Reactive power optimization based on an improved quantum discrete PSO algorithm

The function of reactive power optimization (RPO)is to realize the reactive power of the electric fence and optimal control of voltage in order that the whole network's operation level can be improved and the loss of operation of power network can be reduced. Recently, the research of ORP is mainly focus on the handling of non-liner function and discrete variables and the convergence of the algorithm, which is the key and difficult point of the current research. quantum discrete PSO algorithm, which is applied to reactive power and voltage optimization control of electric power system, has great effect of searching relevance and coverage. However, the premature convergence problem will be appeared probably. In order to prevent some stagnations of the particles in the iteration, a method to improve quantum discrete particle swarm optimization(quantum discrete PSO)is proposed in this paper. Combined with the quantum discrete PSO Algorithm and chaotic optimization method, the global optimal positions which are found in the iteration of the quantum discrete PSO can reach the chaos optimization. By this, the result is randomly substituted for the position of a particle and continued iteration. The simulation results of some IEEE systems and an actual power network show that the method is characterized by the convergent speed greatly and good global search capability.