Environmental Protection

Solar Radiation Database Updated by NREL

The National Renewable Energy Laboratory has released an updated version of the U.S. National Solar Radiation Database. The database tracks hourly solar and meteorological parameters and is widely used by renewable energy analysts and others to plan, size, and site solar electric systems.

The U.S. Department of Energy’s (DOE) National Renewable Energy Laboratory (NREL) and collaborators released a 20-year updated version of the U.S. National Solar Radiation Database, a web-based technical report that provides critical information about solar and meteorological data for 1,454 locations in the U.S. and its territories.

The updated Solar Radiation Database covers 1991-2010 and includes data from 2006-2010 for the first time. The database features improved cloud algorithms for modeling solar radiation data, and an improved State University of New York (SUNY) model for gridded data based on satellite observations.

The National Solar Radiation Database (NSRD) provides solar resource information to industry in support of central solar power plant and distributed rooftop feasibility studies, economic analyses and research. The database also underlies other industry data and tools, including NREL’s Typical Meteorological Year (TMY) data sets, PVWatts calculator, Solar Power Prospector and System Advisor Model (SAM).

The NSRDB solar data fields include global horizontal, direct normal, and diffuse horizontal irradiance. The NSRDB also features a 20-year summary with statistics (monthly/annual, diurnal, and persistence) for the 860 serially complete stations.

NREL has applied uncertainty estimates to each hourly data record to help users determine the suitability of data for each application. Station data are broadly classified based on uncertainty as Class I, II, and III. The first two classifications segregate serially complete stations by data of higher and lower quality respectively. Class III stations have data gaps in the period of record, yet hold enough data in the time series to support many applications.

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