摘要
为了提高高压输电线路弧垂估算精度,提出了一种基于GWO-LSSVM的超特高压输电线路弧垂估算方法。以环境温度、风速、光照强度和线路载流量为LSSVM的支持向量,线路温度为输出量,根据线路温度估算弧垂,采用GWO算法对LSSVM进行优化,建立基于GWO-LSSVM的弧垂估算模型,算例分析结果表明,所提弧垂估算方法的准确性更高,验证了该方法的正确性和实用性。
In order to improve the accuracy of sag estimation for high-voltage transmission lines,a sag estimation method for ultra-high voltage transmission lines based on GWO-LSSVM is proposed.Using environmental temperature,wind speed,light intensity,and line current carrying capacity as the support vectors of LSSVM,and line temperature as the output,sag is estimated based on line temperature.The GWO algorithm is used to optimize LSSVM and establish a sag estimation model based on GWO-LSSVM.The analysis results of the examples show that the sag estimation method proposed in this paper has higher accuracy,verifying the correctness and practicality of the method.
作者
韩学春
宋恒东
潘灵敏
王海亮
HAN Xuechun;SONG Hengdong;PAN Lingmin;WANG Hailiang(State Grid Jiangsu Electric Power Co.,Ltd.,Extra-High Voltage Branch Company,Nanjing 211102,China)
出处
《自动化与仪器仪表》
2025年第3期321-324,共4页
Automation & Instrumentation
基金
国网江苏省电力有限公司超高压分公司科技项目(CGY-2023005)成果之一。
关键词
输电线路
弧垂估算
灰狼算法
最小二乘支持向量机
transmission lines
sag estimation
grey wolf optimization algorithm
least squares support vector machine
作者简介
韩学春(1972-),男,山东五莲人,本科,高级工程师,研究方向为领域为输电线路运检及带电作业;通讯作者:宋恒东(1989-),男,江苏徐州人,硕士,工程师,从事超特高压输电线路巡检与带电作业工作。
