基于有限状态机故障因果链的连锁跳闸故障诊断和预测研究

Research on fault diagnosis and prediction of chain trip based on fault causal chain of finite state machine

随着变电站告警信息的规范化、大数据分析在设备监控中应用的深入,使得利用监控大数据及智能化预测分析方法解决电网连锁故障的识别问题成为可能。为避免连锁故障造成电网大停电事故的发生且针对电网连锁故障识别困难的问题,本文提出了基于连锁故障状态因果链的电网故障诊断、故障演化预测及电网脆弱性评估的方法。本文首先介绍了基于有限状态机模型故障因果链的数学模型,利用故障因果链的数学模型对电网中的单元件故障和连锁故障进行识别,从而形成了单元件诊断以及连锁故障诊断方法,然后研究了基于智能状态因果链的电网故障演变的风险预测方法,即形成了基于智能状态因果链构建的电网故障风险评估系统。最后以实际电网为例,验证了本文所提方法的可行性。

Aiming at the problem that the recognition of chain fault in power grid is difficult, and with the standardization of the warning information in substation as well as the deep application of big data analysis on equipment monitoring. In order to avoid the cascading failure caused by power grid blackout accidents, and in view of the difficulty in identifying the cascading failures of the power grid, this article has come up with the grid vulnerability prediction method of grid fault diagnosis and fault evolution based on chain fault condition causality chain. First of all, the article has introduced the mathematical model of fault causal chain based on finite state machine model, and has used the mathematical model of fault causal chain to identify unit faults and cascading faults in power grid. Then the unit diagnosis and the linkage fault diagnosis method has formed. In addition, the article has dealt with the constitute of evaluating system of the risk of power grid failure based on the causal chain of intelligence state. At last, the article has been verified the feasibility of the method in this article with an actual power grid as an example.