Artificial neural network applied to power system protection

The main objective of this paper is the implementation of an alternative protection model to transmission lines applying artificial neural networks (ANN). An improvement in performance to the conventional distance relay is expected, once the ANNs can learn the different fault conditions as well as network changes in order to operate in less time correctly. In this work, the relay protection zone (96% of a transmission line length) was determined by forward and reverse single-line-to-ground fault condition. The input data shows the trip/no trip decision of a protection system. The approach used in this paper utilizes the voltage and current post-fault samples as input to a moving data window. The implemented neural network should capture the knowledge for the correct relay operation facing the different network conditions.