电力系统保护与控制2024，Vol.52Issue(8)：10-19,10.DOI:10.19783/j.cnki.pspc.231427
基于多指标综合评价的配电网接地故障山火风险等级划分
A method for dividing the forest fire risk levels caused by a ground fault risk levels on distribution lines based on multiple index comprehensive evaluation
摘要
Abstract
In recent years,forest fires caused by power faults have occurred from time to time.If a ground fault in power distribution is not cut off in time,the fault arc discharge may ignite the surrounding vegetation,thereby leading to a forest fire.A method for dividing the forest fire risk levels(FFRLs)caused by a ground fault on distribution lines(DLs)based on multiple index comprehensive evaluation is proposed in order to carry out forest fire prevention measures in a differentiated manner.This paper analyzes the relevant forest fire risk factors based on the integration of unmanned aerial vehicle patrol data,the historical fault data of DLs,meteorological data and the self-designed experiment of an arc combustion characteristic parameter(ACCP).The weights and risk scores of various forest fire risk factors are determined by a Delphi technique network-analytic process.Then the comprehensive risk score is calculated by weighting and summing the factors.The FFRLs of DLs can be determined.An actual case analysis with a 10 kV DL in the Hunan power grid verifies that the method can divide FFRLs of DLs accurately,clarify the important sections of forest fire prevention and control of DLs,and a powerful reference can be provided for the ground fault disposal device of DLs facing forest fire prevention and control.关键词
网络分析法/配电线路/接地故障山火/森林火险等级划分Key words
analytic network process/distribution lines/forest fire caused by ground fault/division of forest fire risk levels引用本文复制引用
欧阳帆,佘笑龙,徐彪,曾举鹏,喻锟,臧欣,贺思林..基于多指标综合评价的配电网接地故障山火风险等级划分[J].电力系统保护与控制,2024,52(8):10-19,10.基金项目
This work is supported by the National Natural Science Foundation of China(No.52037001 and 52177070). 国家自然科学基金项目资助(52037001,52177070) （No.52037001 and 52177070）
国网湖南省电力有限公司科技项目资助(5216A321N303) （5216A321N303）
湖南省自然科学基金项目资助(2021JJ30729) （2021JJ30729）
