基于多种群遗传算法的含分布式电源的配电网 故障区段定位算法

构建了可动态适应多个分布式电源投切的开关函数，同时针对遗传算法的早熟收敛问题，引入多种群遗传算法，提出基于多种群遗传算法的含分布式电源配电网故障区段定位方法。该算法在故障区段定位时规定以系统电源指向用户的方向为馈线正方向，采用多个种群对解空间协同搜索，避免算法陷入局部最优，以最优个体保持代数作为收敛条件，充分提高收敛效率，适用于复杂的含分布式电源的配电网络。通过算例对配电网的故障定位进行仿真，结果表明算法能准确定位，并具有一定的有效性和容错性。

Fault-section location of distribution network containing distributed generation based on the multiple-population genetic algorithm

By building a new switching function which can dynamically adapt itself to the change caused by switching of distributed generation, the multiple-population genetic algorithm for fault-section location of distribution network containing distributed generation, which can avoid the premature convergence of standard genetic algorithm, is proposed. The proposed method is applicable to the complicated distribution network, and it determines the direction of the power of the system to the user as the positive direction when locates fault in distribution networks. Multiple-population collaboratively searches the solution space to avoid falling into local optimal, and the condition of convergence is the optimal individual keeping algebra, which improves convergence efficiency. The simulation results show that the proposed algorithm has the correctness of fault location, and is effective and fault tolerance.