Transmission line fault detection & location using discrete wavelet transform (DWT) and artificial neural network (ANN)

Document Type : Original Article

Authors

1 Asad Academy of Military Engineering, Aleppo, Syria.

2 University of Zagazig, Faculty of Engineering, Zagazig, Egypt.

3 Egyptian Armed Forces.

4 University of Benha, Faculty of Engineering, Shoubra, Egypt.

Abstract

Abstract:
T his paper presents a new fault detector and locator scheme based on (DWT) and
(ANN) for transmission lines. The main idea is to estimate faults detection, faulted
phases distinguishing and faults location. These processes are obtained by calculating
standard deviation of output signals from discrete wavelet analysis for all phase's
currents signals. The final results will be obtained by training the proposed ANNs. The
scheme has been implemented under Matlab-7- with utilization of toolboxes such as
Simulink, WT and ANN. A typical 220 kv transmission system with 100 km of
transmission lines has been simulated to evaluate the studied scheme. The results show
that the proposed scheme is efficient and easy in implement. Also, it is capable to
detect, classify and locate varies faults within a half cycle after their occurrences.

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