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JCR Impact Factor: 0.700
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Current issue: Nov 2024
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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2017 - 9

 HIGH-IMPACT PAPER 

Genetically Optimization of an Asymmetrical Fuzzy Logic Based Photovoltaic Maximum Power Point Tracking Controller

AL-GIZI, A. See more information about AL-GIZI, A. on SCOPUS See more information about AL-GIZI, A. on IEEExplore See more information about AL-GIZI, A. on Web of Science, AL-CHLAIHAWI, S. See more information about  AL-CHLAIHAWI, S. on SCOPUS See more information about  AL-CHLAIHAWI, S. on SCOPUS See more information about AL-CHLAIHAWI, S. on Web of Science, LOUZAZNI, M. See more information about  LOUZAZNI, M. on SCOPUS See more information about  LOUZAZNI, M. on SCOPUS See more information about LOUZAZNI, M. on Web of Science, CRACIUNESCU, A. See more information about CRACIUNESCU, A. on SCOPUS See more information about CRACIUNESCU, A. on SCOPUS See more information about CRACIUNESCU, A. on Web of Science
 
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Download PDF pdficon (1,592 KB) | Citation | Downloads: 1,129 | Views: 2,913

Author keywords
fuzzy logic, genetic algorithms, maximum power point trackers, optimization, photovoltaic systems

References keywords
fuzzy(12), tracking(10), logic(10), power(9), point(9), maximum(8), system(7), photovoltaic(7), algorithms(6), systems(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-11-30
Volume 17, Issue 4, Year 2017, On page(s): 69 - 76
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.04009
Web of Science Accession Number: 000417674300009
SCOPUS ID: 85035755676

Abstract
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This paper introduces a new fuzzy logic controller (FLC) based photovoltaic (PV) maximum power point tracking (MPPT) optimized with the genetic algorithm (GA). Four FLCs with five and seven numbers of triangular (tri) and generalized bell (g-bell) membership functions (MFs) are analyzed. The performances of the analyzed algorithms have been compared with the appropriate performances of the classical perturb and observe (P&O) algorithm by using the following criteria: the rise time (tr), the tracking accuracy of the output power, and the energy yield. The results showed that the FL-based PV MPPT controller with seven triangular (7-tri) MFs provides the best steady-state performances.


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Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 10
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Cited-By CrossRef

[1] Management and Performance Control Analysis of Hybrid Photovoltaic Energy Storage System under Variable Solar Irradiation, Louzazni, Mohamed, Cotfas, Daniel Tudor, Cotfas, Petru Adrian, Energies, ISSN 1996-1073, Issue 12, Volume 13, 2020.
Digital Object Identifier: 10.3390/en13123043
[CrossRef]

[2] FPGA Implementation of a Robust MPPT of a Photovoltaic System Using a Fuzzy Logic Controller Based on Incremental and Conductance Algorithm, Allani, M. Y., Mezghani, D., Tadeo, F., Mami, A., Engineering, Technology & Applied Science Research, ISSN 1792-8036, Issue 4, Volume 9, 2019.
Digital Object Identifier: 10.48084/etasr.2771
[CrossRef]

[3] Power System Topology Proposal of a High-Altitude Pseudo-Satellite: Sizing Method, Power Budget Modeling and Efficient Power Control, SEDDJAR, A., KERROUCHE, K. D. E., KHORCHEF, N., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 22, 2022.
Digital Object Identifier: 10.4316/AECE.2022.01006
[CrossRef] [Full text]

[4] Analytical optimization of photovoltaic output with Lagrange Multiplier Method, Louzazni, Mohamed, Khouya, Ahmed, Al-Dahidi, Sameer, Mussetta, Marco, Amechnoue, Khalid, Optik, ISSN 0030-4026, Issue , 2019.
Digital Object Identifier: 10.1016/j.ijleo.2019.163379
[CrossRef]

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Faculty of Electrical Engineering and Computer Science
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