Modular multilevel converters have emerged as a common solution in high-voltage and medium-voltage applications due to their scalability and modularity. However, these advantages come at the cost of increased control complexity, particularly when compared to other multilevel converter topologies. This paper proposes a new combined control strategy based on virtual synchronous generator (VSG) control and capacitor voltage balancing (CVB) method. The VSG control is applied for power sharing and inertia emulation to increase the dynamic response and improve system stability while the CVB method is used to redistribute the energy stored in the capacitors of the submodules (SMs) in order to ensure uniform voltage levels and equalize the voltage across the capacitors. The simulation results as well as experimental ones confirm the feasibility and effectiveness of the proposed method, enhancing the performance of the energy conversion system.

This paper investigates the emerging field of grid-connected wind-powered pumping kite generator system (PKGS), focusing on the challenges associated with the generator/motor speed control. Conventional use of proportional–integral (PI) controllers faces difficulties in meeting requirements for dynamic response, tracking performance, stability, and disturbance rejection encountered in this technology, notably the periodical variation in the rotational speed reference in maximum power point tracking in generation phases and the dynamic response for the step reference in transient ones. To overcome these limitations, a model-free controller (MFC) approach is introduced, also known as intelligent PID controllers. Unlike traditional methods, MFC does not rely on a control model of the system and adapts to uncertainties and disturbances through online estimation based on the system’s input–output behavior. To further improve the control performances, a tracking differentiator based on a nonlinear hyperbolic tangent function is integrated in the MFC. The effectiveness of the proposed strategy is proved through simulations in MATLAB/Simulink. The results highlight the superior performances of the proposed MFC approach in terms of speed control accuracy, response time, and robustness.