The Application of Hybrid Genetic Particle Swarm Optimization Algorithm in the Distribution Network Reconfigurations Multi-Objective Optimization

According to the single performance of most distribution network reconfigurations (DNR), this paper presents the multi-objective distribution network optimization model with the optimal network loss, load balancing, and power supply voltage. Combined with the evolution idea of genetic algorithm (GA) and population intellectual technique of particle swarm optimization (PSO) algorithm, it applies hybrid genetic particle swarm optimization algorithm (HGPSOA) to search the optimization. By the random-weighted method, it obtains the object that is the searching direction of Pareto front. During searching process, some individuals are iterated by PSO, the others follow the selection, crossover and mutation of GA, and the whole population information is shared by each agent. Simultaneously, it adopts the adaptive parameters mechanism and better fitness individuals surviving rules to evolve the population. Based on the above, distribution network optimization program can furthest enhance the security and the efficiency of distribution system, on the premise of ensuring that the distribution network is spokewise and also could satisfy heat capacity of feeder line, voltage reducing , transformer capacity and etc. Samples show that the algorithm has advantages both in effectiveness and efficiency.