An adaptive fuzzy based relay for protection of distribution networks

The high penetration of Distributed Generators (DGs) increases the need for monitoring and protection of the distribution system. The stochastic nature of the DGs may result in varying fault currents seen by the conventional over-current protection relays and thereby disturb the coordination of the relays. This necessitates an effective numerical relay that can capture the changes in the varying nature of DGs and take effective decisions according to the changing network conditions. Hence, an adaptive fuzzy relay, comprising of a fuzzy inference module and a neural network learning module, has been developed for deciding the optimal protection settings in the numerical relay corresponding to the changes in the network scenarios. A systematic comparison of the proposed adaptive fuzzy relay with conventional relay has been presented on a standard IEEE-test distribution system. The simulation results verify that the adaptive fuzzy relay is able to achieve the desired protection settings using a closed-loop approach.