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Wind Turbine Road Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from roads based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from a road that an energy project may be developed, and these varied widely across the counties in which they exis...

Geospatial Data Science, N. National Renewable Energy Laboratory (NREL)

Jan 01, 2024
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Wind Turbine Railroad Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from railroad based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from a railroad that an energy project may be developed, and these varied widely across the counties in which th...

Geospatial Data Science, N. National Renewable Energy Laboratory (NREL)

Jan 01, 2024
5 Resources
0 Stars
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Wind Turbine Transmission Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from transmission based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from transmission infrastructure that an energy project may be developed, and these varied widely across the...

Geospatial Data Science, N. National Renewable Energy Laboratory (NREL)

Jan 01, 2024
5 Resources
0 Stars
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Wind Turbine Structure Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from structures based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from a structure that an energy project may be developed, and these varied widely across the counties in which...

Geospatial Data Science, N. National Renewable Energy Laboratory (NREL)

Jan 01, 2024
5 Resources
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Annual Average Modeled Wind Speed for Puerto Rico and the Virgin Islands at a 100 Meter Hub Height

This is supplemental data to the 50 m height data set that was validated by NREL and wind energy meteorological consultants in 2007. The data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m spatial re...

Heimiller, D. National Renewable Energy Laboratory

Nov 25, 2014
2 Resources
0 Stars
In curation

Annual Average Modeled Wind Speed (m/s) for Puerto Rico and the Virgin Islands at a 70 Meter Hub Height.

This is supplemental data to the 50 m height data set that was validated by NREL and wind energy meteorological consultants in 2007. The data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m spatial re...

Heimiller, D. National Renewable Energy Laboratory

Nov 25, 2014
2 Resources
0 Stars
In curation

Lidar NOAA High Resolution Doppler Lidar (HRDL) Raw Data

**Data Details** HRDL Water Tank: Lat (40.041), Lon (-105), Alt (1602m)

Brewer, A. Wind Energy Technologies Office (WETO)

Mar 01, 2015
1 Resources
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Lidar NOAA High Resolution Doppler Lidar (HRDL) Derived Data

**Data Details** HRDL Water Tank: Lat (40.041), Lon (-105), Alt (1602m)

Brewer, A. Wind Energy Technologies Office (WETO)

Mar 01, 2015
1 Resources
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Lidar NOAA High Resolution Doppler Lidar (HRDL) Processed Data

**Data Details** HRDL Water Tank: Lat (40.041), Lon (-105), Alt (1602m)

Brewer, A. Wind Energy Technologies Office (WETO)

Mar 01, 2015
1 Resources
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Lidar UMBC WindCube 200S Doppler Lidar Processed Data

**Data Details** UMBC Lidar: Water Tank: lat(40.041) lon(-105) alt(1602) 20150410-20150416 NW Pad: lat(40.051) lon(-105) alt(1578) 20150416-20150428 Visitor's Center: lat(40.045) lon(-105) alt(1587) 20150428 20150502

Brewer, A. Wind Energy Technologies Office (WETO)

Apr 09, 2015
1 Resources
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Lidar UMBC WindCube 200S Doppler Lidar Derived Data

**Data Details** UMBC Lidar: Water Tank: lat(40.041) lon(-105) alt(1602) 20150410-20150416 NW Pad: lat(40.051) lon(-105) alt(1578) 20150416-20150428 Visitor's Center: lat(40.045) lon(-105) alt(1587) 20150428 20150502

Brewer, A. Wind Energy Technologies Office (WETO)

Apr 09, 2015
1 Resources
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Lidar UMBC WindCube 200S Doppler Lidar Raw Data

**Data Details** UMBC Lidar: Water Tank: lat(40.041) lon(-105) alt(1602) 20150410-20150416 NW Pad: lat(40.051) lon(-105) alt(1578) 20150416-20150428 Visitor's Center: lat(40.045) lon(-105) alt(1587) 20150428 20150502

Brewer, A. Wind Energy Technologies Office (WETO)

Apr 09, 2015
1 Resources
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Surface Meteorological Station UND 10m, (2) Sonics 3m 10m, (2) T/RH 3m 10m, Physics site-11 Raw Data

**Overview** The data included features wind, temperature, and turbulence measurements. **Data Details** Each met station (met.z18, met.z19, met.z21, and met.z23) consists of multiple levels of three-dimensional ultrasonic anemometers, RM Young 81000 (sampling frequency = 20 ...

Fernando, J. et al Wind Energy Technologies Office (WETO)

Feb 14, 2016
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Surface Meteorological Station UND 17m, (3) Sonics 3m 10m 17m, (2) T/RH 3m 17m, Physics site-2 Raw Data

**Overview** The data included features wind, temperature, and turbulence measurements. **Data Details** Each met station (met.z18, met.z19, met.z21, and met.z23) consists of multiple levels of three-dimensional ultrasonic anemometers, RM Young 81000 (sampling frequency = 20 ...

Fernando, J. et al Wind Energy Technologies Office (WETO)

Feb 14, 2016
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Surface Meteorological Station UND 10m, (2) Sonics 3m 10m, (2) T/RH 3m 10m (1) Licor 3m, Physics site-1 Raw Data

**Overview** The data included features wind, temperature, and turbulence measurements. **Data Details** Each met station (met.z18, met.z19, met.z21, and met.z23) consists of multiple levels of three-dimensional ultrasonic anemometers, RM Young 81000 (sampling frequency = 20 ...

Fernando, J. et al Wind Energy Technologies Office (WETO)

Feb 13, 2016
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Surface Meteorological Station UND 21m, (3) Sonics 3m 10m 21m, (2) T/RH 3m 21m, Physics site-6 Raw Data

**Overview** The data included features wind, temperature, and turbulence measurements. **Data Details** Each met station (met.z18, met.z19, met.z21, and met.z23) consists of multiple levels of three-dimensional ultrasonic anemometers, RM Young 81000 (sampling frequency = 20 ...

Fernando, J. et al Wind Energy Technologies Office (WETO)

Feb 14, 2016
1 Resources
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United States Land-based Wind Representative Profiles 2007-2013 & 2015-2023

This data packet contains hourly generation profiles (representative profiles) for land-based wind across the contiguous United States. Hourly representative generation profiles are available for each reV supply curve site (~53,000 sites) which represents about 11.5 KM x 11.5 KM s...

Geospatial Data Science, N. National Renewable Energy Laboratory (NREL)

Jun 16, 2025
20 Resources
0 Stars
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Global CFDDA-based Onshore and Offshore Wind Potential Supply Curves by Country, Class, and Depth

This dataset contains global onshore and offshore wind supply curves based on a resource assessment performed at the National Renewable Energy Laboratory (NREL) based on the National Center for Atmospheric Research's (NCAR) Climate Four Dimensional Data Assimilation (CFDDA) mesosc...

Sullivan, P. et al National Renewable Energy Laboratory

Nov 25, 2014
2 Resources
1 Stars
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United States Land-based Wind Supply Curves 2023

This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for land-based wind across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE...

GDS, N. National Renewable Energy Laboratory

Jun 30, 2023
13 Resources
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United States Land-based Wind Supply Curves 2024

This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for land-based wind across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE...

Geospatial Data Science, N. National Renewable Energy Laboratory

Jan 01, 2025
12 Resources
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United States Renewable Energy Technical Potential

Renewable energy technical potential as defined in this report represents the achievable energy generation of a particular technology given system performance, topographic limitations, environmental, and land-use constraints. The primary benefit of assessing technical potential...

Lopez, A. and Laboratory, N. National Renewable Energy Laboratory

Nov 25, 2014
4 Resources
0 Stars
In curation

U.S. State Wind Resource Potential

Estimates for each of the 50 states and the entire United States showing the windy land area with a gross capacity factor (without losses) of 30% and greater at 80-m height above ground and the wind energy potential from development of the “available” windy land area after exc...

Wood, J. and America, W. National Renewable Energy Laboratory

Nov 25, 2014
2 Resources
0 Stars
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Surface Meteorological Station BAO West of Tower, Surface Processed Data

**Overview** Proving basic surface meteorology, soil hydrology and temperature, and fluxes of energy (radiation and turbulent fluxes) and water (precipitation, evaporation, and soil moisture). **Data Details** Contact **David Noone**. **Data Quality** This dataset is prelimi...

Noone, D. Wind Energy Technologies Office (WETO)

Feb 28, 2015
1 Resources
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Freedom Field Site Data: June 14, 2011

Freedom Field is a not-for-profit organization formed to facilitate development and commercialization of renewable energy solutions. The organization has installed a variety of renewable energy generating technologies at their facility (located at Rock River Water Reclamation in R...

Hallett, K. and Field, F. National Renewable Energy Laboratory

Jul 18, 2011
2 Resources
0 Stars
In curation

wfip2.model/realtime.hrrr_esrl.graphics.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Dec 14, 2015
1 Resources
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