Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017)
Abstract
The study assesses the long-term spatial and temporal solar resource variability in America using the 20-year National Renewable Energy Laboratory's (NREL's) National Solar Radiation Database (NSRDB). Specifically, the coefficient of variation (COV) is used to analyze the spatial and temporal (interannual and seasonal) variability. Further, both spatial and temporal long-term variability are analyzed using the Köppen-Geiger climate classification. The temporal variability is found that, on average, the continental United States (CONUS) COV reaches up to 5% for global horizontal irradiance (GHI) and 10% for direct normal irradiance (DNI), and that the NSRDB domain's COV is roughly twice that of CONUS. For the seasonal variability analysis, the winter months are found to exhibit higher COV than the other seasons. In particular, December exhibits the highest variability, reaching on average 30% for DNI and 20% for GHI over various areas. On the other hand, the summer months demonstrate significantly lower variability, reaching only less than 20% for DNI and 10% for GHI, on average. Similarly, the spatial variability is analyzed by comparing each pixel to its neighbors. The long-term spatial variability is found to increase with the number of neighboring pixels being considered, which is equivalent to an increase in distance (withinmore »
- Authors:
-
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Solar Consulting Services, Colebrook, NH (United States)
- US Department of Energy (USDOE), Washington DC (United States). Solar Energy Technologies Office
- Publication Date:
- Research Org.:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
- OSTI Identifier:
- 1665826
- Alternate Identifier(s):
- OSTI ID: 1809915
- Report Number(s):
- NREL/JA-5D00-76353
Journal ID: ISSN 1364-0321; MainId:6575;UUID:9025dd5f-be63-ea11-9c31-ac162d87dfe5;MainAdminID:17420
- Grant/Contract Number:
- AC36-08GO28308; EE0007673
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Renewable and Sustainable Energy Reviews
- Additional Journal Information:
- Journal Volume: 134; Journal ID: ISSN 1364-0321
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 14 SOLAR ENERGY; long-term spatial; National Solar Radiation Database; NSRDB; solar resource; temporal
Citation Formats
Habte, Aron, Sengupta, Manajit, Gueymard, Christian, Golnas, Anastasios, and Xie, Yu. Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017). United States: N. p., 2020.
Web. doi:10.1016/j.rser.2020.110285.
Habte, Aron, Sengupta, Manajit, Gueymard, Christian, Golnas, Anastasios, & Xie, Yu. Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017). United States. https://doi.org/10.1016/j.rser.2020.110285
Habte, Aron, Sengupta, Manajit, Gueymard, Christian, Golnas, Anastasios, and Xie, Yu. Tue .
"Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017)". United States. https://doi.org/10.1016/j.rser.2020.110285. https://www.osti.gov/servlets/purl/1665826.
@article{osti_1665826,
title = {Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017)},
author = {Habte, Aron and Sengupta, Manajit and Gueymard, Christian and Golnas, Anastasios and Xie, Yu},
abstractNote = {The study assesses the long-term spatial and temporal solar resource variability in America using the 20-year National Renewable Energy Laboratory's (NREL's) National Solar Radiation Database (NSRDB). Specifically, the coefficient of variation (COV) is used to analyze the spatial and temporal (interannual and seasonal) variability. Further, both spatial and temporal long-term variability are analyzed using the Köppen-Geiger climate classification. The temporal variability is found that, on average, the continental United States (CONUS) COV reaches up to 5% for global horizontal irradiance (GHI) and 10% for direct normal irradiance (DNI), and that the NSRDB domain's COV is roughly twice that of CONUS. For the seasonal variability analysis, the winter months are found to exhibit higher COV than the other seasons. In particular, December exhibits the highest variability, reaching on average 30% for DNI and 20% for GHI over various areas. On the other hand, the summer months demonstrate significantly lower variability, reaching only less than 20% for DNI and 10% for GHI, on average. Similarly, the spatial variability is analyzed by comparing each pixel to its neighbors. The long-term spatial variability is found to increase with the number of neighboring pixels being considered, which is equivalent to an increase in distance (within a 100-km x 100-km square grid). As expected, the DNI spatial variability is higher than that of GHI. Moreover, the annual solar irradiance anomalies are found to reach ±25% for both GHI and DNI (and even exceed those value in some instances) during each year of the 20-year period.},
doi = {10.1016/j.rser.2020.110285},
journal = {Renewable and Sustainable Energy Reviews},
number = ,
volume = 134,
place = {United States},
year = {Tue Sep 08 00:00:00 EDT 2020},
month = {Tue Sep 08 00:00:00 EDT 2020}
}
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