# 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 Studiesis 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 ciencypotential 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. Theseindividuals 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 2007The Guide for Conducting Energy Effi ciency Potential Studiesis 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

Guide for Conducting Energy Effi ciency Potential Studies ii

# 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 ActionPlan Leadership Group members and observers during the fall of 2006. The work plan was further refi ned during the March 2007 Leadership Group meeting inWashington, 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 facilitatethe National Action Plan for Energy Effi ciency, including this Guide. Key staff include Larry Mansueti (DOE Offi ce of Electricity Delivery and Energy Reliability), DanBeckley (DOE Offi ce of Energy Effi ciency and Renewable Energy), and Kathleen Hogan, Niko Dietsch, StacyAngel, and Katrina Pielli (EPA Climate Protection Partnership Division).

Eastern Research Group, Inc., provided technical review, copyediting, graphics, and production services.

Guide for Conducting Energy Effi ciency Potential Studies iv

# 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 fi**  **ve 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 ciencyprograms, 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. ThisGuide 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 toolfor 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-1continue to be available at low cost in the future. These studies show that energy effi ciency can yield more than20 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 costand 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 ofbuilding policy support and making the case for energy effi ciency programs and funding . Usually thesetypes 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 ciencypotential, 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 efficiency. 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 describethese 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 CompleteLevel of Detail

Low

ES-2 Guide for Conducting Energy Effi ciency Potential Studiesapplication 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 motiva• tion of this study todemonstrate 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 deter• mine 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 whichmarket 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 incorporatethe results into portfolio decisions?What is the history of ef• fi ciency programming in this area? What effect does thishistory 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 electricityused 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 numberof options to consider in pursing these recommendations (Figure 1-1). As of November 2007, nearly 120organizations 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 efficiency 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 implementcost-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 imple ment 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 provenprograms, 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 admin• istering 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 opportu nities 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 stan• dards, 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 manage• ment 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 ef• fi 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.

Guide for Conducting Energy Effi ciency Potential Studies 1-2effi ciency potential study for the purpose of initiating or expanding a portfolio of effi ciency programs. It will alsobe 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 theinformation 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 thatusers 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 thisdocument, 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 thatdoes not rely on the examples in the main text, while Appendix D contains a list of common data sources used forpotential 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. Thiswork 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 inWashington, 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 estab lishing 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, iscost-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 energyconsumer 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 resourceeven 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 thatconsumes 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 2-1controls, 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 supportof 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 thelevel 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

Guide for Conducting Energy Effi ciency Potential Studies 2-2how 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 level 4 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 ultimatelya 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 arelatively modest budget will typically provide the necessary information to support policy decisions (see Section3.4). 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 ofcost-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 ortransmission 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 ciencydisplace 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 ciencyinvestment 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 analyzevarious 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 fewprogram 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 potentialanalysis: 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 2-3and 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 ascompared 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, ignoringany 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 referredto 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 froma 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 achievablewould 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.

Guide for Conducting Energy Effi ciency Potential Studies 2-4Regardless 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 somecontext for these values, reaching the maximum achievable potential (i.e., approaching the total economic potential) of between 20 and 30 percent would requireeffi 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 influenced 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 ciencytechnologies, 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 2-5Table 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** **New Brunswick** Énergie NBPower2004 TechnicalEconomicEconomic32%7%3%32%14%6%13%12%1%24%10%3%N.A. 17 Includes fuelswitching;excludes streetlights**British Columbia** BC Hydro 2002 EconomicMax.Achievable17%4%17%4%27%11%N.A. N.A. 9**California**Xenergy 2002 TechnicalEconomicMax.AchievableBudgetConstrained21%15%10%8%17%13%13%7%13%12%11%4%19%14%10%6%25%16%10%6%10 Integratedmeasures notaddressed;agricultureincluded in industrial sector**Manitoba**ManitobaHydro2002 EconomicMax.Achievable19%4%19%6%5%1%N.A. N.A. 9 Apartmentbuildingsincluded incommercial**Midwest**ACEEE 2003 Max.AchievableN.A. N.A. N.A. 11% N.A. 20**New Mexico**Itron 2006 Max.AchievableN.A. N.A. N.A. 8% 8.90% 10**Connecticut**GDSAssociates/QuantumConsulting2003 TechnicalMax.Achievable24%13%25%14%20%13%24%13%24%13%10 Also includesresults forSouthwest CTregion

Guide for Conducting Energy Effi ciency Potential Studies 2-6Table 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 TechnicalEconomicMax.AchievableN.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.Achievable5.3% 5.1% 6% 5.4% N.A. 15**Massachusetts**RLWAnalytics/SFMC2001 EconomicBudgetConstrained31%5%21% N.A. 24%5%N.A. 5 Excludes nonutility impactsand lowincome**New York**OEI/VEIC/ACEEE2002 TechnicalEconomic37%26%41%38%22%16%37%30%N.A. 10 A lso 5- and20-yearscenarios**Ontario**ICF 2005 TechnicalEconomicN.A. N.A. N.A. 26%21%33%21%20**Oregon**Technical 2003 Ecotope/ACEEE/Tellus28% 32% 35% 31% N.A. 10 Residentialincludesmanufacturedhousing**Puget Sound Region** PugetSoundEnergy2003 Max.TechnicallyAchievableMax.EconomicallyAchievable17%7%7%6%0%0%12%6%33%11%20(continued)

National Action Plan for Energy Effi ciency 2-7Table 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.EconomicallyAchievable8%2%19%6%1%1%7%3%N.A. 8 Residentialsales includefarms; nofarm savingsestimated**Texas**OEI 2007 Max.AchievableN.A. N.A. N.A. 20% 22% 15**Utah**TellusInstitue2001 Max.AchievableN.A. N.A. N.A. 9% N.A. 6**Vermont**OEI/VEIC 2002 Max.TechnicallyAchievable30% 32% 31% 37% 10 Includes fuelswitching;also 5-yearscenario**VELCO**OEI/VEIC 2002 Max.Achievable18% 17% 23% 23% 10 Excludesmeasureswith littlepeak demand,that requireregionalcoordination,and emergingtechnologies;includes fuelswitching;also 5-yearscenario(continued)

Guide for Conducting Energy Effi ciency Potential Studies 2-8Table 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/Tellus2002 Max.Achievable14% 20% 19% 18% N.A. 8 Also 18-yearscenario**NY, NJ, PA**ACEEE 1997 Max.Achievable35% 35% 41% N.A. N.A. 14 Residentialsavings are forall 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, orenergy 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 potentialstudy 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.

Guide for Conducting Energy Effi ciency Potential Studies 2-10

# 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 poten** **tial type(s) to analyze, (3) determine the appropriate level of detail, (4) select and define the methodol ogy, and (5) present the results. The specifics of these five steps need to be explored with or communi**  **cated 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 decisionsregarding 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 cattention 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 bedisplaced 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 lampor 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 implementationissues and estimates of technical and economic potential, these potential estimates do little more than set the context for estimates of achievable and programpotential, 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 opportunitiesfrom 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 3-1limited 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-effectivenessscreening 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 thecontinuum 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 Levelof 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 analystwill 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 roughbudget 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 disaggregateelectricity 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 anddisaggregated 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 ofaccuracy. However, one must ensure that they fully understand the data being used, how they were collected, and whether they introduce bias into the analysis.

Guide For Conducting Energy Effi ciency Potential Studies 3-2

### 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 Consump tion 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 offl oors in the building), they have two primary limitations. First, they only provide data aggregated at eitherthe 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 structurebuilt, 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 programsat 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 aswell 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 3-3forecasts 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 areoften 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, thatover the 10-year study period, computers and televisions use more and more energy, while at the sametime 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 notvery 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 areabeing 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 estimatingexisting 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 savingsand document penetration rates and baseline practices.
If resources are available, primary data can be collectedthrough 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 newsituation. 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.

Guide For Conducting Energy Effi ciency Potential Studies 3-4• 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 isto 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 topromote 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 cientproducts in the absence of any programmatic incentives) or changes in building codes or other energy use standards (e.g., national ENERGY STAR requirements). Insome 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 fromwhich to develop the economic or maximum achievable potential. The total potential estimate can thenbe 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, andlifetimes 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 inkilowatt-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 themeasure. 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 andany 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 Cost Effectiveness** 
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 effectsof 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 ischoosing the cost and benefi t components that are included within the boundary of the comparison, whether at the measure or program level. A particular boundarydefi 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 ofthe 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.

Guide For Conducting Energy Effi ciency Potential Studies 3-6• **Ratepayer impact measure (RIM) test.** This test evaluates the impacts on customer rates. It does soby 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 toexpress 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 tothe 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 toevaluate 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 multipleperspectives. Nevertheless, if effi ciency investments generate a positive net benefi t to society (as demonstrated by the TRC), policy-makers should be able to deviseways 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 specific 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 takeaccount 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 andcosts 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 availabilityand 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 buildingtype 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 representingthe 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. Adetailed 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 intoterms that the lay reader can understand. For example, stating that a program will save enough energyto 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 thestudy 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 constantover 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 ciencymeasures appearing to be more cost-effective because the presGuide For Conducting Energy Effi ciency Potential Studies 3-8ent 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 ratherthan 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 aggre**  **gation, 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 com plete, 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 adesire 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 toinclude 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 recentlycompleted 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 amoderate 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 environ• mental 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 thepotential 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 intoachievable 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 potentialof a package of these measures up to the cost-effectiveness threshold; it does not give an estimate of totaltechnical 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

Guide For Conducting Energy Effi ciency Potential Studies 4-2fully 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 ofsavings (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 approachallows 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 thegreatest 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. Forexample, 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 4-3hospitals 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 thelevel 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 ahigh 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. Subsequentsections 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 examplespresented 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 statescovered 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 timeneeded 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

Guide For Conducting Energy Effi ciency Potential Studies 4-4often 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 ofeffi 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 levelsfor comprehensive programs with widespread marketing efforts and high incentives than for less-aggressive programs that provide only a small portion of the addedcost 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. Toproperly 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 graphdemonstrates 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

YearMarket Share of Clothes Washers ThatMeet Federal Standards (%) 

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

National Action Plan for Energy Effi ciency 4-5aggressive 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 additionalheating 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-effectiveand 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 ina 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 acase 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.

Guide For Conducting Energy Effi ciency Potential Studies 4-6

# 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 costof 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

YearElectricity 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 studyestimated 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.

Guide For Conducting Energy Effi ciency Potential Studies 4-8

## 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/Penetra**tions** 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 4-94. 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 basedon 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.

Guide For Conducting Energy Effi ciency Potential Studies 4-10

# 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 ap plications 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-sideresources. 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 followingquestions 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 high• level 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 ana• lyst 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 com• pelling 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 toupgrade 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.

Guide For Conducting Energy Effi ciency Potential Studies 5-2These two studies differ in their approach to assessing alternatives to supply-side investment. The ACEEE study was prompted by public concern regarding traditionalsupply-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 potentialestimates 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 combinedheat 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 togenerate the necessary savings. This also generates additional demands on the methodology as discussed below. The ACEEE study presents both an economic potentialestimate and a “policy potential” estimate, the latter corresponding in defi nition to program potential as used in this report. The economic potential wasdetermined 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 theexperience 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 tospecifi 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 necessarywhen 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 5-3major 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 dencein 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 efficiency 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 systemneed, additional measures of cost-effectiveness are appropriate to facilitate comparisons with the alternatives.



### 5.6.1 **A Detailed Look at Supply-Side Alterna tives: 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-downanalysis to produce high-level effi ciency potential estimates. A bottom-up approach provides greater detailand is particularly well-suited to analysis of the residential sector for two reasons. First, good data on thenumber 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

Guide For Conducting Energy Effi ciency Potential Studies 5-4on 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 forthe 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 thatwill 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 significantly over time (for example, central air conditioning in moderate northern climates, or plasma TVs) the use of the reciprocal of measure life may not beappropriate. 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 assuminggradual, 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, asmarket 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 transformationprograms, 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 ofmeasures. When using a bottom-up approach, it is important to check the results against the disaggregatedload 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 estimatedpotential that exceeds the total existing heating consumption for all customers. For the VELCO study, thiswas 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 savingspotential 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 Invest ments: 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 5-5electric 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 thepipe. 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 efficiency to address a transmission shortage during winter peak loads. Therefore, the demand reduction calculation consideredsavings 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 ofend-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 potentialnew 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, aclear 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 drawnbetween 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.

Guide For Conducting Energy Effi ciency Potential Studies 5-6

## 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 conductmodeling 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 consistencybetween 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/Penetra**tions** Assumed aggressive pursuit of effi ciency opportunities and high percentages of retrofi t and new construction opportunities over 10years, 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

Guide For Conducting Energy Effi ciency Potential Studies 5-8

# 5.9 Notes

1. These ranges should be viewed as approximate. They are basedon 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 tothat 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 al ready 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 portfo**  **lios 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 thisarea? 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 toolsused 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 ciencyhas 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 specific program, rather than considering all possible technologies and markets. For example, a study might specifically 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 analystthe following questions to help guide the contracting process. Raising these issues early can ensurethat 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 audi• ence? What level of disaggregation of results is important to ensure its usefulness?

What data are available? – Does the contracting fi rm have access to pro– prietary data?

What local utility data are available? – Are available data of suffi cient detail and qual– ity to provide disaggregated results?

Is there a need to do primary onsite data col– lection? If so, what are the most important markets and technologies to collect data for?
What are the trade-offs between statistical preci• sion and level-of-effort in the primary data collection process? What demand-side resources should the analyst • include? Efficiency 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 penetra• tions 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 com– pelling to the target audience?

What level of disaggregation should be pre– sented?

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. Thischapter 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

Guide For Conducting Energy Effi ciency Potential Studies 6-2response 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 maximumachievable 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 priceforecasts. This is the key difference between the program potential and the maximum achievable potentialestimates 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 thecase for effi ciency or to analyze effi ciency as an alternative to supply-side investment. There are two keydifferences 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 maynot 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 underconsideration, rather than a comprehensive list of existing and emerging technologies.

The long history of efficiency 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 relativelylittle 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 theirrole 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 measurecosts 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. Ifa 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 6-3pays 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 areoften determined by applying cost adders to the modeled measure or fi nancial incentive costs, based on typical ratios of program non-measure costs (for thingssuch as administration, etc.) to measure costs or incentives. For a more detailed study that supports program planning and design, more detailed budgets should bederived. 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 detailsare 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, orestimate program costs across all markets that generally refl ect typical categories of programs. However, forestimating 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 individualeffi 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 whichis 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 latoT maFtluM=FMtsaceroF 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.
Guide For Conducting Energy Effi ciency Potential Studies 6-4

# 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 Guidepresents 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 arecertain 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 theanalysis, 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 potentialstudies, 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 CompleteLevel 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 CommissionPresident, 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 BoeckmanManager 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 ConnettManager 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 EspositoSenior 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 DirectorVermont 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 HowesVice 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-1Fred 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 DirectorTexas State Energy Conservation Offi ce
Paul von PaumgarttenDirector, Energy and Environmental Affairs Johnson Controls

Brenna WalravenExecutive 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 DirectorDemand 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 ofRegulatory 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 RelationsNational 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 StudiesJoseph Mattingly Vice President, Secretary and General CounselGas 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 thateffi 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 oreffi ciency program that seeks to encourage the selection of higher-effi ciency equipment or building practicesthan would typically be chosen at the time of a purchase or design decision.

**Measure:** Installation of equipment, subsystems, orsystems, 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, orcould 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 efficiency 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 potentialpossible 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-1materials 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 ofthe 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 includesmonetized 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 willbe 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 isto 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 baselinescenario 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 industrialfacilities) and growth in existing consumers’ consumption. Understanding the relative contribution of these two factors to the baseline forecast provides importantinput 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 energyconsumption. 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 customerpopulation 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-1In 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 cientinformation 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 tothe 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, andlifetimes 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 morevaluable 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 thehourly 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-peakperiods 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 measuressuch 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 theold, 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 initiativewith 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 Studiespresent 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 analysisbecause of the greater amount of data available and homogeneity of the buildings. While this approach does notrely 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 couldresult 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 residentialand commercial sectors due to the relative heterogeneity of energy consumption patterns and end-uses acrossdifferent 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 useestimates 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 asmall 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, atop-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-3available in the area of interest. An example of this approach is found in a study of energy effi ciency potentialin 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-usingequipment 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 sitevisits 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 energysavings 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 mustacknowledge 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 equipmentbecomes 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 overtime 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 inbuilding. 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 Studiesboiler 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 suchas 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 varyover 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 programthat 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 potentialstudy 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 onexpected 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 inworking directly with customers or supporting contractors, architects, or engineers; managing effi ciencyprojects; 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, includingopportunity 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 administrationplus 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 efficiency 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/com missioning/retro-commissioning incentives:**  Project-based incentives separate from direct measureincentives 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 theyare 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. Asdescribed 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 investmentto 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 testsdescribed 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 benefits such as reductions in maintenance or replacements costs as well as water and other resource savings. Effi ciency measuresprovide 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 economicpotential estimates, measures that do not pass the costeffectiveness screen will be eliminated from the analysisresults. 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 proprietarydatabases or spreadsheets, while others rely on commercially available software. Each platform has strengths and weaknesses, typically as a result of its developmentto 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, andexpected 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 thenine 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 En ergy Consumption**  **Survey (MECS)** The manufacturing counterpart to CBECS and RECS. Thebasic 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 theday 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 andforecasts 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 Labora**  **tory (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 orcounty 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 foreffi 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-makersdirection 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 Assess**  **ment of Existing Policies and Prospects for the** 
**Future.** This report applies analytical tools, such as economic and environmental modeling, to demonstrate thevalue of consumer-funded energy effi ciency programs and renewable portfolio standards and addresses market and regulatory barriers. This study was conductedto “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 As**  **sessment 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. andVermont Energy Corporation. It was conducted toprovide feedback for specifi c effi ciency initiatives. <www.neep.org/html/ NEEP_C&IReview.pdf>

**Southeast Powering the South, A** **Clean & Affordable En ergy 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 cleanenergy. 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 ciencyof 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 existingpower 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 theeconomic 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 electricenergy 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 wellas 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 En ergy Effi**  **ciency Potential for Connecticut and the** **Southwest Connecticut Re gion.**  This study estimates themaximum achievable costeffective potential for electric energy and peak demand savings from energy effi ciency measures in the geographic region of Connecticut servedby 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 townsand, 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 anachievable 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; thepotential 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 noexisting 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 En**  **ergy Effi ciency Opportuni**  **ties in Massachusetts.** Thisreport addresses the remaining electric energy effi ciencyopportunities in the residential, commercial, and industrial sectors in Massachusetts. This study focuses on program designs, examining how various funding levels will affect the savings ofvarious 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 efficiency 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 Ef**  **ficiency and Distributed Generation Market Assess** 
**ment.** 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 ciencytargets, and to make recommendations for future policies. <www.policy.rutgers.edu/ ceeep/images/Kema%20 Report.pdf>

**New York Energy Efficiency and Re**  **newable Energy Resource Development Potential In** **New York State. Final Re port Volume One: Summary**  **Report.** This study examines the long-range potential for energy efficiency and renewable energy technologies to displace fossil-fueled electricity generation in New York bylooking at the potential available from existing and emerging effi ciency technologies and practices and by estimatingrenewable electricity generation potential. This study was commissioned to estimate the technical and maximum achievable potentials in New York State, includingthe 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 Con** **servation for the Residen tial, 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 Re source Assessment for the**  **Residential and Commercial**
**Sectors.** This is a resource assessment to evaluate potential natural gas conservation measures that can be appliedto the residential and commercial building stock serviced by Northwest Natural Gas. The purpose of this studywas 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 Alterna tive Path to Meet Electric**  **Needs in Texas.** Estimates the potential for effi ciencyand 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**Funding and printing for this report was provided by the U.S. Department of Energy and U.S. Environmental Protection Agency in their capacity as co-sponsors for the National Action Plan for Energy Effi**  **ciency.**

Recycled/Recyclable—Printed with Vegetable Oil Based Inks on 100% (Minimum 50% Postconsumer) Recycled Paper