本研究使用基於BEM理論設計的三葉微型風機，擺設至本實驗室的開放式風洞進行入流、風機尾流及發電量之量測。主要探討方向分為兩個部分，如下所述：
　　第一部分為使用皮托管、熱線、眼鏡蛇探針以及粒子影像測速儀，量測6種不同的入流風速下的瞬時流向速度，探討各個儀器所量測的結果是否有顯著差異、影響後續的風機尾流量測。結果指出，平均流向速度具有良好的一致性。而流向紊流強度具有顯著差異：熱線量測的紊流強度偏低，原因為裝置的取樣率不夠高，無法正確地量測紊流現象；眼鏡蛇探針在低速時量測的紊流強度過高；隨著風速提升，眼鏡蛇探針、皮托管與PIV具有良好的一致性。鑒於熱線無法準確地量測實際流場之紊流強度，以及本實驗室的PIV設備還未架設至可量測風機尾流的階段，接續的風機尾流實驗將使用皮托管以及眼鏡蛇探針進行量測。
　　第二部分為觀察風機在不同葉尖速比(TSR)條件下的發電性能，以及在最佳發電效率情況下使用皮托管、眼鏡蛇探針量測風機產生的尾流。總計有11組TSR值的情況，紀錄每組情況下風機產生的電流值、葉片轉速以及電阻值，進而計算其他物理量，如電壓、功率、功率係數…。結果指出，在TSR值為4.34時具有最佳的功率係數，其值為0.189，得出一結論：在TSR值約等於4時，風機具有良好的發電效率。接續在TSR為4.34的條件下，我們使用皮托管以及眼鏡蛇探針量測風機後方尾流區的瞬時流向速度，計算無因次化平均流向速度以及流向紊流強度，量測範圍為風機後方一個葉片直徑距離至八倍的葉片直徑距離以及無擺放風機情況的入流情況。無因次化平均流向速度結果指出，兩者儀器的結果並無明顯差異，風機後方速度有顯著下降，並且隨著空間增加而逐漸回復。流向紊流強度結果指出，兩者儀器的結果具有顯著的差異。在皮托管的結果中，整個尾流區具有強烈的紊流分布，而在眼鏡蛇探針的結果中，葉片尖端後方處具有強烈的紊流分布，隨著空間增加漸漸恢復至初始入流狀態。葉片尖端後方除了是速度最小區域外，同時也是剪應力最大的區域，流體易受微小擾動之激發而產生紊流漩渦，紊流強度隨之提升，根據上述分析，我們判斷眼鏡蛇探針的量測結果較為合理的物理現象。從眼鏡蛇探針的結果指出，以BEM理論進行最佳化設計的葉片以及適合的TSR條件下，風機可以保持最大的功率輸出，產生的尾流效應對於下游的流場影響較小，有助於提高下游風機的發電量以及風電場的整體發電效率。

This study focuses on two research topics: The first part is to use pitot tube, hot wire, cobra probe and PIV to measure the inflow’s streamwise velocity at 6 different wind speed and discuss whether there are significant differences. The result of average streamwise velocity has good consistency, it indicates that the average speed measured by different instruments is very close. The results of streamwise turbulence intensity have a significant difference. The main reason is the sampling rate setting of the instrument. The sampling rate is too low to observe the correct flow field disturbance. The second part is to observe the power generation performance of the miniature wind turbine whose blade is designed by the BEM theory under different tip speed ratio (TSR) conditions and use pitot tube and cobra probe to measure the wake generated by the wind turbine under the best power generation efficiency. We found that the miniature wind turbine has the best power coefficient when the TSR value is approximately 4, and the cobra probe is more suitable for measuring wake than the pitot tube, because the analysis of the cobra probe is more in line with physical phenomena. The results from the cobra probe indicate that the blade designed by the BEM theory and the wind turbine operating at a suitable TSR have little impact on the downstream flow field, which helps to improve the power generation of downstream wind turbines and the overall the wind farm.

[1] A. K. Raturi, "Renewables 2020 global status report," 2020.
[2] G. W. E. Council, "GWEC| GLOBAL WIND REPORT 2021," 2021.
[3] "Global Wind Speed Rankings," 4C Offshore.
[4] L. J. Vermeer, J. N. Sørensen, and A. Crespo, "Wind turbine wake aerodynamics," Progress in Aerospace Sciences, vol. 39, no. 6-7, pp. 467-510, 2003.
[5] J. B. Barlow, W. H. Rae, and A. Pope, Low-Speed Wind Tunnel Testing. Wiley, 1999.
[6] J. Whale, K. H. Papadopoulos, C. G. Anderson, C. G. Helmis, and D. J. Skyner, "A study of the near wake structure of a wind turbine comparing measurements from laboratory and full-scale experiments," Solar Energy, vol. 56, no. 6, pp. 621-633, 1996/06/01/ 1996.
[7] "A New Miniature Wind Turbine for Wind Tunnel Experiments. Part I: Design and Performance," Energies, vol. 10, no. 7, 2017.
[8] H. H. Bruun, "Hot-Wire Anemometry: Principles and Signal Analysis," Measurement Science and Technology, vol. 7, no. 10, 1996/10/01 1996.
[9] H. Schümann, F. Pierella, and L. Sætran, "Experimental Investigation of Wind Turbine Wakes in the Wind Tunnel," Energy Procedia, vol. 35, pp. 285-296, 2013.
[10] J. Bossuyt, M. F. Howland, C. Meneveau, and J. Meyers, "Measurement of unsteady loading and power output variability in a micro wind farm model in a wind tunnel," Experiments in Fluids, vol. 58, no. 1, p. 1, 2016/12/15 2016.
[11] D. Węcel, T. Chmielniak, and J. Kotowicz, "Experimental and numerical investigations of the averaging Pitot tube and analysis of installation effects on the flow coefficient," Flow Measurement and Instrumentation, vol. 19, no. 5, pp. 301-306, 2008.
[12] H. P. Hodson and W. N. Dawes, "On the Interpretation of Measured Profile Losses in Unsteady Wake–Turbine Blade Interaction Studies," Journal of Turbomachinery, vol. 120, no. 2, pp. 276-284, 1998.
[13] W.-C. Wang, W. T. Chong, and T.-H. Chao, "Performance analysis of a cross-axis wind turbine from wind tunnel experiments," Journal of Wind Engineering and Industrial Aerodynamics, vol. 174, pp. 312-329, 2018.
[14] I. C. Shepherd, "A Four Hole Pressure Probe for Fluid Flow Measurements in Three Dimensions," Journal of Fluids Engineering, vol. 103, no. 4, pp. 590-594, 1981.
[15] J. D. Hooper and A. R. Musgrove, "Reynolds stress, mean velocity, and dynamic static pressure measurement by a four-hole pressure probe," Experimental Thermal and Fluid Science, vol. 15, no. 4, pp. 375-383, 1997/11/01/ 1997.
[16] G. V. Iungo, "Experimental characterization of wind turbine wakes: Wind tunnel tests and wind LiDAR measurements," Journal of Wind Engineering and Industrial Aerodynamics, vol. 149, pp. 35-39, 2016.
[17] Y.-T. Wu, C.-Y. Lin, C.-E. Huang, and S.-D. Lyu, "Investigation of Multiblade Wind-Turbine Wakes in Turbulent Boundary Layer," Journal of Energy Engineering, vol. 145, no. 6, p. 04019023, 2019/12/01 2019.
[18] A. Melling, "Tracer particles and seeding for particle image velocimetry," Measurement Science and Technology, vol. 8, no. 12, pp. 1406-1416, 1997/12/01 1997.
[19] J. Westerweel, "Fundamentals of digital particle image velocimetry," Measurement Science and Technology, vol. 8, no. 12, pp. 1379-1392, 1997/12/01 1997.
[20] J. M. I. Munoz, D. Dellavale, M. O. Sonnaillon, and F. J. Bonetto, "Real-time particle image velocimetry based on FPGA technology," in 2009 5th Southern Conference on Programmable Logic (SPL), 1-3 April 2009 2009, pp. 147-152, doi: 10.1109/SPL.2009.4914899.
[21] I. Grant, M. Mo, X. Pan, P. Parkin, J. Powell, H. Reinecke, K. Shuang, F. Coton, and D. Lee, "An experimental and numerical study of the vortex filaments in the wake of an operational, horizontal-axis, wind turbine," Journal of Wind Engineering and Industrial Aerodynamics, vol. 85, no. 2, pp. 177-189, 2000/04/04/ 2000.
[22] M. Talavera and F. Shu, "Experimental study of turbulence intensity influence on wind turbine performance and wake recovery in a low-speed wind tunnel," Renewable Energy, vol. 109, pp. 363-371, 2017/08/01/ 2017.
[23] J. A. BETZ and D. G. RANDALL, Einführung in die Theorie der Strömungsmaschinen. Introduction to the theory of flow machines ... Translated by D.G. Randall. Pergamon Press, 1966.
[24] M. A. Yurdusev, R. Ata, and N. S. Çetin, "Assessment of optimum tip speed ratio in wind turbines using artificial neural networks," Energy, vol. 31, no. 12, pp. 2153-2161, 2006/09/01/ 2006.
[25] C. Bottasso, F. Campagnolo, and V. Petrović, "Wind tunnel testing of scaled wind turbine models: Beyond aerodynamics," Journal of Wind Engineering and Industrial Aerodynamics, vol. 127, pp. 11–28, 04/01 2014.
[26] Y.-T. Wu, C.-Y. Lin, and C.-M. Hsu, "An Experimental Investigation of Wake Characteristics and Power Generation Efficiency of a Small Wind Turbine under Different Tip Speed Ratios," Energies, vol. 13, no. 8, 2020.
[27] H. Glauert, "Airplane Propellers," in Aerodynamic Theory: A General Review of Progress Under a Grant of the Guggenheim Fund for the Promotion of Aeronautics, W. F. Durand Ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 1935, pp. 169-360.
[28] R. E. Wilson, P. B. S. Lissaman, and S. N. Walker, "Aerodynamic performance of wind turbines," United States, 1976-06-01 1976.
[29] R. Lanzafame and M. Messina, "Fluid dynamics wind turbine design: Critical analysis, optimization and application of BEM theory," Renewable Energy, vol. 32, no. 14, pp. 2291-2305, 2007.
[30] K. Y. Maalawi and M. A. Badr, "A practical approach for selecting optimum wind rotors," Renewable Energy, vol. 28, no. 5, pp. 803-822, 2003/04/01/ 2003.
[31] C.-M. H. Yu-Ting Wu, "Characteristics of miniature turbine wakes under different tip speed ratios in the freestream flow condition," National Cheng Kung University Department of Engineering Science, 2019.
[32] Y.-T. Wu and F. Porté-Agel, "Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm," Renewable Energy, vol. 75, pp. 945-955, 2015.
[33] M. Raffel, C. E. Willert, F. Scarano, C. J. Kähler, S. T. Wereley, and J. Kompenhans, Particle image velocimetry: a practical guide. Springer, 2018.
[34] R. D. Keane and R. J. Adrian, "Optimization of particle image velocimeters. I. Double pulsed systems," Measurement Science and Technology, vol. 1, no. 11, p. 1202, 1990.
[35] R. D. Keane and R. J. Adrian, "Theory of cross-correlation analysis of PIV images," Applied Scientific Research, vol. 49, no. 3, pp. 191-215, 1992/07/01 1992.
[36] R. N. Bracewell and R. N. Bracewell, The Fourier transform and its applications. McGraw-Hill New York, 1986.