An Efficient Genetic Algorithm with Local Search Operator for Distribution Network Reconfiguration
Genetic algorithm (GA) is one of effective methods to solving distribution network reconfiguration (DNR), but it has the shortages of low converging speed and being premature readily and generating infeasible solutions. In order to improve the performance of GA solving DNR, an efficient genetic algorithm with local search operator (EGA) is proposed. The encoding method based on fundamental loop, small population, hyper-mutation and roulette selection operator with parent-offspring competition are adopted. A greedy local search operator is designed and is used after hyper-mutation operation is completed. Simulation results of IEEE 33-bus system and IEEE 69-bus system show that EGA conforms to the feature of distribution network reconfiguration and possesses fast convergence speed while the quantity of the solution is ensured. Comparing with conventional genetic algorithm (CGA) and allied algorithms in related literatures, EGA promises more excellent performance not only in convergence speed but also in quality of solution.
distribution network reconfiguration genetic algorithm selection operator with parent-offspring competition local search operator
Chao-xue Wang Li-li Dong Chang-hua Li Jing He
School of Information & Control Engineering Xian University of Architecture and Technology Xian 710055, China
国际会议
成都
英文
1333-1337
2010-12-17（万方平台首次上网日期，不代表论文的发表时间）