Chance-Constrained Equilibrium in Electricity Markets With Asymmetric Forecasts

Vladimir Dvorkin, Jalal Kazempour, Pierre Pinson

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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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 - Virtual platform, Liege , Belgium
Duration: 18 Aug 202021 Aug 2020
http://aimontefiore.org/PMAPS2020/

Conference

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

Keywords

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

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