基于仿真分析的输电线路树木超高放电特性研究
石可颂,徐菲
(国网冀北电力有限公司廊坊供电公司,河北 廊坊 065000)
摘 要:架空输电线路常因树木超高生长造成线路故障跳闸,影响输电线路的供电稳定性。架空输电线路树木超高生长会导致电晕放电—隐患放电—闪络放电三个循序渐进的过程,基于树木超高生长中放电过程,搭建 Ansys 仿真模型,研究了不同电压等级的树木超高放电过程净空距离,同时开展树木超高生长试验,对试验过程中树木放电特性行波数据进行分析,获取了不同净空距离下行波特征,并针对行波特征制定树木超高生长预警方法,为架空线路隐患放电提供了科学合理的预警方法,保证了架空输电线路供电的稳定性。
关键词: 架空输电线路;Ansys 仿真;树木放电;行波
中图分类号:TM726.3 文献标识码:A 文章编号:1007-3175(2025)09-0034-08
Research on the Characteristics of Ultra-High Discharge of Trees on
Transmission Lines Based on Simulation Analysis
SHI Ke-song, XU Fei
(State Grid Jibei Electric Power Co., Ltd. Langfang Power Supply Company, Langfang 065000, China)
Abstract: Overhead transmission lines often trip due to the excessive growth of trees, which affects the power supply stability of the transmission lines. The ultra-high growth of trees in overhead transmission lines lead to three progressive processes: corona discharge, hazard discharge and flashover discharge. Based on the discharge process during the ultra-high growth of trees, this paper builds an Ansys simulation model to study the clearance distance of the ultra-high discharge process of trees at different voltage levels, meanwhile the tree ultra-high growth experiment is carried out, then the traveling wave data of tree discharge characteristics are analyzed during the experiment, thus obtaining traveling wave characteristics at different clearance distances to formulate the tree ultra-high growth early warning method, which provided a scientific and reasonable early warning method for hidden discharge of overhead lines and ensured the stability of power supply of overhead transmission lines.
Key words: overhead transmission line; Ansys simulation; tree discharge; traveling wave
参考文献
[1] 陈良琴,唐海城,肖新华,等. 基于深度学习的输电线路风险预警识别研究[J] . 电力大数据,2018,21(12) :1-5.
[2] 周小红,李向欢,石蕾,等. 无人机倾斜摄影技术在电力巡线树障检测中的实践应用研究[J]. 贵州电力技术,2019,22(8) :53-59.
[3] 金伟龙,周美英. 基于不同 BP 网络层数的双目立体视觉标定研究[J]. 光学技术,2015,41(1) :72-76.
[4] 樊高辉,刘尚合,魏明,等. 基于神经网络曲线拟合的电晕电流数学模型研究[J] . 高电压技术,2015,41(3) :1034-1041.
[5] 宋辉,代杰杰,张卫东,等. 复杂数据源下基于深度卷积网络的局部放电模式识别[J] . 高电压技术,2018,44(11) :3625-3633.
[6] 王小匆,刘亚东,盛戈皞,等. 基于改进 BPSO 算法的 PMU 优化配置新方法[J]. 广东电力,2018,31(1) :62-67.
[7] 刘毓, 陆佳政, 罗晶, 等. 架空输电线路山火同步卫星广域监测与杆塔定位[J] . 电网技术,2018,42(4) :1322-1327.
[8] 张燕,杜红乐. 基于异构距离的集成分类算法研究[J].智能系统学报,2019,14(4) :733-742.
[9] 朱付保,谢利杰,汤萌萌,等. 基于模糊 C-Means 的改进型 KNN 分类算法[J]. 华中师范大学学报(自然科学版),2017,51(6) :754-759.
[10] 王蕾,焦明海,代勇,等. 群体主动学习算法的移动电力交易行为研究[J] . 控制工程,2019,26(3) :484-491.