Advances in Science and Research
Advances in Science and Research
ASR
Articles | Volume 22
Articles | Volume 22
https://doi.org/10.5194/asr-22-59-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/asr-22-59-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22
21 Oct 2025
 | 21 Oct 2025

Improving wind power forecasts in the Belgian North Sea with a wind farm parameterization and a neural network

Dieter Van den Bleeken, Geert Smet, Joris Van den Bergh, Idir Dehmous, Daan Degrauwe, Michiel Van Ginderachter, and Alex Deckmyn

Viewed

Total article views: 167 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
127 31 9 167 5 4
  • HTML: 127
  • PDF: 31
  • XML: 9
  • Total: 167
  • BibTeX: 5
  • EndNote: 4
Views and downloads (calculated since 21 Oct 2025)
Cumulative views and downloads (calculated since 21 Oct 2025)

Viewed (geographical distribution)

Total article views: 159 (including HTML, PDF, and XML) Thereof 159 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Nov 2025
Download
Short summary
To better predict offshore wind energy in Belgium, we improved the Royal Meteorological Institute (RMI) weather model by directly incorporating the effects of wind turbines. We also used AI to account for wind farm wake effects, where turbines slow down wind for other turbines. By combining physics-based models with a neural network trained on observations from the Belgian Offshore Zone, we achieved more accurate forecasts. This helps ensure a stable power grid and supports the growing role of offshore wind in our energy mix.
Read more
Share