A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition

A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition

Accurate forecasting of photovoltaic (PV) power is essential for effective grid integration and energy management, particularly in solar-rich regions such as Algeria. This study presents a robust forecasting framework that combines advanced feature selection techniques with deep learning architectu...

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Bibliographic Details
Main Authors: Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem
Format: Article
Language:English
Published: Nigerian Society of Physical Sciences 2025-08-01
Series:Journal of Nigerian Society of Physical Sciences
Subjects:
PV power
Renewable energy
Feature selection
Artificial Neural Networks
Forecasting
Online Access:https://journal.nsps.org.ng/index.php/jnsps/article/view/2795
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