This paper presents an efficient wavelet and neural network (WNN) based approach for distinguishing magnetizing inrush currents from internal fault currents in three phase power transformers. The wavelet transform is applied first to decompose the current signals of the power transformer into a series of detailed wavelet components. The values of the detailed coefficients obtained can discrimin...

This paper presents an efficient wavelet and neural network (WNN) based algorithm for distinguishing magnetizing inrush currents from internal fault currents in three phase power transformers. The wavelet transform is applied first to decompose the current signals of the power transformer into a series of detailed wavelet components. The values of the detailed coefficients obtained can accurate...

This paper presents the development of a wavelet based algorithm, for distinguishing between magnetizing inrush currents and power system fault currents, which is quite adequate, reliable, fast and computationally efficient tool. The proposed technique consists of a preprocessing unit based on discrete wavelet transform (DWT) in combination with an artificial neural network (ANN) for detecting ...

In this work, a new approach applied to digital differential protection relay for a large power transformer is presented. First, the Fourier sine and cosine coefficients required for fundamental, second, third and fifth harmonic extraction have been determined using rectangular transfer technique. Then, these harmonics have been used in harmonics restrain and blocking techniques applied to diff...

For the current transformers (CTs) on the delta side measure the line current instead of the phase current, line current differential protection is adopted in transformers connected in wye-delta mode currently. However, the symmetry feature of inrush current in line current differential protection may invalidate the inrush current restrained criterion. A calculating method of current through de...

This study presents a novel technique based on Support Vector Machine (SVM) for the classification of transient phenomena in power transformer. The SVM is a powerful method for statistical classification of data. The input data to this SVM for training comprises fault current and magnetizing inrush current. SVM classifier produces significant accuracy for classification of transient phenomena i...

Among the most noticeable root causes of improper performance in power transformers, internal short circuit faults can be noted and if not quickly be identified and addressed in the accepted time interval, irrecoverable damages such as interruption or even collapse of the network connected to the power transformer would happen. In this contribution, three-phase transformer behaviors under magne...

When a transformer is energized the phenomenon of magnetizing inrush current occurs and causes a pseudo tripping signal to the differential relay which leads to the problem of mal operation or false tripping of the relay. In order to avoid this false tripping of the differential relay and for safe operation of the transformer the distinction of inrush current with internal fault current is very...