https://www.mdu.se/

mdh.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Marine energy digitalization digital twin's approaches
Mälardalens universitet, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
Center for Artificial Intelligence Research and Optimization, Torrens University Australia, Brisbane, Australia .
Laboratory of Ecological Engineering and Technology, Department of Environmental Engineering, Democritus University of Thrace, Xanthi, 67100, Greece.
Department of Planning, Design, Technology of Architecture, Sapienza University of Rome, Via Flaminia 72, Rome, 00196, Italy .
2024 (engelsk)Inngår i: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 191, artikkel-id 114065Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Digital twins (DTs) promise innovation for the marine renewable energy sector using modern technological advances and the existing maritime knowledge frameworks. The DT is a digital equivalent of a real object that reflects and predicts its behaviours and states in a virtual space over its lifetime. DTs collect data from multiple sources in pilots and leverage newly introduced low-cost sensor systems. They synchronize, homogenize, and transmit the data to a central hub and integrate it with predictive and learning models to optimize plant performance and operations. This research presents critical aspects of DT implementation challenges in marine energy digitalization DT approaches that use and combine data systems. Firstly, the DT and the existing framework for marine knowledge provided by systems are presented, and the DT's main development steps are discussed. Secondly, the DT implementing main stages, measurement systems, data harmonization and preprocessing, modelling, comprehensive data analysis, and learning and optimization tools, are identified. Finally, the ILIAD (Integrated Digital Framework for Comprehensive Maritime Data and Information Services) project has been reviewed as a best EU funding practice to understand better how marine energy digitalization DT's approaches are being used, designed, developed, and launched. 

sted, utgiver, år, opplag, sider
Elsevier Ltd , 2024. Vol. 191, artikkel-id 114065
Emneord [en]
Applications and platforms, Artificial Intelligence, Digital twins, Energy digitalization, European Countries, Marine energy
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-65021DOI: 10.1016/j.rser.2023.114065ISI: 001125012400001Scopus ID: 2-s2.0-85178240801OAI: oai:DiVA.org:mdh-65021DiVA, id: diva2:1819273
Tilgjengelig fra: 2023-12-13 Laget: 2023-12-13 Sist oppdatert: 2024-01-03bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopus

Person

Majidi Nezhad, Meysam

Søk i DiVA

Av forfatter/redaktør
Majidi Nezhad, Meysam
Av organisasjonen
I samme tidsskrift
Renewable & sustainable energy reviews

Søk utenfor DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric

doi
urn-nbn
Totalt: 33 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf