IDAHO POWER ENERGY EFFICIENCY POTENTIAL STUDY

EnerNOC Utility Solutions Consulting

500 Ygnacio Valley Road

Suite 450

Walnut Creek, CA 94596

925.482.2000

www.enernoc.com

Prepared for:

Idaho Power Corporation

Presented on:

February 15, 2013

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. 
Executive Summary 

vi www.enernoc.com 

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 energyefficient 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 data Utility 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
Executive Summary 

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 developed 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%
Executive Summary 

viii www.enernoc.com 

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
Executive Summary 

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

Intensity (kWh/HH)

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%
Executive Summary 

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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; 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. 

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%
Executive Summary 

EnerNOC Utility Solutions Consulting xi

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

Annual Energy Use (1,000 MWh)

Cooling

Heating

Ventilation

Interior Lighting

Exterior Lighting

Motors

Process

Miscellaneous
Executive Summary 

xii www.enernoc.com 

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

Annual Use (1,000 MWh)

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

Annual Use (1,0000 MWh)

Cooling

Heating

Ventilation

Water Heating

Interior Lighting

Exterior Lighting

Refrigeration

Food Preparation

Office Equipment

Miscellaneous
Executive Summary 

EnerNOC Utility Solutions Consulting xiii 

Figure ES-11 Industrial Baseline Projection by End Use 
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xiv www.enernoc.com 

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 

Annual Use (1,000 MWh)

Street Lighting

Irrigation

Industrial

Commercial

Residential
Executive Summary 

EnerNOC Utility Solutions Consulting xv

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 1,048,684 594,772 1,570,770 2,053,161

Economic Potential 1,002,446 732,142 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

Energy Savings (% of Baseline Projection)

Achievable Potential

Economic Potential

Technical Potential
Executive Summary 

xviii www.enernoc.com 

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

Achievable Potential Savings (1,000 MWh) 

Irrigation

Industrial

Commercial

Residential
Executive Summary 

EnerNOC Utility Solutions Consulting xix 

 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 

xx www.enernoc.com 

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 costeffectiveness 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
xxiv www.enernoc.com 

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
EnerNOC Utility Solutions Consulting xxv 

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
EnerNOC Utility Solutions Consulting xxvii 

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 

CHAPTER 1
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 energyefficient 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 acronyms. Table 1-1

shows the abbreviation or acronym, along with what it stands for. 

Table 1-1 Explanation of Abbreviations and Acronyms 

Acronym Explanation

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 data Utility 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

CHAPTER 2
Analysis Approach Data Development 

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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 energyconsuming 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. 
Analysis Approach Data Development 

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 options

Codes 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. 
Analysis Approach Data Development 

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
Analysis Approach Data Development 

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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. 
Analysis Approach Data Development 

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. 
Analysis Approach Data Development 

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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
Analysis Approach Data Development 

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 costeffectiveness 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 
Analysis Approach Data Development 

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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
Analysis Approach Data Development 

EnerNOC Utility Solutions Consulting 2-11

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

ApplicabilityLifetime 

(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 waterrelated 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 costeffectiveness 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. 

 EnergyShape

TM

 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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EnerNOC Utility Solutions Consulting 2-17

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 EIAadministered 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 enduse 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 

Model Inputs Description Key Sources

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 (replaceon-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

Incandescent Advanced Incandescent - tier 1

T8

EISA 2007 Standard

MEF 1.26 MEF 1.6

62.3% Efficiency 70% 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
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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

-

10 

20 

30 

40 

50 

60 

Avoided Energy Cost, $/MWh 

Avoided Capacity Costs ($/kW)

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

Commercial165,226 3,792,283 550

Industrial2117 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 WeatherNormalized Sales (MWh) Adjusted 2011 WeatherNormalized Sales (MWh)Original % of 

C&I Sales

Adjusted % 

of C&I Sales

Commercial13,792,283 3,436,087 63.0% 57.1%

Industrial22,228,827 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

 5,079 12,344

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

Interior 12%

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

Intensity (kWh/Cust/yr)

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

Percentage of Total Energy Use

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%

90%

100%

% of Total Annual Energy Use

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 Warehouse 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 

1,400 

1,600 

Manufacturing -

Food

Agriculture Water and 

Wastewater

Electronics Other

Annual Energy Use (1,000 MWh)

Cooling

Heating

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

% of Total Annual Energy Use

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%

Total 94,407 1,769 100%

% 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

Annual Use (1,000 MWh)

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

Annual Use per Customer (kWh)

Cooling

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 threeyear 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 saturation 

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 -53% -3.6% 45

Clothes Washer 44 42 40 38 34 25 19 -60% -4.4% 17

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 5,075 5,079 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

Annual Use (1,0000 MWh)

Cooling

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 1 0 -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 16 15 16 17 18 21 23 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 

Annual Use (1,000 MWh)

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 energyefficiency 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 1,048,684 594,772 1,570,770 2,053,161

Economic Potential 1,002,446 732,142 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 

0 %

5 %

10%

15%

20%

25%

30%

35%

40%

2012 2013 2015 2017 2022 2027 2032

Energy Savings (% of Baseline Projection)

Achievable Potential

Economic Potential

Technical Potential
Energy Efficiency Potential 

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 

-

500 

1,000 

1,500 

2,000 

2,500 

2015 2017 2022 2032

Achievable Potential Savings (1,000 MWh) 

Irrigation

Industrial

Commercial

Residential
Energy Efficiency Potential 

5-4 www.enernoc.com 

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 costeffectiveness 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 %

10%

20%

30%

40%

50%

60%

2012 2013 2015 2017 2022 2027 2032

Energy Savings (% of Baseline Projection)

Achievable Potential 

Economic Potential

Technical Potential
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 costeffective, 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 - - - 1 8 145 354 699

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

Miscellaneous
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. Singlefamily 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 2 0 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 1 9 1 9 113 1 5 2 5

Electronics 14,561 774 710 4,296 598 888

Miscellaneous 1 8 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 screw-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

Energy Savings (% of Baseline Projection)

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 costeffective, 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

Refrigeration

Miscellaneous

Food 

Preparation

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 11.89 7.65 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 10.21 5.32 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 11.34 6.95 21.03 45.54 56.82 60.39

Water Heating Water Heating 1.04 2.14 3.21 4.89 18.04 8.54 29.13 36.32

High-Bay Fixtures 1.17 1.94 2.58 3.19 4.35 14.61 9.17 19.02

Linear Fluorescent 5.10 14.02 9.42 19.06 28.95 69.36 108.04 97.37

Screw-in 15.41 9.77 20.24 24.35 31.77 46.17 121.40 81.16

HID 1.84 3.14 4.28 5.36 13.71 7.44 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 13.21 8.79 

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 11.18 8.98 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 14.15 6.08 20.84 28.09

Energy Management System 3.20 4.10 4.75 5.43 10.77 6.80 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 10.56 8.56 

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 2.65 2.08 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 0.38 0.31 0.43 0.48 0.57 0.78 1.04 1.34

Refrigerator - Decommissioning 1.93 1.50 2.50 2.85 3.62 5.87 10.64 8.14 

Refrigerator - Demand Defrost 0.82 0.66 0.92 1.02 1.24 1.81 2.49 3.29

Refrigerator - Door Gasket Replacement 0.16 0.13 0.17 0.19 0.22 0.31 0.41 0.53

Refrigerator - Evaporator Fan Controls - - - - - - - -

Refrigerator - Floating Head Pressure - - - - - - - -

Refrigerator - Strip Curtain 0.17 0.14 0.18 0.20 0.23 0.34 0.49 0.67

Refrigerator - High Efficiency Compressor 0.38 0.31 0.43 0.48 0.58 0.86 1.21 1.62

Refrigerator - Variable Speed Compressor 0.56 0.45 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 0.07 0.05 0.08 0.10 0.13 0.23 0.36 0.51

Office Equipment - Plug Load Occupancy Sensors - - - - - - - -

Pool Heater - Solar - - - - - - - -

Retrocommissioning - HVAC 0.42 0.33 0.48 0.54 0.82 1.49 2.52 3.25

Retrocommissioning - Lighting 0.57 0.46 0.85 1.67 1.96 2.99 3.80 4.51

Cooking - Exhaust Hoods with Sensor Control 0.06 0.05 0.07 0.08 0.09 0.11 0.12 0.14

Commissioning - HVAC 0.02 0.01 0.03 0.04 0.06 0.13 0.18 0.24

Commissioning - Lighting - - - - - - - -

Grocery - Display Case - LED Lighting 0.52 0.41 0.60 0.67 0.83 1.25 1.73 2.31

Grocery - Display Case Motion Sensors - - - - - - - -

Grocery - ECMs for Display Cases 0.60 0.48 0.69 0.78 0.95 1.40 1.91 2.52

Grocery - Open Display Case - Night Covers 0.06 0.05 0.07 0.08 0.10 0.16 0.21 0.27

Lodging - Guest Room Controls - - - - - - - -

NE Measures Total

 27.68 42.24 35.07 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

15.0

20.0

25.0

30.0

35.0

40.0 Achievable Potential Savings (1,000 MWh)

Miscellaneous

Office Equipment

Food Preparation

Refrigeration

Exterior Lighting

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

Energy Savings (% of Baseline Projection)

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

Miscellaneous

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

ManufacturingFood 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

Achievable Potential Savings (MWh)

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

Energy Savings (% of Baseline Projection)

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.