浙江电力2024，Vol.43Issue(1)：36-44,9.DOI:10.19585/j.zjdl.202401005
基于WOA-SVM的智能变电站二次系统故障参数映射模型
A WOA-based fault parameter mapping model for the secondary systems of intelli-gent substations
摘要
Abstract
Currently,it is challenging to rapidly and precisely locate faults in the secondary systems of intelligent substations through manual analysis of extensive operational data,making it inadequate for meeting the high reliabil-ity requirements of smart grids.To address this issue,a fault parameter mapping model for the secondary systems of intelligent substations is proposed.Firstly,a knowledge base for fault localization reasoning is established based on characteristic information to encode fault types.Subsequently,utilizing historical operational data from intelligent substations,a training set for the model is constructed.The support vector machine(SVM)is enhanced by introduc-ing a multi-classifier approach,and its parameters are optimized using the whale optimization algorithm(WOA).By taking equipment status as input and secondary system fault types as output,a mapping relationship is established between the parameters of secondary system equipment of intelligent substations and the operational state.Finally,the proposed model is validated using actual data as a test set,demonstrating the effectiveness of the proposed model.关键词
智能变电站/二次系统/故障参数映射/鲸鱼优化算法/支持向量机Key words
intelligent substation/secondary system/fault parameter mapping/WOA/SVM引用本文复制引用
郑翔,杜奇伟,阮黎翔,王海园,周坤,王义波..基于WOA-SVM的智能变电站二次系统故障参数映射模型[J].浙江电力,2024,43(1):36-44,9.基金项目
国网浙江省电力有限公司科技项目(B311QZ220001) （B311QZ220001）
