Transformer magnetizing inrush current discrimination based on wavelet energy moment

JIN Yan， LIU Hua
（School of Information Engineering， Zhejiang University of Technology， Hangzhou 310023， China）

Abstract：Aiming at distinguishing the inrush current and internal fault current correctly，a new method-wavelet energy moment method，based on the wavelet and energy moment was presented. Matlab was used for the simulation calculation about an one-source power system. With the ability of multi-scale analysis and good time-frequency localization of wavelet transform，the “db2” wavelet was chosen to analyze the simulating data attained from the Matlab. The wavelet energy moments of high-frequency components of wavelet transforms were analyzed，to get the energy moment change rate which means harmonic content changes in different scales，then the ratios of the change rate which was labeled by ‘K’ were used to separate the inrush and internal fault current. The reference values of K were determined through simulating different parameters of transformer and fault types. The results indicate that the ratio of the inrush current is lower，the method correctly identifies inrush and fault currents in one power frequency cycle.
Key words： transformer； inrush current； wavelet energy moment； internal fault current； wavelet transform