A wavelet transform based discrimination between internal faults and inrush currents in power transformers

Inrush currents in power transformers are non-sinusoidal, high magnitude currents generated due to flux saturation in the core during energization. This paper describes a decision method for discrimination between internal faults and inrush currents in power transformers using the wavelet transform based feature extraction technique. It is shown that the features extracted by the wavelet transform have a more distinctive property than those extracted by the fast Fourier transform due to the good time and frequency localization characteristics of the wavelet transform. As a result, by quantifying the extracted features, the decision for distinguishing an internal fault from an inrush current in different power transformer system can be accurately made. The experiment simulation studies have verified that the proposed method is more reliable and simpler, and is suitable for different power transformer systems.