WT-ANN Based Approach For Improved Estimation of the Fault Location on 230 KV Shwesaryan-Mansan Transmission Line
This paper presents an improved approach for locating and identifying faults for high voltage overhead
Transmission line by using WT-ANN (wavelet-artificial neural network) technique. The proposed method uses one end data
to identify the fault location. The fundamental components of current signals measured at relay location are used as input
to train Artificial Neural Network. MATLAB® software with its associated Simulink® and simpowersystem® toolboxes
have been used to simulate the three phase 230 kV Shwesaryan- Mansan transmission line. The ANN was trained and tested
using various sets of field data, which was obtained from the simulation of faults at various fault scenarios (fault types,
fault locations and fault resistance) of the selected transmission line. Simulation results confirm that the proposed method
can be used as an efficient for accurate fault location tool on the transmission line fault analysis.
Index Terms— WT-ANN, Artificial Neural Network, fault location, Transmission line.