Author
Listed:
- Kharismi Burhanudin
(Centre for Advanced Computing Technology (C-ACT), Fakulti Kecerdasan Buatan dan Keselamatan Siber (FAIX), Universiti Teknikal Malaysia Melaka (UTeM), 76100 Durian Tunggal, Melaka)
- Mohd Nazrien Zaraini
(Centre for Advanced Computing Technology (C-ACT), Fakulti Kecerdasan Buatan dan Keselamatan Siber (FAIX), Universiti Teknikal Malaysia Melaka (UTeM), 76100 Durian Tunggal, Melaka)
- Muhammad Faheem Mohd Ezani
(Centre for Advanced Computing Technology (C-ACT), Fakulti Kecerdasan Buatan dan Keselamatan Siber (FAIX), Universiti Teknikal Malaysia Melaka (UTeM), 76100 Durian Tunggal, Melaka)
- Muhamad Nabil Hidayat
(College of Engineering, UiTM Shah Alam, Selangor)
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.
Suggested Citation
Kharismi Burhanudin & Mohd Nazrien Zaraini & Muhammad Faheem Mohd Ezani & Muhamad Nabil Hidayat, 2025.
"Proposition of Ant Colony and Perturb and Observe MPPT Combination for Photovoltaic System,"
International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(10), pages 8814-8830, October.
Handle:
RePEc:bcp:journl:v:9:y:2025:i:10:p:8814-8830
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