the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Comparison of wind-farm control strategies under realistic offshore wind conditions: wake quantities of interest
Abstract. Wind-farm control strategies aim to increase the efficiency, and therefore lower the levelized cost of energy, of a wind farm. This is done by using turbine settings such as the yaw angle, blade pitch angles, or generator torque to manipulate the wake that negatively affects downstream turbines in the farm. Two inherently different wind-farm control methods have been identified in literature: wake steering (WS) and wake mixing (WM). As one of two companion papers focused on understanding practical aspects of these two wind-farm control strategies using large-eddy simulation (LES), we below analyze the wake quantities of interest for a single wind turbine performing WS and WM, while the companion article (Frederik et al., 2025) focuses on turbine quantities of interest including power and structural loads for the same computational setup and also includes two-turbine arrays with full and partial wake overlap. The simulations, which are based in the LES solver AMR-Wind, are tailored to have inflow conditions representative of measurements from a site off the east coast of the U.S. including with strong veer and low turbulence. The turbine, which is modeled in OpenFAST and coupled to the LES, is the IEA 15 MW, an open-source offshore design. After presenting an overview of the wake recovery for the different wake-control cases, the analysis probes the fluid-dynamic causes for the different performance of the arrays reported in the companion article by examining control volumes around the wakes and the budget of the mean-flow kinetic energy (MKE) within these volumes. In the high veer environment considered, the MKE recovery is dominated by mean convection, and this is shown to especially benefit the WS strategy when a neighboring turbine is directly downstream; there is ≈70 % more available power for a downstream turbine than the baseline case, and this power is gained primarily through mean convection on the left-tip and top-tip faces of the control volume. However, the case with imperfect knowledge of the exact wind direction favors the pulse-type WM strategy, largely because of ≈8 % increased turbulent entrainment from aloft versus the baseline that could be related to an apparent resistance to skewing in the pulsed wake. The general reduced effectiveness of helix-type and other individual-pitch-based WM strategies for inflow with high veer and low turbulence as reported in the companion paper is due, in part, to low magnitudes of phase-averaged turbulent entrainment. Two main findings of this study are thus that veer has a significant impact on the effectiveness of different wake-control strategies and that pulse-type WM may be a useful strategy when the objective is power maximization in realistic, offshore flow environments including imperfect knowledge of the exact wake overlap position on the downstream turbine.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.- Preprint
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RC1: 'Comment on wes-2024-191', Anonymous Referee #1, 26 Feb 2025
The paper examines the mechanics of wind farm flow control strategies under realistic offshore conditions, specifically high veer. The analysis focuses on a budget analysis of mean kinetic energy, comparing five flow control strategies. This topic is highly relevant for the industrial application of wind farm flow control and this paper delivers some critical insight into the efficacy of different strategies under more complex inflow conditions. The paper's methodology is sound and well explained, and the analysis thoroughly founded on the presented data. I therefore recommend the paper for publication with minor revisions.
The methodology of the paper is very thorough, from the sophisticated determination of inflow conditions to generate to the validation of the budget analysis. However, I believe the thoroughness obstructs the readability of the article in some instances. Therefore, I recommend to move some parts into an appendix, in particular the majority of current section 2.3 and section 3.2.1.
In section 2.2, I think the used model could be described in some more detail, especially how OpenFAST was set up and how the rotational speed of the turbine is controlled.
The authors write that the ratio of smearing width to cell size is 0.8, this appears very low to me and well below commonly found recommendations. If it is indeed not a misprint the authors should add some justification or point to validation.
I find the double naming convention for the wake mixing strategies, i.e. giving the modal numbers and the name, applied throughout the paper too long, it would improve readability to use either the modal numbers or the names.
In the companion paper, the authors speak of active wake mixing instead of wake mixing, for a reader that reads both papers it would be much easier if the same nomenclature is used.
Furthermore, I have the following minor suggestions:
section 2.1: I dont think it is mentioned anywhere explicitly that the origin is at the hub of the turbine, please add this information for the reader´s convenience.
l. 133: why is it called AP?
tables 5,6,7: there is a lot of white space in the tables that can be removed.
figure 14: the color scheme makes it quite difficult to subplot a, especially in greyscale.
figure 14 & 15: the caption says the panels are shown looking upstream, I think it should read downstream.
Figure 17 is very large, the size can be reduced significantly
Throughout the figures the authors use an inconsistent formatting for the normalizations, in most figures (e.g. figure 5), the axis labels are given as (coordinate) / (normalization scale), however, in some figures, e.g. figure 7, the x-axis label reads xD^-1. I think a consistent style would be nice.
Citation: https://doi.org/10.5194/wes-2024-191-RC1 -
AC1: 'Comment on wes-2024-191', Kenneth Brown, 09 Apr 2025
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2024-191/wes-2024-191-AC1-supplement.pdf
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AC1: 'Comment on wes-2024-191', Kenneth Brown, 09 Apr 2025
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RC2: 'Comment on wes-2024-191', Anonymous Referee #2, 07 Mar 2025
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AC1: 'Comment on wes-2024-191', Kenneth Brown, 09 Apr 2025
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2024-191/wes-2024-191-AC1-supplement.pdf
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AC1: 'Comment on wes-2024-191', Kenneth Brown, 09 Apr 2025
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AC1: 'Comment on wes-2024-191', Kenneth Brown, 09 Apr 2025
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2024-191/wes-2024-191-AC1-supplement.pdf
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