Journal cover Journal topic
Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
https://doi.org/10.5194/wes-2018-10
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research articles
12 Feb 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Wind Energy Science (WES).
From lidar scans to roughness maps for wind resource modeling in forested areas
Rogier Floors1, Peter Enevoldsen2,3, Neil Davis1, Johan Arnqvist4, and Ebba Dellwik1 1Department of Wind Energy, Technical University of Denmark
2Center for Energy Technologies, Aarhus University, Denmark
3Envision Energy, Denmark
4Department of Earth Sciences, Uppsala University, 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 modeling, is evaluated via cross-predictions between 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 improvement when using the ORA maps came down to two factors, first they had a higher roughness length for forests, which was confirmed to by increasing the forest roughness value of the land-use based maps to the value of the ORA map, and second, due to the higher resolution of the ORA data, since the ORA maps with the highest resolution had the largest reduction in mean absolute errors.
Citation: Floors, R., Enevoldsen, P., Davis, N., Arnqvist, J., and Dellwik, E.: From lidar scans to roughness maps for wind resource modeling in forested areas, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2018-10, in review, 2018.
Rogier Floors et al.
Rogier Floors et al.
Rogier Floors et al.

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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 rather subjective process, that requires assigning a value to each land use class in 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...
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