摘要
随着现代电力系统的快速发展,配电网的稳定性和可靠性已成为保障电力供应的重要因素。提出了一种基于5G的高效配电网故障检测与诊断方法。该方法综合利用了智能传感器、边缘计算以及大数据分析技术,通过5G网络的高带宽、低延迟以及大连接特性,实时获取配电网运行状态的多维数据,并在边缘节点进行快速分析和处理。通过大数据分析技术对历史故障数据和运行参数进行智能化建模与分析,可以实现对故障位置、性质以及原因的快速诊断,大幅缩短故障检测响应时间,提升故障识别的准确性。实验结果显示,该方法在复杂电力系统环境下能够以极高的精度和实时性有效检测并诊断多种故障类型,为提高配电网的运行效率和可靠性提供了强有力的技术保障。
With the rapid development of modern power systems,the stability and reliability of distribution networks have become crucial factors in ensuring power supply.This paper proposes an efficient fault detection and diagnosis method for distribution networks based on 5G.The method integrates intelligent sensors,edge computing,and big data analysis technology,utilizing the high bandwidth,low latency,and massive connectivity of 5G networks to acquire multidimensional real-time data on the operating status of distribution networks.Fast analysis and processing are conducted at edge nodes.By applying big data analysis to historical fault data and operating parameters,intelligent modeling and analysis can be performed to quickly diagnose fault locations,nature,and causes,significantly reducing fault detection response time and improving fault identification accuracy.Experimental results show that this method can effectively detect and diagnose various types of faults with high precision and real-time performance in complex power system environments,providing strong technical support for enhancing the operational efficiency and reliability of distribution networks.
作者
张国斌
ZHANG Guobin(State Grid Shanxi Electric Power Company Linyi County Power Supply Company,Yuncheng 044100,China)
出处
《通信电源技术》
2024年第23期246-248,共3页
Telecom Power Technology
关键词
5G
配电网
故障检测
智能传感器
边缘计算
5G
distribution network
fault detection
intelligent sensor
edge computing
