| Description |
1 online resource (6 pages) : color illustrations |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Series |
Conference paper ; NREL/CP-5D00-64981 |
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Conference paper (National Renewable Energy Laboratory (U.S.)) ; NREL/CP-5 D 00-64981.
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| Note |
Title from title screen (viewed on July 1, 2016). |
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Published through SciTech Connect. |
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"To be presented at the European PV Solar Energy Conference and Exhibition, Hamburg, Germany, September 14-18, 2015." |
| Bibliography |
Includes bibliographical references (page 6). |
| Summary |
Publicly accessible, high-quality, long-term, satellite-based solar resource data is foundational and critical to solar technologies to quantify system output predictions and deploy solar energy technologies in grid-tied systems. Solar radiation models have been in development for more than three decades. For many years, the National Renewable Energy Laboratory (NREL) developed and/or updated such models through the National Solar Radiation Data Base (NSRDB). There are two widely used approaches to derive solar resource data from models: (a) an empirical approach that relates ground-based observations to satellite measurements and (b) a physics-based approach that considers the radiation received at the satellite and creates retrievals to estimate clouds and surface radiation. Although empirical methods have been traditionally used for computing surface radiation, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Project (GSIP) is an operational physical model from the National Oceanic and Atmospheric Administration (NOAA) that computes global horizontal irradiance (GHI) using the visible and infrared channel measurements from the Geostationary Operational Environmental Satellites (GOES) system. GSIP uses a two-stage scheme that first retrieves cloud properties and then uses those properties in the Satellite Algorithm for Surface Radiation Budget (SASRAB) model to calculate surface radiation. NREL, the University of Wisconsin, and NOAA have recently collaborated to adapt GSIP to create a high temporal and spatial resolution data set. The product initially generates the cloud properties using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms [3], whereas the GHI is calculated using SASRAB. Then NREL implements accurate and high-resolution input parameters such as aerosol optical depth (AOD) and precipitable water vapor (PWV) to compute direct normal irradiance (DNI) using the DISC model. The AOD and PWV, temperature, and pressure data are also combined with the MMAC model to simulate solar radiation under clear-sky conditions. The current NSRDB update is based on a 4-km x 4-km resolution at a 30-minute time interval, which has a higher temporal and spatial resolution. This paper demonstrates the evaluation of the data set using ground-measured data and detailed evaluation statistics. The result of the comparison shows a good correlation to the NSRDB data set. Further, an outline of the new version of the NSRDB and future plans for enhancement and improvement are provided. |
| Funding |
DE-AC 36-08GO28308 |
| Subject |
Solar radiation -- Databases.
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Solar Energy.
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Other Instrumentation.
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Solar radiation. (OCoLC)fst01125164
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| Genre/Form |
Databases. (OCoLC)fst01411643
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Internet resources.
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| Added Author |
National Renewable Energy Laboratory (U.S.), issuing body. Researcher.
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United States. Department of Energy. Office of Solar Electric Technology. Sponsor.
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United States. Department of Energy. Office of Scientific and Technical Information. Distributor.
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| Gpo Item No. |
0430-P-04 (online) |
| Sudoc No. |
E 9.17:NREL/CP-5 D 00-64981 |
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