基于时间序列相似性匹配的输电系统故障诊断方法

A Fault Diagnosing Method in Power Transmission Systems Based on Time Series Similarity Matching

输电系统发生故障后的警报信号具有丰富的时序信息,若能充分利用则会有助于快速和准确地诊断故障。调度中心采集到的故障警报包含了统一时标基准的时序信息,从而构成了时间序列。在此背景下,将时间序列的数据挖掘概念与相关方法引入输电系统故障诊断之中,提出了基于相似性匹配的故障诊断方法。首先,介绍了时间序列的概念及其相似性匹配方法。随后,将这种方法进行了改进并应用于输电系统故障诊断,构造了相应的时间序列模型,定义了时间序列距离,采用子序列匹配查询方法求解,并与近年来提出的两种输电系统故障诊断方法进行了比较分析。所提出的方法利用警报信息序列的时序特征,对于复杂故障、相继故障等情形仍能迅速识别警报漏报/误报等情况,正确诊断出故障元件与故障类型,并对继电保护装置进行评价。最后,用两个实际案例说明了所提出的故障诊断方法的可行性与有效性。

Alarm messages with timestamps observed after a fault occurrence in a transmission system consist of rich and useful temporal information.The alarm messages received in a dispatching center are time-tagged and can be expressed as a time series.Based on the time series data mining technique,a fault diagnosing method for power systems is proposed with temporal information of alarm messages taken into account.First,the concept of time series and the similarity matching method are described.Then,the method is modified for addressing the fault diagnosis problem in a power system.The time series model for a transmission system is next developed and the distance of the time series is defined,with the model solved using the subsequence matching method.Comparisons are made between the proposed and two existing transmission system fault diagnosing methods developed in recent years.With the temporal information of alarm messages fully utilized,the proposed method can not only estimate the fault sections,but also identify the malfunctioned protective relays and/or circuit breakers as well as distorted/missing alarms,even for situations with complicated or successive faults.Finally,historical fault scenarios from two actual power systems are used for demonstrating the correctness and efficiency of the fault diagnosing method developed.