Detection Classification and Location of Faults on 220 Kv Transmission Line with Statcom Using Wavelet Transform and Neural Network

A new scheme to enhance the solution of the problems associated with Transmission line protection with Statcom connected is presented in this paper. The fault detection is carried out by using energy of the detail coefficients of the phase signals and artificial neutral network algorithm used for fault type classification and fault distance location for all the types of faults for 220 KV transmission line. The energies of the all three phases A, B, C and ground phase are given input to the neural network for the fault classification. For each type of fault separate neural network is prepared for finding out the fault location. An improved performance is obtained once the neutral network is trained suitably, thus performance correctly when faced with different system parameters and conditions.