An alternative approach using artificial neural networks for power transformer protection

摘要

This work presents an alternative approach using the differential logic associated to artificial neural networks (ANNs) in order to distinguish between inrush currents and internal faults for the protection of power transformers. The radius basis function (RBF) neural network is proposed as an alternative approach in order to distinguish the situations described, using a smaller amount of data for training purposes, in some cases, if compared with networks such as the multi-layer perceptron (MLP). The ANN results are then compared to those obtained by the traditional differential protection algorithm. An ANN approach for correction of saturated current signals is also presented.