Volume 3, issue 1 | Copyright
Wind Energ. Sci., 3, 353-370, 2018
https://doi.org/10.5194/wes-3-353-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research articles 08 Jun 2018

Research articles | 08 Jun 2018

From lidar scans to roughness maps for wind resource modelling in forested areas

Rogier Floors1, Peter Enevoldsen2,3, Neil Davis1, Johan Arnqvist4, and Ebba Dellwik1 Rogier Floors et al.
  • 1Department of Wind Energy, Technical University of Denmark, Roskilde, Denmark
  • 2Center for Energy Technologies, Aarhus University, Aarhus, Denmark
  • 3Envision Energy, Silkeborg, Denmark
  • 4Department of Earth Sciences, Uppsala University, Uppsala, Sweden

Abstract. Applying erroneous roughness lengths can have a large impact on the estimated performance of wind turbines, particularly in forested areas. In this study, a new method called the objective roughness approach (ORA), which converts tree height maps created using airborne lidar scans to roughness maps suitable for wind modelling, is evaluated via cross predictions among different anemometers at a complex forested site with seven tall meteorological masts using the Wind Atlas Analysis and Application Program (WAsP). The cross predictions were made using ORA maps created at four spatial resolutions and from four freely available roughness maps based on land use classifications. The validation showed that the use of ORA maps resulted in a closer agreement with observational data for all investigated resolutions compared to the land use maps. Further, when using the ORA maps, the risk of making large errors (> 25%) in predicted power density was reduced by 40–50% compared to satellite-based products with the same resolution. The results could be further improved for high-resolution ORA maps by adding the displacement height. The improvements when using the ORA maps were both due to a higher roughness length and due to the higher resolution.

Download & links
Publications Copernicus
Download
Short summary
Applying erroneous boundary conditions (surface roughness) for wind flow modelling can have a large impact on the estimated performance of wind turbines, particularly in forested areas. Traditionally the estimation of the surface roughness is based on a subjective process that requires assigning a value to each land use class in the vicinity of the wind farm. Here we propose a new method which converts lidar scans from a plane into maps that can be used for wind flow modelling.
Applying erroneous boundary conditions (surface roughness) for wind flow modelling can have a...
Citation
Share