A Hybrid Wavelet-ANN-Based Protection Scheme for FACTS Compensated Transmission Lines
Автор: A.Y. Abdelaziz, Amr M. Ibrahim
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 7 vol.5, 2013 года.
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This paper proposes an approach for the protection of transmission lines with FACTS based on Artificial Neural Networks (ANN) using Wavelet Transform (WT). The required features for the proposed algorithm are extracted from the measured transient current and voltage waveforms using discrete wavelet transform (DWT). Those features are employed for fault detection and faulted phase selection using ANN. The type of FACTS compensated transmission lines is the Thyristor-Controlled Series Capacitor (TCSC). System simulation and test results indicate the feasibility of using neural networks using wavelet transforms in the fault detection, classification and faulted phase selection of FACTS compensated transmission lines.
Neural Network, Discrete Wavelet Transform, Distance Protection, FACTS, Fault Detection & Classification
Короткий адрес: https://sciup.org/15010440
IDR: 15010440
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