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系統識別號 U0026-2006201616024600
論文名稱(中文) 利用現地風場資料進行風機安裝評估與風機發電檢證
論文名稱(英文) Assessment of Wind Turbine Installation and Evaluation on Wind Power Generation Using On-Site Wind Data
校院名稱 成功大學
系所名稱(中) 機械工程學系
系所名稱(英) Department of Mechanical Engineering
學年度 104
學期 2
出版年 105
研究生(中文) 戴資桓
研究生(英文) Tzy-Hwan Tai
學號 n16034182
學位類別 碩士
語文別 英文
論文頁數 111頁
口試委員 指導教授-林大惠
共同指導教授-吳毓庭
口試委員-宣崇堯
中文關鍵字 風機  測風塔  光達  功率曲線 
英文關鍵字 Wind turbine  Meteorological mast  LiDAR  Power curve 
學科別分類
中文摘要 本研究首先以風數據評估風機安裝評選合適之風機,以台南七股鹽山觀光區之「中小型風力機系統測試實驗室」為預設地點,並在此地設置一座測量高度為13m的小型測風塔進行風速觀測。接著以韋伯分佈擬合風速分佈後計算風機發電量,再以成本會計中資本預算決策之還本期間與內部報酬率來評選合適的小型風機進行分析與討論。而所有被評選之小型風機必須為經過國際認證機構驗證,符合IEC 61400-2之規範。
另一部份分析風機實際發電量狀況,透過資料採集與監控系統(SCADA)取得桃園大潭地區設置的兩隻風機本身之數據,包含一分鐘平均葉片轉速、偏向角與發電數據。並同時利用LEOSPHEREWINDCUBE v2固定式光達系統至風機現場測量風數據。而光達以都卜勒波束掃瞄法(DBS)收集,依四個方向相繼地發出傾角28°的光束量測徑向風速,第五條垂直光束直接量測垂直風速,以每分鐘約15筆資料解析度計算量測高層一分鐘平均之風速與風向。接著驗證並分析紊流強度後篩除風速小於2m/s數據,將風機偏向角與風向做回歸分析做補償修正。再透過交互比對風向及修正後的轉向角資料,還原風機在不同入流角時之發電功率對葉片轉速的功率曲線。最後統計入流角對風機發電功率的影響後,結果顯示入流角大於15°即會明顯降低輸出功率,且程度並不小於風機受到尾流的影響。
英文摘要 This research initially assesses wind turbine installation to select a suitable wind turbine. The default location is at the “Medium and Small Wind Turbine Testing Laboratory” which is next to the Salt Mountain tourist area in Cigu, Tainan. In order to measure wind data, a 13m height small meteorological mast was erected to install cup anemometers and wind vanes. Then, statistical wind data was fitted using a Weibull distribution to calculate the energy production of the turbines, and then an analysis and discussion of how to choose a suitable turbine in view of internal rate of return (IRR) and payback period were conducted. Nevertheless, an economical turbine is relevant to initial capital cost. All of the selected turbines were required to be certified by international certification bodies and to conform to IEC 61400.
Another part of the research was an evaluation of wind power generation. Data from two large wind turbines was acquired from the Supervisory Control and Data acquisition (SCADA) system, deployed in the Taoyuan Tatan District. The SCADA data include the blade angular velocity, turbine yaw angle and power production recorded as a 1 minute average value. At the same time, the LEOSPHERE WINDCUBE v2 LiDAR system was used to measure wind speed and direction in the field. The approach was based on the Doppler Beam Swinging method to collect the light-of-sight wind speed. In this method, four beams are successively sent along a 28° cone angle in four cardinal directions, followed by a fifth vertical beam sent to measure vertical velocity directly. The resolution of the 1 minute average wind data from LiDAR is 15 records per minute. Wind speed data below 2m/s was removed after verification and an
analysis of turbulence intensity, and then a regression analysis was conducted to compensate for the yaw angle. By making interactive comparisons between wind direction and the compensated yaw angle, the power curve of the different inflow angle to blade rotations was obtained. Finally, the statistics show that the turbine averaged power output will result in a considerable decline at an inflow angle greater than 15°, and the influence is not less than the wake effect.
論文目次 Contents I
List of Tables III
List of Figures V
Nomenclature X
1. Introduction 1
2. Literature Review 8
2.1 Weibull distribution 8
2.2 Wind turbine characteristics 11
2.3 Wind turbine classes 13
2.4 Wind measurement 17
2.5 Effects of Yaw Error on wind turbine performance 21
3. Experimental Apparatus and Research Methods 26
3.1 Assessment of wind turbine installation 26
3.1.1 Site 27
3.1.2 Meteorological mast system 28
3.1.3 Identification of small wind turbine 36
3.2 Evaluation on wind power generation 39
3.2.1 Site of the wind farm 39
3.2.2 Fixed LiDAR 42
3.2.3 Assessment of obstacles 46
3.3 The calculation methods for wind data 48
3.3.1 Wind distribution 48
3.3.2 Discrete energy spectrum 48
3.3.3 Power curve 49
3.3.4 Annual energy production 50
3.3.5 Capacity factor 51
3.3.6 Capital budgeting 51
4. Assessment of wind turbine using wind data 54
4.1 Data processing 54
4.2 Assessment of wind data 61
4.3 Wind turbine performance 65
4.4 Capital-budgeting decisions 69
5. Evaluation on power generation using wind data 71
5.1 Assessment of wind data 71
5.2 Wind direction at layers 76
5.3 Uncertainty of the nacelle anemometer 78
5.4 Inflow angle effect 88
6. Conclusions 96
7. References 98
List of publications 104
Appendix 105
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