Classification of Hotspots in Photovoltaic Modules with Deep Learning Methods

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dc.contributor.authorAÇIKGÖZ, Hakan
dc.contributor.authorKorkmaz, Deniz
dc.contributor.authorDANDIL, Çiğdem
dc.date.accessioned2025-10-24T18:04:17Z
dc.date.available2025-10-24T18:04:17Z
dc.date.issued2022
dc.departmentMalatya Turgut Özal Üniversitesi
dc.description.abstractSolar energy systems are increasing their capacity in the energy industry day by day by operating with higher efficiency in parallel with technological developments. The functional operation of photovoltaic (PV) module contributes greatly to the optimal performance of these systems. On the other hand, detection and classification of faults occurring in PV modules are of vital importance in the operation and maintenance of solar energy systems. In this study, the classification of hotspots, which is one of the most common faults in Photovoltaic (PV) modules, is carried out by deep learning methods. First, data augmentation is applied to the images in the training dataset to improve the classification performance. Then, pre-trained deep learning models namely AlexNet, GoogLeNet, ShuffleNet, SqueezeNet, ResNet-50, and MobileNet-v2 are compared on the same test dataset. According to the obtained experimental results, AlexNet has the best performance with an accuracy value of 98.65%, while ResNet-50 provides the worst result with 94.59%.
dc.identifier.doi10.55525/tjst.1158854
dc.identifier.endpage221
dc.identifier.issn1308-9099
dc.identifier.issue2
dc.identifier.startpage211
dc.identifier.trdizinid1273648
dc.identifier.urihttps://doi.org/10.55525/tjst.1158854
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1273648
dc.identifier.urihttps://hdl.handle.net/20.500.12899/2772
dc.identifier.volume17
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofTurkish Journal of Science & Technology
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzTR-Dizin_20251023
dc.subjectClassification
dc.subjectDeep Learning
dc.subjectHotspot
dc.subjectPhotovoltaic Module
dc.titleClassification of Hotspots in Photovoltaic Modules with Deep Learning Methods
dc.typeArticle

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