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| Élément Dublin Core | Valeur | Langue |
|---|---|---|
| dc.contributor.author | Derriche, Khaled | - |
| dc.contributor.author | Zekoume, Abdellah | - |
| dc.date.accessioned | 2026-10-26T09:55:45Z | - |
| dc.date.available | 2026-10-26T09:55:45Z | - |
| dc.date.issued | 2026-07-07 | - |
| dc.identifier.uri | http://dspace.univ-bouira.dz:8080/jspui/handle/123456789/20429 | - |
| dc.description.abstract | Extracting peak power from solar panels requires reliable tracking systems. Therefore, a photovoltaic system was built using MATLAB/Simulink software and tested under various control strategies. The main objective was to compare the performance of a fuzzy logic controller (FLC) with that of a standard perturbation and observation (P&O) algorithm. The test conditions were simplified by applying a gradual increase in solar irradiance and conducting tests at several fixed temperature points. The FLC easily outperformed the P&O method at the peak power point with an efficiency of 99.3%. At the end of the work, a genetic algorithm (GA) was used to automatically fine-tune the FLC. The optimization gains were constrained primarily by the computational limitations of the simulation hardware; executing the GA to achieve higher optimization margins would require significantly more processing time and higher-performance workstations to prevent system saturation | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | universitè Bouira | en_US |
| dc.subject | Photovoltaic systems, maximum power point tracking MPPT, fuzzy logic control FLC, perturbation and observation algorithm P&O, | en_US |
| dc.subject | genetic algorithm GA | en_US |
| dc.title | MPPT controllers for 100 KW photovoltaic station | en_US |
| dc.type | Thesis | en_US |
| Collection(s) : | Mémoires Master | |
Fichier(s) constituant ce document :
| Fichier | Description | Taille | Format | |
|---|---|---|---|---|
| Master Thesis ZEKOUM ^L0 DERICHE - - M2 ESE 2026 FF (1).pdf | 3,43 MB | Unknown | Voir/Ouvrir |
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