IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v212y2023icp669-682.html
   My bibliography  Save this article

Assessing code-based design wind loads for offshore wind turbines in China against typhoons

Author

Listed:
  • Wang, Hao
  • Wang, Tongguang
  • Ke, Shitang
  • Hu, Liang
  • Xie, Jiaojie
  • Cai, Xin
  • Cao, Jiufa
  • Ren, Yuxin

Abstract

In the areas prone to severe typhoons, such as the south and southeast China waters, offshore wind turbine design will most likely fall into Class-S, but the current design standards have not treated much detail on the technical parameters under the typhoon-induced conditions to guide the structural design. This study set out to investigate the feasibility of extreme wind conditions in existing standards for offshore wind turbines in the south and southeast China waters. The extreme wind conditions in existing standards and actual typhoon cases in the south and southeast China waters were used to compare and analyze the typhoon-induced wind effect on offshore wind turbines. This study supports evidence from previous views that the extreme wind condition specified by existing design standards does not provide a sufficient safety margin for the south and southeast China waters use. Another interesting finding is that from the perspective of the typhoon-resistant design of large-scale offshore wind turbines in the future, it is more inclined to abandon the height of the hub and use the height of 10m as the reference wind speed height to obtain a more reasonable wind speed field as input conditions. The insights gained from this study may be of assistance to the typhoon-resistant design of customized offshore wind turbines in the south and southeast China waters and would help reduce the risks and economic losses of Class-S wind turbines in other typhoon-prone areas.

Suggested Citation

  • Wang, Hao & Wang, Tongguang & Ke, Shitang & Hu, Liang & Xie, Jiaojie & Cai, Xin & Cao, Jiufa & Ren, Yuxin, 2023. "Assessing code-based design wind loads for offshore wind turbines in China against typhoons," Renewable Energy, Elsevier, vol. 212(C), pages 669-682.
    • Handle: RePEc:eee:renene:v:212:y:2023:i:c:p:669-682
    DOI: 10.1016/j.renene.2023.05.052
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148123006754
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2023.05.052?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. 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.
    2. Han, T. & McCann, G. & Mücke, T.A. & Freudenreich, K., 2014. "How can a wind turbine survive in tropical cyclone?," Renewable Energy, Elsevier, vol. 70(C), pages 3-10.
    3. Zhiyu Jiang & Weifei Hu & Wenbin Dong & Zhen Gao & Zhengru Ren, 2017. "Structural Reliability Analysis of Wind Turbines: A Review," Energies, MDPI, vol. 10(12), pages 1-25, December.
    4. Snyder, Brian & Kaiser, Mark J., 2009. "A comparison of offshore wind power development in europe and the U.S.: Patterns and drivers of development," Applied Energy, Elsevier, vol. 86(10), pages 1845-1856, October.
    5. Wen, Yi & Kamranzad, Bahareh & Lin, Pengzhi, 2021. "Assessment of long-term offshore wind energy potential in the south and southeast coasts of China based on a 55-year dataset," Energy, Elsevier, vol. 224(C).
    6. Wang, H. & Ke, S.T. & Wang, T.G. & Zhu, S.Y., 2020. "Typhoon-induced vibration response and the working mechanism of large wind turbine considering multi-stage effects," Renewable Energy, Elsevier, vol. 153(C), pages 740-758.
    7. Hong, Lixuan & Möller, Bernd, 2012. "An economic assessment of tropical cyclone risk on offshore wind farms," Renewable Energy, Elsevier, vol. 44(C), pages 180-192.
    8. Browning, Morgan S. & Lenox, Carol S., 2020. "Contribution of offshore wind to the power grid: U.S. air quality implications," Applied Energy, Elsevier, vol. 276(C).
    9. Chen, Yisu & Wu, Di & Yu, Yuguo & Gao, Wei, 2021. "Do cyclone impacts really matter for the long-term performance of an offshore wind turbine?," Renewable Energy, Elsevier, vol. 178(C), pages 184-201.
    10. Mark D. Powell & Peter J. Vickery & Timothy A. Reinhold, 2003. "Reduced drag coefficient for high wind speeds in tropical cyclones," Nature, Nature, vol. 422(6929), pages 279-283, March.
    11. Tang, Di & Xu, Min & Mao, Jianfeng & Zhu, Hai, 2020. "Unsteady performances of a parked large-scale wind turbine in the typhoon activity zones," Renewable Energy, Elsevier, vol. 149(C), pages 617-630.
    12. Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Jiang, Di, 2020. "Design and implementation of partial offline fuzzy model-predictive pitch controller for large-scale wind-turbines," Renewable Energy, Elsevier, vol. 145(C), pages 981-996.
    13. Qiu, Shuo & Lei, Tian & Wu, Jiangtao & Bi, Shengshan, 2021. "Energy demand and supply planning of China through 2060," Energy, Elsevier, vol. 234(C).
    14. Shu, Z.R. & Li, Q.S. & He, Y.C. & Chan, P.W., 2016. "Observations of offshore wind characteristics by Doppler-LiDAR for wind energy applications," Applied Energy, Elsevier, vol. 169(C), pages 150-163.
    15. Stephen Rose & Paulina Jaramillo & Mitchell J. Small & Jay Apt, 2013. "Quantifying the Hurricane Catastrophe Risk to Offshore Wind Power," Risk Analysis, John Wiley & Sons, vol. 33(12), pages 2126-2141, December.
    16. Kong, Xiaobing & Ma, Lele & Wang, Ce & Guo, Shifan & Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Lee, Kwang Y., 2022. "Large-scale wind farm control using distributed economic model predictive scheme," Renewable Energy, Elsevier, vol. 181(C), pages 581-591.
    17. Sara C. Pryor & Rebecca J. Barthelmie, 2021. "A global assessment of extreme wind speeds for wind energy applications," Nature Energy, Nature, vol. 6(3), pages 268-276, March.
    18. Hallowell, Spencer T. & Myers, Andrew T. & Arwade, Sanjay R. & Pang, Weichiang & Rawal, Prashant & Hines, Eric M. & Hajjar, Jerome F. & Qiao, Chi & Valamanesh, Vahid & Wei, Kai & Carswell, Wystan & Fo, 2018. "Hurricane risk assessment of offshore wind turbines," Renewable Energy, Elsevier, vol. 125(C), pages 234-249.
    Full references (including those not matched with items on IDEAS)

    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. Chen, Yisu & Wu, Di & Yu, Yuguo & Gao, Wei, 2021. "Do cyclone impacts really matter for the long-term performance of an offshore wind turbine?," Renewable Energy, Elsevier, vol. 178(C), pages 184-201.
    2. Rebecca J. Barthelmie & Kaitlyn E. Dantuono & Emma J. Renner & Frederick L. Letson & Sara C. Pryor, 2021. "Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas," Energies, MDPI, vol. 14(4), pages 1-25, February.
    3. Kresning, Boma & Hashemi, M. Reza & Shirvani, Amin & Hashemi, Javad, 2024. "Uncertainty of extreme wind and wave loads for marine renewable energy farms in hurricane-prone regions," Renewable Energy, Elsevier, vol. 220(C).
    4. Cai, Chang & Yang, Yingjian & Jia, Yan & Wu, Guangxing & Zhang, Hairui & Yuan, Feiqi & Qian, Quan & Li, Qing'an, 2023. "Aerodynamic load evaluation of leading edge and trailing edge windward states of large-scale wind turbine blade under parked condition," Applied Energy, Elsevier, vol. 350(C).
    5. Arabgolarcheh, Alireza & Rouhollahi, Amirhossein & Benini, Ernesto, 2023. "Analysis of middle-to-far wake behind floating offshore wind turbines in the presence of multiple platform motions," Renewable Energy, Elsevier, vol. 208(C), pages 546-560.
    6. Yang, Yang & Fu, Jianbin & Shi, Zhaobin & Ma, Lu & Yu, Jie & Fang, Fang & Chen, Shunhua & Lin, Zaibin & Li, Chun, 2023. "Performance and fatigue analysis of an integrated floating wind-current energy system considering the aero-hydro-servo-elastic coupling effects," Renewable Energy, Elsevier, vol. 216(C).
    7. Karijadi, Irene & Chou, Shuo-Yan & Dewabharata, Anindhita, 2023. "Wind power forecasting based on hybrid CEEMDAN-EWT deep learning method," Renewable Energy, Elsevier, vol. 218(C).
    8. Abdoos, Ali Akbar & Abdoos, Hatef & Kazemitabar, Javad & Mobashsher, Mohammad Mehdi & Khaloo, Hooman, 2023. "An intelligent hybrid method based on Monte Carlo simulation for short-term probabilistic wind power prediction," Energy, Elsevier, vol. 278(PA).
    9. 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.
    10. Wen, Yi & Kamranzad, Bahareh & Lin, Pengzhi, 2022. "Joint exploitation potential of offshore wind and wave energy along the south and southeast coasts of China," Energy, Elsevier, vol. 249(C).
    11. Zuo, Haoran & Bi, Kaiming & Hao, Hong & Xin, Yu & Li, Jun & Li, Chao, 2020. "Fragility analyses of offshore wind turbines subjected to aerodynamic and sea wave loadings," Renewable Energy, Elsevier, vol. 160(C), pages 1269-1282.
    12. Sun, Kang & Xu, Zifei & Li, Shujun & Jin, Jiangtao & Wang, Peilin & Yue, Minnan & Li, Chun, 2023. "Dynamic response analysis of floating wind turbine platform in local fatigue of mooring," Renewable Energy, Elsevier, vol. 204(C), pages 733-749.
    13. Wu, Yunna & Zhang, Ting, 2021. "Risk assessment of offshore wave-wind-solar-compressed air energy storage power plant through fuzzy comprehensive evaluation model," Energy, Elsevier, vol. 223(C).
    14. Qin, Mengfei & Shi, Wei & Chai, Wei & Fu, Xing & Li, Lin & Li, Xin, 2023. "Extreme structural response prediction and fatigue damage evaluation for large-scale monopile offshore wind turbines subject to typhoon conditions," Renewable Energy, Elsevier, vol. 208(C), pages 450-464.
    15. Wang, Jianing & Zhu, Hongqiu & Zhang, Yingjie & Cheng, Fei & Zhou, Can, 2023. "A novel prediction model for wind power based on improved long short-term memory neural network," Energy, Elsevier, vol. 265(C).
    16. Yang, Xinrong & Jiang, Xin & Liang, Shijing & Qin, Yingzuo & Ye, Fan & Ye, Bin & Xu, Jiayu & He, Xinyue & Wu, Jie & Dong, Tianyun & Cai, Xitian & Xu, Rongrong & Zeng, Zhenzhong, 2024. "Spatiotemporal variation of power law exponent on the use of wind energy," Applied Energy, Elsevier, vol. 356(C).
    17. Gaige Hunter Kerr & Michelle Meyer & Daniel L. Goldberg & Joshua Miller & Susan C. Anenberg, 2024. "Air pollution impacts from warehousing in the United States uncovered with satellite data," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    18. Chancham, Chana & Waewsak, Jompob & Gagnon, Yves, 2017. "Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand," Energy, Elsevier, vol. 139(C), pages 706-731.
    19. Zhang, Jincheng & Zhao, Xiaowei, 2021. "Three-dimensional spatiotemporal wind field reconstruction based on physics-informed deep learning," Applied Energy, Elsevier, vol. 300(C).
    20. Jin, Xin & Zhang, Zhaolong & Shi, Xiaoqiang & Ju, Wenbin, 2014. "A review on wind power industry and corresponding insurance market in China: Current status and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 1069-1082.

    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:renene:v:212:y:2023:i:c:p:669-682. 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.journals.elsevier.com/renewable-energy .

    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.