Neural network applications in protecting series compensated lines

This paper proposes a technique based on artificial neural networks for fault type classification and faulted phase selection to be used in the protection of series compensated transmission lines. The paper describes in detail the feature extraction, sampling rate, data window length, and training of the desired artificial neural networks (ANNs). The basic idea of the suggested technique is to use an artificial neural network to identify the fault based on extracting useful features in the desired spectra within a certain frequency range. System simulation and test results are presented and analyzed in this work to indicate the feasibility of using an ANN-based protection scheme in series compensated lines.