County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model
This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly weather data (2007-2013) for different sites across the US and is used as one of the inputs to the ReEDS-2.0 model (see the "ReEDS 2.0 GitHub Repository" resource link below), developed by NREL. The weather profiles apply to any capacity that exists or is built in each region and class. This helps calculate the generation that can be provided using these resources.
Open, reference, and limited are 3 scenarios based on land-use allowance, derived from the Renewable Energy Potential (reV) model developed by NREL, which helps generate supply curves for renewable technologies and assess the maximum potential of renewable resources in a designated area. Each zipped file in this dataset corresponds to a technology and contains the respective land-use scenario files required to run that technology in ReEDS.
To use this dataset, download and place the extracted files in the locally cloned ReEDS repository inside one of the folders (inputs/variability/multi_year). After completing this copy, upon running the ReEDS model at the county-level spatial resolution for respective analysis purposes, the program will detect the presence of these files and will not fail.
Citation Formats
TY - DATA
AB - This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly weather data (2007-2013) for different sites across the US and is used as one of the inputs to the ReEDS-2.0 model (see the "ReEDS 2.0 GitHub Repository" resource link below), developed by NREL. The weather profiles apply to any capacity that exists or is built in each region and class. This helps calculate the generation that can be provided using these resources.
Open, reference, and limited are 3 scenarios based on land-use allowance, derived from the Renewable Energy Potential (reV) model developed by NREL, which helps generate supply curves for renewable technologies and assess the maximum potential of renewable resources in a designated area. Each zipped file in this dataset corresponds to a technology and contains the respective land-use scenario files required to run that technology in ReEDS.
To use this dataset, download and place the extracted files in the locally cloned ReEDS repository inside one of the folders (inputs/variability/multi_year). After completing this copy, upon running the ReEDS model at the county-level spatial resolution for respective analysis purposes, the program will detect the presence of these files and will not fail.
AU - Cole, Wesley
A2 - Brown, Maxwell
A3 - Sergi, Brian
A4 - Carag, Vincent
A5 - Serpe, Louisa
A6 - Karmakar, Akash
A7 - Lopez, Anthony
A8 - Williams, Travis
A9 - Pinchuk, Paul
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.25984/2282347
KW - energy
KW - power
KW - Capacity expansion modeling
KW - ReEDS
KW - high resolution capacity expansion
KW - capacity factor data
KW - renewable
KW - onshore wind
KW - offshore wind
KW - concentrated solar power
KW - Utility-scale PV
KW - wind power
KW - solar power
KW - hourly weather data
KW - model
KW - processed data
KW - county-level
KW - wind
KW - solar
KW - Regional Energy Deployment System
KW - computational science
LA - English
DA - 2023/08/01
PY - 2023
PB - National Renewable Energy Laboratory (NREL)
T1 - County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model
UR - https://doi.org/10.25984/2282347
ER -
Cole, Wesley, et al. County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model. National Renewable Energy Laboratory (NREL), 1 August, 2023, Open Energy Data Initiative (OEDI). https://doi.org/10.25984/2282347.
Cole, W., Brown, M., Sergi, B., Carag, V., Serpe, L., Karmakar, A., Lopez, A., Williams, T., & Pinchuk, P. (2023). County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model. [Data set]. Open Energy Data Initiative (OEDI). National Renewable Energy Laboratory (NREL). https://doi.org/10.25984/2282347
Cole, Wesley, Maxwell Brown, Brian Sergi, Vincent Carag, Louisa Serpe, Akash Karmakar, Anthony Lopez, Travis Williams, and Paul Pinchuk. County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model. National Renewable Energy Laboratory (NREL), August, 1, 2023. Distributed by Open Energy Data Initiative (OEDI). https://doi.org/10.25984/2282347
@misc{OEDI_Dataset_5986,
title = {County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model},
author = {Cole, Wesley and Brown, Maxwell and Sergi, Brian and Carag, Vincent and Serpe, Louisa and Karmakar, Akash and Lopez, Anthony and Williams, Travis and Pinchuk, Paul},
abstractNote = {This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly weather data (2007-2013) for different sites across the US and is used as one of the inputs to the ReEDS-2.0 model (see the "ReEDS 2.0 GitHub Repository" resource link below), developed by NREL. The weather profiles apply to any capacity that exists or is built in each region and class. This helps calculate the generation that can be provided using these resources.
Open, reference, and limited are 3 scenarios based on land-use allowance, derived from the Renewable Energy Potential (reV) model developed by NREL, which helps generate supply curves for renewable technologies and assess the maximum potential of renewable resources in a designated area. Each zipped file in this dataset corresponds to a technology and contains the respective land-use scenario files required to run that technology in ReEDS.
To use this dataset, download and place the extracted files in the locally cloned ReEDS repository inside one of the folders (inputs/variability/multi_year). After completing this copy, upon running the ReEDS model at the county-level spatial resolution for respective analysis purposes, the program will detect the presence of these files and will not fail.
},
url = {https://data.openei.org/submissions/5986},
year = {2023},
howpublished = {Open Energy Data Initiative (OEDI), National Renewable Energy Laboratory (NREL), https://doi.org/10.25984/2282347},
note = {Accessed: 2025-05-29},
doi = {10.25984/2282347}
}
https://dx.doi.org/10.25984/2282347
Details
Data from Aug 1, 2023
Last updated Jan 23, 2024
Submitted Jan 18, 2024
Organization
National Renewable Energy Laboratory (NREL)
Contact
Wesley Cole
Authors
Research Areas
Keywords
energy, power, Capacity expansion modeling, ReEDS, high resolution capacity expansion, capacity factor data, renewable, onshore wind, offshore wind, concentrated solar power, Utility-scale PV, wind power, solar power, hourly weather data, model, processed data, county-level, wind, solar, Regional Energy Deployment System, computational scienceDOE Project Details
Project Name ReEDS Spatial Flexibility
Project Number FY23 AOP 2.4.0.1
