电网故障发生后,调度人员要在尽可能短的时间内准确判断故障情况,迅速给出最优调度措施。因此电网发生故障后,如何进行网络最优化重构,保证停电区域的电力供应,同时又不影响非停电区域的过负荷则成为配网运行的一项重大课题。电力系统故障恢复需要多目标规划,而故障后配网重构是一个多目标、多约束、离散寻优问题,常规方法不能有效地解决此问题。遗传算法(GA)以其良好的稳定性、灵活性、通用性,以及特别适合组合 After the grid failure, dispatchers should accurately determine the fault conditions in the shortest time possible and quickly give the optimal scheduling measures. Therefore, after the grid fails, how to optimize the network reconfiguration to ensure the power supply in the power failure area without affecting the over-load in the non-power-failure area has become a major issue for distribution network operation. Multi-objective planning is needed for power system fault recovery. However, post-fault network reconfiguration is a multi-objective, multi-constrained and discrete optimization problem. Conventional methods can not effectively solve this problem. Genetic algorithm (GA) with its good stability, flexibility, versatility, and particularly suitable for combination