PERFORMANCE AND ENVIRONMENTAL IMPACT ANALYSIS OF A GRID-CONNECTED PV POWER PLANT USING AI-BASED REAL-TIME MONITORING

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dc.contributor.authorKisecok, Busra
dc.contributor.authorKoca, Tarkan
dc.contributor.authorCitlak, Aydin
dc.date.accessioned2026-04-04T13:30:40Z
dc.date.available2026-04-04T13:30:40Z
dc.date.issued2025
dc.departmentİnönü Üniversitesi
dc.description.abstractIn this study, the performance evaluation of grid-connected photovoltaic systems with a capacity of 4101.12 kWp installed by Baykan Denim company in Malatya province is carried out. The performance ratio, temperature, energy, radiation values used in the evaluation of the analysis are obtained every five minutes with the Solarify artificial intelligence-based performance monitoring network. The system efficiency is 16.53% and the performance ratio is 0.81. In addition, it was determined that 3022.61 tons of CO2 emissions were reduced annually thanks to the installed SPP (Solar power plant). It is concluded that the installation of PV systems provides considerable environmental and economic benefits.
dc.identifier.doi10.7546/CRABS.2025.11.13
dc.identifier.endpage1702
dc.identifier.issn1310-1331
dc.identifier.issue11
dc.identifier.orcid0000-0002-6881-4153
dc.identifier.scopus2-s2.0-105023574034
dc.identifier.scopusqualityQ4
dc.identifier.startpage1695
dc.identifier.urihttps://doi.org/10.7546/CRABS.2025.11.13
dc.identifier.urihttps://hdl.handle.net/11616/108280
dc.identifier.volume78
dc.identifier.wosWOS:001630633800013
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPubl House Bulgarian Acad Sci
dc.relation.ispartofComptes Rendus De L Academie Bulgare Des Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250329
dc.subjectrenewable energy
dc.subjectsolar power plant
dc.subjectperformance analysis
dc.titlePERFORMANCE AND ENVIRONMENTAL IMPACT ANALYSIS OF A GRID-CONNECTED PV POWER PLANT USING AI-BASED REAL-TIME MONITORING
dc.typeArticle

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