Power system reactive power optimization based on improved PSO

In order to improve optimize performance of basic particle swarm optimization (PSO), a new improved PSO algorithm is presented. In this paper, the mechanisms of bee evolution and inherit selection are involved into particle swarm optimization. At the optimization prophase, the bee evolution particle swarm optimization is adopted in order to enhance the whole optimization ability and increase the diversity of particles. At the optimization anaphase, the inherit selection particle swarm optimization is adopted in order to improve the convergence speed. The improved PSO algorithm is used to the IEEE14 node system and the Daqing real power system, the reactive power optimization result shows that the improved PSO has the better global convergence and the quickly convergence speed compare with other optimization algorithms. It also shows that it's a successful and feasible approach for reactive power optimization.