181
Views
1
CrossRef citations to date
0
Altmetric
Articles

Fast prediction of turbine energy acquisition capacity under combined action of wave and current based on digital twin method

, ORCID Icon, , &
Pages 446-460 | Received 05 Oct 2022, Accepted 04 Jan 2023, Published online: 07 Feb 2023

References

  • Badshah M, Badshah S, Jan S. 2020. Comparison of computational fluid dynamics and fluid structure interaction models for the performance prediction of tidal current turbines. J Ocean Eng Sci. 5(2):164–172.
  • Bahaj AS, Molland AF, Chaplin JR, Batten WMJ. 2007. Power and thrust measurements of marine current turbines under various hydrodynamic flow conditions in a cavitation tunnel and a towing tank. Renew Energy. 32(3):407–426.
  • Cao Y, Liu A, Yu X, Liu Z, Tang X, Wang S. 2021. Experimental tests and CFD simulations of a horizontal wave flow turbine under the joint waves and currents. Ocean Eng. 237:109480. doi:10.1016/j.oceaneng.2021.109480
  • Cao Y, Tang X, Gaidai O, Wang F. 2022. Digital twin real time monitoring method of turbine blade performance based on numerical simulation. Ocean Eng. 263:112347.
  • Guo B, Wang D, Zhou J, Shi W, Zhou X. 2020. Performance evaluation of a submerged tidal energy device with a single mooring line. Ocean Eng. 196:106791.
  • Guo H, Chen M, Mohamed K, Qu T, Wang S, Li J. 2021. A digital twin-based flexible cellular manufacturing for optimization of air conditioner line. J Manuf Syst. 58:65–78. doi:10.1016/j.jmsy.2020.07.012
  • Hosseinpour P, Hosseinpour M, Sharifi Y. 2022. Artificial neural networks for predicting ultimate strength of steel plates with a single circular opening under axial compression. Ships Offsh Struct. 17(11):2454–2469. doi:10.1080/17445302.2021.2000265
  • Lee HH, Kim HJ, Paik JK. 2022. Use of physical testing data for the accurate prediction of the ultimate compressive strength of steel stiffened panels. Ships Offsh Struct. doi:10.1080/17445302.2022.2087358
  • Liu M, Fang S, Dong H, Xu C. 2021. Review of digital twin about concepts, technologies, and industrial applications. J Manuf Syst. 58:346–361. doi:10.1016/j.jmsy.2020.06.017
  • Lloyd C, Allmark M, Ordonez-Sanchez S, Martinez R, Johnstone C, Germain G, Gaurier B, Mason-Jones A, O'Doherty T. 2021. Validation of the dynamic load characteristics on a tidal stream turbine when subjected to wave and current interaction. Ocean Eng. 222:108360. doi:10.1016/j.oceaneng.2020.108360
  • Ma Y, Li T, Zhang L, Sheng Q, Zhang X, Jiang J. 2016. Experimental study on hydrodynamic characteristics of vertical-axis floating tidal current energy power generation device. Chin Ocean Eng. 30(5):749–762.
  • Masilamani R, Nallayarasu S. 2022. Simplified methods for the strength of ring-stiffened tubular T/Y-joints. Ships Offsh Struct. doi:10.1080/17445302.2022.2087358
  • Melikoglu M. 2018. Current status and future of ocean energy sources: a global review. Ocean Eng. 148:563–573.
  • Mohanty A, Viswavandy M, KRay P, Mohanty S. 2016. Reactive power control and optimisation of hybrid off shore tidal turbine with system uncertainties. J Ocean Eng Sci. 1(4):256–267.
  • Park HA, Byeon G, Son W, Jo HC, Kim J, Kim S. 2020. Digital twin for operation of microgrid: optimal scheduling in virtual space of digital twin. Energies. 13(20):5504.
  • Qi Q, Tao F. 2018. Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison. IEEE Access. 6:3585–3593.
  • Qi Q, Tao F, Hu T, Anwer N, Liu A, Wei Y, Wang L, Nee AYC. 2021. Enabling technologies and tools for digital twin. J Manuf Syst. 58:3–21. doi:10.1016/j.jmsy.2019.10.001
  • Ramos V, Giannini G, Calheiros CT, Rosa SP, Taveira PF. 2021. Legal framework of marine renewable energy: a review for the Atlantic region of Europe. Renewable Sustainable Energy Rev. 137:110608.
  • Ramos V, Ringwood JV. 2016. Implementation and evaluation of the international electrotechnical commission specification for tidal stream energy resource assessment: a case study. Energy Convers Manage. 127:66–79.
  • Sheng Q, Jing F, Zhang L, Zhou N, Wang S, Zhang Z. 2016. Study of the hydrodynamic derivatives of vertical-axis tidal current turbines in surge motion. Renewable Energy. 96:366–376.
  • Sun K, Ma G, Wang H, Li Z. 2019. Hydrodynamic performance of a vertical axis tidal current turbine with angular speed fluctuation. Ships Offsh Struct. 14:S311–S319. doi:10.1080/17445302.2019.1589975.
  • Sun L, Liu T, Xie Y, Zhang D, Xia X. 2021. Real-time power prediction approach for turbine using deep learning techniques. Energy. 233:121130. doi:10.1016/j.energy.2021.121130
  • Suzuki T, Mahfuz H. 2018. Analysis of large-scale ocean current turbine blades using fluid-structure interaction and blade element momentum theory. Ships Offsh Struct. 13(5):451–458.
  • Tao F, Zhang M, Liu Y, Nee AYC. 2018. Digital twin driven prognostics and health management for complex equipment. Cirp Annals – Manufact Technol. 67(1):169–172.
  • Uihlein A, Magagna D. 2016. Wave and tidal current energy – a review of the current state of research beyond technology. Renewable Sustainable Energy Rev. 58:1070–1081.
  • Ullah H, Hussain M, Abbas N, Ahmad H, Amer M, Noman M. 2019. Numerical investigation of modal and fatigue performance of a horizontal axis tidal current turbine using fluid-structure interaction. J Ocean Eng Sci. 4(4):328–337.
  • Verbruggen A, Fischedick M, Moomaw W, Weir T, Nadaï A, Nilsson LJ, Nyboer J, Sathaye J. 2010. Renewable energy costs, potentials, barriers: conceptual issues. Energy Policy. 38(2):850–861.
  • Wang K, Sun K, Sheng Q, Zhang L, Wang S. 2016. The effects of yawing motion with different frequencies on the hydrodynamic performance of floating vertical-axis tidal current turbines. Appl Ocean Res. 59:224–235.
  • Yang P, Xiang J, Fang F, Pain CC. 2019. A fidelity fluid-structure interaction model for vertical axis tidal turbines in turbulence flows. Appl Energy. 236:465–477.
  • Zhang D, Wang J, Lin Y, Si Y, Huang C, Yang J, Huang B, Li W. 2017. Present situation and future prospect of renewable energy in China. Renewable Sustainable Energy Rev. 76:865–871.
  • Zhang L, Zhou L, Horn BKP. 2021. Building a right digital twin with model engineering. J Manuf Syst. 59:151–164. doi:10.1016/j.jmsy.2021.02.009
  • Zhou M, Yan J, Feng D. 2019. Digital twin framework and its application to power grid online analysis. CSEE J Power Energy Syst. 5(3):391–398.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.