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WIND Toolkit - Long-Term Ensemble Dataset

In curation License 

WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing time series every 5 min and 2 km, including model uncertainty of wind speed at every modeling grid point so that users are provided with a range of possible wind speeds every 2 km. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: (1) numerical simulations covering the continental United States, Alaska, and Hawaii, with high-resolution data being available for 3 years (2018-2020). (2) Climate simulations from Argonne National Laboratories covering the North American continent, including Alaska, Canada, and most of Mexico and the Caribbean Islands. These simulations complement the new WTK-LED to offer a 4-km dataset covering 20 years, from 2001-2020. (3) Specific long-term, high-resolution offshore simulations have been conducted separately for the US coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind (NOW-23) data set.

Because the accuracy of simulations from a mesoscale model, such as WRF, varies depending on the location and weather situation, and can reach up to several m/s for wind speed, we provide simulated wind speed uncertainty estimates to the community to be used in conjunction with the deterministic model simulations.

This dataset was developed to satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have.

Citation Formats

National Renewable Energy Laboratory (NREL). (2024). WIND Toolkit - Long-Term Ensemble Dataset [data set]. Retrieved from https://data.openei.org/submissions/5987.
Export Citation to RIS
Wang, Jiali, Bodini, Nicola, Purkayastha, Avi, and Young, Ethan. WIND Toolkit - Long-Term Ensemble Dataset. United States: N.p., 24 Jan, 2024. Web. https://data.openei.org/submissions/5987.
Wang, Jiali, Bodini, Nicola, Purkayastha, Avi, & Young, Ethan. WIND Toolkit - Long-Term Ensemble Dataset. United States. https://data.openei.org/submissions/5987
Wang, Jiali, Bodini, Nicola, Purkayastha, Avi, and Young, Ethan. 2024. "WIND Toolkit - Long-Term Ensemble Dataset". United States. https://data.openei.org/submissions/5987.
@div{oedi_5987, title = {WIND Toolkit - Long-Term Ensemble Dataset}, author = {Wang, Jiali, Bodini, Nicola, Purkayastha, Avi, and Young, Ethan.}, abstractNote = {WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing time series every 5 min and 2 km, including model uncertainty of wind speed at every modeling grid point so that users are provided with a range of possible wind speeds every 2 km. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: (1) numerical simulations covering the continental United States, Alaska, and Hawaii, with high-resolution data being available for 3 years (2018-2020). (2) Climate simulations from Argonne National Laboratories covering the North American continent, including Alaska, Canada, and most of Mexico and the Caribbean Islands. These simulations complement the new WTK-LED to offer a 4-km dataset covering 20 years, from 2001-2020. (3) Specific long-term, high-resolution offshore simulations have been conducted separately for the US coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind (NOW-23) data set.

Because the accuracy of simulations from a mesoscale model, such as WRF, varies depending on the location and weather situation, and can reach up to several m/s for wind speed, we provide simulated wind speed uncertainty estimates to the community to be used in conjunction with the deterministic model simulations.

This dataset was developed to satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have.}, doi = {}, url = {https://data.openei.org/submissions/5987}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {01}}

Details

Data from Jan 24, 2024

Last updated Feb 14, 2024

Submitted Jan 24, 2024

Organization

National Renewable Energy Laboratory (NREL)

Contact

Caroline Draxl

Authors

Jiali Wang

Argonne National Laboratory ANL

Nicola Bodini

National Renewable Energy Laboratory NREL

Avi Purkayastha

National Renewable Energy Laboratory NREL

Ethan Young

National Renewable Energy Laboratory NREL

DOE Project Details

Project Name National Wind Resource Databaase

Project Number FY23 AOP 4.1.0.410

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