Behavioral energy feedback program evaluations: a survey of current knowledge and a call to action
- 253 Downloads
Behavioral-based energy efficiency programs are those that utilize strategies intended to influence consumer energy use behaviors to achieve energy and/or peak demand savings. These programs typically include outreach, education, competition, rewards, benchmarking, and/or feedback elements (Todd et al 2012). In North America, over 110 investor-owned utilities included behavior programs in 2012 as part of their energy efficiency portfolios, allocating 0.3 to 10 % of their efficiency portfolio spending to these programs. Emerging plans in Massachusetts allocated as much as 50 % of first year kilowatt hour goals to behavior programs in 2014. Despite the overwhelming growth in spending on these programs, there are many unanswered and important policy questions that must be addressed. This paper argues that the energy industry needs to go further than just assessing energy impacts to address existing gaps in knowledge and find ways to most effectively incorporate these programs into efficiency portfolios. First, the paper presents an overview of behavioral feedback program lessons learned from third party evaluations across North America. Next, a brief analysis of gaps in industry knowledge of how behavioral programs generate savings is provided. In the last section, policy- and planning-focused research questions that need to be answered as behavioral feedback programs mature are discussed. To date, there has been an overwhelming focus on impact evaluations, and there are many key questions that need to be addressed. Future evaluations must focus on both impact and policy questions by addressing existing gaps in knowledge about how behavioral programs generate energy savings and exploring the most effective ways to integrate these programs into program portfolios.
KeywordsEnergy efficiency Behavioral programs Energy feedback Behavior
Compliance with ethical standards
The authors acknowledge that this work has not been submitted to other journals nor has this content been previous published by a peer-reviewed journal.
Note this piece was requested due to its inclusion in the Internal Energy Program and Policy Conference’s proceedings and was delivered as a white paper.
We confirm that all information presented in this article has been appropriately cited and has presented accurately to the author’s knowledge.
- Dougherty & Schlegel (2014). http://aceee.org/files/pdf/conferences/eer/2013/5D-dougherty.pdf.
- Dougherty, A., Schlegel, J., & Schlegel, T. (2013). The promise and reality of behavior programs: are they a reliable resource? http://aceee.org/files/pdf/conferences/eer/2013/5D-dougherty.pdf.
- DNV KEMA. (2013). Puget sound energy’s home energy reports: 2012 impact evaluation. http://www2.opower.com/l/17572/2013-0822/bvhvt/17572/49288/22_Kema_PSE_2012_Year_4.pdf.
- DNV KEMA Inc. (2013). Review of PG&E home energy reports initiative evaluation (joint savings impact analysis). http://opower.com/company/library/verification-reports.
- Esource DSM Insights. (2014). https://www.esource.com/about-dsminsights.
- Freeman and Sullivan Co. (2013). Evaluation of pacific gas and electric company’s home energy report initiative for the 2010-2012 program. http://www.calmac.org/%5C%5C//publications/2012_PGE_OPOWER_Home_Energy_Reports__4-25-2013_CALMAC_ID_PGE0329.01.pdf.
- Goldman, M., & Dougherty, A. (2014) Integrating behavior programs into portfolio plans to encourage cross-program effects. ACEEE Summer Study on Energy Efficiency in Buildings. http://aceee.org/files/proceedings/2014/data/papers/7-683.pdf.
- Integral Analytics. (2012). Impact & persistence evaluation report: Sacramento municipal utility district home energy report program. http://www1.integralanalytics.com/files/documents/related-documents/FinalSMUDHERSEval2012v4.pdf.
- Illume Advising, LLC. (2014). Lake region MyMeter, wright-Hennepin MyMeter: MyMeter multi-utility impact findings. http://mymeter.co/VerifiedSavings/Index.
- Illume Advising, LLC. (2014). Integrating behavior programs into portfolio plans to encourage cross-program effects. http://static1.squarespace.com/static/51facfbce4b0608e4647adf5/t/55c35f39e4b05e733d69add7/1438867257146/Goldman%26Dougherty_2014.pdf.
- Illume Advising, LLC., Vine, E., Mazur-Stommen, S. (2015). Energy efficiency behavioral programs: literature review, benchmarking analysis, and evaluation guideline. St. Paul Minnesota. Minnesota Department of Commerce, Division of Energy Resources. https://www.cards.commerce.state.mn.us/CARDS/security/search.do?method=showPoup&documentId=%7b971F1044-CF64-41EA-A714-7AEF32F2255B%7d&documentTitle=213328&documentType=6.
- Mazur-Stommen, S., & K. Farley. (2013). ACEEE field guide to utility-run behavior programs. Report B132. Washington, DC. American Council for an Energy-Efficient Economy.Google Scholar
- Minnesota Department of Commerce, (2012). Docket No. E,G999/CI-08-133, on February 1, 2012, the division of energy resources staff (Staff) filed analysis, recommendations, and proposed decision (Proposed Decision) regarding the inclusion of behavioral project savings in energy conservation improvement programs (CIP) and Shared Savings Demand-Side Management (DSM) Financial Incentive calculations in order to better balance the allocation of utility program resources between asset-based and CIP programs.Google Scholar
- Navigant Consulting. (2014). C3-CUB energy saver program EPY5 evaluation report. http://ilsagfiles.org/SAG_files/Evaluation_Documents/ComEd/ComEd%20EPY5%20Evaluation%20Reports/ComEd_C3_EMV_Report_PY5_2014-01-21%20Final.pdf.
- Opinion Dynamics. National Grid, Cape Light Compact Energize & Cape Light Compact. (2013). ICES: Massachusetts cross-cutting behavioral program evaluation. http://www.rieermc.ri.gov/documents/2013%20Evaluation%20Studies/ODC_2013_Cross_Cutting_Behavioral_Program_Evaluation.pdf.
- Todd, A., Stuart, E., Schiller, S., & Goldman, C. (2012). State and local energy efficiency action network. 2012. Evaluation, measurement, and verification (EM&V) of residential behavior-based energy efficiency programs: issues and recommendations. Berkeley: Lawrence Berkeley National Laboratory.Google Scholar
- Todd, A., Li, M. (2014). Insights from smart meters: focus on persistence of savings from home energy reports. SEE Action Behavioral Webinar Series. http://www1.eere.energy.gov/seeaction/pdfs/webinar_behavior_based_energy_efficiency.pdf