Improving Solar Radiation Nowcasts by Blending Data-Driven, Satellite-Images-Based and All-Sky-Imagers-Based Models Using Machine Learning Techniques

Improving Solar Radiation Nowcasts by Blending Data-Driven, Satellite-Images-Based and All-Sky-Imagers-Based Models Using Machine Learning Techniques

Accurate solar radiation nowcasting models are critical for the integration of the increasing solar energy in power systems. This work explored the benefits obtained by the blending of four all-sky-imagers (ASI)-based models, two satellite-images-based models and a data-driven model. Two blending ap...

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Bibliographic Details
Main Authors: Miguel López-Cuesta, Ricardo Aler-Mur, Inés María Galván-León, Francisco Javier Rodríguez-Benítez, Antonio David Pozo-Vázquez
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Remote Sensing
Subjects:
solar energy
solar irradiance nowcasting
machine learning models blending
all sky imagers (ASI)
MSG satellite images
Online Access:https://www.mdpi.com/2072-4292/15/9/2328

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