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Title: Assessment of the National Solar Radiation Database (NSRDB 1998-2016)

Abstract

Applying traceable and standardized uncertainty characterization for solar resource data provides confidence in the dataset for use by financiers, developers and site operators of solar energy conversion systems, and ultimately reduces deployment cost. Performance guarantees of solar energy conversion systems are based on the available solar resource from measurement stations or modeled dataset such as the National Solar Radiation Database (NSRDB). In this study we implemented a comprehensive uncertainty determination approach [1]. The study also analyzed how the NSRDB (19982016) - Version 3 compares with the previous NSRDB (19982015) - Version 2. The study also attempted to estimate the uncertainty differences derived by comparing theNSRDB data to the seven measurement stations from the National Oceanic and Atmospheric Administration's Surface Radiation Budget Network (SURFRAD) and University of Oregon Solar Radiation Monitoring Laboratory (SRML). The evaluation was conducted for hourly values, daily totals, monthly mean daily totals, and annual mean monthly mean daily totals and demonstrate the qualityof the new datasets currently available from the NSRDB.

Authors:
 [1]; ORCiD logo [1];  [1];  [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1507663
Report Number(s):
NREL/CP-5D00-73702
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC), 10-15 June 2018, Waikoloa Village, Hawaii
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY; uncertainty; satellites; measurement uncertainty; solar radiation; solar energy; clouds; renewable energy sources

Citation Formats

Habte, Aron M, Sengupta, Manajit, Lopez, Anthony J, Xie, Yu, and Maclaurin, Galen J. Assessment of the National Solar Radiation Database (NSRDB 1998-2016). United States: N. p., 2018. Web. doi:10.1109/PVSC.2018.8547589.
Habte, Aron M, Sengupta, Manajit, Lopez, Anthony J, Xie, Yu, & Maclaurin, Galen J. Assessment of the National Solar Radiation Database (NSRDB 1998-2016). United States. doi:10.1109/PVSC.2018.8547589.
Habte, Aron M, Sengupta, Manajit, Lopez, Anthony J, Xie, Yu, and Maclaurin, Galen J. Thu . "Assessment of the National Solar Radiation Database (NSRDB 1998-2016)". United States. doi:10.1109/PVSC.2018.8547589.
@article{osti_1507663,
title = {Assessment of the National Solar Radiation Database (NSRDB 1998-2016)},
author = {Habte, Aron M and Sengupta, Manajit and Lopez, Anthony J and Xie, Yu and Maclaurin, Galen J},
abstractNote = {Applying traceable and standardized uncertainty characterization for solar resource data provides confidence in the dataset for use by financiers, developers and site operators of solar energy conversion systems, and ultimately reduces deployment cost. Performance guarantees of solar energy conversion systems are based on the available solar resource from measurement stations or modeled dataset such as the National Solar Radiation Database (NSRDB). In this study we implemented a comprehensive uncertainty determination approach [1]. The study also analyzed how the NSRDB (19982016) - Version 3 compares with the previous NSRDB (19982015) - Version 2. The study also attempted to estimate the uncertainty differences derived by comparing theNSRDB data to the seven measurement stations from the National Oceanic and Atmospheric Administration's Surface Radiation Budget Network (SURFRAD) and University of Oregon Solar Radiation Monitoring Laboratory (SRML). The evaluation was conducted for hourly values, daily totals, monthly mean daily totals, and annual mean monthly mean daily totals and demonstrate the qualityof the new datasets currently available from the NSRDB.},
doi = {10.1109/PVSC.2018.8547589},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {11}
}

Conference:
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