20130717IPC Attachment 1-EE Potential Study.PDF

IDAHO POWER ENERGY EFFICIENCY POTENTIAL STUDY

EnerNOC Utility Solutions Consulting iii

This report was prepared by
EnerNOC Utility Solutions Consulting
500 Ygnacio Valley Blvd., Suite 450
Walnut Creek, CA 94596
Project Director: I. Rohmund
Project Manager: J. Borstein

EnerNOC Utility Solutions Consulting v

EXECUTIVE SUMMARY
Idaho Power prepares an Annual Demand Side Management (DSM) report that describes its
programs and achievements. Periodically, Idaho Power performs an EE potential study to assess
the future potential for savings through its programs and to identify refinements that will
enhance savings. As part of this well-established process, Idaho Power contracted with EnerNOC
Utility Solutions Consulting (EnerNOC) to conduct an energy efficiency potential assessment to
quantify the amount, the timing, and the cost of electric energy efficiency resources available
within the Idaho Power service territory. Key objectives for the study include:
 Provide credible and transparent estimation of the technical, economic, and achievable
energy efficiency potential by year over the next 21 years within the Idaho Power service
territory 1
 Assess potential energy savings associated with each potential area by energy efficiency
measure or bundled measure and sector
 Provide an executable dynamic model that will support the potential assessment and allow
for testing of sensitivity of all model inputs and assumptions
 Review and update load profiles by sector, program, and end use
 Develop a final report including summary data tables and graphs reporting incremental and
cumulative potential by year from 2012 through 2032
Definitions of Potential
In this study, the energy efficiency potential estimates represent gross savings developed into
three types of potential: technical potential, economic potential, and achievable potential.
Technical and economic potential are both theoretical limits to efficiency savings. Achievable
potential embodies a set of assumptions about the decisions consumers make regarding the
efficiency of the equipment they purchase, the maintenance activities they undertake, the
controls they use for energy-consuming equipment, and the elements of building construction.
These levels are described below.
Technical potential is defined as the theoretical upper limit of energy efficiency potential. It
assumes that customers adopt all feasible measures regardless of cost. At the time of equipment
failure, customers replace equipment with the most efficient option available. In new
construction, customers and developers also choose the most efficient equipment option.
Technical potential also assumes the adoption of every available other measure, where
applicable. For example, it includes installation of high-efficiency windows in all new construction
opportunities and heat pump maintenance in all existing buildings with heat pump systems. The
retrofit measures are phased in over a number of years, which is longer for higher-cost
measures.
Economic potential represents the adoption of all cost-effective energy efficiency measures.
In this analysis, the total resource cost (TRC) test, which compares lifetime energy and capacity
benefits to the incremental cost of the measure, is applied. Economic potential assumes that

1 The technical, economic, and achievable potential projections are calculated as the savings versus a hypothetical scenario in which
Idaho Power completely stops offering DSM programs in the future. Therefore, they represent total potential, not the marginal
potential compared with current programs.
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customers purchase the most cost-effective option at the time of equipment failure and also
adopt every other cost-effective and applicable measure.
Achievable potential takes into account market maturity, customer preferences for energy -
efficient technologies, and expected program participation. Achievable potential establishes a
realistic target for the energy efficiency savings that a utility can hope to achieve through its
programs. It is determined by applying a series of annual market adoption factors to the
economic potential for each energy efficiency measure. These factors represent the ramp rates
at which technologies will penetrate the market. To develop these factors, the project team
reviewed Idaho Power’s past DSM achievements and program history over the last five year s, as
well as the Northwest Power and Conservation Council (NWPCC) ramp rates used in the Sixth
Plan. Details regarding the market adoption factors appear in Appendix F.
Analysis Approach
To perform the energy efficiency analysis, EnerNOC used a bottom-up analysis approach as
shown in Figure ES-1 and summarized below.
Figure ES-1 Overview of Analysis Approach

1. Held a meeting with Idaho Power staff to refine objectives and develop a study work plan.
2. Performed a market characterization to describe sector-level electricity use for the
residential, commercial, industrial, and irrigation sectors for the base year, 2011. This
included using utility data and secondary data from sources such as the American Community
Survey (ACS), and the Energy Information Administration (EIA).
3. Utilized Idaho Power primary market research from the Idaho Power 2010 Home Energy
Survey and secondary sources including the NWPCC and the Northwest Energy Efficiency
Alliance (NEAA) to understand how customers in the Idaho Power service territory currently
use electricity. Combining this information with the market characterization, we developed
energy market profiles that describe energy use by sector, segment, and end use for 2011.
EE measure dataUtility data
Engineering analysis
Secondary data
Market characterization
Customer participation
Program considerations
Market capacity
Statement of Work Meeting
Establish objectives
Technical and
economic potential
Achievable potential
Utility data
Customer surveys
Secondary data
Base-year energy use
by segment
Baseline projection
Draft report
Supply curves
Final report
Detailed Work Plan
End-use projection by
segment
Prototypes and
energy analysis
Program results
Secondary data
Best-practices research
Forecast data
Synthesis / analysis
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EnerNOC Utility Solutions Consulting vii
4. Developed a baseline electricity projection by sector, segment, and end use for 2012–2032.
This projection provides the metric against which EE savings are measured.
5. Identified and analyzed energy efficiency measures appropriate for the Idaho Power service
territory, including but not limited to measures currently covered in Idaho Power programs.
6. Estimated three levels of energy efficiency potential, Technical, Economic, and Achievable.
The baseline projection and the estimates of EE potential were develope d using EnerNOC’s
Load Management Analysis and Planning (LoadMAPTM) model.
7. Separately estimated potential for Idaho Power’s special-contract customers.
8. Developed supply curves.
The results from these steps are summarized below, with details provided in the body of the
report.
Market Characterization
Idaho Power, established in 1916, is an investor-owned electric utility that serves more than
490,000 customers within a 24,000-square-mile area in southern Idaho and eastern Oregon. To
meet its customers’ electricity demands, Idaho Power maintains a generation portfolio including
17 hydroelectric projects. The company also actively seeks cost-effective ways to encourage wise
use of electricity by providing energy efficiency programs for all customers.
Total electricity use for the residential, commercial, industrial, and irrigation sectors for Idaho
Power in 2011 was 12,869,213 MWh.2 As shown in Figure ES-2, the largest sector is residential,
accounting for 39.5%, or 5,079,293 MWh. The commercial and industrial sectors combined have
sales of 6,021,110 MWh or 46.8% of sales. Irrigation, with annual sales of 1,768,810 MWh
makes up the remaining 13.7%.
Figure ES-2 Sector-Level Electricity Use, 2011

To analyze potential at the measure level, EnerNOC made some adjustments between the
commercial and industrial sales by sector that are shown above in Figure ES-2 to better group
energy use by facility type and end uses. For example, some customers on commercial rates —
such as dairy and agricultural operations, refrigerated warehouses, small manufacturing, water

2 Energy usage as measured “at-the-meter,” i.e., does not include line losses. Excludes special-contract customers, whose potential
was characterized separately.
Residential
39.5%
Commercial
29.5%
Industrial
17.3%
Irrigation
13.7%
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treatment, and waste water treatment — were reclassified as industrial. We did this because
energy use in these operations is more likely dominated by motor and process end uses, rather
than the HVAC, lighting, and office equipment end uses that dominate commercial buildings.
Therefore, energy-savings potential for these facilities can best be estimated by treating them as
industrial. Conversely, some customers on Idaho Power’s industrial rate such as colleges and
hospitals were reclassified as commercial. The amount of sales that were reclassified represent
less than 6% of total C&I sales.
Figure ES-3 presents the shares of residential electricity use for each housing segment used in
the analysis. The chosen threshold for the limited income segments was approximately twice the
federal poverty limit.
Figure ES-3 Residential Market Segmentation by Housing Type, 2011

Figure ES-4 shows the breakdown of annual use per household by end use for each segment and
for the residential sector as a whole. Four main end uses — space conditioning (cooling and
heating), appliances, lighting, and water heating — account for more than 80% of total use. The
remaining energy is allocated to electronics and miscellaneous.
52%55%
6%4%4%5%
24%24%
7%4%
7%8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% of Customers % of Sales
Limited Income Mobile Home
Limited Income Multi Family
Limited Income Single Family
Mobile/MFG Home
Multi Family
Single Family
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EnerNOC Utility Solutions Consulting ix
Figure ES-4 Residential Intensity by End Use and Segment, 2011

Figure ES-5 shows the percentage of the 2011 commercial energy use, 3,411,788 MWh, for each
of the 12 segments analyzed.3 The three largest segments are small office, retail, and hospital
(including doctors’ office and other medical facilities) with 17.3%, 16.7%, and 10.1% of sales
respectively.
Figure ES-5 Commercial Market Segmentation by Building Type, Percentage of Sales,
2011

Figure ES-6 shows the breakdown of annual commercial electricity usage by end use for the
commercial sector as a whole. Space conditioning and lighting are the largest end uses, together
consuming approximately 66% of commercial building energy use.

3 Excludes street lighting sales of 23,879 MWh.
0
2,000
4,000
6,000
8,000
10,000
12,000
Single Family Small Multi
Family
Low-rise
Multi Family
High-rise
Multi Family
Mobile
Home
In
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(
k
W
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Cooling
Space Heating
Heat/Cool
Water Heating
Appliances
Interior Lighting
Exterior Lighting
Electronics
Miscellaneous
Small Office
17.3%
Large Office
6.0%
Restaurant
7.3%
Retail 16.7%
Grocery
7.2%
College 3.8%
School
7.0%
Hospital 10.1%
Lodging 4.9%
Assembly 5.9%
Warehouse
6.0%
Miscellaneous
7.7%
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Figure ES-6 Commercial Sector Energy Use by End Use, 2011

The industrial customers were segmented into four major industries plus an Other category as
shown in Figure ES-7. The Other category represents a wide-range of industry types, including
stone and concrete; lumber and wood products; paper and mill; chemical s; metals and fabricated
metal products; and rubber and plastics. Individually, however, these industries account for less
than 5% of industrial sales and thus were placed in the Other category.
Figure ES-7 Industrial Market Segmentation by Industry Type, Percentage of Sales,
2011

Cooling
18%
Heating
9%
Ventilation
8%
Water Heating
4%
Interior Lighting
28%
Exterior
Lighting
6%
Refrigeration
8%
Food
Preparation
4%
Office
Equipment
6%Miscellaneous
9%
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Figure ES-8 shows how the major industrial segments in the Idaho Power service territory
identified above used electricity in 2011. Motor loads dominate all segments, though process
heating and cooling are more prevalent in the manufacturing — food segment.
Figure ES-8 Industrial Energy Use by Segment and End Use, 2011

The irrigation sector accounted for 1,768,810 MWh in electricity sales in 2011. We characterized
the sector as a single segment with 18,736 irrigation service points. We then used data from
Idaho Power that classifies these service points by motor size categories as a way to characterize
energy use.
Baseline Projection
Prior to developing estimates of energy efficiency potential, a baseline end-use projection was
developed to quantify what consumption is likely to be in the future in absence of new utility
programs. The baseline projection serves as the metric against which energy efficiency potentials
are measured.
Figure ES-9 through Figure ES-11 present the baseline end-use projections for the residential,
commercial, and industrial sectors respectively. Table ES-1 and Figure ES-12 provide a summary
of the baseline projection by sector and for Idaho Power as a whole. Street lighting sales,
although not analyzed in LoadMAP, have been assumed to be flat and have been added in to
align with the total sales shown in Figure ES-2 . Electricity use across all sectors is expected to
increase by 31% between the base year 2011 and 2032, for an average annual growth rate of
1.3%.
 The industrial sector has the highest growth, with a 47% increase (1.8% annual growth rate)
over the projection horizon.
 The commercial sector has the second highest growth at 1.4% per year on average.
 The residential sector shows moderate growth of 27% over the projection period, or an
average annual growth of 1.1%. Growth is particularly slow during the first few years of the
projection, due to the relatively slow economy, as well as the phase in of the EISA lighting
standards and other new equipment standards.
0
200
400
600
800
1,000
1,200
1,400
1,600
Manufacturing -
Food
Agriculture Water and
Wastewater
Electronics Other
An
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E
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U
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(
1
,
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0
0

M
W
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)
Cooling
Heating
Ventilation
Interior Lighting
Exterior Lighting
Motors
Process
Miscellaneous
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Figure ES-9 Residential Baseline Projection by End Use

Figure ES-10 Commercial Baseline Projection by End Use

0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
2011 2012 2013 2015 2017 2022 2027 2032
An
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(
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M
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Cooling
Space Heating
Water Heating
Interior Lighting
Exterior Lighting
Appliances
Electronics
Miscellaneous
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
2011 2012 2013 2015 2017 2022 2027 2032
An
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Cooling
Heating
Ventilation
Water Heating
Interior Lighting
Exterior Lighting
Refrigeration
Food Preparation
Office Equipment
Miscellaneous
Executive Summary

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Figure ES-11 Industrial Baseline Projection by End Use

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Table ES-1 Baseline Projection Summary (1,000 MWh)
Sector 2011 2012 2013 2015 2017 2022 2027 2032 % Change
2011-2032
Avg. Annual
Growth
Rate
Residential 5,079 5,075 5,076 5,159 5,348 5,718 6,058 6,462 27% 1.1%
Commercial 3,412 3,448 3,506 3,625 3,738 4,053 4,282 4,531 33% 1.4%
Industrial 2,585 2,651 2,741 2,895 3,010 3,210 3,493 3,812 47% 1.8%
Irrigation 1,769 1,789 1,790 1,819 1,825 1,900 1,964 2,038 15% 0.7%
Street Lighting 24 24 24 24 24 24 24 24 0% 0.0%
Total 12,869 12,987 13,136 13,521 13,945 14,904 15,821 16,868 31% 1.3%

Figure ES-12 Baseline Projection Summary

-
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
An
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Street Lighting
Irrigation
Industrial
Commercial
Residential
Executive Summary
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Energy Efficiency Measures
The first step of the energy conservation measure analysis was to identify the list of all relevant
conservation measures that should be considered for the potential assessment. Sources for
selecting and characterizing measures included Idaho Power’s programs, the Northwest Power
and Conservation Council’s Regional Technical Forum (RTF) deemed measure databases,
EnerNOC’s building modeling tool BEST and EnerNOC’s measure databases from previous studies
and program work.
The measures are categorized into two types according to the LoadMAP4 taxonomy: equipment
measures and non-equipment measures:
 Equipment measures, or efficient energy-consuming pieces of equipment, save energy by
providing the same service with a lower energy requirement. An example is the replacement
of a standard efficiency refrigerator with an ENERGY STAR model. For equipment measures,
many efficiency levels are available for a specific technology that range from the baseline
unit (often determined by code or standard) up to the most efficient product commercially
available. For instance, in the case of central air conditioners, this list begins with the federal
standard SEER 13 unit and spans a broad spectrum of efficiency, with the highest efficiency
level represented by a SEER 21 unit.
 Non-equipment measures save energy by reducing the need for delivered energy but do
not involve replacement or purchase of major end-use equipment (such as a refrigerator or
air conditioner). An example would be a programmable thermostat that is pre -set to run the
air conditioner only when people are home. Non-equipment measures fall into one of the
following categories:
o Building shell (windows, insulation, roofing material)
o Equipment controls (thermostat, occupancy sensors)
o Equipment maintenance (cleaning filters, changing setpoints)
o Whole-building design (natural ventilation, passive solar lighting)
o Lighting retrofits (included as a non-equipment measure because retrofits are performed
prior to the equipment’s normal end of life)
o Displacement measures (ceiling fan to reduce use of central air conditioners)
o Commissioning and retrocommissioning
Table ES-2 summarizes the number of equipment and non-equipment measures evaluated for
each sector.
Table ES-2 Number of Measures Evaluated
Measures Evaluated Residential Commercial Industrial Irrigation
Total
Number of
Measures
Equipment Measures 1,500 3,528 1,038 88 6,154
Non-Equipment Measures 488 1,784 726 70 3,068
Total 1,988 5,312 1,764 158 9,222

4 EnerNOC’s Load Management Analysis and PlanningTM tool, which was used to perform the energy efficiency potential analysis.
Executive Summary

xvi www.enernoc.com
Energy Efficiency Potential Results
Table ES-3 and Figure ES-13 summarize the energy efficiency savings for the different levels of
potential relative to the baseline projection. Figure ES-14 displays the baseline and potential
projections.
 Achievable potential across the residential, commercial, industrial, and irrigation sectors is
594,772 MWh or 67.9 aMW in 2017 and increases to 234.4 aMW by 2032. This represents
4.3% of the baseline projection in 2017 and 12.2% in 2032. By 2032, Achievable potential of
2,053,161 MWh offsets 53% of the 3,904,245 MWh growth in the baseline projection over
the study period.
 Economic potential, which reflects the savings when all cost-effective measures are taken,
is 1,734,396 MWh or 198.0 aMW in 2017. This represents 12.4% of the baseline energy
projection. By 2032, economic potential reaches 438.3 aMW, 22.8% of the baseline energy
projection.
 Technical potential, which reflects the adoption of all energy efficiency measures
regardless of cost-effectiveness, is a theoretical upper bound on savings. In 2017, technical
potential savings are 2,849,545 MWh or 325.3 aMW, equivalent to 20.4% of the baseline
energy projection. By 2032, technical potential reaches 720.0 aMW, 37.4% of the baseline
energy projection.
Table ES-3 Summary of Energy Efficiency Potential

2012 2013 2015 2017 2022 2027 2032
Baseline Projection (MWh)12,963,424 13,135,778 13,521,442 13,944,808 14,904,276 15,821,200 16,867,669
Cumulative Savings (MWh)
Achievable Potential 128,230 213,793 410,726 594,772 1,048,684 1,570,770 2,053,161
Economic Potential 732,142 1,002,446 1,476,490 1,734,396 2,695,890 3,373,589 3,839,473
Technical Potential 1,177,752 1,587,035 2,329,976 2,849,545 4,372,407 5,545,301 6,307,377
Cumulative Savings (aMW)
Achievable Potential 14.6 24.4 46.9 67.9 119.7 179.3 234.4
Economic Potential 83.6 114.4 168.5 198.0 307.8 385.1 438.3
Technical Potential 134.4 181.2 266.0 325.3 499.1 633.0 720.0
Savings (% of Baseline)
Achievable Potential 1.0%1.6%3.0%4.3%7.0%9.9%12.2%
Economic Potential 5.6%7.6%10.9%12.4%18.1%21.3%22.8%
Technical Potential 9.1%12.1%17.2%20.4%29.3%35.0%37.4%
Executive Summary
EnerNOC Utility Solutions Consulting xvii
Figure ES-13 Summary of Energy Savings by Potential Case

Figure ES-14 Energy Efficiency Potential Projections

0%
5%
10%
15%
20%
25%
30%
35%
40%
2012 2013 2015 2017 2022 2027 2032
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Economic Potential
Technical Potential
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Table ES-4 and Figure ES-15 summarize achievable potential by sector and year.
Table ES-4 Achievable Energy Efficiency Potential by Sector
Sector 2012 2013 2015 2017 2022 2027 2032
Achievable Cumulative Savings (MWh)
Residential 34,123 60,991 132,339 189,469 297,049 473,094 701,104
Commercial 51,289 77,323 135,839 194,418 357,246 512,268 633,771
Industrial 39,772 69,610 122,714 174,526 301,997 415,708 488,465
Irrigation 3,046 5,869 19,833 36,360 92,393 169,700 229,821
Total 128,230 213,793 410,726 594,772 1,048,684 1,570,770 2,053,161
Achievable Cumulative Savings (aMW)
Residential 3.9 7.0 15.1 21.6 33.9 54.0 80.0
Commercial 5.9 8.8 15.5 22.2 40.8 58.5 72.3
Industrial 4.5 7.9 14.0 19.9 34.5 47.5 55.8
Irrigation 0.3 0.7 2.3 4.2 10.5 19.4 26.2
Total 14.6 24.4 46.9 67.9 119.7 179.3 234.4

Figure ES-15 Achievable Energy Efficiency Potential by Sector

Figure ES-16 focuses on the residential cumulative achievable potential in 2017.
 Lighting, primarily the conversion of both interior and exterior lamps to compact fluorescent
lamps, represents 110,904 MWh or 59% of savings.
 Cooling and heating are the next highest sources of achievable potential, at 13% and 11%
respectively, due mainly to savings from duct repair /sealing and thermostats.
 Water heating, including low-flow fixtures, pipe wrap, and efficient water heaters, provide
6% of achievable potential.
-
500
1,000
1,500
2,000
2,500
2015 2017 2022 2032
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Industrial
Commercial
Residential
Executive Summary
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 Electronics, including efficient televisions, computers, and set top boxes, as well as devices
that reduce standby energy use, offer 6% of the potential.
 Appliances, mainly removal of second refrigerators and freezers, provide 5%.
Figure ES-16 Residential Achievable Potential by End Use in 2017 (percentage of total)

As shown in Figure ES-17 , the primary sources of commercial sector achievable savings in 2017
are as follows:
 Interior and exterior lighting, with lamps and fixtures accounting for 40% of commercial
sector achievable potential, and lighting controls and commissioning providing the remaining
6%
 HVAC — with the largest proportion due to converting ventilation systems to variable air
volume (VAV) (8%), followed by high-efficiency chillers (5%), advanced new construction
designs (3%), energy managements systems (4%), and commissioning and other controls
(4%)
 Office Equipment – servers and efficient computers (6%)
 Water heating and refrigeration provide 6% and 5% of savings

Executive Summary

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Figure ES-17 Commercial Achievable Potential Savings by End Use in 2017 (percentage
of total)

Figure ES-17 illustrates the end uses that contribute to achievable potential savings in 2017 for
the industrial sector, reflecting that the preponderance of savings comes from motor loads,
followed by process-related measures.
Figure ES-18 shows the achievable potential savings by end use. The specific measures providing
the greatest savings are variable frequency and variable speed drives for fans, pumps, and other
motors; fan and pump measures such as optimization and controls, compressed air measures,
and refrigeration measures.
Figure ES-18 Industrial Achievable Potential Savings by End Use in 2017 (MWh)

Cooling
8%
Heating
6%
Ventilation
3%
Interior Lighting
10%
Exterior Lighting
1%
Motors
52%
Process
20%
Miscellaneous
0%
Executive Summary
EnerNOC Utility Solutions Consulting xxi
Although the smallest of the sectors analyzed here, the irrigation sector still has significant
achievable potential of 36,360 MWh in 2017. The only end-use in the irrigation sector analysis is
motors. Because of the NEMA motor standards, all new and replacement motors will move to
premium efficiency units in the baseline case and potential savings are only available from
upgrading to still more efficient levels. These higher efficiency units do not pass the cost-
effectiveness test. Nonetheless, savings are available from the following measures:
 Scientific irrigation practices (38% of 2017 savings)
 Proper pressure or head design (21% of 2017 savings)
 Multiple configuration nozzles and nozzle replacement (15% of 2017 savings)
 Variable frequency drives (10% of 2017 savings)
 Multiple pumps to enable part-load operation (6% of 2017 savings)
The special contract customers were not analyzed within LoadMAP, but instead, potential was
assessed separately. Consideration for this analysis included EE measures and actions already
implemented, general business plans, and planned future efficiency measures. Based on this
analysis, potential for these customers was estimated at approximately 10,557 MWh annually.
Report Organization
The body of the report is organized as follows:
1. Introduction
2. Analysis Approach and Data Development
3. Market Assessment and Market Profiles
4. Baseline Projection
5. Energy Efficiency Potential

EnerNOC Utility Solutions Consulting xxiii

CONTENTS
EXECUTIVE SUMMARY ............................................................................................. V
1 INTRODUCTION .................................................................................................... 1-1
Background ................................................................................................................... 1-1
2 ANALYSIS APPROACH DATA DEVELOPMENT ........................................................ 2-1
Introduction................................................................................................................... 2-1
LoadMAP Model ................................................................................................. 2-2
Market Characterization ...................................................................................... 2-3
Baseline Projection ............................................................................................. 2-9
Energy Efficiency Measure Analysis ..................................................................... 2-9
Energy Efficiency Potential ................................................................................ 2-13
Data Development ....................................................................................................... 2-14
Data Sources ................................................................................................... 2-14
Data Application ........................................................................................................... 2-17
Data Application for Market Characterization ...................................................... 2-17
Data Application for Market Profiles ................................................................... 2-18
Data Application for Baseline Forecast ............................................................... 2-19
Data Application for Energy Efficiency Measures ................................................ 2-22
Data Application for Cost-effectiveness Screening .............................................. 2-23
Data Application for Potentials Estimation .......................................................... 2-23
3 MARKET CHARACTERIZATION AND MARKET PROFILES ...................................... 3-1
Residential Sector .......................................................................................................... 3-2
Commercial Sector ......................................................................................................... 3-7
Industrial Sector ............................................................................................................ 3-3
Irrigation Sector ............................................................................................................. 3-6
4 BASELINE PROJECTION ........................................................................................ 4-1
Residential Sector .......................................................................................................... 4-1
Commercial Sector ......................................................................................................... 4-5
Industrial Sector ............................................................................................................ 4-7
Irrigation ....................................................................................................................... 4-9
Baseline Projection Summary ........................................................................................ 4-10
5 ENERGY EFFICIENCY POTENTIAL ......................................................................... 5-1
Residential Sector .......................................................................................................... 5-4
Residential Potential by End Use ......................................................................... 5-5
Residential Potential by Market Segment ............................................................. 5-9
Commercial Sector Potential ......................................................................................... 5-11
Commercial Potential by End Use, Technology, and Measure Type ...................... 5-12
Commercial Potential by Market Segment .......................................................... 5-17
Industrial Sector Potential............................................................................................. 5-21

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Industrial Potential by End Use, Technology, and Measure Type ......................... 5-22
Industrial Sector Potential by Market Segment ................................................... 5-24
Irrigation Sector Potential ............................................................................................. 5-25
Special-Contract Customer Potential .............................................................................. 5-27

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CONTENTS

LIST OF FIGURES
Figure ES-1 Overview of Analysis Approach ................................................................................ vi
Figure ES-2 Sector-Level Electricity Use, 2011 ........................................................................... vii
Figure ES-3 Residential Market Segmentation by Housing Type, 2011 ......................................... viii
Figure ES-4 Residential Intensity by End Use and Segment, 2011 ................................................ ix
Figure ES-5 Commercial Market Segmentation by Building Type, Percentage of Sales, 2011 .......... ix
Figure ES-6 Commercial Sector Energy Use by End Use, 2011 .................................................... x
Figure ES-7 Industrial Market Segmentation by Industry Type, Percentage of Sales, 2011.............. x
Figure ES-8 Industrial Energy Use by Segment and End Use, 2011 .............................................. xi
Figure ES-9 Residential Baseline Projection by End Use .............................................................. xii
Figure ES-10 Commercial Baseline Projection by End Use ............................................................. xii
Figure ES-11 Industrial Baseline Projection by End Use ................................................................ xiii
Figure ES-12 Baseline Projection Summary................................................................................. xiv
Figure ES-13 Summary of Energy Savings by Potential Case ........................................................ xvii
Figure ES-14 Energy Efficiency Potential Projections ................................................................... xvii
Figure ES-15 Achievable Energy Efficiency Potential by Sector .................................................... xviii
Figure ES-16 Residential Achievable Potential by End Use in 2017 (percentage of total) ................ xix
Figure ES-17 Commercial Achievable Potential Savings by End Use in 2017 (percentage of total) ... xx
Figure ES-18 Industrial Achievable Potential Savings by End Use in 2017 (MWh) ........................... xx
Figure 2-1 Overview of Analysis Approach .............................................................................. 2-1
Figure 2-2 LoadMAP Analysis Framework ................................................................................ 2-3
Figure 2-3 Approach for Measure Assessment ....................................................................... 2-10
Figure 2-4 Avoided Costs ..................................................................................................... 2-23
Figure 3-1 Sector-Level Electricity Use, 2011 .......................................................................... 3-1
Figure 3-2 Residential Market Segmentation by Housing Type, 2011 ........................................ 3-3
Figure 3-3 Residential Electricity Use by End Use and Segment (2011), All Homes .................... 3-5
Figure 3-4 Residential Intensity by End Use and Segment, 2011 .............................................. 3-5
Figure 3-5 Percentage of Residential Electricity Use by End Use and Segment (2011) ............... 3-6
Figure 3-6 Commercial Market Segmentation by Building Type, Percentage of Sales, 2011 .... 3-7
Figure 3-7 Commercial Sector Energy Use by End Use, 2011 ............................................... 3-10
Figure 3-8 Commercial Building Intensity by Segment, 2011 .................................................. 3-10
Figure 3-9 Percentage of Annual Electricity Use by End Use for Commercial Buildings ............. 3-11
Figure 3-10 Industrial Market Segmentation by Industry Type, Percentage of Sales, 2011 ....... 3-3
Figure 3-11 Industrial Sector Energy Use by End Use .............................................................. 3-5
Figure 3-12 Industrial Energy Use by Segment and End Use, 2011 ............................................ 3-5
Figure 3-13 Percentage of Annual Electricity Use by End Use for Industry Segments ................... 3-6
Figure 4-1 Residential Baseline Projection by End Use ............................................................. 4-2
Figure 4-2 Residential Baseline Projection Use per Customer by End Use .................................. 4-2
Figure 4-3 Commercial Baseline Projection by End Use ............................................................ 4-6
Figure 4-4 Industrial Baseline Electricity Projection by End Use ................................................ 4-8

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Figure 4-5 Baseline Projection Summary............................................................................... 4-10
Figure 5-1 Summary of Energy Savings by Potential Case ........................................................ 5-2
Figure 5-2 Energy Efficiency Potential Projections ................................................................... 5-2
Figure 5-3 Achievable Energy Efficiency Potential by Sector ..................................................... 5-3
Figure 5-4 Residential Energy Savings by Potential Case ......................................................... 5-5
Figure 5-5 Residential Energy Efficiency Potential Projections .................................................. 5-5
Figure 5-6 Residential Achievable Potential by End Use in 2017 (percentage of total) ................ 5-7
Figure 5-7 Commercial Energy Efficiency Potential Savings .................................................... 5-12
Figure 5-8 Commercial Energy Efficiency Potential Projections ............................................... 5-12
Figure 5-9 Commercial Achievable Potential Cumulative Savings by End Use in 2017 (percentage
of total).............................................................................................................. 5-17
Figure 5-10 Commercial Achievable Savings in 2017 by End Use and Building Type .................. 5-20
Figure 5-11 Industrial Energy Efficiency Potential Savings ....................................................... 5-21
Figure 5-12 Industrial Energy Efficiency Potential Projection .................................................... 5-22
Figure 5-13 Industrial Achievable Potential Savings by End Use in 2017 (MWh) ........................ 5-24
Figure 5-14 Industrial Achievable Potential Savings by Segment and End Use in 2017 (MWh) ... 5-25
Figure 5-15 Irrigation Energy Efficiency Potential Savings........................................................ 5-26
Figure 5-16 Irrigation Energy Efficiency Potential Projection .................................................... 5-26

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LIST OF TABLES
Table ES-1 Baseline Projection Summary (1,000 MWh) ............................................................ xiv
Table ES-2 Number of Measures Evaluated .............................................................................. xv
Table ES-3 Summary of Energy Efficiency Potential.................................................................. xvi
Table ES-4 Achievable Energy Efficiency Potential by Sector .................................................... xviii
Table 1-1 Explanation of Abbreviations and Acronyms ............................................................ 1-3
Table 2-1 Overview of Analysis Segmentation Scheme ........................................................... 2-4
Table 2-2 Residential End Uses and Technologies .................................................................. 2-5
Table 2-3 Commercial End Uses and Technologies ................................................................. 2-8
Table 2-4 Sample Equipment Measures for Air Conditioning – Single Family Existing .............. 2-11
Table 2-5 Sample Non-Equipment Measures Affecting Cooling – Single Family Home, Existing 2-12
Table 2-6 Data Applied for the Market Profiles ..................................................................... 2-18
Table 2-7 Data Needs for the Baseline Projection and Potentials Estimation in LoadMAP ........ 2-19
Table 2-8 Residential Electric Equipment Standards ............................................................. 2-20
Table 2-9 Commercial Electric Equipment Standards ............................................................ 2-21
Table 2-10 Data Needs for the Measure Characteristics in LoadMAP ....................................... 2-22
Table 2-11 Number of Measures Evaluated ........................................................................... 2-23
Table 3-1 Sector Level Market Characterization, Base Year 2011............................................. 3-1
Table 3-2 Commercial and Industrial Sales Adjustments for LoadMAP Modeling ....................... 3-2
Table 3-3 Residential Market Segmentation by Housing Type, Base Year 2011 ........................ 3-3
Table 3-4 Residential Sector Composite Market Profile 2011 ................................................... 3-4
Table 3-5 Residential Electricity Use by End Use and Segment (kWh/cust/year, 2011) ............. 3-6
Table 3-6 Commercial Sector Market Characterization ............................................................ 3-8
Table 3-7 Commercial Sector Composite Market Profile, 2011 ................................................. 3-9
Table 3-8 Commercial Electricity Use by End Use (1,000 MWh, 2011) ..................................... 3-2
Table 3-9 Industrial Market Segmentation and Employment ................................................... 3-3
Table 3-10 Industrial Sector Composite Market Profile, 2011 .................................................... 3-4
Table 3-11 Industrial Electricity Use by End Use and Segment (1,000 MWh, 2011) .................... 3-6
Table 3-12 Irrigation Sector Market Profile, 2011 ..................................................................... 3-7
Table 4-1 Residential Baseline Projection by End Use (1,000 MWh) ......................................... 4-1
Table 4-2 Residential Baseline Projection of Use per Customer by End Use (kWh).................... 4-3
Table 4-3 Residential Baseline Forecast by End Use and Technology (MWh) ............................ 4-4
Table 4-4 Commercial Electricity Consumption by End Use (1,000 MWh) ................................. 4-5
Table 4-5 Commercial Baseline Electricity Projection by End Use and Technology (1,000 MWh) 4-7
Table 4-6 Industrial Electricity Consumption by End Use (MWh) ............................................. 4-8
Table 4-7 Irrigation Baseline Projection ................................................................................. 4-9
Table 4-8 Baseline Projection Summary (1,000 MWh) .......................................................... 4-10
Table 5-1 Summary of Energy Efficiency Potential.................................................................. 5-1
Table 5-2 Achievable Energy Efficiency Potential by Sector ..................................................... 5-3
Table 5-3 Energy Efficiency Potential for the Residential Sector .............................................. 5-4

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Table 5-4 Residential Savings by End Use and Potential Type (MWh) ...................................... 5-6
Table 5-5 Residential Achievable Potential for Equipment Measures (1,000 MWh) .................... 5-8
Table 5-6 Residential Achievable Savings for Non-equipment Measures (1,000 MWh) .............. 5-9
Table 5-7 Residential Achievable Potential by Market Segment ............................................. 5-10
Table 5-8 Residential Potential Summary by Market Segment, 2017 ...................................... 5-10
Table 5-9 Residential Achievable Potential by End Use and Market Segment, 2017 (MWh) ..... 5-11
Table 5-10 Energy Efficiency Potential for the Commercial Sector ........................................... 5-11
Table 5-11 Commercial Potential by End Use and Potential Type (MWh) ................................. 5-13
Table 5-12 Commercial Achievable Savings for Equipment Measures (1,000MWh) ................... 5-14
Table 5-13 Commercial Achievable Savings for Non-equipment Measures (1,000MWh) ............ 5-15
Table 5-14 Commercial Potential by Market Segment, 2017 ................................................... 5-17
Table 5-15 Commercial Achievable Savings in 2017 by End Use and Building Type (1,000 MWh)5-19
Table 5-16 Energy Efficiency Potential for the Industrial Sector .............................................. 5-21
Table 5-17 Industrial Potential by End Use and Potential Type (MWh) .................................... 5-23
Table 5-18 Industrial Potential by Market Segment, 2017 ....................................................... 5-24
Table 5-19 Energy Efficiency Potential for the Irrigation Sector ............................................... 5-25

EnerNOC Utility Solutions Consulting 1-1
INTRODUCTION
Background
Idaho Power has contracted with EnerNOC Utility Solutions Consulting (EnerNOC) to conduct an
energy efficiency (EE) potential assessment to quantify the amount, the timing, and the cost of
electric energy efficiency resources available within the Idaho Power service territory. Key
objectives for the study include:
 Provide credible and transparent estimation of the technical, economic, and achievable
energy efficiency potential by year over the next 21 years within the Idaho Power service
territory
 Assess potential energy savings associated with each potential area by energy efficiency
measure or bundled measure and sector
 Provide an executable dynamic model that will support the potential assessment and allow
for testing of sensitivity of all model inputs and assumptions
 Review and update load profiles by sector, program, and end-use
 Develop a final report including summary data tables and graphs reporting incremental and
cumulative potential by year from 2011 through 2032.
Report Organization
This report contains the following chapters:
1. Introduction
2. Analysis Approach and Data Development
3. Market Assessment and Market Profiles
4. Baseline Projection
5. Energy Efficiency Potential
Definitions of Potential
In this study, the energy efficiency potential estimates represent gross savings developed into
three types of potential: technical potential, economic potential, and achievable potential.
Technical and economic potential are both theoretical limits to efficiency savings. Achievable
potential embodies a set of assumptions about the decisions consumers make regarding the
efficiency of the equipment they purchase, the maintenance activities they undertake, the
controls they use for energy-consuming equipment, and the elements of building construction.
These levels are described below.
Technical potential is defined as the theoretical upper limit of energy efficiency potential. It
assumes that customers adopt all feasible measures regardless of cost. At the time of equipment
failure, customers replace equipment with the most efficient option available. In new
construction, customers and developers also choose the most efficient equipment option.
Examples of measures that make up technical potential in the residential sector include:
Technical potential also assumes the adoption of every available other measure, where
applicable. For example, it includes installation of high-efficiency windows in all new construction
opportunities and heat pump maintenance in all existing buildings with heat pump systems. The
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Introduction
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retrofit measures are phased in over a number of years, which is longer for higher-cost
measures.
Economic potential represents the adoption of all cost-effective energy efficiency measures.
In this analysis, the total resource cost (TRC) test, which compares lifetime energy and capacity
benefits to the incremental cost of the measure, is applied. Economic potential assumes that
customers purchase the most cost-effective option at the time of equipment failure and also
adopt every other cost-effective and applicable measure.
Achievable potential takes into account market maturity, customer preferences for energy-
efficient technologies, and expected program participation. Achievable potential establishes a
realistic target for the energy efficiency savings that a utility can hope to achieve through its
programs. It is determined by applying a series of annual factors to the economic potential for
each energy efficiency measure. These factors represent the ramp rates at which technologies
will penetrate the market. To develop these factors, the project team reviewed Idaho Power’s
past DSM achievements and program history over the last five year, as well as the Northwest
Power and Conservation Council (NWPCC) ramp rates used in the Sixth Plan. Details regarding
the ramp rates appear in Appendix E.
The technical, economic, and achievable potential projections are calculated as the savings
versus a hypothetical scenario in which Idaho Power completely stops offering DSM programs in
the future. Therefore, they represent total potential, not the marginal potential compared with
current programs.

Introduction
EnerNOC Utility Solutions Consulting 1-3
Abbreviations and Acronyms
Throughout the report we make reference to several abbreviations and acronym s. Table 1-1
shows the abbreviation or acronym, along with what it stands for.
Table 1-1 Explanation of Abbreviations and Acronyms
AC Air conditioning
ACS American Community Survey
AEO Annual Energy Outlook
aMW Average megawatt; one aMW equals 8,760 MWh
B/C Ratio Benefit to Cost Ratio
BEST EnerNOC’s Building Energy Simulation Tool
C&I Commercial and Industrial
CBSA Northwest Energy Efficiency Alliance Commercial Building Stock Assessment
CFL Compact Fluorescent Lamp
Cust Customer
DEEM Database of Energy Efficiency Measures
DEER Database for Energy-Efficient Resources
DSM Demand side management
EE Energy Efficiency
EIA Energy Information Administration
EISA Energy Efficiency and Security Act of 2007
EPACT Energy Policy Act of 2005
EPRI Electric Power Research Institute
EUI Energy-use Index
HH Household
HID High Intensity Discharge lighting
HPWH Heat Pump Water Heater
IRP Integrated Resource Plan
LED Light Emitting Diode lamp
LoadMAPTM EnerNOC’s Load Management Analysis and Planning tool
MAR Market Acceptance Rate
NEEA Northwest Energy Efficiency Alliance
NWPCC Northwest Power and Conservation Council
POS Terminal Point-of-Sale Terminal
RTF Regional Technical Forum
RTU Roof top unit
SIC Standard Industrial Classification
Sq. ft. Square feet
TRC Total Resource Cost
UEC Unit Energy Consumption
VAV Variable Air Volume

EnerNOC Utility Solutions Consulting 2-1
ANALYSIS APPROACH DATA DEVELOPMENT
Introduction
To perform the energy efficiency analysis, EnerNOC used a bottom-up analysis approach as
shown in Figure 2-1 and summarized below.
Figure 2-1 Overview of Analysis Approach

1. Held a meeting with Idaho Power staff to refine objectives and develop a study work plan.
2. Performed a market characterization to describe sector-level electricity use for the
residential, commercial, industrial, and irrigation sectors for the base year, 2011. This
included using utility data and secondary data from sources such as the American Community
Survey (ACS), and the Energy Information Administration (EIA).
3. Utilized Idaho Power primary market research from the Idaho Power 2010 Home Energy
Survey and secondary sources including the NWPCC and the Northwest Energy Efficiency
Alliance (NEAA) to understand how customers in the Idaho Power service territory currently
use electricity. Combining this information with the market characterization, we developed
energy market profiles that describe energy use by sector, segment, and end use for 2011.
4. Developed a baseline electricity projection by sector, segment, and end use for 2011–2032.
5. Identified and analyzed energy efficiency measures appropriate for the Idaho Power service
territory, including but not limited to measures currently covered in Idaho Power programs.
EE measure dataUtility data
Engineering analysis
Secondary data
Market characterization
Customer participation
Program considerations
Market capacity
Statement of Work Meeting
Establish objectives
Technical and
economic potential
Achievable potential
Utility data
Customer surveys
Secondary data
Base-year energy use
by segment
Baseline projection
Draft report
Supply curves
Final report
Detailed Work Plan
End-use projection by
segment
Prototypes and
energy analysis
Program results
Secondary data
Best-practices research
Forecast data
Synthesis / analysis
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6. Estimated three levels of energy efficiency potential, Technical, Economic, and Achievable.
7. Separately estimated potential for Idaho Power’s special-contract customers.
8. Developed supply curves.
The steps are described in further detail throughout the remainder of this chapter.
LoadMAP Model
We used the EnerNOC’s Load Management Analysis and Planning tool (LoadMAPTM) to develop
the baseline projection, as well as the estimates of energy efficiency potential for the residential,
commercial, industrial, and irrigation sectors. EnerNOC developed LoadMAP in 2007 and has used
it for the EPRI National Potential Study and numerous utility-specific forecasting and potential
studies. Built in Excel, the LoadMAP framework (see Figure 2-2) is both accessible and
transparent and has the following key features.
 Develops a bottom-up projection based on energy use by end use of major energy-
consuming equipment.
 Embodies the basic principles of rigorous end-use models (such as EPRI’s REEPS and
COMMEND) but in a more simplified, accessible form.
 Includes stock-accounting algorithms that treat older, less efficient appliance/equipment
stock separately from newer, more efficient equipment. Equipment is replaced according to
the measure life defined by the user.
 Balances the competing needs of simplicity and robustness by incorporating important
modeling details related to equipment saturations, efficiencies, vintage, and the like, where
market data are available, and treats end uses separately to account for varying importance
and availability of data resources.
 Uses a simple logic for appliance and equipment decisions. Isolates new construction from
existing equipment and buildings and treats purchase decisions for new construction and
existing buildings separately.
 Includes appliance and equipment models customized by end use. For example, the logic for
lighting equipment is distinct from refrigerators and freezers.
 Can accommodate various levels of segmentation. Analysis can be performed at the sector
level (e.g., total residential) or for customized segments within sectors (e.g., housing type or
income level).
Consistent with the segmentation scheme and the market profiles we describe below, the
LoadMAP model provides projections of baseline energy use by sector, segment, end use and
technology for existing and new buildings. It also provides projections of total energy use and
energy efficiency savings associated with the three types of potential.
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EnerNOC Utility Solutions Consulting 2-3
Figure 2-2 LoadMAP Analysis Framework

Market Characterization
Before assessing energy efficiency potential, it is critical to develop a good understanding of
where Idaho Power is today in terms of electricity use and customer behavior. The purpose of
the market characterization is to develop market profiles that describe current electricity use in
terms of sector, customer segment, and end use. The base year for this study is 2011 because
that was the most recent year for which utility sales data were available.
Analysis Segmentation
The market assessment began by defining the market segments (building types, end uses, and
other dimensions) that are relevant for Idaho Power. The segmentation scheme employed for
this project is presented in Table 2-1.

Forecast Data
Market Profiles
Market size
Equipment saturation
Fuel shares
Technology shares
Vintage distribution
Unit energy consumption
Coincident demand
Base-year Energy
Consumption
by technology,
end use, segment,
vintage & sector
Economic Data
Customer growth
Energy prices
Exogenous factors
Elasticities
Energy-efficiency
analysis
Forecast Results
List of measures
Saturations
Adoption rates
Avoided costs
Cost-effectiveness
screening
Baseline forecast
Savings
Estimates
(Annual & peak)
Technical potential
Economic potential
Achievable potential
Customer segmentation Energy-efficiency
forecasts:Technical
Economic
Achievable
Technology Data
Efficiency optionsCodes and standards
Purchase shares
Analysis Approach Data Development
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Table 2-1 Overview of Analysis Segmentation Scheme
Market Dimension
Segmentation
Variable Dimension Example
Dimension 1 Sector Residential, commercial, industrial, irrigation
Dimension 2 Building type
Residential (Single family, Multi family, Mobile/Mfg
Home, Limited Income Single Family, Limited Income
Multi Family, and Limited Income Mobile/Mfg home)
Commercial (Offices, Restaurant, Retail, etc.)
Industrial (Manufacturing - Food, Agriculture, Water
and Wastewater, Electronics, Other industrial)
Irrigation
Dimension 4 Vintage Existing and new construction (for residential and
commercial sectors)
Dimension 5 End uses Cooling, lighting, water heat, motors, etc. (as
appropriate by sector)
Dimension 6
Appliances/end
uses and
technologies
Technologies such as lamp type, air conditioning
equipment, motors by size, etc.
Dimension 7
Equipment
efficiency levels for
new purchases
Baseline and higher-efficiency options as appropriate
for each technology

For the residential sector, the EE potential study used the following segmentation, based on
housing type. For each housing type, we also analyzed a limited income segment, defined as
approximately twice the federal poverty limit, which also correlates with the income threshold
used in Idaho Power’s Weatherization Solutions program.
 Single-family homes — single-family detached homes and duplexes, non limited income
 Multi-family homes — buildings with 3 or more units, non limited income
 Mobile/Mfg homes — mobile homes and manufactured housing, non limited income
 Limited income single-family homes — single-family detached homes and duplexes,
limited income
 Limited income multi-family homes — buildings with 3 or more units, limited income
 Limited income mobile homes — mobile homes and manufactured housing, limited
income
In addition to segmentation by housing type, we identified the set of end uses and technologies
that are appropriate for Idaho Power. These are shown in Table 2-2.

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EnerNOC Utility Solutions Consulting 2-5
Table 2-2 Residential End Uses and Technologies
End Use Technology
Cooling Central Air Conditioning (CAC)
Cooling Room Air Conditioning (RAC)
Cooling Air-Source Heat Pump
Cooling Geothermal Heat Pump
Cooling Evaporative Air Conditioning
Space Heating Electric Room Heat
Space Heating Electric Furnace
Space Heating Air-Source Heat Pump
Space Heating Geothermal Heat Pump
Water Heating Water Heater <= 55 Gal
Water Heating Water Heater > 55 Gal
Interior Lighting Screw-in Lamps
Interior Lighting Linear Fluorescent Lamps
Interior Lighting Specialty
Exterior Lighting Screw-in Lamps
Appliances Clothes Washer
Appliances Clothes Dryer
Appliances Dishwasher
Appliances Refrigerator
Appliances Freezer
Appliances Second Refrigerator
Appliances Stove
Appliances Microwave
Electronics Personal Computers
Electronics Monitor
Electronics Laptops
Electronics TVs
Electronics Printer/Fax/Copier
Electronics Set-top Boxes/DVR
Electronics Devices and Gadgets
Miscellaneous Pool Pump
Miscellaneous Pool Heater
Miscellaneous Hot Tub / Spa
Miscellaneous Well Pump
Miscellaneous Furnace Fan
Miscellaneous Miscellaneous
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For the commercial sector, it is useful to think of the segments based on the unique
characteristics of the type of building. This study used the following building types:
 Small office (less than 50,000 square feet) —all types of offices
 Large office (greater than or equal to 50,000 square feet) — all types of offices including
large government facilities; data centers are also included
 Restaurant — fast-food, sit-down and cafeteria-style restaurants
 Retail — retail establishments from small boutiques to large box retailers
 Grocery — supermarkets and other grocery stores
 College — colleges, universities and technical colleges
 School — primary and secondary schools
 Hospitals — hospitals, doctors’ offices, and nursing facilities
 Lodging — hotels, motels, resorts and small inns
 Assembly – theatres, places of worship, museums, convention centers, marinas, yacht
clubs, golf clubs, recreation and fitness facilities
 Warehouse — non refrigerated storage
 Miscellaneous — all remaining building types such as fire stations, police stations,
correctional facilities, and parking garages, and cemeteries
In addition to segmentation by building type, we identified the set of end uses and technologies
that are appropriate for Idaho Power.
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EnerNOC Utility Solutions Consulting 2-7
Table 2-3 lists the end uses and technologies used in this study.
The industrial sector is typically segmented by industry type. Because the industrial sector is
complex, the study isolated the largest industries in terms of their energy use for analysis and
combined the remaining industries into a single category. Four remaining major industrial
segments were identified as manufacturing food including refrigerated warehouses, agriculture,
water and wastewater; and electronics. The remaining industries were combined into the Other
category. In addition to segmentation by industry, we identified the set of end uses and
technologies that are appropriate for Idaho Power.
Idaho Power’s special-contract customers were not included in the analysis performed within
LoadMAP. Because these customers are each very large, it is more accurate to characterize their
potential individually, based on known information about these customers, than to estimate their
potential using a model. To do so, we spoke with Idaho Power staff, who in turn spoke with the
individual customers to help develop estimates of their efficiency potential. Consideration for this
analysis included EE measures and actions already implemented, general business plans, and
planned future efficiency measures.
With the segmentation scheme defined, we then performed a high-level market characterization
of electricity sales in the base year to allocate sales to each customer segment. We used various
data sources to identify the annual sales in each customer segment, as well as the number of
customers for residential segments, and the square footage or employee count for the
commercial and industrial segments. This information provided control totals (energy use and
customers counts/square footage/employee totals) for calibrating the LoadMAP model to known
data for the base-year.

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Table 2-3 Commercial End Uses and Technologies
End Use Technology
Cooling Air-Cooled Chiller
Cooling Water-Cooled Chiller
Cooling Roof Top AC
Cooling Air Source Heat Pump
Cooling Geothermal Heat Pump
Cooling Evaporative Air Conditioning
Cooling Other Cooling
Heating Air Source Heat Pump
Heating Geothermal Heat Pump
Heating Electric Room Heat
Heating Electric Furnace
Ventilation Ventilation
Water Heating Water Heating
Interior Lighting Screw-in
Interior Lighting High-Bay Fixtures
Interior Lighting Linear Fluorescent
Exterior Lighting Screw-in
Exterior Lighting HID
Exterior Lighting Linear Fluorescent
Refrigeration Walk-in Refrigerator
Refrigeration Reach-in Refrigerator
Refrigeration Glass Door Display
Refrigeration Open Display Case
Refrigeration Icemaker
Refrigeration Vending Machine
Food Preparation Oven
Food Preparation Fryer
Food Preparation Dishwasher
Food Preparation Hot Food Container
Office Equipment Desktop Computer
Office Equipment Laptop
Office Equipment Server
Office Equipment Monitor
Office Equipment Printer/Copier/Fax
Office Equipment POS Terminal
Miscellaneous Non-HVAC Motors
Miscellaneous Pool Pump
Miscellaneous Pool Heater
Miscellaneous Miscellaneous
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EnerNOC Utility Solutions Consulting 2-9
Market Profiles
The next step was to develop market profiles for each sector, customer segment, end use, and
technology. A market profile includes the following elements:
Market size is a representation of the number of customers in the segment. For the residential
sector, it is number of customers. In the commercial sector, it is floor space measured in square
feet. For the industrial sector, it is number of employees. Floor space and employees are used
for the commercial and industrial sectors respectively because these metrics correlate with
increased energy use.
Saturations define the fraction of buildings with the electric technologies. (e.g., homes with
electric space heating, commercial floor space with space cooling).
UEC (unit energy consumption) or EUI (energy-use index) describes the amount of
electricity consumed in 2011 by a specific technology in buildings that have the technology. We
use UECs expressed in kWh/customer for the residential sector, and EUIs expressed in
kWh/square foot or kWh/employee for the commercial and industrial sectors respectively.
Intensity for the residential sector represents the average use for the technology across all
homes in 2011. It is computed as the product of the saturation and the UEC and is defined as
kWh/customer. For the commercial and industrial sectors, intensity, computed as the product of
the saturation and the EUI, represents the average use for the technology across all floor space
in 2011.
Usage is the annual electricity use by a technology/end use in the segment. It is the product of
the market size and intensity and is quantified in MWh.
The market assessment results and the market profiles are presented in Chapter 3.
Baseline Projection
The next step was to develop the baseline projection of annual electricity use and peak demand
for 2011 through 2032 by customer segment and end use without new utility programs or
naturally occurring efficiency. The end-use projection does include the relatively certain impacts
of codes and standards that will unfold over the study timeframe. All such mandates that were
defined as of January 2011 are included in the baseline. The baseline projection is the
foundation for the analysis of savings from future EE efforts as well as the metric against which
potential savings are measured.
Inputs to the baseline projection include:
 Current economic growth projections (i.e., customer growth, income growth), provided by
Idaho Power
 Electricity price projections, provided by Idaho Power
 Trends in fuel shares and equipment saturations, provided by Idaho Power, and where not
available, developed by the project team
 Existing and approved changes to building codes and equipment standards
 Idaho Power’s internally developed sector-level projections for electricity sales
We present the results of the baseline projection development in Chapter 4.
Energy Efficiency Measure Analysis
This section describes the framework used to assess the savings, costs, and other attributes of
energy efficiency measures. These characteristics form the basis for measure-level cost-
effectiveness analyses as well as for determining measure-level savings. For all measures,
EnerNOC assembled information to reflect equipment performance, incremental costs, and
equipment lifetimes. We used this information, along with Idaho Power’s preliminary avoided
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costs based on 2013 IRP planning assumptions, in the economic screen to determine
economically feasible measures. Figure 2-3 outlines the framework for measure analysis.
Figure 2-3 Approach for Measure Assessment

The framework for assessing savings, costs, and other attributes of energy efficiency measures
involves identifying the list of energy efficiency measures to include in the analysis, determining
their applicability to each market sector and segment, fully characterizing each measure, and
performing cost-effectiveness screening. Potential measures include the replacement of a unit
that has failed or is at the end of its useful life with an efficient unit, retrofit/early replacement of
equipment, improvements to the building envelope, the application of controls to optimize
energy use, and other actions resulting in improved energy efficiency.
We compiled a robust list of energy efficiency measures for each customer sector, drawing upon
Idaho Power’s measure database, and the Regional Technical Forum (RTF) deemed measures
databases, as well as a variety of secondary sources. This universal list of energy efficiency
measures covers all major types of end-use equipment, as well as devices and actions to reduce
energy consumption. If considered today, some of these measures would not pass the economic
screens initially, but may pass in future years as a result of lower projected equipment costs or
higher avoided costs.
The selected measures can be categorized into types, equipment measures and non-equipment
measures, according to the LoadMAP taxonomy:
 Equipment measures, or efficient energy-consuming equipment, save energy by providing
the same service with a lower energy requirement. An example is the replacement of a
standard efficiency refrigerator with an ENERGY STAR model. For equipment measures, many
efficiency levels are available for a specific technology that range from the baseline unit
(often determined by code or standard) up to the most efficient product commercially
available. For instance, in the case of central air conditioners, this list begins with the federal
standard SEER 13 unit and spans a broad spectrum of efficiency, with the highest efficiency
Economic
screen
Measure characterization
Measure
descriptions
Energy
savings Costs
Lifetime Saturation and
applicability
EnerNOC
universal
measure list
Building
simulations
EnerNOC measure data library
Idaho Power
measure data library
Regional Technical Forum
Avoided costs, discount rate, delivery losses
Idaho Power review / feedback
Inputs Process
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level represented by a ductless mini-split system with variable refrigerant flow (at SEER
levels of 18 or greater).
 Non-equipment measures save energy by reducing the need for delivered energy but do
not involve replacement or purchase of major end-use equipment (such as a refrigerator or
air conditioner). An example would be a programmable thermostat that is pre-set to run the
air conditioner only when people are home. Non-equipment measures fall into one of the
following categories:
o Building shell (windows, insulation, roofing material)
o Equipment controls (thermostat, occupancy sensors)
o Equipment maintenance (cleaning filters, changing setpoints)
o Whole-building design (natural ventilation, passive solar lighting)
o Lighting retrofits (included as a non-equipment measure because retrofits are performed
prior to the equipment’s normal end of life)
o Displacement measures (ceiling fan to reduce use of central air conditioners)
o Commissioning and retrocommissioning
Non-equipment measures can apply to more than one end use. For example, insulation levels will
affect the energy use of cooling and space heating.
EnerNOC developed a preliminary list of energy efficiency measures that included measures in
Idaho Power’s existing measure database and the RTF deemed measure workbooks, as well as
other measures that are typically included in utility energy efficiency programs. The final list
included in the study, which reflects feedback and additions from Idaho Power, is presented in
Appendices B, C, D, and E for the residential, commercial, industrial, and irrigation sectors
respectively.
Once we assembled the list of energy efficiency measures, the project team assessed their
energy-saving characteristics. For each measure, we developed estimates of incremental cost,
service life, and other performance factors, drawing upon data from the Idaho Power measure
database, the RTF deemed measure workbooks, EnerNOC’s database of measure characteristics,
and simulation modeling. Following the measure characterization, we performed an economic
screening of each measure, which serves as the basis for developing the economic potential.
Representative Measure Data Inputs
To provide an example of the measure data, Table 2-4 and Table 2-5 present samples of the
detailed data inputs behind equipment and non-equipment measures, respectively, for the case
of residential air-source heat pumps in single-family homes. Table 2-4 displays the various
efficiency levels available as equipment measures, as well as the corresponding useful life,
energy usage, and cost estimates. The columns labeled On Market and Off Market reflect
equipment availability due to codes and standards or the entry of new products to the market.
Table 2-4 Sample Equipment Measures for Air Conditioning – Single Family Existing
Efficiency Level Useful
Life
Equipment
Cost
Energy
Usage(kWh/yr)
On
Market
Off
Market
SEER 13 20 $1,911 2,014 2011 2014
SEER 14 (ENERGY STAR) 20 $2,205 1,847 2011 2032
SEER 15 (CEE Tier 2) 20 $2,646 1,796 2011 2032
SEER 16 (CEE Tier 3) 20 $2,683 1,753 2011 2032
Ductless Mini-split System 20 $4,502 1,716 2011 2032
SEER 21 20 $4,411 1,389 2011 2032
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Table 2-5 lists some of the non-equipment measures affecting an existing single-family home
with a central air conditioner. These measures are also evaluated for cost-effectiveness based on
the lifetime benefits relative to the cost of the measure. The total savings are calculated for each
year of the model and depend on the base year saturation of the measure, the applicability and
feasibility of the measure, and the savings as a percentage of the relevant energy end uses.
Table 2-5 Sample Non-Equipment Measures Affecting Cooling – Single Family Home,
Existing
End Use Measure Saturation
in 20115
Applica-
bility
Lifetime
(years)
Measure
Installed
Cost
Energy
Savings
(%)
Cooling Insulation - Ceiling 36% 90% 20 $594 1.98%
Cooling Insulation - Ducting 0% 10% 25 $350 3.88%
Cooling Insulation - Infiltration
Control 24% 100% 12 $266 1.10%
Cooling Insulation - Radiant Barrier 5% 90% 12 $923 2.08%
Cooling Ducting - Repair and
Sealing 12% 90% 20 $375 11.43%
Cooling Windows - High
Efficiency/ENERGY STAR 61% 100% 25 $7,500 6.79%
Cooling Windows - Install Reflective
Film 5% 45% 10 $895 34.34%
Cooling Doors - Storm and Thermal 38% 100% 12 $320 0.46%
Cooling Roofs - High Reflectivity 5% 10% 15 $1,550 7.68%
Cooling Attic Fan - Installation 4% 50% 18 $116 0.58%
Cooling Attic Fan - Photovoltaic 13% 100% 19 $350 0.58%
Cooling Whole-House Fan -
Installation 8% 25% 18 $200 16.22%
Cooling Ceiling Fan - Installation 21% 100% 10 $160 10.11%
Cooling Thermostat -
Clock/Programmable 52% 85% 12 $114 7.34%
Cooling Home Energy Management
System 2% 40% 20 $600 3.65%
Cooling AC - Early Replacement 0% 80% 15 $2,895 10.00%
Cooling AC - Maint. / Tune-Up 41% 100% 4 $125 9.86%
Cooling Behavioral Feedback Tools 25% 100% 20 $430 1.00%

5 Note that saturation levels reflected for 2011 change over time as more measures are adopted.
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Screening Measures for Cost-Effectiveness
Only measures that are cost-effective are included in economic and achievable potential.
Therefore, for each individual measure, LoadMAP performs an economic screen. This study uses
the total resource cost (TRC) test that compares the lifetime benefits (energy, peak demand, and
non-energy benefit) of each applicable measure with its installed cost, which includes material,
labor, and administration of a delivery mechanism, such as an energy efficiency program. The
lifetime benefits are calculated by multiplying the annual energy and demand savings for each
measure by all appropriate avoided costs for each year, and discounting the dollar savings to the
present value equivalent. The analysis uses each measure’s values for savings, costs, and
lifetimes that were developed as part of the measure characterization process described above.
For economic screening of measures, incentives are not included because they represent a
simple transfer from one party to another, but have no effect on the overall measure cost .
The LoadMAP model performs this screening dynamically, taking into account changing savings
and cost data over time. Thus, some measures pass the economic screen for some — but not all
— of the years in the projection.
It is important to note the following about the economic screen:
 The economic evaluation of every measure in the screen is conducted relative to a baseline
condition. For instance, in order to determine the kilowatt-hour (kWh) savings potential of a
measure, kWh consumption with the measure applied must be compared to the kWh
consumption of a baseline condition.
 The economic screening was conducted only for measures that are applicable to each
building type and vintage; thus if a measure is deemed to be irrelevant to a particular
building type and vintage, it is excluded from the respective economic screen.
 If multiple equipment measures have B/C ratios greater than or equal to 1.0, the most
efficient technology is selected by the economic screen.
 Non-energy benefits are accounted for in the LoadMAP model by means of an additional
factor for measures that have these benefits, such as clothes washers that have water-
related and/or detergent-related benefits.
Additional information on avoided costs appears later in this chapter, and detailed information on
the measure analysis is presented in Appendices B, C, D, and E for the residential, commercial,
industrial, and irrigation sectors respectively.
Energy Efficiency Potential
The approach we used for this study adheres to the approaches and conventions outlined in the
National Action Plan for Energy-Efficiency (NAPEE) Guide for Conducting Potential Studies
(November 2007). The NAPEE Guide represents the most credible and comprehensive industry
practice for specifying energy-efficiency potential. Specifically, three types of potentials were
developed as part of this study:
 Technical potential is a theoretical construct that assumes the highest efficiency measures
that are technically feasible to install are adopted by customers, regardless of cost or
customer preferences. Thus, determining the technical potential is relatively straightforward.
LoadMAP “chooses” the most efficient equipment options for each technology at the time of
equipment replacement. In addition, it installs all relevant non-equipment measures for each
technology to calculate savings. For example, for central air conditioning, as shown in Table
2-4, the most efficient option is a SEER 21. The multiple non-equipment measures shown in
Table 2-5 are then applied to the energy used by the SEER 21 system to further reduce air
conditioning energy use. LoadMAP applies the savings due to the non-equipment measures
one-by-one to avoid double counting of savings. The measures are evaluated in order of
their B/C ratio, with the measure with the highest B/C ratio applied first. Each time a
measure is applied, the baseline energy use for the end use is reduced and the percentage
savings for the next measure is applied to the revised (lower) usage.
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 Economic potential results from the purchase of the most efficient cost-effective option
available for a given equipment or non-equipment measure as determined in the cost-
effectiveness screening process described above. As with technical potential, economic
potential is a phased-in approach. Economic potential is still a hypothetical upper-boundary
of savings potential as it represents only measures that are economic but does not yet
consider customer acceptance and other factors.
 Achievable potential defines the range of savings that is very likely to occur. It accounts
for customers’ awareness of efficiency options, any barriers to customer adoption, limits to
program design, and other factors that influence the rate at which energy efficiency
measures penetrate the market.
The calculation of technical and economic potential is straightforward as described above. To
develop estimates for achievable potential, we specify market adoption rates for each measure.
For Idaho Power, the project team began with the ramp rates specified in the Sixth Plan
conservation workbooks, but modified these to match Idaho Power program history and service
territory specifics. For specific measures, we examined historic program results for the three-year
period of 2009 through 2011, as well as partial-year results for 2012. We then adjusted the 2012
achievable potential for these measures to approximately match the historical results. This
provided a starting for 2012 potential that was aligned to historic results. For future years, we
increased the potential factors to model increasing market acceptance and program
improvements. For measures not currently included in Idaho Power programs, we relied upon the
Sixth Plan ramp rates and recent EnerNOC potential studies to create market adoption rates for
Idaho Power. The market adoption rates for each measure appear in Appendix F.
Results of all the potentials analysis are presented in Chapter 5.
Data Development
This section begins with a description of the data sources used in this study, followed by a
discussion of how these sources were applied.
Data Sources
The data sources are organized into the following categories:
 Idaho Power data
 Energy efficiency measure data
 EnerNOC’s databases and analysis tools
 Other secondary data and reports
Idaho Power Data
In order to enable the project team to appropriately characterize the market, Idaho Power
provided the following information:
 Utility 2011 billing data — customers, usage, revenue
 Number of customers and electricity sales by sector (residential, commercial, industrial,
irrigation)
 Peak demand, summer and winter, by sector
 Results of the Idaho Power 2010 Home Energy Survey, a residential saturation survey
 Non-residential customer 2011 sales data including rate class, annual energy use, SIC code
 Energy forecasts, at the sector level
 Forecasts of population, customer growth, physical home size, income, and business
employment
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 Forecasts of equipment and appliance saturations
 Price forecast
 Avoided costs forecast (peak capacity and energy)
 Discount rate
 Escalation rate
 Line loss factors
 Description of existing conservation and demand side management programs and results
from these programs
 Program administration expenses
 Recent conservation potential studies
 Idaho Power Measure Database, developed by Idaho Power, which includes data of measure
costs and savings.
Energy Efficiency Measure Data
In addition to the Idaho Power Measure Database, several additional sources of data were used
to characterize the energy efficiency measures.
 Northwest Power and Conservation Council Sixth Plan Conservation Supply Curve
Workbooks, 2010. To develop its Power Plan, the Council used workbooks with detailed
information about measures, available at
http://www.nwcouncil.org/energy/powerplan/6/supplycurves/default.htm .
 Regional Technical Forum Deemed Measures. The NWPCC Regional Technical Forum
maintains databases of deemed measure savings data, available at
http://www.nwcouncil.org/energy/rtf/measures/Default.asp .
 Database for Energy Efficient Resources (DEER). The California Energy Commission
and California Public Utilities Commission (CPUC) sponsor this database, which is designed to
provide well-documented estimates of energy and peak demand savings values, measure
costs, and effective useful life (EUL) for the state of California.
 Other cost data sources
o RS Means Facilities Maintenance and Repair Cost Data
o RS Means Mechanical Construction Costs
o RS Means Building Construction Cost Data
o USGBC — LEED New Construction & Major Renovation (2008)
o RS Means Green Buildings Project Planning & Cost Estimating Second Edition (2008)
o Grainger Catalog Volume 398, (2007-2008)
o EIA Technology Forecast Updates – Residential and Commercial Building Technologies –
Reference Case, Navigant Consulting
EnerNOC Databases, Analysis Tools, and Reports
EnerNOC maintains several databases and modeling tools that we use for forecasting and
potential studies.
 Energy Market Profiles Database. Since the late 1990s, EnerNOC staff has maintained a
database of end-use profiles by sector, customer segment and region for electricity and
natural gas. The database contains market size, fuel shares/saturations, UECs/EUIs,
intensities, and total sales.
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 Building Energy Simulation Tool (BEST). BEST is a derivative of the DOE 2.2 building
simulation model, used to estimate base-year UECs and EUIs, as well as measure savings for
the HVAC-related measures.
 Database of Energy Efficiency Measures (DEEM). EnerNOC maintains a database of
energy efficiency measures for residential, commercial, and industrial segments across the
U.S. This is analogous to the DEER database developed for California. EnerNOC updates the
database on a regular basis as it conducts new energy efficiency potential studies.
 EnergyShapeTM Database. This database contains end-use load shapes for residential and
commercial segments for nine regions in the U.S. For the non-HVAC end uses, we used the
EnergyShape data to develop the peak factors that represent the fraction of annual energy
use that occurs during the peak hour. The peak factors were calibrated to available utility
data for the system peak. The final peak factors were applied to annual energy savings to
calculate the peak-demand savings from energy efficiency measures.
 Recent Studies. EnerNOC has conducted numerous studies of energy efficiency potential in
the last five years. We checked our input assumptions and analysis results against the results
from these other studies that include Avista Utilities, Seattle City Light, Inland Power and
Light, Cowlitz PUD, AmerenUE, Los Angeles Department of Water and Power, Consolidated
Edison of New York, State of New Jersey, State of New Mexico, and Tennessee Valley
Authority. In addition, we used the information about impacts of building codes and
appliance standards from a recent report for the Institute for Energy Efficiency.
Other Secondary Data and Reports
Finally, a variety of secondary data sources and reports were used for this study. The main
sources are identified below.
 U.S. Census Data:
o The American Community Survey (ACS) is an ongoing survey that provides data every
year on household characteristics. http://www.census.gov/acs/www/
o Census Bureau’s Economic Census, which is conducted every five years, collects details
on business characteristics. We used the 2007 version.
http://www.census.gov/econ/census07/
 Northwest Energy Efficiency Alliance, Single-Family Residential Existing
Construction Stock Assessment, Market Research Report, E07-179 (10/2007),
http://neea.org/research/reportdetail.aspx?ID=194
 Northwest Energy Efficiency Alliance, Assessment of Multifamily Building Stock in
the Pacific Northwest, Market Research Report, 05-146, August, 2005.
http://neea.org/research/reports/146.pdf
 Northwest Energy Efficiency Alliance, Long-Term Northwest Residential Lighting
Tracking and Monitoring Study, Market Research Report, 11-228, August, 2011.
http://neea.org/research/reports/E11-231_Combinedv2.pdf
 Northwest Energy Efficiency Alliance, Multifamily Residential New Construction
Characteristics and Practices Study, Market Research Report, 07-173, June, 2007.
http://neea.org/research/reports/07%20173.pdf
 Northwest Energy Efficiency Alliance, 2009 Northwest Commercial Building Stock
Assessment (10-211), http://neea.org/research/reportdetail.aspx?ID=546.
 California Statewide Surveys. The Residential Appliance Saturation Survey (RASS) and
the Commercial End Use Survey (CEUS) are comprehensive market research studies
conducted by the California Energy Commission. These databases provide a wealth of
information on appliance use in homes and businesses. RASS is based on information from
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almost 25,000 homes and CEUS is based on information from a stratified random sample of
almost 3,000 businesses in California.
 Annual Energy Outlook. The Annual Energy Outlook (AEO), conducted each year by the
U.S. Energy Information Administration (EIA), presents yearly projections and analysis of
energy topics. For this study, we used data from the 2011 AEO.
 Residential Energy Consumption Survey (RECS). The most recent version of this EIA-
administered survey is the 2009 version.
http://www.eia.gov/consumption/residential/about.cfm
 Electric Power Research Institute – Assessment of Achievable Potential from
Energy Efficiency and Demand Response Programs in the U.S., also known as the
EPRI National Potential Study (2010). In 2010, EnerNOC conducted an assessment of the
national potential for energy efficiency, with estimates derived for the four DOE regions
(including the Rocky Mountain region that includes Idaho Power).
 EPRI End-Use Forecasting Models (REEPS and COMMEND). These models provide the
elasticities we apply to electricity prices, household income, home size and heating and
cooling.
Data Application
We now discuss how the data sources described above were used for each step of the study.
Data Application for Market Characterization
To construct the high-level market characterization of electricity use and customers/floor space
for the residential, commercial, and industrial sectors, we applied 2011 weather-normalized sales
data provided by Idaho Power, Idaho Power’s 2010 Home Energy Survey, the Census ACS, the
NWPCC Sixth Plan, the NEEA CBSA, and the Annual Energy Outlook. The market characterization
for each segment used the following data:
 For the residential sector, Idaho Power estimated the numbers of customers and the average
energy use per customer for each of the six segments, based on its Home Energy Survey,
matched to billing data for surveyed customers. EnerNOC compared the resulting
segmentation with data from the American Community Survey (ACS) regarding housing types
and income and found that the Idaho Power segmentation corresponded well with the ACS
data. (See Chapter 3 for additional details.)
 To segment the commercial and industrial segments, we relied upon Idaho Power data for all
non-residential customers, including annual energy use and 4-digit SIC code. Based on the
SIC codes, EnerNOC made some adjustments between the commercial and industrial sectors
to better group energy use by facility type and predominate end uses. (See Chapter 3 for
additional details.)
 For the irrigation sector, we treated the market as a single segment.
 Special-contract customers were analyzed individually to estimate their energy efficiency
potential.

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Data Application for Market Profiles
To develop the market profiles for each segment, we used the following general approach:
1. Developed control totals for each segment. These include market size, segment -level
normalized annual electricity use, and annual intensity.
2. Used the Idaho Power 2010 Home Energy Survey, the Sixth Plan, and NEEA surveys to
incorporate information on existing appliance and equipment saturations, appliance and
equipment characteristics, building characteristics, customer behavior, operating
characteristics, and energy-efficiency actions already taken.
3. Compared and cross-checked with secondary data sources, EnerNOC’s Energy Market Profiles
Database, and other sources.
4. Ensured calibration to control totals for annual electricity sales in each segment.
5. Worked with Idaho Power staff to vet the data against their knowledge and experience.
The specific data elements for the market profiles, together with the key data sources, are
shown in Table 2-6.
Table 2-6 Data Applied for the Market Profiles
Model Inputs Description Key Sources
Market size Base-year residential dwellings and
C&I floor space
 Utility billing data
 American Community Survey
 NWPCC Sixth Plan
 NEEA Regional Surveys
 Energy Market Profiles
Annual intensity
Residential: Annual energy use
(kWh/customer)
C&I: Annual energy use (kWh/sq ft)
 Utility data
 NWPCC Sixth Plan
 NEEA CBSA
 Energy Market Profiles
 Previous studies
Appliance/equipment
saturations
Fraction of dwellings with an
appliance/technology
Percentage of C&I floor space with
equipment/technology
 Idaho Power RCCS
 NWPCC Sixth Plan
 NEEA CBSA and residential surveys
 Energy Market Profiles
UEC/EUI for each end-
use technology
UEC: Annual electricity use for a
technology in dwellings that have
the technology
EUI: Annual electricity use per
square foot for a technology in floor
space that has the technology
 NWPCC Sixth Plan and RTF data
 HVAC uses: BEST simulations
 Non HVAC uses: Engineering analysis
 Energy Market Profiles
 California RASS and CEUS
 Results from previous studies
Appliance/equipment
vintage distribution Age distribution for each technology
 NWPCC Sixth Plan and RTF data
 NEEA regional survey data
 Utility saturation surveys
 Previous studies
Efficiency options for
each technology
List of available efficiency options
and annual energy use for each
technology
 NWPCC Sixth Plan and RTF data
 DEEM
 DEER
 Annual Energy Outlook
 Previous studies
Peak factors Share of technology energy use that
occurs during the peak hour  EnergyShape database
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Data Application for Baseline Forecast
Table 2-7 summarizes the LoadMAP model inputs required for the baseline projection. These
inputs are required for each segment within each sector, as well as for new construction and
existing dwellings/buildings.
Table 2-7 Data Needs for the Baseline Projection and Potentials Estimation in
LoadMAP
Customer growth
forecasts
Forecasts of residential customer
growth and of C&I employment
growth
 Data provided by Idaho
Power
Forecasts of growth
in home size Trend in new home size (sq. ft.)  Data provided by Idaho
Power
Income growth
forecasts Forecast of per capita income  Data provided by Idaho
Power
Equipment purchase
shares for baseline
forecast
For each equipment/technology,
purchase shares for each efficiency
level; specified separately for
equipment replacement (replace-
on-burnout) and new construction
 Data provided by Idaho
Power on saturation trends
 AEO shipments data
 AEO 2011 forecast
assumptions
Appliance/efficiency
standards analysis
 Idaho Power residential
survey, NEEA CBSA, and
Idaho Power DSM program
historical results
Electricity prices Forecast of average electricity
prices
 Data provided by Idaho
Power
Utilization model
parameters
Price elasticities, elasticities for
other variables (income, weather)
 EPRI’s REEPS and COMMEND
models

We developed initial baseline purchase shares based on the Energy Information Agency’s Annual
Energy Outlook report (2011). These shares were then adjusted to reflect Idaho Power’s past
DSM efforts to incorporate market transformation that has already occurred in the Idaho Power
service territory. For example, for compact fluorescent lighting, we matched the baseline
purchase shares to the existing market saturation to reflect the assumption that for sockets
already converted to CFLs, consumers will continue to purchase CFLs.
Beyond 2011, we assumed a frozen efficiency case in which the purchase shares for efficient
equipment do not change during the study period, unless equipment standards remove a
technology option from the market. Table 2-8 and Table 2-9 show the assumptions regarding
upcoming standards, based on known standards as of January 2011. This approach removes any
effects of naturally occurring conservation or effects of future energy efficiency programs that
may be embedded in the AEO forecasts. Thus the energy efficiency (EE) potential assessment’s
resulting projections of potential compared to this baseline are gross projections because
naturally occurring energy efficiency effects have been removed.

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Table 2-8 Residential Electric Equipment Standards

Today's Efficiency or Standard Assumption 1st Standard (relative to today's standard)
2nd Standard (relative to today's standard)
End Use Technology 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Central AC
Room AC
Evaporative Central AC
Evaporative Room AC
Cooling/Heating Heat Pump
Space Heating Electric Resistance
Water Heater (<=55 gallons)
Water Heater (>55 gallons)
Screw-in/Pin Lamps
Linear Fluorescent
Refrigerator/2nd Refrigerator
Freezer
Dishwasher
Clothes Washer
Clothes Dryer
Range/Oven
Microwave
Personal Computer
Monitor
Laptop Computer
TV
Copier/Printer/Fax
DVD/VCR/Audio
Devices and Gadgets
Pool Pump
Well Pump
Furnace Fan
Conventional
Conventional
5% more efficient (EF 3.17)
Conventional
Conventional
Conventional/Energy Star
Conventional
Conventional
Conventional
Conventional
Conventional
SEER 14
EER 11.0
Conventional
Conventional
SEER 14.0/HSPF 8.0
SEER 13
EER 9.8
SEER 13.0/HSPF 7.7
Conventional (MEF 1.26 for top loader)
Conventional (EF 3.01)
Electric Resistance
EF 0.95
Heat Pump Water Heater
Advanced Incandescent - tier 2
T8
EF 0.90
EF 0.90
Incandescent Advanced Incandescent - tier 1
Miscellaneous
MEF 1.72 for top loader
Cooling
Water Heating
Lighting
Appliances
Electronics
25% more efficient
25% more efficient
14% more efficient (307 kWh/yr)
MEF 2.0 for top loader
Conventional/Energy Star
Conventional/Energy Star
NAECA Standard
NAECA Standard
Conventional (355 kWh/yr)
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Table 2-9 Commercial Electric Equipment Standards

Today's Efficiency or Standard Assumption 1st Standard (relative to today's standard)
2nd Standard (relative to today's standard)
End Use Technology 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Chillers
Roof Top Units
Packaged Terminal AC/HP EER 9.8
Cooling/Heating Heat Pump
Electric Resistance
Electric Furnace
Ventilation Ventilation
Screw-in/Pin Lamps
Linear Fluorescent T12
High Intensity Discharge
Water Heating Water Heater
Walk-in Refrigerator/Freezer
Reach-in Refrigerator
Glass Door Display EPACT 2005
Standard
Open Display Case EPACT 2005
Standard
Vending Machines EPACT 2005
Standard
Icemaker
Desktop Computer
Laptop Computer
Non-HVAC Motors
Commercial Laundry
Miscellaneous
Advanced Incandescent - tier 1Incandescent
T8
EISA 2007 Standard
MEF 1.6MEF 1.26
70% Efficiency62.3% Efficiency
EF 0.97
Office Equipment
Refrigeration
EPACT 2005 Standard
42% more efficient
18% more efficient
33% more efficient
2010 Standard
Conventional/Energy Star
Conventional/Energy Star
Cooling
Space Heating
Lighting
2007 ASHRAE 90.1
EER 11.0/11.2
EER 11.0
EER 11.0/COP 3.3
Advanced Incandescent - tier 2
Electric Resistance
Electric Furnace
Constant Air Volume/Variable Air Volume
Metal Halide
Analysis Approach Data Development
2-22 www.enernoc.com
Data Application for Energy Efficiency Measures
Table 2-10 details the data sources used for developing the lists of measures to include in the
analysis and for measure characterization. Table 2-11 provides the total number of measures
evaluated.
Table 2-10 Data Needs for the Measure Characteristics in LoadMAP
Model Inputs Description Key Sources
Energy Impacts
The annual reduction in consumption
attributable to each specific measure. Savings
were developed as a percentage of the
energy end use that the measure affects.
 Idaho Power measure data
 NWPCC Sixth Plan conservation
workbooks
 RTF deemed measure databases
 BEST
 EPRI National Study
 DEEM
 DEER
 Other secondary sources
Peak Demand
Impacts
Savings during the peak demand periods are
specified for each measure. These impacts
relate to the energy savings and depend on
the extent to which each measure is
coincident with the system peak.
 Idaho Power measure data
 NWPCC Sixth Plan conservation
workbooks
 RTF deemed measure databases
 BEST
 EnergyShape
Costs
Equipment Measures: Includes the full cost of
purchasing and installing the equipment on a
per-unit or per-square-foot basis for the
residential and C&I sectors, respectively
Non-equipment measures: Existing buildings
– full installed cost. New Construction - the
costs may be either the full cost of the
measure, or as appropriate, it may be the
incremental cost of upgrading from a
standard level to a higher efficiency level.
 Idaho Power measure data
 NWPCC Sixth Plan conservation
workbooks
 RTF deemed measure databases
 DEEM
 DEER
 Other secondary sources
Measure
Lifetimes
Estimates derived from the technical data
and secondary data sources that support the
measure demand and energy savings analysis
 Idaho Power measure data
 NWPCC Sixth Plan conservation
workbooks
 RTF deemed measure databases
 DEEM
 DEER
 Other secondary sources
Applicability
and Existing
Saturation
Estimate of the percentage of either
dwellings in the residential sector or square
feet in the C&I sectors where the measures is
applicable and where it is technically feasible
to implement; Estimate of the percentage of
dwellings of square feet in which the
measure is currently implemented
 Idaho Power Residential Energy Use
survey
 Idaho Power DSM program data
 NWPCC Sixth Plan conservation
workbooks
 RTF deemed measure databases
 DEEM
 DEER
 Other secondary sources
On Market and Off
Market Availability
Expressed as years for equipment measures
to reflect when the equipment technology is
available or no longer available in the market
 Appliance, building codes, and
standards analysis
Analysis Approach Data Development
EnerNOC Utility Solutions Consulting 2-23
Table 2-11 Number of Measures Evaluated
Measures Evaluated Residential Commercial Industrial Irrigation
Total
Number of
Measures
Equipment Measures 1,500 3,528 1,038 88 6,154
Non-Equipment Measures 488 1,784 726 70 3,068
Total 1,988 5,312 1,764 158 9,222

Data Application for Cost-effectiveness Screening
To perform the cost-effectiveness screening, the following information was needed:
 Preliminary avoided cost of energy and capacity provided by Idaho Power and based on 2013
IRP planning assumptions, shown in Figure 2-4
 Line losses of 10.9%, provided by Idaho Power
 Discount rate of 7%, provided by Idaho Power
 Program administration costs. Program administration costs can typically vary between 5–
20% of total program costs. For this study, we used values of 16.2% for the residential
sector, 9.3% for the commercial sector, 5.6% for the industrial sector, and 2.3% for
irrigation. These inputs were provided by Idaho Power.
Figure 2-4 Avoided Costs

Data Application for Potentials Estimation
To estimate potentials, two sets of parameters were required.
 Adoption rates for non-equipment measures. Equipment is assumed to be replaced at
the end of its useful life, but for non-equipment measures, a set of factors is required to
model the gradual implementation over time. Rather than installing all non-equipment
measures in the first year of the forecast (instantaneous potential), they are phased in
according to adoption schedules that vary based on equipment cost and measure complexity.
The adoption rates for the Idaho Power study were based on ramp rate curves specified in
0
10
20
30
40
50
60
70
80
90
100
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10
20
30
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50
60
Av
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W
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C
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$
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W
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Avoided Energy Cost, $/MWh
Avoided Capacity Cost ($/kW)
Analysis Approach Data Development
2-24 www.enernoc.com
the NWPCC Sixth Power Plan, but modified to reflect Idaho Power program history. These
adoption rates are used within LoadMAP to generate the technical and economic potentials.
 Market acceptance rates (MARs). These factors are applied to Economic potential to
estimate Achievable potential. These rates were developed by beginning with the Northwest
Power and Conservation Council ramp rates but then adjusting those rates to reflect Idaho
Power DSM program history.
Ramp rates and MARs are discussed in Appendix F.

EnerNOC Utility Solutions Consulting 4-1
CHAPTER 3
MARKET CHARACTERIZATION AND MARKET PROFILES
Idaho Power, established in 1916, is an investor-owned electric utility that serves more than
490,000 customers within a 24,000-square-mile area in southern Idaho and eastern Oregon. To
meet its customers’ electricity demands, Idaho Power maintains a generation portfolio including
17 hydroelectric projects. The company also actively seeks cost-effective ways to encourage wise
use of electricity by providing energy efficiency programs for all customers.
Table 3-1 provides customer counts and weather-normalized electricity use by sector in 2011,
with consumption across the four sectors totaling 12,869,213 MWh. Special-contract customers
are excluded from this total because their potential was estimated individually, rather than
through the LoadMAP analysis. The largest sector is residential, accounting for 39.5% of sales as
shown in Figure 3-1.
Table 3-1 Sector Level Market Characterization, Base Year 2011
Sector /
Rate Class
Number of
Customers
2011 Weather-Normalized
Sales (MWh)
2011 Peak Demand
(MW)
Residential 411,487 5,079,293 1,093
Commercial1 65,226 3,792,283 550
Industrial2 117 2,228,827 330
Irrigation 18,736 1,768,810 735
Total 495,566 12,869,213 2,708
1. Includes street lighting sales of 23,879 MWh, 0.7% of commercial sales.
2. Excludes special-contract customers.
Figure 3-1 Sector-Level Electricity Use, 2011

Residential
39.5%
Commercial
29.5%
Industrial
17.3%
Irrigation
13.7%
Market Characterization and Market Profiles
3-8 www.enernoc.com
To enable characterization of C&I customers, Idaho Power provided EnerNOC with 2011 sales
data including information on use, rate class, and 4-digit SIC code Based on the SIC codes,
EnerNOC made some adjustments between the commercial and industrial sector sales shown
above in Table 3-1 to better group energy use by facility type and end uses. For example, some
customers on commercial rates (EC-SG and EC-LG) — such as dairy and agricultural operations,
refrigerated warehouses, small manufacturing, water treatment, and waste water treatment —
were reclassified as industrial. We did this because energy use in these operations is more likely
dominated by motor and process end uses, rather than the HVAC, lighting, and office equipment
end uses that dominate commercial buildings. Therefore, energy-savings potential for these
facilities can best be estimated by treating them as industrial. Conversely, some customers on
Idaho Power’s industrial rate (EI-IN) such as colleges and hospitals were reclassified as
commercial. The amount of sales that were reclassified represent less than 6% of total C&I
sales. The results of these adjustments appear in Table 3-2.
Table 3-2 Commercial and Industrial Sales Adjustments for LoadMAP Modeling
Sector /
Rate Class
Original 2011 Weather-
Normalized Sales (MWh)
Adjusted 2011 Weather-
Normalized Sales (MWh)
Original % of
C&I Sales
Adjusted %
of C&I Sales
Commercial1 3,792,283 3,436,087 63.0% 57.1%
Industrial2 2,228,827 2,585,023 37.0% 42.9%
Total 6,021,110 6,021,110 100.0% 100.0%
1. Includes street lighting sales of 23,879 MWh, 0.7% of commercial sales.
2. Excludes special-contract customers.
Residential Sector
This section characterizes the residential market at a high level, and then provides a profile of how
customers in each segment use electricity by end use. Total residential electricity use in 2011 was
5,079,293 MWh. Using data from the 2010 Residential Energy Use Survey, Idaho Power divided its
customers into six segments based on housing type and income as shown in Table 3-3 and Figure
3-2. The chosen threshold for the limited income segments was approximately twice the federal
poverty limit, which also correlates with the income threshold used in Idaho Power’s Weatherization
Solutions program. The Single Family segment consumed 52% of total residential sector electricity in
2011 as a result of having the largest number of customers and relatively high intensity. The two
Mobile/Manufactured Home segments, however, have the highest intensity, because these homes are
more likely to be located in rural areas without natural gas services and thus are more likely to use
electricity for space and water heating. The values for customer counts and sales shown in Table 3-3
are referred to throughout the study as the residential sector control totals to which all base year
energy usage is calibrated in the LoadMAP model.

Market Characterization and Market Profiles
EnerNOC Utility Solutions Consulting 3-11
Table 3-3 Residential Market Segmentation by Housing Type, Base Year 2011
Segment Number of
Customers
Weather-Normalized Sales
(1,000 MWh)
Intensity
(kWh/Cust)
Single Family 213,109 2,780 13,045
Multi Family 25,142 220 8,737
Mobile/Mfg Home 17,529 273 15,553
Limited Income SF 98,633 1,222 12,390
Limited Income MF 28,022 190 6,788
Limited Income MH 29,051 395 13,585
Total 411,487 5,079 12,344

Figure 3-2 shows the size of the segments as a percentage of customers and percentage of
residential sector sales.
Figure 3-2 Residential Market Segmentation by Housing Type, 2011

As we describe in the previous chapter, the market profiles provide the foundation upon which
we develop the baseline projection. For each of the six segments defined above, we developed
market profiles that characterize electricity use in terms of sector, customer segment, end use,
and technology for the base year.
For each segment (housing type) within the residential sector, we developed two sets of market
profiles: an Average Home market profile, that represents existing homes in the Idaho Power
service area in 2011 and a similar profile for new construction. Table 3-4 provides an Average
Home market profile for the residential sector as a whole. Appendix A contains the Average
Home and New Home market profiles for the six residential segments.
52%55%
6%4%4%5%
24%24%
7%4%
7%8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% of Customers % of Sales
Limited Income Mobile Home
Limited Income Multi Family
Limited Income Single Family
Mobile/Mfg Home
Multi Family
Single Family
Market Characterization and Market Profiles
3-8 www.enernoc.com
Table 3-4 Residential Sector Composite Market Profile 2011

Figure 3-3 shows the distribution of energy consumption by end use for all homes. Four main
end uses —space conditioning (cooling and heating), appliances, lighting, and water heating —
account for more than 80% of total use. The remaining energy is allocated to electronics
(personal computers, televisions, video game consoles, etc.) and miscellaneous. The
miscellaneous category includes pool pumps and heaters, hot tubs/spas, well pumps, furnace
fans, and various plug loads (hair dryers, power tools, coffee makers, etc.). Within the appliance
category, 47% of energy use is due to refrigerators and freezers.
UEC Intensity Usage
(kWh)(kWh/Cust)(GWh)
Cooling Central AC 64.1%1,938 1,243 511
Cooling Room AC 11.6%296 34 14
Cooling Air-Source Heat Pump 5.2%1,964 102 42
Cooling Geothermal Heat Pump 0.6%1,284 8 3
Cooling Evaporative AC 3.0%1,190 35 15
Space Heating Electric Room Heat 9.7%6,120 594 245
Space Heating Electric Furnace 14.4%8,998 1,299 534
Space Heating Air-Source Heat Pump 5.2%7,269 377 155
Space Heating Geothermal Heat Pump 0.6%4,950 30 12
Water Heating Water Heater <= 55 gal 49.8%2,952 1,469 604
Water Heating Water Heater > 55 gal 1.8%3,901 72 30
Interior Lighting Screw-in 100.0%1,023 1,023 421
Interior Lighting Linear Fluorescent 100.0%131 131 54
Interior Lighting Specialty 100.0%520 520 214
Exterior Lighting Screw-in 100.0%231 231 95
Appliances Clothes Washer 95.4%111 106 44
Appliances Clothes Dryer 94.5%830 785 323
Appliances Dishwasher 82.6%424 351 144
Appliances Refrigerator 100.0%792 792 326
Appliances Freezer 69.6%630 439 180
Appliances Second Refrigerator 33.8%943 319 131
Appliances Stove 83.3%472 393 162
Appliances Microwave 100.0%136 136 56
Electronics Personal Computers 88.0%277 243 100
Electronics Monitor 88.0%55 48 20
Electronics Laptops 89.6%119 106 44
Electronics TVs 214.3%168 359 148
Electronics Printer/Fax/Copier 71.6%42 30 12
Electronics Set-top Boxes/DVR 311.6%112 349 144
Electronics Devices and Gadgets 100.0%52 52 21
Miscellaneous Pool Pump 2.5%1,650 42 17
Miscellaneous Pool Heater 0.6%5,479 35 14
Miscellaneous Hot Tub / Spa 1.7%1,045 18 7
Miscellaneous Well Pump 5.5%549 30 12
Miscellaneous Furnace Fan 73.4%290 212 87
Miscellaneous Miscellaneous 100.0%331 331 136
12,344 5,079
Average Market Profiles
Total
End Use Technology Saturation
Market Characterization and Market Profiles
EnerNOC Utility Solutions Consulting 3-11
Figure 3-3 Residential Electricity Use by End Use and Segment (2011), All Homes

Figure 3-4 and Table 3-8 present the intensity by end-use (kWh/customer) for each housing
type, as well as for all homes on average.
Figure 3-4 Residential Intensity by End Use and Segment, 2011

Cooling
11%
Space Heating
19%
Water
Heating
12%Interior
Lighting
14%Exterior
Lighting
2%
Appliances
27%
Electronics
10%
Misc.
5%
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
Single Family Multi Family Mobile / Mfg LI SF LI MF LI MH/Mfg All Homes
In
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)
Cooling
Heating
Water Heating
Interior Lighting
Exterior Lighting
Appliances
Electronics
Miscellaneous
Market Characterization and Market Profiles
3-8 www.enernoc.com
Table 3-5 Residential Electricity Use by End Use and Segment (kWh/cust/year, 2011)
End Use Single
Family
Multi
Family
Mobile/Mfg
Home
Limited
Income
Single
Family
Limited
Income
Multi
Family
Limited
Income
Mobile/Mfg
Home
All
Customers
Cooling 1,855 635 832 1,238 386 906 1,422
Space Heating 1,851 2,097 6,085 2,013 1,679 5,062 2,300
Water Heating 1,384 1,048 1,944 1,997 972 1,873 1,541
Interior Lighting 1,871 879 1,591 1,778 718 1,523 1,673
Exterior
Lighting 260 113 221 247 91 208 231
Appliances 3,597 2,666 3,309 3,427 2,074 2,687 3,319
Electronics 1,375 932 1,014 1,115 709 858 1,188
Miscellaneous 851 366 557 576 158 468 669
Total 13,045 8,737 15,553 12,390 6,788 13,585 12,344

Figure 3-5 shows the percentage of total energy use consumed by each end use for each
housing type and for the residential sector overall.
Figure 3-5 Percentage of Residential Electricity Use by End Use and Segment (2011)

0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Single Family Multi Family Mobile / Mfg LI SF LI MF LI MH/Mfg All Homes
Pe
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Cooling
Heating
Water Heating
Interior Lighting
Exterior Lighting
Appliances
Electronics
Miscellaneous
Market Characterization and Market Profiles
EnerNOC Utility Solutions Consulting 3-11
Commercial Sector
As discussed above, the portion of C&I sales to include within the study’s commercial sector
analysis was based on facility type, which in turn was determined based on SIC code information
available in IPC’s sales database. The resulting base year sales total for the Commercial sector
was 3,436,087 MWh. For the LoadMAP analysis, we also excluded street lighting sales, reducing
the total to 3,411,788 MWh. The SIC codes associated with customer sales were used to further
divide sales among 12 segments as indicated in Figure 3-6. The three largest segments are small
office, retail, and hospital (including doctors’ office and other medical facilities) with 17.3%,
16.7%, and 10.1% of sales respectively.
Figure 3-6 Commercial Market Segmentation by Building Type, Percentage of Sales,
2011

Next, using data from the Sixth Plan and the NEEA CBSA, the project team estimated floor space and
average intensity values for each building type, calibrating these values so that their product equaled
the annual energy sales values for each segment. Figure 3-6 shows the results, which form the
commercial sector control totals to which base year energy usage is calibrated in the LoadMAP
model. Total commercial floor space is estimated at 216 million square feet, implying an average
intensity of 15.8 kWh per square foot per year. Restaurants and groceries have the highest intensity
due to their cooking and refrigeration usage. Warehouses, schools, assembly, and miscellaneous
have the lowest intensities.

Small Office
17.3%
Large Office
6.0%
Restaurant
7.3%
Retail 16.7%
Grocery
7.2%
College 3.8%
School
7.0%
Hospital 10.1%
Lodging 4.9%
Assembly 5.9%
Warehouse
6.0%
Miscellaneous
7.7%
Market Characterization and Market Profiles
3-8 www.enernoc.com
Table 3-6 Commercial Sector Market Characterization
Building Type Segment Floor Space
(Million sq. ft.)
Intensity
(kWh/sq. ft.)
Annual Use
(MWh)
Small Office 33.250 17.7 589,767
Large Office 9.863 20.8 205,044
Restaurant 5.629 44.3 249,155
Retail 36.935 15.5 571,182
Grocery 5.186 47.4 246,068
College 9.213 14.1 130,284
School 27.921 8.6 239,464
Hospital 11.274 30.6 345,329
Lodging 10.708 15.5 166,045
Assembly 18.519 11.0 202,872
Warehouse 33.965 6.0 204,907
Miscellaneous 13.209 19.8 261,672
Total 215.672 15.8 3,411,788
Note: Excludes street lighting.

Note that the purpose of this study is not to estimate C&I floor space. For this reason, we are
not concerned with absolute square footage, but with the relative size of each segment and its
growth over time. Floor space is used to normalize energy use and develop intensity in terms of
kWh/ sq. ft.
Table 3-7 shows the market profile for the commercial sector as a whole, representing a
composite of the 12 building types. Overall, about 74% of commercial floor space is cooled.
About 29% of commercial floor space is heated using electric equipment, either some form of
resistance heating or heat pumps. Market profiles for each building type are presented in
Appendix A.
Market Characterization and Market Profiles
EnerNOC Utility Solutions Consulting 3-11
Table 3-7 Commercial Sector Composite Market Profile, 2011

EUI Intensity Usage
(kWh)(kWh/Sqft)(GWh)
Cooling Air-Cooled Chiller 9.0%4.07 0.37 79
Cooling Water-Cooled Chiller 9.8%4.06 0.40 86
Cooling Roof top AC 35.4%3.54 1.25 270
Cooling Air Source Heat Pump 13.2%3.36 0.44 96
Cooling Geothermal Heat Pump 0.2%2.06 0.00 1
Cooling Evaporative AC 0.0%9.00 0.00 0
Cooling Other Cooling 6.7%2.91 0.20 42
Heating Air Source Heat Pump 13.2%4.62 0.61 131
Heating Geothermal Heat Pump 0.2%2.95 0.01 1
Heating Electric Room Heat 1.3%6.20 0.08 18
Heating Electric Furnace 14.1%6.14 0.87 187
Ventilation Ventilation 100.0%1.26 1.26 273
Water Heating Water Heating 50.3%1.28 0.65 139
Interior Lighting Screw-in 100.0%1.90 1.90 410
Interior Lighting High-Bay Fixtures 100.0%0.34 0.34 74
Interior Lighting Linear Fluorescent 100.0%2.18 2.18 470
Exterior Lighting Screw-in 100.0%0.21 0.21 46
Exterior Lighting HID 100.0%0.63 0.63 136
Exterior Lighting Linear Fluorescent 100.0%0.03 0.03 7
Refrigeration Walk-in Refrigerator 46.6%0.93 0.43 93
Refrigeration Reach-in Refrigerator 46.6%0.10 0.05 11
Refrigeration Glass Door Display 46.6%1.01 0.47 101
Refrigeration Open Display Case 46.6%0.45 0.21 46
Refrigeration Icemaker 46.6%0.14 0.06 14
Refrigeration Vending Machine 46.6%0.14 0.06 14
Food Preparation Oven 31.0%0.51 0.16 34
Food Preparation Fryer 31.0%0.74 0.23 49
Food Preparation Dishwasher 31.0%0.84 0.26 56
Food Preparation Hot Food Container 31.0%0.23 0.07 16
Office Equipment Desktop Computer 100.0%0.41 0.41 88
Office Equipment Laptop 100.0%0.06 0.06 13
Office Equipment Server 100.0%0.25 0.25 54
Office Equipment Monitor 100.0%0.08 0.08 16
Office Equipment Printer/Copier/Fax 100.0%0.07 0.07 16
Office Equipment POS Terminal 46.3%0.05 0.02 5
Misc Non-HVAC Motors 49.4%0.42 0.21 44
Misc Pool Pump 2.9%0.03 0.00 0
Misc Pool Heater 0.7%0.05 0.00 0
Misc Misc 100.0%1.29 1.29 277
Total 15.82 3,412
Average Market Profiles
End Use Technology Saturation
Market Characterization and Market Profiles
3-8 www.enernoc.com
Figure 3-7 illustrates the overall energy use by end use in the commercial sector as a whole.
Space conditioning and lighting are the largest end uses, together consuming approximately 66%
of commercial building energy use.
Figure 3-7 Commercial Sector Energy Use by End Use, 2011

Figure 3-8 illustrates how intensity varies by building type. Figure 3-9 shows the percentage of
total energy use consumed by each end use within the individual building type segments.
Figure 3-8 Commercial Building Intensity by Segment, 2011

Cooling
18%
Heating
9%
Ventilation
8%
Water Heating
4%
Interior Lighting
28%
Exterior
Lighting
6%
Refrigeration
8%
Food
Preparation
4%
Office
Equipment
6%Miscellaneous
9%
0.0 10.0 20.0 30.0 40.0 50.0
Small Office
Large Office
Restaurant
Retail
Grocery
College
School
Hospital
Lodging
Assembly
Warehouse
Miscellaneous
Intensity (kWh/sq. ft.)
Cooling
Heating
Ventilation
Water Heating
Interior Lighting
Exterior Lighting
Refrigeration
Food Preparation
Office Equipment
Miscellaneous
Market Characterization and Market Profiles
EnerNOC Utility Solutions Consulting 3-11
Figure 3-9 Percentage of Annual Electricity Use by End Use for Commercial Buildings

Observations include the following:
 Lighting remains a major end use across all building types.
 Refrigeration is a significant end use in grocery stores and restaurants.
 Office equipment has substantial use in small and large offices.
 The Miscellaneous segment has a high percentage of miscellaneous loads, indicating that this
segment includes a relatively high percentage of facilities such as cell phone towers, rail
switching equipment, and the like, that in fact are not actually buildings.
 The Miscellaneous end-use loads are also significant in hospitals due to medical equipment.

0%
10%
20%
30%
40%
50%
60%
70%
80%
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%
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Cooling
Heating
Ventilation
Water Heating
Interior Lighting
Exterior Lighting
Refrigeration
Food Preparation
Office Equipment
Miscellaneous

EnerNOC Utility Solutions Consulting 3-1

Table 3-8 provides additional detail by end use.

Market Characterization and Market Profiles
3-2 www.enernoc.com

Table 3-8 Commercial Electricity Use by End Use (1,000 MWh, 2011)
End Use Small
Office
Large
Office Restaurant Retail Grocery College School Hospital Lodging Assembly Ware-
house Misc. Total
Cooling 144 38 25 110 10 29 49 99 22 37 26 21 609
Heating 80 23 6 53 5 13 18 21 24 15 31 14 302
Ventilation 41 31 14 41 11 14 25 51 13 11 9 11 273
Water Heating 21 7 13 22 6 8 13 13 12 10 5 9 139
Interior Lighting 154 49 36 217 49 44 66 71 59 71 83 55 954
Exterior Lighting 35 6 11 35 6 7 18 6 8 23 18 17 189
Refrigeration 1 2 61 27 143 1 12 7 8 4 9 3 278
Food Prep. 1 3 73 17 10 3 13 22 5 5 0 2 155
Office Equip. 73 35 4 20 2 7 16 10 2 9 8 5 191
Misc 39 12 7 29 5 5 9 45 13 18 17 125 322
Total 590 205 249 571 246 130 239 345 166 203 205 262 3,412

Market Characterization and Market Profiles
EnerNOC Utility Solutions Consulting 3-3
Industrial Sector
The industrial sector accounted for 2,585,023 MWh in electricity sales in 2011. This total reflects
adjustments based on SIC code to move some customers on commercial rates into the industrial
sector and vice versa as described previously. The special-contract customers were excluded
from the LoadMAP modeling so that their potential could be estimated separately.
The industrial customers were segmented into four major industries plus an Other category as
shown in Figure 3-10 and Table 3-9. The Other category represents a wide-range of industry
types, including stone and concrete; lumber and wood products; paper and mill; chemicals;
metals and fabricated metal products; and rubber and plastics. Individually, however, these
industries account for less than 5% of industrial sales and thus were placed in the Other
category. The metric against which we normalized energy use is industrial employment.
Figure 3-10 Industrial Market Segmentation by Industry Type, Percentage of Sales,
2011

Table 3-9 Industrial Market Segmentation and Employment
Segment Number of Employees Electricity Use
(1,000 MWh)
Manufacturing — Food 13,174 1,454
Agriculture 2,769 258
Water and Wastewater 3,149 233
Electronics 12,680 188
Other 28,842 452
Total 60,613 2,585

Manufacturing
-Food
22%
Agriculture
4%
Water and
Wastewater
5%
Electronics
21%
Other
48%
Market Characterization and Market Profiles
3-4 www.enernoc.com
As with the residential and commercial sectors, the industrial market profiles characterize
electricity use in terms of end use and technology for the base year 2011. Table 3-10 shows the
composite market profiles for the industrial sector. Market profiles for the individual segments
appear in Appendix A.
Table 3-10 Industrial Sector Composite Market Profile, 2011

Figure 3-11 illustrates the overall use by end use in the industrial sector. Motors and process
loads are the largest end uses, consuming 44% and 30% of the total industrial energy use
respectively. Note that the motor end use includes a wide range of industrial equipment: pumps,
fans, blower, air compressors, and material handling and processing equipment. The process end
use includes process heating, process cooling and refrigeration, and electro-chemical processes.
EUI Intensity Usage
(kWh)(kWh/Employee)(GWh)
Cooling Air-Cooled Chiller 2.5%5,546 139 8.4
Cooling Water-Cooled Chiller 2.5%5,307 133 8.0
Cooling Roof top AC 6.7%6,137 411 24.9
Cooling Air Source Heat Pump 7.5%5,548 419 25.4
Cooling Other Cooling 2.5%4,842 123 7.4
Heating Air Source Heat Pump 7.5%17,582 1,327 80.4
Heating Electric Room Heat 0.9%21,644 194 11.8
Heating Electric Furnace 8.1%22,727 1,835 111.2
Ventilation Ventilation 100%695 695 42.1
Interior Lighting Screw-in 100%801 801 48.5
Interior Lighting High-Bay Fixtures 100%170 170 10.3
Interior Lighting Linear Fluorescent 100%2,332 2,332 141.4
Exterior Lighting Screw-in 100%1 1 0.1
Exterior Lighting HID 100%625 625 37.9
Exterior Lighting Linear Fluorescent 100%0.2 0.2 0.0
Motors Pumps 100%5,956 5,956 361.0
Motors Fans & Blowers 100%3,787 3,787 229.6
Motors Compressed Air 100%1,997 1,997 121.0
Motors Matl Handling 100%2,592 2,592 157.1
Motors Matl Processing 100%3,805 3,805 230.6
Motors Other Motors 100%600 600 36.3
Process Process Heating 100%3,028 3,028 183.6
Process Process Cooling and Refrigeration 100%8,651 8,651 524.4
Process Electro-Chemical Processes 100%199 199 12.1
Process Other Process 100%760 760 46.1
Misc Misc 100%2,068 2,068 125.4
42,648 2,585.0
Average Market Profiles
End Use Technology Saturation
Total
Market Characterization and Market Profiles
EnerNOC Utility Solutions Consulting 3-5
Figure 3-11 Industrial Sector Energy Use by End Use

Figure 3-12 presents the base year consumption by end-use and industry type. Figure 3-13
shows the percentage of total energy use consumed by each end use for the industry types.
Motor loads dominate all segments, though process heating and cooling are more prevalent in
the manufacturing — food segment.
Figure 3-12 Industrial Energy Use by Segment and End Use, 2011

0
200
400
600
800
1,000
1,200
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Manufacturing -
Food
Agriculture Water and
Wastewater
Electronics Other
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Ventilation
Interior Lighting
Exterior Lighting
Motors
Process
Miscellaneous
Market Characterization and Market Profiles
3-6 www.enernoc.com
Figure 3-13 Percentage of Annual Electricity Use by End Use for Industry Segments

Table 3-11 provides additional detail by end use.
Table 3-11 Industrial Electricity Use by End Use and Segment (1,000 MWh, 2011)
End Use Manufacturing
- Food Agriculture Water and
Wastewater Electronics Other Total
Cooling 27 6 2 12 26 74
Heating 75 16 7 33 72 203
Ventilation 16 3 1 7 15 42
Interior Lighting 84 28 8 18 62 200
Exterior Lighting 16 5 2 3 12 38
Motors 635 114 197 39 151 1,136
Process 532 80 10 60 84 766
Misc. 69 5 6 16 29 125
Total 1,454 258 233 188 452 2,585

Irrigation Sector
The irrigation sector accounted for 1,768,810 MWh in electricity sales in 2011. Because this
sector’s use is almost completely due to pump motors, the analysis was simpler than for the
other three sectors. We characterized the sector as a single segment. We then used data from
Idaho Power that classifies its 18,736 irrigation service points by 22 motor size categories as a
way to characterize energy use. For each motor size, we assumed an average starting energy
use, which corresponds to the EUI in other market profiles, and calibrated the values to match
the sector’s overall energy use. Table 3-12 shows the resulting market profile, with the intensity
in units of kWh per service point (SP).
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Manufacturing -
Food
Agriculture Water and
Wastewater
Electronics Other
%
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Cooling
Heating
Ventilation
Interior Lighting
Exterior Lighting
Motors
Process
Miscellaneous
Market Characterization and Market Profiles
EnerNOC Utility Solutions Consulting 3-7
Table 3-12 Irrigation Sector Market Profile, 2011

EUI Intensity Usage
(kWh) (kWh/meter) (GWh)
Motors 5 HP 100.0% 645 645 12 0.7%
Motors 10 HP 100.0% 1,914 1,914 36 2.0%
Motors 15 HP 100.0% 1,385 1,385 26 1.5%
Motors 20 HP 100.0% 1,732 1,732 32 1.8%
Motors 25 HP 100.0% 2,031 2,031 38 2.2%
Motors 30 HP 100.0% 2,161 2,161 40 2.3%
Motors 40 HP 100.0% 3,727 3,727 70 3.9%
Motors 50 HP 100.0% 3,771 3,771 71 4.0%
Motors 60 HP 100.0% 2,905 2,905 54 3.1%
Motors 75 HP 100.0% 4,489 4,489 84 4.8%
Motors 100 HP 100.0% 6,571 6,571 123 7.0%
Motors 125 HP 100.0% 4,926 4,926 92 5.2%
Motors 150 HP 100.0% 5,781 5,781 108 6.1%
Motors 200 HP 100.0% 9,690 9,690 182 10.3%
Motors 250 HP 100.0% 6,006 6,006 113 6.4%
Motors 300 HP 100.0% 6,659 6,659 125 7.1%
Motors 350 HP 100.0% 5,507 5,507 103 5.8%
Motors 400 HP 100.0% 5,534 5,534 104 5.9%
Motors 450 HP 100.0% 3,613 3,613 68 3.8%
Motors 500 HP 100.0% 3,510 3,510 66 3.7%
Motors 600 HP 100.0% 3,799 3,799 71 4.0%
Motors > 600 HP 100.0% 8,051 8,051 151 8.5%
94,407 1,769 100% Total
% of
Total
Average Market Profiles
End Use Technology Saturation

EnerNOC Utility Solutions Consulting 4-1
CHAPTER 4
BASELINE PROJECTION
Prior to developing estimates of energy efficiency potential, a baseline end-use projection was
developed to quantify what consumption is likely to be in the future in absence of new utility
programs. The baseline projection serves as the metric against which energy-efficiency potentials
are measured.
Residential Sector
The baseline projection incorporates assumptions about economic growth, electricity prices, and
appliance/equipment standards and building codes already mandated. Table 4-1and Figure 4-1
present the baseline projection at the end-use level for the residential sector as a whole. Overall,
residential use increases from 5,079,293 MWh in 2011 to 6,408,332 MWh in 2032, a 27%
increase, or an average annual growth rate of 1.1%. Figure 4-2 presents the forecast of use per
customer. Most noticeable is that lighting use decreases significantly throughout the time period
as the lighting efficiency standards from EISA come into effect. Appliance use also decreases
over the projection period due to appliance standards. However, growth in miscellaneous end
uses and electronics keeps energy use per customer relatively flat over the projection period.
Table 4-1 Residential Baseline Projection by End Use (1,000 MWh)
End Use 2011 2012 2013 2015 2017 2022 2027 2032 %
Change
Avg.
Ann.
Growth
Rate
Cooling 585 591 599 622 657 740 826 921 57% 2.2%
Space Heating 947 958 972 1,006 1,054 1,153 1,237 1,313 39% 1.6%
Water Heating 634 632 632 638 657 694 728 761 20% 0.9%
Interior Lighting 689 695 690 647 624 611 618 668 -3% -0.1%
Exterior Lighting 95 90 85 70 62 49 42 45 -53% -3.6%
Appliances 1,366 1,323 1,291 1,245 1,216 1,159 1,147 1,175 -14% -0.7%
Electronics 489 503 515 544 586 694 807 927 90% 3.0%
Miscellaneous 275 283 292 388 493 617 653 653 137% 4.1%
Total 5,079 5,075 5,076 5,159 5,348 5,718 6,058 6,462 27% 1.1%

Baseline Projection
4-2 www.enernoc.com
Figure 4-1 Residential Baseline Projection by End Use

Figure 4-2 Residential Baseline Projection Use per Customer by End Use

0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
2011 2012 2013 2015 2017 2022 2027 2032
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Cooling
Space Heating
Water Heating
Interior Lighting
Exterior Lighting
Appliances
Electronics
Miscellaneous
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
2011 2012 2013 2015 2017 2022 2027 2032
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Space Heating
Water Heating
Interior Lighting
Exterior Lighting
Appliances
Electronics
Miscellaneous
Baseline Projection
EnerNOC Utility Solutions Consulting 4-3
Table 4-3 shows the end-use projection per customer. Table 4-3 provides additional detail at the
technology level.
Table 4-2 Residential Baseline Projection of Use per Customer by End Use (kWh)
End Use 2011 2012 2013 2015 2017 2022 2027 2032 %
Change
Avg.
Ann.
Growth
Rate
Cooling 1,422 1,421 1,426 1,434 1,451 1,508 1,578 1,662 17% 0.7%
Space Heating 2,300 2,305 2,312 2,317 2,327 2,351 2,363 2,371 3% 0.1%
Water Heating 1,541 1,520 1,503 1,470 1,450 1,415 1,390 1,373 -11% -0.5%
Interior Lighting 1,673 1,671 1,642 1,490 1,377 1,246 1,181 1,207 -28% -1.6%
Exterior Lighting 231 216 201 161 137 100 81 81 -65% -5.0%
Appliances 3,319 3,183 3,071 2,869 2,684 2,363 2,190 2,121 -36% -2.1%
Electronics 1,188 1,209 1,224 1,254 1,293 1,416 1,541 1,672 41% 1.6%
Miscellaneous 669 681 695 893 1,087 1,258 1,247 1,178 76% 2.7%
Total 12,344 12,205 12,074 11,888 11,807 11,659 11,572 11,666 -5% -0.3%

Table 4-3 provides additional detail at the technology level.
Baseline Projection
4-4 www.enernoc.com
Table 4-3 Residential Baseline Forecast by End Use and Technology (MWh)

Specific observations include:
 The primary reason for the modest initial growth in the baseline projection is federal lighting
standards, which phase general service incandescent lamps out of the market over a three-
year period, causing a decline in interior screw-in lighting use by 38% and exterior lighting
use by 53% over the 20-year projection period.
 Appliances energy use also decreases, due to mandated efficiency gains, particularly in
refrigeration appliances.
 Cooling increases as population growth and higher saturation of air conditioning in new
construction overrides the effects of appliance standards.
 Space heating use remains relatively flat as increases due to population growth and larger
home size are counterbalanced by decreasing electric heating saturation and efficiency gains
in heat pumps.
 Water heating decreases due to both efficiency gains and decreased saturation of electric
water heating in new construction.
 Growth in electricity use in electronics is substantial and reflects an increase in the sa turation
of electronics and the trend toward higher-powered computers and additional devices such
as electronic gaming. This increase is somewhat tempered by higher efficiency televisions.
 Growth in miscellaneous use is also substantial. This use includes various plug loads not
elsewhere classified (e.g., hair dryers, power tools, coffee makers, etc.). This end use has
End Use Technology 2011 2012 2013 2015 2017 2022 2027 2032 %
Change
Avg. Ann.
Growth
Rate
Central AC 511 516 523 542 572 642 716 796 56%2.1%
Room AC 14 14 15 15 16 18 21 24 69%2.5%
Air-Source Heat Pump 42 42 43 45 47 52 57 62 48%1.9%
Geothermal Heat Pump 3 3 3 4 4 6 7 9 198%5.2%
Evaporative AC 15 15 15 16 18 21 25 29 101%3.3%
Electric Room Heat 245 247 251 259 271 296 316 335 37%1.5%
Electric Furnace 534 541 548 566 590 640 677 708 32%1.3%
Air-Source Heat Pump 155 157 160 167 176 197 217 237 53%2.0%
Geothermal Heat Pump 12 13 13 15 16 21 27 34 174%4.8%
Water Heater > 55 Gal 30 30 30 30 30 31 32 33 11%0.5%
Water Heater <= 55 Gal 604 602 602 608 627 663 696 728 20%0.9%
Screw-in 421 407 389 336 310 265 241 261 -38%-2.3%
Linear Fluorescent 54 54 55 58 61 68 74 80 49%1.9%
Specialty 214 234 246 253 253 278 303 328 53%2.0%
Exterior Lighting Screw-in 95 90 85 70 62 49 42 45 -53%-3.6%
Clothes Washer 44 42 40 38 34 25 19 17 -60%-4.4%
Clothes Dryer 323 312 304 295 289 280 284 297 -8%-0.4%
Dishwasher 144 135 127 114 107 92 94 102 -29%-1.7%
Refrigerator 326 314 305 290 274 244 221 214 -34%-2.0%
Freezer 180 174 168 159 153 141 133 128 -29%-1.6%
Second Refrigerator 131 127 124 119 116 110 106 106 -19%-1.0%
Stove 162 164 166 172 181 199 216 231 43%1.7%
Microwave 56 57 57 59 62 68 74 79 42%1.7%
Personal Computers 100 103 105 108 113 134 155 178 77%2.7%
Monitor 20 20 21 22 23 28 32 37 85%2.9%
Laptops 44 45 46 48 52 61 71 81 86%3.0%
TVs 148 146 144 142 146 166 190 218 47%1.8%
Printer/Fax/Copier 12 13 13 13 14 17 19 22 77%2.7%
Set-top Boxes/DVR 144 154 165 187 211 259 303 349 143%4.2%
Devices and Gadgets 21 22 22 24 26 31 36 42 96%3.2%
Pool Pump 17 18 18 19 20 22 24 26 53%2.0%
Pool Heater 14 14 14 15 15 17 19 20 40%1.6%
Hot Tub / Spa 7 7 8 8 8 9 10 11 53%2.0%
Well Pump 12 13 13 13 14 16 17 18 48%1.9%
Furnace Fan 87 88 90 93 98 109 119 128 47%1.8%
Miscellaneous 136 143 150 240 337 444 464 448 229%5.7%
Total 5,079 5,075 5,076 5,159 5,348 5,718 6,058 6,462 27%1.1%
Electronics
Miscellaneous
Cooling
Space Heating
Water Heating
Interior Lighting
Appliances
Baseline Projection
EnerNOC Utility Solutions Consulting 4-5
grown consistently in the past and we incorporate future growth assumptions that are
consistent with the Annual Energy Outlook.
Commercial Sector
Electricity use in the commercial sector continues to grow during the projection horizon, as new
commercial construction increases overall square footage in the commercial sector. In addition,
existing buildings are renovated to incorporate additional amenities, such as full-scale kitchens
and work-out facilities. Consumption starts at 3,411,788 MWh in 2011 and increases to
4,531,107 MWh in 2032, an overall growth of 33% or 1.4% annually.6
Table 4-4 and Figure 4-3 present the baseline projection at the end-use level for the commercial
sector as a whole. All end uses show growth over the projection period, with the exception of
refrigeration, which is affected by the EPACT 2005 standards for refrigeration. Growth in lighting
is less than in the other end uses, due to the EISA 2007 lighting standards.
Table 4-4 Commercial Electricity Consumption by End Use (1,000 MWh)

6 Street lighting energy use is not included in the results presented in the section.
End Use 2011 2012 2013 2015 2017 2022 2027 2032 %
Change
Avg.
Growth
Rate
Cooling 609 607 608 618 621 632 635 651 7%0.3%
Heating 302 309 316 332 348 379 392 402 33%1.4%
Ventilation 273 274 276 281 285 297 302 308 13%0.6%
Water Heating 139 140 141 146 150 157 161 165 18%0.8%
Interior Lighting 954 935 924 923 896 928 946 972 2%0.1%
Exterior Lighting 189 164 155 153 156 163 167 170 -10%-0.5%
Refrigeration 278 263 252 236 225 210 210 221 -21%-1.1%
Food Preparation 155 157 160 168 175 195 214 236 53%2.0%
Office Equipment 191 192 197 209 223 259 284 307 61%2.3%
Miscellaneous 322 405 476 559 658 833 972 1,099 241%5.8%
Total 3,412 3,448 3,506 3,625 3,738 4,053 4,282 4,531 33%1.4%
Baseline Projection
4-6 www.enernoc.com
Figure 4-3 Commercial Baseline Projection by End Use

Table 4-5 presents the commercial sector projection by technology. Specific observations
include:
 Lighting energy use overall remains nearly flat, driven by the EISA lighting standards. For
linear fluorescent lighting, the effects of the EISA standards have largely already occurred
prior to the start of the projection period, because IPC lighting programs have led to the
replacement of T-12 lighting systems with more efficient T-8s. As a result, interior linear
fluorescent use grows by 16%. On the other hand, the baseline projection indicates that
EISA’s effects during 2012-2015 will be most evident for screw in lighting, causing energy
use for this technology to decrease for both interior and exterior lighting.
 Growth in the HVAC and water heating end uses is commensurate with projected growth in
floor space and employment, the two principal drivers of commercial sector consumption.
Ventilation growth is moderated by a trend toward VAV systems in new construction, while
improved efficiency standards also temper AC growth.
 Refrigeration drops substantially as new standards take effect that cover most types of
commercial refrigeration equipment.
 Food preparation, though remaining a small percentage of total usage, grows at a higher
rate than other end uses. This reflects the addition of kitchen facilities to commercial office
buildings during new construction or renovation, as well as the expansion of food service
offerings in other building types as well.
 Energy use for computers, servers, printers, and other office equipment continues to grow,
due to increased saturation of this category, even as the efficiency of individual units
increases.
 Consumption by miscellaneous equipment, which includes a wide range of plug loads, also
increases. This reflects the assumption that plug loads continue to increase in the
commercial sector as we embrace new uses of electricity.

0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
2011 2012 2013 2015 2017 2022 2027 2032
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Heating
Ventilation
Water Heating
Interior Lighting
Exterior Lighting
Refrigeration
Food Preparation
Office Equipment
Miscellaneous
Baseline Projection
EnerNOC Utility Solutions Consulting 4-7
Table 4-5 Commercial Baseline Electricity Projection by End Use and Technology
(1,000 MWh)

Industrial Sector
Table 4-6 and Figure 4-4 present the baseline projection at the end-use level for the industrial
sector as a whole. Overall, industrial annual energy use increases steadily from 2,585,023 MWh
in 2011 to 3,812,170 MWh in 2032, a 47.5% increase. The study projects that increasing
productivity will lead to increased energy use, beyond that driven by employment growth alone.
End Use Technology 2011 2012 2013 2015 2017 2022 2027 2032 % Change
Avg.
Growth
Rate
Air-Cooled Chiller 79 79 80 82 84 87 87 88 12%0.5%
Water-Cooled Chiller 86 87 89 92 95 100 102 105 22%0.9%
Roof top AC 270 270 271 277 280 289 292 300 11%0.5%
Air Source Heat Pump 131 127 125 122 116 108 106 107 -18%-1.0%
Geothermal Heat Pump 1 1 1 1 1 1 1 1 31%1.3%
Evaporative AC 0 0 0 0 0 0 0 0 0%0.0%
Other Cooling 42 42 43 43 44 47 48 49 17%0.7%
Air Source Heat Pump 96 100 104 112 122 139 147 152 59%2.2%
Geothermal Heat Pump 1 1 1 1 1 2 2 2 78%2.7%
Electric Room Heat 18 18 18 19 20 21 21 22 21%0.9%
Electric Furnace 187 190 193 200 205 217 222 227 21%0.9%
Ventilation Ventilation 273 274 276 281 285 297 302 308 13%0.6%
Water Heating Water Heating 139 140 141 146 150 157 161 165 18%0.8%
Screw-in 410 404 393 382 343 355 364 373 -9%-0.4%
High-Bay Fixtures 74 58 52 49 49 52 53 54 -27%-1.5%
Linear Fluorescent 470 473 479 493 504 522 530 545 16%0.7%
Screw-in 46 40 38 37 38 40 41 42 -8%-0.4%
HID 136 117 110 108 109 115 117 119 -13%-0.6%
Linear Fluorescent 7 8 8 8 8 9 9 10 30%1.2%
Walk-in Refrigerator 93 85 78 69 63 57 59 63 -33%-1.9%
Reach-in Refrigerator 11 10 9 8 8 7 8 8 -22%-1.2%
Glass Door Display 101 96 92 86 82 73 71 74 -27%-1.5%
Open Display Case 46 46 46 47 47 47 46 47 4%0.2%
Icemaker 14 13 13 14 15 16 17 18 34%1.4%
Vending Machine 14 14 13 12 11 9 9 10 -31%-1.7%
Oven 34 35 36 39 42 48 52 58 71%2.6%
Fryer 49 51 52 54 57 61 64 68 37%1.5%
Dishwasher 56 57 58 60 63 73 84 96 72%2.6%
Hot Food Container 16 15 15 14 13 13 14 15 -5%-0.2%
Desktop Computer 88 89 91 95 100 115 123 130 49%1.9%
Laptop 13 13 14 14 15 17 18 20 49%1.9%
Server 54 54 56 61 67 81 93 104 92%3.1%
Monitor 16 16 17 18 19 21 23 24 48%1.9%
Printer/Copier/Fax [phone] 25 58%2.2%
POS Terminal 5 4 4 4 4 5 5 5 9%0.4%
Non-HVAC Motors 44 46 47 51 54 60 64 66 50%1.9%
Pool Pump 0 0 0 0 0 0 0 0 34%1.4%
Pool Heater 0 0 0 0 0 0 0 0 33%1.4%
Miscellaneous 277 359 428 507 603 772 908 1,032 272%6.3%
Total 3,412 3,448 3,506 3,625 3,738 4,053 4,282 4,531 33%1.4%
Food Preparation
Office Equipment
Miscellaneous
Cooling
Heating
Interior Lighting
Exterior Lighting
Refrigeration
Baseline Projection
4-8 www.enernoc.com
Table 4-6 Industrial Electricity Consumption by End Use (MWh)

Figure 4-4 Industrial Baseline Electricity Projection by End Use

End Use 2011 2012 2013 2015 2017 2022 2027 2032 % Change
Avg.
Growth
Rate
Cooling 74 73 72 71 69 66 64 63 -14%-0.7%
Heating 203 207 208 214 216 216 217 218 7%0.3%
Ventilation 42 42 41 41 40 40 40 40 -6%-0.3%
Interior Lighting 200 190 186 187 188 193 197 200 0%0.0%
Exterior Lighting 38 32 29 28 27 27 27 27 -30%-1.7%
Motors 1,136 1,157 1,193 1,269 1,316 1,419 1,568 1,746 54%2.0%
Process 766 781 808 860 895 971 1,092 1,239 62%2.3%
Miscellaneous 125 169 204 225 259 279 288 280 123%3.8%
Total 2,585 2,651 2,741 2,895 3,010 3,210 3,493 3,812 47%1.8%
Baseline Projection
EnerNOC Utility Solutions Consulting 4-9
Irrigation
Table 4-8 presents the baseline projection for the irrigation sector. Because the number of
service points increases, irrigation annual energy use grows from 1,768,810 MWh to 2,038,167
MWh, a 15.2% increase. Use per service point decreases very slightly in the baseline case due to
the replacement of aging motors at the end of their useful lives with more efficient units as
required by standards.
Table 4-7 Irrigation Baseline Projection

2011 2012 2013 2015 2017 2022 2027 2032 % Change
Avg.
Growth
Rate
Number of Service
Points 18,736 18,877 19,018 19,304 19,595 20,341 21,115 21,919 17.0%0.75%
Total Energy Use
(1,000 MWh)1,769 1,789 1,790 1,819 1,825 1,900 1,964 2,038 15.2%0.67%
Use per Service Point
(kWh)94,407 94,781 94,108 94,208 93,140 93,408 93,036 92,986 -1.5%-0.07%
Baseline Projection
4-10 www.enernoc.com
Baseline Projection Summary
Table 4-8 and Figure 4-5 provide a summary of the baseline projection by sector and for Idaho Power as a whole. Street lighting sales, although
not analyzed in LoadMAP, have been assumed to be flat and have been added in to align with the total sales shown in Table 3-1. Overall, the
LoadMAP baseline projection indicates growth of 31% or 1.3% average annual growth.
Table 4-8 Baseline Projection Summary (1,000 MWh)
Sector 2011 2012 2013 2015 2017 2022 2027 2032 % Change
Avg.
Growth
Rate
Residential 5,079 5,075 5,076 5,159 5,348 5,718 6,058 6,462 27% 1.1%
Commercial 3,412 3,448 3,506 3,625 3,738 4,053 4,282 4,531 33% 1.4%
Street Lighting 24 24 24 24 24 24 24 24 0% 0.0%
Industrial 2,585 2,651 2,741 2,895 3,010 3,210 3,493 3,812 47% 1.8%
Irrigation 1,769 1,789 1,790 1,819 1,825 1,900 1,964 2,038 15% 0.7%
Total 12,869 12,987 13,136 13,521 13,945 14,904 15,821 16,868 31% 1.3%
Figure 4-5 Baseline Projection Summary

-
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
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Street Lighting
Irrigation
Industrial
Commercial
Residential

EnerNOC Utility Solutions Consulting 5-1
CHAPTER 5
ENERGY EFFICIENCY POTENTIAL
This chapter presents the results of the potential analysis. First, the overall potential is
presented, followed by results for each sector. Table 5-1 and Figure 5-1 summarize the energy-
efficiency savings for the different levels of potential relative to the baseline forecast.
Key findings related to potentials are summarized below.
 Achievable potential across the residential, commercial, industrial, and irrigation sectors is
594,772 MWh or 67.9 aMW in 2017 and increases to 234.4 aMW by 2032. This represents
4.3% of the baseline projection in 2017 and 12.2% in 2032. By 2032, Achievable potential
offsets 53% of the growth in the baseline projection.
 Economic potential, which reflects the savings when all cost-effective measures are taken,
is 1,734,396 MWh or 198.0 aMW in 2017. This represents 12.4% of the baseline energy
projection. By 2032, economic potential reaches 438.3 aMW, 22.8% of the baseline energy
projection.
 Technical potential, which reflects the adoption of all energy efficiency measures
regardless of cost-effectiveness, is a theoretical upper bound on savings. In 2017, technical
potential savings are 2,849,545 MWh or 325.3 aMW, equivalent to 20.4% of the baseline
energy projection. By 2032, technical potential reaches 720.0 aMW, 37.4% of the baseline
energy projection.
Table 5-1 Summary of Energy Efficiency Potential

2012 2013 2015 2017 2022 2027 2032
Baseline Projection (MWh)12,963,424 13,135,778 13,521,442 13,944,808 14,904,276 15,821,200 16,867,669
Cumulative Savings (MWh)
Achievable Potential 128,230 213,793 410,726 594,772 1,048,684 1,570,770 2,053,161
Economic Potential 732,142 1,002,446 1,476,490 1,734,396 2,695,890 3,373,589 3,839,473
Technical Potential 1,177,752 1,587,035 2,329,976 2,849,545 4,372,407 5,545,301 6,307,377
Cumulative Savings (aMW)
Achievable Potential 14.6 24.4 46.9 67.9 119.7 179.3 234.4
Economic Potential 83.6 114.4 168.5 198.0 307.8 385.1 438.3
Technical Potential 134.4 181.2 266.0 325.3 499.1 633.0 720.0
Savings (% of Baseline)
Achievable Potential 1.0%1.6%3.0%4.3%7.0%9.9%12.2%
Economic Potential 5.6%7.6%10.9%12.4%18.1%21.3%22.8%
Technical Potential 9.1%12.1%17.2%20.4%29.3%35.0%37.4%
Energy Efficiency Potential
5-2 www.enernoc.com
Figure 5-1 Summary of Energy Savings by Potential Case

Figure 5-2 displays the energy use projections for the baseline case and the three potential
levels.
Figure 5-2 Energy Efficiency Potential Projections

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2012 2013 2015 2017 2022 2027 2032
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EnerNOC Utility Solutions Consulting 5-3
Potential results by sector are summarized in Table 5-2 and Figure 5-3.
Table 5-2 Achievable Energy Efficiency Potential by Sector
Sector 2012 2013 2015 2017 2022 2027 2032
Achievable Cumulative Savings (MWh)
Residential 34,123 60,991 132,339 189,469 297,049 473,094 701,104
Commercial 51,289 77,323 135,839 194,418 357,246 512,268 633,771
Industrial 39,772 69,610 122,714 174,526 301,997 415,708 488,465
Irrigation 3,046 5,869 19,833 36,360 92,393 169,700 229,821
Total 128,230 213,793 410,726 594,772 1,048,684 1,570,770 2,053,161
Achievable Cumulative Savings (aMW)
Residential 3.9 7.0 15.1 21.6 33.9 54.0 80.0
Commercial 5.9 8.8 15.5 22.2 40.8 58.5 72.3
Industrial 4.5 7.9 14.0 19.9 34.5 47.5 55.8
Irrigation 0.3 0.7 2.3 4.2 10.5 19.4 26.2
Total 14.6 24.4 46.9 67.9 119.7 179.3 234.4

Figure 5-3 Achievable Energy Efficiency Potential by Sector

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2015 2017 2022 2032
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Residential Sector
Table 5-3 presents estimates for the three types of potential for the residential sector. We note
the following:
 Achievable potential is 189,469 MWh in 2017, or approximately 21.6 aMW. This level of
potential is equivalent to 3.5% of the residential baseline projection for that year. By 2032,
the cumulative achievable projection savings are 701,104 MWh, 10.8% of the baseline
projection.
 Economic potential, which reflects the savings when all cost-effective measures are taken, is
683,391 MWh in 2017, or 12.8% of the baseline energy projection. By 2032, economic
potential reaches 1,312,872 MWh, 20.3% of the baseline energy projection.
 Technical potential in the residential sector is substantial, because measures such as LED
lamps, heat pump water heaters, and solar water heating could cut energy use dramatically.
The 2017 technical potential is 1,465,547 MWh, or 27.4% of the baseline energy projection.
By 2032, technical potential reaches 3,211,915 MWh, 49.7% of the baseline energy
projection. The relatively wide gap between technical and economic potential reflects the fact
that Idaho Power’s long-running residential energy efficiency programs have already
achieved much of the cost-effective energy efficiency. As a result, additional energy
efficiency measures are becoming relatively more costly, and many do not pass the cost-
effectiveness screen based on Idaho Power’s current avoided costs.
Table 5-3 Energy Efficiency Potential for the Residential Sector

Figure 5-4 depicts the potential energy savings estimates graphically. Figure 5-5 displays the
projections under the three types of potential along with the baseline projection.
2012 2013 2015 2017 2022 2027 2032
Baseline Projection (MWh)5,075,486 5,075,763 5,159,026 5,348,213 5,717,700 6,057,762 6,462,345
Cumulative Savings (MWh)
Achievable Potential 34,123 60,991 132,339 189,469 297,049 473,094 701,104
Economic Potential 234,862 373,144 603,800 683,391 939,103 1,148,736 1,312,872
Technical Potential 455,858 702,078 1,150,392 1,465,547 2,199,561 2,781,106 3,211,915
Cumulative Savings (aMW)
Achievable Potential 3.9 7.0 15.1 21.6 33.9 54.0 80.0
Economic Potential 26.8 42.6 68.9 78.0 107.2 131.1 149.9
Technical Potential 52.0 80.1 131.3 167.3 251.1 317.5 366.7
Savings (% of Baseline)
Achievable Potential 0.7%1.2%2.6%3.5%5.2%7.8%10.8%
Economic Potential 4.6%7.4%11.7%12.8%16.4%19.0%20.3%
Technical Potential 9.0%13.8%22.3%27.4%38.5%45.9%49.7%
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-5
Figure 5-4 Residential Energy Savings by Potential Case

Figure 5-5 Residential Energy Efficiency Potential Projections

Residential Potential by End Use
Table 5-4 provides estimates of savings for each end use and type of potential. Focusing first on
technical and economic potential, there are significant savings that are both possible and
economic in numerous end uses:
 Interior lighting offers the highest technical potential savings. The lighting standard begins
its phase-in starting in 2012, which coincides with the widespread availability in the market
place of advanced incandescent lamps that meet the minimum efficacy standard. The
baseline forecast assumes that people will install both advanced incandescent and CFLs in
screw-in lighting applications. For technical potential, LED lamps are the most efficient
option, starting in 2012, which drives the high level of technical potential. However, LED
lamps do not pass the economic screen until 2020, so CFLs are the economic choice until
0%
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2012 2013 2015 2017 2022 2027 2032
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Energy Efficiency Potential
5-6 www.enernoc.com
then. However, because CFLs are also an efficient choice, interior lighting still provides the
highest economic potential.
 Space heating offers the second-highest technical potential, which would be achieved if all
electric furnaces were replaced with SEER 16 heat pumps (either when furnaces fail or by
installing a heat pump in lieu of a furnace during new construction) and all electric resistance
heat was converted to ductless minisplit systems. However, these conversions do not pass
the economic screen.
 Cooling offers the third-highest technical potential, which would be achieved if all air
conditioning systems were converted to the highest efficiency units (e.g., SEER 21 for central
air or ductless mini-splits for air-source heat pumps). Once again, these options are not cost-
effective, but cooling is nonetheless the second highest end-use for economic potential,
mainly due to applicable shell measures and controls.
 Appliances offer the third-largest technical potential in the near term. This reflects both the
replacement of failed white-goods appliances with the highest-efficiency option and removal
of second refrigerators in appliance recycling programs. However, once the new appliance
standards take effect in 2015, relative savings in this category diminish.
 Home electronics has technical potential reflecting the purchase of ENERGY STAR units for
all technologies. As energy use in this end-use category increases over time, so does
potential.
 Water heating also offer substantial technical potential savings opportunities, which
reflects the across the board-installation of heat pump water heaters and solar water
heating.
Table 5-4 Residential Savings by End Use and Potential Type (MWh)

End Use Case 2012 2013 2015 2017 2022 2027 2032
Achievable Potential 2,822 5,897 13,838 25,104 62,137 104,601 140,328
Economic Potential 19,443 26,118 43,701 66,955 128,233 170,148 200,816
Technical Potential 60,554 85,417 142,150 209,845 366,004 474,815 562,348
Achievable Potential 2,078 4,422 11,517 20,370 55,225 105,290 144,242
Economic Potential 17,393 22,671 38,149 55,681 113,740 161,313 196,617
Technical Potential 79,353 119,417 207,774 307,398 534,436 693,274 781,413
Achievable Potential 1,265 2,580 5,902 10,803 27,213 47,643 63,247
Economic Potential 7,053 10,188 19,392 32,590 69,967 103,925 121,768
Technical Potential 35,035 59,513 112,167 172,145 340,945 512,030 590,205
Achievable Potential 22,026 38,011 78,855 99,375 76,036 82,241 160,904
Economic Potential 128,726 213,306 329,340 310,702 302,204 320,611 349,317
Technical Potential 150,602 247,144 385,870 381,389 367,714 377,700 452,416
Achievable Potential 3,556 5,914 10,706 11,530 7,308 8,505 17,622
Economic Potential 16,932 26,766 36,134 29,616 24,980 28,079 30,349
Technical Potential 21,052 32,676 44,948 40,207 28,080 23,441 33,641
Achievable Potential 1,776 2,486 6,051 10,226 27,139 44,893 56,640
Economic Potential 19,804 25,737 45,299 59,101 92,725 104,429 108,397
Technical Potential 67,414 83,354 116,965 155,602 247,653 298,553 320,346
Achievable Potential 600 1,680 5,472 12,043 41,846 79,566 117,423
Economic Potential 25,511 48,358 91,784 128,600 206,455 258,789 303,400
Technical Potential 37,362 66,267 125,158 176,627 276,908 350,299 412,878
Achievable Potential - - - 18 145 354 699
Economic Potential - - - 146 799 1,442 2,208
Technical Potential 4,486 8,289 15,360 22,334 37,823 50,994 58,667
Achievable Potential 34,123 60,991 132,339 189,469 297,049 473,094 701,104
Economic Potential 234,862 373,144 603,800 683,391 939,103 1,148,736 1,312,872
Technical Potential 455,858 702,078 1,150,392 1,465,547 2,199,561 2,781,106 3,211,915
Total
Cooling
Space
Heating
Water
Heating
Interior
Lighting
Exterior
Lighting
Appliances
Electronics
Miscella-
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Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-7
Figure 5-6 present the residential cumulative achievable potential in 2017.
 Lighting, primarily the conversion of both interior and exterior lamps to compact fluorescent
lamps, represents 110,904 MWh or 59% of savings.
 Cooling and heating are the next highest sources of achievable potential, at 13% and 11%
respectively, due mainly to savings from duct repair /sealing and thermostats.
 Water heating, including low-flow fixtures, pipe wrap, and efficient water heaters, provide
6% of achievable potential.
 Electronics, including efficient televisions, computers, and set top boxes, as well as devices
that reduce standby energy use, offer 6% of the potential.
 Appliances, mainly removal of second refrigerators and freezers, provide 5%.
Figure 5-6 Residential Achievable Potential by End Use in 2017 (percentage of total)

As described in Chapter 2, using our LoadMAP model, we develop separate estimates of potential
for equipment and non-equipment measures. Table 5-5 presents results for equipment
achievable potential at the technology level and Table 5-6 presents non-equipment measures.
Measures with zero savings did not pass the cost-effectiveness screening. Initially, the majority
of the savings come from the equipment measures, with lighting leading the way. Appliances and
electronics, mainly televisions, provide savings as well. Over time, non-equipment measures,
which are phased into the market more slowly but produce long-lasting savings (e.g., shell
measures), produce a greater share of savings. In the non-equipment category, ducting
repair/sealing, refrigerator and freezer recycling programs, thermostats, and low-flow fixtures
provide the greatest savings.
Energy Efficiency Potential
5-8 www.enernoc.com
Table 5-5 Residential Achievable Potential for Equipment Measures (1,000 MWh)

End Use Technology 2012 2013 2015 2017 2022 2027 2032
Central AC 0.047 0.148 0.344 0.346 0.357 0.381 0.383
Room AC 0.006 0.018 0.018 0.018 0.015 0.003 0.001
Air-Source Heat Pump 0.011 0.031 0.063 0.064 0.065 0.066 0.061
Geothermal Heat Pump 0.003 0.009 0.031 0.075 0.320 0.655 1.145
Evaporative AC 0.001 0.002 0.021 0.073 0.371 0.749 1.063
Electric Room Heat 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Electric Furnace 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Air-Source Heat Pump 0.040 0.122 0.259 0.261 0.266 0.270 0.253
Geothermal Heat Pump 0.013 0.039 0.136 0.328 1.255 2.416 4.115
Water Heater <= 55 Gal 0.004 0.011 0.042 0.132 0.916 2.587 4.605
Water Heater > 55 Gal 0.002 0.005 0.055 0.188 0.833 2.150 3.498
Screw-in 15.017 24.978 47.023 52.820 33.842 33.981 71.319
Linear Fluorescent 0.000 0.000 0.004 0.013 0.016 0.004 0.000
Specialty 7.009 13.033 31.828 46.542 42.178 48.256 89.585
Exterior Lighting Screw-in 3.556 5.914 10.706 11.530 7.308 8.505 17.622
Clothes Washer 0.018 0.050 0.113 0.173 0.340 0.543 0.620
Clothes Dryer 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Dishwasher 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Refrigerator 0.031 0.088 0.088 0.088 0.089 0.089 0.066
Freezer 0.045 0.127 0.127 0.128 0.129 0.129 0.130
Second Refrigerator 0.018 0.052 0.052 0.052 0.052 0.053 0.044
Stove 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Microwave 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Personal Computers 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Monitor 0.002 0.007 0.030 0.071 0.191 0.263 0.335
Laptops 0.037 0.113 0.451 0.866 2.206 2.989 3.786
TVs 0.165 0.467 1.636 3.733 16.360 29.726 41.302
Printer/Fax/Copier 0.005 0.010 0.024 0.052 0.146 0.206 0.262
Set-top Boxes/DVR 0.391 1.083 3.330 7.321 22.943 46.382 71.738
Devices and Gadgets 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Pool Pump 0.000 0.000 0.000 0.018 0.145 0.354 0.699
Pool Heater 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Hot Tub / Spa 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Well Pump 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Furnace Fan 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Total 26.420 46.305 96.382 124.892 130.343 180.757 312.630
Electronics
Miscellaneous
Cooling
Space Heating
Water Heating
Interior Lighting
Appliances
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-9
Table 5-6 Residential Achievable Savings for Non-equipment Measures (1,000 MWh)

Residential Potential by Market Segment
Single-family homes were slightly more than half of Idaho Power’s residential customers and
represented 55% of the sector’s energy use in 2011. Furthermore, potential as a percentage of
baseline energy use is generally higher in single family homes, which have larger saturations of
equipment beyond the basics of space heating, water heating, and appliances. Thus, single-
2012 2013 2015 2017 2022 2027 2032
- - - - - - -
- - - - - - -
0.049 0.218 1.335 3.407 8.045 12.933 18.408
- - - - 5.517 14.484 25.457
- - - - - - -
0.000 0.001 0.007 0.019 0.045 0.073 0.103
- - - - - 0.654 1.494
2.076 4.207 10.430 17.716 44.099 83.298 109.224
- - - - - - -
0.039 0.079 0.174 0.290 0.689 1.234 1.544
- - - - - - -
- - - - - - -
- - - - - - -
- - - - - - -
0.318 0.649 1.504 2.701 7.666 14.916 20.728
0.805 1.674 3.954 7.798 18.589 25.194 32.680
1.171 2.461 5.571 9.539 23.774 44.237 57.375
- - - - - - -
- - - - - - -
- - - - - - -
- - - - 0.028 0.085 0.122
0.322 0.662 1.506 2.840 6.260 8.246 10.414
- - - - - - -
0.433 0.898 2.214 4.174 8.409 10.397 12.422
0.823 1.653 3.506 6.080 16.496 31.627 41.486
0.003 0.014 0.084 0.230 0.559 0.880 1.235
- - - - - - -
- - - - - - -
Water Heater - Solar System - - - - - - -
Interior Lighting - Occupancy Sensors - - - - - - -
Exterior Lighting - Photosensor Control - - - - - - -
Exterior Lighting - Photovoltaic Installation - - - - - - -
Exterior Lighting - Timeclock Installation - - - - - - -
Refrigerator - Early Replacement - - - - - - -
Refrigerator - Maintenance - - - - - - -
Refrigerator - Remove Second Unit 1.663 2.169 3.982 6.787 18.447 33.809 44.918
Freezer - Remove Second Unit - - 1.689 2.997 8.082 10.269 10.862
Freezer - Early Replacement - - - - - - -
Freezer - Maintenance - - - - - - -
Electronics - Smart Power Strips - - - - - - -
Pool Pump - Timer - - - - - - -
Pool Heater - Solar System - - - - - - -
ENERGY STAR Home Design - - - - - - -
Attic Fan - Solar - - - - - - -
Behavioral Feedback Tools - - - - - - -
Advanced New Construction Design - - - - - - -
Energy Efficient Manufactured Home - - - - - - -
7.702 14.686 35.957 64.577 166.706 292.337 388.474
Measure
Water Heater - Low-Flow Showerheads
Water Heater - Pipe Insulation
Water Heater - Timer
Water Heater - Desuperheater
Attic Fan - Installation
Attic Fan - Photovoltaic - Installation
Whole-House Fan - Installation
Ceiling Fan - Installation
Thermostat - Clock/Programmable
Home Energy Management System
Insulation - Wall Sheathing
Ducting - Repair and Sealing
Windows - High Efficiency/ENERGY STAR
Windows - Install Reflective Film
Doors - Storm and Thermal
Total
Central AC - Early Replacement
Central AC - Maintenance and Tune-Up
Central Heat Pump - Maintenance
Room AC - Removal of Second Unit
Water Heater - Drainwater Heat Recovery
Water Heater - Faucet Aerators
Roofs - High Reflectivity
Insulation - Ceiling
Insulation - Ducting
Insulation - Foundation
Insulation - Infiltration Control
Insulation - Radiant Barrier
Insulation - Wall Cavity
Energy Efficiency Potential
5-10 www.enernoc.com
family homes account for the largest share of potential savings by segment, representing
approximately 58% of achievable potential across the study period as indicated in Table 5-7.
Table 5-8 shows the three potential cases by housing type in 2017.
Table 5-7 Residential Achievable Potential by Market Segment

Table 5-8 Residential Potential Summary by Market Segment, 2017

Table 5-9 shows the savings by end use and market segment in 2017. The segments are similar
in terms of the savings opportunities by end use, but a few notable differences emerge. Single-
family homes are more likely to have swimming pools and spas, and therefore have more
Single Family Multi Family Mobile Home Limited
Income SF
Limited
Income MF
Limited
Income MH
Baseline Forecast (MWh)2,924,242 231,187 291,363 1,280,668 198,307 422,446
Energy Savings (MWh)
Achievable Potential 110,575 5,734 10,256 43,345 4,885 14,674
Economic Potential 405,767 21,765 33,463 156,616 18,128 47,652
Technical Potential 797,849 60,270 83,094 350,870 53,098 120,367
Energy Savings as % of Baseline
Achievable Potential 4%2%4%3%2%3%
Economic Potential 14%9%11%12%9%11%
Technical Potential 27%26%29%27%27%28%
2012 2013 2015 2017 2022 2027 2032
Baseline Forecast (MWh)
Single Family 2,778,180 2,778,139 2,822,026 2,924,242 3,128,860 3,324,492 3,562,633
Multi Family 218,768 218,402 222,202 231,187 248,994 264,823 282,341
Mobile/Mfg Home 273,137 273,872 280,041 291,363 311,733 327,902 345,050
Limited Income SF 1,220,636 1,219,970 1,237,706 1,280,668 1,363,870 1,440,894 1,534,323
Limited Income MF 189,190 188,604 191,234 198,307 211,714 223,152 235,890
Limited Income MH 395,576 396,776 405,816 422,446 452,529 476,500 502,109
Total 5,075,486 5,075,763 5,159,026 5,348,213 5,717,700 6,057,762 6,462,345
Achievable Savings (MWh)
Single Family 19,922 35,531 77,168 110,575 175,999 278,705 409,646
Multi Family 1,038 1,917 4,040 5,734 8,916 14,700 22,014
Mobile/Mfg Home 1,672 3,077 6,756 10,256 18,422 31,017 44,540
Limited Income SF 8,342 14,791 31,138 43,345 61,366 95,960 147,607
Limited Income MF 943 1,676 3,489 4,885 7,289 11,529 18,002
Limited Income MH 2,206 3,998 9,749 14,674 25,058 41,183 59,296
Total 34,123 60,991 132,339 189,469 297,049 473,094 701,104
Achievable - % of Total Savings
Single Family 58%58%58%58%59%59%58%
Multi Family 3%3%3%3%3%3%3%
Mobile/Mfg Home 5%5%5%5%6%7%6%
Limited Income SF 24%24%24%23%21%20%21%
Limited Income MF 3%3%3%3%2%2%3%
Limited Income MH 6%7%7%8%8%9%8%
Total 100%100%100%100%100%100%100%
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-11
potential for savings in pool pumps (captured in the miscellaneous end use). Mobile/Mfg homes
have a relatively larger opportunity in space heating equipment due to the higher saturation of
electric space heating.
Table 5-9 Residential Achievable Potential by End Use and Market Segment, 2017
(MWh)

Commercial Sector Potential
The baseline projection for the commercial sector grows steadily during the projection period as
the region emerges from the economic downturn. As a result, opportunities for energy-efficiency
savings are significant for the commercial sector.
 Achievable potential projects 194,418 MWh (22.2 aMW) of energy savings in 2017, which
corresponds to 5.2% of the baseline projection.
 Economic potential, which reflects the savings when all cost-effective measures are taken,
is 612,619 MWh in 2017, or 16.4% of the baseline energy projection.
 Technical potential, which reflects the adoption of all energy efficiency measures
regardless of cost, is 872,355 MWh or 23.3% of the baseline energy projection...
Table 5-10 and Figure 5-7 present the savings associated with each level of potential. Figure 5-8
shows the commercial sector baseline projection and the three potential level projections.
Table 5-10 Energy Efficiency Potential for the Commercial Sector

Note: Baseline projection includes street lighting.
End Use Single Family Multi Family Mobile Home Limited Income
SF
Limited Income
MF
Limited Income
MH
Cooling 17,801 563 972 3,516 501 1,751
Space Heating 8,793 248 3,463 3,881 20 3,965
Water Heating 4,695 684 585 3,199 707 933
Interior Lighting 57,766 3,075 4,039 25,399 2,713 6,382
Exterior Lighting 6,690 371 468 2,941 331 730
Appliances 251 19 19 113 15 25
Electronics 14,561 774 710 4,296 598 888
Miscellaneous 18 0 0 0 0 0
Total 110,575 5,734 10,256 43,345 4,885 14,674
2012 2013 2015 2017 2022 2027 2032
Baseline Projection (MWh)3,471,595 3,529,438 3,648,761 3,761,465 4,076,572 4,306,054 4,554,986
Cumulative Savings (MWh)
Achievable Potential 51,289 77,323 135,839 194,418 357,246 512,268 633,771
Economic Potential 302,940 390,446 541,384 612,619 1,014,921 1,215,986 1,331,030
Technical Potential 484,824 596,381 781,772 872,355 1,339,940 1,663,446 1,818,324
Cumulative Savings (aMW)
Achievable Potential 5.9 8.8 15.5 22.2 40.8 58.5 72.3
Economic Potential 34.6 44.6 61.8 69.9 115.9 138.8 151.9
Technical Potential 55.3 68.1 89.2 99.6 153.0 189.9 207.6
Savings (% of Baseline)
Achievable Potential 1.5%2.2%3.7%5.2%8.8%11.9%13.9%
Economic Potential 8.7%11.1%14.8%16.3%24.9%28.2%29.2%
Technical Potential 14.0%16.9%21.4%23.2%32.9%38.6%39.9%
Energy Efficiency Potential
5-12 www.enernoc.com
Figure 5-7 Commercial Energy Efficiency Potential Savings

Figure 5-8 Commercial Energy Efficiency Potential Projections

Commercial Potential by End Use, Technology, and Measure Type
Table 5-11 presents the commercial sector savings by end use and potential type. The end uses
with the highest technical and economic potential are:
 Interior lighting, as a result of LED lighting that is now commercially available, has the
highest technical potential at 336,314 MWh in 2017. However, LEDs are not found to be
cost-effective until 2020. Nonetheless, economic potential is high due to CFLs for scre w-in
applications, super T8s for linear fluorescent systems, and T5s for high-bay fixtures.
Therefore, economic potential is highest for lighting as well, at 231,640 MWh in 2021,
roughly two-thirds of technical potential. Control systems also contribute to lighting potential.
 Cooling has the second highest savings for technical potential at 154,859 MWh in 2017.
These savings result from installation of high-efficiency equipment and numerous thermal
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
2012 2013 2015 2017 2022 2027 2032
En
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S
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Achievable Potential
Economic Potential
Technical Potential
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-13
shell measures, HVAC control strategies, and retrocommissioning. Many of these measures
are cost-effective, resulting in economic potential savings of 95,984 MWh in 2025, or 62% of
technical potential savings.
 Ventilation takes third place for technical potential savings at 111,305 MWh in 2017, due
mainly to conversion of constant volume to variable volume systems, but also to control
systems and operating strategies. Economic potential in that year is 84,418 MWh.
 Refrigeration has 2017 technical potential of 62,344 MWh, 61% of which is found to be cost-
effective, for an economic potential of 37,827 MWh.
Water heating, space heating, office equipment and exterior lighting also have savings in terms
of technical and economic potential. The savings potential from food preparation and
miscellaneous uses are relatively small.
Table 5-11 Commercial Potential by End Use and Potential Type (MWh)

End Use Case 2012 2013 2015 2017 2022 2027 2032
Achievable Potential 11,653 15,715 24,004 32,039 54,035 75,568 94,801
Economic Potential 58,528 65,742 81,397 95,984 132,401 164,428 189,511
Technical Potential 89,001 101,910 127,909 154,859 220,040 275,170 306,539
Achievable Potential 3,178 4,192 6,284 8,778 15,769 22,454 29,008
Economic Potential 18,588 20,863 26,190 32,827 49,410 63,653 75,179
Technical Potential 31,241 35,163 43,823 53,316 77,437 96,542 110,912
Achievable Potential 3,279 5,587 15,130 26,974 55,023 70,045 77,126
Economic Potential 21,363 30,329 56,836 84,418 131,179 140,014 145,227
Technical Potential 49,667 59,752 86,753 111,305 157,134 168,520 176,733
Achievable Potential 2,343 3,909 7,781 12,407 24,408 38,721 49,709
Economic Potential 16,193 23,802 37,705 52,360 83,991 109,051 120,176
Technical Potential 20,066 27,733 41,552 55,996 87,698 112,489 123,839
Achievable Potential 21,667 34,038 57,246 77,441 143,006 216,107 276,026
Economic Potential 133,496 179,768 242,492 231,640 449,171 535,708 575,434
Technical Potential 214,652 271,649 346,062 336,314 559,805 706,795 765,139
Achievable Potential 3,359 5,144 8,502 11,953 22,768 32,344 38,105
Economic Potential 17,323 22,841 30,619 35,396 61,103 74,177 77,212
Technical Potential 25,392 32,417 42,046 47,426 84,849 121,630 125,723
Achievable Potential 4,513 5,718 7,762 9,856 15,697 22,272 29,184
Economic Potential 26,704 28,415 32,838 37,827 50,505 63,067 75,627
Technical Potential 39,906 44,056 53,356 62,344 82,719 99,266 115,262
Achievable Potential 232 518 1,774 3,306 7,698 11,643 14,272
Economic Potential 1,864 3,144 6,844 10,530 19,463 23,941 26,991
Technical Potential 5,034 6,543 10,874 15,459 27,397 34,917 40,806
Achievable Potential 1,051 2,470 7,253 11,475 18,398 22,424 24,706
Economic Potential 8,759 15,337 26,049 31,024 36,581 40,479 44,117
Technical Potential 9,416 16,413 27,920 33,121 38,893 42,923 46,707
Achievable Potential 15 32 103 188 444 689 833
Economic Potential 121 204 414 614 1,117 1,469 1,555
Technical Potential 125 212 428 629 1,132 1,481 1,558
Achievable Potential 51,289 77,323 135,839 194,418 357,246 512,268 633,771
Economic Potential 302,940 390,446 541,384 612,619 1,014,921 1,215,986 1,331,030
Technical Potential 484,499 595,848 780,723 870,769 1,337,106 1,659,733 1,813,217
Water
Heating
Interior
Lighting
Exterior
Lighting
Cooling
Heating
Ventilation
Office
Equipment
Refriger-
ation
Miscella-
neous
Food
Prepara-
tion
Total
Energy Efficiency Potential
5-14 www.enernoc.com
Table 5-12 and Table 5-13 present achievable potential savings for equipment measures and
non-equipment measures, respectively.
Table 5-12 Commercial Achievable Savings for Equipment Measures (1,000MWh)

End Use Measure 2012 2013 2014 2015 2017 2022 2027 2032
Air Source Heat Pump 0.01 0.01 0.03 0.05 0.09 0.29 0.46 0.76
Air-Cooled Chiller 0.74 1.43 2.16 2.84 4.00 7.65 11.89 15.37
Evaporative AC - - - - - - - -
Geothermal Heat Pump 0.00 0.00 0.00 0.01 0.02 0.06 0.12 0.17
Other Cooling 0.00 0.01 0.02 0.04 0.08 0.22 0.34 0.42
Roof top AC 0.04 0.10 0.19 0.27 0.56 1.44 2.61 3.12
Water-Cooled Chiller 0.96 1.87 2.84 3.77 5.32 10.21 15.74 20.36
Air Source Heat Pump 0.01 0.02 0.04 0.07 0.13 0.41 0.64 1.01
Electric Furnace - - - - - - - -
Electric Room Heat - - - - - - - -
Geothermal Heat Pump 0.00 0.00 0.00 0.01 0.02 0.06 0.13 0.20
Ventilation Ventilation 1.15 2.90 6.95 11.34 21.03 45.54 56.82 60.39
Water Heating Water Heating 1.04 2.14 3.21 4.89 8.54 18.04 29.13 36.32
High-Bay Fixtures 1.17 1.94 2.58 3.19 4.35 9.17 14.61 19.02
Linear Fluorescent 5.10 9.42 14.02 19.06 28.95 69.36 97.37 108.04
Screw-in 9.77 15.41 20.24 24.35 31.77 46.17 81.16 121.40
HID 1.84 3.14 4.28 5.36 7.44 13.71 18.04 18.37
Linear Fluorescent 0.09 0.16 0.24 0.32 0.50 1.00 1.17 1.23
Screw-in 0.37 0.62 0.87 1.10 1.80 4.63 8.79 13.21
Glass Door Display - - - - - - - -
Icemaker - - 0.00 0.00 0.01 0.07 0.17 0.22
Open Display Case - - - - - - - -
Reach-in Refrigerator 0.01 0.03 0.07 0.11 0.21 0.45 0.71 0.86
Vending Machine 0.04 0.04 0.04 0.04 0.04 0.02 0.01 0.00
Walk-in Refrigerator 0.02 0.05 0.10 0.16 0.39 1.10 2.02 2.61
Dishwasher 0.06 0.14 0.32 0.53 1.00 2.38 3.74 4.71
Fryer 0.03 0.08 0.18 0.29 0.54 1.23 1.77 2.06
Hot Food Container 0.03 0.08 0.19 0.32 0.60 1.40 2.09 2.50
Oven 0.06 0.14 0.33 0.54 1.03 2.45 3.69 4.49
Desktop Computer 0.27 0.80 1.61 2.53 4.49 7.34 8.76 9.44
Laptop 0.08 0.16 0.28 0.42 0.74 1.11 1.32 1.41
Monitor 0.02 0.04 0.06 0.09 0.16 0.25 0.29 0.31
POS Terminal - - - - - - - -
Printer/Copier/Fax 0.04 0.08 0.13 0.20 0.36 0.71 0.88 0.97
Server 0.65 1.40 2.48 4.00 5.72 8.98 11.18 12.57
Non-HVAC Motors 0.01 0.03 0.06 0.10 0.18 0.41 0.62 0.75
Pool Heater - 0.00 0.00 0.00 0.00 0.02 0.03 0.04
Pool Pump 0.00 0.00 0.00 0.00 0.01 0.02 0.04 0.04
Miscellaneous - - - - - - - -
Total 23.61 42.25 63.54 86.01 130.07 255.91 376.30 462.38
Food
Preparation
Office
Equipment
Miscellaneous
Cooling
Heating
Interior
Lighting
Exterior
Lighting
Refrigeration
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-15
Table 5-13 Commercial Achievable Savings for Non-equipment Measures (1,000MWh)

Measure 2012 2013 2014 2015 2017 2022 2027 2032
Advanced New Construction Designs 0.59 1.30 2.31 3.72 6.08 14.15 20.84 28.09
Energy Management System 3.20 4.10 4.75 5.43 6.80 10.77 15.01 19.35
Exterior Lighting - Daylighting Controls 0.85 0.95 1.07 1.22 1.54 2.23 2.69 3.16
HVAC - Occupancy Sensors - - - - - - - -
Insulation - Ceiling 0.07 0.10 0.13 0.16 0.20 0.34 0.47 0.58
Insulation - Ducting 0.23 0.30 0.34 0.39 0.53 0.94 1.25 1.52
Insulation - Wall Cavity 0.05 0.06 0.07 0.08 0.11 0.17 0.23 0.28
Interior Lighting - Daylighting Controls 1.97 2.51 2.90 3.32 4.09 6.53 8.56 10.56
Interior Lighting - Occupancy Sensors - - - - - - - -
Interior Lighting - Task Lighting - - - - - - - -
Non-HVAC Motors - Variable Speed Control - - - - - - - -
Pool Pump - Timer - - - - - - - -
Space Heating - Heat Recovery Ventilator 0.37 0.51 0.71 0.85 1.19 2.31 3.34 4.30
Thermostat - Clock/Programmable 0.76 0.99 1.16 1.34 1.72 2.80 4.00 5.23
Vending Machine - Controller - - - - - - - -
Ventilation - CO2 Controlled 0.27 0.36 0.42 0.47 0.59 0.86 1.16 1.48
Ventilation - Variable Speed Control 1.10 1.33 1.54 1.82 3.27 5.04 7.14 8.91
Windows - High Efficiency 0.03 0.04 0.05 0.05 0.07 0.11 0.14 0.18
Insulation - Radiant Barrier 0.13 0.17 0.20 0.24 0.32 0.53 0.76 0.98
HVAC - Duct Repair and Sealing 1.66 1.99 2.28 2.59 3.44 4.82 5.83 6.66
Doors - High Efficiency - - - - - - - -
Roof - High Reflectivity 0.82 1.04 1.21 1.37 1.71 2.47 3.22 3.96
Air-Cooled Chiller - Cond. Water Temperature Reset 0.10 0.12 0.13 0.15 0.19 0.26 0.29 0.32
Air-Cooled Chiller - Economizer 0.25 0.30 0.35 0.40 0.50 0.74 0.89 1.03
Air-Cooled Chiller - Thermal Energy Storage - - - - - - - -
Air-Cooled Chiller - VSD on Fans 0.35 0.43 0.50 0.57 0.72 1.06 1.28 1.49
Air-Cooled Chiller - Chilled Water Reset 0.31 0.37 0.43 0.48 0.61 0.85 0.98 1.09
Air-Cooled Chiller - Chilled Water Variable-Flow System 0.03 0.03 0.04 0.04 0.06 0.08 0.09 0.11
Air-Cooled Chiller - High Efficiency Cooling Tower Fans - - - - - - - -
Air-Cooled Chiller - Maintenance 0.37 0.43 0.49 0.56 0.71 0.99 1.15 1.27
Air-Cooled Chiller - Chiller Heat Recovery 0.06 0.08 0.10 0.12 0.16 0.30 0.42 0.54
Water-Cooled Chiller - Cond.Water Temperature Reset 0.45 0.54 0.62 0.71 0.88 1.24 1.44 1.61
Water-Cooled Chiller - Economizer 0.20 0.24 0.27 0.31 0.39 0.57 0.68 0.77
Water-Cooled Chiller - Thermal Energy Storage - - - - - - - -
Water-Cooled Chiller - VSD on Fans 1.29 1.55 1.80 2.06 2.62 3.81 4.56 5.28
Water-Cooled Chiller - Chilled Water Reset 0.41 0.49 0.56 0.64 0.80 1.09 1.25 1.38
Water-Cooled Chiller - Chilled Water Variable-Flow System 0.10 0.12 0.14 0.16 0.20 0.28 0.33 0.37
Water-Cooled Chiller - High Efficiency Cooling Tower Fans - - - - - - - -
Water-Cooled Chiller - Maintenance 0.43 0.51 0.58 0.66 0.84 1.14 1.33 1.46
Water-Cooled Chiller - Chiller Heat Recovery 0.06 0.08 0.10 0.12 0.16 0.30 0.42 0.54
RTU - Evaporative Precooler 0.01 0.02 0.02 0.03 0.04 0.07 0.09 0.12
RTU - Maintenance 1.24 1.47 1.68 2.07 2.58 3.68 4.49 5.22
Heat Pump - Maintenance 1.34 1.59 1.81 2.07 2.54 3.64 4.55 5.53
Ventilation - ECM on VAV Boxes - - - - - - - -
Water Heater - Drainwater Heat Recovery 0.05 0.07 0.09 0.10 0.13 0.24 0.35 0.46
Water Heater - Faucet Aerators/Low Flow Nozzles 0.33 0.43 0.54 0.78 1.06 1.09 1.04 1.01
Water Heater - Desuperheater 0.42 0.56 0.74 0.85 1.09 1.86 2.61 3.34
Water Heater - Solar System 0.11 0.17 0.26 0.34 0.54 1.53 3.47 5.99
Water Heater - Pipe Insulation 0.02 0.02 0.03 0.03 0.05 0.05 0.05 0.05
Water Heater - Tank Blanket/Insulation 0.23 0.31 0.39 0.40 0.42 0.44 0.44 0.44
Energy Efficiency Potential
5-16 www.enernoc.com
Table 5-13 Commercial Achievable Savings for Non-equipment Measures (1,000MWh)
(cont.)

As shown in Figure 5-9, the primary sources of commercial sector achievable savings in 2017 are
as follows:
 Interior and exterior lighting, with lamps and fixtures accounting for 40% of commercial
sector achievable potential, and lighting controls and commissioning providing the remaining
6%
 HVAC — with the largest proportion due to converting ventilation systems to VAV (8%),
followed by high-efficiency chillers (5%), advanced new construction designs (3%), energy
managements systems (4%), and commissioning and other controls (4%)
 Office Equipment – servers and efficient computers (6%)
 Water heating and refrigeration provide 6% and 5% of savings
Measure 2012 2013 2014 2015 2017 2022 2027 2032
Interior Lighting - LED Exit Lighting 2.08 2.65 3.29 3.26 3.12 2.98 2.78 2.60
Interior Lighting - Timeclocks and Timers - - - - - - - -
Interior Fluorescent - Bi-Level Fixture - - - - - - - -
Interior Fluorescent - Delamp and Install Reflectors - - - - - - - -
Exterior Lighting - Bi-Level Fixture - - - - - - - -
Exterior Lighting - Photovoltaic Installation - - - - - - - -
Refrigerator - Anti-Sweat Heater 0.31 0.38 0.43 0.48 0.57 0.78 1.04 1.34
Refrigerator - Decommissioning 1.50 1.93 2.50 2.85 3.62 5.87 8.14 10.64
Refrigerator - Demand Defrost 0.66 0.82 0.92 1.02 1.24 1.81 2.49 3.29
Refrigerator - Door Gasket Replacement 0.13 0.16 0.17 0.19 0.22 0.31 0.41 0.53
Refrigerator - Evaporator Fan Controls - - - - - - - -
Refrigerator - Floating Head Pressure - - - - - - - -
Refrigerator - Strip Curtain 0.14 0.17 0.18 0.20 0.23 0.34 0.49 0.67
Refrigerator - High Efficiency Compressor 0.31 0.38 0.43 0.48 0.58 0.86 1.21 1.62
Refrigerator - Variable Speed Compressor 0.45 0.56 0.63 0.70 0.85 1.23 1.69 2.23
Refrigerator - Food Temperature Simulant - - - - - 0.04 0.06 0.08
Office Equipment - ENERGY STAR Power Supplies 0.05 0.07 0.08 0.10 0.13 0.23 0.36 0.51
Office Equipment - Plug Load Occupancy Sensors - - - - - - - -
Pool Heater - Solar - - - - - - - -
Retrocommissioning - HVAC 0.33 0.42 0.48 0.54 0.82 1.49 2.52 3.25
Retrocommissioning - Lighting 0.46 0.57 0.85 1.67 1.96 2.99 3.80 4.51
Cooking - Exhaust Hoods with Sensor Control 0.05 0.06 0.07 0.08 0.09 0.11 0.12 0.14
Commissioning - HVAC 0.01 0.02 0.03 0.04 0.06 0.13 0.18 0.24
Commissioning - Lighting - - - - - - - -
Grocery - Display Case - LED Lighting 0.41 0.52 0.60 0.67 0.83 1.25 1.73 2.31
Grocery - Display Case Motion Sensors - - - - - - - -
Grocery - ECMs for Display Cases 0.48 0.60 0.69 0.78 0.95 1.40 1.91 2.52
Grocery - Open Display Case - Night Covers 0.05 0.06 0.07 0.08 0.10 0.16 0.21 0.27
Lodging - Guest Room Controls - - - - - - - -
NE Measures Total 27.68 35.07 42.24 49.83 64.35 101.33 135.97 171.39
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-17
Figure 5-9 Commercial Achievable Potential Cumulative Savings by End Use in 2017
(percentage of total)

Commercial Potential by Market Segment
Table 5-14 shows potential estimates by segment in 2017. The small office segment has the
largest achievable energy efficiency potential of 109,323 MWh, roughly 17% of the overall
commercial achievable potential and 5% of the segment’s baseline projection. The retail segment
follows close behind at 106,340 MWh. The hospital, college, and grocery segments have the
highest achievable potential as a percentage of their respective baseline consumption.
Table 5-14 Commercial Potential by Market Segment, 2017
Energy Savings (MWh) Energy Savings (% of Baseline)
Baseline
Forecast
Achievable
Potential
Economic
Potential
Technical
Potential
Achievable
Potential
Economic
Potential
Technical
Potential
Small Office 648,706 33,722 109,323 157,362 5.2% 16.9% 24.3%
Large Office 227,029 13,417 38,458 55,907 5.9% 16.9% 24.6%
Restaurant 244,808 12,330 40,659 52,271 5.0% 16.6% 21.4%
Retail 586,191 32,638 106,340 159,114 5.6% 18.1% 27.1%
Grocery 229,607 13,449 46,617 65,165 5.9% 20.3% 28.4%
College 145,476 9,960 29,668 38,861 6.8% 20.4% 26.7%
School 262,053 13,083 40,273 68,003 5.0% 15.4% 26.0%
Hospital 416,263 28,697 82,966 92,205 6.9% 19.9% 22.2%
Lodging 171,721 7,770 26,527 44,351 4.5% 15.4% 25.8%
Assembly 219,711 10,394 33,048 51,742 4.7% 15.0% 23.5%
Warehouse 226,817 10,888 33,576 48,191 4.8% 14.8% 21.2%
Miscellaneous 359,203 8,069 25,163 39,185 2.2% 7.0% 10.9%
Total 3,737,586 194,418 612,619 872,355 5.2% 16.4% 23.3%

Energy Efficiency Potential
5-18 www.enernoc.com
Table 5-15 and Figure 5-10 present the achievable potential in 2017 by end use and building
type. Lighting replacement and upgrade, particularly for screw-in lamps, is a key measure across
all buildings. Other key measures for each building type are as follows:
 Small offices: Ventilation upgrades, high-efficiency servers and computers, daylighting
controls, HVAC duct repair and sealing
 Large Offices: Variable speed drives for chillers, high-efficiency chillers, conversion to VAV
ventilation, high-efficiency computers and servers, and advanced new construction designs
 Restaurants: Lighting upgrades, efficient cooking equipment, daylighting and lighting
controls, VAV ventilation
 Retail: Upgrades to high-bay fixtures and screw-in lighting, conversion to VAV ventilation,
daylighting controls, energy management systems
 Grocery: LED case lighting and anti-sweat heaters, high-efficiency and variable speed
compressors, daylighting controls,
 Colleges: VAV ventilation, daylighting, high-efficiency chillers, energy management systems,
and advanced new construction designs
 Schools: Energy management systems, HVAC duct repair and sealing, VAV ventilation,
advanced new construction designs
 Hospitals and other health: Chiller upgrades, variable speed drives on chillers, VAV
ventilation, water heating upgrades, energy management systems, advanced new
construction designs

Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-19
Table 5-15 Commercial Achievable Savings in 2017 by End Use and Building Type (1,000 MWh)

Segment Cooling Heating Ventil.Water Htg.Interior
Lighting
Exterior
Lighting Refr. Food Prep.Office
Equipt.Misc.Total
Small Office 3.7 2.7 6.6 1.7 12.1 2.3 0.0 0.1 4.6 0.0 33.7
Large Office 2.5 0.7 3.6 0.7 3.7 0.4 0.0 0.1 1.8 0.0 13.4
Restaurant 0.4 0.1 2.7 1.2 3.6 0.7 1.9 1.4 0.2 0.0 12.3
Retail 3.4 1.1 3.3 1.7 19.0 2.1 0.4 0.3 1.3 0.0 32.6
Grocery 0.2 0.2 0.8 0.8 4.2 0.3 6.7 0.2 0.1 0.0 13.4
College 2.3 0.5 0.9 0.9 4.6 0.4 0.0 0.1 0.4 0.0 10.0
School 2.5 0.7 1.4 0.8 4.9 1.1 0.2 0.3 1.1 0.0 13.1
Hospital 13.5 1.0 4.5 1.9 6.2 0.4 0.1 0.5 0.6 0.0 28.7
Lodging 0.5 0.3 1.1 1.1 4.0 0.5 0.1 0.1 0.1 0.0 7.8
Assembly 1.3 0.5 0.7 0.6 5.3 1.4 0.1 0.1 0.5 0.0 10.4
Warehouse 0.9 0.8 0.7 0.3 6.2 1.0 0.3 0.0 0.6 0.0 10.9
Miscellaneous 0.9 0.4 0.7 0.6 3.8 1.2 0.0 0.1 0.3 0.0 8.1
Total 32.0 8.8 27.0 12.4 77.4 12.0 9.9 3.2 11.6 0.2 194.4
Energy Efficiency Potential
5-20 www.enernoc.com
Figure 5-10 Commercial Achievable Savings in 2017 by End Use and Building Type

0.0
5.0
10.0
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Miscellaneous
Office Equipment
Food Preparation
Refrigeration
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Interior Lighting
Water Heating
Ventilation
Heating
Cooling
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-21
Industrial Sector Potential
The Idaho Power industrial sector accounts for 17% of total energy consumption, making for
prime efficiency opportunities. Table 5 16 and Figure 5 11 present the savings for the various
types of potential considered in this study. Figure 5 12 shows the industrial sector baseline
projection and the three potential level projections.
 Achievable potential projects 174,526 MWh (19.9 aMW) of energy savings in 2017, which
corresponds to 18.0% of the baseline projection.
 Economic potential, which reflects the savings when all cost-effective measures are taken,
is 313,888 MWh in 2017, or 29.7% of the baseline energy projection.
 Technical potential, which reflects the adoption of all energy efficiency measures
regardless of cost, is 380,544 MWh or 30.2% of the baseline energy projection...
Table 5-16 Energy Efficiency Potential for the Industrial Sector

Note: Baseline projection and potential exclude special-contract accounts.
Figure 5-11 Industrial Energy Efficiency Potential Savings

2012 2013 2015 2017 2022 2027 2032
Baseline Projection (MWh)2,651,085 2,740,818 2,895,022 3,010,038 3,209,994 3,492,905 3,812,170
Cumulative Savings (MWh)
Achievable Potential 39,772 69,610 122,714 174,526 301,997 415,708 488,465
Economic Potential 144,676 178,165 241,489 313,888 517,143 710,957 858,220
Technical Potential 185,494 225,094 303,357 380,544 596,122 788,460 927,757
Cumulative Savings (aMW)
Achievable Potential 4.5 7.9 14.0 19.9 34.5 47.5 55.8
Economic Potential 16.5 20.3 27.6 35.8 59.0 81.2 98.0
Technical Potential 21.2 25.7 34.6 43.4 68.1 90.0 105.9
Energy Savings (% of Baseline)
Achievable Potential 1.5%2.5%4.2%5.8%9.4%11.9%12.8%
Economic Potential 5.5%6.5%8.3%10.4%16.1%20.4%22.5%
Technical Potential 7.0%8.2%10.5%12.6%18.6%22.6%24.3%
0%
5%
10%
15%
20%
25%
30%
2012 2013 2015 2017 2022 2027 2032
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Achievable Potential
Economic Potential
Technical Potential
Energy Efficiency Potential
5-22 www.enernoc.com
Figure 5-12 Industrial Energy Efficiency Potential Projection

Industrial Potential by End Use, Technology, and Measure Type
Table 5-17 presents the industrial savings by end use and type of potential. Most of the
equipment replacement opportunities are in the machine drive (motors) end use, but potential
savings are diminishing due to the National Electrical Manufacturer’s Association (NEMA)
standards, which now make premium efficiency motors the baseline efficiency level. As a result,
potential savings are only available from upgrading to still more efficient levels. Cooling and
lighting have the next highest savings potential, but are dwarfed in comparison to machine
drives.
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-23
Table 5-17 Industrial Potential by End Use and Potential Type (MWh)

Figure 5-13 shows the achievable potential savings by end use in 2017, reflecting that the
preponderance of savings comes from motor loads, followed by process-related measures.
Specific measures that provide significant savings are as follows:
 Adjustable speed and variable frequency drives for pumps, fans, and other motors provide
21% of savings
 Other measures for fans and pumps, including equipment upgrades, controls, maintenance,
and system optimization, provide about 17% of savings
 Refrigeration measures, including floating head pressure, controls, maintenance and system
optimization provide 17% of savings
 Compressed air measures, including compressor replacement, air usage reduction, system
controls, and system optimization, provide nearly 9% of savings

End Use Potential 2012 2013 2015 2017 2022 2027 2032
Achievable Potential 3,978 6,317 10,472 13,606 18,514 21,593 22,937
Economic Potential 12,411 14,455 18,623 22,302 29,020 33,142 34,441
Technical Potential 12,463 14,533 18,774 22,510 29,334 33,521 34,832
Achievable Potential 2,461 4,517 8,091 11,091 15,833 18,335 19,549
Economic Potential 9,774 11,504 15,809 19,855 28,726 34,876 37,988
Technical Potential 14,475 16,593 21,756 26,518 36,339 42,666 45,586
Achievable Potential 403 830 2,516 4,518 9,123 11,431 12,078
Economic Potential 2,093 3,573 8,051 11,778 18,270 18,654 18,662
Technical Potential 2,202 3,696 8,202 11,952 18,469 18,887 18,910
Achievable Potential 4,964 8,599 13,726 17,974 54,123 92,555 111,084
Economic Potential 17,507 25,421 31,183 35,252 73,868 116,564 136,844
Technical Potential 27,603 36,423 45,690 54,331 97,499 135,534 152,368
Achievable Potential 984 1,605 2,185 2,200 6,468 12,857 14,607
Economic Potential 3,599 4,991 5,008 4,391 10,839 17,430 17,883
Technical Potential 3,916 5,352 5,591 5,375 12,303 18,445 18,855
Achievable Potential 17,423 33,847 61,726 89,991 144,742 188,675 219,662
Economic Potential 71,639 85,700 119,489 158,857 259,240 354,057 432,662
Technical Potential 76,722 92,363 129,506 168,812 269,694 362,983 440,075
Achievable Potential 9,545 13,868 23,945 35,055 52,936 69,671 87,693
Economic Potential 27,565 32,407 43,139 61,145 96,213 133,967 176,293
Technical Potential 48,000 55,991 73,609 90,682 131,406 173,977 213,433
Achievable Potential 13 26 54 90 258 590 857
Economic Potential 88 113 188 308 967 2,265 3,446
Technical Potential 112 142 229 364 1,077 2,446 3,698
Achievable Potential 39,772 69,610 122,714 174,526 301,997 415,708 488,465
Economic Potential 144,676 178,165 241,489 313,888 517,143 710,957 858,220
Technical Potential 185,494 225,094 303,357 380,544 596,122 788,460 927,757
Miscella-
neous
Motors
Process
Total
Cooling
Heating
Ventilation
Interior
Lighting
Exterior
Lighting
Energy Efficiency Potential
5-24 www.enernoc.com
Figure 5-13 Industrial Achievable Potential Savings by End Use in 2017 (MWh)

Industrial Sector Potential by Market Segment
Table 5-17 shows potential estimates by segment in 2017. The Manufacturing — Food segment
has the largest achievable energy efficiency potential of 95,217 MWh, roughly 54% of the overall
commercial achievable potential and 5.5% of the segment’s baseline projection. The Agriculture
segment has the highest achievable potential as a percentage of its respective baseline
consumption.
Table 5-18 Industrial Potential by Market Segment, 2017
Energy Savings (MWh) Energy Savings (% of Baseline)
Baseline
Projection
Achievable
Potential
Economic
Potential
Technical
Potential
Achievable
Potential
Economic
Potential
Technical
Potential
Manufacturing-
Food 1,727,704 95,217 134,188 169,237 201,476 5.5% 9.8%
Agriculture 296,780 21,383 29,960 39,106 48,730 7.2% 13.2%
Water and
Wastewater 275,631 16,481 23,735 29,631 32,988 6.0% 10.8%
Electronics 197,444 10,480 14,632 19,233 29,615 5.3% 9.7%
Other 512,479 30,966 42,772 56,681 67,736 6.0% 11.1%
Total 3,010,038 174,526 245,287 313,888 380,544 5.8% 10.4%

Figure 5-14 shows the achievable potential savings by segment and end use. For all segments,
the preponderance of savings comes from motor loads and process optimization related to motor
loads.
Cooling
8%
Heating
6%
Ventilation
3%
Interior
Lighting
10%
Exterior
Lighting
1%
Motors
52%
Process
20%
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-25
Figure 5-14 Industrial Achievable Potential Savings by Segment and End Use in 2017
(MWh)

Irrigation Sector Potential
Although the smallest of the sectors analyzed here, the irrigation sector still has significant
potential as shown in Table 5-19 and Figure 5-15. Figure 5-16 shows the projected irrigation
sector baseline projection and the three potential cases.
 Achievable potential projects 36,360 MWh (4.2 aMW) of energy savings in 2017, which
corresponds to 2.0% of the baseline projection.
 Economic potential, which reflects the savings when all cost-effective measures are taken,
is 124,499 MWh in 2017, or 6.8% of the baseline energy projection.
 Technical potential, which reflects the adoption of all energy efficiency measures
regardless of cost, is 131,099 MWh or 7.2% of the baseline energy projection.
Table 5-19 Energy Efficiency Potential for the Irrigation Sector

-
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
200,000
Manufacturing
-Food
Agriculture Water and
Wastewater
Electronics Other Grand Total
Ac
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v
a
b
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e

P
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i
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S
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(
M
W
h
)
Miscellaneous
Process
Motors
Exterior Lighting
Interior Lighting
Ventilation
Heating
Cooling
2012 2013 2015 2017 2022 2027 2032
Baseline Projection (MWh)1,789,137 1,789,760 1,818,632 1,825,093 1,900,010 1,964,478 2,038,167
Cumulative Savings (MWh)
Achievable Potential 3,046 5,869 19,833 36,360 92,393 169,700 229,821
Economic Potential 49,664 60,691 89,817 124,499 224,723 297,911 337,351
Technical Potential 51,576 63,482 94,455 131,099 236,784 312,290 349,382
Cumulative Savings (aMW)
Achievable Potential 0.3 0.7 2.3 4.2 10.5 19.4 26.2
Economic Potential 5.7 6.9 10.3 14.2 25.7 34.0 38.5
Technical Potential 5.9 7.2 10.8 15.0 27.0 35.6 39.9
Energy Savings (% of Baseline)
Achievable Potential 0%0.3%1.1%2.0%4.9%8.6%11.3%
Economic Potential 3%3.4%4.9%6.8%11.8%15.2%16.6%
Technical Potential 3%3.5%5.2%7.2%12.5%15.9%17.1%
Participation Rate (Achiev./Econ.)6.1%9.7%22.1%29.2%41.1%57.0%68.1%
Energy Efficiency Potential
5-26 www.enernoc.com
Figure 5-15 Irrigation Energy Efficiency Potential Savings

Figure 5-16 Irrigation Energy Efficiency Potential Projection

The only end-use in the irrigation sector analysis is motors. Because of the NEMA motor
standards, all new and replacement motors will move to premium efficiency units in the baseline
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
2012 2013 2015 2017 2022 2027 2032
En
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S
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B
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Achievable Potential
Economic Potential
Technical Potential
Energy Efficiency Potential
EnerNOC Utility Solutions Consulting 5-27
case and potential savings are only available from upgrading to still more efficient levels. These
higher efficiency units do not pass the cost-effectiveness test. Nonetheless, savings are available
from the following measures:
 Scientific irrigation practices (38% of 2017 savings)
 Proper pressure or head design (21% of 2017 savings)
 Multiple configuration nozzles and nozzle replacement (15% of 2017 savings)
 Variable frequency drives (10% of 2017 savings)
 Multiple pumps to enable part-load operation (6% of 2017 savings)
Special-Contract Customer Potential
The special contract customers were not analyzed within LoadMAP, but instead, potential was
assessed separately. To do so, the project team considered these customers’ past energy-savings
history and asked the Idaho Power customer representatives who work with these customers to
inquire about their upcoming EE plans. Consideration for this analysis included EE measures and
actions already implemented, general business plans, and planned future efficiency measures.
Based on this analysis, potential for these customers was estimated at approximately 10,557
MWh annually.

EnerNOC Utility Solutions Consulting
500 Ygnacio Valley Road, Suite 450
Walnut Creek, CA 94596
P: 925.482.2000 F: 925.284.3147
About EnerNOC
EnerNOC’s Utility Solutions Consulting team is part of EnerNOC’s Utility Solutions,
which provides a comprehensive suite of demand-side management (DSM)
services to utilities and grid operators worldwide. Hundreds of utilities have
leveraged our technology, our people, and our proven processes to make their
energy efficiency (EE) and demand response (DR) initiatives a success. Utilities
trust EnerNOC to work with them at every stage of the DSM program lifecycle –
assessing market potential, designing effective programs, implementing those
programs, and measuring program results.
EnerNOC’s Utility Solutions deliver value to our utility clients through two
separate practice areas – Implementation and Consulting.
• Our Implementation team leverages EnerNOC’s deep “behind-the-meter
expertise” and world-class technology platform to help utilities create and
manage DR and EE programs that deliver reliable and cost-effective energy
savings. We focus exclusively on the commercial and industrial (C&I)
customer segments, with a track record of successful partnerships that
spans more than a decade. Through a focus on high quality, measurable
savings, EnerNOC has successfully delivered hundreds of thousands of MWh
of energy efficiency for our utility clients, and we have thousands of MW of
demand response capacity under management.
• The Consulting team provides expertise and analysis to support a broad
range of utility DSM activities, including: potential assessments; end-use
forecasts; integrated resource planning; EE, DR, and smart grid pilot and
program design and administration; load research; technology assessments
and demonstrations; evaluation, measurement and verification; and
regulatory support.
The team has decades of combined experience in the utility DSM industry. The
staff is comprised of professional electrical, mechanical, chemical, civil, industrial,
and environmental engineers as well as economists, business planners, project
managers, market researchers, load research professionals, and statisticians.
Utilities view EnerNOC’s experts as trusted advisors, and we work together
collaboratively to make any DSM initiative a success.