LBNL-5803E

The Future of Utility CustomerFunded Energy Efficiency Programs 

in the United States: Projected 

Spending and Savings to 2025

Galen L. Barbose, Charles A. Goldman, Ian M. 

Hoffman, Megan Billingsley

Environmental Energy 

Technologies Division

January 2013

This work was supported by the National Electricity Delivery Division of the U.S. 

Department of Energy’s Office of Electricity Delivery and Energy Reliability under 

Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231.

ERNEST ORLANDO LAWRENCE

BERKELEY NATIONAL LABORATORY
Disclaimer

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University of California, nor any of their employees, makes any warranty, express or 

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otherwise, does not necessarily constitute or imply its endorsement, recommendation, 

or favoring by the United States Government or any agency thereof, or The Regents of 

the University of California. The views and opinions of authors expressed herein do 

not necessarily state or reflect those of the United States Government or any agency 

thereof, or The Regents of the University of California.

Ernest Orlando Lawrence Berkeley National Laboratory is an equal opportunity 

employer.
LBNL-5803E

The Future of Utility Customer-Funded Energy Efficiency 

Programs in the United States: 

Projected Spending and Savings to 2025

Prepared for the

Office of Electricity Delivery and Energy Reliability

National Electricity Delivery Division

U.S. Department of Energy

Principal Authors

Galen L. Barbose, Charles A. Goldman, Ian M. Hoffman, Megan Billingsley

Ernest Orlando Lawrence Berkeley National Laboratory

1 Cyclotron Road, MS 90R4000

Berkeley CA 94720-8136

January 2013

The work described in this study was funded by the National Electricity Delivery Division of the 

U.S. Department of Energy’s Office of Electricity Delivery and Energy Reliability under 

Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231.
2

Acknowledgements

The work described in this study was funded by the National Electricity Delivery Division of the 

U.S. Department of Energy’s Office of Electricity Delivery and Energy Reliability under 

Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231. We would 

particularly like to thank Larry Mansueti of the U.S. Department of Energy for his support of 

this work. For providing comments on an earlier draft and/or providing information that was 

used in the analysis, the authors would like to thank Sheryl Carter (NRDC), Rich Sedano (RAP), 

Lara Ettenson (NRDC), Anthony Star (Illinois Commerce Commission), Brian Granahan

(Illinois Commerce Commission), Sam Gomberg (formerly with SACE), Jay Zarnikau (Frontier 

Associates), Amy Martin (Frontier Associates), Steve Schiller (Schiller & Associates), Hale 

Powell (Hale Powell Energy), Dian Grueneich (Dian Grueneich Consulting, LLC), Joe Bryson 

(EPA), David Walker (MI LARA), Howard Geller (SWEEP), Elizabeth Noll (AGA), Mariam 

Arnaout (AGA), Wayne Williams (Pennsylvania PUC), Chrissy Godfrey (MD PSC), Kara 

Rodgers (CEE), Mandy Mahoney (SEEA), Mike Ambrosio (Applied Energy Group), Cheryl 

Roberto (Ohio PUC), Tom Larson (SACE), John Wilson (SACE), Ken Smith (SACE), Jill 

Tauber (SACE), Shawn Carraher (La Capra Associates), Josh Craft (NEEP), Jim O'Reilly 

(NEEP), Tom Eckman (NPCC), Jeff Harris (NEEA), Greg Ehrendreich (MEEA), Marcus 

Preston (NiSource), Jeff Schlegel (SWEEP), Holly Meyer (NW Natural Gas), Bill Edmonds 

(NW Natural Gas), Teri Van Sumeren (Consumers Energy), Steve Bateson (Questar Gas). We 

also thank Anthony Ma for assistance with formatting and production. Of course, any 

remaining omissions or inaccuracies are our own.
3

Table of Contents

Abstract........................................................................................................................................... 5

1. Introduction............................................................................................................................... 6

2. Recent Policy Developments and Trends................................................................................. 7

2.1. Policy Drivers for Utility Customer-Funded Energy Efficiency Programs.................... 8

2.2. Current and Historical Spending on Utility Customer-Funded Energy Efficiency 

Programs....................................................................................................................... 10

3. Analytical Approach ............................................................................................................... 12

3.1. Electric Energy Efficiency Program Spending and Savings Projections...................... 12

3.2. Gas Energy Efficiency Program Spending Projections................................................ 15

4. Results..................................................................................................................................... 17

4.1. Combined Electric and Gas Energy Efficiency Program Spending Projections .......... 17

4.2. Electric Energy Efficiency Program Spending Projections.......................................... 18

4.3. Electric Energy Efficiency Program Savings Projections ............................................ 21

4.4. Gas Energy Efficiency Program Spending Projections................................................ 23

5. Discussion of Key Issues and Uncertainties........................................................................... 25

5.1. Broader Market and Policy Context ............................................................................. 25

5.2. Energy Efficiency Program Implementation and Regulatory Oversight...................... 27

6. Conclusions............................................................................................................................. 30

7. References............................................................................................................................... 31

Technical Appendix A: Methodology and Assumptions Used to Develop Energy Efficiency 

Spending and Savings Projections.......................................................................................... 33

Technical Appendix B: State-Level Spending and Savings Projections...................................... 48
4

List of Figures and Tables

Figure 1. Projected Electric and Gas Energy Efficiency Program Spending ............................... 18

Figure 2. Policy Drivers for Projected Electric Energy Efficiency Spending in the Medium Case 

(2025)...................................................................................................................................... 19

Figure 3. Projected Electric Energy Efficiency Spending by Census Region .............................. 20

Figure 4. Regional Distribution of Electric Energy Efficiency Program Spending (Medium Case)

................................................................................................................................................. 21

Figure 5. Electric Energy Efficiency Program Spending as a Percent of Utility Revenues 

(Medium Case)........................................................................................................................ 21

Figure 6. Projected Electricity Savings from Utility Customer-Funded Efficiency Programs..... 22

Figure 7. Projected Gas Energy Efficiency Program Spending.................................................... 24

Figure 8. Projected Gas Energy Efficiency Program Spending as a Percentage of Gas 

Distribution Utility Revenues................................................................................................. 24

Figure A - 1. U.S. Census Regions Used for Scenario Development........................................... 36

Figure A - 2. Generic Program Cost Function.............................................................................. 43

Table 1: Policy Drivers for Customer-Funded Energy Efficiency Program Activity .................... 9

Table 2. 2010 Expenditures for Utility Customer-Funded Energy Efficiency (EE) Programs.... 11

Table 3. Scenario Assumptions for Electric Energy Efficiency Projections................................ 14

Table 4. Scenario Assumptions for Gas Energy Efficiency Projections ...................................... 15

Table 5. Projected Electric Energy Efficiency Spending.............................................................. 19

Table 6. Projected Incremental Annual Electricity Savings from Utility Customer-Funded 

Programs (TWh) ..................................................................................................................... 22

Table A - 1. AEO Projected Growth Rates in Retail Electricity Sales and Prices ....................... 34

Table A - 2. Estimate Customer-Funded Energy Efficiency Program Savings Embedded in AEO 

Forecasts by EMM Region ..................................................................................................... 35

Table A - 3. Scenario Descriptions for States in the Northeast .................................................... 36

Table A - 4. Scenario Descriptions for States in the South .......................................................... 38

Table A - 5. Scenario Descriptions for States in the Midwest...................................................... 39

Table A - 6. Scenario Descriptions for States in the West............................................................ 40

Table A - 7. Energy Efficiency Spending Assumed for “Uncommitted” States.......................... 42

Table A - 8. Analysis Framework for Natural Gas Energy Efficiency Programs ........................ 44

Table A - 9. Gas Energy Efficiency Program Scenario Descriptions: Tier I States..................... 45

Table A - 10. Gas Energy Efficiency Program Spending: Tier II States...................................... 47

Table B - 1. Electric Efficiency Program Spending Projections by State ($M, nominal)............ 49

Table B - 2. Electric Efficiency Program Savings Projections by State (First-Year GWh)......... 50

Table B - 3. Gas Efficiency Program Spending Projections by State ($M, nominal) .................. 51
5

Abstract

We develop projections of future spending on, and savings from, energy efficiency programs 

funded by electric and gas utility customers in the United States, under three scenarios through 

2025. Our analysis, which updates a previous LBNL study, relies on detailed bottom-up 

modeling of current state energy efficiency policies, regulatory decisions, and demand-side 

management and utility resource plans. The three scenarios are intended to represent a range of 

potential outcomes under the current policy environment (i.e., without considering possible

major new policy developments). 

Key findings from the analysis are as follows:

• By 2025, spending on electric and gas efficiency programs (excluding load management 

programs) is projected to double from 2010 levels to $9.5 billion in the medium case, 

compared to $15.6 billion in the high case and $6.5 billion in the low case. 

• Compliance with statewide legislative or regulatory savings or spending targets is the 

primary driver for the increase in electric program spending through 2025, though a 

significant share of the increase is also driven by utility DSM planning activity and 

integrated resource planning. 

• Our analysis suggests that electric efficiency program spending may approach a more 

even geographic distribution over time in terms of absolute dollars spent, with the 

Northeastern and Western states declining from over 70% of total U.S. spending in 2010 

to slightly more than 50% in 2025, and the South and Midwest splitting the remainder

roughly evenly. 

• Under our medium case scenario, annual incremental savings from customer-funded 

electric energy efficiency programs increase from 18.4 TWh in 2010 in the U.S. (which 

is about 0.5% of electric utility retail sales) to 28.8 TWh in 2025 (0.8% of retail sales). 

• These savings would offset the majority of load growth in the Energy Information 

Administration’s most recent reference case forecast of retail electricity sales through 

2025, given specific assumptions about the extent to which future energy efficiency 

program savings are captured in that forecast. 

• The pathway that customer-funded efficiency programs ultimately take will depend on a 

series of key challenges and uncertainties associated both with the broader market and 

policy context and with the implementation and regulatory oversight of the energy 

efficiency programs themselves.
6

1. Introduction

Electric and natural gas energy efficiency in the United States is pursued through a diverse mix 

of policies and programmatic efforts, which support and supplement private investments by 

individuals and businesses. These efforts include federal and state minimum efficiency 

standards for electric and gas end-use products; state building energy codes; a national 

efficiency labeling program (ENERGY STAR®); tax credits; and a broad array of largely 

incentive-based programs for consumers, funded primarily by electric and natural gas utility

customers (Dixon et al. 2010).1 Over the past four decades, policy support and utility customer 

funding of energy efficiency programs, in particular, has ebbed and flowed.2 Utilities first 

launched substantial programs in the wake of the 1973 energy crisis, and those programs grew 

and matured with the expansion of integrated resource planning and demand-side management 

during the 1980s and 1990s (Nadel 1992). Spending on energy efficiency by utilities then 

declined sharply in many states in the late 1990s, with the restructuring of the electricity 

industry. However, the western energy crisis of 2000-2001 brought renewed attention to energy 

efficiency as an important strategy for managing and containing costs for electric utility 

customers.

3

 

Since then, many state regulatory agencies and legislatures have sought to prioritize energy 

efficiency, in some cases strengthening and supplementing pre-existing policies by requiring 

comprehensive electric and gas system resource planning, developing funding mechanisms and 

energy savings targets, and creating business incentives for program administrators to deliver 

energy efficiency to customers. In some states, regulators have also extended demand-side

planning, savings targets, or business incentive mechanisms from the electricity sector to large 

regulated natural gas utilities. 

A variety of organizations and analysts have examined trends in utility customer-funded energy 

efficiency programs in the United States. These include efforts to document historical and 

recent trends in spending, savings or both (Nadel 1992; Sciortino et al. 2011; Cooper and Wood

2012; CEE 2012), as well as estimates of the projected impact of individual policies related to 

utility customer-funded energy efficiency (Nowak et al. 2011) or in particular regions (Hopper 

et al. 2008). Yet other studies have sought to estimate the potential savings that could be 

obtained through customer-funded efficiency programs, including an innumerable number of 

such studies conducted for individual utilities or states, as well as several national studies (EPRI 

2009). The present study builds upon the body of existing literature by comprehensively 

assessing the potential impact of the full suite of policies and market conditions relevant to the 

future of utility customer-funded energy efficiency programs in the United States, updating an 

earlier LBNL analysis (Barbose et al. 2009). 

 1 The American Recovery and Reinvestment Act (ARRA) provided a massive but temporary infusion of federal 

funding for energy efficiency (~$15-20B in programs administered by federal, state and local governments to be 

spent over three years) (Goldman et al. 2011). 2 Geller et al. (2006) provide an overview of the efficiency policy landscape among nations in the Organization of 

Economic Cooperation and Development, including the U.S., while Gillingham et al. (2006) provide a 

comprehensive review for the United States. 3 Energy efficiency programs administered by U.S. gas distribution utilities have also increased over time but are 

much smaller in size than electric efficiency programs (York et al. 2012). 
7

Specifically, we project future spending on, and savings from, U.S. electric and gas efficiency 

programs to 2025 under low, medium, and high scenarios. The projections are based on a 

detailed, bottom-up review and modeling of all relevant state policies and legislation, regulatory 

decisions, and utility integrated resource and demand-side management plans. The three 

scenarios are intended to represent a range of potential outcomes under the current policy 

environment, given uncertainties in policy implementation and in the broader economic and 

policy environment (e.g., utility business models, the extent to which energy efficiency is a 

policy priority, and concerns about rate impacts). The three scenarios are not intended to 

encompass major new federal policy developments, which could naturally expand the range of 

potential outcomes beyond those modeled here.4 Scenario definitions and assumptions were 

also informed by interviews with regional and national energy efficiency experts, program 

administrators, regulatory staff and other industry stakeholders. Based on the quantitative 

analysis of projected spending and savings under varying policy implementation scenarios, we 

identify and discuss the broader themes and issues that will influence which of the potential 

projections are most likely to transpire. 

The study has relevance to a broad range of audiences: utilities and other entities responsible for 

administering customer-funded efficiency programs and the state regulatory agencies 

responsible for overseeing their implementation; policymakers, planners, and industry analysts 

seeking to understand the potential impact of these programs on the broader electricity market or 

their implications for other policies; and the energy services industry seeking to understand 

market trends and opportunities. While this study focuses on the United States, the analysis also 

has relevance to policymakers abroad where energy and environmental policies may require the 

development of specific long-term energy savings goals and/or funding mechanisms for 

voluntary incentive-based programs, such as those that are prevalent in the United States. For 

example, the set of potential trajectories of U.S. efforts potentially offers a window on the 

prospects and issues raised by the 2012 European Union Energy Efficiency Directive

(Directive 2012/27/EU), in which the European Parliament and Council committed member 

states to adopting efficiency targets and submitting implementation plans consistent with a EUwide target of saving 20% of the projected primary energy consumption in 2020 (Boonekamp 

2011).

The remainder of the paper is organized as follows. Section 2 provides an overview of the key 

policy drivers that influence future efficiency program spending and savings, and summarizes 

current trends in spending on energy efficiency programs across states. Our modeling approach 

for capturing policy and market influences on future spending and savings for electric and gas 

efficiency programs is described in Section 3. The results of our analysis are presented in 

Section 4. In Section 5, we identify key challenges and discuss significant uncertainties in 

market and policy drivers that may influence the path forward for customer-funded efficiency 

programs.

2. Recent Policy Developments and Trends 

 4 By virtue of limiting the analysis to current energy efficiency policies, we do not consider the potential impact of 

major new federal (or state) policy initiatives (e.g., a national energy efficiency resource standard, clean energy 

standard, or carbon policy) that could result in customer-funded energy efficiency program spending and savings 

that exceed the values in our High Case.
8

Over the past decade, an increasing number of states have adopted policies that encourage or 

require utility customer-funded energy efficiency programs. In this section, we summarize 

recent trends in the development of these policies and the current and historical spending levels 

across states. 

2.1. Policy Drivers for Utility Customer-Funded Energy Efficiency Programs

In the utility sector, policies that drive investment in energy efficiency include: system benefit 

charges; energy efficiency resource standards; renewable portfolio standards under which 

energy efficiency is a qualifying resource; requirements that utilities obtain “all cost-effective 

energy efficiency” resources; long-term integrated resource planning requirements; and multiyear demand-side management planning requirements (see Table 1). Naturally, the scope and 

level of aggressiveness of each type of policy can vary substantially across states, and many 

states have adopted multiple policies in tandem. 

A number of these policy drivers are relatively recent, most notably energy efficiency resource 

standards (EERS), which have thus far been adopted in 15 states and require utilities to achieve 

minimum energy efficiency savings targets over a lengthy period of time.5

 Similarly, several 

others states have adopted broader renewable portfolio standards (RPS) or alternative energy 

standards under which energy efficiency is a qualifying resource. Many of these EERS policies 

and RPS policies with energy efficiency allowances have been enacted in states that previously 

had not aggressively pursued customer-funded energy efficiency and have therefore required 

rapid development of the regulatory and administrative structures necessary to implement and 

oversee sizable energy efficiency program portfolios. Another recent policy development in a 

number of states, all of which have offered large-scale energy efficiency programs for more than 

a decade, is the development of statutory or regulatory requirements that utilities acquire “all 

cost effective” energy efficiency. In these states, program administrators or regulatory staff may 

then conduct studies that estimate the long-term, cost-effective savings potential and then 

propose annual or multi-year savings targets and budgets in order to capture this potential over a 

defined time period. 

Other facets of the energy efficiency policy landscape are less recent. System benefit charges 

(SBC), which exist in 14 states and were typically established more than a decade ago as part of 

larger electric industry restructuring processes, serve to set an approximate floor on energy 

efficiency program spending via a non-bypassable surcharge on customers’ utility bills. 

Integrated resource planning (IRP) also exists in many states, whereby utilities are required to 

plan for the long-term needs of their customers by considering and assessing a broad range of 

resource options, including energy efficiency resources. Depending upon the manner and extent 

to which utilities are required to assess energy efficiency options, the IRP may culminate in a 

 5 In this study, we define Energy Efficiency Resource or Portfolio Standards as requirements under statute or 

regulatory order that some or all utilities within a state (e.g., all utilities or investor-owned utilities only) achieve 

specified minimum savings levels over a period greater than three years. States with shorter term DSM plans (i.e. 

one to three years) and/or multi-year efficiency budgets approved by state regulators are separately listed. Note that 

other entities (e.g., ACEEE) that track the status of energy efficiency policies in various states may use slightly 

different criteria for defining an EERS than LBNL; thus their tallies of the number of states with such policies may 

differ.
9

10- to 20-year plan with specified levels of energy efficiency resource acquisition. Finally, 

utilities in many states are required to regularly submit a demand-side management (DSM) plan

to their state regulator, proposing a specific portfolio of programs that meet cost-effectiveness 

guidelines and other policy objectives, typically on a one- to three-year cycle.

Although IRP and DSM planning have both been utilized for more than 20 years, their 

application has expanded somewhat in recent years as a result of policy spill-over or crossborder effects from other states within a given region. For example, Arkansas regulators 

developed a step-by-step energy efficiency program development template that has been cited as 

a policy influence in other southern states (e.g., Mississippi and Alabama).6 Multi-state utilities 

also are developing territory-wide efficiency programs designed to meet one state’s mandates, in 

effect carrying that state’s energy saving policies de facto into neighboring states.7 Lastly, the 

move by the Tennessee Valley Authority (TVA)8 to set savings targets through its IRP, and to 

offer programs and encourage its member distributors to offer programs, is expected to spread 

the pursuit of energy efficiency across the seven states where it provides wholesale power. 

Table 1: Policy Drivers for Customer-Funded Energy Efficiency Program Activity

Key Policy Drivers for Energy 

Efficiency Spending and Savings 

Applicable to Electric Efficiency 

Programs 

Applicable to Natural Gas 

Efficiency Programs 

Energy Efficiency Resource Standard 

(EERS)

AZ, CA, CO, HI, IL, IN, MD, MI, 

MN, MO, NM, NY, OH, PA, TX

CA, CO, MI, MN, NY, IL

Energy efficiency eligibility under state 

RPS 

HI, MI, NC, NV, OH 

Statutory requirement that utilities acquire 

all cost-effective energy efficiency 

CA, CT, MA, RI, VT, WA CA, CT, MA, RI, VT, WA

Systems benefit charges CA9 CA, DC, ME, MT, NJ, NY, 

RI,WI

, CT, DC, MA, ME, MT, NH, 

NJ, NY, OH, OR, RI, VT, WI

Integrated resource planning 34 States (primarily in the West and 

Southeast) and TVA

17 States (primarily in the 

West and Northeast)

Demand Side Management plan or multiyear energy efficiency budget28 States 21 States (primarily in the 

Northeast and Midwest)

In addition to the energy efficiency policy drivers summarized in Table 1, other broad market 

and policy dynamics may also play a critical role in shaping the trajectory of future spending and 

 6 In Arkansas, the process began with a collaborative among regulators, utilities and other stakeholders, then 

proceeded to “quick start” programs designed to test the viability of utility customer-funded programs in that 

jurisdiction and begin building program infrastructure. In the final step, regulators set modest but increasing savings 

targets.

7 For example, Duke Energy Carolinas and Progress Energy Carolinas are subject to an RPS in North Carolina in 

which energy efficiency is an eligible resource, and both submitted a pro rata version of the same efficiency plan 

from North Carolina for the rest of their service territory in South Carolina. Likewise, West Virginia’s requirement 

that an American Electric Power subsidiary initiate efficiency programs resulted in submission of similar program 

plans in neighboring Virginia.

8 The Tennessee Valley Authority (TVA) is the largest U.S. public power utility and serves 155 distributors and 57 

industrial customers in TN, KY, AL, MS, GA, NC and VA.

9 The systems benefit charge in California expired at the end of 2011, although legislative efforts are underway to 

renew it. 
10

savings from customer-funded energy efficiency programs. We discuss several of these factors in 

Section 5.1, including the timing and pace of the economic recovery, the long-term trend in 

natural gas prices, the stringency of future federal and state minimum efficiency standards for 

appliances and building codes, and the outcome of federal air emissions regulations. 

2.2. Current and Historical Spending on Utility Customer-Funded Energy Efficiency 

Programs

Over the latter half of the past decade, spending on electric and gas utility customer-funded 

energy efficiency programs (excluding load management)

10

Table 2

more than doubled, from roughly $2 

billion in 2006 to $4.8 billion in 2010, consisting of $3.9 billion for electric energy efficiency 

programs and $0.8 billion for natural gas programs (CEE 2008; CEE 2012). Approved budgets 

for 2011 – which may diverge from actual expenditures – were significantly higher than 2010 

spending, totaling $6.7 billion, consisting of roughly $5.6 billion for electric efficiency 

programs and $1.2 billion for gas efficiency programs (CEE 2012). With the steady increase in 

spending on utility customer-funded efficiency programs in recent years, relative spending as a 

percentage of utility revenues has also risen, with electric program expenditures in 2010 

equivalent to roughly 1.1% of total U.S. electric utility revenues in that year, while gas program 

expenditures were equivalent to roughly 0.7% of total U.S. gas distribution utility revenues. 

The geographical distribution of both electric and gas spending has spread over time, as 

numerous states with recently adopted policies have ramped up their efforts. That said, total 

spending on utility customer-funded energy efficiency programs, in absolute dollar terms, still 

remains highly concentrated within a relatively small number of states (see ).11

In particular, the majority of funding for electric efficiency programs is concentrated in 

California, the Pacific Northwest (OR, WA), and the Northeast (MA, NJ, NY, CT), all states 

with a long history of commitment to energy efficiency. Other states, many located in the 

Midwest (e.g., OH, PA, IL, IN, and MI), are in the process of ramping up program spending, 

often driven by long-term electricity savings targets. The top 10 states, in terms of absolute 

dollar expenditures account for about 70% of 2010 spending on electric energy efficiency 

programs. Program administrators in the leading states with the highest per capita energy 

efficiency spending typically offer a comprehensive portfolio of programs tailored to residential, 

commercial, and industrial customers that utilize a variety of designs and intervention strategies 

(e.g., technical assistance to end users and trade allies, incentives to customers to buy down the 

cost of high-efficiency equipment, and incentives to upstream manufacturers and retailers to 

stock and distribute high-efficiency products). 

Gas efficiency programs are less widespread than electric programs, and thus funding is even 

more highly concentrated in a small number of states, where the top-10 states account for almost 

80% of the national budget for gas efficiency programs. Specifically, gas efficiency spending is 

 10 Electric utility expenditures on load management programs in 2010 represented an additional $0.9 billion (CEE 

2012). 

11 Metrics based on total budget for energy efficiency tend to favor states with large populations. It is important to 

note that program administrators in several small states (e.g. VT, RI, and IA) have significant energy efficiency 

budgets, if metrics are based on efficiency spending per capita. In the U.S., the 10 leading states spend more than 

$25 per capita on utility customer-funded electric efficiency programs, while the average spending on these 

programs among the 50 states is about $12 per capita.
11

concentrated in about a dozen states in various regions: NY, MA, and NJ in the Northeast; IL, 

MI, IA, MN and WI in the Midwest; and CA, OR and UT in the West. Most southern utilities 

have modest retail gas sales or function largely as distribution entities that convey 

“transportation gas”,12 and they consequently spend little on gas efficiency programs. 

Nationally, gas efficiency program budgets are dominated by residential and low income 

programs, together comprising 68% of total program expenditures in 2010 (CEE 2012), which is 

quite different from the program mix for electric efficiency programs.13

Table 2. 2010 Expenditures for Utility Customer-Funded Energy Efficiency (EE) Programs

Rank Combined Electric & Gas EE 

Spending ($M) Electric EE Spending ($M) Gas EE Spending ($M)

1 CA $1,139 CA $938 CA $201 

2 NY $521 NY $482 NJ $126 

3 NJ $317 MA $245 MA $72 

4 MA $317 WA $218 MI $41 

5 WA $247 NJ $191 IA $40 

6 FL $176 FL $165 NY $39 

7 OR $158 OR $135 MN $36 

8 MN $144 TX $114 UT $36 

9 CT $119 CT $108 OH $32 

10 MI $116 MN $107 WA $29 

Top 10 

States

$M $3,255 $2,702 $653 

% of U.S. 68% 68% 78%

Remainder 

of U.S.

$M $1,531 $1,246 $185 

% of U.S. 32% 32% 22%

Total U.S. $M $4,786 $3,948 $838 

Source: CEE (2012), with several modifications

 12 See approach section on modeling of gas programs for more details. 13 On a national basis, electric energy efficiency spending in 2010 was allocated among market sectors as follows: 

commercial and industrial (47%), residential (28%), low-income residential (8%) and other programs or 

expenditure categories not directly attributable to a sector (16%).
12

3. Analytical Approach

We developed low, medium, and high case projections of electric and natural gas efficiency 

program spending to 2025, as well as accompanying projections of electric program energy 

savings.14 These projections are based on a state-by-state review of current policies, regulatory 

decisions, utility IRPs and DSM plans, and other key regulatory and planning documents, 

further supported through interviews with state PUC and utility staff and regional energy 

efficiency experts. The projections are intended to represent alternative pathways for the future 

evolution of energy efficiency programs, given the current set of policies in place and the larger 

market and policy environment in which programs operate. As explained further below, we took 

different approaches to developing projections for electric and gas energy efficiency program 

spending. These methodological differences reflect both that enabling efficiency policies are 

more prevalent among electric utilities compared to gas utilities, and that the level of 

development and experience with administering electric efficiency programs is much greater 

than for gas programs.

3.1. Electric Energy Efficiency Program Spending and Savings Projections

The projections of electric program spending and savings are based primarily on state-specific 

assumptions about how effectively and aggressively current energy efficiency policies are 

implemented and about the impact of broader market conditions. The scenario assumptions are 

summarized by census region in Table 3. The projections for these states typically begin with 

assumptions about either future spending or savings (depending on the state and scenario), and 

then future spending or savings are derived from the other based on assumptions about the cost 

of savings. For a group of seven “uncommitted” states that currently have little efficiency 

program activity and no established policy framework, we instead employ a standardized 

approach by which spending increases above current levels by a stipulated amount under each 

scenario, also described in Table 3.15 Additional methodological details, including state-by-state 

descriptions of scenario definitions, are provided in Appendix A.

Although the scenario definitions were developed on a state-by-state basis, with consideration of 

the specific policy and market context in that state, the low, medium, and high scenarios can be 

characterized in broad terms. At a conceptual level, the low scenario represents a less prominent 

role for energy efficiency as a resource in many states, as program spending remains at current 

levels or increases very modestly (or decreases in a few states) in subsequent years. The 

medium scenario reflects a future in which states that historically have been leaders in energy 

efficiency continue down that path and in some cases expand the role of energy efficiency as a 

 14 In the context of this report, “spending” refers to the flow of money from the energy efficiency program 

administrator into the market, including all program administration costs but excluding performance incentives. To 

the extent possible, electric spending projections are intended to reflect “gross” savings, prior to accounting for freeriders or free-drivers. This approach was taken in order to abstract from potential inconsistencies across states in 

methods for estimating net-to-gross ratios. However, the underlying data used to derive the cost of savings for some 

states were not explicit about whether savings are reported in “net” or “gross” terms; thus, some ambiguity exists in 

whether the spending projections for a number of states reflect net or gross savings. Gas efficiency program savings 

projections were not included for several reasons (e.g., relative paucity of mature, multi-year gas efficiency 

programs from which to draw reliable data). 15 These seven uncommitted states include: AK, KS, LA, ND, NE, SD, and WV.
13

resource, while other states are fairly successful in ramping up their energy efficiency programs 

to meet legislative saving targets. Note that in the medium scenario, our estimates of future 

savings account for constraints that may limit the ability of program administrators to achieve 

savings targets – e.g., ability for energy efficiency services infrastructure to ramp up quickly in 

early years and rate or spending caps that limit program spending increases in later years. The 

high scenario reflects a future in which many states establish a very prominent role for energy 

efficiency as a resource: states with EERS statutes are assumed to meet savings targets (and 

overcome constraints), states in each region are inclined to follow the example (and goals) 

established by leading states in that region, and those states that are currently “uncommitted” are 

assumed to adopt policies that lead to savings in 2025 of roughly the national average savings 

targets achieved by utilities currently.
14

Table 3. Scenario Assumptions for Electric Energy Efficiency Projections 

Region Scenario Representative Assumptions

South 

Low

TX IOUs meet minimum EERS targets. TVA savings based on 2010 IRP “Baseline Portfolio.” 

NC IOUs achieve only as much savings as can be applied towards their RPS. Utilities maintain 

spending at the level in the last year of recent DSM plans (in terms of percentage of revenues).

Medium 

TX IOUs maintain savings at current levels (0.2% of sales), exceeding EERS targets. FL IOUs 

ramp up savings to 0.3% of sales. IRP savings targets are achieved (TVA, KY, GA). Otherwise 

similar to low case.

High 

TX utilities ramp up savings to 0.3% of sales, offsetting 50% of demand growth. FL IOUs 

ramp up to long-term savings targets established by regulators (0.48% of sales in 2019) and to 

0.75% by 2025. TVA and IOUs in GA, NC, and SC ramp up savings to roughly 1% of retail 

sales. MD utilities meet state EERS goals.

Midwest 

Low

IL, IN, and OH utilities fall short of EERS targets (e.g., due to cost caps or opt-out), but MI and 

MN utilities fully meet their more-modest EERS targets. IA utilities maintain current spending 

levels, and WI spending is equal to current legislative cap of 1.2% of revenues.

Medium 

EERS targets are achieved in most cases, one exception being IL, where cost cap is eased but 

not to the extent required to meet ultimate targets. IA spending continues at the level in the last 

year of the most recent DSM plans. WI spending rebounds to 1.7% of revenues, half way 

between current legislative cap and historical peak.

High All states reach savings of roughly 1.5% to 2% of retail sales, meeting or exceeding EERS 

targets by varying degrees. 

West 

Low

CA IOU savings are based on 90% of market potential, as estimated in Navigant (2012) , 

which decline from current levels. AZ and NM utilities achieve EERS targets. Many utilities in 

the Northwest achieve savings equal to 60% of NPCC’s 6th Power Plan conservation targets, 

with remainder achieved through codes and standards. Utilities in other states achieve savings 

based on most recent IRP or maintain constant savings based on the final year of their most 

recent DSM program plan, whichever is less.

Medium 

CA IOU savings are based on 110% of market potential in Navigant (2012). CO utilities 

achieve EERS targets. In the Northwest, utility savings equal 75% of NPCC conservation 

targets, with remainder achieved through codes/standards. Utilities in most other states achieve 

savings based on most recent IRP or maintain constant savings based on the last year of their 

most recent DSM program plan, whichever is greater.

High 

CA IOU savings are based on 130% of market potential in Navigant (2012). AZ IOUs meet 

EERS targets without reliance on retroactive credit for historical programs, and SRP achieves 

similar savings levels. CO is same as medium case. In the Northwest, utility savings equal 85% 

of NPCC conservation targets, with remainder achieved through codes/standards. Utilities in 

many other states achieve savings of roughly 1.5% of retail sales.

Northeast 

Low

Spending levels in most states remain flat at roughly the statutory minimum (constituting a 

decline from current spending in some states) and/or continue at current funding levels. In NJ, 

spending declines by more than 50% from current levels, as reliance shifts to revolving loan 

funds, with program spending equal to roughly 70% of the levels specified in the recent RFP 

for program administration.

Medium 

Spending in most states, as a percentage of revenues, remains flat at the level in the final year 

of the most recent energy efficiency program plan. NY meets its EERS target for 2015, but 

spending thereafter reverts to the 2010-2015 average. PA spending rises to current cap. NJ 

programs shift to revolving loan funds, but spending levels declines less severely than Low 

Case to reflect a more successful transition to financing model.

High 

New England IOUs capture all cost-effective energy efficiency, up to a stipulated spending cap 

(10% of revenues for MA, RI, and VT; 6.5% for CT). NY meets its EERS target for 2015, and 

spending thereafter continues at 2015 levels. Savings in other states rises to 1-2% of retail 

sales. 

Uncommitted 

Low Spending increases to 0.3% of revenues above current levels 

Medium Spending increases to 0.5% of revenues above current levels

High Spending increases to 0.8% of revenues above current levels
15

3.2. Gas Energy Efficiency Program Spending Projections

For the purpose of developing projections of utility customer funding of gas efficiency 

programs, we first grouped states into three categories: Tier I consists of the 13 states that 

comprise more than 80% of current national funding for gas efficiency programs, Tier II 

consists of another 15 states where 2010 spending on gas efficiency programs exceeded $0.50 

per capita, and Tier III consists of the remaining 23 states. (See Technical Appendix A for the 

set of states included within each tier). 

The process for developing scenario definitions for each state differed according to its tier (see

Table 4). For Tier I states, gas efficiency program spending projections are based on statespecific policies, gas DSM program plans, and regulatory decisions that set savings targets for 

gas utilities, and were further informed by interviews with program administrators, regulators 

and other experts in the field. For most Tier I states, the low and medium case spending 

projections track the most recent multi-year gas DSM program plans to their terminal year 

(typically 2012 to 2014). In the low case, we assume that spending on residential gas efficiency 

programs in most Tier 1 states will decline to 25% of the level in the terminal year of the most 

recent DSM plan, while spending on commercial and industrial (C&I) programs will decline to 

roughly 80% of the level in the terminal year of the DSM plan. This decline in spending is due 

to the combination of sustained low natural gas prices, which reduce the cost effectiveness of 

gas efficiency programs, and tightening federal minimum efficiency standards for gas furnaces, 

which reduce the savings for voluntary programs – both of which are discussed further in 

Section 5. In the medium case, we assume a more modest drop-off in residential program 

spending, typically to 50% of the level from the terminal year of the most recent gas DSM Plan, 

but that C&I program spending increases slightly, as program managers shift budgets towards 

markets with greater savings opportunities. In both the low and medium scenario, we assume 

that spending on gas low-income programs remains constant at the level from the last year of the 

DSM plan, as these programs meet broader policy objectives (e.g. equity, reductions in bill 

arrearages) and therefore are less susceptible to the dynamics putting downward pressure on gas 

program spending for the other sectors. Finally, in the high case, we assume that many Tier I 

states achieve gas savings levels on par with the gas EERS targets recently adopted in several 

states (i.e., generally 1.0-1.5% of total gas distribution utility retail sales). 

Table 4. Scenario Assumptions for Gas Energy Efficiency Projections

Category Scenario Representative Assumptions

(specific assumptions vary by state)

Tier I States

Low

Assume new furnace equipment standards and moderate gas prices cause a reduction in

residential program spending to 25% of the level from the most recent gas DSM plan, and to 

80% for commercial & industrial programs. No change in low-income program spending.

Medium

Assume new furnace equipment standards and moderate gas prices cause a reduction in

residential program spending to 50% of the level from the most recent gas DSM plan, but a 

slight increase in C&I program spending. No change in low-income program spending.

High States reach stipulated benchmarks for gas program savings ranging from 1.0% to 1.5% of total 

gas distribution utility sales.

Tier II States All Regional benchmark (average) based on low, medium and high scenarios in Tier I

Tier III States

Low Spending remains at 2010 levels in absolute nominal dollar terms

Medium Spending remains at 2010 levels as a percentage of gas distribution utility revenues

High Spending percentage increases above current levels by 0.25% of gas distribution utility revenues
16

The 15 Tier II states have relatively aggressive spending levels on a per capita basis, but small 

populations and therefore small spending levels in absolute terms. Thus, for simplicity, the 

spending projections for these states were developed based on regional benchmark trajectories 

that were developed from the projections for Tier I states in the corresponding region. These 

regional benchmark trajectories were developed by averaging the change in spending as a 

percentage of gas distribution utility revenues per year by region for the Tier I states in each 

census region. Those growth curves were then applied to the 2010 spending for each Tier II 

state. As an example, in the medium case, spending for the three Tier I states in the Northeast 

(MA, NY, and NJ) is projected to increase by, on average, 0.6% of revenues; thus, the same 

0.6% increase in spending as a percent of revenues was stipulated for the Tier II northeastern 

states in the medium case. For further details, please refer to Technical Appendix A.

For the remaining 23 Tier III states that currently have little or no customer-funded gas program 

activity, we assumed that future gas efficiency spending will, in the low case, remain at 2010 

levels in absolute nominal dollar terms (thus declining as a percentage of gas distribution utility 

revenues, as revenues grow). In the medium case, we assume that program administrators 

maintain gas efficiency spending at their present level, in terms of the percentage of utility 

revenues. The high case posits that program administrators will increase program spending to 

approximately 0.25% of revenues above 2010 levels by 2025.
17

4. Results 

In this section, we present our projections of spending on utility customer-funded energy 

efficiency programs through 2025. We first present total projected spending for electric and gas 

efficiency programs, combined, before turning to the projections for each fuel individually. We 

also present projections of electric energy savings associated with the three spending trajectories 

for electric efficiency programs and consider the potential significance of these savings 

projections in relation to current expectations about future load growth in the electric sector.16 

The results presented throughout this section focus primarily on national and regional trends; the 

corresponding state-level projections are provided in Technical Appendix B.

4.1. Combined Electric and Gas Energy Efficiency Program Spending Projections

Total spending on electric and gas energy efficiency programs is expected to increase in all 

scenarios across the study period. By 2025, we project that total electric and gas efficiency 

program spending, in nominal dollars, will rise from $4.8 billion in 2010 to $6.5 billion in the 

low case, $9.5 billion in the medium case, and $15.6 billion in the high case (see Figure 1). 

These projections correspond to compound growth rates of approximately 2% per year (low 

case), 5% per year (medium case), and 8% per year (high case). Although the projected increase 

in spending in both the medium and high cases is sizable in absolute dollar terms, the associated 

growth rates in all cases are substantially lower than that witnessed over the past half-decade, 

when total electric and gas efficiency program rapidly accelerated at an average rate of 26% per 

year from 2006 to 2010 (Eldridge et al. 2008, CEE 2012). In the decade preceding this recent 

and rapid expansion of energy efficiency program activity, however, electric program spending 

grew by less than 5% per year from 1997 to 2006, which is on par with the projected growth in 

spending under the medium case.

As discussed further in the following sections, projected growth rates for electric efficiency 

program spending are somewhat higher than for gas program spending in both the low and 

medium cases, with projected electric program spending growth of 2.3% and 4.9% per year in 

the low and medium cases, versus less than 1.1% and 3.8% per year for gas programs. In the 

high case, however, gas efficiency spending grows faster than electric spending (9.7% vs. 

7.8%). These differing trends reflect, in large part, the broader base of underlying policy support 

for, and historical experience with, electric efficiency programs, leading to stronger growth in 

the low and medium cases for electric programs, while leaving a large upside potential for 

growth in gas program spending under the high-case conditions.

 16 We do not present projections of natural gas program savings, as insufficient data exists to link the projected 

spending amounts to specific savings trajectories. 
18

Source: 2010 spending based on CEE (2012)

Figure 1. Projected Electric and Gas Energy Efficiency Program Spending

4.2. Electric Energy Efficiency Program Spending Projections

Spending on electric utility customer-funded energy efficiency programs is expected to increase, 

in nominal dollar terms, across all scenarios (see Table 5). Relative to 2010 spending of $3.9 

billion (1.1% of total electric utility retail revenues), spending is expected to more than double 

to $8.1 billion by 2025 in the medium case (1.7% of revenues). In comparison, spending in the 

low case is projected to increase more slowly, reaching $5.5 billion by 2025 (1.1% of revenues). 

As described in Section 3, this slower pace of spending growth reflects a future scenario in 

which regulators and administrators “stay the course” at current funding levels, and many states 

with aggressive savings targets fall short of those goals. In the high case, spending more than 

triples from 2010 levels, reaching $12.2 billion (2.7% of revenues), due to the impact of “all 

cost effective efficiency” policies in leading states, successful achievement of EERS targets, and 

an increase in program savings in a number of states to the levels projected for regional peers.

Importantly, the projected growth in electric program spending across all cases does not occur 

smoothly over the forecast period, but rather is “front-loaded”, with much faster growth 

projected through 2015 (Table 5). In the medium case, for example, spending grows by 11% 

per year through 2015 but by only 2% per year from 2020 to 2025. This dynamic is partly due 

to the fact that, in many states, recent multi-year DSM plans entail significant spending 

increases over the next several years, but no longer-term targets or resource planning process 

currently exists to guide program activity beyond the time horizon of the DSM plan. The frontloaded spending projections also reflect the trajectory of EERS schedules, which typically reach 

their terminal targets by 2020 or sooner. From 2020 onward, we assume that spending growth 

in many states tapers off and grows roughly in proportion with projected revenues, reflecting 

both a lack of strong policy drivers for continued spending growth after 2020, as well as the 

assumption that savings potential within the 2020-2025 period will be diminished due to the 
19

success of programs implemented over the prior decade and tightening federal efficiency 

standards.

Table 5. Projected Electric Energy Efficiency Spending

Scenario

Projected Spending 

($B, nominal)

Projected Spending 

(% of Revenues) Average Annual Spending Growth

2015 2020 2025 2015 2020 2025 2010-2015 2015-2020 2020-2025

Low 4.8 5.2 5.5 1.2% 1.2% 1.1% 4% 2% 1%

Medium 6.5 7.4 8.1 1.7% 1.8% 1.7% 11% 3% 2%

High 8.3 10.8 12.2 2.2% 2.6% 2.7% 16% 5% 3%

Not surprisingly, total U.S. electric program spending across all scenarios are driven, in large 

measure, by EERS policies, energy efficiency eligibility under RPS policies and legislative 

mandates requiring utilities to acquire all cost-effective energy efficiency. In the medium case, 

for example, the 15 states with an electric EERS, plus the additional five states with legislative 

“all cost-effective energy efficiency” mandates (and no associated EERS) and the two states that 

qualify energy efficiency as an eligible resource under a renewable portfolio standard (again, 

without an associated EERS) together account for 72% of the total projected electric efficiency 

program spending in the U.S. in 2025 (see Figure 2). The remaining spending is associated 

primarily with the additional 18 states that rely primarily on DSM planning and/or IRP (without 

an associated EERS or “all cost-effective energy efficiency” mandate) to establish their electric 

efficiency budgets and targets, together comprising 28% of total projected spending on electric 

efficiency programs. 

Figure 2. Policy Drivers for Projected Electric Energy Efficiency Spending in the Medium Case 

(2025)

Projected trends in total U.S. spending are, to some extent, an overlay of distinct quasi-regional 

trends (see Figure 3). In the medium scenario, overall growth of national efficiency program 

spending is driven chiefly by projected growth in the Midwest and South, which together 

represent 70% of projected total U.S. electric program spending growth over the 2010-2025 

period. In the Midwest, spending growth is associated with a contingent of populous states (IL, 

IN, MI, OH) that are currently ramping up to meet statutory EERS targets, while in the South, 
20

increases in efficiency program spending are associated with a collection of relatively modest 

EERS policies and nascent IRP/DSM planning processes in states with a large base of energy 

consumption (TX, FL, NC, MD, KY). The same underlying policy drivers propel spending 

growth in these two regions in the low and high scenarios as well, though to differing degrees. 

In the West and Northeast – the traditional bastions of energy efficiency activity – electric 

program spending is also projected to increase in the medium case, though by lesser amounts 

than the other two regions, reflecting the more mature state of those markets. In the Northeast, 

efficiency program spending is projected to increase under all three scenarios, where differences 

in spending levels between the medium and high cases are largely driven by assumptions about

how utility program administrators and state regulators translate statutes requiring acquisition of 

all cost-effective efficiency into multi-year savings goals. For the West, the regional trends are 

dominated by California, where electric program spending in both the medium and low cases is 

projected to decline over the long term, as saturation within key end-use markets occurs and as 

the state leans more heavily on other energy efficiency policies (Navigant 2012). In the medium 

case, those declines are offset by spending growth in other western states, leading to net 

spending growth for the region as a whole, while in the low case, total electric program 

spending in the West is projected to decline slightly. 

Figure 3. Projected Electric Energy Efficiency Spending by Census Region

The differing regional trends imply a continued shifting of the energy efficiency map over the 

coming decade and beyond (see Figure 4). While states in the West and Northeast accounted for 

more than 70% of efficiency program spending in 2010, that percentage declines to just over 

50% by 2025 in the medium case, with the South and Midwest splitting the remaining spending 

about evenly. Notwithstanding the greater regional balance in absolute dollar spending on 

electric efficiency programs, the South is still projected to lag well behind other regions in terms 

of relative spending levels as a percentage of electric utility revenues. As shown in Figure 5, 

spending as a percentage of revenues in the medium case is projected to rise from 1.8% and 

2.8% in the Northeast over the 2010 to 2025 timeframe, and decline slightly from 2.4% to 2.1% 

in the West. In the Midwest, efficiency spending is expected to increase quite dramatically
21

(from 0.7% to 2.2% of revenues). However, in the South, while spending as a percentage of 

total electric utility revenues rises from 0.4% of revenues in 2010 to 0.9% in 2025, this is onethird to one-half the spending levels projected in the other three regions.

Figure 4. Regional Distribution of Electric Energy 

Efficiency Program Spending (Medium Case)

Figure 5. Electric Energy Efficiency Program 

Spending as a Percent of Utility Revenues (Medium 

Case)

4.3. Electric Energy Efficiency Program Savings Projections

In 2010, electric energy efficiency programs in the U.S. achieved incremental energy savings of 

18.4 TWh, equivalent to 0.49 % of electric utility retail sales nationally (Foster et al. 2012).17 In 

comparison, leading states, where program administrators typically have a decade or more of 

experience in delivering energy efficiency programs, have achieved annual savings of more than 

1.0% of retail sales (e.g., CA, CT, MA, OR, VT, NV, HI, RI, and MN), and a sizeable 

contingent of other states has consistently achieved savings in excess of 0.50% of retail sales.

As explained previously in Section 3 (and in greater detail in Appendix A), the electric 

efficiency program spending projections are linked to a corresponding set of savings projections 

(see Table 6 and Figure 6), where in some cases savings estimates are derived from spending, 

and in other cases vice-versa.18

 17 Note that energy savings number cited here represents first-year savings from programs implemented in 2009, and 

should not be confused or compared with other estimates (e.g., CEE 2012) that refer to the combined impact in any 

given year from both programs implemented in that year and from programs implemented in prior years.

In the medium case, incremental annual energy savings from 

electric efficiency programs are projected to increase to 28.8 TWh and 0.76% of retail sales in 

2025. This represents roughly a 50% increase over the impact of electric efficiency programs in 

2010. As was the case for the spending projection, much of the projected increase in annual 

incremental savings is concentrated in the initial years of the forecast period, as the projection 

18 To the extent possible, spending projections are intended to reflect “gross” savings (i.e., prior to accounting for 

free-riders or spillover effects). This approach was taken in order to abstract from potential inconsistencies across 

states in methods for estimating net-to-gross ratios. 
22

follows the trajectory of the most recent batch of utility energy efficiency plans (which typically 

terminate in the 2012-2014 period) and EERS targets (which typically reach their final 

percentage targets by 2020 or sooner).19 In the low case, incremental annual savings rise 

moderately by 2015 before largely flattening out over the remainder of the forecast period, 

reaching 20.6 TWh or 0.53% of retail sales by 2025. In the high case, annual incremental 

savings rise to 41.6 TWh by 2025, more than double the level achieved in 2010, equivalent to 

1.13% of total electric utility retail sales. Thus, in effect, the high case represents a scenario in 

which the national average savings rise to the level currently being attained by the top tier of 

states. In both the medium case and the high case, savings levels nationally are within the 

bounds of most studies of “achievable” energy efficiency potential. This suggests, among other 

things, that the level of savings projected in these two cases could potentially be reached 

through accelerated deployment of current technologies, without significant reliance on new 

efficiency technologies. 

Table 6. Projected Incremental Annual Electricity Savings from Utility Customer-Funded 

Programs (TWh) 

Scenario 2010 2015 2020 2025

Low

18.4

20.4 21.1 20.6

Medium 26.6 28.6 28.8

High 33.1 39.8 41.6

Figure 6. Projected Electricity Savings from Utility Customer-Funded Efficiency Programs

To place these savings projections in perspective, the Energy Information Administration 

(EIA)’s most recent reference case forecast (EIA 2012) projects that total U.S. retail electricity 

sales will grow at a compound annual growth rate (CAGR) of 0.58% over the 2010 to 2025 

period, which is substantially lower than the average U.S. load growth of 1.6% per year over the 

past two decades. The EIA’s modeling framework (the National Energy Modeling System, or 

 19 For many states, our analysis assumes constant savings percentages from 2020 to 2025; those assumptions are 

reflected in the national totals in Figure 7, which similarly shows a flat or slight decline in savings percentages from 

2020 to 2025. 
23

NEMS) does not explicitly account for the impacts of future utility customer-supported 

efficiency programs; however, the electricity sales forecast generated by NEMS implicitly 

assumes that historical trends in utility customer-funded efficiency programs will continue over 

the forecast period. For the period 2000 to 2010, we estimate that utility customer-funded 

energy efficiency programs nationally achieved incremental savings of roughly 0.18% per year, 

on average.20 Thus, if one were to assume that the EIA reference case forecast implicitly 

assumes that savings from customer-funded electric efficiency programs continue to accrue at 

this historic rate, then a hypothetical reference case forecast with no future customer-funded 

energy efficiency activity would correspond to a CAGR of 0.76% (i.e., 0.58% plus 0.18%). 

Our medium case projection corresponds to average annual incremental electricity savings of 

0.72% of retail electric sales per year between 2010 and 2025. This, in turn, implies that if 

electric utility customer-funded efficiency programs achieve savings at the level projected under 

our medium case, they would reduce growth in U.S. retail electricity sales to just 0.04% per year

through 2025 (i.e., 0.76% annual growth with no future efficiency program activity minus 

projected annual incremental savings of 0.72% of retail sales per year under the median case), 

offsetting almost all projected load growth under EIA’s 2012 reference case forecast.21 

Following the same logic, our low case and high case savings projections would offset roughly 

70% and 120% of load growth, respectively, yielding average annual growth rates for retail 

electricity sales of 0.21% and -0.18% from 2010 to 2025. To be sure, these benchmarks should 

be considered no more than a “back-of-the-envelope” estimate of the impact of projected 

customer-funded efficiency program savings on load growth in the United States. Nevertheless, 

they suggest that rising savings levels, in combination with modest underlying drivers for load 

growth, could potentially lead to flat, or even negative, load growth over the next 10 to 15 years.

4.4. Gas Energy Efficiency Program Spending Projections

Our analysis suggests a very different set of trajectories for gas efficiency programs compared to 

electric efficiency programs (see Figure 7 and Figure 8). While the low and medium scenarios 

both show gas efficiency spending increasing from 2010 to 2015, associated primarily with

increases that have already been planned or approved in recent multi-year gas DSM plans, we 

currently see little evidence to expect significant further spending growth at a national level 

beyond 2015. Thus, in the low case, spending on gas efficiency programs recedes from its 

elevated level in 2015 to below $1 billion in 2025 (0.5% of revenues), which is slightly higher 

than 2010 spending in absolute nominal dollar terms but lower as a percentage of gas 

 20 EIA’s National Energy Modeling System (NEMS) is calibrated to historical data on end-use stock efficiency and 

shipments, and the customer adoption simulation assumes, in essence, that consumers will continue purchasing 

equipment that exceeds minimum efficiency standards to the same extent as has historically occurred. This estimate 

of incremental savings from efficiency programs is based on ACEEE data for national electric efficiency program 

savings for 2006-2010, and savings for 2000-2005 are estimated based electric efficiency program spending for 

those years.

21 One must interpret this finding with a certain degree of caution given that: (a) EIA’s 2012 reference case load 

forecast projects much slower growth in electricity demand and in economic activity than has historically occurred, 

and (b) uncertainty regarding the precise extent to which EIA’s load forecast accounts for the impacts of future 

electric utility customer-funded efficiency programs. Our results suggest that additional analysis of the amount of 

future energy efficiency program savings that is implicit in EIA’s reference case forecast and more consistent 

accounting of free rider and spillover effects is warranted, although beyond the scope of this study.
24

distribution utility revenues. In the medium case, spending remains roughly flat at projected 

2015 levels, reaching almost $1.5 billion in 2025, equivalent to 0.8% of revenues, a slight 

increase over the 2010 level. As discussed in Section 3, the low and medium case projections

are driven largely by scheduled increases in federal minimum efficiency standards for furnaces, 

with differing assumptions between the low and medium cases about the extent of the impact on 

residential gas efficiency spending and the degree to which declines in residential program 

spending may be offset by increased spending on programs that target commercial/industrial 

customers. In the high case, however, where gas program savings in the leading states are 

assumed rise to levels on par with current leading states for electric efficiency, spending on gas 

programs roughly triples from 2010 levels, reaching $3.3 billion in 2025 (1.8% of revenues).

Figure 7. Projected Gas Energy Efficiency Program Spending

Figure 8. Projected Gas Energy Efficiency Program Spending as a Percentage of Gas Distribution 

Utility Revenues
25

5. Discussion of Key Issues and Uncertainties

The preceding set of projections suggest a wide range of potential trajectories for utility 

customer-funded energy efficiency program spending and savings in the United States – even 

without considering the possibility of fundamentally new policy developments. In this section, 

we identify some of the significant issues and uncertainties that may influence the spending 

course and impact of these programs over the next 10 to 15 years and which we attempted to 

account for – either directly or indirectly – within the projections. These interrelated issues and 

uncertainties include both external factors, such as the broader policy and market context within 

which utility customer-funded programs operate, and internal factors related to the 

implementation and regulatory oversight of these programs.

5.1. Broader Market and Policy Context

Utility customer-funded energy efficiency programs and their enabling policies function within 

a broader context, influenced by a variety of market forces and conditions, as well as by

interactions with other policies. We briefly highlight four key elements of this broader market 

and policy context that may be particularly critical to the future trajectory of customer-funded 

efficiency programs: the state of the economy, natural gas prices, federal minimum efficiency 

standards, and environmental regulations affecting the electric power sector.22 

The Economy

The timing and extent of the economic recovery may complicate and restrain efforts to scale-up 

energy efficiency spending and savings over the near to medium term, for several reasons. First, 

utility customer-funded energy efficiency programs typically requires customers to pay a portion 

of the capital outlay for energy efficiency measures; as households and businesses struggle to 

manage their day-to-day expenses, and as declining home values reduce the equity available for 

financing efficiency improvements, many customers may be reluctant to make new investments, 

even those with short payback periods. As a result, program participation may be suppressed, or 

program costs may rise if program administrators are required to increase financial incentives or 

expend greater sums on marketing efforts. Second, a stagnant economy is likely to reduce the 

rate of stock turnover and new housing starts, thereby reducing the amount of energy savings 

that could be captured through utility customer-funded programs targeting these market 

opportunities. Third, a slow economy may indirectly constrain energy efficiency program 

efforts in at least three ways: heightened sensitivity to potential near-term rate impacts 

associated with efficiency program spending,23

 22 Other aspects of the broader market and policy context that may impact future customer-funded energy 

efficiency program activity include the development of alternative utility business models, increasing capital costs 

for conventional generation technologies, greenhouse gas mitigation policies, and the lasting effects of ARRAfunding on energy efficiency program delivery infrastructure and energy efficiency potential.

increased risk that policymakers will re-direct 

23 Lawmakers in Wisconsin and regulators in Florida, for example, have both cited rate impacts in repealing or 

lowering energy savings targets. 
26

dedicated funding for energy efficiency to shore-up state budgets24 or other non-efficiency 

purposes, and slowed load growth, thereby reducing the avoided capacity costs and cost 

effectiveness of energy efficiency programs.

Moderate Natural Gas Prices

As of April 2012, natural gas was trading at wellhead prices of less than $2 per million British 

thermal units (MMBtu), the lowest level in 10 years and nearing a record low. Although natural 

gas prices are projected to rise over the next 20 years (EIA 2012), they are nevertheless expected 

to remain lower, in real terms, than the prices that characterized most of the past decade, when 

most state energy savings targets were set.25 For electric and gas energy efficiency programs, 

lower gas prices translate into reduced program benefits, which in turn constrains total 

efficiency spending and flexibility in program design as benefit-cost ratios decrease. More 

aggressive efficiency portfolios and comprehensive, multi-measure programs may be especially 

at risk, because costlier measures will result in longer payback periods for customers and will 

not be as cost effective from a total resource cost perspective. The effects of moderate gas prices 

will be especially pronounced for natural gas efficiency programs because lower gas commodity 

costs means lower avoided energy costs to gas utilities, which affects program cost 

effectiveness. Lower gas prices also mean that customers will have incentive to increase 

consumption or convert to gas heating from other fuels and will have less direct financial 

incentive to invest in energy efficiency.

State and Federal End-Use Codes and Standards

In recent years, state adoptions of building energy codes have increased, and federal minimum 

efficiency standards for appliances and end-use equipment have been tightened. These policies 

affect utility customer-funded programs by essentially raising the baseline against which savings 

are measured, thereby influencing both the size of the remaining potential that can be harvested 

through those programs and the mix of technologies targeted. Two specific federal efficiency 

standards that are planned to go into effect over the near-term – for lighting in 2012 to 2014, 

then again in 2020, and for non-weatherized natural gas furnaces in 2013 – may have potentially 

significant impacts on customer-funded efficiency programs. The impact of the federal lighting 

standards is somewhat less certain, because program administrators have other lighting 

technologies that are likely to remain cost effective after the standards come into effect. Gas 

program administrators, however, may have fewer options. Starting in 2013, the new furnace 

standards would raise the minimum heat-to-fuel efficiency of furnaces from 78% to 90% 

AFUE26

 24 Actual diversions of SBC funds to state general funds have been considered by state legislators in a number of 

states and have actually occurred in several states. For example, nearly a third of program revenues in Connecticut 

were redirected to the state general fund and California lawmakers considered diverting $161 million in gas SBC 

funds to the state general fund but a state court denied the transfer. 

in northern states (generally the states with the nation’s most substantial spending and 

25 The trajectory for gas prices, and the implications for spending and performance of gas energy efficiency 

programs, could change in response to, for example, tighter regulation of hydraulic fracturing, an acceleration in the 

expected increase of demand among gas-fired generators or a rapid increase in exports of liquified natural gas. 26 Annual fuel use efficiency (AFUE) is an equipment rating intended to measure the season-long, average 

efficiency of equipment as a ratio of thermal energy output to fuel energy input. An AFUE of 78%, the current U.S. 

standard for furnaces, represents an average of 78 Btus of heat for every 100 Btus of energy in the combusted fuel.
27

savings targets). Programs can continue to provide incentives for higher efficiency gas furnaces, 

but with a technological efficiency limit of about 98% AFUE, the incremental savings will be 

lower, and residential gas furnace programs are therefore less likely to continue as the mainstay 

of gas efficiency program portfolios.

Emissions Regulations

Proposed or final air emissions regulations that are being considered or adopted by state and 

federal environmental agencies27- in combination with low-priced, abundant gas – have become 

important drivers for utility customer-funded energy efficiency programs, as part of utilities’ 

multi-faceted strategies for managing the retirement of older coal-fired generators.28 For 

example, many utility resource plans have discussed the potential role of demand-side resources 

as part of a strategy for complying with emissions requirements (e.g., Tennessee Valley 

Authority), as a prerequisite for utility customer funding of low carbon replacement generation 

(American Electric Power in West Virginia, Florida Power & Light in Florida), or as a means of 

deferring retirement and replacement decisions (Duke Energy Carolinas). The ultimate import 

of these regulations for future energy efficiency program budgets, however, depends on several 

factors. These factors include: the timing and stringency of the final rules; the price of natural 

gas (as gas-fired generation is expected to offset the majority of the retired coal-fired 

generation); the capital cost profile of clean energy generation alternatives (e.g., renewable 

energy, nuclear power, coal with carbon capture and sequestration); the regulatory and business 

models in place that govern the balance and relative attractiveness of supply- and demand-side 

investments; and the degree to which utilities and utility regulators integrate state and tribal 

Clean Air Act implementation plans with utility resource plans.

5.2. Energy Efficiency Program Implementation and Regulatory Oversight

There are also a variety of other critical issues and uncertainties specific to the regulatory and 

administrative institutions within which utility customer-funded efficiency programs operate and 

that may strongly influence the spending and savings trajectories of those programs. Here, we 

highlight several: general aversion to rate impacts, challenges associated with developing 

innovative program designs to reach deeper and broader savings, and the limited ability in some 

states to extend gas efficiency programs to transportation gas customers.

Aversion to Rate Impacts

In most states, utilities typically expense program costs for energy efficiency as they are 

incurred. As a result, energy efficiency program cost recovery is relatively front-loaded 

compared to cost recovery for most utility supply-side resource alternatives. As a result, the rate 

 27 Efforts to limit these emissions span multiple sets of regulations – for air toxics, for nitrogen and sulfur oxides, 

for greenhouse gases, for managing coal ash and for limiting once-through cooling for generators – and each of 

these regulations has its own timeline and likelihood of coming into effect. 28 Coal-fired generators are the nation’s largest single source of acid gases, carbon dioxide and air toxics such as 

mercury. The oldest coal-fired generators in the U.S., generally those of 1960s vintage or earlier would be most 

affected by these environmental regulations. See CRS (2011), Brattle Group (2010) and Bipartisan Policy 

Commission (2011) for a more detailed discussion of these regulations, their timing and the projected impacts on the 

electric power industry. 
28

impacts from energy efficiency tend to occur sooner (even if the rate impacts are less over the 

long-term, and even if average utility bills are reduced compared to supply-side alternatives). 

The short-term rate impacts associated with attaining very aggressive levels of savings (or even 

relatively modest levels of savings in states that are higher than has historically occurred) could

pose a political challenge for state regulators, particularly in states that have seen significant rate 

hikes in recent years or whose rates are well-above national averages. Across all states, these 

challenges are further heightened during periods of economic hardship. Concerns about rate 

impacts from energy efficiency programs have been institutionalized in a number of states, 

either through explicit caps on spending or rate impacts, or by the application of the ratepayer 

impact measure (RIM) test.29 Meeting aggressive EERS targets in some states will likely 

require exceeding these caps or otherwise justifying rate increases, which may be feasible only 

in a robust, growing economy.

Developing Innovative Program Designs to Reach Deeper and Broader Savings

A number of states have established aggressive energy efficiency savings goals for future years 

that are well beyond current experience and practice in most leading states (e.g., annual 

incremental electric savings on the order of 1.5% to 2% or more of retail sales). The challenge

for these program administrators will be to design and implement programs that can achieve 

both deeper savings, on average, at customer facilities and have a broader reach in terms of 

market penetration over a sustained period of time. Service providers will have to achieve 

savings levels of 25-40% of existing usage at customer facilities compared to current practice in 

utility customer-funded programs, which is typically in the 5-20% range. Achieving higher 

market penetration rates will require programs to target and reach traditionally under-served 

markets (e.g., small commercial, multi-family, rental housing, moderate income households, 

non-owner occupied commercial facilities) in far greater numbers than current practice 

(MEEAC 2009). We are also likely to see increased attention to integrated delivery of electric 

and gas efficiency programs as well as coordinated delivery of energy efficiency, on-site 

renewables and combined heat and power, in order to reduce transaction costs and provide 

customers with tailored, customized service offerings.

Extending Programs to Transportation Gas Customers

In many states, energy savings in the large commercial and industrial markets are, in effect, 

beyond the reach of program administrators. This is especially true for gas efficiency programs, 

as large commercial and industrial customers often purchase natural gas on the competitive 

market through alternative retailers, and may not pay into or be able to participate in gas utility 

customer-funded energy efficiency programs.30

 29 For example, Michigan and Illinois have spending caps in their EERS legislation. In Wisconsin, lawmakers 

rescinded regulatory discretion over program spending and capped spending at about half the levels anticipated to 

meet original savings targets. In Florida, the PSC continues to rely heavily on the RIM test to screen energy 

efficiency programs; the RIM test highlights potential rate impacts on non-participants rather than reductions in 

average customer bills from cost-effective efficiency investments. 

 This “transportation gas” accounts for 46% of 

total U.S. gas sales and 79% of all commercial and industrial sales. The ability for many states 

30 Related, large electricity customers in many utility service areas may either “opt out” of paying charges for 

energy efficiency programs or direct most or all of their share of those charges into their own, “self-direct” energy 

efficiency investments.
29

to significantly increase gas efficiency program savings and spending may therefore hinge, to a 

large degree, on whether mechanisms can be developed (e.g., non-bypassable charges for 

program funding) to bring these customers and savings opportunities into the program fold.
30

6. Conclusions

Energy efficiency programs funded by utility customers are poised for dramatic growth over the 

course of the next 10 to 15 years, especially in the Midwest and South – with a contingent of 

populous Midwest states ramping up to meet statutory EERS targets, and in the South, the 

expectation that a collection of relatively modest EERS policies and nascent IRP/DSM planning 

processes in states with a large base of energy consumption will push spending upward from 

currently low levels. As a result, program spending is expected to become more evenly 

distributed nationwide by 2025. 

Program spending is projected to roughly double to $9.5 billion in 2025 and could reach $15.6

billion under aggressive assumptions about the policy support, implementation and effectiveness 

of current policies. Program administrators in many states are projected to achieve annual 

electricity savings of between 1.5% and 2%, surpassing the achievements of most leading states 

today. 

Given forecasts for a slow economy recovery and modest load growth, the projected growth in 

electricity program spending and savings under our medium case scenario would offset most 

aggregate annual U.S. electric load growth through 2025, based on the load forecast in EIA’s 

most recent reference case (and given assumptions about the extent to which EIA’s forecast 

captures the impact of future efficiency programs). 

However, program administrators and state regulators face emerging challenges and 

uncertainties. The combined effects of economic torpor, moderate gas prices, and tightening 

energy codes and minimum efficiency standards pose challenges for continued growth in 

electric and, especially, gas efficiency programs. The degree to which leading states and a new 

vanguard of fast-rising states can overcome these challenges and offset reduced efforts 

elsewhere is likely to govern the longer term path for national-level spending and savings on 

efficiency programs. 
31

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Energy Efficiency in the U.S. Berkeley, CA: Lawrence Berkeley National Laboratory. LBNL2258E. http://eetd.lbl.gov/ea/emp/reports/lbnl-2258e.pdf

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Budgets, Expenditures and Impacts 2011. 

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2012)

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Foster, B., A. Chittum, S. Hayes, M. Neubauer, S. Nowak, S. Vaidyanathan, K. Farley, K. 

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Increasing Energy Efficiency: Thirty Years of Experience in OECD Countries. Energy Policy

34(5): 556–573.

Gillingham, K., R. Newell, and K. Palmer. June 2004, revised September 2004. Retrospective 

Examination of Demand-Side Energy Efficiency Policies. RFF DP 04-19 REV. 

http://www.rff.org/RFF/Documents/RFF-DP-04-19REV.pdf.

Goldman, C., E. Stuart, I. Hoffman, M. Fuller and M. Billingsley. 2011. Interactions Between 

Energy Efficiency Programs Funded Under the Recovery Act and Utility Customer-Funded 

Energy Efficiency Programs. Lawrence Berkeley National Laboratory, LBNL-4322E. 

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Hopper, Nicole, Galen Barbose, Charles Goldman, and Jeff Schlegel. 2008. “Energy Efficiency 

as a Preferred Resource: Evidence from Utility Resource Plans in the Western United States and 

Canada.” Energy Efficiency, 14(2):126-34, October 2008. 

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Efficiency Savings: Electric Savings Update, Electric Net Benefits and Gas Savings. 

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Targets For 2013 And Beyond. Prepared for the California Public Utilities Commission. 

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Nowak, S., M. Kushler, M. Sciortino, D. York, and P. Witte. 2011. Energy Efficiency resource 

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(http://www.aceee.org/sites/default/files/publications/researchreports/u121.pdf)
33

Technical Appendix A: Methodology and Assumptions Used to Develop 

Energy Efficiency Spending and Savings Projections 

This technical appendix describes the methods and assumptions used to develop projections of 

energy efficiency program spending by U.S. electric and natural gas customers and savings 

(electric only) through 2025.

A1. Electric Energy Efficiency Spending & Savings Projections

Low, medium, and high projections of future electric energy efficiency program savings and 

spending were developed on a state-by-state basis. Although many of the specific assumptions 

and the approach to defining scenarios varied by state, the basic methodology used in all states 

consisted of several common components, including:

• Developing projections of retail electricity sales and revenues from retail electricity sales;

• Defining low, medium, and high scenarios of future utility customer-funded energy;

efficiency program savings and spending for the electricity sector; and

• Estimating the amount of spending required to achieve different levels of savings.

Each of these elements is described further below.

A1.1 Retail Sales and Revenue Projections

Projections of annual retail electricity sales and revenues were used as an input to develop 

energy efficiency program savings and spending projections; for example, in those states that 

establish EERS targets as a percent of retail sales, savings projections were calculated based on 

projected retail sales. Sales and revenue projections were also used to develop metrics that allow 

for comparison of spending and savings levels across states of differing sizes (e.g., savings as a 

percent of retail sales and spending as a percent of revenues).

Baseline Retail Sales and Revenue Projections

An initial set of baseline retail sales and retail price projections for each state was developed by 

applying annual growth rate projections from the Energy Information Administration (EIA)’s 

2012 Annual Energy Outlook (AEO2012) reference case forecast to actual 2010 retail sales and 

price data for each state, as reported on EIA’s Form-860. The electricity retail sales and price 

projections in AEO2012 are specified at the Electricity Market Module (EMM) level, the regions 

used in EIA’s National Energy Modeling System (NEMS); the state-level retail electricity sales 

and average retail electricity price projections were developed by applying the EMM-level 

growth rates to historical retail sales and revenues for each state in the respective region. Table 

A-1 summarizes the annual average growth rates (2011 to 2025) of retail electricity sales and 

electricity prices in each EMM region from the AEO2012 reference case forecast. Revenue 

projections were calculated by multiplying projected retail electricity prices by projected retail 

electricity sales.
34

Table A - 1. AEO Projected Growth Rates in Retail Electricity Sales and Prices

Electricity Market Model (EMM) Region States

AEO2012 Average Annual 

Growth Rate (2011-2025)

Retail

Electricity 

Sales

Retail Electricity 

Prices

Price (nominal)

Electric Reliability Council of Texas TX 0.7% 2.0%

Florida Reliability Coordinating Council FL 0.9% 1.6%

Midwest Reliability Council / East WI 0.1% 1.5%

Midwest Reliability Council / West IA, MN, ND, NE, SD 0.2% 1.6%

Northeast Power Coordinating Council / Northeast CT, MA, ME, NH, 

RI, VT 0.2% 1.2%

Northeast Power Coordinating Council / NYC-Westchester NY 0.3% 1.1%

Northeast Power Coordinating Council / Long Island NY 0.1% 1.4%

Northeast Power Coordinating Council / Upstate New 

York NY 0.0% 1.4%

Reliability First Corporation / East DC, DE, MD, NJ, PA 0.3% 1.4%

Reliability First Corporation / Michigan MI 0.1% 1.5%

Reliability First Corporation / West IL, IN, OH, WV 0.2% 2.4%

SERC Reliability Corporation / Delta AR, LA, MS 0.7% 2.2%

SERC Reliability Corporation / Gateway MO 0.2% 2.2%

SERC Reliability Corporation / Southeastern AL, GA 0.8% 1.4%

SERC Reliability Corporation / Central KY, TN 0.8% 1.0%

SERC Reliability Corporation / Virginia-Carolina NC, SC, VA 0.9% 1.4%

Southwest Power Pool / North KS 0.3% 2.1%

Southwest Power Pool / South OK 0.7% 2.3%

Western Electricity Coordinating Council / Southwest AZ, NM, NV 1.3% 2.0%

Western Electricity Coordinating Council / California CA 0.8% 1.9%

Western Electricity Coordinating Council / Northwest 

Power Pool Area

ID, MT, OR, WA, 

WY 0.9% 0.4%

Western Electricity Coordinating Council / Rockies CO, UT 1.3% 1.8%

State-Specific Adjustments for Each Scenario

Future retail sales and revenues in each state will depend, in part, on the amount of savings 

achieved from future customer-funded energy efficiency programs. In order to maintain internal 

consistency, we adjusted the retail sales and revenue projections for each scenario in each state, 

to reflect the energy efficiency savings assumed for the given scenario. The adjustments 

consisted of decreasing (or increasing) the baseline sales and revenue in each year, to account for 

the cumulative difference between the savings assumed for the scenario and the savings assumed 

to be implicit in the AEO2012 forecast. To provide an example: if we project, under one 

scenario, that future annual incremental savings in a given state will be equal to 0.3% of retail 

sales in each year, and the energy efficiency savings assumed to be implicit in the baseline retail 

sales forecast are 0.1% of retail sales, then we would reduce the forecast in each year to account 

for the cumulative effect of the additional 0.2% of retail sales saved each year (i.e., reduce the 

retail sales projection by 0.2% in year one, by 0.4% in year two, and by 0.6% in year three and 

so on).

The foregoing adjustment requires an estimate of the savings embedded in the AEO-derived 

baseline retail sales forecast for each state. Although NEMS does not explicitly account for the 

impacts of future utility customer-supported efficiency programs, the model operates under the 
35

implicit assumption that historical trends in utility customer-funded efficiency programs will 

continue over the forecast period.31 We therefore assumed that the baseline retail sales 

projections, derived from the AEO2012 forecasted growth rates, implicitly account for a 

continuation of customer-funded energy efficiency program savings equal to the average level 

achieved over the 2000 to 2010 period. Comprehensive and reliable state-level data on 

efficiency program savings are available only from 2006 onward, although sufficiently reliable 

historical spending data for the U.S. as a whole are available going back to 2000. Thus, the 

average annual incremental savings in each EMM region over the 2000-2010 period were

calculated via a two-step process. First, historical state-level savings from 2006 to 2009 were 

aggregated up to each EMM region to calculate the average annual incremental savings in each 

EMM region over that period. Second, the 2000-2010 average EMM savings were calculated by 

multiplying the 2006-2009 average EMM savings (from the previous step) by the ratio of 

average U.S. spending over 2000 to 2010 to average U.S. spending over 2006 to 2009. The 

result of this two-step calculation yielded the annual incremental energy efficiency program 

savings assumed to be embedded in the AEO-derived baseline retail sales forecast for each EMM 

region (see Table A-2).

Table A - 2. Estimate Customer-Funded Energy Efficiency Program Savings Embedded in AEO 

Forecasts by EMM Region

Electricity Market Model (EMM) Region Annual Incremental Savings

(% of Retail Sales)

Electric Reliability Council of Texas 0.1%

Florida Reliability Coordinating Council 0.1%

Midwest Reliability Council / East 0.4%

Midwest Reliability Council / West 0.3%

Northeast Power Coordinating Council / Northeast 0.6%

Northeast Power Coordinating Council / NYC-Westchester 0.3%

Northeast Power Coordinating Council / Long Island 0.3%

Northeast Power Coordinating Council / Upstate New York 0.3%

Reliability First Corporation / East 0.1%

Reliability First Corporation / Michigan 0.1%

Reliability First Corporation / West 0.0%

SERC Reliability Corporation / Delta 0.0%

SERC Reliability Corporation / Gateway 0.0%

SERC Reliability Corporation / Southeastern 0.0%

SERC Reliability Corporation / Central 0.0%

SERC Reliability Corporation / Virginia-Carolina 0.1%

Southwest Power Pool / North 0.0%

Southwest Power Pool / South 0.0%

Western Electricity Coordinating Council / Southwest 0.3%

Western Electricity Coordinating Council / California 0.6%

Western Electricity Coordinating Council / Northwest Power Pool Area 0.3%

Western Electricity Coordinating Council / Rockies 0.3%

 31 NEMS is calibrated to historical data on end-use stock efficiency and shipments, and the customer adoption 

simulation operates under the assumption that, in essence, consumers will continue purchasing equipment that 

exceeds minimum efficiency standards to the same extent as has historically occurred. 
36

A1.2 Scenario Definitions

Scenarios were defined on a state-by-state basis, driven primarily by each state’s unique policies, 

regulatory dynamics, program histories, available reports and approved DSM or IRP plans. In 

order to simplify the scenario development and characterization process, we grouped states into 

Census Regions (see Figure A-1). Tables A-3 through A-6 summarize the assumptions used for 

each state by region. For scenarios defined in terms of assumed savings, spending levels are 

derived from savings, and vice-versa. For a group of seven “uncommitted” states that currently 

have little efficiency program activity and no established policy framework, we instead 

employed a standardized approach by which spending as a percentage of revenues was stipulated 

to increase above current levels by a specified amount under each scenario, as described in Table 

A-7.

32 Unless otherwise indicated, spending and savings projections for municipal utilities and

cooperatives within the states covered in Tables A-3 through A-6 are also developed using the 

same assumptions as for uncommitted states. 

Figure A - 1. U.S. Census Regions Used for Scenario Development

Table A - 3. Scenario Descriptions for States in the Northeast

State Case Scenario Assumptions

CT

Low SBC funding remains at current approved levels, but RGGI and FCM funding are no longer used for 

utility customer-funded energy efficiency.

Medium Spending percentage remains at current levels indefinitely; RGGI and FCM funding remains at 

current levels over entirety of forecast period.

High IOU savings equal to all achievable energy efficiency potential, based on NEEP potential analysis, but 

 32 These seven uncommitted states include: AK, KS, LA, ND, NE, SD, and WV
37

subject to an annual spending cap equal to 6.5% of revenue

MA

Low

IOU spending/savings from 2010 to 2012 based on most recent plans. For subsequent years, utility 

customer funding declines to the legislatively mandated SBC plus current RGGI/FCM levels (e.g., 

consistent with a future in which very aggressive codes and standards exhaust much of the costeffective energy efficiency potential). POU spending/savings based on generic assumptions in all 

scenarios.

Medium IOU savings levels remain flat at 2012 level, equal to 2.3% percent of retail sales.

High

IOUs meet state policy of acquiring all cost-effective energy efficiency, with savings estimated based 

on the energy efficiency potential study conducted by NEEP, subject to an assumed annual spending 

cap equal to 10% of revenue from retail sales.

ME

Low Spending remains constant at 2011 level of 1.6% of revenues from retail sales

Medium Spending from 2011 to 2013 based on Efficiency Maine's projected budget, and remains at 2013 level, 

equal to 2.9% of revenues from retail sales, through 2025.

High Savings rise to achieve all cost-effective energy efficiency, based on NEEP analysis, but subject to a 

spending cap equal to 3.6% of revenues.

NH

Low Spending levels through 2020 are based on a continuation of planned 2012 SBC & FCM funding 

levels for electric energy efficiency, equal to 1.3% of revenues from statewide electricity retail sales.

Medium Savings ramp up from 0.6% of retail sales in 2012 (the projected savings under current approved 

funding levels) to 1.2% of retail sales in 2020, and remain constant at that level thereafter.

High Same as the Medium Case, except savings ramp up to 2.0% of retail sales in 2020.

NJ

Low

Spending from 2013 to 2016 is based on RFP (strawman) issued by BPU for a new program 

administrator, de-rated to 70% to reflect historical levels of under-spending. After 2016, spending on 

incentive-based programs remains flat at the 2016 level, and spending on financing programs remains 

at the average of the projected level over the 2013-2016 period.

Medium

Spending from 2013 to 2016 is based on RFP (strawman) issued by BPU for a new program 

administrator, with no de-rating as is applied in the Low Case. After 2016, spending on both 

incentive-based programs and financing programs remains flat at the projected 2016 level.

High

Same as Medium Case through 2016, and after 2016, spending on financing programs is also the same 

as the Medium Case. However, spending on incentive-based programs after 2016 rises such that total 

savings from both incentive-based programs and financing programs reaches 1.5% of retail sales in 

2025 .

NY

Low Funding remains at 2010 levels at 2.5% revenues.

Medium

Savings from 2009 to 2015 are based on the portion of the state's overall EEPS target allocated by the 

NYPSC to utility customer-funded programs. Spending from 2016 to 2020 remains constant at the 

average level during 2009 to 2015, equal to 2.9% of revenues.

High

Savings from 2009 to 2015 are based on the portion of the state's overall EEPS target allocated by the 

NYPSC to utility customer-funded programs. Spending from 2016 to 2020 remains constant at 3.9% 

of revenues.

PA

Low Spending through 2012 is based on approved budget, and decreases to 75% of 2012 spending in 2013, 

equal to 1.5% of revenue

Medium Spending rises to 2% of 2008 revenue, equal to $268 million (current cap) in 2013 and continues 

indefinitely

High Same as Low/Medium case through 2013, but then rate cap is removed and IOU savings increase to 

1.0% of retail sales in 2025

RI

Low Spending through 2025 remains flat at the 2011 level proposed by National Grid in the approved 

settlement for the 2011 Energy Efficiency Plan, estimated to be 4.3% of revenues.

Medium Savings ramp up from planned 1.3% of retail sales in 2011 to 1.9% in 2025, as achieved by MA IOUs 

under Medium Case.

High

IOUs acquire all cost-effective energy efficiency, with savings estimated based on the energy 

efficiency potential study conducted by NEEP, subject to an assumed annual spending cap equal to 

10% of revenue from retail sales.

VT

Low

Spending through 2014 is based on Efficiency Vermont's approved 2012-2014 budgets plus 

Burlington Electric's 2010 spending; spending from 2015 onward remains constant at the average of 

2012-2014 levels, equal to 6.7% of statewide revenues.

Medium Same as Low Case

High Acquire all cost-effective EE, with savings estimated based on the EE potential study conducted by 

NEEP, subject to an assumed annual spending cap equal to 10% of revenue from retail sales.
38

Table A - 4. Scenario Descriptions for States in the South

State Case Scenario Assumptions

AL

Low TVA savings based on 2010 IRP “Baseline Portfolio,” rising to 0.3% of retail sales. Non-TVA load 

based on "uncommitted state" low scenario.

Medium TVA savings based on 2010 IRP selected portfolio, rising to 0.7% of retail sales. Non-TVA load 

based on "uncommitted state" medium scenario.

High TVA savings based on 2010 IRP "High EEDR" portfolio, rising to 1.0% of retail sales. Non-TVA 

load based on "uncommitted state" state high scenario.

AR

Low Annual savings from IOU utility customer-funded energy efficiency through 2013 are based on most 

recently approved DSM plans, and savings remain flat at 2013 levels (0.8% of retail sales) thereafter.

Medium Same as Low Case, except IOU savings rise to 1.0% annual savings in 2017 and remain flat at that 

level thereafter.

High Same as Low Case, except IOU savings rise to 1.25% annual savings in 2021 and remain flat at that 

level thereafter.

DC

Low

The DC City Council terminated all but about $2 million in funding for 2011 programs. Energy 

efficiency spending drops that year then ramps gradually to 1% of revenues in 2020 and remains flat 

to 2025.

Medium Savings ramp up to 1% of retail sales in 2013 (a year later than mandated in the District contract with 

VEIC) and remains flat to 2025.

High Savings ramp up to 1% in 2013 as in the Medium Case, then to 1.2% of retail sales in 2020, then flat 

to 2025

DE

Low

The Sustainable Energy Utility ceases to exist in 2012. No utility customer funding for energy 

efficiency until utilities start their own programs in 2020 (next IRP, assumed funding is equal to 

RGGI funding).

Medium SEU continues to exist funded by the proceeds of the RGGI auctions (assumed constant at 2011 

levels).

High SEU contines to exist with RGGI funding, utilities start their own programs in addition to the SEU. 

Savings achieve 1% of retail sales in 2020.

FL

Low

IOUs and large munis achieve savings in their site plans, which fall to 0.14% of retail sales in 2021, 

and remain flat at that level to 2025. Remaining utilities based on "uncommitted state" low case 

assumptions. 

Medium

Savings for IOUs and large munis in each year are equal to the mid-point of the low and high cases. 

Remaining utilities based on "uncommitted state" medium case assumptions through 2019, reaching 

savings of 0.3% of retail sales and remaining at that level thereafter.

High

Savings for IOUs and large munis ramp from current levels of 0.2% to 0.5% in 2019, per the FPUC's 

adopted 2010-2019 goals, and then ramp up further to 0.75% in 2025. Remaining utilities based on 

"uncommitted state" high case assumptions.

GA

Low GA Power savings through 2013 are based on approved 2011-2013 DSM plan, and remain flat at 2013 

level thereafter (0.3% of retail sales).

Medium GA Power savings based on 2010 IRP targets, which rise to 0.4% of retail sales by 2020, and are 

assumed to remain flat thereafter.

High GA Power savings assumed to ramp up to 1.0% of retail sales by 2025.

KY

Low IOUs realize early-year savings from 2011 DSM plan and 2011 IRP, reaching 0.4% of retail sales in 

2013 and flat thereafter. For TVA load, see Alabama (AL). 

Medium IOUs realize savings from DSM portfolio and 2010 IRP, reaching 0.6% of retail sales in 2014 and 

constant thereafter. For TVA load, see Alabama (AL).

High IOUs realize highest level of savings from 2011 DSM plans and 2011 IRP, reaching 0.8% of retail 

sales in 2014 and constant thereafter. For TVA load, see Alabama (AL).

MD

Low IOU and SMECO spending through 2015 based on their proposed 2012 energy efficiency plans, but 

with a 1-year lag. For 2015 to 2020, spending remains flat at 2015 level, equal to 2.3% of revenues.

Medium IOU and SMECO spending through 2014 based on their proposed 2012 energy efficiency plans. For 

2015 to 2020, spending remains flat at the 2015 level, equal to 2.3% of revenues.

High IOU and SMECO achieve the EmPower Maryland energy efficiency savings target in 2015. For 2015

to 2020, savings levels stay at 1.6% of retail sales.

MS

Low Same as Alabama (AL)

Medium Same as Alabama (AL)

High Same as Alabama (AL)

NC Low

IOUs exhaust, but do not exceed, the energy efficiency allowance under the state RPS; POUs first 

exhaust their allowable use of large hydro, and then meet 50% of remaining RPS needs (after all setasides are met) with energy efficiency.
39

Medium Use the Baseline EE Scenario adopted by the NC. Energy Policy Commission (based upon the La 

Capra Associates report). 

High

All utilities ramp up from annual savings levels of 0.3% of retail sales in 2010 (as projected for that 

year in the Low/Medium Cases) to 1.3% in 2020, then flat through 2025. This is largely consistent 

with the NC Energy Policy Commission's high energy efficiency scenario, which is based upon 

$0.10/kWh avoided costs.

SC

Low Majority of savings and spending are SC share of NC REPS-driven savings and spending by Duke 

and Progress. Extend IOU savings at 2013 levels (0.5% of retail sales) through 2025. 

Medium Assume Duke, Progress and SCEG realize the base case savings projections from their IRPs, rising to 

0.7% of retail sales by 2020.

High

Assume Duke meets its IRP High Case and other large IOUs take their IRP base case savings 

projection, with total IOU savings rising to 0.8% of retail sales in 2020 and ramping up further to 

1.1% of retail sales in 2025.

TN

Low Same as Alabama (AL)

Medium Same as Alabama (AL)

High Same as Alabama (AL)

TX

Low IOU savings meet current EERS goal (20% of incremental peak demand, ramping to 25% in 2012 and 

30% from 2013 on); POU savings/spending are based on generic low case assumptions.

Medium

IOU savings assumed to continue at present levels of over-performance relative to EERS goal. POU 

savings/spending are based on the generic high case assumptions, with savings ramping up to 0.5% of 

retail sales by 2025.

High

Statewide savings are based on both IOUs and POUs meeting the current EERS savings targets 

through 2014 (as in the Mid-Case), with savings from 2015 onward equal to 50% of demand growth 

in each year (as previously proposed). 

VA

Low Spending as a percent of revenues by Dominion Virginia Power continues at the current rate (0.2% of 

revenues).

Medium IOUs reach 0.4% annual savings in 2018 and remain flat thereafter, based roughly on the spending 

trajectory from Dominion Virginia's most recent IRP. 

High All IOUs meet 10% by 2022 voluntary EERS (relative to 2006 load).

Table A - 5. Scenario Descriptions for States in the Midwest

State Case Scenario Assumptions

IA

Low Statewide spending (IOUs & POUs) continues indefinitely at 2010 approved spending levels, 2.9% of 

revenue, with corresponding savings roughly constant at 1.0% of retail sales.

Medium

For 2009 to 2013, IOU spending projections are based on the approved budgets in their 2009-2013 

energy efficiency plans, and POU energy efficiency spending is equal to the projected annual spending 

for 2010 to 2013. For 2014 to 2020, continue IOU & POU spending at projected 2013 level 3.4% of 

revenues, with corresponding savings roughly constant at 1.2% of retail sales.

High

All utilities (IOUs & POUs) achieve savings equal to 1.5% of retail sales by 2011 (the target that IOUs 

were required to evaluate in their most recent energy efficiency plans) and continue at that level until 

2020 when they reach 2% savings.

IL

Low

IOU savings/spending through 2013 are based on approved energy efficiency plans. From 2014 to 

2020, savings equal EEPS targets until statutory cost caps are reached, which limits savings to 

approximately 0.8% of retail sales. 

Medium Same as Low Case, except IOU savings are assumed to rise to 1.3% of retail sales in 2016

High IOU savings/spending through 2013 are based on approved energy efficiency plans. Statutory EEPS 

spending cap is assumed to be lifted or increased, and EEPS targets are assumed to be fully achieved.

IN

Low IURC-jurisdictional utilities (IOUs and some coops and munis) achieve savings levels equal to 75% of 

EERS levels.

Medium IURC-jurisdictional utilities fully meet EERS savings targets.

High Same as Medium Case.

MI

Low Statewide savings based on full compliance with statutory EEPS targets, which reach 1.0% of retail 

sales in 2012.

Medium Same as Low Case.

High Assumes that statewide savings ramp up from 1.0% of retail sales in 2012 to 1.4% in 2020.

MN

Low All utilities meet the minimum 1.0% EEPS target for conservation improvement programs.

Medium Savings ramp up from 1.0% of retail sales in 2010 to 1.2% in 2020.

High Same as Medium Case, except savings ramp up to 2.0% in 2020.
40

MO

Low IOU annual savings are based on most recently approved IRPs and DSM plans through 2015, and 

savings thereafter remain flat at that level.

Medium Same as the Low Case through 2015; from 2016 onward, IOU savings as a percentage of retail sales 

are the mid-point between the Low and High Cases.

High IOU savings track approved/submitted plans through 2014, then meet voluntary goals in MO PSC's 

MEEIA regulations, rising to 1.9% of retail sales in 2020 and remaining at that level thereafter.

OK

Low IOU savings and spending through 2015 based on most recent filed plans, and savings thereafter 

remain flat at the 2015 level. 

Medium Same as Low Case through 2015, after which IOU savings ramp up to 0.75% of retail sales in 2020 (as 

a proxy for the soft rate cap on residential DSM charges) and remain flat at that level thereafter. 

High Same as Medium Case through 2020, but IOU savings continue to ramp up to 1.0% of retail sales in 

2025.

OH

Low

Most IOUs achieve savings equal to 50% (First Energy meets 25%) of legislated EEPS targets, rising 

to 1.0% of retail sales by 2019; stipulated savings reflect a possible reduction in EEPS savings targets, 

and/or high assumed levels of mercantile customer opt-out, reliance on T&D measures, and noncompliance.

Medium

IOUs meet EEPS savings targets in 2022 (delayed four years to ramp to 2022) with the exception of 

First Energy. First Energy meets 50% of its savings targets relying on high assumed levels of 

mercantile customer opt-out, reliance on T&D measures, and non-compliance.

High

IOU savings meet legislated EEPS targets of 2% retail sales in 2019, First Energy meets 75% of EEPS 

target; stipulated savings reflects lower assumed levels (relative to Low/Medium Case) of mercantile 

customer opt-out, reliance on T&D measures, and non-compliance.

WI

Low Spending declines from 2.1% of revenues in 2011, back to 2008 level of 1.2%, consistent with 

legislative rate cap, and remains flat at that level through 2025

Medium Same as Low Case through 2015, then spending rebounds to 1.7% of revenues by 2020 (the mid-point 

between the current spending cap and the maximum historical spending level).

High

Savings based on lagged 2010 regulatory targets and lagged EEPS policy recommendation in 

Governor's Task Force on Global Warming, with spending rising to 3.8% of revenues and savings 

rising to 2.0% of retail sales by 2014.

Table A - 6. Scenario Descriptions for States in the West

State Case Scenario Assumptions

AZ

Low

IOUs and Coops meet minimum EERS requirements; annual savings decline over the 2016 to 2020 

timeframe because utilities are able to use retroactive credit from pre-EERS programs during that 

period, and the savings percentage after 2020 remains flat at the 2020 level. SRP savings remain 

flat at actual 2010 level. Other utilities (munis, tribes, irrigation districts) based on generic method 

in each scenario.

Medium IOUs and Coops are same as the Low Case. SRP savings through 2016 based on targets in 2010 

Sustainability Report Summary, and remain flat at the 2016 level thereafter.

High

IOUs and Coops meet EERS requirements without relying on retroactive credit from historical 

programs. SRP savings follow the targets in the Sustainable Portfolio Plan through 2020, which rise 

to 2% of retail sales, and remain constant thereafter (per-unit costs for SRP are higher, to reflect a 

proportionally lower reliance on M-Power program than in other scenarios). 

CA

Low

For IOUs, savings through 2012 are based on level in approved 2010-2012 energy efficiency plans, 

savings from 2013 to 2014 are based on 90% of levels in the proposed plans, and savings from 2015 

onward are equal to 90% of the maximum achievable potential identified in Navigant's 2012 

potential study for the CPUC. POU annual savings remain flat at 2010 levels.

Medium

For IOUs, savings through 2012 are based on level in approved 2010-2012 energy efficiency plans, 

savings from 2013 to 2014 are based on 100% of levels in the proposed plans, and savings from 

2015 onward are equal to 110% of the maximum achievable potential identified in the Navigant 

potential study. POU annual savings equal 100% of the average annual savings from their 2010-

2020 energy efficiency goals.

High

For the IOUs, savings through 2012 are based on level in approved 2010-2012 energy efficiency

plans, savings from 2013 to 2014 are based on 125% of levels in the proposed plans, and savings 

from 2015 onward are equal to 130% of the maximum achievable potential identified in the 

Navigant potential study. POU annual savings equal 125% of the average annual levels identified in 

their 2010-2020 energy efficiency goals.

CO Low

IOUs maintain savings at levels in approved 2011 DSM plans, equal to 0.9% of retail sales in 

aggregate; Colorado Springs and Fort Collins continue at 2010 savings levels equal to 0.5% of retail 

sales; generic assumptions for all other POUs are made in each scenario.
41

Medium

IOUs meet EEPS targets, which rise to 1.9% of retail sales in 2020; Colorado Springs and Fort 

Collins achieve and maintain savings of roughly 1% of retail sales by 2015, consistent with CSU's 

Energy Vision goal.

High Same as Medium Case

HI

Low Statewide savings exhaust, but do not exceed, the 50% energy efficiency allowance under state RPS.

Medium Same as Low Case

High Same as Low/Medium Cases through 2011, but savings increase from 1.2% of retail sales in 2011 to 

2.0% in 2020.

ID

Low

IOU savings are based on projections from each utility's most-recent IRP (Idaho Power's projected 

savings are well below 2010 program results). POU savings based on achieving their pro-rated 

share of the NPCC 6th Plan conservation targets, with 60% of the savings assumed to come from 

utility customer-funded energy efficiency (and the remainder from new codes/standards); savings 

taper off in the latter years as the retrofit potential is exhausted.

Medium

Idaho Power savings remain flat at level achieved in 2010, and other IOU savings are based on their 

IRP projections. POU savings are same as the Low Case through 2020, except that 75% of the 

conservation target is assumed to come from utility customer-funded energy efficiency, and after 

2020, the savings level remains constant at the 2020 level, rather than tapering off as in the Low 

Case.

High

IOU savings ramp up from 1.1% of retail sales in 2010 to 1.5% in 2020, and remain flat at that level 

thereafter. POU savings through 2020 are based on their pro-rated share of NPCC's 6th Plan 

conservation targets under NPCC's high ramp rate trajectory, and 85% of the savings is assumed to 

come from utility customer-funded energy efficiency; savings after 2020 remain at the 2020 level, 

rather than tapering off as under NPCC's projection.

MT

Low

NorthWestern savings based on the targets identified in its 2009 Electric Supply Resource 

Procurement Plan, which remains flat at approximately 1.0% of retail sales per year. BPA-served 

POU savings based on same assumptions as Idaho POUs.

Medium For NorthWestern, same as Low Case. BPA-served POU savings based on same assumptions as 

Idaho POUs.

High NorthWestern savings ramp up to 1.5% of retail sales per year in 2025. BPA-served POU savings 

based on same assumptions as Idaho POUs.

NM

Low

IOU savings through 2013 based on most recent approved DSM plans, and savings thereafter 

decline to the minimum level necessary for EERS compliance, which requires average annual 

savings of approximately 0.7% over the 2014-2025 period. Savings/spending projections for POUs 

are based on generic assumptions in each scenario.

Medium IOU savings through 2013 based on most recent approved DSM plans, and remain constant at the 

2013 level thereafter, equal to 0.8% of retail sales.

High IOU savings ramp up to 1.5% of retail sales in 2020

NV

Low

IOU savings and spending through 2013 are based on most recent DSM plans, and thereafter decline 

to the maximum energy efficiency allowance under the RPS. POU savings/spending projections are 

based on generic assumptions under each scenario.

Medium IOU savings after 2013 remain flat at 2013 levels, equal to 0.7% of retail sales, which far exceeds 

the energy efficiency allowance under the RPS

High Same as Medium Case, except that savings ramp up to 1.5% of retail sales in 2020

OR

Low

PGE and PacifiCorp savings are based on Energy Trust 2010-2014 Strategic Plan savings projection 

under "current funding" scenario, and remain at the 2014 level thereafter. Idaho Power savings are 

based on most-recent IRP. POU savings based on same assumptions as in Idaho (ID).

Medium

PGE and PacifiCorp savings are based on Energy Trust 2010-2014 Strategic Plan savings projection 

under "IRP-achievable" scenario, and remain at the 2014 level thereafter. Idaho Power savings are 

based on most-recent IRP. POU savings based on same assumptions as in Idaho (ID).

High

Statewide savings through 2020 is based on Oregon's pro-rated share of the NPCC's 6th Plan 

conservation targets, under NPCC's "high ramp rate" trajectory, and 85% of the savings is assumed 

to come from utility customer-funded energy efficiency; savings after 2020 remain at the 2020 level, 

rather than tapering off as under NPCC's projection.

UT

Low IOU (PacifiCorp) savings remain constant at 2010 level of 0.9% of retail sales. POU 

savings/spending in all scenarios are based on generic assumptions.

Medium PacifiCorp savings follow 2011 IRP schedule, which rises to 1.2% of retail sales in 2021, and stays 

flat at that level thereafter

High PacifiCorp savings rise to 1.5% of retail sales in 2020, and stay flat at that level thereafter

WA Low Savings based on achieving WA's pro-rated share of the conservation targets in the NPCC's 6th 

Plan, with 60% of the savings assumed to come from utility customer-funded energy efficiency (and 
42

the remainder from new codes/standards); the savings trajectory tapers off in the latter years as the 

retrofit potential is exhausted.

Medium

Same as the Low Case, except 75% of the conservation target is assumed to come from utility 

customer-funded energy efficiency, and after 2020, the savings level remains constant at the 2020 

level, rather than tapering off as in the Low Case.

High

Savings through 2020 are based on WA's pro-rated share of the conservation targets in the NPCC's 

6th Plan, under NPCC's "high ramp rate" trajectory, and 85% of the savings is assumed to come 

from utility customer-funded energy efficiency (and the remainder from new codes/standards); 

savings after 2020 remain at the 2020 level, rather than tapering off as under NPCC's projection.

WY

Low

PacifiCorp 2009-2013 savings and spending are based on approved DSM plan settlement, and 

savings from 2014 to 2025 are held constant at 2013 level, equal to 0.5% of retail sales, which is 

roughly in line with the savings projection from PacifiCorp's 2011 IRP. For all other utilities, 

spending/savings projections are based on generic assumptions for each scenario.

Medium Same as Low Case

High Same as the Low Case through 2013, but savings thereafter ramp up to 1.0% of retail sales in 2020 

and remain constant at that level thereafter.

Table A - 7. Energy Efficiency Spending Assumed for “Uncommitted” States

Case Increase in Spending as a Percent of Utility Revenue Relative to 2010

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Low 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3% 0.3%

Medium 0.4% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5%

High 0.4% 0.5% 0.5% 0.6% 0.6% 0.7% 0.7% 0.7% 0.8% 0.8% 0.8% 0.8% 0.8% 0.8% 0.8%

A1.3 Cost of Savings Assumptions

Depending on the particular state and scenario, the spending projection may have been estimated 

from projected first-year savings or vice-versa. In either case, first-year savings were translated 

into annual spending (or vice-versa) using an assumed cost of savings. We assume that the 

average cost of savings depends in part on the savings level achieved. To capture this 

relationship, we developed a generic “cost function” that relates the average cost of first-year 

electricity savings to the savings level expressed as a percentage of the utility (or state)’s retail 

sales (see Figure A-2). The y-axis values in the figure are expressed on a normalized 

(dimensionless) basis, with a cost index of 1.00 at a savings level equal to 1.0% of retail sales.

The rationale for this cost function is to reflect the fact that, based on our review of energy 

efficiency program experience, utility costs to acquire savings (on a dollar-per-MWh basis) can 

be somewhat higher when portfolio savings levels are low (i.e., annual savings <0.5% of retail 

sales), due to the effect of fixed program delivery costs and because the utility is implementing 

pilot programs or is ramping up its administrative and delivery infrastructure. There is also 

evidence to suggest that program costs increase at relatively high savings targets (i.e., annual 

savings >1.5% of retail sales) either because rebate levels may be raised in order to achieve 

higher market penetration or because the utility includes more expensive energy efficiency 

measures in its program portfolio.

The cost function was then applied to each state by “scaling” the generic cost function shown in 

Figure A-2 using either state-specific program cost data (if available) or an assumed average cost 

of savings.

33

 33 For example, if data for a given state indicate that average program costs are $200 per first-yr. MWh saved at 

savings equal to 1.0% of retail sales, then the generic cost function would yield an average cost of $250 per first-yr. 

MWh at savings equal to 2.0% of retail sales (i.e., 1.25 times the cost at a savings level equal to 1.0% of retail 

sales).

State-specific cost of savings data (i.e., cost per first-year MWh saved) were used 
43

for 23 states, based on recent program results or recently-approved DSM program plans. For the 

remaining 27 states, a generic cost of savings value was used to scale the cost function. These 

states were first categorized as either a low-cost state or a high-cost state. Low-cost states were 

then assumed to have average program costs equal to $150 per first-year MWh saved at a savings 

level of 1.0% of retail sales, based on data compiled by ACEEE (Sciortino et al. 2011). Highcost states were assumed to have average program costs equal to $300 per first-yr. MWh saved at 

a savings level of 1.0% of retail sales, which is based roughly on average costs currently 

observed among some Northeastern states.

Figure A - 2. Generic Program Cost Function

A2. Natural Gas Energy Efficiency Spending Projections

We developed low, medium, and high projections of spending through 2025 on energy efficiency 

programs funded by customers of natural gas utilities. Given that spending on natural gas 

programs represents a relatively small portion of total (electric plus gas) customer-funded 

spending, we used a simpler and more standardized approach to project future spending, 

compared to electric energy efficiency programs.

A2.1 Revenue Projections

Projections of revenue from retail natural gas sales to residential, commercial, and industrial 

customers (i.e., excluding sales to electric utilities) were developed in a similar manner as the 

baseline projections of revenue from retail electricity sales. Retail sales and retail price 

projections were first developed for each state by applying annual growth rate projections from 

the AEO2012 reference case forecast to actual 2010 retail sales and price data for each state, as 

reported by EIA. Retail gas sales include sales to residential, commercial, industrial, and 

transportation sectors, but exclude sales to the electric power sector. Average annual retail gas 

prices were calculated as the average of EIA’s forecast of prices for the residential, commercial, 

industrial, and transportation sectors, weighted by the quantity of sales to each sector. The 

0.50

0.75

1.00

1.25

1.50

1.75

2.00

0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0%

Program Costs per 1st-Yr. MWh 

Normalized to 1.00 at 1% Savings

Savings as % of Retail Sales
44

natural gas retail sales and retail price projections in AEO2012 are specified at the census-region 

level. Thus, the growth rates in each census region were applied to each state in their respective 

region. Revenue projections were calculated by multiplying projected retail gas prices by 

projected retail gas sales, and were converted to nominal dollars using the AEO2012 reference 

case forecast of the GDP chain-type price index. Unlike the electricity revenue projections, no 

adjustments were made to the natural gas revenue projections to account for differing levels of 

energy efficiency savings across scenarios.

A2.2 Scenario Definitions

For the purpose of developing projections of utility customer funding of gas efficiency programs, 

we first grouped states into three categories: Tier I consists of the 13 states that comprise more 

than 80% of current national funding for gas efficiency programs, Tier II consists of another 15 

states where 2010 spending on gas efficiency programs exceeded $0.50 per capita, and Tier III 

consists of the remaining 23 states. Table A-9 identifies the states in each group.

Table A - 8. Analysis Framework for Natural Gas Energy Efficiency Programs

Tier I CA, CO, IA, IL, IN, MA, MI, MN, NJ, NY, OR, UT, WI

Tier II AR, CT, ID, MD, MO, NH, NM, NV, OH, PA, RI, SD, VT, WA, WY

Tier III AK, AL, AZ, DC, DE, FL, GA, HI, KS, KY, LA, ME, MS, MT, NC, ND, NE, OK, SC, TN, TX, VA, 

WV

Tier I Scenario Definitions

For Tier I states, gas efficiency program spending projections are based on state-specific 

policies, gas DSM program plans, and regulatory decisions that set savings targets for gas 

utilities. Table A-10 describes the specific assumptions underlying the three scenarios in each 

Tier I state. For most Tier I states, the low and medium case spending projections track the most 

recent multi-year gas DSM program plans to their terminal year (typically 2012 to 2014). In the 

low case, we assume that spending on residential gas efficiency programs in most Tier I states 

will decline by 50% to 75% relative to the level in the terminal year of the most recent DSM 

plan, while spending on commercial and industrial (C&I) programs will decline by roughly 20%. 

This decline in spending is due to the combination of sustained low natural gas prices, which 

reduce the cost effectiveness of gas efficiency programs and tightening federal minimum 

efficiency standards for gas furnaces, which reduce the savings for voluntary programs. In the 

medium case, we assume a more modest drop-off in residential program spending, typically to 

50% of the level from the terminal year of the most recent gas DSM Plan, but that C&I program 

spending increases slightly, as program managers shift spending towards markets with greater 

savings opportunities. In both the low and medium scenario, we assume that gas efficiency 

programs for low-income programs, however, remain constant at the level from the last year of 

the DSM plan, as these programs meet broader policy objectives (e.g. equity, reductions in bill 

arrearages), and therefore are less susceptible to the dynamics putting downward pressure on gas 

program spending for the other sectors. Finally, in the high case, we assume that many Tier I
45

states achieve gas savings levels on par with gas EERS targets in a number of states (i.e., 1.0-

1.5% of total utility retail sales).

Table A - 9. Gas Energy Efficiency Program Scenario Descriptions: Tier I States

State Case Scenario Description

CA

Low

Program savings are assumed to track 60% of the total gross market potential excluding 

codes and standards, based on the Navigant (2012) potential study; spending is calculated 

from savings, based on the planned savings and spending in the IOU 2013-2014 program 

plans.

Medium Similar to Low Case, except savings are assumed to track 80% of the total gross market 

potential excluding codes and standards.

High Spending as a percent of revenues remains flat at 2012 levels

CO

Low

Spending tracks most recent gas DSM plan to terminal year. Thereafter, residential program 

spending as a percentage of revenues declines over time by 75% and C/I spending declines 

by 20%, to reflect impact of furnace standards and low gas prices. Low-income program 

spending as a percentage of revenues continues at the same level as in the DSM plan.

Medium

Spending tracks most recent gas DSM plan to terminal year. Thereafter, residential program 

spending as a percentage of revenues declines over time by 50%, while C/I spending 

increases 30%, as funds are shifted across market segments. Low-income program spending 

as a percentage of revenues continues at the same level as in the DSM plan.

High Savings ramps up to 1% of retail sales to non-transportation gas customers

IA

Low

Spending tracks most recent gas DSM plan to terminal year. Thereafter, residential program 

spending as a percentage of revenues declines over time, beginning in 2017, by 75% and C/I 

spending declines by 20%, to reflect impact of furnace standards and low gas prices. Lowincome program spending as a percentage of revenues continues at the same level as in the 

DSM plan.

Medium

Spending tracks most recent gas DSM plan to terminal year. Thereafter, residential program 

spending as a percentage of revenues declines over time by 50%, while C/I spending 

increases 30%, as funds are shifted across market segments. Low-income program spending 

as a percentage of revenues continues at the same level as in the DSM plan.

High Savings ramps up to 1.5% of retail sales to non-transportation gas customers, on par with the 

gas EERS targets in IL and MN

IL

Low See Iowa (IA) Low Case

Medium See Iowa (IA) Medium Case

High Savings ramps up to meet Illinois gas EERS savings targets (1.5% of retail sales to nontransportation gas customers)

IN

Low See Iowa (IA) Low Case

Medium See Iowa (IA) Low Case

High Savings ramps up to 1% of retail sales to non-transportation gas customers

MA

Low

Spending tracks most recent gas DSM plan to terminal year. Thereafter, residential program 

spending as a percentage of revenues declines over time by 50% and C/I spending declines 

by 20%, to reflect impact of furnace standards and low gas prices. Low-income program 

spending as a percentage of revenues continues at the same level as in the DSM plan.

Medium

Spending tracks most recent gas DSM plan to terminal year. Thereafter, residential program 

spending as a percentage of revenues declines over time by 20%, while C/I spending 

increases 30%, as funds are shifted across market segments. Low-income program spending 

as a percentage of revenues continues at the same level as in the DSM plan.

High Savings ramps up to 1.5% of total statewide gas retail sales, a proxy for achievement of all 

cost-effective gas energy efficiency

MI

Low See Iowa (IA) Low Case

Medium See Iowa (IA) Medium Case

High See Iowa (IA) High Case

MN Low See Iowa (IA) Low Case

Medium See Iowa (IA) Medium Case
46

High Savings ramps up to meet Minnesota gas EERS savings targets (1.5% of retail sales to nontransportation gas customers)

NJ

Low Similar to Colorado (CO) Low Case, except total spending is de-rated by 70% to reflect 

historical gap between actual expenditures and planned budgets.

Medium

Similar to Colorado (CO) Medium Case, except total spending is de-rated by 70% to reflect 

historical gap between actual expenditures and planned budgets, and C/I spending as a 

percentage of revenues remains flat, rather than increasing.

High Savings ramps up to 1% of total statewide retail sales

NY

Low Similar to Massachusetts (MA) Low Case, but projections to 2015 are based on 

achievement of New York’s gas EERS targets

Medium Similar to Massachusetts (MA) Medium Case, but projections to 2015 are based on 

achievement of New York’s gas EERS targets

High Similar to New Jersey (NJ) High Case, but projections to 2015 are based on achievement of 

New York’s gas EERS targets

OR

Low See Iowa (IA) Low Case

Medium See Iowa (IA) Medium Case

High See Iowa (IA) High Case

UT

Low See Iowa (IA) Low Case

Medium Similar to Colorado (CO) Medium Case, except residential program spending declines by 

70% rather than 50%, based on information provided by program managers.

High See Iowa (IA) High Case

WI

Low Spending is based on the current legislative cap (1.2% of revenues)

Medium Same as Low Case

High See Iowa (IA) High Case

Tier II Scenario Definitions

The 15 Tier II states have relatively aggressive spending levels on a per capita basis, but small 

populations and therefore small spending levels in absolute terms. Thus, for simplicity, the 

spending projections for these states were developed based on regional benchmark trajectories 

that were developed from the projections for Tier I states in the corresponding region. These 

regional benchmark trajectories were developed by averaging the change, relative to 2010, in 

spending as a percentage of gas distribution utility revenues across Tier I states in each census 

region (see Table A-11). Those growth curves were then applied to the 2010 spending for each 

Tier II state. As an example, in the medium case, spending for the three Tier I states in the 

northeast (MA, NY, and NJ) is projected to increase by, on average, 0.6% of revenues; thus, the 

same 0.6% increase in spending as a percent of revenues was stipulated for the Tier II 

northeastern states in the medium case.

Tier III Scenario Definitions

For states in Tier III that currently have little or no customer-funded gas efficiency program 

activity, we assumed that spending will stay flat as an absolute dollar value in the low scenario. 

In the medium scenario, we project that gas efficiency programs will continue spending at their 

present percentage of retail gas revenues. In the high case, we assume that gas efficiency 

programs will increase program spending to approximately 0.25% of revenues above their 

current levels (e.g., if current gas program spending is equal to 0.5% of revenues, then we 

assume in the high case that spending rises to 0.75% of revenues).
47

Table A - 10. Gas Energy Efficiency Program Spending: Tier II States

Case Increase (Relative to 2010) in Customer-Funded Gas EE Spending as a Percent of Revenues from Retail Gas Sales

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Northeast

Low 0.0% 0.8% 1.3% 1.4% 1.4% 1.4% 1.4% 0.9% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5%

Medium 0.0% 0.8% 1.3% 1.4% 1.4% 1.4% 1.4% 1.1% 1.1% 1.1% 1.2% 1.2% 1.2% 1.2% 1.2% 1.2%

High 0.0% 0.8% 1.3% 1.6% 1.8% 2.0% 2.3% 2.7% 2.9% 3.3% 3.6% 3.4% 3.3% 3.3% 3.2% 3.2%

Midwest 

& South

Low 0.0% 0.2% 0.4% 0.6% 0.6% 0.6% 0.6% 0.3% 0.0% 0.0% 0.0% -0.2% -0.2% -0.2% -0.2% -0.2%

Medium 0.0% 0.2% 0.4% 0.6% 0.6% 0.6% 0.6% 0.6% 0.6% 0.6% 0.4% 0.2% 0.2% 0.2% 0.2% 0.2%

High 0.0% 0.2% 0.4% 0.6% 0.8% 0.8% 1.0% 1.2% 1.3% 1.5% 1.5% 1.4% 1.3% 1.3% 1.3% 1.2%

West

Low 0.0% 0.1% 0.2% 0.1% 0.3% 0.3% 0.3% -0.2% -0.6% -0.6% -0.7% -1.0% -1.0% -1.0% -1.0% -1.0%

Medium 0.0% 0.1% 0.2% 0.1% 0.3% 0.3% 0.3% 0.2% 0.2% 0.2% -0.1% -0.5% -0.5% -0.6% -0.7% -0.7%

High 0.0% 0.1% 0.2% 0.0% 0.4% 0.6% 0.9% 1.1% 1.2% 1.4% 1.5% 1.4% 1.3% 1.2% 1.2% 1.1%
48

Technical Appendix B: State-Level Spending and Savings Projections

The results presented in Section 4 focused on regional and national spending and savings 

projections. This technical appendix provides additional state-level details. Table B - 1 presents

projected electric efficiency program spending by state, Table B - 2 presents projected electric 

efficiency program savings by state, and Table B - 3 presents projected gas efficiency program 

spending by state. Note that the spending projections are presented in terms of nominal dollars, 

as used throughout the report, and the savings projections are presented in terms of first-year 

GWh. Please refer to Technical Appendix A for details on the underlying scenario definitions 

and assumptions used for each state in order to develop these spending and savings projections.
49

 

Table B - 1. Electric Energy Efficiency Program Spending Projections by State ($M, nominal)

State 2010* Low Medium High

2015 2020 2025 2015 2020 2025 2015 2020 2025

AK - 2 3 4 5 5 6 6 9 9

AL 9 23 34 38 51 61 68 60 94 104

AR 9 38 44 48 46 59 65 48 73 85

AZ 88 191 117 136 199 138 160 250 321 361

CA 938 755 721 701 927 878 852 1,203 1,050 1,021

CO 48 62 71 82 105 167 180 107 173 186

CT 108 86 88 89 102 109 123 278 282 301

DC 15 8 17 18 19 20 22 19 24 26

DE 7 0 7 7 7 7 7 12 21 22

FL 165 145 134 160 234 278 325 310 433 727

GA 15 60 73 83 70 93 106 84 143 216

HI 25 66 78 95 66 78 95 62 100 106

IA 59 103 110 119 123 130 140 161 264 288

ID 57 32 40 34 43 51 57 48 71 77

IL 85 233 235 235 314 373 389 666 675 681

IN 5 150 255 267 200 385 395 202 389 399

KS 6 8 13 14 19 21 24 23 34 37

KY 21 45 54 63 75 89 102 93 124 142

LA - 17 28 32 39 45 53 48 72 84

MA 245 200 221 243 568 580 593 613 625 666

MD 74 172 182 193 174 181 192 168 269 292

ME 14 22 24 27 40 42 46 48 50 54

MI 75 167 172 185 167 172 185 205 278 338

MN 107 110 117 129 121 141 153 175 284 296

MO 36 91 87 93 97 184 188 135 322 342

MS 6 16 22 26 34 42 48 39 63 72

MT 17 14 17 17 17 19 21 20 27 33

NC 52 66 113 124 103 116 147 110 202 314

ND 8 2 3 4 5 5 6 6 9 10

NE - 5 8 9 12 13 15 14 21 23

NH 18 20 22 26 30 48 52 41 98 101

NJ 191 129 93 97 184 188 194 211 348 532

NM 18 22 25 27 27 31 36 35 59 66

NV 33 16 18 21 36 41 48 49 97 109

NY 482 552 559 608 778 653 704 778 865 913

OH 70 78 162 175 170 297 451 183 463 484

OK 21 53 59 67 57 111 123 58 121 195

OR 135 107 126 131 158 181 199 152 223 243

PA 98 210 224 245 240 240 240 263 329 405

RI 44 43 46 51 73 74 74 96 97 103

SC 15 75 89 103 89 114 131 109 140 210

SD 0 2 3 4 5 5 6 6 8 9

TN 38 47 58 66 93 121 136 98 172 189

TX 114 119 150 171 163 215 254 246 252 285

UT 48 54 60 70 35 46 51 39 63 71

VA 0 27 34 39 43 63 72 115 130 143

VT 36 44 45 48 44 45 48 64 63 66

WA 218 167 229 192 209 287 317 295 428 466

WI 74 83 92 99 83 126 135 255 264 268

WV - 6 9 10 13 15 17 16 24 27

WY 3 11 12 12 12 13 14 14 23 25

Total 3,948 4,757 5,202 5,536 6,522 7,398 8,062 8,336 10,769 12,222

* Source of 2010 spending data: CEE (2012), with minor modifications
50

Table B - 2. Electric Energy Efficiency Program Savings Projections by State (First-Year GWh)

State 2009* Low Medium High

2015 2020 2025 2015 2020 2025 2015 2020 2025

AK 1 11 16 16 29 28 27 36 46 45

AL 63 121 164 170 288 314 322 337 496 520

AR 60 224 233 236 268 313 318 280 396 421

AZ 571 1,101 761 810 1,164 894 945 1,281 1,430 1,474

CA 2,293 2,497 2,202 1,979 3,067 2,681 2,402 3,670 3,214 2,887

CO 255 327 346 365 546 696 704 556 725 736

CT 250 287 268 248 338 332 342 633 591 577

DC 56 44 90 89 113 111 110 113 133 130

DE 0 0 35 32 40 35 32 73 112 110

FL 365 384 324 343 640 697 747 877 1,166 1,796

GA 54 336 370 388 399 499 517 493 800 1,113

HI 113 176 185 195 176 185 195 172 218 211

IA 410 422 415 410 503 489 480 653 861 864

ID 186 193 218 167 254 274 282 283 351 352

IL 553 1,085 1,005 923 1,465 1,600 1,528 2,494 2,331 2,156

IN 40 885 1,289 1,239 1,183 1,675 1,574 1,191 1,697 1,596

KS 1 42 60 62 103 106 108 126 175 177

KY 65 253 278 294 439 476 501 543 666 699

LA 0 87 129 139 205 220 236 261 377 401

MA 459 563 572 578 1,077 1,008 944 1,105 1,037 1,013

MD 274 688 666 648 698 666 648 673 928 891

ME 94 114 113 117 183 175 171 215 204 202

MI 376 956 936 919 990 936 919 959 1,191 1,279

MN 638 651 635 640 714 766 760 967 1,232 1,178

MO 86 348 355 349 385 755 707 611 1,170 1,086

MS 31 84 111 118 193 220 231 219 341 358

MT 57 75 82 77 88 93 93 101 124 135

NC 52 364 591 591 608 631 733 650 1,095 1,562

ND 3 11 15 16 25 26 27 31 43 44

NE 65 26 37 38 62 64 65 75 105 107

NH 68 60 60 64 90 131 128 123 214 201

NJ 497 211 112 110 311 197 191 374 631 1,018

NM 59 123 125 126 148 156 165 197 282 289

NV 439 89 92 93 211 223 239 287 491 507

NY 950 2,563 2,311 2,299 2,647 2,414 2,449 2,647 2,894 2,936

OH 530 458 875 864 1,007 1,522 1,857 1,084 2,082 1,999

OK 20 174 188 197 198 368 379 208 415 606

OR 292 472 507 484 642 676 681 640 785 782

PA 279 831 815 815 951 872 798 1,042 1,197 1,346

RI 82 107 103 102 149 140 131 172 159 155

SC 46 311 341 362 383 447 470 469 562 760

SD 22 10 15 15 24 25 26 30 42 44

TN 121 256 292 305 552 658 674 581 933 942

TX 751 650 755 786 924 1,118 1,211 1,451 1,364 1,409

UT 177 210 220 232 233 281 286 268 371 381

VA 1 189 214 223 318 454 479 972 1,000 1,003

VT 90 114 110 105 114 110 105 176 164 164

WA 665 722 909 698 903 1,137 1,152 1,231 1,487 1,482

WI 584 435 441 435 435 606 592 1,301 1,220 1,161

WV 0 30 42 44 70 72 76 89 124 128

WY 7 62 62 61 70 68 66 81 122 124

Total 13,147 20,433 21,092 20,613 26,624 28,641 28,823 33,102 39,792 41,561

* Source of 2009 savings data: Sciortino et al. (2011)
51

Table B - 3. Gas Efficiency Program Spending Projections by State ($M, nominal)

State 2010* Low Medium High

2015 2020 2025 2015 2020 2025 2015 2020 2025

AK 0 0 0 0 0 0 0 0 1 1

AL 0 0 0 0 0 0 0 2 4 7

AR 2 11 3 2 11 10 8 14 29 30

AZ 2 2 2 2 2 3 4 3 5 8

CA 201 152 100 118 171 134 157 198 249 315

CO 19 15 10 12 15 17 17 31 74 83

CT 12 31 23 27 31 35 41 39 73 80

DC 0 0 0 0 0 0 0 0 1 2

DE 0 0 0 0 0 0 0 0 1 2

FL 11 11 11 11 12 14 17 13 17 23

GA 0 0 0 0 0 0 0 3 8 14

HI 0 0 0 0 0 0 0 0 0 0

IA 40 51 39 34 51 55 55 66 115 127

ID 2 3 1 1 4 4 1 4 12 13

IL 26 126 86 69 126 127 118 126 235 254

IN 11 18 14 12 18 18 18 18 45 44

KS 0 0 0 0 0 0 0 1 3 6

KY 1 1 1 1 1 1 1 2 4 7

LA 0 0 0 0 0 0 0 4 10 18

MA 72 139 114 136 139 157 186 182 277 308

MD 6 18 8 3 18 18 15 23 45 47

ME 1 1 1 1 1 1 2 1 2 3

MI 41 87 74 74 87 95 99 99 138 149

MN 36 40 33 33 40 48 52 47 63 69

MO 7 20 9 4 20 21 17 26 52 55

MS 0 0 0 0 0 0 0 1 2 4

MT 0 0 0 0 0 0 0 1 1 2

NC 1 1 1 1 1 2 2 3 6 11

ND 0 0 0 0 0 0 0 0 1 1

NE 0 0 0 0 0 0 0 1 2 4

NH 4 15 15 18 15 18 21 17 26 30

NJ 126 101 78 72 101 83 99 156 247 273

NM 2 4 1 1 5 5 1 5 15 16

NV 3 6 1 1 6 7 1 7 21 23

NY 39 158 135 160 158 178 211 158 371 410

OH 32 68 38 24 68 69 61 84 152 156

OK 0 0 0 0 0 0 0 2 6 10

OR 23 40 32 28 40 45 45 41 62 70

PA 13 95 53 63 95 103 122 132 266 287

RI 5 13 10 12 13 15 17 17 31 34

SC 0 0 0 0 0 0 1 1 3 5

SD 1 4 2 1 4 4 3 5 9 9

TN 0 0 0 0 0 0 0 2 4 7

TX 2 2 2 2 2 3 3 10 22 39

UT 36 34 23 16 34 34 20 36 65 72

VA 3 3 3 3 3 4 5 5 9 14

VT 2 4 3 4 4 4 5 4 7 8

WA 29 14 3 3 15 17 3 18 49 53

WI 24 21 25 30 21 25 30 104 122 132

WV 0 0 0 0 0 0 0 1 1 3

WY 0 1 0 1 2 1 1 2 7 8

Total 838 1,313 957 982 1,335 1,376 1,458 1,721 2,968 3,346

* Source of 2010 spending data: CEE (2012), with minor modifications