Internal Fault/ Inrush Currents Discrimination Based on Fuzzy/ Wavelet Transform in Power Transformers

Transformers are major elements of any power systems. Normally they must be properly protected by differential relays. This protection system should be precise and reliable via implementation of strong algorithms that able to differentiate between faulted and unfaulted condition to fully grantee of power continuity. This system should be able to detect the non-faulted condition, such as inrush currents which should not be activated in this condition meanwhile; it must be activated in internal fault conditions as fast as possible. This paper presents an approach for differential protection of power transformers this uses wavelet transform (WT) and adaptive network-based fuzzy inference system (ANFIS) to discriminate internal faults from inrush currents. The proposed algorithm has been designed based on the differences between both amplitudes of wavelet transform coefficients in a specific frequency band and rising and decaying duration generated by faults and inrush currents. The performance of this simulated model is demonstrated by simulation of different faults and switching conditions on a power transformer using Matlab/Simulink software Package.