摘要
随着我国电网规模持续扩大和电力负荷快速增长,高压电力系统的安全稳定运行面临新的挑战。近年来,因设备老化、极端天气、外力破坏等因素导致的高压线路故障频发,依赖人工巡检和事后抢修的传统运维模式已难以满足现代电网高效运行的需求。本文针对高压电力故障报修过程中的技术瓶颈,系统研究了基于多源信息融合的智能诊断方法。通过整合SCADA(数据采集与监视控制)系统实时数据、在线监测装置信息及历史故障案例库,构建了高压线路故障特征分析模型;结合机器学习算法,提出了分级分类的故障诊断策略,有效提升了复杂工况下的故障识别准确率,旨在为智能电网的故障管理提供新的技术思路。
With the continuous expansion of the scale of China's power grid and the rapid growth of power load,the safe and stable operation of high-voltage power systems is facing new challenges.In recent years,high-voltage line faults caused by factors such as equipment aging,extreme weather,and external damage have occurred frequently.The traditional operation and maintenance mode that relies on manual inspection and post-fault repair has been difficult to meet the needs of efficient operation of modern power grids.This paper systematically studies the intelligent diagnosis method based on multi-source information fusion in the process of high-voltage power fault reporting and repair.By integrating real-time data from the SCADA system,information from online monitoring devices,and historical fault case libraries,a high-voltage line fault feature analysis model is constructed;combined with machine learning algorithms,a hierarchical and classified fault diagnosis strategy is proposed,effectively improving the accuracy of fault identification under complex working conditions,providing new technical ideas for fault management in smart grids.
作者
王碧琼
WANG Biqiong(Ningdong County Power Supply Company,State Grid Ningxia Electric Power Company,Yinchuan 750411,P.R.China)
出处
《灯与照明》
2025年第6期110-112,共3页
Light & Lighting
关键词
高压电力
故障报修
诊断技术
high-voltage power
fault reporting and repair
diagnosis technology
