Deep Neural Network Based Transmission Line Fault Location Algorithm
Keywords:
Transmission lines; Fault; Wavelets; Principal Component Analysis; MATLAB/Simulink; NeuralNetwork; Decomposition CoefficientsAbstract
The transmission lines form a very important component of the power system. Hence, they have to work reliably in transmitting the power. It has been observed that fault occurrence chances on transmission lines are more. Hence to make the network reliable there arises a need for detection and isolation of faults taking place at various locations of the line. In this paper a method using Deep Neural Network is being implemented for location of fault. The research work is carried out for a network consisting of two busesand 100 km length line and 132 kV as working voltage. The feature extraction is done using the Discrete Wavelet Transform (DWT) in combination with Principal Component Analysis (PCA). The features are used in training the neural network. The model works on feed forwardalgorithm. The network helps in locating the faults with higher accuracy.
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