Improving the Performance of Distance Relay-Based Artificial Neural Network

Distance relays for protection of power transmission lines used, which can be based on fixed stings Adjusted. But usually, the amplitude of operation of these relays changes with changing network conditions (network topology, load value, output value, etc.) and causes the relay to malfunction, using methods that can process information and pattern recognition, such as the use of fine processors and intelligent algorithms can use new relays that have high accuracy and thus achieve proper protection. In this paper, a distance relay is simulated by a neural network and it is observed that the neural relay has higher accuracy than a normal relay. In addition to fault detection and location, the type and phase of the fault can perform simultaneous protection of three phases. As a result, the number of line relays can be reduced by using neural relays. The MLP neural network is used to simulate the distance relay.