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Offshore wind turbine maintenance access: a closed-form probabilistic method for calculating delays caused by sea-state

Authors

  • Julian Feuchtwang,

    Corresponding author
    1. Institute for Energy and Environment, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK
    • Correspondence: Julian Feuchtwang, Institute for Energy and Environment, Department of Electronic and Electrical Engineering, Royal College Building, University of Strathclyde, 204 George Street, Glasgow G1 1XW, UK.

      E-mail: julian.feuchtwang@eee.strath.ac.uk

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  • David Infield

    1. Institute for Energy and Environment, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK
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ABSTRACT

Offshore wind energy is fast developing and with it a growing understanding of the challenge to maintain high levels of turbine availability and to keep down maintenance costs. Loss of turbine availability is, of course, related to component failure rate but is also highly dependent on access to the turbine, and this in turn reflects the wind and sea conditions occurring at the site as well as the operational limits of the vessels and plant being used.

A computational approach has been developed on the basis of probability calculations, enabling very fast estimates to be made of offshore access probabilities and expected delays. These can be used directly to explore the impact of different parameters such as key component reliability, time to repair and access constraints at specific offshore sites. The methodology used is derived and explained in detail. Different numerical techniques are available to calculate the probability distributions and their parameters as required by the methodology. These are presented and contrasted. Example applications of the methodology are provided for two specific sites that provide a degree of validation and also allow comparison of the different numerical approaches to probability distribution identification. It is shown that the accessibility calculated using the developed method is believable in the context of operational access data for the sites in question. Copyright © 2012 John Wiley & Sons, Ltd.

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