Evaluation of Fuzzy Logic Control for Maximum Power Point Tracking in Renewable Energy Systems

This study focuses on photovoltaic (PV) panels and investigates the application of fuzzy logic control for maximum power point tracking (MPPT) in renewable energy systems. Historically, a range of algorithms have been created to maximize solar panel power extraction under a variety of operating circumstances. One clear benefit of fuzzy logic algorithms is their ease of implementation, which eliminates the need for an exact mathematical model of the solar panel. This work uses MATLAB Simulink to build and construct a fuzzy controller for solar panels. Through numerical simulations, the efficacy of the suggested fuzzy MPPT algorithm is shown, with output power levels approaching the solar panel's full capacity. The study goes on to assess how well the fuzzy logic MPPT performs in various environmental settings, such as temperature and light intensity. It is imperative to sustain the output power around the maximum power point in spite of variations in the surrounding conditions. By giving the fuzzy logic controller a third input parameter, beta, the suggested method introduces a fresh strategy. The suggested fuzzy logic MPPT approach has been shown effective by experimental findings, which demonstrate its higher accuracy and efficiency over current fuzzy logic control models. Furthermore, the suggested method shows reduced power fluctuations, which helps to provide electricity in steady and dependable manner under a variety of climatic conditions. Overall, this study highlights how fuzzy logic control may improve MPPT system performance for RE applications, especially when it comes to solar PV system optimization under varying environnmental conditions.