accurate intelligently trained dc microgrid fault locator

Quickly locating a fault in micro-networks is essential for reliable power delivery. in this respect, to locate a fault, in a dc source line, auxiliary capacitors are fixed after circuit breakers to maintain power for the faulty circuit to generate strong signal for fault locating unit. the method is a one-ended one where the fluctuation in the line current is applied to a black box neural network (nn). the performance of the network is enhanced where intelligent trainer algorithms are employed. in this respect, several methods among them the classical levenberg–marquardt (lm) and intelligent african vultures optimization algorithm (avoa) are utilized. the results indicate that avoa delivers superior performance regarding the others. comparing the finding with several already published ones shows that the proposed method is promising