Reactive Power Optimization Based on Hybrid Particle Swarm Optimization Algorithm

Reactive power optimization in power system is a typical non-linear optimization problem with characteristics of multi-objective, multi-constrained, non-linear combination and discreteness. Conventional mathematical programming techniques are inadequate and insufficient to the optimal operation of power systems due to the inherent complexity. A solution to reactive power optimization of power system via an improved particle swarm optimization algorithm is presented. In order to increasing the amount of particles’ available information and the diversity of particles, the third extremely value is added to the optimal operation of power systems on the understanding of the differences of evolutionary; In the process of evolution, the selection factor of genetic algorithm is introduced, and improves the optimization of the characteristics of PSO. Case study on IEEE 14-bus, IEEE 30-bus and proves that the proposed algorithm has higher search efficiency and better capability of global optimization than standard PSO.