Model predictive control based autonomous DC microgrid integrated with solar photovoltaic system and composite energy storage

In this paper, a model predictive controller (MPC) is developed along with a simplified power management algorithm (PMA) for the autonomous DC microgrid. The autonomous DC microgrid includes a solar photovoltaic (SPV) unit integrated with composite energy storage (CES). The CES unit is composed of lithium-ion battery storage and supercapacitor storage units. Compared to conventional DC-microgrids with the SPV source alone, the integrated CES unit effectively handles the long-term and short-term power fluctuations due to the abrupt load variations and uncertainty in power generation by the SPV. This results in providing sustainable and reliable power supply to the remote accessing loads in rural electrification and improving the flexible operation of the microgrid. In addition, the integration of the supercapacitor with battery storage regulates the common dc-link voltage smoothly and is maintained at its reference value. Furthermore, with the proposed control strategy, the performance indices such as maximum peak overshoot, settling time, and steady-state error of the dc-link voltage have been improved as compared to the conventional control techniques. Besides that, the rate of change in battery current responds quickly to the step load variation. The efficacy and performance of the proposed system are verified and validated through MATLAB/Simulink and real-time simulation results using OPAL-RT OP4510 real-time simulator under various dynamic operating conditions.