Cloud Detection Methodology Based on a Sky-imaging System

Abstract : This paper deals with an image processing methodology based on a sky-imaging system developed at the PROMES-CNRS laboratory. It is a part of a project which aims at improving solar plant control procedures using Direct Normal Irradiance (DNI) forecasts under various sky conditions at short term horizon (5-30 minutes) and high spatial resolution (~1 km²). The work presented in this paper is about the improvement of the cloud cover estimation, which is the main step in DNI forecasting. First, an overview of the existing sky-imaging systems and the current cloud detection algorithms is presented. Next, the experimental setup is introduced. Then, the methodology used to estimate the cloud cover is detailed. Finally, the paper ends with some results and discussion.
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Rémi Chauvin, Julien Nou, Stéphane Thil, Adama Traoré, Stéphane Grieu. Cloud Detection Methodology Based on a Sky-imaging System. Energy Procedia, Elsevier, 2015, International Conference on Concentrating Solar Power and Chemical Energy Systems, SolarPACES 2014, 69, pp.1970-1980. ⟨10.1016/j.egypro.2015.03.198⟩. ⟨hal-01273353⟩

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