Abstract
Purpose of Review
This paper introduces the major state-level regulations and policies for improving energy efficiency in buildings. The purpose of the review is to discuss the challenges and issues in policy implementation and the latest trend in adopting innovative instruments.
Recent Findings
The implementation of customer efficiency programs increasingly incorporates non-price instruments to encourage participation and deep savings. States pay attention to not only code adoption and update but also compliance and evaluation. Many states have adopted innovative policy instruments, including decoupling mechanisms and performance incentives to make energy efficiency a good business model for utilities, dynamic pricing to reduce consumption and peak load, flexible financing to provide incentives, and green labeling and benchmarking policies to increase information transparency.
Summary
State governments continue to be the primary decision-makers for improving energy efficiency in buildings. Combined efforts on code/standard compliance and innovative policies are the leading strategy to promote energy efficiency.
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Introduction
State governments are key decision-makers in improving energy efficiency (EE) of buildings. Unlike the federal regulations that provide uniform solutions, state governments have the flexibility to enact regulations and establish targets that reflect local circumstances and considerations. Local energy efficiency markets are driven by customer efficiency programs and state standards and regulations, which may exceed the stringency of federal standards. States take pro-efficiency actions because of multiple internal factors, such as public awareness and environmental movement, pressure for job creation, and requirement for grid stability and energy security [1, 2]. States also learn from their neighbors, peers, and leaders in adopting new policies for clean energy [3, 4]. Sometimes the federal government sets up targets and provides incentives that frame and guide state actions. For instance, the American Recovery and Reinvestment Act (ARRA) of 2009 provides large amount of grant funding to state and local governments, conditioning on their adoption of the most stringent building energy codes. Overall, policy design and implementation for energy efficiency needs to take into consideration of utility planning [5], stakeholder involvement [6], and indirect cost, consumer perception and other behavioral barriers [7].
This paper provides an overview of the state-level regulatory, financial, and information-based policies that aim at improving energy performance for products, equipment, appliances, homes, and buildings. Special attention is paid to the issues and challenges with policy design and implementation, as well as the recent trend in the adoption of innovative policy instruments. Massachusetts and California are selected to showcase how leading states take the strategy of combined efforts to promote energy efficiency.
Ratepayer-Funded Energy Efficiency Programs
All states have customer efficiency programs funded through public benefit funds, which are collected through charges wrapped into customer rates or other charges that appear on customer utility bills. Ratepayer-funded programs are administrated either directly by utilities in most states, or by third parties in some cases.Footnote 1 Customer efficiency programs have fast growing budgets—increased from $3.2 billion in 2010 to $7.6 billion in 2016 [8]. Program budget is spent primarily on electricity efficiency measures, with expenditure on natural gas efficiency improvements. CA, MA, and NY are the states that have large budgets for EE programs [8,9,10]. Budgets for EE programs are lower in smaller states; but some of them, such as RI, VT, and D.C., have budgeted high percentages (about 6%) of their utility revenues on energy efficiency [8].
Ratepayer-funded programs typically combine financial incentives with energy audit and training/educational services. Some utilities design separate programs to target specific consumer sub-segments with fine-tailored offerings. For instance, the Efficiency Vermont and Vermont Gas Systems provide generous financial incentives for new homes constructed in compliance with stringent building energy codes. The Northwest Energy Efficiency Alliance runs a program to accelerate the adoption of ductless heat pumps by developing marketing strategies to increase customer awareness and supply chain capacity. Recent trend in designing EE programs focuses more on tackling information and behavioral barriers by incorporating non-price instruments [11], such as social media marketing, relationship building, process simplification, and quality assurance [12].
The estimated energy saved by customer efficiency programs has more than doubled since 2010: increased from 10.6 GWh to 25.4 GWh in 2016 [8]. From 2014 to 2016, EE programs have realized on average 25.9 GWh of electricity savings (0.69% of retail sales), and 353 MMTherm of natural gas savings (0.42% of retail sales) each year [8,9,10]. The top performing programs can save up to 3% of electricity [13]. The estimated cost of saved electricity was $0.030/kWh for residential customers and $0.053/kWh for non-residential customers, based on a study of EE programs in 20 states from 2009 to 2013 [14]. Many of the programs have also reduced peak demand and achieved non-energy benefits, such as health benefits, job creation, and water savings [15].
Customer efficiency programs are frequently criticized for the program effectiveness, the incomplete and inconsistent data, and the discrepancies in measurement of energy savings [16]. A review estimates the average savings is merely 0.9% from ratepayer-funded EE programs between 1992 and 2006 [17]. The estimated energy savings delivered by the programs may not reflect sustained load reduction over long time. The evaluation, measurement and verification (EM&V) of energy savings are critical, but methods always vary from case to case. Study suggests that third-party evaluations tend to generate lower verified savings than self-reported savings by customers programs, while the selection of the third-party evaluator also affects the estimate of energy savings [14]. But EM&V procedure is increasingly standardized and automated [18], with tools emerged for measuring and verifying energy savings from EE projects.Footnote 2 Benchmarking the baseline or pre-participation consumption is a key first step. The accounting of free-ridership [19] and the rebound effect [20, 21] also affect program performance and evaluation.
Nevertheless, research on behavioral science provides new opportunities to save energy by using non-price instruments to tackle the behavioral barriers in the EE market. Multiple behavioral nudges have been tested in pilot studies, such as framing and psychological cues [22, 23], tailored information, consumption feedback, goal setting, and commitment [24, 25], as well as in large-scale projects [26••]. Novel design features and behavioral “nudges” become popular with EE programs to target the “hard-to-reach” customers and encourage deep, sustained, and long-term savings.
State Regulations and Policies on Energy Efficiency
Investor owned utility (IOU) companies are not interested in energy efficiency due to the throughput incentive for energy sales. State governments attempt to better engage utilities in energy efficiency through mandatory energy savings requirement, decoupling utility revenue from sales, and providing performance-based incentives. Policies are also enacted to improve efficiency performance for products and buildings and motivate consumers through dynamic pricing of energy and flexible financing.
Energy Efficiency Resource Standard (EERS)
States adopt EERS to set up mandatory energy-saving targets, which are binding targets for utilities and non-utility program administrators to reach certain levels of savings through end-use efficiency. Most of the EERS targets require long-term energy savings with specified incremental annual savings in either percentage or quantity measures. For instance, CA’s target requires on average 1,738 GWh electricity savings, 440 MW peak demand reduction, and 54.3 MMTh natural gas savings every year from 2016 to 2024 (see CA Public Utility Commission Decision 15-10-028). Some states set EERS targets to pursue deeper savings in later years, such as MI’s target starting from 0.3% in 2008 and ramping up to 1% in 2012 through 2012 (Public Act 495 & SB 438). EERS is popular among states, and efforts have been devoted toward a federal target.Footnote 3
As of January 2017, 20 states have statewide mandatory targets for energy efficiency, and six other states have set up non-binding efficiency goals [27]. Seven of these states have specified cost-effective efficiency measures. Some of the states impose efficiency targets for all utilities, while others only mandate energy savings for IOUs. The coverage of the EERS targets ranges roughly from 57 to 100% of total energy sales [28•]. In addition, NV and NC have classified energy efficiency as an eligible resource (with caps) in their Renewable Portfolio Standards. The design of EERS targets also varies in funding method, baseline setting, incentive/penalty setting [28•], and demand-side technology eligibility [29]. See Palmer et al. [28•] for a summary of the EERS policy design and implementation.
The energy-saving requirements of EERS vary substantially; if normalized into annual saving, EERS targets are 0.7% per year on average [8]. MA and RI require the highest energy savings, which are over 2.5% incremental savings each year. EERS targets of OH, AZ, and NY are considered to be more stringent than others, based on the converted % savings of impacted entities with consideration of future population growth [28•].
Mandating energy savings provide some level of legislative certainty that greatly encourages market actors to invest in energy efficiency [28•]. Evidence has shown that EERS are more successful at driving energy-efficiency improvements than regulatory tools affecting utility business models [30]. The implementation of EERS may lead to electricity rate increase, but this customer rate impact can be alleviated when utility business model is adjusted [31]. A comprehensive strategy is recommended to achieve high efficiency gains—“getting the business model right and setting specific efficiency targets” [30].
Decoupling
Decoupling utility profits from electricity sales is designed to ensure that utilities are “indifferent” to demand-side efficiency versus supply-side investment. Decoupling can be accomplished by using periodic rate reconciliations to cover cost. Allowed rate adjustments are commonly calculated on a per-customer basis to compensate for under- or over-collection of revenues. Another decoupling approach is “lost revenue adjustment mechanism” (LRAM), which allows utilities to recover lost contribution to fixed costs by redistributing it over all sales by class. Lost revenue can also be remedied by using straight fixed variable rates (SFVR). The SFVR mechanism recovers all fixed costs through a flat charge, and recovers variable costs through a volumetric rate.
Allowing recovery of direct program cost and lost revenue is not enough to make utilities “indifferent”. IOUs are subject to the Averch and Johnson effect that they tend to expand investment to earn more profit for the present stockholders [32]. Demand-side efficiency will reduce the rate bases for utilities and lower the return on equity for stockholders, but this disincentive cannot be 100% offset with decoupling [33]. Many states provide “additional” performance-based incentives to reward utilities for achieving pre-established goals so that they can earn an extra stream of revenue from energy efficiency. Performance incentives are popular with decoupled utilities, and mechanisms based on “shared benefits” are the most common type [34]. The shared savings is calculated based on a share of the net benefits from approved efficiency programs. Other types of incentives include an allowed percentage of program costs and an allowed rate of return on program spending.
Evidence shows that utilities have increased their expenditures on energy efficiency when decoupling policies are in place [35]. Brown et al. study the decoupling mechanism in the southeast—LRAM combined with direct program cost recovery and shared benefit incentives based on program administrator cost test. This business model has largely increased the rate of return on equity to exceeding the authorized rate of 11.25% [36•]. However, studies show that allowing rate adjustments through decoupling leads to the disproportionate distribution of the efficiency benefits. That is, participating customers enjoy savings from efficiency improvements, but non-participant may face with increased rates and costs [36•, 37]. Great scrutiny should be given to minimize the rate impact for customers when altering utility business models [36•].
Dynamic Pricing
The cost of power production varies significantly from hour to hour. Dynamic pricing is the idea to provide accurate price signals to customers so that they can cut down usage during high-rate peak times. Mechanisms for dynamic pricing include time-of-use pricing (TOU), critical peak pricing (CPP), and real-time pricing (RTP). Dynamic pricing enables utilities charge different rates for electricity based on time, generation cost and conditions of the grid. Dynamic pricing can remove subsidies to peak users embodied in flat rates, encouraging customers to shift load to non-peak time [38, 39].
Time-of-use Pricing sets and publishes electricity prices for peak and off-peak periods in advance. Electricity prices in peak periods are higher than off-peak time, which encourages load shifting and reduces peak demand. The rates for each time block are usually adjusted two or three times each year; however, TOU pricing does not address unforeseen weather conditions or equipment failures that can unexpectedly drive up generation costs. CA utilities implement Critical Peak Pricing, which adds one more rate in “critical” summer peak hours to recover the full generation cost. There can be a number of CPP event days in a year, and utilities usually notify customers ahead of time. Real-time pricing disseminates price singles in much smaller time intervals: typically hourly or even sub-hourly. RTP can reflect the changes in marginal costs and capture most of the cost variation in electricity generation. Technology improvements have helped enhance customers’ ability to respond to real-time prices [40].
The implementation of dynamic pricing does not always lead to electricity savings [41], because not all customers have the capability or willingness to reduce peak demand or shift load [42]. Dynamic pricing is recommended to be combined with demand response or other demand-side solutions to achieve great savings [43, 44]. However, load shift may save money but increase CO2 emissions due to the heterogeneity in hourly CO2 intensity for electricity generation [40]. Another challenge to the use of real-time price and usage data is data security and privacy. States are beginning to set requirements regarding the use of metered-data. TX, for example, has determined that all meter data belongs to a customer; however, energy providers can be granted access to the data with customer authorization [45].
Other Policies Targeting Market Sub-Segments
Building Energy Codes
Many states have adopted building energy codes to ensure efficiency improvement in new homes and commercial buildings. Imposing minimum energy performance requirements for new and renovated buildings can reduce energy consumption and save building owners and occupants money. Model codes are developed and updated periodically by independent organizations.Footnote 4 In the U.S., state governments have the authority in building code adoption and modification. Some states have decided to directly adopt the model codes, and many states have adopted revised versions of the model codes tailored to address location climate conditions. A few of the states draft codes using their own knowledge, capacity, and resources. As a prerequisite by the 2009’s stimulus package, many states adopted building energy codes around that time so that they are qualified to receive funds from the federal government. Building energy codes have been found to be effective in a wide range of countries (see a review by Evans et al. [46]), and more attention has been paid to code compliance and implementation [46, 47]. Effective strategies for code compliance include performance testing, independent testing and review, professional accountability, incentives, training, and streamlining processes [46]. Automated tools are also in development for checking code compliance [48].
Appliance Standard
The federal government has implemented minimum energy performance standards (MEPS) to phase out the least efficient models of appliances and equipment in the marketplace. Different from design standards mandating particular technologies or processes, appliance standards mandate performance outcomes, which provide design flexibility and motivate innovation. Currently, nationwide MEPSs cover 42 product types in 13 major end-uses, including refrigerators, HVAC, lighting, laundry equipment, cooking equipment, water heating, distribution transformers, and motors [1]. MEPSs are effective in improving product efficiency and stimulating R&D. But implementing uniform national standards is frequently criticized. States intending to set more stringent standards may find the US federal standards to be a barrier since the application for exemption tends to be slow and tedious. Currently, state governments take the lead in developing minimum efficiency standards for portable electronic devices, such as compact audio equipment, DVD players, pool pumps, portable electric spas, etc. [49]. The new technologies of smart appliances and Internet of Things impose new challenges to the development of appliance standards [50, 51].
Flexible Financing
Innovative financing approaches, particularly on-bill financing, are beginning to take hold in the building sector. On-bill financing provides opportunities for end-users who want to adopt efficient technologies but have limited access to financing options. On-bill financing offers low- or zero-interest loans, with short payback time (typically less than 3–5 years). Utilities sometimes provide free products and installation, but customer monthly bill stays at the same level as pre-installation consumption [52]. Utilities get the investment back by capturing the savings—the differences between customers monthly bill and their actual consumption. On-bill financing tackles the split incentive problem because the monthly payment stays with the meter even if tenants moved out [53].
Benchmarking and Green Labeling
States have taken the leading role in running information-based programs [54], such as energy audits and green labeling, home energy rating [55], building benchmarking, and the “Lead by Example” program for public buildings. Some states lead by example though setting up savings requirements for public buildings to demonstrate efficiency improvement opportunities. Benchmarking information is increasingly available for public and commercial buildings, as more and more states and cities adopted policies to require utilities and building operators to make their energy use data publicly available.Footnote 5 According to the estimation by the Institute for Market Transformation, these policies affect over 10^9 sf of floor space in major real estate markets [56]. Empirical studies demonstrate energy savings for certified efficient buildings [57, 58], and in return, energy performance labels and certificates provide price premiums for efficient homes in the real estate market [59, 60].
State Case Studies
MA and CA are widely recognized for their outstanding performances and leadership in energy efficiency due to strong and innovative policies, large customer efficiency programs, and significant energy savings. Short case studies of the two states are provided to exemplify the policy options for energy efficiency that are at state legislator’s disposal.
Massachusetts
MA economy is driven by non-energy-intensive service industries, with energy consumption per capita lower than the national average [61]. MA also has some of the highest electricity rates in the country [13], a factor that tends to lead to high overall efficiency performance [1]. The state passed the “Green Communities Act” in 2008, requiring electric utilities to first exhaust all cost-effective energy-efficiency resources prior to utilizing other supply-side resource options. The legislation also requires utilities to meet escalating annual savings targets, ramped up to 2.94% of electricity, and 1.24% of natural gas by 2016. The energy savings targets are higher than most targets of the states that have adopted EERS. Large budget (over 6% of utility revenue) is planned for the customer efficiency program, “Mass Save,” which has realized electricity savings for over 2.5% of retail sales for multiple consecutive years (calculated using data from EIA from 861 [13]). One of the most successful programs, the “Small Business Program’s” direct install model has been recognized as one of the best delivery mechanisms, which got adopted by other states. According to program evaluation, the benefit/cost ratio is 3.14 for electricity and 9.6 for natural gas based on the total resource cost test. Three key elements for the success of the program are the turnkey approach, the generous incentives, and the on-bill repayment option [12].
To make efficiency a business model for utilities, Massachusetts allow them to propose decoupled rate structures and collect supplemental revenue (less than 1%) with rate adjustments. Utilities are also offered incentives through shared savings and performance targets. The shared savings incentive is particularly rewarding because participating utilities are able to receive a return on benefits on top of the net benefits that result in “double earning” [1]. Massachusetts is a restructured market, which allows for consumer choices for competitive electric suppliers. Electric utilities (Eversource and National Grid) also offer time-of-use rates to residential consumers.
State government is obligated to lead by example (Executive Order 484), by setting aggressive energy savings targets for its public buildings—35% by 2025, and support efficiency improvement with government funding. For residential and commercial buildings, energy-performance codes are updated to the most stringent codes, which are estimated to be 10% more efficient than the baseline codes. To ensure savings, analysis and compliance studies have been conducted and a “strategic compliance plan” has been developed. Massachusetts is also the only state that has more stringent minimum efficiency standard for gas furnace that is granted a waiver of federal standard. Information about home energy audits has mandatory disclosure to homebuyers throughout the state. There is no comparable information-based policy for commercial buildings, but the city of Boston and Cambridge have adopted benchmarking policies for their public, commercial, and multifamily buildings.
California
Over the last 4 decades, CA’s per capita energy use has remained steady as the result of a sustained emphasis on energy efficiency. CA’s customer efficiency program has the highest budget of all states—over $1364 million in 2016 [13]. CA’s energy efficiency industry is strongly motived by its long-term savings targets, decoupling utilities, and performance incentives. All IOUs (74% market share) are decoupled to allow revenue requirement being adjusted for customer growth, productivity, weather, and inflation. Critical peak pricing is default for large commercial and industrial customers, and an option available for small customers on voluntary basis. Critical peak events happen 5–15 days for different utilities, and estimated demand reduction is higher for large customers (over 5%) than small-sized customers (about 2%) [62].
Code and standard development has been a very important driver for efficiency improvement in CA. The Golden State has arguably the most advanced code program in the country, with the latest residential code being estimated to exceed the IECC 2015 by 29% and the commercial code exceed the ASHREA 2013 by 13% [63, 64]. The latest code expands the capacity of demand response (DR) by requiring large commercial buildings to be designed with the capability to reduce lighting energy use when utilities issue a DR signal. CA has also promulgated minimum efficiency standards for 17 appliances that exceed federal standards, including computers, televisions, faucets, showerheads, small-diameter directional lamps, and toilets.
CA is currently the only state that requires public, commercial, and residential multifamily buildings to disclose energy use data. California is also the first state in the nation to implement a mandatory green building standards to design standards that exceed the mandatory codes and standards for zero net energy buildings. State-owned buildings not only have water efficiency requirements, but also have a target to reach zero net energy for 100% new construction and 50% existing square footage.
Conclusions
States have been running ratepayer-funded efficiency programs, and have enacted energy savings targets, building energy codes, and appliance standards to improve energy efficiency for appliances, equipment, and buildings. More attention has been paid to the challenges to the implementation of such regulations and programs, particularly behavioral barriers and issues. Innovative policy instruments are gaining popularity with state governments, such as decoupling mechanism to engage utilities, dynamic pricing and innovative financing to incentivize customers, and benchmarking and other information-based programs. New concerns associated with the innovative policies include consumer behavior and data security, which are to be solved with future technology improvements and the passage of new legislations. Study of the leading states—MA and CA—suggests that combined efforts on compliance to codes and standards and adoption of innovative policy instruments strongly motivate end-use efficiency.
Notes
In DE, D.C., HI, ME, NJ, NY, OR, VT, and WI, customer EE programs are funded through public benefit funds and run by third parties.
The International Performance Measurement and Verification Protocol is one of the most important tools that are widely used by EM&V processes.
A Senate bill was introduced in 2015, proposing a 20% electricity savings and 13% natural gas savings target by 2030.
The International Energy Conservation Codes (IECC) for residential buildings developed by the International Code Council are widely adopted. For non-residential buildings, codes developed by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHREA) are used by many states in the USA and by other countries.
The U.S. Department of Energy is promoting the Energy Star Portfolio Manager, an online benchmarking and data management tool, for energy and water usage information.
References
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
Brown MA, Wang Y. Green savings: how policies and markets drive energy efficiency. Preager: Santa Barbara; 2015.
Berry F, Berry W. Innovation and diffusion models in policy research. P. Sabatier and C. Weible, ed., Theories of the Policy Process. 3rd ed. Boulder, CO: Westview Press 2014. p. 307–38.
Matisoff DC, Edwards J. Kindred spirits or intergovernmental competition ? The innovation and diffusion of energy policies in the American states ( 1990–2008 ). Environ Politics. 2014;4016(July 2016).
Matisoff DC. The adoption of state climate change policies and renewable portfolio standards: regional diffusion or internal determinants?. Rev Policy Res [Internet]. Blackwell Publishing Inc; 2008;25(6):527–46. Available from: https://doi.org/10.1111/j.1541-1338.2008.00360.x
Iskin I, Daim TU. An assessment model for energy efficiency program planning in electric utilities: case of Northwest U.S. Sustain Energy Technol Assess [Internet]. 2016;15(Supplement C):42–59. Available from: http://www.sciencedirect.com/science/article/pii/S2213138816000242
Chandrashekeran S, Zuckerman J, Deason J. Raising the stakes for energy efficiency: a qualitative case study of California’s risk/reward incentive mechanism. Util Policy [Internet]. 2015;36(Supplement C):79–90. Available from: http://www.sciencedirect.com/science/article/pii/S0957178715300229
Craig CA, et al. Appl Energy [Internet]. 2016;165(Supplement C):660–9. Available from: http://www.sciencedirect.com/science/article/pii/S0306261915016426
Berg W, Nowak S, Kelly M, Vaidyanathan S, Shoemaker M, Chittum A, et al. The 2017 State Energy Efficiency Scorecard. American Council for an Energy-Efficient Economy. Report Number U1710. Washington D.C.; 2017.
Berg W, Nowak S, Kelly M, Vaidyanathan S, Shoemaker M, Chittum A, et al. The 2016 State Energy Efficiency Scorecard. American Council for an Energy-Efficient Economy. Report Number U1606. Washington D.C.; 2016.
Gilleo A, Nowak S, Kelly M, Vaidyanathan S, Shoemaker M, Anna Chittum, et al. The 2015 State Energy Efficiency Scorecard. American Council for an Energy-Efficient Economy. Report Number U1509. Washington D.C.; 2015.
Stern PC, Gardner GT, Vandenbergh MP, Dietz T, Gilligan JM. Design principles for carbon emissions reduction programs. Environm Sci Technol-Columbus. 2010;44(13):4847–8. https://doi.org/10.1021/es100896p.
Nowak S, Kushler M, Witte P, York D. Leaders of the pack: ACEEE ’ s third national review of exemplary energy efficiency programs. American Council for an Energy-Efficient Economy. Report Number U132. Washington D.C.; 2013.
Energy Information Administration. Form 861 [Internet]. Washington D.C.: Energy Information Administration (EIA); 2017. Available from: https://www.eia.gov/electricity/data/eia861/.
Kaufman N, Palmer KL. Energy efficiency program evaluations: opportunities for learning and inputs to incentive mechanisms. Energy Effic [Internet]. 2012;5(2):243–68. https://doi.org/10.1007/s12053-011-9130-x.
Freed M, Felder FA. Non-energy benefits: workhorse or unicorn of energy efficiency programs? Electr J [Internet]. 2017;30(1):43–6. Available from: http://www.sciencedirect.com/science/article/pii/S1040619016302305. https://doi.org/10.1016/j.tej.2016.12.004.
Hoffman IM, Goldman CA, Rybka G, Leventis G, Schwartz L, Sanstad AH, et al. Estimating the cost of saving electricity through U.S. utility customer-funded energy efficiency programs. Energy Policy [Internet]. 2017;104(Supplement C):1–12. Available from: http://www.sciencedirect.com/science/article/pii/S0301421516307042
Arimura TH, Newell RG, Medina Z, Iwata K, Myers E, Mi J, et al. Cost-effectiveness of electricity energy efficiency programs. Cambridge, MA; 2011. Report No.: 17556.
Granderson J, Touzani S, Fernandes S, Taylor C. Application of automated measurement and verification to utility energy efficiency program data. Energy and Buildings [Internet]. 2017;142(Supplement C):191–9. Available from: http://www.sciencedirect.com/science/article/pii/S0378778817300294
Malm E. An Actions-Based estimate of the free rider fraction in electric utility DSM programs. Energy J [Internet]. Int Assoc Energy Econ. 1996;17(3):41–8. Available from: http://www.jstor.org/stable/41322692
Greening LA, Greene DL, Difiglio C. Energy efficiency and consumption—the rebound effect—a survey. Energy Policy [Internet]. 2000;28(6–7):389–401. Available from: http://www.sciencedirect.com/science/article/pii/S0301421500000215. https://doi.org/10.1016/S0301-4215(00)00021-5.
Nadel S. The potential for additional energy efficiency savings including how the rebound effect could affect this potential. Curr Sustain Renew Energy Rep [Internet]. 2016;3(1):35–41. https://doi.org/10.1007/s40518-016-0044-2.
Heinzle SL. Disclosure of energy operating cost information: a silver bullet for overcoming the energy-efficiency gap? J Consum Policy [Internet]. Dordrecht, Netherlands, Dordrecht; 2012;35(1):43–64. Available from: http://www.library.gatech.edu:2048/login?url=http://search.proquest.com/docview/922368369?accountid=11107.
Bertrand M, Karlan D, Mullainathan S, Shafir E, Zinman J. What’s advertising content worth? Evidence from a consumer credit marketing field experiment*. Q J Econ [Internet]. 2010;125(1):263–306. https://doi.org/10.1162/qjec.2010.125.1.263.
Abrahamse W, Steg L, Vlek C, Rothengatter T. The effect of tailored information, goal setting, and tailored feedback on household energy use, energy-related behaviors, and behavioral antecedents. J Environ Psychol [Internet]. 2007;27(4):265–76. Available from: http://www.sciencedirect.com/science/article/pii/S0272494407000540. https://doi.org/10.1016/j.jenvp.2007.08.002.
Abrahamse W, Steg L, Vlek C, Rothengatter T. A review of intervention studies aimed at household energy conservation. J Environ Psychol [Internet]. 2005;25(3):273–91. Available from: http://www.sciencedirect.com/science/article/pii/S027249440500054X. https://doi.org/10.1016/j.jenvp.2005.08.002.
•• Allcott H, Mullainathan S. Behavior and energy policy. Science [Internet]. 2010;327(5970):1204 LP-1205. Available from: http://science.sciencemag.org/content/327/5970/1204.abstract. This article provides a brief review of the findings from behavioral research and the application (both pilot projects and large-scale projects) of behavioral nudges on energy efficiency.
NC Clean Energy Technology Center. Database of State Incentives for Renewables & Efficiency (DSIRE). 2017.
• Palmer KL, Grausz S, Beasley B, Brennan TJ. Putting a floor on energy savings: comparing state energy efficiency resource standards. Util Policy [Internet]. 2013;25(Supplement C):43–57. Available from: http://www.sciencedirect.com/science/article/pii/S0957178713000180. This review summarizes the design of EERS policies and the challenges and issues with implementation.
Thoyre A. Energy efficiency as a resource in state portfolio standards: lessons for more expansive policies. Energy Policy [Internet]. 2015;86(Supplement C):625–34. Available from: http://www.sciencedirect.com/science/article/pii/S0301421515300598
Molina M, Kushler M. Policies matter: creating a foundation for an energy-efficient utility of the future. American Council for an Energy-Efficient Economy. Washington D.C.; 2015.
Satchwell A, Cappers P, Goldman C. Carrots and sticks: a comprehensive business model for the successful achievement of energy efficiency resource standards. Util Policy [Internet]. 2011;19(4):218–25. Available from:http://www.sciencedirect.com/science/article/pii/S0957178711000531. https://doi.org/10.1016/j.jup.2011.07.004.
Baumol WJ, Klevorick AK. Input choices and rate-of-return regulation: an overview of the discussion. The Bell Journal of Economics and Management Science [Internet]. [Wiley, RAND Corporation]; 1970;1(2):162–90. Available from: http://www.jstor.org/stable/3003179.
Kihm S. When revenue decoupling will work … and when it won’t. Electr J [Internet]. 2009;22(8):19–28. Available from: http://www.sciencedirect.com/science/article/pii/S1040619009002176. https://doi.org/10.1016/j.tej.2009.08.002.
Nowak S, Baatz B, Gilleo A, Kushler M, Molina M, York D. Beyond carrots for utilities: a national review of performance incentives for energy efficiency. American Council for an Energy-Efficient Economy. Report Number U1504. Washington D.C.; 2015.
Nissen W, Williams S. The link between decoupling and success in utility-led energy efficiency. Electr J [Internet]. 2016;29(2):59–65. Available from: http://www.sciencedirect.com/science/article/pii/S1040619016300070. https://doi.org/10.1016/j.tej.2016.02.003.
• Brown MA, Staver B, Smith AM, Sibley J. Alternative business models for energy efficiency: emerging trends in the Southeast. Electr J [Internet]. 2015;28(4):103–17. Available from: http://www.sciencedirect.com/science/article/pii/S1040619015000664. This study examines the utility business model for energy efficiency in regulated market and the impacts on consumer benefits.
Karier T. Why some utilities hate energy efficiency. Electr J [Internet]. 2016;29(2):7–11. Available from: http://www.sciencedirect.com/science/article/pii/S1040619016300021. https://doi.org/10.1016/j.tej.2016.01.008.
Miller R, Golab L, Rosenberg C. Modelling weather effects for impact analysis of residential time-of-use electricity pricing. Energy Policy [Internet]. 2017;105(Supplement C):534–46. Available from: http://www.sciencedirect.com/science/article/pii/S0301421517301568
Faruqui A, Sergici S. Household response to dynamic pricing of electricity: a survey of 15 experiments. J Regul Econ [Internet]. 2010;38(2):193–225. https://doi.org/10.1007/s11149-010-9127-y.
Nilsson A, Stoll P, Brandt N. Assessing the impact of real-time price visualization on residential electricity consumption, costs, and carbon emissions. Resour Conserv Recycl [Internet]. 2017;124(Supplement C):152–61. Available from: http://www.sciencedirect.com/science/article/pii/S0921344915301051
Nezamoddini N, Wang Y. Real-time electricity pricing for industrial customers: survey and case studies in the United States. Appl Energy [Internet]. 2017;195(Supplement C):1023–37. Available from: http://www.sciencedirect.com/science/article/pii/S0306261917303458
Salies E. Real-time pricing when some consumers resist in saving electricity. Energy Policy [Internet]. 2013;59(Supplement C):843–9. Available from: http://www.sciencedirect.com/science/article/pii/S0301421513003030
Campillo J, Dahlquist E, Wallin F, Vassileva I. Is real-time electricity pricing suitable for residential users without demand-side management? Energy [Internet]. 2016;109(Supplement C):310–25. Available from: http://www.sciencedirect.com/science/article/pii/S0360544216305187
Farrokhifar M, Momayyezi F, Sadoogi N, Safari A. Real-time based approach for intelligent building energy management using dynamic price policies. Sustain Cities Soc [Internet]. 2018;37(Supplement C):85–92. Available from: http://www.sciencedirect.com/science/article/pii/S2210670717302676
Brown MA, Zhou S. Smart-grid policies: an international review. Wiley Interdiscip Rev: Energy Environ. 2013;2(2):121–39. https://doi.org/10.1002/wene.53.
Evans M, Roshchanka V, Graham P. An international survey of building energy codes and their implementation. J Cleaner Prod [Internet]. 2017;158(Supplement C):382–9. Available from: http://www.sciencedirect.com/science/article/pii/S0959652617300057
Nair G, Allard I, Åstrand A, Olofsson T. Building professionals’ views on energy efficiency compliance requirements. Energy Procedia [Internet]. 2017;132(Supplement C):988–93. Available from: http://www.sciencedirect.com/science/article/pii/S1876610217348440
Macit İlal S, Günaydın HM. Computer representation of building codes for automated compliance checking. Autom Constr [Internet]. 2017;82(Supplement C):43–58. Available from: http://www.sciencedirect.com/science/article/pii/S0926580517305289
Mauer J, Dimascio M. States go first: how states can save consumers money , reduce energy and water waste , and protect the environment with new appliance standards. Appliance Standards Awareness Project and American Council for an Energy-Efficient Economy. Report Number A1702. Washington D.C.; 2017.
Fensel A, Tomic DK, Koller A. Contributing to appliances’ energy efficiency with Internet of Things, smart data and user engagement. Futur Gener Comput Syst [Internet]. 2017;76(Supplement C):329–38. Available from: http://www.sciencedirect.com/science/article/pii/S0167739X16306653
AlFaris F, Juaidi A, Manzano-Agugliaro F. Intelligent homes’ technologies to optimize the energy performance for the net zero energy home. Energy Buildings [Internet]. 2017;153(Supplement C):262–74. Available from: http://www.sciencedirect.com/science/article/pii/S0378778817309477
Johnson K, Willoughby G, Shimoda W, Volker M. Lessons learned from the field: key strategies for implementing successful on-the-bill financing programs. Energy Effic [Internet]. 2012;5(1):109–19. https://doi.org/10.1007/s12053-011-9109-7.
Bird S, Hernández D. Policy options for the split incentive: increasing energy efficiency for low-income renters. Energy Policy [Internet]. 2012;48(Supplement C):506–14. Available from: http://www.sciencedirect.com/science/article/pii/S0301421512004661
Pérez-Lombard L, Ortiz J, González R, Maestre IR. A review of benchmarking, rating and labelling concepts within the framework of building energy certification schemes. Energy Buildings [Internet]. 2009;41(3):272–8. Available from: http://www.sciencedirect.com/science/article/pii/S037877880800220X. https://doi.org/10.1016/j.enbuild.2008.10.004.
Mills E, Bourassa NJ, Rainer LI, Homan G, Merket N, Parker D, et al. Asset rating with the home energy scoring tool. Energy Buildings [Internet]. 2014;80(Supplement C):441–50. Available from: http://www.sciencedirect.com/science/article/pii/S0378778814004484
Institute of Market Transformation. Building Energy Performance Policy. Available from: http://www.imt.org/policy/building-energy-performance-policy. Accessed 12 Dec 2017.
Li H, Carrión-Flores CE. An analysis of the ENERGY STAR® program in Alachua County, Florida. Ecol Econ [Internet]. 2017;131(Supplement C):98–108. Available from: http://www.sciencedirect.com/science/article/pii/S092180091530505X
Zhao D, McCoy A, Du J. An empirical study on the energy consumption in residential buildings after adopting green building standards. Procedia Eng [Internet]. 2016;145(Supplement C):766–73. Available from: http://www.sciencedirect.com/science/article/pii/S1877705816301059
Zhang L, Li Y, Stephenson R, Ashuri B. Valuation of energy efficient certificates in buildings. Energy Buildings [Internet]. 2017; Available from: http://www.sciencedirect.com/science/article/pii/S0378778817323241.
Bruegge C, Carrión-Flores C, Pope JC. Does the housing market value energy efficient homes? Evidence from the energy star program. Reg Sci Urban Econ [Internet]. 2016;57(Supplement C):63–76. Available from: http://www.sciencedirect.com/science/article/pii/S016604621500109X
U.S. Energy Information Administration. State Energy Data System [Internet]. 2017 [cited 2017 Feb 1]. Available from: http://www.eia.gov/state/seds/.
Bell E, Blundell M, Ciccone A, Cummings T. California statewide critical peak pricing evaluation. Demand response measurement and evaluation committe (DRMEC) load impact workshop. California Public Utilities Commission; 2017. p. 1–19.
California Energy Commission. Energy Efficiency Comparison: California’s 2016 Building Energy Efficiency Standards and ASHRAE/IESNA Standard 90.1–2013 [Internet]. 2017. Available from: http://www.energy.ca.gov/business_meetings/2016_packets/2016-09-14/Item_05/Item_05.pdf.
California Energy Commission. Energy Efficiency Comparison: California’s 2016 Building Energy Efficiency Standards and International Energy Conservation Code - 2015. 2017.
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Yu Wang is a section editor for Current Sustainable/Renewable Energy Reports. She declares no other conflicts of interest.
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Wang, Y. Overview of State Policies for Energy Efficiency in Buildings. Curr Sustainable Renewable Energy Rep 5, 101–108 (2018). https://doi.org/10.1007/s40518-018-0100-1
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DOI: https://doi.org/10.1007/s40518-018-0100-1