Enhancing Photovoltaic Efficiency: Optimal Tilt Angle Estimation Using Advanced Machine Learning Techniques

This study explores the enhancement of the tilt angle of photovoltaic (PV) systems using both traditional empirical models and advanced machine learning techniques. Traditional methods, including second-degree polynomial, third-degree polynomial, and Fourier series models, were implemented and evaluated. In addition, advanced machine learning algorithms such as model-agnostic meta-learning (MAML), automated machine learning (AutoML) using TPOT, and transfer learning with domain adaptation were applied to optimize the tilt angle. The research aims to demonstrate the potential advantages of using sophisticated machine learning approaches over conventional methods.