A Comparative Study for Forecasting of Fault Locations in DC Microgrid Using Ordinary Least Squares Method and Non-linear Regression Method

For the occurrence of fault in the line, the action of the protection system should be prompt. It includes the swift identification, isolation, and localization of the fault. The fast detection of fault location enriches the reliability and effectiveness of the power system. The rapid restoration of the faulty section should be done to avoid the destruction of power supply to loads. Nowadays, DC microgrids undergo expansion and improvement due to their inherent properties. For the growth of DC microgrids, the protection scheme should ensure it works efficiently under any sort of fault. For DC microgrids, the line to ground (L-G) and line to line (L-L) short circuit fault severity and chances of occurrence is more. In this work, a comparative study has been done to detect the accurate L-G and L-L short circuit fault location in a DC line. For this study, the ordinary least squares (OLS) method and non-linear regression method have been implemented. Here, non-linear regression proves itself to be a better choice to detect low resistance L-G and L-L fault location in low voltage DC (LVDC) microgrid. This whole investigation is done in a DC microgrid model using MATLAB/Simulink.