Enhancing PV efficiency: A comparative study of FLC, SMC, and P&O MPPT algorithms using Matlab/Simscaper
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Abstract
The growing demand for sustainable energy has accelerated the development of efficient photovoltaic power conversion systems. However, the nonlinear behavior of photovoltaic generators and their strong dependence on solar irradiance and temperature significantly affect the amount of extractable power. Therefore, effective control strategies are required to ensure continuous operation at the optimal operating point where maximum power can be delivered. This study presents a comparative investigation of three maximum power point tracking techniques applied to a photovoltaic system: Perturb and Observe, Improved Sliding Mode Control, and Fuzzy Logic Control. A detailed simulation model of the photovoltaic energy conversion system is developed to evaluate the dynamic performance of each control strategy under varying irradiance conditions. The comparison focuses on key performance indicators including tracking speed, stability, power oscillations, and robustness. The obtained results demonstrate that intelligent and nonlinear control approaches significantly enhance the energy harvesting capability of photovoltaic systems compared with conventional methods. In particular, Fuzzy Logic Control provides superior tracking accuracy, faster dynamic response, and reduced steady-state oscillations, whereas Improved Sliding Mode Control offers strong robustness with reduced oscillatory behavior. These findings confirm the effectiveness of advanced control strategies in improving the efficiency and stability of photovoltaic energy conversion systems.
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