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Strategic bidding for wind power producers in electricity markets
•Game theoretic bidding strategy approach developed to optimize wind power producers bids.•Rival behavior modeled through Stochastic Cournot model.•Location based dual imbalance price mechanism proposed to obtain imbalance charges.•Proposed approach evaluated using two realistic case studies.•Propos...
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Published in: | Energy conversion and management 2014-10, Vol.86, p.259-267 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Game theoretic bidding strategy approach developed to optimize wind power producers bids.•Rival behavior modeled through Stochastic Cournot model.•Location based dual imbalance price mechanism proposed to obtain imbalance charges.•Proposed approach evaluated using two realistic case studies.•Proposed approach increases profit of strategic wind power producers significantly.
In evolving electricity markets, wind power producers (WPPs) would increase their profit through strategic bidding. However, generated power by WPPs 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 day-ahead 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 charges, strategic WPPs can maximize their expected payoff or profit through the proposed Nash equilibrium based bidding strategy. Nash equilibrium is obtained using payoff matrix approach. Proposed approach is evaluated on two realistic case studies considering different technical constraints. Obtained results shows that proposed bidding strategy mechanism offers quantum increase in profit for WPPs, when their behavior is modeled in a game theoretic framework. Flexibility of approach offers opportunities for its extension to associated challenges. |
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ISSN: | 0196-8904 1879-2227 |
DOI: | 10.1016/j.enconman.2014.05.002 |