The backpropagation algorithm applied to protective relaying

Abstract

Distance relays have attracted considerable attention for the protection of transmission lines. They are usually designed on the basis of fixed settings. Therefore, the reach of such relays is affected by the changing network conditions. The implementation of a pattern recognizer for power system diagnosis can provide great advances in the protection field. This paper demonstrates the use of an artificial neural network as a pattern classifier for distance relay operation. The backpropagation algorithm is utilized for the learning process. The scheme utilizes the magnitude of three phase voltage and current phasors as inputs. An improved performance with the use of an artificial neural network approach is experienced once the relay can operate correctly, keeping the reach when faced with different fault conditions as well as network configuration changes.