Stochastic cournot model for wind power trading in electricity markets

Kailash Chand Sharma, Rohit Bhakar, Narayana Prasad Padhy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)
186 Downloads (Pure)

Abstract

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
PublisherIEEE
DOIs
Publication statusPublished - 29 Oct 2014
EventPES General Meeting/ Conference & Exposition, 2014 IEEE - National Harbor, USA United States
Duration: 27 Jul 201431 Jul 2014

Conference

ConferencePES General Meeting/ Conference & Exposition, 2014 IEEE
CountryUSA United States
CityNational Harbor
Period27/07/1431/07/14

Keywords

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

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