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Intelligent solar module: Application of AI to improve failure rate due to Climate change

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dc.contributor.authorPark, Junhyun-
dc.contributor.authorYoon, Guwon-
dc.contributor.authorCho, Keonhee-
dc.contributor.authorLee, Tacklim-
dc.contributor.authorChoi, Myeong-In-
dc.contributor.authorPark, Sehyun-
dc.date.accessioned2023-07-14T02:46:20Z-
dc.date.available2023-07-14T02:46:20Z-
dc.date.issued2022-10-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/67109-
dc.description.abstractThis paper proposes a method to apply artific ial intelligence to prevent the failure of photovol taic modules and the degradation of energy effic iency. Intelligent solar modules can maintain m aximum energy efficiency while responding app ropriately to climate changes that can cause sol ar modules to fail such as heat waves, heavy sno w, and strong winds. Consumers can efficiently manage with monitoring applications and stably supply solar energy through these systems.-
dc.language영어-
dc.language.isoENG-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titleIntelligent solar module: Application of AI to improve failure rate due to Climate change-
dc.typeArticle-
dc.identifier.doi10.1109/ICCE-Asia57006.2022.9954638-
dc.identifier.bibliographicCitation2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85143833902-
dc.citation.title2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022-
dc.type.docTypeConference Paper-
dc.subject.keywordAuthorArtificial Intelligence-
dc.subject.keywordAuthorPhotovoltaic Generation Forecasting-
dc.subject.keywordAuthorSolar Energy-
dc.description.journalRegisteredClassscopus-
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