文章提出一种适用于有源配电网故障定位的多目标优化模型，采用带精英策略的非支配排序遗传算法(non-dominant sorting genetic algorithm with elite strategy,NSGA-II)进行优化求解。传统的有源配电网故障定位方法采用单目标优化模型进行求解，其目标函数由分目标函数加权而成，但权值选取不当会影响定位结果，导致误判或漏判。而基于Pareto最优概念的NSGA-II算法计算简单，能综合全局找到最优解，无需考虑权值的影响；最后，通过PSCAD搭建修正的IEEE33节点模型，分别从单一、多重故障两方面进行仿真，并考虑到智能终端单元信息误报的三种情况，分别进行仿真得到定位结果，将四种典型的故障情形分别用文章方法和基于标准遗传算法(standard genetic algorithm,SGA)的单目标优化模型进行对比，的通过对比发现，基于NSGA-II的多目标优化的故障定位方法在单一或多种类型信息误报情形下依然能够准确定位故障区段，可靠性高。
英文摘要:
This paper proposes a multi-objective optimization model suitable for fault location of active distribution network, and adopts the non-dominant sorting genetic algorithm with elite strategy (NSGA-II) for optimization solution.The traditional fault location method of active distribution network adopts the single objective optimization model to solve the problem, and its objective function is weighted by the sub-objective function.The NSGA-II based on Pareto optimal concept is simple to calculate and can find the optimal solution comprehensively without considering the influence of weights.Finally, by PSCAD builds modified IEEE33 node model, respectively from two aspects of single and multiple faults are simulated, and considering the three conditions of the intelligent terminal unit information misstatement, to locate simulation results respectively, the fault situation of four typical separately using article method and standard genetic algorithm (SGA) of single objective optimization model for comparison, by comparing the findings, based on the NSGA-II fault location method of multi-objective optimization in a single or multiple types information misstatement cases are still able to accurately locate the fault section with high reliability.