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Title: Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M)

Abstract

The second Wind Forecast Improvement Project (WFIP2) is a multi-agency field campaign held in the Columbia Gorge area (October 2015 - March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well-known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT&M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011 - August 2012). The RT&M was designed to explicitly measure the skill of NWP models at forecasting wind ramp events. Here we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and 3 lidars, and to forecasts from the High Resolution Rapid Refresh (HRRR), 3-km, and from the High Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of rampmore » events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.« less

Authors:
 [1];  [2];  [3];  [4];  [3];  [1]; ORCiD logo [5];  [1];  [6];  [7];  [8]; ORCiD logo [5];  [9];  [10];  [11];  [12]
  1. NOAA
  2. University of Colorado
  3. National Oceanic and Atmospheric Administration
  4. NOAA/ETL, Boulder, CO
  5. BATTELLE (PACIFIC NW LAB)
  6. Argonne National Laboratory
  7. University of Notre Dame
  8. Project collaborator
  9. UNIVERSITY OF COLORADO AT BOULDER
  10. ARGONNE NATL LAB
  11. NOAA National Severe Storms Laboratory
  12. Lawrence Livermore National Lab
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1721681
Report Number(s):
PNNL-SA-156607
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Weather and Forecasting
Additional Journal Information:
Journal Volume: 35; Journal Issue: 6
Country of Publication:
United States
Language:
English

Citation Formats

Djalalova, Irina V., Bianco, L., Akish, Elena, Wilczak, J. M., Olson, Joseph B., Kenyon, Jaymes, Berg, Larry K., Choukulkar, Aditya, Coulter, Richard L., Fernando, H, Grimit, Eric, Krishnamurthy, Raghavendra, Lundquist, Julie K., Muradyan, Paytsar, David, Turner, and Wharton, Sonia. Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M). United States: N. p., 2020. Web. doi:10.1175/WAF-D-20-0072.1.
Djalalova, Irina V., Bianco, L., Akish, Elena, Wilczak, J. M., Olson, Joseph B., Kenyon, Jaymes, Berg, Larry K., Choukulkar, Aditya, Coulter, Richard L., Fernando, H, Grimit, Eric, Krishnamurthy, Raghavendra, Lundquist, Julie K., Muradyan, Paytsar, David, Turner, & Wharton, Sonia. Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M). United States. https://doi.org/10.1175/WAF-D-20-0072.1
Djalalova, Irina V., Bianco, L., Akish, Elena, Wilczak, J. M., Olson, Joseph B., Kenyon, Jaymes, Berg, Larry K., Choukulkar, Aditya, Coulter, Richard L., Fernando, H, Grimit, Eric, Krishnamurthy, Raghavendra, Lundquist, Julie K., Muradyan, Paytsar, David, Turner, and Wharton, Sonia. Tue . "Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M)". United States. https://doi.org/10.1175/WAF-D-20-0072.1.
@article{osti_1721681,
title = {Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M)},
author = {Djalalova, Irina V. and Bianco, L. and Akish, Elena and Wilczak, J. M. and Olson, Joseph B. and Kenyon, Jaymes and Berg, Larry K. and Choukulkar, Aditya and Coulter, Richard L. and Fernando, H and Grimit, Eric and Krishnamurthy, Raghavendra and Lundquist, Julie K. and Muradyan, Paytsar and David, Turner and Wharton, Sonia},
abstractNote = {The second Wind Forecast Improvement Project (WFIP2) is a multi-agency field campaign held in the Columbia Gorge area (October 2015 - March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well-known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT&M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011 - August 2012). The RT&M was designed to explicitly measure the skill of NWP models at forecasting wind ramp events. Here we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and 3 lidars, and to forecasts from the High Resolution Rapid Refresh (HRRR), 3-km, and from the High Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of ramp events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.},
doi = {10.1175/WAF-D-20-0072.1},
url = {https://www.osti.gov/biblio/1721681}, journal = {Weather and Forecasting},
number = 6,
volume = 35,
place = {United States},
year = {2020},
month = {12}
}