基于因子分析的母线负荷异常数据辨识方法

针对现有母线负荷数据异常辨识方法适应性差、辨识精度不高的问题,基于母线负荷数据现状剖析异常数据的基本特征,分析因子分析的理论及其应用于母线负荷异常数据辨识的原理,提出了基于因子分析的母线负荷异常数据辨识方法.该方法引入因子分析将母线负荷曲线分解为表征曲线正常时序变化规律的基本分量和表征曲线数据异常或随机波动特征的随机分量;同时基于负荷曲线随机分量给出了异常数据辨识的3σ判定准则.最后,以重庆某供电公司算例验证了所提方法较现有方法更具合理性、有效性.

Identification method of abnormal data in bus load based on factor analysis

To solve the problems of poor adaptability and low identification accuracy of the existing identification methods of bus load abnormal data, this paper profiles the basic characteristics of abnormal data based on the current bus load data. By examining the theory of factor analysis and its application in the identification of abnormal data of bus load, an identification method of abnormal bus load data based on factor analysis is put forward. With this method, factor analysis is introduced to decompose and reconstruct the bus load curve into the basic component which represents the normal time sequence variation law of the curve and the random component that represents the abnormal or random fluctuation characteristics of the curve data. At the same time, based on the reconstructed random component of the load curve, the 3σ criteria for identifying abnormal data are given. Finally, a case study of a power supply company in Chongqing shows that the proposed method is more reasonable and effective than the existing methods.