Bidirectional DCDC Converters and ACDC Interlinking Converter Model Predictive Control

Variable power demand and varying energy source outputs may have an effect on the voltage quality of renewable energy systems. This study proposes a model predictive controller as an alternative to proportional-integral-derivative (PID) controllers. The proposed strategy includes a model predictive current and power (MPCP) control scheme and a model predictive voltage and power (MPVP) control method. By using the MPCP algorithm to control the bidirectional dc-dc converter of the battery energy storage system, it is possible to smooth out the fluctuating output of renewable energy sources. The ac/dc interlinking converter (MPVP) control is used to regulate the converter in order to maintain a constant ac voltage supply and proper power flow between the utility grid and the microgrid. The creation of a system-level energy management strategy, which takes into account the changing power supply, variable power consumption, battery state of charge, and electricity pricing, is the final step in ensuring stable operation under a variety of operating modes. The proposed method, which is based on a 3.5 MW PV-wind-battery system with real-world solar and wind profiles and is demonstrated in simulation, is more straightforward and efficient than the conventional cascade control.