Enhancing PV System Efficiency: An Analysis of Intelligent MPPT Algorithms

Abstract

The efficiency of photovoltaic (PV) systems is highly dependent on their ability to operate at the Maximum Power Point (MPP) under varying environmental conditions. Traditional Maximum Power Point Tracking (MPPT) algorithms, such as Perturb and Observe (P&O) and Incremental Conductance, often fall short in rapidly changing irradiance and temperature scenarios. This work explores the implementation of intelligent MPPT algorithms using Metaheuristic Optimization Methods, to improve tracking efficiency, response time and overall system performance. Specifically, the analysis focuses on the adaptability and robustness of these algorithms in handling the nonlinear characteristics of PV systems. Simulation results and performance comparisons demonstrate the potential of these algorithms to enhance the overall energy yield of PV systems, particularly in dynamic environments.