Abstract The accurate identification of the converter transformer magnetizing inrush current can ensure safety operation UHV DC transmission system. In differential protection transformer, it is extremely hard to distinguish between excitation generated when closed and Fault due internal fault, which leads frequent misoperation extent that access fails. This paper proposes a model based on empi...

This paper presents the use of Artificial Neural Networks (ANN) as a pattern classifier for the combined differential protection of generator-transformer unit with an aim to build a backup protection system to improve the overall reliability of the system. The proposed neural network model is trained and tested with an efficient Resilient Back propagation (RPROP) algorithm and Genetic Algorithm...

This article presents a novel technique to distinguish between magnetizing inrush current and internal fault current of power transformer. An algorithm has been developed around the theme of the conventional differential protection method in which parallel combination of Probabilistic Neural Network (PNN) and Power Differential Protection (PDP) methods have been used. Both PNN and PDP method ar...

This paper presents the use of ANN as a pattern classifier for differential protection of power transformer, which makes the discrimination among normal, magnetizing inrush, over-excitation, external fault and internal fault currents. The Back Propagation Neural Network Algorithm and Genetic Algorithm are used to train the multi-layered feed forward neural network and simulated results are comp...