Multi-branch Distribution Network Fault Location Based on LSD Algorithm

doi:10.11930/j.issn.1004-9649.202411045

Abstract

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

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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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202411045

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

Figures/Tables 23

Fig.1 Transmission path of fault-generated traveling wave

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

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

Fig.4 Waveform graph linear detection results

Fig.5 Area map linear detection results

Fig.6 The process of generating a linear support domain

Fig.7 Rectangular approximation of a linearly supported domain

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

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

Fig.10 Multi-branch distribution network fault localization flow

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

Fig.11 Raw faulty traveling wave line-mode signal

Fig.12 Calibration results of db wavelet transform

Fig.13 Results for wavefront calibration based on LSD algorithm

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

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

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

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

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

Fig.16 Topology of multi-branch distribution network

Fig.17 Results for M-terminal wavefront calibration

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

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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