近年來風能研究與應用的發展逐漸擴張，風速資料的量測與分析也愈來愈重要。本研究著重於遠端遙測量測儀器LEOSPHERE LIDAR WINDCUBE (light detection and ranging)的資料分析並採用傳統測風塔上螺槳式風速計與超音波風速計所量測的資料結果相互驗證。我們以彰濱工業區的岸上風力發電場作為量測地點，並在當地的測風塔旁邊架設LIDAR儀器，從垂直高度40公尺至140公尺之間設置12個高度點測量當地的風速資料，量測時間分別為2015年1月29號至1月30號以及2016年7月4號至7月6號。
LIDAR量測主要對空間做光束掃描並以都卜勒效應原理進而計算風速及風向等資料。為了能夠使測風塔的風速資料與LIDAR儀器測量到的資料進行比較，我們必須在空間座標上對LIDAR量測的風速資料做轉換，因此本研究根據LIDAR的原始資料與量測原理，提出了兩種速度轉換的方法，並計算出40、50以及70公尺高度處的10分鐘平均風速、平均風向與紊流強度，然後同樣使用測風塔上螺槳式風速計與超音波風速計所量測的風速資料計算其對應的平均值相互比對。我們利用回歸分析後的結果可得知從LIDAR資料所計算的平均風速與風向是可以和傳統風速計相互驗證，但是對於紊流強度，LIDAR儀器無法準確評估數值，只能夠大約得到隨時間變化的趨勢。此外我們也用能量頻譜分析來比較LIDAR與螺槳式風速計在高度70公尺處的頻率變化與紊流消散的情況並加以探討LIDAR量測資料的特性。

Because of increasing demand from wind energy applications, analysis of wind data obtained from field measurements has become very important. The study focuses on the analysis of wind speed data obtained from a remote sensing device, a Leosphere Windcube LIDAR (light detection and ranging) device, and compares the data measured by the propeller and sonic anemometers on a meteorological mast. We carried out field measurements where a LIDAR device installed next to the mast was deployed in the Changhua Coastal Industrial Park onshore wind farm in January of 2015 and in July of 2016, respectively. The setup of the LIDAR included a total of 12 measurement heights ranging from 40m to 140m above the ground to collect wind speed data at those levels.
A LIDAR device is capable of sensing the moving velocity of aerosols by faithfully following the dynamics of flows in the atmosphere. This allows the measurement of speed and flow direction through the tracking of particle motion. The LIDAR device measures only the velocity magnitude along laser beams (also called light-of-sight velocity; LOS velocity) with the application of the Doppler effect of light in space. It cannot directly measure the velocity components of local wind speeds. The velocity components must be converted from the LOS velocity components with a conversion technique. In this study, we propose two methods for the flow conversion and compare the converted wind speed data with the data measured from anemometers installed on the meteorological mast. The proposed conversion methods are used to calculate the 10-min mean wind speed, 10-min mean wind direction and 10-min turbulence intensity at heights of 40m, 50m, and 70m.
The results provide a comparison of the 10-min mean wind speed, 10-min wind direction, and 10-min turbulence intensity obtained from LIDAR at all heights with the mean characteristics obtained from anemometers installed on the meteorological mast. Then, based on the normal turbulence model, it is possible to obtain the suitable turbine class for a local wind condition. An energy spectrum analysis also enabled observations as to whether the inertial subrange exists and also provoked a discussion of the comparison between the two methods in spectrum plots at a height of 70 m.

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