Articles | Volume 7, issue 4
https://doi.org/10.5194/wes-7-1551-2022
https://doi.org/10.5194/wes-7-1551-2022
Research article
 | 
20 Jul 2022
Research article |  | 20 Jul 2022

Computational fluid dynamics studies on wind turbine interactions with the turbulent local flow field influenced by complex topography and thermal stratification

Patrick Letzgus, Giorgia Guma, and Thorsten Lutz

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Revised manuscript accepted for WES
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Cited articles

Abkar, M., Sharifi, A., and Porté-Agel, F.: Wake Flow in a Wind Farm during a Diurnal Cycle, J. Turbul., 17, 1–22, https://doi.org/10.1080/14685248.2015.1127379, 2016. a
Bangga, G., Weihing, P., Lutz, T., and Krämer, E.: Effect of computational grid on accurate prediction of a wind turbine rotor using delayed detached-eddy simulations, J. Mech. Sci. Technol., 31, 2359–2364, https://doi.org/10.1007/s12206-017-0432-6, 2017. a
Barber, S., Schubiger, A., Koller, S., Eggli, D., Radi, A., Rumpf, A., and Knaus, H.: The wide range of factors contributing to Wind Resource Assessment accuracy in complex terrain, Wind Energ. Sci. Discuss. [preprint], https://doi.org/10.5194/wes-2021-158, in review, 2022. a, b, c
Barthelmie, R., Pryor, S., Wildmann, N., and Menke, R.: Wind Turbine Wake Characterization in Complex Terrain via integrated Doppler Lidar Data from the Perdigão Experiment, J. Phys. Conf. Ser., 1037, 052022, https://doi.org/10.1088/1742-6596/1037/5/052022, 2018. a
Bechmann, A. and Sørensen, N. N.: Hybrid RANS/LES Method for Wind Flow over Complex Terrain, Wind Energy, 13, 36–50, https://doi.org/10.1002/we.346, 2010. a
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The research article presents the results of a study of highly resolved numerical simulations of a wind energy test site in complex terrain that is currently under construction in the Swabian Alps in southern Germany. The numerical results emphasised the importance of considering orography, vegetation, and thermal stratification in numerical simulations to resolve the wind field decently. In this way, the effects on loads, power, and wake of the wind turbine can also be predicted well.
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