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This review paper examines hybrid techniques for photovoltaic (PV) power estimation and forecasting, integrating physical models with machine learning approaches. It categorizes these hybrid methodologies into three main types: physics-informed machine learning models, optimized physical models, and physics-guided models, while discussing their applications, strengths, and weaknesses. The paper aims to provide insights that can enhance the accuracy and reliability of PV power forecasting, contributing to th
- Author
- drouichenaima40
- Language
- EN