A Comparative Study between Different MPPT Algorithms for PV System

Abstract

Maximum Power Point Tracking (MPPT) algorithms are essential for optimizing the performance of photovoltaic (PV) generation systems. This study introduces a Fuzzy Logic Controller (FLC) for MPPT in PV systems, which is compared to conventional tracking algorithms, namely Perturb and Observe (P&O) and Incremental Conductance (INC).  In addition to the MPPT algorithm, the optimal selection of a DC-DC boost converter is critical for enhancing the efficiency of PV systems. Boost converters are particularly advantageous in applications where the output voltage needs to be higher than the input voltage provided by the solar panels. When selecting a boost converter, factors such as efficiency, cost, size, and operational reliability must be considered. The conventional boost converter is commonly evaluated options; which has distinct characteristics that affect its performance under varying environmental conditions. The proposed system was simulated and tested using MATLAB Simulink with a PV solar panel model. Results indicate that the FLC-based MPPT tracking requires less time to reach the maximum power point and provides more accurate performance under rapidly changing atmospheric conditions compared to P&O and INC methods.