IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i11p3112-d181962.html
   My bibliography  Save this article

Comparative Study of Time-Domain Fatigue Assessments for an Offshore Wind Turbine Jacket Substructure by Using Conventional Grid-Based and Monte Carlo Sampling Methods

Author

Listed:
  • Chi-Yu Chian

    (Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 106, Taiwan)

  • Yi-Qing Zhao

    (Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 106, Taiwan)

  • Tsung-Yueh Lin

    (R/D Section, Research Department, CR Classification Society, Taipei 10487, Taiwan)

  • Bryan Nelson

    (R/D Section, Research Department, CR Classification Society, Taipei 10487, Taiwan)

  • Hsin-Haou Huang

    (Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 106, Taiwan)

Abstract

Currently, in the design standards for environmental sampling to assess long-term fatigue damage, the grid-based sampling method is used to scan a rectangular grid of meteorological inputs. However, the required simulation cost increases exponentially with the number of environmental parameters, and considerable time and effort are required to characterise the statistical uncertainty of offshore wind turbine (OWT) systems. In this study, a K-type jacket substructure of an OWT was modelled numerically. Time rather than frequency-domain analyses were conducted because of the high nonlinearity of the OWT system. The Monte Carlo (MC) sampling method is well known for its theoretical convergence, which is independent of dimensionality. Conventional grid-based and MC sampling methods were applied for sampling simulation conditions from the probability distributions of four environmental variables. Approximately 10,000 simulations were conducted to compare the computational efficiencies of the two sampling methods, and the statistical uncertainty of the distribution of fatigue damage was assessed. The uncertainty due to the stochastic processes of the wave and wind loads presented considerable influence on the hot-spot stress of welded tubular joints of the jacket-type substructure. This implies that more simulations for each representative short-term environmental condition are required to derive the characteristic fatigue damage. The characteristic fatigue damage results revealed that the MC sampling method yielded the same error level for Grids 1 and 2 (2443 iterations required for both) after 1437 and 516 iterations for K- and KK-joint cases, respectively. This result indicated that the MC method has the potential for a high convergence rate.

Suggested Citation

  • Chi-Yu Chian & Yi-Qing Zhao & Tsung-Yueh Lin & Bryan Nelson & Hsin-Haou Huang, 2018. "Comparative Study of Time-Domain Fatigue Assessments for an Offshore Wind Turbine Jacket Substructure by Using Conventional Grid-Based and Monte Carlo Sampling Methods," Energies, MDPI, vol. 11(11), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3112-:d:181962
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/11/3112/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/11/3112/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Kewen & Bian, Huiyuan & Liu, Changwei & Zhang, Danfeng & Yang, Yanan, 2015. "Comparison of geothermal with solar and wind power generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1464-1474.
    2. Tao Pang & Yipeng Yang & Dai Zhao, 2015. "Convergence Studies on Monte Carlo Methods for Pricing Mortgage-Backed Securities," IJFS, MDPI, vol. 3(2), pages 1-15, May.
    3. Dong, Wenbin & Moan, Torgeir & Gao, Zhen, 2012. "Fatigue reliability analysis of the jacket support structure for offshore wind turbine considering the effect of corrosion and inspection," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 11-27.
    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. Ju, Shen-Haw, 2022. "Increasing the fatigue life of offshore wind turbine jacket structures using yaw stiffness and damping," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    2. Wang, L. & Kolios, A. & Liu, X. & Venetsanos, D. & Rui, C., 2022. "Reliability of offshore wind turbine support structures: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    3. Song, Yupeng & Sun, Tao & Zhang, Zili, 2023. "Fatigue reliability analysis of floating offshore wind turbines considering the uncertainty due to finite sampling of load conditions," Renewable Energy, Elsevier, vol. 212(C), pages 570-588.
    4. Clemens Hübler & Wout Weijtjens & Cristian G. Gebhardt & Raimund Rolfes & Christof Devriendt, 2019. "Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design," Energies, MDPI, vol. 12(4), pages 1-20, February.
    5. Tsung-Yueh Lin & Yi-Qing Zhao & Hsin-Haou Huang, 2020. "Representative Environmental Condition for Fatigue Analysis of Offshore Jacket Substructure," Energies, MDPI, vol. 13(20), pages 1-20, October.

    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. Deirdre O’Donnell & Jimmy Murphy & Vikram Pakrashi, 2020. "Damage Monitoring of a Catenary Moored Spar Platform for Renewable Energy Devices," Energies, MDPI, vol. 13(14), pages 1-22, July.
    2. Yanara Tranamil-Maripe & José M. Cardemil & Rodrigo Escobar & Diego Morata & Cristóbal Sarmiento-Laurel, 2022. "Assessing the Hybridization of an Existing Geothermal Plant by Coupling a CSP System for Increasing Power Generation," Energies, MDPI, vol. 15(6), pages 1-28, March.
    3. Li, Xiao-Yang & Chen, Wen-Bin & Kang, Rui, 2021. "Performance margin-based reliability analysis for aircraft lock mechanism considering multi-source uncertainties and wear," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    4. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    5. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
    6. Dong, Y. & Teixeira, A.P. & Guedes Soares, C., 2018. "Time-variant fatigue reliability assessment of welded joints based on the PHI2 and response surface methods," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 120-130.
    7. Salvatore Digiesi & Giovanni Mummolo & Micaela Vitti, 2022. "Minimum Emissions Configuration of a Green Energy–Steel System: An Analytical Model," Energies, MDPI, vol. 15(9), pages 1-21, May.
    8. Vonsée, Bram & Crijns-Graus, Wina & Liu, Wen, 2019. "Energy technology dependence - A value chain analysis of geothermal power in the EU," Energy, Elsevier, vol. 178(C), pages 419-435.
    9. Gude, Veera Gnaneswar, 2016. "Geothermal source potential for water desalination – Current status and future perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1038-1065.
    10. Luo, Shihua & Hu, Weihao & Liu, Wen & Zhang, Zhenyuan & Bai, Chunguang & Huang, Qi & Chen, Zhe, 2022. "Study on the decarbonization in China's power sector under the background of carbon neutrality by 2060," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    11. Yeter, B. & Garbatov, Y. & Guedes Soares, C., 2020. "Risk-based maintenance planning of offshore wind turbine farms," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    12. Dong, Y. & Teixeira, A.P. & Guedes Soares, C., 2020. "Application of adaptive surrogate models in time-variant fatigue reliability assessment of welded joints with surface cracks," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    13. Lin, David T.W. & Hsieh, Jui Ching & Shih, Bo Yen, 2019. "The optimization of geothermal extraction based on supercritical CO2 porous heat transfer model," Renewable Energy, Elsevier, vol. 143(C), pages 1162-1171.
    14. Ossai, Chinedu I., 2017. "Optimal renewable energy generation – Approaches for managing ageing assets mechanisms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 269-280.
    15. Anderson, Austin & Rezaie, Behnaz, 2019. "Geothermal technology: Trends and potential role in a sustainable future," Applied Energy, Elsevier, vol. 248(C), pages 18-34.
    16. Soltani, M. & Moradi Kashkooli, Farshad & Souri, Mohammad & Rafiei, Behnam & Jabarifar, Mohammad & Gharali, Kobra & Nathwani, Jatin S., 2021. "Environmental, economic, and social impacts of geothermal energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    17. Wang, Yongzhen & Li, Chengjun & Zhao, Jun & Wu, Boyuan & Du, Yanping & Zhang, Jing & Zhu, Yilin, 2021. "The above-ground strategies to approach the goal of geothermal power generation in China: State of art and future researches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    18. Ma, Yuanyuan & Li, Shibin & Zhang, Ligang & Liu, Songze & Liu, Zhaoyi & Li, Hao & Shi, Erxiu, 2020. "Study on the effect of well layout schemes and fracture parameters on the heat extraction performance of enhanced geothermal system in fractured reservoir," Energy, Elsevier, vol. 202(C).
    19. Xia, Liangyu & Zhang, Yabo, 2019. "An overview of world geothermal power generation and a case study on China—The resource and market perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 411-423.
    20. Chen, Chao & Duffour, Philippe & Fromme, Paul & Hua, Xugang, 2021. "Numerically efficient fatigue life prediction of offshore wind turbines using aerodynamic decoupling," Renewable Energy, Elsevier, vol. 178(C), pages 1421-1434.

    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:11:y:2018:i:11:p:3112-:d:181962. 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.