use. These interaction terms allow pre-program
usage to have a different effect on post-program usage in each calendar month.
The model specification is as follows:
Equation 2-5: Post-Program Regression (PPR) Model Specification
𝐴𝐷𝐶#$=𝛼"+𝛽%(𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡)#+𝛽! (𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒)#+𝛽& (𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟)#+𝛽'(𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟)#+𝛽((𝑀𝑜𝑛𝑡ℎ)$+𝛽)(𝑀𝑜𝑛𝑡ℎ× 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒)#$+𝛽*(𝑀𝑜𝑛𝑡ℎ× 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟)#$+𝛽+(𝑀𝑜𝑛𝑡ℎ× 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟)#$
+𝛽,(𝐻𝐷𝐷)#$+𝛽%"(𝐶𝐷𝐷)#$+𝛽%%(𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡× 𝐻𝐷𝐷)#$+𝛽%!(𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡× 𝐶𝐷𝐷)#$+𝜀#$
Where,
n i = the ith household
n t = the first, second, third, etc. month of the post-treatment period
n 𝐴𝐷𝐶#$ = Average daily usage for reading t for household i during the post-treatment period
n 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡# = A dummy variable indicating treatment status of home i
n 𝑀𝑜𝑛𝑡ℎ$ = Dummy variable indicating month of month t
n 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒# = Average daily usage across household i’s available pre-treatment billing reads
n 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟# = Average daily usage in the summer months across household i’s
available pretreatment billing reads
n 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟# = Average daily usage in the winter months across household i’s available
pre-treatment billing reads
n 𝐻𝐷𝐷#$ = Average heating degree days (base with optimal Degrees Fahrenheit) during
period t at home i

Evaluation Report 23
n 𝐶𝐷𝐷#$ = Average cooling degree days (base with optimal Degrees Fahrenheit) during period t
at home i (if electric usage)
n 𝜀#$ = Customer-level random error
n 𝛼"= The model intercept for home i
n 𝛽%-%! = Coefficients determined via regression
The coefficient 𝛽% represents the average change in consumption between the pre-period and post-
period for the treatment group and 𝛽%% and 𝛽%! represent the change in weather-related daily
consumption in the post-period between the groups. Typical monthly and annual savings were
estimated by extrapolating the 𝛽%% and 𝛽%! coefficients with Typical Meteorological Year (TMY) HDD and
CDD data.
The equation below displays how savings were extrapolated for a full year utilizing the coefficients in the
regression model and TMY data.
Equation 2-6: Savings Extrapolation
𝐴𝑛𝑛𝑢𝑎𝑙 𝑆𝑎𝑣𝑖𝑛𝑔𝑠= 𝛽%∗365.25 +𝛽%%∗𝑇𝑀𝑌 𝐻𝐷𝐷+𝛽%!∗𝑇𝑀𝑌 𝐶𝐷𝐷
Model 3: Gross Billing Analysis, Treatment-Only Regression Model
The sections above detail the Evaluator’s methodology for estimating net energy savings for each
measure. The results from the above methodology report net savings due to the inclusion of the
counterfactual comparison group. However, for planning purposes, it is useful to estimate gross savings
for each measure. To estimate gross savings, the Evaluators employed a similar regression model;
however, only including participant customer billing data. This analysis does not include control group
billing data and therefore models energy reductions between the pre-period and post-period for the
measure participants (treatment customers).
To calculate the impacts of each measure, the Evaluators applied linear fixed effects regression using
participant billing data with weather controls in the form of Heating Degree Days (HDD) and Cooling
Degree Days (CDD). The following equation displays the model specification to estimate the average
daily savings due to the measure.
Equation 2-7: Treatment-Only Fixed Effects Weather Model Specification
𝐴𝐷𝐶#$=𝛼"+𝛽%(𝑃𝑜𝑠𝑡)#$+𝛽!(𝐻𝐷𝐷)#$+𝛽&(𝐶𝐷𝐷)#$+𝛽'(𝑃𝑜𝑠𝑡× 𝐻𝐷𝐷)#$+𝛽((𝑃𝑜𝑠𝑡× 𝐶𝐷𝐷)#$
+𝛽)(𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦)#+𝛽*(𝑀𝑜𝑛𝑡ℎ)$+𝜀#$
Where,
n i = the ith household
n t = the first, second, third, etc. month of the post-treatment period
n 𝐴𝐷𝐶#$ = Average daily usage for reading t for household i during the post-treatment period
n 𝐻𝐷𝐷#$ = Average heating degree days (base with optimal Degrees Fahrenheit) during
period t at home i
n 𝐶𝐷𝐷#$ = Average cooling degree days (base with optimal Degrees Fahrenheit) during period t
at home i (if electric usage)

Evaluation Report 24
n 𝑃𝑜𝑠𝑡#$ = A dummy variable indicating pre- or post-period designation during period t at
home i
n 𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦# = a customer-specific dummy variable isolating individual household
effects
n 𝜀#$ = Customer-level random error
n 𝛼"= The model intercept for home i
n 𝛽%-) = Coefficients determined via regression
The results of the treatment-only regression models are gross savings estimates. The gross savings
estimates are useful to compare against the net savings estimates. However, the treatment-only models
are unable to separate the effects of the COVID19 pandemic. The post-period for PY2020 and perhaps
also PY2021 are affected by the stay-at-home orders that had taken effect starting March 2020 in Idaho.
The stay-at-home orders most likely affect the post-period household usage. Because there is
insufficient post-period data before the shelter-in-place orders, the Evaluators were unable to separate
the effects on consumption due to the orders and the effects on consumption due to the measure
installation. Therefore, the results from this additional gross savings analysis are unable to reflect actual
typical year savings. However, for planning purposes, these estimates may be useful.
2.2.4 Net-To-Gross
The Northwest RTF UES measures do not require NTG adjustments as they are built into the deemed
savings estimates. In addition, billing analyses with counterfactual control groups, as proposed in our
impact methodology, does not require a NTG adjustment, as the counterfactual represents the
efficiency level at current market (i.e. the efficiency level the customer would have installed had they
not participated in the program).
2.2.5 Cost-Effectiveness Tests
The Evaluators calculated each program’s cost-effectiveness, avoided energy costs, and implementation
costs. The Evaluators used our company-developed cost-effectiveness tool to provide cost-effectiveness
assessments for the Residential Portfolio by program, fuel type, program year, and measure, for each
state.
As specified in this solicitation, the Evaluators determined the economic performance with the following
cost-effectiveness tests:
n Total Resource Cost (TRC) test;
n Utility Cost Test (UCT);
n Participant Cost Test (PCT); and
n Rate Impact Measure (RIM).
2.2.6 Non-Energy Benefits
The Evaluators used the Regional Technical Forum (RTF) to quantify non-energy benefits (NEBs) for
residential measures with established RTF values where available. Measures with quantified NEBs
include residential insulation, high efficiency windows, air source heat pumps, and ductless heat pumps.

Evaluation Report 25
In addition to the residential NEBs, the Evaluators applied the end-use non-energy benefit and health
and human safety non-energy benefit to the Low-Income Program. The Evaluators understand that the
two major non-energy benefits referenced above are uniquely applicable to the Low-Income Program.
The Evaluators applied those benefits to the program impacts as well as additional non-energy benefits
associated with individual measures included in the program. The Evaluators incorporated additional
NEBs to the impact evaluation, as applicable. Additional details on the non-energy benefits applied can
be found in Section 7.2.

Work Plan 26
3. Residential Impact Evaluation Results
The Evaluators completed an impact evaluation on Avista’s Residential portfolio to verify program-level
and measure-level energy savings for PY2020. The following sections summarize findings for each
natural gas impact evaluation in the Residential Portfolio in the Idaho service territory. The Evaluators
used data collected and reported in the tracking database, online application forms, Avista TRM, RTF,
and billing analysis of participants and nonparticipants to evaluate savings. This approach provided the
strongest estimate of achieved savings practical for each program, given its delivery method, magnitude
of savings, number of participants, and availability of data. Table 3-1 summarizes the Residential verified
impact savings by program. Table 3-2 summarizes the Residential portfolio’s cost-effectiveness.
Table 3-1: Residential Verified Impact Savings by Program
Program
Expected
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
Total Costs
Water Heat 38,131.80 37,975.80 99.59% $200,782.21
HVAC 204,211.46 266,938.58 130.72% $1,063,438.94
Shell 20,121.75 11,999.75 59.64% $160,163.25
Fuel Efficiency 0.00 0.00 - -
ENERGY STAR Homes 402.00 401.94 99.99% $2,018.87
Simple Steps, Smart Savings 299.69 233.56 77.93% $0.03
Total Res 263,166.70 317,549.63 120.66% $1,426,403.31

Table 3-2: Residential Portfolio Cost-Effectiveness Summary
Sector TRC UCT
Benefits Costs B/C Ratio Benefits Costs B/C Ratio
Residential $3,852,633 $3,466,442 1.11 $3,502,394 $1,426,403 2.46

In PY2020, Avista completed and provided incentives for residential natural gas measures in Idaho and
reported total natural gas savings of 317,549.63 Therms. All programs except the Water Heat Program
and the Shell Program met savings goals based on reported savings, leading to an overall achievement
of 120.66% of the expected savings for the residential programs. The Evaluators estimated the TRC value
for the Low-Income portfolio is 1.11 while the UCT value is 2.46. Further details of the impact evaluation
results by program are provided in the sections following.
3.1 Simple Verification Results
The Evaluators surveyed 261 unique customers that participated in Avista’s residential energy efficiency
program in February and March 2021 using a mixed mode approach (phone/email). Customers with a
valid email were sent the survey via an email invitation. Fifty-three did not have email addresses in
program records and were invited to take the survey by the Evaluators’ in-house survey administration
team. The Evaluators also conducted targeted follow-up outreach to customers for certain measures.

Evaluation Report 27
The Evaluators surveyed customers that received rebates for HVAC, Water Heater, and Fuel Efficiency
Programs.
Table 3-3: Summary of Survey Response Rate
Population Respondents
Initial email contact list 959
Invalid email addresses 3
Bounced email 43
Undeliverable email 27
Invalid email (%) 8%
Email invitations sent (unique valid) 886
Email completions 208
Email response rate (%) 23%
Initial phone list 190
Phone numbers w/ email addresses 138
Phone numbers w/ no email address 52
Disconnected/wrong number 20
Invalid phone (%) 11%
Phone calls (unique valid) 170
Phone completions 54
Phone response rate (%) 32%
Total invites (unique) 938
Total completions 262
Response rate (%) 28%
Initial email contact list 959
Invalid email addresses 3

3.1.1 In-Service Rates
The Evaluators calculated in-service rates of installed measures from simple verification surveys
deployed to program participants for the Water Heat and HVAC Programs. The Fuel Efficiency program
was surveyed for the electric measures; the sample is provided in the Idaho Electric Impact Evaluation
report and does not contribute to the precision for the Idaho Gas impacts. The Evaluators asked
participants if the rebated equipment is currently installed and working, in addition to questions about
the new equipment fuel type. The Evaluators achieved ±4.24% precision across the programs surveyed
for the natural gas measures in Avista’s service territory, summarized in Table 3-4.
Table 3-4: Simple Verification Precision by Program
Sector Program Population Respondents Precision
at 90% CI
Residential Water Heat 957 115 ±7.20%
Residential HVAC 7,401 246 ±5.16%
Residential Fuel Efficiency N/A N/A N/A
Total 8,358 361 ±4.24%

The measure-level ISRs determined from the verification survey for each program in which simple
verification was conducted is presented in Table 3-5 and Table 3-6.

Evaluation Report 28
Table 3-5: Water Heat Program ISRs by Measure
Measure Respondents ISR
G 50 Gallon Natural Gas Water Heater 11 100%
G Tankless Water Heater 102 100%

Table 3-6: HVAC Program ISRs by Measure
Measure Respondents ISR
G Natural Gas Boiler 4 100.00%
G Natural Gas Furnace 92 98.86%
G Natural Gas Wall Heater 2 100.00%
G Smart Thermostat DIY with Natural
Gas Heat 20 100.00%
G Smart Thermostat Paid Install with
Natural Gas Heat 52 94.12%
These ISR values were utilized in the desk reviews for the Water Heat and HVAC Programs in order to
calculate verified savings. Additional insights from the survey responses are summarized in Appendix B.
3.2 Impacts of COVID-19 Pandemic
On average, about three people lived at the residence that had the rebated equipment installed and
about 60% of respondents said that two or fewer lived at the residence that had the rebated equipment
installed.
About two-thirds of respondents (66%) observed that the pandemic had not changed the number of
people in their household that worked or went to school remotely.11 Twenty-two percent of
respondents said that more members of their household were attending school remotely or working
from home since the COVID-19 pandemic began. Twelve percent of respondents indicated that more
members of their household had gone to work or school remotely before the COVID-19 pandemic.
Three-quarters of respondents said that the amount of time they spend at home has increased since the
COVID-19 pandemic began. A much smaller portion of respondents indicated that other members of
their household were spending more time at home, as displayed in Figure 3-1. About half of
respondents indicated that their utility bill had increased, as displayed in Figure 3-2.

11 n=257

Evaluation Report 29
Figure 3-1: Change in amount of time spent at home

Figure 3-2: Change in natural gas bill since COVID19 pandemic began

3.3 Program-Level Impact Evaluation Results
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Residential sector in the section below.

Evaluation Report 30
3.3.1 Water Heat Program
The Water Heat Program encourages customers to replace their existing electric or natural gas water
heater with high efficiency equipment. Customers receive incentives after installation and after
submitting a completed rebate form. Table 3-7 summarizes the measures offered under this program.
Table 3-7: Water Heat Program Measures
Measure Description
Impact
Analysis
Methodology
G 50 Gallon Natural Gas Water Heater Storage tank natural gas water heater, 50 gallons or
less Avista TRM
G Tankless Water Heater Tankless natural gas water heater Avista TRM
The following table summarizes the verified natural gas savings for the Water Heat Program impact
evaluation.
Table 3-8: Water Heat Program Verified Natural Gas Savings
Measure PY2020
Participation
Expected
Savings
(Therms)
Adjusted
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
G 50 Gallon Natural Gas Water Heater 22 457.80 457.80 457.80 100.00%
G Tankless Water Heater 485 37,674.00 37,674.00 37,518.00 99.59%
Total 507 38,131.80 38,131.80 37,975.80 99.59%
The Water Heat Program displayed verified savings of 37,975.80 Therms with a realization rate of
99.59% against the expected savings for the program. The following table summarizes the incentive and
non-incentive costs from the program.
Table 3-9: Water Heat Program Costs
Measure Incentive
Costs
Non-Incentive
Costs Total Costs
G 50 Gallon Natural Gas Water Heater $2,200.00 $42.51 $2,242.51
G Tankless Water Heater $193,600.00 $4,939.70 $198,539.70
Total $195,800.00 $4,982.21 $200,782.21
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Water Heat Program in the section below.
3.3.1.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Water Heat Program.
3.3.1.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the Water Heat
Program. The Evaluators selected a subset of rebate applications to cross-verify tracking data inputs,
summarized in Section 2.2.2.1.

Evaluation Report 31
The Evaluators found all Water Heat Program rebates to have completed rebate applications with the
associated water heater model number and efficiency values filled in either the Customer Care & Billing
(CC&B) web rebate data or mail-in rebate applications.
However, the Evaluators note that the CC&B web rebate data does not reflect the same values found in
the mail-in rebate applications and/or invoices or AHRI certification documents submitted with the
rebate application. The Evaluators recommend Avista work to improve methods for collecting mail-in
rebate application information to reconcile the CC&B database. For example, ten of the 111 sampled
rebates were not found in the CC&B dataset. A number of the sampled rebates were found to have
discrepancies in model numbers between the CC&B data and the mail-in rebate applications and/or
invoices.
In addition, not all rebates were accompanied with AHRI certification. In order to acquire accurate
equipment efficiencies and tank sizes, AHRI certifications are recommended to be required and
submitted with the rebate application, with an invoice that matches the model number found in the
AHRI certification.
The Evaluators found all sampled rebate equipment met or exceeded the measure efficiency
requirements for the Water Heat Program.
3.3.1.3 Verification Surveys
The Evaluators randomly selected a subset of participant customers to survey for simple verification of
installed measure. The Evaluators included questions such as:
n Was this water heater a new construction, or did it replace another water heater?
n Was the previous water heater functional?
n Is the newly installed water heater still properly functioning?
In addition, the Evaluators asked participants how the COVID19 pandemic stay-at-home orders have
affected their household’s energy consumption. The responses to this verification survey were used to
calculate ISRs for the measures offered in the Water Heat Program.
Table 3-10 displays the ISRs for each of the Water Heat measures for Idaho and Washington territory
combined.
Table 3-10: Water Heat Verification Survey ISR Results
Measure Number of
Rebates*
Number of
Survey
Completes
Program-Level
Precision at 90%
Confidence
In-Service Rate
G 50 Gallon Natural Gas
Water Heater 119 11 7.20%* 100%
G Tankless Water Heater 838 104 100%
*This count includes rebates from Washington and Idaho
All survey respondents for each water heater measure described equipment to be currently functioning,
leading to a 100% ISR. The Evaluators applied these ISRs to each rebate to quantify verified savings for
each measure.

Evaluation Report 32
3.3.1.4 Impact Analysis
This section summarizes the verified savings results for the Water Heat Program. The Evaluators
conducted a billing analysis for measures where participation allowed. The Evaluators calculated verified
savings for the remaining measures using active values from the Avista TRM workbook. These values
were applied to a random sample of participants, with verification of project documents such as rebate
applications to verify installation, quantity, and efficiency of the equipment.
3.3.1.5 Billing Analysis
The Evaluators explored a billing analysis for the natural gas water heater measures within this program.
However, the G 50 Gallon Natural gas Water Heater lacked sufficient participation to estimate savings
and the G Tankless Gas Water Heater measure resulted in savings that were not statistically significant.
Therefore, the Evaluators elected to use Avista TRM values to estimate verified savings. The Evaluators
will explore further billing analyses for these measures during the next program year. Further details of
the billing analysis for the variable speed motor measure can be found Appendix A.
3.3.1.6 Verified Savings
The Evaluators reviewed and applied the current Avista TRM values along with verified tracking data to
estimate net program savings for this measure. The verified savings for the program is 37,975.80 Therms
with a realization rate of 99.59%, as displayed in Table 3-8.
The realization rate for the natural gas savings in the Water Heat Program deviate from 100% for the G
Tankless Gas Water Heat measure because two rebates were duplicated. Therefore, the Evaluators
removed these rebates from savings, lowering the realization rate for the program.
3.3.2 HVAC Program
The HVAC program encourages installation of high efficiency HVAC equipment and smart thermostats
through customer incentives. The program is available to residential electric or natural gas customers
with a winter heating season usage of 4,000 or more kWh, or at least 160 Therms of space heating in the
prior year. Existing or new construction homes are eligible to participate in the program. Table 3-7
summarizes the measures offered under this program.
Table 3-11: HVAC Program Measures
Measure Description Impact Analysis
Methodology
G Natural Gas Boiler Natural gas boiler Avista TRM
G Natural Gas Furnace Natural gas forced air furnace IPMVP Option A
with billing data
G Natural Gas Wall Heater Natural gas wall heater Avista TRM
G Smart Thermostat DIY with
Natural Gas Heat
Professionally installed connected
thermostats in natural gas-heated home Avista TRM
G Smart Thermostat Paid Install
with Natural Gas Heat
Variable speed motor in natural gas-
heated home Avista TRM
The following table summarizes the verified natural gas savings for the HVAC Program impact
evaluation.

Evaluation Report 33
Table 3-12: HVAC Program Verified Natural Gas Savings
Measure PY2020
Participation
Expected
Savings
(Therms)
Adjusted
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
G Natural Gas Boiler 18 1,854.00 1,836.00 1,836.00 99.03%
G Natural Gas Furnace 2,012 170,502.60 142,497.00 234,361.24 137.45%
G Natural Gas Wall Heater 0 0.00 0.00 0.00 -
G Smart Thermostat DIY with
Natural Gas Heat 190 5,077.18 5,160.82 5,110.38 100.65%
G Smart Thermostat Paid Install
with Natural Gas Heat 1,009 26,777.68 27,263.18 25,630.97 95.72%
Total 3,229 204,211.46 176,757.00 266,938.58 130.72%
The HVAC Program displayed verified savings of 226,938.58 Therms with a realization rate of 130.72%
against the expected savings for the program. The following table summarizes the incentive and non-
incentive costs associated with the program.
Table 3-13: HVAC Program Costs
Measure Incentive Costs Non-Incentive
Costs Total Costs
G Natural Gas Boiler $8,100.00 $241.23 $8,341.23
G Natural Gas Furnace $904,950.00 $30,792.49 $935,742.49
G Natural Gas Wall Heater $0.00 $0.00 $0.00
G Smart Thermostat DIY with
Natural Gas Heat $14,316.14 $671.45 $14,987.59
G Smart Thermostat Paid Install
with Natural Gas Heat $101,000.00 $3,367.63 $104,367.63
Total $1,028,366.14 $35,072.80 $1,063,438.94

The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the HVAC Program in the section below.
3.3.2.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the HVAC Program.
3.3.2.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the HVAC
Program. The Evaluators selected a random subset of rebate applications to cross-verify tracking data
inputs, summarized in in Section 2.2.2.1.
The Evaluators found all HVAC Program rebates to have project documentation with the associated
HVAC model number and efficiency values in either the CC&B web rebate data or mail-in rebate
applications. However, the Evaluators note that some of the model numbers were incomplete and the
Evaluators were unable to identify a single AHRI certification that matched the description in the rebate
application. In order to acquire accurate equipment efficiencies, AHRI certifications are recommended

Evaluation Report 34
to be required and submitted with the rebate application, with an invoice that matches the
manufacturer and model number found in the AHRI certification.
The Evaluators note that not all rebate applications contained existing/new construction field. This field
is an input to apply correct RTF UES values. The Evaluators recommend requiring this field be completed
in rebate applications, both mail-in and web-based.
The Evaluators cross-referenced the billing data to verify if customers that received a rebate for E
Natural Gas To Air Source Heat Pump or E Natural Gas To Ductless Heat Pump demonstrate a heating
season electricity usage of 8,000 kWh and natural gas usage of less than 340 Therms, as defined in the
program requirements. The Evaluators found many customers used less than 8,000 kWh or 340 Therms
annually (not just heating months). In addition, some customers had insufficient pre-period data to
determine annual usage. The Evaluators recommend Avista verify if customers meet the requirements
prior to completing the rebate.
3.3.2.3 Verification Surveys
The Evaluators randomly selected a subset of participant customers to survey for simple verification of
installed measure described in Section 2.2.2.2. The Evaluators included questions such as:
n What type of thermostat did this thermostat replace?
n Is your home heating with electricity, natural gas, or another fuel?
n Was the previous equipment functional?
n Is the newly installed equipment still properly functioning?
The responses to this verification survey were used to calculate ISRs for the measures offered in the
HVAC Program. In addition, the Evaluators asked participants how the COVID19 pandemic stay-at-home
orders have affected their household’s energy consumption. The responses to these additional
questions can be found in Appendix A.
Table 3-14 displays the ISRs for each of the HVAC measures for Idaho and Washington natural gas
territory combined. The ISRs resulted in 5.16% precision at the 90% confidence interval for the program.
Table 3-14: HVAC Verification Survey ISR Results
Measure
Number
of
Rebates*
Number of
Survey
Completes
Precision
at 90%
Confidence
In-Service
Rate
G Natural Gas Boiler 40 4
5.16%
100.00%
G Natural Gas Furnace 4,531 166 98.86%
G Natural Gas Wall Heater 1 1 100.00%
G Smart Thermostat DIY with Natural Gas Heat 765 20 100.00%
G Smart Thermostat Paid Install with Natural Gas
Heat 2,064 55 94.12%
*This count includes rebates from Washington and Idaho
Survey respondents described equipment to be currently functioning, leading to a 100% ISR for all
measures except the G Natural Gas Furnace and G Smart Thermostat Paid Install with Natural Gas Heat.
Although less than 100%, the ISR for the referenced two measures measure still exceeded ISRs of 90%.

Evaluation Report 35
The Evaluators applied the ISRs listed in Table 3-14 to each rebate to quantify verified savings for each
measure.
3.3.2.4 Impact Analysis
This section summarizes the verified savings results for the HVAC Program. The Evaluators conducted a
billing analysis for measures where participation allowed. The Evaluators calculated verified savings for
the remaining measures using active values from the Avista TRM workbook. These values were applied
to a random sample of participants, with verification of project documents such as rebate applications
to verify installation, quantity, and efficiency of the equipment.
3.3.2.5 Billing Analysis
The results of the billing analysis for the HVAC program are provided in this section. The methodology
for the billing analysis is provided in Section 2.2.3.2.
Table 3-15 displays customer counts for customers considered for billing analysis (i.e. customer with
single-measure installations) and identifies measures that met the requirements for a billing analysis.
The customers considered for billing analysis include customers in both Washington and Idaho service
territories as well as program years 2019 and 2020 in order to gather the maximum number of
customers possible for precise savings estimates.
Table 3-15: Measures Considered for Billing Analysis, HVAC Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations*
Sufficient
Participation
for Billing
Analysis
G Natural Gas Boiler ü 38
G Natural Gas Furnace ü 4,531
G Natural Gas Wall Heater ü 0
G Smart Thermostat DIY with Natural Gas Heat ü 1,053 ü
G Smart Thermostat Paid Install with Natural Gas
Heat ü 362 ü
*This count includes rebates from Washington and Idaho
The Evaluators were provided a considerable pool of control customers to draw upon. The Evaluators
used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each treatment customer was
matched to 5 similar control customers. The final number of customers in each the treatment and
control group are listed in Table 3-16.
The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for each measure and the Evaluators conducted a linear
regression using the matched participant and nonparticipant monthly billing data.

Evaluation Report 36
Table 3-16 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the HVAC Program as it provided the highest adjusted R-squared among the regression
models. Savings are statistically significant at the 90% level for the DIY smart thermostat measure.
However, the paid install smart thermostat displayed negative savings that were not statistically
significant.
Table 3-16: Measure Savings, HVAC Program
Measure Treatment
Customers
Control
Customers
Annual
Savings
per
Customer
(Therms)
90%
Lower
CI
90%
Upper
CI
Adjusted
R-
Squared
Model
Smart
Thermostat
DIY with
Natural Gas
Heat
128 637 16.14 3.91 28.38 0.91 Model
2: PPR
Smart
Thermostat
Paid Install
with Natural
Gas Heat
90 450 -34.80 -50.06 -19.54 0.91 Model
2: PPR
Because the results from these two billing analyses for smart thermostats are contradicting and/or
inconclusive, the Evaluators elected to utilize Avista TRM values to estimate verified savings for these
measures. The findings from the PY2020 billing analyses for these measures may have been impacted by
the COVID19 pandemic. Further details of the billing analysis for the variable speed motor measure can
be found Appendix A.
Retrofit Isolation Results
A retrofit isolation approach was used to estimate savings for Natural Gas Furnaces. Although this
measure was initially considered as part of the scope of the billing data regression analysis, the
Evaluators could not isolate statistically significant savings via a regression approach. Because the
retrofit isolation approach relies on extracting baseload usage estimates from June, July, and August
billing data, the sample was restricted to customers who had a full 12 months of post-installation data
prior to February of 2020. This was to prevent a potential comparison of higher baseload to lower
seasonal load just as an artifact of increased occupation due to COVID-19 restrictions.
Table 3-17 presents the total number of customers and the number of sampled customers.
Table 3-17: Customer Counts for Natural Gas Furnaces, HVAC Program
Measure Data Restriction # of Treatment Customers
G Natural Gas Furnace Starting Count 2,065
12 Months of Post Data prior to 2020-02-01 74

Evaluation Report 37
Table 3-18 provides annual savings for Natural Gas Furnaces. The Evaluators estimate the G Natural Gas
Furnace measure to display an annual savings of 118.70 Therms. This verified value was applied to all
associated rebates in the Idaho gas service territory.
Table 3-18: Measure Savings for Natural Gas Furnaces, HVAC Program
Measure # of Treatment
Customers
Annual
Savings/Customer
(Therms)
90%
Lower CI
90%
Upper CI
Relative
Precision (90%
CI)
G Natural Gas Furnace 74 118.70 116.26 121.14 2.1%

Figure 3-3 provides monthly weather-normalized savings for natural gas furnaces.
Figure 3-3: Natural Gas Furnaces Monthly Savings, HVAC Program

The savings for the natural gas furnace range between 15 and 23 Therms per month in the winter
months, with summer months displaying no Therms savings.
3.3.2.6 Verified Savings
The HVAC Program in total displays a realization rate of 130.72% with 266,938.58 Therms verified
natural gas savings in the Idaho service territory, as displayed in Table 3-12. The realization rate for the
natural gas savings in the HVAC Program deviate from 100% due to the differences between the applied
Avista TRM prescriptive savings value and the updated Avista TRM or updated RTF UES value.
The Evaluators applied the results of the retrofit isolation results to each of the G Natural Gas Furnace
measures. The Evaluators reviewed the Avista TRM values along with verified tracking data to estimate
net program adjusted savings for measures not evaluated through billing analysis. In addition, the
Evaluators reviewed and applied the current Avista TRM values for the natural gas measures along with
verified tracking data to estimate net program verified savings for this measure.

Evaluation Report 38
The smart thermostat measures’ realization rates are low because an outdated Avista TRM value was
applied to the project data to calculate expected savings. The Evaluators assigned the appropriate,
active Avista TRM value for each smart thermostat measure.
The G Natural Gas Furnace measure has a high realization rate because the billing analysis resulted in a
savings value that was 137% of the value previously used in the Avista TRM. The Evaluators recommend
adjusting the Avista TRM to reflect the observed savings value from this impact evaluation.
3.3.3 Shell Program
The Shell Program provides incentives to customers for improving the integrity of the home’s envelope
with upgrades to windows and storm windows. Rebates are issued after the measure has been installed
for insulation and window measures. Participating homes must have natural gas or natural gas heating
and itemized invoices including measure details such as insulation levels, window values, and square
footage. In order to be eligible for incentive, the single-family households, including fourplex or less,
must demonstrate an annual electricity usage of at least 8,000 kWh or an annual gas usage of at least
340 Therms. Multifamily homes have no usage requirement. This program includes free manufactured
home duct sealing implemented by UCONS. Table 3-7 summarizes the measures offered under this
program.
Table 3-19: Shell Program Measures
Measure Description Impact Analysis
Methodology
G Attic Insulation With Natural Gas
Heat
Attic insulation for homes heated with natural
gas
Billing analysis with
counterfactual
group
G Floor Insulation With Natural Gas
Heat
Floor insulation for homes heated with natural
gas Avista TRM
G Storm Windows with Natural Gas
Heat
High-efficiency storm window replacement for
homes heated with natural gas Avista TRM
G Wall Insulation With Natural Gas
Heat
Wall insulation for homes heated with natural
gas Avista TRM
G Window Replc With Natural Gas
Heat
High-efficiency window replacement for homes
heated with natural gas
Billing analysis with
counterfactual
group
The following table summarizes the adjusted and verified natural gas savings for the Shell Program
impact evaluation.
Table 3-20: Shell Program Verified Natural Gas Savings
Measure PY2020
Participation
Expected
Savings
(Therms)
Adjusted
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
G Attic Insulation With Natural Gas
Heat 35 5,633.10 5,633.10 1,944.60 34.52%
G Floor Insulation With Natural Gas
Heat 10 749.34 749.34 749.34 100.00%
G Wall Insulation With Natural Gas
Heat 11 883.19 780.84 883.19 100.00%

Evaluation Report 39
G Window Replc With Natural Gas Heat 229 12,856.12 8,328.28 8,422.62 65.51%
Total 285 20,121.75 15,491.56 11,999.75 59.64%
The Shell Program displayed verified savings of 11,999.75 Therms with a realization rate of 59.64%
against the expected savings for the program. The following table summarizes the incentive and non-
incentive costs associated with the program.
Table 3-21: Shell Program Costs
Measure Incentive Costs Non-Incentive
Costs Total Costs
G Attic Insulation With Natural Gas
Heat $28,029.20 $672.12 $28,701.32
G Floor Insulation With Natural Gas
Heat $9,366.75 $259.00 $9,625.75
G Wall Insulation With Natural Gas
Heat $9,462.75 $305.26 $9,768.01
G Window Replc With Natural Gas Heat $109,157.00 $2,911.16 $112,068.16
Total $156,015.70 $4,147.55 $160,163.25
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Shell Program in the section below.
3.3.3.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Shell Program.
3.3.3.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the Shell
Program. The Evaluators selected a random subset of rebate applications to cross-verify tracking data
inputs, summarized in Section 2.2.2.1.
The Evaluators reviewed each measure number of units, square footage, and insulation where available.
The Evaluators found one instance in which square footage quantity in the rebate application does not
match the values presented in the project data attic insulation. Two rebates showed R-values that did
not align with TRM or RTF values related to the measure (R38 and R64). The Evaluators recommend
collecting information in a standardized manner. The Evaluators assumed insulation levels closest to
those presented for those two instances.
The Evaluators found the square footage for the floor insulation, wall insulation, and storm windows to
be equivalent between the project data and the rebate applications, where available. However, the
Evaluators found one floor insulation rebate in which the new R-value did not match TRM or RTF values
(R21). The Evaluators recommend collecting this information in a standardized manner in addition to the
R-values, detailed above.
The Evaluators recommend collecting information on single/double pane windows of the baseline
windows and class of the efficient windows.

Evaluation Report 40
The Evaluators also recommend collecting information on single-family/multi-family/manufactured in
the web rebate form. This allows the Evaluators to categorize home type during the impact evaluation
methodologies. The mail-in rebates collect this information; however, it does not seem to be required to
complete the rebate and therefore many rebates are missing this information.
The Evaluators note several instances in which the web-based rebate data indicates the household has
electric heating, but all other sources (project data and document verification) indicate natural gas space
heating, and vice versa. The Evaluators recommend verifying the household space heating type prior to
completing the rebate.
The Evaluators also note one instance in which the R-values for a window was assigned incorrectly. The
Evaluators reassigned this window from an insulation of R0 to R49 to an insulation of R11 to R49.
The Evaluators cross-referenced the billing data to verify if customers demonstrate a heating season
electricity usage of 8,000 kWh and natural gas usage of less than 340 Therms, as defined in the program
requirements. The Evaluators found many customers used less than 8,000 kWh or 340 Therms annually
(not just heating months). In addition, some customers had insufficient pre-period data to determine
annual usage. The Evaluators recommend Avista verify if customers meet the requirements prior to
completing the rebate.
The Evaluators found no duplicate rebates in the project data and therefore did not remove any rebates
from verified savings.
3.3.3.3 Verification Surveys
The Evaluators did not conduct verification surveys for the Shell Program. Weatherization measures
historically have high verification rates.
3.3.3.4 Impact Analysis
This section summarizes the verified savings results for the Shell Program. The Evaluators calculated
verified savings for the natural gas measures using the active Avista TRM values. The Evaluators
calculated adjusted savings for each measure using the active Avista TRM values and verified tracking
data. These values were applied to a random sample of participants, with verification of project
documents such as rebate applications to verify installation, quantity, and efficiency of the equipment.
3.3.3.5 Billing Analysis
The results of the billing analysis for the Shell program are provided in this section. The methodology for
the billing analysis is provided in Section 2.2.3.2.
Table 3-15 displays customer counts for customers considered for billing analysis (i.e. customer with
single-measure installations) and identifies measures that met the requirements for a billing analysis.
The customers considered for billing analysis include customers in both Washington and Idaho service
territories as well as program years 2019 and 2020 in order to gather the maximum number of
customers possible for precise savings estimates.

Evaluation Report 41
Table 3-22: Measures Considered for Billing Analysis, HVAC Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation
for Billing
Analysis
G Attic Insulation With Natural Gas Heat ü 291 ü
G Floor Insulation With Natural Gas Heat ü 8
G Storm Windows with Natural Gas Heat ü 9
G Wall Insulation With Natural Gas Heat ü 24
G Window Replc With Natural Gas Heat ü 1,309 ü

The Evaluators were provided a considerable pool of control customers to draw upon. The Evaluators
used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each treatment customer was
matched to 5 similar control customers. The final number of customers in each the treatment and
control group are listed in Table 3-16.
The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for each measure and the Evaluators conducted a linear
regression using the matched participant and nonparticipant monthly billing data.
Table 3-16 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the Shell Program as it provided the highest adjusted R-squared among the regression
models. Savings are statistically significant at the 90% level for all measures and the adjusted R-squared
shows the model provided an excellent fit for the data (adjusted R-squared > 0.90).
Table 3-23: Measure Savings, HVAC Program
Measure Treatment
Customers
Control
Customers
Annual
Savings
per
Customer
(Therms)
90%
Lower
CI
90%
Upper
CI
Adjusted
R-
Squared
Model
G Attic Insulation With
Natural Gas Heat 109 545 55.56 38.06 73.06 0.94 Model
2: PPR
G Window Replc With
Natural Gas Heat 181 902 36.78 26.64 46.91 0.91 Model
2: PPR

The Evaluators found the G Attic Insulation With Natural Gas Heat measure to display a statistically
significant verified savings value of 55.56 Therms per year. In addition, the Evaluators found statistically
significant savings of 36.78 Therms per year for the G Window Replacement with Natural Gas Heat
measure. The Evaluators used these savings estimates towards calculating verified savings for the
program. Further details of the billing analysis for the variable speed motor measure can be found
Appendix A.

Evaluation Report 42
3.3.3.6 Verified Savings
The Shell Program in total displays a realization rate of 59.64% with 11,999.75 Therms verified natural
gas savings in the Idaho service territory, as displayed in Table 3-20. The realization rate for the natural
gas savings in the Shell Program deviate from 100% due to the differences between the billing analysis
results and the Avista TRM prescriptive savings values as well as outdated Avista TRM values being
applied in the expected savings calculations.
The Evaluators did not conduct a verification survey for the Shell Program and therefore did not adjust
verified savings with an ISR.
3.3.4 Fuel Efficiency Program
The Residential Fuel Efficiency Program encourages customers to consider converting their resistive
electric space and water heating equipment to natural gas. This program is offered to residential
customers in the Idaho service territory. Customers must use Avista electricity for electric straight-
resistance heating or water heating in order to qualify for the rebate, which is verified by evaluating
their energy use. The home’s electric baseboard or furnace heat consumption must indicate at least
8,000 kWh during the previous heating season. Customers receive incentives after installation and after
submitting a completed rebate form. Table 3-7 summarizes the measures offered under this program.
Table 3-24: Fuel Efficiency Program Measures
Measure Description Impact Analysis
Methodology
E Electric to Air Source Heat Pump
Electric central ducted forced
air furnace to air source heat
pump (9.0 HFSP or greater)
RTF UES
E Electric To Natural Gas Furnace
Electric baseboard or forced air
furnace heat to natural gas
forced air furnace
Billing Analysis
E Electric To Natural Gas Furnace & Water Heat Electric to natural gas furnace
and water heat combo Avista TRM
The following table summarizes the verified electric energy savings for the Fuel Efficiency Program
impact evaluation. The program does not contain any natural gas saving measures; however, the
program includes a Therms penalty due to converting electric equipment to natural gas equipment. The
verified Therms penalty is 32,378.27 Therms and represents a 78.59% realization rate against the
expected Therms penalty amount of 46,831.00 Therms. The following table displays the Therms penalty
by measure.
Table 3-25: Fuel Efficiency Program Verified Natural Gas Penalty
Measure PY2020
Participation
Expected
Savings
(Therms)
Adjusted
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
E Electric to Air Source Heat Pump* 0 N/A N/A N/A N/A
E Electric To Natural Gas Furnace 59 -22,445.00 -26,491.00 -13,419.29 59.79%
E Electric To Natural Gas Furnace &
Water Heat 36 -18,756.00 -20,340.00 -18,958.98 101.08%
Total 95 -41,201.00 -46,831.00 -32,378.27 78.59%

Evaluation Report 43
*The E Electric to Air Source Heat Pump measure had 0 rebates completed in PY2020
The Therms penalties represented in the table above are not aggregated in the Residential portfolio
impact evaluation and are summarized here for planning purposes. The costs associated with this
program are claimed in the Idaho Electric Impact Evaluation Report. The Evaluators summarize the
program-specific and measure-specific impact analysis activities, results, conclusions, and
recommendations for the Fuel Efficiency Program in Idaho Electric Impact Evaluation Report for PY2020.
3.3.5 ENERGY STAR® Homes Program
The ENERGY STAR® Homes Program provides rebates for homes within Avista’s service territory that
attain an ENERGY STAR® certification. This program incentivizes for ENERGY STAR® Eco-rated homes.
Table 3-7 summarizes the measures offered under this program.
Table 3-26: ENERGY STAR® Homes Program Measures
Measure Description Impact Analysis
Methodology
G Energy Star Home - Manufactured,
Natural Gas
ENERGY STAR-rated manufactured
home with natural gas furnace RTF UES
G Energy Star Home - Manufactured,
Gas & Electric
ENERGY STAR-rated manufactured
home with natural gas and electric RTF UES
The following table summarizes the verified natural gas savings for the ENERGY STAR® Homes Program
impact evaluation.
Table 3-27: ENERGY STAR® Homes Program Verified Natural Gas Savings
Measure PY2020
Participation
Expected
Savings
(Therms)
Adjusted
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
G Energy Star Home - Manufactured,
Natural Gas 1 134.00 133.98 133.98 99.99%
G Energy Star Home - Manufactured,
Gas & Electric 2 268.00 0.00 267.96 99.99%
Total 3 402.00 133.98 401.94 99.99%
The ENERGY STAR® Homes Program displayed verified savings of 401.94 Therms with a realization rate
of 99.99% against the expected savings for the program. The following table summarizes the incentive
and non-incentive costs associated with the program.
Table 3-28: ENERGY STAR® Homes Program Costs
Measure Incentive Costs Non-Incentive
Costs Total Costs
G Energy Star Home - Manufactured,
Natural Gas $650.00 $22.96 $672.96
G Energy Star Home - Manufactured,
Gas & Electric $1,300.00 $45.92 $1,345.92
Total $1,950.00 $68.87 $2,018.87
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the ENERGY STAR® Homes Program in the section below.

Evaluation Report 44
3.3.5.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the ENERGY STAR® Homes Program.
3.3.5.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the ENERGY
STAR® Homes Program. The Evaluators selected a random subset of rebate applications to cross-verify
tracking data inputs, summarized in Section 2.2.2.1.
The Evaluators found one duplicate rebate in the project data. The Evaluators confirmed this instance
with Avista and removed the rebate from verified savings.
3.3.5.3 Verification Surveys
The Evaluators did not conduct verification surveys for the ENERGY STAR® Homes Program.
3.3.5.4 Impact Analysis
This section summarizes the verified savings results for the ENERGY STAR® Homes Program. The
Evaluators calculated verified savings for the natural gas measures using the most recent RTF workbook
for the ENERGY STAR® Homes measures. These RTF UES values were applied to a random sample of
participants, with verification of project documents such as rebate applications to verify installation,
quantity, and efficiency of the equipment.
3.3.5.5 Verified Savings
The Evaluators reviewed the Avista TRM values along with verified tracking data to estimate adjusted
program savings for each of the ENERGY STAR® Homes measures. In addition, the Evaluators reviewed
and applied the current RTF UES values for each measure along with verified tracking data to estimate
net program savings.
The ENERGY STAR® Homes Program in total displays a realization rate of 99.99% with 401.94 Therms
verified natural gas energy savings in the Idaho service territory, as displayed in Table 3-27. The
realization rate for the natural gas savings in the ENERGY STAR® Homes Program deviate from 100% due
to rounding of the expected savings using the Avista TRM. The Evaluators included savings up to the
hundredth Therms from the RTF, which led to the 99.99% realization rate.
The Evaluators note that the Avista TRM applies RTF savings values from heating zone 2 to all rebates. In
addition, the Avista TRM does not take into account cooling zone, which also affects savings assigned in
the RTF. The Evaluators applied the appropriate RTF savings values for the heating zone and cooling
zone for each rebated household. This did not impact the two three rebates included in the Idaho Gas
territory, but did affect the realization rates of rebates in Washington.
The Evaluators did not conduct a verification survey for the ENERGY STAR® Homes Program and
therefore did not adjust verified savings with an ISR.

Evaluation Report 45
3.3.6 Simple Steps, Smart Savings Program
The Simple Steps, Smart Savings Program is a midstream lighting and appliance program which
encourages consumer to purchase and install high-quality LEDs, light fixtures, energy-efficient
showerheads, and energy-efficient clothes washers by marking down retail prices in the Idaho service
territory. The Simple Steps, Smart Savings Program was implemented in Idaho during the month of
January 2020 and therefore reflect a small percentage of savings for the residential natural gas savings.
This section summarizes the impact results of the evaluation results for the Simple Steps, Smart Savings
Program. Table 3-29 summarizes the measures offered under this program.
Table 3-29: Simple Steps, Smart Savings Program Measures
Measure Description
Impact
Analysis
Methodology
Lighting General purpose and specialty bulbs and fixtures RTF UES
Showerhead 2.0 GPM showerheads RTF UES
Appliance High efficiency clothes washers RTF UES
The following table summarizes the verified natural gas savings for the Simple Steps, Smart Savings
Program impact evaluation.
Table 3-30: Simple Steps, Smart Savings Program Verified Natural Gas Savings
Measure PY2020
Units
Expected
Savings
(Therms)
Adjusted
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization Rate
Lighting12 234,446 0.00 0.00 0.00 -
Showerhead 1,128 299.69 0.00 231.50 77.25%
Appliances 1 0.00 0.00 2.06 -
Total 235,575 299.69 0.00 233.56 77.93%
The Simple Steps, Smart Savings Program displayed verified savings of 233.56 Therms with a realization
rate of 77.93% against the expected savings for the program. The costs associated with this program are
entirely claimed in the Idaho Electric Impact Evaluation Report. The Evaluators summarize the program-
specific and measure-specific impact analysis activities, results, conclusions, and recommendations for
Simple Steps, Smart Savings Program in the section below.
3.3.6.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Simple Steps, Smart Savings Program.

12 The lighting measures in the Simple Steps, Smart Savings program included a verified Therms penalty of 22,604.26 Therms.
However, this penalty is not included in the Idaho Gas Residential Impact Evaluation impacts.

Evaluation Report 46
3.3.6.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for Simple Steps,
Smart Savings Program. The Evaluators requested the monthly invoices for each month in PY2020 for
the Simple Steps, Smart Savings Program from Avista.
The Evaluators collected and reviewed product-level quantity and pricing on each invoice. The
Evaluators found no discrepancies between the invoiced amounts and quantities and the project data
provided by Avista.
3.3.6.3 Verification Surveys
The Evaluators did not conduct verification surveys for the Simple Steps, Smart Savings Program.
3.3.6.4 Impact Analysis
This section summarizes the verified savings results for the Simple Steps, Smart Savings Program. The
Evaluators calculated verified savings for this program’s measures using the RTF UES values in effect
before October 1, 2019.
The Evaluators note that the RTF version used to evaluate this program represents the residential
lighting workbook active at the time the Bonneville Power Administration (BPA) planning for this
program was established (October 1, 2019).
3.3.6.5 Verified Savings
The Evaluators reviewed the Avista TRM values along with verified tracking data to estimate net
adjusted program savings for those measures. Final verified savings were estimated using the RTF UES
values associated with each measure. Simple Steps, Smart Savings Program displayed 77.93% realization
with 233.56 Therms saved, as displayed in Table 3-30.
The Simple Steps, Smart Savings Program did not have any Therms penalty expectations because the
Avista TRM does not include a Therms penalty for the measures provided in the program. However, the
RTF UES includes a Therms penalty, which the Evaluators applied to the project data. This Therms
penalty does not contribute to the program’s natural gas savings impacts.
3.4 Conclusions and Recommendations
The Evaluators provide the following conclusions and recommendations for Avista’s Residential Portfolio
program implementation.
3.4.1 Conclusions
The Evaluators provide the following conclusions regarding Avista’s Residential natural gas programs:
n The Evaluators found the Residential portfolio to demonstrate a total of 317,549.63 Therms with
a realization rate of 120.66%. The Evaluators also conducted a cost-benefit analysis in order to
estimate the Residential portfolio’s cost-effectiveness. The resulting TRC value for this sector is

Evaluation Report 47
1.11 while the UCT value is 2.46. Further details on cost-effectiveness methodology can be
found in Appendix C.
n The Residential Portfolio impact evaluation resulted in a realization rate of 120.66% due to slight
differences between the applied Avista TRM values and the most active Avista TRM value for
each measure in addition to the difference in savings values between the results from billing
analyses and the Avista TRM.
n The HVAC Program, which contributes 78% of the expected savings, resulted in a realization rate
of 130.72% whereas each of the other programs resulted in a combined 74% realization rate.
The Shell Program contributed to a 35% increase in the overall residential sector, which
displayed a realization rate of 120.66%.
n The Evaluators conducted verification surveys via web survey and phone calls to collect
information from customers who participated in the Water Heat and HVAC Programs. A total of
261 unique customers were surveyed between February and March 2021. The Evaluators
collected information including the functionality of the efficient equipment, the functionality of
the replaced equipment, and information on how the COVID19 stay-at-home orders have
affected the household energy usage. The Evaluators calculated in-service rates for the
measures within these two programs in order to apply findings to the verified savings results for
each program.
n The realization rate for the natural gas savings in the Water Heat Program was 99.59%. This
program deviated from 100% realization because two rebates were duplicates. Therefore, the
Evaluators removed these rebates from savings, lowering the realization rate for the program.
n The Evaluators explored a billing analysis for the natural gas water heater measures within the
Water Heat Program. However, the G 50 Gallon Natural gas Water Heater lacked sufficient
participation to estimate savings and the G Tankless Gas Water Heater measure resulted in
savings that were not statistically significant. Therefore, the Evaluators elected to use Avista
TRM values to estimate verified savings. The Evaluators will explore further billing analyses for
these measures during the next program year.
n The HVAC Program in total displays a realization rate of 130.72% with 266,938.58 Therms
verified natural gas savings in the Idaho service territory. The realization rate for the natural gas
savings in the HVAC Program deviate from 100% due to the differences between the applied
Avista TRM prescriptive savings value and the updated Avista TRM or updated RTF UES value.
The smart thermostat measures’ realization rates are low because an outdated Avista TRM
value was applied to the project data to calculate expected savings. The furnace measure has a
high realization rate because the billing analysis resulted in a savings value that was 137% of the
value previously used in the Avista TRM.
n The Evaluators attempted to estimate smart thermostat measure savings values for the HVAC
Program. However, because the results from the billing analyses for smart thermostats were
contradicting and/or inconclusive, the Evaluators elected to utilize Avista TRM values to
estimate verified savings for these measures. The findings from the PY2020 billing analyses for
these measures may have been impacted by the COVID19 pandemic. The Evaluators will explore
additional billing analyses for these measures during program year 2021.
n The Shell Program displayed verified savings of 11,999.75 Therms with a realization rate of
59.64% against the expected savings for the program. The realization rate for the natural gas

Evaluation Report 48
savings in the Shell Program deviate from 100% due to the differences between the billing
analysis results and the Avista TRM prescriptive savings values as well as outdated Avista TRM
values being applied in the expected savings calculations.
n For the Shell Program, the Evaluators conducted a billing analysis for two measures that had
sufficient participation. The Evaluators found the G Attic Insulation With Natural Gas Heat
measure to display a statistically significant verified savings value of 55.56 Therms per year. In
addition, the Evaluators found statistically significant savings of 36.78 Therms per year for the G
Window Replacement with Natural Gas Heat measure. The Evaluators used these savings
estimates towards calculating verified savings for the program.
n Final verified savings for the Simple Steps, Smart Savings Program were estimated using the RTF
UES values associated with each measure. Simple Steps, Smart Savings Program displayed
77.93% realization with 233.56 Therms saved. The discrepancy between expected and verified
Therms for the measures in this program are due to the differences between the BPA values
assigned and the appropriately applied RTF values the Evaluators assigned.
3.4.2 Recommendations
The Evaluators offer the following recommendations regarding Avista’s Residential natural gas
programs:
n The Evaluators recommend Avista work to improve methods for collecting mail-in rebate
application information to reconcile the CC&B database. The values found in the project
documentation should accurately reflect the values represented in the CC&B database.
n A number of rebates were not accompanied with AHRI certification. In order to acquire accurate
equipment efficiencies and tank sizes, AHRI certifications are recommended to be required and
submitted with the rebate application, with an invoice that matches the model number found in
the AHRI certification.
n The Evaluators note that some of the model numbers for the rebated equipment were
incomplete and the Evaluators were unable to identify a single AHRI certification that matched
the description in the rebate application. In order to acquire accurate equipment efficiencies,
AHRI certifications are recommended to be required and submitted with the rebate application,
with an invoice that matches the manufacturer and model number found in the AHRI
certification.
n The Evaluators cross-referenced the billing data to verify if customers demonstrated the
required heating season electricity usage of 8,000 kWh and natural gas usage of less than 340
Therms, as defined in the program requirements. The Evaluators found many customers used
less than 8,000 kWh or 340 Therms annually. In addition, some customers had insufficient pre-
period data to determine annual usage. The Evaluators recommend Avista verify if customers
meet the requirements prior to completing the rebate.
n For the Shell Program, the Evaluators found rebates in which the R-values did not align with
TRM or RTF values (R38 and R64). The Evaluators recommend collecting information in a
standardized manner.
n The Evaluators recommend collecting information on single/double pane windows of the
baseline windows and class of the efficient windows in order to correctly assign RTF UES values.

Evaluation Report 49
n The Evaluators note several instances in which the web-based rebate data indicates the
household has electric space heating, but all other sources (project data and document
verification) indicate natural gas space heating, and vice versa. The Evaluators recommend
updating data collection standards in order for all sources of information to reflect the same
values as the project documentation.
n The natural gas furnace measure in the HVAC has a high realization rate because the billing
analysis resulted in a savings value that was 137.45% of the value previously used in the Avista
TRM. The Evaluators recommend adjusting the Avista TRM to reflect the observed savings
values from all billing analyses from this impact evaluation.
n The Evaluators recommend adjusting expected savings calculations in the Simple Steps, Smart
Savings Program to include Therms penalty for the measures offered, in order to more
accurately reflect the approved RTF savings values.
4. Low-Income Impact Evaluation Results
The Low-Income Program delivers energy efficiency measures to low-income residential customers in its
Idaho service territory with a partnership with five network Community Action Agencies (“Agencies”)
and one tribal weatherization organization. The Agencies qualify income to prioritize and treat
households based on several characteristics. In-house or contract crews install approved program
measures. In addition, the Agencies have access to other monetary resources which allow them to
weatherize a home or install additional energy efficiency measures.
The Evaluators completed an impact evaluation on Avista’s Low-Income portfolio to verify program-level
and measure-level energy savings for PY2020. The following sections summarize findings for each
natural gas impact evaluation in the Low-Income Portfolio in the Idaho service territory. The Evaluators
used data collected and reported in the tracking database, online application forms, Avista TRM, and
RTF values to evaluate verified savings. This approach provided the strongest estimate of achieved
savings practical for each program, given its delivery method, magnitude of savings, number of
participants, and availability of data. Table 4-1 summarizes the Low-Income verified impact savings by
program. Table 4-2 summarizes the Low-Income portfolio cost-effectiveness results.
Table 4-1: Low-Income Verified Impact Savings by Program
Program
Expected
Savings
(Therms)
Adjusted
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
Low-Income 5,009.32 4,719.08 5,494.69 109.69%
Total 5,009.32 4,719.08 5,494.69 109.69%

Evaluation Report 50
Table 4-2: Low-Income Portfolio Cost-Effectiveness Summary
Sector TRC UCT
Benefits Costs B/C Ratio Benefits Costs B/C Ratio
Low Income $168,428 $638,498 0.26 $68,285 $662,514 0.10
In PY2020, Avista completed and provided incentives for low-income gas measures in Idaho and
achieved total natural gas savings of 5,494.69 Therms. The Low-Income Program exceeded savings
expectations based on reported savings with an achieved realization rate of 109.69%. The Evaluators
estimated the TRC value for the Low-Income portfolio is 0.26 while the UCT value is 0.10. Further details
of the impact evaluation results by program are provided in the sections following.
4.1 Program-Level Impact Evaluation Results
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Low-Income sector in the section below.
4.1.1 Low-Income Program
The Low-Income Program delivers energy efficiency measures to low-income residential customers in its
Idaho service territory with a partnership with five network Community Action Agencies (“Agencies”)
and one tribal weatherization organization. The Agencies qualify income to prioritize and treat
households based on several characteristics. In-house or contract crews install approved program
measures. In addition, the Agencies have access to other monetary resources which allow them to
weatherize a home or install additional energy efficiency measures.
Avista provides CAP agencies with the following approved measure list, which are reimbursed in full by
Avista. Avista also provides a rebate list of additional energy saving measures the CAP agencies are able
to utilize which are partially reimbursed. The following table summarizes the measures offered under
this program.
Table 4-3 summarizes the measures offered under this program.
Table 4-3: Low-Income Program Measures
Measure Impact Analysis Methodology
Air Infiltration
Avista TRM
Air source heat pump
Attic insulation
Duct insulation
Duct sealing
Natural gas to air source heat
pump
Natural gas to ductless heat
pump
ENERGY STAR® door

Evaluation Report 51
Measure Impact Analysis Methodology
ENERGY STAR® refrigerator
ENERGY STAR® window
Floor insulation
Heat pump water heater
LED lighting
Wall insulation
High efficiency furnace
High efficiency tankless natural
gas water heater
Natural gas boiler
Table 4-4 summarizes the verified natural gas savings for the Low-Income Program impact evaluation.
Table 4-4: Low-Income Program Verified Natural Gas Savings
Measure PY2020
Participation
Expected
Savings
(Therms)
Adjusted
Savings
(Therms)
Verified
Savings
(Therms)
Verified
Realization
Rate
G Air Infiltration 18 218.91 220.14 220.14 100.56%
G Duct Sealing 1 20.17 20.17 20.17 100.00%
G Energy Star Doors 7 66.96 67.62 67.62 100.99%
G Energy Star Windows 17 369.48 368.25 376.70 101.95%
G HE Furnace 49 3,342.84 3,049.76 3,796.64 113.58%
G HE WH 50G 25 174.10 176.28 176.28 101.25%
G INS - Attic 3 370.98 370.98 383.35 103.33%
G INS - Duct 0 0.00 0.00 0.00
G INS - Floor 4 296.76 296.76 310.18 104.52%
G INS - Wall 2 82.62 82.62 77.11 93.33%
Health and Safety 22 0.00 0.00 0.00
G Tankless Water Heater 1 66.50 66.50 66.50 100.00%
Total 149 5,009.32 4,719.08 5,494.69 109.69%
The Low-Income Program displayed verified savings of 5,494.69 Therms with a realization rate of
109.69% against the expected savings for the program. The following table summarizes the incentive
and non-incentive costs associated with the program.
Table 4-5: Low-Income Program Costs
Measure Incentive
Costs
Non-
Incentive
Costs
Total Costs
G Air Infiltration $1,454.03 $1,211.01 $2,665.04
G Duct Sealing $173.61 $156.99 $330.60
G Energy Star Doors $5,511.00 $1,200.91 $6,711.91
G Energy Star Windows $50,625.76 $7,713.02 $58,338.78
G HE Furnace $281,070.11 $23,737.30 $304,807.41
G HE WH 50G $104,110.27 $816.18 $104,926.45

Evaluation Report 52
G INS - Attic $5,361.75 $7,849.05 $13,210.80
G INS - Duct $0.00 $0.00 $0.00
G INS - Floor $4,609.56 $6,350.88 $10,960.44
G INS - Wall $1,142.91 $1,578.88 $2,721.79
Health and Safety $89,410.19 $64,039.16 $153,449.35
G Tankless Water Heater $3,873.60 $517.59 $4,391.19
Total $547,342.79 $115,170.97 $662,513.76
The Evaluators summarize the program-specific and measure-specific impact analysis activities, results,
conclusions, and recommendations for the Low-Income Program in the section below.
4.1.1.1 Database Review & Verification
The following sections describe the Evaluator’s database review and document verification findings for
the Low-Income Program.
4.1.1.2 Database Review & Document Verification
Before conducting the impact analysis, the Evaluators conducted a database review for the Low-Income
Program. The Evaluators selected a subset of rebate applications to cross-verify tracking data inputs,
summarized in Section 2.2.2.1.
The Evaluators reviewed the project documentation provided by Avista and identified conflicting square
footage or number of units between the aggregated project data from the CC&B and the rebate project
documentation provided in the data request for document verification. The Evaluators, updated
quantity based on project documentation.
The Evaluators note that some project data account numbers do not match the account numbers
referenced in the project documentation. In addition, the Evaluators found conflicting information in the
project documentation on a number of homes’ heating type. The Evaluators recommend confirming and
documenting all rebate applications for completed and accurate heating type details.
The Evaluators also note that project documentation contains additional equipment included in some
invoices. These additional equipment contribute to the total project cost. The Evaluators identified and
removed three duplicated rebates. These rebates seem to have been duplicated due to rebate
administration corrections.
The Evaluators also utilized the delivered billing data to check the household-level annual usage. The
Low-Income Program requires a 20% annual energy usage cap on claimed energy savings. The
Evaluators found some discrepancies between the 20% annual consumption cap and the claimed energy
savings. The Evaluators recommend checking each project against billing data prior to reporting energy
savings for the project, as well as documenting each household’s usage as well as the date range used to
calculate the household consumption estimate.
4.1.1.3 Verification Surveys
The Evaluators did not conduct verification surveys for the Low-Income Program.

Evaluation Report 53
4.1.1.4 Impact Analysis
This section summarizes the verified savings results for the Low-Income Program. The Evaluators
calculated verified savings for Low-Income Program measures using the Avista TRM. However, a whole
building billing analysis was completed to supplement the findings from the desk review.
4.1.1.5 Billing Analysis
The results of the billing analysis for the Low-Income Program are provided below. Table 4-6 displays
customer counts for customers considered for billing analysis (i.e. customer with single-measure
installations) and identifies measures that met the requirements for a billing analysis.
The Evaluators attempted to estimate measure-level Low-Income Program energy savings through
billing analysis regression with a counterfactual group selected via propensity score matching. The
Evaluators attempted to isolated each unique measure. In doing so, the Evaluators also isolate the
measure effects using the customer’s consumption billing data. However, participation for the Low-
Income program resulted in a small number of customers with isolated measures, as displayed in Table
4-6 and therefore the Evaluators were unable to estimate measure-level savings through billing analysis.
The customers considered for billing analysis include customers in both Washington and Idaho service
territories as well as program years 2019 and 2020 in order to gather the maximum number of
customers possible for precise savings estimates.
Table 4-6: Measures Considered for Billing Analysis, Low-Income Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation for
Billing Analysis*
G Air Infiltration ü 0
G Duct Sealing ü 0
G Energy Star Doors ü 0
G Energy Star Windows ü 6
G HE Furnace ü 27
G HE WH 50G ü 0
G INS – Attic ü 0
G INS – Duct ü 0
G INS – Floor ü 0
G INS – Wall ü 0
Health And Safety ü 0
G Tankless Water Heater ü 2
*No measures had sufficient participation of isolated measures
The Evaluators instead conducted a whole-home billing analysis for all the natural gas measures
combined in order to estimate savings for the average household participating in the program, across all
measures. The Evaluators successfully created a matched cohort for the natural gas measure
households. Customers were matched on zip code (exact match) and their average pre-period seasonal
usage, including summer, fall, winter, and spring for each control and treatment household. The
Evaluators were provided a considerable pool of control customers to draw upon. The Evaluators used

Evaluation Report 54
nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each treatment customer was
matched to 5 similar control customers.
Table 4-7 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the Low-Income Program as it provided the highest adjusted R-squared among the
regression models. Savings are statistically significant at the 90% level for all measures and the adjusted
R-squared shows the model provided an excellent fit for the data.
Table 4-7: Measure Savings, Low-Income Program
Measure Treatment
Customers
Control
Customers
Annual Savings
per Customer
(Therms)
90%
Lower
CI
90%
Upper
CI
Adjusted
R-
Squared
Model
All Gas Measures
(Therms) 79 369 54.53 26.33 83.1 0.91 Model 2: PPR

The Evaluators applied these regression savings estimates to the program as a whole, by the number of
unique households in the program and found a realization rate of 139.64% for all natural gas measures
in the program. Further details of the billing analysis can be found in Appendix A.
4.1.1.6 Verified Savings
Due to insufficient participation to conduct measure-level billing analyses, the Evaluators reviewed the
Avista TRM values along with verified tracking data to estimate net program savings for those measures.
Adjusted savings were estimated using the Avista TRM. The Low-Income Program in total displays a
realization rate of 109.69% with 5,494.69 Therms verified natural gas savings in the Idaho service
territory, as displayed in Table 4-4. The billing analysis supports this estimate, with the billing analysis
estimating a 139.64% realization. Due to requirements for measure-level verified savings for cost-
effectiveness testing, the Evaluators designated the adjusted savings as final.
The Evaluators note that the majority of deviations from 100% realization rate is due to the change in
square footage or number of units verified in the project documentation. The Evaluators updated the
quantity based on new project data.
4.2 Conclusions and Recommendations
The Evaluators provide the following conclusions and recommendations for Avista’s Low-Income
Portfolio program implementation.
4.2.1 Conclusions
The Evaluators provide the following conclusions regarding Avista’s Residential natural gas programs:
n The Evaluators found the Low-Income portfolio to demonstrate a total of 5,494.69 Therms with
a realization rate of 109.69%. The Low-Income Portfolio impact evaluation resulted in verified
savings that exceeded expected savings.
n The Evaluators conducted a cost-benefit analysis in order to estimate the Low-Income
portfolio’s cost-effectiveness. The resulting TRC value for this sector is 0.26 while the UCT value

Evaluation Report 55
is 0.10. These values are expected, as the Low-Income portfolio is not expected to meet cost-
effectiveness but are implemented in order to provide energy efficiency benefits to low-income
customers. Further details on cost-effectiveness methodology can be found in Appendix C.
n The Evaluators attempted to estimate measure-level Low-Income Program energy savings
through billing analysis regression with a counterfactual group selected via propensity score
matching. The Evaluators attempted to isolate each unique measure. However, participation for
the Low-Income program resulted in a small number of customers with isolated measures and
therefore the Evaluators conducted a whole-home billing analysis for all the natural gas
measures combined in the Low-Income in order to estimate savings for the average household
participating in the program, across all measures. The Evaluators found a realization rate of
139% for all natural gas measures in the program, which supported the realization rate of 110%
from the desk review.
n The Evaluators note that the majority of deviations from 100% realization rate is due to the
change in square footage or number of units verified in the project documentation.
4.2.2 Recommendations
The Evaluators offer the following recommendations regarding Avista’s Low-Income natural gas
programs:
n The Evaluators note that the majority of deviations from 100% realization rate is due to the
change in square footage or number of units verified in the project documentation. The
Evaluators reviewed the project documentation provided by Avista and identified conflicting
square footage or number of units between the aggregated project data from the CC&B and the
rebate project documentation provided in the data request for document verification. In
addition, the unit type, in terms of square footage or number of measures (windows, doors, etc)
was not documented consistently and therefore savings values were applied inaccurately. The
Evaluators recommend updating CC&B documentation standards to more accurately reflect
values present on the rebate applications.
n The Evaluators found discrepancies between the 20% annual consumption cap and the claimed
energy savings. The Evaluators recommend checking each project against billing data prior to
reporting energy savings for the project, as well as documenting each household’s usage as well
as the date range used to calculate the household consumption estimate.

Evaluation Report 56
5. Appendix A: Billing Analysis Results
This appendix provides additional details on the billing analyses conducted for each program.
5.1 Water Heat Program
The results of the billing analysis for the Water Heat program are provided in this section. The
methodology for the billing analysis is provided in Section 2.2.3.2. Table 5-1 displays customer counts for
customers considered for billing analysis (i.e. customer with single-measure installations) and identifies
measures that met the requirements for a billing analysis.
The Evaluators attempted to estimate measure-level HVAC Program energy savings through billing
analysis regression with a counterfactual group selected via propensity score matching. The Evaluators
attempted to isolated each unique measure. In doing so, the Evaluators also isolate the measure effects
using the customer’s consumption billing data.
A billing analysis was completed for measures that had at least 75 customers with single-measure
installations. This ensured that measures would have a sufficient sample size after applying PSM data
restrictions (e.g. sufficient pre- and post-period data). The billing analysis included participants in both
PY2019 and PY2020 in order to acquire the maximum number of customers possible. However, results
from billing analyses are only extrapolated to PY2020 participants.
Table 5-1: Measures Considered for Billing Analysis, HVAC Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation
for Billing
Analysis
G 50 Gallon Natural Gas Water Heater ü 23
G Tankless Gas Water Heater ü 285 ü

The Evaluators were provided a considerable pool of control customers to draw upon, as shown in Table
5-2. However, the G 50 Gallon Natural Gas Water Heater measure had insufficient participation to
conduct a billing analysis. The Evaluators moved forward with billing analysis for the G Tankless Gas
Water Heater.
The Evaluators used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each treatment
customer was matched to 5 similar control customers. Also shown in Table 5-7, are the impact of
various restrictions on the number of treatment and control customers that were included in the final
regression model. The “Starting Count” displays the beginning number of customers available prior to
applying the data restrictions, while the “Ending Count” displays the number of customers after applying
data restrictions and final matching.
Table 5-2: Cohort Restrictions, HVAC Program
Measure Data Restriction Treatment
Customers
Control
Customers
Starting Count 231 42,191

Evaluation Report 57
G Tankless Gas
Water Heater
Install Date Range: 2019-01-01 to 2020-06-30 134 42,191
Control Group Usage Outlier (>2X max treatment usage) 134 42,186
Incomplete Post-Period Bills (<24 months) 106 28,196
Incomplete Pre-Period Bills 99 25,523
Ending Count (Matched by PSM) 99 495
Figure 5-1 and Figure 5-2 display the density of each variable employed in propensity score matching for
the G Tankless Gas Water Heater, before and after conducting matching. The figures following display the
density of each variable employed in propensity score matching for the other billing analysis measures,
before and after matching.
The distributions prior to matching appear to be less similar in summer, with control customers averaging
higher usage. However, after matching, the pre-period usage distribution in summer is more similar
between the groups. The remaining pre-period seasons (winter, summer, fall), closely overlap before and

Evaluation Report 58
after matching, indicating little differences exist on average between the groups prior to matching and
validating the initial selection of control customers.
Figure 5-1: Covariate Balance Before Matching, Tankless Gas Water Heater

Figure 5-2: Covariate Balance After Matching, Tankless Gas Water Heater

The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for the measure. T-tests of monthly pre period usage can
yield a statistically significant difference 40% of the time for one to two months out of 12. Thus, the
Evaluators set a tolerance band allowing two months out of 12 to vary in pre-period usage at the 95%
confidence level. All groups passed this threshold. In addition, the chi-squared test returned a p-value
well over 0.05 for all measures, indicating that pre-period usage was balanced between the groups.
Lastly, the standardized difference test returned values well under the recommended cutoff of 25,
typically falling under 10, further indicating the groups were well matched on all included covariates.

Evaluation Report 59
Table 5-3 provides customer counts for customers in the final regression model by assigned weather
station ID for each measure. In addition, TMY HDD and CDD from the nearest available TMY weather
station is provided as well as the weighted HDD/CDD for each measure. The HDD and CDD was weighted
by the number of treatment customers assigned to a weather station.
Table 5-3: TMY Weather, HVAC Program
Measure USAF Station
ID
Treatment
Customers
TMY
USAF ID
TMY
HDD
TMY
CDD
Weighted
TMY HDD
Weighted
TMY CDD
G Tankless Gas Water Heater 720322 6 727834 6,915 376 6,859 398
G Tankless Gas Water Heater 726817 3 727834 6,915 376 6,859 398
G Tankless Gas Water Heater 727830 4 727830 5,511 907 6,859 398
G Tankless Gas Water Heater 727834 86 727834 6,915 376 6,859 398

Table 5-4 provides annual savings per customer for the HVAC program for each measure and regression
model. However, savings are not statistically significant at the 90% level for any of the models explored
for the G Tankless Gas Water Heater.
Table 5-4: Measure Savings for All Regression Models, HVAC Program
Measure Model Treatment
Customers
Control
Customers
Annual
Savings per
Customer
(Therms)
90%
Lower
CI
90%
Upper CI
Relative
Precision
(90% CI)
Adjusted
R-
Squared
G Tankless Gas
Water Heater Diff-in-diff 99 495 16.71 -38.11 71.54 328% 0.50
G Tankless Gas
Water Heater PPR 99 495 -0.76 -19.34 17.81 2439% 0.88
G Tankless Gas
Water Heater
Treatment
Only (Gross) 99 N/A -18.51 -56.35 19.32 204% 0.75
*Not statistically significant
Table 5-5 provides results for the t-test on pre-period usage between the treatment and control groups
after matching for the Water Heat program. The Evaluators placed a threshold of two rejects for each
measure as there is a 40% likelihood that one or two months may show statistical variance due to
chance. The variable speed motor measure did not exceed this threshold.
Table 5-5: Pre-period Usage T-test for Tankless Gas Water Heater, Water Heater Program
Month
Average Daily
Usage
(Therms),
Control
Average Daily
Usage
(Therms),
Treatment
T Statistic Std
Error P-Value Reject
Null?
Jan 3.808 3.893 -0.355 0.241 0.723 No
Feb 3.740 3.948 -0.861 0.242 0.390 No
Mar 3.023 3.217 -0.977 0.198 0.330 No
Apr 1.840 1.920 -0.685 0.117 0.494 No
May 0.776 0.767 0.156 0.059 0.876 No

Evaluation Report 60
Jun 0.608 0.570 0.662 0.057 0.508 No
Jul 0.521 0.529 -0.099 0.076 0.921 No
Aug 0.553 0.622 -0.493 0.140 0.623 No
Sep 0.903 0.909 -0.065 0.095 0.948 No
Oct 1.810 1.818 -0.060 0.126 0.952 No
Nov 3.127 3.186 -0.307 0.193 0.759 No
Dec 3.731 3.773 -0.188 0.222 0.851 No

5.2 HVAC Program
The results of the billing analysis for the HVAC program are provided in this section. The methodology
for the billing analysis is provided in Section 2.2.3.2. Table 5-6 displays customer counts for customers
considered for billing analysis (i.e. customer with single-measure installations) and identifies measures
that met the requirements for a billing analysis.
The Evaluators attempted to estimate measure-level HVAC Program energy savings through billing
analysis regression with a counterfactual group selected via propensity score matching. The Evaluators
attempted to isolated each unique measure. In doing so, the Evaluators also isolate the measure effects
using the customer’s consumption billing data.
A billing analysis was completed for measures that had at least 75 customers with single-measure
installations. This ensured that measures would have a sufficient sample size after applying PSM data
restrictions (e.g. sufficient pre- and post-period data). The billing analysis included participants in both
PY2019 and PY2020 in order to acquire the maximum number of customers possible. However, results
from billing analyses are only extrapolated to PY2020 participants.
Table 5-6: Measures Considered for Billing Analysis, HVAC Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation
for Billing
Analysis
G Natural Gas Boiler ü 18
G Natural Gas Furnace ü 2,958 ü
G Natural Gas Wall Heater ü 0
G Smart Thermostat DIY with Natural Gas Heat ü 347 ü
G Smart Thermostat Paid Install with Natural Gas
Heat ü 571 ü

The Evaluators conducted a separate analysis for the G Natural Gas Furnace measure, displayed in
Section 3.3.2.5 as it provided more reasonable and statistically significant results than the billing
analysis. The following details the billing analysis for the remaining measures.
The Evaluators were provided a considerable pool of control customers to draw upon, as shown in Table
5-7. The Evaluators used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each
treatment customer was matched to 5 similar control customers. Also shown in Table 5-7, are the

Evaluation Report 61
impact of various restrictions on the number of treatment and control customers that were included in
the final regression model. The “Starting Count” displays the beginning number of customers available
prior to applying the data restrictions, while the “Ending Count” displays the number of customers after
applying data restrictions and final matching.
Table 5-7: Cohort Restrictions, HVAC Program
Measure Data Restriction Treatment
Customers
Control
Customers
Smart Thermostat
DIY with Natural
Gas Heat
Starting Count 347 42,191
Install Date Range: 2019-01-01 to 2020-06-30 233 42,191
Control Group Usage Outlier (>2X max treatment usage) 232 42,186
Incomplete Post-Period Bills (<24 months) 152 28,173
Incomplete Pre-Period Bills 128 25,505
Ending Count (Matched by PSM) 128 637
Smart Thermostat
Paid Install with
Natural Gas Heat
Starting Count 571 42,191
Install Date Range: 2019-01-01 to 2020-06-30 299 42,191
Control Group Usage Outlier (>2X max treatment usage) 298 42,186
Incomplete Post-Period Bills (<24 months) 121 28,158
Incomplete Pre-Period Bills 90 25,490
Ending Count (Matched by PSM) 90 450
Figure 5-3 and Figure 5-4 display the density of each variable employed in propensity score matching for
the DIY installed smart thermostat with natural gas heat measure, before and after matching. Additionally,
Figure 5-5 and Figure 5-6 display the density of each variable employed in propensity score matching for
the professionally installed smart thermostat with natural gas heat measure, before and after matching.
The distributions prior to matching appear to be less similar in summer, with control customers averaging
higher usage. However, after matching, the pre-period usage distribution in summer is more similar
between the groups. The remaining pre-period seasons (winter, summer, fall), closely overlap before and

Evaluation Report 62
after matching, indicating little differences exist on average between the groups prior to matching and
validating the initial selection of control customers.
Figure 5-3: Covariate Balance Before Matching, Smart Thermostat DIY with Natural Gas Heat

Figure 5-4: Covariate Balance After Matching, Smart Thermostat DIY with Natural Gas Heat

Figure 5-5: Covariate Balance Before Matching, Smart Thermostat Paid Install with Natural Gas Heat

Evaluation Report 63

Figure 5-6: Covariate Balance After Matching, Smart Thermostat Paid Install with Natural Gas Heat

The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for each measure. T-tests of monthly pre period usage can
yield a statistically significant difference 40% of the time for one to two months out of 12. Thus, the
Evaluators set a tolerance band allowing two months out of 12 to vary in pre-period usage at the 95%
confidence level. All groups passed this threshold. In addition, the chi-squared test returned a p-value
well over 0.05 for all measures, indicating that pre-period usage was balanced between the groups.
Lastly, the standardized difference test returned values well under the recommended cutoff of 25,
typically falling under 10, further indicating the groups were well matched on all included covariates.
Further details on the results of the three tests performed to determine PSM success are available in the
Appendix.
Table 5-8 and Table 5-9 provide results for the t-test on pre-period usage between the treatment and
control groups after matching for the HVAC program. The Evaluators placed a threshold of two rejects

Evaluation Report 64
for each measure as there is a 40% likelihood that one or two months may show statistical variance due
to chance. All three measures do not exceed this threshold.
Table 5-8: Pre-period Usage T-test for Smart Thermostat DIY with Natural Gas Heat, HVAC Program
Month
Average Daily
Usage
(Therms),
Control
Average Daily
Usage
(Therms),
Treatment
T Statistic Std Error P-Value Reject Null?
Jan 3.522 3.587 -0.476 0.137 0.635 No
Feb 3.433 3.487 -0.394 0.137 0.694 No
Mar 2.758 2.826 -0.564 0.121 0.574 No
Apr 1.682 1.733 -0.577 0.088 0.564 No
May 0.682 0.703 -0.375 0.056 0.708 No
Jun 0.501 0.519 -0.380 0.050 0.704 No
Jul 0.414 0.414 0.002 0.045 0.999 No
Aug 0.421 0.410 0.257 0.043 0.798 No
Sep 0.741 0.789 -0.685 0.070 0.494 No
Oct 1.628 1.701 -0.858 0.085 0.392 No
Nov 2.820 2.879 -0.520 0.113 0.603 No
Dec 3.495 3.514 -0.152 0.128 0.880 No

Table 5-9: Pre-period Usage T-test for Smart Thermostat Paid Install with Natural gas Heat, HVAC
Program
Month
Average Daily
Usage
(Therms),
Control
Average Daily
Usage
(Therms),
Treatment
T Statistic Std Error P-Value Reject Null?
Jan 3.435 3.529 -0.514 0.182 0.608 No
Feb 3.474 3.634 -0.871 0.184 0.385 No
Mar 2.883 3.032 -0.951 0.156 0.343 No
Apr 1.825 1.889 -0.645 0.099 0.520 No
May 0.800 0.856 -1.113 0.050 0.267 No
Jun 0.596 0.658 -1.472 0.042 0.143 No
Jul 0.487 0.561 -2.000 0.037 0.047 Yes
Aug 0.487 0.542 -1.517 0.036 0.131 No
Sep 0.825 0.873 -0.963 0.050 0.337 No
Oct 1.643 1.727 -0.934 0.090 0.352 No
Nov 2.733 2.894 -1.121 0.143 0.264 No
Dec 3.274 3.505 -1.328 0.174 0.187 No

Evaluation Report 65
Table 5-10 provides customer counts for customers in the final regression model by assigned weather
station ID for each measure. In addition, TMY HDD and CDD from the nearest available TMY weather
station is provided as well as the weighted HDD/CDD for each measure. The HDD and CDD was weighted
by the number of treatment customers assigned to a weather station.
Table 5-10: TMY Weather, HVAC Program
Measure USAF Station
ID
# of
Treatment
Customers
TMY
USAF ID
TMY
HDD
TMY
CDD
Weighted
TMY HDD
Weighted
TMY CDD
Smart Thermostat DIY
with Natural Gas Heat 720322 7 727834 6,915 376 6,564 509
Smart Thermostat DIY
with Natural Gas Heat 720923 1 727834 6,915 376 6,564 509
Smart Thermostat DIY
with Natural Gas Heat 726817 3 727834 6,915 376 6,564 509
Smart Thermostat DIY
with Natural Gas Heat 727830 32 727830 5,511 907 6,564 509
Smart Thermostat DIY
with Natural Gas Heat 727834 85 727834 6,915 376 6,564 509
Smart Thermostat Paid
Install with Natural Gas
Heat
720322 2 727834 6,915 376 6,822 412
Smart Thermostat Paid
Install with Natural Gas
Heat
727830 6 727830 5,511 907 6,822 412
Smart Thermostat Paid
Install with Natural Gas
Heat
727834 82 727834 6,915 376 6,822 412

Table 5-11 provides estimated annual savings per customer for each measure. Model 2 (PPR) was
selected as the final model for the HVAC Program as it provided the highest adjusted R-squared among
the regression models. Savings are statistically significant at the 90% level for the DIY Smart Thermostat
with Natural Gas Heat. However, savings for Smart Thermostat Paid Install with Natural Gas Heat
statistically significant and negative, as shown in the table and figures below. The adjusted R-squared
shows the model provided an excellent fit for the data.
Table 5-11: Measure Savings, HVAC Program
Measure Treatment
Customers
Control
Customers
Annual
Savings
per
Customer
(Therms)
90%
Lower
CI
90%
Upper
CI
Adjusted
R-Squared Model
Smart
Thermostat
DIY with
Natural Gas
Heat
128 637 16.14 3.91 28.38 0.91 Model 2:
PPR

Evaluation Report 66
Smart
Thermostat
Paid Install
with
Natural Gas
Heat
90 450 -34.80 -50.06 -19.54 0.91 Model 2:
PPR

Figure 5-7 and Figure 5-8 provide monthly TMY savings per customer for the HVAC program.
Figure 5-7: Smart Thermostat DIY with Natural Gas Heat Monthly Savings, HVAC Program

Figure 5-8: Smart Thermostat Paid Install with Natural Gas Heat Monthly Savings, HVAC Program

Evaluation Report 67
The Evaluators note that the negative savings for DIY and Paid Smart Thermostats are not typical. This
may be attributable to increased household occupation during the post-treatment period due to COVID-
19 pandemic restrictions. Additionally, Smart Thermostats may be subject to a snapback effect in which
energy usage increases due to the replacement of faulty or ineffective equipment. Therefore, the
Evaluators elected to use TRM values for verified savings for the smart thermostat measures in the
Idaho Gas impact evaluation for PY2020. The Evaluators will re-evaluate the smart thermostat measures
in PY2021.
5.3 Shell Program
The results of the billing analysis for the Shell program are provided below. Table 5-12 shows customer
counts for customers considered for billing analysis (i.e. customer with single-measure installations) and
identifies measures that met the requirements for a billing analysis. A billing analysis was completed for
measures that had at least 75 customers with single-measure installations. This ensured that measures
would have a sufficient sample size after applying PSM data restrictions (e.g. sufficient pre- and post-
period data).
Table 5-12: Measures Considered for Billing Analysis, Shell Program
Measure
Measure
Considered for
Billing Analysis
Number of Customers
w/ Single-Measure
Installations
Sufficient
Participation
for Billing
Analysis
G Attic Insulation With Natural Gas Heat ü 33613 ü
G Floor Insulation With Natural Gas Heat ü 6
G Storm Windows with Natural Gas Heat ü 1
G Wall Insulation With Natural Gas Heat ü 4
G Window Replc With Natural Gas Heat ü 370 ü

The Evaluators were successful in creating a matched cohort for each of the measures with sufficient
participation. Customers were matched on zip code (exact match) and their average pre-period seasonal
usage, including summer, fall, winter, and spring for each control and treatment household. The
Evaluators were provided a considerable pool of control customers to draw upon, as shown in Table
5-13. The Evaluators used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each
treatment customer was matched to 5 similar control customers. Also shown in Table 5-13, are the
impact of various restrictions on the number of treatment and control customers that were included in
the final regression model. The “Starting Count” displays the beginning number of customers available
prior to applying the data restrictions, while the “Ending Count” displays the number of customers after
applying data restrictions and final matching.
Table 5-13: Cohort Restrictions, Shell Program
Measure Data Restriction
# of
Treatment
Customers
# of
Control
Customers

13 This estimate includes 291 customers from WA with attic insulation; ID on its own had an insufficient number of attic
installations for a billing analysis (45 customers).

Evaluation Report 68
G Attic Insulation With
Natural Gas Heat

Starting Count 336 116,739
Install Date Range: January 1, 2019 to June 30, 2020 189 116,739
Control Group Usage Outlier (>2X max treatment usage) 189 116,732
Incomplete Post-Period Bills (<24 months) 133 79,804
Incomplete Pre-Period Bills (<10 months) 109 73,096
Ending Count (Matched by PSM) 109 545
G Window Replc With
Natural Gas Heat

Starting Count 370 42,191
Install Date Range: January 1, 2019 to June 30, 2020 241 42,191
Control Group Usage Outlier (>2X max treatment usage) 240 42,186
Incomplete Post-Period Bills (<24 months) 204 28,174
Incomplete Pre-Period Bills (<10 months) 181 25,506
Ending Count (Matched by PSM) 181 902
Figure 5-9 and Figure 5-10 display the density of each variable employed in propensity score matching for
the attic insulation measure, before and after conducting matching. In addition, Figure 5-11 and Figure
5-12 display the density of each variable employed in propensity score matching for the window
replacement measure, before and after conducting matching.
The distributions prior to matching appear to be less similar in summer, with control customers averaging
higher usage. However, after matching, the pre-period usage distribution in summer is more similar
between the groups. The remaining pre-period seasons (winter, summer, fall), closely overlap before and
after matching, indicating little differences exist on average between the groups prior to matching and
validating the initial selection of control customers.

Evaluation Report 69
Figure 5-9: Covariate Balance Before Matching, Shell Attic Insulation

Figure 5-10: Covariate Balance After Matching, Shell Attic Insulation

Evaluation Report 70
Figure 5-11: Covariate Balance Before Matching, Shell Window Replacement

Figure 5-12: Covariate Balance After Matching, Shell Window Replacement

The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for each measure. The t-test displayed no statistically
significant differences at the 95% level in average daily consumption between the treatment and control
groups for any month in the pre-period. In addition, the chi-squared test returned a p-value well over
0.05 for all measures, indicating that pre-period usage was balanced between the groups. Lastly, the
standardized difference test returned values well under the recommended cutoff of 25, and always
falling under 10, further indicating the groups were well matched on all included covariates. Further
details on the results of the three tests performed to determine PSM success are available in the
Appendix.
Table 5-14 and Figure 5-13 provide results for the t-test on pre-period usage between the treatment and
control groups after matching for the Shell program. The P-Value is over 0.05 for each month, meaning
pre-period usage between treatment and control groups is similar at the 95% confidence level.

Evaluation Report 71
Table 5-14: Pre-period Usage T-test for Attic Insulation, Shell Program
Month
Average Daily
Usage
(Therms),
Control
Average Daily
Usage
(Therms),
Treatment
T Statistic Std Error P-Value Reject Null?
Jan 4.156 4.113 0.198 0.214 0.843 No
Feb 4.064 4.083 -0.087 0.212 0.931 No
Mar 3.214 3.347 -0.761 0.175 0.447 No
Apr 1.946 1.988 -0.353 0.119 0.724 No
May 0.849 0.805 0.439 0.099 0.662 No
Jun 0.699 0.640 0.416 0.140 0.678 No
Jul 0.574 0.508 0.511 0.129 0.610 No
Aug 0.577 0.595 -0.101 0.171 0.920 No
Sep 0.902 0.912 -0.063 0.148 0.950 No
Oct 1.883 1.849 0.294 0.116 0.769 No
Nov 3.320 3.333 -0.074 0.180 0.941 No
Dec 3.969 4.166 -0.934 0.211 0.351 No
Table 5-15: Pre-period Usage T-test for Window Replacement, Shell Program
Month
Average Daily
Usage
(Therms),
Control
Average Daily
Usage
(Therms),
Treatment
T Statistic Std Error P-Value Reject Null?
Jan 3.522 3.587 -0.476 0.137 0.635 No
Feb 3.433 3.487 -0.394 0.137 0.694 No
Mar 2.758 2.826 -0.564 0.121 0.574 No
Apr 1.682 1.733 -0.577 0.088 0.564 No
May 0.682 0.703 -0.375 0.056 0.708 No
Jun 0.501 0.519 -0.380 0.050 0.704 No
Jul 0.414 0.414 0.002 0.045 0.999 No
Aug 0.421 0.410 0.257 0.043 0.798 No
Sep 0.741 0.789 -0.685 0.070 0.494 No
Oct 1.628 1.701 -0.858 0.085 0.392 No
Nov 2.820 2.879 -0.520 0.113 0.603 No
Dec 3.495 3.514 -0.152 0.128 0.880 No

Table 5-16 provides customer counts for customers in the final regression model by assigned weather
station ID for each measure. In addition, TMY HDD and CDD from the nearest available TMY weather
station is provided as well as the weighted HDD/CDD for each measure. The HDD and CDD was weighted
by the number of treatment customers assigned to a weather station.

Evaluation Report 72
Table 5-16: TMY Weather, Shell Program
Measure USAF
Station ID
# of
Treatment
Customers
TMY USAF ID TMY
HDD
TMY
CDD
Weighted
TMY HDD
Weighted
TMY CDD
G Attic Insulation With
Natural Gas Heat 727830 5 727830 5,511 907 6,312 518
G Attic Insulation With
Natural Gas Heat 727834 7 727834 6,915 376 6,312 518
G Attic Insulation With
Natural Gas Heat 727850 0 727850 6,707 379 6,312 518
G Attic Insulation With
Natural Gas Heat 727855 5 727855 7,360 439 6,312 518
G Attic Insulation With
Natural Gas Heat 727856 88 727856 6,246 519 6,312 518
G Attic Insulation With
Natural Gas Heat 727857 3 727857 6,467 299 6,312 518
G Attic Insulation With
Natural Gas Heat 727870 1 727856 6,246 519 6,312 518
G Window Replc With
Natural Gas Heat 720322 4 727834 6,915 376 6,186 652
G Window Replc With
Natural Gas Heat 720923 1 727834 6,915 376 6,186 652
G Window Replc With
Natural Gas Heat 726817 18 727834 6,915 376 6,186 652
G Window Replc With
Natural Gas Heat 727830 94 727830 5,511 907 6,186 652

Table 5-17 provides annual savings per customer for the Shell program for each measure and regression
model. The PPR model was selected for ex post savings because it provided the best fit for the data
(highest adjusted R-squared).
Table 5-17: Measure Savings for All Regression Models, Shell Program
Measure Model
# of
Treatment
Customers
# of
Control
Customers
Annual
Savings/Customer
(Therms)
90%
Lower
CI
90%
Upper
CI
Adjusted
R-Squared
G Attic Insulation With
Natural Gas Heat Diff-in-diff 109 545 44.82* -42.58 132.23 0.30
G Attic Insulation With
Natural Gas Heat PPR 109 545 55.56 38.06 73.06 0.94
G Attic Insulation With
Natural Gas Heat
Treatment
Only (Gross) 109 N/A 50.05 18.00 82.11 0.81
G Window Replc With
Natural Gas Heat Diff-in-diff 181 902 34.30 0.04 68.56 0.55
G Window Replc With
Natural Gas Heat PPR 181 902 36.78 26.64 46.91 0.91
G Window Replc With
Natural Gas Heat
Treatment
Only (Gross) 181 N/A 11.28* -5.75 28.31 0.86

Evaluation Report 73

Savings are statistically significant at the 90% level for all measures and the adjusted R-squared shows
the model provided an excellent fit for the data.
Table 5-18: Measure Savings, Shell Program
Measure
# of
Treatment
Customers
# of
Control
Customers
Annual
Savings/Customer
(Therms)
90%
Lower
CI
90%
Upper
CI
Adjusted
R-
Squared
Model
G Attic Insulation
With Natural Gas Heat 109 545 55.56 38.06 73.06 0.94 Model 2: PPR
G Window Replc With
Natural Gas Heat 181 902 36.78 26.64 46.91 0.91 Model 2: PPR

Figure 5-13 and Figure 5-7 provide monthly TMY savings per customer for the Shell program. As
expected for gas weatherization measures, the greatest savings occur during the winter months.
Figure 5-13: Attic Insulation Monthly Savings, Shell Program

11.4
9.4
9.7
4.1
2.6
-1.1
-2.8 -2.8
-0.9
5.2
8.8
11.8
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Mo
n
t
h
l
y

S
a
v
i
n
g
s
/
C
u
s
t
o
m
e
r

(
T
h
e
r
m
s
)
Month

Evaluation Report 74
Figure 5-14: Window Replacement Monthly Savings, Shell Program

5.4 Fuel Efficiency Program
The results of the billing analysis for the Fuel Conversion program are provided in this section. The
methodology for the billing analysis is provided in Section 2.2.3.2. Table 5-19 displays customer counts
for customers considered for billing analysis (i.e. customer with single-measure installations) and
identifies measures that met the requirements for a billing analysis.
The Evaluators attempted to estimate measure-level Fuel Efficiency Program energy savings through
billing analysis regression with a counterfactual group selected via propensity score matching. The
Evaluators attempted to isolated each unique measure. In doing so, the Evaluators also isolate the
measure effects using the customer’s consumption billing data.
A billing analysis was completed for measures that had at least 75 customers with single-measure
installations. This ensured that measures would have a sufficient sample size after applying PSM data
restrictions (e.g. sufficient pre- and post-period data). The billing analysis included participants in both
PY2019 and PY2020 in order to acquire the maximum number of customers possible. However, results
from billing analyses are only extrapolated to PY2020 participants.
Table 5-19: Measures Considered for Billing Analysis, Fuel Efficiency Program
Measure
Measure
Considered for
Billing Analysis
Number of
Customers w/
Isolated-Measure
Installations
Sufficient
Participation
for Billing
Analysis
E Electric To Natural Gas Furnace ü 186 ü
E Electric To Natural Gas Furnace &
Water Heat ü 33

7.3
6.2
4.8
2.6
1.7
-0.3
-1.0
-1.1
0.8
3.4
5.4
7.0
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Mo
n
t
h
l
y

S
a
v
i
n
g
s
/
C
u
s
t
o
m
e
r

(
T
h
e
r
m
s
)
Month

Evaluation Report 75
The Evaluators were successful in creating a matched cohort for each of the measures with sufficient
participation. Customers were matched on zip code (exact match) and their average pre-period seasonal
usage, including summer, fall, winter, and spring for each control and treatment household.
The Evaluators were provided a considerable pool of control customers to draw upon, as shown in Table
5-20. The Evaluators used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each
treatment customer was matched to 5 similar control customers. Also shown in Table 5-20, are the
impact of various restrictions on the number of treatment and control customers that were included in
the final regression model. The “Starting Count” displays the beginning number of customers available
prior to applying the data restrictions, while the “Ending Count” displays the number of customers after
applying data restrictions and final matching.
Table 5-20: Cohort Restrictions, Fuel Efficiency Program
Measure Data Restriction
# of
Treatment
Customers
# of
Control
Customers
E Electric To Natural Gas Furnace Starting Count 186 132,725
E Electric To Natural Gas Furnace Install Date Range: January 1, 2019 to June 30,
2020 162 132,725
E Electric To Natural Gas Furnace Control Group Usage Comparable to Treatment
Group 158 132,654
E Electric To Natural Gas Furnace Incomplete Post-Period Bills (<4 months) 132 89,361
E Electric To Natural Gas Furnace Incomplete Pre-Period Bills (<10 months) 85 69,413
E Electric To Natural Gas Furnace Restrict to Controls w/ Probable Electric
Resistance14 85 10,412
E Electric To Natural Gas Furnace Ending Count (Matched by PSM) 85 421
Figure 5-15 and Figure 5-16 display the density of each variable employed in propensity score matching
for the E Electric to Natural Gas Furnace measure, before and after conducting matching.
The distributions prior to matching appear to be less similar, with control customers averaging lower
usage. However, after matching, the pre-period usage distribution is more similar between the groups.
The pre-period usage in the winter before and after matching averages a more spread distribution for the
treatment group, however, the average usage between groups appears the same after matching (verified
with t-test on pre-usage).

14 The Evaluators restricted to controls with pre-period winter usage higher than the 85th percentile (i.e. top 15%) as these
customers are more likely to have electric resistance heating.

Evaluation Report 76
Figure 5-15: Covariate Balance Before Matching, E Electric to Natural Gas Furnace

Figure 5-16: Covariate Balance After Matching, E Electric to Natural Gas Furnace

The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for the measure. The t-test displayed no statistically
significant differences at the 95% level in average daily consumption between the treatment and control
groups for any month in the pre-period. In addition, the chi-squared test returned a p-value well over
0.05 for all measures, indicating that pre-period usage was balanced between the groups. Lastly, the
standardized difference test returned values well under the recommended cutoff of 25, and always
falling under 10, further indicating the groups were well matched on all included covariates.
Table 5-21 provides the results for the t-test on pre-period usage between the treatment and control
groups after matching for the Fuel Efficiency Program. The P-Value is over 0.05 for each month, meaning
pre-period usage between treatment and control groups is similar at the 95% confidence level.

Evaluation Report 77
Table 5-21: Pre-period Usage T-test for Electric to Gas Furnace, Fuel Conversion Program
Month
Average Daily
Usage (kWh),
Control
Average Daily
Usage (kWh),
Treatment
T Stat Std Error P-Value Reject Null?
Jan 72.502 69.978 0.699 3.613 0.486 No
Feb 69.808 67.655 0.611 3.522 0.542 No
Mar 59.063 60.098 -0.344 3.006 0.731 No
Apr 43.331 43.494 -0.077 2.133 0.939 No
May 30.497 29.155 0.915 1.466 0.362 No
Jun 29.164 27.861 0.802 1.624 0.423 No
Jul 34.092 33.291 0.364 2.198 0.716 No
Aug 33.202 32.844 0.175 2.050 0.862 No
Sep 30.944 30.174 0.435 1.766 0.664 No
Oct 41.417 41.816 -0.156 2.567 0.877 No
Nov 59.142 60.794 -0.389 4.246 0.698 No
Dec 69.305 69.601 -0.072 4.086 0.942 No

Table 5-22 provides customer counts for customers in the final regression model by assigned weather
station ID for each measure. In addition, TMY HDD and CDD from the nearest available TMY weather
station is provided as well as the weighted HDD/CDD for each measure. The HDD and CDD was weighted
by the number of treatment customers assigned to a weather station.
Table 5-22: TMY Weather, Fuel Efficiency Program
Measure
USAF
Station
ID
# of
Treatment
Customers
TMY USAF
ID TMY HDD TMY
CDD
Weighted
TMY HDD
Weighted
TMY CDD
E Electric to Natural Gas Furnace 720322 3 727834 6,915 376 6,333 517
E Electric to Natural Gas Furnace 726817 3 727834 6,915 376 6,333 517
E Electric to Natural Gas Furnace 727827 4 727827 5,428 731 6,333 517
E Electric to Natural Gas Furnace 727830 7 727830 5,511 907 6,333 517
E Electric to Natural Gas Furnace 727834 13 727834 6,915 376 6,333 517
E Electric to Natural Gas Furnace 727855 2 727855 7,360 439 6,333 517
E Electric to Natural Gas Furnace 727856 47 727856 6,246 519 6,333 517
E Electric to Natural Gas Furnace 727857 4 727857 6,467 299 6,333 517
E Electric to Natural Gas Furnace 727870 2 727856 6,246 519 6,333 517

Table 5-23 provides annual savings per customer for each measure. Model 2 (PPR) was selected as the
final model for the Fuel Efficiency Program as it provided the highest adjusted R-squared among the
regression models. Savings are statistically significant at the 90% level for all measures and the adjusted
R-squared shows the model provided an excellent fit for the data.

Evaluation Report 78
Table 5-23: Measure Savings, Fuel Efficiency Program
Measure
# of
Treatment
Customers
# of
Control
Customers
Annual
Savings/Customer
(kWh)
90%
Lower
CI
90%
Upper
CI
90%
Relative
Precision
Adjusted
R-
Squared
Model
E Electric to Natural
Gas Furnace 85 421 5,068 4,384 5,7512 0.13 0.73 Model 2:
PPR

Figure 5-17 provides monthly TMY savings per customer for the Fuel Conversion program. As expected,
the greatest savings occur during the winter months.
Figure 5-17: E Electric to Gas Furnace Monthly Savings, Fuel Conversion Program

The Evaluators found the E Electric To Natural Gas Furnace measure to display 5,068 kWh savings per
year. This estimate was statistically significant at the 90% confidence interval with precision of 13%. The
Evaluators estimate the Therms penalty for this measure with the following equation:
Equation 5-1: Furnace Conversion Heating Load
𝐻𝑒𝑎𝑡𝑖𝑛𝑔 𝐿𝑜𝑎𝑑=𝐴𝑛𝑛𝑢𝑎𝑙 𝑘𝑊ℎ 𝑆𝑎𝑣𝑖𝑛𝑔𝑠∗𝐶𝑂𝑃/012$3#2 ∗3,412 𝑘𝑊ℎ
𝐵𝑇𝑈100,000 𝑇ℎ𝑒𝑟𝑚𝑠
𝐵𝑇𝑈

Equation 5-2 Furnace Conversion Therms Penalty
𝑇ℎ𝑒𝑟𝑚𝑠 𝑃𝑒𝑛𝑎𝑙𝑡𝑦=𝐻𝑒𝑎𝑡𝑖𝑛𝑔 𝐿𝑜𝑎𝑑
0.80 𝐵𝑎𝑠𝑒 𝐴𝐹𝑈𝐸
Where,
n 𝐻𝑒𝑎𝑡𝑖𝑛𝑔 𝐿𝑜𝑎𝑑 = The number of full load hours required for heating the home per year
n 𝐴𝑛𝑛𝑢𝑎𝑙 𝑘𝑊ℎ 𝑆𝑎𝑣𝑖𝑛𝑔𝑠 = measure saving result from linear regression (5,068 kWh/year)
n 𝐶𝑂𝑃/012$3#2 = Coefficient of performance (equal to 1, assuming electric resistance baseline)
919.0
769.1 722.3
385.4
281.9
21.6
-98.6 -103.4
76.1
464.9
716.4
913.5
-200.0
0.0
200.0
400.0
600.0
800.0
1000.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Mo
n
t
h
l
y

S
a
v
i
n
g
s
/
C
u
s
t
o
m
e
r

(
T
h
e
r
m
s
)
Month

Evaluation Report 79
The Therms penalty for the E Electric to Natural Gas Furnace measure is 216.15 Therms. This penalty is
applied in the Idaho Gas Impact Evaluation Report.
Due to the insufficient isolated measure participation for the E Electric To Natural Gas Furnace & Water
Heater measure, the Evaluators assigned savings for this measure using the Avista TRM value of 9,789
kWh and -565 Therms savings per year.
Evaluators also conducted a treatment-only regression model for each of the measures described above.
This analysis was completed at the request of Avista in order to help with program planning. Table 5-24
provides annual savings/customer for the Fuel Conversion program for each measure and regression
model. The PPR model was selected for ex post savings because it provided the best fit for the data
(highest adjusted R-squared). The treatment-only model represents estimated gross savings for this
measure at 5,430 Therms saved per year.
Table 5-24: Measure Savings for All Regression Models, Fuel Efficiency Program
Measure Model
# of
Treatment
Customers
# of
Control
Customers
Annual
Savings/Customer
(kWh)
90%
Lower
CI
90%
Upper
CI
90%
Relative
Precision
Adjusted
R-
Squared
Electric to Natural
Gas Furnace Diff-in-diff 85 421 5,267.69 3,572.27 6,963.10 0.32 0.26
Electric to Natural
Gas Furnace PPR 85 421 5,068.03 4,384.25 5,751.80 0.13 0.73
Electric to Natural
Gas Furnace
Treatment
Only (Gross) 85 N/A 5,430.42 4,625.74 6,235.10 0.15 0.70

5.5 Low-Income Program
The Evaluators conducted a whole-home billing analysis for all the natural gas measures combined in
order to estimate savings for the average household participating in the program, across all measures.
The Evaluators successfully created a matched cohort for the natural gas measure households.
Customers were matched on zip code (exact match) and their average pre-period seasonal usage,
including summer, fall, winter, and spring for each control and treatment household.
The Evaluators were provided a considerable pool of control customers to draw upon, as shown in Table
5-25. The Evaluators used nearest neighbor matching with a 5 to 1 matching ratio. Therefore, each
treatment customer was matched to 5 similar control customers. Also shown in Table 5-25, are the
impact of various restrictions on the number of treatment and control customers that were included in
the final regression model. The “Starting Count” displays the beginning number of customers available
prior to applying the data restrictions, while the “Ending Count” displays the number of customers after
applying data restrictions and final matching.
Table 5-25: Cohort Restrictions, Low-Income Program
Measure Data Restriction
# of
Treatment
Customers
# of
Control
Customers
Whole home natural
gas
Starting Count 146 1,252
Install Date Range: January 1, 2019 to June 30, 2020 89 1,252

Evaluation Report 80

Control Group Usage Outlier (>2X max treatment usage) 89 1,252
Incomplete Post-Period Bills (<4 months) 82 1058
Incomplete Pre-Period Bills (<10 months) 79 970
Ending Count (Matched by PSM) 79 369
Figure 5-18 and Figure 5-19 display the density of each variable employed in propensity score matching
for the combined natural gas measures before and after conducting matching.
The distributions prior to matching appear to be less similar in summer, with control customers averaging
higher usage. However, after matching, the pre-period usage distribution in summer is more similar
between the groups. The remaining pre-period seasons (winter, summer, fall), closely overlap before and
after matching, indicating little differences exist on average between the groups prior to matching and
validating the initial selection of control customers.
Figure 5-18: Covariate Balance Before Matching, Low Income Gas Measures

Figure 5-19: Covariate Balance After Matching, Low Income Gas Measures

The Evaluators performed three tests to determine the success of PSM:
1. t-test on pre-period usage by month

Evaluation Report 81
2. Joint chi-square test to determine if any covariates are imbalanced
3. Standardized difference test for each covariate employed in matching
All tests confirmed that PSM performed well for each measure. The t-test displayed no statistically
significant differences at the 95% level in average daily consumption between the treatment and control
groups for any month in the pre-period. In addition, the chi-squared test returned a p-value well over
0.05 for all measures, indicating that pre-period usage was balanced between the groups. Lastly, the
standardized difference test returned values were under 10 (well under the recommended cutoff of 25),
further indicating the groups were well matched on all included covariates.
Table 5-26 provides customer counts for customers in the final regression model by assigned weather
station ID for each measure. In addition, TMY HDD and CDD from the nearest available TMY weather
station is provided as well as the weighted HDD/CDD for each measure. The HDD and CDD was weighted
by the number of treatment customers assigned to a weather station.
Table 5-26: TMY Weather, Low-Income Program
Measure USAF
Station ID
# of
Treatment
Customers
TMY USAF ID TMY
HDD
TMY
CDD
Weighted
TMY HDD
Weighted
TMY CDD
All Natural Gas
Measures 727827 2 727827 5,428 731 6,300 501
All Natural Gas
Measures 727830 5 727830 5,510 906 6,300 501
All Natural Gas
Measures 727834 7 727834 6,915 376 6,300 501
All Natural Gas
Measures 727850 2 727850 6,246 519 6,300 501
All Natural Gas
Measures 727855 2 727855 7,360 439 6,300 501
All Natural Gas
Measures 727856 49 727856 6,246 519 6,300 501
All Natural Gas
Measures 727857 12 727857 6,467 299 6,300 501
Table 5-27 provides annual savings/customer for the Low-Income program for each measure and
regression model. The PPR model was selected for ex post savings because it provided the best fit for
the data (highest adjusted R-squared).
Table 5-27: Measure Savings for All Regression Models, Low-Income Program
Measure Model
# of
Treatment
Customers
# of
Control
Customers
Annual
Savings/Customer
90%
Lower
CI
90%
Upper
CI
Adjusted
R-Squared
All Natural
Gas
Measures
Diff-in-diff 79 485 16.00* 0 84.41 0.61
All Natural
Gas
Measures
PPR 79 485 54.53 26.33 83.1 0.91

Evaluation Report 82
All Natural
Gas
Measures
Treatment
Only (Gross) 79 485 46.22 0 128.56 0.81
*Not statistically significant
The Evaluators estimate each household in the Low-Income Program saved an average of 54.53 Therms
per year. The treatment-only model displays an average household savings of 46.22 Therms per year.
This estimate represents a gross savings estimate for the program rather than a net savings estimate.
Table 5-28 provides results for the t-test on pre-period usage between the treatment and control groups
after matching for the Low-Income program. The P-Value is over 0.05 for each month, meaning pre-
period usage between treatment and control groups is similar at the 95% confidence level.
Table 5-28: Pre-period Usage T-test for Natural Gas Measures, Low-Income Program
Month
Average Daily
Usage
(Therms),
Control
Average Daily
Usage
(Therms),
Treatment
T Statistic Std Error P-Value Reject
Null?
Jan 3.55 3.52 0.166 0.189 0.868 No
Feb 2.69 2.68 0.101 0.135 0.920 No
Mar 3.30 3.26 0.300 0.153 0.765 No
Apr 1.80 1.80 -0.021 0.083 0.983 No
May 1.40 1.38 0.302 0.080 0.763 No
Jun 0.58 0.60 -0.543 0.043 0.588 No
Jul 0.10 0.11 -0.127 0.045 0.899 No
Aug 0.05 0.04 0.153 0.044 0.879 No
Sep 0.14 0.16 -0.373 0.050 0.710 No
Oct 0.75 0.78 -0.511 0.063 0.609 No
Nov 2.65 2.69 -0.283 0.120 0.777 No
Dec 3.14 3.07 0.464 0.152 0.643 No

6. Appendix B: Summary of Survey Respondents
This section summarizes additional insights gathered from the simple verification surveys deployed by
the Evaluators for the impact evaluation of Avista’s Residential and Low-Income Programs.
Survey respondents confirmed installing between one and three measures that were rebated by Avista,
displayed in Table 6-1.

Evaluation Report 83
Table 6-1: Type and Number of Measures Received by Respondents
Measure Category Total Percent
One Measure 161 61%
Two Measures 69 26%
Three Measures 32 12%
HVAC 140 53%
Water Heater 138 53%
Smart Thermostat 113 43%
Variable Speed Motors 4 2%
The Evaluators asked respondents to provide information regarding their home, as displayed in Table
6-2. Most respondents noted owning a single-family home between 1,000-3,000 square feet with
central air conditioning.

Evaluation Report 84
Table 6-2: Survey Respondent Home Characteristics15

15 Four contractors or construction companies were not asked these questions.
Question Response Percent (n=258)
Own 97%
Rent 3%
Single-family house detached from any
other house 89%
Single-family house attached to one or
more other houses (e.g., duplex,
condominium, townhouse)
4%
Mobile or manufactured home 6%
Apartment with 2 or 3 units 1%
Garage/outbuilding 1%
Don’t Know 1%
Window air conditioning / a room AC unit 12%
Central air conditioning 73%
Neither 14%
Don’t Know 1%
Less than 1,000 square feet 6%
1,000-1,999 square feet 38%
2,000-2,999 square feet 35%
3,000-3,999 square feet 14%
4,000 or more square feet 6%
Don’t know 1%
Before 1960 21%
1960 to 1969 5%
1970 to 1979 17%
1980 to 1989 12%
1990 to 1999 12%
2000 to 2009 16%
2010 to 2018 15%
Don’t know 1%
Do you rent or your home?
Which of the following best
describe your home?
Does your home have central air
conditioning, window air
conditioning, or neither?
About how many square feet is
your home?
When was your home built?

Evaluation Report 85
7. Appendix C: Cost Benefit Analysis Results
The Evaluators estimated the cost-effectiveness for the Avista Residential and Low-Income Programs
using evaluated savings results, economic inputs provided by Avista, and incremental costs and non-
energy impacts from the RTF. The table below presents the cost-effectiveness results for the PY2020
portfolio.
Table 7-1: Cost-effectiveness Results
Program TRC UCT RIM PCT TRC Net
Benefits
Residential 1.11 2.46 0.30 1.41 $386,191
Low Income 0.26 0.10 0.08 N/A* ($470,010)
Total 0.98 1.71 0.28 N/A* ($83,220)
*Low Income is offered at no cost to participants; PCT is not calculable.

7.1 Approach
The California Standard Practice Model was used as a guideline for the calculations. The cost-
effectiveness analysis methods that were used in this analysis are among the set of standard methods
used in this industry and include the Utility Cost Test (UCT)16, Total Resource Cost Test (TRC), Ratepayer
Impact Measure Test (RIM), and Participant Cost Test (PCT). All tests weigh monetized benefits against
costs. These monetized amounts are presented as NPV evaluated over the lifespan of the measure. The
benefits and costs differ for each test based on the perspective of the test. The definitions below are
taken from the California Standard Practice Manual.
n The TRC measures the net costs of a demand-side management program as a resource option
based on the total costs of the program, including both the participants' and the utility's costs.
n The UCT measures the net costs of a demand-side management program as a resource option
based on the costs incurred by the program administrator (including incentive costs) and
excluding any net costs incurred by the participant. The benefits are similar to the TRC benefits.
Costs are defined more narrowly.
n The PCT is the measure of the quantifiable benefits and costs to the customer due to
participation in a program. Since many customers do not base their decision to participate in a
program entirely on quantifiable variables, this test cannot be a complete measure of the
benefits and costs of a program to a customer.
n The RIM test measures what happens to customer bills or rates due to changes in utility
revenues and operating costs caused by the program. Rates will go down if the change in
revenues from the program is greater than the change in utility costs. Conversely, rates or bills
will go up if revenues collected after program implementation is less than the total costs

16 The UCT is also referred to as the Program Administrator Cost Test (PACT).

Evaluation Report 86

incurred by the utility in implementing the program. This test indicates the direction and
magnitude of the expected change in customer bills or rate levels.
A common misperception is that there is a single best perspective for evaluation of cost-effectiveness.
Each test is useful and accurate, but the results of each test are intended to answer a different set of
questions. The questions to be addressed by each cost test are shown in the table below.17
Table 7-2: Questions Addressed by the Various Cost Tests
Cost Test Questions Addressed
Participant Cost Test (PCT)
n Is it worth it to the customer to install energy efficiency?
n Is it likely that the customer wants to participate in a utility program that
promotes energy efficiency?
Ratepayer Impact Measure (RIM)
n What is the impact of the energy efficiency project on the utility’s
operating margin?
n Would the project require an increase in rates to reach the same
operating margin?
Utility Cost Test (UCT)
n Do total utility costs increase or decrease?
n What is the change in total customer bills required to keep the utility
whole?
Total Resource Cost Test (TRC)
n What is the regional benefit of the energy efficiency project (including
the net costs and benefits to the utility and its customers)?
n Are all of the benefits greater than all of the costs (regardless of who
pays the costs and who receives the benefits)?
n Is more or less money required by the region to pay for energy needs?

Overall, the results of all four cost-effectiveness tests provide a more comprehensive picture than the
use of any one test alone. The TRC cost test addresses whether energy efficiency is cost-effective
overall. The PCT, UCT, and RIM address whether the selection of measures and design of the program
are balanced from the perspective of the participants, utilities, and non-participants. The scope of the
benefit and cost components included in each test are summarized in the table below.18

17 http://www.epa.gov/cleanenergy/documents/suca/cost-effectiveness.pdf
18 Ibid.

Evaluation Report 87

Table 7-3: Benefits and Costs Included in Each Cost-Effectiveness Test
Test Benefits Costs
PCT (Benefits and costs from
the perspective of the
customer installing the
measure)
n Incentive payments
n Bill Savings
n Applicable tax credits or
incentives
n Incremental equipment
costs

n Incremental installation
costs
UCT (Perspective of utility,
government agency, or third
party implementing the
program
n Energy-related costs avoided by
the utility
n Capacity-related costs avoided by
the utility, including generation,
transmission, and distribution
n Program overhead costs

n Utility/program
administrator incentive
costs
TRC (Benefits and costs from
the perspective of all utility
customers in the utility service
territory)
n Energy-related costs avoided by
the utility
n Capacity-related costs avoided by
the utility, including generation,
transmission, and distribution
n Additional resource savings
n Monetized non-energy benefits
n Program overhead costs

n Program installation costs

n Incremental measure costs
RIM (Impact of efficiency
measure on non-participating
ratepayers overall)
n Energy-related costs avoided by
the utility

n Capacity-related costs avoided by
the utility, including generation,
transmission, and distribution
n Program overhead costs

n Lost revenue due to
reduced energy bills

n Utility/program
administrator installation
costs

7.2 Non-Energy Benefits
Non-energy Benefits (NEBs) were sourced from the most updated RTF workbooks. NEBs included wood
fuel credits, increased comfort, and reductions in PM 2.5 emissions.
n Residential measures with NEBs included air source heat pumps, ductless heat pumps, windows,
and insulation measures.
n Low Income NEBs included the NEBs described for Residential as well as a dollar-for-dollar benefit
adder for health and safety spending.

Evaluation Report 88

7.3 Economic Inputs for Cost Effectiveness Analysis
The Evaluators used the economic inputs provided by Avista for the cost benefit analysis. Avista
provided the Evaluators with avoided costs on the following basis:
n Hourly avoided commodity costs
n Modifications for the Clean Premium
n Avoided capacity costs
n Avoided transmission
n 10% Conservation Adder
n Line losses
n Discount rate (after tax Weighted Average Cost of Capital)
The values were aggregated to provide a single benefit multiplier on a Therms basis for every hour of
the year (8,760). Savings by measure were then parsed out to the following load shapes provided by
Avista:
n Residential Space Heating
n Residential Air Conditioning
n Residential Lighting
n Residential Refrigeration
n Residential Water Heating
n Residential Dishwasher
n Residential Washer/Dryer
n Residential Furnace Fan
n Residential Miscellaneous
The Evaluators in addition created a Residential Heat Pump load shape by weighting the relative
magnitude of cooling versus heating savings from a heat pump and assigning these to weight the
Residential Space Heating and Residential Air Conditioning load shapes.
7.4 Results
The tables below outline the results for each test, for both the programs and the portfolio as a whole.
Summations may differ by $1 due to rounding.
Table 7-4: Cost-Effectiveness Results by Sector
Sector TRC UCT RIM PCT
Residential 1.11 2.46 0.30 1.41
Low Income 0.27 0.10 0.08 N/A*
Total 0.98 1.71 0.28 N/A*
*Low Income is offered at no cost to participants; PCT is not calculable.

Evaluation Report 89

Table 7-5: Cost-Effectiveness Benefits by Sector
Program TRC Benefits UCT Benefits RIM Benefits PCT Benefits
Residential $3,852,633 $3,502,394 $3,502,394 $4,821,706
Low Income $168,428 $68,285 $68,285 $596,928
Total $4,021,061 $3,570,679 $3,570,679 $5,418,635

Table 7-6: Cost-Effectiveness Costs by Sector
Program TRC Costs UCT Costs RIM Costs PCT Costs
Residential $3,466,442 $1,426,403 $11,836,441 $3,422,171
Low Income $638,498 $662,514 $823,100 $523,327
Total $4,105,041 $2,089,019 $12,659,643 $3,945,498

Table 7-7: Cost-Effectiveness Net Benefits by Sector
Program TRC Net Benefits UCT Net Benefits RIM Net Benefits PCT Net Benefits
Residential $386,191 $2,075,991 ($8,334,047) $1,399,536
Low Income ($469,310) ($594,229) ($754,815) $73,601
Total ($83,220) $1,481,660 ($9,088,964) $1,473,137

2020 Idaho Annual Conservation Report Appendices
APPENDIX E – 2020 PROCESS EVALUATION REPORT

Appendix to the 2020 Annual
Conservation Report
PROCESS EVALUATION REPORT
April 16, 2021
Prepared for:
Avista
1411 E. Mission Avenue
Spokane, WA 99202

i
Table of Contents
Executive Summary .............................................................................................................................. 1
Summary of Milestones and Deliverables ............................................................................................. 1
Key Conclusions ..................................................................................................................................... 2
Nonresidential ................................................................................................................................. 2
Multifamily ...................................................................................................................................... 3
Residential ....................................................................................................................................... 4
Third-Party Implementer ................................................................................................................. 5
Recommendations ................................................................................................................................. 5
Nonresidential ................................................................................................................................. 5
Multifamily ...................................................................................................................................... 6
Residential ....................................................................................................................................... 6
Third-Party Implementer ................................................................................................................. 6
Introduction ......................................................................................................................................... 7
Program Descriptions ............................................................................................................................ 7
Methodology ......................................................................................................................................... 8
Program Administrator and Implementer Interviews ..................................................................... 8
Market Actor Ally Interviews ........................................................................................................... 9
Participant Surveys .......................................................................................................................... 1
Nonresidential Programs ...................................................................................................................... 2
Nonresidential Site Specific Findings ..................................................................................................... 2
Program Changes ............................................................................................................................ 2
Customer Awareness ...................................................................................................................... 2
Participation Motivations and Benefits ........................................................................................... 3
Customer Experience ...................................................................................................................... 4
Energy Efficiency Attitudes and Behaviors ...................................................................................... 8
Survey Respondent Profile .............................................................................................................. 9
Nonresidential Prescriptive Findings ..................................................................................................... 9
Program Changes ............................................................................................................................ 9
Customer Awareness .................................................................................................................... 10
Participation Motivations and Benefits ......................................................................................... 12

ii
Customer Experience .................................................................................................................... 13
Energy Efficiency Attitudes and Behaviors .................................................................................... 15
Survey Respondent Profiles ........................................................................................................... 16
Nonresidential Conclusions and Recommendations ........................................................................... 17
Nonresidential Conclusions ........................................................................................................... 17
Nonresidential Recommendations ................................................................................................ 18
Multifamily Programs ......................................................................................................................... 19
Multifamily Direct Install Program Findings ........................................................................................ 19
Stakeholder Interviews .................................................................................................................. 19
Participant Interviews ................................................................................................................... 21
Multifamily Market Transformation Program Findings ....................................................................... 24
Avista Staff Interview .................................................................................................................... 24
Home Builder Interviews ............................................................................................................... 26
Multifamily Conclusions and Recommendations ................................................................................ 27
Multifamily Conclusions ................................................................................................................ 27
Multifamily Recommendations ..................................................................................................... 28
Residential Programs .......................................................................................................................... 29
Residential Program Findings .............................................................................................................. 29
ENERGY STAR Homes .................................................................................................................... 29
Space Heat, Water Heat, Shell, and Windows Customer Survey Results ...................................... 30
Residential Conclusions and Recommendations ................................................................................. 38
Residential Conclusions ................................................................................................................. 38
Residential Recommendations ...................................................................................................... 39
Third-Party Implementer Program ...................................................................................................... 40
Third-Party Program Findings .............................................................................................................. 40
Program Changes .......................................................................................................................... 40
Marketing and Outreach ............................................................................................................... 40
Customer and Retailer Experiences .............................................................................................. 40
Challenges and Successes .............................................................................................................. 41
Third-Party Program Conclusions and Recommendations .................................................................. 42
Conclusions ................................................................................................................................... 42
Recommendations ........................................................................................................................ 42

iii
Low-Income Program .......................................................................................................................... 43

Figures
Figure 1. How Participants First Learned of Program ................................................................................... 3
Figure 2. How Participants Prefer to Learn of Programs and Offers ............................................................ 3
Figure 3. Site Specific Participant Motivation .............................................................................................. 4
Figure 4. Site Specific Participation Benefits ................................................................................................ 4
Figure 5. Respondents Satisfied with Site Specific Program Components ................................................... 6
Figure 6. Site Specific Program Successes .................................................................................................... 7
Figure 7. Important Criteria for Making Energy Efficiency Improvements ................................................... 8
Figure 8. Equipment Installed by Previous Avista Program Participants .................................................... 10
Figure 9. How Participants First Learned of Program ................................................................................. 11
Figure 10. How Participants Preferred to Learn of Programs and Offers ................................................... 11
Figure 11. Prescriptive Participant Motivation ........................................................................................... 12
Figure 12. Prescriptive Participation Benefits ............................................................................................ 13
Figure 13. Satisfaction with Prescriptive Program Components ................................................................ 14
Figure 14. Participation Challenges ............................................................................................................ 14
Figure 15. Important Criteria for Making Energy Efficiency Improvements ............................................... 16
Figure 16. PY 2020 Prescriptive Survey Sample Organization Types .......................................................... 17
Figure 17. Satisfaction with Program Measures, PY 2020 .......................................................................... 22
Figure 18. Awareness of Avista Energy Efficiency Programming ............................................................... 31
Figure 19. Preferred Method to Learn About Programming ...................................................................... 32
Figure 20. Motivation to Participate in Residential Programs ................................................................... 33
Figure 21. Benefits of Participation in Residential Programs ..................................................................... 34
Figure 22. Satisfaction with Residential Program Elements ....................................................................... 35
Figure 23. Satisfaction with Avista and Residential Programs Overall ....................................................... 35
Figure 24. Residential Program Participant Education by Program Year ................................................... 37
Figure 25. Residential Program Participant Income Ranges by Program Year ........................................... 38

Tables
Table 1. PY 2020 Process Evaluations ........................................................................................................... 1

iv
Table 2. PY 2020 Completed Milestones and Deliverables .......................................................................... 2
Table 3. PY 2020 Evaluated Program Descriptions ....................................................................................... 7
Table 4. PY 2020 Stakeholder Interviews .................................................................................................... 9
Table 5. PY 2020 Trade Ally Interviews ........................................................................................................ 9
Table 6. Residential Participant Survey Sample Frame, Target, and Completes by Program ...................... 1
Table 7. Nonresidential Participant Survey Sample Frame, Target, and Completes by Program ................ 1
Table 8. PY 2020 Participation Challenges ................................................................................................... 7
Table 9. Prescriptive Lighting Rebate Changes ............................................................................................. 9
Table 10. Aspects of Avista Prescriptive Programs Working Well .............................................................. 15
Table 11. Suggestions to Improve Avista Prescriptive Programs ............................................................... 15
Table 12. PY 2020 Target and Achieved New Homes – ENERGY STAR Homes ........................................... 30

1
Executive Summary
As part of the Avista 2020 demand-side management (DSM) portfolio evaluation, Cadmus conducted
process evaluation activities for program year (PY) 2020. The process evaluation focused on three
fundamental objectives:
• Assess participant and market actor program journey, including motivation for participation, barriers
to participation, and satisfaction
• Assess Avista and implementer staff experiences, including organizational structure,
communication, and program processes
• Document areas of success, challenges, and changes to the program
This report describes Cadmus’ data collection and process methods, presents analysis results,
summarizes findings, draws conclusions, and recommends possible improvements for the
Nonresidential, Multifamily, and Residential programs listed in Table 1.
Table 1. PY 2020 Process Evaluations
Program Idaho Washington
Nonresidential Programs
Site Specific P P
Prescriptive a P P
Multifamily Programs
Multifamily Direct Install (MFDI) P P
Multifamily Market Transformation (MFMT) P
Residential
ENERGY STAR® Homes P P
Simple Steps, Smart Savings P
HVAC P
Water Heat P
Shell and Windows P
a Includes Lighting, Food Service Equipment, Green Motors Rewind, Commercial HVAC, Insulation, HVAC Motor Controls,
Grocer, Fleet Heat, and AirGuardian Compressed Air.
Summary of Milestones and Deliverables
Cadmus conducted the evaluation by reviewing documents, surveying participants, and interviewing
program and implementation staff and contractors. Table 2 lists the completed process evaluation
activities.

2
Table 2. PY 2020 Completed Milestones and Deliverables
Milestones and Deliverables Completed
Document and Database Review P
Avista and Implementer Interviews P
Participant Surveys P
Trade Ally Interviews
Multifamily Property Managers P
Builders P

Key Conclusions
Nonresidential
• The impact of COVID-19 on project scope was minimal, but going forward there may be slight
reductions in the number or scope of energy efficiency projects due to budget or staff
constraints.
§ Ten of 13 Site Specific respondents and 88% (n=59) of Prescriptive participants said COVID-
19 did not create any obstacles to their 2020 project; most respondents who reported
obstacles said the obstacles were minor.
§ Four of 13 Site Specific respondents and 24% of Prescriptive respondents expected
reductions to budget or staff availability to support energy efficiency upgrades in PY 2021.
• Although contractors drive a significant portion of participation, continued Avista outreach
and messaging is important to support contractor sales.
§ Eight of 15 Site Specific participants and 70% (n=63) of Prescriptive participants reported
first hearing about the Avista program from a contractor, vendor, or retailer.
§ Twelve of 15 Site Specific participants and 55% (n=64) of Prescriptive participants thought
the best way to learn about rebates and incentives was through Avista emails or direct mail,
or communication from an Avista account representative.
• Despite some process issues in PY 2020, participants are satisfied with the application process
and the program overall.
§ Site Specific satisfaction was lowest for process-related aspects, including submitting the
rebate application (75% satisfied, n=15) and the time to process the application (87%
satisfied), but 100% of respondents were satisfied with the program overall.
§ Though 14% of Prescriptive participants mentioned the application paperwork was
burdensome, and 9% had some difficulty understanding requirements, 100% of participants
were satisfied with the program overall, and several respondents mentioned the easy and
fast process as an aspect of the program that worked well. Suggestions for process
improvements were related to potential enhancements (such as a searchable database of
eligible products, or chat feature for application support) rather than suggestions to correct
significant problems.

3
Multifamily
• MFDI: Collaborative relationships between Avista and the program implementer allowed new
delivery methods and future implementation techniques to be conceptualized quickly in
response to COVID-19. Open communication between the implementer and property
managers ensured the quick dissemination of new implementation information to
maintenance staff and tenants allowing the program to continue in PY 2020 despite
challenges due to the pandemic.
§ In response to continued COVID-19 restrictions, Avista and implementer staff developed a
contactless delivery method.
§ Due to low uptake in the first post-COVID-19 implementation phase, Avista and the
implementer adjusted the program to increase participation and measure installation by
limiting measures and working with property managers.
• MFDI: Property managers were satisfied with the program but suggested some tenants were
not satisfied with all the measures included in the program. Additionally, some tenants did
not install measures that were difficult to install or for which they did not have appropriate
tools.
§ Four of five property managers (4 of 5) were very satisfied with their MFDI program
experience overall.
§ Two property managers reported tenants were not satisfied with faucet aerators and
kitchen aerators due to low water pressure and appearance while three property managers
reported tenants were dissatisfied with showerheads due to restricted water flow.
§ One property manager reported that tenants’ participating in Phase 1 were not at all
satisfied with installation and educational materials provided by Avista.
• MFDI: The reliance of current data tracking on tenants’ willingness to return uninstalled or
unused equipment, together with low recovery rates, may be a contributing factor to minor
inconsistencies in measure-level data.
§ The drop-off delivery phases relied heavily on documentation filled out by maintenance
staff and tenants detailing the location and type and quantity of both installed and removed
measures. The implementer noted during the drop-off phases difficulty in tracking measure
installation locations in tenants’ units without the presence of a field technician to
document measure implementation.
• MFMT: Overall, the MFMT program was successful meeting the energy savings goal and
achieving high program satisfaction.
§ The program surpassed its electric savings goal of 476 MWh per year for PY 2020.
§ Builders have told Avista staff that they appreciate the incentive because it allows them
to install natural gas appliances which provides a competitive advantage, since they say
natural gas appliances are more attractive and can help increase the value of units.
§ The builder who completed a survey said they were very satisfied with the program and
planned to participate to a greater extent in 2021.

4
• The MFMT program has had success working with HVAC installers to help market the
program, though more can be done to increase marketing efforts and participation, as a
result.
§ Avista reported success working with HVAC installers to help promote the program. Staff
said this is a beneficial relationship as the HVAC installers are provided with additional work
and the program with more participants.
§ Avista reported that there used to be a flyer handed out as promotional material for the
program, though it is no longer used. Staff also said there is no current way in which they
monitor effectiveness of their marketing efforts and do not cross-promote the MFMT
program with other Avista programs.
Residential
• Like some utility energy efficiency programs, the ENERGY STAR Homes program was
negatively affected by the COVID-19 pandemic.
§ Avista achieved its target number of rebates for electric and electric/natural gas homes in
Idaho but otherwise fell short of other state-specific, fuel-specific, and overall goals. The
pandemic forced local manufactured homes dealers to close down, slowed the
ENERGY STAR certification process for newly constructed manufactured homes, and, as was
seen nationally, likely increased income insecurity among Avista’s target customer base.
• Contractors remain an important way to learn about the Residential programs but survey
respondents also indicated an increased interest in learning about the programs through
email from Avista.
§ The share of respondents who learned about Avista’s program through contractors
increased from 38% in PY 2019 to 52% in PY 2020. Additionally, 15% of PY 2020 respondents
said that contractors would be the best way for Avista to inform them about energy
efficiency, compared to 9% in PY 2019.
§ The most common way PY 2020 respondents would like for Avista to inform them about
energy efficiency is through email from Avista (37%). This percentage increased from 10% in
PY 2019 respondents, indicating more interest in this method of communication.
• Saving money or energy are key drivers of motivation to participate in the program.
§ Eighty-eight percent of PY 2020 respondents said that saving money or saving energy
motivated them to participate, and 96% of respondents listed energy savings, rebates, or
lower operating costs as a benefit of participating in the program.
• Participants remain highly satisfied with most aspects of the program.
§ More than 99% of respondents were very satisfied or somewhat satisfied with their
interactions with Avista staff and the program overall, as well as with the time it took to
receive the rebate, the application process, and their new energy-saving equipment.
• Information from equipment retailers or installers heavily influenced respondents’ decision to
participate.

5
§ Ninety-six percent of respondents rated this information as very important or somewhat
important, compared to information about the equipment from friends and relatives, which
67% of respondents rated as very important or somewhat important.
Third-Party Implementer
• The implementer responded to the COVID-19 pandemic thoughtfully, which enabled the
program to continue to perform well despite the circumstances until its termination in
September 2020.
§ The implementer let retailers permit or deny store visits from implementation field staff,
allowed field staff the flexibility to reschedule store visits, and conducted virtual store visits
to educate store associates about the program and products (such as LEDs) like it typically
would. Avista and the implementer also scaled back marketing and outreach efforts and
allowed each retail location to tailor marketing, including point-of-purchase materials
provided by the implementer, to their individual needs.
• Avista and the implementer faced uncertainty with the repeal of the Energy Independence
and Security Act, which led to the Simple Steps, Smart Savings program being implemented
differently in Washington.
§ The implementer offered rebates for clothes washers in Washington and for LEDs,
showerheads, and clothes washers in Idaho. Avista did not set goals for clothes washers in
Washington or for LEDs in Idaho.
• Avista observed unexpectedly low throughput for clothes washers, which the implementer
attributed to the challenge it faced when recruiting retail locations to participate.
§ Despite showing a willingness to participate, some retail locations for franchised and
individually owned stores like Ace Hardware could not offer program rebates because of a
lack of communication/direction from their corporate offices. Thus, fewer retailers offered
buy-downs for clothes washers, and fewer customers obtained clothes washer rebates.
Recommendations
Nonresidential
Nonresidential Recommendation 1: Develop tools to help participants sort through options and scope
eligible projects more quickly. For example, although the Avista website currently directs customers to
search for eligible lighting on the ENERGY STAR Product Finder database or DesignLights Consortium
websites, both of which have advanced search functionality, the search results can be overwhelming. A
resource such as an “Energy Efficiency Buying Guide” for specific products could help customers with
less technical background navigate their options or evaluate and understand proposals they receive
from contractors.
Nonresidential Recommendation 2: If not already doing so, use email blasts, bill inserts, and other
promotional tools that are direct from Avista to its customers, and use Avista branding to promote
Nonresidential programs and incentives. Participants were more likely to want communication directly

6
from Avista than through their contractor or vendor. These marketing efforts will enhance any
contractor and vendor marketing or advertising, and give sales representatives better credibility,
enabling them to make more sales through the program.
Multifamily
MFDI Recommendation 1: If the MFDI program continues to request tenants install measures directly,
consider offering an additional incentive such as an entry in a drawing for returning measures that are
not installed and for providing information on installed measures and their location.
MFDI Recommendation 2: If the MFDI program continues to operate using the drop-off delivery method
which requires tenants to install measures directly, continue focusing on simple and easy-to-install
measures like LEDs. Provide easy to follow installation instructions and remind tenants of the benefits of
installation in the program materials.
MFMT Recommendation 1: Develop marketing materials which can be used by HVAC contractors to
help promote the MFMT program. Due to the strengthening relationships between program staff and
HVAC contractors, promotional materials could be greatly beneficial to provide information about the
program in instances where the contractors may encounter potential participants.
MFMT Recommendation 2: Develop strategies to evaluate the effectiveness of marketing efforts and
cross-promotion with other Avista programs. In order to understand if marketing efforts are successful,
evaluation standards or goals should be set to better understand what the primary forces are that drive
participation to the program. Cross-promotion is also a simple and effective way to increase visibility of
the program and garner interest from potential participants.
Residential
Residential Recommendation 1: If not already doing so, use email blasts, bill inserts, and other
promotional tools that are direct from Avista to customers, with Avista branding, to promote Residential
programs and incentives. Although most participants learned about the programs from their contractor,
they were more likely to want communication directly from Avista than through their contractor or
vendor. These marketing efforts will enhance any contractor and vendor marketing or advertising, and
give them better credibility, enabling them to make more sales through the program.
Residential Recommendation 2: Focus program outreach on home comfort to encourage participants
since this was mentioned as a motivating factor for participation.
Third-Party Implementer
Because Simple Steps, Smart Savings discontinued in PY 2020, Cadmus does not have any
recommendations to make for the program.

7
Introduction
In program year (PY) 2020, Avista provided rebates and services to its Nonresidential and Residential
electric and natural gas customers throughout its Washington and Idaho service territories. The PY 2020
portfolio process evaluation sought to identify and document each program’s successes and challenges
by reviewing program materials; conducting interviews with program and implementation staff and
trade allies; and conducting surveys with Nonresidential and Residential program participants.
Program Descriptions
Table 3 provides a summary of programs included in Avista’s 2020 demand-side management (DSM)
portfolio’s evaluation.
Table 3. PY 2020 Evaluated Program Descriptions
Program Measure(s) Implementer Program Summary
Nonresidential
Site Specific Custom measure(s) Avista
Customers design energy efficiency projects
with documented energy savings and a
minimum 10-year measure life for a technical
review and possible rebates.
Prescriptive
Lighting, HVAC, variable
frequency drives (VFDs),
food service equipment,
grocer, and shell
Avista
Customers identify potential energy efficiency
projects, submit paperwork, and receive
Prescriptive rebates for projects.
Fleet Heat a Smart block heating system Avista
Electric customers receive a smart block
heating system to install on vehicles. The device
controls the water temperature in the block
and the air temperature outside the block.
HOTSTART can provide Installation help.
Green Motor Rewind Repair/rewind of motors
The Green Motors
Practices Group
(CMPG)
Electric customers who receive a green motor
rewind at a participating service receive a
rebate. The rebate applies to 15 hp to 5,000 hp
industrial motors.
AirGuardian a Compressed air leak
reduction device
Sight Energy
Group
Following a compressed air audit, electric
customers receive direct installation of a
compressed air leak reduction device.
Multifamily
Multifamily Direct
Install (MFDI)
Lighting, water-saving
measures, smart power
strips, VendingMisers
SBW Consulting
Direct installation of energy-saving measures,
on-site audits to identify opportunities and
interest in existing Avista programs, and follow-
up- visits to install supplemental lighting
measures.
Multifamily Market
Transformation
(MFMT)
Natural gas space and water
heat Avista
New multifamily development receives
incentives to install natural gas space and water
heating.

8
Program Measure(s) Implementer Program Summary
Residential
HVAC Space heat and smart
thermostats
Avista
Customers complete energy efficiency projects,
submit paperwork, and receive Prescriptive
rebates for projects.
Water Heat Water heat
Shell and Windows
Wall, floor, and attic
insulation; standard and
storm windows
ENERGY STAR Homes New ENERGY STAR
manufactured homes
Home dealers promote and sell ENERGY STAR-
certified manufactured homes to customers.
Residential Third-Party Implementer Programs
Simple Steps, Smart
Savings
LEDs, LED fixtures,
showerheads, clothes
washers
CLEAResult
Midstream program markdowns are offered for
certain products in retail stores; CLEAResult
receives monthly sales data and provides
program support through retailer visits.
a Cadmus planned to evaluate the Fleet Heat and AirGuardian programs, but there were no participants in 2020.

Methodology
This section describes the interview and survey methodology.
Program Administrator and Implementer Interviews
Cadmus conducted telephone interviews with the program staff and third-party implementers listed in
Table 4. Interviews focused on the following program topics:
• Program roles and responsibilities
• Program goals and objectives
• Program design and implementation
• Data tracking
• Program participation
• Marketing and outreach
• Program successes
• Market barriers
• Program impacts on the market
• Future program changes, including redesigns

9
Table 4. PY 2020 Stakeholder Interviews
Program Avista Staff Implementer Staff
Nonresidential Programs
Site Specific P N/A
Prescriptive a – N/A
Multifamily Programs
Multifamily Direct Install P P
Multifamily Market Transformation P N/A
Residential Programs
ENERGY STAR® Homes P
N/A HVAC –
Water Heat –
Shell and Windows –
Simple Steps, Smart Savings P P
a Includes Lighting, Food Service Equipment, Green Motors Rewind, Commercial HVAC,
Insulation, HVAC Motor Controls, Grocer, Fleet Heat, and AirGuardian Compressed Air.

Market Actor Ally Interviews
In PY 2020, Cadmus conducted telephone interviews with various market actors to assess levels of
program awareness, experiences, successes, and challenges. Avista provided contact lists for each
audience. Table 5 lists the program, audience, number of records provided by Avista, interview target,
and number of interviews. Cadmus was unable to meet the MFDI target despite multiple attempts to
contact every record and unable to meet the MFMT target due to a lower than expected population
size.
Table 5. PY 2020 Trade Ally Interviews
Program Audience Number of
Records Target Number of
Interviews
Multifamily Direct Install Participating Property managers 11 10 5
Multifamily Market Transformation Participating multifamily home builders 3 5 1

1
Participant Surveys
Cadmus completed 119 online surveys in PY 2020 with Residential program participants in Washington
and 81 online surveys in PY 2020 with Nonresidential program participants in Washington and Idaho.
Cadmus relied on site visits and telephone reminder calls to increase Nonresidential survey
participation. The participant survey guides gathered critical insights into participants’ program journey,
covering the following topics:
• Program awareness
• How respondents learned about
the program
• General program participation
• Reasons for participation
• Program benefits
• Program delivery experience
• Overall program satisfaction
• Satisfaction with Avista
• Current energy-efficient behaviors
and purchases
• Suggestions for program improvements
Residential Sampling
To prepare the participant contact list for the Residential survey, Cadmus removed duplicate records,
records with incorrect or missing email addresses, and records selected by the Residential impact
evaluator for impact analysis activities. After preparing the list, Cadmus randomly selected a sufficient
number of records proportionate to participation in each of the programs to include in the sample
frame. Cadmus sent an email invitation to participants included in the sample frame, followed by a
reminder email. Overall, Cadmus collected 119 responses for process evaluation purposes, as shown in
Table 6.
Table 6. Residential Participant Survey Sample Frame, Target, and Completes by Program
Program Total
Sample Frame a Target Complete
HVAC 906
70
64
Shell and Windows 388 48
Water Heating 106 7
Total 1,400 70 119
a Sample frame refers to the records selected for the survey contact list.

Nonresidential Sampling
To prepare the contact lists for each Nonresidential survey, Cadmus removed duplicate records and
records with incorrect or missing email addresses. Cadmus sent an email invitation to a census of all
participants in each program, followed by two reminder emails. To increase the number of survey
responses, the field engineers urged participants to complete the survey during virtual site visits if they
had not yet done so. Additionally, because of low initial participation in the Site Specific survey, Cadmus
made one telephone attempt to Site Specific participants to increase participation.

1
As shown in Table 7, Nonresidential participants completed 81 surveys in PY 2020.
Table 7. Nonresidential Participant Survey Sample Frame, Target, and Completes by Program
Program PY 2020 Total
Sample Frame a Target Completes
Nonresidential Site Specific
Electric 64
All eligible
14
Gas 5 1
Dual 4 -
Nonresidential Prescriptive
Lighting 750 30 to 40 63
Food Service Equipment 8
AMAP (between
10 and 20)
1
Green Motors Rewind 8 1
Commercial HVAC 7 -
Insulation 5 1
HVAC Motor Controls 1 -
Grocer 1 -
Fleet Heat 0 -
AirGuardian 0 -
Total 853 81
a Sample frame refers to the records available for surveys after removing duplicate records, records with only
installer contact information, and records with incomplete or bad contact information.

2
Nonresidential Programs
This section focuses on two Nonresidential programs: Site Specific and Prescriptive. The Site Specific
program provides incentives to customers who install custom energy efficiency projects, while the
Prescriptive program offers incentives for specific measures and services.
Nonresidential Site Specific Findings
This section describes the findings from 15 surveys completed with PY 2020 Site Specific participants.
Where meaningful, Cadmus compares PY 2019 results to PY 2020.
Program Changes
In PY 2020, Avista made one change to the Site Specific program, transitioning to the iEnergy data
tracking system. Avista now inputs all project level details, savings, payments, and sales after project
approval in both iEnergy and InfoCRM. Avista plans to use iEnergy as the primary analysis and storage
tool for all Site Specific projects moving forward and plans to transition to iEnergy fully by the end of
2021.
In addition to this program change, Avista specifically started targeting small businesses in rural service
territories where Avista programs are less active. Avista targets rural customers through direct mail
communication and informs them about the availability of energy efficiency and billing assistance
services, along with other Avista resources.
The program manager did not report problems or issues in implementing the Site Specific program,
other than customers were more focused on the financial viability of their businesses, due to COVID-19,
instead of energy efficiency.
Customer Awareness
The PY 2020 Site Specific survey indicated that the majority of participants (10 of 14) had previously
participated in an Avista energy efficiency program, which is consistent with PY 2019 results. As shown
in Figure 1, survey respondents first learned about the Site Specific program through a variety of
sources. The Avista website and contractors were both mentioned by 33% of PY 2020 respondents,
followed by equipment vendors or retailers. PY 2020 respondents were less likely to mention contact
with an Avista representative, word of mouth, or Avista direct marketing through emails or direct mail
than PY 2019 respondents.

3
Figure 1. How Participants First Learned of Program

Source: Site Specific survey questions C2: “How did you first hear about the Site Specific program?”
When asked how they preferred to learn of rebates and incentives, PY 2020 respondents were most
likely to select email, followed by their account executive. This is notably different from the actual
channel through which they learned about the program, as discussed above. As shown in Figure 2,
responses in PY 2020 closely matched responses in PY 2019.
Figure 2. How Participants Prefer to Learn of Programs and Offers
Source: Site Specific survey questions C3: “What is the best way for Avista to inform commercial customers
like you about their rebates and incentives for energy efficiency improvements?”
Participation Motivations and Benefits
Figure 3 shows the distribution of motivations identified by PY 2020 Site Specific survey respondents.
Participants were primarily driven by economic motivations including saving energy, taking advantage of
the Avista rebate, and saving money on utility bills. Increasing occupant comfort or improving the
appearance of a space and helping the environment were also frequently mentioned.

4
Figure 3. Site Specific Participant Motivation

Source: Site Specific survey question C4: “What motivated you to participate in the Site Specific Program?”
Multiple responses allowed.
Respondents’ perceived benefits aligned closely with their motivations, as shown in Figure 4. The
majority of respondents cited using less energy and saving money on utility bills as benefits, over half of
respondents noted better aesthetics from improved lighting, reduced maintenance costs, and the
rebate payment.
Figure 4. Site Specific Participation Benefits

Source: Site Specific survey question C5: “What would you say are the main benefits your
company has experienced as a result of participation?” Multiple responses allowed.
Customer Experience
Program Delivery
Most PY 2020 respondents (12 of 15) reported their contractor, vendor, or retailer was involved in the
design or implementation of their project. Six of those respondents reported their Avista account

5
executive was also involved. Two-thirds of those respondents (8 of 12) said the contractor, vendor, or
retailer also took the lead in preparing the application, and three of those respondents received a
discount from the contractor rather than receive the rebate directly.
Of the three who did not mention a contractor helping implement their project, one said their Avista
account representative was involved in the design of the project, and two respondents said they
completed the projects on their own.
Program Satisfaction
Figure 5 compares the percentage of PY 2020 respondents rating themselves very satisfied or somewhat
satisfied with different aspects of the Site Specific program with responses from PY 2019. Respondents
were less likely to be satisfied with several components in PY 2020 than in PY 2019, in particular with the
process to submit the application and the time it took to process it. In comments explaining their
satisfaction levels, one respondent had difficulty understanding the paperwork, another experienced
delays after their Avista representative retired, and a third reported this was their first energy efficiency
project, and they were unsure how to proceed.

6
Figure 5. Respondents Satisfied with Site Specific Program Components

Source: PY 2020 and 2019 Site Specific survey question E1: “In terms of the Site Specific program, how
satisfied were you with the following aspects? Please think about each item individually as you select your
answer.” Showing only respondents that indicated they were very satisfied or somewhat satisfied.
Program Challenges and Successes
As shown in Table 8, 10 of 15 PY 2020 respondents reported experiencing program participation
challenges. Another respondent reported having no challenges, while four others did not respond. In
PY 2020, the most common challenge reported by participants was just learning about the program.
Another two respondents reported internal challenges, related to getting approval to pursue the project
and for the upfront capital expense.

7
Table 8. PY 2020 Participation Challenges
Challenge PY 2020 (n=10)
Discovering the program 3
Getting internal interest and approval 2
Finding eligible equipment 1
Understanding what equipment is eligible 1
Slow communication from Avista 1
Delay in receiving the rebate check 1
Finding a contractor willing to work with the program 1
Source: Site Specific survey question E3: “What do so see as the biggest challenges to
participating in Avista's Site Specific program?”

Despite these issues, 11 PY 2020 respondents identified aspects of the program that they viewed as
working well. For example, one PY 2020 Site Specific participant said, “It is great that Avista is working
with business[es] and residents to reduce the electrical demand with new tech.” Figure 6 shows the full
break down of responses.
Figure 6. Site Specific Program Successes

Source: Site Specific survey question E5: “What would you say is working particularly
well with Avista’s Site Specific program?” Multiple responses allowed.
While seven PY 2020 respondents indicated they could not think of ways to improve the program, four
survey respondents provided recommendations:
• Quicker response and interim check-ins from Avista (2 respondents)
• Increase awareness (1 respondent)
• More information about process provided upon initiating a project, including information about
factors that might cause delays (1 respondent)
• Simplify the approval process (1 respondent)

8
Energy Efficiency Attitudes and Behaviors
Twelve of 15 PY 2020 respondents said the rebate provided by Avista was very important in their
decision to complete their project. Another two said it was somewhat important and one said the rebate
was not too important in their decision. All respondents said energy efficiency was very or somewhat
important when making capital upgrades or improvements.
As shown in Figure 7, respondents most commonly selected the project’s return on investment and
energy or operating costs as the most important criteria in their decision to complete their project,
followed closely by rebate or outside funding availability. These responses are similar to those from
PY 2019.
Figure 7. Important Criteria for Making Energy Efficiency Improvements

Source: Site Specific survey question F5: “Which of the following criteria are important in deciding whether
your company makes energy efficiency improvements?” Multiple responses allowed.
Since participating in the Site Specific program, four PY 2020 respondents purchased energy-efficient
equipment, and two adopted new energy-efficient protocols. Three respondents who mentioned
purchasing new equipment had invested in lighting upgrades, and one had purchased a new ventilation
system. One respondent with new protocols had changed their refrigeration setpoints, and the second
had adopted a checklist for turning off equipment.
In PY 2020, participants faced potential obstacles related to COVID-19 shut-downs. However, 10
respondents said there were no impacts to their project from the pandemic. One respondent said their
project scope was impacted because it was difficult to get supplies. Two respondents said their project
timeline was impacted, but the delays were minor. Going forward, nine respondents thought the COVID-
19 economic impacts would not affect their organization’s interest in or ability to complete other energy
efficiency projects, but three respondents thought there would be less budget available and one
respondent thought there would be less staff time available for such projects.

9
Survey Respondent Profile
The majority of PY 2020 Site Specific survey respondents (13 of 15) owned their facilities, while two
leased. Employee numbers at each facility ranged from six to 330, with an average of 80 per facility
(n=11). Eleven of 15 facilities used gas for heating, and four used electricity. The PY 2020 sample
included a range of sectors, including industrial, commercial, public, and nonprofits.
Nonresidential Prescriptive Findings
This section describes findings from 65 online surveys completed with Prescriptive participants for
PY 2020. Because 63 of the 65 respondents installed lighting projects, the results primarily represent
lighting participants rather than non-lighting participants. Because the PY 2020 sample did not reflect
the same mix of lighting and non-lighting as the PY 2019 survey, Cadmus did not compare PY 2020
results to prior years.
Program Changes
As shown in Table 9, Avista made several changes to the lighting program in PY 2020; the PY 2020 Avista
Washington Annual Conservation Plan, Appendix A, page 12, compares the PY 2019 and PY 2020
Prescriptive lighting rebates.
Table 9. Prescriptive Lighting Rebate Changes
Change PY19 PY20
Fluorescent Tubular Lamps
T5HO four-foot TLED $15 $12.50
T8 four-foot TLED $6.50 $6.50
U-bend LED $8 $10.00
T8 eight-foot TLED $13 $11.50
Fluorescent Fixtures
2, 3, or 4-lamp T12/T8 fixture to LED qualified 2x4 fixture $40 $45
2-lamp T12/T8 fixture to LED qualified 2x2 fixture $30 $20
250-watt HID fixture to ≤140-watt LED fixture or lamp $155 $125
1,000-watt HID fixture to ≤400-watt LED fixture or lamp $205 $185
1,000-watt HID fixture to ≤400-watt LED fixture or lamp $460 $270
2-watt to 9-watt MR16 lamp $10 $5.50
Occupancy sensors with built-in relays $40 $25
70-watt to 89-watt HID fixture to ≤25-watt LED fixture, retrofit kit, or lamp $60 $65
90-watt to 100-watt HID fixture to ≤30-watt LED fixture, retrofit kit, or lamp $80 $85
150-watt HID fixture to ≤50-watt LED fixture, retrofit kit, or lamp $125 $130
175-watt HID fixture to ≤100-watt LED fixture, retrofit kit, or lamp $130 $130
250-watt HID fixture to ≤140-watt LED fixture, retrofit kit, or lamp $140 $160
320-watt HID fixture to ≤160-watt LED fixture, retrofit kit, or lamp $180 $195
400-watt HID fixture to ≤175-watt LED fixture, retrofit kit, or lamp $255 $280
750-watt HID fixture to ≤300-watt LED fixture, retrofit kit, or lamp $450 $490
1,000-watt HID fixture to ≤400-watt LED fixture, retrofit kit, or lamp $610 $610
175-watt code HID fixture to ≤100-watt LED fixture $130 $130
250-watt code HID fixture to ≤140-watt LED fixture $140 $160
320-watt and 400-watt code HID fixture to ≤160-watt LED fixture $250 $195

10
Change PY19 PY20
T12 to LED sign lighting $17/sq ft $22/sq ft
LLLC Fixture - $35

Customer Awareness
Just over one-half of PY 2020 survey respondents (50%, n=60) previously participated in an Avista
business energy efficiency program, for a previous participation rate about equal to the PY 2019
program year (56%, n=75). Of the 31 respondents who participated previously, 24 provided details
about programs in which they participated. As shown in Figure 8, most reported installing lighting, with
five respondents reporting they participated multiple times in previous years, and one respondent
reporting having previously upgraded a furnace.
Figure 8. Equipment Installed by Previous Avista Program Participants
Source: Prescriptive survey question C1.2: “What other Avista Nonresidential energy efficiency
programs has your business participated in?”
In PY 2020, respondents were most likely to say they first learned about the program from a contractor
(44%, n=63), followed by a vendor or retailer (25%). Figure 9 shows the frequency that each information
channel was mentioned.

11
Figure 9. How Participants First Learned of Program

Source: Prescriptive survey questions C2: “How did you first hear about the program?”
Percentages may not total 100% due to rounding.
Respondents most commonly said that the best way for Avista to inform them of rebate programs was
by an email from Avista (31%) or through a bill insert (19%). Figure 10 shows the distribution of
preferred methods across all respondents in PY 2020.
Figure 10. How Participants Preferred to Learn of Programs and Offers

Source: Prescriptive survey question C3: “What is the best way for Avista to inform commercial customers like
you about their rebates and incentives for energy efficiency improvements?”

12
Participation Motivations and Benefits
In PY 2020, respondents most commonly reported saving money and taking advantage of the rebate as
participation motivations, followed closely by saving energy. This is similar to the PY 2019 result, except
that receiving the rebate was not a survey choice in PY 2019. As shown in Figure 11, PY 2020
respondents identified several other motivations, but were less likely than PY 2019 respondents to
mention wanting to increase occupant comfort, or that they were responding to a contractor or vendor
recommendation. This difference is likely attributable to the lower percentage of non-lighting projects in
the sample.
Figure 11. Prescriptive Participant Motivation

Source: Prescriptive survey question C4: “What motivated you to participate in the program?”
Multiple responses accepted.
As shown in Figure 12, PY 2020 participants’ main reported benefits somewhat reflected their
motivations, with saving money on utility bills being the most commonly mentioned benefit (67%,
n=63), and using less energy being the third most common benefit (55%). However, while receiving the
rebate was a commonly reported motivation, it was mentioned as a benefit less frequently than better
aesthetics.

13
Figure 12. Prescriptive Participation Benefits

Source: Prescriptive survey question C5: “What would you say are the main benefits your company
has experienced as a result of participation?” Multiple responses accepted.
Customer Experience
Program Delivery
Although the majority of PY 2020 respondents reported a contractor or vendor (71%, n=66) or an Avista
account executive (14%) was involved in a project’s design or implementation, half of respondents (50%)
took the lead on their own applications. These results are similar to PY 2019.
Most PY 2020 respondents (79%; n=47) also received their rebate checks directly, rather than as instant
discounts from a contractor or vendor. Of nine PY 2020 respondents who did receive an instant
discount, three said they chose the instant discount because it was easier for them, allowing them to
complete projects with less cash outlay or to process less paperwork. Three other respondents chose
the instant discount to reduce the amount they had to cover upfront. Another respondent wanted to
avoid being responsible for any errors on the application and the last respondent wanted to reward the
contractor for providing good service.
Program Satisfaction
PY 2020 respondents were nearly all somewhat satisfied or very satisfied with all aspects of the Avista
program, as shown in Figure 13. Two respondents reported being not too satisfied with aspects of the
program. One of these explained that the contractor had been difficult to work with and the process
difficult to understand. The other respondent did not provide additional detail on their rating.

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Figure 13. Satisfaction with Prescriptive Program Components

Source: Prescriptive survey questions H1: “In terms of the [PROGRAM], how satisfied were you with
the following aspects? Please think about each item individually as you select your answer.”
Program Challenges and Successes
When asked what challenges the program presented, 35% provided no response and 27% took the
opportunity to report there were no problems, or to compliment the program. Excessive paperwork was
the most common challenge reported, mentioned by 14% of respondents.
Figure 14. Participation Challenges

Source: Prescriptive survey question H9: “What do so see as the biggest challenges to
participating in Avista’s [PROGRAM_NAME]?”

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Respondents called out several program aspects that they viewed as working well. As shown in Table 10,
respondents most commonly mentioned the fast or easy application process, followed by the
opportunity to save energy and money on utility bills. Several respondents who mentioned the fast
process also mentioned good customer support. For example, one respondent stated, “Great customer
service and fast rebate turn around.”
Table 10. Aspects of Avista Prescriptive Programs Working Well
Program Aspects Number of Respondents
Easy/fast process 11
Saving energy and money on utility bills 10
Overall program works well 7
Access to better lighting 5
Good customer service 5
Rebate amount 5
Contractor support 2
Access to quality products 1
Source: Prescriptive survey question H11: “What would you say is working particularly well with Avista’s program?”
(Multiple responses allowed; n=39)

As shown in Table 11, 16 participants provided suggestions for program improvements. The most
common suggestion was to provide more information about program requirements, or better customer
support. For example, one respondent suggested having a chat function for customer support, instead
of just phone and email. Another person requested a searchable database for eligible products.
Table 11. Suggestions to Improve Avista Prescriptive Programs
Suggestion Number of
Respondents
More information/better customer support 7
More marketing 5
Bigger rebates 3
Outreach to contractors 1
Source: Prescriptive survey question H10: “What recommendations, if any, would you make to
improve the program?” (n=16)
Energy Efficiency Attitudes and Behaviors
All PY 2020 respondents (100%, n=63) considered energy efficiency either somewhat or very important
to their organization when making capital upgrades or improvements. As shown in Figure 15,
respondents cited energy or operating costs (74%) as the most important criteria in their decisions to
undertake energy efficiency improvements, followed by initial cost of equipment (57%) and
maintenance costs (52%).

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Figure 15. Important Criteria for Making Energy Efficiency Improvements

Source: Prescriptive survey question I4: “Which of the following criteria are important in deciding whether
your company makes energy efficiency improvements?” Multiple responses allowed.
The survey asked respondents how the COVID-19 pandemic affected their project. The majority of
respondents, 88% (n=59) reported there was no impact, while 8% said the pandemic impacted the
project timeline, and 3% said both the timeline and the scope were impacted. Those who reported
impacts described them as due to the following factors (some respondents mentioned multiple factors):
• Suspension of operations/shutdown (3 respondents)
• Shortage of materials (2 respondents)
• Additional safety requirements for contractors (1 respondent)
• Employees staying home due to illness (1 respondent)
• Short delay receiving the rebate (1 respondent)
When asked how their interest in energy efficiency projects will be impacted by COVID-19 going
forward, 64% (n=55) said they expected no change relative to before the pandemic. The second most
common response was that respondents expected to have less budget available to pay for projects
(24%). However, 11% expected their organization to have more interest in cost-cutting projects such as
energy efficiency upgrades.
Survey Respondent Profiles
Most PY 2020 survey respondents reported natural gas as their primary heating fuel (69%; n=54); 76%
owned their facilities. Most respondents did not provide their facilities’ square footage, but of the 28
who did respond, sizes ranged from 2,000 to 200,000 square feet, with an average of 25,500 square feet
(n=28). The number of people employed at the project site ranged from 0 to 200, with an average of 28
employees (n=44). Figure 16 shows respondents’ organization types. Retail trade, followed by
manufacturing were the most common types.
n=61

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Figure 16. PY 2020 Prescriptive Survey Sample Organization Types

Source: Prescriptive survey question J1: “What is the primary industry of your organization?”

Nonresidential Conclusions and Recommendations
Conclusions and recommendations for the Nonresidential programs are presented in this section.
Nonresidential Conclusions
• The impact of COVID-19 on project scope was minimal, but going forward there may be slight
reductions in the number or scope of energy efficiency projects due to budget or staff
constraints.
§ Ten of 13 Site Specific respondents and 88% (n=59) of Prescriptive participants said COVID-
19 did not create any obstacles to their 2020 project; most respondents who reported
obstacles said the obstacles were minor.
§ Four of 13 Site Specific respondents and 24% of Prescriptive respondents expected
reductions to budget or staff availability to support energy efficiency upgrades in PY 2021.
• Although contractors drive a significant portion of participation, continued Avista outreach
and messaging is important to support contractor sales.
§ Eight of 15 Site Specific participants and 70% (n=63) of Prescriptive participants reported
first hearing about the Avista program from a contractor, vendor, or retailer.

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§ Twelve of 15 Site Specific participants and 55% (n=64) of Prescriptive participants thought
the best way to learn about rebates and incentives was through Avista emails or direct mail,
or communication from an Avista account representative.
• Despite some process issues in PY 2020, participants are satisfied with the application process
and the program overall.
§ Site Specific satisfaction was lowest for process-related aspects, including submitting the
rebate application (75% satisfied, n=15) and the time to process the application (87%
satisfied), but 100% of respondents were satisfied with the program overall.
§ Though 14% of Prescriptive participants mentioned the application paperwork was
burdensome, and 9% had some difficulty understanding requirements, 100% of participants
were satisfied with the program overall, and several respondents mentioned the easy and
fast process as an aspect of the program that worked well. Suggestions for process
improvements were related to potential enhancements (such as a searchable database of
eligible products, or chat feature for application support) rather than suggestions to correct
significant problems.
Nonresidential Recommendations
Nonresidential Recommendation 1: Develop tools to help participants sort through options and scope
eligible projects more quickly. For example, although the Avista website currently directs customers to
search for eligible lighting on the ENERGY STAR Product Finder database or DesignLights Consortium
websites, both of which have advanced search functionality, the search results can be overwhelming. A
resource such as an “Energy Efficiency Buying Guide” for specific products could help customers with
less technical background navigate their options or evaluate and understand proposals they receive
from contractors.
Nonresidential Recommendation 2: If not already doing so, use email blasts, bill inserts, and other
promotional tools that are direct from Avista to its customers, and use Avista branding to promote
Nonresidential programs and incentives. Participants were more likely to want communication directly
from Avista than through their contractor or vendor. These marketing efforts will enhance any
contractor and vendor marketing or advertising, and give sales representatives better credibility,
enabling them to make more sales through the program.

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Multifamily Programs
This section focuses on two Multifamily programs: Multifamily Direct Install (MFDI) and Multifamily
Market Transformation (MFMT). The MFDI program provides energy efficiency measures through a
direct-install phase and an optional supplemental phase; however, due to the COVID-19 pandemic,
Avista adjusted the program to a contactless delivery method midway through the year. The MFMT
program provides incentives for natural gas space and water heating equipment in new multifamily
developments.
Multifamily Direct Install Program Findings
The MFDI program typically consists of a direct-install phase that includes energy efficiency measures,
such as faucet aerators, kitchen aerators, LEDs, Tier I smart power strips, and VendingMisers.1 However,
due to COVID-19, Avista changed the delivery mechanism midyear to a contactless model which is
addressed in the next section.
An optional supplemental lighting phase typically follows, in which SBW Consulting offers lighting
upgrades in facilities’ common areas. Various lighting contractors perform an audit and provide SBW
with the best lighting retrofit options.
Cadmus conducted stakeholder interviews with Avista program and implementation staff, in addition to
five phone interviews with multifamily property managers who participated in the program in PY 2020.
Stakeholder Interviews
In January 2021, Cadmus interviewed Avista and program implementation staff about the MFDI
program. Consistent with previous years, the program implementer, SBW, is responsible for recruiting
and treating multifamily units and due to a robust participant pipeline no additional marketing was
needed in 2020. The implementer said that, due to COVID-19 and the temporary suspension of the
program, multiple properties were unable to participate. Irrespective of the pandemic and program
suspension, the implementer noted participation interest from qualifying properties was high.
Program Implementation
Direct Install. As a result of the COVID-19 shutdown, Avista temporarily suspended the program in mid-
March, as implementation staff were barred from entering tenant units. The program remained in a
sustained critical phase through July 2020. In response to continued COVID-19 restrictions, Avista and
implementer staff developed two drop-off pilot concepts. The rest of the report refers to the drop-off
pilot concepts as Phase 1 and Phase 2.

1 Devices that can be installed on beverage vending machines that use a motion sensor to determine when the
machine should be powered on and off. The device measures ambient room temperatures every few hours to
determine how much power to utilize.

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Phase 1 targeted smaller multifamily properties in Avista’s service territories. SBW provided property
managers with drop-off kits that included LEDs, faucet aerators, kitchen aerators, showerheads,
installation instructions and notices, a return equipment bag, and additional documentation explaining
the program. SBW instructed property staff to leave drop-off kits outside of tenants’ units and ask
tenants to install the measures themselves. Avista and the implementer reported low uptake and
difficulty recovering unused or uninstalled measures.
Phase 2 was a hybrid model that targeted three additional facilities. Avista provided property managers
with drop-off kits that included LEDs, faucet aerators, kitchen aerators, installation instructions and
notices, and documentation explaining the program. Property managers could install measures in
tenants’ units using facility staff or instruct tenants to install the drop-off kit measures themselves. The
implementer reported greater uptake during Phase 2 and attributed this to better communication with
facility staff. Avista changed program documentation in drop-off kits to emphasize item exchange, which
led to an increase in recovery of unused or uninstalled measures.
Supplemental Lighting. In addition to the direct-install phases, Avista and the implementer offered a
supplemental lighting phase, during which installers, hired by the implementer, revisited multifamily
properties to install additional common area lighting for property managers expressing interest.
Eligibility requirements included the following: the property must be an Avista electric customer, lighting
must be 24/7, and supplemental lighting must be deemed cost-effective. Pre-COVID-19, while
completing the direct install of measures, the implementer identified and reviewed opportunities for
common area lighting with Avista and participating properties, all subject to Avista’s approval. If
approved by Avista, a subcontractor later returned to the property to install the lighting.
In response to COVID-19, Avista temporarily suspended the supplemental lighting phase. Avista
completed eligible projects with supplemental exterior lighting and did not pursue any mixed interior
and exterior supplemental lighting projects. Avista modified eligibility for the supplemental lighting
phase to only include exterior common area lighting projects in 2021.
Communication. Throughout PY 2020, Avista and the implementer met monthly to discuss program
progress, address program issues, and conceptualize new delivery methods in response to COVID-19.
Avista noted there was an open line of communication with the implementer and both called
impromptu meetings as necessary. The implementer expressed gratitude for Avista’s flexibility during
the pandemic and noted a strong sense of partnership.
Data tracking. The drop-off phases posed an issue for Avista and implementer staff, as implementer
staff were no longer able to verify where or if measures were installed. Avista and the implementer
relied on tenants to return unused or uninstalled measures to track installation. Avista reported high
variability across participating properties in terms of returned measures. The implementer reported
difficulty in collecting detailed measure level data and suggested low measure return rates exacerbated
this issue.
Tenant installation. Avista mentioned that some tenants participating in Phase 1 and Phase 2 of the
drop-off pilot were unable to, or did not have the necessary equipment to, properly install measures.

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Aerators and showerheads saw the lowest uptake in PY 2020 and Avista attributed this to lack of
installation knowledge and necessary tools. Due to COVID-19 restrictions, implementer staff were
unable to conduct quality control checks to determine whether measures were installed correctly.
Future Plans. Avista and the implementer are considering an exchange-based delivery system for
PY 2021. The exchange pilot model encourages participating tenants to return uninstalled or unused
equipment and allows the implementer to track measure-level details with greater accuracy. The
exchange pilot will offer LEDs only, and implementer staff will pre-audit the property to gauge
compatible offerings. A facility manager or SBW staff member will be on site with an assortment of
lighting products and ask tenants to remove outdated bulbs from their units and deliver them to the
exchange. Upon exchange, tenants will receive LEDs compatible with their pre-existing fixtures. The
process allows for social distancing, proof of exchange, enhanced data tracking, and enables staff to give
tenants installation and educational guidance.
In PY 2021, showerheads will no longer be offered through the program. Avista is planning to suspend
the offering of faucet and kitchen aerators in PY 2021, but will consider re-integrating these measures
into the program if the pre-COVID-19 delivery model is reinstated.
Participant Interviews
In February and March of 2021, Cadmus interviewed five multifamily property managers who
participated in the MFDI program to understand their awareness of and satisfaction with the program,
identify the program’s challenges and successes, and assess its influence on other energy-saving
behaviors. The five property managers had not participated in the program in the past and attributed
this to lack of awareness. Of the five property managers who participated, two were through the initial
direct install phase, one was through Phase 1, and two were through Phase 2. Participating multifamily
residences could have the following measures installed:
• Faucet aerators
• LEDs (indoor)
• Kitchen aerators
• Showerheads
Consistent with PY 2019, the implementer no longer offered the following in PY 2020: water heater
temperature assessments, water heater blanket installs, water heater pipe wrap installs, shower valves
with automatic temperature shut-offs, or smart plugs. Avista reported VendingMisers and smart power
strips were offered where possible in the initial direct install phase pre-COVID-19, but both measures
were not included in Phase 1 or Phase 2.
Awareness and Motivation
Two property managers said they learned about the program from the implementer, two learned about
the program through fliers mailed by Avista, and one heard of the program through word of mouth.

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With regards to energy savings, three property managers said Avista or the implementer usually
informed them of ways to save in their buildings, one property manager said he uses past experiences to
inform them of ways to save energy, and the remaining property manager reported hearing little about
energy-saving opportunities as a result of being recently hired. These results were similar to PY 2019
findings.
Measure Satisfaction
In terms of tenant satisfaction, all property managers reported that their tenants were very satisfied
with the LEDs, as shown in Figure 17. One property manager reported not receiving tenant feedback
about satisfaction with installed measures. Tenant satisfaction with LEDs was consistent across the 2019
and 2020 program years. Unlike PY 2019, when most tenants were very satisfied with program
measures, in PY 2020, multiple tenants expressed dissatisfaction with the faucet aerators, kitchen
aerators, and showerheads.
Two property managers reported tenants were a little satisfied with faucet aerators and kitchen
aerators due to low water pressure and the aesthetically displeasing appearance. Three property
managers reported tenants were dissatisfied with showerheads due to restricted water flow, of which
two were a little satisfied and one was not at all satisfied. One property manager suggested that tenants
with no obligation to pay their water bill were uninterested in installing aerators or showerheads, and
instead preferred installing LEDs.
Figure 17. Satisfaction with Program Measures, PY 2020

Source: MFDI Program Participant Interview, Question C1:
“In your perspective (given your interactions with them), are your tenants very satisfied,
somewhat satisfied, a little satisfied, or not at all satisfied with their new…?”
Of the four PY 2020 property managers who participated in the supplemental lighting phase, all were
very satisfied with the new outdoor lighting. When asked about tenant feedback, three did not report
tenant issues or complaints. One reported that tenants provided positive feedback, such as being able to
see clearly at night.

23
Program Delivery
Cadmus asked property managers whether implementer staff, maintenance staff, or tenants installed
program measures. Two property managers who participated in the program pre-COVID-19 reported
SBW staff installed energy efficiency measures while being accompanied by maintenance staff. In
addition, two property managers reported maintenance staff installed measures. Both property
managers who participated in Phase 2 were very satisfied with the instructional materials provided by
SBW and reported no issues during the installation process. The property manager who participated in
Phase 1 reported tenants were uninterested in the program and not at all satisfied with the installation
instructions and educational material. This property manager said, “Because they’re renters, many of
the tenants didn’t care as much to install the measures. The educational materials and installation
instructions didn’t provide enough information to show tenants how these measures will save them
money and energy. I talked with one of the tenants at C*** Apartments, and he commented on how he
didn’t look through the bag that Avista provided. He left the drop-off kit in the closet.”
All three property managers who participated in either Phase 1 or 2 were very satisfied with the unused
or uninstalled equipment pick-up process.
Program Satisfaction
Consistent with PY 2019, most property managers (4 of 5) were very satisfied with their MFDI program
experience overall. One property manager was a little satisfied with the additional time that resulted
from tenant installation and suggested changing program delivery to maintenance staff installation only.
Four property managers who received supplemental lighting addressed questions about their
satisfaction with this program phase. All supplemental lighting participants reported being very satisfied
with the contractors’ professionalism, the time required to complete the installations, the quality of
outdoor lighting, and the scheduling process.
Participation Barriers
As in previous years, property managers did not report any barriers to program participation in the
direct install portion of the program.
In PY 2020, one property manager was unaware of the supplemental lighting phase and expressed
interest in pursuing a common area lighting retrofit. The property manager reported the implementer
reached out to the property’s improvement manager, who never relayed the information, and
recommended enhanced communication. This was consistent with PY 2019 feedback.
Program Influence
Cadmus asked property managers if they took energy-saving actions after participating in the MFDI
program, and, if so, how important the program was in influencing that behavior. Two property
managers installed additional energy-saving items. One of these property managers reported that the
program was somewhat important in influencing this decision while the other property manager would

24
have installed the measures anyway and considered the program’s influence not at all important. 2 Four
respondents were very likely to seek out energy efficiency measures, while one said they were
somewhat likely to do so.3
Multifamily Market Transformation Program Findings
The MFMT program provides incentives for natural gas space and water heating equipment in new
multifamily developments in Idaho. Builders are eligible to receive incentives of up to $3,000 per unit to
pay for the incremental cost of installing natural gas heat and/or water heat in new multifamily
developments of five or more units per building. Water heating applications can either be individual
natural gas hot water heaters in each unit or a central natural gas hot water system. Participants are
required to sign a contract prior to construction and complete their project within two years. Cadmus
conducted interviews with Avista staff and home builders as part of the MFMT program evaluation in
PY 2020.
Avista Staff Interview
Program Changes
Avista discontinued the Washington portion of the program at the end of PY 2019 and reported that all
Washington projects were required to finish by the end of the year. Avista also reported that the
incentive for installing equipment through the program decreased from $3,500 to $3,000 at the
beginning of PY 2020. If a project was contracted before the start of PY 2020, participants could receive
$3,500 if they completed and verified their installation within two years. Avista does not expect
significant changes for PY 2021.
Program Goals and Delivery
The program set and achieved an electric savings goal of 476 MWh per year for PY 2020. Avista tracks
certain targets related to the number of projects completed through the program, current year-to-date
pace, and kWh savings. Avista did not see a large impact from COVID-19 on program delivery aside from
initial challenges with conducting final inspections on projects near the beginning of the pandemic.
Avista also noted that program participants were in a slower time of the year when these challenges
arose, so it did not create any long-term challenges for the program.
Aside from processing the rebate, Avista takes the role of confirming and verifying installations of
equipment in new developments. While participants have up to two years after signing their contract to
install their equipment, Avista confirmed the incentive is typically paid to the participant within a week
of the verification. Avista also said that data tracking is different for the MFMT program than other
Avista programs because the data are considered Site Specific and therefore project tracking is more

2 Using the following scale: not at all important, a little important, somewhat important, very important.
3 Using the following scale: not at all likely, a little likely, somewhat likely, very likely.

25
customized. Avista did not track any new data in PY 2020 that were not already being tracked and
indicated the current data tracking and reporting systems and processes meet their needs.
Marketing and Outreach
The program is marketed primarily by Avista interacting directly with multifamily developers and
builders—a strategy that Avista indicated has succeeded. Avista also lists the incentive for the program
on their website. While the program previously had an informational flyer which could be distributed,
staff noted this is no longer in use. Avista said there are currently no efforts to increase customer
participation in hard-to-reach areas, but did note that a “gas growth team” was recently established in
Idaho and that increasing participation in hard-to-reach areas may be a goal of the initiative.
Avista said that staff currently does not have a good way to monitor or assess marketing and outreach
efforts for their effectiveness, but noted that the marketing department tracks activity on their website.
Staff also indicated there are no current cross-promotional efforts for the MFMT program with other
Avista programs. They emphasized that they have had success marketing the program through HVAC
installers and would recommend targeting them more to enhance program marketing. While these
HVAC installers do not act officially as trade allies for the program, some can promote the program if
they have a good understanding and relationship with the program. Avista did not report any effects
from COVID-19 related shutdowns on the program marketing efforts.
Stakeholder and Customer Experience
Avista reported good relationships with other groups involved in working with the MFMT program.
These groups include builders, developers, HVAC installers, and development CPCs. Avista noted a good
level of communication between groups, which allows program efforts to be handled relatively easily.
Avista faces two main barriers to participation among builders in the area. The first is that some
regulations in Washington affect builders who operate there and in Idaho as well and that they need to
limit their inventory of developments with natural gas appliances as a result. The second barrier is the
price point of equipment compared to the incentive they offer. Avista said that the current incentive
level, $3,000 per unit, continued to generate interest but explained if the incentive decreases further,
some builders said the incentive will not offset the cost because installation is too expensive. To combat
these barriers, Avista continues to work with builders and developers to bring natural gas into their
developments in Idaho, despite the Washington regulations and plans to keep incentives at their current
level.
Avista reported positive feedback from customers regarding their participation in the program. Staff
noted that builders appreciate the incentive that allows them to install these natural gas appliances.
They also said that the appliances can add value to the developments, especially in times when there is
more competition for multifamily living spaces, as the natural gas appliances are more attractive and
can help increase the value of units.

26
Home Builder Interviews
Cadmus interviewed one home builder who participated in the program in 2020 to assess their reasons
for and obstacles to participation as well as measuring their overall satisfaction and experience with the
program. Cadmus attempted to interview two other participating home builders but were unsuccessful
after multiple attempts.
Program Experience
The participating home builder reported learning about Avista’s MFMT program from family members
who had previously worked for Avista and had connections to program staff. This builder said their main
motivation for participating in the program was to help offset costs of heating in their buildings. They
noted they were originally planning to install electric cadet heaters, but the incentive from the program
made natural gas heaters more affordable and allowed them to provide a better product to their
customers. This home builder claimed it was very easy4 to qualify a new building for the incentive
offered by the program.
When asked about their relationship with Avista, the home builder said it was “fantastic” and added
“Avista is above and beyond the most flexible company to work with in our local area.” This builder did
not report experiencing any barriers to participation but noted there are occasional obstacles with other
service providers for their buildings, though Avista has been able to assist them in those instances. The
builder said they were very satisfied5 with the MFMT program overall and planned to participate to a
greater extent in 2021 as they have additional projects planned and will use the program.
Program Impact
The home builder was also asked what kind of impact the program has had on their operations. This
builder reported that the program has greatly influenced the way they build multifamily housing
because they primarily install natural gas heaters rather than electric cadet heaters. They also said the
incentive is what makes this possible and would not complete any natural gas space heating projects
without the incentive due to the associated costs. The home builder said in the projects they have
completed through the program; they have only installed natural gas space heating and have not
installed natural gas water heating. They said this was because the venting system in these buildings
would have to be re-designed in order to install natural gas water heating. Although, they would have
liked to install natural gas water heating they felt it was not worth the effort. The home builder did not
report any effects on their participation in the program due to COVID-19 related shutdowns and/or stay-
at-home orders. This builder also noted that the program has had a positive effect on their business
because they are able to provide a different product than other companies in their area. They also said it
is more attractive to their tenants because the natural gas appliances help keep utility costs lower than
if it were electric heating.

4 Using the following scale: not at all easy, not too easy, somewhat easy, very easy.
5 Using the following scale: not at all satisfied, a little satisfied, somewhat satisfied, very satisfied.

27
Builder Profile
Cadmus interviewed the owner of a home building company who said they primarily do field work and
ensure the installations go as planned, with respect to the MFMT program. They said their company has
been building multifamily housing in Idaho for 6 years and first participated in the program in 2019.
They indicated they did not build any multifamily housing in Avista’s service territory that did not
participate in the program in 2020.
Multifamily Conclusions and Recommendations
Conclusions and recommendations for the Multifamily programs are presented in this section.
Multifamily Conclusions
• MFDI: Collaborative relationships between Avista and the program implementer allowed new
delivery methods and future implementation techniques to be conceptualized quickly in
response to COVID-19. Open communication between the implementer and property
managers ensured the quick dissemination of new implementation information to
maintenance staff and tenants allowing the program to continue in PY 2020 despite
challenges due to the pandemic.
§ In response to continued COVID-19 restrictions, Avista and implementer staff developed a
contactless delivery method.
§ Due to low uptake in the first post-COVID-19 implementation phase, Avista and the
implementer adjusted the program to increase participation and measure installation by
limiting measures and working with property managers.
• MFDI: Property managers were satisfied with the program but suggested some tenants were
not satisfied with all the measures included in the program. Additionally, some tenants did
not install measures that were difficult to install or for which they did not have appropriate
tools.
§ Four of five property managers (4 of 5) were very satisfied with their MFDI program
experience overall.
§ Two property managers reported tenants were not satisfied with faucet aerators and
kitchen aerators due to low water pressure and appearance while three property managers
reported tenants were dissatisfied with showerheads due to restricted water flow.
§ One property manager reported that tenants’ participating in Phase 1 were not at all
satisfied with installation and educational materials provided by Avista.
• MFDI: The reliance of current data tracking on tenants’ willingness to return uninstalled or
unused equipment, together with low recovery rates, may be a contributing factor to minor
inconsistencies in measure-level data.
§ The drop-off delivery phases relied heavily on documentation filled out by maintenance
staff and tenants detailing the location and type and quantity of both installed and removed
measures. The implementer noted during the drop-off phases difficulty in tracking measure

28
installation locations in tenants’ units without the presence of a field technician to
document measure implementation.
• MFMT: Overall, the MFMT program was successful meeting the energy savings goal and
achieving high program satisfaction.
§ The program surpassed its electric savings goal of 476 MWh per year for PY 2020.
§ Builders have told Avista staff that they appreciate the incentive because it allows them
to install natural gas appliances which provides a competitive advantage, since they say
natural gas appliances are more attractive and can help increase the value of units.
§ The builder who completed a survey said they were very satisfied with the program and
planned to participate to a greater extent in 2021.
• The MFMT program has had success working with HVAC installers to help market the
program, though more can be done to increase marketing efforts and participation, as a
result.
§ Avista reported success working with HVAC installers to help promote the program. Staff
said this is a beneficial relationship as the HVAC installers are provided with additional work
and the program with more participants.
§ Avista reported that there used to be a flyer handed out as promotional material for the
program, though it is no longer used. Staff also said there is no current way in which they
monitor effectiveness of their marketing efforts and do not cross-promote the MFMT
program with other Avista programs.
Multifamily Recommendations
MFDI Recommendation 1: If the MFDI program continues to request tenants install measures directly,
consider offering an additional incentive such as an entry in a drawing for returning measures that are
not installed and for providing information on installed measures and their location.
MFDI Recommendation 2: If the MFDI program continues to operate using the drop-off delivery method
which requires tenants to install measures directly, continue focusing on simple and easy-to-install
measures like LEDs. Provide easy to follow installation instructions and remind tenants of the benefits of
installation in the program materials.
MFMT Recommendation 1: Develop marketing materials which can be used by HVAC contractors to
help promote the MFMT program. Due to the strengthening relationships between program staff and
HVAC contractors, promotional materials could be greatly beneficial to provide information about the
program in instances where the contractors may encounter potential participants.
MFMT Recommendation 2: Develop strategies to evaluate the effectiveness of marketing efforts and
cross-promotion with other Avista programs. In order to understand if marketing efforts are successful,
evaluation standards or goals should be set to better understand what the primary forces are that drive
participation to the program. Cross-promotion is also a simple and effective way to increase visibility of
the program and garner interest from potential participants.

29
Residential Programs
The Space Heat, Water Heat, Shell, and Windows programs provide Residential households with
Prescriptive rebates for installing space heat, water heat, smart thermostats, storm and standard
windows, and natural gas space and water heat. The ENERGY STAR Homes program provides rebates to
customers who purchase newly constructed manufactured homes that are ENERGY STAR-certified.
Residential Program Findings
For the PY 2020 process evaluation, Cadmus completed interviews with the Avista program manager for
the ENERGY STAR Homes program and conducted online surveys with Space Heat, Water Heat, Shell,
and Windows program participants.
Cadmus completed online surveys with 119 customers who participated in the Space Heat, Water Heat,
Shell, and Windows programs in PY 2020. Respondents who participated in the Shell or Windows
programs are reported together. The following sections present results and detail the findings.
ENERGY STAR Homes
Avista’s program manager for the ENERGY STAR Homes program said the PY 2020 program operated
similarly to how it operated in previous years. Participants purchase new homes from manufactured
home dealers who ensure the new homes are ENERGY STAR-certified. The dealer provides a name
certificate to the customer, who submits it to Avista with required program paperwork as proof of
participation. Avista approves the paperwork and processes rebates shortly thereafter. Avista typically
develops marketing campaigns to promote the program but relies primarily on dealers to drive
participation by directly informing customers of the program at point of purchase.
Changes to ENERGY STAR Homes program include increased rebates for natural gas homes from $400 to
$600, which Avista said has received “very positive” feedback from home dealers. Like most utility
energy efficiency programs, the ENERGY STAR Homes program was affected by the COVID-19 pandemic.
The pandemic forced some local businesses that sold manufactured homes to close permanently and
inhibited the certification of new homes that, at the time, were in the process of becoming ENERGY
STAR-certified. Additionally, a marketing campaign that Avista planned to launch the week the
shutdown occurred in March 2020 was tabled, and the pandemic limited Avista’s partnership with
Northwest Energy Efficiency Alliance (NEEA), which in past years had helped market the program.
Primarily because of the pandemic, the ENERGY STAR Homes program came close to, but ultimately fell
short of, achieving its participation and savings goals. Table 12 shows the target and achieved numbers
of homes rebated in each state.

30
Table 12. PY 2020 Target and Achieved New Homes – ENERGY STAR Homes
State Fuel Type Target Achieved
Washington Natural Gas 5 3
Electric or Electric/Natural Gas 50 30
Idaho Natural Gas 5 3
Electric or Electric/Natural Gas 2 13
Total 62 49

Avista speculated that, generally, investment in manufactured homes was dampened because
customers who typically purchase manufactured homes may have experienced income insecurity
induced by the pandemic.
In terms of planning for PY 2021 and beyond, Avista plans to increase rebates for electric-only and
combination electric/natural gas homes, continue evaluating its outreach partnership with NEEA, and
explore partnerships directly with local manufactured home builders (in addition to partnerships with
manufactured home dealers).
Space Heat, Water Heat, Shell, and Windows Customer Survey Results
Customer Awareness
Cadmus asked survey respondents where they learned about the program in which they participated. In
PY 2020, respondents most commonly learned about Avista programs through contractors (52%),
followed by Avista’s website (21%) and bill inserts (9%). The share of customers who learned about
programs primarily through contractors increased from PY 2019 (38%). Otherwise, respondents learned
more frequently about the program through Avista’s website (21% in PY 2020 compared to 19% in
PY 2019), while respondents learned about the program less frequently through word of mouth (6% in
PY 2020 compared to 26% in PY 2019). Figure 18 shows program-specific results.

31
Figure 18. Awareness of Avista Energy Efficiency Programming
Source: Residential Programs Participant Survey, Question D1: “How did you first hear about Avista’s Energy
Efficiency Rebate program?”
Cadmus also asked respondents how they preferred to learn about Avista’s energy efficiency programs.
Though most PY 2020 respondents preferred Avista’s emails (37%), they also cited bill inserts (27%) as
an effective method for spreading information. A small portion of PY 2020 respondents preferred
contractors (15%) or Avista’s website (9%). From PY 2019 to PY 2020, Avista emails saw the greatest
increase as an information source (from 10% to 37%), while bill inserts experienced the biggest decrease
(from 43% to 27%). Figure 19 shows program-specific results.

32
Figure 19. Preferred Method to Learn About Programming
Source: Residential Programs Participant Survey, Question D2: “What is the best way for Avista to inform
Residential customers like you about their energy efficiency improvement rebates?”
Motivation and Program Benefits
In PY 2020, respondents participated in Avista’s programs primarily to save money (80%), save energy
(50%), and/or increase their homes’ comfort (33%). From PY 2019 to PY 2020, saving money provided
the largest motivation increase (from 25% to 80%), followed by saving energy (from 22% to 50%).
Necessary upgrades realized the largest decrease in motivation (from 31% to 4%). Figure 20 shows
program-specific results.

33
Figure 20. Motivation to Participate in Residential Programs
Source: Residential Programs Participant Survey, Question D3: “What motivated you to participate in
Avista’s Energy Efficiency Rebate program?” Multiple responses allowed.
Cadmus asked respondents a multiple-response question about benefits they associated with Avista’s
Residential programs. In PY 2020, most cited energy savings (81%), lower operating and maintenance
costs (67%), rebates (64%), and increased comfort (48%). Though some respondents preferred to keep
up with technological trends and to produce less waste and better environmental outcomes, the largest
increase in perceived application benefits from PY 2019 to PY 2020 occurred for energy savings (from
34% to 81%). Figure 21 shows program-specific results.

34
Figure 21. Benefits of Participation in Residential Programs

Source: Residential Programs Participant Survey, Question D4. “What benefits come to mind when thinking
about your participation in Avista’s Energy Efficiency Rebate program?” Multiple responses allowed.
Program Satisfaction
Cadmus asked survey respondents to indicate their satisfaction levels with various program elements
associated with their rebate, new equipment, and installing contractor. Respondents’ satisfaction levels
with the PY 2020 program ranged from 97% to 100%6 with the five elements shown in Figure 22.
Respondents were least often very satisfied with the rebate amount. Lower satisfaction with rebates—
as customers self-reported via the survey—occurs commonly among Prescriptive rebate programs;
hence, Cadmus does not find this result unusual. From PY 2019 to PY 2020, the time it took to receive
the rebate increased the most in very satisfied responses (from 76% to 91%). Conversely, satisfaction
with the energy-saving equipment decreased the most in very satisfied responses (from 89% to 80%).

6 The combination of very satisfied and somewhat satisfied responses.

35
Figure 22. Satisfaction with Residential Program Elements

Source: Residential Programs Participant Survey, Question E1: “How would you rate your
overall experience with...”
Respondents satisfaction levels with the PY 2020 program ranged from 96% to 100%7 with the three
elements shown in Figure 23.
Figure 23. Satisfaction with Avista and Residential Programs Overall

Source: Residential Programs Participant Survey, Questions E1, E4: “How would you rate your
overall experience with...”

7 The combination of very satisfied and somewhat satisfied responses.

36
After asking respondents about their satisfaction with the PY 2020 programs and their elements,
Cadmus solicited respondents’ recommendations and feedback regarding possible program
improvements. Nineteen percent of respondents (23 of 119) provided feedback, consisting mostly of the
following recommendations:
• Increase advertising (9 of 23)
• Simplify rebate applications (4 of 23)
• Increase rebate amounts (2 of 23)
Decision Influencers
Cadmus asked respondents to rate the importance of several items on their decision to purchase and
install the equipment. Respondents rated information about the equipment from retailers and installers
as very important the most (70%), followed by Avista’s information about energy efficiency (42%) and
the rebate amount (41%). Respondents’ reported importance of all four items is shown in Figure 28.
Figure 28. Influences on Program Participation
Source: Residential Programs Participant Survey, Question F1: “Please rate the following items on
how important each item was on your decision to purchase and install the [MEASURE].”
Cadmus asked respondents if anything else was very important in their decision to purchase and install
the equipment. Forty-six percent of respondents (49 of 119) provided an answer, consisting mostly of
the following reasons:
• Equipment needed to be replaced (17 of 49)
• Increased comfort (11 of 49)
• Desired to be more energy efficient (7 of 49)

37
Survey Respondent Profile
As shown in Figure 24, most survey respondents in PY 2020 had a two-year, four-year, or master’s
degree (90%), results were consistent with PY 2019.
Figure 24. Residential Program Participant Education by Program Year
Source: Residential Programs Participant Survey, Question G1: “What is the highest level of education
that you have completed?”
In PY 2020, 77% of respondents earned at least $50,000 annually, as shown in Figure 25.

38
Figure 25. Residential Program Participant Income Ranges by Program Year
Source: Residential Programs Participant Survey, Question G5: “Select the category that applies to your
total household income for the year 2019.”
In PY 2020, survey respondents reported an average household size of roughly 2.6 residents (n=111).
Over 98% of respondents owned their homes (n=119).
Residential Conclusions and Recommendations
Conclusions and recommendations for the Residential programs are presented in this section.
Residential Conclusions
• Like some utility energy efficiency programs, the ENERGY STAR Homes program was
negatively affected by the COVID-19 pandemic.
§ Avista achieved its target number of rebates for electric and electric/natural gas homes in
Idaho but otherwise fell short of other state-specific, fuel-specific, and overall goals. The
pandemic forced local manufactured homes dealers to close down, slowed the
ENERGY STAR certification process for newly constructed manufactured homes, and, as was
seen nationally, likely increased income insecurity among Avista’s target customer base.
• Contractors remain an important way to learn about the Residential programs but survey
respondents also indicated an increased interest in learning about the programs through
email from Avista.
§ The share of respondents who learned about Avista’s program through contractors
increased from 38% in PY 2019 to 52% in PY 2020. Additionally, 15% of PY 2020 respondents

39
said that contractors would be the best way for Avista to inform them about energy
efficiency, compared to 9% in PY 2019.
§ The most common way PY 2020 respondents would like for Avista to inform them about
energy efficiency is through email from Avista (37%). This percentage increased from 10% in
PY 2019 respondents, indicating more interest in this method of communication.
• Saving money or energy are key drivers of motivation to participate in the program.
§ Eighty-eight percent of PY 2020 respondents said that saving money or saving energy
motivated them to participate, and 96% of respondents listed energy savings, rebates, or
lower operating costs as a benefit of participating in the program.
• Participants remain highly satisfied with most aspects of the program.
§ More than 99% of respondents were very satisfied or somewhat satisfied with their
interactions with Avista staff and the program overall, as well as with the time it took to
receive the rebate, the application process, and their new energy-saving equipment.
• Information from equipment retailers or installers heavily influenced respondents’ decision to
participate.
§ Ninety-six percent of respondents rated this information as very important or somewhat
important, compared to information about the equipment from friends and relatives, which
67% of respondents rated as very important or somewhat important.
Residential Recommendations
Residential Recommendation 1: If not already doing so, use email blasts, bill inserts, and other
promotional tools that are direct from Avista to customers, with Avista branding, to promote Residential
programs and incentives. Although most participants learned about the programs from their contractor,
they were more likely to want communication directly from Avista than through their contractor or
vendor. These marketing efforts will enhance any contractor and vendor marketing or advertising, and
give them better credibility, enabling them to make more sales through the program.
Residential Recommendation 2: Focus program outreach on home comfort to encourage participants
since this was mentioned as a motivating factor for participation.

40
Third-Party Implementer Program
Simple Steps, Smart Savings is a midstream program that provides markdowns on specific items (such as
LEDs, LED fixtures, showerheads, and clothes washers) through participating retailers. Avista administers
the program and CLEAResult implements it. As part of the implementation process, CLEAResult gathers
all sales data from participating retailers, occasionally sends program staff to visit each retailer, and
provides marketing materials as well as any other relevant program information.
Third-Party Program Findings
For the process evaluation of Simple Steps, Smart Savings, Cadmus conducted stakeholder interviews
with Avista and implementer staff.
Program Changes
Avista confirmed that most of Washington’s Simple Steps, Smart Savings program terminated at the end
of PY 2019, except for rebates for clothes washers. Idaho’s Simple Steps, Smart Savings program
operated in PY 2020 as it did in PY 2019, offering rebates on LED lamps and fixtures, showerheads, and
clothes washers until the program’s sunset in September 2020. Rebates did not change from PY 2019
levels.
In PY 2019, Avista considered implementing new data tracking software for the program. Avista used the
software for other programs in its portfolio but did not move the Simple Steps, Smart Savings program
onto the software because PY 2020 would be its last year in operation. The existing data tracking
processes met Avista’s needs.
Marketing and Outreach
As with past years, the implementer’s field team provided marketing materials to participating retailers;
Avista allows retail locations to choose if and how to use those materials in their stores. In response to
the COVID-19 pandemic, the implementer provided marketing materials and conducted store visits
based on both the preferences of the retail location and of its field staff. The implementer respected the
individual wishes of every participating retail location; for example, some did not want any non-
customers to enter for safety of their employees and customers. In those instances, the implementer
did not conduct visits. Similarly, if an implementation field staff felt uncomfortable entering a store that
appeared too crowded, the field staff could choose to not enter and revisit later.
Avista typically supplements point-of-purchase materials with marketing of its own materials but chose
not to do so in PY 2020 in the wake of the pandemic. The implementer also scaled back online marketing
in response to both the pandemic and the end of Energy Independence and Security Act (EISA)
regulations.
Customer and Retailer Experiences
Because Simple Steps, Smart Savings is a third-party midstream program, Avista and the implementer
cannot directly collect customer feedback or gauge satisfaction, which has always been a limitation for it

41
and similar program models. However, feedback from retailers and the implementer suggests customers
are satisfied with the program.
In past years, the implementer’s field team would visit retail locations to educate customers and store
associates, answer their lighting questions, and help them find the correct LED products for their needs.
For health and safety reasons, implementation field staff stopped visiting stores to educate customers
and store associates. Per the implementer, this left the burden of customer education on the retailers
themselves; however, store associates often relied on product education as much as customers did. To
overcome this barrier, the implementer arranged recurring virtual appointments between field staff and
store associates to explain the program and answer any general or product-specific questions that store
associates had. The implementer said its pandemic protocols, and especially its virtual visits, “worked
really well.” Despite the pandemic, the implementer observed sustained interest from customers in
LEDs. Both Avista and the implementer speculated this could be attributed to people spending much
more time at home than they normally would.
Ultimately, retailers were appreciative of their opportunity to participate in Simple Steps, Smart Savings
and saddened to learn of the program’s discontinuation. Per the implementer, retailers complimented
the program as a “selling tool” and “a good way to get customers looking at more-efficient products.”
Challenges and Successes
In addition to challenges caused by the COVID-19 pandemic described above, Avista and the
implementer indicated three other challenges for the Simple Steps, Smart Savings program:
• Goals: When Avista set goals for PY 2020, it expected Idaho program activity to include only
showerheads and clothes washers and Washington program activity to have ceased completely.
Instead, Avista continued to offer rebates for LED lamps and fixtures in Idaho and for clothes
washers in Washington. Accordingly, Avista did not have goals set for LEDs or clothes washers in
their respective states.
The implementer described the market as “fluid” and said, because of this fluidity, the goal of
the program is to generate as much energy savings as possible using open-ended budgets. In
response to the pandemic, the implementer did scale back savings program-wide in anticipation
of declining activity. However, the implementer observed sustained interest in LEDs.
• Retailer participation: The implementer said some retail locations—especially franchises and
individually owned stores such as Ace Hardware—wanted to participate in the program but
could not because of unclear communication or direction from the retailer’s corporate office.
This resulted in unexpectedly low retailer participation.
• EISA uncertainty: The implementer said, for LED products, it was difficult to navigate the repeal
of EISA. Because the Simple Steps, Smart Savings program is designed to be a turnkey program,
the implementer faced challenges in adapting the program to the unique lighting guidelines
developed by each state in response to EISA’s repeal. Avista and the implementer discontinued
the program in Washington largely because of the state’s adoption of stricter guidelines than
the federal guidelines originally imposed by EISA, a decision that rendered lighting savings in

42
Washington nearly obsolete. The repeal of EISA was a challenge for PY2020 that Avista and the
implementer anticipated in PY 2019.
The implementer continues to maintain good relationships with utility partners, manufacturers, and
retailers, and utilities find the program easy to sponsor, with current reporting systems making the
program easy to maintain.
Third-Party Program Conclusions and Recommendations
Conclusions for the Simple Steps, Smart Savings program are presented in this section.
Conclusions
• The implementer responded to the COVID-19 pandemic thoughtfully, which enabled the
program to continue to perform well despite the circumstances until its termination in
September 2020.
§ The implementer let retailers permit or deny store visits from implementation field staff,
allowed field staff the flexibility to reschedule store visits, and conducted virtual store visits
to educate store associates about the program and products (such as LEDs) like it typically
would. Avista and the implementer also scaled back marketing and outreach efforts and
allowed each retail location to tailor marketing, including point-of-purchase materials
provided by the implementer, to their individual needs.
• Avista and the implementer faced uncertainty with the repeal of EISA, which led to the Simple
Steps, Smart Savings program being implemented differently in Washington.
§ The implementer offered rebates for clothes washers in Washington and for LEDs,
showerheads, and clothes washers in Idaho. Avista did not set goals for clothes washers in
Washington or for LEDs in Idaho.
• Avista observed unexpectedly low throughput for clothes washers, which the implementer
attributed to the challenge it faced when recruiting retail locations to participate.
§ Despite showing a willingness to participate, some retail locations for franchised and
individually owned stores like Ace Hardware could not offer program rebates because of a
lack of communication/direction from their corporate offices. Thus, fewer retailers offered
buy-downs for clothes washers, and fewer customers obtained clothes washer rebates.
Recommendations
Because Simple Steps, Smart Savings discontinued in PY 2020, Cadmus does not have any
recommendations to make for the program.

43
Low-Income Program
Cadmus did not complete any process evaluation activities in PY 2020 for the Low-Income program.
Cadmus will conduct a process evaluation for both Idaho and Washington for PY 2021 as indicated in the
evaluation plan.
2020 Idaho Annual Conservation Report Appendices
APPENDIX F – 2020 EXPENDITURES BY PROGRAM
Electric Natural Gas
Program Participants
Evaluated
Savings
(kWh)
Utility Cost Participants
Evaluated
Savings
(Therms)
Utility Cost
Low-Income
Weatherization 56 Homes 34,091 $ 111,511 52 Sq ft/Units 1,455 $ 94,939
Fuel Conversions 22 Units 89,678 $ 229,820 - Units 0 $ 0
HVAC 16 Units 90,034 $ 234,510 49 Units 3,797 $ 304,807
Water Heat 0 Units 0 $ 0 26 Units 243 $ 109,318
Outreach/Giveaways 27 Events 1,458 $ 1,590 - NA 0 $ 0
Health and Safety 24 HHS 0 $ 59,415 22 HHS 0 $ 153,449
ENERGY STAR
Refrigerator 1 Units 39 $ 782 - Units 0 $ 0
Low-Income Total 215,300 $ 637,629 5,495 $ 662,514
Residential
ENERGY STAR Homes 16 Homes 50,705 $ 13,552 3 Homes 402 $ 2,019
Fuel Conversions 95 Units 635,962 $ 340,785 - Units 0 $ 0
HVAC 198 Furnace, Tstat 508,131 $ 135,219 3,229 Furnace, Tstat 266,939 $ 1,063,439
Water Heat 10 Units 12,986 $ 3,367 507 Units 37,976 $ 200,782
Multifamily Direct
Install 16,925 Units
(Measures)747,227 $ 445,952 - Units
(Measures)0 $ 0
Shell 119 Windows,
Insulation 358,972 $ 192,570 285 Windows,
Insulation 12,000 $ 160,163
Simple Steps, Smart
Savings 235,575 LEDs, Washers,
Showerheads 2,968,563 $ 476,600 235,575 Showerheads 234 $ 0
Residential Total 5,282,546 $ 1,608,046 317,550 $ 1,426,403
Commercial/Industrial
Site-Specific 108 Projects 4,113,196 $ 922,158 1 Projects 94 $ 1,204
Compressed Air 0 Units 0 $ 0 - NA 0 $ 0
Grocer 5 Projects 45,938 $ 8,157 - Projects 0 $ 0
Food Services 3 Projects 13,761 $ 2,309 20 Projects 13,597 $ 72,721
Green Motors 11 Motor Rewinds 52,038 $ 11,747 - NA 0 $ 0
HVAC 0 Units 0 $ 0 40 Units 13,992 $ 104,126
Shell 4 Projects 1,341 $ 448 4 Projects 1,821 $ 18,391
Multifamily Market
Transformation 4 Units
(multifamily)489,597 $ 492,967 - Units
(multifamily)0 $ 0
Exterior Lighting 557 Projects 2,552,295 $ 962,080 - NA 0 $ 0
Interior Lighting 331 Projects 3,944,956 $ 630,696 - NA 0 $ 0
Motor Control HVAC 0 Projects 0 $ 0 - Projects 0 $ 0
Commercial/Industrial Total 11,213,122 $ 3,030,561 29,503 $ 196,443
Energy Efficiency Total 16,710,968 $ 5,276,236 352,548 $ 2,285,36
Appendix F includes programmatic costs that are directly related to or allocated to specific programs, including costs for incentives as well as non-incentive utility
costs. These costs exclude market transformation, Idaho research costs, pilot programs, EM&V/CPA, and labor that is not associated with a specific program.
2020 Idaho Annual Conservation Report Appendices
APPENDIX G – 2020 PROGRAM ACTIVITY
Program Electric Natural Gas Total
Low-Income
Low-Income $ 211,199 $ 457,933 $ 669,132
Health and Safety $ 59,415 $ 89,410 $ 148,826
Low-Income Fuel Conversions $ 125,236 $ 0 $ 125,236
Residential
ENERGY STAR Homes $ 6,500 $ 1,950 $ 8,450
HVAC $ 75,613 $ 1,028,366 $ 1,103,979
Multifamily Direct Install $ 278,555 $ 0 $ 278,555
Fuel Efficiency $ 225,600 $ 0 $ 225,600
Shell $ 78,703 $ 156,016 $ 234,718
Simple Steps, Smart Savings $ 214,050 $ 0 $ 214,050
Water Heater $ 2,365 $ 195,800 $ 198,165
Commercial/Industrial
Site-Specific $ 679,152 $ 282 $ 679,434
Compressed Air $ 0 $ 0
Grocer $ 6,410 $ 0 $ 6,410
Food Services $ 1,800 $ 26,750 $ 28,550
Green Motors $ 9,334 $ 0 $ 9,334
Multifamily Market Transformation $ 444,000 $ 0 $ 444,000
HVAC $ 0 $ 41,507 $ 41,507
Shell $ 240 $ 7,724 $ 7,964
Exterior Lighting $ 815,360 $ 0 $ 815,360
Interior Lighting $ 391,670 $ 0 $ 391,670
Motor Control HVAC $ 0 $ 0
Energy Efficiency Total $ 3,625,202 $ 2,005,738 $ 5,630,940
Market Transformation
Market Transformation $ 655,310 $ 139,208 $ 794,518
Market Transformation Total $ 655,310 $ 139,208 $ 794,518
Other Programs and Activities
General Implementation $ 1,762,346 $ 296,315 $ 2,058,661
Idaho Research and Development $ 254,121 $ 0 $ 254,121
Pilot Programs $ 33,290 $ 1,050 $ 34,340
EM&V/CPA $ 142,064 $ 39,947 $ 182,011
Other Programs and Activities $ 2,191,821 $ 337,312 $ 2,529,133
Grand Total $ 6,472,333 $ 2,482,258 $ 8,954,591
Appendix G is inclusive of all costs booked to the Company’s Energy Efficiency Tariff Rider. Costs included in Low-Income, Residential and Commercial/Industrial
represent incentive costs paid to customers. Costs in Market Transformation and Other Programs and Activities represent other non-incentive utility costs.
2020 Idaho Annual Conservation Report Appendices
APPENDIX H – 2020 IDAHO COST-EFFECTIVENESS TABLES
Idaho Cost-Effectiveness Summary
Table 1 shows the overall cost-effectiveness results in Idaho.
TABLE 1 – 2020 IDAHO COST-EFFECTIVENESS SUMMARY
Benefit Cost Ratios
Portfolio
Electric Gas
Utility Cost Test (UCT) 2.09 1.64
Total Resource Cost (TRC) 1.38 0.94
Participant Cost Test (PCT) 2.52 1.34
Ratepayer Impact (RIM) 0.49 0.29
Idaho Portfolio Cost-Effectiveness Results
Table 2 and Table 3 shows the portfolio level cost-effectiveness results in Idaho by fuel type.
TABLE 2 – IDAHO ELECTRIC PORTFOLIO COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 12,280,877 $ 5,886,868 2.09
Total Resource Cost (TRC)$ 13,576,343 $ 9,852,524 1.38
Participant Cost Test (PCT)$ 19,406,684 $ 7,712,680 2.52
Ratepayer Impact (RIM)$ 12,280,877 $ 25,099,813 0.49
TABLE 3 – IDAHO NATURAL GAS PORTFOLIO COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 3,751,762 $ 2,285,360 1.64
Total Resource Cost (TRC)$ 4,220,253 $ 4,475,939 0.94
Participant Cost Test (PCT)$ 5,638,507 $ 4,196,316 1.34
Ratepayer Impact (RIM)$ 3,751,762 $ 12,999,595 0.29
2020 Idaho Annual Conservation Report Appendices
Idaho Commercial/Industrial Cost-Effectiveness Results
Table 4 and Table 5 show commercial/industrial cost-effectiveness results in Idaho by fuel type.
TABLE 4 – IDAHO COMMERCIAL/INDUSTRIAL ELECTRIC COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 6,434,778 $ 3,207,038 2.01
Total Resource Cost (TRC)$ 7,078,256 $ 5,975,711 1.18
Participant Cost Test (PCT)$ 11,301,365 $ 5,238,461 2.16
Ratepayer Impact (RIM)$ 6,434,778 $ 12,020,967 0.54
TABLE 5 – IDAHO COMMERCIAL/INDUSTRIAL NATURAL GAS COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 181,083 $ 196,443 0.92
Total Resource Cost (TRC)$ 199,192 $ 370,999 0.54
Participant Cost Test (PCT)$ 219,873 $ 250,818 0.88
Ratepayer Impact (RIM)$ 181,083 $ 340,054 0.53
Idaho Residential Cost-Effectiveness Results
Table 6 shows residential cost-effectiveness results for electric.
TABLE 6 – IDAHO RESIDENTIAL ELECTRIC COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 5,573,921 $ 2,133,107 2.61
Total Resource Cost (TRC)$ 6,131,313 $ 3,271,662 1.87
Participant Cost Test (PCT)$ 7,417,708 $ 2,019,940 3.67
Ratepayer Impact (RIM)$ 5,573,921 $ 12,060,227 0.46
Table 7 shows residential cost-effectiveness results for natural gas.
TABLE 7 – IDAHO RESIDENTIAL NATURAL GAS COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 3,502,394 $ 1,426,403 2.46
Total Resource Cost (TRC)$ 3,852,633 $ 3,466,442 1.11
Participant Cost Test (PCT)$ 4,821,706 $ 3,422,171 1.41
Ratepayer Impact (RIM)$ 3,502,394 $ 11,836,441 0.30
2020 Idaho Annual Conservation Report Appendices
Idaho Low-Income Cost-Effectiveness Results
Table 8 shows residential cost-effectiveness results for low-income electric.
TABLE 8 – IDAHO LOW-INCOME ELECTRIC COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 272,178 $ 546,723 0.50
Total Resource Cost (TRC)$ 366,774 $ 605,151 0.61
Participant Cost Test (PCT)$ 687,611 $ 454,279 1.51
Ratepayer Impact (RIM)$ 272,178 $ 1,018,619 0.27
Table 9 shows residential cost-effectiveness results for low-income natural gas.
TABLE 9 – IDAHO LOW-INCOME NATURAL GAS COST-EFFECTIVENESS RESULTS
Cost-Effectiveness Test Benefits Costs Benefit/Cost Ratio
Utility Cost Test (UCT)$ 68,285 $ 662,514 0.10
Total Resource Cost (TRC)$ 168,428 $ 638,498 0.26
Participant Cost Test (PCT)$ 596,928 $ 523,327 1.14
Ratepayer Impact (RIM)$ 68,285 $ 823,100 0.08
2020 Idaho Annual Conservation Report Appendices
APPENDIX I – 2020 UES MEASURE LIST
Measure Name UOM Measure
Life
Customer
Incremental Cost
Annual kWh
Savings
Annual
Therm
Savings
Commercial/Industrial – Electric – AirGuardian
AirGuardian Unit 10 $ 1,440.00 6,000.00
Commercial/Industrial – Electric – Prescriptive Exterior Lighting
100 watt fixture Unit 12 $ 187.81 681.18
100 watt NC fixture Unit 12 $ 337.08 737.88
140 watt fixture Unit 12 $ 241.04 910.42
140 watt NC fixture Unit 12 $ 357.88 817.83
160 watt fixture Unit 12 $ 475.43 1,142.86
160 watt NC fixture Unit 12 $ 417.80 984.07
175 watt fixture Unit 12 $ 401.58 1,415.50
25 watt fixture Unit 12 $ 147.03 329.18
30 watt fixture Unit 12 $ 211.38 439.27
300 watt fixture Unit 12 $ 794.82 2,468.82
400 watt fixture Unit 12 $ 876.04 3,493.04
50 watt fixture Unit 12 $ 225.11 675.00
Sign lighting Unit 10 $ 31.78 107.20
Commercial/Industrial – Electric – Food Services
0.81 to 1.00 GPM electric pre-rinse sprayer Unit 4 $ 71.63 570.00
10 or larger pan electric steamer Unit 7 $ 4,287.00 29,954.00
3 pan electric steamer Unit 7 $ 1,036.90 9,066.00
4 pan electric steamer Unit 7 $ 2,489.00 12,123.00
5 pan electric steamer Unit 7 $ 3,111.00 15,013.00
6 pan electric steamer Unit 7 $ 1,020.02 17,906.00
Efficient combination oven (>= 16 pan and <= 20 pan) electric Unit 7 $ 493.08 5,528.00
Efficient combination oven (>= 6 pan and <= 15 pan) electric Unit 7 $ 878.40 5,107.00
Efficient electric convection oven full size Unit 8 $ 161.04 977.00
Efficient hot food holding cabinet, 1/2 size Unit 10 $ 280.59 1,607.00
Efficient hot food holding cabinet, double size Unit 10 $ 2,520.75 5,238.00
Efficient hot food holding cabinet, full size Unit 10 $ 597.41 2,860.00
Electric fryer (large vat size) Unit 6 $ 255.62 1,660.00
Fleet heat Unit 12 $ 520.50 8,000.00
High temp electric hot water dishwasher Unit 12 $ 2,297.00 4,110.00
2020 Idaho Annual Conservation Report Appendices
Low temp electric hot water dishwasher Unit 12 $ 2,297.00 3,801.00
Standard efficiency appliance to ENERGY STAR ice maker, air
cooled, ice making head, 200 to 399 lbs./day capacity Unit 10 $ 185.00 592.00
Standard efficiency appliance to ENERGY STAR ice maker, air
cooled, ice making head, 400 to 599 lbs./day capacity Unit 10 $ 204.00 804.00
Standard efficiency appliance to ENERGY STAR ice maker, air
cooled, ice making head, 600 to 799 lbs./day capacity Unit 10 $ 220.00 1,000.00
Standard efficiency appliance to ENERGY STAR ice maker, air
cooled, ice making head, 800 to 999 lbs./day capacity Unit 10 $ 240.00 173.00
Standard efficiency appliance to ENERGY STAR ice maker, air
cooled, ice making head, under 200 lbs./day capacity Unit 10 $ 317.67 940.00
Standard efficiency appliance to high-efficiency electric griddle,
70% efficient or better Unit 12 $ 1,000.00 1,636.00
Commercial/Industrial – Electric – Green Motors
100 HP industrial Unit 8 $ 374.61 1,723.00
1000 HP industrial Unit 8 $ 1,946.32 16,682.00
125 HP industrial Unit 8 $ 373.40 1,990.00
1250 HP industrial Unit 9 $ 2,325.02 17,812.00
15 HP industrial Unit 7 $ 125.07 525.00
150 HP industrial Unit 8 $ 415.93 2,366.00
1500 HP industrial Unit 9 $ 2,663.37 21,329.00
1750 HP industrial Unit 9 $ 3,039.84 24,779.00
20 HP industrial Unit 7 $ 139.54 703.00
200 HP industrial Unit 8 $ 500.72 3,138.00
2000 HP industrial Unit 9 $ 3,409.96 28,201.00
2250 HP industrial Unit 9 $ 3,714.88 31,527.00
25 HP industrial Unit 8 $ 159.43 893.00
250 HP industrial Unit 8 $ 643.55 3,799.00
2500 HP industrial Unit 9 $ 4,064.37 34,957.00
30 HP industrial Unit 8 $ 175.10 962.00
300 HP industrial Unit 8 $ 650.50 4,535.00
3000 HP industrial Unit 9 $ 4,752.00 41,686.00
350 HP industrial Unit 8 $ 681.80 5,287.00
3500 HP industrial Unit 9 $ 5,251.18 48,532.00
40 HP industrial Unit 8 $ 213.98 1,121.00
400 HP industrial Unit 8 $ 761.51 5,994.00
4000 HP industrial Unit 9 $ 5,862.69 55,466.00
450 HP industrial Unit 8 $ 832.39 6,732.00
4500 HP industrial Unit 9 $ 6,318.17 62,269.00
2020 Idaho Annual Conservation Report Appendices
50 HP industrial Unit 8 $ 236.88 1,206.00
500 HP industrial Unit 8 $ 899.26 7,491.00
5000 HP industrial Unit 9 $ 6,744.35 69,044.00
60 HP industrial Unit 8 $ 279.38 1,269.00
600 HP industrial Unit 8 $ 1,353.31 10,137.00
700 HP industrial Unit 8 $ 1,476.45 11,777.00
75 HP industrial Unit 8 $ 301.98 1,305.00
800 HP industrial Unit 8 $ 1,638.17 13,431.00
900 HP industrial Unit 8 $ 1,806.00 15,077.00
Commercial/Industrial – Electric – Grocer
Add doors to open medium temp cases Unit 20 $ 385.00 533.00
Anti-sweat heater controls – low temp Unit 12 $ 47.90 305.00
Anti-sweat heater controls – medium temp Unit 12 $ 47.90 217.00
Evap motors: shaded pole to ECM in display case Unit 15 $ 94.38 685.00
Evap motors: shaded pole to ECM in walk-in – greater than 23
watts Unit 15 $ 275.73 1,355.00
Evap motors: shaded pole to ECM in walk-in – less than 23 watts Unit 15 $ 275.73 583.00
Evaporator fan ECM motor controller – walk-In – low temp – >23
watt – 3 or more motors/controller Unit 15 $ 154.55 253.00
Evaporator fan ECM motor controller – walk-In – low temp – ≤23
watt – 7 or more motors/controller Unit 15 $ 59.32 119.00
Floating head pressure control w/ VFD – air cooled Unit 15 $ 200.00 915.00
Floating head pressure for single compressor systems, LT
condensing unit Unit 15 $ 306.99 855.00
Floating head pressure for single compressor systems, LT remote
condenser Unit 15 $ 163.25 685.00
Floating head pressure for single compressor systems, MT remote
condenser Unit 15 $ 214.50 473.00
Gaskets for low temp reach-in glass doors Unit 4 $ 111.12 243.00
Gaskets for medium temp reach-in glass doors Unit 4 $ 89.95 248.00
Gaskets for walk-in cooler – main Unit 4 $ 84.66 204.00
Gaskets for walk-in freezer – main door Unit 4 $ 125.93 347.00
LT case: 2 T12 to 1 high power LED inside lamp Unit 7 $ 22.93 223.00
LT case: 2 T8 to 1 high power LED inside lamp Unit 7 $ 22.93 142.00
LT case: T12 to LP LED inside lamp Unit 7 $ 14.18 104.00
LT case: T8 to LP LED inside lamp Unit 7 $ 14.18 63.00
MT case: 2 T12 to 1 high power LED inside lamp Unit 7 $ 22.93 183.00
MT case: 2 T12 to 1 high power LED outside lamp Unit 7 $ 22.93 156.00
MT case: 2 T8 to 1 high power LED inside lamp Unit 7 $ 22.93 116.00
2020 Idaho Annual Conservation Report Appendices
MT case: 2 T8 to 1 high power LED outside lamp Unit 7 $ 22.93 99.00
MT case: T12 to LP LED inside lamp Unit 7 $ 14.18 85.00
MT case: T8 to LED inside lamp Unit 7 $ 14.18 52.00
On-demand commercial overwrapper Unit 10 $ 306.77 1,588.00
Strip curtains for convenience store walk-in freezers Unit 2 $ 10.14 31.00
Strip curtains for restaurant walk-in freezers Unit 2 $ 10.14 129.00
Strip curtains for supermarket walk-in coolers Unit 2 $ 10.14 123.00
Strip curtains for supermarket walk-in freezers Unit 2 $ 10.14 535.00
T12 to LP LED outside lamp Unit 7 $ 14.18 73.00
T8 to LP LED outside lamp Unit 7 $ 14.18 44.00
Commercial/Industrial – Electric – Prescriptive Interior Lighting
12-20 watt LED fixture retrofit Unit 12 $ 30.51 159.87 (1.98)
140 watt fixture/lamp – interior Unit 12 $ 182.46 627.23 (7.79)
175 watt fixture/lamp – interior Unit 12 $ 268.43 1,015.33 (12.60)
2-9 watt MR16 Unit 12 $ 7.92 57.20 (0.71)
2x2 fixtures Unit 12 $ 100.57 106.15 (1.32)
2x4 fixtures Unit 12 $ 112.01 139.83 (1.74)
400 watt fixture/lamp – interior Unit 12 $ 389.22 2,723.66 (33.81)
8’ T8 TLED Unit 12 $ 23.39 57.84 (0.72)
LLLC fixture Unit 20 $ 75.00 187.20 (2.32)
occupancy sensors Unit 20 $ 91.27 127.92 (1.59)
T5HO TLED Unit 12 $ 18.13 105.40 (1.31)
T8 TLED Unit 12 $ 12.41 48.38 (0.60)
U-Bend Unit 12 $ 23.69 52.09 (0.65)
Commercial/Industrial – Electric – MFMT
Multifamily NG Market Transformation (per unit) Unit 20 $ 6,000.00 5,874.00 (258.00)
Commercial/Industrial – Electric – Prescriptive Shell
Less than R11 attic insulation (E/E) to R30-R44 attic insulation Sq Ft 22 $ 0.76 1.02
Less than R11 attic insulation (E/E) to R45+ attic insulation Sq Ft 22 $ 0.86 1.39
Less than R11 roof insulation (E/E) to R30+ roof insulation Sq Ft 22 $ 0.62 1.36
Less than R4 wall insulation (E/E) to R11-R18 wall insulation Sq Ft 22 $ 0.61 2.82
Less than R4 wall insulation (E/E) to R19+ wall Insulation Sq Ft 22 $ 0.65 4.11
Commercial/Industrial – Electric – Variable Frequency Drives
Prescriptive VFDs – HVAC cooling pump Unit 16 $ 200.00 1,091.00
Prescriptive VFDs – HVAC fan Unit 16 $ 200.00 1,022.00
Prescriptive VFDS – HVAC heating pump or combo Unit 16 $ 200.00 1,756.00
2020 Idaho Annual Conservation Report Appendices
Commercial/Industrial – Natural Gas – Food Services
0.81 to 1 GPM gas pre-rinse sprayer Unit 4 $ 108.42 16.81
10 or larger pan gas steamer Unit 9 $ 4,287.16 3,043.24
3 pan gas steamer Unit 9 $ 1,867.00 586.22
4 pan gas steamer Unit 9 $ 2,489.00 779.91
5 pan gas steamer Unit 9 $ 3,111.00 973.63
6 pan gas steamer Unit 9 $ 3,733.00 1,167.36
Efficient combination oven (>= 16 pan and <= 20 pan) gas Unit 10 $ 5,717.00 500.00
Efficient combination oven (>= 6 pan and <= 15 pan) gas Unit 10 $ 5,717.00 403.00
Efficient convection oven full size Unit 10 $ 5,717.00 450.00
ENERGY STAR 50% efficiency gas fryer Unit 12 $ 2,500.00 505.00
Gas rack oven Unit 8 $ 4,933.00 1,034.00
H.E. gas convection oven, 40% efficiency or better Unit 12 $ 700.00 323.00
H.E. gas griddle, 40% efficiency or better Unit 12 $ 491.00 88.00
High temp gas hot water dishwasher Unit 12 $ 2,297.00 102.82
Low temp gas hot water dishwasher Unit 12 $ 2,297.00 140.10
Commercial/Industrial – Natural Gas – HVAC
Gas boiler <300 kBtu .85-.89 AFUE KBTU 16 $ 12.31 1.77
Gas boiler <300 kBtu .90+ AFUE KBTU 16 $ 14.77 2.87
Multi-stage furnace <225 kBtu .90-.95 AFUE KBTU 16 $ 8.61 3.67
Multi-stage furnace <225 kBtu .95+ AFUE KBTU 16 $ 10.76 4.22
Single-stage furnace <225 kBtu .90-.95 AFUE KBTU 16 $ 6.66 2.87
Single-stage furnace <225 kBtu .95+ AFUE KBTU 16 $ 8.61 3.67
Commercial/Industrial – Natural Gas – Shell
Less than R11 attic insulation (E/G) to R30-R44 attic insulation Sq Ft 22 $ 0.76 0.09
Less than R11 attic insulation (E/G) to R45+ attic insulation Sq Ft 22 $ 0.86 0.13
Less than R11 roof insulation (E/G) to R30+ roof insulation Sq Ft 22 $ 0.62 0.12
Less than R4 wall insulation (E/G) to R11-R18 wall insulation Sq Ft 22 $ 0.61 0.24
Less than R4 wall insulation (E/G) to R19+ wall Insulation Sq Ft 22 $ 0.65 0.36
Residential – Electric – Fuel Conversion
Natural gas furnace Unit 20 $ 3,031.98 7,384.00 (449.00)
Natural gas furnace + water heater Unit 20 $ 4,416.43 9,789.00 (565.00)
Residential – Electric – MFDI
Multifamily Direct Install Unit 12 $ 769,391 $1,288,412
2020 Idaho Annual Conservation Report Appendices
Residential – Electric – Prescriptive
Attic insulation less than R11 to R49 Sq Ft 45 $ 1.17 1.75
Ductless heat pump (displace zonal) Unit 15 $ 3,553.36 2,348.00
E ESTAR HOME – MANUF, ELEC/DF Unit 25 $ 2,400.94 3,315.00
ELEC resistance to ASHP Unit 18 $ 4,359.21 5,865.33
ElEC storm windows Sq Ft 20 $ 9.90 12.25
ELEC windows --> <0.30 U Sq Ft 45 $ 22.32 11.13
ELEC windows --> <0.30 U Sq Ft 45 $ 22.32 11.00
Floor insulation R0->=R19+ Sq Ft 45 $ 1.41 1.00
Front load washer Unit 14 $ 61.54 143.00
Heat pump water heater (any size ave tier 2/3) Unit 13 $ 629.17 1,166.00
Vented ENERGY STAR clothing dryer Unit 23 $ 20.44 68.00
Wall insulation R0->=R11+ Sq Ft 45 $ 1.54 2.00
Web Tstat Elec Cont Unit 15 $ 294.25 748.50
Web Tstat Elec DIY Unit 15 $ 240.35 748.50
Residential – Electric – Simple Steps
Clothing washer Unit 11 $ 55.00 108.58
LED – decorative ceiling flush mount fixture – 2000-7999 lumens Unit 20 $ 7.80 25.00
LED – exterior porch light fixture – 2000-7999 Lumens Unit 20 $ 1.48 37.00
LED – general purpose and dimmable – 1050-1489 lumens Unit 13 $ 3.32 5.00
LED – general purpose and dimmable – 1490-2600 lumens Unit 13 $ 2.67 6.00
LED – general purpose and dimmable – 250-1049 lumens Unit 13 $ 0.55 1.00
LED – globe – 250-1049 lumens Unit 13 $ 1.04 6.00
LED – reflectors and outdoor – 1050-1489 lumens Unit 13 $ 0.69 6.00
LED – reflectors and outdoor – 1490-2600 lumens Unit 13 $ 5.44 59.00
LED – reflectors and outdoor – 250-1049 lumens Unit 13 $ 0.50 10.00
LED – track light fixture – 2000-7999 Lumens Unit 20 $ 8.20 63.50
LED – bathroom vanity – 2000-7999 Lumens Unit 13 $ 5.15 17.50
LED – MR Bi-Pin base – 250-499 Lumens Unit 12 $ 0.88 4.00
LED – MR Bi-Pin base – 500-999 Lumens Unit 12 $ 0.88 8.00
LED – recessed retrofit – 500-1999 Lumens Unit 20 $ 0.56 18.50
Showerhead 2.0 GPM Unit 10 $ 0.37 19.96
Residential – Natural Gas – Prescriptive
ENERGY STAR home – gas only Unit 25 $ 2,117.00 133.98
Attic insulation Sq Ft 45 $ 1.30 0.15
Floor insulation Sq Ft 45 $ 1.31 0.06
2020 Idaho Annual Conservation Report Appendices
HE water heaters (<= 55)(.65 or greater) Unit 15 $ 315.85 21.80
Wall insulation Sq Ft 45 $ 1.38 0.07
Web Tstat gas cont Unit 15 $ 294.25 26.00
Web Tstat gas DIY Unit 15 $ 240.35 26.00
Windows dual pane <0.30 U-value Sq Ft 45 $ 22.58 0.37
Windows single pane <0.30 U-value Sq Ft 45 $ 22.32 0.37
High efficiency wall furnace (AFUE 90%) Unit 20 $ 2,000.00 103.00
Natural gas boiler 96% AFUE Unit 20 $ 2,855.00 112.40
Natural gas furnace 90% Unit 20 $ 823.10 103.00
Natural gas furnace 90% Unit 20 $ 823.10 71.00
Storm windows Sq Ft 20 $ 9.90 0.42
Low-Income – Electric
Duct sealing Unit 20 $ 394.00 689.00 -
Ductless heat pump (displace Zonal) Unit 15 $ 4,103.00 2,348.00 -
Ductless heat pump w FAF Unit 15 $ 4,103.00 3,902.55 -
Air infiltration Sq Ft 15 $ 0.73 1.00 -
ENERGY STAR rated doors Unit 40 $ 608.53 186.86 -
ENERGY STAR refrigerator Unit 20 $ 100.23 39.00 -
HE AIR HPUMP Unit 15 $ 4,055.53 2,053.50 -
INS – ceiling/attic Sq Ft 45 $ 1.81 0.46 -
INS – DUCT Sq Ft 45 $ 2.83 2.61 -
INS – floor Sq Ft 45 $ 2.93 1.23 -
INS – wall Sq Ft 45 $ 2.03 1.48 -
E TO G combo Unit 20 $ 9,613.00 9,075.00 (402.00)
E TO G furnace conversion Unit 20 $ 2,950.00 3,496.00 (133.00)
E TO G H2O conversion Unit 15 $ 1,518.00 1,586.00 (84.50)
Elec Res --> heat pump Unit 15 $ 4,055.53 5,865.33 -
HHS Unit 1 $ 1.00 1.00 1.00
Outreach LEDs Unit 13 $ 1.10 9.00 -
Tier 2-3 any size HPWH Unit 13 $ 697.39 587.33 -
Windows Sq Ft 45 $ 8.55 1.64 -
Low-Income – Natural Gas
INS – DUCT Sq Ft 45 $ 8.01 0.07
INS – floor Sq Ft 45 $ 4.48 0.07
2020 Idaho Annual Conservation Report Appendices
APPENDIX J – 2020-2021 EVALUATION WORK PLANS

Work Plan: Evaluation, Measurement and
Verification (EM&V) of Avista’s 2020-2021
Energy Efficiency Programs
Prepared for: 

Avista Corporation 

Delivered on: 
January 7, 2020 

Prepared by: 

ADM Associates, Inc.
3239 Ramos Circle 
Sacramento, CA95827 
916.363.8383 

In Partnership with:  
Cadeo Group
107 SE Washington St, Suite 450 
Portland, OR 97214 

Tables of Contents and Tables    ii 
Table of Contents 
1.  Technical Evaluation Plan ..................................................................................................................... 4 
1.1  Summary of Avista’s Residential and Low‐Income Portfolio ....................................................... 4 
1.2  Evaluation Approach ................................................................................................................... 4 
1.3  Program‐Level EM&V Approaches ............................................................................................ 21 
1.4  Management Plan & Schedule .................................................................................................. 34 

admenergy.com | 3239 Ramos Circle, Sacramento, CA 95827| 916.363.8383        iii 
List of Tables   
Table 1‐1: Impact Evaluation Activities by Program ..................................................................................... 4 
Table 1‐2: Sample Design for Document Review for Washington and Idaho Combined ........................... 10 
Table 1‐3: Sample Design for Verification Survey for Washington and Idaho Combined .......................... 11 
Table 1‐4: Water Heat Program Measures ................................................................................................. 21 
Table 1‐5: HVAC Program Measures ........................................................................................................... 23 
Table 1‐6: Shell Program Measures ............................................................................................................ 25 
Table 1‐7: Residential Fuel Efficiency Program Measures .......................................................................... 26 
Table 1‐8: HVAC Program Measures ........................................................................................................... 28 
Table 1‐9: Residential Small Home & Multifamily Weatherization Program Measures ............................. 29 
Table 1‐10: Low‐Income Program Measures .............................................................................................. 31 
Table 1‐11: Multi‐family CEEP Program Measures ..................................................................................... 33 
Table 1‐12: Income‐Qualified Single‐family CEEP Program Measures ....................................................... 33 
Table 1‐13: Project Team Members ............................................................................................................ 34 
Table 1‐14: Schedule ................................................................................................................................... 36 

Work Plan    4 
1. Technical Evaluation Plan 
This Evaluation, Measurement, and Verification (EM&V) Plan details the methods by which ADM 
Associates, Inc. (ADM) and Cadeo will complete the impact evaluation of Avista Utility’s (Avista) 2020 
Programs as‐specified in ADM’s response to the Request for Proposals (RFP) for evaluating Avista 
Utility’s (“Avista”) 2020‐2021 residential and residential low‐income (collectively, “residential”) energy 
efficiency programs in Idaho and Washington. 
1.1 Summary of Avista’s Residential and Low‐Income Portfolio 
Table 1‐1 summarizes the programs offered to residential and low‐income customers in the Avista 
service territory as well as ADM’s evaluation tasks and impact methodology for each program.  
Table 1‐1: Impact Evaluation Activities by Program 
Program Database
Review
Survey
Verification Impact Methodology
Water Heat    Billing analysis with comparison group 
HVAC   Billing analysis with comparison group 
Shell    Billing analysis with comparison group 
ENERGY STAR Homes   Simulation modeling/Billing analysis with 
comparison group 
Residential Small Home & 
Multifamily Weatherization*    RTF UES/ 
Billing analysis with comparison group 
Residential Fuel Efficiency 
Program     Billing analysis with comparison group 
Low‐Income     Billing analysis with comparison group 
CEEP    RTF UES/Billing analysis with comparison 
group 
*This program was not deployed for the 2020 program year. Evaluation of this program will commence in 2021. 
1.2 Evaluation Approach 
ADM will perform an impact evaluation on each of the programs. ADM will use the following approaches 
to calculate energy impact defined by the International Performance Measurement and Verification 
Protocols (IPMVP) and the Uniform Methods Project (UMP): 
 Simple verification (web‐based survey) 
 Deemed savings and/or Engineering Algorithms (IPMVP Options A & B) 
 Whole building billing analysis (IPMVP Option C) 
 Simulation modeling (IPMVP Option D) 
ADM will complete and report the results of the above impact tasks for each the electric impacts and 
the natural gas impacts for each state separately.  

Work Plan    5 
The M&V methodologies are program‐specific and determined by previous Avista evaluation 
methodologies as well as the relative contribution of a given program to the overall energy efficiency 
impacts. Besides drawing on IPMVP, we will also review relevant information on infrastructure, 
framework, and guidelines set out for EM&V work in several guidebook documents that have been 
published over the past several years. These include the following: 
 Northwest Regional Technical Forum (RTF) 
 National Renewable Energy Laboratory (NREL), United States Department of Energy (DOE) The 
Uniform Methods Project (UMP): Methods for Determining Energy Efficiency Savings for Specific 
Measures, April 20131 
 International Performance Measurement and Verification Protocol (IPMVP) maintained by the 
Efficiency Valuation Organization (EVO) with sponsorship by the U.S. Department of Energy (DOE)2 
We will keep our data collection instruments, calculation spreadsheets, and monitored/survey data 
available at the request of Avista. Any component of the data collection or analysis will be made 
available at request. All communications (including data transfer) will be consistently performed with 
constant communication and data sharing protocols.  
1.2.1 Impact Evaluation Approach 
This section presents our general cross‐cutting approach to accomplishing the scope of work outlined in 
the Request for Proposal (RFP) for impact evaluation of Avista’s Residential and Low‐Income programs 
listed in Table 1‐1. The Evaluators start by presenting our general evaluation approach. This chapter is 
organized by general task due to several overlap across programs. Section 1.3 describes the Evaluators’ 
program‐specific impact evaluation methods in further detail. 
ADM outlines our approach to verifying, measuring, and reporting the residential portfolio impacts as 
well as cost‐effectiveness and summarizing potential program and portfolio improvements. The primary 
objective of the impact evaluation is to determine ex‐post verified net energy savings. There will be no 
on‐site verification or equipment monitoring. 
Our general approach for this evaluation considers the cyclical feedback loop among program design, 
implementation, and impact evaluation. Our activities during the evaluation will estimate and verify 
annual energy savings and identify whether a program is meeting its goals. These activities are aimed to 
provide guidance for continuous program improvement and increased cost effectiveness for the 2020 
and 2021 program years. ADM will provide the following services and objectives as deliverables to Avista 
for this evaluation, as specified in the RFP: 

1 Notably, The Uniform Methods Project (UMP) includes the following chapters authored by ADM. Chapter 9 (Metering Cross‐ 
Cutting Protocols) was authored by Dan Mort and Chapter 15 (Commercial New Construction Protocol) was Authored by Steven 
Keates.  
2 Core Concepts: International Measurement and Verification Protocol. EVO 100000 – 1:2016, October 2016. 

Work Plan    6 
1. Independently  verify,  measure  and  document  energy  savings  impacts  from  each  of  Avista’s 
electric  and  natural  gas  energy  efficiency  Programs,  or  for  Program  categories  representing 
consolidated small‐scale offerings from January 1, 2020 through December 31, 2021; 
2. Analytically substantiate the measurement of those savings; 
3. Calculate  the  cost  effectiveness  of  the  Portfolio  and  component  Programs  using  the  Total 
Resource Cost Test (TRC), Utility Cost Test (UCT), Participant Cost Test (PCT), Ratepayer Impact 
Measure Test (RIM), and, potentially, the Resource Values Test (RVT) tests; 
4. Identify Program improvements, if any; and 
5. Identify possible future Programs. 

In addition to the above services, we have identified the following deliverables to Avista for this 
evaluation: 
 Two (2) separate and independent evaluation reports, one for Idaho and one for Washington, of 
Avista’s Residential Natural Gas Impact Evaluation for each program year 
 Two (2) separate and independent evaluation reports, one for Idaho and one for Washington, of 
Avista’s Residential Electric Impact Evaluation for each program year 
 An independent estimate of kWh and Therm savings for 2020 and 2021 through thorough and 
proper evaluation of program impacts with statistical precision and confidence at a minimum of 
10%/90% for each state and fuel type 
 Presentation of evaluation findings to Avista’s Spokane offices or other regional locations, as 
required, along with additional stakeholders, as necessary 
 Updates to Avista’s Technical Reference Manual (TRM), annually, based on Avista’s evaluation 
findings and secondary information 
 All supporting workpapers for calculations, tables, graphs, and other documents as necessary 
 State‐specific reports on any project where realization rate is expected to be less than 90% as well 
as a complete listing of all projects where any material adjustments were made 
 Summary of any deviations from historical methodology for calculating cost‐effectiveness in the 
final report in addition to a presentation of deviations to the Advisory Group. 
ADM will deliver the 2020 program year results by April 15, 2021, and the 2021 program year results by 
April 15, 2022. We approach evaluation with the frame of mind that the final report should not contain 
information that has not already been communicated with Avista. This is achieved through the 
following: 
 Transparency of Evaluation Effort. In  our  evaluations,  we  will  keep  our  data  collection 
instruments, models, calculation spreadsheets, programming scripts, and monitored data/survey 
data available at the request of Avista. All components of the data collection or analysis will be 
made available in their native format with all formulas intact, informing Avista as to how the 
calculation of energy savings is performed and allowing for independent review of ADM’s efforts. 
 Regular Updates on Impact Findings. ADM approaches the evaluation effort with the frame of 
mind that Avista should know the realized savings of the program prior to delivery of evaluation 
reporting. This will be accomplished through regular updating of all involved parties as to the 

Work Plan    7 
findings  of  the  impact  evaluation  effort.  This  allows  for  real‐time  feedback  regarding  the 
performance of varying measures or participant classes, feeding into a process of continuous 
program improvement. This also allows for Avista to conduct an independent review or quality 
check  of  ADM’s  analysis,  if  desired.  ADM’s  analysis  will  be  kept  transparent  throughout  the 
evaluation effort. 
This document contains the approach for the evaluation of Avista’s 2020 and 2021 program year. It is 
ADM’s intention to formalize this workplan in collaboration with Avista; This is a collaborative effort 
with Avista to ensure Idaho Public Utilities Commission (PUC) and Washington Utilities and 
Transportation Commission (WUTC) receives accurate and reliable program findings and that Avista 
receives meaningful insights to continue energy efficiency efforts and improve program results. ADM 
will provide comprehensive documentation and transparency for all evaluation tasks and will provide 
ongoing technical reviews and guidance throughout the evaluation cycle.  
ADM will employ the following approach to complete impact evaluation activities for the programs. 
ADM defines three major approaches to determining net savings for Avista’s programs: 
 A Deemed Savings approach involves using stipulated savings for energy conservation measures 
for which savings values are well‐known and documented. These prescriptive savings may also 
require an adjustment for certain measures, such as lighting measures in which site operating 
hours may differ from RTF values. ADM will work with Avista to identify these instances and 
develop a method for calculated an adjusted value. This approach aligns with the IPMVP Option 
A and B. 
 A Billing Analysis approach involves estimating energy savings by applying a linear regression to 
measured participant energy consumption utility meter billing data. Billing analyses may also 
include billing data from nonparticipant customers. This approach does not require on‐site data 
collection for model calibration. However, a sample of customers or sites may be selected and 
surveyed to confirm that the energy conservation measures were installed and are still operating. 
This approach aligns with the IPMVP Option C. 
 A Simulation Model Analysis approach involves a whole building simulation using the program 
REM/Rate and a User Defined Reference Home (UDRH) to compare the efficient home and the 
baseline home. The UDRH is designed as an exact replica of each program participating home in 
terms of size, structure, and climate zone. This approach aligns with the IPMVP Option D. ADM 
will apply appropriate net‐to‐gross (NTG) values to estimate net impacts. 
ADM will accomplish the following quantitative goals as part of the impact evaluation: 
 Verify savings with 10% precision at the 90% confidence level by program year; 
 Where appropriate, apply the RTF to verify measure impacts; and 
 Where available data exists, conduct billing analysis with a suitable comparison group to estimate 
measure savings. 

Work Plan    8 
1.2.2 Database Review 
At the outset of the evaluation, ADM will review the databases to ensure that each program tracking 
database conforms to industry standards and adequately tracks key data required for evaluation. ADM 
will additionally review program materials – such as program theory and logic models to identify 
potential issues and key barriers to end‐use behavior changes that could be influenced by efforts by 
each program.  
Measure‐level gross savings will be evaluated primarily by reviewing measure algorithms and values in 
the tracking system to assure that they are appropriately applied using the Avista TRM. The ADM team 
will then aggregate and cross‐check program and measure totals. The ADM team will calculate verified 
gross program savings by summing deemed kWh and Therm savings per project. 
The ADM team will clearly identify, clarify, and substantiate any variations in the savings calculations we 
uncover. We will integrate all findings into the final evaluation report. In addition to reporting the total 
gross realization rates, we will also quantify the associated impact each adjustment had on the overall 
program savings.  
1.2.3 Simple Verification Methods 
ADM will verify a sample of participating households for detailed review of the installed measure 
documentation and development of verified savings. Proposed sample sizes for documentation review is 
detailed in Table 1‐2 in the section below. ADM will work with Avista to adjust the sampling plan once 
program tracking data has been delivered and participation rates are finalized. 
ADM will also verify tracking data by reviewing invoices and surveying a sample of participant customer 
households. We will coordinate as needed with Avista’s process evaluation contractor in conducting 
participant surveys. Proposed sample sizes for documentation review are detailed in Table 1‐3 in the 
section below. The following sections describe ADM’s general methodology for conducting document‐
based verification and survey‐based verification.  
1.2.3.1 Documentation‐Based Verification 
ADM will first screen each rebate household to ensure the customer who received a measure did not 
also receive another measure that disqualifies that customer from participating in either program, such 
as the ENERGY STAR Homes rebate in combination with an HVAC rebate. Tracking data will be reviewed 
to verify each measure satisfies all program efficiency requirements. 
ADM will also request rebate documentation for a subset of participating customers. These documents 
will include invoices, rebate applications, and additional materials required for accepting rebate 
applications for each of the following programs: 
 Water Heat Program 
 HVAC Program 
 Shell Program 
 ENERGY STAR Homes Program 

Work Plan    9 
This sample of documents will be used to cross‐verify tracking data inputs. If ADM finds any deviations 
between the tracking data and application values, ADM will note and summarize these differences to 
Avista through periodic updates and the final report under each program. 
ADM will develop a sampling plan that achieves a sampling precision of ±10% with 90% statistical 
confidence – or “90/10 precision” – to estimate the percentage of projects for which the claimed savings 
are verified or require some adjustment. ADM will use the following equations to estimate sample size 
requirements for each program and fuel type. If the population of participants is small, ADM will use the 
finite population size equation. Otherwise, ADM will use the infinite population size equation. 
Equation 1‐1 Sample Size for Infinite Sample Size 
𝑛 𝑍 𝐶𝑉
𝑑 
Equation 1‐2 Sample Size for Finite Population Size 
𝑛 𝑛
1 𝑛𝑁

Where, 
n = Sample size 
𝑍 = Z‐value 
𝐶𝑉 = Coefficient of variation 
𝑑 = Precision level 
𝑁 = Population 
For a sample that provides 90/10 precision, Z = 1.645 (the critical value for 90% confidence) and d = 0.10 
(or 10% precision). The remaining parameter is CV, or the expected coefficient of variation of measures 
for which the claimed savings may be accepted. The most conservative value of CV is 0.5, as that results 
in the largest sample size. Specifically, it yields a sample size of 68 for an infinite population. In cases in 
which the participant population is small enough that Equation 1‐2 produces a smaller sample size, we 
will use that sample size.  
Based on the above considerations, ADM proposes the following sample sizes for the above programs’ 
document review (Table 1‐2). The representative participant sample will be adjusted for each of the 
programs in Washington and Idaho, by fuel type. 

Work Plan    10 
Table 1‐2: Sample Design for Document Review for Washington and Idaho Combined 
Program
Fuel Population
Sample
(With Finite Population
Adjustment)1
Water Heat Electric  127  45 
Natural Gas  957  64 
HVAC Electric  419  59 
Natural Gas  7,401  68 
Shell Electric  379  58 
Natural Gas  1,337  65 
ENERGY STAR Homes Electric  44  27 
Natural Gas  6  6 
Residential Small Home & 
MF Weatherization 
Electric  NA  NA 
Natural Gas  NA  NA 
Residential Fuel Efficiency 
Program Electric  95  40 
Low‐Income Electric  364  58 
Natural Gas  550  61 
CEEP Electric  21  17 
Natural Gas  0  0 
*Residential and Low‐Income combined 
1Assumes sample size of 68 for an infinite population, based on CV (coefficient of variation) = 0.5, d (precision) = 10%, Z (critical 
value for 90% confidence) = 1.645. 

The above values represent our preliminary sample design. ADM will work with Avista to adjust these 
sample sizes once program tracking data has been delivered for the program year in evaluation. ADM 
understands that representation of participants in each state in Avista’s service territory is critical. 
Therefore, ADM will ensure the samples for document review includes participants in both Washington 
and Idaho in addition to representation of each the electric and natural gas fuel types. 
1.2.3.2 Survey‐Based Verification 
The primary purpose of conducting a verification survey would be to confirm that the measure was 
installed and is still currently operational and whether the measure was early retirement or replace‐on‐
burnout. Units found to be inoperative prior to replacement could be re‐classifies as replace‐on‐
burnout. This would aid in providing more accurate estimation of annual savings by replacement type.  
ADM proposes to conduct survey‐based verification for the Water Heat Program and the HVAC Program. 
The evaluation of these programs would benefit from additional information from the participating 
customer on baseline equipment and home heating and cooling type. Survey responses for these 
programs may be used to confirm assumptions made during the impact analysis via billing regression. 
ADM concluded that it is unlikely a survey would provide additional insight or adjustments to the Shell 

Work Plan    11 
Program or ENERGY STAR Homes Program; therefore, these programs are not included in the survey‐
based verification effort. 
If there is reason to believe, however, that the misclassification of measures is rare, then the likely value 
of collecting such information must be weighed against the effort and cost of surveying customers. This 
is especially a concern, given that the process evaluation contactor may be fielding a survey of the same 
customer population at the same time or nearly the same time. One possible approach is for the process 
evaluation contractor to include a question about the operability of the old equipment at the time the 
new measure was purchased.  
Therefore, we suggest holding off making a final decision on fielding a survey until ADM has been able to 
confer with the process evaluation contractor. Should the decision be made to proceed with a 
verification survey, ADM will also ask the participant questions about additional details of the installed 
unit, such as sizing of furnace, model number, number of light bulbs installed, etc.  
ADM proposes the sample sizes shown in Table 1‐3 for the Water Heat and HVAC document review. The 
representative participant sample will be adjusted for each of the programs in Washington and Idaho, 
by fuel type. ADM will develop a sampling plan that achieves a sampling precision of ±10% with 90% 
statistical confidence – or “90/10 precision” – for net realized savings estimates at the measure category 
level for all significant measures during web‐based survey verification. 
Table 1‐3: Sample Design for Verification Survey for Washington and Idaho Combined 
Program Fuel Survey Verification Goal
Water Heat Electric  45 
Natural Gas  64 
HVAC Electric  59 
Natural Gas  68 
Fuel Efficiency  Electric  40 
The above values represent our preliminary sample design. ADM will work with Avista to adjust these 
sample sizes during the kickoff meeting and the formation of Avista’s Electric and Natural Gas 
Residential EM&V Plan for Idaho and Washington. 
ADM will develop the web‐based verification guide for review and comment by Avista staff prior to 
deploying these verification surveys. ADM will employ our in‐house survey research center to support all 
survey‐based data collection efforts. In cases where the web‐based survey response does not meet 
sampling target, ADM will use our in‐house survey research center to reach out to customers via phone 
call.  
ADM will develop a sampling plan that achieves 90/10 precision at the measure category level for all 
significant measures during web‐based survey verification. The selected sample participants will be 
offered a $10 gift card incentive to participate in the verification survey. In the case the targeted 
number of web‐based survey completes is not reached, ADM will supplement with phone interviews to 
reach the 90/10 precision goal. 

Work Plan    12 
These surveys will be designed to ensure that best practices and lessons learned from individual 
programs are then shared and incorporated across the entire program portfolio. In order to facilitate 
evaluation among and between programs, customer surveys will contain a standard set of questions to 
be addressed across all Avista programs.  
The findings from these activities will serve to: 
 Verify measure was installed 
 Verify measure is functional 
 Gather pre‐retrofit equipment information 
 Gather retrofit equipment information 
1.2.4 Impact Evaluation Methods 
ADM will employ the following approach to complete impact evaluation activities for the programs. 
ADM defines three major approaches to determining net savings for Avista’s programs: 
 Deemed Savings  
 Billing Analysis  
 Simulation Model Analysis 
ADM will also estimate gross savings for all measures that require billing analyses for planning purposes 
at the request of Avista.  
In the following sections, we summarize the general guidelines and activities ADM will follow to conduct 
each of the above analyses. 
1.2.4.1 Deemed Savings 
This section summarizes the deemed savings analysis method ADM will employ for the evaluation of a 
subset of measures for each program. ADM will complete the validation for specific measures across 
each program using the RTF unit energy savings (UES) values, where available. The goal is to ensure that 
the proper measure unit savings were recorded and used in the calculation of Avista’s ex‐ante measure 
savings. ADM will request and use the RTF document version Avista employed during calculation of ex‐
ante measure savings. The ADM team will document any cases where we recommend values differing 
from the specific unit energy savings workbooks used by Avista.  
In cases where the RTF has existing unit energy savings (“UES”) applicable to Avista’s measures, ADM 
will verify the quantity and quality of installations and apply the RTF’s UES to determine verified savings. 
If we find any projects that do not use the RTF values, we will complete additional investigation and 
review of measures with custom savings inputs through engineering algorithms. ADM understands that 
for measures using RTF UES, no NTG adjustments are necessary. 
ADM will verify the following home specifications, as required by the RTF: 
 Verify heating system type 
 Verify heating and cooling zone 

Work Plan    13 
ADM will review program application documents for a sample of incented measures to verify the 
tracking data accurately represents the program documents. ADM will ensure the home installed 
measures that meet or exceed program efficiency standards.  
1.2.4.2 Billing Analysis 
This section summarizes the general billing analysis methods ADM will employ for the evaluation of a 
subset of measures for each program. For further details on the specific model specifications to be 
explored for each measure, see Section 1.3.  
For the purposes of this summary, a household is considered a treatment household if it has received a 
program incentive. Additionally, a household is considered a control household if the household has not 
received a program incentive. To conduct a linear regression billing analysis for energy efficiency 
measures, ADM requires billing data for a control group to compare against treatment households via 
quasi‐experimental methods. The evaluation team will request billing data for nonparticipant customers 
to serve as the control group. This method assumes Avista is able to provide consumption data for a 
group of similar non‐participating customers in the service area. 
ADM will attempt to create a statistically similar control group using propensity score matching (PSM), a 
method that allows the evaluators to find the most similar nonparticipant customer households based 
on a range of independent variables. ADM has extensive experience conducting propensity score 
matching for residential program billing analyses of similar measures and is familiar with the 
implications and uncertainties involved in this type of analysis. ADM will use available datasets to ensure 
the control households are similar to the treatment homes, using variables such household square 
footage, household heating type, household occupancy date, household zip code, and any other 
information available for the nonparticipant customers specific to the program. For example, to create a 
sufficient counterfactual group for the Low‐Income Program, ADM will request flags for income 
eligibility across nonparticipant customers.  
Further information on the selection of customers for a counterfactual control group is detailed below, 
as well as potential risks and implications. If a sufficient control group can be constructed, ADM will 
compare participant billing data to the control billing data, as detailed in IPMVP Option C. ADM will fit a 
regression model to estimate weather‐dependent daily consumption differences between participating 
customer households and nonparticipating customer households. ADM will include independent 
variables such as Heating Degree Days for weather controls, square footage, and other household 
characteristics where applicable to improve model confidence. We will tailor our regression model 
specifications to each program and measure. ADM will explore the following regression models: 
 Fixed effect Difference‐in‐Difference (D‐n‐D) regression model (recommended in UMP protocols) 
 Random effects post‐program regression model (recommended in UMP protocols) 
Further details on model specifications can be found below. It is important to note that because whole 
household consumption is used, the savings value includes the positive or negative effects of any non‐
measure changes made in the household. This option is used to determine the collective savings of all 
measures applied to the program‐participating household by the energy meter. Therefore, ADM will 
attempt to isolate households that have installed only the measure in evaluation. For example, in 

Work Plan    14 
evaluating the furnace measure in billing analyses, ADM will exclude households that have also installed 
an incented water heater in order to effectively isolate the effects of the furnace retrofit.  
The period of billing data should cover the same timeframe for both groups. To evaluate the 2020 and 
2021 program years, ADM will request billing data ranging from at least one year prior to measure 
intervention (i.e. date measure was installed, or date household was built) through the most recent date 
available from each household.  
The following lists the data requirements for billing analysis: 
1. Monthly billing data for program participants (treatment) 
2. Monthly billing data for a group of non‐program participants (control) 
3. Household‐level data provided by Avista and public sources relevant to program requirements 
and targeted customers 
The following steps will be taken to prepare data: 
1. Gather billing data for homes that participated in the program. 
2. Exclude  participant  homes  that  also  participated  in  the  other  programs,  if  either  program 
disqualifies the combination of any other rebate or participation. 
3. Gather billing data for similar customers that did not participate in the program in evaluation 
4. Create a matched control group using non‐participant billing and customer and/or household 
characteristic data. 
5. Exclude homes missing sufficient billing data. 
6. Exclude bills with consumption indicated to be outliers. 
ADM will report parameters necessary to portray model accuracy and significance such as coefficient p‐
values, adjusted R‐squared values, and household‐level and program‐level kWh and Therm savings at 
the 90% confidence intervals for each state. Program‐year savings estimates at the monthly‐ and 
annual‐level will also be reported for each state and fuel type. 
One major caveat of this method is that we must be able to gather a sufficiently large sample of control 
households that are statistically similar to the treatment households. If the nonparticipant homes are 
statistically different from the participant homes in the pre‐treatment period, this analytical approach 
will not provide meaningful results and ADM will therefore validate savings via RTF or Avista TRM 
engineering algorithms as well as additional literature review.  
Billing analysis with a valid counterfactual group can provide reliable net impact estimates at the 
measure‐level and program‐level. However, the success of a billing analysis depends on the availability 
of several key factors: 
 A sufficient number of customers have installed the measure to isolate measure‐level savings; 
 A  sufficient  number  of  similar  nonparticipant  customers  can  be identified  and  used  towards 
propensity score matching to create a valid counterfactual group for the measure;  
 Install dates for the measure display sufficient variability; and 

Work Plan    15 
 Historical billing data is available for at least one year prior to customer install dates. 
ADM will also conduct an additional billing analysis for these measures to estimate gross savings. This 
analysis is very similar to the net estimate methodology, but it will not require the use of a 
counterfactual control group. 
ADM provides further detail on the implications of each of the components listed above. 
Comparison Group 
To estimate reliable net impacts through billing analysis, a similar counterfactual group must be 
selected. In program designs where treatment and control customers are not randomly selected at the 
outset, such as for downstream rebate programs, quasi‐experimental designs are required. ADM 
proposes to construct a comparison group of nonparticipants who are similar to participants and reflect 
the counterfactual condition. ADM aims to achieve this by selecting customers from one of the two 
following options: 
 Future program participants or 
 Nonparticipants selected through propensity score matching (PSM)  
For the prior case, ADM would isolate customers that participated later in the program year as the 
control group to compare against customers that participated earlier in the program year (the treatment 
group). ADM will then verify that the treatment and control groups display similar pre‐period average 
daily consumption through t‐testing and run a linear regression model to estimate the measure effect 
on consumption in the post‐period. 
In the latter case, ADM will use propensity‐scoring matching (PSM) to match nonparticipants to similar 
participants using pre‐period data, test the validity of the matches with t‐testing, and run a linear 
regression to estimate the measure effect. PSM allows the evaluators to find the most similar household 
based on the customers’ billed consumption trends in the pre‐period and verified with statistical 
difference testing.  
A propensity score is a metric that summarizes several dimensions of household characteristics into a 
single metric that can be used to group similar households. ADM will create a post‐hoc control group by 
compiling billing data from a subset of nonparticipants in the Avista territory to compare against 
treatment households using quasi‐experimental methods. This will allow ADM to select from a large 
group of similar households that have not installed an incented measure. With this information, ADM 
will attempt to create a statistically valid matched control group via seasonal pre‐period usage. After 
matching, ADM will conduct a t‐test for each month in the pre‐period to help determine the success of 
PSM. 
After creating a PSM control group, ADM will carry out linear regression modeling on the treatment and 
matched control group. 
For measures that are active during the heating season only, such as the air source heat pump or 
furnace, ADM will include heating degree days in the model specification. For measures that are active 
during the heating season and cooling season, such as water heaters and thermostats, ADM will include 
heating degree days and cooling degree days in the model specification. 

Work Plan    16 
In addition, ADM will test and select the optimal temperature base for heating degree days and cooling 
degree days based on model R‐squared values. ADM will select a value between 60‐ and 80‐degrees 
Fahrenheit that displays the optimal model R‐squared value. The selected base temperature therefore 
maximizes the total variation the model is able to explain. 
Fixed Effects Difference‐in‐Difference Regression Model 
To calculate the impacts of each measure, ADM will apply a linear fixed effects regression using 
participant and nonparticipant billing data with weather controls in the form of Heating Degree Days 
(HDD) and Cooling Degree Days (CDD). The following equation displays the model specification to 
estimate the average daily savings due to the measure. 
Equation 1‐3: Fixed Effects Difference‐in‐Difference (D‐n‐D) Model Specification 
𝐴𝐷𝐶 𝛼 𝛽𝑃𝑜𝑠𝑡 𝛽𝑃𝑜𝑠𝑡 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 𝛽𝐻𝐷𝐷 𝛽𝐶𝐷𝐷
𝛽𝑃𝑜𝑠𝑡 𝐻𝐷𝐷 𝛽𝑃𝑜𝑠𝑡 𝐶𝐷𝐷 𝛽𝑃𝑜𝑠𝑡 𝐻𝐷𝐷 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡
𝛽𝑃𝑜𝑠𝑡 𝐶𝐷𝐷 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 𝛽𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦 𝜀
Where, 
𝐴𝐷𝐶 = Estimated average daily consumption (dependent variable) in home i during period t 
𝑃𝑜𝑠𝑡 = A dummy variable indicating pre‐ or post‐period designation during period t at home i 
𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 = A dummy variable indicating treatment status of home i 
𝐻𝐷𝐷 = Average heating degree days (base with optimal Degrees Fahrenheit) during period t at home i 
𝐶𝐷𝐷 = Average cooling degree days (base with optimal Degrees Fahrenheit) during period t at home i 
𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦= A dummy variable indicating customer‐specific identifier at home i 
𝜀 = Customer‐level random error 
𝛼= The model intercept for home i 
𝛽 = Coefficients determined via regression 
The Average Daily Consumption (ADC) is calculated as the total monthly billed usage divided by the 
duration of the bill month. 𝛽 represents the average change in daily baseload in the post‐period 
between the treatment and control group and 𝛽 and 𝛽 represent the change in weather‐related daily 
consumption in the post‐period between the groups. Typical monthly and annual savings will then be 
estimated by extrapolating the 𝛽 and 𝛽 coefficients with Typical Meteorological Year (TMY) HDD and 
CDD data or actual weather displayed in the program year, gathered from NOAA. Note that the 
Treatment term is dropped from the model specification due to fixed effects. This term is not included 
because it would be collinear with the customer‐specific dummy variable. 
This option is used to determine the collective savings of all measures applied to the program‐
participating household by the energy meter. It is important to note that because whole household 
consumption is used, the savings value includes the positive or negative effects of any non‐measure 
changes made in the household.  

Work Plan    17 
Random Effects Post‐Program Regression Model 
ADM will also explore the post‐program regression model with random effects to estimate net program 
savings. The post‐program regression (PPR) model combines both cross-sectional and time series data in 
a panel dataset. This model uses only the post-program data, with lagged energy use for the same 
calendar month of the pre-program period acting as a control for any small systematic differences 
between the treatment and control customers; in particular, energy use in calendar month t of the post-
program period is framed as a function of both the participant variable and energy use in the same 
calendar month of the pre-program period. The underlying logic is that systematic differences between 
treatment and control customers will be reflected in the differences in their past energy use, which is 
highly correlated with their current energy use. These interaction terms allow pre-program usage to 
have a different effect on post-program usage in each calendar month. 
The model specification is as follows: 
Equation 1‐4 Post‐Program Regression (PPR) Model Specification 
𝐴𝐷𝐶 𝛼 𝛽𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 
𝛽 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒 
𝛽 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟 
𝛽𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟 
𝛽𝑀𝑜𝑛𝑡ℎ 
𝛽𝑀𝑜𝑛𝑡ℎ 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒 
𝛽𝑀𝑜𝑛𝑡ℎ 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟 
𝛽𝑀𝑜𝑛𝑡ℎ 𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟 
𝜀 
Where, 
i = the ith household 
t = the first, second, third, etc. month of the post‐treatment period 
𝐴𝐷𝐶 = Average daily usage for reading t for household i during the post‐treatment period 
𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 = Dummy variable indicating whether household i was in the treatment or control 
group 
𝑀𝑜𝑛𝑡ℎ = Dummy variable indicating month‐year of month t 
𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒 = Average daily usage across household i’s available pre‐treatment billing reads 
𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑆𝑢𝑚𝑚𝑒𝑟 = Average daily usage in the summer months across household i’s available 
pre‐treatment billing reads 

Work Plan    18 
𝑃𝑟𝑒𝑈𝑠𝑎𝑔𝑒𝑊𝑖𝑛𝑡𝑒𝑟 = Average daily usage in the winter months across household i’s available 
pre‐treatment billing reads 
𝜀 = Customer‐level random error 
𝛼= The model intercept for home i 
𝛽 = Coefficients determined via regression 
The coefficient 𝛽 represents the average change in consumption between the pre‐period and post‐
period for the treatment group. 
In this specification, savings are calculated by: 
Equation 1‐5 Monthly Savings Estimate 
𝑆𝑎𝑣𝑖𝑛𝑔𝑠 𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 𝐶𝑜𝑒𝑓𝑓 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑟𝑒𝑐𝑖𝑝𝑖𝑒𝑛𝑡𝑠 𝑖𝑛 𝑚𝑜𝑛𝑡ℎ 𝑖
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑑𝑎𝑦𝑠 𝑖𝑛 𝑚𝑜𝑛𝑡ℎ 𝑖 
Gross Billing Analysis 
The sections above detail ADM’s methodology for estimating net energy savings for each measure. The 
results of the above methodology report net savings due to the inclusion of the counterfactual 
comparison group. However, for planning purposes, it would also be useful to estimate gross savings for 
each measure. To estimate gross savings, ADM will employ similar regression models, but only with the 
participant customer billing data. This analysis will not include any control group billing data and will 
only model energy reductions between the pre‐period and post‐period for the measure participants. 
To calculate the impacts of each measure, ADM will apply a linear fixed effects regression using 
participant billing data with weather controls in the form of Heating Degree Days (HDD) and Cooling 
Degree Days (CDD). The following equation displays the model specification to estimate the average 
daily savings due to the measure. 
Equation 1‐6: Treatment‐Only Fixed Effects Weather Model Specification 
𝐴𝐷𝐶 𝛼 𝛽𝑃𝑜𝑠𝑡 𝛽𝐻𝐷𝐷 𝛽𝐶𝐷𝐷 𝛽𝑃𝑜𝑠𝑡 𝐻𝐷𝐷 𝛽𝑃𝑜𝑠𝑡 𝐶𝐷𝐷
𝛽𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦 𝜀
ADM also will explore the monthly regression model rather than degree days to estimate gross program 
savings.
Equation 1‐7 Treatment‐Only Fixed Effects Monthly Model Specification 
𝐴𝐷𝐶 𝛼 𝛽𝑃𝑜𝑠𝑡 𝛽𝑀𝑜𝑛𝑡ℎ 𝛽𝑀𝑜𝑛𝑡ℎ 𝑃𝑜𝑠𝑡 𝛽𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝐷𝑢𝑚𝑚𝑦 𝜀 
ADM will test and select the optimal regression model and temperature base for heating degree days 
and cooling degree days based on model R‐squared values.  
The results of the treatment‐only regression models will be gross savings estimates. The gross savings 
estimates will be useful to compare against the net savings estimates. However, the treatment‐only 
models are unable to separate the effects of the COVID19 pandemic. The post‐period for PY2020 and 

Work Plan    19 
perhaps also PY2021 will be affected by the stay‐at‐home orders that had taken effect starting March 
2020 in Idaho and Washington. The stay‐at‐home orders most likely will affect the post‐period 
household usage. Because there is insufficient post‐period data before the shelter‐in‐place orders, ADM 
is unable to separate the effects on consumption due to the orders and the effects on consumption due 
to the measure installation. Therefore, the results from this additional gross savings analysis are unable 
to reflect actual typical year savings.   
1.2.4.3 Simulation Model Analysis 
ADM provides the following method for deriving savings from the ENERGY STAR Homes Program. This 
method involves a whole building simulation (IPMVP Option D) in addition to a billing analysis with a 
counterfactual control group.  
The simulation analysis results in gross savings estimates whereas a billing analysis with a control group 
results in net savings estimates. Therefore, ADM will use a simulation analysis with a net‐to‐gross (NTG) 
savings adjustment or a billing analysis with a counterfactual control group. 
This approach involves the comparison of participating homes with a User Defined Reference Home 
(UDRH). The methodology detailed in this section is supported by the IPMVP Option D as a whole 
building simulation using calibrations. ADM will use the simulation models to compare a sample of 
participating homes with a User Defined Reference Home (UDRH), an agreed upon set of efficiency 
standards built to represent the baseline residential home in the region. The UDRH is defined in more 
detail in the following subsection.  
ADM will use the program REM/Rate to complete whole building simulation modeling efforts. The UDRH 
feature in REM/Rate allows energy consumption to be calculated using energy efficiency input values for 
both the efficient home and the baseline home. The UDRH will be designed as an exact replica of each 
program participating home in terms of size, structure, and climate zone. However, instead of using the 
actual HERS‐rated efficiency values, we use the energy codes defined in the UDRH. ADM will gather 
energy characteristics for the efficient, rated home by requesting HERS datafiles from the certified HERS‐
raters or by gathering information from the HERS certificates required by the program and provided by 
Avista. 
To calculate the gross savings for a given home, first, the as‐built home is verified using building 
characteristics found in supporting documentation. Once the efficient home is modeled, the energy 
model calculates the unadjusted gross savings by subtracting the energy use of the as‐built home from 
the energy use of its UDRH baseline home. This method provides a reliable and supported means of 
verifying gross residential new construction home savings.  
Energy savings will be calculated per‐home with the following calculation: 
Equation 1‐8: Whole Building Model Energy Savings 
𝐸𝑛𝑒𝑟𝑔𝑦 𝑆𝑎𝑣𝑖𝑛𝑔𝑠 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛
Where, 

Work Plan    20 
𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 = Simulated energy consumption values from REMRate for a household under the 
UDRH efficient code standards 
𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛  = Simulated energy consumption from REM/Rate for a household built 
referencing the HERS certification values 
ADM defines the UDRH used to evaluate simulated savings in the following section. 
User Defined Reference Home (UDRH) 
The UDRH represents a home built to meet the state of Idaho’s and Washington’s current minimum 
energy efficiency code requirements. Idaho uses the residential 2015 International Energy Conservation 
Code (IECC) with amendments3 for newly constructed residential homes until January 1, 2021. Starting 
in 2021, Idaho will use the residential 2018 IECC with Idaho amendments. ADM will use the residential 
2015 IECC with Idaho‐specific amendments efficiency values to create the UDRH when evaluating homes 
built in Idaho during the 2020 program year and the 2018 IECC with Idaho‐specific amendments when 
evaluating homes built in Idaho during the 2021 program year. This comparison will provide an accurate 
simulation of a newly constructed minimum efficient code residential home to compare against 
efficiency, program‐participating homes. For homes built in Avista’s territory in Washington state lines, 
ADM will create a UDRH based on Washington residential building codes, which are modeled after 
International Residential Code (IRC) 2015. 
Realization rates from the home‐level analyses can be used to provide strategic guidance for program 
improvement. We will examine realization rates for commonalities among home builders or HERS raters 
and inform Avista if any program partner demonstrates a statistically significant increased likelihood of 
association with low realization rates. We will then review the home results in further detail to identify a 
root‐cause (errors in model input, construction practice, equipment sizing, etc.) 
1.2.5 Net‐To‐Gross 
The Northwest RTF UES measures do not require NTG adjustments. In addition, billing analyses with 
counterfactual control groups, as proposed in our impact methodology, does not require a NTG 
adjustment, as the counterfactual represents the efficiency level at current market (i.e. the efficiency 
level the customer would have installed had they not participated in the program). 
However, the simulation model analysis presented for the ENERGY STAR Homes Program results in gross 
savings estimates.  
1.2.6 Cost‐Effectiveness Tests 
ADM will calculate each program’s cost‐effectiveness, avoided energy costs, and implementation costs. 
ADM will use our ADM‐developed cost‐effectiveness tool to provide cost‐effectiveness assessments for 
the Residential Portfolio by program, fuel type, program year, and measure, for each state.  
As specified in this solicitation, ADM will determine the economic performance with the following cost‐
effectiveness tests: 

3 https://www.energycodes.gov/adoption/states/idaho 

Work Plan    21 
 Total Resource Cost (TRC) test; 
 Utility Cost Test (UCT); 
 Participant Cost Test (PCT); 
 Rate Impact Measure (RIM) test; and 
 Resource Valuation Test (RVT). 
1.2.7 Non‐Energy Benefits 
ADM will use the Regional Technical Forum (RTF) to quantify non‐energy benefits (NEBs) for residential 
measures with established RTF values where available. Measures with quantified NEBs include 
residential insulation, high efficiency windows, air source heat pumps, and ductless heat pumps. ADM 
understands the RTF provides NEB values for electric measures, but not natural gas measures.  
In addition to the residential NEBs, ADM will apply the end‐use non‐energy benefit and health and 
human safety non‐energy benefit to the Low‐Income Program. ADM understands that the two major 
non‐energy benefits referenced above are uniquely applicable to the Low‐Income Program. ADM will 
apply those benefits to the program impacts as well as additional non‐energy benefits associated with 
individual measures included in the program. 
ADM will incorporate additional NEBs to the impact evaluation, as applicable and under guidance from 
Avista.  
1.3 Program‐Level EM&V Approaches 
ADM presents a summary of the program‐specific impact evaluation work procedures. ADM will work 
with Avista to adjust program‐specific impact and sampling plans as additional information is received 
about program participation, program restrictions, measure offerings, and available data. 
1.3.1 Water Heat Program 
The Water Heat Program encourages customers to replace their existing electric or natural gas water 
heater with high efficiency equipment. Customers receive incentives after installation and after 
submitting a completed rebate form. Table 1‐4 summarizes the measures offered under this program.  
  Table 1‐4: Water Heat Program Measures 
Measure Impact Analysis
Methodology
Electric Water Heater (0.94 EF or higher)  Billing Analysis 
Natural Gas Water Heater (0.60 EF or higher)  Billing Analysis 
Natural Gas Tankless Water Heater (0.82 EF or higher)  Billing Analysis 
ADM summarizes the program‐specific and measure‐specific impact analysis activities and requirements 
for the Water Heat Program in the section below. 

Work Plan    22 
1.3.1.1 Database Review & Verification 
Before conducting the impact analysis, ADM will conduct a database review for the Water Heat 
Program. ADM will select a subset of rebate applications to cross‐verify tracking data inputs, 
summarized in Table 1‐2. If ADM finds any deviations between the tracking data and application values, 
ADM will note and summarize these differences to Avista through periodic updates and the final report. 
In addition, ADM will randomly select a subset of participant customers to survey for simple verification 
of installed measure, displayed in Table 1‐3. ADM will include questions such as: 
 Was this water heater a new construction, or did it replace another water heater? 
 Was the previous water heater functional? 
 Is the newly installed water heater still properly functioning? 
 What is the efficiency and sizing of the newly installed water heater? 
These questions will help ADM verify that the measure was documented accurately and that data 
collection activities are progressing smoothly for the program. In addition, in the event that billing 
analysis is infeasible, this simple verification will help ADM more accurately estimate measure‐level 
impacts using engineering algorithms. 
1.3.1.2 Impact Analysis 
ADM will conduct a billing analysis regression using with a counterfactual group selected via propensity 
score matching on each of the water heater measures in the Water Heat Program. ADM will isolate each 
unique measure and verify the participant did not also participate in other programs; therefore, ADM 
will be able to isolate the measure effects using the customer’s consumption billing data.  
ADM will attempt to create a valid quasi‐experimental control group using nonparticipant customer data 
and available household characteristics. ADM will work with Avista to identify household characteristics 
the Water Heat Program targets in order to identify nonparticipant customers similar to program 
participants. ADM will then explore the linear regressions summarized in Section 1.2.4.2 with controls 
for HDD and CDD to estimate weather‐related impacts from each measure. ADM will summarize the 
measure‐level impacts by extrapolating regression coefficients with TMY data or actual weather data. 
1.3.1.3 Required Data 
ADM requires the following data to complete the analysis for this program: 
 Program tracking data, including customer identifiers, address, and date of measure install 
 Filled rebate application forms and applicable invoices 
 Monthly billed consumption data for participating customers 
 Monthly billed consumption data for non‐participating customers 
In addition, ADM will gather the following datasets to complete the analysis: 
 Historical NOAA weather data 
 Typical Meteorological Year weather data 
 Publicly available household characteristics from county assessor data, if available 

Work Plan    23 
1.3.1.4 Technical Comments 
In the event that the required data is not available or sufficient to conduct a billing regression analysis, 
ADM will review RTF values and Avista TRM methods along with verified tracking data to estimate net 
program savings. 
1.3.2 HVAC Program 
The HVAC program encourages installation of high efficiency HVAC equipment and smart thermostats 
through customer incentives. The program is available to residential electric or natural gas customers 
with a winter heating season usage of 4,000 or more kWh, or at least 160 Therms of space heating in the 
prior year. Existing or new construction homes are eligible to participate in the program. Table 1‐5 
summarizes the measures offered under this program. 
Table 1‐5: HVAC Program Measures 
Measure Impact Analysis Methodology
Variable speed motor  Billing Analysis 
Electric to air source heat pump  Billing Analysis 
High efficiency natural gas furnace  Billing Analysis 
High efficiency natural gas boiler  Billing Analysis 
Smart thermostat  RTF UES 
ADM summarizes the program‐specific and measure‐specific impact analysis activities and requirements 
for the HVAC Program in the section below. 
1.3.2.1 Database Review & Verification 
Before conducting the impact analysis, ADM will conduct a database review for the HVAC Program. ADM 
will select a subset of rebate applications to cross‐verify tracking data inputs, summarized in Table 1‐2. If 
ADM finds any deviations between the tracking data and application values, ADM will note and 
summarize these differences to Avista through periodic updates and the final report. 
In addition, ADM will randomly select a subset of participant customers to survey for simple verification 
of installed measure, displayed in Table 1‐3. ADM will include questions such as: 
 What type of thermostat did this thermostat replace? 
 Is your home heating with electricity, natural gas, or another fuel? 
 Was the previous equipment functional? 
 Is the newly installed equipment still properly functioning? 
These questions will help ADM verify that the measure was documented accurately and that data 
collection activities are progressing smoothly for the program. The verification for smart thermostats 
will allow ADM to calculate measure‐level savings more accurately. In addition, in the event that billing 
analysis is infeasible, this simple verification will help ADM more accurately estimate measure‐level 
impacts for the other measures using engineering algorithms. 

Work Plan    24 
1.3.2.2 Required Data 
ADM requires the following data to complete the analysis for this program: 
 Program tracking data, including customer identifiers, address, and date of rebate 
 Rebate application forms and applicable invoices 
 Monthly billed consumption data for participating customers 
 Monthly billed consumption data for non‐participating customers 
In addition, ADM will gather the following datasets to complete the analysis: 
 Historical NOAA weather data 
 Typical Meteorological Year weather data 
 Publicly available household characteristics from county assessor data, if necessary 
1.3.2.3 Impact Analysis 
ADM will conduct billing analysis regression using with a counterfactual group selected via propensity 
score matching on the HVAC measures in the HVAC Program listed in Table 1‐5. The smart thermostat 
measure will be estimated using RTF UES values. ADM will apply the RTF UES values to the types and 
quantities of each connected thermostat, after applying adjustments from verification surveys, if found.  
In order to estimate daily impacts of each measure, ADM will isolate the customers that received an 
isolated measure. For example, to evaluate the air source heat pump measure, ADM will select only 
customers that have retrofitted their air source heat pump and have not installed any additional 
program measures during the same program year. ADM will connect these isolated customers to billing 
data, provided by Avista as well as historical weather data collected from NOAA. ADM will conduct 
billing cleaning and estimate fixed‐effects panel regression models referenced in Section 1.2.4.2 with 
heating season and cooling season controls to estimate the relationship between the energy 
consumption and weather during the pre‐ and post‐periods, for electric or gas, as applicable to the 
measure. 
1.3.2.4 Technical Comments 
In the event that the required data is not available or sufficient to conduct a billing regression analysis, 
ADM will review RTF UES values and Avista TRM methods along with verified tracking data to estimate 
net program savings. 
1.3.3 Shell Program 
The Shell Program provides incentives to customers for improving the integrity of the home’s envelope 
with upgrades to windows and storm windows. Rebates are issued after the measure has been installed 
for insulation and window measures. Participating homes must have electric or natural gas heating and 
itemized invoices including measure details such as insulation levels, window values, and square 
footage. In order to be eligible for incentive, the single‐family households, including fourplex or less, 
must demonstrate an annual electricity usage of at least 8,000 kWh or an annual gas usage of at least 
340 Therms. Multifamily homes have no usage requirement. This program includes free manufactured 

Work Plan    25 
home duct sealing implemented by UCONS. Table 1‐6 summarizes the measures offered under this 
program. 
Table 1‐6: Shell Program Measures 
Measure Impact Analysis Methodology
Attic insulation  RTF UES 
Wall insulation  RTF UES 
Floor insulation  RTF UES 
Window insulation  RTF UES 
Low‐E Storm Windows  RTF UES 
Manufactured home duct sealing  Billing Analysis 
ADM will attempt to isolate the duct sealing measure in order to isolate the performance of the duct 
improvement measure. 
1.3.3.1 Database Review & Verification 
Before conducting the impact analysis, ADM will conduct a database review for the Shell Program. ADM 
will select a subset of rebate applications to cross‐verify tracking data inputs, summarized in Table 1‐2. If 
ADM finds any deviations between the tracking data and application values, ADM will note and 
summarize these differences to Avista through periodic updates and the final report. 
In addition, ADM will randomly select a subset of participant customers to survey for simple verification 
of installed measure, displayed in Table 1‐3. ADM will include questions such as: 
 When did the weatherization measures get installed? 
 What type of fuel is used to heat your home? 
 Does your home have central air conditioning, window, or neither? 
 How long did the contractors take to complete the work? 
These questions will help ADM verify that the measure was documented accurately and that data 
collection activities are progressing smoothly for the program. The verification of heating and cooling 
type will allow ADM to calculate measure‐level savings more accurately based on RTF value. In addition, 
in the event that billing analysis is infeasible, this simple verification will help ADM more accurately 
estimate measure‐level impacts for the other measures using engineering algorithms. 
1.3.3.2 Required Data 
ADM requires the following data to complete the analysis for this program: 
 Program tracking data, including customer identifiers, address, and date of rebate 
 Rebate application forms and applicable invoices 
 Monthly billed consumption data for participating customers 
 Monthly billed consumption data for non‐participating customers 
In addition, ADM will gather the following datasets to complete the analysis: 

Work Plan    26 
 Historical NOAA weather data 
 Typical Meteorological Year weather data 
 Publicly available household characteristics from county assessor data, if necessary 
1.3.3.3 Impact Analysis 
ADM will conduct billing analysis regression using with a counterfactual group selected via propensity 
score matching on the duct sealing measure in the Shell Program listed in Table 1‐6. The remaining 
measures will be estimated using RTF UES values. ADM will apply the RTF UES values to the types and 
quantities of each measure, after applying adjustments from database review and verification surveys, if 
necessary.  
In order to estimate daily impacts of each measure, ADM will isolate the customers that received an 
isolated measure. For example, to evaluate the duct sealing measure, ADM will select only customers 
that have installed the duct sealing measure and have not installed any additional program measures 
during the same program year. ADM will connect these isolated customers to billing data, provided by 
Avista as well as historical weather data collected from NOAA. ADM will conduct billing cleaning and 
estimate fixed‐effects panel regression models referenced in Section 1.2.4.2 with heating season and 
cooling season controls to estimate the relationship between the energy consumption and weather 
during the pre‐ and post‐periods, for electric or gas, as applicable to the duct sealing measure. 
1.3.3.4 Technical Comments 
In the event that the required data is not available or sufficient to conduct a billing regression analysis 
for duct sealing, ADM will review RTF UES values and Avista TRM methods along with verified tracking 
data to estimate net program savings. 
1.3.4 Residential Fuel Efficiency Program 
The Residential Fuel Efficiency Program encourages customers to consider converting their resistive 
electric space and water heating equipment to natural gas. This program is offered to residential 
customers in the Idaho service territory. Customers must use Avista electricity for electric straight‐
resistance heating or water heating in order to qualify for the rebate, which is verified by evaluating 
their energy use. The home’s electric baseboard or furnace heat consumption must indicate at least 
8,000 kWh during the previous heating season. Customers receive incentives after installation and after 
submitting a completed rebate form. Table 1‐4 summarizes the measures offered under this program.  
  Table 1‐7: Residential Fuel Efficiency Program Measures 
Measure Impact Analysis
Methodology
Electric central ducted forced air furnace to air source heat pump (9.0 HFSP or greater)  Billing Analysis 
Electric baseboard or forced air furnace heat to natural gas forced air furnace  Billing Analysis 
Electric to natural gas furnace and water heat combo  Billing Analysis 
ADM summarizes the program‐specific and measure‐specific impact analysis activities and requirements 
for the Residential Fuel Efficiency Program in the section below. 

Work Plan    27 
1.3.4.1 Database Review & Verification 
Before conducting the impact analysis, ADM will conduct a database review for the Residential Fuel 
Efficiency Program. ADM will select a subset of rebate applications to cross‐verify tracking data inputs, 
summarized in Table 1‐2. If ADM finds any deviations between the tracking data and application values, 
ADM will note and summarize these differences to Avista through periodic updates and the final report. 
There will be no verification surveys for this program. 
1.3.4.2 Impact Analysis 
ADM will conduct a billing analysis regression using with a counterfactual group selected via propensity 
score matching on each of the water heater measures in the Residential Fuel Efficiency Program. ADM 
will isolate each unique measure and verify the participant did not also participate in other programs; 
therefore, ADM will be able to isolate the measure effects using the customer’s consumption billing 
data.  
ADM will attempt to create a valid quasi‐experimental control group using nonparticipant customer data 
and available household characteristics. ADM will work with Avista to identify household characteristics 
the Residential Fuel Efficiency Program targets in order to identify nonparticipant customers similar to 
program participants. ADM will then explore the linear regressions summarized in Section 1.2.4.2 with 
controls for HDD and CDD to estimate weather‐related impacts from each measure. ADM will 
summarize the measure‐level impacts by extrapolating regression coefficients with TMY data or actual 
weather data. 
1.3.4.3 Required Data 
ADM requires the following data to complete the analysis for this program: 
 Program tracking data, including customer identifiers, address, and date of measure install 
 Filled rebate application forms and applicable invoices 
 Monthly billed consumption data for participating customers 
 Monthly billed consumption data for non‐participating customers 
In addition, ADM will gather the following datasets to complete the analysis: 
 Historical NOAA weather data 
 Typical Meteorological Year weather data 
 Publicly available household characteristics from county assessor data, if available 
1.3.4.4 Technical Comments 
In the event that the required data is not available or sufficient to conduct a billing regression analysis, 
ADM will review RTF values and Avista TRM methods along with verified tracking data to estimate net 
program savings. 

Work Plan    28 
1.3.5 ENERGY STAR Homes Program 
The Energy Star Homes Program provides rebates for homes within Avista’s service territory that attain 
an ENERGY STAR certification.  This program incentivizes for ENERGY STAR Eco‐rated homes. Table 1‐8 
summarizes the measures offered under this program. 
  Table 1‐8: HVAC Program Measures 
Measure Impact Analysis Methodology
ENERGY STAR ECO‐rated home  Simulation Model Analysis 
ENERGY STAR‐rated manufactured home  RTF UES 
ADM will verify a sample of participating homes for detailed review of the home’s documentation and 
development of a simulation model. ADM will work with Avista to make adjustments to the sampling 
plan summarized in Table 1‐3 and create an approved sampling plan and stratification method for the 
measure before submitting a data request.  
1.3.5.1 Database Review & Verification 
Before conducting the impact analysis, ADM will conduct a database review for the ENERGY STAR 
Homes Program. ADM will select a subset of rebate applications to cross‐verify tracking data inputs, 
summarized in Table 1‐2. If ADM finds any deviations between the tracking data and application values, 
ADM will note and summarize these differences to Avista through periodic updates and the final report. 
ADM will also ensure that ENERGY STAR Homes Program participants did not also participate in another 
Avista program, as this would be deemed as a disqualification for the ENERGY STAR Homes Program. In 
the case that a customer did participate in another program, ADM will remove the rebate from claiming 
any savings. 
In addition, ADM will randomly select a subset of participant customers to survey for simple verification 
of installed measure, displayed in Table 1‐3. ADM will include questions such as: 
 When did you purchase and move into the household? 
 What type of fuel is used to heat your home? 
 Does your home have central air conditioning, window, or neither? 
 What appliances were present in your home during move‐in? 
These questions will help ADM verify that the HERS rater documented accurately and that data 
collection activities are progressing smoothly for the program and adjust simulation model components 
accordingly.  
1.3.5.2 Required Data 
ADM requires the following data to complete the analysis for this program: 
 Program tracking data, including customer identifiers, address, and date of rebate 
 Rebate application forms and certifications 
 A sample of REM/Rate project files from HERS raters 
 Monthly billed consumption data for participating customers 

Work Plan    29 
 Monthly billed consumption data for non‐participating customers 
 Program builder contact information  
In addition, ADM will gather the following datasets to complete the analysis: 
 Historical NOAA weather data 
 Typical Meteorological Year weather data 
 Publicly available household characteristics from county assessor data, if necessary 
1.3.5.3 Impact Analysis 
ADM will calculate verified energy savings for the ENERGY STAR Homes Program using a whole building 
simulation (IPMVP Option D) to estimate gross savings. In addition, ADM will explore the option for an 
additional billing analysis with a counterfactual control group to estimate net savings.  
1.3.6 Residential Small Home & Multifamily Weatherization Program 
The Residential Small Home & Multifamily Weatherization Program provides Avista multifamily 
residential customers with weatherization improvementsto improve home energy efficiency. Table 1‐9 
summarizes the measures offered under this program. 
Table 1‐9: Residential Small Home & Multifamily Weatherization Program Measures 
Measure Impact Analysis Methodology
Air infiltration  Billing Analysis 
Attic insulation  RTF UES 
Duct insulation  Billing Analysis 
Duct sealing  Billing Analysis 
Floor insulation  RTF UES 
Wall insulation  RTF UES 
Window replacements and upgrades  RTF UES 
Door retrofit  RTF UES 
Low‐E storm windows  RTF UES 
This program was not in effect for the 2020 program year but will be offered to residential customers in 
Avista’s service territory in the 2021 program year. Therefore, ADM will not evaluate this program as 
part of the 2020 impact evaluation report. ADM will complete the following impact tasks for the 2021 
program year evaluation. 
1.3.6.1 Database Review & Verification 
Before conducting the impact analysis, ADM will conduct a database review for the Residential Small 
Home & Multifamily Weatherization Program. ADM will select a subset of rebate applications to cross‐
verify tracking data inputs, summarized in Table 1‐2. If ADM finds any deviations between the tracking 
data and application values, ADM will note and summarize these differences to Avista through periodic 
updates and the final report. 
There will be no verification surveys for this program. 

Work Plan    30 
1.3.6.2 Required Data 
ADM requires the following data to complete the analysis for this program: 
 Program tracking data, including customer identifiers, address, and date of rebate 
 Rebate application forms and applicable invoices 
1.3.6.3 Impact Analysis 
ADM will measure net savings for each measure in the program using RTF UES values. ADM will apply 
the RTF UES values to the types and quantities of each measure, after applying adjustments from data 
review, if deviations found between invoices and tracking data.  
1.3.6.4 Technical Comments 
ADM provides no technical comments for this program’s evaluation. 
1.3.7 Low‐Income Program 
The Low‐Income Program delivers energy efficiency measures to low‐income residential customers in its 
Washington service territory with a partnership with five network Community Action Agencies 
(“Agencies”) and one tribal weatherization organization. The Agencies qualify income to prioritize and 
treat households based on several characteristics. In‐house or contract crews install approved program 
measures. In addition, the Agencies have access to other monetary resources which allow them to 
weatherize a home or install additional energy efficiency measures. 
Avista provides CAP agencies with the following approved measure list, which are reimbursed in full by 
Avista. Avista also provides a rebate list of additional energy saving measures the CAP agencies are able 
to utilize which are partially reimbursed. Weatherization measures under this program may also be 
funded by CEEP. The following table summarizes the measures offered under this program. 
Table 1‐10 summarizes the measures offered under this program. 

Work Plan    31 
Table 1‐10: Low‐Income Program Measures 
Measure Impact Analysis Methodology
Air Infiltration 
Billing analysis 
Air source heat pump 
Attic insulation 
Duct insulation 
Duct sealing 
Electric to air source heat pump 
Electric to natural gas water heater and or furnace (ID Only) 
Electric to ductless heat pump 
ENERGY STAR door 
ENERGY STAR refrigerator 
ENERGY STAR window 
Floor insulation 
Heat pump water heater 
LED lighting 
Wall insulation 
High efficiency furnace 
High efficiency tankless natural gas water heater 
Natural gas boiler 
Database Review & Verification 
Before conducting the impact analysis, ADM and Cadeo will conduct a database review for the Low‐
Income Program. ADM and Cadeo will select a subset of rebate applications to cross‐verify tracking data 
inputs, summarized in Table 1‐2 (above). If ADM and Cadeo finds any deviations between the tracking 
data and application values, we will note and summarize these differences to Avista through periodic 
updates and the final report. There will be no verification surveys for this program. 
1.3.7.1 Required Data 
ADM and Cadeo will request the following data to complete the analysis for this program: 
 Program tracking data, including customer identifiers, address, and date of rebate 
 Program materials 
 Rebate application forms and applicable invoices 
 Monthly billed consumption data for participating customers 
 Monthly billed consumption data for non‐participating customers 
 Identifiers,  if  available,  for  low‐  to  moderate‐income  households  in  both  participant  and 
nonparticipant customers in the Avista Washington territory 
 Stakeholder contact information, such as CAP agencies 
In addition, ADM will gather the following datasets to complete the analysis: 

Work Plan    32 
 Historical NOAA weather data 
 Typical Meteorological Year weather data 
 Publicly available household characteristics from county assessor data, if necessary 
1.3.7.2 Impact Analysis 
In order to estimate daily impacts of each measure, ADM will identify the customers that participated in 
the Low‐Income program. ADM will connect these identified participants to billing data, provided by 
Avista as well as historical weather data collected from NOAA. ADM will conduct billing cleaning and 
estimate fixed‐effects panel regression models referenced in Section 1.2.4.2 with heating season and 
cooling season controls to estimate the relationship between the energy consumption and weather 
during the pre‐ and post‐periods, for electric or gas, as applicable to the measure. The team will explore 
the Difference‐in‐Difference (D‐in‐D) regression and Post‐Program Regression (PPR) billing analysis 
model to estimate verified energy savings for a subset of measures. 
Our approach uses either a control group made up of “future” participants from the same program (i.e., 
those that received measures in late 2020 and/or early 2021 for the 2020 analysis period, and those that 
received measures in late 2021 and/or early 2022 for the 2021 analysis period) or a control group 
matched via quasi‐experimental methods. A control group will account for the impact of various 
macroeconomic factors and other influences on pre‐ and post‐program energy consumption that are 
unrelated to the installation of program measures. These include economic effects, the movement of 
people in and out of dwelling units, fluctuations in per‐unit energy costs, or, for example, shelter‐in‐
place orders for COVID19.  
The quasi‐experimental method goes beyond random sampling of treatment and comparison groups 
and instead uses a nearest‐neighbor algorithm via propensity score matching to match each participant 
(treatment group) customer with a specific best‐match from a pool of future participants (control group) 
based on pre‐program energy usage. This approach identifies the future participant whose energy 
consumption pattern over the most recent 12 pre‐participation months was most similar to that of the 
participant.  
1.3.7.3 Technical Comments 
In the event that the required data is not available or sufficient to conduct a billing regression analysis, 
ADM and Cadeo will review RTF UES values and Avista TRM methods along with verified tracking data to 
estimate net program savings. It is likely that insufficient instances of isolated measure installs can be 
identified. In this case, ADM and Cadeo will attempt to conduct a billing analysis for the combined 
measures.  
Unlike other programs the Avista portfolio, the responsibility of evaluating the Low‐Income Program will 
primarily be that of Cadeo. Specifically, Cadeo will perform the database review, billing analysis and 
reporting portions of the Low‐Income Program evaluation using the framework described above. 
1.3.8 Community Energy Efficiency Program 
Avista partners with the Community Energy Efficiency Program (CEEP) and community action agencies in 
Washington to identify hard‐to‐reach markets such as rental properties, homes with alternative heat 

Work Plan    33 
(wood, oil, propane), and households that are considered low to moderate income for potential energy 
efficiency improvements. In addition, CEEP provides energy efficiency improvements for small 
businesses in rural communities. Avista matches the CEEP contribution to share the cost of the 
improvements. Table 1‐11 and Table 1‐12 summarizes the measures offered under this program. 
Table 1‐11: Multi‐family CEEP Program Measures 
Measure Impact Analysis Methodology
Electric ductless heat pump  Billing analysis with comparison group 
Line voltage control thermostats  Billing analysis with comparison group 
Air infiltration  Billing Analysis 
Attic insulation  RTF UES 
Duct insulation  Billing Analysis 
Duct sealing  Billing Analysis 
Floor insulation  RTF UES 
Wall insulation  RTF UES 
Lighting  RTF UES 

Table 1‐12: Income‐Qualified Single‐family CEEP Program Measures 
Measure Impact Analysis Methodology
Alternative heat to ductless heat pump  Billing analysis with comparison group 
Alternative heat to air source heat pump Billing analysis with comparison group 

CEEP also funds some of the weatherization measures in the Low‐Income Program as well as the Small 
Business Initiative Program. 
1.3.8.1 Database Review & Verification 
Before conducting the impact analysis, ADM will conduct a database review for the CEEP Program. ADM 
will select a subset of rebate applications to cross‐verify tracking data inputs, summarized in Table 1‐2. If 
ADM finds any deviations between the tracking data and application values, ADM will note and 
summarize these differences to Avista through periodic updates and the final report. 
There will be no verification surveys for this program. 
1.3.8.2 Required Data 
ADM requires the following data to complete the analysis for this program: 
 Program tracking data, including customer identifiers, address, and date of rebate 
 Rebate application forms and applicable invoices 
 Monthly billed consumption data for participating customers 
 Monthly billed consumption data for non‐participating customers 

Work Plan    34 
 Identifiers  for  low‐  to  moderate‐income  households  in  both  participant  and  nonparticipant 
customers in the Avista Washington territory 
In addition, ADM will gather the following datasets to complete the analysis: 
 Historical NOAA weather data 
 Typical Meteorological Year weather data 
 Publicly available household characteristics from county assessor data, if necessary 
ADM will review delivered tracking data for inconsistencies  
1.3.8.3 Impact Analysis 
ADM will conduct a billing analysis regression using with a counterfactual group selected via propensity 
score matching on the heat pump and thermostat measures in the CEEP Program, as displayed in Table 
1‐11. All other measure savings for the program will be estimated using RTF UES values. ADM will apply 
the RTF UES values to the types and quantities of each measure, after applying adjustments from 
database review, if necessary.  
In order to estimate daily impacts of each measure, ADM will isolate the customers that received an 
isolated measure. For example, to evaluate the heat pump measure, ADM will select only customers 
that have installed the heat pump and have not installed any additional program measures during the 
same program year. ADM will connect these isolated customers to billing data, provided by Avista as 
well as historical weather data collected from NOAA. ADM will conduct billing cleaning and estimate 
fixed‐effects panel regression models referenced in Section 1.2.4.2 with heating season controls for the 
heat pump and heating season and cooling season controls for thermostat to estimate the relationship 
between the energy consumption and weather during the pre‐ and post‐periods, for electric or gas, as 
applicable to the measure. 
1.3.8.4 Technical Comments 
In the event that the required data is not available or sufficient to conduct a billing regression analysis, 
ADM will review RTF UES values and Avista TRM methods along with verified tracking data to estimate 
net program savings. There is a possibility that insufficient instances of isolated measure installs can be 
identified. In this case, ADM will attempt to conduct a billing analysis for both the heat pump and 
thermostat, combined. This will give a reliable estimate of both measures, but not individual measure 
savings. 
1.4 Management Plan & Schedule 
This section presents information on the ADM team’s project management structure and the 
organization of the project team. 
1.4.1 Team Members 
Table 1‐13 summarizes the key program staff for the EM&V of Avista’s programs.  
Table 1‐13: Project Team Members 

Work Plan    35 
Team Member Role
Adam Thomas, PMP Principal‐in‐charge 
Ryan Bliss Overall Project Manager 
Doug Bruchs Cadeo Project Manager 
Melissa Kosla Impact evaluation lead 
Chris Johnson Impact evaluation lead 
Fred Schaefer Cadeo Principal 
Jonah Hessels Cadeo Associate 
Analyst II Staff Supporting impact analysis 
Analyst I Staff Supporting impact analysis 
Admin Staff Call center support –surveys 

Figure 1‐1 shows our project organization. 
Figure 1‐1: Project Organization 

1.4.2 Schedule 
Table 1‐14 presents our expected schedule for the evaluation of program year 2020. A similar project 
schedule will be developed for program year 2021 evaluation tasks.  

Work Plan    36 
Table 1‐14: Schedule 
Time Period Time Period
Kickoff meeting  November 23, 2020 
Submit data request  December 4, 2020 
Submit evaluation plan  December 18, 2020 
Avista fulfills data request  December 18, 2020 
Submit participant survey instruments  December 23, 2020 
Develop sampling plan  December 23, 2020 
Survey data collection  January 15, 2021 – February 26, 2021 
Submit billing data request  January 8, 2021 
Avista fulfills billing data request  January 15, 2021 
Conduct impact analysis  January 15, 2021 – February 26, 2021 
Perform cost‐effectiveness analysis  February 26, 2021 – March 5, 2021 
Submit draft version of PY2020 final report  March 12, 2021 
Submit revised version of PY2020 final report  April 9, 2021 
In addition to the schedule above, ADM will meet and participate with advisory groups, subcommittees, 
and others as needed, in addition to presenting annual results at Avista’s convenience. 
2021 Washington Natural Gas Energy Efficiency Annual Conservation Plan Appendices

Avista Corporation 
2020‐2021 Evaluation Work 
Plan 
October 15, 2020 
Prepared for: 
Avista Corporation 
1411 East Mission Avenue 
Spokane, WA 99252 

i 
Table of Contents 
Introduction and Goals ........................................................................................................................ 1 
Evaluation Work Plan Overview ........................................................................................................... 2 
Evaluation Team ..................................................................................................................................... 2 
Budget .................................................................................................................................................... 3 
Timeline and Reporting .......................................................................................................................... 3 
Communication ...................................................................................................................................... 5 
Impact Evaluation ................................................................................................................................ 7 
Overview of Nonresidential Impact Evaluation Methods ...................................................................... 7 
Impact Sampling Plan ........................................................................................................................... 10 
Impact Evaluation Activities by Program .............................................................................................. 12 
Remote Verification Strategy ............................................................................................................... 14 
Real‐Time Evaluation and Measurement ............................................................................................. 16 
EM&V for Advanced Metering Infrastructure (AMI) ............................................................................ 16 
Cost‐Effectiveness Analysis ................................................................................................................ 20 
Process Evaluation ............................................................................................................................. 21 
Process Sampling Plans ........................................................................................................................ 26 
Process Evaluation Activities by Program ............................................................................................ 27 
Cadmus QA/QC Procedures ............................................................................................................... 31 
Impact Evaluation ................................................................................................................................. 31 
Process Evaluation ................................................................................................................................ 31 
Cost Effectiveness Analysis ................................................................................................................... 31 
Reporting .............................................................................................................................................. 32 

ii 
Figures 
Figure 1. Cadmus Evaluation Team Organizational Chart ............................................................................ 2 
Figure 2. Process Evaluation Research Areas and Tasks ............................................................................. 21 

Tables 
Table 1. Cadmus Staffing Plan ....................................................................................................................... 3 
Table 2. PY 2020 and PY 2021 Task and Deliverable Schedule ..................................................................... 4 
Table 3. PY 2020–2021 Natural Gas and Electric Impact Evaluation Activities ............................................ 7 
Table 4. Sample Design for Verification Surveys and Site Visits for Washington and Idaho Combined .... 12 
Table 5. Model Classes for Selection .......................................................................................................... 18 
Table 6. Potential Confounding Variables ................................................................................................... 19 
Table 7. PY 2020–2021 Idaho Process Evaluation Activities ....................................................................... 22 
Table 8. PY 2020–2021 Washington Process Evaluation Activities ............................................................ 22 
Table 9. Implementation Research by Program ......................................................................................... 23 
Table 10. Customer Research by Program .................................................................................................. 25 
Table 11. Estimated Participant Survey Sample Design .............................................................................. 27 

1 
Introduction and Goals 
Avista Corporation contracted with Cadmus to evaluate its Nonresidential program portfolio for 
program year (PY) 2020 and PY 2021. For this engagement, the Nonresidential evaluation also includes 
the Multifamily Direct Install program. Cadmus will also conduct a process evaluation of Avista’s entire 
portfolio, including Nonresidential, Residential, and Low Income programs.  
The primary goals for the evaluation are these: 
 Independently verify, measure, and document energy savings impacts from each electric and natural 
gas energy efficiency program or from program categories representing consolidated small‐scale 
program offerings, from January 1, 2020, through December 31, 2021 
 Analytically substantiate the measurement of those savings 
 Calculate the cost‐effectiveness of the portfolio and component programs 
 Identify any program improvements 
 Identify possible future programs 
This evaluation work plan reflects Cadmus’ understanding of the programs as described in Avista’s 2020 
Annual Conservation Plans as well as at the project kickoff. The work plan may change in response to 
program modifications or at Avista’s request during PY 2020 and PY 2021. Cadmus will relay to Avista all 
modifications to evaluation approaches prior to proceeding. 
Presently, this document offers proven methods to conduct full impact and process evaluations for 
Avista’s Nonresidential portfolio and the Multifamily Direct Install program, as well as process 
evaluations for Avista’s Residential and Low‐Income portfolio of programs.  
The following chapter summarizes the overall evaluation effort and includes an introduction to project 
staff, overview of the budget, and list of deliverables. Subsequent chapters present the evaluation 
methodologies for the impact and process evaluations, cost‐effectiveness calculations, and Cadmus’ 
quality assurance and quality control (QA/QC) processes.  

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Evaluation Work Plan Overview 
Cadmus’ highly skilled evaluators have considerable knowledge from many years of evaluating Avista’s 
portfolio of programs and can rely on resources such as Cadmus’ inventory of data monitoring 
equipment and Portfolio Pro+. The team has experience conducting virtual site visits, even before the 
limiting effects from Covid‐19, and its proactive approach to project management will ensure the 
evaluation objectives are achieved in the most cost‐effective manner. The following sections introduce 
the evaluation team and present the budget, timeline, and communication activities. 
Evaluation Team 
Cadmus’ evaluation team is organized as shown in Figure 1 and features key personnel who have previous 
experience with Avista’s evaluations.  
Figure 1. Cadmus Evaluation Team Organizational Chart 

Table 1 presents the projected staffing hours by state and includes current Cadmus titles and billing 
rates.  

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Table 1. Cadmus Staffing Plan 
Staff FY2021 Title FY2021 Billing Rate Projected Hours 
Washington Idaho 
Jeffrey Cropp  Principal II  $310  195  132 
Jerica Stacey  Associate I  $180  343  326 
Nathan Hinkle  Associate II  $190  287  203 
Kristie Rupper  Associate III  $205  67  64 
Max Blasdel  Analyst  $125  113  60 
Romio Mikhael  Associate III  $205  63  50 
Evan Talan  Sr. Analyst II  $165  215  174 
Brandon Kirlin  Analyst II  $135  192  181 
Ian Nimmo  Engineering Tech III  $135  73  71 
Aaron Huston  Engineering Tech II  $115  16  12 
Nora Twichell  Engineering Tech II  $115  107  99 
Mitt Jones  Sr. Associate II  $250  12  29 
Kean Amidi‐Abraham  Research Analyst  $115  120  108 
Brian Hedman  Principal II  $310  10  10 
Maggie Buffum  Associate I  $180  31  31 
Taylor La Prairie  Analyst I  $125  84  52 
Amanda McLeod  Analyst II  $135  116  76 
Alex Chamberlain  Sr. Analyst I  $155  68  55 
Alexander Opipari   Research Analyst  $115  179  160 
Leslie Anderson  Technical Editor   $125  42  40 

Budget 
Avista awarded Cadmus $413,211.25 for the PY 2020‐2021 Washington evaluation and $336,252.50 for 
the Idaho evaluation. This budget includes $33,169 in travel and other direct costs for site visits.  
Timeline and Reporting 
The overall timeline presented in Table 2 broadly depicts progress for each of the work tasks. The work 
plans for each program cluster include their own specific evaluation timelines. Deliverables associated 
with work tasks are specified after the table.  

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Table 2. PY 2020 and PY 2021 Task and Deliverable Schedule 
Task PY 2020 PY 2021 PY 2022 
Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 
Kickoff Meeting                        
Work Plan                        
Project Management                 
Advisory Group Meetings, as needed                  
Verification Surveys                     
On‐Site or Virtual M&V and Analysis                   
Cost‐Effectiveness Analysis                     
Document and Database Review                       
Avista and Implementer Interviews                        
Participant Surveys and Interviews                      
Market Actor Interviews              
Electric Impact Memos                       
Natural Gas Impact Memos                       
Process Memo and Report                       
Cost‐Effectiveness Memos               

  Deliverables  Impact evaluation activities   Process evaluation activities 

Cadmus will provide the following deliverables by the dates listed: 
 April 9, 2021 
 PY 2020 Washington Nonresidential electric impact evaluation memorandum 
 PY 2020 Washington Nonresidential natural gas impact evaluation memorandum 
 PY 2020 Washington Nonresidential electric and natural gas cost‐effectiveness analysis 
 April 16, 2021 
 PY 2020 Idaho Nonresidential electric impact evaluation memorandum  
 PY 2020 Idaho Nonresidential natural gas impact evaluation memorandums  
 PY 2020 Idaho Nonresidential electric and natural gas cost‐effectiveness analysis   
 PY 2020 Washington and Idaho (combined) process evaluation memorandum  
 April 8, 2022 
 PY 2020 – 2021 Washington Nonresidential electric impact evaluation memorandum 
 PY 2020 – 2021 Washington Nonresidential natural gas impact evaluation memorandum 
 PY 2020 – 2021 Washington Nonresidential electric and natural gas cost‐effectiveness 
analysis 

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 April 15, 2022 
 PY 2021 Idaho Nonresidential electric impact evaluation memorandum 
 PY 2021 Idaho Nonresidential natural gas impact evaluation memorandum 
 PY 2021 Idaho Nonresidential electric and natural gas cost‐effectiveness analysis 
 PY 2020 – 2021 Washington and Idaho (combined) process evaluation memorandum 
Prior to delivery of each memorandum, Cadmus will prepare a comprehensive outline for Avista’s 
review and approval. The memorandums will describe data collection and process methods, present 
results of the analysis and summarize findings, draw conclusions, and provide meaningful 
recommendations. Data collection instruments used for the process evaluation will be included as 
appendices to the final report. Cadmus will submit all supporting workpapers for the calculations, tables, 
graphs, and other illustrations contained in the deliverables.  
Cadmus will also prepare ad hoc reports to document problems, urgent issues, and resolutions as they 
arise.  
Communication  
Avista expects multiple communication and reporting activities to be performed as part of this 
evaluation effort. Cadmus will design its project communications based on the following:  
 The Avista DSM Planning and Analytics team serves as the lead contact for all evaluation aspects 
(impact and process) and, for contract purposes, is the client. Ryan Finesilver of the DSM Planning 
and Analytics team will serve as the contract manager and primary contact for the Cadmus team. 
 The Avista DSM Planning and Analytics team will work with the Cadmus team to facilitate 
incorporation of Avista’s implementation team’s input into the final product. Avista may encourage 
the implementation team to actively participate in the evaluations, seeking to deliver the best 
product possible, consistent with the evaluation’s independent character. 
 An Avista DSM Planning and Analytics team member may be present (in person, by phone, or copied 
on e‐mails) during any interactions between the Cadmus team and Avista’s DSM implementation 
team. 
Cadmus will hold biweekly conference calls with the Avista DSM Planning and Analytics team. These calls 
will provide updates about the project’s status and issues. Ad hoc calls may be required to address 
specific project issues and activities. Cadmus anticipates attending and occasionally facilitating in‐
person, telephone, or web‐based meetings in addition to regular and ad hoc project meetings and a final 
close‐out meeting.  
Throughout the evaluation process, Cadmus will remain engaged with Avista’s regional stakeholders, 
participating as requested in DSM Advisory Group and Technical Committee meetings. Cadmus will 
provide the following support to Avista through these meetings: 
 Present evaluation plans 

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 Present interim or final results on energy savings, realization rates, and cost‐effectiveness 
 Act as a technical resource to explain details of the evaluation methodologies and the rationale 
behind the methods employed for Avista 
 Explore opportunities for new or expanded techniques to evaluate programs or inform program 
design  

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Impact Evaluation 
Cadmus will apply the methods described below to develop findings that will determine the impacts of 
Avista’s Nonresidential programs and guide the development of current and future programs.  
Overview of Nonresidential Impact Evaluation Methods  
Cadmus’ analyses will use standard engineering approaches such as those defined by the International 
Performance Measurement and Verification Protocols (IPMVP) and the Uniform Methods Project 
(UMP). Cadmus will employ the following primary methods: 
 Simple verification (desk review, phone, online, remote walk‐through, or on‐site) 
 Energy calculation models 
 Metering (IPMVP A and B) 
 Whole building billing analysis (IPMVP Option C) 
 Simulation modeling (IPMVP Option D) 
Table 3 lists the impact evaluation data collection and analysis activities by program. Cadmus will 
conduct the online, phone, remote, and on‐site measurement and verification activities in two waves in 
both 2020 and 2021 to obtain a reasonable sample from each program year. 
Table 3. PY 2020–2021 Natural Gas and Electric Impact Evaluation Activities 
Sector Program Database/ Document Review 
Remote Verification/Site Visit Metering Billing 
Analysis 
Simulation 
Modeling 
Multifamily 
Multifamily Direct Install   
Multifamily Market 
Transformation – Fuel 
Efficiency (Idaho) 
    
Nonresidential  
Site Specific     
Interior Lighting     
Exterior Lighting     
Prescriptive Shell     
Green Motors     
Motor Control HVAC (VFD)      
HVAC     
Fleet Heat     
Food Services     
Compressed Air     
Grocer     

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Simple Verification 
Cadmus will verify some prescriptive measures (particularly those with relatively small reported savings) 
on site, via remote video walkthrough, by phone, by reviewing submitted documentation, or through an 
on‐line questionnaire to confirm that measures are installed in the reported quantity and operating in a 
manner consistent with deemed‐savings assumptions. Cadmus will also verify recorded nameplate 
efficiency data against manufacturer’s specifications. Cadmus will accept reported savings without 
further investigation if it can confirm that these details match the assumptions used for unit energy 
savings in the Regional Technical Forum (RTF) or Avista technical reference manual (TRM). Cadmus will 
adjust the savings for any inconsistencies based on equipment and operating parameters found at the 
site.  
Engineering Calculation Models 
For some Nonresidential Site Specific measures, Avista uses spreadsheets to calculate the estimated 
energy savings for a variety of measures based on relevant inputs, such as quantity, fixture wattage, 
square footage, efficiency value, HVAC system details, and location details. For each spreadsheet, 
Cadmus will review input requirements and outputs to determine if the approach is reasonable. We will 
discuss any concerns about the approach with Avista’s implementation team and explain why we think a 
different method may yield more accurate results. Where applicable, we will update calculations using 
on‐site verification data, energy management system (EMS) trend data, spot measurements, and 
metering data. 
Metering Analysis (IPMVP Options A and B) 
To estimate the relevant operational parameters needed to inform engineering calculation models, 
Cadmus may perform data logging for a period of days, weeks, or months. During the site visits, we will 
confirm relevant information such as installation of the efficient equipment, set points, sequence of 
operations, operating schedules, and ambient conditions. We will also estimate the baseline energy 
performance, according to program documentation, on‐site conditions, facility interviews, and relevant 
energy code requirements.  
After downloading, we will clean meter data, checking key fields for missing data, correcting bad data, 
and removing sites with insufficient data. We will flag anomalies and send them to a senior engineer 
who will determine if the data should be used, corrected, or excluded from the analysis. Next, we will 
analyze the key variables in the metering data using spreadsheet tools or Python. We will use the 
resulting information to calculate savings (as input variables in an engineering model) or for comparison 
to consumption estimates. 
Whole Building Analysis (IPMVP Option C) 
Cadmus can use monthly billing or interval data to conduct regression analyses for nonresidential 
retrofit projects, particularly in the Site Specific and HVAC‐related prescriptive programs (for example, 
HVAC and Shell). This analysis method is particularly useful for accurately assessing the energy savings 
from comprehensive retrofit projects, especially those involving custom HVAC or controls measures.  

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Using the pre‐ and post‐modeling approach, Cadmus will develop retrofit‐savings estimates for the 
sampled sites, accounting for cooling degree days (CDDs) and heating degree days (HDDs). We will 
match the participant‐consumption data to the nearest weather station by zip code. We will then 
calculate the building balance‐point temperature by correlating monthly energy use with monthly 
average temperature.  
Cadmus will use the balance‐point temperature to calculate the CDDs and HDDs then match these to the 
monthly billing data. We will use the resulting regression estimates to extrapolate average energy 
savings based on normalized weather conditions. (For this calculation, we will use typical meteorological 
year [TMY], 15‐year normal weather averages from 1991–2005, obtained from the National Oceanic and 
Atmospheric Administration.) 
For each project, Cadmus will model average daily consumption in kilowatt hours (kWh) and/or therms 
as a function of base load, HDDs and CDDs, and, where appropriate, daily production. For the evaluated 
sites, we will estimate two demand models—one for the pre‐period and one for the post‐period. We 
typically choose this methodology over a single standard‐treatment‐effects model to account for 
structural changes in demand that can occur with retrofits, such as changes in occupancy or usage 
patterns. We will then estimate the annual consumption based these values. 
Simulation Model Analysis (IPMVP Option D) 
Cadmus may review and verify the savings calculated from simulation models if this methodology is 
applied on projects. Our simulation approach, which is based on in situ observations and measurements, 
is calibrated to the best available energy‐use indices. It entails the use of well‐developed, sophisticated 
building‐simulation tools, such as DOE‐2, and follows methods described in the U.S. Department of 
Energy M&V Guideline and ASHRAE Guideline 14.1,2  
We will obtain the existing as‐built and baseline models, utility billing data, and any available 
documentation for each simulated measure project in the sample. Step one will be to conduct a side‐by‐
side comparison of the existing baseline and as‐built models. Because different versions of the same 
software (mainly eQuest and EnergyPlus) can return conflicting results, we will open models only in the 
software‐build version in which they were developed.  
Our goal for the site visit will be to gather all data necessary to improve and calibrate the model. Using 
our on‐site data collection form and following our facility operator interview guide, we will verify all 
necessary assumptions and obtain any available EMS data needed to further inform the calibration 
process.  

1   U.S. Department of Energy. M&V Guidelines: Measurement and Verification for Performance‐Based Contracts 
(Version 4.0). Available online at: http://energy.gov/sites/prod/files/2016/01/f28/mv_guide_4_0.pdf  
2   ASHRAE. Measurement of Energy, Demand, and Water Savings. Atlanta, GA. 2014. 

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Following the site visit, Cadmus will update the model with the verified values and actual meteorological 
year (AMY) weather data for the appropriate location and time period then test statistical calibration, 
comparing model results with utility and metered data. In accordance with ASHRAE Guideline 14, we will 
target a monthly accuracy within a mean bias error (MBE) of ±5% and a coefficient of variation root 
mean square error (CVRMSE) of ±15%. We will make logical improvements, based on engineering 
judgment where anomalies are identified. In our analysis, we will account for fluctuations, such as those 
from initial building commissioning or first‐year occupancy changes.  
Once the adjusted as‐built model has achieved the accuracy requirements, the remaining steps are 
straightforward. We will replace the AMY data used for calibration purposes with typical meteorological 
year (TMY) data. To develop the baseline model, we will back out the conservation measures based on 
incentive documentation, changes between existing models documented during the initial comparison, 
and any measure stipulations, such as code requirements. Unless instructed otherwise by Avista, we will 
calculate measure savings in the same order and manner suggested by the existing models and 
documentation (that is, first measure in, last measure out, and so on). We will determine savings by 
comparing results from the calibrated typical year as‐built and baseline models. 
Impact Sampling Plan 
Cadmus’ approach to developing impact evaluation sampling plans is consistent with the methods 
described in the UMP. Specifically, we will include these guidelines in our approach:  
 Determine confidence and precision requirements for key metrics. Our team will use key metrics to 
support our gross and net energy estimates for each program. For programs with more complex or 
comprehensive offerings, we typically expect variation between customers to be larger than for 
programs with fewer variables or more streamlined installations. We will rely on our experience 
evaluating Avista’s programs to estimate the homogeneity or heterogeneity of the population of 
participants and rely on coefficients of variance calculated from the previous round of evaluation to 
inform the variability in the expected sample population. When possible, we will design a sample for 
each program so that we can estimate the overall portfolio energy savings with 90% confidence and 
±10% precision for each fuel type within each state.  
 Develop the sample design. We will apply a sample design that primarily features stratified random 
sampling. The optimal design depends on the homogeneity or heterogeneity of the population of 
participants within each program as well as any targeted research we plan to perform (that is, if we 
are particularly interested in evaluating savings for a particular measure or collection of measures, 
we will stratify accordingly to ensure ample sample sizes from that population). We may select very 
large projects with certainty, when their expected savings are expected to differ substantially from 
the rest of the population. We will select at minimum the number of projects in each program as 
necessary to calculate confidence and precision within the program, even if participation or savings 
are low. 

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 Calculate sample sizes. We will calculate sample sizes based on the confidence and precision 
requirements, expected variation, sample design, and population size for each program. Sample 
sizes will be sufficient to estimate gross savings for each program and the portfolio as a whole. 
For Nonresidential programs and Multifamily Market Transformation, Cadmus proposes a stratified 
sample design, with strata defined based on fuel type (electric and natural gas) and project savings. For 
each program and fuel type, we will stratify the sample into large‐ or small‐savings projects and conduct 
verification on a simple random sample of the projects within each stratum. We will include dual fuel 
projects in the natural gas stratum for sampling purposes but will include electric savings from dual fuel 
measures with the electric stratum. We will evaluate the electric savings as a certainty selection for any 
dual fuel projects selected for random sampling. For the Multifamily Direct Install program, Cadmus will 
apply a simple random sample to select projects.  
We will determine sample sizes for each program and fuel type separately in Washington and Idaho. 
Data we obtain during site visits will inform our calculation of realization rates used to estimate 
population savings for each program and fuel type. We will report these results and the corresponding 
state‐specific program savings results.  
After receiving program population data from Avista for January to September 2020 we determined 
sample sizes according to the most recent evaluation results, actual participant and project population 
sizes, additional stratification variables, and/or alternative sampling approaches (for example, 
probability proportional to size), with portfolio‐level target confidence of 90% and precision of 10%. If 
possible, we will apply a finite correction to sample sizes to decrease the sample sizes. Table 4 shows the 
sample design for Washington and Idaho combined. 

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Table 4. Sample Design for Verification Surveys and Site Visits for Washington and Idaho Combined 
Program Fuel Type Confidence Precision 
Washington Idaho 
Expected 
Population 
Size* 
Sample Size 
Expected 
Population 
Size* 
Sample Size 
Site Specific Electric  80  20  184  34  64  30 
Natural Gas  80  20  32  6  7  4 
Grocer   Electric  90  20  13  2  12  2 
Interior Lighting  Electric  90  20  1084  17  516  20 
Exterior Lighting  Electric  90  20  1304  17  712  20 
Green Motors  Electric  90  20  16  8  16  0 
Compressed Air  Electric  90  20  2  1  1  1 
Fleet Heat  Electric  90  20  1  1  0  0 
Motor Control HVAC 
(VFD) Electric  90  20  4  7  3  1 
HVAC   Natural Gas  90  20  80  10  80  6 
Prescriptive Shell Electric  90  20  16  3  1  1 
Natural Gas  90  20  16  4  4  2 
Food Services Electric  90  20  28  5  8  2 
Natural Gas  90  20  56  9  52  4 
Multifamily Market 
Transformation 
Fuel 
Efficiency 90  20  N/A  N/A  7  3 
Total Nonresidential Site Visits/Verification Surveys 2836 124 1483 96 
* Expected population size is extrapolated from 2020 Q1‐Q2 participation and 2018‐2019 participation. Dual fuel 
measures are counted as gas for population size and sampling purposes.  

Impact Evaluation Activities by Program 
Cadmus will conduct the verification activities in four waves—fall 2020, January 2021, summer 2021, 
and January 2021—using desk reviews, remote or physical site visits, and phone surveys to collect 
baseline data, operations data, and other information to inform the energy savings analyses. The 
following sections describe each Avista program and the proposed impact evaluation activities.  
Multifamily Direct Install Program  
Avista provides free gas and electric direct‐install measures to multifamily residences (of five units or 
more) and common areas in its service territory though the Multifamily Direct Install program. Cadmus 
will conduct document reviews on the census of projects installed through this program to assess the 
quality of program tracking data (noting missing, duplicate, and out‐of‐range values) and will verify that 
values of key metrics are within expected limits.  
We will provide Avista with ex post savings values by measure and will also calculate the program’s cost‐
effectiveness. 

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Nonresidential Site Specific Program 
The Nonresidential Site Specific program provides flexible opportunities to achieve energy savings for 
measures that do not fit a prescriptive path. In the past, these projects have been for compressed air, 
custom lighting, process improvement, and complex HVAC measures, among others. Multifamily Market 
Transformation projects for Idaho are also included in this program. 
Cadmus will calculate participants’ gross reductions in electricity and natural gas consumption using 
data collected through desk reviews, remote or on‐site visits, customer billing histories (as needed), and 
engineering models and calculations, for the projects selected by the sample. The number of site visits 
will depend on actual enrollment and sample‐size calculations, based on expected variability and the 
desired confidence and precision of evaluated savings. During the site visits, we will verify measure 
installations, collect baseline and equipment data, and identify addressable enrollment or installation 
issues.  
We will analyze gross program impacts using data collected from site visits and from tracking data. We 
will verify reported ex ante savings by recalculating energy savings using Excel spreadsheet analysis 
tools, site‐specific data, and standard engineering analysis methods. Data may include savings 
calculations, manufacturers’ specification sheets, and commissioning reports. We may also conduct 
regression analyses, as needed, for measures such as comprehensive HVAC controls, whose savings 
impact cannot readily be evaluated through other means. Information collected during our site visits will 
determine if the sample projects reasonably address the measure’s operating parameters and 
accurately reflect operating conditions. 
Because we will not inspect all participant sites, we need a mechanism to extrapolate the difference 
between ex ante and ex post savings to the population. To resolve this, we will apply a correction factor 
based on the realization rates to ex ante savings to calculate evaluated ex post gross savings. We will 
document the reasons and impacts on savings of all adjustments and will review these with Avista’s 
implementation team during a presentation before committing results to the draft reports. 
Nonresidential Prescriptive Programs 
Avista implements these ten prescriptive programs that provide incentives directly to customers for a 
variety of measures supported by unit energy savings in the RTF or Avista’s TRM: 
 Compressed Air 
 Fleet Heat 
 Food Services 
 Green Motors 
 Grocer 
 HVAC 
 Lighting Interior 
 Lighting Exterior 
 Prescriptive Shell 
 Variable Frequency Drives 
Cadmus will first work with Avista to prioritize and review prescriptive measures in the TRM to identify 
those with the most variance based on previous impact evaluation results. These measures may benefit 
from primary data collection and analysis during the 2020‐2021 impact evaluation. This review requires 

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in‐depth knowledge and understanding about the specifics of each measure to ensure that the baseline 
and savings calculations reflect the best possible ex ante values for the region. Cadmus and Avista 
engineers will coordinate to ensure consistency in inputs and calculations and to ensure that the TRM 
uses the most up‐to‐date sources for Avista’s engineering calculations. We may recommend measures 
to examine, as necessary, including references, algorithms, and inputs. 
Cadmus will design a sample for verification activities to include all prescriptive programs, with primary 
emphasis on those that contribute the most savings or represent the highest level of uncertainty. We 
will apply sampling weights accordingly as part of the correction factor. 
We will conduct desk reviews, remote, or on‐site inspections during the initial round of impact data 
collection to confirm that Avista’s quality‐assurance processes have been maintained. This is particularly 
relevant for any new programs or programs with updated processes. If we find a high correlation 
between the ex ante and ex post results in our initial inspections, we may increase our reliance on less‐
intrusive data collection methods including desk reviews and phone interviews with participants.  
We will review project documents, verify assumptions, adjust reported calculations, and compute ex 
post savings using Excel spreadsheet analysis tools or by approving installation rates for RTF measures 
with well‐defined unit energy savings. We will derive baseline data from virtual/on‐site visits, customer 
interviews, and Avista’s program data. We will calculate ex post savings using submitted documentation, 
site visit data, and standard engineering analysis practices. We will also calculate a realization rate based 
on sampled sites and will apply this rate to the project population to estimate program total ex post 
savings. 
In the Prescriptive program, as with the Site Specific program, we will document all reasons and impacts 
on savings for adjustments and will review these with Avista’s implementation team before committing 
the results to the draft reports. 
Remote Verification Strategy 
The COVID‐19 pandemic has resulted in significant and rapid changes to facility operations and caused 
uncertainty about future operations. This has complicated impact evaluation and especially affected on‐
site project verification site visits. Cadmus has developed a virtual and contactless approach that 
prioritizes customer comfort, preference, privacy concerns and operational policies, and is designed to 
minimize the burden on the customer throughout the data collection and inspection process. 
Our virtual verification process involves using a web‐based audio and video connection to simulate in‐
person customer interactions with a project‐specific site contact. To verify savings, our evaluation staff 
may use a combination of: 
 Existing submitted project documentation, including project application files, invoices, specification 
sheets, calculation models, and Installation Verification reports provided by Avista or available in the 
iEnergy web software 

15 
 Virtual site visit observations, for example a video recording, interview with the site contact, and 
photos taken during a virtual project tour 
 Additional information provided by the site contact, for example additional trend data from the 
equipment, control system, or meter, more detailed photos or videos of equipment operation, or 
other documentation requested during the virtual site visit 
Cadmus has conducted over 100 virtual site visits for 12 clients throughout the country across a wide 
variety of project types, and over the next 12 months we expect to have completed over 1,000 virtual 
site visits across the country. Our process has been designed for the long haul and we plan to keep the 
virtual/contactless option as a part of our evaluation offerings moving forward. In addition to the safety 
benefits related to the COVID‐19 pandemic, our virtual site visit process saves travel costs, and allows 
for more flexible scheduling, particularly for geographically remote sites in rural regions of Avista’s 
service territory.  
We will review each project selected for verification to ascertain whether it is appropriate for remote 
verification and what level of remote verification is required to sufficiently verify the measures.  
 Desk review: Lower‐complexity projects which can be verified through a review of existing complete 
documentation.   
 Desk review with interview: Projects with nearly complete documentation requiring additional 
photos, invoices, spec sheets, or other simple documentation. Projects with complete 
documentation where assumptions need to be reviewed or discussed. Interview may be conducted 
via email, phone call, or web video conference.  
 Virtual site visit: Projects that have large savings, higher complexity, or incomplete documentation. 
Remote verification and interview will be conducted via video walkthrough of the project with a site 
contact involved in the implementation or operation of the system.  
 Physical site visit: Projects that are too complex for remote verification, require on‐site data 
collection or meter installation, projects with a large number of measures or large quantity of 
equipment, or where safety concerns, participant availability, or time required on site make a virtual 
site visit impractical or unsafe.  
To be eligible for remote verification, a project must meet criteria for participant safety, data security 
and privacy, suitability of measures to remote verification, and site contact knowledge, availability, and 
technology limitations. Cadmus will provide a detailed virtual site visit protocol to Avista, and will notify 
the Avista account executive assigned to each project prior to initiating recruitment for remote or on‐
site verification. Physical site visits may be postponed until travel to the region is safe and prudent. We 
will review all in‐person site visit plans with Avista prior to scheduling travel and will adhere to all COVID 
safety procedures provided by Cadmus, Avista, and the participant.  

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Real‐Time Evaluation and Measurement 
Cadmus may coordinate with Avista’s implementation team to identify projects with both relatively 
large expected energy savings and relatively high uncertainty (for example, demand control ventilation 
and multi‐stage compressed air retrofit). In comparison, projects such as large lighting retrofits may not 
require real‐time EM&V because the savings should be relatively certain if the operating hours are well‐
characterized. Once Avista identifies the most likely projects for real‐time EM&V, we will coordinate 
with implementation engineers and/or contractors to track project installation progress and estimate 
the completion date.  
We will develop a site‐specific EM&V plan for each project. Our metering engineer will be prepared to 
travel to the site to install meters during a timeframe estimated by Avista’s implementation team. After 
removing the meter, we will follow our standard procedures for analyzing the data. We will summarize 
our methodology and results for further discussion with Avista before finalizing the energy savings. 
EM&V for Advanced Metering Infrastructure (AMI) 
Where relevant, and to support Avista’s move toward advanced meter infrastructure (AMI), Cadmus will 
conduct EM&V for projects with AMI data. To support this type of analysis, we assume that electricity 
interval consumption data will be available for the pre‐treatment, or baseline, and treatment, or 
reporting, periods.  
The approach to calculating energy savings starts with building a predictive statistical model using 
baseline data, which includes baseline weather conditions and facility operating conditions as 
explanatory variables in the model. By applying the baseline model to the explanatory data measured 
during the reporting period, the model outputs represent the expected energy usage during the 
reporting period that would have occurred without the influence of the energy‐saving measures. 
Therefore, subtracting the observed energy usage and predicted energy usage at each point in time 
results in the evaluated energy savings (adjusted for reporting period weather and facility operations).  
Our proposed method has several advantages over other approaches:  
 The method allows for flexible modeling of each facility’s energy consumption. Because we conduct 
a separate analysis for each facility, it is possible to select a set of variables that are specific to that 
facility.  
 Baseline models are uncontaminated by project treatment effects. Because the model is fit with 
baseline period data, the parameters of the adjusted baseline consumption reflect only baseline 
period operation.  
 The model‐building process is objective. Because we rely on automated machine‐learning to select 
the model variables, we can identify relevant variables affecting a facility’s consumption from a 
larger set of candidate variables based on pre‐determined criteria, which reduces time and the 
possibility for idiosyncratic choice by the analyst in building a model.  

17 
 The proposed approach is versatile, scalable, and cost‐effective. Much of the estimation can be 
automated and applied to a variety of commercial building types and samples with large numbers of 
facilities.  
Our proposed analysis approach has four main steps—data collection and pre‐processing, modeling, 
savings estimation, and reporting— as described in the next sections. 
Data Collection and Preprocessing 
Cadmus will collect the following data for the evaluation: 
 Interval data of facility energy consumption 
 Project implementation data including installation dates, project description, and ex ante savings 
estimate 
 Building systems data from the facility’s energy management system (if available) 
 Interval weather data from nearest weather station 
Cadmus will then conduct a quality review of the raw data. This process involves a visual inspection by a 
domain expert and automated checks for max and min values, consumption per square footage, rates of 
change, completeness of the data, etc. Once the validity of the data is established, we will define the 
facility’s baseline and reporting periods from documentation about the project implementation. 
Modeling 
Cadmus will develop models using these steps: 
 Identify candidate model inputs. Cadmus will begin by plotting energy usage against all 
explanatory variables and identify trends. Trends identified from visual inspection will be linear, 
non‐linear, or periodic. These will require evaluation in the context of Cadmus’ understanding of 
the physical systems involved and experience modeling similar facilities. We will also consider 
derived variables, such as day of week or degree days, and will assess correlations of these 
inputs and interactive effects between variables.  
 Select model type. Cadmus has applied a range of modeling techniques and methods and knows 
that performance of an algorithm can depend on the dataset it is attempting to fit. Our approach is 
to select a class of models based on a specific use case and test performance (that is, predictive 
accuracy, minimization of prediction error, minimal data requirements, etc.) for the various model 
types within that class. Table 5 summarizes the collection of models we have used. 

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Table 5. Model Classes for Selection 
Model Class Model Type Use Case 
Linear  Single and multiple linear, ridge, Lasso regression Low temporal resolution usage data, known 
physical relationships, observed linear trends 
Time Series Autoregressive integrated moving average 
(ARIMA), error term models, transfer functions 
High temporal periodicity and seasonality, 
predicting future response 
Bayesian  Decision trees, random forests, neural networks Nonlinear relationships, complex systems, large 
amounts of data 

Model validation and testing. Cadmus will create a set of candidate models based on prior experience 
and understanding of energy‐savings projects and will rigorously evaluate these models against the 
facility‐specific data and choose the best model in the energy‐savings calculations. As a starting point in 
selecting the best model, we will apply graphical analysis of the relationship between energy usage and 
possible explanatory variables. We will then evaluate existing seasonality or temporal changes in 
selecting model types. In this initial step, we will consider using the model that is the simplest, has the 
fewest explanatory variables, and can be interpreted based on good engineering judgment. 
Cadmus will test model prediction ability using a procedure that minimizes selection bias. This involves 
randomly splitting the baseline period data into training and testing sets, giving us two datasets of 
independent variables and measured energy consumption. Models are fit to the training data, applied to 
the test data, and scored on bias, model fit, and prediction accuracy metrics, such as the mean 
prediction error, relative root mean‐squared error of prediction, mean absolute percentage error of 
prediction, and the median and other percentiles of prediction errors, r‐square, and Akaike information 
criterion (AIC).  
Randomly splitting the data does introduce bias and to fully understand a model we repeat this process 
for each model many times. These simulations build distributions of test statistics for each model that 
inform the selection of a final model.  
Furthermore, we will identify patterns in the prediction errors by plotting or regressing the errors 
against variables such as hour of the day and day of the week. Also, we will investigate the evolution of 
errors over weeks and months to determine if there are prolonged trends that require further 
investigation. 
Cadmus will fit the selected model to the entire set of baseline data. If, in the model validation and 
testing phase, we find that several models provide relatively good fit and predictions, we will calculate 
energy savings using several models and provide the results to Avista. For any given model that is 
chosen during the validation and testing phase, we will calculate the uncertainty in energy savings 
obtained using the entire dataset.  
Cadmus expects that a variety of factors could confound the savings analysis. For example, a facility may 
undertake energy efficiency projects that are not funded through Avista during the reporting period. If 

19 
these other projects are unaccounted for, the estimate of electricity savings could be biased upward. 
Table 6 lists possible confounding factors and the strategies for addressing them. 
Table 6. Potential Confounding Variables 
Confounding Variable Problem Solution Strategy 
Other Energy Efficiency Projects 
Unaccounted savings from other 
energy efficiency projects during the 
reporting period may bias the 
savings estimate. 
Develop an engineering estimate of savings for 
the other project(s) and subtract validated 
savings estimates from Cadmus’ regression‐
based estimate. 
Floor Space Additions or Changes in Use of Facility Space These changes can bias the savings estimates. 
Cadmus will review project documentation and available energy management system data to identify significant changes. Cadmus may make engineering‐based adjustments to the savings estimates or model energy intensity instead of consumption.  

Savings Estimation 
After developing a model, estimating savings is straightforward. Cadmus will fit the model to the 
baseline data and apply it to the conditions present during the reporting period, generating facility 
consumption at each interval, and subtract these estimates from the actual measured consumption. To 
calculate “typical year” savings, Cadmus fits a baseline model and a reporting period model, applies each 
of these models to TMY3 data, and takes the difference in the estimated energy consumption. Savings 
are provided on a per‐site basis in each of these cases. 

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Cost‐Effectiveness Analysis 
Cadmus will calculate and report the program’s cost‐effectiveness using evaluated savings, avoided 
energy costs, and actual incurred implementation costs. We will use Portfolio Pro+ to provide cost‐
effectiveness assessments by portfolio, program, fuel type, year, measure, and state level. 
We will determine the economic performance of a program from four standard perspectives—a 
combination of the utility and program participants, the utility, program participants, and all ratepayers 
(including nonparticipants). Cadmus will evaluate these perspectives using four cost‐effectiveness 
tests—total resource cost (TRC) test, utility cost test (UCT), participant cost test (PCT), and rate impact 
measure (RIM) test. If requested, we may also look into applying the Resource Valuation Test (RVT).  
We will populate a database with Avista’s utility data common to all programs (such as discount rates, 
avoided costs, load shapes, and retail rates) so that we can maintain a consistent approach to cost‐
effectiveness valuation across all programs and portfolios.  

21 
Process Evaluation 
The process evaluation approach considers past evaluation findings, insight from the kickoff meeting, 
and Avista’s 2020 Annual Conservation Plans. 
For all programs, our research methods will consider these three fundamental objectives: 
 Assess participant and market actor program journey including motivation for participation, barriers 
to participation, and satisfaction   
 Assess Avista and implementer staff experiences including organizational structure, communication, 
and program processes 
 Document areas of success, challenge, and changes to the program  
To address these research objectives, we will conduct implementation and customer research. Our 
implementation research will include a document and database review for each program, in‐depth 
interviews with key Avista and implementation staff and contractor and Community Action Partner 
(CAP) agencies for relevant programs. Our customer research will include participant surveys and 
interviews, as well as builder and property manager interviews for relevant programs (Figure 2). We 
discuss each of these research areas and the associated tasks in more detail below. 
Figure 2. Process Evaluation Research Areas and Tasks 
 Table 7 shows the research areas by program and year in Idaho and Table 8 shows the research areas by 
program and year in Washington. Cadmus will not complete a process evaluation for Simple Steps Smart 
Savings because the program will be discontinued soon. 

22 
Table 7. PY 2020–2021 Idaho Process Evaluation Activities 
Program Name Implementation Research Customer Research 
PY 2020 PY 2021 PY 2020 PY 2021 
Residential Programs 
ENERGY STAR Homes 
Shell    
HVAC    
Water Heat    
Fuel Efficiency     
Low‐Income Programs 
Low‐Income    
Multifamily Programs
Multifamily Direct Install    
Multifamily Market Transformation     
Nonresidential Programs 
Site Specific    
Prescriptive*    
Grocer     
*Nonresidential Prescriptive: Lighting, HVAC, Shell, Motor Control HVAC (VFD), Food Services, Green Motors, Compressed 
Air, and Fleet Heat.

Table 8. PY 2020–2021 Washington Process Evaluation Activities 
Program Name Implementation Research Customer Research 
PY 2020 PY 2021 PY 2020 PY 2021 
Residential Programs 
ENERGY STAR Homes 
Shell    
HVAC    
Water Heat    
Low‐Income Programs 
Low‐Income    
Community Energy Efficiency Program    
Multifamily Programs
Multifamily Direct Install    
Nonresidential Programs 
Site Specific  
Prescriptive**   
Grocer   
*Residential prescriptive: space and water heating, smart thermostats, insulation, and windows. 
**Prescriptive: Lighting, HVAC, Shell, Motor Control HVAC (VFD), Food Services, Green Motors, Compressed Air, and Fleet 
Heat.

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The next sections describe the task methods for each research area. 
Implementation Research 
Cadmus will assess program processes and provide timely and actionable recommendations for 
continuous implementation improvement by reviewing the database and program documentation and 
conducting interviews with key Avista and third‐party implementation staff, such as SBW Consulting, 
Washington State University Energy Program, 4 Sight Energy Group, the Green Motors Practices Group, 
contractors in the residential programs, and CAP agencies in the Low‐Income program. Our reviews of 
key program documents and corresponding databases will inform what data we collect to meet the 
research objectives. 
Table 9 lists the implementation research by program. 
Table 9. Implementation Research by Program 
Program 
Implementation Research 
Document 
Review 
Avista 
Interviews 
Implementer 
Interviews 
Contractor and CAP Agency Interviews 
Residential Programs 
ENERGY STAR Homes      
Shell    
* HVAC    
Water Heat    
Fuel Efficiency      
Low‐Income Programs 
Low‐Income     
Community Energy Efficiency Program     
Multifamily Programs 
Multifamily Direct Install     
Multifamily Market Transformation      
Nonresidential Programs 
Site Specific      
Prescriptive Lighting      
HVAC      
Prescriptive Shell      
Motor Control HVAC (VFD)      
Food Services      
Green Motors     
Compressed Air     
Fleet Heat      
Grocer       
*Contractor group to be determined after consulting with Avista.  

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The following sections describe the implementation research tasks. Program‐level details are provided in 
the Process Evaluation Activities by Program section of this work plan. 
Document and Database Review 
Cadmus will review operation manuals, the program website, and the program database to gain a 
thorough understanding of how the program is implemented. In our database review, we will also assess 
the quality of program tracking data as it relates to our customer research.  
We also will review Avista’s most recent process and impact evaluation results to learn how Avista has 
incorporated earlier recommendations and to identify trends in program performance. We will apply 
our findings from the program document and database reviews to refine program‐specific research 
objectives and develop data‐collection instruments.  
Avista Staff and Third‐Party Implementer Interviews  
Avista and its third‐party implementers hold critical insight into program administration and delivery 
processes. Telephone interviews with these key stakeholders will focus on these topics: 
 Program roles and responsibilities  
 Program goals and objectives 
 Program design and implementation  
 Data tracking  
 Program participation 
 Marketing and outreach  
 Program successes 
 Market barriers  
 Program impact on the market 
 Future program changes including redesign 
During the interview, we will be conscientious of staff members’ time. Because we know they 
sometimes oversee multiple programs, our interview guides will avoid repetitive questions for programs 
with similar processes, such as data tracking, and we may cover all programs overseen by one or more 
staff members in one interview. We will build on our early findings from these program staff interviews 
to focus interviews with third‐party staff about areas of interest.  
For Residential and low‐income programs in which contractors or agencies play a vital role, we will 
conduct contractor and CAP agency interviews.  
Contractor Interviews  
For many customers, contractors are an important source of program awareness and their involvement, 
cooperation, and understanding can be an indicator of program success. Cadmus proposes to conduct 
in‐depth interviews to gain insights into contractors’ motivations, experience, marketing strategies, how 
contractors identify customers, their standard business practices, knowledge about customer 
perceptions and experience, perspectives on program processes, the program’s influence on business, 
and the opportunities for improvement. 
Cadmus plans to complete up to 10 interviews with residential contractors (five per state). We will 
probably concentrate Residential contractor interviews on the HVAC program but will consult with 
Avista staff to determine if this is the best group to target. We will ask Avista program managers and 

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account executives to identify target contactors and will coordinate communication to program 
contractors.  
CAP Agency Interviews 
Cadmus plans to complete up to five interviews with CAP Agency staff. These interviews will be focused 
on program experience, marketing strategies, knowledge about customer perceptions and experience, 
and program successes and opportunities for improvement.  
Customer Research 
As shown in Table 10, Cadmus will conduct online participant surveys, as well as interviews with trade 
allies where smaller populations exist. 
Table 10. Customer Research by Program 
Program Category Customer Research  
Participant Surveys Trade Ally Interviews  
Residential Programs 
Shell   
HVAC   
Water Heat   
Fuel Efficiency   
Multifamily Programs 
Multifamily Market Transformation (Builders)    
Multifamily Direct Install (Property Managers)    
Nonresidential Programs 
Site Specific    
Prescriptive*   
Grocer   
*Nonresidential Prescriptive: Lighting, HVAC, Shell, Motor Control HVAC (VFD), Food Services, Green Motors, 
Compressed Air, and Fleet Heat.  
Participant Online Surveys and Interviews 
Cadmus will prepare participant survey and interview guides in each of Avista’s programs. Questions will 
focus on topics that can help Avista understand trends in measure adoption and overall program 
performance and that gather critical data to inform the impact evaluation.  
Our participant survey and interview guides will gather critical insights into participants’ program 
journey, such as these aspects: 
 Program awareness 
 How respondents learned about the program 
 General program participation 
 Program delivery experience 
 Overall program satisfaction 
 Satisfaction with Avista 

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 Reasons for participation 
 Program benefits 
 Current energy‐efficient behaviors and 
purchases 
 Suggestions for program improvements  
All participant surveys will be online and will involve emailing a link to the survey to participating 
customers for whom an email address is available.  
We typically recommend simple random sampling when the population is sufficiently large but will 
finalize the sampling plan according to the target sample sizes and expected response rates and after 
receiving comprehensive participant tracking data. See Table 11 in the Process Sampling Plans section 
for sampling details.  
For programs with unique populations (Multifamily Market Transformation and Multifamily Direct 
Install), we will conduct participating builder and property manager telephone interviews, respectively, 
to allow for a greater range of topic exploration. We will conduct up to five builders participating in the 
Multifamily Market Transformation program and up to five property managers in each state for the 
Multifamily Direct Install program. 
Process Sampling Plans 
For the participant surveys, Cadmus will calculate sample sizes for each program category and fuel type 
based on unique participant population sizes, expected variation, and confidence and precision targets. 
For this work plan, we have described the sample design and estimated sample sizes but will revise 
them according to actual participant and project population sizes.  
In Table 11, we provide the anticipated survey sample sizes for each program category and fuel type, 
determined based on target 90% confidence and 15% precision for each program category and to far 
exceed 90% confidence and 10% precision for the portfolio overall with error ratios of 0.5. For programs 
with limited sample sizes, we will send the survey to a census of participants in the planned year and 
gather as many survey responses as possible.  
We will conduct in‐depth interviews with up to five builders participating in the Multifamily Market 
Transformation program and up to five property managers in each state of the Multifamily Direct Install 
program. 

27 
Table 11. Estimated Participant Survey Sample Design 
Program Category Fuel Type 
Idaho and Washington Combined 
Annual 
Participant Size*  
Survey  
Target ** 
HVAC, Shell, Water Heat Electric  ~4,000  30 
Natural Gas  ~12,000  40 
Fuel Efficiency  Natural Gas  ~500 AMAP (estimating  
between 10 and 20) 
Residential Total ~16,500 ~90 
Site Specific   Both  ~400 AMAP (estimating  
between 10 and 20) 
Prescriptive Lighting  Electric  ~700  30 
HVAC  Natural Gas 
~400 AMAP  (estimating between  10 and 20) 
Prescriptive Shell  Both 
Motor Control HVAC (VFD)  Electric 
Food Services  Both 
Green Motors  Electric 
Compressed Air  Electric 
Fleet Heat  Electric 
Nonresidential Total ~1,500 ~70 
Portfolio Total ~18,000 ~160 
* Participant size is the number of residential program participants and nonresidential program projects. These are estimates 
based on previous years.  
**Final survey target will be based on actual unique participants/project by state in each program category in the year survey 
is scheduled. Due to small population sizes, Cadmus will send email invite to census and gather as many completed surveys as 
possible. 

Process Evaluation Activities by Program 
This section describes the process evaluation activities by program. Although many process research 
activities are similar, such as reviewing program documents and tracking database to assess roles and 
responsibilities, marketing and outreach, participation trends, and informing subsequent interview and 
survey questions, the following descriptions note more program‐specific focus areas.  
Residential HVAC, Shell, and Water Heat Programs 
The process evaluation of these programs will include the following data‐collection activities:  
 Review program documents and database to assess program changes and determine if database 
contains all necessary fields for customer surveys.  
 Interview Avista staff to assess differences between the implementation of the program in Idaho 
and Washington, assess the impact of Washington’s Clean Energy Transformation Act on program 
design and implementation, document program changes and goals, and identify program successes 
and challenges. 

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 Interview participating contractors (n=10) to assess program understanding, experience, and 
satisfaction, how contractors identify customers, use of rebates as a sales factor, customer 
awareness of the program prior to engaging the contractor, standard business practices, influence 
of the program on business, and qualifying equipment offered. 
 Survey participating customers to explore their experience, including application processing and 
influence of the contractor, continued levels of satisfaction, and marketing preferences. 
ENERGY STAR Homes Program   
The process evaluation of the ENERGY STAR Homes program will include the following data‐collection 
activities:  
 Review program documents to assess program changes. 
 Interview Avista staff to document program changes and goals, assess differences between the 
implementation of the program in Idaho and Washington, identify program successes and 
challenges, assess regional communication and coordination with NEEA and other partnering 
utilities, and assess builder and dealer perceived experience and relationship. 
Residential Fuel Efficiency Program (Idaho only) 
The process evaluation of the Fuel Efficiency program will include the following data‐collection activities: 
 Review program documents and database to assess program changes and determine if database 
contains all necessary fields for customer surveys.  
 Interview Avista staff to document program changes and goals and identify program successes and 
challenges. 
 Survey participating customers to explore their experience, including application processing and 
influence of the contractor, continued levels of satisfaction, and marketing preferences. 
Low‐Income Program 
The process evaluation of the Low‐Income program will include the following data‐collection activities: 
 Review program document to assess program changes.  
 Interview Avista staff to assess program changes and goals, assess differences between the 
implementation of the program in Idaho and Washington, identify program successes and 
challenges, and assess CAP agency and contractor experience and relationship.   
 Interview CAP agencies (up to n=5) to assess program implementation, document marketing 
methods, assess experience with contractors, Avista staff, and customers, and identify program 
successes and challenges.  
Community Energy Efficiency Program (Washington Only) 
The process evaluation of the Community Energy Efficiency Program will include the following data‐
collection activities:  
 Review program documents to document program processes, marketing efforts, and data tracking. 

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 Interview Avista and implementer staff to document program design including goal setting, 
delivery process, customer eligibility, incentive structure, and data tracking, as well as roles and 
responsibilities, and areas of success and challenge. 
Multifamily Direct Install Program 
The process evaluation of the Multifamily Direct Install program will include the following data 
collection activities:  
 Review program documents to assess program changes. 
 Interview Avista staff to document program changes and goals, assess differences between the 
implementation of the program in Idaho and Washington, identify program successes and 
challenges, and assess trade ally relationship.  
 Interview implementer to document program understanding, including coordination of program 
marketing and outreach, and overall program experience, including satisfaction and suggestions for 
improvement. 
 Interview participating property managers (up to 5 per state) to explore customer experience, 
including program awareness, satisfaction, energy efficiency actions, barriers to energy efficiency 
programs, and marketing preferences. 
Multifamily Market Transformation (Idaho Only) 
The process evaluation of the Multifamily Market Transformation program will include the following 
data collection activities:  
 Review program documents to assess program changes. 
 Interview Avista staff to document program changes and goals, identify program successes and 
challenges, and assess trade ally relationship.  
 Interview participating builders (up to 5) to assess motivation and challenges, explore customer 
satisfaction and experience, and asses influence of the program on business practices.  
Nonresidential Site Specific and Prescriptive Programs 
The process evaluation of the Site Specific and Prescriptive programs (Interior and Exterior lighting, 
HVAC, Shell, Motor Control HVAC [VFD], Food Services, Green Motors, Compressed Air, Fleet Heat, and 
Grocer) will include the following data‐collection activities: 
 Review program documents and database to assess program changes and determine if database 
contains all necessary fields for customer surveys.  
 Interview Avista staff to assess differences between the implementation of the program in Idaho 
and Washington, assess the impact of Washington’s Clean Energy Transformation Act on program 
design and implementation, document program changes and goals, identify program successes and 
challenges and to assess contractor relationships.  
 Interview implementers to document program understanding, roles and responsibilities, 
experience, satisfaction, and suggestions for improvement. 

30 
 Green Motors: Green Motor Program Group  
 Compressed Air: 4Sight Energy Group, LLC 
 Survey participating customers to explore their experience and continued levels of satisfaction, 
including satisfaction with and influence of the contractor or designer, assess energy‐saving 
behavior and document marketing preferences. 
2020 Idaho Annual Conservation Report Appendices
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Coffee shop, Wallace, Idaho