摘要
随着智能电网发展,配电网运行可靠性至关重要。针对传统配电网设备监测精度低、故障处理滞后的问题,该文研究其电气设备状态监测与故障自愈技术。明确监测目标与关键设备感知方法,提出多源数据加权融合模型(结合3σ准则筛选异常数据),构建“检测—定位—隔离—恢复”故障自愈架构,并基于MATLAB/Simulink搭建10 kV配电网仿真平台验证。结果显示,变压器油中溶解气体监测误差小于等于3.2%(较传统降低61.5%),单相接地故障处理时间小于等于18 s(较人工缩短95%以上),可提升配电网可靠性。
With the development of smart grids,the operational reliability of distribution networks is crucial.Aiming at the problems of low monitoring accuracy and lagging fault handling of traditional distribution network equipment,this paper studies its electrical equipment condition monitoring and fault self-healing technology:clarifying the monitoring targets and key equipment sensing methods,proposing a multi-source data weighted fusion model(based on the 3σcriterion to filter abnormal data),building a"detection-location-isolation-recovery"fault self-healing architecture,and building a 10 kV distribution network simulation platform based on MATLAB/Simulink for verification.The results show that the monitoring error of dissolved gas in transformer oil is≤3.2%(61.5%less than traditional),and the single-phase ground fault processing time is≤18 s(more than 95%less than manual),which can improve the reliability of the distribution network.
出处
《科技创新与应用》
2025年第36期185-188,共4页
Technology Innovation and Application
关键词
智能电网
配电网
电气设备
状态监测
故障自愈
smart grid
distribution network
electrical equipment
condition monitoring
fault self-healing
