Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/4397
DC FieldValueLanguage
dc.contributor.authorMekki, Hamza-
dc.contributor.authorMellit, Adel-
dc.contributor.authorKalogirou, Soteris A.-
dc.contributor.authorMessai, Adnane-
dc.contributor.authorFurlan, G.-
dc.date.accessioned2013-03-04T10:55:34Zen
dc.date.accessioned2013-05-17T10:30:33Z-
dc.date.accessioned2015-12-09T12:08:10Z-
dc.date.available2013-03-04T10:55:34Zen
dc.date.available2013-05-17T10:30:33Z-
dc.date.available2015-12-09T12:08:10Z-
dc.date.issued2010-
dc.identifier.citationProgress in Photovoltaics: Research and Applications, 2010, vol. 18, no. 2, pp. 115-127en_US
dc.identifier.issn10627995-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/4397-
dc.description.abstractAn implementation of an intelligent photovoltaic module on reconfigurable Field Programmable Gate Array (FPGA) is described in this paper. An experimental database of meteorological data (irradiation and temperature) and output electrical generation data of a Photovoltaic (PV) module (current and voltage) under variable climate condition is used in this study. Initially, an Artificial Neural Network (ANN) is developed under Matlab/Similuk, environment for modeling the PV module. The inputs of the ANN–PV module are the global solar irradiation and temperature while the outputs are the current and voltage generated from the PV-module. Subsequently, the optimal configuration of the ANN model (ANN–PV module) is written and simulated under the Very High Description Language (VHDL) and ModelSim. The synthesized architecture by ModelSim is then implemented on an FPGA device. The designed MLP-photovoltaic module permits the evaluation of performance of the PV module using only environmental parameters and involves less computational effort. The device can also be used for predicting the output electrical energy from the PV module and for a real time simulation in specific climatic conditionsen_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofProgress in Photovoltaics: Research and Applicationsen_US
dc.rights© Wileyen_US
dc.subjectNeural networksen_US
dc.subjectPhotovoltaic moduleen_US
dc.subjectFPGAen_US
dc.subjectPredictionen_US
dc.subjectSimulationen_US
dc.subjectVDHLen_US
dc.titleFPGA-based implementation of a real time photovoltaic module simulatoren_US
dc.typeArticleen_US
dc.collaborationBlida Universityen_US
dc.collaborationJijel Universityen_US
dc.collaborationUniversity of Technologyen_US
dc.collaborationCRNB Ain Ousseraen_US
dc.collaborationInternational Center for Theoretical Physicsen_US
dc.subject.categoryEnvironmental Engineeringen_US
dc.journalsSubscriptionen_US
dc.reviewpeer reviewed-
dc.countryAlgeriaen_US
dc.countryCyprusen_US
dc.countryItalyen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1002/pip.950en_US
dc.dept.handle123456789/141en
dc.relation.issue2en_US
dc.relation.volume18en_US
cut.common.academicyear2010-2011en_US
dc.identifier.spage115en_US
dc.identifier.epage127en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextNo Fulltext-
crisitem.journal.journalissn1099-159X-
crisitem.journal.publisherWiley-
crisitem.author.deptDepartment of Mechanical Engineering and Materials Science and Engineering-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-4497-0602-
crisitem.author.parentorgFaculty of Engineering and Technology-
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