PROJECT TITLE :

Model Predictive Control of Bidirectional DCDC Converters and ACDC Interlinking Converter

ABSTRACT:

It is possible that the voltage quality of renewable energy systems may be impacted by varying outputs from energy sources and variable power demand. An alternative to proportional-integral-derivative (PID) controllers is offered in this study for model predictive control. A model predictive current and power (MPCP) control scheme and a model predictive voltage and power (MPVP) control approach are part of the suggested strategy. The fluctuating output of renewable energy sources can be smoothed by managing the bidirectional dc-dc converter of the battery energy storage system using the MPCP algorithm. To maintain a consistent ac voltage supply and proper power flow between the microgrid and the utility grid, ac/dc interlinking converter (MPVP) control is used to regulate the converter. Finally, a system-level energy management strategy is created to ensure stable operation under varied operating modes, taking into account changing power supply, variable power consumption, battery state of charge, and electricity pricing. The proposed method is simpler and more effective than the usual cascade control, which is based on a 3.5-MW PV-wind-battery system with real-world solar and wind profiles, and is proven in simulation.