the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Simulating low-frequency wind fluctuations
Abstract. Large-scale flow structures are vital in influencing the dynamic response of floating wind turbines and wake meandering behind large offshore wind turbines. It is imperative that we develop an inflow wind turbulence model capable of replicating the large-scale and low-frequency wind fluctuations occurring in the marine atmosphere since the current turbulence models do not account well for this phenomenon. Here, we present a method to simulate low-frequency wind fluctuations. This method employs the two-dimensional spectral tensor for low-frequency, anisotropic wind fluctuations presented by Syed and Mann (2023) to generate stochastic wind fields. The simulation method generates large-scale 2D wind fields for the longitudinal u and lateral v wind components. The low-frequency wind turbulence is assumed to be independent of the high-frequency turbulence thus a broad spectral representation can be obtained just by superposing the two turbulent wind fields. The method is tested by comparing the simulated and theoretical spectra and co-coherences of the combined low- and high-frequency fluctuations. Furthermore, the low-frequency wind fluctuations can also be subjected to anisotropy. The resulting wind fields from this method can be used to analyze the impact of low-frequency wind fluctuations on wind turbine loads and dynamic response and for studying the wake meandering behind large offshore wind farms.
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RC1: 'Comment on wes-2023-142', Anonymous Referee #1, 03 Feb 2024
REVIEW OF Simulating low-frequency wind fluctuations by A.H. Syed and J. Mann
This paper addresses the important problem of generating synthetic turbulent fields. This is an area of significance for wind energy applications and other wind-structure interaction problems. Much effort has been placed on generating 3D fields representing turbulence fine structure including anisotropy and shear effects (RDT), but the arguably even more important aspect of large-scale, slow variations, has been less explored.
The paper provides useful details how to construct the fields and illustrates example results convincingly, culminating in fields where 2D and 3D fields (assumed independent) are successfully superposed (Fig.6). This paper is therefore a welcome addition to the literature. Publication is recommended after the authors take the following comments into account:
(1) The paper often says "low frequency" but means "low wavenumber". It is only if Taylor's frozen flow hypothesis is used and the spatial field is "swept" into a domain does it become frequency. The distinction is important since there are further, more refined models that include both 2 wavenumbers and frequency (see e.g. Wilczek et al (2015), J. Fluid Mech. 769, R1) and references therein). It may be worth stating more explicitly that this work neglects any of those effects and feeds in a "temporally frozen" spatial field. For proper perspective it would be useful if readers are informed that there are more general (but more complicated) "spatiotemporal" models in the literature that have been developed. And avoid saying "low frequency" and replace with "low wavenumber" throughout... On Line 110 you say
"Taylor’s frozen turbulence hypothesis is also employed to convert the frequency domain into the wavenumber domain". In the method, it is the reverse, k_1 wavenumber domain is being converted into frequency domain. Please correct.(2) The figure 5 shows an "increase" in u' when going from left to right. This is presumably due to the large-scale 2D component. What would be helpful would be to show another panel covering the entire large-scale field (presumably 100 or more of km's) and then showing fig 5a as a "enlarged" portion so we can see that the increase is just a "local" increase in the large-scale part.
(3) Also in terms of visualization, it would be useful to show the fluctuations also in the z-direction (treated as entirely 3D without any large-scale variation).
(4) Is there a way to further improve the method by imposing different large-scale length-scales L for the different velocity components? It is often the case that the L for u component is larger than for the other two components. Here it appears that while the velocity variances are allowed to be anisotropic, the length-scales for these components are still isotropic. Some comments about this issue would be welcome.
Citation: https://doi.org/10.5194/wes-2023-142-RC1 - AC2: 'Reply on RC1', Abdul Haseeb Syed, 15 Apr 2024
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RC2: 'Comment on wes-2023-142', Anonymous Referee #2, 18 Mar 2024
- AC1: 'Reply on RC2', Abdul Haseeb Syed, 15 Apr 2024
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