A fast wavelet transform based algorithm for discrimination of transformers magnetizing inrush currents from faults

Transformers are crucial equipment in a power system, which require reliable solutions for their protection to ensure smooth operation. Identification between internal fault current and inrush current is a challenging problem in the design of transformer protection relay. This paper proposes an algorithm based on discrete wavelet transform (DWT) for discriminating among inrush current and internal fault in power transformers. The technique is based on pattern recognition of the instantaneous differential currents using wavelet transform. The high -frequency components generated during the disturbance are extracted using a wavelet-based processor stage. In this method, an appropriate criterion at a suitable frequency range is developed. The proposed algorithm is evaluated using various simulated inrush and internal fault current cases on a power transformer that has been modeled using Electromagnetic Transients Program software. The results obtained from the proposed technique show good accuracy for discriminating faults in the considered system. In addition, the proposed algorithm uses data of the differential current with a time of quarter cycle under the analysis.

Keywords:

internal fault , power transformer , discrete wavelet transforms , inrush current