Assessment of machine and deep learning models integrated with variational mode decomposition for photovoltaic power forecasting using real-world data from the semi-arid region of Djelfa, Algeria

Robrini, Ferial El, Amrouche, Badia, Cali, Umit orcid.org/0000-0002-6402-0479 et al. (1 more author) (2025) Assessment of machine and deep learning models integrated with variational mode decomposition for photovoltaic power forecasting using real-world data from the semi-arid region of Djelfa, Algeria. Energy Conversion and Management: X. 101108. ISSN 2590-1745

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Item Type: Article
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Publisher Copyright: © 2025 The Author(s)

Keywords: Deep learning,Grid-connected photovoltaic power plant,Long short-term memory,Prediction
Dates:
  • Accepted: 14 June 2025
  • Published (online): 23 June 2025
  • Published: 1 July 2025
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Electronic Engineering (York)
Depositing User: Pure (York)
Date Deposited: 02 Jul 2025 09:50
Last Modified: 02 Jul 2025 09:50
Published Version: https://doi.org/10.1016/j.ecmx.2025.101108
Status: Published
Refereed: Yes
Identification Number: 10.1016/j.ecmx.2025.101108
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Description: Assessment of machine and deep learning models integrated with variational mode decomposition for photovoltaic power forecasting using real-world data from the semi-arid region of Djelfa, Algeria

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