Received: 16 Feb 2018 – Discussion started: 03 Apr 2018
Abstract. To observe accurate wind climate from the available met mast measured wind data at different heights an accurate wind shear model is necessary. Since WAsP and windPRO is software package which provide the better representation of wind profile over homogeneous terrain only. Though, a separate module named as WAsP CFD has been added in both of the software to predict correct wind resource in complex terrain also. Nowadays terrain dependent wind resource model has become a key issue for the researchers. Out of many wind extrapolating model such as PL (power law), LogL (log law), LogLL (Log linear law) and Deaves and Harris Model Log law was found to be a better representation of wind profile. This study presents a comparative analysis of three different wind extrapolation models. Based on one year (2016–2017) wind data from met mast of 10 min. interval at 10, 50, 80, 100 and 102 m, and the result was compared with the relation of atmospheric stability. The licensed version of WAsP and windPRO software was also used to calculate wind resource parameter such as roughness index and roughness class etc. RMSE and NRMSE was found to be least in case of log linear model which is 0.11 and 0.01784 respectively in compare to PL and Deaves and Harris models.
This preprint has been retracted.
How to cite. Sharma, P. K., Warudkar, V., and Ahmed, S.: Effect of Atmospheric Stability on the Wind Resource extrapolating models for large capacity Wind Turbines: A Comparative Analysis of Power Law, Log Law and Deaves and Harris mode, Wind Energ. Sci. Discuss. [preprint], https://doi.org/10.5194/wes-2018-16, 2018.
Due to increasing demand of energy, Wind resource prediction has become a crucial issue markedly for energy investors to accurately analyze the wind speed at different hub height of WT. This is very much necessary during the feasibility study to abate the cost of wind farm installation. There are many researchers who worked on different wind extrapolating models such as PL, LogL, LogLL and DH.
Due to increasing demand of energy, Wind resource prediction has become a crucial issue markedly...