https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Marine energy digitalization digital twin's approaches
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
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 (English)In: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 191, article id 114065Article in journal (Refereed) 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. 

Place, publisher, year, edition, pages
Elsevier Ltd , 2024. Vol. 191, article id 114065
Keywords [en]
Applications and platforms, Artificial Intelligence, Digital twins, Energy digitalization, European Countries, Marine energy
National Category
Energy Engineering
Identifiers
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
Available from: 2023-12-13 Created: 2023-12-13 Last updated: 2024-01-03Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Majidi Nezhad, Meysam

Search in DiVA

By author/editor
Majidi Nezhad, Meysam
By organisation
Future Energy Center
In the same journal
Renewable & sustainable energy reviews
Energy Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 40 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf