基于最优编码集及智能状态估计的电网故障诊断方法

当电网发生故障时,大量的遥信告警和变位信息上传到调度端,使得调度人员很难在短时间内对故障设备及故障类型做出准确的判断.因此提出了利用分组遥信数据识别故障类型,利用人工智能方法纠正差错遥信的电网故障诊断方法.对于此,将各种设备的标准遥信数据映射到故障诊断空间中,求取最优编码集,把故障遥信的故障空间编码值和故障空间最优编码...

A fault diagnosis method of a power grid based on an optimal coding set and intelligent state estimation

When a fault occurs in the power grid,a large number of remote signaling alarms and amount of displacement information are uploaded to the dispatching terminal.This makes it difficult for dispatchers to make accurate judgments on the faulty equipment and the type of the fault in a short time.Therefore,this paper proposes a power grid fault diagnosis method that combines classification with fault space optimal coding and intelligent state estimation and error correction of remote signal data.It proposes mapping the remote signal data to the fault diagnosis space,and compares and classifies it with the optimal coding set of the fault space to realize fault diagnosis of the power grid.Through the remote signal displacement data of different failure modes,the intelligent state estimation model is trained to correct the misplaced or missed data of the remote signal to realize the front-end data error correction of the remote signal data,and thus improve the accuracy of fault diagnosis.Finally,an intelligent fault diagnosis method for power grid faults suitable for big data platform applications is formed.The validity of the intelligent state estimation model and fault diagnosis model for fault diagnosis of power grids is verified by case simulation verification and actual big data platform network operation.