Web tools for performance analysis and planning support for solar energy plants (PV, CSP, CPV) starting from remotely sensed optical images
|Potenza, Marco Alberto Carlo
|Fleischer, Andreas G.
|We present new services, developed also under the GMES ENDORSE (ENergy DOwnstream SErvices) project, for the performance analysis and the support in the planning of solar plants (photovoltaic, CSP, CPV) that combine a detailed model of each part of the plant (solar field, thermal storage system, electrical power system and inverters) and the near real-time remote sensing of the global (or direct component) of solar irradiance incident on the plane normal to sun rays (DNI) at ground level. Starting from temporal series of satellite Meteosat Second Generation (MSG) optical images, elaborated via the Heliosat algorithm (MACC Core Service), we obtain firstly the solar global horizontal irradiance (GHI) and then the GTI or the BNI using a model to derive irradiance on tilted planes from GHI. Combining these parameters with the model and technical features of the solar power plant, using also air temperature values (measured in-situ), we can assess in near-real-time the daily evolution of the alternate current power coming from the plant and then, using a temporal integration, we can finally obtain the expected daily energy yield by the plant. We are therefore able to compare this energy yield based on satellite measurements with the measured one and, consequently, to readily detect any possible malfunctions and to evaluate the performances of the plant. This method has been successfully applied for the performance analysis of several test solar plants, showing always a precision less than 15% with respect to the measured values of energy yield by a well-functioning plant.
|Proceedings of the 27th Conference on Environmental Informatics - Informatics for Environmental Protection, Sustainable Development and Risk Management
|Web tools for performance analysis and planning support for solar energy plants (PV, CSP, CPV) starting from remotely sensed optical images
|Web services for assessment of Resources and Impacts of Renewable Energies (EnerGEO/ENDORSE)