Certain investigations on MPPT controller for photovoltaic system with super lift boost converter

Abstract

In recent years, the electrical energy demand increases gradually and the power generation does not meet the demand due to lack of fossil fuel and environmental issues. The production of green energy is the only solution for consumer demand. In this work, a photovoltaic power system analyses the performance under various weather conditions. The primary objective is testing Super Lift Boost Converter (SLBC) for photovoltaic system and second objective of the work is applying various Maximum Power Point Tracking (MPPT) controllers such as Increment Conductance, Fuzzy, Adaptive Neuro-Fuzzy Interference System (ANFIS) and Hybrid Fuzzy and Firefly Algorithm (HFFFA) for Maximum Power Point Tracking (MPPT) of PV system using a Super Lift Boost Converter (SLBC) and comparing their effectiveness. newlineThe mathematical modeling of the PV system is analyzed by the V-I and P-V characteristics using MATLAB/Simulink. The PV power output has been improved by using the boost converter with the modeled PV system. The effectiveness of these MPPT controllers in achieving maximum power point tracking has been analyzed with incremental conductance and fuzzy-based MPPT for PV array under different irradiance conditions. The primary objective has been achieved for different climatic irradiance conditions with maximum power output from the PV system. newlineIn the second approach, the modeling of super lift boost converter for PV system has been developed using MATLAB/Simulink, in which, the incremental conductance-based MPPT algorithm has been tested under various atmospheric conditions. The obtained results are compared with the MATLAB/Simulink output of the first task. The hardware setup is developed using an ARM processor. newline