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| Titre: | Guided Seagull Optimization for Improved PV MPPT in Partial Shading |
| Auteur(s): | Belmadani, Hamza
Merabet, Oussama
Obelaid, Adel
Kheldoun, Aissa
Mohit, Bajaj
Ansari, Md Fahim
Bradai, Rafik |
| Mots-clés: | Maximum Power Point Tracking
Metaheuristic algorithms
Partial Shading
Photovoltaic systems
Seagull Optimization Algorithm |
| Date de publication: | 2023 |
| Editeur: | Institute of Electrical and Electronics Engineers Inc |
| Collection/Numéro: | 2023 IEEE 3rd International Conference on Applied Electromagnetics, Signal Processing, & Communication (AESPC), Bhubaneswar, India, 2023;pp. 1-5 |
| Résumé: | Based on the Seagull Optimization approach, this paper proposes a completely new, rapid Maximum Power Point tracking method. After adding opposition learning and adjusting the convergence factor to the initial version, the intended algorithm - dubbed The Guided Seagull Optimizer (GSO) - was produced. Essentially, the goal of the new technique is to increase convergence speed while maintaining a reasonable global search capability. The GSO algorithm was tested on a stand-alone photovoltaic system subjected to complex multi-peak partial shadowing patterns. Overall, the findings reveal that the technique outperforms typical SOA and PSO algorithms when it comes to of convergence time, efficiency, and adaptability. |
| URI/URL: | https://ieeexplore.ieee.org/document/10390053
10.1109/AESPC59761.2023.10390053
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/13844 |
| ISBN: | 979-835035874-2 |
| Collection(s) : | Communications Internationales
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