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ANN Based Discrimination of Inrush and Fault Currents in Three Phase Power Transformer using Statistical Approaches

This paper proposes a discrimination of inrush current and fault current of power transformer for proper protection scheme, called as DSIF. In the proposed scheme, feed forward artificial neural network (ANN) is used as a classifier that addresses the challenging task of detecting magnetizing inrush and fault currents. The key aspect of this task is to incorporate an ANN that is trained on the statistical data samples using back-propagation training algorithm. These data samples are formulated using statistical approaches from the combination of differential relay and over current relay based protection scheme for a three phase power transformer. Precisely, this protection scheme provides the differential current signal and over current signal during faulty conditions. Thus, our proposed DSIF can address the challenging task of detecting the magnetizing inrush current and fault current. In order to evaluate the proposed scheme, MATLAB simulation based experiments have been conducted. The results confirm that the proposed scheme works well for the discrimination of magnetizing inrush and fault currents for a three phase transformer comparing to the other models.