Articles | Volume 11, issue 8
https://doi.org/10.5194/wes-11-2845-2026
https://doi.org/10.5194/wes-11-2845-2026
Research article
 | 
07 Aug 2026
Research article |  | 07 Aug 2026

Validation of RANS-calibrated engineering models and ANN-based surrogate for wind farm flow simulation and layout optimization

Jens Peter Schøler, Ernestas Simutis, M. Paul van der Laan, Julian Quick, and Pierre-Elouan Réthoré

Viewed

Total article views: 668 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
432 201 35 668 33 56
  • HTML: 432
  • PDF: 201
  • XML: 35
  • Total: 668
  • BibTeX: 33
  • EndNote: 56
Views and downloads (calculated since 13 Feb 2026)
Cumulative views and downloads (calculated since 13 Feb 2026)

Viewed (geographical distribution)

Total article views: 668 (including HTML, PDF, and XML) Thereof 646 with geography defined and 22 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 07 Aug 2026
Download
Short summary
Wind turbines create wakes, which reduce downstream power. Optimizing turbine placement requires accounting for these reductions. We compared a neural network trained on numerical simulations against engineering wake models across various farm sizes. The neural network predicted flow most accurately but was slower. Surprisingly, a simple TurbOPark model produced layouts with higher validated energy output, suggesting that accuracy is not the only important metric for such models.
Share
Altmetrics
Final-revised paper
Preprint