Communication science et technologie
Volume 23, Numéro 1, Pages 36-44
2025-07-23
Machine Learning Algorithms For Enhancing Mppt In Clean Energy Systems
Authors : Addou Asmaa . Mazouz Nacera .
Abstract
Artificial Intelligence (AI) and Machine Learning (ML) play a crucial role in improving clean energy systems, particularly solar energy. This study proposes a data-driven MPPT approach using a regression tree algorithm in photovoltaic (PV) systems. A novel dataset, built from high-resolution experimental data under various environmental conditions, served for training and validation. The ML model achieved 96% accuracy in predicting optimal operating parameters. This AI-based framework enables dynamic and precise estimation of the Maximum Power Point (MPP). The system enhances overall efficiency and supports the clean energy transition. Realtime model deployment confirms its practical feasibility. The method shows potential for integration into smart solar regulators. The approach offers adaptive control and improved sustainability. This research highlights the synergy between ML and clean energy technologies.
Keywords
Maximum Power Point Tracking MPPT ; Machine Learning ; Artificial Intelligence ; Clean Energy Optimization ; Intelligent Control Strategies
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