Fault detection, classification and section identification on distribution network with D-STATCOM using ANN

This paper presents easy and efficient method of fault detection, fault classification and section identification in distribution networks with distribution static synchronous compensator (D-STATCOM) using artificial neural networks (ANN). The neural network uses Levenberg-Marquardt backpropagation algorithm for training. The D-STATCOM (average) model available in MATLAB has been modified to perform fault analysis. D-STATCOM is used for reactive power compensation, and regulates the system voltage by absorbing and generating reactive power. Fault is simulated for different function of D-STATCOM in which it absorbs reactive power like an inductor and generates reactive power like a capacitor. The present work reports the results of fault detection, fault classification and section identification whether it is forward fault and reverse fault in distribution network with D-STATCOM.