Adaptive Particle Swarm Optimization Algorithm for Power System Reactive Power Optimization

Abstract

Aiming at the precocious convergence problem of particle swarm optimization algorithm, adaptive particle swarm optimization(APSO) algorithm was presented. In this algorithm, the notion of species was introduced into population diversity measure. The species technique is based on the concept of dividing the population into several species according to their similarity. The inertia weight was nonlinearly adjusted by using population diversity information at each iteration step. Velocity mutation operator and position crossover operator were both introduced and the global performance was clearly improved. The algorithm had been applied to reactive power optimization. The simulation results of the standard IEEE-30-bus power system had indicated that APSO was able to undertake global search with a fast convergence rate and a feature of robust computation. It was proved to be validity, fast convergence and computation efficiency during the reactive power optimization.