In case of analyzing the wind turbine design conditions and power productions accurately, the wind data at hub height is generally ideated for simulation. Recently, due to the increase in the size of the wind turbine, it is difficult to measure wind data of hub height by the cylindrical observation tower. Therefore, lattice tower mast is adopted and there are cases where high altitude measurement is performed instead of cylindrical tower mast. However, even in case of measuring wind data using lattice tower mast, there are some uncertainty of flow distortions by tower shadowing. This paper shows a study on wind speed correction method of lattice tower mast using CFD simulations (Fluent). As a result of performing the wind speed correction using the inflow wind speed ratio by CFD calculation, the uncertainty of corrected wind speed fell by less than 1 % which is recommended by IEC 61400-12-1.
Naïve estimation of horizontal wind velocity over complex terrain using measurements from a single wind-LiDAR introduces a bias due to the assumption of uniform velocity in any horizontal plane. While Computational Fluid Dynamics (CFD)-based methods have been proposed for bias removal, there are several issues exist in the implantation. For instance, the upstream atmospheric boundary layer thickness or direction are unknown. Conventional CFD-based corrections use trial and error to estimate the bias. Such approaches not only become numerically intractable for complicated flows, e.g. when the number of unknowns is large, but they also suffer from the fact that there is no guarantee for optimality of the obtained results. We propose a direct-adjoint-loop (DAL) optimization based framework to estimate such unknown parameters in a systematic way. For the validation of the method, we performed an experimental study using DIABREZZA LiDAR on a complex terrain for two wind directions of northwesterly (NW) and southeasterly (SE). The slope error associated with linear regression improved from -0.09 to -0.02 for SE and from -0.09 to +0.04 for NW.
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