Preprints
https://doi.org/10.5194/wes-2024-29
https://doi.org/10.5194/wes-2024-29
05 Apr 2024
 | 05 Apr 2024
Status: this preprint is currently under review for the journal WES.

Observations of wind farm wake recovery at an operating wind farm

Raghavendra Krishnamurthy, Rob Newsom, Colleen Kaul, Stefano Letizia, Mikhail Pekour, Nicholas Hamilton, Duli Chand, Donna M. Flynn, Nicola Bodini, and Patrick Moriarty

Abstract. The interplay of momentum within wind farms significantly influences wake recovery, affecting the speed at which wakes return to their free-stream velocities. Under stable atmospheric conditions, wind farm wakes can extend over considerable distances, leading to sustained vertical momentum flux downstream, with variations observed throughout the diurnal cycle. Particularly in regions such as the US Great Plains, stable conditions can induce low-level jets, impacting wind farm performance and power output. This study examines the implications of wake recovery using long-term observations of vertical momentum flux profiles across diverse atmospheric conditions. In these observations, several key findings were observed, such as a) low-level jet heights are altered downstream of a wind farm, b) a notable impact of low-level jet height on wake recovery is observed using momentum flux profiles at upwind and downwind location, c) detection of wake effects is almost always observed throughout the atmospheric boundary layer height, and finally d) enhancement of wake recovery is observed in the presence of propagating gravity waves. These insights deepen our understanding of the intricate dynamics governing wake recovery in wind farms, advancing efforts to model and predict their behaviour across varying atmospheric contexts. In addition, the performance of large-eddy simulation-based semi-empirical internal boundary layer height model estimates incorporating real-world atmospheric and turbine inputs was evaluated using observations during low-level jet conditions.

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.
Raghavendra Krishnamurthy, Rob Newsom, Colleen Kaul, Stefano Letizia, Mikhail Pekour, Nicholas Hamilton, Duli Chand, Donna M. Flynn, Nicola Bodini, and Patrick Moriarty

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Review comment on wes-2024-29', Anonymous Referee #1, 03 May 2024 reply
Raghavendra Krishnamurthy, Rob Newsom, Colleen Kaul, Stefano Letizia, Mikhail Pekour, Nicholas Hamilton, Duli Chand, Donna M. Flynn, Nicola Bodini, and Patrick Moriarty

Data sets

Doppler Lidar Site A2 Rob Newsom and Raghavendra Krishnamurthy https://doi.org/10.21947/2283040

Doppler Lidar at Site H Rob Newsom and Raghavendra Krishnamurthy https://doi.org/10.5439/1890922

Sonic Anemometer Mikhail Pekour https://doi.org/10.21947/1899850

Ceilometer Nicholas Hamilton https://doi.org/10.21947/2221789

Raghavendra Krishnamurthy, Rob Newsom, Colleen Kaul, Stefano Letizia, Mikhail Pekour, Nicholas Hamilton, Duli Chand, Donna M. Flynn, Nicola Bodini, and Patrick Moriarty

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Short summary
The growth of wind farms in the central United States in the last decade has been staggering. This study looked at how wind farms affect the recovery of wind wakes – the disturbed air behind wind turbines. In places like the US Great Plains, phenomena such as low-level jets can form, changing how wind farms work. We studied how wind wakes recover under different weather conditions using real-world data, which is important for making wind energy more efficient and reliable.
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