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On the optimal design of demand response policies

Author

Listed:
  • David P. Brown

    (University of Alberta)

  • David E. M. Sappington

    (University of Florida)

Abstract

We characterize the optimal regulatory policy to promote efficient demand response (DR) in the electricity sector. DR arises when consumers reduce their purchases of electricity below historic levels at times when the utility’s marginal cost of supplying electricity is relatively high. The US Federal Energy Regulatory Commission (FERC) advocates compensation for DR that reflects the utility’s marginal cost. We show that the optimal policy often provides less generous compensation, and demonstrate that implementation of the FERC’s policy can reduce welfare well below the level secured by the optimal DR policy.

Suggested Citation

  • David P. Brown & David E. M. Sappington, 2016. "On the optimal design of demand response policies," Journal of Regulatory Economics, Springer, vol. 49(3), pages 265-291, June.
  • Handle: RePEc:kap:regeco:v:49:y:2016:i:3:d:10.1007_s11149-016-9297-3
    DOI: 10.1007/s11149-016-9297-3
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    1. David P. Brown & David E. M. Sappington, 2016. "On the optimal design of demand response policies," Journal of Regulatory Economics, Springer, vol. 49(3), pages 265-291, June.
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    10. Hung-po Chao, 2011. "Demand response in wholesale electricity markets: the choice of customer baseline," Journal of Regulatory Economics, Springer, vol. 39(1), pages 68-88, February.
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    Cited by:

    1. David P. Brown & David E. M. Sappington, 2017. "Optimal policies to promote efficient distributed generation of electricity," Journal of Regulatory Economics, Springer, vol. 52(2), pages 159-188, October.
    2. Tooraj Jamasb and Manuel Llorca, 2019. "Energy Systems Integration: Economics of a New Paradigm," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 2).
    3. David P. Brown & David E. M. Sappington, 2016. "On the optimal design of demand response policies," Journal of Regulatory Economics, Springer, vol. 49(3), pages 265-291, June.
    4. Celik, Berk & Roche, Robin & Suryanarayanan, Siddharth & Bouquain, David & Miraoui, Abdellatif, 2017. "Electric energy management in residential areas through coordination of multiple smart homes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 260-275.
    5. Vij, Akshay & Ryan, Stacey & Sampson, Spring & Harris, Susan, 2020. "Consumer preferences for on-demand transport in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 823-839.
    6. Ren'e Aid & Dylan Possamai & Nizar Touzi, 2018. "Optimal electricity demand response contracting with responsiveness incentives," Papers 1810.09063, arXiv.org, revised May 2019.
    7. Thakur, Jagruti & Chakraborty, Basab, 2016. "Demand side management in developing nations: A mitigating tool for energy imbalance and peak load management," Energy, Elsevier, vol. 114(C), pages 895-912.
    8. Zhang, Xiangyu & Pipattanasomporn, Manisa & Rahman, Saifur, 2017. "A self-learning algorithm for coordinated control of rooftop units in small- and medium-sized commercial buildings," Applied Energy, Elsevier, vol. 205(C), pages 1034-1049.

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    More about this item

    Keywords

    Electricity pricing; Demand response; Regulation;
    All these keywords.

    JEL classification:

    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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