本論文利用自適應類神經網路控制器於混合交流/直流微電網系統中的雙向交流對直流轉換器控制輸出，以調整微電網系統在併網模式、孤島模式下，分配直流微電網與交流微電網之功率傳輸、控制交流微電網之電壓及頻率。本論文使用架構是由風力發電系統、太陽能發電系統、雙向直流對直流轉換器以及雙向直流對交流轉換器所組成，其中以超級電容器與全釩氧化還原液流電池為基礎之混合儲能系統，應對再生能源波動特性，且直流微電網通過雙向直流對交流轉換器與交流側連接。類神經網路控制器亦與傳統比例-積分控制器在性能上做比較，在動態及暫態模擬案例下，於各性能表現上都有所改善。

This thesis proposes a hybrid AC/DC microgrid (MG) containing different renewable-energy power-generation systems, which consists of a wind power-generation system, a solar power-generation system, a bidirectional DC/DC converter, and a bidirectional AC/DC converter. The vanadium redox flow battery (VRFB)-based hybrid energy-storage system is connected to the DC MG via the bidirectional DC/DC converter, while the DC MG is connected to the AC MG via a bidirectional AC/DC converter. This thesis employs an adaptive neural network controller (ANNC) to distribute power transmission between the DC MG and the AC MG and control the voltage magnitude and frequency of AC MG under grid-connected mode and islanding mode, respectively. The performance of the proposed ANNC is also compared with the one of a traditional proportional-integral controller. The steady-state responses of the hybrid AC/DC MG are performed under time-domain simulations, while the dynamic and transient simulations of the hybrid AC/DC MG under different disturbance conditions are also achieved.

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