On Bridging A Modeling Scale Gap: Mesoscale to Microscale Coupling for Wind Energy

doi:10.1175/BAMS-D-18-0033.1

Title: On Bridging A Modeling Scale Gap: Mesoscale to Microscale Coupling for Wind Energy

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Abstract

Accurately representing flow across the mesoscale to the microscale is a persistent roadblock for completing realistic microscale simulations. The science challenges that must be addressed to coupling at these scales include the following: 1) What is necessary to capture the variability of the mesoscale flow, and how do we avoid generating spurious rolls within the terra incognita between the scales? 2) Which methods effectively couple the mesoscale to the microscale and capture the correct nonstationary features at the microscale? 3) What are the best methods to initialize turbulence at the microscale? 4) What is the best way to handle the surface-layer parameterizations consistently at the mesoscale and the microscale? 5) How do we assess the impact of improvements in each of these aspects and quantify the uncertainty in the simulations? The U.S. Department of Energy Mesoscale-to-Microscale-Coupling project seeks to develop, verify, and validate physical models and modeling techniques that bridge the most important atmospheric scales determining wind plant performance and reliability, which impacts many meteorological applications. The approach begins with choosing case days that are interesting for wind energy for which there are observational data for validation. The team has focused on modeling nonstationary conditions for both flat and complexmore »« less

Authors:

Haupt, Sue Ellen ^[1]; Kosovic, Branko ^[1];

^[2];

^[2]; Churchfield, Matthew J. ^[3]; Cline, Joel ^[4]; Draxl, Caroline ^[3]; Ennis, Brandon ^[5]; Koo, Eunmo ^[6]; Kotamarthi, Rao ^[7]; Mazzaro, Laura J. ^[6]; Mirocha, Jeffrey D. ^[8]; Moriarty, Patrick ^[3]; Muñoz-Esparza, Domingo ^[1]; Quon, Eliot ^[3]; Rai, Raj K. ^[9]; Robinson, Michael ^[3]; Sever, Gokhan ^[7]

National Center for Atmospheric Research, Boulder, CO (United States)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States)
National Oceanic and Atmospheric Administration (NOAA), Washington, DC (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Pacific Northwest National Lab. (PNNL), Redmond, WA (United States)

Publication Date:: 2020-01-07

Research Org.:: Pacific Northwest National Lab. (PNNL), Richland, WA (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind Energy Technologies Office (EE-4WE); National Science Foundation (NSF); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)

OSTI Identifier:: 1593309

Alternate Identifier(s):: OSTI ID: 1567029; OSTI ID: 1608682

Report Number(s):: PNNL-SA-139881; NREL/JA-5000-74152; LA-UR-19-28445
Journal ID: ISSN 0003-0007

Grant/Contract Number:: AC05-76RL01830; AC36-08GO28308; 89233218CNA000001

Resource Type:: Accepted Manuscript

Journal Name:: Bulletin of the American Meteorological Society

Additional Journal Information:: Journal Volume: 100; Journal Issue: 12; Journal ID: ISSN 0003-0007

Publisher:: American Meteorological Society

Country of Publication:: United States

Language:: English

Subject:: 17 WIND ENERGY; wind energy; mesoscale; microscale; coupling; large-eddy simulation; wind-plant flow; Earth Sciences

Citation Formats


                    Haupt, Sue Ellen, Kosovic, Branko, Shaw, William, Berg, Larry K., Churchfield, Matthew J., Cline, Joel, Draxl, Caroline, Ennis, Brandon, Koo, Eunmo, Kotamarthi, Rao, Mazzaro, Laura J., Mirocha, Jeffrey D., Moriarty, Patrick, Muñoz-Esparza, Domingo, Quon, Eliot, Rai, Raj K., Robinson, Michael, and Sever, Gokhan. On Bridging A Modeling Scale Gap: Mesoscale to Microscale Coupling for Wind Energy.  United States: N. p., 2020. 
        Web.  doi:10.1175/BAMS-D-18-0033.1.

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                    Haupt, Sue Ellen, Kosovic, Branko, Shaw, William, Berg, Larry K., Churchfield, Matthew J., Cline, Joel, Draxl, Caroline, Ennis, Brandon, Koo, Eunmo, Kotamarthi, Rao, Mazzaro, Laura J., Mirocha, Jeffrey D., Moriarty, Patrick, Muñoz-Esparza, Domingo, Quon, Eliot, Rai, Raj K., Robinson, Michael, & Sever, Gokhan. On Bridging A Modeling Scale Gap: Mesoscale to Microscale Coupling for Wind Energy.  United States.  doi:10.1175/BAMS-D-18-0033.1.

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                    Haupt, Sue Ellen, Kosovic, Branko, Shaw, William, Berg, Larry K., Churchfield, Matthew J., Cline, Joel, Draxl, Caroline, Ennis, Brandon, Koo, Eunmo, Kotamarthi, Rao, Mazzaro, Laura J., Mirocha, Jeffrey D., Moriarty, Patrick, Muñoz-Esparza, Domingo, Quon, Eliot, Rai, Raj K., Robinson, Michael, and Sever, Gokhan. Tue .  
        "On Bridging A Modeling Scale Gap: Mesoscale to Microscale Coupling for Wind Energy".  United States.  doi:10.1175/BAMS-D-18-0033.1.  https://www.osti.gov/servlets/purl/1593309.

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@article{osti_1593309,

  title        = {On Bridging A Modeling Scale Gap: Mesoscale to Microscale Coupling for Wind Energy},

  author       = {Haupt, Sue Ellen and Kosovic, Branko and Shaw, William and Berg, Larry K. and Churchfield, Matthew J. and Cline, Joel and Draxl, Caroline and Ennis, Brandon and Koo, Eunmo and Kotamarthi, Rao and Mazzaro, Laura J. and Mirocha, Jeffrey D. and Moriarty, Patrick and Muñoz-Esparza, Domingo and Quon, Eliot and Rai, Raj K. and Robinson, Michael and Sever, Gokhan},

  abstractNote = {Accurately representing flow across the mesoscale to the microscale is a persistent roadblock for completing realistic microscale simulations. The science challenges that must be addressed to coupling at these scales include the following: 1) What is necessary to capture the variability of the mesoscale flow, and how do we avoid generating spurious rolls within the terra incognita between the scales? 2) Which methods effectively couple the mesoscale to the microscale and capture the correct nonstationary features at the microscale? 3) What are the best methods to initialize turbulence at the microscale? 4) What is the best way to handle the surface-layer parameterizations consistently at the mesoscale and the microscale? 5) How do we assess the impact of improvements in each of these aspects and quantify the uncertainty in the simulations? The U.S. Department of Energy Mesoscale-to-Microscale-Coupling project seeks to develop, verify, and validate physical models and modeling techniques that bridge the most important atmospheric scales determining wind plant performance and reliability, which impacts many meteorological applications. The approach begins with choosing case days that are interesting for wind energy for which there are observational data for validation. The team has focused on modeling nonstationary conditions for both flat and complex terrain. This paper describes the approaches taken to answer the science challenges, culminating in recommendations for best approaches for coupled modeling.},

  doi          = {10.1175/BAMS-D-18-0033.1},

  journal      = {Bulletin of the American Meteorological Society},

  number       = 12,

  volume       = 100,

  place        = {United States},

  year         = {2020},

  month        = {1}

}

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