Comparative Analysis of MPPT Control Techniques to Enhance Solar Energy Utilization and Convergence Time Under Varying Meteorological Conditions and Loads

The electrical energy generated from solar energy photovoltaic (PV) technology is intermittent, varying, and irregular. With PV technology's limited energy conversion efficiency, it is imperative to extract the maximum of converted energy. The zero slopes of the power versus voltage curve are utilized to determine the maximum power point. Conventional algorithms provide lower convergence time along with low power oscillations. This paper proposes an adaptive perturb and observe (A-P&O) maximum power point tracking (MPPT) technique for the energy conversion system. The primary objectives of the proposed technique are to obtain a more robust, better tracking capability, improved efficiency, and fast response lesser oscillations under steady-state with a simple structure to implement. Maximum power point (MPP) tracking under varying meteorological conditions and load variations is still a challenge. The proposed P&O technique has been tested under realistic meteorological variations and load variations. The comparative evaluation of the proposed adaptive-step size A-P&O MPPT technique and other conventional techniques such as perturb and observe (P&O), incremental conductance (IC), modified P&O and fuzzy logic control (FLC) have also been performed. The performance of the proposed control technique is evaluated using a MATLAB/Simulink environment. The obtained results confirm that the proposed control technique is superior in performance as compared to the other four conventional techniques.