High voltage transmission line fault classification based on neural network trained by particle swarm optimization

The use of neural system way to deal with recognize the fault classification of the transmission lines is led in this review. Fault turned into an essential issue that dependably happen inside the transmission lines. The distinctive fault has been distinguished in the transmission lines and it must be spotted and characterized precisely and effectively. Stability of the system must be maintaining isolated. New approach has been made based on artificial neural network (ANN) for the fault classification. The ANN classifier are tried by various and different sorts, areas, resistances and commencement points. Every one of these factors then will be tried and thought about by Particle Swarm Optimization (PSO) algorithm to the outcomes got. Extension of simulation carried out by MATLAB with the highlight PSO features and advantages over others algorithms that very reliable, fast and efficient. This research has shown that the resulted in the excellent classification performances is extremely accurate and error of performance is decrease when apply the PSO algorithm. The result and performance of machine learning algorithm is proven that the PSO capable to optimizing the solution.