A co-evolutionary approach for optimal bidding strategy of multiple electricity suppliers

Abstract

Determining the optimal bidding strategies in a competitive electricity market has become an important research topic over the last few decades. In this paper, a supply function equilibrium game model is considered and formulated as a bilevel optimization problem, where the upper level is used to maximize the individual profit of each supplier and the lower one to minimize the overall operating cost. To solve this problem, a co-evolutionary approach is designed in which each supplier uses its own sub-population of a genetic algorithm to maximize its profit through a bidding strategy based on each of its generators' cost coefficients, while either a self-adaptive differential evolution or sequential quadratic programming is used to optimally allocate the generation of each supplier by minimizing the operation cost. To validate the results obtained from the proposed method, an iterative method is also used to solve the two well-known benchmarks in the literature. The results are compared with those from a state-of-art method in the literature which reveals that the co-evolutionary approach has some merits in terms of quality and reliability.