Enhanced MPPT in Partially Shaded PV Systems Using PSO Optimization Technique

This project proposes the design of Maximum Power Point Tracking (MPPT) using the Particle Swarm Optimization (PSO) technique under partial shading conditions. Besides that, a DC-DC buck converter was designed to adapt the voltage to its appropriate value to reach a maximal power extraction for a ph...

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Bibliographic Details
Published in:2024 IEEE 4th International Conference in Power Engineering Applications (ICPEA) pp. 264 - 269
Main Authors: Darus, Rosheila, Samat, Ahmad Asri Bin Abd, Ghazali, Muhammad Eillieyin Mohd, Gumilar, Langlang, Kamarudin, Nornaim, Tajudin, Mohammad Faridun Naim
Format: Conference Proceeding
Language:English
Published: IEEE 04-03-2024
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Summary:This project proposes the design of Maximum Power Point Tracking (MPPT) using the Particle Swarm Optimization (PSO) technique under partial shading conditions. Besides that, a DC-DC buck converter was designed to adapt the voltage to its appropriate value to reach a maximal power extraction for a photovoltaic (PV) system. The scope of the study focused on tracking the Maximum Power Point (MPP) of the PV system, simulating uniform, and non-uniform shading conditions, and using a MATLAB/Simulink to model the overall system for validation purposes. The process of this research involved designing the PV system, and the buck converter, and implementing the PSO algorithm to track the MPP. The results showed that the PSO-based MPPT system effectively tracked the MPP, with varying levels of accuracy and tracking time for different shading conditions. In conclusion, the study demonstrated the feasibility of using PSO-based MPPT for PV systems under partial shading conditions was successfully designed with an accuracy of 95% and above to track the maximum power of the system. The results highlight the effectiveness of the Particle Swarm Optimization (PSO) method in significantly improving the Maximum Power Point Tracking (MPPT) technique in partially shaded photovoltaic (PV) systems.
DOI:10.1109/ICPEA60617.2024.10498762