Reconfiguration Of Distribution Networks Of The Genetic Algorithm Based On Particle Swarm Cloning

Distribution network reconfiguration is an important method of optimizing the distribution system, which is significant to enhance the security, the efficiency and the reliability of the system.To resolve mutation probability and slow later-period convergence in the clonal genetic algorithm (CGA), this paper combines the particle swarm algorithm (PSO) with it, and proposes the particle clonal genetic algorithm (PCGA). It builds PSO mutation operator, and makes up premature convergence of PSO and blindness of CGA. It ensures evolution direction and range based on historical records and swarm records. Global optimal solution is found with fewer generations and shorter time. According to distribution network characteristic, initial swarm, code strategy and conditions of convergence of PCGA are optimized. The cause of infeasible solutions of distribution network reconfiguration is analyzed, and the method to eliminate infeasible solutions of the both loop and trip loop is given.Besides, this paper adopts list data structure of adapting distribution network, accomplishes topology identification based on layer of traversal sort and backward/forward flow algorithm. Distribution network reconfiguration operation interface is design using GUI of MATLAB. Using IEEE standard examples, this paper separately takes the minimum network loss and the maximum power reliability as the objective functions, and reconfigures the normal and interrupted distribution network. The simulation results indicate that PCGA with application to distribution network reconfiguration can not only avoid slow running rate of CGA and precocity of PSO, eliminate infeasible solutions during search process, and improve convergence capability, but also have higher search efficiency and calculation rate than other methods.