基于大数据挖掘技术的智能变电站故障追踪架构

Framework of Fault Trace for Smart Substation Based on Big Data Mining Technology

文中提出了一种基于大数据平台的电网故障追踪方法,将故障诊断数据源延展至变电站层,利用Spark作为大数据处理工具对各类故障信息进行处理,有效地解决了海量监控数据的管理问题。通过数据挖掘技术对故障信息进行分析,找到故障元件的同时能够运用决策树对保护或断路器的不正确动作进行反向追踪,给出故障原因,使电网故障诊断的功能得到进一步优化。相比于目前依靠事故级报警信息的电网故障诊断,所提出的方法能够有效利用变电站层的各级监控数据,对故障做到追本溯源。

This paper puts forward a new fault trace method for power grid based on big data platform. It extends the data source of fault diagnostic to the transformer substation and deals with the variety of fault date by the technology of Spark. This method can solve the problem of mass data processing. This paper analyzes the fault information by the data mining technology. The incorrect operation of protection or circuit breaker is traced-back by decision tree while the fault components are found. The reasons of the faults are given and the function of fault diagnosis system is optimized. Compared with the traditional fault diagnosis system which is based on the alarm messages, the proposed method can effectively use the monitoring data at every level in the substation and give the reasons of the faults.