基于改进鲸鱼算法的含DG配电网故障区段定位

doi:10.16180/j.cnki.issn1007-7820.2023.01.003

摘要/Abstract

摘要：

针对鲸鱼优化算法存在收敛速度较慢、定位精度不够高等问题,文中提出了一种基于改进鲸鱼算法的含分布式电源配电网故障区段定位方法。构建了一种适用于多电源配电网故障定位的数学模型,采用自适应惯性权重策略来优化鲸鱼算法,并利用改进后的鲸鱼算法对构建的定位模型进行求解。在33节点含分布式电源的配电网上进行算例仿真,仿真结果表明在配电网发生单重、多重故障的情况下,改进后的鲸鱼算法能快速准确地定位出故障区段,且具有良好的容错性能。相较于传统鲸鱼算法,改进鲸鱼算法收敛速度更快,定位准确性更高,定位的可靠性也更高。

关键词: 分布式电源, 故障定位, 传统鲸鱼算法, 自适应惯性权重, 改进鲸鱼算法, 配电网, 容错性, 可靠性

Abstract:

In view of the problems of slow convergence speed and low positioning accuracy of whale optimization algorithm, a fault section location method based on improved whale algorithm for distribution network with distributed generation is proposed in this study. A mathematical model suitable for fault location of multi-source distribution network is constructed. The adaptive inertia weight strategy is used to optimize the whale algorithm, and the improved whale algorithm is used to solve the location model. The simulation results of a 33-node distribution network with distributed power supply show that in the case of single and multiple faults in the distribution network, the improved whale algorithm can quickly and accurately locate the faulty section, and has good fault-tolerant performance. Compared with the traditional whale algorithm, the improved whale algorithm has faster convergence speed, higher positioning accuracy, which improves the reliability of positioning.

Key words: distributed generation, fault location, traditional whale algorithm, adaptive inertia weight, improved whale algorithm, distribution network, fault tolerance, reliability

中图分类号:

TP183

徐立立,杨超,曾浩然. 基于改进鲸鱼算法的含DG配电网故障区段定位[J]. 电子科技, 2023, 36(1): 15-20.

XU Lili,YANG Chao,ZENG Haoran. Fault Section Location of Distribution Network with DG Based on Improved Whale Algorithm[J]. Electronic Science and Technology, 2023, 36(1): 15-20.

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实验编号	[K₁,K₂,K₃]	故障区段	畸变位置	定位结果	适应度值
1	[0,0,0]	5	无	5	0.5
2	[0,0,1]	10	7	10	1.5
3	[0,1,1]	17	9,27	17	2.5
4	[1,1,1]	9	无	9	0.5
5	[1,1,1]	6	10,16,31	6	3.5

实验编号	[K₁,K₂,K₃]	故障区段	畸变位置	定位结果	适应度值
6	[0,0,0]	10,29	4	10,29	2.0
7	[0,0,1]	14,28	7,32	14,28	3.0
8	[0,1,1]	10,24,27	16	10,24,27	2.5
9	[1,1,1]	13,20,26	无	13,20,26	1.5
10	[1,1,1]	16,31	11,29	16,31	3.0

故障情形	算法类型	平均迭代次数	准确次数	正确率/%
1	IWOA	6.7	50	100
1	WOA	8.4	50	100
2	IWOA	7.6	50	100
2	WOA	9.6	49	98
3	IWOA	12.8	50	100
3	WOA	15.7	48	96
4	IWOA	13.1	50	100
4	WOA	16.3	47	94