Improved MICROPSO Algorithm and Its Application on Reactive Power Optimization

In this paper, micro-particle swarm optimizer (MICROPSO) is improved and applied on the reactive power optimization problem. Self-adapted mutation operator is introduced in MICROPSO. For self-adapted mutation operator, mutation ratio is inverse-proportional to the fitness. So particles with worse fitness have higher mutation probability, and the algorithm can evolve. The self-adapted mutation operator keeps diversity of the particles. Simulation results on reactive power optimization of IEEE 30 system show that the solution of improved micro-particle swarm optimizer (IMICROPSO) with 4 particles is even better than standard PSO (SPSO) and MICROPSO with 30 particles. The advantage becomes more obvious with the population size enlarging.