Deep learning methods for intra-day cloudiness prediction using geostationary satellite images in a solar forecasting framework

Franco Marchesoni-Acland; Andrés Herrera; Franco Mozo; Ignacio Camiruaga; Alberto Castro; Rodrigo Alonso-Suárez

doi:10.1016/j.solener.2023.111820

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Deep learning methods for intra-day cloudiness prediction using geostationary satellite images in a solar forecasting framework

Franco Marchesoni-Acland Andrés Herrera Franco Mozo Ignacio Camiruaga Alberto Castro Rodrigo Alonso-Suárez

Year: 2023 Journal: Solar Energy Vol: 262 Pages: 111820-111820 Publisher: Elsevier BV

DOI: 10.1016/j.solener.2023.111820

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Keywords:

Geostationary orbit Cloud cover Cloud computing Solar irradiance Computer science Pixel Meteorology Geostationary Operational Environmental Satellite Satellite Environmental science Remote sensing Artificial intelligence Geography

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Solar Radiation and Photovoltaics

Physical Sciences → Computer Science → Artificial Intelligence

Photovoltaic System Optimization Techniques

Physical Sciences → Energy → Renewable Energy, Sustainability and the Environment

Image Enhancement Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Deep learning methods for intra-day cloudiness prediction using geostationary satellite images in a solar forecasting framework

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