Presenting New Triple Methods for Fault Detection, Location, and Its Identification in DC Microgrid

Abstract

Unlike conventional AC systems, the DC systems cannot sustain high-magnitude fault currents. Therefore, detection, location, and identification of faults are the issues of great importance. On this basis, in this paper, three methods are investigated to detect a fault and determine its exact location and its type in DC microgrids. A module is installed at the beginning and end of all grid lines to implement the proposed method. Modules provide current and voltage sample signals and using the proposed triple algorithms analyze these signals online. Accordingly, modules use current amplitude, voltage amplitude, and current differential to detect fault occurrence. After detecting a fault, fault location algorithm activates to determine the fault location. On this basis, modules which have detected the fault use the fault current direction to determine its location. In the proposed fault-type identification algorithm, its type is identified by modules that detect the fault using the voltage drop that is caused by the fault. The proposed triple methods are implemented on two sample DC microgrids in DIgSILENT software. The results prove that the proposed method is capable of determining the occurrence of all types of DC faults, their exact location, and their identification considering structural uncertainties of the network. In addition, the proposed method can discriminate between transient and permanent faults with high accuracy.