Abstract

This paper proposes an oligopolistic model for a wind power producer (WPP) with a market power to compete with other Gencos and take part in day-ahead, intraday and balancing markets. In order to model the mentioned oligopoly markets from WPP's viewpoint, a bi-level optimization framework is proposed based on multi-agent system and incomplete information game theory. In this context, the WPP participates in the intraday market where demand response resources are incorporated, to update its day-ahead offers. The problem uncertainties, i.e., wind power and market prices, are considered using a multi-stage stochastic programming approach. Because of these uncertainties, a well-known risk measurement, CVaR, is considered for problem optimization. Several numerical studies are accomplished and various aspects of the problem are analyzed. According to the obtained results, the proposed WPP model reveals that the prices of day-ahead and balancing markets could be increased due to the market power of WPP.

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