Revolutionizing Hybrid Wind/Photovoltaic/Battery Systems: State-of-the-Art Predictive Control and Real-Time Testing for Optimal Performance

Abstract

This article presents the design of a continuous-time model predictive control (CTMPC) incorporating a disturbance observer (DO) for ensuring robustness against load disturbances. The developed model addresses the control effectiveness in grid-connected hybrid energy systems, under unknown variations of parameters in different operating conditions. These multiple power conversion subsystems are integrated to compose the entire configuration: a boost DC/DC converter for the photovoltaic generator, a bidirectional DC/DC converter for the battery energy storage system, an AC/DC converter for the wind turbine, and a voltage source inverter (VSI) for interfacing with the grid. All of these components are connected through a common DC bus, which is the backbone of the hybrid system. To mitigate disturbances affecting the performance of power converters based on the renewable energy sources, a DO is added to the proposed CTMPC. This ensures a balanced distribution of active power between the common DC bus and the grid via the bidirectional DC/DC converter and maintains a stable DC-link voltage through the VSI. Extensive simulations performed in the matlab/simulink under different operating scenarios prove the superiority of the CTMPC-DO controller against conventional proportional-integral. The obtained results showed near-perfect tracking performance and significantly improved overall system stability, demonstrating the potential of the CTMPC-DO approach to replace conventional control strategies. Finally, an experimental validation of the proposed CTMPC-DO method by using the hardware-in-the loop was developed to verify the applicability and efficiency of the controller in a DC microgrid. This largely proves the ability of the developed controller in handling hybrid energy system complexities and this is considered a major contribution toward improving control strategies in DC microgrids.