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研究生: 博拉帆
Barapati, Meharkumar
論文名稱: 彰化離岸風場平均風速與風能評估之研究
Mean Wind Speed Comparison and Wind Farm Energy Prediction at Chang-Hua Offshore
指導教授: 苗君易
Miau, Jiun-Jih
學位類別: 碩士
Master
系所名稱: 工學院 - 航空太空工程學系
Department of Aeronautics & Astronautics
論文出版年: 2016
畢業學年度: 104
語文別: 英文
論文頁數: 158
外文關鍵詞: Mean wind speed, Probability (%), Wind farm efficiency, Roughness length (z0), Power law exponent (P)
相關次數: 點閱:80下載:5
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  • A Light Detection and Ranging (Lidar) was set up at Chang-Hua development zone one on the sea. The three days mean wind speeds of WRF (3.33km &2 km) simulated and WAsP predicted is compared with Lidar wind speed observations. Based on four wind data sets developed five cases for comparison and found error (%) & R-squared values.
    Lukang meteorological station 5m height anemometer long term wind data (10- years) is used to predict the wind climate at the domain (13x24 km2), and Fuhai met mast. The yearly variation of wind climate predicted at Fuhai met mast under neutral and stable atmospheric condition.
    At Fuhai met mast location TGC (Taiwan generation corp.) interested in installing 28 and two demo wind turbines. Two sets of wind farm layouts (0o, 30o and 60o) are design with traditional (SWT 3.6 MW h generator used) and TGC (SWT 4.0 MW h generator used) spacing. Each set of wind farm layouts is designed leading towards 0o, 30o and 60o degrees concerning North, in a clockwise direction as per WAsP. WAsP used to predict the yearly variation of wind farm and wind turbines efficiency (%) & capacity factor (%).
    The Fuhai met mast at Chang-Hua 26 days (10-Oct-2015 to 5-Nov-2015) wind data categorized as daytime, night time and one day is 24 hours. Totally 78 data points are used to estimate the roughness length (z0), friction velocity (u*), power law exponent (p) and shear stress () at day time, night time, and the whole day (24 hours).

    TABLE OF CONTENTS ABSTRACT I ACKNOWLEDGEMENT II TABLE OF CONTENTS III LISTOF TABLES VI LIST OF FIGURES XII CHAPTER I: INTRODUCTION 1 1.1 Research Background 1 1.2 Objectives 4 1.3 Thesis Structure 5 CHAPTER II: LITERATURE REVIEW 6 2.1 Weibull Distribution 6 2.2 Wind profile and Wind stress 8 2.3 Terrain roughness effect 9 2.4 Wind rose and Wind speed 10 2.5 Seasonal variation of Wind over Taiwan Strait 12 2.6 Weather Research and Forecasting (WRF) 14 2.7 Power curve & Wind farm efficiency 15 2.7.1 Betz’s law 16 2.8 Wind farm layout 17 2.9 Wake effect and Wake model 19 CHAPTER III: RESEARCH METHOD 24 3.1 Wind Data Resources at Chang-Hua 24 3.2 WAsP (Wind Atlas Analysis and Application Program) 26 3.2.1 Wind Climate Assessment at Location and Domain 27 3.2.2 Wind Farm Energy Prediction 28 3.3 Wind Profile Curve Fitting for Roughness Length 30 CHAPTER IV: RESULTS AND DISCUSSION 32 4.1 Three Days mean Wind Speed Comparison 32 4.1.1Comparison between WAsP & Lidar 32 4.1.2 Comparison between WAsP, Lidar & WRF 34 4.2 Seasonal Wind Climate Comparison between Fuhai met mast and Domain 37 4.3 100 m Height Yearly Variation of Probability Distribution (%) and Wind Speed at Fuhai met mast Under Neutral & Stable Condition 39 4.4 SWT 3.6 MW h Generator Wind Farms Energy Predictions 40 4.5 TGC & TGC Spacing Wind Farms Energy Predictions by using SWT 4.0 MW h Generator 42 4.5.1 Yearly Variation of Wind Farms Energy Predictions 43 4.5.2 Comparison of Wind Turbine Energy Predictions between 60 degrees and TGC Layouts 45 4.5.3 Yearly Variation of TGC Wind Farm’s Wind Turbines Energy Prediction at Stable Condition 46 4.6 Marine Meteorological Wind Energy Application Parameters 47 4.7 Discussion of my Colleague Work 50 CHAPTER V – CONCLUSION AND SUGGESTIONS 52 5.1 Conclusion 52 5.2 Future Work Suggestions 55 LIST OF PUBLICATIONS 56 REFERENCES 57 Appendix 64

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