Nash-equilibrium electricity portfolios in the smart grid: A genetic annealing solution

Abstract

To leverage the potential of bilateral contracts in the smart grid, we address the conflict-of-interest problem of designing energy portfolios. From the viewpoint of competing Utility companies, we present a game theoretical formulation for contract offering with integration of wind energy. We propose a heuristic algorithm, the Recursive Genetic Annealing algorithm (RGAn), to find the Nash-Equilibrium solution, that is, the best trade-off between cost and uncertainty. To hedge the portfolios, we model the decision making process as a non-cooperative game. Expected Utility theory is used to define the minimum cost energy mix. We show the RGAn outperforms the genetic algorithm.