Proposition of Ant Colony and Perturb and Observe MPPT Combination for Photovoltaic System

Abstract

This research presents a novel hybrid Maximum Power Point Tracking (MPPT) technique that combines Ant Colony Optimization (ACO) with the Perturb and Observe (P&O) method to enhance the efficiency and convergence speed of photovoltaic (PV) systems. The ACO MPPT, based on swarm intelligence, is utilized for its ability to conduct a global search for the maximum power point. In contrast, the P&O method provides steady-state tracking with low computational complexity. By integrating these two approaches, the research aims to leverage their respective strengths to achieve faster and more reliable convergence under varying environmental conditions. The study employs the NTR 5E3E monocrystalline PV module (173.5W) as the test subject, with the implementation carried out in a MATLAB Simulink environment. The experimental results demonstrate that the hybrid approach outperforms the standalone P&O and ACO MPPT methods in terms of convergence speed, accuracy, and stability, indicating promising potential for practical applications in PV systems.