IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i15p5464-d873960.html
   My bibliography  Save this article

Digital Twin for the Prediction of Extreme Loads on a Wave Energy Conversion System

Author

Listed:
  • Eirini Katsidoniotaki

    (Renewable Energy Unit, RISE—Research Institutes of Sweden, P.O. Box 857, SE-501 15 Boras, Sweden
    Centre of Natural Hazards and Disaster Science (CNDS), Villavägen 16, SE-752 36 Uppsala, Sweden)

  • Foivos Psarommatis

    (SIRIUS, Department of Informatics, University of Oslo, Gaustadalleen 23 B, 0373 Oslo, Norway)

  • Malin Göteman

    (Renewable Energy Unit, RISE—Research Institutes of Sweden, P.O. Box 857, SE-501 15 Boras, Sweden
    Centre of Natural Hazards and Disaster Science (CNDS), Villavägen 16, SE-752 36 Uppsala, Sweden)

Abstract

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.

Suggested Citation

  • Eirini Katsidoniotaki & Foivos Psarommatis & Malin Göteman, 2022. "Digital Twin for the Prediction of Extreme Loads on a Wave Energy Conversion System," Energies, MDPI, vol. 15(15), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5464-:d:873960
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/15/5464/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/15/5464/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christian Windt & Josh Davidson & John V. Ringwood, 2020. "Investigation of Turbulence Modeling for Point-Absorber-Type Wave Energy Converters," Energies, MDPI, vol. 14(1), pages 1-18, December.
    2. Josh Davidson & John V. Ringwood, 2017. "Mathematical Modelling of Mooring Systems for Wave Energy Converters—A Review," Energies, MDPI, vol. 10(5), pages 1-46, May.
    3. Simon Thomas & Mikael Eriksson & Malin Göteman & Martyn Hann & Jan Isberg & Jens Engström, 2018. "Experimental and Numerical Collaborative Latching Control of Wave Energy Converter Arrays," Energies, MDPI, vol. 11(11), pages 1-16, November.
    4. Windt, Christian & Davidson, Josh & Ransley, Edward J. & Greaves, Deborah & Jakobsen, Morten & Kramer, Morten & Ringwood, John V., 2020. "Validation of a CFD-based numerical wave tank model for the power production assessment of the wavestar ocean wave energy converter," Renewable Energy, Elsevier, vol. 146(C), pages 2499-2516.
    5. Dawid Augustyn & Martin D. Ulriksen & John D. Sørensen, 2021. "Reliability Updating of Offshore Wind Substructures by Use of Digital Twin Information," Energies, MDPI, vol. 14(18), pages 1-23, September.
    6. Foivos Psarommatis & Gökan May & Paul-Arthur Dreyfus & Dimitris Kiritsis, 2020. "Zero defect manufacturing: state-of-the-art review, shortcomings and future directions in research," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 1-17, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. do Amaral, J.V.S. & dos Santos, C.H. & Montevechi, J.A.B. & de Queiroz, A.R., 2023. "Energy Digital Twin applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Jincheng & Zhao, Xiaowei & Greaves, Deborah & Jin, Siya, 2023. "Modeling of a hinged-raft wave energy converter via deep operator learning and wave tank experiments," Applied Energy, Elsevier, vol. 341(C).
    2. Oliveira, D. & Lopes de Almeida, J.P.P.G. & Santiago, A. & Rigueiro, C., 2022. "Development of a CFD-based numerical wave tank of a novel multipurpose wave energy converter," Renewable Energy, Elsevier, vol. 199(C), pages 226-245.
    3. Pasta, Edoardo & Faedo, Nicolás & Mattiazzo, Giuliana & Ringwood, John V., 2023. "Towards data-driven and data-based control of wave energy systems: Classification, overview, and critical assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    4. Metzker Soares, Paula & Thevenin, Simon & Adulyasak, Yossiri & Dolgui, Alexandre, 2024. "Adaptive robust optimization for lot-sizing under yield uncertainty," European Journal of Operational Research, Elsevier, vol. 313(2), pages 513-526.
    5. Rosmaini Ahmad & Rabiatul Fakhira Mohd Amin & Shaliza Azreen Mustafa, 2022. "Value stream mapping with lean thinking model for effective non-value added identification, evaluation and solution processes," Operations Management Research, Springer, vol. 15(3), pages 1490-1509, December.
    6. Gomes, Rui P.F. & Gato, Luís M.C. & Henriques, João C.C. & Portillo, Juan C.C. & Howey, Ben D. & Collins, Keri M. & Hann, Martyn R. & Greaves, Deborah M., 2020. "Compact floating wave energy converters arrays: Mooring loads and survivability through scale physical modelling," Applied Energy, Elsevier, vol. 280(C).
    7. Stavropoulou, Charitini & Goude, Anders & Katsidoniotaki, Eirini & Göteman, Malin, 2023. "Fast time-domain model for the preliminary design of a wave power farm," Renewable Energy, Elsevier, vol. 219(P2).
    8. Gubesch, Eric & Abdussamie, Nagi & Penesis, Irene & Chin, Christopher, 2022. "Effects of mooring configurations on the hydrodynamic performance of a floating offshore oscillating water column wave energy converter," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    9. Hong Li & Bo Zhang & Li Qiu & Shiyu Chen & Jianping Yuan & Jianjun Luo, 2019. "Advection-Based Coordinated Control for Wave-Energy Converter Array," Energies, MDPI, vol. 12(18), pages 1-21, September.
    10. Dell’Edera, Oronzo & Niosi, Francesco & Casalone, Pietro & Bonfanti, Mauro & Paduano, Bruno & Mattiazzo, Giuliana, 2024. "Understanding wave energy converters dynamics: High-fidelity modeling and validation of a moored floating body," Applied Energy, Elsevier, vol. 376(PA).
    11. Housner, Stein & Hall, Matthew & Tran, Thanh Toan & de Miguel Para, Borja & Maeso, Aimar, 2024. "Shared mooring system designs and cost estimates for wave energy arrays," Renewable Energy, Elsevier, vol. 231(C).
    12. Sun, Pengyuan & Liu, Senming & He, Hongzhou & Zhao, Yingru & Zheng, Songgen & Chen, Hu & Yang, Shaohui, 2021. "Simulated and experimental investigation of a floating-array-buoys wave energy converter with single-point mooring," Renewable Energy, Elsevier, vol. 176(C), pages 637-650.
    13. Gokan May & Foivos Psarommatis, 2023. "Maximizing Energy Efficiency in Additive Manufacturing: A Review and Framework for Future Research," Energies, MDPI, vol. 16(10), pages 1-28, May.
    14. Paduano, Bruno & Parrinello, Luca & Niosi, Francesco & Dell’Edera, Oronzo & Sirigu, Sergej Antonello & Faedo, Nicolás & Mattiazzo, Giuliana, 2024. "Towards standardised design of wave energy converters: A high-fidelity modelling approach," Renewable Energy, Elsevier, vol. 224(C).
    15. Penalba, Markel & Davidson, Josh & Windt, Christian & Ringwood, John V., 2018. "A high-fidelity wave-to-wire simulation platform for wave energy converters: Coupled numerical wave tank and power take-off models," Applied Energy, Elsevier, vol. 226(C), pages 655-669.
    16. Farajvand, Mahdiyeh & Grazioso, Valerio & García-Violini, Demián & Ringwood, John V., 2023. "Uncertainty estimation in wave energy systems with applications in robust energy maximising control," Renewable Energy, Elsevier, vol. 203(C), pages 194-204.
    17. Luan, Zhengxiao & Chen, Bangqi & Jin, Ruijia & He, Guanghua & Ghassemi, Hassan & Jing, Penglin, 2024. "Validation of a numerical wave tank based on overset mesh for the wavestar-like wave energy converter in the South China Sea," Energy, Elsevier, vol. 290(C).
    18. Foivos Psarommatis & Gokan May, 2025. "A Cost–Benefit Model for Sustainable Product Reuse and Repurposing in Circular Remanufacturing," Sustainability, MDPI, vol. 17(1), pages 1-16, January.
    19. Matthew Leary & Curtis Rusch & Zhe Zhang & Bryson Robertson, 2021. "Comparison and Validation of Hydrodynamic Theories for Wave Energy Converter Modelling," Energies, MDPI, vol. 14(13), pages 1-18, July.
    20. Yaoyao Ping & Yongkui Liu & Lin Zhang & Lihui Wang & Xun Xu, 2024. "Enterprise and service−level scheduling of robot production services in cloud manufacturing with deep reinforcement learning," Journal of Intelligent Manufacturing, Springer, vol. 35(8), pages 3889-3916, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5464-:d:873960. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.