Recently, Finite Control Set Model Predictive Control (FCS-MPC) has been successfully applied in the grid-tied inverter with LCL filter. However, to achieve active damping and grid synchronization, many sensors are required, increasing cost and complexity. In addition, a considerable computational delay should be addressed when it is experimentally implemented, which may degrade the performance of overall system. In order to reduce the number of sensors, eliminate the computational delay, and enhance the control reliability of system, a novel FCS-MPC strategy with merely grid-injected current sensors is proposed, which contains four compositions: virtual flux observer, state observer, delay compensation and FCS-MPC algorithm based on estimations. A 3-kW/3-phase/110V experimental platform is established to validate that utilizing the proposed observations-based control method with only grid-injected current sensors is capable to obtain satisfactory performance of grid synchronization and high quality grid-injected current both under balanced and unbalanced grid voltage condition.

To improve the operation economy of the microgrid in a complex environment, a low-carbon operation strategy of microgrid with distributed compressed air energy storage is proposed. Firstly, considering the complex environment of regional microgrids, the coupling structure of distributed compressed air energy storage systems and microgrids is proposed. The new energy output and compressed air energy storage system model are established. On this basis, considering the consumption of new energy, a low-carbon operation strategy of the microgrid is constructed to improve the consumption level of new energy in the microgrid. Finally, the feasibility and competitiveness of the proposed low-carbon operation scheme are verified by simulation. The results show that the operation strategy of a low-carbon microgrid with distributed compressed air energy storage can reduce the operation cost by 57.3 %, and the new energy consumption rate can reach 97.2 %. The research results provide a theoretical basis and decision-making reference for applying distributed compressed air energy storage systems in complex environments.