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    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

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Increasing spatial resolution of wind resource prediction using NWP and RANS simulation

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Increasing spatial resolution of wind resource prediction using NWP and RANS simulation. / Castorrini, Alessio; Gentile, Sabrina; Geraldi, Edoardo; Bonfiglioli, Aldo.

In: Journal of Wind Engineering and Industrial Aerodynamics, Vol. 210, 104499, 31.03.2021.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Castorrini, A, Gentile, S, Geraldi, E & Bonfiglioli, A 2021, 'Increasing spatial resolution of wind resource prediction using NWP and RANS simulation', Journal of Wind Engineering and Industrial Aerodynamics, vol. 210, 104499. https://doi.org/10.1016/j.jweia.2020.104499

APA

Castorrini, A., Gentile, S., Geraldi, E., & Bonfiglioli, A. (2021). Increasing spatial resolution of wind resource prediction using NWP and RANS simulation. Journal of Wind Engineering and Industrial Aerodynamics, 210, [104499]. https://doi.org/10.1016/j.jweia.2020.104499

Vancouver

Castorrini A, Gentile S, Geraldi E, Bonfiglioli A. Increasing spatial resolution of wind resource prediction using NWP and RANS simulation. Journal of Wind Engineering and Industrial Aerodynamics. 2021 Mar 31;210. 104499. https://doi.org/10.1016/j.jweia.2020.104499

Author

Castorrini, Alessio ; Gentile, Sabrina ; Geraldi, Edoardo ; Bonfiglioli, Aldo. / Increasing spatial resolution of wind resource prediction using NWP and RANS simulation. In: Journal of Wind Engineering and Industrial Aerodynamics. 2021 ; Vol. 210.

Bibtex

@article{a1dbd1a2adb94a5b8e23a33be9e23d01,
title = "Increasing spatial resolution of wind resource prediction using NWP and RANS simulation",
abstract = "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.",
keywords = "Mesoscale, NWP, RANS, wind, WRF",
author = "Alessio Castorrini and Sabrina Gentile and Edoardo Geraldi and Aldo Bonfiglioli",
note = "This is the author{\textquoteright}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",
year = "2021",
month = mar,
day = "31",
doi = "10.1016/j.jweia.2020.104499",
language = "English",
volume = "210",
journal = "Journal of Wind Engineering and Industrial Aerodynamics",
issn = "0167-6105",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Increasing spatial resolution of wind resource prediction using NWP and RANS simulation

AU - Castorrini, Alessio

AU - Gentile, Sabrina

AU - Geraldi, Edoardo

AU - Bonfiglioli, Aldo

N1 - 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

PY - 2021/3/31

Y1 - 2021/3/31

N2 - 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.

AB - 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.

KW - Mesoscale

KW - NWP

KW - RANS

KW - wind

KW - WRF

U2 - 10.1016/j.jweia.2020.104499

DO - 10.1016/j.jweia.2020.104499

M3 - Journal article

AN - SCOPUS:85099370243

VL - 210

JO - Journal of Wind Engineering and Industrial Aerodynamics

JF - Journal of Wind Engineering and Industrial Aerodynamics

SN - 0167-6105

M1 - 104499

ER -