Game based strategic bidding in pay as bid markets considering incomplete information and risk factor

Abstract

The strategic bidding problem for generation companies (GENCOs) in a pay as bid market is considered with respect to risk analysis for different participant types, in which GENCOs suffer of lack of complete information about opponents bidding strategies. According to Iran power market characteristics, in which participants should declare their maximum available energy to the ISO, Bertrand model is adopted for strategic bidding in the power market. Then, by transforming incomplete data that each GENCO has from others, into complete information using Bayesian Nash equilibrium, a proper method are proposed considering the power market characteristics, for maximization of GENCOs' profit according to the other GENCOs' bidding behaviors and power system operating conditions. Because of uncertainty of sources in a power system such as strategic behavior of opponent GENCOs, demand fluctuations and forced outage of network components, calculation of equilibrium point is not enough in proper strategic bidding, so the problem utilized so that risk factor is taken into account. The method is tested on a partial system, including five GENCOs, and the numerical results showed in detail the efficiency of the modeling and the proposed method of bidding behavior for generation companies.