Internal fault current identification based on wavelet transform in power transformers

This paper presents a novel approach for differential protection of power transformers. This method uses wavelet transform (WT) and adaptive network-based fuzzy inference system (ANFIS) to discriminate internal faults from inrush currents. The proposed method has been designed based on the differences between amplitudes of wavelet transform coefficients in a specific frequency band generated by faults and inrush currents. The performance of this algorithm is demonstrated by simulation of different faults and switching conditions on a power transformer using PSCAD/EMTDC software. Also the proposed algorithm is tested off-line using data collected from a prototype laboratory three-phase power transformer. The test results show that the new algorithm is very quick and accurate.