skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

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

Abstract

Developing operational numerical weather prediction models to improve wind energy forecasts by leveraging a multi-scale dataset from the second Wind Forecast Improvement Project field campaign in the northwest U.S. 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 thatmore » 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.« less

Authors:
 [1];  [1];  [1];  [1];  [2];  [1];  [1];  [1];  [2];  [3];  [2];  [4];  [4];  [5]; ORCiD logo [6]; ORCiD logo [7];  [8];  [1];  [1];  [1] more »;  [2];  [2];  [9];  [10];  [10];  [11] « less
  1. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, and National Oceanic and Atmospheric Administration
  2. National Oceanic and Atmospheric Administration/Earth System Research Laboratory
  3. Science and Technology Corporation
  4. National Center for Atmospheric Research
  5. Lawrence Livermore National Laboratory
  6. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  7. National Renewable Energy Laboratory (NREL), Golden, CO (United States); University of Colorado
  8. Vaisala, Inc.
  9. Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder
  10. Pacific Northwest National Laboratory
  11. National Oceanic and Atmospheric Administration/National Weather Service
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1566803
Report Number(s):
NREL/JA-5000-72552
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article
Journal Name:
Bulletin of the American Meteorological Society
Additional Journal Information:
Journal Name: Bulletin of the 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, James A., Djalalova, Irina, Bianco, Laura, Turner, David D., Pichugina, Yelena, Chokulkar, Aditya, Toy, Michael D., Brown, John M., Akish, Elena, Bao, Jian-Wen, Jimenez, Pedro, Kosovic, Branko, Lundquist, Katherine A., Draxl, Caroline, Lundquist, Julie, McCaa, Jim, McCaffrey, Katherine, Lantz, Kathy, Long, Chuck, Wilczak, Jim, Marquis, Melinda, Redfern, Stephanie, Berg, Larry K., Shaw, Will, 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, James A., Djalalova, Irina, Bianco, Laura, Turner, David D., Pichugina, Yelena, Chokulkar, Aditya, Toy, Michael D., Brown, John M., Akish, Elena, Bao, Jian-Wen, Jimenez, Pedro, Kosovic, Branko, Lundquist, Katherine A., Draxl, Caroline, Lundquist, Julie, McCaa, Jim, McCaffrey, Katherine, Lantz, Kathy, Long, Chuck, Wilczak, Jim, Marquis, Melinda, Redfern, Stephanie, Berg, Larry K., Shaw, Will, & 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, James A., Djalalova, Irina, Bianco, Laura, Turner, David D., Pichugina, Yelena, Chokulkar, Aditya, Toy, Michael D., Brown, John M., Akish, Elena, Bao, Jian-Wen, Jimenez, Pedro, Kosovic, Branko, Lundquist, Katherine A., Draxl, Caroline, Lundquist, Julie, McCaa, Jim, McCaffrey, Katherine, Lantz, Kathy, Long, Chuck, Wilczak, Jim, Marquis, Melinda, Redfern, Stephanie, Berg, Larry K., Shaw, Will, and Cline, Joel. Thu . "Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development". United States. doi:10.1175/BAMS-D-18-0040.1.
@article{osti_1566803,
title = {Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development},
author = {Olson, Joseph B. and Kenyon, James A. and Djalalova, Irina and Bianco, Laura and Turner, David D. and Pichugina, Yelena and Chokulkar, Aditya and Toy, Michael D. and Brown, John M. and Akish, Elena and Bao, Jian-Wen and Jimenez, Pedro and Kosovic, Branko and Lundquist, Katherine A. and Draxl, Caroline and Lundquist, Julie and McCaa, Jim and McCaffrey, Katherine and Lantz, Kathy and Long, Chuck and Wilczak, Jim and Marquis, Melinda and Redfern, Stephanie and Berg, Larry K. and Shaw, Will and Cline, Joel},
abstractNote = {Developing operational numerical weather prediction models to improve wind energy forecasts by leveraging a multi-scale dataset from the second Wind Forecast Improvement Project field campaign in the northwest U.S. 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},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}