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dc.contributor.authorChen, Hao
dc.contributor.authorBirkelund, Yngve
dc.contributor.authorRicaud, Benjamin
dc.contributor.authorZhang, Qixia
dc.date.accessioned2024-02-01T08:58:22Z
dc.date.available2024-02-01T08:58:22Z
dc.date.issued2023
dc.description.abstractAs renewable energy sources offshore wind energy develop quickly, countries like Norway with long coastlines are exploring their potential. However, the diverse wind resources across different regions of Norway present challenges for study for effective utilization of offshore wind energy. This study proposes a novel method that utilizes transfer learning techniques to analyse the resource differences between these areas for optimum energy generation. The suggested approach is tested using real-world wind data from Norway’s southern, middle, and northern regions. The results show that transfer learning successfully bridges resource discrimination, boosting wind resource prediction precision in the target domains. The work can contribute to optimizing offshore wind energy utilization in Norway by addressing the resource disparities and forecasting between the different regions.en_US
dc.identifier.citationChen, Birkelund, Ricaud, Zhang. A southern, middle, and northern Norwegian offshore wind energy resources analysis by a transfer learning method for Energy Internet. Journal of Physics: Conference Series (JPCS). 2023;2655(1)en_US
dc.identifier.cristinIDFRIDAID 2231666
dc.identifier.doi10.1088/1742-6596/2655/1/012011
dc.identifier.issn1742-6588
dc.identifier.issn1742-6596
dc.identifier.urihttps://hdl.handle.net/10037/32802
dc.language.isoengen_US
dc.publisherIOP Publishingen_US
dc.relation.journalJournal of Physics: Conference Series (JPCS)
dc.relation.projectIDEquinor: Akademiaavtale Equinor UiT Norges arktiske universiteten_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/3.0en_US
dc.rightsAttribution 3.0 International (CC BY 3.0)en_US
dc.subjectVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Datateknologi: 551en_US
dc.subjectVDP::Technology: 500::Information and communication technology: 550::Computer technology: 551en_US
dc.subjectVDP::Teknologi: 500::Elektrotekniske fag: 540en_US
dc.subjectVDP::Technology: 500::Electro-technical sciences: 540en_US
dc.subjectVDP::Matematikk og naturvitenskap: 400::Geofag: 450::Meteorologi: 453en_US
dc.subjectVDP::Mathematics and natural scienses: 400::Geosciences: 450::Meteorology: 453en_US
dc.subjectVDP::Matematikk og naturvitenskap: 400::Matematikk: 410::Statistikk: 412en_US
dc.subjectVDP::Mathematics and natural scienses: 400::Mathematics: 410::Statistics: 412en_US
dc.subjectMaskinlæring / Machine learningen_US
dc.subjectMeteorologi / Meteorologyen_US
dc.subjectOffshore Wind / Offshore vinden_US
dc.subjectVindenergi / Wind energyen_US
dc.titleA southern, middle, and northern Norwegian offshore wind energy resources analysis by a transfer learning method for Energy Interneten_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 3.0 International (CC BY 3.0)
Except where otherwise noted, this item's license is described as Attribution 3.0 International (CC BY 3.0)