An Adaptive Virtual Synchronous Generator based Model Predictive Control with Enhanced Frequency Support Capability in Micro-Energy Systems

Micro-energy systems are essential to integrated multiple distributed renewable energy. However, due to lack of equivalent inertia, a slight power fluctuation will lead to severe frequency oscillation. Virtual synchronous generator (VSG) control strategy is introduced to cope with this problem. The classical VSG solution includes the outer power droop loop and the inner cascaded voltage and current double closed loop, which increases the complexity of system, resulting in reduced dynamic response speed. Additionally, the virtual synchronous generator freedom, adjustable via parameters, has not been fully exploited, leading to insufficient utilization of this technique for multiple operation conditions. In this work, we propose an adaptive virtual synchronous generator based model predictive control in micro-energy systems. With the proposed solution, parameters are adaptively adjusted. Meanwhile, the accuracy of voltage and current tracking are enhanced with the multi-step predictive control technology. Finally, the effectiveness of the proposed strategy is validated with experimental data.