Comparative Assessment of MPPT Techniques for Optimizing Photovoltaic System Efficiency

The weather uncertainties and fluctuating nature of solar radiations and varying temperature results in low conversion efficiency of the PV panel thereby necessitating the extraction of maximum power from the system. To operate the system at its peak power, track of maximum power point becomes essential for any PV system. To handle the input fluctuations and inherent non-linearities of the system, an effective MPPT technique needs to be employed. In this research paper, various classical and intelligent MPPT techniques are listed, discussed and compared on various parameters. The classical Incremental Conductance algorithm, intelligent MPPT based on fuzzy logic control and ANN method is designed and tested on a PV system using MATLAB/Simulink. The PV system entails a PV array, a boost converter, MPPT control unit, and load. These methods diverge in their characteristics and their performance is evaluated on various parameters such as tracking efficiency, response time, implementation complexity, and stability under dynamic conditions. In this work, the drawbacks of the studied methods are also pointed out. Among the implemented techniques, superiority of neural network based MPPT technique is established over the classical as well Fuzzy Logic based MPPT controller for optimizing the performance of the system.