基于大数据挖掘的电网监控信息智能监控研究

Research onsmart monitoring of power grid monitoring information based on big data mining

为解决电网变电站集中监控后,人工监控高达上百万信息点时,监控工作质效低、信息淹没风险突出的问题,避免漏监信号、误判信号,严重影响电网安全运行。本文结合信息发生机制,分析电网监控信息发生规律,创新提出监控信息事件化方法,以大数据驱动为核心理念,提出历史信息挖掘、实时信息应用的两阶段智能监控方案。首先,基于多时间精度Apriori算法,应用R语言对历史监控信息与电网AVC、缺陷管理等事件信息进行关联规则挖掘,形成事件库;然后,为事件构造属性矩阵,建立实时监控信息智能告警模型,形成基于事件推送、分窗显示的智能监控方案。仿真表明该方案将人工处理告警信息量平均降至30%以下,提高了电网监控信息监控效率,提升了电网安全水平。

In order to solve the problem of low quality and effectiveness of monitoring work and information inundation risk,when manual monitoring is up to millions of information points,after centralized monitoring of power grid substations,to avoid missed monitoring signals and misjudgment signals,which will seriously affect the safe operation of the power grid.This paper considers the mechanism of information occurrence and analyze the law of power grid monitoring information occurrence,proposes the concept of monitoring information event.With big data-driven as its core and causal mechanism analysis,two-stage intelligent monitoring scheme is put forward which concludes the historical information mining,real-time information application.First of all,multi-time precision Apriori algorithm are put forward,the R language is used to mine the historical monitoring information and the event information such as grid AVC and defect management to form an event library.Then,the event matrix is constructed for the event,and a real-time monitoring information intelligent alarm model is established.Form an intelligent monitoring solution based on event push and window display.The simulation shows that the scheme reduces the amount of manual processing alarm information to less than 30%on average,which improves the monitoring efficiency of power grid monitoring information and improves the security level of the power grid.