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A Study on the Patent Trend of AI-based Renewable Power Generation Forecasting Technologies

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dc.contributor.authorJang, Moon-Jong-
dc.contributor.authorKim, Taehoon-
dc.contributor.authorOh, Eunsung-
dc.date.accessioned2024-07-08T05:00:38Z-
dc.date.available2024-07-08T05:00:38Z-
dc.date.issued2023-04-
dc.identifier.issn1975-8359-
dc.identifier.issn2287-4364-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/91845-
dc.description.abstractIn order to utilize renewable power generation that contains uncertainty due to natural intermittence, it is essential to develop renewable power generation forecasting technologies. This paper focuses on identifying the technology development of artificial intelligence (AI)-based renewable power generation by the analysis of patents. In this study, AI-based renewable power generation forecasting technology is comprehensively defined, and related patent applications are systematically identified to analyze country, period, and technological trends. The results indicate that 1) renewable power generation forecasting has reached a technological maturity in Japan, the United States, and Europe, 2) to overcome this, AI technology has been being grafted onto renewable power generation forecasting, 3) the use of meteorological data was described as a major right, and AI technology was described as an applicable additional item due to the characteristics of AI technology patents. Copyright © The Korean Institute of Electrical Engineers.-
dc.format.extent7-
dc.language한국어-
dc.language.isoKOR-
dc.publisherKorean Institute of Electrical Engineers-
dc.titleA Study on the Patent Trend of AI-based Renewable Power Generation Forecasting Technologies-
dc.typeArticle-
dc.identifier.doi10.5370/KIEE.2023.72.4.496-
dc.identifier.bibliographicCitationTransactions of the Korean Institute of Electrical Engineers, v.72, no.4, pp 496 - 502-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85153889117-
dc.citation.endPage502-
dc.citation.startPage496-
dc.citation.titleTransactions of the Korean Institute of Electrical Engineers-
dc.citation.volume72-
dc.citation.number4-
dc.type.docTypeArticle-
dc.publisher.location대한민국-
dc.subject.keywordAuthorArtificial intelligence-
dc.subject.keywordAuthorforecasting-
dc.subject.keywordAuthorinternational patent classification-
dc.subject.keywordAuthorpatent trend-
dc.subject.keywordAuthorrenewable-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
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