fault location and classification in non-homogeneous transmission line utilizing breaker transients

In this paper, a single-ended fault location method is presented based on a circuit breaker operation using the frequencies of traveling waves. the proposed method receives the required data from voltage traveling waves with the aid of fast fourier transform (fft) and wavelet transform. then, the artificial neural network (ann) identifies the fault type and determines its location. for the evaluation of the proposed method, numerous simulations were done by varying parameters including fault resistance, fault inception angle, fault location, the presence of noise in waves, different sampling frequencies, and different structures of the power system in pscad/emtdc software. then, by using the matrix data obtained from voltage signals, the training process of the proposed algorithm is implemented in matlab software. the given results show the acceptable accuracy of the proposed technique in the classification of fault type and in the determination of fault location comparing with the previous studies. also, the maximum error of the proposed method is 1.29 percent. it stands for the robustness of the proposed scheme and is higher than those of the previous studies in the situations that may affect fault identification process.

fault location and classification in non-homogeneous transmission line utilizing breaker transients

in this paper, a single-ended fault location method is presented based on a circuit breaker operation using the frequencies of traveling waves. the proposed method receives the required data from voltage traveling waves with the aid of fast fourier transform (fft) and wavelet transform. then, the artificial neural network (ann) identifies the fault type and determines its location. for the evaluation of the proposed method, numerous simulations were done by varying parameters including fault resistance, fault inception angle, fault location, the presence of noise in waves, different sampling frequencies, and different structures of the power system in pscad/emtdc software. then, by using the matrix data obtained from voltage signals, the training process of the proposed algorithm is implemented in matlab software. the given results show the acceptable accuracy of the proposed technique in the classification of fault type and in the determination of fault location comparing with the previous studies. also, the maximum error of the proposed method is 1.29 percent. it stands for the robustness of the proposed scheme and is higher than those of the previous studies in the situations that may affect fault identification process.