Demand-Side Energy Efficiency Technical Support Document                                   August 2015

                                   Contents

                                                                           Page List of Figures	v List of Tables	v 1.	Introduction	1 2.	Background	1 2.1	EE Technologies and Practices	2 2.2	Barriers to EE Investment	3 2.3	EE Policies	5 2.3.1	Objectives and Role in Reducing CO2 Emissions from the Power Sector	5 2.3.2	Policy Types	7 3.	History of EE Policies in the United States	9 4.	EE Programs	15 4.1	EE Programs	15 4.1.1	Administrators	16 4.1.2	Policy Drivers	16 4.1.3	Funding Sources	17 4.2	The Demand-Side EE Opportunity	17 4.2.1	Rapid Growth in Demand-Side EE	17 4.2.2	EE Program Impacts	18 <IP_ADDRESS>	Impacts to-date	18 <IP_ADDRESS>	Projected Impacts	22 4.2.3	EE Potential	23 <IP_ADDRESS>	Evaluations of EE Potential	23 <IP_ADDRESS>	Overview of Results	25 4.3	Costs and Cost-Effectiveness of State EE Policies	26 4.3.1	EE Cost-Effectiveness	26 4.3.2	Costs of Saved Energy	28 5.	Other EE Strategies	30 5.1	Building Energy Codes	30 5.1.1	Overview	30 5.1.2	Authority / Obligated Parties	31 5.1.3	Building Code Regulations Over Time	31 5.1.4	Remaining Market Potential	33 5.2	State Appliance Standards	34 5.2.1	Overview	34 5.2.2	Authority / Obligated Parties	34 5.2.3	Appliance Standards over Time	35 5.2.4	Remaining Market Potential	36 5.3	Energy Service Performance Contracting	37 5.3.1	Overview	37 5.3.2	History of ESPC Programs and the ESCO Business Model	38 5.3.3	Remaining Market Potential	39 5.4	Volt/VAR Optimization	40 5.4.1	Overview	40 5.4.2	History of VVO Programs	42 5.4.3	VVO Market Potential	43 6.	Utility Regulatory Models for Supporting Demand-Side EE	43 7.	Energy Efficiency Certificates	46 8.	Demand-Side EE Plan Scenario: Magnitude and Timing of Savings	49 8.1	Approach	49 8.2	Inputs	50 8.2.1	Step 1: Determine Current Level of Demand-Side EE Performance	50 8.2.2	Step 2: Determine EE Plan Scenario Level of Performance	51 8.2.3	Step 3: Determine Start Year for EE Plan Scenario	54 8.2.4	Step 4: Determine Start Year Level of Performance	54 8.2.5	Step 5: Determine Pace of Improvement from Start Year to EE Plan Scenario Level of Performance	54 8.2.6	Step 6: Determine Average Portfolio Measure Life and Distribution of Measure Lives	55 8.2.7	Step 7: Determine Sustainability of EE Plan Scenario Level of Performance	57 8.2.8	Summary of the Demand-Side EE Plan Scenario Construction	58 8.3	Calculations	59 8.3.1	Step 1: Determine Annual Business as Usual (BAU) Sales	59 8.3.2	Step 2: Determine Annual Incremental EE Savings as a Percentage of Sales	60 8.3.3	Step 3: Determine Annual Incremental EE Savings (GWh)	60 8.3.4	Step 4: Determine Annual Expiring EE Savings (GWh)	61 8.3.5	Step 5: Determine Net Cumulative EE Savings (GWh)	61 8.3.6	Step 6: Determine Sales after Net EE (GWh)	61 8.3.7	Step 7: Determine Net Cumulative EE Savings as a Percentage of BAU Sales	62 8.3.8	Summary of Calculation Formulas and Results by Step for South Carolina	62 8.4	Results	63 8.4.1	Summary of Results	63 8.4.2	Results in Context	65 9.	Demand-Side EE Plan Scenario: Assessment of Costs	66 9.1	Approach	66 9.2	Inputs	67 9.2.1	Step 1: Determine Incremental Electricity Savings	67 9.2.2	Step 2: Determine First-Year Program Costs and Cost Factors	67 9.2.3	Step 3: Determine the Ratio of Program to Participant Costs	69 9.2.4	Summary of Inputs for Demand-Side EE Cost Analysis	70 9.3	Calculations	71 9.3.1	Step 1: Calculate Annual First-Year Costs	71 9.3.2	Step 2: Calculate Levelized Cost of Saved Energy	72 9.3.3	Step 3: Calculate Annualized Costs	73 9.3.4	Summary of General Formulas and Results by Step for South Carolina	73 9.4	Results	74 9.4.1	Summary of National Results	74 9.4.2	Results in Context	75 9.4.3	Costs per Tonne CO2 Reduced	75 10.	Analysis Considerations	76 10.1	State EE Policies in the Baseline Electricity Demand	76 10.2	Energy Information Administration Form EIA-861 as Data Source	77 References	86

                                  Appendices

Appendix 1: Summary of Recent Energy Efficiency Potential Studies (2009-2014)	81 Appendix 2: Incremental Electricity Savings Pace of Improvement Analysis	82 Appendix 3: Demand-Side Energy Efficiency Plan Scenario: Data, Calculations and Results	85

                                List of Figures                                                                            Page Figure 1. EE Program Portfolio	16 Figure 2. Residential Energy Building Code Adoption (2005 to 2014)	33 Figure 3. Remaining Market Potential for ESCOs	40 Figure 4. Hypothetical Voltage Profiles with and without VVO Technologies	42 Figure 5. The Four-Tier Distribution of Demand-Side EE Program Measure Lifetime	56

                                List of Tables                                                                            Page Table 1. Relative Opportunities Provided by Key EE Programs and Building Codes	9 Table 2. U.S. Electric Utility EE Program Funding (2006-2013)	18 Table 3. U.S. State Adoption of EE Resource Standards	18 Table 4. Aggregate Electricity Savings by State, Tribal Area and Territory	20 Table 5. Summary of Impacts: Scenarios of Future Utility  Customer-Funded Electric EE Programs	23 Table 6. Summary of EE Potential Studies (2009 to 2014)	26 Table 7. Estimated Energy Savings Potential of State Appliance Standards	36 Table 8. Summary of State Regulatory Frameworks: December 2014	44 Table 9. International Examples of Trading Energy Savings	48 Table 10. 2013 State Levels of Incremental Annual Savings	52 Table 11. 2013 Incremental Annual Savings  -  Investor-Owned Utilities	52 Table 12. 2013 Incremental Annual Savings  -  Cooperative-Owned Utilities	52 Table 13. 2013 Incremental Annual Savings  -  Municipal-Owned Utilities	53 Table 14. Levels of Incremental Savings Required by State EERS	53 Table 15. NPCC Achievable EE Potential and Achieved Incremental Savings (1998-2010)	58 Table 16. Summary of Demand-Side EE Plan Scenario Inputs	58 Table 17. BAU Sales for South Carolina	60 Table 18. Annual Incremental EE Savings as a Percentage of Sales for South Carolina	60 Table 19. Annual Incremental EE Savings (GWh) for South Carolina	60 Table 20. Expiring EE Savings for South Carolina	61 Table 21. Net Cumulative EE Savings for South Carolina	61 Table 22. Sales after Net EE Savings for South Carolina	62 Table 23. Net Cumulative EE Savings as a Percentage of BAU Sales for South Carolina	62 Table 24. Summary of Results by Step for South Carolina	62 Table 25. Demand-Side EE Plan Scenario: Magnitude and  Timing of Net Cumulative Savings	63 Table 26. Average Annual Savings Rates of Demand-Side EE Plan Scenario	65 Table 27. Summary of EE Cost Analysis Inputs	70 Table 28. Calculation of Annual First-Year Costs for South Carolina	71 Table 29. Levelized Cost of Saved Energy for South Carolina (at 3% discount rate)	72 Table 30. Annualized Costs for South Carolina	73 Table 31. Summary of Results by Step for South Carolina.	73 Table 32. First-Year Demand-Side EE Costs (billions 2011$) (Continental U.S.)	74 Table 33. Annualized Demand-Side EE Costs (3% discount rate, billions 2011$) (Continental U.S.)	74 Table 34. Levelized Cost of Saved Energy (3% discount rate, 2011$/MWh) (Continental U.S.)	74 Table 35. Annual Growth Rates of Demand-Side EE Program Spending  -  Historic and Demand-Side EE Plan Scenario	75

Introduction This chapter provides information on demand-side energy efficiency (EE) as a measure for reducing carbon dioxide (CO2) emissions from fossil fuel-fired electric generating units (EGUs). Specifically, this chapter supports the discussion of demand-side EE as a non-BSER compliance measure in section V, "The Best System of Emission Reduction (BSER) and Associated Building Blocks," and section VIII, "State Plans," of the preamble. In addition, support is provided for the magnitude, timing, and cost of demand-side EE measures included in the illustrative demand-side EE plan scenario developed as a basis for the Regulatory Impact Analysis (RIA) and related discussion in section X, "Impacts of this Action," of the preamble. The chapter is organized as follows: 2. Background 3. History of EE Policies in the United States 4. EE Programs 5. Other EE Strategies 6. Utility Business Models 7. Experience with EE Certificates 8. Demand-Side EE Plan Scenario: Magnitude and Timing of Savings 9. Demand-Side EE Plan Scenario: Assessment of Costs 10. Analysis Considerations Sections 2 through 7 provide support for both the preamble sections cited above as well as background for the illustrative demand-side EE plan scenario presented in sections 8 and 9. Sections 8 and 9 provide details on the approach, inputs, calculations, and results for the magnitude and timing of savings and the assessment of associated costs for the demand-side EE plan scenario. Lastly, section 10 discusses considerations relevant to sections 8 and 9. Background Demand-side EE policies and programmatic efforts have existed for decades and are now used in all 50 states. These strategies are intended to help states achieve energy savings goals, reduce the environmental impacts (including CO2 emissions) of meeting energy service needs, save energy and money for consumers, and provide a significant resource for meeting power system capacity requirements (EPA 2015). EE policies currently in place are generally considered by states to be cost-effective strategies for contributing to these policy objectives. Moreover, states  -  through their utilities, primarily  -  have been rapidly increasing their funding of EE programs in recent years, more than tripling budgets in the five years from 2006 to 2011, from $1.6 billion to $5.9 billion (ACEEE 2014c). In 2012, the utility-reported cumulative impacts of these programs represented a 3.7% reduction in national electricity demand (EIA 2012a). And, EE spending is projected to continue to grow at a substantial rate. A recent study by Lawrence Berkeley National Laboratory (LBNL) projects EE program spending to reach $8.1 billion to $12.2 billion ("Medium Case" and "High Case," respectively) in 2025 (Barbose et al. 2013).  EE Technologies and Practices EE is using less energy to provide the same or greater level of service. Demand-side EE refers to an extensive array of technologies, practices and measures that are applied throughout all sectors of the economy to reduce energy demand while providing the same, or better, level and quality of service. Utilities employ an array of strategies in implementing EE programs, these include financial incentives such as rebates and loans, technical services such as audits and retrofits, and educational campaigns about the benefits of EE improvements. The purpose of these EE programs is to induce EE investments and practices that would not otherwise occur due to market failures and behavioral impediments. In the residential sector, examples of EE activities include the purchase of more efficient products and equipment (e.g., ENERGY STAR labeled), the upgrading of insulation in attics and walls, sealing of air leaks, and undertaking home energy audits leading to customized whole home retrofits. Opportunities for cost-effective EE in commercial buildings can include optimization of heating, ventilation, and air conditioning (HVAC) systems, upgrades of windows, and use of more efficient office equipment at replacement. In the industrial sector key EE strategies include motor upgrades and maintenance programs, recovery of waste heat streams, and optimization of processes through modern instrumentation and controls systems. The opportunity presented for economic investment in EE is dynamic, growing over time as technologies and practices advance, as populations grow, and as investment occurs in the construction of new homes, buildings, and industrial facilities. After decades of experience implementing policies to accelerate investment in cost-effective EE, states are finding renewed opportunities as they develop more sophisticated and effective strategies, evolving from a focus on individual end-uses and products to whole-building and systems-based strategies that account for the interactions between the many energy end-uses in buildings and industry (ACEEE 2013). As will be discussed, the experience in the U.S. has been that, on balance, a persistent and large potential for achievable and cost-effective EE is expected to remain even as the impact of past and ongoing efforts have accumulated. Barriers to EE Investment Despite the persistent and large potential for electricity savings through investment in EE technologies and practices, market failures, as well as non-market barriers and behavioral impediments, limit the realization of the many benefits of these investments. Several market failures that lead to inefficiencies in the investment in energy efficiency are widely recognized by analysts and practitioners, and are discussed extensively in the literature (Levine et al. 1995; Gillingham et al. 2009;Gerarden et al. 2015). In the presence of market failures, users of electricity, or those making EE investments, face prices or incentives that prevent them from weighing the full social benefits and costs of their investments and thus under-invest in approaches to reduce electricity consumption. The behavioral impediments provide another explanation for why individuals do not always make EE investments that are seemingly in their own best interest. Some of the most common examples of these market failures include:  Pollution externalities. Fossil energy consumption is associated with negative externalities, such as emissions of CO2, SO2, and NOx that cause human health and environmental damages. Energy prices that do not correctly reflect the externalities associated with energy use would lead to investments in EE below the socially optimal levels.  Imperfect information. Energy users often lack accurate information about energy savings and other attributes of energy efficient products or practices to understand the costs and benefits of EE investments.  Split incentives (or the "principal-agent problem"). Incentives of individuals who make EE investment decisions are not always aligned with incentives of those who use and pay for energy. Examples include misalignment between landlords and tenants, between builders and homeowners, and within organizations and institutions (DeCanio 1998; McKinsey 2007). Credit constraints. Limited access to credit may prevent some consumers, especially low-income consumers, from making cost-effective EE improvement with higher upfront cost.  Under-provision of research and development (R&D). Because of the public good nature of knowledge, firms involved in technology development may be less willing to invest in R&D, leading to sub-optimal levels of EE investments from a social perspective (Jaffe et al. 2003). Supply market imperfections. Markets for energy efficient products are often incomplete and fragmented, leading to underinvestment in innovation and limited EE supplied by the manufacturers. In addition, supply chain fragmentation may also add complexity to the purchase and installation of otherwise economically rational investments, thereby slowing the adoption of EE technologies (Fischer 2005). Behavioral impediments. Behavioral economics and psychology have identified potential behavioral phenomena that lead to consumers to deviate from the standard theory of welfare maximizing in consumption and other decisions, including EE investments (Gillingham and Palmer 2014). Other factors, such as hidden costs, risk and uncertainty experienced by both consumers and suppliers of energy efficient products, and heterogeneity among consumers, may also influence EE investment decisions. Examples of such barriers include: Risk and uncertainty. Adopting an unfamiliar, typically more expensive EE technology can be an uncertain undertaking given the lack of credible information on product performance and future energy prices, and the irreversibility of the investment. Imperfect or asymmetric information can exacerbate the perceived risk of EE investments and help explain why consumers and firms do not always invest in EE measures. Suppliers also face risk and uncertainty, without perfect information of consumer preferences for EE. In the presence of risk and uncertainties, consumers and suppliers alike will invest less in EE.  Transaction costs. Consumers face transaction costs in searching, assessing and acquiring energy efficient technologies and services. It can be time-consuming and difficult for consumers to estimate lifetime operating costs of a product. The complexity of the search process may put more efficient products at a disadvantage relative to better-known less-efficient products with, sometimes, lower upfront costs.  Capital market barriers. Consumers sometimes face higher interest rates to finance EE investments compared to other investments. Lenders can be reluctant to invest in EE loan portfolios in part because EE loans may lack standardization and financial markets have difficulty ascertaining the likely payoff from such investments. EE policies and programs can play an important role in correcting market failures and addressing the barriers to the investment and adoption of socially beneficial EE opportunities. Examples of effective EE policies and programs include public funding of R&D, information programs (such as energy labeling, the ENERGY STAR program, and consumer education), rebates for high-efficiency products, product energy performance standards, financing and loan programs, and technical assistance.  EE Policies Objectives and Role in Reducing CO2 Emissions from the Power Sector EE policies are implemented by states to meet a number of closely related policy goals, including:  Reducing costs to electricity customers, Providing a significant resource for meeting power system capacity needs, Meeting energy savings goals, Stimulating local economic development and new jobs,  Reducing the environmental impacts of meeting electricity service needs, and Improving the health of lower-income households (EPA and DOE 2006; EPA 2015). EE policies currently in place are considered by states to be cost-effective strategies for contributing to each of these policy objectives (EPA and DOE 2006). While each of these objectives, and others, contribute to the motivation of policymakers and utilities to pursue EE policies and programs, reducing energy costs to consumers over the long term is a primary purpose in pursuing these policies. In addition, EE policies are central to meeting state objectives for reducing CO2 emissions from the power sector. EE policies are a leading tool for achieving CO2 reductions from power plants, accounting for 35% to 70% of reductions of sector emissions in ten states with statutory requirements for greenhouse gas reductions (EPA 2015). Many evaluations of the economic potential for carbon dioxide reductions from the United States' power sector identify demand-side EE as the lowest cost strategy (typically, as noted above, with positive net present value) as well as the strategy having the greatest reduction potential.  For example, McKinsey found that EE accounted for more than 60% of their mid-range potential for greenhouse gas reductions from the U.S. power sector and that it was available at positive net present value if "persistent barriers to market efficiency" could be addressed (McKinsey 2007). Similarly, economy-wide studies of climate mitigation scenarios confirm that EE can play a critical role in reducing the costs and enhancing the flexibility of meeting long-term climate stabilization targets (Clarke et al. 2014; Kriegler et al. 2014). An analysis by the International Energy Agency (IEA) suggested that in order to stabilize the carbon concentration in the atmosphere at 450 ppm, as much as 44% of the estimated global abatement potential in 2035 derives from greater EE in the world economy (IEA 2012b). Several recent Energy Modeling Forum (EMF) studies have investigated the role of technology in achieving climate policy objectives in the U.S. ("EMF 24" and "EMF 25" studies) and globally ("EMF 27" study). These studies concluded that compared to business-as-usual EE, improvements in EE in various economic sectors would slow the increases of GHG emissions in the short run, substantially reduce the costs of GHG mitigation (on average, by about 50%), and ease the technology transformation pathways to achieve long-term carbon reduction goals (Kriegler et al. 2014; Kyle et al. 2011). Several economic studies (including EMF25 studies) examined the role of EE policies (such as EE standards and subsidies) in relation to other climate policy instruments (such as carbon taxes). These studies found that when EE policies address market failures, they are welfare improving and can complement climate policy (Comstock and Boedecker 2011; Fischer 2005; RFF 2010). In addition, EE policies are recognized to be an appropriate response to demonstrated market failures and behavioral impediments, particularly in contexts where these failures have broader societal implications such as environmental externalities (Gillingham et al. 2009). In addition to providing cost-effective opportunities for reducing GHG emissions, EE is recognized to provide other co-benefits, including air quality and public health benefits, waste reduction from energy generation, energy security, energy system reliability, community economic and social development, and consumer amenities (RAP 2012). EE investments and policies that apply to industry have been found to spur productivity growth, technology learning and innovation (Boyd and Pang 2000; Worrell et al. 2003). Recently, more attention has been paid to developing methods for recognizing these co-benefits and integrating them into the cost-benefit analysis framework used by state utility commissions and administrators of EE programs. These co-benefits have not been fully accounted for in the EPA analysis. Policy Types EE policies come in many forms. The most prominent and impactful EE policies in most states include those that drive development and funding of EE programs,  and building energy codes. Other policies that are leading to significant impacts in some states include state appliance and equipment standards, "lead by example" strategies targeting energy use in state operations through energy services performance contracting, and "volt-VAR optimization." See section 5 for further description of these policies, their history, and potential for achieving significant electricity savings. Comparing the relative impact (potential or achieved) of the different policy types is challenging, particularly to do so comprehensively, across all states, and at the national level. EE programs are the only state EE approach that has comprehensive and detailed reporting of impacts, costs, and other characteristics from all 50 states. This information is generally based upon measurement and verification studies submitted annually, most commonly to state utility commissions, and reported to the Energy Information Administration (EIA) for all program administrator types (including all utility types, third-parties, and government agencies). EE program data reported to EIA includes: incremental savings (also referred to as "first-year" savings), cumulative savings, peak demand savings, program costs broken down by component, and composition by end-use sector (residential, commercial, industrial). As of 2013 EIA ended their collection of cumulative savings data. In 2013, utilities and other program administrators in all 50 states and the District of Columbia states reported savings from EE programs to EIA through form EIA-861. At a national level, the EPA is not aware of a comprehensive dataset reported by states of the achieved impacts of strategies other than those that lead to investment in EE programs. However, state and regional-level information does exist. For example, the Northwest Power and Conservation Council (NPCC) has been compiling the impacts of EE policies (including utility and third-party EE programs, state building energy codes, and federal appliance standards) across their member states (ID, MT, OR, WA) for more than three decades. For the past decade, EE programs have accounted for more than 75% of the cumulative energy savings from state EE policies for NPCC, with building energy codes accounting for the remaining savings (NPCC 2010).  Another representation of the relative opportunity provided by different state EE strategies is presented by evaluations of EE achievable potential or projections of the impacts of EE policies. The results from two recent evaluations at a national level are presented in Table 1. EE programs account for 77% and 82% of achievable savings in studies by ACEEE and Georgia Tech, respectively (ACEEE 2014a; Wang and Brown 2013). These studies indicate that the substantial majority of potential savings from state EE efforts are available through EE programs, and that state and local building energy codes can make a significant additional contribution. Massachusetts provides a state example of the impacts of EE programs relative to other state EE policies. The Massachusetts Global Warming Solutions Act of 2008 established statewide limits on greenhouse gas (GHG) emissions of 25 percent below 1990 levels by 2020. To achieve this target, Massachusetts is relying upon an integrated portfolio of clean energy policies. State EE policies are expected to provide the largest contribution to meeting the 25 percent target with utility-sponsored EE programs and state building energy codes accounting for 76% and 17%, respectively, of those policies (Massachusetts EOEEA 2010). In their 2013 progress report, Massachusetts indicates that they are generally on track for meeting or exceeding these projections (Massachusetts EOEEA 2013). Table 1. Relative Opportunities Provided by Key EE Programs and Building Codes  Study Year  EE Programs Building Codes Other ACEEE 2030 77% 13% 10% Georgia Tech 2035 82% 18% 0% Source: ACEEE 2014a, and Wang and Brown 2013 The next section reviews the lengthy history of EE policies in the U.S. In the following section, the focus returns to the EE programs highlighted here for an in-depth review of this important strategy.  History of EE Policies in the United States Demand-side EE has been repeatedly supported through federal policies and market innovations over the past four decades, in recognition of its multiple benefits, including increased energy security, reduced emissions from the power sector, lower customer energy bills, enhanced economic development and job creation, and improved reliability and resiliency of the electricity system. Following the 1973 Organization of Petroleum Exporting Countries (OPEC) oil embargo, the Nixon administrated established the Federal Energy Administration, imposed oil price regulations, and created Project Independence to put the U.S. back on the path toward improved energy security.  The 94[th] Congress took the first major U.S. legislative action on energy through the 1975 Energy Policy and Conservation Act (EPCA). Among other provisions, EPCA authorized the creation of vehicle fuel economy standards, and labeling requirements and efficiency standards for major household appliances (Congress 1975). Also in 1975, the American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE) developed the first national model building energy code, 90-75 "Energy Conservation in New Building Design," for residential and commercial buildings (BCAP n.d.). Continuing this trend of energy policy initiatives, Congress passed the Energy Conservation and Production Act in 1976, which authorized the creation of mandatory national building energy performance standards (BEPS). BEPS, which were repealed in the 1980s, provided loan guarantees for saving energy in public and commercial buildings, authorized grants to states for low-income weatherization and state energy conservation programs, and encouraged the development of electric utility rate structures designed to save energy. Federal energy efficiency policy action continued during the Carter administration. President Carter's 1977 National Energy Plan included energy efficiency as "the quickest, cheapest, and most practical source of energy In the same year President Carter also issued the first executive order on energy efficiency, Energy Policy and Conservation E.O. 12003 requiring federal agencies to develop energy conservation plans (Woolley and Peters n.d.).  Other policy actions in 1977 included the creation of the U.S. Department of Energy, thereby consolidating multiple federal agencies and programs, including many that support energy efficiency, into one cabinet-level department.    In 1978, partly in response to the Administration's new energy plan, Congress enacted the National Energy Act, including the National Energy Conservation Policy Act (NECPA), which made EPCA's provisions for federal efficiency standards mandatory and pre-emptive of state law; established the Residential Conservation Service (RCS), which required utilities to provide home energy audits; and authorized the Institutional Conservation Program (ICP), a grant program for schools and hospitals. NECPA also provides the core authority for the federal government's energy management goals and requirements, which have been updated and amended since 1978 (Congress 1978a). Congress also passed the Public Utility Regulatory Policies Act (PURPA) in 1978 which, among other provisions, introduced competition into generation markets, and required state utility commissions to consider ratemaking practices that encourage energy efficiency (Congress 1978b). As state commissions pursued PURPA-related requirements as well as their own related policy interests, integrated resource planning became more widely used, and the concept of demand-side management (DSM) emerged, in which utilities implement programs to influence customer loads through energy efficiency and other demand-side initiatives (RAP 2011). The energy service company (ESCO) business model also emerged during the 1970s and 1980s. Leaders in the Federal Energy Administration, such as Roger Sant, defined the term "energy services" in the 1970s as the services people want from energy, such as lighting and comfort, and distinct from energy commodities such as fuels and electricity. This concept gave rise to the energy services business, in which ESCOs could reduce energy service costs through energy efficiency. The ESCO industry's growth was supported by utilities paying ESCOs for services such as utility-supported energy audits, and by helping federal agencies implementing federal energy management goals (NAESCO 2011). ESCOs also succeeded in contracting with state and local and institutional customers, whose limited ability to finance energy improvements matched up well with ESCOs' ability to bring private capital to energy improvement projects.  Federal policy support for energy efficiency declined dramatically in the 1980s under the Reagan Administration as energy supplies improved, prices stabilized, and a less favorable climate for federal regulation emerged. The BEPS and RCS programs were repealed, and a "no-standard" standard was issued under NECPA appliance standards authority.  Some states acted to fill these policy vacuums, enacting their own building codes, appliance standards, and utility programs.  Appliance manufacturers, concerned about the proliferation of multiple, different state standards, supported a compromised effort that resulted in the 1987 National Appliance Energy Conservation Act (NAECA) (Congress 1987). NAECA, which was further amended in 1988, established the first national home appliance efficiency standards by amending NECPA. During the 1980s, state and local residential and commercial building energy codes were also adopted to achieve greater energy savings in new construction (BCAP n.d.). As integrated resource planning and DSM practices continued to spread in the 1980s, and electric utilities began to offer customers DSM programs under formal regulatory processes, including programs to incentivize more efficient technologies and practices.  These DSM programs sometimes resembled utility conservation programs launched in the 1970s, but signified a larger shift to integrate energy efficiency into broader utility planning and operations (ACEEE 2012b).  The rapid growth of DSM in the 1980s was the result of the 1970s' increased energy prices, energy security concerns, and the environmental consequences of electricity generation. Rising power plant capital and fuel costs resulted in rate increases, rising customer dissatisfaction, and new requirements for utilities to pursue IRP to manage electricity demand, supply and risk (LBNL 1996). By the end of the decade, 41 states had made some progress towards implementing a rule to require integrated resource planning by electric utilities (Synapse 2011). Utilities also played a key role in supporting ESCO projects into the 1990s by providing incentives that offset energy efficiency project costs, as integrated resource plans found that investments in energy efficiency were lower-cost alternative to new power plants. The 1990s began with the Clean Air Act Amendments and the Pollution Prevention Act of 1990, each of which in their own ways recognized the role energy efficiency can play in protecting human health and the environment. The Clean Air Act amendments provided the authority to use demand-side energy efficiency as a compliance option that gives utilities flexibility to obtain needed sulfur dioxide emission reductions through programs that encourage customers to conserve energy. In 1992, EPA introduced the ENERGY STAR label for office products which manufacturers voluntarily design to perform at superior levels of energy savings. President Clinton signed Executive Order 12845 in 1993 requiring federal agencies to purchase ENERGY STAR qualified products. The Pollution Prevention Act gave EPA new authority to reduce emissions via voluntary and other approaches that reduce pollution sources. The Energy Policy Act (EPAct) of 1992 also advanced energy efficiency through a broad suite of policies, including federal appliance and equipment efficiency standards, requirements for states and the Department of Energy on model building codes, new requirements for federal energy management, new provisions on least-cost planning for federal electric utilities, and new research and development authorizations. EPAct 1992 also included provisions to encourage states to adopt policies to support energy savings through electric utility regulatory reforms (Congress 1992).  In 1996, DOE and EPA signed a joint Memorandum of Understanding to cooperate in delivering the growing suite of ENERGY STAR programs, increasing the number of products and markets covered and leveraging expertise and resources across the federal government. During the early 1990s, electric utility DSM programs grew rapidly, with energy savings exceeding 50 billion kilowatt-hours (kWh) and utility spending at $2.7 billion in 1994 (ACEEE 2000). About 95 percent of the reported energy savings, though only slightly over half of the spending, was attributed to programs reported as targeting energy efficiency (ACEEE 2000). These utility programs accelerated the commercialization of advanced energy efficiency technologies, often by partnering with federal energy efficiency programs like ENERGY STAR (ENERGY STAR 2012a, 2012b). By the late 1990s, funding for utility-sponsored energy efficiency programs fell to less than one-third of its 1994 peak, as about half of the states from a wave of electricity restructuring policies, accompanied by  increased political and regulatory pressures to hold down electricity prices (EPA and DOE 2006). Some restructured electric utilities shifted their focus away from regulated DSM programs to unregulated power marketing and ESCO businesses to deliver energy sales and services directly to customers. However, the business model for these market-based ESCOs limited their ability to reach all but the largest industrial, commercial and institutional customers. Recognizing the limits of private-market delivery of EE, and seeking to preserve the benefits of EE programs, as the more states restructured their electricity markets in the 1990s, some 20 states adopted public benefit funds (PBFs) to ensure continuation of ratepayer-funded programs. Several states and local governments also expanded the authorized use of ESCO services in public facilities via lead-by-example policies. Following the year 2000, energy efficiency policies and programs gained increased attention and, supported by decades of implementation experience, began to be widely recognized as a legitimate, measureable, and low-cost option to serve the nation's energy and environmental goals. Congress displayed a strong commitment to energy efficiency in the Energy Policy Act (EPAct) of 2005, which included sweeping energy efficiency provisions: it authorized $250 million over five years to provide energy efficiency appliance rebates, $1.8 billion over three years for weatherization services, included direct enactment of federal efficiency standards, and authorized a national consumer education campaign on energy efficiency (Congress 2005).  At the same time, however, the ESCO market declined due to an authorization lapse for the federal Energy Savings Performance Contracting (ESPC) program and loss of market confidence for industrial financing mechanisms (NAESCO 2011). This trend was soon reversed as ESCOs increased focus on state and local public buildings and innovated in order to provide customers new technologies and financial models. Eventual resolution of the ESPC authorization program, and executive orders by both President Bush and President Obama have also required more aggressive energy savings in federal facilities (White House 2007, 2009, 2015). By the mid-2000s, the electric utility and regional electricity markets also solidified the validity of rate-payer funded energy efficiency programs as system resources. In 2006, the National Action Plan for Energy Efficiency Leadership Group of more than 60 leading gas and electric utilities, state agencies, energy consumers, energy service providers, environmental groups, and energy efficiency organizations released five policy recommendations recognizing energy efficiency as a high-priority energy resource. States, utilities, and key stakeholders across 49 states joined in making aggressive commitments to energy efficiency and endorsing the Action Plan recommendations (EPA and DOE 2006). In the years following the Action Plan's efforts, about half the states enacted Energy Efficiency Resource Standards (EERS), which are long-term, quantified energy savings targets designed to drive ratepayer-funded program plans. These policy drivers lead to the evaluation, planning, and adoption of EE programs and associated budgets, which are supported through different funding mechanisms. Funding for utility electricity energy efficiency programs has in turn increased rapidly, from $1.6 billion in 2006 to $6.3 billion in 2013 (ACEEE 2014c). At the regional level, the wholesale electricity market operator in New England began to allow energy efficiency to participate in regional capacity markets as part of a 2006 settlement agreement with their regulator, the Federal Energy Regulatory Commission (FERC). Since 2009, energy efficiency providers have been compensated for its measureable contribution to meeting New England's regional capacity needs, helping to ensure sufficient electricity will be available in the future to reliably meet demand across the region. PJM, the wholesale electricity market operator across 13 states around the Mid-Atlantic region, also integrated energy efficiency into this capacity market rules in 2009 (Booz Allen 2012). In 2007, the Energy Independence and Security Act (EISA) passed due to growing concerns over both energy prices and climate change. EISA included several new, and strengthened existing, appliance and equipment standards including a major incandescent lamp efficiency standard, authorized industrial energy efficiency programs, and included a provision for states to consider adopting policies to support greater energy efficiency. EISA also enacted the federal agency savings goals of President Bush's 2007 Executive Order 13423, Strengthening Federal Environmental, Energy and Transportation Management, which required even more aggressive building energy savings than previous Executive Orders.  The American Recovery and Reinvestment Act of 2009 (ARRA 2009) recognized energy efficiency for its economic benefits, including job creation, bill savings and economic development. ARRA 2009 allocated DOE around $16 billion for energy efficiency programs, including appliance rebates, grants to local governments, state energy programs, weatherization assistance, and smart grid grants (DOE 2012c). These investments brought results: for example, ARRA's weatherization program helped more than 650,000 low-income families nationwide, exceeding the original target of 600,000 homes. These retrofits improved the energy efficiency of the homes, saving families an average of $437 a year on their energy bills (DOE 2012c). EE Programs EE Programs Portfolios of EE programs are comprised of numerous measures and measure types that are applied across all sectors of electricity end-users. Figure 1 illustrates the multi-level composition and breadth of EE program portfolios (LBNL 2013b). The diversity represented by a typical portfolio of EE programs implemented by a utility (or other program administrator) is an important characteristic relevant to analysis of EE policies. Every detailed program type (as illustrated in the lower half of the figure) represents a unique set of characteristics including costs of energy saved, ratio of program to participant costs, investment life, scale, M&V approach, etc. Figure 1. EE Program Portfolio

Source:  LBNL 2013b Administrators EE programs are administered by a variety of entities ("program administrators") including utilities of all ownership types (investor-owned, municipals, and cooperatives), non-profit and for-profit third-parties (e.g., Vermont Energy Investment Corporation), and state and local government agencies (e.g., NYSERDA). Most EE programs (including all investor-owned utilities which account for more than 75% of reported savings) are overseen by state utility commissions, which review and approve program plans, projected impacts, and associated budgets; and establish annual reporting and M&V requirements (EIA 2013). Policy Drivers  EE programs result from a number of different policy approaches or "drivers." These include EE resource standards (EERS) (26 states), system benefit charges (14 states), integrated resource planning (IRP) requirements (34 states), demand-side management plan or multi-year EE budget (28 states), and statutory requirement to acquire "all-cost-effective EE" (6 states) (ACEEE 2014c; Barbose et al. 2013). EERS is a more recently developed strategy and has quickly become the leading driver of the rapid growth in EE programs due to their clear goals and proven success as a policy tool (ACEEE 2011). These policy drivers lead to the evaluation, planning, and adoption of EE programs and associated budgets, which are supported through different funding mechanisms. Funding Sources Funding sources for EE programs are varied but for most states are dominated by revenues collected from ratepayers through electricity surcharges, typically ranging from $1 to $4 per megawatt-hour (ACEEE 2014c). More recently adopted funding sources include proceeds from the auction of allowances in the Regional Greenhouse Gas Initiative (RGGI) states and from EE resources bid into the forward capacity market operated by the New England Independent System Operator (NE-ISO). Ratepayer-funding accounts for more than 90% of total EE program support nationally. The Demand-Side EE Opportunity As discussed, states are employing a number of EE strategies with EE programs yielding the most significant impacts both historically as well as in terms of future potential. Furthermore, EE programs are unique among state EE strategies in the comprehensiveness and transparency of their reported impacts, funding, and other characteristics. In this section we address the rapid growth in EE programs, estimated impacts of EE programs to-date and projections of the impacts of existing EE programs and trends, and the electricity savings potential achievable through expanded use of EE policies and programs. Finally, we will discuss the costs and cost-effectiveness of EE programs, specifically. Rapid Growth in Demand-Side EE Funding for EE programs has increased rapidly in recent years driven by recent policy innovations and increasing evidence of the effectiveness of these new strategies. Table 2 presents levels of EE program funding in the U.S. since 2006 (ACEEE 2014c). In the previous five years, funding increased by more than 250%, from $1.6 billion in 2006 to $5.9 billion in 2011. Table 2. U.S. Electric Utility EE Program Funding (2006-2013)                                         Year                                         2006 2007 2008 2009 2010 2011 2012 2013 Electric Efficiency Program Budgets (billions of $s, nominal) 1.6 2.2 2.6 3.4 4.6 5.9 5.9 6.3 Source: ACEEE 2014c Key new state policies that have helped to drive these rapid increases in EE program funding include EERS, electricity savings goals, and "all cost-effective EE" requirements. The adoption of EERS, in particular, increased through this period and clearly has been the primary driving force behind the increasing success of and investment in EE programs. Table 3 shows the number of states adopting EERS by year (ACEEE 2014c). Table 3. U.S. State Adoption of EE Resource Standards  Year States Adopting an EERS Total 1997-2004 California, Hawaii, Texas, Vermont 4 2005 Nevada, Pennsylvania 2 2006 Rhode Island, Washington 2 2007 Colorado, Connecticut, Illinois, Minnesota, North Carolina 5 2008 Maryland, Michigan, New Mexico, New Year, Ohio 5 2009 Arizona, Indiana, Iowa, Maine, Massachusetts 5 2010 Arkansas, Oregon 2 2011 Wisconsin 1 1997-2011

26 Source: ACEEE 2014c EE Program Impacts Impacts to-date The primary sources for EE program information (including costs and impacts) are annual EE program reports required by utility commissions, or cooperative or municipal utility boards of directors. Program impact results provided in these reports are based on evaluation, measurement, and verification (EM&V) procedures and methods used to estimate the electricity savings from EE programs within the program portfolio. The EIA has been collecting data on EE programs through Form 861, "Annual Electric Power Industry Report," for more than three decades. The data collection reflects an increasing degree of breadth and detail over time. For example, third-party-administered programs were not initially required to report but were added beginning in 2011. Data fields have been added over the years to reflect industry trends (e.g., EE programs are now reported separately from load management programs). Outside organizations have taken the EIA data, supplemented it with additional sources including surveys of utility commissions and program administrators, and published their own annual reports that capture EE program impacts (ACEEE 2014c; CEE 2015).  The EPA has relied on the EIA Form 861 dataset for identifying historical impacts of EE programs by state, tribe and territory. Specifically, the reported sales data and incremental electricity savings in the 2013 EIA 861 dataset are used to estimate electricity EE impacts by state. EIA data is reported by program administrator (e.g., utility, third-party, or state agency) and requires the disaggregation of reported data by state for administrators with programs in multiple states (e.g., multi-state investor-owned utilities). Program administrators in 50 states and the District of Columbia reported savings in 2013. The EPA has compiled this information to derive aggregate electricity sales and incremental electricity savings at the state, tribal and territorial levels.  Three tribal areas (Navajo, Ute, and Fort Mojave) and two territories (Puerto Rico and Guam) have affected EGUs under the final rule. The 2013 EIA form 861 data contain information to identify historical electricity sales and EE activities in these tribal areas and territories. The tribes are located in three states  -  Arizona, New Mexico, and Utah. Electricity sales within the tribal areas are taken out of the total sales within these three states and reported separately. For Arizona, this includes utility sales in the "Navajo Tribal Utility Authority" (Navajo tribe) and the "Aha Macav Power Service" (Fort Mojave tribe). For New Mexico, this includes utility sales in the "Navajo Tribal Utility Authority" (Navajo tribe). For Utah, this includes utility sales in the "Navajo Tribal Utility Authority" (Navajo tribe) and the "Moon Lake Electric Assn, Inc." (Ute tribe).  Table 4 provides a summary of the estimated electricity savings data by state, tribal area and territory for the latest year of available data. At the national level, incremental electricity savings in 2013 was 0.66% of retail sales with individual state values ranging from 0.00% to 2.00%. Cumulative electricity savings (representing the remaining impacts of programs from all prior years) reported at the national level for 2012 represent 3.73% of retail sales with individual state values ranging from 0.0% to 15.44%. 2012 was the most recent year that EIA Form 861 included cumulative savings data, which has been discontinued in the 2013 version of the form. Table 4. Aggregate Electricity Savings by State, Tribal Area and Territory                                      State              Incremental Savings as a Percent of Retail Sales (%)                                      2013               Cumulative Savings as a Percent of Retail Sales (%)                                      2012                                     Alabama                                      0.10%                                      0.78%                                     Arizona                                      1.59%                                      5.43%                                    Arkansas                                      0.49%                                      0.39%                                   California                                      1.16%                                     13.67%                                    Colorado                                      0.92%                                      4.67%                                   Connecticut                                      1.00%                                     13.39%                                    Delaware                                      0.01%                                      0.00%                              District of Columbia                                      0.45%                                      0.57%                                     Florida                                      0.17%                                      3.60%                                     Georgia                                      0.26%                                      0.67%                                      Idaho                                      0.54%                                      6.20%                                    Illinois                                      1.06%                                      2.15%                                     Indiana                                      0.93%                                      1.72%                                      Iowa                                      1.18%                                      7.80%                                     Kansas                                      0.01%                                      0.24%                                    Kentucky                                      0.38%                                      1.04%                                    Louisiana                                      0.03%                                      0.00%                                      Maine                                      1.14%                                      5.42%                                    Maryland                                      1.07%                                      2.47%                                  Massachusetts                                      1.06%                                      6.27%                                    Michigan                                      1.15%                                      2.77%                                    Minnesota                                      1.13%                                     13.10%                                   Mississippi                                      0.23%                                      0.50%                                    Missouri                                      0.49%                                      0.55%                                     Montana                                      0.54%                                      5.85%                                    Nebraska                                      0.15%                                      0.99%                                     Nevada                                      0.48%                                      6.19%                                  New Hampshire                                      0.15%                                      4.90%                                   New Jersey                                      0.70%                                      1.04%                                   New Mexico                                      0.57%                                      1.87%                                    New York                                      1.20%                                      6.89%                                 North Carolina                                      0.60%                                      1.26%                                  North Dakota                                      0.02%                                      0.22%                                      Ohio                                      1.04%                                      3.20%                                    Oklahoma                                      0.26%                                      0.70%                                     Oregon                                      1.20%                                      7.72%                                  Pennsylvania                                      0.91%                                      3.08%                                  Rhode Island                                      2.00%                                     11.22%                                 South Carolina                                      0.46%                                      1.12%                                  South Dakota                                      0.13%                                      0.33%                                    Tennessee                                      0.31%                                      1.76%                                      Texas                                      0.20%                                      1.54%                                      Utah                                      0.82%                                      6.70%                                     Vermont                                      1.77%                                     15.44%                                    Virginia                                      0.02%                                      0.30%                                   Washington                                      1.00%                                      7.37%                                  West Virginia                                      0.25%                                      0.20%                                    Wisconsin                                      1.32%                                      6.61%                                     Wyoming                                      0.17%                                      0.71%                                     Navajo                                      0.00%                                      0.00%                                       Ute                                      0.00%                                      0.00%                                   Fort Mojave                                      0.00%                                      0.00%                             Continental U.S. Total                                      0.66%                                      3.76%                                     Alaska                                      0.05%                                      0.15%                                     Hawaii                                      0.04%                                      0.33%                                   Puerto Rico                                      0.00%                                      0.00%                                      Guam                                      0.00%                                      0.00%                           U.S. Total and Territories                                      0.66%                                      3.73%         Source: EPA calculation based EIA 2013 and EIA 2012a Projected Impacts In 2013, Lawrence Berkeley National Laboratory (LBNL) published an update to a 2009 analysis and projected future spending levels and savings through 2025 from EE programs funded by electric and gas utility customers in the United States under three scenarios (high, medium, and low cases) (Barbose et al. 2013). The scenarios represent "a range of potential outcomes under the current policy environment" and were based on detailed, bottom-up analysis of existing state EE policies. Significantly, the study presumes no new major policy developments such as a "national EE standard, clean energy standard, or carbon policy" and specifies that such policy changes could "result in customer-funded EE program spending and savings that exceed the values in our High Case." The study concludes that efficiency programs are "poised for dramatic growth over the course of the next 10 to 15 years" with the most significant increases occurring in regions with lower levels of program spending, historically, including the Midwest and South. For example, under the medium scenario total U.S. spending on electric efficiency programs increase by 40% to $8.1 billion in 2025 from 2012 levels. Under the high scenario, spending more than doubles from 2012 levels to $12.2 billion in 2025. Incremental savings levels grow commensurately, to 0.8% and 1.1% of sales under the medium and high scenarios, respectively. The study results indicate that under the high scenario 20 states would be achieving 1.5% or higher levels of incremental savings, with 11 of those reaching or exceeding 2.0%. Table 5 summarizes the results of the LBNL analysis. Table 5. Summary of Impacts: Scenarios of Future Utility  Customer-Funded Electric EE Programs  Case 2025

Incremental Savings (% of Sales) Program Costs (billions of $, nominal) Programs Costs (% of Revenues) Low 0.5% 5.5 1.1% Medium 0.8% 8.1 1.7% High 1.1% 12.2 2.7% Source: Barbose et al. 2013 EE Potential Evaluations of EE Potential EE potential studies are a common tool for informing the development of EE program plans and budgets, as well as supporting the development of electricity savings targets, required savings levels under an EERS, or "all cost-effective" EE requirement. In conducting these studies, states and utilities have developed a methodology that is often described as a "bottom-up, engineering-based" approach (EPA and DOE 2007a). EE potential studies are conducted at various geographic scopes (national, regional, state, and utility service territory level) and at different degrees of aggregation (e.g., economy-wide, sectoral, and program), and can be broadly grouped into a few types: technical, economic, market, and program. Technical potential represents the theoretical maximum amount of energy use that could be displaced by efficiency, without regard to non-engineering constraints such as costs and the willingness of energy consumers to adopt the efficiency measures. It often assumes immediate implementation of all technologically feasible energy saving measures, with additional efficiency opportunities assumed as they arise.  Economic potential refers to the subset of the technical potential that is economically cost-effective. Definition of "economic potential" can vary to some degree by study. Some estimate economic potential by evaluating technology upfront cost, operating costs that considers energy prices, product lifetime and discount rate, compared to a conventional alternative or the supply-side energy resources. Others incorporate consideration of consumer preferences in addition to consumers' out-of-pocket expenditure when evaluating the economic potential. Both technical and economic potential estimates assume immediate implementation of efficiency measures without regard to technology adoption process or real-life program implementation. In addition, these estimates do not always reflect market failures or barriers that impede EE and often fail to capture transaction costs (e.g., administration, marketing, analysis, etc.) beyond the costs of efficiency measures. Another key factor determining economic potential is the level of aggregation at which the cost-effectiveness evaluation is applied. Applying the cost test at lower levels of aggregation (e.g., at the measure or program level, rather than the sector level) will typically lead to lower economic potential when evaluating a portfolio of programs. Market potential (or "achievable" potential) refers to the subset of economic potential that reflects the estimated amount of energy savings that can realistically be achieved, taking into account factors such as technology adoption process, market failures or barriers that inhibit technology adoption, transaction costs, consumer preferences, social and institutional constraints, and possibly the capability of programs and administrators to ramp up program activity over time. Program potential refers to the subset of market potential that can be realized given specific program funding levels and designs. Program potential studies can consider scenarios ranging from a single program to a full portfolio of programs.  As mentioned, the EE industry standard for potential studies is the bottom-up, engineering evaluation of EE potential of individual end-use technologies and measures (EPA and DOE 2007a). Bottom-up analyses all employ a similar methodology but can vary significantly in key assumptions (e.g., breadth of sectors and end-uses considered, aggregation level at which cost tests are applied, study period, discount rate, pattern of technology penetration, whether economically justified early replacement of technologies is allowed for, and whether continued improvement in efficiency of technology is provided for). As a result, estimated efficiency potential can vary significantly among studies. Overview of Results EE potential studies have been conducted for decades and in recent years numerous studies have been conducted at utility, state, regional, and national levels. This section presents a summary of more than 50 recent studies (2009 through 2014) collected by EPA. Further detail on the collection of studies is provided in Appendix 1, including a database of study sources and results. Studies were identified by reviewing three recent meta-studies (Sreedharan 2013; ACEEE 2014b; and EPA 2014a) and supplementing those reviewed studies with more recent or overlooked studies. By focusing on studies conducted after 2008, the potentially significant effects of the lighting provisions of the Energy Independence and Security Act of 2007 (Congress 2007) are accounted for. The collected studies cover all major end-use sectors (residential, commercial and industrial) and all regions of the U.S. To normalize results of analyses addressing different study periods, we present average annual achievable potential by dividing cumulative percentage savings in the last year of the study by the duration (in years) of the study period. This is a common method of normalization for EE potential studies and allows for comparison with results from the EPA's demand-side EE plan scenario later in this chapter (section 8) (Sreedharan 2013; ACEEE 2008, 2014b). Many studies provided multiple estimates of achievable potential. Some studies use the terms "high," "medium" and "low" achievable potential, while others used terms such as "high achievable" and "achievable" potential or, in some cases "achievable" and "programmatic" potential. For studies that provided multiple levels of achievable potential, the highest value was classified as high potential and the lowest value was classified as low potential. If a study provided just a single value, it was used as both the high and low potential value for that study. In many instances, low potential values in the studies were arrived at using assumptions of limited budgets or other limiting factors. To be conservative, the EPA has included these low values but generally consider the high achievable values to be the more appropriate point of comparison in evaluating the magnitude and timing of savings represented in the illustrative EE plan scenario.  Table 6 provides summary results of EPA's review of recent EE potential studies. Across all sectors for all studies, average annual achievable potential ranges from 0.9% to 1.3% per year for low to high potential estimates, respectively. Results vary between end-use sectors with the industrial sector showing less potential than residential and commercial sectors. Results for all sectors indicate very substantial opportunity for achievable EE savings. Table 6. Summary of EE Potential Studies (2009 to 2014) Sector Average Annual Achievable Potential (% per year)

High Low

Median Mean Median Mean Residential 1.0%/year 1.2%/year 0.7%/year 0.8%/year Commercial 1.3%/year 1.3%/year 0.8%/year 0.9%/year Industrial 0.9%/year 1.0%/year 0.5%/year 0.7%/year All 1.3%/year 1.2%/year 0.9%/year 0.9%/year Source: Appendix 1 Costs and Cost-Effectiveness of State EE Policies EE Cost-Effectiveness States enact EE policies to meet multiple policy objectives including reduction of customer electricity bills, lower costs of meeting electricity supply needs, energy reduction, environment and health benefits, and local economic development benefits (EPA and DOE 2006). Most states evaluate their EE policy options through the application of cost tests, weighing the projected benefits with the costs of the EE technologies and practices (EPA and DOE 2008; RAP 2012). Each state determines their own policies for the specific costs and benefits to include in these tests. The costs and benefits are compared on an equal footing by using present value analysis. This is necessary because EE typically requires primarily upfront expenditures (e.g., a whole home retrofit) while the economic benefits (e.g., electricity bill savings) accrue over the life of the investment ("measure life") which can range from a few to twenty or more years. As such, the choice of discount rate and the estimation of measure life are significant determinants of the cost-effectiveness results. Most states employ multiple tests, adjusting cost and benefit categories depending upon the economic perspective of interest (e.g., utility, ratepayer, program participant, society), and consider the results from each one, usually with an identified primary test type. Policies that are selected are those that are found to be cost-effective, with benefits greater than costs, as determined by the utility applying methods defined by their state utility commission. There are five primary cost-effective tests used in the U.S.: Participant cost test from the perspective of the customer installing the measure. Costs may include incremental equipment and installation costs; benefits include incentive payments, bill savings, and applicable tax credits or incentives.  Utility/program administrator cost test from the perspective of utility, government agency or third-party implementing the program. Costs may include program incentive, installation, and overhead costs; benefits may include avoided energy and capacity costs - including generation, transmission and distribution - by the utility.  Ratepayer impact measure test from the perspective of utility ratepayers not participating in available EE programs. This text includes the costs and benefits that will affect utility rates, including program and administration costs, as well as "lost revenues" to the utility; benefits include avoided energy and capacity costs, and additional resource savings. Total resource cost test from the perspective of all utility customers in the service area. Costs may include the full incremental cost of the measure, program installation and overhead costs; benefits may include avoided energy and capacity costs, and additional resource savings. Societal cost test from the social perspective. In addition to benefits considered in total resource cost test, may also include non-monetized benefits such as environmental and health benefits.  While many states consider more than one cost test in evaluating EE programs, the most commonly used (29 states) primary test is the total resources cost test. This test is considered to be the best measure of the interests of all utility customers. The utility and societal cost tests are the next most commonly used primary tests, used by five states each. The utility cost test is considered to be the most comparable metric to compare with supply-side resource investments from a utility resource planning perspective.  Costs of Saved Energy A common metric for comparing alternative electricity resource options within utility resource plans is the levelized cost of energy (LCOE) or, for EE resources, the levelized cost of saved energy (LCSE) (EPA and DOE 2007b). LCSE EE is often compared favorably with LCOE of alternative new generation sources such as fossil-fueled or nuclear power plants, or renewable energy resources like wind or solar-power generation. In these comparisons, typically only utility (or program) costs are considered, not the total costs of saved energy that are discussed later in this chapter. The EE analysis literature reports average LCSE in the range of 1-6 cents/kWh based on program administrator cost. A recent review by ACEEE examined studies across 20 states between 2009 and 2012, and estimated LCSE for electricity EE programs in the range of 1.3-5.6 cents/kWh, with a mean value of 2.8 cents/kWh (ACEEE 2014d). Earlier reviews of utility EE programs identified a similar range of LCSE. In 2009 ACEEE reviewed 14 utility studies of LCSE and found a range from 1.6 to 3.3 cents/kWh, with a mean value of 2.5 cents/kWh (ACEEE 2009). An earlier ACEEE study reviewed cost-effectiveness analysis results in nine states and suggested that reported utility LCSE ranged between 2.3-4.4 cents/kWh, with a mean value of 3 cents/kWh (ACEEE 2004). In 2014, an LBNL analyzed the program cost of saved energy based on data from their DSM Program Impacts Database. The database includes program results reported to state regulators by more than 100 program administrators in 31 state, primarily for the years 2009-2011 (LBNL 2014b). LBNL found a national average LCSE of 2.1 cents/kWh of gross savings. The economic literature also evaluates the LCSE from EE measures using other techniques (e.g., econometrics, top-down modeling), although this body of studies is much smaller compared to the bottom-up, engineering-based analysis. The economic literature has varying treatment of the free ridership, EE program endogeneity, and the rebound effect. The different assumptions used in these analyses make direct comparison challenging, but overall these empirical analyses present a wider range of estimates of cost of saved energy. For example, a 2008 study in the Energy Journal examining utility DSM programs estimated the average utility cost of saved energy in the range of 5.1 to 14.6 cents per kWh (Auffhammer et al. 2008). Some other studies in the economic literature suggest estimated LCSE in a similar range as from the bottom-up analyses. RFF calculated an average cost of 3.4 cents per kWh saved from utility EE programs, based on the utility-reported savings in the EIA Form 861 (Gillingham et al. 2006). A 2012 econometric analysis of utility rate-payer funded demand-side management and EE programs between 1992 and 2006 found that the estimated energy savings in electricity consumption were achieved at an expected average cost to utilities of approximately 5 cents/kWh (Arimura et al. 2012). In 2011, using a top-down approach that evaluates the savings potential of EE investments using state- and region-specific price elasticity, an RFF study estimated that electricity savings of 1 to 3 percent were available at a marginal cost of 5 cents/kWh and a corresponding average cost of 2.5-3.5 cents/kWh (RFF 2011).  A number of analytical and data considerations related to LCSE estimation are also discussed in the literature, including the issue of "free riders" in EE programs, and the accuracy of utility reported costs and energy savings (Train 1994; Joskow and Marron 1992). EE practitioners also recognize the need to consider "free rider" and "spillover" effects in program evaluation (Gillingham et al. 2006). A slight majority of states adjust for free ridership in energy savings estimates, leading to higher LCSE values than otherwise would be the case (ACEEE 2012a). A smaller number of states adjust for spillover effects which reduce LCSE values when addressed. Another consideration related to LCSE estimation is the rebound effect. The economic literature has extensive discussion of the potential rebound effect, market interactions and economy-wide response of EE policies and investments. An improvement in EE would effectively reduce the cost of a service or production input, potentially boosting its demand or production output thus increasing energy use ("direct" rebound). In addition, money saved from EE can be used for consumption or investment that can increase energy consumption for other goods and services in the economy (two forms of "indirect" rebound). Reviews suggest that both direct and indirect rebound effects exist and the size of such effects varies among different studies, technologies, sectors and income groups (UKERC 2007). Overall, however, rebound effects are found to be relatively modest in most markets and settings (Greening et al. 2000; Davis 2008; Gillingham et al. 2013; UKERC 2007). Other EE Strategies In addition to ratepayer-funded EE programs, many other strategies are available to increase investment in EE and realize associated energy savings, emissions reductions and other benefits. In this section we address a few of the more significant opportunities for realizing additional EE potential: building energy codes, state appliance standards, energy service performance contracting, and volt/VAR optimization. Building Energy Codes Overview Building energy codes establish minimum efficiency requirements for new and renovated residential and commercial buildings. Building energy codes lock in long-term energy savings at a low cost during the building design and construction phase; some of which would not be feasible or cost-effective as building retrofits. The primary policy rationale for energy codes is the need to overcome large and persistent market barriers, the largest of which is the concern over split-incentives or "principal-agents," in which builders' incentives to minimize the initial costs of constructing a building are misaligned with occupants' incentives to minimize total occupancy costs. Building energy codes are designed to eliminate inefficient technologies and building practices, minimizing total ownership and operating costs over the life of the building. Additional co-benefits of implementing building energy codes include pollution prevention, improved electric system reliability, avoidance of new energy supply investment, and improved occupant comfort and health. Energy building code requirements are also designed to overcome the complexity of advanced codes, lack of local-level implementation resources, and a shortage of empirical data on the costs and benefits of codes. Building energy codes specify thermal performance criteria for building thermal envelope components such as walls, ceilings, floors, and windows, and also set air leakage and duct leakage standards. They also address lighting system efficiency, hot water system efficiency, and heating and cooling equipment efficiency in cases where federal standards do not cover the affected equipment or system types. For the residential sector, the International Energy Conservation Code (IECC) is the prevailing model code, and ASHRAE 90.1 is the model code for the commercial sector (EPA 2014b). Various versions of these model codes are adopted and enforced at the state and local government levels. Authority / Obligated Parties Model energy building codes are typically developed at the national or international level, adopted at the state or local level, and administered and enforced locally. Local building industry parties, such as developers and property owners requiring building permits, are the most common obligated parties (EPA 2014b). Federal authority affecting state code adoption was established in the Energy Policy Act (EPAct) of 1992 (Congress 1992); its provisions require the U.S. Department of Energy to review each new version of the IECC and ASHRAE 90.1, released about every three years, to determine whether they save energy compared to the previous version (EPA 2015). When DOE concludes that a new version of the code would improve energy efficiency, states must review and consider adopting the new code. However, since EPAct 1992, not all states have adopted or updated residential and commercial building energy codes per the current DOE determination. Building Code Regulations Over Time Federal authority for building codes was established in Energy Conservation and Production Act of 1976 (ECPA), which authorized DOE to create national Building Energy Performance Standards (BEPS) that would be legally binding nationwide. The BEPS provision was repealed by Congress in the early 1980s. States, however, continued to develop energy codes. In 1978, California became the first state to include energy requirements in its code (EPA 2015). Other states, such as New York, Massachusetts, Florida, and Minnesota, developed their own energy codes during the 1980s. In response to the EPAct 1992 requirements, most states adopted various versions of the IECC and ASHRAE 90.1. Over the last decade, the number of states adopting residential and commercial energy codes has remained relatively stable at about 40 (EPA 2006, 2015). Figure 2 shows this consistency for residential energy codes, as the states with the lightest shading are the ones that had either not adopted or recently updated their energy codes. However, the stringency of these codes has been updated multiple times since 2005 in most states. Eleven of the 40 states with residential building codes are using the 2012 IECC version, which DOE has determined would improve the energy efficiency of residential buildings by approximately 30 percent compared to the 2006 IECC (EPA 2015). A recent study estimated that upgrading the energy efficiency of a typical new home in Arizona from the 2006 IECC would save homeowners an average of $3,245 over 30 years with the 2009 IECC and $6,550 over 30 years with the 2012 IECC (DOE 2012b). DOE estimates that currently-adopted building energy codes across the country will result in a financial benefit of nearly $2 billion annually by 2015 and over $15 billion annually by 2030 (DOE 2014). Figure 2. Residential Energy Building Code Adoption (2005 to 2014)

Source: EPA 2006 and EPA 2015 Remaining Market Potential There is still significant potential for savings from building energy code adoption. From 1992 to 2012, building energy codes in the U.S. saved a cumulative 4 quadrillion Btu and reduced greenhouse gas emissions by 300 million metric tons (ACEEE 2015a). From 2013 to 2040, the continued adoption of increasingly stringent building energy codes in the U.S. is expected to save 40.1 quadrillion Btu (ACEEE 2015a). A recent study by ACEEE also found that for residential and commercial building codes, the potential for energy savings by 2030 was 155 million megawatt-hours (MWh) annually, or 4.2 percent of annual electricity consumption relative to 2012 (ACEEE 2014a). State Appliance Standards Overview State appliance standards establish minimum energy efficiency levels for those appliances and other energy-consuming products that are not already covered by the federal government. These standards typically prohibit the sale of less efficient models within a state. States are finding that appliance standards offer a cost-effective strategy for improving energy efficiency and lowering energy costs for businesses and consumers, though these standards are superseded when federal standards are enacted for new product categories (EPA 2014b). The key objectives of appliance efficiency standards are to: Raise the efficiency of a range of residential and commercial energy-consuming products, where cost-effective. Overcome market barriers, such as split incentives between homebuilders and homebuyers and between landlords and tenants, and panic-purchase situations in which appliances break and must be replaced on an emergency basis. Ensure energy use reductions to prevent criteria air pollution and greenhouse emissions, improve electric system reliability, and reduce consumer energy bills (EPA 2015). While state appliance standards can be useful in testing and exploring the effectiveness of standards for new products, many state appliance standards have been preempted or superseded by existing federal standards. States may apply to DOE for a waiver to implement more stringent standards. This is sometimes granted if a certain period of time has passed since the federal standard has been updated (EPA 2015). Authority / Obligated Parties Establishing efficiency standards in a state typically requires enabling legislation from the state legislature. However, once legislation is enacted, it may allow an executive agency to set further standards administratively (EPA 2015). State energy offices, which typically administer the federal state energy program funds, have generally acted as the administrative lead for implementing standards. In contrast, inspection and enforcement of appliance standards regulations has typically involved self-policing among industry. Manufacturers of products being sold in a given state are typically obligated to ensure their appliances meet the appropriate energy efficiency standards (EPA 2014b).  Appliance Standards over Time California's appliance standards program dates to the 1970s, when the state began to pursue standards before the enactment of federal legislation. When the federal government opted not to issue standards under its legislative mandate in 1982, other states joined California in developing state standards. These state initiatives helped create the impetus for new federal legislation in 1987 (the National Appliance Energy Conservation Act or NAECA), the Energy Policy Acts (EPActs) in 1992 and 2005, and the Energy Independence and Security Act (EISA) in 2007 (EPA 2015). These federal laws have established appliance efficiency standards for more than 50 products, representing about 90% of home energy use, 60% of commercial building energy use, and about 30% of industrial energy use (DOE 2015a). Bolstered by new standards contained in the EPAct 2005, EISA 2007, and additional DOE rules, these savings rose to 278 terawatt-hours (TWh), or 7% of U.S. electricity use in 2010. By 2025, total electricity savings from existing federal standards are projected to increase to 682 TWh per year, or 14% of the projected annual U.S. electricity use. Net savings to consumers and businesses are also expected to increase from $27 billion in 2010 to $61 billion in 2025 (ASAP 2012). While the NAECA effectively preempted state action on federally covered consumer products, California has continued to develop efficiency standards for other products and technologies that aren't included in the Act. California's standards program has contributed to substantial improvements in energy efficiency. Since its inception, the program has saved consumers over $75 billion on electricity bills (CEC 2013). Since 2001, 15 states and the District of Columbia have enacted appliance efficiency standards. While most of these individual standards have been superseded by federal standards, as of February 2014, 12 states and the District of Columbia have one or more appliance efficiency standards for products not covered by federal standards (ASAP 2014). Remaining Market Potential While federal appliance standards continue to expand, the direct economic and environmental benefits of state standards are still substantial. California draft regulations for 15 new appliance standards are expected to save 50 billion gallons of water, 1,400 MW of peak electricity, 9.8 TWh of electricity, and 162 million therms of natural gas per year. This is expected to result in annual savings of $2 billion (CEC 2014). From a national perspective, there is still untapped potential for states to move into product areas not yet covered by federal standards. Table 7 shows potential energy savings from products that do not currently have federal standards. The three products with the greatest potential in the residential, commercial and industrial, and lighting sectors are shown, along with a summary line for each sector. Some of the greatest potential savings in 2035 are in the residential sector, specifically improvements in water heater efficiency.  Implementing all of these standards through federal regulations would result in annual savings of 212 TWh in 2025, or 5% of projected national electricity consumption (ASAP 2012; EIA 2015). Table 7. Estimated Energy Savings Potential of State Appliance Standards                                                                     Annual savings in 2025                             Annual savings in 2035

                              Electricity savings                                   Peak demand                                   Natural gas                               Electricity savings                                   Peak demand                                   Natural gas                                    Products                                      (TWh)                                      (GW)                                     (Tbtu)                                      (TWh)                                      (GW)                                     (Tbtu)                              RESIDENTIAL STANDARDS Water heaters                                      18.2                                       2.5                                        --                                       43.0                                       5.9                                        --  Set top boxes and digital communication equipment                                      14.7                                       2.0                                        --                                       14.7                                       2.0                                        --  Air handlers                                      13.7                                       5.6                                        --                                       29.1                                      11.9                                        --  Total (14 products)                                      98.5                                      16.8                                      51.6                                      142.3                                      27.0                                      51.6                       COMMERCIAL AND INDUSTRIAL STANDARDS Walk-in coolers and freezers                                      14.7                                       3.4                                        --                                       14.7                                       3.4                                        --  Distribution transformers                                      10.9                                       1.5                                        --                                       22.4                                       3.1                                        --  Electric motors                                       9.0                                       1.4                                        --                                       18.6                                       2.9                                        --  Total (13 products)                                      62.4                                      15.5                                      74.2                                      98.5                                      24.5                                      139.9                               LIGHTING STANDARDS Incandescent reflector lamps                                      20.2                                       5.0                                        --                                       20.2                                       5.0                                        --  Outdoor lighting fixtures                                      10.3                                       0.7                                        --                                       26.1                                       1.8                                        --  General service fluorescent lamps                                       6.9                                       1.7                                        --                                        6.9                                       1.7                                        --  Total (7 products)                                      50.8                                       9.3                                        --                                       65.6                                      15.6                                        --  ALL PRODUCTS                                       212                                       42                                       126                                       306                                       67                                       235 Source: ASAP 2012 Energy Service Performance Contracting Overview Energy service performance contracting (ESPC) uses cost savings from reduced energy consumption to repay the cost of installing energy conservation measures (HUD 2014). Under an EPC program, an Energy Service Company (ESCO) first conducts an energy audit. The ESCO then designs and constructs a project that achieves the building owner's energy efficiency needs and arranges for the project's financing, usually through a third party. The third party is repaid by the building owner/operator from the savings in their energy costs. In this type of ESPC arrangement, the builder owner/operator does not need to incur upfront expenses, and will experience the benefits of the upgrades, including monetary savings once the financer's costs have been repaid (ICF 2007). ESPC programs have been used extensively by state, federal, and local facilities to reduce utility and operating costs and to help meet environmental and energy efficiency goals, which can include the use of combined heat and power (CHP). Forty-nine states have implemented performance contracting activities, primarily through legislation, covering a combination of entities that include public agencies, school districts, municipalities, state colleges and universities, counties, or the state as a whole (ORNL 2015). While ESPC programs are already widespread, states have found that they can further utilize this approach by extending eligibility to all public facilities in the state (EPA 2015). While ESCOs deliver ESPC projects, and the ESPC market is the main driver for ESCOs, the two markets do not overlap completely. Since 2006, the share of the ESCO market consisting of ESPC projects has remained stable at about 70 percent (ICF 2007; LBNL 2014a). The other 30 percent of the market is comprised of design/build services; engineering, procurement, and construction services; consulting services; and operation and maintenance contracts. These services are not considered to be EPC projects since the project financial performance risk is not incurred by the ESCO or potential third party lenders (ICF 2007). History of ESPC Programs and the ESCO Business Model The ESCO business model emerged during the 1970s, supported in part by utilities paying ESCOs a fee for services such as energy audits provided to customers via their electric utilities and implementing federal energy management goals (NAESCO 2011). EPC activities emerged in the mid-1980s as power plants became more expensive to build and utilities were ordered to produce Integrated Resource Plans (IRPs) where energy efficiency measures could be used to meet projected demand. ESCOs were used to deliver energy savings from projects implemented at industrial and institutional sites, relying on advances in energy efficiency monitoring and verification techniques (ICF 2007). By the late 1990s, funding for utility-sponsored energy efficiency programs was reduced in about half of the states due to changed regulatory structures and increased political and regulatory pressures to maintain lower electricity prices (EPA 2006). Many restructured electric utilities shifted their focus away from sponsoring programs to starting new affiliated ESCOs to deliver energy services directly to customers. However, the business model for these market-based ESCOs was limited in reach to mainly larger industrial, commercial and institutional customers. Several states and local governments also turned to EPC activities to provide services in public facilities via lead-by-example policies (see section 3). These governments also saw the benefits of addressing capital equipment and maintenance projects that would not have otherwise been addressed through the capital budget process (ICF 2007). Commercial lenders also became involved in EPC funding, lowering the cost of projects through competition and paving the way for new financing vehicles (ICF 2007). During the early 2000s, however, the growth of the EPC and ESCO market declined due to loss of both performance contracting in federal buildings and market confidence for industrial financing mechanisms (NAESCO 2011). This trend reversed in 2005 as the EPC and ESCO market increased focus on state and local public buildings and innovated program offerings to provide customers new technologies and financial models (see section 3 and ICF 2007). Remaining Market Potential The market potential for EPC programs and ESCOs remain significant. Annual revenues for the U.S. ESCO market was expected to increase from $5.3 billion in 2011 to about $6.4 billion in 2013 (LBNL 2014a). An analysis by Lawrence Berkeley National Lab estimated the investment opportunity for ESCOs ranged between $71 billion and $133 billion (LBNL 2013a). Figure 3 shows a breakdown of investment opportunity by market segment. Commercial buildings, K-12 schools, and the health and hospital sectors have the highest remaining potential for ESCOs. Commercial buildings in particular have high barriers to implementing energy efficiency under EPC activities, as the private sector is generally averse to financing energy efficiency activities and has more stringent requirements for a lower payback period on projects (LBNL 2013a). While the two markets do not overlap completely, the potential for ESCO investments provide a strong indicator for the remaining potential of EPC activities. Figure 3. Remaining Market Potential for ESCOs                                         Source: LBNL 2013a Volt/VAR Optimization Overview Volt/VAR optimization (VVO) refers to coordinated efforts by utilities to manage and improve the delivery of real and reactive power in order to increase the efficiency of electricity distribution. VVO is accomplished primarily through the implementation of Smart Grid technologies that improve the real-time response to the demand for real and reactive power. Technologies for VVO include load tap changers and voltage regulators, which can help manage voltage levels, as well as capacitor banks, which allow for the delivery of reactive power. By using local capacitor banks to respond to reactive power demand, rather than adjusting the output of remote generators, systems can achieve reductions in transmission line loss. The U.S. Energy Information Administration (EIA) estimates that on average, 7.5% of generated electricity is lost in transmission and distribution, a number that could be reduced by effective use of VVO (EIA 2012b). VVO efforts are often closely related to conservation voltage reduction (CVR), which are actions taken to reduce initial delivered voltage levels in feeder transmission lines while remaining within the 114 volt to 126 volt range required at the customer meter (based on ANSI C84.1 standards). Like VVO, CVR relies on the use of Smart Grid technologies in order to more effectively manage voltage levels across all loads in a system. A simple presentation of these benefits are shown in Figure 4, where the implementation of VVO technologies allows electricity distributors to deliver electricity initially at a lower voltage, thus decreasing the generation fuel requirements, while still delivering within the acceptable range to all 7 loads. The combination of VVO and CVR can lead to a range of benefits, including reductions in peak electricity demand, reductions in energy requirements necessary to meet a certain level of demand, and a reduction in line loss. Figure 4. Hypothetical Voltage Profiles with and without VVO Technologies                                         Source: DOE 2011 History of VVO Programs VVO and CVR efforts were first introduced with partial implementation in California in 1977 (UNLV 2014). In 1987, the Snohomish Public Utility District instituted a pilot CVR project that demonstrated the possibility of reducing voltage and energy requirements by approximately 2.1% (NRECA 2013). More recently, the advent of Smart Grid technology with increased availability of energy use data, has led to a renewed interest in VVO and CVR as the potential for increased efficiency has become more apparent. Of the 99 projects funded by the Smart Grid Investment Grant program under the American Recovery and Reinvestment Act of 2009, 26 included the implementation of VVO technologies. These projects, which target reduced voltage during peak demand, electricity conservation due to reduced voltage, and reduced losses from feeder lines, are expected to achieve a 1% reduction in energy consumption for every 1% reduction in voltage level (DOE 2012a). There is no formal state requirement directing implementation of Volt/VAR optimization. However, in 2012, the National Association of Regulatory Utility Commissioners published a resolution in support of VVO implementation at the state-level. The resolution encouraged public utility commissions to work with state legislature to include deployment of VVO technologies as part of energy efficiency resource standards (NARUC 2012).  VVO Market Potential Large market potential currently exists for the implementation of VVO. The Pacific Northwest National Laboratory estimates that implementing VVO nationwide could potentially yield as much as a 3.2% annual reduction in energy consumption (PNNL 2012). The Bonneville Power Administration estimates that the cost-benefit ratio for transmission and distribution optimization is positive and well understood, and that CVR is a key component of these positive effects (BPA n.d.). McKinsey estimates that VVO could provide $43 billion in gross annual benefits in 2019 in the U.S., with CVR comprising the largest share of these benefits (McKinsey 2010). IHS Technology estimates that the shipments of VVO technology devices will double between 2013 and 2018, with a quadrupling of revenue over the same time period (IHS 2013). The Institute of Electrical and Electronics Engineers estimates that CVR has the potential to save approximately 750 trillion BTUs of electricity, equivalent to 5.4% of total U.S. electricity generation, at a total cost of $3.3 billion dollars (IEEE 2014). While these estimates vary in level of impact, they display the strong market potential that exists for VVO projects. Utility Regulatory Models for Supporting Demand-Side EE The electricity sector widely recognizes that state utility regulatory models for supporting energy efficiency are key to expanding utility investments and higher energy savings from programs (IEI 2014).  Further, all states which regulate investor-owned utilities have adopted or modified one or more policies in order to better align utility incentives with the delivery of cost-effective energy efficiency (IEI 2014).  States with the highest per capita spending on energy efficiency programs have the most comprehensive regulatory models for energy efficiency in place (NRDC 2012).   The most common regulatory models for incentivizing energy efficiency through electric utilities include decoupling revenue from sales volumes, ensuring program cost recovery, and providing shareholder incentives linked to program performance.  The Edison Foundation reports on the adoption of these policies across states through its Institute for Electric Innovation, as shown in Table 8.  Table 8. Summary of State Regulatory Frameworks: December 2014                      Energy Efficiency Incentive Mechanism                                Number of States                                     Pending Fixed-Cost Recovery Mechanisms Lost Revenue Recovery                                       19                                        0