Fault detection and location in a microgrid using mathematical morphology and recursive least square methods

Abstract

The concept of microgrids has been proposed as an economical, reliable, and efficient way to integrate a large number of distributed energy resources (DERs) into distribution networks. To ensure the safe operation of a microgrid fast and accurate fault detection and location are crucial. This paper proposes fault detection and location in a microgrid using mathematical morphology (MM) and recursive least-square (RLS) methods. The proposed method first applies dilation and erosion median filter (DEMF) on a current signal to detect and classify the faults in microgrids. Then, the RLS method estimates the fault location using a differential equation derived from an equivalent model of the microgrid. The performance of the proposed method is evaluated on a medium voltage microgrid test system through simulations using MATLAB/SIMULINK. The simulation results depict that the proposed method provides faster fault detection and accurate fault location.