PSO based social welfare maximization of wind thermal coordinated system in a deregulated power market

Abstract

This paper presents maximization of social welfare in a wind thermal coordinated, deregulated wholesale power market using Particle Swarm Optimization algorithm. As the real power demand is always variable in nature, power generators can be rescheduled to meet the demand with the objective of maximizing the social welfare. In the proposed approach, wind turbine speeds are generated for various values of demand and the generators are rescheduled accordingly with the objective of maximization of social welfare using Particle Swarm Optimization algorithm. The proposed method is tested on Modified WSCC-9 bus system, where one of the generators is treated as thermal unit while the other two generators are wind power generators. Simulations are done with MATLAB 10.0 version.