摘要
传统变电站故障预警方式存在难发现间隔中的突发故障、阈值报警误报漏报等问题,为提高变电站故障预警能力,开展基于大数据分析的故障预警系统研究。文章研究了某220 kV变电站的概况、故障问题与挑战以及大数据分析在故障预警中的应用情况;分析了基于大数据分析的故障预警系统设计,包括系统架构设计、故障预警模型构建、系统功能与特性;最后阐述了系统实施过程与运行效果评估,并给出技术反馈与改进措施,该研究成果有效提高了变电站故障预警的准确率,降低误报率和漏报率,全面覆盖并及时发现设备潜在故障风险,为运维争取处理时间,保障变电站稳定运行。
In order to improve the fault early warning ability of substation,the fault early warning system based on big data analysis is studied.In this paper,the overview,fault problems and challenges of a medium-sized 220kV substation are studied,as well as the application of big data analysis in fault early warning.The design of the fault early warning system based on big data analysis was analyzed,including the system architecture design,fault early warning model construction,system functions and characteristics.Finally,the system implementation process and operation effect evaluation are discussed,and technical feedback and improvement measures are given,which effectively improves the accuracy of substation fault warning,reduces the false alarm rate and false positive rate,comprehensively covers and timely discovers the potential failure risk of equipment,strives for processing time for operation and maintenance,and ensures the stable operation of substation.
作者
孙楠
SUN Nan(Nanrui Group(State Grid Electric Power Research Institute)Co.,Ltd.,Jiagnsu Nanjing 210000,China)
出处
《农村电气化》
2025年第7期50-52,80,共4页
Rural Electrification
关键词
大数据分析
智慧变电站
故障预警系统
big data analysis
smart substation
fault early warning system
作者简介
孙楠(1992-),男,大学本科,中级工程师,研究方向为电气及其自动化,E-mail:snhower@163.com。
