雙向電動車充電器對電網提供多項優勢，包括實時功率支援，通過供應電力來滿足負載需求，在電網負載低的時候接收電力，補償電網電流中的諧波，以及減少再生能源發電的不確定性。然而，雙向充電器可能會對電網引入有害諧波，導致電力質量下降、效率降低和不穩定性增加。因此，對於雙向電動車充電器來說，有效的控制策略至關重要。本論文提出了一種有限控制集模型預測控制（MPC）用於雙向電動車充電器。該方法包括用於控制直流/直流轉換器的MPC和用於控制帶LCL濾波器的交流/直流轉換器的MPC。我們使用MATLAB/Simulink展示了在穩態性能、動態性能和魯棒性分析下的模擬結果。結果顯示，與傳統的PI控制方法相比，所提出的MPC方法可以實現良好的穩態性能、快速的瞬態響應，並且對於電網電感變化具有魯棒性。此外，通過在OPAL-RT實時模擬測試環境中進行實際測試，我們驗證了模擬結果的有效性。;Bidirectional EV chargers offer several benefits to the grid, including real power support, meeting load demand by supplying power, receiving power during low grid loads, compensating for harmonics in grid current, and reducing uncertainties in generating renewable energy sources. However, bidirectional chargers can introduce harmful harmonics to the grid, leading to poor power quality, decreased efficiency, and instability. Therefore, effective control strategies are essential for bidirectional EV chargers. This thesis presents a finite control set model predictive control (MPC) for bidirectional EV chargers. The proposed method consists of MPC to control DC/DC converter and MPC to control AC/DC converter with an LCL filter. The simulation results under steady-state performance, dynamic-state performance, and robustness analysis are presented using MATLAB/Simulink. The results show that the proposed MPC method can achieve good steady-state performance, fast transient response, and robustness against grid inductance changes compared with the conventional PI control method. Furthermore, the validity of the simulation results is verified through real-life experimentation in a real-time simulation testing environment with OPAL-RT.
