# I DAHO 

# P OWER 

# E NERGY 

# E FFICIENCY 

# P OTENTIAL 

# S TUDY

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, 2013EnerNOC 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. BorsteinEnerNOC 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 re sources 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 co st -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

.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 develope d using EnerNOC’s Load Management Analysis and Planning (LoadMAP TM ) 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’ el ectricity 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.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 su ch 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 Res

idential 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 FamilyExecutive Summary

EnerNOC Utility Solutions Consulting ix Figure ES-4 Residential Intensity by End Use and Segment, 201 1

Figure ES-5

shows the percentage of the 2011 commercial energy use, 3,411, 78 8 MWh, for each

of the 12

segments analyzed. 3

The three largest segments are small office, retail, and hospital (including doct ors’ 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
, 201 1

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.Executive Summary

x www.enernoc.com 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,

2011Executive 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 account ed 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.Executive Summary

xii www.enernoc.com Figure ES

-9 Residential Baseline Projection by End Use

Figure ES

- 10 Commercial Baseline Projection by End UseExecutive Summary

EnerNOC Utility Solutions Consulting xiii Figure ES

- 11 Industrial Baseline Projection by End UseExecutive Summary

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 2 7 % 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 3 1 % 1.3%

Figure ES

- 12 Baseline Projection SummaryExecutive 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 T echnical 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 LoadMAP 4 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 Planning TM tool, which was used to perform the energy efficiency potential analysis.Executive Summary

xvi www.enernoc.com 

### Energy Efficien cy

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 PotentialExecutive Summary

EnerNOC Utility Solutions Consulting xvii Figure ES-

13 Summary of Energy Savings by Potential Case

Figure ES-

14 Energy Efficiency Potential ProjectionsExecutive 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 201 2 201 3 20 15 20 17 20 22 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 20 17

.

 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.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 20 17 (percentage of total)

As shown in Figure ES

- 17 , the primary sources of commercial sector achievable savings in 20 17

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 savingsExecutive 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 20 17 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 u se . 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)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 fromupgrading 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)

 Mu ltiple 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 PotentialEnerNOC 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- 21xxiv 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- 27EnerNOC 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 Re sidential 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

................................................ 4-8xxvi www.enernoc.com

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 Re sidential 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- 26EnerNOC 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

.............................................. 5-4xxviii www.enernoc.com

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- 25EnerNOC 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 re sources 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 203 2.



### 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 1Introduction

1-2 www.enernoc.com 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

LoadMAP TM 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 VolumeEnerNOC 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. 

### CHAPTER 2Analysis Approach Data Development

2-2 www.enernoc.com 6. Estimated three levels of en ergy 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 (LoadMAP TM ) to develop the baseline projection, as well as the estimates of energy efficiency potential for the residential, commercial, industrial, and irrigation sectors

. En erNOC 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 mod els (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, an d other dimensions) that are relevant for Idaho Power. The segmentation scheme employed for this project is presented in Table 2-1

.Analysis Approach Data Development

2-4 www.enernoc.com 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 I ncome Single Family, Limited Income Multi Family, and Limited I ncome Mobile /Mfg home)

Commercial (Offices, Restaurant, Retail, etc.)

Industrial ( Manuf acturing

- 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 a ppropriate

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 MiscellaneousAnalysis Approach Data Development

2-6 www.enernoc.com 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 in cluding 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

2-8 www.enernoc.com 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 MiscellaneousAnalysis 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 201 1 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 ofenergy 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 avoidedAnalysis Approach Data Development

2- 10 www.enernoc.com 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 efficiencyAnalysis 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 2032Analysis Approach Data Development

2- 12 www.enernoc.com 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 Satu ra tion

in 2011 5 Applica

bility Lifetime

(years) Measure

Installed

Cost Energy

Savings (%)

Cool ing Insulation

- Ceiling 36% 90% 20 $594 1.98%

Cool ing Insulation

- Ducting 0% 10% 25 $350 3.88%

Cool ing Insulation

- Infiltration

Control 24% 100% 12 $266 1.10%

Cool ing Insulation

- Radiant Barrier 5% 90% 12 $92 3 2.08%

Cool ing Ducting

- Repair and

Sealing 12% 90% 20 $375 11.43%

Cool ing Windows

- High

Efficiency/ENERGY STAR 61% 100% 25 $7,500 6.79%

Cool ing Windows

- Install Reflective

Film 5% 45% 10 $895 34.34%

Cool ing Doors

- Storm and Thermal 38% 100% 12 $320 0.46%

Cool ing Roofs

- High Reflectivity 5% 10% 15 $1,5 50 7.68%

Cool ing Attic Fan

- Installation 4% 50% 18 $11 6 0.58%

Cool ing Attic Fan

- Photovoltaic 13% 100% 19 $350 0.58%

Cool ing Whole

- House Fan

-

Installation 8% 25% 18 $200 16.22%

Cool ing Ceiling Fan

- Installation 21% 100% 10 $160 10.11%

Cool ing Thermostat

-

Clock/Programmable 52% 85% 12 $114 7.34%

Cool ing Home Energy Management

System 2% 40% 20 $600 3.65%

Cool ing AC

- Early Replacement 0% 80% 15 $2,895 10.00%

Cool ing AC

- M aint . / Tune

- Up 41% 100% 4 $12 5 9.86%

Cool ing 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.Analysis Approach Data Development

EnerNOC Utility Solutions Consulting 2- 13 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.Analysis Approach Data Development

2- 14 www.enernoc.com  Economic potential results from the purchase of the most efficient cost-effective optionavailable 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

 N on -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 employmentAnalysis Approach Data Development

EnerNOC Utility Solutions Consulting 2- 15  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 Foru m 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.Analysis Approach Data Development

2- 16 www.enernoc.com  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 cond ucted 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

As sessment (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 fromAnalysis Approach Data Development

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 o f 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.Analysis Approach Data Development

2- 18 www.enernoc.com 

### 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 201 0 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

Percent age of C&I floor space with equipment/technology  Idaho Power RCCS

 NWPCC Sixth Plan

 NEEA CBSA and residential surveys

 Energy Market Profiles

UEC/EUI for each end

use technology UEC: Annual electricity use for a
technology in dwelling s 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 simula tions

 Non HVAC uses: E ngin eering 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  E nergyShape databaseAnalysis Approach Data Development

EnerNOC Utility Solutions Consulting 2- 19 

### 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; speci fied separately for equipment replacement (replace

on

- burnout) and new construction  Data provided by Idaho

Power on saturation trends

 AEO s hipments 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 (incom e, 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 I daho 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.Analysis Approach Data Development

2- 20 www.enernoc.com Table 2-8 Residential Electric Equipment StandardsAnalysis Approach Data Development

EnerNOC Utility Solutions Consulting 2- 21 Table 2-9 Commercial Electric Equipment StandardsAnalysis Approach Data Development

2- 22 www.enernoc.com 

### Data Application for Energy Efficiency Measures

Table 2- 10

details the data sources used for developing the lists of measures to include in the analysis and for measure characterization. Table 2- 11 provides the total number of measures

evaluated.

Table 2-

10 Data Needs for the Measure Characteristics in LoadMAP

Model Inputs Description Key Sources

Energy Impacts The annual reduction in consumption

attributable to each specific measure. Savings were developed as a percentage of the energy end use that the measure affects.  Idaho Power measure data

 NWPCC Sixth Plan conservation

workbooks

 RTF deemed measure databases

 BEST

 EPRI National Study

 DEEM

 DEER

 Other secondary sources

Peak Demand
Impacts Savings during the peak demand periods are

specified for each measure. These impacts
relate to the energy savings and depend on

the extent to which each measure is coincident with the system peak.  Idaho Power measure data

 NWPCC Sixth Plan conservation

workbooks

 RTF deemed measure databases

 BES T

 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

workbo oks

 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 marke t  Appliance, building codes, and standards analysisAnalysis 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 inAnalysis 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 d emands, 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 a s shown in Figure 3-1

.

Table 3-1 Sector Level Market Characterization, Base Year 2011

Sector /

Rate Class N umber of

Customers 2011 Weather

- Normalized Sales (MWh) 2011 Peak Demand (MW)

Residential 411,487 5,079,293 1,093

Commercial 1 65,226 3,792,283 550

Industrial 2 117 2,228,827 330

Irrigation 18,736 1,768,810 735

Total 495,566 12,869,213 2,708

1. Includes street lighting sales of 23,879 MWh, 0.7% of commercial sales.
2. Excludes special-contract customers.

Figure 3-1 Sector-Level Electricity Use, 2011Market Characterization and Market Profiles

3-8 www.enernoc.com To enable characterization of C&I customers, Idaho Power provided EnerNOC with 2011 sales data including information on use, rate class, and 4-digit SIC code Based on the SIC codes, EnerNOC made some adjustments between the commercial and industrial sector sales shown

above in Table 3-1 to better group energy use by facility type and end uses. For example, some customers on commercial rates ( EC -SG and EC- LG )

— such as dairy and agricultural operations, refrigerated warehouses, small manufacturing, water treatment, and waste water treatment

— were reclassified as industrial. We did this because energy use in these operations is more likely dominated by motor and process end uses, rather than the HVAC, lighting, and office equipment end uses that dominate commercial buildings. Therefore, energy-savings potential for these facilities can best be estimated by treating them as industrial. Conversely, some customers on Idaho Power’s industrial rate ( EI

- IN ) such as colleges and hospitals were reclassified as commercial. The amount of sales that were reclassified represent less than 6% of total C&I sales. The results of these adjustments appear in Table 3-2

.

Table 3-2 Commercial and Industrial Sales Adjustments for LoadMAP Modeling

Sector /

Rate Class Original 2011 Weather

Normalized Sales (MWh) Adjusted 2011 Weather

Normalized Sales (MWh) Original % of

C&I Sales Adjusted %

of C&I Sales

Commercial 1 3,792,283 3,436,087 63.0% 57 .1%

Industrial 2 2,228,827 2,585,023 37.0% 42.9 %

Total 6,021,110 6,021,110 100.0% 100.0%

1. Includes street lighting sales of 23,879 MWh, 0.7% of commercial sales.
2. Excludes special-contract customers.



## Residential Sector

This section characterizes the residential market at a high level, and then provides a profile of how customers in each segment use electricity by end use. Total residential electricity use in 2011 was 5,079,293 MWh. Using data from the 2010 Residential Energy Use Survey, Idaho Power divided its customers into six segments based on housing type and income as shown in Table 3-3 and Figure

3-2

. The chosen threshold for the limited income segments was approximately twice the federal poverty limit, which also correlates with the income threshold used in Idaho Power’s Weatherization Solutions program. The Single Family segment consumed 52 % of total residential sector electricity in 2011 as a result of having the largest number of customers and relatively high intensity. The two Mobile/Manufactured Home segments, however, have the highest intensity, because these homes are more likely to be located in rural areas without natural gas services and thus are more likely to use electricity for space and water heating. The values for customer counts and sales shown in Table 3-3 are referred to throughout the study as the residential sector control totals to which all base year energy usage is calibrated in the LoadMAP model.Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3- 11 Table 3-3 Residential Market Segmentation by Housing Type, Base Year 2011

Segment Number of

Customers Weather

- Normalized Sales (1,000 MWh) Intensity (kWh/ Cust )

Single Family 213,109 2,780 13,045

Multi Family 25,142 220 8,737

Mobile /Mfg Home 17,529 273 15,553

Limited Income SF 98,633 1,222 12,390

Limited Income MF 28,022 190 6,788

Limited Income MH 29,051 395 13,585

Total 411,487 5,079 12,344

Figure 3-2

shows the size of the segments as a percentage of customers and percentage of

residential sector sales.

Figure 3-2 Residential Market Segmentation by Housing Type, 2011

As we describe in the previous chapter, the market profiles provide the foundation upon which we develop the baseline projection

. For each of the six segments defined above, we developed market profiles that characterize electricity use in terms of sector, customer segment, end use, and technology for the base year.

For each segment (housing type) within the residential sector, we develop ed 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 FamilyMarket 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.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, 201 1Market 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)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, 78 8 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 the ir

cooking and refrigeration usage. Warehouses, schools, assembly, and miscellaneous

have the lowest intensities.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, 2011Market 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, 2011Market 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.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 Rest aurant Retail Grocery College School Hospital Lodging Assembly Ware

house Misc. Total

Cooling 144 38 25 110 10 29 49 99 22 37 26 21 609

Heating 80 23 6 53 5 13 18 21 24 15 31 14 302

Ventilation 41 31 14 41 11 14 25 51 13 11 9 11 273

Water Heating 21 7 13 22 6 8 13 13 12 10 5 9 139

Interior Lighting 154 49 36 217 49 44 66 71 59 71 83 55 954

Exterior Lighting 35 6 11 35 6 7 18 6 8 23 18 17 189

Refrigeration 1 2 61 27 143 1 12 7 8 4 9 3 278

Food Prep. 1 3 73 17 10 3 13 22 5 5 0 2 155

Office Equip. 73 35 4 20 2 7 16 10 2 9 8 5 191

Misc 39 12 7 29 5 5 9 45 13 18 17 125 322

Total 590 205 249 571 246 130 239 345 166 203 205 262 3,412Ma rket Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-3 

## Industrial Sector

The industrial sector account ed 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 a n 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 2,585Market 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.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, 2011Market 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 Manufactur ing

- 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 account ed 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 us e. Table 3- 12 shows the resulting market profile, with the intensity in units of kWh per service point (SP)

.Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-7 Table 3-

12 Irrigation Sector Market Profile, 2011

EUI Intensity Usage

(kWh) (kWh/meter) (GWh)

Motors 5 HP 100.0% 645 645 12 0.7%

Motors 10 HP 100.0% 1,914 1,914 36 2.0%

Motors 15 HP 100.0% 1,385 1,385 26 1.5%

Motors 20 HP 100.0% 1,732 1,732 32 1.8%

Motors 25 HP 100.0% 2,031 2,031 38 2.2%

Motors 30 HP 100.0% 2,161 2,161 40 2.3%

Motors 40 HP 100.0% 3,727 3,727 70 3.9%

Motors 50 HP 100.0% 3,771 3,771 71 4.0%

Motors 60 HP 100.0% 2,905 2,905 54 3.1%

Motors 75 HP 100.0% 4,489 4,489 84 4.8%

Motors 100 HP 100.0% 6,571 6,571 123 7.0%

Motors 125 HP 100.0% 4,926 4,926 92 5.2%

Motors 150 HP 100.0% 5,781 5,781 108 6.1%

Motors 200 HP 100.0% 9,690 9,690 182 10.3%

Motors 250 HP 100.0% 6,006 6,006 113 6.4%

Motors 300 HP 100.0% 6,659 6,659 125 7.1%

Motors 350 HP 100.0% 5,507 5,507 103 5.8%

Motors 400 HP 100.0% 5,534 5,534 104 5.9%

Motors 450 HP 100.0% 3,613 3,613 68 3.8%

Motors 500 HP 100.0% 3,510 3,510 66 3.7%

Motors 600 HP 100.0% 3,799 3,799 71 4.0%

Motors > 600 HP 100.0% 8,051 8,051 151 8.5%

94,407 1,769 100% Total % of

Total Average Market Profiles

End Use Technology SaturationEnerNOC 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 4-1 and 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 UseBaseline Projection

EnerNOC Utility Solutions Consulting 4-3 Table 4-3

shows the end-use project ion 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 lightingstandards, 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 hasBaseline 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 3,4 11

, 788 MWh in 2011 and increases to
4,5 31

, 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 sectio n.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 we ll.

 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.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.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 UseBaseline 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 ProjectionBaseline 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 2 7 % 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 3 1 % 1.3%

Figure 4-5 Baseline Projection SummaryEnerNOC 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 PotentialEnergy 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 ProjectionsEnergy 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 En ergy Efficiency Potential by Sector

Sector 201 2 201 3 20 15 20 17 20 22 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 SectorEnergy 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

po tential 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 energyefficiency 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.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 untilEnergy 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 centralair 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)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 o r 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)Energy Efficiency Potential

EnerNOC Utility Solutions Consulting 5-9 Table 5-6 Residential Achievable Savings for Non- eq uipment Measures (1,000 MWh)



### Residential Potential by Market Segment

Single-family homes were slightly more than half of Idaho Power ’s reside ntial 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-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 20 17

.

Table 5-7 Residential Achievable Potential by Market Segment

Table 5-8 Residential Potential Summary by Market Segment, 20 17

Table 5-9

shows the savings by end use and market segment in 2017. The segments are similarin 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 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.Energy Efficiency Potential

5- 12 www.enernoc.com Figure 5-7 Commercial Energy Efficiency Potential Savings

Figure 5-8 Commercial Energy Efficiency Potential Projection s



### 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 20 17

. 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 20 17

. These savings result from installation of high-efficiency equipment and numerous thermalEnergy 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 20 17 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)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)Energy Efficiency Potential

EnerNOC Utility Solutions Consulting 5- 15 Table 5-

13 Commercial Achievable Savings for Non-equipment Measures (1,000MWh)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 savingsEnergy Efficiency Potential

EnerNOC Utility Solutions Consulting 5- 17 Figure 5-9 Commercial Achievable Potential Cumulative Savings by End Use in 201 7 (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, 20 17



### 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 designsEnergy 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)Energy Efficiency Potential

5- 20 www.enernoc.com Figure 5-

10 Commercial Achievable Savings in 2017 by End Use and Building TypeEnergy 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

0% 5% 10% 15% 20% 25% 30%

2012 2013 2015 2017 2022 2027 2032Energy Savings (% of Baseline Projection) Achievable Potential

Economic Potential

Technical PotentialEnergy Efficiency Potential

5- 22 www.enernoc.com Figure 5-

12 Industrial Energy Efficiency Potential Projection



### Industrial Potential by End Use, Technology, and Measure Ty pe

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 diminish ing 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 f an s 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 savingsEnergy 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, 20 17

Energy Savings (MWh) Energy Savings (% of Baseline)

Baseline
Projection Achievable

Potential Economic

Potential Technical

Potential Achievable

Potential Economic

Potential Technical

Potential

Manufacturing

Food 1,727,704 95,217 134,188 169,237 201,476 5.5% 9.8%

Agriculture 296,780 21,383 29,960 39,106 48,730 7.2% 13.2%

Water and

Wastewater 275,631 16,481 23,735 29,631 32,988 6.0% 10.8%

Electronics 197,444 10,480 14,632 19,233 29,615 5.3% 9.7%

Other 512,479 30,966 42,772 56,681 67,736 6.0% 11.1%

Total 3,010,038 174,526 245,287 313,888 380,544 5.8% 10.4%

Figure 5- 14

shows the achievable potential savings by segment and end use. For all segments, the preponderance of savings comes from motor loads and process optimization related to motor

loads.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 cas es

.

 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 SectorEnergy 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 2032Energy Savings (% of Baseline Projection)

Achievable Potential

Economic Potential

Technical PotentialEnergy 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 consider ed these customers ’ past energy-savings history and asked the Idaho Power customer representatives who work with the se 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 dem and

- 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. Uti lities
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 th at 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; evalua tion, 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.