Profit-Based Unit Commitment Problem Using PSO with Modified Dynamic Programming

This paper proposes a hybrid approach utilizing particle swarm optimization along with dynamic programming to solve unit commitment problem based on the profit under the deregulated power market. In the deregulated market, power and reserve prices are important factors in the decision process for unit commitment scheduling and offer freedom to utilities to schedule their generators to produce less than predicted load as well as reserve to maximize their profit. To solve the profit based unit commitment problem (PBUCP), the model is divided into exterior and interior dependent sub problems, which are discrete and continuous, respectively. The proposed model helps GENCOs to make a decision, how much power and reserve that must be put up for sale in the market, and how to schedule generators in order to receive the maximum profit. GENCOs with 3 and 10 generating units are used to demonstrate the effectiveness of the proposed approach.