Hybrid Renewable Energy Sources for Grid Connected System with Model Predictive Control for Maximum Power Extraction

This paper proposes a finite-set model predictive torque control (FS-MPTC) for a wind energy conversion system (WECS) to maximize power extraction. The method focuses on optimizing the wind generator system (WGS) control to efficiently convert wind energy into electrical power. In parallel, the paper also explores the application of model predictive control (MPC) for photovoltaic systems (PVS). With this method, the photovoltaic system is guaranteed to continually extract the maximum power, maximizing energy acquisition in the face of fluctuating solar irradiation conditions. Additionally, MPC is utilized on the grid side to manage and regulate both active and reactive power, ensuring stable and efficient operation of the entire energy system. The hybrid system includes both WGS and the PVS which are connected to the same DC link via controlled rectifier and DC-DC converter, respectively. Then, a three-phase inverter is used to feed the power into the grid. The MPC is adopted in this work to eliminate the proportional-integral (PI) controllers and the associated tuning complexities. Moreover, the MPC offers a more responsive control strategy, which is necessary for managing the dynamic response of renewable energy sources. The system performances are validated through simulations and testing under fixed wind speed and varying solar irradiation. This testing condition highlights the potential of MPC in improving the efficiency of hybrid renewable energy systems by demonstrating the capacity to maintain maximum output power and reliable grid integration.