As tapping energy from wind expands rapidly worldwide, it is a common procedure to locate a practicable site to extract energy from abundant wind flow by building wind farms. Comprehensive understanding of wind resource at a site   is important to perform the main activities say, wind flow modeling, wind   turbines micro siting, annual energy yield calculation and cost of energy   estimation. Wind measuring campaigns involve using of measuring instruments   such as meteorological tower instrumented with anemometers, wind vanes and   temperature sensors; remote sensing devices such as SoDAR, LiDAR. These   meteorological devices provide detailed information on wind behavior with   respect to the height, time and temperature. These systems were proven in   providing promising wind measurements even though they are susceptible to   certain weather conditions. The   study progressed by focusing on the wind behavior at three locations to   investigate the possible factors that varies the wind character. A location   with one met mast and two AQ500 SoDAR systems was considered for this project   where one AQ500 is 800m away and other AQ500 is 5515m away from the point of   Met mast. The location is contemplated as a decent approach to the spatial   analysis of the wind resource as there is a large scope to analyze the wind   character between two nearby sites and two faraway sites. Monostatic 3-beam   SoDAR systems from AQ System, Sweden and 100m meteorological tower with   instruments are used in this project work for collecting the wind data.   One-year worth of wind data at standard 10min intervals has been collected   from the three systems. This report outlines the theoretical description of project location, AQ500 SoDAR and Met mast. A detailed explanation of the data quality control and filtering methods are discussed along with respective reasons. The conclusion is drawn after performing the statistical analysis between wind speed and other parameters such as turbulent intensity, wind direction, thermal stability and temperature. Mat lab is used for computing and analyzing the wind data from three systems.

Wind energy is rapidly expanding worldwide, and it is common practice to maximize production by selecting sites with higher wind potential. To perform critical operations such as wind flow modeling, wind turbine micro placement, annual energy yield calculation, and cost of energy estimation, a thorough understanding of a site's wind resource is required. The present study examines data from three independent wind measurement systems to see how measured data depends on the choice of the measurement system and how this might forecast the wind resource and, consequently, the energy output of a potential wind farm.  The present analysis uses three measurement units, one meteorological mast (met mast), and ground-based AQ510 Sound Detection And Ranging (SoDAR) & SoDAR and ZX 300 Light Detection And Ranging (LiDAR) devices to capture wind data for nearly a year. This study describes the operating concept of remote sensing devices such as AQ510 SoDAR and ZX 300 LiDAR, the linear regression relationship between wind speed measured on the Met Mast versus SoDAR, Met Mast versus LiDAR, and SoDAR versus LiDAR. Additionally, an understanding of stratification for this potential wind farm’s site is explored for specific days during spring, summer, and winter.  The results of the intercomparison study among Met Mast, SoDAR & LiDAR show quite a good relationship between the different measurement systems, being the correlation coefficient between the mast and the LiDAR measurements being slightly larger than between the mast and the SoDAR measurements. Comparison during the stability and instability regimes show a larger difference in some cases. Python and MS Excel are used to build data filtering procedures, the Richardson number, and comparison computations.