Ray George

A new operational model for satellite-derived irradiances: description and validation

We present a new simple model capable of exploiting geostationary satellite visible images for the production of site/time-specific global and direct irradiances The new model features new clear sky global and direct irradiance functions, a new cloud-index-to-irradiance index function, and a new global-to-direct-irradiance conversion model. The model can also exploit operationally available snow cover resource data, while deriving local ground specular reflectance characteristics from the stream of incoming satellite data. Validation against 10 US locations representing a wide range of climatic environments indicates that model performance is systematically improved, compared to current visible-channel-based modeling practice.

Calculation of solar radiation using a methodology with worldwide potential

Surface meteorological observations from the DATSAV2 database provide the capability to use the METSTAT (meteorological/statistical) model to calculate hourly values of direct normal, diffuse horizontal, and global horizontal solar radiation for locations throughout the world. Opaque cloud cover, a key input parameter to the METSTAT model, is derived from the DATSAV2 layered cloud cover information. Resulting multiyear data sets include solar radiation and other meteorological data such as dry bulb temperature, dew point temperature, wind speed, and atmospheric pressure. Data filling procedures ensure that the multiyear data sets are serially complete. A minor revision to METSTAT improved solar radiation estimates for conditions of high cloud amounts and low ceiling heights. The methodology was applied to regions of Southern Africa and Saudi Arabia.

Solar and Wind Resource Assessments for Afghanistan and Pakistan

The U.S. National Renewable Energy Laboratory (NREL) has recently completed the production of high-resolution wind and solar energy resource maps and related data products for Afghanistan and Pakistan. The resource data have been incorporated into a geospatial toolkit (GsT), which allows the user to manipulate the resource information along with country-specific geospatial information such as highway networks, power facilities, transmission corridors, protected land areas, etc. The toolkit allows users to then transfer resource data for specific locations into NREL’s micropower optimization model known as HOMER.

Adapting Existing Spatial Data Sets to New Uses: An Example from Energy Modeling

ABSTRACT Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, and economic projections. These data are available at various spatial and temporal scales, which may be different from those needed by the energy modeling community. If the translation from the original format to the format required by the energy researcher is incorrect, then resulting models can produce misleading conclusions. This is of increasing importance because of the fine resolution data required by models for new alternative energy sources such as wind and distributed generation. This paper addresses the matter by applying spatial statistical techniques which improve the usefulness of spatial data sets (maps) that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) imputing missing data and (3) merging spatial data sets.