本篇研究論文利用直軸訊號注入法並結合智慧型控制器提出一新型主動式孤島偵測法，所提之主動式孤島偵測法基於將擾動訊號透過與直軸電流的結合轉換至換流器系統，此直軸電流的擾動在市電脫離時將導致RLC負載端的頻率偏移。所提之孤島偵測法將於UL1741安全規範的反孤島測試系統中評估可行性，此直軸擾動訊號注入法旨在達成類似零的盲點偵測區和最小化功率品質的影響並且在不需其它感測元件或裝置的情況下簡易執行。此外為近一步的增進孤島偵測能力，本論文提出小波模糊類神經網路控制器來取代傳統的比例積分控制器於孤島偵測控制法中，此小波模糊類神經網路具有倒傳遞與模糊類神經之智慧學習演算功能，最後，於實驗結果中驗證所提之智慧型直軸訊號注孤島偵測法之可行性與有效性。 A novel active islanding detection method using d-axis disturbance signal injection with intelligent control is proposed in this study. The proposed active islanding detection method is based on injecting a disturbance signal into the system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the grid is disconnected. The feasibility of the proposed method is evaluated under the UL1741 anti-islanding test configuration. The proposed d-axis disturbance signal injection method is intended to achieve a reliable detection with quasi zero non-detection zone (NDZ), minimum effects on power quality and easy implementation without additional sensing devices or equipments. Moreover, to further improve the performance of islanding detection method, a wavelet fuzzy neural network (WFNN) intelligent controller is proposed to replace the proportional-integral (PI) controller used in traditional injection method for islanding detection. Furthermore, the network structure and the on-line learning algorithm of the WFNN are introduced in detail. Finally, the feasibility and effectiveness of the proposed d-axis disturbance signal injection method is verified with experimental results.
