电力建设2025，Vol.46Issue(11)：110-120,11.DOI:10.12204/j.issn.1000-7229.2025.11.010
基于直线检测算法和模态时间差的多分支配电网故障定位
Multi-branch Fault Location in Distribution Networks Based on the Line Segment Detector Algorithm and Modal Time Differences
摘要
Abstract
[Objective]To address the challenges of low reliability and high cost of fault location in multibranch distribution networks using wavefront detection,this study proposes a novel fault location method based on the line segment detector(LSD)algorithm and modal time differences.[Methods]First,considering that the initial fault wavefront exhibited steep linear characteristics when reaching the busbar,the method converted zero-and line-mode traveling waves into images.Using the LSD algorithm,the sub-pixel-level steep line segments in the images were identified to achieve precise wavefront detection.Next,by leveraging the difference in the propagation speeds of the zero-and line-mode traveling waves over short distribution lines,the fault location was determined solely by measuring the modal time difference of the initial traveling wavefronts at both ends of the main feeder.This approach eliminated the need for measurement devices on branch lines,significantly reducing the cost of fault location.Finally,a multibranch distribution network model was developed using MATLAB/Simulink.[Results]Compared with traditional fault location methods,the proposed method achieved an average error of approximately 6 m,representing an error reduction of approximately 80%.Furthermore,it exhibited accurate wavefront identification even under strong noise conditions of 10 dB.[Conclusions]Simulation results demonstrated that the proposed method achieved high reliability,cost efficiency,and accuracy in fault location.关键词
配电网/多分支线路/波头标定/故障定位Key words
distribution network/multibranch line/wave head calibration/fault location分类
信息技术与安全科学引用本文复制引用
刘艳坤,常仲学,孙勇卫,王德龙,黄心月,吉兴全,张玉敏..基于直线检测算法和模态时间差的多分支配电网故障定位[J].电力建设,2025,46(11):110-120,11.基金项目
This work is supported by the National Natural Science Foundation Youth Fund of China(No.52107111),Shandong国家自然科学基金青年科学基金项目(52107111) （No.52107111）
山东省自然科学基金项目(ZR2022ME219)Provincial Natural Science Foundation of China(No.ZR2022ME219). （ZR2022ME219）
