Concentrating Solar Power- the Determination of Solar Resources for any Latitude - Longitude location in Florida. (Final Report)

Report Number



Solar Energy; Solar Thermal


The objective of this project was to produce a detailed map of Florida that shows the monthly solar direct beam and global resource available for the past eleven years. This solar resource map will give potential users or designers of solar systems, the solar resource input values for their location's latitude and longitude in the form of a table of solar energy monthly averages for that specific site. The concept employed to determine these solar resource values was to use NOAA satellite photos from the past eleven years and utilize the brightness of the cloud cover as a clearness factor predictor of the solar resource that gets through to the ground below. Solar concentrating systems use direct beam solar energy focused to produce high temperatures for power production. They hold promise for Florida given a sufficient direct beam resource and assuming the technology can meet production and cost goals. The evaluation of solar concentration systems for performance and energy production requires as input, a prediction of the solar direct beam resource throughout the year for the anticipated installation location. These systems have been previously installed in the desert southwest where direct beam data has been accumulated over many years. Existing measurements of direct beam solar energy are limited to a few Florida locations and, thus, a problem was identified, the lack of validated direct beam measurements for the State of Florida. This information is a necessary input for existing performance/output models to determine projected cost per kWh of solar concentrating power plants in the Florida environment. Various methodologies to resolve the direct beam problem were investigated. Over 40 published papers were reviewed for information on the determination of the direct beam resource and the establishment and validation of predicting equations. The Heliostat-2 method was selected as the most viable to provide validated direct beam historical data for Florida. This method (developed a few years ago by Ecole de Mines de Paris) basically consist of using two parameters, turbidity (atmospheric conditions), and elevation as input, to provide an estimation of the total, beam and diffuse radiation based on a 'clear sky model'. That is, the amount of direct beam and diffuse radiation that would reach the ground for a totally clear sky, given location, time of year, and time of day. From the literature and experience, equations were derived and programmed that predict theoretical optimum clear sky daily insolation (Hc). The clearness value (x) of each pixel in satellite photos was used to mediate the clear sky insolation values to produce ground level predicted values (H) for that pixel area (5 miles x 5 miles). The hypothesis was tested by comparing NOAA weather satellite data from summer and fall of 2010 retrieved and real irradiance values that were measured at FSEC. Correlations (r sq) of predicted vs. real values were found to be above 0.90 at the 95% confidence level.Using the NOAA historical data sets developed and actual ground measured data taken at Florida Solar Energy Center (FSEC), new correlations were developed that calculate the ground measured direct beam and direct diffuse solar daily insolation. Using these correlations, solar direct beam and direct diffuse radiation values were calculated for each day of the eleven year data base for each of the 10,272 Florida locations (each pixel). Each daily value for each location was averaged across the 11 years of data to produce an average value representative of each day of the year. Daily values for each month were then averaged to produce direct beam and direct diffuse monthly averages for each of the Florida locations. These monthly data were also averaged to produce an annual average data set. Monthly averages and annual average data were formulated into a master table and loaded into an excel spreadsheet.

Date Published



Solar Energy; Solar Thermal

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