基于LSD算法的多分支配电网故障定位

doi:10.11930/j.issn.1004-9649.202411045

摘要/Abstract

摘要：

针对多分支配电网行波故障定位方法存在波头标定精度低和测距成本高的问题，提出一种基于直线检测算法（line segment detector，LSD）的多分支配电网故障定位方法。首先，明晰故障行波波头的陡斜直线特征，图像化处理长时窗下的故障行波数据，采用LSD算法实现图像中陡斜直线段的亚像素级检测，建立陡斜直线段的像素位置与行波波头位置之间的转换关系，实现故障行波波头的标定。其次，针对后续波头难以辨识的问题，提出一种基于单双端行波法相结合的多分支配电网故障定位方法，剖析配电网分支线路故障行波的传输特性，依据波头到达时间和极性构造行波筛选条件，判别含有效信息的区段行波，进而推断分支线路故障点的位置，并基于双端初始行波波头时差推断主干线路故障点的位置，进而在无须配置分支线路末端量测终端的前提下，实现多分支配电网的故障定位。最后，采用Matlab/Simulink仿真软件搭建多分支配电网仿真模型，对所提方法进行测试，仿真结果表明，所提方法能够有效标定波头并具有较高的故障定位精度。

关键词: 直线检测算法, 故障定位, 波头标定, 多分支配电网, 行波测距

Abstract:

In order to solve the problems of low wavefront detection accuracy and high ranging cost of traveling wave fault localization methods in multi-branch distribution networks, a multi-branch distribution network fault localization method based on line segment detector (LSD) is proposed. Firstly, after clarifying the characteristics of the steep straight-line segments of the faulty traveling wave, the fault traveling wave data can be image processed. The LSD algorithm is used to realize the sub-pixel level detection of steep-slope straight lines in the image, and to establish the conversion relationship between the pixel position of steep-slope straight lines and the position of traveling wave data, so as to realize the faulty traveling wave head calibration. Secondly, in order to solve the problem that it is difficult to recognize the subsequent wavefronts, a multi-branch distribution network fault localization technique method based on the combination of single and double-ended traveling wave method is proposed. For the faulty traveling wave, after analyzing the transmission characteristics, the traveling wave screening conditions is formulated based on the arrival time and polarity of the wavefront and the segment traveling wave containing valid information is identified. The location of branch line faults is determined by initial traveling wave, and the location of trunk line faults is determined by extrapolating based on double-ended starting traveling wavefronts. Thus, the accurate localization of faults in multi-branch distribution networks can be realized without the need to increase the measuring devices network simulation model is built in Matlab/Simulink and used to test the proposed method. The simulation results show that the proposed method can effectively calibrate the wavefront and has high fault localization accuracy.

Key words: line segment detector, fault location, wavefront detection, multi-branch distribution, traveling wave location

吉兴全, 张祥星, 张玉敏, 叶平峰, 王德龙, 黄心月. 基于LSD算法的多分支配电网故障定位[J]. 中国电力, 2025, 58(9): 54-67.

JI Xingquan, ZHANG Xiangxing, ZHANG Yumin, YE Pingfeng, WANG Delong, HUANG Xinyue. Multi-branch Distribution Network Fault Location Based on LSD Algorithm[J]. Electric Power, 2025, 58(9): 54-67.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202411045

https://www.electricpower.com.cn/CN/Y2025/V58/I9/54

图/表 23

图 1 故障行波传播路径

Fig.1 Transmission path of fault-generated traveling wave

图 2 M端故障行波线模信号波形

Fig.2 Waveform of M-end fault traveling wave mode signal

图 3 M端故障行波线模信号合理时窗

Fig.3 Reasonable time window for M-end fault traveling wave mode signal

图 4 波形图直线检测结果

Fig.4 Waveform graph linear detection results

图 5 区域图直线检测结果

Fig.5 Area map linear detection results

图 6 直线支撑域的生成过程

Fig.6 The process of generating a linear support domain

图 7 直线支撑域的矩形近似

Fig.7 Rectangular approximation of a linearly supported domain

图 8 多分支线路故障行波传播路径

Fig.8 Fault wave propagation path in multi-branch lines

图 9 多分支线路故障行波网格

Fig.9 Multi-branch line fault traveling wave grid diagram

图 10 多分支配电网故障定位流程

Fig.10 Multi-branch distribution network fault localization flow

表 1 配电线路参数

Table 1 Parameters of Distribution Lines

相序	R/(Ω·km^–1)	L/(H·km^–1)	C/(F·km^–1)
正序	0.17	1.209×10^–3	9.693×10^–3
零序	0.23	5.475×10^–3	5.997×10^–3

图 11 原始故障行波线模信号

Fig.11 Raw faulty traveling wave line-mode signal

图 12 db小波变换标定结果

Fig.12 Calibration results of db wavelet transform

图 13 基于LSD算法的波头标定结果

Fig.13 Results for wavefront calibration based on LSD algorithm

表 2 不同情况下2种检测方法的故障定位结果（初始行波波头）

Table 2 Fault localization results of the two detection methods in different cases (initial traveling wavefront)

检测方法	故障距M 端距离/m	故障类型	过渡电阻/Ω	定位结果/m	绝对误差/m
db小波变换	900	Ag	300	910.35	10.35
	1800	AB	100	1845.13	45.13
	2700	ABC	200	2663.06	36.94
	3600	ABg	500	3597.84	2.16
	4500	Ag	1000	4518.01	18.01
本文	900	Ag	300	905.15	5.15
	1800	AB	100	1802.50	2.50
	2700	ABC	200	2691.40	8.60
	3600	ABg	500	3597.65	2.35
	4500	Ag	1000	4498.31	1.69

表 3 不同情况下2种检测方法的故障定位结果（后续行波波头）

Table 3 Fault localization results of the two detection methods in different cases (subsequent traveling wavefront)

检测方法	故障距M 端距离/m	故障类型	过渡电阻/Ω	定位结果/m	绝对误差/m
db小波变换	900	Ag	300	817.93	82.07
	1800	AB	100	1811.13	11.13
	2700	ABC	200	2745.91	45.91
	3600	ABg	500	3563.83	36.17
	4500	Ag	1000	4498.61	1.39
本文	900	Ag	300	915.78	15.78
	1800	AB	100	1813.93	13.93
	2700	ABC	200	2716.73	16.73
	3600	ABg	500	3613.41	13.41
	4500	Ag	1000	4525.02	25.02

图 14 不同故障初相角下基于LSD算法的行波波头标定结果

Fig.14 Results of wavefront calibration based on LSD algorithm under different fault initial angles

表 4 不同故障初相角下的故障定位结果

Table 4 Fault localization results for different fault initial angles

故障距M端距离/m	故障初相角/(°)	定位距离/m	绝对误差/m
2700	10	2715.61	15.61
2700	30	2710.70	10.70
2700	60	2710.12	10.12
2700	90	2709.98	9.98

图 15 不同噪声干扰下基于LSD算法的行波波头标定结果

Fig.15 Results for wavefront calibration based on LSD algorithm under different noise interference

图 16 多分支配电网拓扑结构

Fig.16 Topology of multi-branch distribution network

图 17 M端波头标定结果

Fig.17 Results for M-terminal wavefront calibration

表 5 不同情况下的多分支故障定位结果

Table 5 Results of multi-branch fault localization in different cases

故障支路	故障距M 端距离/m	故障类型	过渡电阻/Ω	定位结果/m	绝对误差/m
T₁P₁	4600	Ag	500	4606.58	6.58
T₁P₁	6600	AB	300	6601.88	1.88
T₁P₁	6600	ABC	10	6595.81	4.19
T₂P₂	8400	ABg	500	8398.67	1.33
T₂P₂	10400	AB	100	10398.07	1.93
T₂P₂	10400	ABC	200	10398.00	2.00
T₃P₃	10500	Ag	50	10500.39	0.39
T₃P₃	12500	AB	200	12503.26	3.26
T₃P₃	12500	ABC	300	12503.63	3.63
MT₁	1300	Ag	300	1317.42	17.42
T₁T₂	4500	AB	100	4501.97	1.97
T₂T₃	7400	ABC	200	7396.48	3.52
T₃N	10600	ABg	50	10591.17	8.83

表 6 不同定位方法测点数量对比

Table 6 Comparison of measurement point quantity under different Fault Location Methods

方法		测点数量/台
文献[31]		5
本文		2

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