Chance-Constrained Equilibrium in Electricity Markets With Asymmetric Forecasts

Vladimir Dvorkin, Jalal Kazempour, Pierre Pinson

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    Abstract

    We develop a stochastic equilibrium model for an electricity market with asymmetric renewable energy forecasts. In our setting, market participants optimize their profits using public information about a conditional expectation of energy production but use private information about the forecast error distribution. This information is given in the form of samples and incorporated into profit-maximizing optimizations of market participants through chance constraints. We model information asymmetry by varying the sample size of participants’ private information. We show that with more information available, the equilibrium gradually converges to the ideal solution provided by the perfect information scenario. Under information scarcity, however, we show that the market converges to the ideal equilibrium if participants are to infer the forecast error distribution from the statistical properties of the data at hand or share their private forecasts
    Original languageEnglish
    Title of host publicationProceedings of the 16th International Conference on Probabilistic Methods Applied to Power Systems
    Number of pages6
    PublisherIEEE
    Publication date2020
    ISBN (Print)978-1-7281-2822-1
    DOIs
    Publication statusPublished - 2020
    Event16th International Conference on Probabilistic Methods Applied to Power Systems - Online, Liege , Belgium
    Duration: 18 Aug 202021 Aug 2020
    Conference number: 16
    http://aimontefiore.org/PMAPS2020/

    Conference

    Conference16th International Conference on Probabilistic Methods Applied to Power Systems
    Number16
    LocationOnline
    Country/TerritoryBelgium
    CityLiege
    Period18/08/202021/08/2020
    Internet address

    Keywords

    • Chance-constrained programming
    • Equilibrium
    • Forecast asymmetry
    • Information asymmetry
    • Uncertainty

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