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SHORT-RANGE SOLAR RADIATION FORECASTS IN SUPPORT OF SMART GRID TECHNOLGY

Solar and wind energy generation assets are fast emerging as sources that will eventually supply a greater share of domestic electricity needs. The US power grid will require new infrastructure to connect these power generation facilities with consumers, as well as smarter controls to better match fluctuating supply and demand cycles. For example, solar energy generation facilities will be impacted by changes in the local cloud distribution. If these intra-day changes could be detected and forecast, the information could be used to order increases (decreases) in power production (consumption) from elsewhere. In this paper we describe a prospective solar radiation forecast system that integrates cloud analysis, prediction, and radiative transfer technologies to provide the smart grid with this valuable information. The proposed system combines imager data from groundand space-based remote sensing systems, a cloud forecast model to provide a detailed forecast of various cloud properties for time periods of minutes up to an hour or more, and a radiative transfer model for computation of downwelling solar irradiance in the appropriate waveband at the solar collector. In later sections we describe the components of the forecast system in further detail and illustrates some of its capabilities.