Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/9629
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dc.contributor.authorChekired, F.-
dc.contributor.authorMellit, Adel-
dc.contributor.authorKalogirou, Soteris A.-
dc.contributor.authorLarbes, Cherif-
dc.contributor.otherΚαλογήρου, Σωτήρης-
dc.date.accessioned2017-02-13T12:13:10Z-
dc.date.available2017-02-13T12:13:10Z-
dc.date.issued2014-03-01-
dc.identifier.citationSolar Energy, 2014, Volume 101, Pages 83-99en_US
dc.identifier.issn0038092X-
dc.identifier.urihttp://ktisis.cut.ac.cy/handle/10488/9629-
dc.description.abstractIn this paper, various intelligent methods (IMs) used in tracking the maximum power point and their possible implementation into a reconfigurable field programmable gate array (FPGA) platform are presented and compared. The investigated IMs are neural networks (NN), fuzzy logic (FL), genetic algorithm (GA) and hybrid systems (e.g. neuro-fuzzy or ANFIS and fuzzy logic optimized by genetic algorithm). Initially, a complete simulation of the photovoltaic system with intelligent MPP tracking controllers using MATLAB/Simulink environment is given. Secondly, the different steps to design and implement the controllers into the FPGA are presented, and the best controller is tested in real-time co-simulation using FPGA Virtex 5. Finally, a comparative study has been carried out to show the effectiveness of the developed IMs in terms of accuracy, quick response (rapidity), flexibility, power consumption and simplicity of implementation. Results confirm the good tracking efficiency and rapid response of the different IMs under variable air temperature and solar irradiance conditions; however, the FL-GA controller outperforms the other ones. Furthermore, the possibility of implementation of the designed controllers into FPGA is demonstrated.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherElsevier Limiteden_US
dc.rights© 2013 Elsevier Ltd.en_US
dc.subjectCo-simulationen_US
dc.subjectFPGAen_US
dc.subjectIntelligent MPPTsen_US
dc.subjectPhotovoltaic systemen_US
dc.subjectReal time implementationen_US
dc.titleIntelligent maximum power point trackers for photovoltaic applications using FPGA chip: A comparative studyen_US
dc.typeArticleen_US
dc.doihttp://dx.doi.org/10.1016/j.solener.2013.12.026en_US
dc.collaborationDevelopment Unit of Solar Equipmentsen_US
dc.collaborationJijel Universityen_US
dc.collaborationThe Abdus Salam International Centre for Theoretical Physicsen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationNational Polytechnic School of Algiersen_US
dc.subject.categoryEnvironmental Engineeringen_US
dc.journalsSubscription Journalen_US
dc.countryAlgeriaen_US
dc.countryItalyen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.languageiso639-1other-
crisitem.author.deptDepartment of Mechanical Engineering and Materials Science and Engineering-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-3654-1437-
crisitem.author.parentorgFaculty of Engineering and Technology-
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