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.
Original language | American English |
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Pages | 2305-2308 |
Number of pages | 4 |
DOIs | |
State | Published - 26 Nov 2018 |
Event | 7th IEEE World Conference on Photovoltaic Energy Conversion, WCPEC 2018 - Waikoloa Village, United States Duration: 10 Jun 2018 → 15 Jun 2018 |
Conference
Conference | 7th IEEE World Conference on Photovoltaic Energy Conversion, WCPEC 2018 |
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Country/Territory | United States |
City | Waikoloa Village |
Period | 10/06/18 → 15/06/18 |
Bibliographical note
See NREL/CP-5D00-71607 for preprintNREL Publication Number
- NREL/CP-5D00-73702
Keywords
- clouds
- measurement uncertainty
- renewable energy sources
- satellites
- solar energy
- solar radiation
- uncertainty