Wind Energy Science
Wind Energy Science
WES
Articles | Volume 8, issue 9
Articles | Volume 8, issue 9
https://doi.org/10.5194/wes-8-1387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-8-1387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 8, issue 9
Research article
 | 
08 Sep 2023
Research article |  | 08 Sep 2023

Extending the dynamic wake meandering model in HAWC2Farm: a comparison with field measurements at the Lillgrund wind farm

Jaime Liew, Tuhfe Göçmen, Alan W. H. Lio, and Gunner Chr. Larsen

Related authors

Enabling efficient sizing of hybrid power plants: a surrogate-based approach to energy management system modeling
Charbel Assaad, Juan Pablo Murcia Leon, Julian Quick, Tuhfe Göçmen, Sami Ghazouani, and Kaushik Das
Wind Energ. Sci., 10, 559–578, https://doi.org/10.5194/wes-10-559-2025,https://doi.org/10.5194/wes-10-559-2025, 2025
Short summary
Field comparison of load-based wind turbine wake tracking with a scanning lidar reference
David Onnen, Gunner Christian Larsen, Alan Wai Hou Lio, Paul Hulsman, Martin Kühn, and Vlaho Petrović
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-188,https://doi.org/10.5194/wes-2024-188, 2025
Preprint under review for WES
Short summary
Aerodynamic effects of leading-edge erosion in wind farm flow modeling
Jens Visbech, Tuhfe Göçmen, Özge Sinem Özçakmak, Alexander Meyer Forsting, Ásta Hannesdóttir, and Pierre-Elouan Réthoré
Wind Energ. Sci., 9, 1811–1826, https://doi.org/10.5194/wes-9-1811-2024,https://doi.org/10.5194/wes-9-1811-2024, 2024
Short summary
Introducing a data-driven approach to predict site-specific leading-edge erosion from mesoscale weather simulations
Jens Visbech, Tuhfe Göçmen, Charlotte Bay Hasager, Hristo Shkalov, Morten Handberg, and Kristian Pagh Nielsen
Wind Energ. Sci., 8, 173–191, https://doi.org/10.5194/wes-8-173-2023,https://doi.org/10.5194/wes-8-173-2023, 2023
Short summary
Comparison of large eddy simulations against measurements from the Lillgrund offshore wind farm
Ishaan Sood, Elliot Simon, Athanasios Vitsas, Bart Blockmans, Gunner C. Larsen, and Johan Meyers
Wind Energ. Sci., 7, 2469–2489, https://doi.org/10.5194/wes-7-2469-2022,https://doi.org/10.5194/wes-7-2469-2022, 2022
Short summary
More articles (12)

Related subject area

Thematic area: Dynamics and control | Topic: Dynamics and aeroservoelasticity
Analysis and calibration of optimal power balance rotor-effective wind speed estimation schemes for large-scale wind turbines
Atindriyo Kusumo Pamososuryo, Fabio Spagnolo, and Sebastiaan Paul Mulders
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-158,https://doi.org/10.5194/wes-2024-158, 2024
Revised manuscript accepted for WES
Short summary
Coleman free aero-elastic stability methods for three- and two-bladed floating wind turbines
Bogdan Pamfil, Henrik Bredmose, and Taeseong Kim
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-136,https://doi.org/10.5194/wes-2024-136, 2024
Revised manuscript accepted for WES
Short summary
Investigating the interactions between wakes and floating wind turbines using FAST.Farm
Lucas Carmo, Jason Jonkman, and Regis Thedin
Wind Energ. Sci., 9, 1827–1847, https://doi.org/10.5194/wes-9-1827-2024,https://doi.org/10.5194/wes-9-1827-2024, 2024
Short summary
Uncertainty quantification of structural blade parameters for the aeroelastic damping of wind turbines: a code-to-code comparison
Hendrik Verdonck, Oliver Hach, Jelmer D. Polman, Otto Schramm, Claudio Balzani, Sarah Müller, and Johannes Rieke
Wind Energ. Sci., 9, 1747–1763, https://doi.org/10.5194/wes-9-1747-2024,https://doi.org/10.5194/wes-9-1747-2024, 2024
Short summary
The rotor as a sensor – observing shear and veer from the operational data of a large wind turbine
Marta Bertelè, Paul J. Meyer, Carlo R. Sucameli, Johannes Fricke, Anna Wegner, Julia Gottschall, and Carlo L. Bottasso
Wind Energ. Sci., 9, 1419–1429, https://doi.org/10.5194/wes-9-1419-2024,https://doi.org/10.5194/wes-9-1419-2024, 2024
Short summary
More articles (6)

Cited articles

Alcayaga, L., Larsen, G. C., Kelly, M., and Mann, J.: Large-Scale Coherent Turbulence Structures in the Atmospheric Boundary Layer over Flat Terrain, J. Atmos. Sci., 79, 3219–3243, 2022. a
Anderson, E., Bai, Z., Bischof, C., Blackford, S., Demmel, J., Dongarra, J., Du Croz, J., Greenbaum, A., Hammarling, S., McKenney, A., and Sorensen, D.: LAPACK Users' Guide, third edn., Society for Industrial and Applied Mathematics, Philadelphia, PA, ISBN 978-0-89871-447-0, 1999. a
Becker, M., Ritter, B., Doekemeijer, B., van der Hoek, D., Konigorski, U., Allaerts, D., and van Wingerden, J.-W.: The revised FLORIDyn model: implementation of heterogeneous flow and the Gaussian wake, Wind Energ. Sci., 7, 2163–2179, https://doi.org/10.5194/wes-7-2163-2022, 2022. a, b
Boersma, S., Doekemeijer, B., Vali, M., Meyers, J., and van Wingerden, J.-W.: A control-oriented dynamic wind farm model: WFSim, Wind Energ. Sci., 3, 75–95, https://doi.org/10.5194/wes-3-75-2018, 2018. a
Bossanyi, E., Ruisi, R., Larsen, G. C., and Pedersen, M. M.: Axial induction control design for a field test at Lillgrund wind farm, J. Phys. Conf. Ser., 2265, 042032, https://doi.org/10.1088/1742-6596/2265/4/042032, 2022. a
More articles (38)
Download
Short summary
We present recent research on dynamically modelling wind farm wakes and integrating these enhancements into the wind farm simulator, HAWC2Farm. The simulation methodology is showcased by recreating dynamic scenarios observed in the Lillgrund offshore wind farm. We successfully recreate scenarios with turning winds, turbine shutdown events, and wake deflection events. The research provides opportunities to better identify wake interactions in wind farms, allowing for more reliable designs.
Read more
Share
Altmetrics
Final-revised paper
Preprint