DEVELOPMENT OF ELECTRICITY TRADING STRATEGIES UNDER NETA USING EVOLUTIONARY ALGORITHMS AND GAME THEORY

摘要

The energy crisis happening in California and problems emerging in other electricity power markets cross the world have led to more collusion and price tricks among energy companies and have motivated research into strategic gaming behaviors seen on power markets. Britain's power market trades physically and economically similar to that of California. Power generation companies in the U.K. make effort to attempt gaming strategies in trading. This paper explores a hybrid Game Theory and Evolutionary Computing method to study the possibility and impact of market manipulation in the U.K. power markets and hence to search for an optimal trading strategy for best profit.