IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v235y2019icp1335-1350.html
   My bibliography  Save this article

Seismic response of offshore wind turbine with hybrid monopile foundation based on centrifuge modelling

Author

Listed:
  • Wang, Xuefei
  • Zeng, Xiangwu
  • Yang, Xu
  • Li, Jiale

Abstract

Some large capacity offshore wind turbines are constructed in seismically active areas. The occurrence of soil liquefaction during an earthquake can result in severe failures of the offshore wind turbine. The seismic response of the structure and the failure mechanism of the soil-structure interactions are necessary to investigate. In this study, the seismic response of an innovative hybrid monopile foundation is investigated through a series of centrifuge tests. The seismic performance of the combined system of the superstructure, foundation, and soil are demonstrated. Five hybrid foundation models are tested by considering the influence of the foundation thicknesses and diameters, and a monopile foundation is tested for comparison. Centrifuge test results reveal that the hybrid monopile foundation is effective in reducing the lateral displacement during the shaking. In the saturated condition, soil keeps its strength and stiffness beneath and adjacent to the foundation. The hybrid foundation system tends to settle more due to the larger shear stress caused by the soil structure interactions. Influences of the wheel specifications are illustrated. The foundations with larger thicknesses lead to smaller lateral displacements and lower tendencies of liquefaction, but the settlements are intensified. The larger diameter foundation provides a longer drainage path for the excess pore water pressure. With a similar weight, the structure settles less during the earthquake.

Suggested Citation

  • Wang, Xuefei & Zeng, Xiangwu & Yang, Xu & Li, Jiale, 2019. "Seismic response of offshore wind turbine with hybrid monopile foundation based on centrifuge modelling," Applied Energy, Elsevier, vol. 235(C), pages 1335-1350.
  • Handle: RePEc:eee:appene:v:235:y:2019:i:c:p:1335-1350
    DOI: 10.1016/j.apenergy.2018.11.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918317641
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2018.11.057?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Jincheng & Wang, Feng & Stelson, Kim A., 2018. "A mathematical approach to minimizing the cost of energy for large utility wind turbines," Applied Energy, Elsevier, vol. 228(C), pages 1413-1422.
    2. Feng, Ju & Shen, Wen Zhong, 2017. "Design optimization of offshore wind farms with multiple types of wind turbines," Applied Energy, Elsevier, vol. 205(C), pages 1283-1297.
    3. Li, Jiale & Yu, Xiong (Bill), 2018. "Onshore and offshore wind energy potential assessment near Lake Erie shoreline: A spatial and temporal analysis," Energy, Elsevier, vol. 147(C), pages 1092-1107.
    4. Gentils, Theo & Wang, Lin & Kolios, Athanasios, 2017. "Integrated structural optimisation of offshore wind turbine support structures based on finite element analysis and genetic algorithm," Applied Energy, Elsevier, vol. 199(C), pages 187-204.
    5. Li, Jiale & Wang, Xuefei & Yu, Xiong (Bill), 2018. "Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment," Applied Energy, Elsevier, vol. 213(C), pages 469-485.
    6. Kaldellis, J.K. & Apostolou, D. & Kapsali, M. & Kondili, E., 2016. "Environmental and social footprint of offshore wind energy. Comparison with onshore counterpart," Renewable Energy, Elsevier, vol. 92(C), pages 543-556.
    7. Sklenicka, Petr & Zouhar, Jan, 2018. "Predicting the visual impact of onshore wind farms via landscape indices: A method for objectivizing planning and decision processes," Applied Energy, Elsevier, vol. 209(C), pages 445-454.
    8. Wang, Xuefei & Yang, Xu & Zeng, Xiangwu, 2017. "Seismic centrifuge modelling of suction bucket foundation for offshore wind turbine," Renewable Energy, Elsevier, vol. 114(PB), pages 1013-1022.
    9. Hou, Peng & Enevoldsen, Peter & Hu, Weihao & Chen, Cong & Chen, Zhe, 2017. "Offshore wind farm repowering optimization," Applied Energy, Elsevier, vol. 208(C), pages 834-844.
    10. Wang, Xuefei & Zeng, Xiangwu & Yang, Xu & Li, Jiale, 2018. "Feasibility study of offshore wind turbines with hybrid monopile foundation based on centrifuge modeling," Applied Energy, Elsevier, vol. 209(C), pages 127-139.
    11. Jiale Li & Xiong (Bill) Yu, 2017. "Analyses of the Extensible Blade in Improving Wind Energy Production at Sites with Low-Class Wind Resource," Energies, MDPI, vol. 10(9), pages 1-24, August.
    12. Pérez-Collazo, C. & Greaves, D. & Iglesias, G., 2015. "A review of combined wave and offshore wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 141-153.
    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. Mo, Renjie & Cao, Renjing & Liu, Minghou & Li, Miao, 2021. "Effect of ground motion directionality on seismic dynamic responses of monopile offshore wind turbines," Renewable Energy, Elsevier, vol. 175(C), pages 179-199.
    2. Wang, H. & Ke, S.T. & Wang, T.G. & Kareem, A. & Hu, L. & Ge, Y.J., 2022. "Multi-stage typhoon-induced wind effects on offshore wind turbines using a data-driven wind speed field model," Renewable Energy, Elsevier, vol. 188(C), pages 765-777.
    3. Zi Lin & Xiaolei Liu, 2020. "Assessment of Wind Turbine Aero-Hydro-Servo-Elastic Modelling on the Effects of Mooring Line Tension via Deep Learning," Energies, MDPI, vol. 13(9), pages 1-21, May.
    4. He, Kunpeng & Ye, Jianhong, 2023. "Seismic dynamics of offshore wind turbine-seabed foundation: Insights from a numerical study," Renewable Energy, Elsevier, vol. 205(C), pages 200-221.
    5. Li, Jiale & Wang, Xuefei & Guo, Yuan & Yu, Xiong Bill, 2020. "The loading behavior of innovative monopile foundations for offshore wind turbine based on centrifuge experiments," Renewable Energy, Elsevier, vol. 152(C), pages 1109-1120.
    6. Guo, Yaohua & Zhang, Puyang & Ding, Hongyan & Le, Conghuan, 2021. "Design and verification of the loading system and boundary conditions for wind turbine foundation model experiment," Renewable Energy, Elsevier, vol. 172(C), pages 16-33.
    7. Shaohui Xiao & Hongjun Liu & Kun Lin, 2023. "Dynamic Performance of Monopile-Supported Wind Turbines (MWTs) under Different Operating and Ground Conditions," Energies, MDPI, vol. 17(1), pages 1-18, December.
    8. Lin, Zi & Liu, Xiaolei, 2020. "Wind power forecasting of an offshore wind turbine based on high-frequency SCADA data and deep learning neural network," Energy, Elsevier, vol. 201(C).
    9. He, Kunpeng & Ye, Jianhong, 2023. "Dynamics of offshore wind turbine-seabed foundation under hydrodynamic and aerodynamic loads: A coupled numerical way," Renewable Energy, Elsevier, vol. 202(C), pages 453-469.
    10. Li, Xinyao & Zeng, Xiangwu & Yu, Xiong & Wang, Xuefei, 2021. "Seismic response of a novel hybrid foundation for offshore wind turbine by geotechnical centrifuge modeling," Renewable Energy, Elsevier, vol. 172(C), pages 1404-1416.

    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. Li, Jiale & Wang, Xuefei & Yu, Xiong (Bill), 2018. "Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment," Applied Energy, Elsevier, vol. 213(C), pages 469-485.
    2. Wang, Xuefei & Zeng, Xiangwu & Li, Xinyao & Li, Jiale, 2019. "Investigation on offshore wind turbine with an innovative hybrid monopile foundation: An experimental based study," Renewable Energy, Elsevier, vol. 132(C), pages 129-141.
    3. Li, Jiale & Yu, Xiong (Bill), 2018. "Onshore and offshore wind energy potential assessment near Lake Erie shoreline: A spatial and temporal analysis," Energy, Elsevier, vol. 147(C), pages 1092-1107.
    4. Zi Lin & Xiaolei Liu, 2020. "Assessment of Wind Turbine Aero-Hydro-Servo-Elastic Modelling on the Effects of Mooring Line Tension via Deep Learning," Energies, MDPI, vol. 13(9), pages 1-21, May.
    5. Li, Jiale & Wang, Xuefei & Guo, Yuan & Yu, Xiong Bill, 2020. "The loading behavior of innovative monopile foundations for offshore wind turbine based on centrifuge experiments," Renewable Energy, Elsevier, vol. 152(C), pages 1109-1120.
    6. Valsaraj, P. & Thumba, Drisya Alex & Asokan, K. & Kumar, K. Satheesh, 2020. "Symbolic regression-based improved method for wind speed extrapolation from lower to higher altitudes for wind energy applications," Applied Energy, Elsevier, vol. 260(C).
    7. Su, Jie & Li, Yu & Chen, Yaoran & Han, Zhaolong & Zhou, Dai & Zhao, Yongsheng & Bao, Yan, 2021. "Aerodynamic performance assessment of φ-type vertical axis wind turbine under pitch motion," Energy, Elsevier, vol. 225(C).
    8. Nguyen, Thi Anh Tuyet & Chou, Shuo-Yan, 2018. "Impact of government subsidies on economic feasibility of offshore wind system: Implications for Taiwan energy policies," Applied Energy, Elsevier, vol. 217(C), pages 336-345.
    9. Lin, Zi & Cevasco, Debora & Collu, Maurizio, 2020. "A methodology to develop reduced-order models to support the operation and maintenance of offshore wind turbines," Applied Energy, Elsevier, vol. 259(C).
    10. Vasileiou, Margarita & Loukogeorgaki, Eva & Vagiona, Dimitra G., 2017. "GIS-based multi-criteria decision analysis for site selection of hybrid offshore wind and wave energy systems in Greece," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 745-757.
    11. Yang, Zihao & Dong, Sheng, 2024. "A novel framework for wind energy assessment at multi-time scale based on non-stationary wind speed models: A case study in China," Renewable Energy, Elsevier, vol. 226(C).
    12. Lin, Zi & Liu, Xiaolei, 2020. "Wind power forecasting of an offshore wind turbine based on high-frequency SCADA data and deep learning neural network," Energy, Elsevier, vol. 201(C).
    13. Li, Jiale & Song, Zihao & Wang, Xuefei & Wang, Yanru & Jia, Yaya, 2022. "A novel offshore wind farm typhoon wind speed prediction model based on PSO–Bi-LSTM improved by VMD," Energy, Elsevier, vol. 251(C).
    14. Sun, Haiying & Yang, Hongxing & Gao, Xiaoxia, 2019. "Investigation into spacing restriction and layout optimization of wind farm with multiple types of wind turbines," Energy, Elsevier, vol. 168(C), pages 637-650.
    15. Ju, Shen-Haw & Huang, Yu-Cheng & Huang, Yin-Yu, 2020. "Study of optimal large-scale offshore wind turbines," Renewable Energy, Elsevier, vol. 154(C), pages 161-174.
    16. Artigao, Estefania & Martín-Martínez, Sergio & Honrubia-Escribano, Andrés & Gómez-Lázaro, Emilio, 2018. "Wind turbine reliability: A comprehensive review towards effective condition monitoring development," Applied Energy, Elsevier, vol. 228(C), pages 1569-1583.
    17. He, J.Y. & Chan, P.W. & Li, Q.S. & Lee, C.W., 2022. "Characterizing coastal wind energy resources based on sodar and microwave radiometer observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    18. Sergen Tumse & Mehmet Bilgili & Alper Yildirim & Besir Sahin, 2024. "Comparative Analysis of Global Onshore and Offshore Wind Energy Characteristics and Potentials," Sustainability, MDPI, vol. 16(15), pages 1-28, August.
    19. Mo, Renjie & Cao, Renjing & Liu, Minghou & Li, Miao, 2021. "Effect of ground motion directionality on seismic dynamic responses of monopile offshore wind turbines," Renewable Energy, Elsevier, vol. 175(C), pages 179-199.
    20. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Levelized income loss as a metric of the adaptation of wind and energy storage to variable prices," Applied Energy, Elsevier, vol. 238(C), pages 1179-1191.

    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:eee:appene:v:235:y:2019:i:c:p:1335-1350. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.