Stochastic cournot model for wind power trading in electricity markets

Kailash Chand Sharma, Rohit Bhakar, Narayana Prasad Padhy

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

11 Citations (SciVal)
233 Downloads (Pure)


In evolving electricity markets, wind generators would submit bids to the system operator, with an aim to maximize their profits. Generation offered by wind firms is highly random, which may result into heavy imbalance charges. In markets dominated by wind generators, they would optimize their offered bids, considering rival behavior. In oligopolistic electricity markets, this strategic behavior can be represented as a Stochastic Cournot model. Wind uncertainty is represented by scenarios generated using Auto Regressive Moving Average (ARMA) model. With a consideration of wind power uncertainty and imbalance cost, the expected profit of generators is calculated for a practical case study of wind firms located at Massachusetts, USA. Nash equilibrium is obtained using payoff matrix approach. This bidding strategy mechanism offers quantum increase in profit for wind firms, when their behavior is modeled in a game theoretic framework. Flexibility of approach offers opportunities for its extension to associated challenges.

Original languageEnglish
Title of host publicationPES General Meeting/Conference & Exposition, 2014 IEEE
Publication statusPublished - 29 Oct 2014
EventPES General Meeting/ Conference & Exposition, 2014 IEEE - National Harbor, USA United States
Duration: 27 Jul 201431 Jul 2014


ConferencePES General Meeting/ Conference & Exposition, 2014 IEEE
Country/TerritoryUSA United States
CityNational Harbor


  • Electricity markets
  • Nash equilibrium
  • Stochastic cournot model
  • Wind power uncertainty


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