Evaluation of different methods for determining the angle of attack on wind turbine blades with CFD results under axial inflow conditions

Abstract

This work presents an investigation on different methods for the calculation of the angle of attack and the underlying induced velocity on wind turbine blades using data obtained from three-dimensional Computational Fluid Dynamics (CFD). Several methods are examined and their advantages, as well as shortcomings, are presented. The investigations are performed for two 10MW reference wind turbines under axial inflow conditions, namely the turbines designed in the EU AVATAR and INNWIND.EU projects. The results show that the evaluated methods are in good agreement with each other at the mid-span, though some deviations are observed at the root and tip regions of the blades. This indicates that CFD results can be used for the calibration of induction modeling for Blade Element Momentum (BEM) tools. Moreover, using any of the proposed methods, it is possible to obtain airfoil characteristics for lift and drag coefficients as a function of the angle of attack. Nomenclature ρ Air density [kg m −3 ] Γ Circulation [m 2 s −1 ]

Extraction of the wake induction and angle of attack on rotating wind turbine blades from PIV and CFD results

“…This is not the case for AAT; thus, we consider the results obtained with the new method to be more realistic. This interpretation is supported by the results of two different turbines presented in Rahimi et al (2018), who show that the method proposed by Shen et al (2006), which presents the advantage of computing the local blade velocities more accurately, is in excellent agreement with our method in the root and tip region, and it also deviates considerably from the AAT.…”

“…A comparison of several methods for obtaining them concluded that three out of four methods were reasonably consistent and reliable (Guntur et al, 2011). In a very recent benchmark study of multiple methods for computing the AoA (including the one presented here), similar results were obtained from all methods except at the tip and root of the blade, where substantial disagreement between some methods was found (Rahimi et al, 2018). A detailed description of all the existing methods is out of the scope of this article, although the reader is referred to Guntur et al (2011) and Rahimi et al (2018) for a good overview of the different methods.…”

“…In addition, according to our experience many of the available methods are often rather complicated to employ and automatize. Last but not least, existing methods usually require user-defined input parameters such as control points or correction models for the root and tip (Rahimi et al, 2018). This increases the uncertainty of the calculations.…”

Dynamic inflow effects in measurements and high-fidelity computations

“…Another option is to use dynamic inductions from the CFD solution to estimate the time constants. However, a recent comparison has shown that there is still considerable uncertainty in induced velocities from CFD towards the root and tip of the blade (Rahimi et al, 2018). This uncertainty complicates the estimation of the radially varying dynamic inflow time constants.…”

Free-flow wind speed from a blade-mounted flow sensor

“…In the current study, however, it is neglected as the two verification environments, HAWC2 and EllipSys3D-Flex5, do not model the surface of the airfoils. Shen et al (2006Shen et al ( , 2009, Guntur and Sørensen (2014), and Rahimi et al (2018) present several methods to calculate the flow near the airfoil that also take 3-D effects into account, but the methods require information that cannot be obtained directly from a BMFS. Pedersen et al (2017) describes how to obtain the effective 3-D inflow from the relative wind speed and two perpendicular angles measured by a blade-mounted five-hole pitot, including compensation for bound circulation.…”