Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Wind Engineering and Industrial Aerodynamics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Wind Engineering and Industrial Aerodynamics, 210, 2021 DOI: 10.1016/j.jweia.2020.104499
Accepted author manuscript, 21 MB, PDF document
Available under license: CC BY-NC-ND
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Article number | 104499 |
---|---|
<mark>Journal publication date</mark> | 31/03/2021 |
<mark>Journal</mark> | Journal of Wind Engineering and Industrial Aerodynamics |
Volume | 210 |
Number of pages | 18 |
Publication Status | Published |
Early online date | 13/01/21 |
<mark>Original language</mark> | English |
The detailed prediction of the upcoming wind on wind farms can support optimization of wind energy production and operation and maintenance. Numerical Weather Prediction (NWP) tools allow to simulate the wind over long-term forecasting horizons (up to several days) with a spatial resolution ranging between the continental level down to a few hundred meters. We present a methodology, based upon Computational Fluid Dynamics (CFD) and Reynolds Averaged Navier Stokes (RANS) modelling, that allows to downscale the spatial resolution of the wind prediction supplied by a NWP model down to the typical length-scale of wind energy applications. The proposed approach combines a number of standard tools, including: Geographical Information Systems (GIS), Advanced Research - Weather Research and Forecasting (WRF-ARW) and OpenFOAM, and proposes methods to interface these tools and set-up the local-scale simulation. Models and problem sizes are selected to keep the computational cost of the system sustainable in view of its implementation in operational forecasting. Finally, we present the application of the method on a given onshore site, and for three different meteorological conditions, showing the potential of the approach, but also giving an account of the limitations that it may encounter when dealing with complex planetary boundary layers.