• DocumentCode
    647889
  • Title

    Wave height forecasting to improve off-shore access and maintenance scheduling

  • Author

    Dinwoodie, Iain ; Catterson, V.M. ; McMillan, David

  • Author_Institution
    Inst. for Energy & Environ., Univ. of Strathclyde, Glasgow, UK
  • fYear
    2013
  • fDate
    21-25 July 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents research into modelling and predicting wave heights based on historical data. Wave height is one of the key criteria for allowing access to off-shore wind turbines for maintenance. Better tools for predicting wave height will allow more accurate identification of suitable “weather windows” in which access vessels can be dispatched to site. This in turn improves the ability to schedule maintenance, reducing costs related to vessel dispatch and recall due to unexpected wave patterns. The paper outlines the data available for wave height modelling. Through data mining, different modelling approaches are identified and compared. The advantages and disadvantages of each approach, and their accuracies for a given site implementation, are discussed.
  • Keywords
    data mining; geophysics computing; maintenance engineering; ocean waves; oceanographic techniques; offshore installations; wind turbines; access vessels; costs reducing; data mining; maintenance scheduling; off-shore access; off-shore wind turbines; wave height forecasting; wave height modelling; Artificial neural networks; Data models; Maintenance engineering; Mathematical model; Predictive models; Training; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting (PES), 2013 IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESMG.2013.6672438
  • Filename
    6672438