Intrahour Direct Normal Irradiance Forecasting Based on Sky Image Processing and Time-Series Analysis - CNRS - Centre national de la recherche scientifique
Communication Dans Un Congrès Année : 2024

Intrahour Direct Normal Irradiance Forecasting Based on Sky Image Processing and Time-Series Analysis

Résumé

The present paper exhibits a hybrid model for intrahour forecasting of direct normal irradiance (DNI). It combines a knowledge-based model, which is used for clear-sky DNI forecasting from DNI measurements, with a machine-learning-based model, that evaluates the impact of atmospheric disturbances on the solar resource, through the processing of high dynamic range sky images provided by a ground-based camera. The performance of the hybrid model is compared with that of two machine learning models based on past DNI observations only. The results highlight the pertinence of combining knowledge-based models with data-driven models, and of integrating sky-imaging data in the DNI forecasting process. Parts of this paper were published as journal articleKarout, Y.; Thil, S.; Eynard, J.; Guillot, E.; Grieu, S. Hybrid intrahour DNI forecast model based on DNI measurements and sky-imaging data. Solar Energy. 2023, 249, 541-558. https://doi.org/10.1016/j.solener.2022.11.032
Fichier principal
Vignette du fichier
648_Karout_et_al.pdf (1.59 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04751054 , version 1 (25-10-2024)

Licence

Identifiants

Citer

Youssef Karout, Stéphane Thil, Julien Eynard, Emmanuel Guillot, Stéphane Grieu. Intrahour Direct Normal Irradiance Forecasting Based on Sky Image Processing and Time-Series Analysis. SolarPACES 2022, Sep 2022, Albuquerque, United States. ⟨10.52825/solarpaces.v1i.648⟩. ⟨hal-04751054⟩
11 Consultations
2 Téléchargements

Altmetric

Partager

More