Selecting ANN structures to find transmission faults

Abstract

Programming models based on artificial neural networks (ANN) have seen increased usage. ANNs are used in various fields (industry, medicine, finance, or new technology, among others). There is a wide range of possible power system applications of neural networks in operation and control processes, including stability assessment, security monitoring, load forecasting, state estimation, load flow analysis, contingency analysis, emergency control actions, HVDC system design, etc. This article features an automatic system that selects the most adequate ANN structure to solve any type of problem. The ANN Automatic Selection System (SARENEUR) was implemented in a specific case in order to obtain a neural network structure that shows better results in fault location within a two-terminal transmission line. The fault location is obtained according to the values of steady-state voltages and currents measured at one end.