Developing an Optimization Method for Bidding Strategies in an Open Electricity Market

Deregulation of power sector has highly maximized competition of market by reforming conventionally integrated utility of power into competitive EM. Purpose of this research is to develop an optimization method by combining the genetic algorithm, adaptive metropolis search, particle swarm optimization and differential evolution methods for strategy of optimal bidding in an open electricity market. Maximum profit for power exchange and optimal result has been obtained with minimum convergence with the proposed algorithm. Developed algorithm gives much faster convergence of the optimal result Further the proposed algorithm can be expanded for complicated power system issue of optimization under deregulated environment. 