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SUNYA Satellite Model. One goal of the updated NSRDB is a spatial resolution greater than the ancillary interpolated products that were later produced based on the 239 NSRDB meteorological stations. Toward that end, we are considering using a model that estimates solar radiation from satellite imagery. The Atmospheric Sciences Research Center (ASRC) at SUNYA has been developing such a model, which derives 10- km-pixel solar estimates based on differences between a pixel’s clear-sky reflectance as seen by the satellite and the brighter values that occur with increasing cloud reflectance of incoming solar radiation. The SUNYA model has been refined to take into account anomalous ground conditions that occur either geographically (specular reflections from bright sand or water) or with time (snow cover). Perez et al. have shown that the refined model, when compared with 13 ground measurement stations, has an average mean bias error (MBE) in global irradiance of 3 W/m2 (less than 1% of the average irradiance) and an average root mean square error (RMSE) of 54 W/m2 (14%). The errors for direct normal estimates are an MBE of 4 W/m2 (1%) and RMSE of 137 W/m2 (30%). Analysis. The three models described above have been run using the available input data to produce modeled solar radiation data for the 33 station test sites. The resulting output data set holds a total of 396 station months, or 245,909 daylight station hours available, for comparison with the measured data in the test sites. Because the objective of the project is to produce a data base of solar radiation with the same statistical properties as the measured data, our primary focus for model performance is not on hour-by-hour comparisons of model and measured data, but comparison of appropriate statistics for the measured and modeled data. This was the objective of the original NSRDB: the philosophy being that even if there were great discrepancies in hour-by-hour modeled data with respect to measured data (if it were available), if the model data set provided the correct statistics (mean, variance) for monthly solar radiation data, then hourly simulations using these data over periods of a month to a year to many years would result in correct computation of simulation results. Preliminary investigations will look at the clear- sky envelopes, which are the basis of the model computations, in comparison with measured clear- sky data to discern possible inherent biases between the models. We will then investigate MBE, RMSE, scatter plots, and correlations between measured and modeled data, the difference between measured and modeled data as a function of measured irradiance, and as cumulative probability functions as in Fig. 1. Fig. 1. Preliminary cumulative probability plots for two years of hourly measured global horizontal (squares) and three model data sets (satellite, circles; METSTAT, triangles; ASHRAE: diamonds) for a single test site. We will intensively investigate the hypothesis that the difference between monthly means of daily total and hourly average modeled and measured solar radiation is zero. For the proposed Solar Resource Knowledge Management task, meetings of technical experts were held in Washington, DC, in December 2003 and in Madrid, Spain, in February 2004. A draft work plan for the task was developed at these meetings and formally submitted to the Solar Heating and Cooling Program Executive Committee (ExCo). The work plan was presented at their semi-annual meeting in Helsinki in May, and the ExCo then directed the NREL Task Organizer to prepare a formal annex to submit to the IEA and to the ExCo for formal approval. The annex will be reviewed at the next ExCo meeting in Costa Rica in November 2004. NREL willPDF Image | FY 2004 ANNUAL REPORT DOE Solar
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