Optimization of Virtual Inertia Control for DC Microgrid Based on Model Predictive Control

To mitigate voltage transients caused by power fluctuations in microgrid systems, this study investigates model predictive control and virtual inertia control for the voltage regulation strategy of energy storage unit converters. By drawing an analogy with the virtual synchronous machine equation in AC systems, the virtual capacitor inertia equation is derived for DC systems. Subsequently, model predictive control (MPC) is integrated with virtual inertia (VI) control, leading to the development of an MPC-VI cooperative control method. The reference value for the inner control loop is computed in real time using model prediction, enabling the injection of a counteracting signal opposite to the direction of DC bus voltage fluctuation during disturbances. This approach effectively suppresses rapid voltage variations and enhances system inertia. Furthermore, by incorporating a threshold-based mechanism, the issue of prolonged dynamic response time is mitigated. Simulation and experimental results demonstrate that, compared to conventional control strategies, the proposed MPC-VI method significantly attenuates instantaneous and severe voltage fluctuations, allowing for a more gradual voltage transition during transient events. Additionally, with the implementation of the threshold equation, the system returns to steady state without notable delay, preserving the droop characteristics of the control scheme.