Comparison and Performance Enhancement of Maximum Power Point Tracking Technique for Photovoltaic Systems using Genetic Algorithm

Maximum Power Point Tracking (MPPT) techniques are commonly used in photovoltaic (PV) systems to optimize power output, but conventional methods often cause power oscillations around the MPP and non-conventional methods can be complex. This paper presents a Genetic Algorithms (GAs) based MPPT method that aims to improve convergence speed, accuracy, and overall performance. It effectively tracks the global MPP, especially in partial shading scenarios. The research includes an algorithm overview, test examples, and a comparative study using MATLAB/Simulink against Perturb and Observe (PO) and Incremental Conductance (IC) techniques. Results show the proposed method reduces MPP oscillations, enhances system stability, and improves output power efficiency.