Fault identification in electrical power systems - Quyen Huy Anh; Nguyen Phat Loi (Journal of Technical Education Science, 2014)
This paper proposed using neural networks to detect and classify the types of electrical faults on transmission lines. The data set was created by using Power World software and online training with Matlab software. Efficient identification is illustrated by example fault identification and classification of power system IEEE 9 buses, with the number of training samples is 1280 which are corresponding to the failure mode. Feed – forward neural networks in the one hidden layers with high accuracy, the result that demonstrates can replace protective relay systems in power transmission with recognition system which is proposed.