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distributions, probability distributions, correlation, and autocorrelation. In the figure below, the analysis reveals little significant differences among the three candidate models (Northeast Regional Climate Center, SUNYA, and METSTAT). Our analysis illustrates not only the closeness of the model performance, but also the similarity of excursions for all models in site-to-site variability. These excursions may indicate a common bias in the models or input data, or an error in the ground validation data. Whatever the cause, it is important in this context to note that all models perform similarly. 3.2 “Solar Resource Knowledge Management” IEA Task 36 The three subtasks in Task 36 will contribute to achieving the vision of fast and easy access to relevant, qualified, and reliable solar resource information that has been benchmarked to international standards. Subtask A: This is a standard qualification for solar resource products. This subtask will develop and produce deliverables designed to provide: • Coherence and benchmarking of models producing surface irradiance values from satellite data (these will include SUNYA, NREL Climatological Solar Radiation (CSR) model, and NASA Surface Meteorology and Solar Energy (SSE) models, which are also being used for the NSRDB updates) • Accessibility and coherence of ancillary model input data such as atmospheric conditions and land surface parameters • Sensitivity analyses • Ground truth validations with high-quality data • Definition of validation protocols and measures of end-product confidence • Cross-satellite platform and cross-model comparisons. An example of visual benchmarking approaches is shown in the figures below, which compare the SUNYA with the NREL CSR model results applied for Central America. SUNYA NREL CSR Subtask B: Common structure for archiving and accessing resource products. This subtask will develop and produce deliverables designed to provide: • Development of worldwide networking between distributed data centers, resulting in a global coverage for high-quality solar resource data • Development of information and data exchange protocols • Reliable and fast end-user access • Preparation of data documentation for specific end-user applications. The main outcome of Subtask B will be a unique Web entry point that performs a smart network of resources and products. Specifically, Subtask B will build on the existing knowledge and precursor Web services, such as the portals SoDa or NASA services, to construct an advanced prototype of the information system. Resources (e.g., a database) will comprise a Web server and will be connected on a voluntary basis to this information system. Providers of such resources (e.g., NASA, German Aerospace Center [DLR]) are deemed to have a strong strategic interest in maintaining these resources, whether on a free or commercial basis. In the latter case, other sources of revenues may be obtained by opening to other domains such as agriculture or tourism. The Web service (entry point) will be made of core software only and will be easy to maintain, transfer, operate, and duplicate (to ensure reliability). This service will be maintained by motivated partners, such as Armines, with possible commercial revenues. Subtask C: Improved techniques for solar resource characterization and forecasts. This Photovoltaic R&D Fundamental Research 35PDF Image | DOE Solar Energy Technologies Program
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