The Estimate of Fault Location based on Transmission Tower Coordinates

Abstract

This study was conducted to predict the fault location based on tower coordinates using the Artificial Neural Network (ANN). The electrical power system modeled made use of an actual system including 150 kV transmission line with KP bus to the GS bus and 64 km length while ANN technique was used to coordinate the points for the fault location on the electric power transmission line due to its ability to predict what will happen in the future based on the pattern of past events. The ANN was tested and trained at certain iterations with different data which were simulated for short circuit fault type at several locations to achieve the best value. The results obtained with fault location coordinates were in the form of latitude and longitude while the simulation results for the AG fault were at 0.0381 km distance starting from the KP bus to the GS bus at 8,246 kA. Moreover, the estimated error values were found in the 2-phase fault to the ground at 4.01×10- 3 % while the ANN structure performance showed the MSE value to be 2.08 - 4 % with a very small error value of 0.57 % and this means it is included in the existing standard tolerance category. The data validation of this system modeling was conducted on the short circuit current value between simulation and theoretical estimation.