Estimation of power output and thermodynamic analysis of standard and finned photovoltaic panels

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dc.authorscopusid6506635786
dc.authorscopusid23984042700
dc.authorscopusid56575516000
dc.contributor.authorAkyol, Uğur
dc.contributor.authorAkal, Dinç
dc.contributor.authorDurak, Ahmet
dc.date.accessioned2022-05-11T14:02:57Z
dc.date.available2022-05-11T14:02:57Z
dc.date.issued2021
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Makine Mühendisliği Bölümü
dc.departmentMeslek Yüksekokulları, Hayrabolu Meslek Yüksekokulu, Motorlu Araçlar ve Ulaştırma Teknolojileri Bölümü
dc.description.abstractThis study deals with the estimation of power output and also thermodynamic analysis of two different photovoltaic panels. One of the panels is a standard photovoltaic module without fins (SPV), and the other one is a photovoltaic module with fins (FPV). First, a multi-layer feed-forward neural network structure is designed to estimate the daily power produced by photovoltaic modules. Furthermore, energy and exergy analyses were carried out to compare the performance of SPV and FPV panels. According to the thermodynamic analysis results using the experimental data obtained for two days (July 3, 2020 and August 4, 2020), it was calculated that the energy efficiency increased by a maximum of 8.77% and the exergy efficiency increased by a maximum of 25.9% in the FPV panel compared to the SPV panel. Moreover, considering the data obtained for each day during three months (July, August, and September), the total energy production increase in the FPV panel is approximately 6.7% compared to the SPV panel. © 2021 Taylor & Francis Group, LLC.
dc.identifier.doi10.1080/15567036.2021.1928337
dc.identifier.issn1556-7036
dc.identifier.scopus2-s2.0-85107371393
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1080/15567036.2021.1928337
dc.identifier.urihttps://hdl.handle.net/20.500.11776/4549
dc.identifier.wosWOS:000656327700001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAkyol, Uğur
dc.institutionauthorDurak, Ahmet
dc.language.isoen
dc.publisherBellwether Publishing, Ltd.
dc.relation.ispartofEnergy Sources, Part A: Recovery, Utilization and Environmental Effects
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectartificial neural network
dc.subjectenergy analysis
dc.subjectexergy analysis
dc.subjectfin
dc.subjectpassive cooling
dc.subjectPhotovoltaic
dc.subjectprediction
dc.subjectEnergy efficiency
dc.subjectExergy
dc.subjectFeedforward neural networks
dc.subjectFins (heat exchange)
dc.subjectPhotovoltaic cells
dc.subjectThermoanalysis
dc.subjectEnergy and exergy analysis
dc.subjectExergy efficiencies
dc.subjectMultilayer feedforward neural networks
dc.subjectPhotovoltaic modules
dc.subjectPhotovoltaic panels
dc.subjectPower out put
dc.subjectThermo dynamic analysis
dc.subjectTotal energy
dc.subjectMultilayer neural networks
dc.titleEstimation of power output and thermodynamic analysis of standard and finned photovoltaic panels
dc.typeArticle

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