Reactive power optimization based on PSO in a practical power system

This paper presents a particle swarm optimization (PSO) method to deal with reactive power optimization problem in a province power system in China. The objective the optimization problem is to minimize the real power losses whilst maintaining acceptable voltage profiles. Particle swarm optimization, a new evolutionary computation method, relieves the derivative assumptions of objective function and deals with continuous and discrete variables conveniently. The effects of PSO parameters, such as inertia weight, learning factors and population size have been empirically studied. The successful application to the practical Heilongjiang power system indicates the possibility of PSO as a practical tool for various optimization problems in power system.