An optimal Fuzzy logic controller based MPPT controller for a PV system

Abstract

The increasing demand for electrical energy in remote locations necessitates exploration into alternative power sources. This thesis examines the viability of solar energy, a renewable source predominantly influenced by meteorological conditions. We conduct a comprehensive study of the photovoltaic (PV) system and its components, with a particular focus on Maximum Power Point Tracking (MPPT) methods. Simulation studies investigate the performance of two prevalent MPPT techniques—Perturbation and Observation (P&O) and Fuzzy Logic—to optimize power output by tracking the PV system's maximum power point. Furthermore, this research introduces an innovative approach by integrating a Genetic Algorithms (GAs) with the fuzzy logic method to enhance its effectiveness and efficiency. Comparative studies show that the optimized fuzzy logic strategy works better, which highlights its potential benefits for making photovoltaic systems more efficient in remote power applications.