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Digital Twin for the Prediction of Extreme Loads on a Wave Energy Conversion System
RISE Research Institutes of Sweden. Centre of Natural Hazards and Disaster Science, Sweden.
University of Oslo, Norway.
RISE Research Institutes of Sweden. Centre of Natural Hazards and Disaster Science, Sweden.
2022 (English)In: Energies, E-ISSN 1996-1073, Vol. 15, no 15, article id 5464Article in journal (Refereed) Published
Abstract [en]

Wave energy is a renewable energy source with the potential to contribute to the global electricity demand, but a remaining challenge is the survivability of the wave energy converters in harsh offshore conditions. To understand the system dynamics and improve the reliability, experimental and numerical studies are usually conducted. However, these processes are costly and time-consuming. A statistical model able to provide equivalent results is a promising approach. In this study, the digital twin of the CFD solution is developed and implemented for the prediction of the force in the mooring system of a point-absorber wave energy converter during extreme wave conditions. The results show that the digital twin can predict the mooring force with 90.36% average accuracy. Moreover, the digital twin needs only a few seconds to provide the solution, while the CFD code requires up to several days. By creating a digital analog of a wave energy converter and showing that it is able to predict the load in critical components during extreme wave conditions, this work constitutes an innovative approach in the wave energy field. © 2022 by the authors.

Place, publisher, year, edition, pages
MDPI , 2022. Vol. 15, no 15, article id 5464
Keywords [en]
CFD, design, digital twin, extreme loads, survivability, wave energy, Mooring, Offshore oil well production, Offshore technology, Renewable energy resources, Wave energy conversion, Energy conversion systems, Extreme waves, Global electricity demands, Offshore conditions, Renewable energy source, Wave conditions, Wave energy converters, Forecasting
National Category
Marine Engineering
Identifiers
URN: urn:nbn:se:ri:diva-60179DOI: 10.3390/en15155464Scopus ID: 2-s2.0-85136519044OAI: oai:DiVA.org:ri-60179DiVA, id: diva2:1699857
Note

Funding details: Centrum för naturkatastrofslära, Uppsala Universitet, CNDS; Funding details: European Commission, EC, 101016175; Funding details: Vetenskapsrådet, VR, 2020-03634; Funding details: Energimyndigheten, 47264-1; Funding details: Alexander S. Onassis Public Benefit Foundation, FZP 021-1/2019-2020; Funding text 1: The research in this paper was supported by the Centre of Natural Hazards and Disaster Science (CNDS), the Swedish Research Council (VR, grant number 2020-03634), the Swedish Energy Agency (project number 47264-1), the Onassis Foundation (Scholarship ID: FZP 021-1/2019-2020). Also, this paper was partially supported by EU funded project Eur3ka, under grant agreement No. 101016175. This research work reflects only the authors’ views, and the Commission is not responsible for any use that may be made of the information it contains.

Available from: 2022-09-29 Created: 2022-09-29 Last updated: 2023-08-28Bibliographically approved

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