標題: 風力發電系統強健控制與性能監測技術研究
Robust Control and Structural Measurements of Variable-Speed Wind Turbine System
作者: 鄭泗東
Cheng Shih-Tung
國立交通大學機械工程學系(所)
關鍵字: 風力發電機;遠端監控;阻抗源變流器;順滑動控制;倒階控制;風速預測;wind turbine;remote sensing;Z-source inverter;sliding mode control;backstepping control;wind speed prediction.
公開日期: 2011
摘要: 本研究計畫之核心研究內容為全橋半控型整流器及阻抗源變流器整合之風力發電電力轉換系 統,並進行基於倒階控制法則之積分型順滑模態控制應用於可變速風力發電機。研究載具為5KW 永 磁同步發電機,使用32 位元數位控制板實現可變結構型的積分型順滑動控制,以驗證控制法則之性 能,改善風能的瞬時變化性對輸出功率的影響,並追蹤風力機運轉點,使其保持在最大功率點運轉, 提高發電效率以及實用性,開發高效率的小型風力發電系統。同時進行建立葉片應力應變之無線感測 平台監測及控制技術,結合風場監測平台、結構負載感測、網路伺服器、資料庫,建立一套小型風力 發電系統即時監測安全防護系統架構。並由長期監控的風力發電系統資料庫,以類神經網路(ANN)及 馬爾科夫轉移矩陣法(Markov Models)進行短期風速與風向預測系統。
This project carries on the research and conduct a half-controlled converter and Z-source inverter based wind energy transformation system. The control of variable-speed permanent-magnet synchronous wind turbine generator is based on integral-type sliding mode control via backstepping approach which is performed by a 32-bit digital signal controller. This control strategy presents attractive features such as robustness to parametric uncertainties of the turbine for ensuring stability in operation regions. The wind turbine is instrumented with sensors for recording turbine operational parameters, meteorological conditions, electrical quantities and mechanical loads in terms of strain gauge signals. The wireless data acquisition system will be designed and implemented to track the blade deformation during operation. This project also proposes Artificial Neural Network model and Markov Models for local area short term wind speed prediction.
官方說明文件#: NSC100-2221-E009-134
URI: http://hdl.handle.net/11536/99216
https://www.grb.gov.tw/search/planDetail?id=2340504&docId=368752
顯示於類別:研究計畫


文件中的檔案:

  1. 1002221E009134.PDF