Improved Model-Free Predictive Control Strategy for Three-Phase Grid-Connected Inverter with Double-Vector
Rui Tao1, Xu Wanlun2, Hu Cungang2, Feng Zhuangzhuang2, Lu Geye3
1. School of Internet Anhui University Hefei 230601 China; 2. School of Electrical Engineering and Automation Anhui University Hefei 230601 China; 3. School of Electrical Engineering Beijing Jiaotong University Beijing 100091 China
Abstract：In recent years, renewable energy has seen rapid development. Microgrids effectively integrate the increasing share of renewable energy, enhancing power systems’ energy efficiency, flexibility, and stability. In microgrids, three-phase grid-connected inverters play a crucial role in ensuring the efficient utilization of renewable energy, as their grid current performance directly impacts the overall operation of the microgrid. Model predictive control (MPC), known for its excellent dynamic performance and multi-objective control capabilities, can effectively regulate the grid current of inverters. However, finite-control-set MPC (FCS-MPC) suffers from significant grid current ripple due to the absence of modulation. Furthermore, FCS-MPC is highly sensitive to changes in inverter parameters. Any mismatch between the model and actual parameters can compromise the accuracy of current prediction, leading to grid current distortion and potentially affecting system stability. This paper proposes an improved double-vector model-free predictive control (DV-MFPC) strategy for three-phase grid-connected inverters.
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2025, Vol. 40 
