Operational forecasting based on a modified Weather Research and Forecasting model

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Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution ... continued below

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Lundquist, J; Glascoe, L & Obrecht, J March 18, 2010.

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Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

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PDF-file: 8 pages; size: 0.1 Mbytes

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  • Presented at: The Fifth International Symposium on Computational Wind Engineering, Chapel Hill, NC, United States, May 21 - May 23, 2010

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  • Report No.: LLNL-CONF-426094
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 1009203
  • Archival Resource Key: ark:/67531/metadc833411

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • March 18, 2010

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  • May 19, 2016, 3:16 p.m.

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  • Nov. 30, 2016, 2:50 p.m.

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Lundquist, J; Glascoe, L & Obrecht, J. Operational forecasting based on a modified Weather Research and Forecasting model, article, March 18, 2010; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc833411/: accessed October 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.