Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/1468
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ünlütürk, Muhammed | - |
dc.contributor.author | Kulaksız, A.A. | - |
dc.contributor.author | Ünlütürk, A. | - |
dc.date.accessioned | 2021-12-13T10:41:24Z | - |
dc.date.available | 2021-12-13T10:41:24Z | - |
dc.date.issued | 2019 | - |
dc.identifier.isbn | 9781538680865 | - |
dc.identifier.uri | https://doi.org/10.1109/GPECOM.2019.8778578 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.13091/1468 | - |
dc.description | 1st IEEE Global Power, Energy and Communication Conference, GPECOM 2019 -- 12 June 2019 through 15 June 2019 -- -- 150174 | en_US |
dc.description.abstract | Numerous environmental factors significantly affect the energy yield of solar photovoltaic (PV) power plants. Among these, solar irradiance, photovoltaic module temperature, dust and shading are prominent. The level of soiling is directly related to the installation site of the PV plant. In this study, to investigate the impact of dust shading factor on energy efficiency, artificial light source in laboratory environment is used and power outputs are compared for three different densities of dust accumulation on the module surface. For each level of dust accumulation, images are obtained from PV modules. From the PV module images obtained by a camera for different levels of dust accumulation, new features are obtained based on Gray Level Co-occurrence Matrix. The obtained data with new features are classified on the basis of Artificial Neural Networks to determine dust level and its effect on PV module performance. © 2019 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | Proceedings - 2019 IEEE 1st Global Power, Energy and Communication Conference, GPECOM 2019 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | dust deposition | en_US |
dc.subject | Photovoltaic module | en_US |
dc.subject | Soiling | en_US |
dc.subject | solar energy | en_US |
dc.title | Image Processing-based Assessment of Dust Accumulation on Photovoltaic Modules | en_US |
dc.type | Conference Object | en_US |
dc.identifier.doi | 10.1109/GPECOM.2019.8778578 | - |
dc.identifier.scopus | 2-s2.0-85070647542 | en_US |
dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
dc.identifier.startpage | 308 | en_US |
dc.identifier.endpage | 311 | en_US |
dc.identifier.wos | WOS:000851517900057 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.authorscopusid | 57215308531 | - |
dc.authorscopusid | 6506541745 | - |
dc.authorscopusid | 55972949100 | - |
item.grantfulltext | open | - |
item.openairetype | Conference Object | - |
item.cerifentitytype | Publications | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
Files in This Item:
File | Size | Format | |
---|---|---|---|
Image_Processing-based_Assessment_of_Dust_Accumulation_on_Photovoltaic_Modules.pdf | 1.53 MB | Adobe PDF | View/Open |
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