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 and inability to respond increases depletion. Energy supplies are rapidly decreasing. Electricity use causes the energy crisis. Sustainable energy essentially meets the energy demand of the growing population. In addition, it benefits the environment by reducing carbon emissions. In this situation, sustainable energy sources have supplemented traditional energy sources and promoted sustainable energy use. Solar, wind, and fuel cell energy are examples 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 follows the solar panel’s highest MPP. This study involves a system comprised of a DC-DC boost converter, a PV panel, and an ohmic load. The IC and FLC MPPT algorithms generate the duty ratio, and the PWM signal is generated by comparing it with the triangle wave. This generated signal is applied to the DC-DC boost converter. This research investigates 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 simulation findings, it has been determined that the FLC MPPT algorithm achieves the MPP faster than the IC MPPT algorithm. Consequently, the fluctuation level is minimal, and the efficiency is high.