| Issue |
E3S Web Conf.
Volume 680, 2025
The 4th International Conference on Energy and Green Computing (ICEGC’2025)
|
|
|---|---|---|
| Article Number | 00036 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/e3sconf/202568000036 | |
| Published online | 19 December 2025 | |
Comparative Performance Analysis of Fuzzy Logic and PSO MPPT Controllers for Photovoltaic Systems
Laboratory of Advanced Electronic System And Sustainable Energy (ESSE), University of Sfax, ENET’COM, Sfax, Tunisia
* Corresponding author: oa.walid@gmail.com
Photovoltaic energy plays a key role in reducing greenhouse gas emissions and tackling climate change. A crucial part of maximizing the energy output of photovoltaic systems is effective maximum power point tracking (MPPT). The control strategy used for MPPT not only affects the system’s performance but also determines how well it can handle disturbances, making it essential for long-term efficiency. This study looks at two advanced control methods for photovoltaic systems: fuzzy logic (FL) and particle swarm optimization (PSO). Fuzzy logic proves to be quick, accurate, and reliable, even when sunlight levels change rapidly. In comparison, PSO is precise over time but struggles with slower adjustments, leading to short-term energy losses during sudden changes in sunlight.
Key words: Photovoltaic energy (PV) / Maximum Power Point Traking (MPPT) / Particle Swarm Optimization (PSO) / Fuzzy Logic (FL)
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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