On Bridging A Modeling Scale Gap: Mesoscale to Microscale Coupling for Wind Energy
[2];
[2];
- 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)
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.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); National Renewable Energy Laboratory (NREL), Golden, CO (United States); Argonne National Laboratory (ANL), Argonne, IL (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office; National Science Foundation (NSF); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
- Grant/Contract Number:
- AC05-76RL01830; AC36-08GO28308; 89233218CNA000001; AC02-06CH11357
- OSTI ID:
- 1593309
- Alternate ID(s):
- OSTI ID: 1567029; OSTI ID: 1608682; OSTI ID: 1774625
- Report Number(s):
- PNNL-SA-139881; NREL/JA-5000-74152; LA-UR-19-28445
- Journal Information:
- Bulletin of the American Meteorological Society, Vol. 100, Issue 12; ISSN 0003-0007
- Publisher:
- American Meteorological SocietyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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