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This study investigates the optimization of photovoltaic (PV) systems through advanced data-driven regression models for predicting the Maximum Power Point (PMPP). It compares various techniques, including Ridge, Lasso, Decision Tree, and Random Forest Regression, highlighting that tree-based models, particularly Random Forest, provide superior predictive accuracy. The findings emphasize the importance of precise irradiance data and suggest future research directions to further enhance PMPP prediction accur

Author

miguelarderius

Language

EN