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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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    3. Sylwia Słupik & Joanna Kos-Łabędowicz & Joanna Trzęsiok, 2021. "How to Encourage Energy Savings Behaviours? The Most Effective Incentives from the Perspective of European Consumers," Energies, MDPI, vol. 14(23), pages 1-25, November.
    4. Matteo Caldera & Asad Hussain & Sabrina Romano & Valerio Re, 2023. "Energy-Consumption Pattern-Detecting Technique for Household Appliances for Smart Home Platform," Energies, MDPI, vol. 16(2), pages 1-23, January.
    5. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    6. Yilmaz, S. & Weber, S. & Patel, M.K., 2019. "Who is sensitive to DSM? Understanding the determinants of the shape of electricity load curves and demand shifting: Socio-demographic characteristics, appliance use and attitudes," Energy Policy, Elsevier, vol. 133(C).
    7. Brännlund, Runar & Vesterberg, Mattias, 2021. "Peak and off-peak demand for electricity: Is there a potential for load shifting?," Energy Economics, Elsevier, vol. 102(C).
    8. Wang, Peiguang & Zhang, Zhaoyan & Fu, Lei & Ran, Ning, 2021. "Optimal design of home energy management strategy based on refined load model," Energy, Elsevier, vol. 218(C).
    9. Andreolli, Francesca & D’Alpaos, Chiara & Moretto, Michele, 2022. "Valuing investments in domestic PV-Battery Systems under uncertainty," Energy Economics, Elsevier, vol. 106(C).
    10. Shen, Meng & Li, Xiang & Lu, Yujie & Cui, Qingbin & Wei, Yi-Ming, 2021. "Personality-based normative feedback intervention for energy conservation," Energy Economics, Elsevier, vol. 104(C).
    11. Azarova, Valeriya & Cohen, Jed J. & Kollmann, Andrea & Reichl, Johannes, 2020. "Reducing household electricity consumption during evening peak demand times: Evidence from a field experiment," Energy Policy, Elsevier, vol. 144(C).
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    13. 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.

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    More about this item

    Keywords

    Household electricity usage; Smart metering; Demand response; Randomized control trial; Difference-in-differences;
    All these keywords.

    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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