Wind Ramp Events Validation in NWP Forecast Models during the Second Wind Forecast Improvement Project (WFIP2) Using the Ramp Tool and Metric (RT&M)
[9];
- Univ. of Colorado, Boulder, CO (United States); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
- National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Univ. of Colorado, Boulder, CO (United States); Vibrant Clean Energy LLC, Boulder CO (United States)
- Argonne National Lab. (ANL), Lemont, IL (United States)
- Univ. of Notre Dame, IN (United States)
- Vaisala Inc., Seattle, WA (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Univ. of Notre Dame, IN (United States)
- Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
The second Wind Forecast Improvement Project (WFIP2) is a multiagency 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. In this work we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and three 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.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office; National Oceanic and Atmospheric Administration (NOAA)
- Grant/Contract Number:
- AC36-08GO28308; AC02-06CH11357; AC52-07NA27344
- OSTI ID:
- 1735639
- Alternate ID(s):
- OSTI ID: 1774095; OSTI ID: 1841864
- Report Number(s):
- NREL/JA-5000-76803; LLNL-JRNL-830741; MainId:9464; UUID:ee5322a2-b20e-4dce-9d7e-dcabfc7fcc85; MainAdminID:18970
- Journal Information:
- Weather and Forecasting, Vol. 35, Issue 6; ISSN 0882-8156
- Publisher:
- American Meteorological SocietyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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