Classificação e localização de faltas em linhas de transmissão usando diferentes arquiteturas de redes neurais artificiais. / Classification and location faults in transmission lines, using different artificial neural networks architectures.

AUTOR(ES)
DATA DE PUBLICAÇÃO

2008

RESUMO

This work presents the development of algorithms for determination of the estimate of the distance of occurrence of fault in a high voltage transmission line, in relation to a local terminal, and also the classification of the fault type, using techniques based on artificial neural networks. The tests and the validation of the proposed algorithms are made using simulated data for the voltage and current phasors, in steady state, with use of the MATLAB language. The phasors are obtained with use of traditional calculation of short-circuit and real parameters of a known transmission line. In real cases the phasors would be obtained with samples of voltages and currents detected by protection devices located in the local and remote terminals of the transmission line in analysis. The simulations of the neural networks for the classification of the fault type and for the obtaining the estimate of the fault distance were done with two routines written in MATLAB taking into account measurement errors of the phasors. The obtained results allow to evaluate the efficiency and the accuracy of the proposed algorithms in relation to the already existent and known in the literature, and that use only electric equations.

ASSUNTO(S)

artificial neural networks fault location linhas de transmissão de energia elétrica transmission lines artificial intelligence redes neurais

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