Szczegóły publikacji

Opis bibliograficzny

Optimization of fuzzy-based MPPT controller via reptile search algorithm for stand-alone PV systems / Hossein Molashahi, Sanaz Jalali Zand, Saleh Mobeyen, Paweł SKRUCH // Ain Shams Engineering Journal ; ISSN  2090-4479 . — 2026 — vol. 17 iss. 1 art. no. 103873, s. 1-17. — Bibliogr. s. 16, Abstr. — Publikacja dostępna online od: 2025-12-04

Autorzy (4)

Słowa kluczowe

PVparticle swarm optimizationfuzzy logic controllerPSOCOAcuckoo optimization algorithmreptile search algorithmFLCmaximum power point trackingMPPTphotovoltaicRSA

Dane bibliometryczne

ID BaDAP165036
Data dodania do BaDAP2026-01-22
Tekst źródłowyURL
DOI10.1016/j.asej.2025.103873
Rok publikacji2026
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Creative Commons
Czasopismo/seriaAin Shams Engineering Journal

Abstract

The performance of photovoltaic (PV) systems is highly dependent on the accurate tracking of the maximum power point (MPPT) of the system because the efficiency of the system is maximized in this way. MPP depends on the environmental conditions and changes with changes in temperature, radiation and partial shade. Therefore, various methods for MPPT have been proposed and improved, but not all the challenges of these systems such as power ripples, undesirable efficiency and low convergence speed have been completely resolved. In this research, a new fuzzy logic controller (FLC) for MPPT is introduced, and the reptile search algorithm (RSA) is used to optimize the performance of this controller. The performance of the proposed RSA-FLC MPPT method is compared with several modern algorithms, including the cuckoo optimization algorithm (COA) with fuzzy controller, which is one of the most efficient methods in parameter optimization, and the particle swarm optimization (PSO) algorithm with fuzzy controller (PSO-FLC), the standard fuzzy controller (FLC), as well as the traditional incremental conductance (InC) algorithm and a PV system without MPPT. The simulation results performed in the MATLAB/Simulink environment show that the proposed method increases the system efficiency in a highly optimal manner under all dynamic conditions, including changes in radiation, temperature, and even variable loads, as well as in partial shade conditions.

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