Mesoscale to microscale wind farm flow modeling and evaluation
Abstract
The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge is how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, ‘building the bridge’ means developing models for the so-called ‘terra incognita,’ a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research dealsmore »
- Authors:
-
- National Renewable Energy Centre (CENER), Sarriguren (Spain)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- National Center for Atmospheric Research, Boulder, CO (United States)
- Technical Univ. of Denmark, Roskilde (Denmark)
- Technical Univ. of Denmark, Lyngby (Denmark)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- DNV GL, San Diego CA (United States)
- Publication Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA); ‘MesoWake’ Marie Curie International Outgoing Fellowship; New European Wind Atlas; Ministry of Trade, Industry & Energy
- OSTI Identifier:
- 1682526
- Report Number(s):
- LLNL-JRNL-774258
Journal ID: ISSN 2041-8396; 964924
- Grant/Contract Number:
- AC52-07NA27344; 624562; FP7‐PEOPLE‐2013‐IOF; FP7‐ENERGY.2013.10.1.2; 20138520021140
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Wiley Interdisciplinary Reviews. Energy and Environment
- Additional Journal Information:
- Journal Volume: 6; Journal Issue: 2; Journal ID: ISSN 2041-8396
- Publisher:
- Wiley
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 17 WIND ENERGY
Citation Formats
Sanz Rodrigo, Javier, Chávez Arroyo, Roberto Aurelio, Moriarty, Patrick, Churchfield, Matthew, Kosović, Branko, Réthoré, Pierre-Elouan, Hansen, Kurt Schaldemose, Hahmann, Andrea, Mirocha, Jeffrey D., and Rife, Daran. Mesoscale to microscale wind farm flow modeling and evaluation. United States: N. p., 2016.
Web. doi:10.1002/wene.214.
Sanz Rodrigo, Javier, Chávez Arroyo, Roberto Aurelio, Moriarty, Patrick, Churchfield, Matthew, Kosović, Branko, Réthoré, Pierre-Elouan, Hansen, Kurt Schaldemose, Hahmann, Andrea, Mirocha, Jeffrey D., & Rife, Daran. Mesoscale to microscale wind farm flow modeling and evaluation. United States. https://doi.org/10.1002/wene.214
Sanz Rodrigo, Javier, Chávez Arroyo, Roberto Aurelio, Moriarty, Patrick, Churchfield, Matthew, Kosović, Branko, Réthoré, Pierre-Elouan, Hansen, Kurt Schaldemose, Hahmann, Andrea, Mirocha, Jeffrey D., and Rife, Daran. Wed .
"Mesoscale to microscale wind farm flow modeling and evaluation". United States. https://doi.org/10.1002/wene.214. https://www.osti.gov/servlets/purl/1682526.
@article{osti_1682526,
title = {Mesoscale to microscale wind farm flow modeling and evaluation},
author = {Sanz Rodrigo, Javier and Chávez Arroyo, Roberto Aurelio and Moriarty, Patrick and Churchfield, Matthew and Kosović, Branko and Réthoré, Pierre-Elouan and Hansen, Kurt Schaldemose and Hahmann, Andrea and Mirocha, Jeffrey D. and Rife, Daran},
abstractNote = {The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge is how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, ‘building the bridge’ means developing models for the so-called ‘terra incognita,’ a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to direct future research in this area.},
doi = {10.1002/wene.214},
journal = {Wiley Interdisciplinary Reviews. Energy and Environment},
number = 2,
volume = 6,
place = {United States},
year = {Wed Aug 31 00:00:00 EDT 2016},
month = {Wed Aug 31 00:00:00 EDT 2016}
}
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