Wind Energy Science
Wind Energy Science
WES
Articles | Volume 4, issue 2
Articles | Volume 4, issue 2
https://doi.org/10.5194/wes-4-287-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-4-287-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 4, issue 2
Research article
 | 
22 May 2019
Research article |  | 22 May 2019

Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm

Thomas Duc, Olivier Coupiac, Nicolas Girard, Gregor Giebel, and Tuhfe Göçmen

Viewed

Total article views: 7,008 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
5,610 1,292 106 7,008 187 172
  • HTML: 5,610
  • PDF: 1,292
  • XML: 106
  • Total: 7,008
  • BibTeX: 187
  • EndNote: 172
Views and downloads (calculated since 11 Oct 2018)
Cumulative views and downloads (calculated since 11 Oct 2018)

Viewed (geographical distribution)

Total article views: 7,008 (including HTML, PDF, and XML) Thereof 5,499 with geography defined and 1,509 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Nov 2025
Download
Short summary
Wind turbine wake recovery is very sensitive to ambient atmospheric conditions. This paper presents a way of including a local turbulence intensity estimation from SCADA into the Jensen wake model to improve its accuracy. This new model procedure is used to optimize power production of an operating wind farm and shows that some gains can be expected even if uncertainties remain high. These optimized settings are to be implemented in a field test campaign in the scope of the SMARTEOLE project.
Read more
Share
Altmetrics
Final-revised paper
Preprint