A Game Theory Strategy-Based Bidding Evaluation for Power Generation Market

In a deregulated power market, the economical-risk due to real-time pricing is critical as it is not permitted to alter the decisions taken once. The existing generation market needs improvement in terms of enhancing its effectiveness and reliability. This article presents a game-theoretic approach-based bidding strategy decision-making through a case study. In this case, three thermal generating units feed three different constant loads for base load demand, one at a time. The economic load dispatch has been obtained using MATLAB software applying the particle swarm optimization (PSO) method. Three different bidding strategies for individual generators have been chosen to create 27 combinations to create data where the zero-sum game theory is applied. The marginal costs are calculated for each of the 27 combinations to formulate a game theory matrix. The game theory dominance method is then applied to obtain the market clearing price (MCP). The proposed methodology can help the GENCOs in making a profit or reducing the risk of making a loss by making a judicious selection among the possible available strategies.