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.