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El Fezazi, Nabil
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Computer Science & IT Electrical & Electronics Engineering

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Enhancing photovoltaic system maximum power point tracking with fuzzy logic-based perturb and observe method Aziz Jafar, Muhammad Ihsan; Zakaria, Muhammad Iqbal; Dahlan, Nofri Yenita; Kamarudin, Muhammad Nizam; El Fezazi, Nabil
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp2386-2399

Abstract

Photovoltaic systems have emerged as a promising energy resource that caters to the future needs of society, owing to their renewable, inexhaustible, and cost-free nature. The power output of these systems relies on solar cell radiation and temperature. In order to mitigate the dependence on atmospheric conditions and enhance power tracking, a conventional approach has been improved by integrating various methods. To optimize the generation of electricity from solar systems, the maximum power point tracking (MPPT) technique is employed. To overcome limitations such as steady-state voltage oscillations and improve transient response, two traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb and observe (P&O), have been modified. This research paper aims to simulate and validate the step size of the proposed modified P&O and FLC techniques within the MPPT algorithm using MATLAB/Simulink for efficient power tracking in photovoltaic systems.
Comparative assessment of an improved asymmetrical fuzzy logic control-based maximum power point tracking for photovoltaic systems under partially shaded conditions Ariffin, Athirah Batrisyia Kamal; Zakaria, Muhammad Iqbal; Munim, Wan Noraishah Wan Abdul; Kamarudin, Muhammad Nizam; El Fezazi, Nabil
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp2642-2654

Abstract

This paper presents an enhanced asymmetrical fuzzy logic control (AFLC) based maximum power point tracking (MPPT) algorithm designed for photovoltaic (PV) systems under partial shading conditions (PSCs). With the increasing global energy demand and growing environmental concerns, maximizing solar energy efficiency has become more essential than ever. The proposed AFLC-MPPT algorithm tackles the challenges of accurately tracking the global maximum power point (GMPP) in PSCs, where conventional methods frequently underperform. By utilizing asymmetrical membership functions and optimized rule sets, the algorithm significantly improves sensitivity and precision in detecting and responding to variations in shading. Simulations conducted in MATLAB/Simulink compare the performance of the proposed AFLC-based MPPT with the conventional perturb and observe (P&O) method across multiple shading scenarios. The results demonstrate that the AFLC approach outperforms the conventional method in terms of tracking speed, stability, and overall efficiency, particularly in dynamically changing environmental conditions. Furthermore, the AFLC algorithm provides substantial improvements in voltage regulation, reduces settling time, and minimizes steady-state oscillations, contributing to the more efficient and reliable operation of PV systems under partial shading conditions.
Co-Authors Ariffin, Athirah Batrisyia Kamal Aziz Jafar, Muhammad Ihsan Dahlan, Nofri Yenita Muhammad Nizam Kamarudin Munim, Wan Noraishah Wan Abdul Zakaria, Muhammad Iqbal