A new approach for distance protection using artificial neural network

This paper presents an artificial neural network (ANN) based approach for three-zone distance protection of transmission lines. The proposed neural network-based distance relay has multilayer feedforward architecture with two inputs and three trip/(no trip) output signals. The first output is responsible for main protection of the transmission line section, whereas the other two outputs provide back-up protection for the adjacent line sections. The input features of the neural network are the fundamental frequency voltage and current magnitudes extracted by discrete-Fourier transform. In this paper, the backpropagation training technique has been used for off-line training of the proposed ANN distance relay. The input-output patterns were simulated for faults covering the three zones of protection at different locations, operating conditions, and fault inception angles. The simulation results presented in this paper show that the proposed ANN distance relay is very effective in detection and classification of line faults and therefore can be considered as a good tool for main and backup digital distance protection.