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研究生：	柯貝曼 Prahmana, Rico Aditia
論文名稱：	利用浮動式光達分析颱風風況 Analysis on Wind Characteristics of Typhoons by using Floating LiDAR
指導教授：	林大惠 Lin, Ta-Hui
共同指導教授:	吳毓庭 Wu, Yu-Ting
學位類別：	碩士 Master
系所名稱：	工學院 - 機械工程學系 Department of Mechanical Engineering
論文出版年：	2015
畢業學年度：	103
語文別：	英文
論文頁數：	70
中文關鍵詞：	浮動式光達 (LiDAR) 、颱風、風速、風向、紊流強度
外文關鍵詞：	Floating light detection and ranging (LiDAR), typhoon, wind speed, wind direction, turbulence intensity.
相關次數：	點閱：163 下載：3
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由於台灣每年都會被數個颱風所侵襲，因此颱風侵襲台灣的過程，其風速、風向與紊流強度等，均會有相當大的變化。為了確保風力發電機在颱風期間的安全性，則是必須先了解颱風可能造成的風況。本研究主要是利用浮動式光達(LiDAR)量測蘇利颱風 (2013年7月)、潭美颱風 (2013年7月) 和麥德姆颱風 (2014年8月)的風速、風向與紊流強度，並且與中央氣象局或各區域之氣象站(台北、台中、苗栗跟高雄)的數據進行比較。
結果顯示浮動式光達 (LiDAR) 在量測蘇利、潭美和麥德姆颱風侵襲台灣時，在200公尺高層中所測得的最大風速分別為24、28和27 m/s。然而在這相同的時間點，由中央氣象局的資料顯示，颱風中心最大風速分別為38、30、和 38 m/s。此風速的差異性應該是浮動式光達 (LiDAR)所量測的位置並未在颱風中心的原因所導致。
蘇利颱風期間的風速比平常日的風速還要高，所以颱風期間的紊流強度會比平常日還低。潭美和麥德姆颱風期間的平均風速顯示，由於200公尺高層的風速高於55 和 110 公尺高層，因此200公尺高層的紊流強度會較低。此外，因為颱風由東向西移動並且逆時針旋轉，所以風向會由北風轉為南風。而且在颱風天的紊流強度也會低於一般正常日。最後，期待在此研究中所有測量方式的呈現，能讓台灣和全世界風力產業的風機設計人員感到有興趣。

Taiwan generally experiences several typhoons every year. To ensure the safety of wind turbines used for power generation, it is important that the wind conditions in a typical typhoon are known in advance. Accordingly, the present study uses the data of the floating light detection and ranging (LiDAR) system in Tainan and Miaoli, and meteorological stations in Taipei, Taichung, and Kaohsiung to observe and measure the wind speed and wind direction during Typhoon Soulik in July 2013, Typhoon Trami in August 2013, and Typhoon Matmo in August 2014. The wind data are used to calculate the corresponding turbulence intensity.
The results show that the maximum wind speeds for typhoons Soulik, Trami, and Matmo reached 24, 28, and 27 m/s, respectively, as measured from floating LiDAR at a height of 200 m. At same time the maximum wind speed announced by Central Weather Bureau (CWB) for typhoons Soulik, Trami, and Matmo near at the center of typhoons reached 38, 30, and 38 m/s, respectively. The different between wind speed measured by Floating LiDAR and CWB because the different location of typhoon measurement.
Moreover, for a typhoon moving from east to west, the wind direction changes from northward to southward as a result of the counterclockwise rotation of the typhoon. Furthermore, the turbulence intensity on typhoon days was lower than that on normal days. Finally, it is expected that the measurement methods presented in this study will be of interest to wind turbine designers in Taiwan in particular and around the world in general.

ABSTRACT	I
ACKNOWLEDGEMENTS	III
CONTENTS	IV
LIST OF FIGURES	VII
LIST OF TABLES	XI
1.	INTRODUCTION	1
2.	LITERATURE REVIEW	4
   2.1 Typhoons in western North Pacific	4
      2.1.1 Classification of typhoon strength	5
      2.1.2 Naming and numbering of typhoons	6
   2.2 Topography in Taiwan	7
   2.3 Extreme wind speed	8
   2.4 Wind speed without topographic effect	10
   2.5 Wind speed with topographic effect	11
   2.6 Turbulence intensity	12
3.	EXPERIMENTAL APPARATUS AND RESEARCH METHOD	13
   3.1 Overview	13
      3.1.1 WindSentinel floating LiDAR	13
            3.1.1.1 Working principle	14
            3.1.1.2 Specification of floating LiDAR	16
      3.1.2 Meteorological stations	18
            3.1.2.1 Taipei MET	18
            3.1.2.2 Hsinchu MET	19
            3.1.2.3 Taichung MET	20
            3.1.2.4 Kaohsiung MET	21
      3.1.3 MET instruments	22
            3.1.3.1 Wind cup and propeller anemometer	22
            3.1.2.2 Wind vane	22
            3.1.2.3 Humidity sensor	23
            3.1.2.4 Precipitation sensor	23
            3.1.2.5 Pressure sensor	24
            3.1.2.6 Temperature sensor	25
   3.2 Research method	26
      3.2.1 WindSentinel floating LiDAR	26
            3.2.1.1 SmartWeb	26
            3.2.1.2 Compact Flash card	26
      3.2.2 CWB METs	27
            3.2.2.1 Typhoons data	27
            3.2.2.2 Monitoring of typhoons	27
4.	ANALYSIS OF TYPHOONS SOULIK, TRAMI, AND MATMO	28
   4.1 Typhoon Soulik	28
      4.1.1 Typhoon Soulik track	28
      4.1.2 Location of floating LiDAR	30
      4.1.3 Typhoon data analysis	30
            4.1.3.1 Wind speed and direction	30
            4.1.3.2 Turbulence intensity	32
            4.1.3.3	Comparison of wind speed and direction between normal and typhoon days	32
            4.1.3.4	Comparison of turbulence intensity between normal and typhoon days	33
            4.1.3.5	Comparison of temperature, average humidity, and pressure between normal and typhoon days	33
   4.2 Typhoon Trami	40
      4.2.1 Typhoon Trami track	40
      4.2.2 Location of floating LiDAR	42
      4.2.3 Typhoon data analysis	42
            4.2.3.1 Wind speed and direction	42
            4.2.3.2 Turbulence intensity	43
            4.2.3.3 Temperature, average humidity, and pressure	43
   4.3 Typhoon Matmo	49
      4.3.1 Typhoon Matmo track	49
      4.3.2 Location of WindSentinel	51
      4.3.3 Typhoon data analysis	51
            4.3.3.1 Wind speed and direction	51
            4.3.3.2 Turbulence intensity	52
            4.3.3.3 Temperature, average humidity, and pressure	52
5.	CONCLUSION	58
6.	REFERENCES	60
LIST OF PUBLICATIONS	67
APPENDIX	68
                                    

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