Wind Energy Science
Wind Energy Science
WES
Articles | Volume 2, issue 1
Articles | Volume 2, issue 1
https://doi.org/10.5194/wes-2-77-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/wes-2-77-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 2, issue 1
Research article
 | 
10 Feb 2017
Research article |  | 10 Feb 2017

An error reduction algorithm to improve lidar turbulence estimates for wind energy

Jennifer F. Newman and Andrew Clifton

Viewed

Total article views: 4,131 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,227 1,730 174 4,131 179 226
  • HTML: 2,227
  • PDF: 1,730
  • XML: 174
  • Total: 4,131
  • BibTeX: 179
  • EndNote: 226
Views and downloads (calculated since 08 Jul 2016)
Cumulative views and downloads (calculated since 08 Jul 2016)
Latest update: 18 Nov 2025
Download
Short summary
Remote-sensing devices such as lidars are often used for wind energy studies. Lidars measure mean wind speeds accurately but measure different values of turbulence than an instrument on a tower. In this paper, a model is described that improves lidar turbulence estimates. The model can be applied to commercially available lidars in real time or post-processing. Results indicate that the model performs well under most atmospheric conditions but retains some errors under daytime conditions.
Read more
Share
Altmetrics
Final-revised paper
Preprint