A matrix game model for analyzing FTR bidding strategies in deregulated electric power markets

Suppliers in deregulated electric power markets compete for financial transmission rights (FTRs) to hedge against congestion charges. The system operator receives the bids for FTRs submitted by the suppliers and develops an allocation strategy by solving an optimization model. Each FTR bid is defined by a path, a quantity indicating the amount of FTRs the supplier is bidding for in that path, and the price that the supplier is willing to pay for each FTR. The FTR revenue is calculated only after the electricity market has been cleared by computing the differences in the LMPs at the pair of nodes that connect each path. Thus, suppliers rely on forecasts of locational marginal prices (LMPs) to develop their FTR bids. In this paper, we present a game theoretic modeling approach to develop FTR bidding strategies for power suppliers assuming that they have forecasts of LMPs. The game theoretic model considers multiple participants as well as network contingencies. We apply the game theoretic model on a sample network to assess impacts of variations of bid and network parameters on the FTR market outcome.