Adaptive P&O algorithm for fast and acurate maximum power point tracking for PV system

Abstract

In this study, we proposed an adaptive perturb and observe (P&O) algorithm designed for efficient maximum power point tracking (MPPT) in photovoltaic (PV) systems. This method addresses key challenges in solar energy systems, including variability in solar irradiation and partial shading conditions. The proposed method introduced a dynamic and adaptive in adjusting the step size of the P&O as it nears the maximum power point (MPP), enhancing tracking precision and reducing energy losses. To show the ability of the proposed, we compared it with the conventional P&O and GWO & P&O. The proposed adaptive P&O MPPT algorithm consistently maintains near ideal tracking efficiency of ≈99.7% across various irradiance scenarios, significantly outperforming conventional P&O, which drops to 74.45% under partial shading. Overall, it achieves an average efficiency of 99.71%, surpassing hybrid P&O GWO (99.52%) and conventional P&O (91.30%), demonstrating superior reliability and energy harvesting performance. The results indicated that the proposed could reduce power deviations and obtain greater accuracy in detecting MPP. The study confirms the method's potential for optimizing energy extraction and suggests further refinement for broader applicability. This advancement represents a significant step in enhancing the reliability and efficiency of PV systems in both grid-connected and off-grid applications.