基于波形相关性分析的变压器励磁涌流识别新算法

A NEW ALGORITHM OF DISCRIMINATION BETWEEN INRUSH CURRENT AND FAULT CURRENT OF TRANSFORMER BASED ON SELF-CORRELATION ANALYSIS

提出一种利用数字信号处理中的相关函数的基本概念 ,对采样数据进行分析 ,计算采样数据在不同时段上的自相关系数 ,利用自相关系数的大小来区分变压器励磁涌流和内部故障差流的新方法。由于波形自相关性的定义中不仅包含波形幅值大小、形状的信息 ,而且还包含波形的相位信息 ,因此 ,文中所提出的波形相关性分析方法 ,不是单纯地利用涌流或故障电流的单一方面的特征 ,而是对波形进行有机、综合地分析。理论分析和 EMTP仿真结果均表明 :该算法原理清晰 ,识别正确 ,特征明显 ,且不受非周期分量和电流互感器饱和等的影响。

A new algorithm of discrimination between inrush currentand fault currentof transformer is brought forward based on self- correlation analysis,which is to calculate self- correlation coefficients of variant periods after analyzing the sam pling data and then discrim inate between inrush current and fault current by using the m agnitudes of the calculated coefficients. Due to the self- correlation of differential current comprises not only the information of the magnitude value,waveform ,but the phase information,all those information can be used to analyze organically and synthetically. Sim ulation studies with respect to different faults and inrush conditions are conducted,and the results prove that the proposed technique is able to offer fast responses on protection and accurately discriminate between inrush magnetizing current and internal faults.