摘要
随着智能电网技术的发展,大数据分析在配电网异常检测与故障诊断中发挥着重要作用。文章基于大数据分析技术,以提高配电网安全性和稳定性为宗旨,提出智能配电网异常检测与故障诊断技术。配电网运行状态的实时监控与分析,是通过数据采集与预处理,结合异常检测算法和故障诊断模型实现的。实验结果显示,该技术可以有效检测配电网络中的异常情况,并准确诊断故障,为配电运行维护提供重要支撑。
With the advancement of smart grid technology,big data analysis plays a significant role in anomaly detection and fault diagnosis in distribution grids.This paper proposes an intelligent distribution grid anomaly detection and fault diagnosis technology based on big data analysis,aiming to enhance the safety and stability of distribution grids.Real-time monitoring and analysis of grid operation status are achieved through data collection and preprocessing,combined with anomaly detection algorithms and fault diagnosis model construction.Experimental results demonstrate that this technology effectively detects anomalies in distribution networks and accurately diagnoses faults,providing crucial support for grid operation and maintenance.
作者
胥晓龙
刘晓军
高彬彬
夏远德
刘元振
XU Xiaolong;LIU Xiaojun;GAO Binbin;XIA Yuande;LIU Yuanzhen(State Grid Kashgar Power Supply Company,Kashgar 844200,China)
出处
《通信电源技术》
2024年第13期209-211,共3页
Telecom Power Technology
关键词
智能配电网
大数据分析
异常检测
故障诊断
运行状态监测
intelligent distribution grid
big data analysis
anomaly detection
fault diagnosis
operation status monitoring
作者简介
胥晓龙(1976-),男,四川西充人,本科,工程师,主要研究方向为电网规划、建设、物资管理及新能源发展。
