the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 01 Aug 2025
Investigation of onshore wind farm wake recovery with in-situ aircraft measurements during AWAKEN
Abstract. The generation of power from wind farms is crucial for achieving sustainability goals. To enhance power output and ensure network stability with an increasing share of variable renewable energy sources, improving the prediction of power output is essential. The interaction between wind farm wakes and the atmospheric boundary layer (ABL) introduces uncertainties in power production that warrant detailed investigation. The flow downwind of wind farms is characterized by a reduction in wind speed and an increase in turbulence which both vary with atmospheric conditions. During the American Wake Experiment (AWAKEN), the Technische Universität Braunschweig conducted measurement flights with a research aircraft upwind and downwind of onshore wind farms in the Southern Great Plains in Oklahoma in the USA. This study utilizes data from twenty flights conducted at approximately hub height in September 2023 to investigate the wind field variability downwind of the wind farms, and vertical profiles to observe atmospheric stratification. The flights were aligned perpendicular to the main wind direction downwind of the wind farms King Plains and Armadillo Flats. Additionally, LIDAR data from both upwind and downwind ground-based measurement sites and sonic anemometer data were used for comprehensive analysis.
Results indicate that under stable ABL conditions, the wake persists until greater downwind distances with a higher velocity deficit within the wake relative to the undisturbed flow compared to unstable stratification. In homogeneous terrain under stable conditions, wake recovery to 95 % occurs between a distance of 4.5 km and 9 km downwind of the wind farm. In the semi complex terrain characterized by shallow hills, slopes, and valleys, the wake exhibits a higher velocity deficit compared to homogeneous terrain while in some cases the wake was amplified by the terrain resulting in higher velocity deficit 10 km downwind of the wind farm compared to the measurements closer to the wind farm. The turbulent kinetic energy (TKE) and "TKE deficit" was found to be a valuable measure in understanding wakes in a semi-complex terrain, showing a clear wake recovery and formation depending on the stratification of the ABL.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science. The authors also have no other competing interests to declare.
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 paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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RC1: 'Comment on wes-2025-113', Anonymous Referee #1, 16 Aug 2025
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The paper provides a study of wind farm wakes at two wind farms in the midwestern USA using data acquired from a test aircraft. The data collected is quite interesting and the authors investigate some nice features of the data, producing some valuable insights. This type of study, using data collected from an aircraft, is unique and will be helpful to the community. However, in my opinion some of the authors' conclusions are a bit too strong given the limited data available. I suggest the authors reduce the certainty of some of their conclusions. Please see my specific comments as follows:
p. 5, line 125: "low altitudes (close to hub height, between 100 m and 1000 m a.g.l.) for measurements in the ABL (Lampert et al., 2024), allowing high-resolution measurements of atmospheric and surface properties." The hub height is 89 m, so how would altitudes in excess of 100 m be "close to hub height"? An altitude of 1000 m agl would not be considered low altitude for a general aviation aircraft like the F406.
p. 5, line 125: The authors describe how the wind vector is derived, but more information is necessary. For instance, what is meant by high precision position measurements? Is only GPS used, or tightly coupled GPS-INS? Deriving wind speed from airspeed means that you need precise ground speed measurements (to solve the wind triangle). The use of a standard aircraft-grade GPS may not be suitable for solving this problem accurately, particularly at a sample rate of 100 Hz. What make/model GPS-INS was used? Is there a reference which describes how the aircraft is instrumented, how wind speed and turbulence was estimated, and how the data integrity/accuracy (particularly for wind speed) was verified? If not available from an external reference, that information should be provided here. The reliability and accuracy of the wind speed measurements must be established given its importance for this study.
The term "radio altitude" should be changed to "radar altitude" throughout the paper as this is more common terminology in the aviation industry.
Can the authors comment on the velocity deficit at 11:35 am in Figure 7 (c)? It seems there is a ~30% velocity deficit at an altitude of 350-400 m, which is over 2x tip height. I do not think this is mentioned in the text. Do the authors think this is due to the wind farm wake, or perhaps not caused by the turbines due to its height?
Figure 8 is really interesting. Can the authors comment on why the sharp peak in the TKE is so far to one side of the wind farm in the 500 m plot? The velocity deficit is more "centered" on the wind farm, while the TKE plot shows a sharp peak but really far off to one side. Could this have to do with the number of turbines on that side, or the location of the turbine closest to the aircraft as it passed downwind of the wind farm (i.e., it passed close to a turbine near the edge of the farm, but those in the center were farther away)? It might be good to add a sentence or two about this feature of the plot.
End of p. 14: I am a little uncertain about the authors' conclusions regarding Figure 10. The number of data samples is very low, yet the authors seem to draw some fairly big conclusions ("This raises the question if the wind speed is the best indicator for identifying onshore wind farm wakes.") For instance, the authors state " In an unstable stratification, the velocity deficit decreases at 5 km downwind of the wind farm and increases again at 10 km distance of the wind farm". Looking at Figure 10 c, I see 6 data points equally spaced about 0 at 5 km, and 4 points above zero and 1 well below zero at 10 km. This is not very much data in total and the effect is not statistically significant in my opinion. Overall, based on the results in Figure 10 I think the authors' claims in this paragraph are too strong. TKE and the velocity deficit both show the expected trends in terms of stratification and distance, although admittedly the data in the velocity deficit is noisier.
p. 16: "The velocity deficit at 0.5 km (Fig. 12 b) and 2 km (Fig. 12 c) downwind of the wind farm is similar to the values of the homogeneous terrain at this distance from the wind farm,". The meaning of the sentence is unclear - should it be "values of velocity deficit"? In fact, the whole section following this sentence is written poorly and is difficult to follow. Please rewrite to improve clarity. Can the values in the paragraphs at the bottom of pp. 16 and 17 be presented in a table perhaps?
p. 19 line 312 sensible->sensitive
p. 19: "As 1000 values per wind component are factored into the TKE, the TKE has more statistical significance compared to the raw wind speed measurements which are very sensitive to gusts." Why are the TKE measurements not also sensitive to gusts? This gets back to my question about how the wind speed was actually computed from the instrumentation on the aircraft. As it stands I am not convinced that the TKE measurements were necessarily more accurate than the wind speed (also not clear what is meant by "raw" wind speed - no distinction between "raw" and processed is ever defined).
Conclusion: In my opinion, the authors' conclusions about topography are a bit too strong given the very limited data presented. Given the various factors at play, can the authors really say conclusively that terrain "can lead to an amplification of the wind farm wake"? They appear to have data based on one or two flight passes. These are very strong conclusions based on one or two small data sets. I suggest changing "can lead" to "may lead" in order to suggest that it is possible, although not conclusively proven in the paper. Also, "can amplify wakes and reduce wind speed for wind farms further downwind under certain conditions" should be changed to "may amplify" as I don't think it is wise to make such important conclusions without more data. The authors seem to acknowledge this in the last sentence of the conclusion.
While the paper is well-written, there are numerous typos and grammatical errors throughout. The paper would really benefit from a thorough proofread.
Citation: https://doi.org/10.5194/wes-2025-113-RC1
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