南方电网技术2024，Vol.18Issue(6)：58-68,97,12.DOI:10.13648/j.cnki.issn1674-0629.2024.06.008
基于多维波形差异度聚类分析的配电网故障区段定位方法
Fault Section Location Method for Distribution Network Based on Multi-Dimensional Waveform Difference Clustering Analysis
摘要
Abstract
The resonant grounding system has a complex operating environment and variable single-phase grounding fault occurrence status.The distribution network traditional fault section location methods based on a single characteristic quantity have their own location blind zones,and the reliability and applicability of methods are also difficult to be guaranteed.To solve the above problems,a fault section location method for distribution network based on multi-dimensional waveform difference clustering analysis without tuning is proposed.According to the waveform difference characteristics of the zero-sequence current transient and steady-state components at each detection point upstream and downstream of the fault point,the transient and steady-state waveform differences between adjacent detection points are quantified by discrete Fréchet distance algorithm,and fuzzy C-means(FCM)is used to synthesize multi-feature information to divide the normal section and fault section.The location blind zones with single feature are eliminated effectively and the accurate fault section location is realized adaptively.The simulation results of PSCAD/EMTDC and 10kV true experimental test show that the proposed method not only ensures reliability and applicability under different fault condi-tions,but also has high resistance resistance and noise resistance.关键词
谐振接地系统/故障定位/零序电流/离散Fréchet距离/模糊C均值算法(FCM)聚类Key words
resonant grounding system/fault location/zero sequence current/discrete Fréchet distance/fuzzy C-means clustering分类
信息技术与安全科学引用本文复制引用
罗晗菁,曾祥君,喻锟,李志,谢志成,邓军..基于多维波形差异度聚类分析的配电网故障区段定位方法[J].南方电网技术,2024,18(6):58-68,97,12.基金项目
国家自然科学基金资助项目(51737002,52177070) （51737002,52177070）
湖南省自然科学基金项目(2021JJ30729) （2021JJ30729）
湖南省教育厅项目(22A0231) （22A0231）
湖南省研究生科研创新项目(CX20210792) （CX20210792）
国网浙江省电力公司科技项目(2021FD05). Supported by the National Natural Science Foundation(51737002,52177070) （2021FD05）
Hunan Provincial Natural Science Foundation of China(2021JJ30729) （2021JJ30729）
Hunan Provincial Education Department Project(22A0231) （22A0231）
Hunan Province Postgraduate Research and Innovation Project(CX20210792) （CX20210792）
the Science and Technology Project of State Grid Zhejiang Electric Power Corporation(2021FD05). （2021FD05）
