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Move it! How an electric contest motivates households to shift their load profile

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  • Weber, Sylvain
  • Puddu, Stefano
  • Pacheco, Diana

Abstract

Photovoltaic systems generate electricity around noon, when many homes are empty. Conversely, residential electricity demand peaks in the evening, when production from solar sources is impossible. Based on a randomized control trial, we assess the effectiveness of alternative demand response measures aimed at mitigating these imbalances. More precisely, through information feedback and financial rewards, we encourage households to shift electricity consumption toward the middle of the day. Using a difference-in-differences approach, we find that financial incentives induce a significant increase of the relative consumption during the period of the day when most solar radiation takes place. Information feedback, however, pushes households to decrease overall consumption, but induces no load shifting.

Suggested Citation

  • Weber, Sylvain & Puddu, Stefano & Pacheco, Diana, 2017. "Move it! How an electric contest motivates households to shift their load profile," Energy Economics, Elsevier, vol. 68(C), pages 255-270.
  • Handle: RePEc:eee:eneeco:v:68:y:2017:i:c:p:255-270
    DOI: 10.1016/j.eneco.2017.10.010
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    References listed on IDEAS

    as
    1. Chen, Victor L. & Delmas, Magali A. & Kaiser, William J. & Locke, Stephen L., 2015. "What can we learn from high-frequency appliance-level energy metering? Results from a field experiment," Energy Policy, Elsevier, vol. 77(C), pages 164-175.
    2. Valeria Di Cosmo, Sean Lyons, and Anne Nolan, 2014. "Estimating the Impact of Time-of-Use Pricing on Irish Electricity Demand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    3. Lynham, John & Nitta, Kohei & Saijo, Tatsuyoshi & Tarui, Nori, 2016. "Why does real-time information reduce energy consumption?," Energy Economics, Elsevier, vol. 54(C), pages 173-181.
    4. repec:ags:stataj:116069 is not listed on IDEAS
    5. Takanori Ida & Kayo Murakami & Makoto Tanaka, 2015. "Electricity demand response in Japan:Experimental evidence from a residential photovoltaic generation system," Discussion papers e-15-006, Graduate School of Economics Project Center, Kyoto University.
    6. Buchanan, Kathryn & Russo, Riccardo & Anderson, Ben, 2014. "Feeding back about eco-feedback: How do consumers use and respond to energy monitors?," Energy Policy, Elsevier, vol. 73(C), pages 138-146.
    7. Weber, Sylvain, 2010. "bacon: An effective way to detect outliers in multivariate data using Stata (and Mata)," Stata Journal, StataCorp LP, vol. 10(3), pages 1-8.
    8. Pina, André & Silva, Carlos & Ferrão, Paulo, 2012. "The impact of demand side management strategies in the penetration of renewable electricity," Energy, Elsevier, vol. 41(1), pages 128-137.
    9. Steinke, Florian & Wolfrum, Philipp & Hoffmann, Clemens, 2013. "Grid vs. storage in a 100% renewable Europe," Renewable Energy, Elsevier, vol. 50(C), pages 826-832.
    10. McCoy, Daire & Lyons, Seán, 2016. "Unintended Outcomes of Electricity Smart-metering: trading off consumption and investment behaviour," Papers RB2016/3/3, Economic and Social Research Institute (ESRI).
    11. Buchanan, Kathryn & Russo, Riccardo & Anderson, Ben, 2015. "The question of energy reduction: The problem(s) with feedback," Energy Policy, Elsevier, vol. 77(C), pages 89-96.
    12. repec:bpj:jecome:v:7:y:2018:i:1:p:16:n:9 is not listed on IDEAS
    13. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    14. ITO Koichiro & IDA Takanori & TANAKA Makoto, 2015. "The Persistence of Moral Suasion and Economic Incentives: Field experimental evidence from energy demand," Discussion papers 15014, Research Institute of Economy, Trade and Industry (RIETI).
    15. Kondziella, Hendrik & Bruckner, Thomas, 2016. "Flexibility requirements of renewable energy based electricity systems – a review of research results and methodologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 10-22.
    16. Katrina Jessoe & David Rapson, 2014. "Knowledge Is (Less) Power: Experimental Evidence from Residential Energy Use," American Economic Review, American Economic Association, vol. 104(4), pages 1417-1438, April.
    17. repec:cup:apsrev:v:89:y:1995:i:03:p:634-647_00 is not listed on IDEAS
    18. Denholm, Paul & Margolis, Robert M., 2007. "Evaluating the limits of solar photovoltaics (PV) in electric power systems utilizing energy storage and other enabling technologies," Energy Policy, Elsevier, vol. 35(9), pages 4424-4433, September.
    19. Delmas, Magali A. & Fischlein, Miriam & Asensio, Omar I., 2013. "Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012," Energy Policy, Elsevier, vol. 61(C), pages 729-739.
    20. Bartusch, Cajsa & Wallin, Fredrik & Odlare, Monica & Vassileva, Iana & Wester, Lars, 2011. "Introducing a demand-based electricity distribution tariff in the residential sector: Demand response and customer perception," Energy Policy, Elsevier, vol. 39(9), pages 5008-5025, September.
    21. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    22. repec:kap:enreec:v:67:y:2017:i:3:d:10.1007_s10640-016-0094-3 is not listed on IDEAS
    23. Hunt Allcott & Todd Rogers, 2014. "The Short-Run and Long-Run Effects of Behavioral Interventions: Experimental Evidence from Energy Conservation," American Economic Review, American Economic Association, vol. 104(10), pages 3003-3037, October.
    24. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, Oxford University Press, vol. 119(1), pages 249-275.
    25. David M. Drukker, 2003. "Testing for serial correlation in linear panel-data models," Stata Journal, StataCorp LP, vol. 3(2), pages 168-177, June.
    26. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    27. Halvorsen, Robert & Palmquist, Raymond, 1980. "The Interpretation of Dummy Variables in Semilogarithmic Equations," American Economic Review, American Economic Association, vol. 70(3), pages 474-475, June.
    28. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    29. Kempton, Willett & Layne, Linda L., 1994. "The consumer's energy analysis environment," Energy Policy, Elsevier, vol. 22(10), pages 857-866, October.
    30. Denholm, Paul & Hand, Maureen, 2011. "Grid flexibility and storage required to achieve very high penetration of variable renewable electricity," Energy Policy, Elsevier, vol. 39(3), pages 1817-1830, March.
    31. Mark Bernstein & Myles Collins, 2014. "Saving Energy Through Better Information: A New Energy Paradigm?," Contemporary Economic Policy, Western Economic Association International, vol. 32(1), pages 219-229, January.
    32. Brewer Mike & Crossley Thomas F. & Joyce Robert, 2018. "Inference with Difference-in-Differences Revisited," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-16, January.
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    Cited by:

    1. Bernadeta Gołębiowska & Anna Bartczak & Wiktor Budziński, 2019. "Impact of social comparison on DSM in Poland," Working Papers 2019-10, Faculty of Economic Sciences, University of Warsaw.

    More about this item

    Keywords

    Household electricity usage; Smart metering; Demand response; Randomized control trial; Difference-in-differences;

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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