计算机与数字工程2024，Vol.52Issue(2)：343-348,6.DOI:10.3969/j.issn.1672-9722.2024.02.008
基于改进灰狼算法优化SVR的避雷器阻性电流预测
Improved Grey Wolf Algorithm to Optimize SVR for Resistive Current Prediction of Arrester
杨政1
作者信息
- 1. 中国南方电网有限责任公司超高压输电公司南宁局 南宁 530021
- 折叠
摘要
Abstract
The magnitude and variation of arrester resistive current under the operating voltage reflect the state of arrester.Aiming at the problem that the data samples of on-line measurement are small,the support vector regression(SVR)optimized by improved grey wolf optimizer(IGWO)is proposed to predict resistive current of arrester.In view of the fact that the resistive current is significantly affected by ambient temperature and interphase interference,the prediction method takes the phase,historical resis-tive current,ambient temperature and temperature difference as characteristic inputs.An improved grey wolf optimizer based on Lo-gistic chaotic mapping for population initialization and nonlinear convergence factor is adopted.Three phase on-line measurement datas of a 500kV arrester in recent 10 years are used for modeling and analysis.The results of calculation example show that the pro-posed method is accuracy and feasible.关键词
阻性电流预测/改进灰狼优化/支撑向量回归/混沌映射/金属氧化物避雷器Key words
prediction of resistive current/improved grey wolf optimizer/support vector regression/chaotic mapping/metal oxide arrester分类
信息技术与安全科学引用本文复制引用
杨政..基于改进灰狼算法优化SVR的避雷器阻性电流预测[J].计算机与数字工程,2024,52(2):343-348,6.
