Wind Energy Science
Wind Energy Science
WES
Articles | Volume 10, issue 1
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.
https://doi.org/10.5194/wes-10-245-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 1
Research article
 | 
23 Jan 2025
Research article |  | 23 Jan 2025

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, Sara Porchetta, Sophia Buckingham, Gertjan Glabeke, Jeroen van Beeck, and Wim Munters

Viewed

Total article views: 1,497 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,155 310 32 1,497 32 30
  • HTML: 1,155
  • PDF: 310
  • XML: 32
  • Total: 1,497
  • BibTeX: 32
  • EndNote: 30
Views and downloads (calculated since 07 Mar 2024)
Cumulative views and downloads (calculated since 07 Mar 2024)

Viewed (geographical distribution)

Total article views: 1,497 (including HTML, PDF, and XML) Thereof 1,459 with geography defined and 38 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 17 Apr 2025
Download
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint