Hybrid AI-Based Framework for Renewable Energy Forecasting: One-Stage Decomposition and Sample Entropy Reconstruction with Least-Squares Regression

Hybrid AI-Based Framework for Renewable Energy Forecasting: One-Stage Decomposition and Sample Entropy Reconstruction with Least-Squares Regression

Accurate renewable energy forecasting is crucial for grid stability and efficient energy management. This study introduces a hybrid model that combines signal decomposition and artificial intelligence to enhance the prediction of solar radiation and wind speed. The framework uses a one-stage decompo...

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Bibliographic Details
Main Authors: Nahed Zemouri, Hatem Mezaache, Zakaria Zemali, Fabio La Foresta, Mario Versaci, Giovanni Angiulli
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Energies
Subjects:
solar radiation
wind speed
hybrid deep learning forecasting
least-squares regression hybrid model
Online Access:https://www.mdpi.com/1996-1073/18/11/2942
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