设备监控信息大数据与设备模型的互校验及实用化事件分析

Mutual verification and practical event analysis of big data and equipment model for equipment monitoring information

为了应对日益复杂的电网设备监控信息,通过建立统一的大数据管理平台,实现多元数据共享、信息规范化,从而提高调控人员的决策能力和工作效率。本文针对设备监控管理实际提出设备监控信息校验及实用化事件分析管理方法。首先,通过自然语言解析和设备拓扑关系,实现一、二次设备监控信息的关联融合。其次,通过设备监控信息与EMS模型中监控信息智能比对和检验,实现监控信息表完整性核查。采用变压器负载率智能校验新算法,排查全电网遥测存在的隐患缺陷,为消缺处理提供了重要依据。最终,通过监控数据事件化打包分组和自动识别方法,结合电力设备状态大数据共享平台,有效判断故障、异常"事件",辅助快速完成对各类电网事件的全过程分析,从而提高事故处理效率,科学评价监测报警质量。

In order to deal with the increasingly complex monitoring information of power grid equipment,a unified big data management platform is established to realize multiple data sharing and information standardization,so as to improve the decision-making ability and work efficiency of regulators. This paper proposes a device monitoring information verification and practical event analysis management method for equipment monitoring and management. Firstly,through the natural language analysis and the device topology relationship,the association and fusion of the monitoring information of the primary and secondary devices is realized. Subsequently,through the intelligent comparison and inspection of the monitoring information between the equipment monitoring information and the EMS model,the integrity check of the monitoring information table is realized. The new algorithm of transformer load rate intelligent verification is used to check the hidden defects in the whole power grid telemetry,which provides an important basis for defect elimination. Finally,by monitoring data eventization,packetization and automatic identification methods,Combined with big data shared platform of power equipment condition,the fault and abnormal " events" can be effectively judged,and the whole process analysis of all kinds of grid events can be completed quickly,so as to improve the efficiency of accident handling and scientifically evaluate the quality of monitoring and alarm.