Kalman filter-based power compensation strategy for Microgrids under uncertain disturbance

The measurement and model errors always exist in the sample or data analysis part of Microgrids (MGs) system, bringing oscillation and inaccuracy to the controller and energy management system (EMS). This paper proposed a Kalman filter (KF)-based control strategy for the battery energy storage system (BESS) in MGs with integrated renewable energy sources. The control scheme aims at minimizing the active and reactive power purchased from the main grid by regulating the output current of BESS. A detailed model of a wind-PV-battery MG is built, and the sampling and measurement inaccuracy is considered. The control strategy is tested under rapid power supply oscillation and load changes, and the results show good performance.