Procena mesta nastanka kvara na električnom vodu primenom veštačkih neuralnih mreža

Abstract

This paper deals with the application of neural networks to fault location on extra-high voltage (EHV) transmission lines. A relatively simple power system, consisting of two 220 kV power grids connected with one transmission line, has been modelled using MATLAB/Simulink software. Simulating different fault scenarios (fault types, locations, resistances, and inception angles), the proposed neural network fault locator was trained using various sets of terminal line data (line-to-line voltages and phase currents). Feedforward networks have been employed along with the backpropagation algorithm. An analysis of the neural networks with a varying number of hidden layers and neurons per hidden layer has been performed in order to validate the choice of the neural networks in each step. All analyses were carried out using Neural Network Toolbox.