Fault detection on a ring-main type power system network using artificial neural network and wavelet entropy method

Abstract

This paper intends to present an approach to classify different types of faults and to identify the location of the faults in a non-radial power system network using ElectroMagnetic Transients Program(ATP/EMTP)software and Artificial Neural Network(ANN).Firstly, a balanced threephase system is designed with a RLC load and then different types of faults(single line to ground fault, line to line fault, double line to ground fault and three phase fault) are created at various points of the transmission line. The transmission line model is simulated using the EMTP software. The resulting current waveforms under different fault conditions are observed from the sending end. Fault occurs at the point where peaks appear in the current signal when viewed from the sending end. These current waveforms are analyzed using the wavelet toolbox in MATLAB and the entropy values of the current signals, so obtained, are given as input to the artificial neural network for automatic fault classification and identification of the faulty line. This scheme is also tested under different types of faults with different fault resistances and varying fault locations and the results show that it is able to discriminate the faults and identify the fault locations rapidly and correctly.

Comparison of Various Mother Wavelets for Fault Classification in Electrical Systems

“…AI has been combined with wavelets to improve the accuracy of fault classification algorithms in electrical systems [7][8][9][10][11][12]. AI enhances accuracy and reduces the time to classify faults.…”

“…AI enhances accuracy and reduces the time to classify faults. Wavelets with neural networks (NNs) have been used to detect and identify fault types in transmission line systems [7][8][9][10][11]. The algorithm makes use of wavelet transform-based approximate coefficients of three-phase voltage and current signals obtained over a quarter cycle to detect and classify faults.…”

“…However, many studies only focus on transmission lines or transformers, and few have combined the two components when analyzing systems. Most of the references use wavelets to detect and identify fault types in electrical systems, but they do not analyze the mother wavelet [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]20,21]. Additionally, there are research articles that compare mother wavelets [18,19,22,23].…”