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Title: Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development

Abstract

The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements mademore » in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.« less

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [2];  [1];  [1];  [1];  [2];  [1];  [3];  [2];  [4];  [4];  [5]; ORCiD logo [6]; ORCiD logo [1];  [7];  [1];  [1] more »;  [1];  [2];  [2];  [2];  [8]; ORCiD logo [9]; ORCiD logo [9];  [10] « less
  1. Univ. of Colorado, Boulder, CO (United States); National Oceanic and Atmospheric Administration/Earth System Research Lab., Boulder, CO (United States)
  2. National Oceanic and Atmospheric Administration/Earth System Research Lab., Boulder, CO (United States)
  3. Science and Technology Corp., Boulder, CO (United States)
  4. National Center for Atmospheric Research, Boulder, CO (United States)
  5. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  6. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  7. Vaisala, Inc., Seattle, WA (United States)
  8. Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
  9. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  10. National Oceanic and Atmospheric Administration/National Weather Service, Washington, D.C. (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W); USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1566803
Alternate Identifier(s):
OSTI ID: 1597610; OSTI ID: 1614927
Report Number(s):
NREL/JA-5000-72552; LLNL-JRNL-759278; PNNL-SA-138938
Journal ID: ISSN 0003-0007
Grant/Contract Number:  
AC36-08GO28308; AC52-07NA27344; AC02-06CH11357; AC05-76RL01830
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Bulletin of the American Meteorological Society
Additional Journal Information:
Journal Volume: 100; Journal Issue: 11; Journal ID: ISSN 0003-0007
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY; wind energy; model development; WFIP2; complex terrain; forecasting; numerical weather prediction

Citation Formats

Olson, Joseph B., Kenyon, Jaymes S., Djalalova, Irina, Bianco, Laura, Turner, David D., Pichugina, Yelena, Choukulkar, Aditya, Toy, Michael D., Brown, John M., Angevine, Wayne M., Akish, Elena, Bao, Jian -Wen, Jimenez, Pedro, Kosovic, Branko, Lundquist, Katherine A., Draxl, Caroline, Lundquist, Julie K., McCaa, Jim, McCaffrey, Katherine, Lantz, Kathy, Long, Chuck, Wilczak, Jim, Banta, Robert, Marquis, Melinda, Redfern, Stephanie, Berg, Larry K., Shaw, William J., and Cline, Joel. Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development. United States: N. p., 2019. Web. doi:10.1175/BAMS-D-18-0040.1.
Olson, Joseph B., Kenyon, Jaymes S., Djalalova, Irina, Bianco, Laura, Turner, David D., Pichugina, Yelena, Choukulkar, Aditya, Toy, Michael D., Brown, John M., Angevine, Wayne M., Akish, Elena, Bao, Jian -Wen, Jimenez, Pedro, Kosovic, Branko, Lundquist, Katherine A., Draxl, Caroline, Lundquist, Julie K., McCaa, Jim, McCaffrey, Katherine, Lantz, Kathy, Long, Chuck, Wilczak, Jim, Banta, Robert, Marquis, Melinda, Redfern, Stephanie, Berg, Larry K., Shaw, William J., & Cline, Joel. Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development. United States. doi:10.1175/BAMS-D-18-0040.1.
Olson, Joseph B., Kenyon, Jaymes S., Djalalova, Irina, Bianco, Laura, Turner, David D., Pichugina, Yelena, Choukulkar, Aditya, Toy, Michael D., Brown, John M., Angevine, Wayne M., Akish, Elena, Bao, Jian -Wen, Jimenez, Pedro, Kosovic, Branko, Lundquist, Katherine A., Draxl, Caroline, Lundquist, Julie K., McCaa, Jim, McCaffrey, Katherine, Lantz, Kathy, Long, Chuck, Wilczak, Jim, Banta, Robert, Marquis, Melinda, Redfern, Stephanie, Berg, Larry K., Shaw, William J., and Cline, Joel. Mon . "Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development". United States. doi:10.1175/BAMS-D-18-0040.1. https://www.osti.gov/servlets/purl/1566803.
@article{osti_1566803,
title = {Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development},
author = {Olson, Joseph B. and Kenyon, Jaymes S. and Djalalova, Irina and Bianco, Laura and Turner, David D. and Pichugina, Yelena and Choukulkar, Aditya and Toy, Michael D. and Brown, John M. and Angevine, Wayne M. and Akish, Elena and Bao, Jian -Wen and Jimenez, Pedro and Kosovic, Branko and Lundquist, Katherine A. and Draxl, Caroline and Lundquist, Julie K. and McCaa, Jim and McCaffrey, Katherine and Lantz, Kathy and Long, Chuck and Wilczak, Jim and Banta, Robert and Marquis, Melinda and Redfern, Stephanie and Berg, Larry K. and Shaw, William J. and Cline, Joel},
abstractNote = {The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.},
doi = {10.1175/BAMS-D-18-0040.1},
journal = {Bulletin of the American Meteorological Society},
issn = {0003-0007},
number = 11,
volume = 100,
place = {United States},
year = {2019},
month = {11}
}

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