Transmission line fault detection & location using discrete wavelet transform (DWT) and artificial neural network (ANN) | ||||
The International Conference on Electrical Engineering | ||||
Article 66, Volume 6, 6th International Conference on Electrical Engineering ICEENG 2008, May 2008, Page 1-13 PDF (372.44 K) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/iceeng.2008.34306 | ||||
View on SCiNiTO | ||||
Authors | ||||
G. Kahela1; A. F. Abdel-Gawad2; W. Sabry3; F. El-Bendary4 | ||||
1Asad Academy of Military Engineering, Aleppo, Syria. | ||||
2University of Zagazig, Faculty of Engineering, Zagazig, Egypt. | ||||
3Egyptian Armed Forces. | ||||
4University 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. | ||||
Keywords | ||||
Transmission Line; Fault Detection; fault location; Discrete Wavelet Transform; Artificial Neural Networks | ||||
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