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基于阻抗渐变特性检测的中压线路树枝碰线故障识别方法

唐瑞 张文海 杨淳岚 陈天翔

电力系统保护与控制2025,Vol.53Issue(3):148-159,12.
电力系统保护与控制2025,Vol.53Issue(3):148-159,12.DOI:10.19783/j.cnki.pspc.240252

基于阻抗渐变特性检测的中压线路树枝碰线故障识别方法

Tree-contact single-phase-to-ground fault identification for medium voltage distribution lines based on impedance gradient property detection

唐瑞 1张文海 1杨淳岚 2陈天翔3

作者信息

  • 1. 四川大学电气工程学院,四川 成都 610065
  • 2. 四川大学电气工程学院,四川 成都 610065||成都理工大学核技术与自动化工程学院,四川 成都 610059
  • 3. 成都理工大学核技术与自动化工程学院,四川 成都 610059
  • 折叠

摘要

Abstract

A tree-to-wire fault(TF)in medium voltage distribution lines can cause wildfires and serious safety accidents.Sensitive and accurate TF identification is of great significance in ensuring power supply and public safety.Based on the publicly available experimental data of the"Vegetation Conduction Ignition Tests"in Australia,for tree-contact single-phase-to-ground fault(TSF),an analysis of the entire physical process from contact to fire ignition reveals that over 95%of TSF exhibit a similar impedance gradient pattern in the initial stage.The tree impedance shows a double exponential decay characteristic due to discharge heating.Also a method for detecting and identifying impedance gradient properties based on double exponential curve fitting is proposed.The proposed method is validated using PSCAD/EMTDC simulation data,public experimental datasets,and real experimental test data.The results show that the proposed method can be quickly and accurately applied to different neutral grounding methods and types of tree species,providing a new approach for identifying TSF.

关键词

树枝碰线故障/阻抗渐变特性/最小二乘拟合/非线性识别

Key words

tree-contact single-phase-to-ground faults(TSF)/impedance gradient property/least squares fitting/nonlinear identification

引用本文复制引用

唐瑞,张文海,杨淳岚,陈天翔..基于阻抗渐变特性检测的中压线路树枝碰线故障识别方法[J].电力系统保护与控制,2025,53(3):148-159,12.

基金项目

This work is supported by the Natural Science Foundation of Sichuan Province(No.2022NSFSC0234). 四川省自然科学基金项目资助(2022NSFSC0234) (No.2022NSFSC0234)

国家自然科学基金项目资助(52307125) (52307125)

电力系统保护与控制

OA北大核心

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