The performance of photovoltaic (PV) systems is affected by unexpected irradiation, temperature and weather conditions, degrading their performance and yield. Many researchers around the world have developed various maximum power point tracking (MPPT) techniques to increase the efficiency and lifetime of these PV systems. In this work, a method based on a fuzzy logic controller type 2 (FLC-T2) is presented, which corrects the limitations of the proposed fuzzy logic controller type 1 (FLC-T1) algorithms, such as the trade-off between dynamic response and steady-state oscillation. This technique combines the advantages of P&O-MPPT (Perturb & Observe MPPT) to take into account slow and fast variations in solar irradiance, and the reduced processing time of FLC-MPPT, to solve complex technical problems with a reduced number of membership function rules. Experimental results validated and executed using MATLAB/Simulink software prove that the proposed FLC-T2 MPPT controller outperforms the conventional FLC-T1 MPPT controller in all performance metrics considered, leading to improved power output and, consequently, reduced power losses.
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Amokrane et al. (2024) studied this question.
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