Hybrid neural network with bat approach for smart grid fault location

This paper proposes identification of fault location in smart distribution grid based on artificial intelligence using currents and voltages measured; with the help of sensor nodes in distribution system. The approach presented here is the hybrid bat algorithm with neural network, implemented on latest smart distribution system which comprises distributed generation. The fault lengths for various types of faults on distribution feeders are recognised using system parameters measured, before and after the occurrence of a fault. For verifying the performance of proposed algorithm, the MATLAB-based coding is developed and executed on sample modified IEEE test feeders. The performance of a proposed technique is compared with the simple neural network method. The proposed method founds more accurate and fast in speed.