Guide for Conducting 

Energy Effi ciency 

Potential Studies 

A RESOURCE OF THE NATIONAL ACTION PLAN FOR 

ENERGY EFFICIENCY 

NOVEMBER 2007 
About This Document 

This Guide for Conducting Energy Effi ciency Potential Studies is 

provided to assist state offi cials, regulators, legislators, and others 

in the implementation of the recommendations of the National 

Action Plan for Energy Effi ciency (Action Plan) and the pursuit of its 

longer-term goals. 

This Guide identifi es three main applications for energy effi ciency 

potential studies and provides examples of each, along with a description of how key decisions regarding scope and methodology 

are made to best achieve the studies’ objectives. It also provides 

an overview of the main analytical steps in conducting a potential 

study and introduces several related concepts. 

The primary intended audience for this Guide is policy-makers, 

state offi cials, utility staff, and effi ciency advocates looking for 

guidance on the process of conducting potential studies. These 

individuals can also use the Guide to review the results of alreadycompleted studies. 
Guide for Conducting 


Energy Effi ciency 


Potential Studies
 

A RESOURCE OF THE NATIONAL ACTION PLAN FOR 

ENERGY EFFICIENCY 

NOVEMBER 2007 
The Guide for Conducting Energy Effi ciency Potential Studies is a product of the National Action Plan for Energy Effi ­

ciency Leadership Group and does not refl ect the views, policies, or otherwise of the federal government. The role of the 

U.S. Department of Energy and U.S. Environmental Protection Agency is limited to facilitation of the Action Plan.
 

This document was fi nal as of December 2007 and incorporates minor modifi cations to the original release.
 

If this document is referenced, it should be cited as:
 

National Action Plan for Energy Effi ciency (2007). Guide for Conducting Energy Effi ciency Potential Studies. Prepared by 


Philip Mosenthal and Jeffrey Loiter, Optimal Energy, Inc. <www.epa.gov/eeactionplan>
 

For More Information 

Regarding the Guide for Conducting Energy Effi ciency Potential Studies, please contact: 

Niko Dietsch 

U.S. Environmental Protection Agency 

Offi ce of Air and Radiation 

Climate Protection Partnerships Division 

Tel: (202) 343-9299 

E-mail: dietsch.nikolaas@epa.gov 

Regarding the National Action Plan for Energy Effi ciency, please contact: 

Stacy Angel 

U.S. Environmental Protection Agency 

Offi ce of Air and Radiation 

Climate Protection Partnerships Division 

Tel: (202) 343-9606 

E-mail: angel.stacy@epa.gov 

Larry Mansueti 

U.S. Department of Energy 

Offi ce of Electricity Delivery and Energy Reliability 

Tel: (202) 586-2588 

E-mail: lawrence.mansueti@hq.doe.gov 

or visit www.epa.gov/eeactionplan 
Table of Contents
 

List of Figures .................................................................................................................................................... i
 

List of Tables .....................................................................................................................................................ii
 

List of Abbreviations and Acronyms..................................................................................................................iii
 

Acknowledgements .........................................................................................................................................iv
 

Executive Summary ................................................................................................................................. ES-1
 

Importance of Conducting Energy Effi ciency Potential Studies ............................................................... ES-1
 

Chapter 1: Introduction ............................................................................................................................. 1-1
 

1.1 Guide for Conducting Energy Effi ciency Potential Studies .................................................................. 1-1
 

1.2 Notes................................................................................................................................................ 1-3
 

Chatper 2: Energy Efficiency Potential Studies as a Policy Tool ............................................................ 2-1
 

2.1 What Is a Potential Study? ................................................................................................................ 2-1
 

2.2 Defi nition of Key Terms ..................................................................................................................... 2-1
 

2.3 Potential Studies as Policy Tool .......................................................................................................... 2-2
 

2.4 Types of Effi ciency Potential ............................................................................................................... 2-3
 

2.5 Review of Results from Previous Potential Studies .............................................................................. 2-4
 

2.6 Notes.............................................................................................................................................. 2-10
 

Chapter 3: General Concepts and Steps to Completing a Potential Study............................................ 3-1
 

3.1 Identify the Objective and the Audience............................................................................................ 3-1
 

3.2 Select Potential Type(s) to Analyze ..................................................................................................... 3-1
 

3.3 Determine Appropriate Level of Detail and Assess Data Requirements ............................................... 3-2
 

3.4 Select and Defi ne the Methodology .................................................................................................. 3-4
 

3.5 Present the Results ............................................................................................................................ 3-8
 

3.6 Notes................................................................................................................................................ 3-8
 

Chapter 4: Applying the Concepts: Building a Case for Energy Effi ciency ............................................ 4-1
 

4.1 Key Questions................................................................................................................................... 4-1
 

4.2 Objective and Audience .................................................................................................................... 4-1
 

4.3 Example Applications: SWEEP “Mother Lode” and Texas “Power to Save” ........................................ 4-1
 

4.4 Potential Type ................................................................................................................................... 4-2
 

4.5 Level of Detail and Data Requirements .............................................................................................. 4-3
 

4.6 Methodology .................................................................................................................................... 4-4
 

National Action Plan for Energy Effi ciency 
Table of Contents (continued)
 

4.7 Presentation of Results ...................................................................................................................... 4-7
 

4.8 Conclusion........................................................................................................................................ 4-8
 

4.9 Notes.............................................................................................................................................. 4-10
 

Chapter 5: Applying the Concepts: Identifying Alternatives to Supply-Side Investments .................. 5-1
 

5.1 Key Questions................................................................................................................................... 5-1
 

5.2 Objective and Audience .................................................................................................................... 5-1
 

5.3 Example Applications: VELCO “Southern Loop” and ACEEE “Texas” Potential Studies. ..................... 5-1
 

5.4 Potential Type ................................................................................................................................... 5-3
 

5.5 Level of Detail and Data Requirements .............................................................................................. 5-3
 

5.6 Methodology .................................................................................................................................... 5-4
 

5.7 Presentation of Results ...................................................................................................................... 5-6
 

5.8 Conclusion........................................................................................................................................ 5-7
 

5.9 Notes................................................................................................................................................ 5-9
 

Chapter 6: Applying the Concepts: Detailed Planning and Program Design ........................................ 6-1
 

6.1 Key Questions................................................................................................................................... 6-1
 

6.2 Objective and Audience .................................................................................................................... 6-1
 

6.3 Example Application: California Potential Study ................................................................................. 6-1
 

6.4 Potential Type ................................................................................................................................... 6-2
 

6.5 Level of Detail and Data Requirements .............................................................................................. 6-3
 

6.6 Methodology .................................................................................................................................... 6-3
 

6.7 Presentation of Results ...................................................................................................................... 6-4
 

6.8 Conclusion........................................................................................................................................ 6-5
 

6.9 Notes................................................................................................................................................ 6-5
 

Chapter 7: Conclusion................................................................................................................................ 7-1
 

Appendix A: National Action Plan for Energy Efficiency Leadership Group ........................................ A-1
 

Appendix B: Glossary.................................................................................................................................B-1
 

Appendix C: Detailed Methodology Discussion ......................................................................................C-1
 

Appendix D: Data Sources ........................................................................................................................ D-1
 

Appendix E: Example Potential Studies ................................................................................................... E-1
 

Appendix F: References ............................................................................................................................. F-1 


Guide for Conducting Energy Effi ciency Potential Studies 
List of Figures
 

Figure ES-1. Considerations for Conducting Potential Studies .................................................................... ES-2
 

Figure 1-1. National Action Plan for Energy Effi ciency Recommendations and Options ................................. 1-2
 

Figure 2-1. Considerations for Conducting Potential Studies ........................................................................ 2-2
 

Figure 4-1. Sample Penetration Curve for a Clothes Washer Program. .......................................................... 4-5
 

Figure 4-2. Total Electricity Consumption in the Base and High Effi ciency Scenarios ...................................... 4-7
 

Figure 4-3. Energy Savings Potential in 2020 by Sector and State in the Southwest ...................................... 4-8
 

Figure 6-1. Savings Estimates for Select Measures ........................................................................................ 6-4
 

Figure 7-1. Considerations for Conducting Potential Studies ........................................................................ 7-1
 

National Action Plan for Energy Effi ciency i
List of Tables
 

Table ES-1. Key Issues for Selecting a Potential Study Application............................................................... ES-3
 

Table 2-1. Sample of Gas Savings Potential Studies....................................................................................... 2-5
 

Table 2-2. Sample of Electricity Savings Potential Studies .............................................................................. 2-6
 

Table 4-1. Summary of Example Potential Studies: Building a Case for Energy Effi ciency ............................... 4-9
 

Table 5-1. Sample Table Comparing Transmission Alternatives in VELCO Territory ......................................... 5-7
 

Table 5-2. Summary of Example Potential Studies: Identifying Alternatives to Supply-Side Investment ........... 5-8
 

Table 6-1. Summary of Example Potential Study: Detailed Planning and Program Design .............................. 6-5
 

ii Guide for Conducting Energy Effi ciency Potential Studies 
 

 

 

List of Abbreviations and Acronyms
 

A
 

Action Plan National Action Plan for Energy Efficiency 

AC air conditioning 

ACEEE American Council for an Energy Efficient 

Economy 

ARC alternative resource configuration 

ARI American Refrigeration Institute 

C 

CBECS Commercial Building Energy Consumption 

Survey 

CEE Consortium for Energy Efficiency 

D 

DEER Database for Energy Efficiency Resources 

(California) 

DOE U.S. Department of Energy 

DSM demand-side management 

E 

EIA Energy Information Administration 

EPA U.S. Environmental Protection Agency 

ERCOT Electric Reliability Council of Texas 

G 

GWh gigawatt-hour 

H 

HVAC heating, ventilation, and air conditioning 

I 

IOU investor-owned utility
 

K
 

kW kilowatt 

kWh kilowatt-hour 

L 

LBL Lawrence Berkeley National Laboratory 

M 

MCES Manufacturing Energy Consumption Survey 

MCF thousand cubic feet 

MW megawatt 

MWh megawatt-hour 

N 

NEMA National Electrical Manufacturers 

Association 

R 

RECS Residential Energy Consumption Survey 

RIM ratepayer impact measure 

S 

SCT societal cost test 

SWEEP Southwest Energy Efficiency Project 

T 

TRC total resource cost 

V 

VELCO Vermont Electric Power Company, Inc.
 

National Action Plan for Energy Effi ciency iii
Acknowledgements
 

The Guide for Conducting Energy Effi ciency Potential 

Studies is a key product of the Year Two Work Plan for 

the National Action Plan for Energy Effi ciency. This work 

plan was developed based on feedback from Action 

Plan Leadership Group members and observers during the fall of 2006. The work plan was further refi ned 

during the March 2007 Leadership Group meeting in 

Washington, D.C. A full list of Leadership Group members is provided in Appendix A. 

Philip Mosenthal of Optimal Energy, Inc., served as 

project manager and co-authored the Guide along with 

Jeffrey Loiter, under contract to the U.S. Environmental 

Protection Agency (EPA). In addition to direction and 

comment by the Action Plan Leadership Group, Rich 

Sedano of the Regulatory Assistance Project and Alison 

Silverstein of Alison Silverstein Consulting provided their 

expertise during review and editing of the Guide. 

The U.S. Department of Energy (DOE) and EPA facilitate 

the National Action Plan for Energy Effi ciency, including this Guide. Key staff include Larry Mansueti (DOE 

Offi ce of Electricity Delivery and Energy Reliability), Dan 

Beckley (DOE Offi ce of Energy Effi ciency and Renewable Energy), and Kathleen Hogan, Niko Dietsch, Stacy 

Angel, and Katrina Pielli (EPA Climate Protection Partnership Division). 

Eastern Research Group, Inc., provided technical review, 

copyediting, graphics, and production services. 

iv Guide for Conducting Energy Effi ciency Potential Studies 
Executive Summary 


This Guide provides information on standard approaches for parties looking to build the policy case for 

energy efficiency, evaluate efficiency as an alternative to supply-side resources, and formulate detailed 

program design plans by understanding the potential for cost-effective energy effi ciency. Policy-makers, 

state officials, utility staff, efficiency advocates, and others can use this information to quantify the 

magnitude of the energy efficiency resource. The Guide is provided to assist in the implementation of the 

National Action Plan for Energy Effi ciency’s five key policy recommendations for creating a sustainable, 

aggressive national commitment to energy effi ciency. 

Importance of Conducting Energy 

Efficiency Potential Studies 

Improving energy effi ciency in our homes, businesses, 

schools, governments, and industries—which consume 

more than 70 percent of the natural gas and electricity 

used in the country—is one of the most constructive, 

cost-effective ways to address the challenges of high 

energy prices, energy security and independence, air 

pollution, and global climate change. Despite these 

benefi ts and the success of energy effi ciency programs 

in some regions of the country, energy effi ciency 

remains critically underutilized in the nation’s energy 

portfolio. It is time to take advantage of more than two 

decades of experience with successful energy effi ciency 

programs, broaden and expand these efforts, and capture the savings that energy effi ciency offers. Conducting a potential study provides key information to inform 

policies and approaches to advance energy effi ciency. 

The National Action Plan for Energy Effi ciency was 

released in July 2006 as a call to action to bring diverse 

stakeholders together at the national, regional, state, 

or utility level, as appropriate, and foster the discussions, decision-making, and commitments necessary to 

take investment in energy effi ciency to a new level. This 

Guide directly supports the Action Plan recommendation to “make a strong, long-term commitment to implement cost-effective energy effi ciency as a resource.” 

A key option to consider under this recommendation is 

establishing the potential for long-term, cost-effective 

energy effi ciency savings (see page 1-2 for a full listing 

of options to consider under each Action Plan recommendation). Conducting a potential study supports 

this option and provides critical data for the design of 

policies and programs aimed at increasing investment in 

energy effi ciency, including: 

• 	Setting attainable energy savings targets. 

• 	Quantifying the energy effi ciency resource for system 

planning. 

• 	Determining funding levels for delivering energy 

effi ciency programs. 

• 	Designing programs to achieve the long-term potential. 

• 	Reassessing energy effi ciency opportunities as conditions change. 

Energy effi ciency potential studies are an effective tool 

for building the policy case for energy effi ciency, evaluating effi ciency as an alternative to supply side resources, and formulating detailed program design plans. 

They are typically the fi rst step taken by entities interested in initiating or expanding a portfolio of effi ciency 

programs, and serve as the analytic basis for efforts 

to treat energy effi ciency as a high-priority resource 

equivalent with supply-side options. 

Potential studies conducted by utilities, state agencies, 

advocacy groups, and other entities consistently fi nd 

that signifi cant gains in cost-effective energy savings 

(e.g., MWh of electricity, MCF of natural gas) and 

capacity (e.g., MW, MCF/day) are currently possible in 

all sectors and regions of the country, and are likely to 

National Action Plan for Energy Effi ciency	 ES-1
continue to be available at low cost in the future. These 

studies show that energy effi ciency can yield more than 

20 percent savings in total electricity demand nationwide by 2025. This is equivalent to reducing the forecast 

growth in electric demand by 50 percent under some 

forecasts (Nadel et al., 2004; NEEP, 2005; SWEEP, 2002). 

Energy effi ciency potential studies can be broadly characterized by how the results are applied in a policy and 

program development context. In each case, the cost 

and time needed to complete a study is directly correlated with the level of detail and accuracy of results. 

This Guide identifi es three main applications for energy 

effi ciency potential studies: 

1. Potential studies that are written with the aim of 

building policy support and making the case for energy effi ciency programs and funding. Usually these 

types of studies are done at a high level of aggregation, and focus on the macro-level societal benefi ts 

of doing effi ciency. 

2. Potential studies that are written with the aim of 

evaluating effi ciency as an alternative to a specifi c 

supply-side project. These types of studies present 

highly accurate estimates of the energy effi ciency 

potential, as they need to provide certainty and foster confi dence in energy resource planners to invest 

in energy effi ciency instead of traditional “steel in 

the ground” resources. 

3. Potential studies that are written with the aim of 

determining how much to spend on effi ciency, and 

how that money can best be spent. These potential 

studies are conducted in situations where the policy 

decision to invest in effi ciency has already been made 

and there is no need to make a case for supporting 

effi ciency. These studies focus more on the disaggregated results (e.g., is there more opportunity in lighting or HVAC?) than other types of potential studies. 

Each of these potential study applications incorporates 

general concepts and steps (discussed in Chapter 3), 

which include potential-type analyzed (technical, economic, or achievable), data collection approaches, level 

of aggregation, expected accuracy of results, and the 

type of output produced. Chapters 4 through 6 describe 

these concepts and steps, briefl y address their implications for study cost and completion time, and provide 

recommendations for how each should be handled in 

the context of the three potential study applications 

(given a state or utility’s overall policy goals). 

After reading this Guide, parties seeking to undertake a 

potential study will better understand: (a) the questions 

to ask to ensure that the appropriate potential study 

Figure ES-1. Considerations for Conducting Potential Studies 

Detailed Planning and Program Design
 High (Single Program) (Program Portfolio)
 

Identifying Alternatives to Medium
 

Supply-Side Investment
 

Building the Case for 


Energy Efficiency
 

Low Medium High 

Cost and Length of Time to Complete 

Level of Detail 

Low

ES-2 Guide for Conducting Energy Effi ciency Potential Studies 
application is selected, (b) the basic approach and steps (c) the types of results and insights that can (and can-


for conducting the study, including the key questions not) be expected, including how potential studies can 


and issues to raise with the analyst doing the work, and be used to advance the Action Plan recommendations.
 

Table ES-1. Key Issues for Selecting a Potential Study Application 

Building a Case for 

Energy Effi ciency 

Identifying 

Alternatives to 

Supply-Side 

Investments 

Detailed Planning 

and Program Design 

Typical Cost* $20,000–$75,000 $75,000–$300,000 $75,000–$500,000 

Estimated 

Time* 1 to 4 months 4 and 12 months 4 and 12 months 

Key Questions • Are we in the process 

of deciding whether 

to invest in effi ciency 

and if so, are we 

deciding how much 

to invest? 

• Is the primary motivation of this study to 

demonstrate the benefi ts of effi ciency and 

build policy support? 

• Can we accept a fairly

high level of aggregation and thus uncertainty in our results? 

• Are the desired 

outputs primarily 

macro-level energy 

and capacity savings, 

and is there a role for 

related economic and 

environmental data? 

• Will this study determine whether energy 

effi ciency can be used 

to defer or eliminate 

plans to build new 

capacity or upgrade 

transmission lines? 

• Are energy effi ciency 

objectives best supported by “investmentgrade” analysis with 

the aim of ensuring 

the future reliability of 

the power system? 

• Are energy effi ciency 

objectives best supported by detailed 

measure-level data? 

Should certain measures (i.e., those that 

provide summer peak 

reductions) be given 

priority? 

• Has the decision to invest in

effi ciency already been made? 

• Are data needed primarily to 

aid in decisions about which 

market sectors, targeted geographic areas, end uses, measures, and programs should 

be tapped to realize effi ciency 

potential? 

• Are study fi ndings intended 

primarily for energy effi ciency 

planners who will incorporate 

the results into portfolio decisions? 

• What is the history of effi ciency programming in this 

area? What effect does this 

history have on the assumptions we make about program 

potential? 

• Should the study focus on one

particular end use, customer 

segment, or set of measures? 

Are data available that can 

give reasonable disaggregated 

results? 

* These ranges should be viewed as approximate. They are based on a sample of studies and are not intended to defi ne the absolute limit of these 

parameters. 

National Action Plan for Energy Effi ciency ES-3

1: Introduction
 

Improving the energy effi ciency of homes, businesses, 

schools, governments, and industries—which consume 

more than 70 percent of the natural gas and electricity 

used in the United States—is one of the most constructive, cost-effective ways to address the challenges of 

high energy prices, energy security and independence, 

air pollution, and global climate change. Mining this 

effi ciency could help us meet on the order of 50 percent 

or more of the expected growth in U.S. consumption 

of electricity and natural gas in the coming decades, 

yielding many billions of dollars in saved energy bills and 

avoiding signifi cant emissions of greenhouse gases and 

other air pollutants.1 

Recognizing this large opportunity, more than 60 leading organizations representing diverse stakeholders 

from across the country joined together to develop the 

National Action Plan for Energy Effi ciency. The Action 

Plan identifi es many of the key barriers contributing to 

underinvestment in energy effi ciency; outlines fi ve key 

policy recommendations for achieving all cost-effective 

energy effi ciency, focusing largely on state-level energy 

effi ciency policies and programs; and provides a number 

of options to consider in pursing these recommendations (Figure 1-1). As of November 2007, nearly 120 

organizations have endorsed the Action Plan recommendations and made public commitments to implement them in their areas. Understanding the potential 

for cost-effective energy effi ciency is key to making the 

Action Plan a reality. 

1.1 Guide for Conducting Energy 

Efficiency Potential Studies 

The Leadership Group of the National Action Plan for 

Energy Efficiency (see Appendix A for a list of group 

members) identified the area of energy effi ciency potential studies as one where additional guidance is needed 

to help parties pursue the recommendations and meet 

their commitments to energy effi ciency. Specifi cally, this 

Guide directly supports the Action Plan recommendation 

to “make a strong, long-term commitment to implement 

cost-effective energy efficiency as a resource.” A key option to consider under this recommendation is establishing 

the potential for long-term, cost-effective energy effi ciency 

savings. Further, this Guide was developed in conjunction 

with and complements other documents prepared as part 

of the Action Plan. 

Potential studies of a state or region inform the comparison of energy efficiency with supply-side options, and 

therefore serve as the analytic basis for implementing four 

key options to consider under the Action Plan: 

• 	Integrate energy effi ciency into utility, state, and 

regional resource planning activities. 

• 	Establish funding requirements for delivering longterm, cost-effective energy effi ciency. 

• 	Develop long-term energy saving goals as part of 

energy planning processes. 

• 	Establish and educate stakeholders on the business 

case for energy effi ciency. 

1.1.1 How to Use This Guide 

This Guide is provided as a resource for implementing the recommendations of the Action Plan. It was 

developed in conjunction with and complements other 

documents prepared as part of the Action Plan. One 

such document is the Guide to Resource Planning with 

Energy Effi ciency (National Action Plan for Energy Effi ciency, 2007), which details how potential studies play 

a critical role in the utility resource planning process. 

The audience for the Guide includes policy-makers, 

state offi cials, utility staff, effi ciency advocates, and 

other entities interested in conducting an energy 

National Action Plan for Energy Effi ciency 1-1
Figure 1-1. National Action Plan for Energy Efficiency Recommendations and Options 

Recognize energy efficiency as a high-priority 

energy resource. 

Options to consider: 

• Establishing policies to establish energy effi ciency as a 

priority resource. 

• Integrating energy effi ciency into utility, state, and regional 

resource planning activities. 

• Quantifying and establishing the value of energy effi ciency, 

considering energy savings, capacity savings, and environmental benefi ts, as appropriate. 

Make a strong, long-term commitment to implement cost-effective energy efficiency as a resource. 

Options to consider: 

• Establishing appropriate cost-effectiveness tests for a 

portfolio of programs to refl ect the long-term benefi ts of 

energy effi ciency. 

• Establishing the potential for long-term, cost-effective 

energy effi ciency savings by customer class through proven 

programs, innovative initiatives, and cutting-edge technologies. 

• Establishing funding requirements for delivering long-term, 

cost-effective energy effi ciency. 

• Developing long-term energy saving goals as part of

energy planning processes. 

• Developing robust measurement and verifi cation procedures. 

• Designating which organization(s) is responsible for administering the energy effi ciency programs. 

• Providing for frequent updates to energy resource plans to 

accommodate new information and technology. 

Broadly communicate the benefits of and opportunities for energy effi ciency. 

Options to consider: 

• Establishing and educating stakeholders on the business

case for energy effi ciency at the state, utility, and other 

appropriate level, addressing relevant customer, utility, and 

societal perspectives. 

• Communicating the role of energy effi ciency in lowering 

customer energy bills and system costs and risks over time. 

• Communicating the role of building codes, appliance standards, and tax and other incentives. 

Provide sufficient, timely, and stable program 

funding to deliver energy effi ciency where 

cost-effective. 

Options to consider: 

• Deciding on and committing to a consistent way for

program administrators to recover energy effi ciency 

costs in a timely manner. 

• Establishing funding mechanisms for energy effi ciency 

from among the available options, such as revenue 

requirement or resource procurement funding, system 

benefi ts charges, rate-basing, shared-savings, and 

incentive mechanisms. 

• Establishing funding for multi-year period.

Modify policies to align utility incentives with 

the delivery of cost-effective energy effi ciency 

and modify ratemaking practices to promote 

energy effi ciency investments. 

Options to consider: 

• Addressing the typical utility throughput incentive and 

removing other regulatory and management disincentives to energy effi ciency. 

• Providing utility incentives for the successful management of energy effi ciency programs. 

• Including the impact on adoption of energy effi ciency 

as one of the goals of retail rate design, recognizing 

that it must be balanced with other objectives. 

• Eliminating rate designs that discourage energy effi ciency by not increasing costs as customers consume 

more electricity or natural gas. 

• Adopting rate designs that encourage energy effi ciency 

by considering the unique characteristics of each customer class and including partnering tariffs with other 

mechanisms that encourage energy effi ciency, such as 

benefi t-sharing programs and on-bill fi nancing. 

Source: National Action Plan for Energy Effi ciency, 2006. 

1-2 Guide for Conducting Energy Effi ciency Potential Studies 
effi ciency potential study for the purpose of initiating or 

expanding a portfolio of effi ciency programs. It will also 

be useful for regulators, legislators, and other decisionmakers tasked with overseeing utilities and assessing 

the merits of a particular energy effi ciency approach 

or outcome. The Guide provides answers to—or the 

information needed to develop answers to—the following questions: 

• 	What is a potential study? 

• 	What objectives are met by a potential study? 

• 	Do I need to conduct or commission a potential study 

for my jurisdiction? 

• 	What are the key steps in conducting a potential 

study? 

• 	What are the likely costs of different types of potential studies, and what are the pros and cons of each? 

• 	Based on stated objectives, what type of potential 

study should I conduct or commission? What should 

its boundaries and analytical parameters be? 

The Guide is “policy-neutral” such that it can be applied to energy effi ciency programs irrespective of their 

policy objectives and constraints. The Guide lays out a 

basic potential study structure and methodology while 

fl agging issues that need to be addressed in specifi c 

circumstances. Chapters 2 and 3 present key topics 

and approaches applicable to all potential studies. They 

defi ne the types of potential that are typically analyzed 

and the expected range of results from each. They also 

summarize the most important steps in performing a 

potential study. The Guide also identifi es three contexts 

for application of potential studies. Chapters 4 through 

6 identify specifi c approaches and provide guidance for 

each step in relation to these three study applications. 

Case studies are used to illustrate best practices, with 

pros and cons of different methods presented so that 

users can make the best decision for their circumstances. Chapter 7 summarizes the discussion and identifi es 

important considerations in conducting a potential 

study. Appendix C provides a detailed discussion on 

potential study methodology. 

Note that this guide is not intended to give the general 

reader enough information to conduct a potential study 

on their own. Rather, we hope that after reviewing this 

document, the reader will be able to participate in efforts to plan for, contract for, contribute to, and review 

the results of potential studies. Where potential studies 

are conducted, the reader should be able to effectively 

collaborate with the entity doing the work. To this end, 

specifi c “questions for the analyst” are provided at the 

beginning of Chapters 4 through 6. 

1.1.2 Structure of the Guide 

This document presents much of its information in the 

context of several example studies. To avoid repetition, 

different aspects of conducting a potential study are 

emphasized in Chapters 4 through 6. Appendix C repeats 

much of this information in a more linear fashion that 

does not rely on the examples in the main text, while Appendix D contains a list of common data sources used for 

potential studies and a short description of each. Appendix E provides short descriptions of 17 recent potential 

studies, with Web links where available. 

1.1.3 Development of the Guide 

The Guide is a key product of the Year Two Work Plan 

for the National Action Plan for Energy Effi ciency. This 

work plan was developed based on feedback from Action Plan Leadership Group members and observers during the fall of 2006. The work plan was further refi ned 

during the March 2007 Leadership Group meeting in 

Washington, D.C. A full list of Leadership Group members is provided in Appendix A. 

Philip Mosenthal of Optimal Energy, Inc., served as 

project manager and co-authored the Guide along with 

Jeffrey Loiter, under contract to the U.S. Environmental 

Protection Agency. 

1.2 Notes 

1. 	 See the National Action Plan for Energy Effi ciency (2006), available at <www.epa.gov/cleanenergy/actionplan/report.htm>. 

National Action Plan for Energy Effi ciency 1-3

Energy Effi ciency Potential 2: Studies as a Policy Tool 

This chapter of the Guide explains why conducting potential studies is a critical best practice for establishing energy efficiency as a first-priority resource, and describes how such studies can serve as the 

quantitative basis for actions aimed at achieving the Action Plan’s recommendations. 

2.1 What Is a Potential Study? 

Simply put, a potential study is a quantitative analysis 

of the amount of energy savings that either exists, is 

cost-effective, or could be realized through the implementation of energy effi ciency programs and policies. 

The Action Plan notes that “potential studies illuminate 

the nature of the energy effi ciency resource, and can be 

used by legislators and regulators to inform effi ciency 

policy and programs.”1 The boundaries of a potential 

study can be as small as a neighborhood experiencing 

transmission or distribution constraints, or as large as an 

entire region of the country. The study may consider all 

sectors of the economy or focus on a particular industry 

or type of energy-user. It may focus solely on electricity, 

natural gas, or another fuel or provide a comprehensive 

look at all energy consumption. As with any analysis 

used to support public policy, the scope of the study 

depends on the question being answered. 

2.2 Definition of Key Terms 

As in any field of study, energy efficiency practitioners use 

a vocabulary of terms with generally accepted meanings to 

convey their ideas, methods, and results. The following list 

defines some of the key terms used in this guide. 

• 	Energy effi ciency: using less energy to provide the 

same or an improved level of service to the energy 

consumer in an economically effi cient way. Sometimes “conservation” is used as a synonym, but that 

term is usually taken to mean using less of a resource 

even if this results in a lower service level (e.g., setting a thermostat lower or reducing lighting levels). 

The Action Plan recognizes that energy effi ciency 

includes using less energy at any time, including at 

times of peak demand through demand response and 

peak shaving efforts. 

• 	Measure: any action taken to increase effi ciency, 

whether through changes in equipment, control 

strategies, or behavior. Examples are higher-effi ciency 

central air conditioners, occupancy sensor control 

of lighting, and retro-commissioning. In some cases, 

bundles of technologies or practices may be modeled 

as single measures. For example, an ENERGY STARTM 

home package may be treated as a single measure. 

• 	Program: a mechanism for encouraging energy 

effi ciency. May be funded by a variety of sources and 

pursued by a wide range of approaches. Typically 

includes multiple measures.2 

• 	End-use: a category of equipment or service that 

consumes energy (e.g., lighting, refrigeration, heating, process heat). 

• 	Cost-effectiveness: a measure of the relevant economic effects resulting from the implementation of an 

energy effi ciency measure. If the benefi ts outweigh the 

cost, the measure is said to be cost-effective. 

• 	Lost-opportunity: refers to an effi ciency measure 

or effi ciency program that seeks to encourage the 

selection of higher-effi ciency equipment or building 

practices than would typically be chosen at the time 

of a purchase or design decision. 

• 	Retrofi t: refers to an effi ciency measure or effi ­

ciency program that seeks to encourage the replacement of functional equipment before the end of its 

operating life with higher-effi ciency units (also called 

“early retirement”) or the installation of additional 

National Action Plan for Energy Effi ciency 2-1
controls, equipment, or materials in existing facilities 

for purposes of reducing energy consumption (e.g., 

increased insulation, lighting occupancy controls, 

economizer ventilation systems). 

2.3 Potential Studies as Policy Tool
 

Potential studies can serve multiple objectives in support 

of efforts to advance a long-term commitment to costeffective energy effi ciency. Their results provide critical 

input for the design of policies and programs aimed at 

increasing the penetration of effi ciency, including: 

• 	Setting attainable energy savings targets. 

• 	Quantifying the energy effi ciency resource for system 

planning. 

• 	Determining a funding level for delivering energy 

effi ciency programs. 

• 	Designing programs to achieve the long-term potential. 

• 	Reassessing energy effi ciency opportunities as conditions change. 

The type of report and analysis methodology will vary 

depending on the ultimate goal or objective, so it is 

important to have a clear idea of the objectives of the 

study and type of information needed before beginning 

the analysis. This section describes three applications for 

which a potential study can inform policy decisions: 

• 	Building a case for investment in energy effi ciency. 

• 	Identifying alternatives for supply-side investments. 

• 	Detailed effi ciency program design and planning. 

These were chosen because the studies that result from 

these objectives cover a range of approaches, levels of 

detail, and costs. They also represent the majority of 

studies conducted. For each, we touch on some of the 

concepts discussed in greater detail later on, such as the 

level of detail of the potential study and whether sitespecifi c data are gathered to support the potential analysis. In general, the greater the detail and data needs 

for a study, the greater the specifi city of the results and 

the greater the cost and time to complete a study. The 

fi gure below depicts this relationship graphically, placing 

the three potential study scenarios in context with one 

another. 

2.3.1 Building a Case for Effi ciency Investment 

Potential studies are most frequently used either to 

make the initial case for energy effi ciency programs and 

effi ciency portfolio investments or to support continued 

(and possibly increased) funding of existing programs. 

In this situation, a study seeks to answer the two-part 

question of whether to invest in effi ciency and if so, 

Figure 2-1. Considerations for Conducting Potential Studies 

Detailed Planning and Program Design
 High (Single Program) (Program Portfolio)
 

Level of Detail

Medium 

Building the Case for Low Energy Efficiency 

Low 

Identifying Alternatives to 

Supply-Side Investment 

Medium High 

Cost and Length of Time to Complete 

2-2 Guide for Conducting Energy Effi ciency Potential Studies 
how much to invest.3 To support this objective, decision-makers need to understand the overall magnitude 

of the effi ciency resource and the associated costs and 

benefi ts. The analysis in this case focuses on providing 

a reasonable estimate of effi ciency potential at a high 

level4 of aggregation. Results from these studies are 

typically used to establish the magnitude of effi ciency 

opportunities and to support high-level decisions on 

funding levels for effi ciency portfolios. While the level 

of funding allocated to effi ciency programs is ultimately 

a political decision, a potential study can help all stakeholders to clearly see the possibilities. 

In many cases, needlessly detailed and expensive studies 

are performed where simpler analyses would suffi ce. For 

example, if available program funding (whether proposed 

or currently available) will only support a modest level of 

effi ciency investment, a high-level study conducted for a 

relatively modest budget will typically provide the necessary information to support policy decisions (see Section 

3.4). In cases where jurisdictions are beginning to pursue a high percentage of effi ciency opportunities, more 

detailed studies may be necessary to refi ne estimates of 

cost-effective spending levels as well as to provide information on the remaining effi ciency opportunities. 

2.3.2 Identifying Alternatives to Supply-Side 

Investments 

Energy effi ciency is increasingly being considered as an 

alternative to supply-side investment in generation or 

transmission resources, especially in the context of reliability constraints. In cases where parties wish to understand the relative magnitude of the effi ciency potential 

and whether it can defer alternative investments, a 

potential study can answer the question: Can effi ciency 

displace needed investments in supply-side or transmission resources? Investment decisions, especially those regarding investments to meet future reliability, may require 

a more detailed potential study than under the previous 

scenario. These studies typically focus on a specifi c set 

of conditions (e.g., geographic area, customer loads) to 

facilitate comparison with alternative solutions. Ideally, 

the methodology is based on detailed, site-specifi c data 

to support investment-grade analysis. Such a potential 

study is designed to produce estimates of what can be 

accomplished from a specifi c program design, rather 

than on generally aggressive effi ciency investments. 

2.3.3 Detailed Planning and Program Design 

In some cases, policy-makers have decided to invest in 

effi ciency and need guidance on which market sectors, 

targeted geographic areas, end uses, measures, and 

programs should be tapped to realize the effi ciency 

potential in their regions of interest. For example, when 

dealing with equity issues, a policy-maker may wish to 

fully understand the level of cost-effective effi ciency 

investment that can be achieved in the low-income sector. It may also be desirable to establish specifi c savings, 

spending, or net benefi ts goals for one or more market 

segments (e.g., new construction). For this purpose, 

detailed potential studies are needed to describe the effi ciency potential by specifi c characteristics or to analyze 

various program options for the purpose of understanding additional opportunities for effi ciency. Very detailed 

studies may be warranted to determine the magnitude 

and economics of specifi c measures, market segments, 

or detailed program designs. A greater level of segmentation generally requires a more detailed and expensive 

study. The effort required for a greater level of detail 

may be offset by limiting the analysis to one or a few 

program concepts or market sectors, rather than addressing all effi ciency opportunities. 

2.4 Types of Effi ciency Potential 

Energy effi ciency practitioners often distinguish between four different types of effi ciency potential 

analysis: technical, economic, achievable, and program. Still, there are often important defi nitional issues 

between studies, and terms are used in different ways 

by different people. Therefore, it is important when 

reviewing studies to fully understand the defi nition and 

scope that applies to any given estimate. Below are 

typical defi nitions of these terms. The fi rst two types of 

studies—technical and economic—provide a theoretical 

upper bound of existing effi ciency resources. Even the 

best-designed portfolio of programs, with unlimited 

funding, will not capture 100 percent of the technical 

or economic potential. The latter two types—achievable 

National Action Plan for Energy Effi ciency 2-3
and program—tend to be more useful in that they 

estimate what can actually be achieved, when it can be 

captured, and how much it will cost to do so. 

• 	Technical potential is the theoretical maximum 

amount of energy use that could be displaced by effi ­

ciency, disregarding all non-engineering constraints such 

as cost-effectiveness and the willingness of end-users to 

adopt the efficiency measures. It is often estimated as a 

“snapshot” in time assuming immediate implementation of all technologically feasible energy saving measures, with additional efficiency opportunities assumed 

as they arise from activities such as new construction. 

• 	Economic potential refers to the subset of the technical potential that is economically cost-effective as 

compared to conventional supply-side energy resources. Both technical and economic potential are theoretical numbers that assume immediate implementation 

of effi ciency measures, with no regard for the gradual 

“ramping up” process of real-life programs. In addition, they ignore market barriers to ensuring actual 

implementation of effi ciency. Finally, they only consider 

the costs of effi ciency measures themselves, ignoring 

any programmatic costs (e.g., marketing, analysis, administration) that would be necessary to capture them. 

• 	Achievable potential is the amount of energy use 

that effi ciency can realistically be expected to displace 

assuming the most aggressive program scenario 

possible (e.g., providing end-users with payments 

for the entire incremental cost of more effi ciency 

equipment). This is often referred to as maximum 

achievable potential. Achievable potential takes into 

account real-world barriers to convincing end-users 

to adopt effi ciency measures, the non-measure costs 

of delivering programs (for administration, marketing, 

tracking systems, monitoring and evaluation, etc.), 

and the capability of programs and administrators to 

ramp up program activity over time.5 

• 	Program potential refers to the effi ciency potential 

possible given specifi c program funding levels and 

designs. Often, program potential studies are referred 

to as “achievable” in contrast to “maximum achievable.” In effect, they estimate the achievable potential 

from a given set of programs and funding. Program 

potential studies can consider scenarios ranging from 

a single program to a full portfolio of programs. A typical potential study may report a range of results based 

on different program funding levels. 

Variations exist on the above definitions. For example, 

most studies consider achievable potential as a subset 

of economic potential, but some studies consider it as a 

subset of technical potential. The rationale for this is that 

as avoided costs and measure costs change over time, 

non-cost-effective measures may become economical. 

Maximum technically achievable would be a more informative term for such a view. This is especially true when 

considering efficiency resources as an alternative to defer 

or replace substantial new supply-side investment. In this 

case, what is economical may not be known until the 

magnitude of efficiency is established and components or 

new supply-side investments can be analyzed to determine 

the potential cost and benefits of deferral. Finally, we note 

that in reality, potential exists along a continuum rather 

than in discrete steps. While the terms defi ned above 

facilitate discussion and comparison of different studies, 

it is important to understand the scope of the particular 

definition of potential in use for any given study. 

2.5 Review of Results from 


Previous Potential Studies
 

There have been numerous potential studies released in 

the past decade covering regions throughout the United 

States and Canada. The tables below summarize the 

technical, economic, and achievable potential found in 

21 studies, 19 of which are from the United States.6 It 

is important to note that the studies vary in their scope, 

objectives, methodology, time horizon, and defi nitions. 

This is especially true in regard to achievable potential. 

Some studies defi ne this as the maximum potential 

that could be captured assuming infi nite budget (i.e., 

100 percent of incremental effi ciency costs covered by 

incentives, as well as aggressive marketing and other 

supporting initiatives). Other studies defi ne achievable 

potential as that which could reasonably be captured 

through likely policies or specifi c funding constraints. 

2-4 Guide for Conducting Energy Effi ciency Potential Studies 
Regardless of defi nition, the results reported in the 

tables as “achievable” are those for the most aggressive 

program evaluated in that study. 

Despite the differences, it is informative to compare the 

range of results found in these studies. To provide some 

context for these values, reaching the maximum achievable potential (i.e., approaching the total economic 

potential) of between 20 and 30 percent would require 

effi ciency spending in excess of 5 percent of utility revenue. Historically, this has been beyond levels pursued 

by even the most aggressive jurisdictions and has not 

been accomplished except in a few limited instances. 

Tables 2-1 and 2-2 present detailed results for 

specifi c studies for both electric and natural gas 

potential, respectively.7 Recognize that the wide divergence of results tends to have more to do with the 

scope, comprehensiveness of the studies, and timeframe 

rather than the different regions considered. For example, 

the number of measures analyzed can vary widely from 

study to study, from less than 20 to over 1,000. Some 

studies may eliminate new construction, early retirement, 

or other important markets. In addition, many studies 

will use simplifi ed methods for economic screening or for 

factors such as equipment stock adjustments that can 

bias results. While the potential in each region is infl uenced by the climate and mix of customers (e.g., prominent industrial sectors), the overall percentage of savings 

potential does not vary dramatically. For many effi ciency 

technologies, the percentage energy savings is only minimally dependent on operating conditions. For example, 

higher effi ciency cooling equipment may save, say, 15 

percent of cooling energy used by commercial buildings, 

regardless of climate. In warmer climates, where more 

energy is used for cooling, the total energy savings in 

MWh will be higher than in cooler climates. 

Table 2-1. Sample of Natural Gas Savings Potential Studies 

Area(s) Covered Author(s) Year Completed Type of Savings 

Potential 

Total Gas 

Reduction as a 

% of Sales 

Years to 

Achieve 

Estimated 

Savings 

Potential 

California ACEEE 2003 Technical 

Economic 

Max. Achievable 

35% 

21% 

9% 

20 

Georgia ICF 2000 Technical 

Economic 

Max. Achievable 

10% 

11% 

1.8–5.5% 

5 

Iowa ORNL 2001 Max. Achievable 3.7% 15 

Midwest ACEEE 2003 Max. Achievable 9.30% 20 

Midwest Quantec 2005 Technical 

Max. Achievable 

46.6% 

25.2% 

20 

New York OEI/VEIC/ACEEE 2002 Economic 

Max. Achievable 

28% 

1.5% 

5 

Utah GDS/Quantum 2004 Technical 

Max. Achievable 

38% 

20% 

10 

National Action Plan for Energy Effi ciency 2-5
Table 2-2. Sample of Electricity Savings Potential Studies

Area(s)

Covered 

Author(s) Year

Completed 

Type of

Savings

Potential 

Estimated Consumption Savings as

% of Sales 

Estimated

Summer Peak

Demand

Savings as

% of Total 

Capacity 

Years to 

Achieve

Estimated

Savings

Potential 

Comments 

Res. Comm. Indus. Total 

NewBrunswick 

Énergie NBPower 

2004 Technical

EconomicEconomic 

32%7%3% 

32%14%6% 

13%12%1% 

24%10%3% 

N.A. 17 Includes fuel

switching;excludes street lights 

BritishColumbia 

BC Hydro 2002 Economic

Max.Achievable 

17%4% 

17%4% 

27%11% 

N.A. N.A. 9 

California Xenergy 2002 Technical 

EconomicMax.AchievableBudgetConstrained 

21%15%10%8% 

17%13%13%7% 

13%12%11%4% 

19%14%10%6% 

25%16%10%6% 

10 Integrated

measures not addressed; agriculture included in industrial sector 

Manitoba Manitoba

Hydro 

2002 Economic

Max.Achievable 

19%4% 

19%6% 

5%1% 

N.A. N.A. 9 Apartment

buildingsincluded incommercial 

Midwest ACEEE 2003 Max.

Achievable 

N.A. N.A. N.A. 11% N.A. 20 

New Mexico Itron 2006 Max.

Achievable 

N.A. N.A. N.A. 8% 8.90% 10 

Connecticut GDS

Associates/QuantumConsulting 

2003 Technical

Max.Achievable 

24%13% 

25%14% 

20%13% 

24%13% 

24%13% 

10 Also includes

results for Southwest CTregion 

2-6 Guide for Conducting Energy Effi ciency Potential Studies 
Table 2-2. Sample of Electricity Savings Potential Studies

Area(s)

Covered 

Author(s) Year

Completed 

Type of

Savings

Potential 

Estimated Consumption Savings as

% of Sales 

Estimated

Summer Peak

Demand

Savings as

% of Total 

Capacity 

Years to 

Achieve

Estimated

Savings

Potential 

Comments 

Res. Comm. Indus. Total 

Georgia ICF 2005 Technical 

EconomicMax.Achievable 

N.A. N.A. N.A. 29%

20%2.3%–8.7% 

33%18%1.8%–5.5% 

5 

Illinois ACEEE 1998 Achievable N.A. N.A. N.A. 43% N.A. 20 Iowa ORNL 2001 Max.

Achievable 

5.3% 5.1% 6% 5.4% N.A. 15 

Massachusetts RLW 

Analytics/SFMC 

2001 Economic

BudgetConstrained 

31%5% 

21% N.A. 24%

5% 

N.A. 5 Excludes nonutility impacts

and lowincome 

New York OEI/VEIC/

ACEEE 

2002 Technical 

Economic 

37%26% 

41%38% 

22%16% 

37%30% 

N.A. 10 A lso 5- and

20-yearscenarios 

Ontario ICF 2005 Technical 

Economic 

N.A. N.A. N.A. 26%

21% 

33%21% 

20 

Oregon Technical 2003 Ecotope/

ACEEE/Tellus 

28% 32% 35% 31% N.A. 10 Residential

includesmanufactured housing 

Puget SoundRegion 

PugetSoundEnergy 

2003 Max.

TechnicallyAchievableMax.EconomicallyAchievable 

17%7% 

7%6% 

0%0% 

12%6% 

33%11% 

20 

(continued) 

National Action Plan for Energy Effi ciency 2-7
Table 2-2. Sample of Electricity Savings Potential Studies

Area(s)

Covered 

Author(s) Year

Completed 

Type of

Savings

Potential 

Estimated Consumption Savings as

% of Sales 

Estimated

Summer Peak

Demand

Savings as

% of Total 

Capacity 

Years to 

Achieve

Estimated

Savings

Potential 

Comments 

Res. Comm. Indus. Total 

Quebec OEI/VEIC 2004 Max.

TechnicallyAchievableMax.EconomicallyAchievable 

8%2% 

19%6% 

1%1% 

7%3% 

N.A. 8 Residential

sales includefarms; nofarm savingsestimated 

Texas OEI 2007 Max.

Achievable 

N.A. N.A. N.A. 20% 22% 15 

Utah Tellus 

Institue 

2001 Max.

Achievable 

N.A. N.A. N.A. 9% N.A. 6 

Vermont OEI/VEIC 2002 Max.

TechnicallyAchievable 

30% 32% 31% 37% 10 Includes fuel

switching;also 5-yearscenario 

VELCO OEI/VEIC 2002 Max.

Achievable 

18% 17% 23% 23% 10 Excludes

measures with littlepeak demand,that require regional coordination, and emergingtechnologies;includes fuelswitching;also 5-yearscenario 

(continued) 

2-8 Guide for Conducting Energy Effi ciency Potential Studies 
Table 2-2. Sample of Electricity Savings Potential Studies

Area(s)

Covered 

Author(s) Year

Completed 

Type of

Savings

Potential 

Estimated Consumption Savings as

% of Sales 

Estimated

Summer Peak

Demand

Savings as

% of Total 

Capacity 

Years to 

Achieve

Estimated

Savings

Potential 

Comments 

Res. Comm. Indus. Total 

AZ,CO,NV,NM,UT,WY 

SWEEP/ACEEE/Tellus 

2002 Max.

Achievable 

14% 20% 19% 18% N.A. 8 Also 18-year

scenario 

NY, NJ, PA ACEEE 1997 Max.

Achievable 

35% 35% 41% N.A. N.A. 14 Residential

savings are for all fuels, notjust electricity 

(continued) 

National Action Plan for Energy Effi ciency 2-9
2.6 Notes
 

1. 	 National Action Plan for Energy Effi ciency (2006), pp. 6-15. 

2. 	 Projects, one or more measures at a single facility or site, are also 

aggregated into programs. Considerations at the measure level 

are most applicable to potential studies. 

3. 	 These questions may arise from a variety of policy, economic, or 

energy supply needs. For example, one might wish to understand the potential role of energy effi ciency in meeting emissions reduction targets or energy portfolio standards such as the 

Regional Greenhouse Gas Initiative. 

4. 	 Note that the term “high-level” is used as in “a high-level view.” 

It implies a lesser level of detail, not greater. 

5. 	 Maximum achievable potential generally refers to assuming the 

most aggressive, fully funded programs possible. However, studies 

will sometimes refer to achievable potential while estimating the 

savings from a less aggressive strategy (e.g., programs that are 

limited to funding a fraction of the cost of effi ciency measures). 

These funding- or program-constrained scenarios may more 

closely represent program potential as defi ned here. 

6. 	 In some cases, achievable potential is for a limited funding or 

program scenario and more closely refl ects what this document 

refers to as “program potential.” 

7. 	 Potential studies, like many quantitative policy analyses, have a 

“useful life” determined in part by changes in the markets, technologies, and demographic entities being analyzed. For example, 

future changes in appliance standards not captured in a potential 

study may dramatically alter the savings available from an appliance program. On the other hand, the effi ciency of the best units 

continues to improve with new technologies, creating additional 

effi ciency opportunities between the new, higher effi ciency level 

and the new, higher baseline. 

2-10 Guide for Conducting Energy Effi ciency Potential Studies 
General Concepts and
 

Steps to Completing
 3: a Potential Study 

This chapter of the Guide describes general concepts relevant to completing a potential study and breaks 

the process down into five broad steps: (1) identify the objective and the audience, (2) select the potential type(s) to analyze, (3) determine the appropriate level of detail, (4) select and define the methodology, and (5) present the results. The specifics of these five steps need to be explored with or communicated to the entity performing the study. The general information provided in this chapter informs this 

process, and is supplemented with “questions for the analyst” listed at the beginning of Chapters 4, 5, 

and 6. The concepts introduced here are expanded upon in these subsequent chapters. 

3.1 Identify the Objective and the 

Audience 

There are a number of different objectives for undertaking a potential study, each with important implications 

for the necessary rigor and cost of the study. Clearly 

identifying the objective and the desired results is the 

necessary fi rst step in planning a study. Where there 

are multiple and perhaps competing objectives, there 

should be an attempt to reach consensus as to which 

objective is most important. This will facilitate decisions 

regarding any analytical trade-offs that become necessary as a result of limitations in data, resources, or time 

available to undertake the study. 

The audience for a potential study can inform the 

analytical methods and data used to produce the fi nal 

report. Typically, the audience is closely related to the 

objective, and may be implicitly or explicitly defi ned 

once the objectives are determined. Regardless, specifi c 

attention should be paid to the needs of the audience. Since potential studies often look 10 or 20 years 

into the future, questions arise as to the reliability and 

trustworthiness of the data and results. For this reason, 

audiences should be consulted to determine what data 

sources they trust, what issues need addressing, and 

what level of detail they require. In some cases, a formal 

advisory board of stakeholders or a collaborative may be 

formed to guide or manage the study. 

3.2 Select Potential Type(s) to 

Analyze 

Estimates of technical and economic potential are 

independent of the efforts necessary to actually capture 

that potential. As described above, technical potential 

is the maximum amount of energy use that could be 

displaced by effi ciency, assuming immediate implementation of all technically feasible energy-saving measures. 

This includes, for example, the replacement of every 

incandescent bulb with a compact fl uorescent lamp 

or high-effi ciency fi xture, regardless of cost. Considerations of initiative strategies, performance, willingness 

of end-users to adopt technologies, or budget do not 

affect this potential estimate. Economic potential can 

then be determined by factoring in the measure cost. 

Because of the disconnect between implementation 

issues and estimates of technical and economic potential, these potential estimates do little more than set 

the context for estimates of achievable and program 

potential, or for actual program results. Technical potential in particular has little bearing on decision-making, 

as failure to meet standard cost-effectiveness tests (i.e., 

economic potential) generally excludes opportunities 

from inclusion in actual implemented effi ciency programs. Economic potential estimates do not include 

initiative budgets, do not provide likely timelines of 

energy effi ciency acquisition, and do not represent 

quantities of effi ciency that can actually be acquired. As 

a result, technical and economic potential studies are of 

National Action Plan for Energy Effi ciency 3-1
limited value for planning purposes. While they set the 

theoretical upper bound for effi ciency, they cannot be 

readily captured. 

In most cases, policy-makers should consider foregoing 

technical potential analyses altogether. In practice, most 

technical and economic potential studies generate very 

similar estimates. Because analysts generally pre-screen 

possible effi ciency technologies and practices based 

on an understanding of which measures are likely to 

be cost-effective, most measures that are technically 

feasible but very unlikely to pass a cost-effectiveness 

screening will not be included in the analysis in the interest of conserving time and effort for other aspects of 

the analysis. This results in the technical potential being 

virtually the same as the economic potential. 

It may be more diffi cult to determine where along the 

continuum of potential studies to focus efforts for a particular objective. Chapters 4 through 6 discuss this issue 

with respect to the examples presented and the objective 

of the study. The type of potential analyzed should be 

chosen to best support the objectives of the work. 

3.3 Determine Appropriate Level 

of Detail and Assess Data Requirements 

This section describes two related activities in planning a 

potential study: selecting a level of detail and gathering 

the data necessary to support the study. These activities 

are discussed separately here, but in reality the analyst 

will likely consider them simultaneously, with each infl uencing the other. Some iteration may also be required; if 

the analyst does not fi nd appropriate data sources, she 

may need to modify the level of detail for the study. For 

more information on data sources, see Appendix D. 

3.3.1 Level of Detail 

Energy effi ciency potential studies can be conducted 

at a range of detail levels. There are, of course, cost 

implications for this—many high-level energy effi ciency 

potential studies can be completed for under $50,000 

in total costs, while more detailed potential studies can 

cost anywhere from $200,000 to $1 million depending 

upon the geographic area in question, the degree to 

which results are segmented, and the level of detail and 

data collection required.1 Ultimately, the level of detail 

should be driven by the study objectives. High-level 

studies can drive “yes/no” policy decisions and/or rough 

budget allocations, while more detailed potential studies give shape to or refi ne existing effi ciency efforts. 

The level of detail of a potential study might also be 

driven by data availability. As discussed below, a wide 

range of data are needed to support a potential study. 

While information is generally available to disaggregate 

electricity or natural gas sales into residential, commercial, and industrial sectors, the data needed to further 

disaggregate sales into building types or end-uses are 

more diffi cult to obtain.2 Information on current standard (“baseline”) practices and penetrations of effi ­

ciency measures may also be scarce. Decision-makers 

may wish to pursue a high-level study in the absence of 

fully disaggregated sales data, as a more detailed study 

would imply a false level of precision. 

When data are not available to support a detailed and 

disaggregated study, primary research may be conducted. This will typically take the form of onsite data 

collection from a sampling of different building types, 

along with modeling. This type of effort can signifi ­

cantly refi ne baseline assumptions and accuracy, but at 

substantial cost. These types of detailed studies tend to 

cost in the $500,000 to $1 million range. 

If the costs or time required for primary research are 

prohibitive, studies typically rely on secondary research 

data.3 In this case, detailed studies from neighboring 

regions or similar market segments may be used as a 

proxy for the actual region or segment being analyzed. 

With appropriate adjustments and careful selection of 

comparison areas, this can provide a fairly high level of 

accuracy. However, one must ensure that they fully understand the data being used, how they were collected, 

and whether they introduce bias into the analysis. 

3-2 Guide For Conducting Energy Effi ciency Potential Studies 
3.3.2 Common Data Sources 

The quality and availability of data is often the limiting 

factor of a potential study and drives the methods used. 

Data issues can drive the cost of the potential study as 

well as limit its possible scope. Detailed potential studies 

must include data in the following areas: 

• Baseline end-use and effi ciency data. 

• Energy forecasts. 

• Measure costs and savings as well as measure life. 

• Sales disaggregation information. 

As described below, all of these data can be found with 

varying levels of ease and reliability. Data collection is 

one major additional cost in performing a detailed study 

over a high-level study. 

In general, good-state level end-use data are not readily 

available and must be patched together using a variety 

of different sources. The Energy Information Agency 

(EIA) of the U.S. Department of Energy (<http://www. 

eia.doe.gov>) publishes three surveys about energy 

consumption in the major sectors of the economy: The 

Residential Energy Consumption Survey (RECS), 

Manufacturing Energy Consumption Survey 

(MECS), and Commercial Building Energy Consumption Survey (CBECS).4 While these surveys contain a 

wealth of information on energy use by different types 

of buildings sorted by a variety of characteristics (e.g., 

energy use by commercial buildings, by number of 

fl oors in the building), they have two primary limitations. First, they only provide data aggregated at either 

the level of four Census regions or nine Census divisions. (They also provide data for the four most populous states: California, Florida, New York, and Texas.) 

Second, while they give the total energy use sorted by 

end-use characteristics, current versions of the surveys 

do not provide the energy consumption associated with 

that end-use. For example, while RECS presents the 

total electricity consumed by houses that have central 

air conditioning, it does not provide data on how much 

of that electricity is consumed by the air conditioning 

system. Some older versions of the survey do provide 

this type of information, but these data are several years 

old and should be used with caution, as the effi ciency 

and characteristics of some major energy-consuming 

equipment has changed dramatically over time. 

Some household data are available at much fi ner resolution than in RECS from the U.S. Bureau of the Census 

(<http://www.census.gov>). The U.S. Census Fact Finder 

allows users to access census data tables by geographic 

location and attribute, including profi les of selected 

social, economic, and housing characteristics. Housing 

characteristics include units in structure, year structure 

built, number of rooms, and type of heating fuel. Census data are particularly helpful for determining both 

the relative number of single-family vs. multi-family 

structures and for accessing historical data that may 

inform forecasts of new residential construction activity. 

Energy profi les that provide hourly end-use data on 

energy consumption by building type can be purchased 

from businesses specializing in these data. Typically 

available at the state level and for major metropolitan 

areas, these datasets are usually the result of many 

thousands of energy audits conducted on commercial, 

industrial, and residential buildings throughout the 

United States. Energy profi les are particularly important 

for determining the effect of energy savings on peak 

system loads and for distributing energy savings into 

different energy use periods (e.g., seasonal peak hours, 

daily peak hours). Another source of energy profi les are 

existing effi ciency programs. Long-established programs 

at large utilities occasionally conducted evaluation studies on their customers and may have generated data 

on customer load-shapes and energy use profi les. Care 

must be taken when using older studies, as energy use 

patterns have changed over time. 

The EIA is also a source of energy forecast data. The 

Annual Energy Outlook provides forecasts of energy 

consumption by sector for the nine census divisions as 

well as by Electricity Market Module Region, which disaggregates the data into 12 regions covered by electric 

coordinating organizations. A different report, Electric 

Power Annual, contains historical data and a forecast, 

although the forecast is for fewer years than found in 

the Energy Outlook. Public utility commissions often 

have forecasts for their states, and most utilities have 

National Action Plan for Energy Effi ciency 3-3
forecasts for their service territories. The analyst should 

consider all of the potential data sources and develop 

a supportable forecast. For past years, energy sales can 

often be disaggregated into building type based on 

historical data from the utilities or states’ public utility 

commissions. 

For current year data, forecasts of economic growth are 

often used. These forecasts can also help derive important information about the relative importance of end 

use sales in future years. It may be, for example, that 

over the 10-year study period, computers and televisions use more and more energy, while at the same 

time more and more people replace their old refrigerators with newer, more effi cient models. It is important 

that these shifts in the relative importance of end-use 

sales be captured in the energy forecast. Economic 

forecasts are available from several public and private 

sources. 

Some publicly available data exist on measure savings 

and costs. For example, the DEER database (<http:// 

www.calmac.org>) provides estimated incremental costs 

in California from a variety of measures culled from 

utility program databases. Commercial construction cost 

publications such as those by the construction trades 

can be a source of measure installation labor costs and 

are often used by contractors to estimate construction 

budgets. 

In general, the above national public data sources 

should be considered sources of last resort: they provide 

data averaged over large regions, sometimes are not 

very current, and it is often diffi cult to ascertain suffi cient background information to fully understand the 

underlying methods used to determine what biases may 

exist. For many studies, utility, state, or other local data 

may be available that is specifi c to the geographic area 

being studied and will provide greater detail and accuracy. In some cases, studies from reasonable comparison 

areas may exist. As with energy profi les, utilities may be 

a good source of this information. Examples of locally 

developed data that may exist include: 

• 	Appliance saturation studies. 

• 	Baseline studies that characterize the types and effi ciency of equipment in existing and new buildings. 

• 	Energy use forecasts, often separately estimating 

existing and new construction energy use and separated by major consuming sector. 

• 	End-use disaggregation data—this may be from statistical models, metering, or simulation models. 

• 	Program evaluations that identify measure savings 

and document penetration rates and baseline practices. 

If resources are available, primary data can be collected 

through phone and onsite surveys of samples of facilities and market actors in the region being analyzed. 

This can provide the most specifi c and accurate data, 

but obviously requires higher commitments of time and 

budget. 

Finally, any effort to “transfer” data from one geographic or demographic unit to another should be done 

with caution and an understanding of the factors that 

might affect the applicability of the data to the new 

situation. Differences in climate, economic and demographic factors, and the prevalent commercial and 

industrial customer types should be investigated and 

adjustments made if supported by good data. 

3.4 Select and Defi ne the 

Methodology 

In general, a potential analysis involves the following steps: 

• 	Identify the baseline energy consumption forecast, including a specifi c understanding of what it does and 

does not include in terms of future changes to codes 

and standards, natural effi ciency adoption, planned 

effi ciency programs, etc. 

• 	Disaggregate the baseline forecast into customer and 

other segments (e.g., end uses) appropriate for the 

analysis. 

3-4 Guide For Conducting Energy Effi ciency Potential Studies 
• 	Characterize effi ciency measures: 

–	 Identify energy, demand, and other savings (e.g., 

operations and maintenance) of each measure, 

including changes over time.5 

–	 Identify costs associated with each measure, 

including changes over time, such as prices coming down because of greater volume sold and 

technology improvements. 

• 	Screen measures for economic effects, cost-effectiveness, and other resource effects. 

• 	Develop program designs, in terms of bundled measures targeting particular customer groups and/or 

end-uses. 

• 	Estimate measure penetrations for baseline and effi ­

cient scenarios for each program year using program 

design information, available studies, past program 

results, understanding of the specifi c markets, etc. 

• 	Calculate total savings for all effi ciency measures. 

• 	Present the results. 

The following sections provide additional detail on each 

step and examples of how these steps were handled in 

several example potential studies. Appendix C presents 

a more detailed discussion of these steps and some of 

the key analytical issues that arise with each. 

3.4.1 Forecast and Disaggregate the Baseline 

Broadly speaking, the objective of a potential study is 

to estimate future energy savings opportunities resulting from the presence of some program or policy to 

promote effi ciency. That is, the potential estimate is 

relative to some scenario that represents “business as 

usual.” Therefore, the fi rst step in any potential study is 

to predict the future in the absence of intervention to 

promote additional effi ciency investments. This “baseline scenario” forecast provides the context for the comparison of the “effi cient scenario.” The baseline can be 

characterized in terms of annual kWh consumed, peak 

demand of the system (whatever its boundaries) in MW, 

tons of pollutants emitted, or other metrics. In practice, 

the fi rst two metrics are most typically used. 

It is critical to understand what the baseline forecast 

represents. For example, many jurisdictions have some 

existing effi ciency programming. The analyst should 

determine if the forecasts include continuation of the 

existing program, ignore it altogether, or something 

in between. Furthermore, the forecast might include 

assumptions about “natural effi ciency” (the proportion 

of all equipment purchases that will fl ow to effi cient 

products in the absence of any programmatic incentives) or changes in building codes or other energy use 

standards (e.g., national ENERGY STAR requirements). In 

some cases, the analyst may choose to add the projected energy savings from such programs back into the 

forecast in order to have an appropriate baseline from 

which to develop the economic or maximum achievable potential. The total potential estimate can then 

be divided into the “existing” potential and the “additional” potential that would be available from new or 

expanded effi ciency programming. 

Baseline disaggregation will be determined in part on 

the data available, as described in Section 3.3. When 

disaggregated data specifi c to the area of the analysis 

are not available, data from other areas may be used 

as a proxy. The uncertainty in using energy end-use 

patterns from a neighboring state is likely to be of 

similar magnitude to other sources of uncertainty in the 

analysis. This is particularly true for residential effi ciency 

measures, whereas industrial energy use varies widely 

from industry to industry. Transferring industrial energy 

data from state to state should be done with caution. 

3.4.2 Characterize Effi ciency Measures 

Measure characterization is the determination of parameters for individual or bundles of technologies, services, 

or design practices that defi ne the costs, savings, and 

lifetimes for different measures. Measure characterization will typically rely on research about existing technologies available in the market and their performance, 

as well as engineering calculations and cost estimation. 

Typical steps include: 

• 	Identifying an effi ciency measure, including defi ning 

the baseline effi ciency or practice as well as that of 

the effi cient scenario. 

National Action Plan for Energy Effi ciency 3-5
• 	Calculating the annual energy savings (measured in 

kilowatt-hours [kWh]) and peak demand impact coincident with the utility system (measured in kilowatts 

[kW]). This is generally specifi c to individual customer 

types, refl ecting differences in operating hours, load 

shapes, existing effi ciency levels, etc. 

• 	Determining the pattern of savings over time. This 

is dependent on the energy-use load shape of the 

measure. Because energy reductions are more valuable at some times than others (e.g., electric system 

peaks typically occur during business hours on a hot 

summer day, driving up energy prices and therefore 

the economic benefi t of energy savings at that time), 

some method of accounting for this variability should 

be included in the analysis. At a minimum, the analysis 

should account for seasonal on- and off-peak periods. 

• 	Determining other costs and benefi ts of the measure, 

such as differences in operation and maintenance 

costs between effi cient and baseline measures and 

any non-energy costs and benefi ts such as water savings, waste reduction, or productivity improvements. 

• 	Determining the measure cost. For “lost opportunity” 

measures such as in new construction and planned 

replacement of failing equipment, this will typically 

be the incremental cost of effi cient equipment as 

compared to baseline equipment. For discretionary 

early retirement measures that replace functioning 

equipment or other retrofi t measures such as building 

shell improvements, costs will typically represent the 

total labor and equipment costs of new systems. 

3.4.3 Screen Measures and Programs for CostEffectiveness 

Once all of the data are available to determine the 

energy savings and costs associated with a forecast set 

of effi ciency investments, the analyst can determine 

the overall effects of effi ciency investments or policies. 

Economic effects are of particular interest to decisionmakers. The process of assessing the economic effects 

of effi ciency investments is typically referred to as “costeffectiveness screening.” This refers to the comparison 

of the benefi ts of the investment to its cost. Effi ciency 

measures should pass the “cost-effectiveness screen” of 

having positive net benefi ts (i.e., benefi ts greater than 

costs), based on whatever economic tests are applied. 

A primary consideration in cost-effectiveness analysis is 

choosing the cost and benefi t components that are included within the boundary of the comparison, whether 

at the measure or program level. A particular boundary 

defi nition is referred to as a “test.” The test used depends upon the perspective of the decision-makers and 

where their concern lies: overall societal impact, utility 

system impact, or customer-level impact. The standard 

range of economic tests (CPUC, 2001) includes: 

• 	Total resource cost (TRC) test. One of the most 

common tests, the TRC assesses the impacts of 

a portfolio of energy effi ciency initiatives on the 

economy at large. It does not concern itself with 

distributional equity between different segments of 

society. The test compares the present value of costs 

of effi ciency for all members of society (including 

costs to participants and program administrators) 

compared to the present value of benefi ts, including avoided energy supply and demand costs.6 The 

assessment of participant costs extends beyond the 

energy source in question to increases or decreases in 

operations and maintenance costs and costs for other 

resources (e.g., water), as well as non-resource cost 

impacts. Results are typically expressed as either net 

benefi ts or a benefi t-to-cost ratio. 

• 	Societal cost test (SCT). This test is a variation of 

the TRC test that includes monetized effects of externalities (e.g., emissions impacts) benefi ts.7 It may also 

use a “social” discount rate that is lower than that 

used in the TRC. Note that the lower the discount 

rate selected, the more cost-effective effi ciency will 

appear.8 

• 	Participant cost test. This test focuses on either 

“typical” or aggregate participating customer(s), 

comparing quantifi able benefi ts and costs. Benefi ts 

include reductions in utility bills, incentive payments, 

and tax credits. Costs include ratepayer-funded 

spending on energy effi ciency technologies and 

changes in other fuel or resource costs. 

3-6 Guide For Conducting Energy Effi ciency Potential Studies 
• 	Ratepayer impact measure (RIM) test. This test 

evaluates the impacts on customer rates. It does so 

by evaluating changes in utility revenues and operating costs, comparing savings (or increases) from 

avoided supply costs, changes in revenues, and 

incurred administration costs. There are many ways to 

express the results, including lifecycle revenue impact, annual or fi rst-year revenue impact, benefi t-cost 

ratio, and net benefi ts. 

• 	Program administrator cost test. This test evaluates the impacts of the effi ciency initiatives on the 

administrator or energy system (sometimes referred 

to as the utility cost test or energy systems test). It 

compares administrator costs (e.g., incentives paid, 

staff labor, marketing, printing, data tracking and 

reporting) to accrued benefi ts, including avoided 

energy and demand supply costs, and also revenues 

for any forward capacity market auctions. It does not 

assess issues of utility revenue not directly related to 

the value in a secondary market from effi ciency credits (see RIM test, above). 

The test selected for a potential study should ensure 

that results are comparable to the criteria being used to 

evaluate other options, either for electric supply or public funds. The most common test in most jurisdictions is 

the TRC, as it provides an understanding of the overall 

effect on society. Because it includes all of the benefi ts 

of effi ciency investment, regardless of benefi ciary, it 

typically generates the greatest net benefi t estimates, 

which supports a strong commitment to energy effi ­

ciency. On the other hand, the TRC does not capture all 

of the distributional effects of effi ciency investments on 

all parties (e.g., utilities, non-participants, and program 

administrators). More than one test may be necessary 

to understand all of the potential effects from multiple 

perspectives. Nevertheless, if effi ciency investments generate a positive net benefi t to society (as demonstrated 

by the TRC), policy-makers should be able to devise 

ways of addressing distributional concerns. The examples in Chapters 4 through 6 describe the conditions 

under which different tests may be most appropriate. 

3.4.4 Develop Program Designs and Estimate 

Measure Penetrations 

This step is highly specifi c to the analysis being performed. Measure penetrations are dependent in part on 

the potential type (i.e., achievable vs. program). Chapters 

4 through 6 describe the program designs assumed in 

each of the example studies and some of the important 

factors to consider when selecting penetration values. 

3.4.5 Calculate Total Savings 

While the forecast and measure characterization data 

provide many of the inputs to a potential estimate, an 

analytical approach to combine all these data and take 

account of the many moving parts is necessary. In general, there are two main approaches to calculating the 

potential of an effi ciency measure or set of measures: 

top-down and bottom-up. 

A bottom-up approach fi rst starts with the savings and 

costs associated with replacing one piece of equipment with its effi cient counterpart, and then multiplies 

these values by the number of measures expected to be 

installed throughout the life of the program. The key 

factor in the energy savings calculation is the number of 

kilowatt-hours saved annually from the installation of a 

more effi cient unit such as a dishwasher, air conditioner, 

or boiler. Often, a bottom-up approach is preferred for 

residential analysis because of better data availability 

and greater homogeneity of the building and equipment stock to which measures are applied. The residential sector portions of the potential studies presented in 

Chapter 5 are examples of bottom-up analyses. 

A top-down approach begins with a disaggregated energy sales forecast over the time period under study and 

then determines what percentage of these sales a given 

effi ciency measure will save. For more detailed studies, 

the sales data are broken down by end use and building 

type before the savings percent is applied. The key factor is then expressed as, for example, the percentage of 

all energy used for interior lighting in an offi ce building 

that would be saved by switching to high performance 

lighting fi xtures. The potential studies presented in 

Chapter 4 are examples of top-down analyses. 

National Action Plan for Energy Effi ciency 3-7
3.5 Present the Results
 

The results generated from potential studies are a function of both the type of potential study (e.g., economic, 

achievable) and the level of detail and aggregation. One 

of the key objectives of a potential study is to provide 

an estimate of the energy and demand impacts of 

energy effi ciency. For an economic potential study, the 

result is essentially a single set of numbers representing 

the amount of cost-effective energy effi ciency available over an analyzed time horizon. For an achievable 

potential study, the result is not just the amount of 

energy effi ciency potential, but also the time horizon 

over which planners can expect effi ciency savings to be 

generated by the programs. In both of these cases, the 

presentation should also include the economic effects 

of the effi ciency investments. 

The presentation will be driven in part by the type of study 

conducted and in part by the audience for the study and 

their needs. Study authors or those who commission a 

study should also address where and when results will 

be presented. If the objective of the study is to infl uence 

change, then an influential presentation is needed. A 

detailed discussion of strategic marketing and media approaches is beyond the scope of this document, but the 

following list highlights some strategies that have proven 

effective for supporting potential studies in the past: 

• 	For studies that are likely to be widely distributed, 

energy-related information should be translated into 

terms that the lay reader can understand. For example, stating that a program will save enough energy 

to power 16,000 homes has broader appeal that saying it will save 100 gigawatt-hours of electricity. 

• 	Develop an executive summary that presents the key 

fi ndings of the study in clear, user-friendly language. 

• 	Use figures and tables to convey numerical information. 

• 	Support the publication of the report with a press 

release. Notify any reporters with whom you have 

relationships or who report on relevant issues (e.g., 

climate change, consumer affairs, electricity and 

energy markets). 

• 	Look for opportunities to partner with other organizations. Organizations interested in the topic and the 

results of the study can alert their own constituents 

and their own network of organizations and partners. 

3.6 Notes 

1. 	 This and all references to the range of potential study costs 

should be viewed as approximate. They are based on a sample of 

studies and are not intended to defi ne the absolute limit of the 

cost range. 

2. 	 In the context of a potential study, the term “disaggregate” 

means to divide a total value (e.g., annual kWh consumed by the 

customers of a particular utility) into component parts such as 

customer building type (e.g., single-family house, offi ce building, 

warehouse, retail), energy end-use (e.g., lighting, appliances, 

water heating), or other characteristic. 

3. 	 Primary research refers to collection of new data directly for the 

area being analyzed (e.g., the energy use in buildings within the 

study area). Secondary research generally refers to the adoption and use of data already collected from outside the specifi c 

customers or region being analyzed, and applying it—often with 

appropriate adjustments—to the specifi c analysis area. 

4. 	 These surveys can be found on EIA’s Web site at < http://www.eia. 

doe.gov/emeu/recs (or /mecs or /cbecs)>. 

5. 	 The energy savings from a measure are not necessarily constant 

over time. For example, consider the replacement of an operating piece of equipment before the end of its life with a moreeffi cient unit (a so-called “retrofi t” measure). If the replacement 

unit is equal in effi ciency to that required by code or standard 

practice, then the savings should only count until the end of the 

original equipment’s life. At that time, the old unit would have 

been replaced by a unit with the same effi ciency as the retrofi t 

measure. There is no increase in effi ciency after the end of the 

original equipment’s life. This effect is called the retrofi t baseline 

adjustment and is important to consider so as to not overstate 

the savings from retrofi t measures. 

6. 	 Refer to the Guide to Resource Planning with Energy Effi ciency 

(National Action Plan for Energy Effi ciency, 2007) for additional 

discussion of avoided costs. 

7. 	 If emissions have a market value (as with the current program 

for sulfur dioxide allowances), then these should be included 

as a cost or benefi t in any test. “Externalities” refers to impacts 

that are external to existing markets. They have societal costs or 

benefi ts that are not captured in any market. The emissions costs 

or benefi ts captured in an SCT, but not a TRC, might include 

emissions without market value or with additional value over and 

above any market prices. 

8. 	 Selecting a lower discount rate will result in energy effi ciency 

measures appearing to be more cost-effective because the pres3-8 Guide For Conducting Energy Effi ciency Potential Studies 
ent value of the benefi ts (i.e., future energy savings) is greater 

under this condition, while the present value of the costs will 

remain largely unchanged. Analysts should use a discount rate 

that is consistent with that chosen for other policy studies in the 

same jurisdiction. From a policy perspective, it is preferable to 

demonstrate the cost-effectiveness of energy effi ciency through 

careful and thorough accounting of its costs and benefi ts rather 

than through inconsistently low discount rates or other potentially controversial analytical assumptions. 

National Action Plan for Energy Effi ciency 3-9

Applying the Concepts: 

Building a Case for 4: Energy Effi ciency 

This chapter discusses potential studies that are written with the aim of building policy support for 

energy efficiency programs and funding. Usually these types of studies are done at a high level of aggregation, and focus on the macro-level opportunities for savings and societal benefits of doing effi ciency. 

They typically cost in the range of $20,000 to $75,000 and take anywhere from 1 to 4 months to complete, depending on factors such as data availability.1 

4.1 Key Questions 

The following questions will help entities ensure that a 

potential study to build a case for energy effi ciency is 

the appropriate application: 

• 	Are we in the process of deciding whether to invest 

in effi ciency and, if so, are we deciding how much 

to invest? 

• 	Is the primary motivation of this study to demonstrate 

the benefi ts of effi ciency and build policy support? 

• 	Can we accept a fairly high level of aggregation and 

thus uncertainty in our results? 

• 	Are the desired outputs primarily macro-level energy 

and capacity savings, and is there a role for related 

economic and environmental data? 

4.2 Objective and Audience 

Potential studies are most frequently associated with a 

desire to support energy effi ciency investments. Whether put forward by utilities, state or local governments, 

or advocacy groups, the potential study provides quantitative evidence that energy effi ciency will generate economic and/or environmental benefi ts for the public and 

for both public and private institutions. Potential studies 

with this objective may present a macro-level look at 

effi ciency potential in support of: (1) discussions over 

whether or not to implement effi ciency programs and 

initiatives where none currently exist, (2) consideration 

of whether to continue existing programs, (3) changes 

in funding level for existing programs, (4) establishing 

funding levels for programs where none currently exist, 

or (5) efforts to understand the potential for effi ciency 

to contribute to emissions or portfolio standards. These 

studies have a wide-ranging audience that is likely to 

include state and local governments, public utility commissions, regional interest groups, utilities, ratepayers, 

and advocacy groups. 

4.3 Example Applications: 

SWEEP “Mother Lode” and Texas 

“Power to Save” 

To illustrate potential studies aimed at building the case 

for energy effi ciency, this chapter presents two recently 

completed and related examples. These two case studies are used to represent high-level studies that can 

provide important information to decision-makers at a 

relatively low cost. 

• 	The New Mother Lode: The Potential for More Effi cient Electricity Use in the Southwest (SWEEP, 2002) 

examines the potential for and benefi ts from increasing the effi ciency of electricity use in the southwest 

states of Arizona, Colorado, Nevada, New Mexico, 

Utah, and Wyoming. Using energy modeling at a 

moderate level of detail and with limited data collection, it provides an estimate of the maximum achievable electric effi ciency potential. 

National Action Plan for Energy Effi ciency 4-1
Questions for the Analyst 

After deciding that the objective for a potential study is to build a case for energy effi ciency, the project manager should ask the analyst the following questions to help guide the contracting process. Raising these issues 

early can ensure that key assumptions and data inputs are incorporated into the analysis, and that the fi nal 

“deliverable” meets the project manager’s requirements for cost, scope, and rigor. 

• Who is the target audience for the study?

• What specifi c results are necessary? Does the audience require only overall percent savings and costs, or more 

disaggregated results that identify savings by sector, building type, market, or technology? 

• What data are available? 

• Are other studies available that can be relied on for key information and data? 

• Does the contracting fi rm have access to proprietary data? 

• What local utility data are available? 

• What is the most compelling way to present results to the target audience? 

• Should the analyst focus on the economic benefi ts to society? What about energy reliability and/or environmental benefi ts? 

• How should naturally occurring effi ciency be accounted for? 

• Are the costs and benefi ts of effi ciency carefully accounted for and presented in cost-effectiveness tests? Are 

discount rates and other assumptions clearly stated and reasonable? 

• What demand-side resources should the analyst include? Effi ciency only? Demand response? Combined heat 

and power? Fuel switching? Onsite distributed generation? Renewables? 

• 	Power to Save: An Alternative Path to Meet Electric 

Needs in Texas (Optimal Energy, 2007), commissioned 

by national nonprofi t groups with an interest in 

energy effi ciency and climate change, estimates the 

potential for effi ciency and other demand-side strategies to offset Texas’ growing electricity needs. It relied 

upon the results of other studies in similar or nearby 

regions to develop an achievable potential estimate at 

a high level. While Texas currently has some effi ciency 

programming, many stakeholders felt that the level 

of spending on effi ciency should be increased. This 

report assessed the potential for greater effi ciency 

savings with commensurately higher spending. 

4.4 Potential Type 

To make a case for energy effi ciency, one must consider the economic impacts of energy effi ciency, and 


likely address market barriers that are incorporated into 

achievable potential estimates. Therefore, a technical potential estimate is not particularly useful in this 

context. Indeed, neither of the two example studies 

reviewed here present the technical potential for the 

areas under study. 

The SWEEP study began with a list of technically feasible measures but only aggregated the savings potential 

of a package of these measures up to the cost-effectiveness threshold; it does not give an estimate of total 

technical potential. The “maximum cost-effective savings potential” (i.e., economic potential) served as the 

basis for developing a “high-effi ciency” scenario which 

represented “aggressive but potentially achievable 

implementation of cost-effective measures” (SWEEP, 

2002, p. 2-7). Using the defi nitions presented in Section 2.4, this is a version of achievable potential, likely 

approaching maximum achievable. Only this potential is 

4-2 Guide For Conducting Energy Effi ciency Potential Studies 
fully analyzed and applied to the forecast energy needs 

of the region to develop a savings estimate in both 

energy (kWh) and dollar terms. The economic potential 

is presented simply as a percentage of energy savings 

for a variety of building types. In this way, the study 

provides some indication of the possible upper limit of 

savings (the economic potential) while focusing attention on results that are more relevant to policy-making. 

The Texas study began with a review of existing studies, 

particularly those that included Texas, nearby regions, 

or regions with similar climate zones. It adopted economic savings potential percentages by customer sector, 

and major building types based on these studies, and 

then applied penetration rates considering the market 

barriers and likely programs. This generated a set of 

estimates that can be supported as realistic assuming an 

appropriately structured regulatory and political climate. 

Because the purpose of the Texas study was to establish the ability of energy effi ciency to meet future load 

growth and reliability constraints, a high-level approach 

was suffi cient. 

4.5 Level of Detail and 

Data Requirements 

For any potential study, regardless of application, there 

are many parameters and dimensions for which the 

analyst must determine the level of detail to include. 

Ultimately, the level of aggregation depends upon the 

needs and objectives of the study, the available data 

and budgetary resources, and the uniqueness of a given 

region. With respect to the latter factor, greater detail 

may be necessary if there are specifi c market segments 

that strongly dominate loads (e.g., mobile homes, 

chemical plants). The following summary of the different levels of aggregation and categorization schemes 

generally proceeds from lesser to greater levels of detail. 

• 	Programs. Effi ciency programming can be considered at a high level or programs targeted at particular 

opportunities (e.g., residential new construction, 

small business retrofi ts) or energy end-uses (e.g., 

lighting, HVAC). 

• 	Market decisions. Potential studies often differentiate the savings potential by the type of investment 

decision to be made, particularly between retrofi t 

measures and incremental improvements at the time 

of planned investment in equipment and systems 

(“lost opportunity”). 

• 	Market segments. At the least detailed level, a 

potential study might estimate savings relative to 

total energy consumption. More typical is an estimate 

differentiated by structural sector (e.g., residential, 

commercial, industrial). More detailed studies estimate effi ciency potential by smaller market segments, 

for example dividing residential potential into singlefamily, multifamily, and mobile home sub-segments. 

• 	End-uses. Many mid-level potential studies will 

evaluate energy effi ciency opportunities by assigning 

an effi ciency potential to a type of customer, such 

as an offi ce building or a school. The potential is 

then estimated against the total number of offi ces or 

schools affected. More detailed studies can determine 

savings by specifi c end-uses within each of these 

segments, such as offi ce cooling. Such an approach 

allows for a more detailed analysis of baseline technology penetrations and can better support program 

design activities.2 

• 	Measures. At the most detailed level, individual 

measure potential broken out by facility or customer 

type can be considered. This approach provides the 

greatest level of information to support program design. In reality, most studies begin with measure-level 

detail even if the ultimate results and purpose is to 

present higher-level aggregated results. 

To build the case for energy effi ciency, the example 

studies in this section rely on a moderate level of detail 

to generate potential estimates. They aim to engender 

confi dence in the results without striving for a level 

of precision unsupported by the underlying data. For 

example, both the Texas study and the SWEEP study included only four commercial building types (offi ce, retail, 

school, and food service/sales) and two residential building types (single- and multifamily). While there are clearly 

many buildings that do not fall into these categories (say, 

National Action Plan for Energy Effi ciency 4-3
hospitals and warehouses), the six selected building types 

likely represent a sizable majority of square footage and 

energy use in the area under study. Furthermore, because 

other parameters were included at a lower level of detail 

(e.g., only two locations for the climate data were used 

in the energy modeling to represent all six states), the 

purpose of the study, data available, resources needed 

for increased detail, and improvement in accuracy must 

be weighed when selecting an approach. 

An additional factor to consider when determining the 

level of detail necessary in a potential study is the availability and/or cost of data. As good end-use energy data 

are not available for all locales, data availability may be the 

limiting factor in an analysis. A potential study conducted 

to build the case for energy efficiency may not require a 

high level of detail and therefore not warrant the expenditure of resources on a primary data collection effort. 

4.6 Methodology 

As a reminder, completing a potential analysis involves 

the following steps: 

• 	Identify and disaggregate the baseline 

energy forecast. 

• 	Characterize effi ciency measures. 

• 	Screen measures for cost-effectiveness. 

• 	Develop program designs and measure penetrations. 

• 	Calculate total savings for all effi ciency measures and 

present the results. 

This section addresses some of these steps with respect 

to building the case for energy effi ciency and their 

treatment in the SWEEP and Texas studies. Subsequent 

sections will address other steps with respect to additional examples. 

In general terms, both of the examples presented in 

this section are high-level estimates that relied upon 

a simple top-down methodology to estimate electric 

effi ciency potential. As pieces intended to support 

energy effi ciency at a broad political level, they relied on 

cost-effectiveness tests that incorporate a broad view of 

costs and benefi ts to demonstrate the value of effi ­

ciency investments. These choices are described in more 

detail below. 

4.6.1 A Simple Approach to Building the Case 

for Efficiency: Top-Down Potential Estimates 

When seeking support for effi ciency investments (or 

support for continued or increased effi ciency funding), a 

simple top-down approach is often suffi cient to support 

the political process that will ultimately result in effi ­

ciency program implementation; both of the examples 

presented here rely on a top-down approach to generate a potential estimate. 

A top-down potential estimate begins with a disaggregated energy sales forecast over the time period under 

study and then determines what percentage of these 

sales a given effi ciency measure will save. Often, the 

sales data are broken down by end-use and building 

type before the savings percent is applied. In the case 

of the SWEEP study, the savings estimates were applied 

to sales disaggregated by building type, but not by end 

use. For example, the study authors determined that the 

economic savings potential from a package of effi ciency 

measures for new offi ce buildings is 54 percent.3 In 

this case, it was not necessary to determine the savings 

potential with greater detail, say, for offi ce building 

lighting or residential HVAC. Addressing the different 

distribution of a few key building types in the six states 

covered by the study increased the specifi city and (presumably) the accuracy of the estimate without incurring 

substantial additional cost. In short, the level of detail 

selected for analysis matched the application. 

To generate an estimate of the achievable savings 

potential, the economic savings potential was adjusted 

using penetration factors to account for the existence 

of market barriers to effi ciency investment and the time 

needed to design and implement programs to overcome these barriers. Continuing with the SWEEP study, 

the authors assumed that in the fi rst year of implementation, 50 percent of the effi ciency potential could be 

realized, increasing to 100 percent by the seventh year.4 

A set of penetration factors over time such as this is 

4-4 Guide For Conducting Energy Effi ciency Potential Studies 
 

often referred to as a penetration curve. Sources for 

penetration factors and curves include other evaluations 

of successful effi ciency programs, a full understanding 

of the markets addressed and the program or policy 

strategies that would be used to intervene in these 

markets, extrapolation from observed penetration of 

effi ciency measures to date, and assumptions regarding 

mandatory effi ciency standards and natural turn-over in 

equipment stock. 

The set of assumptions regarding the penetration of 

effi ciency savings is a key factor in the ultimate savings estimate. The penetrations are a function of the 

program designs and will drive program funding levels. 

Analysts typically assume greater penetration levels 

for comprehensive programs with widespread marketing efforts and high incentives than for less-aggressive 

programs that provide only a small portion of the added 

cost of effi cient equipment or that rely solely on information and education efforts. The Texas study relied on 

the economic savings potential factors from the SWEEP 

study but assumed a lower level of penetration and 

thus a lower (relative) achievable potential. In this case, 

the objective was not to present a maximum or highly 

Forecasting Measure Predictions 

Developing effi ciency measure penetrations under various program scenarios is not an exact science. It relies on 

a detailed understanding of the market for a given technology, the barriers faced by a given customer type, and 

likely future effi ciency policies and standards. In addition, many programs are design to transform the market for 

a particular appliance or equipment type, with the goal of infl uencing state or national codes or standards. To 

properly estimate savings impacts and cost-effectiveness, accurate modeling of current and likely future penetrations for each individual combination of technology, market, and customer type under both the business-as-usual scenario and the “with program” intervention is necessary. Below is an example of the penetration curve for 

a clothes washer program that specifi cally affected the start date of federal standards. It shows the percentage 

of new clothes washers sold in each year that meet a federal effi ciency standard (i.e., ENERGY STAR). The graph 

demonstrates how explicitly modeling both baseline and “with program” penetrations is important to determining the net effect of effi ciency programming. 

100% 

90% 

80% 

70% 

60% 

50% 

40% 

20% 

30% 

10% 

0% 

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 

1998: regional

 initiative begins 

2001: Whirlpool

 enters market 

1998: 6 manufacturers, 

15 qualified products 

2002:18 manufacturers, 

99 qualified products 

2003: national clothes 

washers campaign kicks off 

2004: more stringent ENERGY STAR 

spec takes effect 

2007: federal minimum efficiency 

standard in effect 

Sponsor states without initiative 

Sponsor states with initiative 

National average 

Year 

Market Share of Clothes Washers That 

Meet Federal Standards (%) 

Figure 4-1. Sample Penetration Curve for a Clothes Washer Program 

National Action Plan for Energy Effi ciency 4-5
aggressive effi ciency effort. Any potential study, regardless of objective, should clearly state the assumptions 

underlying the selection of penetration rates. In the 

Texas case, lower penetration rates were selected based 

on the limited existing effi ciency programming and a 

desire to acknowledge the real diffi culties in developing, 

funding, and implementing effi ciency programming to 

the maximum achievable level. 

4.6.2 Building the Case for Everyone: Total 

Resource Cost-Effectiveness 

Investment in energy effi ciency generates a variety of 

benefi ts and costs. Benefi ts include the avoided cost of 

generating electricity or supplying a fuel in the amount 

saved by the investment; reduced need for transmission 

and distribution capacity; avoided water costs; avoided 

pollutant emissions,5 whether from electric generation 

or fuel end-use; savings in maintenance costs; and other 

non-resource benefi ts. The costs of the investment 

include the actual cost of the equipment and potential 

increases in other costs, such as the need for additional 

heating energy that results when more effi cient lighting generates less waste heat. If the investment occurs 

as the result of an energy effi ciency program, the costs 

of administering the program might also be included. 

This sub-section discusses ways in which the costs and 

benefi ts of effi ciency investments can be compared with 

one another. It also discusses the application of one of 

these comparisons in the context of building the case 

for energy effi ciency. 

In most potential studies, there are actually two levels of 

cost-effectiveness screening. A measure-level screening 

fi rst considers the costs and benefi ts of each effi ciency 

measure to determine if that measure is cost-effective 

and therefore warrants inclusion in an effi ciency program. For example, a measure to support the purchase 

of high-effi ciency clothes washers would compare the 

value of energy savings (both electric and fossil fuel, if 

used for water heating) from the new appliance with 

the cost difference between the higher-effi ciency the 

standard units.6 If the value of the savings outweighs 

the additional costs, the measure would be included in 

a bundle of measures making up an effi ciency program or initiative. The program-level screening adds 

the costs of delivering an effi ciency program made up 

of one or more (presumably) cost-effective measures 

to the comparison. Program delivery costs can include 

utility or other administrator staff and operating costs, 

program-wide marketing costs, training costs and other 

costs not attributable to a specifi c measure. In addition, 

it accounts for free ridership where participants in the 

program may have implemented the effi ciency measure 

anyway, and spillover or market effects where energy 

users not participating in the program may still benefi t 

from it and adopt effi ciency measures. 

The most common test used in many jurisdictions is the 

TRC because it provides an understanding of the overall 

effect on society. This is certainly true when building a 

case for energy effi ciency, where the objective is to provide support for effi ciency programming on the grounds 

that it will provide economic benefi ts to society overall. 

Despite this, the SWEEP study diverged slightly from the 

typical tests, adopting something similar to a participant 

test for the measure-level analysis. All measures with 

overall lifecycle costs less than retail electric rates were 

considered to be economic. This differs from a true TRC 

test because retail electric rates refl ect an average cost 

of service (including amortized capital costs), rather 

than the costs avoided by saving 1 kWh on the margin. 

Measure-level cost-effectiveness screening was not conducted for the Texas study, which was done at a higher 

level of aggregation. The overall effi ciency savings for 

each of the three sectors were screened using the TRC. 

As with the SWEEP study, externality impacts in the 

form of pollutant reductions were not monetized, but 

were reported in physical quantities. 

While they were not performed for the two examples 

presented here, other economic tests may be desired to 

better understand issues such as the impact on a utility’s 

economics and possible rate impacts. These issues are 

often important to public discourse over the desirability 

of effi ciency programming. Other economic tests are 

often best used in conjunction with, rather than as a 

substitute for, a broader test such as the TRC and SCT, 

where they can identify some of the potential distributional effects of public policy alongside the overall 

societal impacts. 

4-6 Guide For Conducting Energy Effi ciency Potential Studies 
4.7 Presentation of Results
 

The results that can be generated from potential studies 

are a function of both the type of potential study (e.g., 

economic, achievable) and the level of detail and aggregation. Furthermore, there are a range of outputs that 

are relevant to decision-makers and other stakeholders. 

These include the potential energy savings and peak 

demand reductions, the cost of capturing this potential, 

the economic benefi ts from avoided energy purchases, 

other resource benefi ts such as reduced water usage, 

and non-resource benefi ts such as emissions reductions. 

For studies that aim to support effi ciency programming 

and that therefore must reach a wide audience, simple 

presentations of energy and economic savings should 

be the primary means of communication the results of 

the analysis. All presentations of energy savings should 

clearly distinguish between energy savings (measured in 

kWh) and peak demand savings (measured in kW). 

There are some challenges to generating these data. Because effi ciency technologies create savings for multiple 

years following installation, energy effi ciency savings are 

cumulative. That is, the total savings in any particular 

year of the program are the sum of the annual savings 

generated by all of the installations in all of the previous 

years.7 The fi gure below, taken from the SWEEP study, 

demonstrates the accumulation of savings as a program 

progresses. The difference between the “base” case 

(blue line) and “high-effi ciency” case (pink line) represents the cumulative annual savings, which increase 

each year the program continues. 

It is important to distinguish between incremental savings and cumulative savings when reporting the future 

effects of a program. The cumulative energy or demand 

savings each year is more relevant to comparisons with 

load forecasts and for power planning purposes, while 

the incremental savings are more closely correlated with 

program spending in any given year, as the full cost 

of the measure is usually borne at the time of installation. Looking at the example studies referenced above, 

SWEEP uses both fi gures and tables to convey the 

cumulative energy savings potential. 

Figure 4-2. Total Electricity Consumption in the Base and High Effi ciency Scenarios 

320,000 

300,000 

280,000 

33% 

260,000 

240,000 

220,000 

18% 

200,000
 

180,000
 

2000 2005 

Year 

Electricity Consumption (GWh) 

2010 2015 2020 

Base 

High Efficiency 

Source: SWEEP, 2002. 

National Action Plan for Energy Effi ciency 4-7
Figure 4-3. Energy Savings Potential in 2020 by Sector and State in the Southwest
 

Source: SWEEP, 2002. 

Region AZ CO NV NM UT WY 

Commercial Sector 

Baseline Consumption GWh 

Savings Potential GWh 

Savings Potential % 

134,780 

50,291 

37.3 

50,667 

18,862 

37.2 

36,903 

13,655 

37.0 

16,625 

6,087 

36.6 

11,261 

4,356 

38.7 

15,645 

5,866 

37.5 

3,680 

1,465 

39.8 

Residential Sector 

Baseline Consumption GWh 

Savings Potential GWh 

Savings Potential % 

93,557 

24,593 

26.3 

38,602 

11,546 

29.9 

19,902 

4,408 

22.1 

14,085 

3,067 

21.8 

7,488 

2,319 

31.0 

10,474 

2,506 

23.9 

3,007 

748 

24.9 

Industrial Sector 

Baseline Consumption GWh 

Savings Potential GWh 

Savings Potential % 

74,043 

24,150 

32.6 

18,522 

6,180 

33.3 

14,875 

4,290 

28.8 

14,812 

5,000 

33.8 

6,122 

2,220 

36.3 

10,766 

3,130 

29.1 

8,947 

3,340 

37.3 

All Sectors 

Baseline Consumption GWh 

Savings Potential GWh 

Savings Potential % 

302,381 

99,039 

32.8 

107,790

 36,584 

33.9 

71,680 

22,351 

31.2 

45,521 

14,154 

31.1 

24,871 

8,896 

35.8 

36,885 

11,500 

31.2 

15,633 

5,552 

35.5 

In addition to providing this information at the aggregate level, more detailed presentations may be possible. For example, the SWEEP study includes potential 

estimates for each of the six states analyzed by sector 

(see example table on the next page); the Texas study 

estimated the savings potential by sector (i.e., residential, commercial, industrial). 

The economic effects of effi ciency investment can be 

diffi cult to convey in a manner readily understood by 

the broad audience typical for a high-level potential 

study. While policy-makers are usually familiar with 

terms such as benefi t-cost ratio, most lay readers are 

not. Often, the net benefi t (total benefi ts minus total 

costs) is the simplest and most accessible result: “This 

program will save $X million dollars over 5 years.” 

4.8 Conclusion 

The table on the next page summarizes the key attributes of the two example studies presented in this 

chapter. A similar table appears in the each of the next 

two sections. 

4-8 Guide For Conducting Energy Effi ciency Potential Studies 
Table 4-1. Summary of Example Potential Studies: Building a Case 

for Energy Effi ciency 

SWEEP “Mother Lode” “Power to Save” 

Scope Electric potential in six Southwest 

states 

Electric potential in Texas 

Potential Type Maximum achievable Maximum achievable 

Objective Build a case for energy effi ciency 

programs 

Build a case for increased funding in effi ciency as an alternative 

to investment in new traditional 

power supply 

Audience 

Data Sources 

Political policy groups 

Primary (modeling), Census, and EIA 

Texas legislature and action groups 

EIA, ERCOT (system operator), 

SWEEP “Mother Lode” 

Analytical Methodology Bottom-up and top-down: modeling used to estimate percent savings from a set of effi ciency measures for several building types; 

savings applied to total electrical 

use by building type 

Top-down, using savings percentages from SWEEP study applied to 

Texas load forecast 

Program Design/Penetrations 

Assumed aggressive pursuit of 

effi ciency opportunities and high 

percentages of retrofi t and new 

construction opportunities over 

10 years 

Assumed moderate pursuit of effi ciency opportunities and percentages of retrofi t and new construction opportunities over 10 years 

Cost-Effectiveness Tests Modifi ed participant Modifi ed participant (based on 

SWEEP savings estimates) 

Results Effi ciency could: 

• Reduce demand growth from 

2.6% to 0.7% 

• Eliminate the need to build 34 

500 MW plants 

• Save consumers $28 billion net 

• Increase regional employment 

by 0.45% per year 

Effi ciency could: 

• Shrink demand by 0.5% per 

year 

• Cause a 20% reduction in 

energy use 

• Generate $38 billion in 

net benefi ts 

• Prevent 52 million tons of carbon dioxide emissions per year 

National Action Plan for Energy Effi ciency 4-9
4. 	 The study notes that “a high level of implementation is possible 4.9 Notes in new buildings through the adoption and enforcement of build1. 	 These ranges should be viewed as approximate. They are based 

on a sample of studies and are not intended to defi ne the absolute limit of these parameters. 

2. 	 For example, single-family detached homes may have higher 

levels of central air conditioning than duplexes or multifamily 

dwellings. 

3. 	 The building-specifi c savings estimates in the SWEEP study were 

developed by using a building energy model to aggregate the 

savings from specifi c effi ciency measures. While this is a type of 

“bottom-up” approach, it is different from the approach applied 

in more detailed potential studies (described in later sections) 

where the actual energy savings over the entire area of study are 

calculated on a measure-by-measure basis. 

ing energy codes” (SWEEP, 2002, p. 2-7). 

5. 	 Monetized pollution values are generally considered a benefi t under the societal cost test, but not included under a total resource 

cost test. 

6. 	 Note that there may also be other costs and savings. Higheffi ciency washers also save energy for drying, since they extract 

more water from the clothes. On the other hand, they may have 

shorter lifetimes or require additional maintenance, which should 

be counted on the cost side of the comparison. 

7. 	 Savings continue for the life of the measure, which for most 

effi ciency measures is greater than 7 years. Compact fl uorescent 

lamps are an important exception: they have a relatively short life 

(between 3 and 6 years, depending on where they are installed) 

and can be responsible for a substantial portion of overall program savings, depending on the program design. 

4-10 Guide For Conducting Energy Effi ciency Potential Studies 
Applying the Concepts: 

Identifying Alternatives to 5: Supply-Side Investments 

This chapter discusses potential studies that are written with the aim of evaluating efficiency as an 

alternative to a specific supply-side project. It is critical that these applications present highly accurate 

estimates of the energy efficiency potential, as they need to provide certainty and foster confi dence in 

supply-side resource planners to invest in energy efficiency instead of supply resources. The study applications described in this chapter typically cost anywhere between $75,000 and $300,000 and can take 

between 4 and 12 months to complete. Studies that involve primary data collection efforts are more 

expensive and take longer to complete compared to studies where building and measure characteristics 

in the region are known in advance.1 

5.1 Key Questions 

The following questions will help entities ensure that a 

potential study that identifi es alternatives to supply-side 

investments is the appropriate application: 

• 	Will this study determine whether energy effi ciency 

can be used to defer or eliminate plans to build new 

capacity or upgrade transmission lines? 

• 	Are energy effi ciency objectives best supported by 

“investment grade” analysis with the aim of ensuring 

the future reliability of the power system? 

• 	Are energy effi ciency objectives best supported by 

detailed measure-level data? Should certain measures 

(e.g., those that provide summer peak reductions) be 

given priority? 

5.2 Objective and Audience 

While all potential studies are at some level designed 

to make the case for energy effi ciency, some support a 

more specifi c objective. Effi ciency is now considered as 

an alternative to supply-side investments as utilities and 

others gain experience with it and other demand-side 

resources. In the past, utilities or states facing generation or transmission shortfalls in the face of growing 

electric consumption and peak loads would consider 

building new generation or transmission facilities to 

maintain reliability and suffi cient power supply without 

looking to increasing investment in energy effi ciency 

to provide relief. In many jurisdictions, utilities are now 

required to also consider demand-side resources as 

alternatives to these construction projects. To support 

this type of planning effort, the characteristics of the 

effi ciency potential (effect on peak demand, timing of 

savings, economic effects) must be known with more 

certainty than is typically required for a potential study 

that simply builds the case for effi ciency as a policy 

outcome. This type of study is also likely to have an 

informed audience that is more familiar with effi ciency 

and power system concepts. 

5.3 Example Applications: VELCO 

“Southern Loop” and ACEEE 

“Texas” Potential Studies 

This section discusses some of the issues to consider 

when planning a potential study to identify alternatives 

to supply-side investments, using two recent example 

studies. These studies were chosen as representative of 

moderately detailed studies aimed at providing a robust 

potential estimate using a combination of primary and 

secondary data. The studies are: 

• 	Potential for Energy Effi ciency, Demand Response, 

and Onsite Renewable Energy to Meet Texas’s Growing Electricity Needs (ACEEE, 2007) was prepared 

by the American Council for an Energy Effi cient 

National Action Plan for Energy Effi ciency 5-1
Questions for the Analyst 

After deciding that the objective for a potential study 

is to identify alternatives to supply-side investments, 

project managers should ask the analyst the following 

questions to help guide the contracting process. Raising these issues early can ensure that key assumptions 

and data inputs are incorporated into the analysis, 

and that the fi nal deliverable meets the project manager’s requirements for cost, scope, and rigor. 

• What is the current reliability need? Should a highlevel scoping study be performed fi rst to identify 

whether effi ciency is likely to defer or replace 

supply resources? 

• What does the load forecast include and rely on?

– Does it assume any effi ciency capture already? 

– What is the uncertainty associated with it?

• What demand-side resources should the analyst include? Effi ciency only? Demand response? 

Combined heat and power? Fuel switching? Onsite 

distributed generation? Renewables? 

• What specifi c results are necessary? 

– Does the target audience need only overall

annual and peak demand savings? 

– Does the analyst need to separately evaluate

specifi c geographic regions to address transmission and distribution constraints? 

• What data are available?

– What other studies can be relied on for 

information?

– Does the analyst have access to proprietary 

data? 

– What local utility data are available? 

• What kind of risk analysis should be performed?

– Should a range of scenarios be analyzed or a

sensitivity analysis conducted? 

– Should economic scenarios that include the

costs associated with air emissions such as 

carbon dioxide be analyzed? 

• What kind of integration with supply resources 

should be performed? 

– Will the analyst need hourly data to perform 

production cost simulations? 

– Do the data support such analysis?

• Are the costs and benefi ts of effi ciency carefully 

accounted for and presented in cost-effectiveness 

tests? Are discount rates and other assumptions 

clearly stated and reasonable? 

• How should results be presented to be most compelling to the target audience? Should the analyst 

focus on the economic benefi ts to society? Reliability 

benefi ts? Environmental benefi ts? Risk mitigation 

benefi ts? 

Economy (ACEEE) in 2007. Its title accurately describes 

the objective of the analysis. This study was prepared 

in response to announced plans to construct several 

large coal-fi red power plants to meet future peak 

loads in Texas. This chapter focuses on the effi ciency 

potential estimate contained in the report. 

• 	Assessment of Energy Effi ciency and Customer-Sited 

Generation Investments in the Southern Loop (Optimal Energy, forthcoming) was prepared on behalf of 

the Vermont Electric Power Company, Inc. (VELCO) 

in relation to efforts to build a new transmission 

line serving a small geographic region in Southern 

Vermont.2 This area faces transmission capacity 

constraints during the winter peak. As a result, the 

transmission and distribution utilities proposed to 

upgrade the transmission line. This study was commissioned because Vermont statutes and regulation 

require the utilities to consider non-transmission 

alternatives to the project, including effi ciency. 

5-2 Guide For Conducting Energy Effi ciency Potential Studies 
These two studies differ in their approach to assessing 

alternatives to supply-side investment. The ACEEE study 

was prompted by public concern regarding traditional 

supply-side investments to meet growing energy demand. In contrast to the VELCO case, there was no specifi c proceeding or pending decision regarding a specifi c 

investment. In addition, the study included potential 

estimates for other demand-side strategies such as combined heat and power and customer-sited renewables, 

which are not covered by this report. Therefore, the 

treatment of the effi ciency potential was not as detailed 

as in the VELCO study, where effi ciency was considered 

side-by-side with other alternatives, including combined 

heat and power, distributed generation, and transmission system upgrades. These were analyzed through 

an integrated transmission resource planning process, 

to support an ultimate decision by the Vermont Public 

Service Commission on the appropriate solution. 

5.4 Potential Type 

To provide a realistic and credible alternative to supplyside investments, a potential study should put forth an 

estimate of the effi ciency potential that is achievable 

with current best-practice programming. The analysis 

must generate high confi dence that the estimated 

potential is feasible and practicable to acquire in the 

required timeframe if effi ciency is to be truly comparable 

to wires-based infrastructure investment. The timing 

of savings is particularly relevant in assessing reliability 

impacts and the feasibility of supply upgrade deferral. 

Therefore, funds are best spent assessing achievable and 

program potential, rather than economic potential, since 

these convey what can actually be accomplished and 

the economics associated with capturing effi ciency. Note 

that an achievable potential estimate (which represents 

the maximum portion of the economic potential that can 

be acquired given market barriers) may raise questions 

about the uncertainty of the estimate and the confi dence 

with which the effi ciency resource can be relied upon to 

generate the necessary savings. This also generates additional demands on the methodology as discussed below. 

The ACEEE study presents both an economic potential 

estimate and a “policy potential” estimate, the latter corresponding in defi nition to program potential 

as used in this report. The economic potential was 

determined using a detailed bottom-up analysis (described in more detail below). The VELCO study presents a program potential that represents a substantial 

portion of the achievable potential. 

Ideally, the potential estimate for a study assessing 

the alternatives to supply-side investment is supported 

by program design information developed from the 

experience of other jurisdictions. The program potential in the ACEEE study is based on an expansion of 

legislatively mandated effi ciency programs to levels less 

than or equal to those already occurring in other states. 

Because the location of effi ciency savings is critical to 

specifi c upgrade components, the analysis was segmented into small geographic areas and relied heavily 

on onsite data collection from some of the biggest end 

users to refi ne estimates. Also, to increase the level of 

certainty that impacts can be captured reliably and in a 

timely fashion, penetration rates were developed that 

refl ect a high level of confi dence, as opposed to typical 

best estimates for maximum achievable levels in which 

confi dence may be lower. 

5.5 Level of Detail and 

Data Requirements 

Generally speaking, a higher level of rigor is necessary 

when assessing effi ciency as an alternative to supplyside investments, which requires a greater level of 

detail than in the previously described scenario outlined 

in Chapter 4. That discussion notes that the level of 

detail required in the analysis and the available data are 

closely linked, and both of these infl uence the overall 

cost of performing the study. 

Both of the two studies considered here evaluated 

effi ciency potential at the level of individual effi ciency 

measures. For the commercial and industrial part of the 

VELCO study, this meant that the energy use by each 

National Action Plan for Energy Effi ciency 5-3
major end-use (e.g., lighting, space heating, water heating) for each building type (e.g., offi ce, retail, grocery) 

needed to be known. While this information is often 

diffi cult to locate, in this case building-type data were 

provided by the utility. Site-specifi c information is usually 

preferable in this scenario, as it increases the confi dence 

in the end result. This end-use data was collected for major end users. To further improve the accuracy of the data 

used in the analysis, the project included onsite surveys 

for a sample of individual non-residential customers (see 

sidebar). This greater level of accuracy for disaggregated 

inputs at the building type and end use level becomes 

especially critical when evaluating the potential for small 

geographic areas. While a statewide or regional study 

can rely to a large extent on averages, for very small 

areas a few building types or customers may comprise a 

disproportionate share of the opportunities or load. For 

example, in the VELCO areas studied, a few ski resorts 

account for a large portion of the winter peak, and fully 

understanding their opportunities and expansion plans 

was critical to the ultimate outcome of the study. 

Another difference between a potential study designed 

to make the case for effi ciency and one aimed at assessing the alternatives to supply-side investments is the potential benefi t of tailoring the analysis more closely to the 

specifi c situation. In the case of the VELCO analysis, the 

additional effort necessary to develop a set of effi ciency 

measures specifi cally selected to address the winter peak 

was justifi ed by the value of a more precise estimate. This 

is an example of pursuing additional detail in areas of the 

analysis where it will provide the greatest value. Because 

of the relatively high saturation of electric space heat and 

water heating, additional effort was spent characterizing 

fuel switching measures. A further example of this is the 

emphasis on estimating the peak demand impacts of effi ­

ciency measures in the VELCO study, explained in greater 

detail in the next section. 

5.6 Methodology 

In contrast to the studies presented in Chapter 4, the 

ACEEE and VELCO potential estimates rely at least in part 

on a more detailed “bottom-up” methodology. Also, 

Field Verification of Baseline Conditions 

For the VELCO potential study, site visits were 

conducted to determine both the distribution of 

end-use technologies already in place (e.g., age 

and type of fl uorescent lighting fi xtures) and the 

available opportunities for effi ciency investments 

(e.g., percentage of lighting fi xtures that are screwbased). Because this potential study was conducted 

to support an analysis of transmission alternatives, 

the site visits played an important role in strengthening the confi dence in the results. 

because one of the studies addresses a very specifi c system 

need, additional measures of cost-effectiveness are appropriate to facilitate comparisons with the alternatives. 

5.6.1 A Detailed Look at Supply-Side Alternatives: Bottom-Up Potential Estimates 

Section 3.4.5 introduced the concept of bottom-up and 

top-down analyses of effi ciency potential and Section 

4.6.1 described the application of a simple top-down 

analysis to produce high-level effi ciency potential estimates. A bottom-up approach provides greater detail 

and is particularly well-suited to analysis of the residential sector for two reasons. First, good data on the 

number of households and their characteristics are generally available (often from the U.S. Census). Second, 

the effi ciency opportunities in the residential sector are 

far more homogeneous than in the commercial sector. 

For example, each residence typically has one heating 

system, one refrigerator, one dishwasher, etc. 

A bottom-up calculation of the effi ciency potential for 

an individual measure takes the following form: 

Measure Savings = Per Unit Savings 

× # of Households or Customers 

× Applicability Factor 

× Feasibility Factor 

× Turnover Factor 

× Net Penetration Rate 

where: 

• 	Applicability factor is the number of units per 

customer eligible for a certain measure. Depending 

5-4 Guide For Conducting Energy Effi ciency Potential Studies 
on the measure, it may range from less than one 

(say, the fraction of households with a dishwasher) 

to greater than one (say, the number of incandescent 

light bulbs per household) 

• 	Feasibility factor is the fraction of the units that can 

technically be replaced with an efficient alternative from 

an engineering point of view. This factor accounts for 

the fact that certain pieces of equipment cannot possibly be replaced by more efficient units, due to such 

factors as temperature, location, infrastructure, etc. 

• 	Turnover factor is the portion of existing units that 

will be naturally replaced each year due to failure, remodeling, or renovation. It is usually calculated as one 

divided by the equipment average service life, under 

the assumption that if equipment lasts for 10 years, 

one- tenth of the units in existence will be replaced 

each year. For measures where saturation is changing 

signifi cantly over time (for example, central air conditioning in moderate northern climates, or plasma TVs) 

the use of the reciprocal of measure life may not be 

appropriate. In this case, efforts to collect actual annual sales data should be made. This factor is not used 

in the retrofi t market, where ineffi cient equipment is 

replaced before its natural life is over. Nor is it used for 

new construction analyses, where all new equipment is 

eligible for effi ciency upgrade at the time of purchase. 

• 	Net penetration rate is the difference between 

the anticipated adoption rate of the effi ciency 

measures after intervention and the “business as 

usual” adoption rate absent effi ciency intervention. 

In the case of technical or economic potential, the 

theoretical effi ciency-case penetration is generally 

100 percent. For achievable and program potential 

analyses, it is the percentage of eligible measures 

that can reasonably be expected to occur assuming 

gradual, real-world adoption of the effi cient technology. The penetration rates should account for the 

fact that not everyone will automatically replace their 

ineffi cient technology as soon as a program starts, 

and that programs usually ramp up over time, as 

market acceptance of the effi cient technology increases. The baseline penetration rate should account 

for the natural measure adoption (people who would 

buy the effi cient technology in the absence of any 

program intervention). For market transformation 

programs, penetration rates will typically be modeled for a time period exceeding the duration of the 

program to account for post-program market effects 

attributed to the program. See Section 4.6.1 for more 

detail on modeling penetration rates. 

Both the VELCO and ACEEE studies included bottom-up 

analyses: the residential (and partially the commercial 

and industrial) sectors in the VELCO study,3 and the 

estimate of economic potential in ACEEE report. In the 

VELCO study, the authors used the formula above to 

estimate achievable effi ciency potential for a range of 

measures. When using a bottom-up approach, it is important to check the results against the disaggregated 

load forecast to ensure that credible results are obtained. For example, if one has an overly high estimate 

of the number of households with electric heat, relying 

only on a bottom-up approach could result in estimated 

potential that exceeds the total existing heating consumption for all customers. For the VELCO study, this 

was addressed by calibrating the end-use disaggregation data to overall forecast data. 

In the ACEEE analysis, the bottom-up approach was used 

only for the economic potential. As in the VELCO study, 

a simple formula was used to estimate the total savings 

potential from each measure based on per-measure savings, the size of the eligible population, and the percent 

turnover. Recall that an economic potential estimate for 

retrofi t opportunities typically refl ects a snapshot at one 

point in time, rather than the distribution of savings over 

time that one would estimate from an actual program. 

5.6.2 Ability to Displace Supply-Side Investments: Assessing Demand Impacts 

Electricity usage is characterized by two factors: the 

total amount of energy consumed over a period of time 

and the intensity of this consumption. The fi rst, usually 

referred to as “energy,” is measured in kilowatt-hours 

(or alternatively, megawatt- or gigawatt-hours).4 Energy 

is the basis for energy transactions; one consumes 

kWh and pays a per-kWh charge. The intensity of the 

National Action Plan for Energy Effi ciency 5-5
electric usage is termed “peak load,” or “demand.” It 

is measured in kilowatts, megawatts, or gigawatts. A 

good analogy is that demand refers to the size of a pipe 

and energy to the amount of water fl owing through the 

pipe. The amount of generation or transmission capacity in a network is primarily driven by the peak load. 

Therefore, a potential estimate that addresses the ability 

of effi ciency to displace a supply-side investment must 

address the ability of effi ciency to reduce the peak load. 

This must include consideration of the timing of the 

system peak load, both daily and seasonally. 

Most potential estimates are initially based on the 

calculation of energy savings for two reasons. First, the 

monetary savings from an effi ciency measure are most 

directly related to the amount of energy saved, and 

second, energy is easier to measure than demand, as 

timing and diversity between individual loads is not as 

critical. There are a variety of methods for estimating 

the peak demand reduction from an effi ciency measure, 

described in more detail in Appendix C. 

The VELCO study assessed the ability of effi ciency to address a transmission shortage during winter peak loads. 

Therefore, the demand reduction calculation considered 

savings from measures that reduce load during the winter peak. For example, air conditioning measures do not 

contribute to winter peak savings, although they might 

contribute substantial energy savings over the course of 

the year. The demand reduction calculation in the VELCO 

study used hourly load-shape information for a variety of 

end-uses and building types, based on simulation modeling of large numbers of prototypical buildings. These 

load-shapes were analyzed to determine the percentage 

of all energy consumed during the periods of interest, 

from which coincidence and diversity factors were developed. Other approaches include direct metering studies, 

or impact evaluations of past effi ciency program efforts. 

5.6.3 Supply-Side Alternatives for the Utility: 

Additional Cost-Effectiveness Tests 

Regardless of a potential study’s objective, the TRC 

and SCT provide important indicators of the economic 

effects of pursuing effi ciency. In some cases, such as 

when conducting a potential study to assess alternatives 

to supply-side investments, additional cost-effectiveness 

tests provide important context for decision-makers. In 

the VELCO case, the utility responsible for the potential 

new transmission line needed to understand the relative costs and benefi ts of the different supply-side and 

demand-side alternatives. The effect of these choices on 

its ratepayers was also an important concern. The utility 

therefore implemented the utility cost test and RIM test. 

Because it excludes the benefi ts that accrue to the enduse customers (primarily from energy savings), the RIM 

test usually results in lower cost-effectiveness than the 

TRC or SCT. In addition, investment in effi ciency may 

result in higher utility rates (i.e., price per kWh or therm) 

for the average customer, even though average total 

energy bills (i.e., total dollar spending on energy) will 

go down.5 

5.7 Presentation of Results 

A potential study that identifi es alternatives to supplyside investments still generates the same set of outputs 

as do potential studies for other objectives. On the 

other hand, a different results presentation may be 

more informative or useful for the decision-makers. 

If multiple cost-effectiveness tests are conducted, a 

clear explanation of their differences and a side-byside comparison of the results will highlight the tradeoffs between, for example, the societal and ratepayer 

perspectives. Additional comparisons may be drawn 

between the effi ciency case and the supply-side alternative if data on the latter are available. Although they 

have not yet been made public, preliminary strategies 

for conveying the results of the VELCO study have 

focused on comparing the costs of the transmission 

alternative to various alternative resource confi gurations 

(ARCs) that include differing combinations of effi ciency 

and distributed generation. The example table below 

indicates the types of data of primary interest to the 

intended audience. 

5-6 Guide For Conducting Energy Effi ciency Potential Studies 
Table 5-1. Sample Table Comparing Transmission Alternatives in VELCO Territory 

Transmission 

ARC1 

(100% Effi ciency 

Plus DR) 

ARC2 (Generation) 

ARC3 

(50% Effi ciency 

+ Generation) 

NPV Societal Costs $x million $x million $x million $x million 

Firm MW, 2016 xxx xxx xxx xxx 

Capital Required 

2008-2016 (000’s) $xxx,xxx $xxx,xxx $xxx,xxx $xxx,xxx 

Illustrative Retail 

Rate, 2016 (cents/ 

kWh) 

xx xx xx xx 

Table is presented for illustrative purposes only without results. Actual study data are not yet available. 

In this case, a comparison of the energy impacts was 

secondary, as the effi ciency case was designed to provide 

comparable peak energy “supply” as the supply-side 

alternative. Note the importance of economic outputs of 

the study, and the need to ensure comparability with the 

outputs from other modeling or planning efforts such as 

those focused on the costs and benefi ts of investment in 

new generation, as modeled in the ARC2 scenario. 

An additional consideration when assessing alternatives to supply-side investments is the need to interface 

with the utility planning process. Often, utilities conduct 

modeling to evaluate the effects of different investments on the energy system. These models may require 

more detail than typically generated by a potential 

study. In particular, utility modeling is usually based on 

an hour-by-hour simulation of the energy system over 

an entire year, but an hourly distribution of effi ciency 

measure savings is rarely available. One approach is to 

use the same load-shape information that facilitates 

peak demand reduction calculations to determine the 

annual hourly distribution, which ensures consistency 

between the peak load calculation and the hourly outputs. If this is done, care must be taken to ensure that 

hourly loadshapes for each end-use and building type 

are calibrated to overall system hourly loads. 

5.8 Conclusion 

The following table summarizes the key attributes of 

the two example studies presented in this chapter. 

National Action Plan for Energy Effi ciency 5-7
Table 5-2. Summary of Example Potential Studies: Identifying Alternatives to 

Supply-Side Investment 

VELCO “Southern Loop” ACEEE Texas 

Scope Electric potential in small geographic area 

Electric potential in Texas 

Potential Type Achievable program potential in 

targeted geographic area 

Economic and program 

Objective Determine whether the construction of a transmission line could 

be deferred or replaced with 

aggressive effi ciency 

Determine the potential for effi ciency as an alternative to new 

coal plants 

Audience The VELCO decision-makers Legislature and action groups 

Data Sources Primary (site audits), Census, and 

state forecasts 

Census, EIA, ERCOT, commercial 

economic data 

Analytical Methodology Bottom-up for residential, 

top-down for commercial 

and industrial 

Bottom-up for economic potential, 

top-down for program potential 

Program Design/Penetrations 

Assumed aggressive pursuit of 

effi ciency opportunities and high 

percentages of retrofi t and new 

construction opportunities over 10 

years, plus staggered implementation of retrofi ts measures in two 

sub-regions 

Develops savings factors for the 

proposed policies from a variety 

of sources 

Cost-Effectiveness Tests SCT Modifi ed participant for economic, 

N/A for program 

Results Effi ciency could: 

• Provide yearly savings of more 

than 30 MW and 150 GWh on 

the Southern Loop 

• Yield nearly $70 million in net 

utility benefi ts 

Effi ciency could: 

• Meet 107% of growth in summer peak demand 

• Reduce energy consumption by 

22% in 15 years 

5-8 Guide For Conducting Energy Effi ciency Potential Studies 
5.9 Notes
 

1. 	 These ranges should be viewed as approximate. They are based 

on a sample of studies and are not intended to defi ne the absolute limit of these parameters. 

2. 	 The cited report is part of testimony to be fi led with the Vermont 

Public Service Board in relation to the Southern Loop project. It 

had not yet been fi led at the time of this Guide’s publication. 

Preliminary information regarding the consideration of effi ciency 

as an alternative to transmission investments can be found in 

Southern Loop Utility Search Conference Background Report, produced for CVPS and VELCO and available at <www.velco.com/ 

Files/Southern%20Loop/VTsoloop%20rpt%20fi nal.pdf>. When 

fi led, the testimony will be available on the Public Service Board 

Web site, <www.state.vt.us/psb>. 

3. 	 The VELCO study used a combination of top-down and bottom-up analyses for the commercial and industrial sector. The 

top-down portion was implemented with greater detail and 

customer-specifi c information than the analyses described in 

Chapter 4. The more detailed approach includes a calculation of 

savings potential for each measure, using a formula similar to 

that used in the residential bottom-up analysis. The main difference is the use of a factor for percentage of energy saved in place 

of a per-unit energy savings quantity. 

4. 	 In non-electric effi ciency potential studies, the units of energy 

might be gallons of oil, therms of natural gas, or pounds of steam. 

5. 	 This rate versus bill distinction is an important part of the policy 

considerations for effi ciency programming, as it raises issues of 

the distributional effects of effi ciency policies and spending. A 

discussion of these issues and potential policy approaches to 

addressing them is beyond the scope of this paper. Please refer 

to the National Action Plan for Energy Effi ciency (2006) for 

additional information. 

National Action Plan for Energy Effi ciency 5-9

Applying the Concepts: 

Detailed Planning and 6: Program Design 

This chapter discusses potential studies in situations where the policy decision to invest in efficiency has already be made. For this study application, it is assumed that there is no need to build a case for supporting 

efficiency, as the decision to invest in energy efficiency has already been made. Instead, these studies focus 

on how much to spend on efficiency and how that money can best be spent. The types of studies described 

in this chapter tend to focus more on the disaggregated results (e.g., is there more opportunity in lighting 

or HVAC?) than other types of potential studies. The cost is typically $75,000–$500,000, with the associated 

time-to-completion between 4 and 12 months. The large ranges with this application are mostly due to 

variations in study design. This application can be used to evaluate both small programs and large portfolios of programs, with the latter being more expensive and time-consuming.1 

6.1 Key Questions
 

The following questions will help entities ensure that 

a detailed planning and program potential study is the 

appropriate application: 

• 	Has the decision to invest in effi ciency already been 

made? 

• 	Are data needed primarily to aid in decisions about 

which market sectors, targeted geographic areas, 

end uses, measures, and programs should be tapped 

to realize effi ciency potential? 

• 	Are study fi ndings intended primarily for energy effi ciency planners who will incorporate the results into 

portfolio decisions? 

• 	What is the history of effi ciency programming in this 

area? What effect does this history have on the assumptions we make about program potential? 

• 	Should the study focus on one particular end use, customer segment, or set of measures? Are data available 

that can give reasonable disaggregated results? 

6.2 Objective and Audience 

Previous chapters presented potential studies as tools 

used when attempting to answer the question of whether or not effi ciency programming should be pursued, 

whether for general policy reasons or to address specifi c energy system needs. This chapter presents a third 

scenario, one where the decision to invest in effi ciency 

has been made and the questions are how the investment should be made and to what extent. A potential 

study with this objective might provide guidance on the 

best ways to structure effi ciency programs, the relative 

costs and benefi ts of different approaches to acquiring a 

given effi ciency resource, or the effi ciency potential given 

a particular program structure and budget. It also might 

focus on specifi c sets of measures or customer types that 

are applicable to a specifi c program, rather than considering all possible technologies and markets. For example, 

a study might specifi cally look at commercial lighting opportunities. These studies likely have a narrower audience 

than those discussed previously, with utilities, effi ciency 

program administrators, and public utility commissions 

the most interested parties. 

6.3 Example Application: 


California Potential Study
 

California is one of the nation’s most energy-effi cient 

states, having kept per capita energy use fl at for over 

two decades (Goldstein, 2007). Sustained energy effi ­

ciency efforts have been a key contributor to this accomplishment, yet the state continues to seek additional 

effi ciency opportunities. Several years ago, the four large 

investor-owned utilities (IOUs) in California commissioned 

National Action Plan for Energy Effi ciency 6-1
Questions for the Analyst 

• After deciding that the objective of a potential

study is to inform the planning and program design 

process, the project manager should ask the analyst 

the following questions to help guide the contracting process. Raising these issues early can ensure 

that key assumptions and data inputs are incorporated into the analysis, and that the fi nal “deliverable” meets the project manager’s requirements for 

cost, scope, and rigor. 

• What is the main purpose of the study? To which 

specifi c program areas or markets is it targeted? 

• How will the study be used, and by what audience? What level of disaggregation of results is 

important to ensure its usefulness? 

– What data are available? 

– Does the contracting fi rm have access to proprietary data? 

– What local utility data are available? 

– Are available data of suffi cient detail and quality to provide disaggregated results? 

– Is there a need to do primary onsite data collection? If so, what are the most important 

markets and technologies to collect data for? 

• What are the trade-offs between statistical precision and level-of-effort in the primary data collection process? 

• What demand-side resources should the analyst 

include? Effi ciency only? Demand response? Combined heat and power? Fuel switching? Onsite 

distributed generation? Renewables? 

• Should the analysis be tied to specifi c program 

designs? What level of detail on program budgets 

is required? 

• What is the basis for estimated market penetrations of effi ciency? 

– How are baseline assumptions developed? 

– Are they consistent with the underlying 

forecast? 

• Should the analyst focus on maximum achievable

potential for different markets, or focus on the 

achievable levels given specifi c program designs 

and funding levels? What are the most important 

pieces of information needed? 

• Are the costs and benefi ts of effi ciency carefully 

accounted for and presented in cost-effectiveness 

tests? Are discount rates and other assumptions 

clearly stated and reasonable? 

• What specifi c results are necessary? 

– How can results be presented to be most compelling to the target audience? 

– What level of disaggregation should be presented? 

– Should sensitivity analyses be conducted to

provide a range of results given different 

assumptions? 

a series of studies to assess energy effi ciency potential 

in the wake of the energy crisis in 2000 and 2001. This 

chapter describes one study from this series that addressed energy effi ciency (both electric and natural gas) 

in the residential sector (KEMA-XENERGY, 2003a). 

6.4 Potential Type
 

The California study was conducted because “policymakers are most interested in knowing the amount 

of savings or resource reduction that could occur in 

6-2 Guide For Conducting Energy Effi ciency Potential Studies 
response to a particular set of programs or policies” (p. 

1-6). Although the study presents a sequence of analyses to estimate the technical, economic, and maximum 

achievable potentials, the end product is a set of program potential estimates that provide a range of results 

based on variation in program funding and energy price 

forecasts. This is the key difference between the program potential and the maximum achievable potential 

estimates in this case. By modeling the interaction between program spending, energy costs, and the adoption of effi ciency measures, the study is able to assess 

program potential for a number of scenarios. 

6.5 Level of Detail and Data 

Requirements 

Studies that are intended primarily for program design 

purposes may be similar to studies done to build the 

case for effi ciency or to analyze effi ciency as an alternative to supply-side investment. There are two key 

differences when supporting detailed program planning. First, the level of accuracy of disaggregated results 

is much more important. Second, the level of effort 

put into program budgeting and measure penetration 

rates is higher and must explicitly recognize the specifi c 

detailed program designs contemplated. The latter is 

discussed more fully below. 

Planners may contemplate programs that target very 

specifi c markets (e.g., an “effi cient schools” program 

or an air conditioner program). Obviously, this means 

that, for example, estimates of schools’ potential need 

to be reasonably accurate. When building a case for 

effi ciency, if the distribution of opportunities between, 

say, schools and offi ces is somewhat inaccurate it may 

not matter, so long as overall results refl ect the entire area studied. Similarly, if only air conditioners are 

promoted, having precision on the actual distribution 

of different size air conditioners and annual sales of AC 

units is obviously more critical. As a result, while some 

program planning potential studies are limited in scope, 

they generally require more detailed data and better 

disaggregation. 

For example, the California study is limited to existing 

residential construction; new homes are not included. 

The analysis includes a relatively limited set of measures 

that were commercially available at the time and most 

likely to be included in potential new programs under 

consideration, rather than a comprehensive list of existing and emerging technologies. 

The long history of effi ciency programs in California generated a comparatively rich data set from which the study 

authors drew information to inform their analysis. In 

particular, the California Energy Commission has a long 

history of conducting research and evaluation of energy 

consumption and effi ciency programs. While this will not 

necessarily be the case in other jurisdictions, one is more 

likely to conduct this type of potential study where effi ­

ciency programming already exists. In areas with relatively 

little experience, proven program designs may be implemented without the need to conduct detailed potential 

estimates. Where more detailed data are necessary but 

not available, primary research may be indicated. 

6.6 Methodology 

Previous chapters describe both top-down and bottomup methodologies and address the variety of cost-effectiveness tests applied to potential estimates. This section 

addresses issues of program budget estimates and their 

role in cost-effectiveness screening. In addition, the connection between program spending and assumptions of 

penetrations warrants additional focus. 

Though energy effi ciency almost always provides positive net benefi ts to both society and program administrators, it costs money to make it happen. The costs 

of effi ciency programs can be divided into measure 

costs related directly to effi ciency measures and nonmeasure costs that are necessary and important to 

effi ciency programs but do not directly lead to measure 

adoptions. Accounting for measure costs depends on 

the perspective taken in the cost-effectiveness tests. If 

a societal or total resource cost test is used, the measure costs include the incremental cost of effi ciency 

measures and any installation costs, regardless of who 

National Action Plan for Energy Effi ciency 6-3
 

pays them. When using a utility or ratepayer test, the 

measure costs are limited to the program measure 

costs, and do not include participant contributions. 

Non-measure costs consist of spending on administrative, staffi ng, marketing, data tracking, monitoring, and 

evaluation activities. 

For a high-level study, non-measure cost estimates are 

often determined by applying cost adders to the modeled measure or fi nancial incentive costs, based on 

typical ratios of program non-measure costs (for things 

such as administration, etc.) to measure costs or incentives. For a more detailed study that supports program 

planning and design, more detailed budgets should be 

derived. There are a range of budget categories to consider, including staffi ng, outside engineering assistance, 

annual evaluation costs, etc. 

The California study estimates administrative costs for 

a range of effi ciency scenarios. While specifi c details 

are not given, the administrative cost estimate is constructed using a formula that includes both a fi xed 

component and a component that varies with the 

program savings estimate. This is likely to be a better 

representation than a simple cost adder. Other example 

studies discussed earlier in this Guide, including the 

VELCO study, relied on non-measure cost estimates built 

up from individual line items for staffi ng, contractors, 

marketing, and other components. 

For higher level studies, one may apply typical penetration rates across broad categories of measures, or 

estimate program costs across all markets that generally refl ect typical categories of programs. However, for 

estimating the actual program potential for a given program, specifi c penetrations by measure and customer 

type should be estimated based on the actual program 

strategies. Similarly, specifi c program budgets should 

be built up based on estimates of costs for each major 

budget item. 

6.7 Presentation of Results 

Again, the results from a potential study that contributes to program planning and design are no different 

than the results of other potential studies. If supported 

by a greater level of detail in the inputs, the study can 

provide decision-makers with more detailed results, 

even to the level of building type, end-use, or individual 

effi ciency measures. In support of summary results tables, appendices to the California study provide detailed 

tables listing the savings estimates for each effi ciency 

measure under each program scenario, one of which 

is shown in part below. These data can facilitate discussion regarding program design by indicating which 

measures are likely to generate the largest savings. 

Figure 6-1. Savings Estimates for Select Measures
 

Utility and Segment 

CEC SF=Sing Fam 

maFtluM=FMtsaceroF latoT GWh Potentials 

PG&E-CZ01 SF pre-7 Air Conditioning 35.0 49.9% 19.3% 7.1% 2.4% 1.6% 1.1% 0.1% 

PG&E-CZ01 SF pre-79 Clothes Drying 107.6 2.6% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

PG&E-CZ01 SF pre-79 Clothes Washing 25.0 40.2% 40.2% 12.7% 9.8% 7.2% 4.9% 0.4% 

PG&E-CZ01 SF pre-79 Dishwashing 37.6 8.4% 8.4% 2.8% 2.1% 1.6% 1.2% 0.1% 

PG&E-CZ01 SF pre-79 Freezer 40.8 7.7% 7.7% 2.0% 0.2% 0.1% 0.0% 0.0% 

PG&E-CZ01 SF pre-79 Lighting 324.1 32.5% 30.4% 23.1% 21.1% 12.8% 6.3% 1.1% 

PG&E-CZ01 SF pre-79 Other 192.5 

PG&E-CZ01 SF pre-79 Pool Pump 31.3 43.5% 43.5% 14.2% 8.4% 6.3% 4.4% 0.5% 

PG&E-CZ01 SF pre-79 Refrigerator 167.3 43.5% 34.8% 27.5% 7.0% 5.2% 3.9% 1.5% 

PG&E-CZ01 SF pre-79 Space Heating 165.6 30.4% 18.1% 12.9% 9.2% 6.5% 4.3% 1.1% 

PG&E-CZ01 SF pre-79 Water Heating 30.7 56.3% 14.1% 4.7% 3.8% 3.5% 3.1% 4.6% 

PG&E-CZ01 SF post-78 Air Conditioning 56.3 62.8% 30.0% 7.9% 3.1% 2.1% 1.3% 0.2% 

PG&E-CZ01 SF post-78 Clothes Drying 111.3 2.6% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

PG&E-CZ01 SF post-78 Clothes Washing 25.9 40.2% 40.2% 12.7% 9.8% 7.2% 4.9% 0.4% 

PG&E-CZ01 SF post-78 Dishwashing 38.9 8.4% 8.4% 2.8% 2.1% 1.6% 1.2% 0.1% 

PG&E-CZ01 SF post-78 Freezer 42.2 7.7% 7.7% 2.0% 0.2% 0.1% 0.0% 0.0% 

PG&E-CZ01 SF post-78 Lighting 311.8 34.9% 32.7% 24.9% 22.6% 13.7% 6.7% 1.2% 

Source: KEMA-Xenergy, 2003b. 

6-4 Guide For Conducting Energy Effi ciency Potential Studies 
6.8 Conclusion 6.9 Notes 

1. These ranges should be viewed as approximate. They are based The following table summarizes the key attributes of on a sample of studies and are not intended to defi ne the abso­ the example study presented in this chapter. lute limit of these parameters. 

Table 6-1. Summary of Example Potential Study: Detailed Planning and 

Program Design 

KEMA California 

Scope Electric and natural gas potential in residential sector existing 

buildings 

Potential Type Technical, economic, maximum achievable, and program 

Objective Develop a comprehensive effi ciency plan 

Audience City Public Service (a utility serving the San Antonio area) 

Data Sources California Energy Commission, other state-specifi c reports 

Analytical Methodology Bottom-up for all potential types 

Program Design/Penetrations Detailed “adoption model” to estimate penetrations based on 

incentives and energy costs 

Cost-Effectiveness Tests 

Results 

TRC 

Effi ciency could: 

• Achieve 15,643 MW (36%) and 19,710 GWh (28%) in technical 

potential 

• Achieve 3,564 MW (23%) and 15,084 GWh (21%) in economic 

potential 

• Achieve 1,773 MW (11%) and 9,826 GWh (14%) with maximum 

achievable funding levels 

• Achieve 907 MW (6%) and 6,327 GWh (9%) with a 100% budget 

increase 

• Achieve 611 MW (4%) and 4,149 GWh (6%) with a 50% budget 

increase 

• Achieve 385 MW (2%) and 2,413 GWh (3%) with unchanged 

budget 

National Action Plan for Energy Effi ciency 6-5

7: Conclusion
 

The objective of this Guide is to provide decision-makers 

with suffi cient information to understand the process of 

conducting a potential study and the important inputs 

and methodological considerations involved. The Guide 

presents this information in the form of several completed potential studies that cover a range of scenarios, 

objectives, and applications. The fi gure below, repeated 

from Chapter 2, summarizes the relationship between 

cost, level of detail, and the scenarios. While there are 

certain to be some exceptions, the general trend is a useful heuristic for decision-makers commissioning a study. 

This Guide identifi es a number of important considerations in conducting a potential study. These are: 

• 	Because data availability is often the limiting factor 

for an analysis, structure the methodology and level 

of detail based on the best available data. Consider 

primary data collection when the study objectives 

warrant the additional expense and complexity. 

• 	Select the appropriate potential type(s) to analyze. 

For most applications, an achievable or program potential is likely to provide the most useful information 

for decision-makers and stakeholders. 

• 	Select the appropriate cost-effectiveness tests to 

apply to effi ciency investment. Presenting results 

from multiple tests, while adding complexity to the 

analysis, provides important information on the distribution of the costs and benefi ts of effi ciency investments among consumers, utilities, and public entities. 

For additional detail on the methodology of potential 

studies, please refer to Appendix C, Detailed Methodology Discussion. 

Figure 7-1. Considerations for Conducting Potential Studies 

Detailed Planning and Program Design High (Single Program) (Program Portfolio) 

Identifying Alternatives to Medium
 

Supply-Side Investment
 

Building the Case for 


Energy Efficiency
 

Low Medium High 

Cost and Length of Time to Complete 

Level of Detail 

Low

National Action Plan for Energy Effi ciency 7-1

National Action Plan 

Appendix for Energy Effi ciency A: Leadership Group
 

Co-Chairs
 

Marsha Smith 

Commissioner, Idaho Public 

Utilities Commission 

President, National Association of Regulatory Utility 

Commissioners 

James E. Rogers 

Chairman, President, and 

C.E.O.
 

Duke Energy
 

Leadership Group 

Barry Abramson 

Senior Vice President 

Servidyne Systems, LLC 

Tracy Babbidge 

Director, Air Planning 

Connecticut Department of 

Environmental Protection 

Angela S. Beehler 

Director of Energy 

Regulation 

Wal-Mart Stores, Inc. 

Jeff Bladen 

General Manager, Market 

Strategy 

PJM Interconnection 

Sheila Boeckman 

Manager of Business Operations and Development 

Waverly Light and Power 

Bruce Braine 

Vice President, Strategic 

Policy Analysis 

American Electric Power 

Cheryl Buley 

Commissioner 

New York State Public 

Service Commission 

Jeff Burks 

Director of Environmental 

Sustainability 

PNM Resources 

Kateri Callahan 

President 

Alliance to Save Energy 

Jorge Carrasco 

Superintendent 

Seattle City Light 

Lonnie Carter 

President and C.E.O. 

Santee Cooper 

Gary Connett 

Manager of Resource Planning and Member Services 

Great River Energy 

Larry Downes 

Chairman and C.E.O. 

New Jersey Natural Gas 

(New Jersey Resources 

Corporation) 

Roger Duncan 

Deputy General Manager, 

Distributed Energy Services 

Austin Energy 

Angelo Esposito 

Senior Vice President, Energy Services and Technology 

New York Power Authority 

Jeanne Fox 

President 

New Jersey Board of Public 

Utilities 

Anne George 

Commissioner 

Connecticut Department 

of Public Utility Control 

Dian Grueneich 

Commissioner 

California Public Utilities 

Commission 

Blair Hamilton 

Policy Director 

Vermont Energy Investment Corporation 

Leonard Haynes 

Executive Vice President, 

Supply Technologies, 

Renewables, and Demand 

Side Planning 

Southern Company 

Mary Healey 

Consumer Counsel for the 

State of Connecticut 

Connecticut Consumer 

Counsel 

Joe Hoagland 

Vice President, Energy 

Effi ciency and Demand 

Response 

Tennessee Valley Authority 

Sandy Hochstetter 

Vice President, Strategic 

Affairs 

Arkansas Electric 

Cooperative Corporation 

Helen Howes 

Vice President, Environment, Health and Safety 

Exelon 

Bruce Johnson 

Director, Energy 

Management 

Keyspan 

Mary Kenkel 

Consultant, Alliance One 

Duke Energy 

Ruth Kiselewich 

Director, Conservation 

Programs 

Baltimore Gas and Electric 

Rick Leuthauser 

Manager of Energy 

Effi ciency 

MidAmerican Energy 

Company 

Harris McDowell 

Senator 

Delaware General Assembly 

Mark McGahey 

Manager 

Tristate Generation 

and Transmission 

Association, Inc. 

Ed Melendreras 

Vice President, Sales and 

Marketing 

Entergy Corporation 

Janine Migden-Ostrander 

Consumers’ Counsel 

Offi ce of the Ohio 

Consumers’ Counsel 

Michael Moehn 

Vice President, Corporate 

Planning 

Ameren Services 

National Action Plan for Energy Effi ciency Appendix A-1 
Fred Moore 

Director Manufacturing & 

Technology, Energy 

The Dow Chemical 

Company 

Richard Morgan 

Commissioner 

District of Columbia Public 

Service Commission 

Brock Nicholson 

Deputy Director 

Division of Air Quality 

North Carolina Air Offi ce 

Pat Oshie 

Commissioner 

Washington Utilities and 

Transportation Commission 

Douglas Petitt 

Vice President, 

Government Affairs 

Vectren Corporation 

Bill Prindle 

Deputy Director 

American Council for an 

Energy-Effi cient Economy 

Phyllis Reha 

Commissioner 

Minnesota Public Utilities 

Commission 

Roland Risser 

Director, Customer Energy 

Effi ciency 

Pacifi c Gas and Electric 

Gene Rodrigues 

Director, Energy Effi ciency 

Southern California Edison 

Art Rosenfeld 

Commissioner 

California Energy 

Commission 

Gina Rye 

Energy Manager 

Food Lion 

Jan Schori 

General Manager 

Sacramento Municipal 

Utility District 

Ted Schultz 

Vice President, 

Energy Effi ciency 

Duke Energy 

Larry Shirley 

Division Director 

North Carolina Energy 

Offi ce 

Tim Stout 

Vice President, Energy 

Effi ciency 

National Grid 

Deb Sundin 

Director, Business Product 

Marketing 

Xcel Energy 

Paul Suskie 

Chairman 

Arkansas Public Service 

Commission 

Dub Taylor 

Director 

Texas State Energy Conservation Offi ce 

Paul von Paumgartten 

Director, Energy and Environmental Affairs 

Johnson Controls 

Brenna Walraven 

Executive Director, National Property Management 

USAA Realty Company 

Devra Wang 

Director, California Energy 

Program 

Natural Resources Defense 

Council 

J. Mack Wathen 

Vice President, Regulatory 

Affairs 

Pepco Holdings, Inc. 

Mike Weedall 

Vice President, Energy 

Effi ciency 

Bonneville Power 

Administration 

Zac Yanez 

Program Manager 

Puget Sound 

Henry Yoshimura 

Manager, Demand 

Response 

ISO New England Inc. 

Dan Zaweski 

Assistant Vice President 

of Energy Effi ciency and 

Distributed Generation 

Long Island Power Authority 

Observers 

Keith Bissell 

Attorney 

Gas Technology Institute 

Rex Boynton 

President 

North American Technician 

Excellence 

James W. (Jay) Brew 

Counsel 

Steel Manufacturers 

Association 

Roger Cooper 

Executive Vice President, 

Policy and Planning 

American Gas Association 

Dan Delurey 

Executive Director 

Demand Response Coordinating Committee 

Reid Detchon 

Executive Director 

Energy Future Coalition 

Roger Fragua 

Deputy Director 

Council of Energy 

Resource Tribes 

Jeff Genzer 

General Counsel 

National Association of 

State Energy Offi cials 

Donald Gilligan 

President 

National Association of 

Energy Service Companies 

Chuck Gray 

Executive Director 

National Association of 

Regulatory Utility Commissioners 

Steve Hauser 

President 

GridWise Alliance 

William Hederman 

Member, IEEE-USA Energy 

Policy Committee 

Institute of Electrical and 

Electronics Engineers 

Marc Hoffman 

Executive Director 

Consortium for Energy 

Effi ciency 

John Holt 

Senior Manager of 

Generation and Fuel 

National Rural Electric 

Cooperative Association 

Eric Hsieh 

Manager of Government 

Relations 

National Electrical Manufacturers Association 

Lisa Jacobson 

Executive Director 

Business Council for 

Sustainable Energy 

Kate Marks 

Energy Program Manager 

National Conference of 

State Legislatures 

Appendix A-2 Guide For Conducting Energy Effi ciency Potential Studies 
Joseph Mattingly 

Vice President, Secretary 

and General Counsel 

Gas Appliance Manufacturers Association 

Kenneth Mentzer 

President and C.E.O. 

North American Insulation 

Manufacturers Association 

Diane Munns 

Executive Director, Retail 

Energy 

Edison Electric Institute 

Michelle New 

Director, Grants and 

Research 

National Association of 

State Energy Offi cials 

Ellen Petrill 

Director, Public/Private 

Partnerships 

Electric Power Research 

Institute 

Alan Richardson 

President and C.E.O. 

American Public Power 

Association 

Andrew Spahn 

Executive Director 

National Council on 

Electricity Policy 

Rick Tempchin 

Director, Retail Distribution 

Policy 

Edison Electric Institute 

Mark Wolfe 

Executive Director 

Energy Programs 

Consortium 

Facilitators
 

U.S. Department of Energy 

U.S. Environmental 

Protection Agency 

National Action Plan for Energy Effi ciency Appendix A-3 

Appendix

B: Glossary

Achievable potential: The amount of energy use that 

effi ciency can realistically be expected to displace assuming the most aggressive program scenario possible 

(e.g., providing end-users with payments for the entire 

incremental cost of more effi ciency equipment). This is 

often referred to as maximum achievable potential. 

Applicability factor: The number of units per customer eligible for a certain measure. 

Cost-effectiveness: A measure of the relevant economic effects resulting from the implementation of an 

energy effi ciency measure. If the benefi ts outweigh the 

cost, the measure is said to be cost-effective. 

Economic potential: Refers to the subset of the 

technical potential that is economically cost-effective as 

compared to conventional supply-side energy resources. 

End-use: A category of equipment or service that 

consumes energy (e.g., lighting, refrigeration, heating, 

process heat). 

Energy effi ciency: The use of less energy to provide 

the same or an improved level of service to the energy 

consumer in an economically effi cient way. 

Feasibility factor: The fraction of the units that can 

technically be replaced with an effi cient alternative from 

an engineering point of view. 

Lost-opportunity: Refers to an effi ciency measure or 

effi ciency program that seeks to encourage the selection of higher-effi ciency equipment or building practices 

than would typically be chosen at the time of a purchase or design decision. 

Measure: Installation of equipment, subsystems, or 

systems, or modifi cation of equipment, subsystems, systems, or operations on the customer side of the meter, 

in order to improve energy effi ciency. 

Net penetration rate: The difference between the anticipated adoption rate of the effi ciency measures after 

intervention and the “business as usual” adoption rate 

absent effi ciency intervention. 

Participant cost test: A cost-effectiveness test that 

focuses on either “typical” or aggregate participating 

customer(s), comparing quantifi able benefi ts and costs. 

Portfolio: Either (a) a collection of similar programs addressing the same market, technology, or mechanisms or 

(b) the set of all programs conducted by one organization. 

Potential study: A quantitative analysis of the amount 

of energy savings that either exists, is cost-effective, or 

could potentially be realized through the implementation of energy effi cient programs and policies. 

Program: A group of projects with similar characteristics and installed in similar applications. 

Program administrator cost test: A cost-effectiveness 

test that evaluates the impacts of the effi ciency initiatives on the administrator or energy system (sometimes 

referred to as the utility cost test or energy systems test). 

Program potential: Refers to the effi ciency potential 

possible given specifi c program funding levels and designs. Often, program potential studies are referred to 

as “achievable” in contrast to “maximum achievable.” 

Project: An activity or course of action involving one or 

more energy efficiency measures, at a single facility or site. 

Ratepayer impact measure (RIM) test: A cost-effectiveness test that evaluates the impacts on customer rates. 

Retrofi t: Refers to an efficiency measure or effi ciency 

program that seeks to encourage the replacement of 

functional equipment before the end of its operating life 

with higher efficiency units (also called “early-retirement”) 

or the installation of additional controls, equipment, or 

National Action Plan for Energy Effi ciency Appendix B-1 
materials in existing facilities for purposes of reducing 

energy consumption (e.g., increased insulation, lighting 

occupancy controls, economizer ventilation systems). 

Spillover: Reductions in energy consumption and/or 

demand caused by the presence of the energy effi ciency 

program, beyond the program-related gross savings of 

the participants. There can be participant and/or nonparticipant spillover. 

Societal cost test (SCT): A cost-effectiveness test that 

is a variation of the total resource cost test that includes 

monetized effects of externalities (e.g., emissions impacts) benefi ts. 

Technical potential: The theoretical maximum amount 

of energy use that could be displaced by effi ciency, 

disregarding all non-engineering constraints such as 

cost-effectiveness and the willingness of end-users to 

adopt the effi ciency measures. 

Total resource cost (TRC) test: A cost-effectiveness 

test that assesses the impacts of a portfolio of energy 

effi ciency initiatives on the economy at large. The test 

compares the present value of costs of effi ciency for 

all members of society (including costs to participants 

and program administrators) compared to the present 

value of benefi ts, including avoided energy supply and 

demand costs. 

Turnover factor: The portion of existing units that will 

be naturally replaced each year due to failure, remodeling, or renovation. 

Appendix B-2 Guide For Conducting Energy Effi ciency Potential Studies 
Appendix Detailed Methodology C: Discussion 

This appendix provides a summary of a typical analytical framework for conducting a potential study 

as well as additional discussion of the individual components. This is not intended to provide suffi cient 

detail to direct readers to conduct their own studies, but rather to inform them of the types of issues 

that arise during a study so that they may participate meaningfully in discussions of methodology, data 

sources, etc. It should also be noted that this is an example of a typical analytical approach. Numerous 

variations on this method can and do exist, and will generally be developed in consideration of data, 

budget, and time available. 

C.1 Forecasts and Disaggregation
 

Broadly speaking, the objective of a potential study is 

to estimate future energy savings opportunities resulting from the presence of some program or policy to 

promote effi ciency. That is, the potential estimate is 

relative to some scenario that represents business as 

usual. Therefore, the fi rst step in any potential study is 

to predict the future in the absence of intervention to 

promote additional effi ciency investments. This baseline 

scenario forecast provides the context for the comparison of the effi cient scenario. The baseline can be 

characterized in terms of annual kWh consumed, peak 

demand of the system (whatever its boundaries) in MW, 

tons of pollutants emitted, or other metric. In practice, 

the fi rst two metrics are most typically used. 

It is critical to understand what the baseline forecast 

represents. For example, many jurisdictions have some 

effi ciency programming already. Do the forecasts 

include expansion of the existing program, ignore it 

altogether, or somewhere in between? Furthermore, 

does the forecast include assumptions about “natural 

effi ciency” (the proportion of all equipment purchases 

that will fl ow to effi cient products in the absence of any 

programmatic incentives) or changes in building codes 

or other energy use standards (e.g., national ENERGY 

STAR requirements)? 

The effect of economic growth and new construction 

on the forecast should also be understood. Electricity 

demand and consumption typically grow over time 

because there are both new consumers (represented by 

new households, commercial buildings, and industrial 

facilities) and growth in existing consumers’ consumption. Understanding the relative contribution of these 

two factors to the baseline forecast provides important 

input to assumptions made later in the analysis, particularly in determining the number of opportunities for 

different types of effi ciency investment. 

Care should also be taken to ensure that, if forecasts for 

different sectors are derived from different sources, they 

are harmonized to the extent possible. For example, 

the underlying economic or demographic assumptions behind a forecast of residential energy growth 

should match those used to determine industrial energy 

consumption. Another potential pitfall concerns different treatment of some industries or building types by 

different data sources.1 A detailed discussion of this 

issue is beyond the scope of this paper; suffi ce it to say 

that the user should try to understand the underlying 

assumptions and limitations in their input data, as with 

any analytical effort. 

Disaggregating the baseline forecast typically presents 

challenges. Good state- or utility-level energy use data 

are typically not readily available. Utilities may have data 

sets that provide some information on their customer 

population such as building size or industry classifi cation, but many do not. Refer to Section 3.3.2 for a more 

detailed discussion of some of the primary data sources 

on energy consumption in the United States. 

National Action Plan for Energy Effi ciency Appendix C-1 
In some cases, utilities or states have undertaken enduse surveys, particularly in the residential sector. Such 

information is highly valuable for potential studies. Even 

if the survey is several years old, there may be suffi cient 

information to adjust for changes in technology, economy, and demographics since the data were collected. 

For studies that require a robust, detailed understanding 

of energy use by building type or end-use, fi eld visits 

and/or site surveys—which can add substantial cost to 

the overall effort—may be needed to acquire the necessary information. 

C.2 Measure Characterization 

Measure characterization is the determination of parameters for individual or bundles of technologies, services, 

or design practices that defi ne the costs, savings, and 

lifetimes for different measures. Measure characterization will typically rely on research about existing technologies available in the market and their performance, 

as well as engineering calculations and cost estimation. 

Typical steps include: 

• 	Determination of an effi ciency measure, including 

defi ning the baseline effi ciency or practice as well as 

that of the effi cient scenario. 

• 	Calculation of the annual energy savings and peak 

demand impact coincident with the utility system. 

This generally will be specifi c to individual customer 

types, refl ecting differences in operating hours, load 

shapes, existing effi ciency levels, etc. 

• 	Determination of the pattern of savings over time. 

This is dependent on the energy-use load shape of 

the measure. Because energy reductions are more 

valuable at some times than others (e.g., during business hours on a hot summer day versus during the 

night in the winter for electric systems), modeling the 

hourly occurrence of savings is important to estimating the benefi ts from effi ciency. Ideally, hourly data by 

building type and measure will be used. If potential 

study results are integrated with power production 

models, hourly data will typically be necessary. If 

not, aggregated data for seasonal on- and off-peak 

periods may suffi ce, along with “coincidence factors,” which estimate the portion of customer peak 

demand savings that will be coincident with the time 

of the utility system peak. Often development of this 

data requires building simulation modeling or reliance 

on secondary research. 

• 	Determination of differences in operation and maintenance costs of effi cient versus baseline measures. 

For example, if effi cient equipment lasts longer than 

baseline equipment, savings in avoided replacement 

parts may occur. 

• 	Determination of non-energy costs and benefi ts, such 

as savings in water, waste reduction, improvements 

in productivity, etc., related to adoption of effi cient 

systems. 

• 	Determination of the measure cost. For “lost opportunity” measures such as in new construction 

and planned replacement of failing equipment, this 

will typically be the incremental cost of effi cient 

equipment as compared to baseline equipment. For 

discretionary early retirement measures that replace 

functioning equipment or other retrofi t measures 

such as building shell improvements, costs will typically represent the total labor and equipment costs of 

new systems. 

• 	Determination of the average service life of the effi cient alternative. 

• 	Determination of shifts in savings and capital investments over time. For example, initial savings from 

equipment retrofi t measures represent the difference 

in effi ciency between the effi cient equipment and the 

old, ineffi cient existing equipment at a facility. However, this old equipment would naturally be replaced 

at some point in the absence of an effi ciency initiative 

with new equipment at the standard effi ciency available at that time. As a result, the long-term savings 

from early retirement measures are often much less 

than the initial savings. Similarly, the retrofi t defers 

the need for new capital investment to replace the 

old equipment at the normal replacement time. The 

Appendix C-2	 Guide For Conducting Energy Effi ciency Potential Studies 
 

 

 

 

 

present value of this permanent shift in capital expenditures must be taken into account to properly assess 

the cost-effectiveness of these measures. 

C.3 Applying Data Parameters 

While the disaggregated forecast and measure-level 

data provide many of the inputs to a potential estimate 

(along with specifi c penetration rates, described above), 

an analytical approach to combine all these data and 

take account of the many moving parts is necessary. In 

general, there are two main approaches to calculating 

the potential of an effi ciency measure: top-down and 

bottom-up. 

A bottom-up approach fi rst starts with the savings and 

costs associated with replacing one piece of equipment 

with its effi cient counterpart, and then multiplies these 

numbers by the number of measures expected to be 

installed throughout the life of the program. Often, a 

bottom-up approach is preferred for residential analysis 

because of the greater amount of data available and homogeneity of the buildings. While this approach does not 

rely as directly on a disaggregation of the energy use forecast, when using a bottom-up approach it is important to 

calibrate results to the disaggregated data to ensure that 

credible results are obtained. For example, if one has an 

overly high estimate of the number of households with 

electric heat, relying only on a bottom-up approach could 

result in estimated potential that exceeds the total existing heating consumption of all customers. A bottom-up 

approach requires the same basic factors as a top-down 

approach, with a couple of key differences: 

• 	The applicability factor is not expressed as the percentage of eligible kWh sales, but rather as the 

number of customers eligible for a certain measure. 

Depending on the measure, it may range from less 

than one (say, the fraction of customers with a 

dishwasher) to greater than one (say, the number of 

incandescent light bulbs per customer). 

• 	The savings factor is not needed, since a bottom-up 

approach already starts with the energy and demand 

saved by a given measure. 

The resulting formula is: 

Measure Savings = Per Unit Savings 

× # of Households or Customers 

× 	Applicability Factor 

× Feasibility Factor 

× Turnover Factor 

× Net Penetration Rate 

C.4 Industrial Effi ciency Potential
 

Developing a potential analysis for industrial energy consumers can be more complicated than for the residential 

and commercial sectors due to the relative heterogeneity of energy consumption patterns and end-uses across 

different industries. Industrial effi ciency potential estimates can be developed using either a top-down or a 

bottom-up approach, depending on data availability, the 

variability in facility type included in the study, and other 

factors. 

Whereas industry-level data on energy consumption 

may be diffi cult to come by, it is often relatively easy to 

gather economic data at the industry level within an 

area of interest. Therefore, a useful approach starts with 

these data and develops industry-specifi c energy use 

estimates using average energy intensities for each industry. Expressed in kWh per dollar value of output, sales 

volume, or other economic measure, these factors are 

available from the Energy Information Administration’s 

Manufacturing Energy Consumption Survey (see Section 

3.3.2). Depending on the level of rigor required, these 

factors may be verifi ed and/or adjusted by surveying a 

sample of local industries to determine if local conditions 

result in substantially different energy intensities from 

the published averages. Given that most regions have a 

small number of industries responsible for a large fraction of industrial energy use, this type of survey need not 

be exhaustive to provide a valuable increase in accuracy. 

Once industry-level energy use forecasts are in hand, a 

top-down approach using published factors for the potential energy savings available in different industries— 

applied to industry-sector-specifi c economic forecasts—is 

a relatively straightforward way to assess the potential 

National Action Plan for Energy Effi ciency	 Appendix C-3 
available in the area of interest. An example of this approach is found in a study of energy effi ciency potential 

in New York State (NYSERDA, 2003). The potential savings in each industry from this study may be transferred 

to other states or regions and applied to the distribution 

of industrial energy use there. This was recently done in 

a high-level potential study for Texas (Optimal Energy, 

2007). 

A bottom-up approach requires more detailed data 

regarding the average saturation of key energy-using 

equipment in industrial facilities, such as motors, mechanical equipment, refrigeration, etc. Assuming suffi cient data are available or are captured through onsite 

visits, this approach would proceed in the same fashion 

as described above. For a targeted study, resources can 

be focused on accurately characterizing one or a small 

number of industries in the area of interest through site 

visits or surveys. When applying this approach to industrial facilities, it is important to note the heterogeneity in 

the energy savings of various effi ciency measures across 

industries. For example, whereas the average energy 

savings in residential applications are relatively consistent (say, for a more effi cient refrigerator), industrial 

equipment operates under widely variable conditions in 

different facilities. A motor may be in use 250 hours per 

year or 7,500. Any industrial potential estimate must 

acknowledge this variability, include mechanisms to address it, and clearly state the assumptions that result. 

C.5 Understanding Interactions 

Between Effi ciency Opportunities 

While Section 3.4 provides a general overview of typical analytical methods for quantifying overall effi ciency 

potential, care must be taken to recognize the dynamic 

nature of real-world effi ciency adoption and interactions 

among different effi ciency resources. Three major factors 

must be explicitly addressed in any analysis: 

• 	Acknowledging and accounting for the changing 

building and equipment stock over time and its effect 

on future effi ciency opportunities. 

• 	Identifying and adjusting for mutually exclusive 

effi ciency opportunities. 

• 	Estimating the interactions among different effi ciency 

measures. 

Without explicitly adjusting for the above three items, 

signifi cant errors can occur in analysis that result in double counting or other large overestimation of potential. 

The fi rst issue recognizes that as one assumes adoption 

of aggressive effi ciency, the baseline stock of equipment 

becomes different so that future years’ effi ciency opportunities are diminished. For example, in the extreme case 

of a technical or economic potential study, all retrofi t 

opportunities are assumed to be captured immediately. 

Under this scenario, in the short term no remaining opportunities to improve effi ciency at the time of natural 

replacement exist because they have all been captured 

through retrofi t. In the case of achievable potential, 

keeping track of the changes to existing equipment over 

time becomes more critical, as some percentage of opportunities may be captured through retrofi t programs 

while others will be targeted at the time of natural 

replacement. 

The second issue is important because many technologies analyzed may be mutually exclusive. For example, 

an offi ce can replace an existing tank-type water heater 

with either: 1) a high effi ciency tank-type water heater; 

2) a separate storage tank with water heated through a 

heat exchanger off a central boiler; and 3) a point-of-use 

heater. However, all three would not simultaneously be 

installed. Therefore, while each technology’s individual 

effi ciency potential is initially calculated, the aggregate 

effi ciency potential must parse out how much adoption 

will occur from each technology in consideration of the 

others to avoid double counting. 

Finally, the cumulative effi ciency potential will necessarily be less than the sum of the individual potential for 

each measure. This is the result of interactions between 

systems. For example, adoption of effi cient windows or 

insulation will lower the cooling and heating loads in 

building. As a result, once these are installed the effi ciency potential from an effi cient air conditioner or 

Appendix C-4	 Guide For Conducting Energy Effi ciency Potential Studies 
boiler will be lower, as will its cost-effectiveness. Therefore, once individual measure potential is estimated, an 

iterative process must be undergone to properly refl ect 

interactions to determine ultimate total potential for a 

given market segment, customer class, or total sector. 

C.6 Program Budgets 

Though energy effi ciency almost always provides positive 

net benefi ts to both society and program administrators, 

it costs money to make it happen. The budgets associated with energy effi ciency are important components of 

all of the economic tests. The degree of detail that goes 

into determining budgets for an achievable or program 

potential study is driven by the level of detail desired and 

the study’s uses. 

For a high-level study, program budget estimates are often determined by applying cost adders to the modeled 

measure or fi nancial incentive costs, based on typical 

ratios of program non-measure costs (for things such 

as administration, marketing, data tracking, monitoring and evaluation, etc.) to measure costs or incentives. 

Ideally, when using adders, distinct adders should be 

applied to different programs, and adders should vary 

over time. For example, a market transformation program that focuses on upstream efforts at manufacturers 

and distributors may have proportionally much higher 

non-measure costs than an industrial retrofi t program 

that focuses on distinct, site-specifi c opportunities. Similarly, some programs may have very high adders in early 

years for training and marketing, with signifi cant drops 

over time as participation increases and start-up costs go 

away. As with any economic analysis, all dollars should 

be consistent between budgets, avoided costs, measure 

costs, and other inputs in terms of whether they are real 

or nominal, and the years dollars they are expressed in. 

For a more detailed study, especially where the potential 

study may or will be used as a starting point for initiative planning, more detailed budgets should be derived. 

While incentive costs will be driven by estimates of 

installed measure costs and the incentive design (e.g., 

50 percent of incremental costs for new construction), 

there are a range of budget categories to consider. Program budgets should be built up by line item, based on 

expected needs of things like staffi ng, outside engineering assistance, annual evaluation costs, etc. Some typical 

budget line items that should be considered include, but 

are not limited to: 

• 	Administrative management: The portion of upperlevel management costs that will be assigned to any 

individual or portfolio of initiatives. 

• 	Program management: This labor cost is incurred by 

overseeing implementation of any initiative, whether 

using in-house or outsourced staff. 

• 	Project management: Represents labor spent in 

working directly with customers or supporting contractors, architects, or engineers; managing effi ciency 

projects; and providing coordination services and inhouse documentation. 

• 	Business development: Labor costs associated with 

face-to-face sales efforts in bringing participants and 

partners into the initiatives. 

• 	Planning: Costs of establishing initiative strategies 

and ongoing program design and analysis. 

• 	Technical assistance: Providing customers with analysis of individual effi ciency opportunities, including 

opportunity identifi cation and quantifi cation of benefi ts, costs, and performance issues. May be provided 

by a combination of in-house and outsourced staff. 

• 	Administrative: Costs for day-to-day administration 

plus allocated costs for offi ce management, accounting, payroll, fulfi llment (e.g., cutting incentive checks). 

• 	Subcontractors: Could range from outsourced labor 

for any of the above, to subcontractors representing 

the entire workforce for a particular initiative. 

• 	Measurement and verifi cation: Costs to verify 

claimed energy effi ciency savings. Typically includes inhouse quality assurance/control activities as well as preand post-installation inspections of customer sites. 

National Action Plan for Energy Effi ciency	 Appendix C-5 
• 	Tracking: The development, maintenance, and use 

of a data tracking system for customer interaction, 

claimed energy savings (both by customer and in 

aggregate), associated costs, and management and 

regulatory reporting. 

• 	Marketing and advertising: Ranges from radio and/ 

or television advertisements, to developing articles to 

be published in local newspapers or trade journals, to 

the development and maintenance of a Web site and 

program materials. Often includes labor to directly 

market to various entities. 

• 	Technical assistance/design assistance/commissioning/retro-commissioning incentives: 

Project-based incentives separate from direct measure 

incentives to support market-based design and technical service costs. 

• 	Evaluation: The costs of performing third-party 

evaluations of programs. This may include process, 

market, and impact evaluations. 

• 	Performance incentives and lost revenue: Some 

jurisdictions provide performance incentives to program administrators to encourage exemplary performance. Others provide compensation to utilities for 

revenue losses from effi ciency programs. Where these 

costs are a required part of implementing programs, 

they should be included in budgets, depending on the 

economic tests being performed. In economic tests 

from a societal perspective, performance incentives 

and lost revenue are not resource costs in that they 

are simply transfer payments—typically from ratepayers to shareholders or some other entity. 

C.7 Cost-Effectiveness Screening
 

Once all of the data are available to determine the 

energy savings and costs associated with a forecast set 

of effi ciency investments, the analyst can determine the 

overall effects of effi ciency investments or policies. As 

described in Section 3.4, economic effects are of particular interest to decision-makers. The process of assessing 

the economic effects of effi ciency investments is typically 

referred to as “cost-effectiveness screening.” This refers 

to the comparison of the benefi ts of the investment 

to its cost. Effi ciency measures should pass the “costeffectiveness screen” of having positive net benefi ts (i.e., 

benefi ts greater than costs), based on whatever economic tests are applied. 

Screening is conducted using one or more of the tests 

described in Section 3.4.3. To calculate the economic benefi ts from individual measures, benefi ts in individual years 

are calculated, added together, and discounted to provide 

a present value. Accurate estimates ensure that energy 

savings are not counted beyond the predicted lifetime of 

a measure and adjust savings when the baseline changes 

or “shifts” (as discussed above). The major component of 

economic benefi ts generally result from the direct energy 

and demand savings, and are calculated by multiplying 

the savings in each year by that year’s avoided costs for 

energy and demand (if applicable). Additional benefi ts 

can include non-energy economic benefi ts such as reductions in maintenance or replacements costs as well as 

water and other resource savings. Effi ciency measures 

provide savings across multiple years, while costs are typically assumed to be borne in the installation year, so all 

benefi ts and costs should be expressed in terms of their 

present-value in a common year. In the case of economic 

potential estimates, measures that do not pass the costeffectiveness screen will be eliminated from the analysis 

results. These economic results are then used in the application of the range of economic tests. 

Numerous models exist to perform these economic 

screens. Some analysts have their own proprietary 

databases or spreadsheets, while others rely on commercially available software. Each platform has strengths 

and weaknesses, typically as a result of its development 

to support a particular project or projects. A detailed review of these models is beyond the scope of this Guide. 

Nevertheless, just as with other aspects of the analysis, 

the policy-maker should understand the key limitations 

of any model used as part of a potential study and any 

potential biases introduced as a result (e.g., whether 

the model tends to overestimate or underestimate the 

potential, or the cost of achieving that potential). 

Appendix C-6	 Guide For Conducting Energy Effi ciency Potential Studies 
C.8 Notes
 

1. 	For example, municipal wastewater treatment plants 

are sometimes categorized as an industrial load and 

sometimes as commercial. 

National Action Plan for Energy Effi ciency	 Appendix C-7 

Appendix

D: Data Sources 

This appendix lists some common data sources used for potential studies, and a short description of each.
 

Title Description URL Address 

Database for 

Energy Effi cient 

Resources (DEER) 

Sponsored by the California Energy Commission and the 

California Public Utilities commission, this database provides 

a list of measures, with their associate costs, savings, and 

expected lifetime. Note that these data are based on California information, and may have to be adjusted for use in 

other regions. 

<www.energy.ca.gov/ 

deer/> 

Commercial 

Building Energy 

Consumption 

Survey (CBECS) 

CBECS is a survey conducted by the Energy Information 

Administration (EIA) every 4 years. It collects and quantifi es 

“information on the stock of U.S. commercial buildings, 

their energy-related building characteristics, and their energy consumption and expenditures.” This has data for the 

nine census divisions, and is mostly used to fi nd the applicability of a given measure (e.g., the percent of buildings that 

have air conditioning). 

<www.eia.doe.gov/emeu/ 

cbecs/> 

Residential Energy 

Consumption 

Survey (RECS) 

This is the residential counterpart to CBECS, though in addition to the nine census divisions, it also has data for the 

four most populous states–California, Florida, New York, 

and Texas. It also tends to have better consumption data by 

end-use than CBECS. 

<www.eia.doe.gov/emeu/ 

recs/> 

Manufacturing Energy Consumption 

Survey (MECS) 

The manufacturing counterpart to CBECS and RECS. The 

basic unit of data for MECS is the manufacturing establishment, and MECS provides consumption information on 48 

industry groups and 21 industry subsectors. 

<www.eia.doe.gov/emeu/ 

mecs/contents.html> 

Annual Energy 

Outlook 

Released annually by the EIA, this report gives electric load 

forecasts by end-use for the nine census divisions. 

<www.eia.doe.gov/oiaf/ 

aeo/index.html> 

eShapes eShapes data, owned by ITron, are based on audit data for 

more than 20,000 buildings across the country. They consist 

of hourly electricity consumption data for various sectors 

and end-uses. These data are used to fi nd what time of the 

day and year energy savings occur, and the coincidence factor for demand savings. 

<www.itron.com/ 

pages/products_detail. 

asp?ID=itr_000491. 

xml&pgtype=&subID=fb> 

Economy.com Economy.com provides a wide range of economy data and 

forecasts that can be used to help develop an accurate prediction for future load growth. 

<www.economy.com/ 

default.asp> 

National Action Plan for Energy Effi ciency Appendix D-1 
Title Description URL Address 

Utility Information Often, the utilities in the region of interest can provide valuable information on the size of the electric load, load forecast, electric consumption by sector, and more. Also, some 

utilities fund separate organizations to perform market 

research. For example, California’s Pacifi c Gas and Electric 

Company started the Food Service Technology Center to 

test the performance and effi ciency of commercial kitchen 

equipment. 

Food Service Technology 

Center: <www.fi shnick. 

com/> 

Lawrence Berkeley 

National Laboratory (LBNL) 

LBNL is a federal laboratory that performs much research on 

new energy systems and environmental solutions. It releases 

many helpful reports on emerging technology, which can be 

used for measure characterizations. 

<www.lbl.gov/> 

Consortium for 

Energy Effi ciency 

(CEE) 

CEE is a nonprofi t corporation dedicated to promoting the 

manufacture and purchase of energy effi cient products and 

services. It performs market research and sets reasonable 

high-effi ciency standards for a range of different products 

and appliances. 

<www.cee1.org/> 

Industry data Often it is possible to get relevant measure data directly 

from the industry group or manufacturer. Examples include 

the National Electrical Manufacturers Association (NEMA) 

and the American Refrigeration Institute (ARI). Also, equipment catalogs and information sheets are often good 

sources for cost and consumption data. 

NEMA: 

<www.nema.org/> 

ARI: 

<www.ari.org/> 

Census The Energy Consumption Surveys contain good data at the 

census division level, but if you need data at the state or 

county level, you can go to the U.S. Census. While the Census does not contain energy consumption data, it can tell 

you the number of households or businesses in a region. 

<www.census.gov/> 

Appendix D-2 Guide For Conducting Energy Effi ciency Potential Studies 
Appendix Example E: Potential Studies 

This appendix provides a list of past potential studies, with brief descriptions. 

Title/Description Purpose URL Address 

Midwest Examining the Potential 

for Energy Effi ciency to 

Address the Natural Gas 

Crisis in the Midwest. The 

results of this study suggest 

that a modestly aggressive, 

but pragmatically achievable, 

energy effi ciency campaign 

(achieving about a 5% reduction in both electricity and 

natural gas customer use over 

5 years) could produce tens 

of billions of dollars in net 

cost savings for residential, 

commercial, and industrial 

customers in the Midwest. 

This study was conducted 

to examine effi ciency to 

mitigate the effects of rising 

gas prices in the Midwest, 

which uses natural gas at 

a much higher rate than 

the rest of America. Thus 

this case builds a case for 

effi ciency, but also examines how much gas usage 

can be offset by effi ciency 

efforts. 

<www.aceee.org/pubs/ 

u051.htm> 

Northeast Economically Achievable 

Energy Effi ciency Potential 

in New England. This report 

provides an overview of areas 

where energy effi ciency could 

potentially be increased in the 

six New England states. 

This is a meta-study, designed to give policy-makers 

direction on how to implement and direct energy 

effi ciency efforts. 

<www.neep.org/fi les/ 

Updated_Achievable_ 

Potential_2005.pdf> 

Electric Energy Effi ciency 

and Renewable Energy in 

New England: An Assessment of Existing Policies 

and Prospects for the 

Future. This report applies 

analytical tools, such as 

economic and environmental 

modeling, to demonstrate the 

value of consumer-funded energy effi ciency programs and 

renewable portfolio standards 

and addresses market and 

regulatory barriers. 

This study was conducted 

to “contribute to a growing body of work applying 

analytical tools to show the 

value of consumer funded 

energy effi ciency programs 

and renewable portfolio 

standards with new rigor.” 

<www.neep.org/html/ 

NEEP_C&IReview.pdf> 

National Action Plan for Energy Effi ciency Appendix E-1 
Title/Description Purpose URL Address 

Northeast NEEP Initiative Review: 

Commercial/Industrial 

Sectors Qualitative Assessment and Initiative 

Ranking for the Residential 

Sector. Shtick Consulting. 

Submitted to Northeast Energy Effi ciency Partnerships, 

Inc., October 1, 2004. 

This is a qualitative assessment of commercial and industrial initiatives based on 

a quantitative study done 

by Optimal Energy, Inc. and 

Vermont Energy Corporation. It was conducted to 

provide feedback for specifi c effi ciency initiatives. 

<www.neep.org/html/ 

NEEP_C&IReview.pdf> 

Southeast Powering the South, A 

Clean & Affordable Energy Plan for the Southern 

United States. This report 

shows that a clean generation 

mix can meet the region’s 

power demands and reduce 

pollution without raising 

the average regional cost of 

electricity and lists the policy 

initiatives that can make the 

changes. 

This report was developed 

mainly for the purpose of 

building a case for clean 

energy. It estimates potential not only for effi ciency, 

but also for renewables and 

combined heat and power, 

with the aim of offering a 

comprehensive energy plan 

for the Southeast. 

<www.crest.org/articles/ 

static/1/binaries/pts_repp_ 

book.pdf> 

Southwest The New Mother Lode: 

The Potential for More 

Efficient Electricity Use in 

the Southwest. This report 

for the Southwest Energy 

Effi ciency Project examines 

the potential for, and benefi ts 

from, increasing the effi ciency 

of electricity use in the southwest states of Arizona, Colorado, Nevada, New Mexico, 

Utah, and Wyoming. 

This report builds a case 

for effi ciency, analyzing the 

achievable potential and 

macro-economic benefi ts, 

but also examines specifi c 

savings opportunities and 

proposes a range of policy 

recommendations. 

<www.swenergy.org/nml/ 

index.html> 

Appendix E-2 Guide For Conducting Energy Effi ciency Potential Studies 
Title/Description Purpose URL Address 

Southwest A Balanced Energy Plan This report fi rst makes a <http://westernresources. 

(continued) for the Interior West. This 

report shows how energy effi ­

ciency, renewable energy, and 

combined heat and power 

resources can be integrated 

into the region’s existing 

power system to meet growing electric demands in a way 

that is cost-effective, reliable, 

and reduces risk and improves environmental quality 

for the interior west region of 

Arizona, Colorado, Montana, 

New Mexico, Nevada, Utah, 

and Wyoming. 

case for effi ciency and 

renewables, analyzing the 

economic and environmental costs of the status quo, 

and then proposes a specifi c 

“balanced energy plan” for 

the interior west region that 

would essential eliminate 

load growth. 

org/energy/bep.html> 

California California’s Secret Energy 

Surplus: The Potential for 

Energy Effi ciency. This study 

focuses on assessing electric 

energy potential in California through the assessment 

of technical, economic, and 

achievable potential savings 

over the next 10 years. 

This study was commissioned to expand previous 

studies to cover all sectors 

and vintages in California 

for a 10-year horizon. 

<http://docs.cpuc.ca.gov/ 

published/report/30114.pdf> 

California Statewide 

Residential Sector Energy 

Efficiency Potential Study. 

Presents a sequence of analyses to estimate the technical, 

economic, and maximum 

achievable potentials, as well 

as a set of program potential estimates that provide 

a range of results based on 

variation in program funding 

and energy price forecasts. 

Conducted for policymakers interested in knowing 

the amount of savings or 

resource reduction that 

could occur in response to 

a particular set of programs 

or policies. 

<www.env-ne.org/ 

Publications/CT_EE_ 

MaxAchievablePotential 

%20Final%20Report 

June%202004.pdf> 

National Action Plan for Energy Effi ciency Appendix E-3 
Title/Description Purpose URL Address 

Connecticut Independent Assessment 

of Conservation and Energy Effi ciency Potential 

for Connecticut and the 

Southwest Connecticut Region. This study estimates the 

maximum achievable costeffective potential for electric 

energy and peak demand 

savings from energy effi ciency 

measures in the geographic 

region of Connecticut served 

by United Illuminating Company and Connecticut Light 

and Power Company. 

This study gives an estimate of the total potential in Connecticut, but it 

focuses on the 52 towns 

and, in particular, 16 critically constrained areas in 

southwest Connecticut. The 

study concludes that there 

is signifi cant potential in the 

areas it examines. 

<www.env-ne.org/ 

Publications/CT_EE_ 

MaxAchievablePotential 

%20Final%20Report 

June%202004.pdf> 

Florida Potential for Energy 

Efficiency and Renewable 

Energy to Meet Florida’s 

Growing Energy Demands. 

Estimates the capacity for energy effi ciency using building 

energy simulations. 

Provides the state with an 

achievable effi ciency estimate and a suite of policy 

options to consider towards 

realizing this potential. 

<www.aceee.org/pubs/ 

e072.htm> 

Georgia Assessment of Energy Effi ­

ciency Potential in Georgia. 

This report presents a profi le 

of energy use in Georgia; the 

potential for, and public benefi ts of, energy effi ciency; and 

a public policy review. 

This report was written primarily to build the case for 

effi ciency, as there were no 

existing programs in Georgia when the report was 

released. 

<www.gefa.org/Modules/ 

ShowDocument.aspx? 

documentid=46> 

Iowa The Potential for Energy 

Efficiency in Iowa. This 

report uses existing programs, 

surveys, savings calculators, 

and economics simulation 

to estimate the potential for 

energy savings in Iowa. 

The purpose of this study 

was to provide an initial 

estimate of the potential, to 

build the case for effi ciency. 

<www.ornl.gov/sci/btc/ 

apps/Restructuring/ 

IowaEEPotential.pdf> 

Appendix E-4 Guide For Conducting Energy Effi ciency Potential Studies 
Title/Description Purpose URL Address 

Massachusetts The Remaining Electric Energy Effi ciency Opportunities in Massachusetts. This 

report addresses the remaining electric energy effi ciency 

opportunities in the residential, commercial, and industrial sectors in Massachusetts. 

This study focuses on program designs, examining 

how various funding levels 

will affect the savings of 

various building and enduse sectors. 

<www.mass.gov/Eoca/docs/ 

doer/pub_info/e3o.pdf> 

Nevada Nevada Energy Effi ciency 

Strategy. Nevada has taken 

a number of steps to increase 

energy effi ciency. This report 

provides 14 policy options for 

further increasing the effi ciency of electricity and natural 

gas and reducing peak power 

demand. 

This study focuses on policy 

and program design. 

<www.swenergy.org/pubs/ 

Nevada_Energy_Effi ciency_ 

Strategy.pdf> 

New Jersey New Jersey Energy Efficiency and Distributed 

Generation Market Assessment. This study estimates 

mid- and long-term potential 

for energy and peak-demand 

savings from energy effi ciency 

measures and for distributed 

generation in New Jersey. 

This study was conducted 

to analyze the achievable 

and business-as-usual cases 

to see whether New Jersey 

is meeting its effi ciency 

targets, and to make recommendations for future 

policies. 

<www.policy.rutgers.edu/ 

ceeep/images/Kema%20 

Report.pdf> 

New York Energy Efficiency and Renewable Energy Resource 

Development Potential In 

New York State. Final Report Volume One: Summary 

Report. This study examines 

the long-range potential for 

energy effi ciency and renewable energy technologies to 

displace fossil-fueled electricity 

generation in New York by 

looking at the potential available from existing and emerging efficiency technologies and 

practices and by estimating 

renewable electricity generation potential. 

This study was commissioned to estimate the 

technical and maximum 

achievable potentials in 

New York State, including 

the potential from renewables and combined heat 

and power. 

<www.nyserda.org/sep/EE& 

ERpotentialVolume1.pdf> 

National Action Plan for Energy Effi ciency Appendix E-5 
Title/Description Purpose URL Address 

Oregon Energy Efficiency and Conservation for the Residential, Commercial, Industrial, 

and Agricultural Sectors. 

This report is designed to inform the project development 

and selection process for a 

list of potential energy effi ­

ciency and renewable energy 

measures that could provide 

electricity savings for Oregon 

consumers. 

The stated goal of this projected was “to provide the 

Energy Trust of Oregon, Inc. 

with a list of potential energy effi ciency and renewable 

energy measures that could 

provide electricity savings for 

Oregon consumers.” 

<www.energytrust.org/ 

library/reports/Resource_ 

Assesment/ETOResource 

AssessFinal.pdf> 

Natural Gas Effi ciency and 

Conservation Measure Resource Assessment for the 

Residential and Commercial 

Sectors. This is a resource assessment to evaluate potential natural gas conservation 

measures that can be applied 

to the residential and commercial building stock serviced by 

Northwest Natural Gas. 

The purpose of this study 

was to evaluate potential natural gas effi ciency 

measures, to fi nd out if they 

are technically feasible and 

cost-effective. 

<www.energytrust.org/ 

library/reports/Resource_ 

Assesment/GasRptFinal_ 

SS103103.pdf> 

Texas Potential for Energy Effi ­

ciency, Demand Response, 

and Onsite Renewable 

Energy to Meet Texas’s 

Growing Electricity Needs. 

Presents both economic and 

program potential estimates. 

The economic potential was 

determined using a detailed 

bottom-up analysis. 

Prepared in response to announced plans to construct 

several large coal-fi red 

power plants to meet future 

peak loads in Texas. 

<http://aceee.org/pubs/ 

e073.pdf> 

Power to Save: An Alternative Path to Meet Electric 

Needs in Texas. Estimates 

the potential for effi ciency 

and other demand-side strategies by relying on the results 

of other studies in similar or 

nearby regions. 

Commissioned by national 

nonprofi t groups with an 

interest in energy effi ciency 

and climate change. 

<www.ceres.org/pub/docs/ 

Ceres_texas_power.pdf> 

Appendix E-6 Guide For Conducting Energy Effi ciency Potential Studies 
Title/Description Purpose URL Address 

Vermont Assessment of Energy Effi ­

ciency and Customer-Sited 

Generation Investments 

in the Southern Loop. A 

detailed analysis of program 

potential given aggressive 

effi ciency programming. 

Prepared in relation to 

efforts to build a new 

transmission line serving a 

small geographic region in 

Southern Vermont. 

<www.velco.com/Templates/ 

default.asp?pageId=48> 

National Action Plan for Energy Effi ciency Appendix E-7 

Appendix

F: References

American Council for an Energy-Effi cient Economy 

[ACEEE] (2007). Potential for Energy Effi ciency, 

Demand Response, and Onsite Renewable Energy 

to Meet Texas’s Growing Electricity Needs. Report 

No. E073. 

California Public Utilities Commission [CPUC] (2001). 

California Standard Practice Manual: Economic 

Analysis of Demand-Side Programs and Projects. 

Goldstein, D.B. (2007). Saving Energy, Growing Jobs. 

Berkeley: Bay Tree Publishing. 

KEMA-XENERGY, Inc. (2003a). California Statewide 

Residential Sector Energy Effi ciency Potential Study. 

Study ID #SW063, Vol. 1. 

KEMA-XENERGY, Inc. (2003b). California Statewide 

Residential Sector Energy Effi ciency Potential Study. 

Study ID #SW063, Vol. 2. 

Nadel, S., A. Shipley, and R.N. Elliott (2004). The Technical, Economic and Achievable Potential for Energy 

Effi ciency in the U.S.—A Meta-Analysis of Recent 

Studies. Washington, DC: American Council for an 

Energy-Effi cient Economy [ACEEE]. 

National Action Plan for Energy Effi ciency (2006). The National Action Plan for Energy Effi ciency. <www.epa. 

gov/cleanenergy/pdf/napee/napee_report.pdf> 

National Action Plan for Energy Effi ciency (2007). Guide 

to Resource Planning with Energy Effi ciency. Prepared by Snuller Price, Energy and Environmental 

Economics, Inc. 

New York State Energy Research and Development 

Authority [NYSERDA] (2003). Energy Effi ciency and 

Renewable Energy Resource Development Potential 

in New York State—Final Report, Volume One: 

Summary Report. 

Northeast Energy Effi ciency Partnerships [NEEP] (2005). 

Economically Achievable Energy Effi ciency Potential 

in New England. Optimal Energy. 

Optimal Energy, Inc. (2007). Power to Save: An Alternative Path to Meet Electric Needs in Texas. Report 

commissioned by the Natural Resources Defense 

Council and Ceres. 

Optimal Energy, Inc. (forthcoming). Assessment of 

Energy Effi ciency and Customer-Sited Generation 

Investments in the Southern Loop. Prepared for 

Vermont Electric Power Company. 

Southwest Energy Effi ciency Project [SWEEP] (2002). 

The New Mother Lode: The Potential for More 

Effi cient Electricity Use in the Southwest. Report 

for the Hewlett Foundation Energy Series. 

National Action Plan for Energy Effi ciency Appendix F-1 




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