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dc.contributor.authorDerriche, Khaled-
dc.contributor.authorZekoume, Abdellah-
dc.date.accessioned2026-10-26T09:55:45Z-
dc.date.available2026-10-26T09:55:45Z-
dc.date.issued2026-07-07-
dc.identifier.urihttp://dspace.univ-bouira.dz:8080/jspui/handle/123456789/20429-
dc.description.abstractExtracting 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 saturationen_US
dc.language.isoenen_US
dc.publisheruniversitè Bouiraen_US
dc.subjectPhotovoltaic systems, maximum power point tracking MPPT, fuzzy logic control FLC, perturbation and observation algorithm P&O,en_US
dc.subjectgenetic algorithm GAen_US
dc.titleMPPT controllers for 100 KW photovoltaic stationen_US
dc.typeThesisen_US
Collection(s) :Mémoires Master

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