Game theoretic approach for generation capacity expansion in restructured power markets

With a significant number of states in the U.S. trading electricity in restructured markets, a significant proportion of capacity expansion in the future will have to take place in market based environments. However, since a majority of the literature on capacity expansion is focused on regulated market structures, there is a critical need for comprehensive multiperiod, multi-player, capacity expansion models. In this research, we present a 3-tier game theoretic model to obtain multi-period, multi-player equilibrium capacity expansion plans, while considering several relevant market features. We will develop a reinforcement learning based approach to obtain the model solution. The model will be tested on sample power networks and benchmarked using data from a currently restructured electricity market.