U.S. Department of EnergyOffice of Scientific and Technical Information
Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications
Abstract
To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024).more »
- Authors:
-
- The National Renewable Energy Lab (NREL)
- Publication Date:
- Other Number(s):
- 6218
- Research Org.:
- DOE Open Energy Data Initiative (OEDI); The National Renewable Energy Lab (NREL)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)
- Collaborations:
- The National Renewable Energy Lab (NREL)
- Subject:
- Array; BCHRRR; HRRR; NOAA; data; energy; meteorology; operational forecast; power; spatiotemporal; weather; weather years; wind; wind power; wind resource; wind toolkit
- OSTI Identifier:
- 2480349
- DOI:
- https://doi.org/10.25984/2480349
Citation Formats
Buster, Grant, Pinchuk, Pavlo, Lavin, Luke, Benton, Brandon, and Bodini, Nicola. Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications. United States: N. p., 2024.
Web. doi:10.25984/2480349.
Buster, Grant, Pinchuk, Pavlo, Lavin, Luke, Benton, Brandon, & Bodini, Nicola. Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications. United States. doi:https://doi.org/10.25984/2480349
Buster, Grant, Pinchuk, Pavlo, Lavin, Luke, Benton, Brandon, and Bodini, Nicola. 2024.
"Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications". United States. doi:https://doi.org/10.25984/2480349. https://www.osti.gov/servlets/purl/2480349. Pub date:Tue Oct 15 04:00:00 UTC 2024
@article{osti_2480349,
title = {Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications},
author = {Buster, Grant and Pinchuk, Pavlo and Lavin, Luke and Benton, Brandon and Bodini, Nicola},
abstractNote = {To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.},
doi = {10.25984/2480349},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Oct 15 04:00:00 UTC 2024},
month = {Tue Oct 15 04:00:00 UTC 2024}
}