A Novel Power Management Strategy Based on Combination of 3D Droop Control and EKF in DC Microgrids

Voltage regulation and power management are necessary to maintain balance of supply and demand in DC microgrids. In such systems, power sharing is normally done through parallel operation of distributed energy resources equipped with droop controllers. However, low power sharing accuracy and not allowing the microgrid to maximise the available power from the renewable sources are two main problems associated with conventional droop control methods. In addition, the 2D droop method is a parameter‐dependent method for extracting maximum available energy from renewable sources. In this paper, a novel power management strategy based on the optimal 3D droop coefficients is developed for a DC microgrid. Optimal state estimation is attained using a combination of extended Kalman filter and adaptive recursive least square method. Reference currents of renewable energy sources (wind and solar) and battery energy storage system are estimated using the proposed prediction based model. The proposed strategy not only increases the power sharing accuracy but also remains the bus voltage around a nominal value. The performance of the proposed method is evaluated for the considered DC microgrid in two different scenarios. Results show the high effectiveness and robustness of the proposed method. It has been concluded that precise estimation of the sources reference currents and 3D droop coefficients are critical for optimal power management and bus voltage regulation in DC microgrids.