Maximum Power Point Tracking with Incremental Conductance and Fuzzy Logic Controller in Solar Energy Systems

Abstract

Energy benefits both individuals and nations. Humanity's reliance on fossil fuels an inability to respond increases depletion. Energy supplies are rapidly decreasing. Electricity use causes the energy crisis. Sustainable energy largely meets the energy demand of the growing population. In addition, it benefits the environment by reducing carbon emissions. This situation sustainable energy sources have supplemented traditional energy sources and promoted sustainable energy use. Solar, wind, and fuel cell energy are given example of sustainable energy. Power generating facilities are employed nowadays because of their extended lifespan, inexpensive maintenance, no hazardous waste, and independence from dwindling energy sources. Solar power generation depends on environmental circumstances, hence MPP generation must be observed. MPPT follow solar panel highest MPP. This study involves a system is comprised by a DC-DC boost converter, PV panel, and a ohmic load. The duty ratio is generated by the IC and FLC MPPT algorithms, and the PWM signal is generated by comparing it with the triangle wave. This generated signal is applied to the DC-DC boost converter. The aim of this research is to investigate the effectiveness, variability, and duration required to attain the MPP of the implemented MPPT methods. The system has been developed within the MATLAB/Simulink framework. Based on the findings of the simulation, it has been determined that the FLC MPPT algorithm achieves the MPP at a faster rate compared to the IC MPPT algorithm. Consequently, the level of fluctuation is minimum and the efficiency is high.