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Other literature type . 2026
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Conference object . 2026
License: CC BY NC ND
Data sources: Datacite
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Conference object . 2026
License: CC BY NC ND
Data sources: Datacite
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Wind farms: Understanding the gravity of their atmospheric interactions

Authors: Rafferty, Timothy; Vogel, Christopher;

Wind farms: Understanding the gravity of their atmospheric interactions

Abstract

With the growth of offshore wind farm capacity in the North Sea, the challenges that come from the increased interaction with large scale atmospherics must be understood. Notably the newest turbines, which now reach up to hundreds of metres, can trigger Atmospheric Gravity Waves (AGWs). The buoyancy driven AGWs can cause a redistribution of the pressure field in and around a wind farm altering the flow that the turbines interact with. Whilst it has been shown this will alter farm efficiency and power distribution around the farm, it is not known if the AGWs will impact the flow on the turbine scale. To evaluate the impact of AGWs on turbine wake dynamics and blade loading, Large Eddy Simulations (LES) of turbine rows were carried out using an actuator line method for turbine representation. Through comparisons to cases without AGWs, it was found the waves could change the turbine wake recovery profile. Simulations also showed turbine spacing within a farm is correlated to the wave strength. To accurately model the North Sea conditions for AGWs required simulations with domains spanning 10s of kms and solvers which could capture turbulent shear layer dynamics, thermal profiles, Coriolis forces and unsteady flow dynamics. Therefore, with the findings in this work also demonstrating the need for a more complete understanding of AGW impacts, it also shows the necessity of the ARCHER2 computational resources for reaching the government’s net zero energy goals.

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Keywords

ARCHER2, Atmospherics, LES, Wind turbines, Celebration of Science, fluid dynamics, wake dynamics, Gravity Waves

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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