Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the Assessment of PV System and Wind Turbine Performance
This dataset comprises Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the efficient assessment of PV system and wind turbine performance for over 2,000 locations across the U.S. TSYs and TWYs are single synthetic years generated from the National Aeronautics and Space Administration (NASA) Prediction of Worldwide Energy Resources (POWER) data spanning from 2001 to 2022. These synthetic years represent the long-term average solar and wind resource conditions of a location, respectively. The POWER solar data is derived from satellite observations and has a spatial resolution of 1 degree * 1 degree (latitude/longitude). The meteorological variables are sourced from NASA's Goddard Earth Observing System (GEOS) Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) assimilation model, which features a spatial resolution of 1/2 degree * 5/8 degree (latitude/longitude).
The methods for creating TSYs and TWYs are adapted from the Sandia method. Specifically, the weights assigned to different weather parameters have been adjusted, and the final selection step has been omitted. For TSYs, a weight of 0.7 is assigned to daily cumulative GHI, and 0.3 is assigned to daily cumulative DNI. For TWYs, weights of 0.2, 0.2, and 0.6 are assigned to daily median zonal wind speed, daily median meridional wind speed, and daily 0.75 quantile wind speed, respectively. These weights have been optimized based on the simulated solar PV system and wind turbine outputs. 12 representative months are then selected based on their Finkelstein-Schafer (FS) statistics and concatenated into a synthetic year. The paper describing our methodology has been published in Applied Energy and is available via the "Project Publication" resource link below.
The TSYs and TWYs are provided for the centroids of all Public Use Microdata Areas (PUMAs) in the U.S. PUMAs are non-overlapping statistical geographic areas that partition each state or equivalent entity into regions containing no fewer than 100,000 people each. The 2,378 PUMAs collectively cover the entire U.S. A file named "PUMA information.csv" is included with the dataset, containing the PUMA number, PUMA name, latitude, longitude, elevation, and time zone of all PUMA centroids. Users can reference this file to find the PUMAs corresponding to their locations of interest.
To accommodate different user communities, the data is provided in three formats. The TSYs are available in EPW and SAM weather file formats, while the TWYs are available in EPW, SAM weather file, and CSV formats. The EPW format, developed by the U.S. Department of Energy, is a de facto standard for weather data in building energy modeling and is compatible with various building energy modeling programs, including EnergyPlus, ESP-r, and IESVE. The SAM weather file format is designed for the System Advisor Model (SAM), a renewable energy project evaluation tool developed by the National Renewable Energy Laboratory (NREL).
If you use this dataset in your research, please consider citing our paper: Zeng, Z., Stackhouse, P., Kim, J.-H. (Jeannie), & Muehleisen, R. T. (2025). Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S. Applied Energy, 377, 124698. https://doi.org/10.1016/j.apenergy.2024.124698.
Citation Formats
TY - DATA
AB - This dataset comprises Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the efficient assessment of PV system and wind turbine performance for over 2,000 locations across the U.S. TSYs and TWYs are single synthetic years generated from the National Aeronautics and Space Administration (NASA) Prediction of Worldwide Energy Resources (POWER) data spanning from 2001 to 2022. These synthetic years represent the long-term average solar and wind resource conditions of a location, respectively. The POWER solar data is derived from satellite observations and has a spatial resolution of 1 degree * 1 degree (latitude/longitude). The meteorological variables are sourced from NASA's Goddard Earth Observing System (GEOS) Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) assimilation model, which features a spatial resolution of 1/2 degree * 5/8 degree (latitude/longitude).
The methods for creating TSYs and TWYs are adapted from the Sandia method. Specifically, the weights assigned to different weather parameters have been adjusted, and the final selection step has been omitted. For TSYs, a weight of 0.7 is assigned to daily cumulative GHI, and 0.3 is assigned to daily cumulative DNI. For TWYs, weights of 0.2, 0.2, and 0.6 are assigned to daily median zonal wind speed, daily median meridional wind speed, and daily 0.75 quantile wind speed, respectively. These weights have been optimized based on the simulated solar PV system and wind turbine outputs. 12 representative months are then selected based on their Finkelstein-Schafer (FS) statistics and concatenated into a synthetic year. The paper describing our methodology has been published in Applied Energy and is available via the "Project Publication" resource link below.
The TSYs and TWYs are provided for the centroids of all Public Use Microdata Areas (PUMAs) in the U.S. PUMAs are non-overlapping statistical geographic areas that partition each state or equivalent entity into regions containing no fewer than 100,000 people each. The 2,378 PUMAs collectively cover the entire U.S. A file named "PUMA information.csv" is included with the dataset, containing the PUMA number, PUMA name, latitude, longitude, elevation, and time zone of all PUMA centroids. Users can reference this file to find the PUMAs corresponding to their locations of interest.
To accommodate different user communities, the data is provided in three formats. The TSYs are available in EPW and SAM weather file formats, while the TWYs are available in EPW, SAM weather file, and CSV formats. The EPW format, developed by the U.S. Department of Energy, is a de facto standard for weather data in building energy modeling and is compatible with various building energy modeling programs, including EnergyPlus, ESP-r, and IESVE. The SAM weather file format is designed for the System Advisor Model (SAM), a renewable energy project evaluation tool developed by the National Renewable Energy Laboratory (NREL).
If you use this dataset in your research, please consider citing our paper: Zeng, Z., Stackhouse, P., Kim, J.-H. (Jeannie), & Muehleisen, R. T. (2025). Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S. Applied Energy, 377, 124698. https://doi.org/10.1016/j.apenergy.2024.124698.
AU - Zeng, Zhaoyun
A2 - Stackhouse, Paul
A3 - Kim, Ji-Hyun
A4 - Muehleisen, Ralph
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO -
KW - Renewable energy
KW - Photovoltaic system
KW - Solar power
KW - Wind turbine
KW - Wind power
KW - Typical meteorological year
KW - pv system
KW - TSY
KW - TWY
KW - system performance
KW - data
KW - solar
KW - wind
KW - typical wind year
KW - typical solar year
KW - resource conditions
KW - PUMA
LA - English
DA - 2024/07/14
PY - 2024
PB - Argonne National Laboratory
T1 - Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the Assessment of PV System and Wind Turbine Performance
UR - https://data.openei.org/submissions/6112
ER -
Zeng, Zhaoyun, et al. Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the Assessment of PV System and Wind Turbine Performance. Argonne National Laboratory, 14 July, 2024, Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/6112.
Zeng, Z., Stackhouse, P., Kim, J., & Muehleisen, R. (2024). Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the Assessment of PV System and Wind Turbine Performance. [Data set]. Open Energy Data Initiative (OEDI). Argonne National Laboratory. https://data.openei.org/submissions/6112
Zeng, Zhaoyun, Paul Stackhouse, Ji-Hyun Kim, and Ralph Muehleisen. Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the Assessment of PV System and Wind Turbine Performance. Argonne National Laboratory, July, 14, 2024. Distributed by Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/6112
@misc{OEDI_Dataset_6112,
title = {Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the Assessment of PV System and Wind Turbine Performance},
author = {Zeng, Zhaoyun and Stackhouse, Paul and Kim, Ji-Hyun and Muehleisen, Ralph},
abstractNote = {This dataset comprises Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the efficient assessment of PV system and wind turbine performance for over 2,000 locations across the U.S. TSYs and TWYs are single synthetic years generated from the National Aeronautics and Space Administration (NASA) Prediction of Worldwide Energy Resources (POWER) data spanning from 2001 to 2022. These synthetic years represent the long-term average solar and wind resource conditions of a location, respectively. The POWER solar data is derived from satellite observations and has a spatial resolution of 1 degree * 1 degree (latitude/longitude). The meteorological variables are sourced from NASA's Goddard Earth Observing System (GEOS) Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) assimilation model, which features a spatial resolution of 1/2 degree * 5/8 degree (latitude/longitude).
The methods for creating TSYs and TWYs are adapted from the Sandia method. Specifically, the weights assigned to different weather parameters have been adjusted, and the final selection step has been omitted. For TSYs, a weight of 0.7 is assigned to daily cumulative GHI, and 0.3 is assigned to daily cumulative DNI. For TWYs, weights of 0.2, 0.2, and 0.6 are assigned to daily median zonal wind speed, daily median meridional wind speed, and daily 0.75 quantile wind speed, respectively. These weights have been optimized based on the simulated solar PV system and wind turbine outputs. 12 representative months are then selected based on their Finkelstein-Schafer (FS) statistics and concatenated into a synthetic year. The paper describing our methodology has been published in Applied Energy and is available via the "Project Publication" resource link below.
The TSYs and TWYs are provided for the centroids of all Public Use Microdata Areas (PUMAs) in the U.S. PUMAs are non-overlapping statistical geographic areas that partition each state or equivalent entity into regions containing no fewer than 100,000 people each. The 2,378 PUMAs collectively cover the entire U.S. A file named "PUMA information.csv" is included with the dataset, containing the PUMA number, PUMA name, latitude, longitude, elevation, and time zone of all PUMA centroids. Users can reference this file to find the PUMAs corresponding to their locations of interest.
To accommodate different user communities, the data is provided in three formats. The TSYs are available in EPW and SAM weather file formats, while the TWYs are available in EPW, SAM weather file, and CSV formats. The EPW format, developed by the U.S. Department of Energy, is a de facto standard for weather data in building energy modeling and is compatible with various building energy modeling programs, including EnergyPlus, ESP-r, and IESVE. The SAM weather file format is designed for the System Advisor Model (SAM), a renewable energy project evaluation tool developed by the National Renewable Energy Laboratory (NREL).
If you use this dataset in your research, please consider citing our paper: Zeng, Z., Stackhouse, P., Kim, J.-H. (Jeannie), & Muehleisen, R. T. (2025). Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S. Applied Energy, 377, 124698. https://doi.org/10.1016/j.apenergy.2024.124698.},
url = {https://data.openei.org/submissions/6112},
year = {2024},
howpublished = {Open Energy Data Initiative (OEDI), Argonne National Laboratory, https://data.openei.org/submissions/6112},
note = {Accessed: 2025-04-24}
}
Details
Data from Jul 14, 2024
Last updated Apr 15, 2025
Submitted Jul 15, 2024
Organization
Argonne National Laboratory
Contact
Zhaoyun Zeng