Improved Particle Swarm Optimization Algorithm in Power System Network Reconfiguration

With the rapid development of social economy, all circles places higher demands on electricity industry. As a fundamental industry supporting salvation national society, and human life, will face significant improvement restructuring network as an important part power system should also be optimised. This paper first introduces history swarm intelligence algorithm related research work at home abroad. Secondly, it puts forward importance particle optimization for reconfiguration expounds basic principle, essential characteristics, model algorithm. completes improving PSO through common improved methods introduction mutation operation tent mapping. In experimental simulation part, is used to simulate 10-machine 39-bus in IEEE, data are compared with chaos genetic discrete Through data, we can know that has least number actions switching times, only 4 5 times; other two algorithms, fastest convergence speed highest accuracy. The proposed this provides excellent solution significance subsequent improvement.