Articles | Volume 10, issue 1
https://doi.org/10.5194/wes-10-245-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-10-245-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improving wind and power predictions via four-dimensional data assimilation in the WRF model: case study of storms in February 2022 at Belgian offshore wind farms
Tsvetelina Ivanova
CORRESPONDING AUTHOR
Environmental and Applied Fluid Dynamics Department, von Karman Institute for Fluid Dynamics, Chau. de Waterloo 72, 1640 Rhode-Saint-Genèse, Belgium
Department of Engineering Technology, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
Sara Porchetta
Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 1–290, Cambridge, MA 02139, United States of America
Department of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands
Sophia Buckingham
Research & Innovation, ENGIE Laborelec, Rodestraat 125, 1630 Linkebeek, Belgium
Gertjan Glabeke
Environmental and Applied Fluid Dynamics Department, von Karman Institute for Fluid Dynamics, Chau. de Waterloo 72, 1640 Rhode-Saint-Genèse, Belgium
Department of Civil Engineering, Hydraulics Laboratory, Ghent University, Sint-Pietersnieuwstraat 41, 9000 Gent, Belgium
Jeroen van Beeck
Environmental and Applied Fluid Dynamics Department, von Karman Institute for Fluid Dynamics, Chau. de Waterloo 72, 1640 Rhode-Saint-Genèse, Belgium
Wim Munters
Environmental and Applied Fluid Dynamics Department, von Karman Institute for Fluid Dynamics, Chau. de Waterloo 72, 1640 Rhode-Saint-Genèse, Belgium
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Konstantinos Vratsinis, Rebeca Marini, Pieter-Jan Daems, Lukas Pauscher, Jeroen van Beeck, and Jan Helsen
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-32, https://doi.org/10.5194/wes-2025-32, 2025
Preprint under review for WES
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Using data collected over 13 months at an offshore wind farm, our study shows that a wind turbine’s position within the farm influences its energy output at a given wind speed. Front-row turbines respond differently to similar wind speeds and turbulence than those further back. This finding suggests that current methods for characterizing inflow conditions may not fully capture actual wind behavior, underscoring the need for improved performance analysis techniques.
Majid Bastankhah, Marcus Becker, Matthew Churchfield, Caroline Draxl, Jay Prakash Goit, Mehtab Khan, Luis A. Martinez Tossas, Johan Meyers, Patrick Moriarty, Wim Munters, Asim Önder, Sara Porchetta, Eliot Quon, Ishaan Sood, Nicole van Lipzig, Jan-Willem van Wingerden, Paul Veers, and Simon Watson
Wind Energ. Sci., 9, 2171–2174, https://doi.org/10.5194/wes-9-2171-2024, https://doi.org/10.5194/wes-9-2171-2024, 2024
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Dries Allaerts was born on 19 May 1989 and passed away at his home in Wezemaal, Belgium, on 10 October 2024 after battling cancer. Dries started his wind energy career in 2012 and had a profound impact afterward on the community, in terms of both his scientific realizations and his many friendships and collaborations in the field. His scientific acumen, open spirit of collaboration, positive attitude towards life, and playful and often cheeky sense of humor will be deeply missed by many.
Sara Porchetta, Michael F. Howland, Ruben Borgers, Sophia Buckingham, and Wim Munters
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-58, https://doi.org/10.5194/wes-2024-58, 2024
Revised manuscript has not been submitted
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This study delves into how hourly and monthly variations of wakes of a newly constructed wind farm cluster impacts adjacent existing farms. Using a simulation of a full year, it compares results from both a numerical weather prediction model and different fast-running engineering models. The results reveal significant differences in wake predictions, both quantitatively and qualitatively. Such insights are important for making informed decisions for the siting and design of future wind turbines.
Adithya Vemuri, Sophia Buckingham, Wim Munters, Jan Helsen, and Jeroen van Beeck
Wind Energ. Sci., 7, 1869–1888, https://doi.org/10.5194/wes-7-1869-2022, https://doi.org/10.5194/wes-7-1869-2022, 2022
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The sensitivity of the WRF mesoscale modeling framework in accurately representing and predicting wind-farm-level environmental variables for three extreme weather events over the Belgian North Sea is investigated in this study. The overall results indicate highly sensitive simulation results to the type and combination of physics parameterizations and the type of the weather phenomena, with indications that scale-aware physics parameterizations better reproduce wind-related variables.
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Short summary
This study explores how wind and power predictions can be improved by introducing local forcing of measurement data in a numerical weather model while taking into account the presence of neighboring wind farms. Practical implications for the wind energy industry include insights for informed offshore wind farm planning and decision-making strategies using open-source models, even under adverse weather conditions.
This study explores how wind and power predictions can be improved by introducing local forcing...
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