Fault Detection in DC Microgrid: A Transient Monitoring Function-Based Method

This article develops a transient monitoring function (TMF) based fault detection method for dc microgrids (DCMGs). In this method, the measured currents from one-end of the poles are first transformed into modal components. Then, the modal current is estimated using TMF concept. Afterward, the residual signal is defined as the absolute value of the difference between the modal and estimated currents. This signal has negligible fluctuations during the normal operation, while it experiences significant variations after fault occurrence. This feature is selected to reflect the fault incidence. To do so, the Teager-Kaiser energy operator is applied to the residual signal to amplify the changes, followed by a fault detection index (FDI). Comparing FDI with a threshold can reveal the fault. Furthermore, FDI can discriminate the faulty conditions in different operation modes of DCMG with a wide variation of fault conditions. To assess the developed scheme performance, a DCMG with different kinds of sources and loads is simulated in MATLAB/Simulink. The results confirm the quickness and the high accuracy of the proposed technique. Moreover, the method is validated in an experimental laboratory small-scale test bench. Finally, to demonstrate the superiority of the method, a comparative study with recent methods is presented.

Automated summary

This article proposes a fault detection method for dc microgrids (DCMGs) based on the transient monitoring function (TMF). The method utilizes modal components of the measured currents and estimates the modal current using TMF concept. A residual signal is defined as the absolute difference between the modal and estimated currents, which exhibits significant variations after a fault occurrence. The Teager-Kaiser energy operator is then applied to amplify the changes, followed by a fault detection index (FDI) to reveal the fault and distinguish faulty conditions in different operation modes of DCMGs.