Lightning Trip Risk Assessment in Transmission Line Area Based on Multi-factor Driving

FAN Kai; ZHOU Lawu; LIANG Yu; LONG Leyun; HUANG Biao

doi:10.13296/j.1001-1609.hva.2026.04.018

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Lightning Trip Risk Assessment in Transmission Line Area Based on Multi-factor Driving

Research & Analysis | 更新时间：2026-04-08

- Lightning Trip Risk Assessment in Transmission Line Area Based on Multi-factor Driving
- High Voltage Apparatus Vol. 62, Issue 4, Pages: 160-167(2026)
- 作者机构：
  
  长沙理工大学电气与信息工程学院，长沙 410114
  山东电网有限责任公司临沂供电局，山东临沂 276000
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(52177015)
- DOI：10.13296/j.1001-1609.hva.2026.04.018
  CLC：
- Received：24 June 2025，
  
  Revised：2025-09-21，
  
  Published：16 April 2026
- 稿件说明：
移动端阅览
FAN Kai, ZHOU Lawu, LIANG Yu, et al. Lightning Trip Risk Assessment in Transmission Line Area Based on Multi-factor Driving[J]. High Voltage Apparatus, 2026, 62(4): 160-167.
DOI：

FAN Kai, ZHOU Lawu, LIANG Yu, et al. Lightning Trip Risk Assessment in Transmission Line Area Based on Multi-factor Driving[J]. High Voltage Apparatus, 2026, 62(4): 160-167. DOI： 10.13296/j.1001-1609.hva.2026.04.018.

摘要

雷击是引发输电线路跳闸故障的主要原因之一，严重影响电网安全稳定运行。为有针对性地指导输电线路的防雷设计和改造，文中提出了基于多因素驱动的输电线路区域雷击跳闸风险评估方法。首先，综合考虑气象、电网、环境影响因素，构建完整有效的样本空间；其次，基于6种较优回归算法（XGBoost、RF、Bagging、GBRT、DT及KNN），对样本数据进行训练及验证；然后，选取拟合优度最高的XGBoost算法构建输电线路区域雷击跳闸风险评估模型；最后，算例结果表明：雷击故障点落在风险区域占75%，区域风险等级与单位面积跳闸次数的相关系数为0.983 3。风险评估等级越高，发生雷击跳闸故障的概率越大，验证了所提方法对输电线路雷击跳闸的风险区域识别性与风险等级评估有效性。

Abstract

Lightning strike is one of the main causes of transmission line trip fault

which seriously affects the safe and stable operation of power grid. In order to guide the lightning protection design and transformation of transmission line

a risk assessment method for regional lightning trip fault of transmission line based on multi-factor driving is proposed. Firstly

a complete and effective sample space is constructed by considering the factors of meteorology

power grid and environmental impact.Secondly

based on six better regression algorithms(XGBoost

Bagging

GBRT

DT and KNN)

the sample data is trained and verified.Then

the XGBoost algorithm with the highest goodness of fit is selected to construct the risk assessment model of lightning trip fault in transmission line area; Finally

the results of the example show that the lightning fault point falls in the risk area accounting for 75%

and the correlation coefficient between the regional risk level and the number of trips per unit area is 0.9833. The higher the risk assessment level

the greater the probability of lightning trip fault. All of the above verify the effectiveness of the proposed method in identifying the risk area and evaluating the risk level of lightning trip of transmission line.

关键词

Keywords

references

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