IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i5p1108-d1598759.html
   My bibliography  Save this article

Comparative Analysis of Offshore Wind Resources and Optimal Wind Speed Distribution Models in China and Europe

Author

Listed:
  • Yanan Chen

    (Department of Mechanics, School of Mechanical Engineering, Tianjin University, Tianjin 300350, China)

  • Ming Zhao

    (Department of Mechanics, School of Mechanical Engineering, Tianjin University, Tianjin 300350, China
    Tianjin Key Laboratory of Modern Engineering Mechanics, Tianjin University, Tianjin 300350, China)

  • Zhengxian Liu

    (Department of Mechanics, School of Mechanical Engineering, Tianjin University, Tianjin 300350, China
    Tianjin Key Laboratory of Modern Engineering Mechanics, Tianjin University, Tianjin 300350, China)

  • Jianlong Ma

    (School of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010051, China
    Key Laboratory of Wind Energy and Solar Energy Technology, Ministry of Education, Hohhot 010051, China
    Engineering Research Center of Renewable Energy at Universities of Inner Mongolia Autonomous Region, Hohhot 010051, China)

  • Lei Yang

    (DongFang Electric Wind Power Co., Ltd., Deyang 618000, China)

Abstract

Offshore wind resources in China and Europe are systematically compared, focusing on wind speed characteristics and the selection of optimal wind speed probability distribution models. Using 20 years of data at 10 m and 100 m above sea level, seven unimodal wind speed probability distribution models were applied. The results point out that China’s offshore wind resources exhibit high spatial and temporal variability, influenced by monsoons and typhoons, while European seas are characterized by stable wind patterns. Among the models tested, the Weibull distribution is the most accurate one for wind speed fitting, while the Generalized Extreme Value and Gamma models perform better in regions with higher skewness and extreme wind events. This study highlights the importance of wind speed characteristics, such as skewness and kurtosis, in selecting the optimal model. These findings provide valuable guidance for the improvement of offshore wind energy assessments and the selection of appropriate models. Future research should explore advanced techniques, such as machine learning and hybrid models, to better capture complex wind patterns and enhance model accuracy.

Suggested Citation

  • Yanan Chen & Ming Zhao & Zhengxian Liu & Jianlong Ma & Lei Yang, 2025. "Comparative Analysis of Offshore Wind Resources and Optimal Wind Speed Distribution Models in China and Europe," Energies, MDPI, vol. 18(5), pages 1-51, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:5:p:1108-:d:1598759
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/5/1108/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/5/1108/
    Download Restriction: no
    ---><---

    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:18:y:2025:i:5:p:1108-:d:1598759. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.