基于模糊优化多目标进化算法的配电网故障定位

摘要/Abstract

摘要：

提出了一种基于模糊优化多目标进化算法（FMOEA）的配电网故障定位新方法。FMOEA对基于排序选择的传统多目标进化算法进行改良,有效避免了其种群早熟的问题,在排序结果中引入模糊优选决策因子,得到本代个体的最终适应度值,之后再经过复制、交叉、变异和迭代等过程,直到满足终止条件得到最终的Pareto解集;最后对适用于故障定位的最优解集处理办法进行了探讨与分析,以便从最优解集中筛选出符合故障情况的唯一解。算例仿真测试针对不同的配电网系统结构,分别模拟系统单点、多点故障,以及信息完备与部分信息畸变的情况,结果表明该算法可以实现配电网故障的有效定位,通过对比遗传算法,验证了该方法寻找全局最优Pareto解集的有效性及良好的收敛性能。

关键词: 配电网, 故障定位, 模糊优化, 多目标进化算法, 容错性

Abstract:

A new method of fault section location and isolation in distribution network based on fuzzy multi-objective evolutionary algorithm (FMOEA) is presented. The traditional multi-objective evolutionary algorithm based on ranking selection is improved by FMOEA to avoid its premature problem effectively. FMOEA introduces fuzzy optimization decision factor in ranking results to obtain the generation of the individual values. In the process of copy, crossover, mutation and iteration, we can get the final Pareto solution set satisfied by the termination conditions. The optimal solution set approach for fault location is provided for detecting the only proper one from the multi-objective solution set. Based on the different system structure of distribution network single-point and multi-point faults are simulated in two conditions: with and without partial information distortion. Finally the simulation results show that the FMOEA can realize the goal of fault location and the comparison results with genetic algorithm show that the FMOEA has the capacity of effectively finding out the distributed Pareto optimal solution. In addition, the algorithm has performed very well in its efficiency of convergency.

Key words: Distribution network, fault location, fuzzy optimization, multi-objective evolutionary algorithm, fault tolerance

中图分类号:

TM727

郭琰,刘淼淼,张萌,杨琰冲,陈江涛,赵晓晨. 基于模糊优化多目标进化算法的配电网故障定位[J]. 电气工程学报, 2015, 10(5): 61-67.

Guo Yan,Liu Miaomiao,Zhang Meng,Yang Yanchong,Chen Jiangtao,Zhao Xiaochen. Fault Location of Distribution Network Based on Fuzzy Multi-objective Evolutionary Algorithm[J]. Journal of Electrical Engineering, 2015, 10(5): 61-67.

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参考文献 13

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序号	权值	设备状态	定位结果
1	0.8	10000	区段1
2	1.0	00000或10000	无故障或区段1
3	3.0	00000	无故障

越限信息	IQF1	IS1	IS2	IS3	IS4
1	1	0	0	0	0
2	1	1	0	1	1

设备状态	区段1	区段2	区段3	区段4	区段5
1	1	0	0	0	0
2	0	0	0	0	1

故障区段	各个FTU 上传信息	信息畸变	馈线区段实际状态	平均迭代次数
4	111100 000000	无	000100 000000	3.2
4	101100 000000	S₂漏报	000100 000000	3.5
7、12	000011 101111	无	000000 100001	4.8
7、12	001011 110111	S₃误报	000000 100001	4.3

故障区段	信息畸变	收敛条件	正确次数（程序共运行20次）
故障区段	信息畸变	收敛条件	FMOEA	GA
4	无	10次迭代	19	14
4	无	10次迭代或3次最优解无变化	19	8
4	有（S₂）	10次迭代	19	16
4	有（S₂）	10次迭代或3次最优解无变化	18	6
7、12	无	10次迭代	19	3
7、12	无	10次迭代或3次最优解无变化	18	1
7、12	有（S₃）	10次迭代	18	2
7、12	有（S₃）	10次迭代或3次最优解无变化	18	1