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Money for Nothing? Why FERC Order 745 Should have Died

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  • Xu Chen and Andrew N. Kleit

Abstract

Customer baseline load (CBL) measurement is designed to represent participants' expected usage in a number of electricity demand response (DR) programs. Our empirical results, however, show that CBLs can be systematically higher than DR participants' estimated load, especially for those experienced in DR activities, likely due to manipulation behaviors. Thus, the integrity of CBL may degrade over time. With an inflated CBL, the impact of DR programs may therefore be highly exaggerated, and consumers can be paid money when they are not actually reducing their demand. In particular, we design a manipulation-indicating variable "seemingly unattractive free-money opportunity" (SUFO) and discover system-wide manipulative behaviors that increase with time and are widely adopted by experienced DR participants. We suggest that policy makers in FERC, RTOs, and states regulatory agencies consider the threat of manipulation when modifying DR market rules following the abolishment of FERC Order 745.

Suggested Citation

  • Xu Chen and Andrew N. Kleit, 2016. "Money for Nothing? Why FERC Order 745 Should have Died," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    • Handle: RePEc:aen:journl:ej37-2-chen
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    References listed on IDEAS

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    Cited by:

    1. Ottavia Valentini & Nikoleta Andreadou & Paolo Bertoldi & Alexandre Lucas & Iolanda Saviuc & Evangelos Kotsakis, 2022. "Demand Response Impact Evaluation: A Review of Methods for Estimating the Customer Baseline Load," Energies, MDPI, vol. 15(14), pages 1-36, July.
    2. Tim Schittekatte & Valerie Reif & Leonardo Meeus, 2021. "Welcoming New Entrants into European Electricity Markets," Energies, MDPI, vol. 14(13), pages 1-20, July.
    3. Goulden, Murray & Spence, Alexa & Wardman, Jamie & Leygue, Caroline, 2018. "Differentiating ‘the user’ in DSR: Developing demand side response in advanced economies," Energy Policy, Elsevier, vol. 122(C), pages 176-185.
    4. Lambin, Xavier, 2020. "Integration of Demand Response in Electricity Market Capacity Mechanisms," Utilities Policy, Elsevier, vol. 64(C).
    5. Gabaldón, A. & García-Garre, A. & Ruiz-Abellón, M.C. & Guillamón, A. & Álvarez-Bel, C. & Fernandez-Jimenez, L.A., 2021. "Improvement of customer baselines for the evaluation of demand response through the use of physically-based load models," Utilities Policy, Elsevier, vol. 70(C).
    6. Stede, Jan & Arnold, Karin & Dufter, Christa & Holtz, Georg & von Roon, Serafin & Richstein, Jörn C., 2020. "The role of aggregators in facilitating industrial demand response: Evidence from Germany," Energy Policy, Elsevier, vol. 147(C).
    7. Cédric Clastres & Haikel Khalfallah, 2021. "Dynamic pricing efficiency with strategic retailers and consumers: An analytical analysis of short-term market interactions," Post-Print hal-03193212, HAL.
    8. Saebi, Javad & Ghasemi, Abolfazl & Hojjat, Mehrdad, 2022. "Design and implementation of a competitive framework for a day-ahead demand-response program in Iran," Utilities Policy, Elsevier, vol. 77(C).
    9. Cédric Clastres & Haikel Khalfallah, 2020. "Retailers' strategies facing demand response and markets interactions," Working Papers hal-03167543, HAL.
    10. Iliopoulos, Nikolaos & Esteban, Miguel & Kudo, Shogo, 2020. "Assessing the willingness of residential electricity consumers to adopt demand side management and distributed energy resources: A case study on the Japanese market," Energy Policy, Elsevier, vol. 137(C).
    11. Clastres, Cédric & Khalfallah, Haikel, 2021. "Dynamic pricing efficiency with strategic retailers and consumers: An analytical analysis of short-term market interactions," Energy Economics, Elsevier, vol. 98(C).
    12. Dahlke, Steven & Prorok, Matt, 2018. "Consumer savings, price, and emissions impacts of increasing demand response in the Midcontinent electricity market," OSF Preprints d83bu, Center for Open Science.
    13. Fu, Xueqian & Zhang, Xiurong & Qiao, Zheng & Li, Gengyin, 2019. "Estimating the failure probability in an integrated energy system considering correlations among failure patterns," Energy, Elsevier, vol. 178(C), pages 656-666.

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