IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v238y2023ics0951832023003897.html
   My bibliography  Save this article

Impact of condition monitoring on the maintenance and economic viability of offshore wind turbines

Author

Listed:
  • Yan, Rundong
  • Dunnett, Sarah
  • Jackson, Lisa

Abstract

This study explores how condition monitoring (CM) can help operate offshore wind turbines (OWTs) effectively and economically. In this paper, the Petri Net (PN) simulation models are developed to quantitatively assess the OWT availability and operation and maintenance (O&M) costs. By investigating the impact of two CM approaches (i.e. purpose-designed CM and Supervisory Control and Data Acquisition (SCADA)-based CM) and their combinations with various maintenance strategies, the paper addresses two fundamental questions about OWT CM that have plagued the offshore wind sector for many years. They are ‘is a wind farm SCADA system a viable alternative to purpose-designed condition monitoring system (CMS)’ and ‘what is the best way to integrate CMSs and maintenance strategies to maximise the financial benefit of OWTs’. The research suggests that although utilising both a wind farm SCADA system and a purpose-designed CMS can achieve the highest turbine availability, it is not the most cost-effective option in terms of maintenance expenses. Instead, combining purpose-designed CM with less frequent advanced service can achieve the desired availability at the lowest cost. Furthermore, the use of a purpose-designed CMS is essential for the economical operation of OWTs and cannot be replaced by the current wind farm SCADA system.

Suggested Citation

  • Yan, Rundong & Dunnett, Sarah & Jackson, Lisa, 2023. "Impact of condition monitoring on the maintenance and economic viability of offshore wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
  • Handle: RePEc:eee:reensy:v:238:y:2023:i:c:s0951832023003897
    DOI: 10.1016/j.ress.2023.109475
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023003897
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2023.109475?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhu, Dongping & Huang, Xiaogang & Ding, Zhixia & Zhang, Wei, 2024. "Estimation of wind turbine responses with attention-based neural network incorporating environmental uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Dui, Hongyan & Zhang, Yulu & Bai, Guanghan, 2024. "Analysis of variable system cost and maintenance strategy in life cycle considering different failure modes," Reliability Engineering and System Safety, Elsevier, vol. 243(C).

    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:reensy:v:238:y:2023:i:c:s0951832023003897. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.