一种电能质量异常数据剔除的有效方法

An Effective Method for Eliminating Abnormal Date of Power Quality

海量的电能质量数据常存在异常数据,会干扰电能质量数据分析,甚至带来错误的分析结果。为此,提出一种新的电能质量异常数据剔除方法,用于电能质量在线监测数据及测试数据中的异常数据发现。对于电能质量稳态数据,首先是根据各指标的业务取值范围对数据进行初判,找出整体异常数据,分析其数据曲线的斜率变化率,滤除曲线的异常点;其次是根据各数据之间的业务关系对数据进行相互校验,完成电能质量稳态数据的异常剔除。对于电能质量扰动波形数据,采用基于S变换的方法对待筛选数据和异常模板库进行对比,与异常模板库中信号相近的扰动波形,认为是异常数据,从而完成电能质量扰动波形数据的异常剔除。该方法已用于某省级电能质量监测系统中,实践证明该方法有效、可行。

There are often existing abnormal data in mass power quality data which may intervene analysis on power quanty data and even cause false analysis results. Therefore, this paper proposes a kind of new method for eliminating abnormal da- ta of power quality which is used in online monitoring data and discovering abnormal data in testing data of power quality. For steady-state data of power quality, it is firstly to make initial judgement according to business scope of each index, find out the overall abnormal data, analyze rate of change of slope of data curve and remove abnormal points of the curve. Sec- ondly, mutual verification is carried out according to business relationship of various data for accomplishing abnormal data elimination of steady-state data of power quality. For disturbance waveform of power quality, it uses method based on S transformation to compare data for screening and abnormal template base and considers disturbance waveform of signal simi- lar with that in abnormal template base is abnormal. Thereby, abnormal data elimination for disturbance waveform data of power quality is finished. This method has been applied in some provincial level power quality monitoring system and prac- tice proves effectiveness and feasibility of this method.