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Price computation in electricity auctions with complex rules: An analysis of investment signals

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  • Vazquez, Carlos
  • Hallack, Michelle
  • Vazquez, Miguel

Abstract

This paper discusses the problem of defining marginal costs when integer variables are present, in the context of short-term power auctions. Most of the proposals for price computation existing in the literature are concerned with short-term competitive equilibrium (generators should not be willing to change the dispatch assigned to them by the auctioneer), which implies operational-cost recovery for all of the generators accepted in the auction. However, this is in general not enough to choose between the different pricing schemes. We propose to include an additional criterion in order to discriminate among different pricing schemes: prices have to be also signals for generation expansion. Using this condition, we arrive to a single solution to the problem of defining prices, where they are computed as the shadow prices of the balance equations in a linear version of the unit commitment problem. Importantly, not every linearization of the unit commitment is valid; we develop the conditions for this linear model to provide adequate investment signals. Compared to other proposals in the literature, our results provide a strong motivation for the pricing scheme and a simple method for price computation.

Suggested Citation

  • Vazquez, Carlos & Hallack, Michelle & Vazquez, Miguel, 2017. "Price computation in electricity auctions with complex rules: An analysis of investment signals," Energy Policy, Elsevier, vol. 105(C), pages 550-561.
  • Handle: RePEc:eee:enepol:v:105:y:2017:i:c:p:550-561
    DOI: 10.1016/j.enpol.2017.02.003
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    References listed on IDEAS

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    2. Eldridge, B. & O’Neill, R. & Hobbs, B., 2018. "Pricing in Day-Ahead Electricity Markets with Near-Optimal Unit Commitment," Cambridge Working Papers in Economics 1872, Faculty of Economics, University of Cambridge.
    3. Chris Johnathon & Ashish Prakash Agalgaonkar & Joel Kennedy & Chayne Planiden, 2021. "Analyzing Electricity Markets with Increasing Penetration of Large-Scale Renewable Power Generation," Energies, MDPI, vol. 14(22), pages 1-15, November.
    4. Mays, Jacob & Morton, David P. & O’Neill, Richard P., 2021. "Investment effects of pricing schemes for non-convex markets," European Journal of Operational Research, Elsevier, vol. 289(2), pages 712-726.
    5. Hansol Shin & Tae Hyun Kim & Kyuhyeong Kwag & Wook Kim, 2021. "A Comparative Study of Pricing Mechanisms to Reduce Side-Payments in the Electricity Market: A Case Study for South Korea," Energies, MDPI, vol. 14(12), pages 1-19, June.
    6. Vazquez, Miguel & Hallack, Michelle, 2018. "The role of regulatory learning in energy transition: The case of solar PV in Brazil," Energy Policy, Elsevier, vol. 114(C), pages 465-481.
    7. Brito-Pereira, Paulo & Rodilla, Pablo & Mastropietro, Paolo & Batlle, Carlos, 2022. "Self-fulfilling or self-destroying prophecy? The relevance of de-rating factors in modern capacity mechanisms," Applied Energy, Elsevier, vol. 314(C).
    8. Villalobos, Cristian & Negrete-Pincetic, Matías & Figueroa, Nicolás & Lorca, Álvaro & Olivares, Daniel, 2021. "The impact of short-term pricing on flexible generation investments in electricity markets," Energy Economics, Elsevier, vol. 98(C).

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