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Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

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Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience.

NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on gold standard wind datasets. One important factor identified by ESIG's 2023 report "Weather Dataset Needs for Planning and Analyzing Modern Power Systems" for gold standard wind data is regular updates.

To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA). See the HRRR resources linked below for more information.

One barrier to NREL using HRRR is consistency with NREL's existing wind datasets (e.g. WIND Toolkit, "WTK") across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NREL's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). Similar to the WTK, BC-HRRR includes wind speed, direction, temperature, and humidity data across the contiguous United States (both onshore and offshore) at several hub heights.

BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling to 15+ weather years of wind data with low-overhead extensibility to future years as they occur and are made available by NOAA.

This data conforms to the typical NREL wind/solar resource data format, which is described in the "NREL Renewable Energy Resource Data Documentation" resource below. Additionally, it can be used in the same way as other NREL wind/solar data

Citation Formats

The National Renewable Energy Lab (NREL). (2024). Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications [data set]. Retrieved from https://data.openei.org/submissions/6218.
Export Citation to RIS
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., 15 Oct, 2024. Web. https://data.openei.org/submissions/6218.
Buster, Grant, Pinchuk, Pavlo, Lavin, Luke, Benton, Brandon, & Bodini, Nicola. Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications. United States. https://data.openei.org/submissions/6218
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. https://data.openei.org/submissions/6218.
@div{oedi_6218, title = {Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications}, author = {Buster, Grant, Pinchuk, Pavlo, Lavin, Luke, Benton, Brandon, and Bodini, Nicola.}, abstractNote = {Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience.

NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on gold standard wind datasets. One important factor identified by ESIG's 2023 report "Weather Dataset Needs for Planning and Analyzing Modern Power Systems" for gold standard wind data is regular updates.

To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA). See the HRRR resources linked below for more information.

One barrier to NREL using HRRR is consistency with NREL's existing wind datasets (e.g. WIND Toolkit, "WTK") across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NREL's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). Similar to the WTK, BC-HRRR includes wind speed, direction, temperature, and humidity data across the contiguous United States (both onshore and offshore) at several hub heights.

BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling to 15+ weather years of wind data with low-overhead extensibility to future years as they occur and are made available by NOAA.

This data conforms to the typical NREL wind/solar resource data format, which is described in the "NREL Renewable Energy Resource Data Documentation" resource below. Additionally, it can be used in the same way as other NREL wind/solar data}, doi = {}, url = {https://data.openei.org/submissions/6218}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {10}}

Details

Data from Oct 15, 2024

Last updated Nov 26, 2024

Submitted Nov 22, 2024

Organization

The National Renewable Energy Lab (NREL)

Contact

Grant Buster

720.495.6245

Authors

Grant Buster

National Renewable Energy Lab

Pavlo Pinchuk

National Renewable Energy Lab

Luke Lavin

National Renewable Energy Lab

Brandon Benton

National Renewable Energy Lab

Nicola Bodini

National Renewable Energy Lab

DOE Project Details

Project Name Energy Sector Modeling and Impacts (WETO Modeling & Analysis)

Project Number 71140

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