MAXIMUM POWER POINT TRACKING USING FUZZY LOGIC CONTROLLER IN SOLAR PV SYSTEMS

Abstract

This study conducts a comparative analysis between the conventional Perturb and Observe (P&O) method and fuzzy logic control (FLC) to determine the superior approach for maximizing power extraction in solar photovoltaic (PV) systems.  The P&O method, frequently employed for Maximum Power Point Tracking (MPPT), demonstrates significant oscillations upon reaching the maximum power point (MPP) and necessitates a considerable duration to achieve stability.  The dynamic performance of the PV system output is examined by utilizing MATLAB simulations of P&O method while considering different irradiance levels.  To overcome the use of the P&O method, a fuzzy logic controller is employed to manage the constraints and evaluate the system. The experiments were conducted in different irradiance and the output performance of both FLC, and P&O was noted such as at 800 W/m² irradiance, FLC stabilizes at a voltage of approximately
258 V but P&O continues to show significant oscillations with lower voltage around 240 V to 250 V. The findings indicate that FLC significantly mitigates variations at the MPP and achieves a greater output value with a more rapid response time while the P&O algorithm exhibits significant oscillations and delayed responses, particularly under higher irradiance levels. The study's findings indicate that FLC is a superior and more dependable solution for MPPT in PV systems, resulting in enhanced overall reliability and efficiency.