Power transformer differential protection scheme based on symmetrical component and artificial neural network

This paper proposes a differential protection scheme for power transformers using the symmetrical component and neural network algorithms. It utilizes the artificial neural network (ANN) as the pattern classifier and the symmetrical component of current as the input´s ANN. Extensive simulation studies show that the symmetrical components of current provide suitable inputs for classification or different transient cases. The proposed scheme achieves outstanding performance and the ability to discriminate internal faults fast and accurately. Details of the proposed relay design are given in the paper. Some performance studies results are also given.