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IMA Journal of Management Mathematics Advance Access published online on July 11, 2008
IMA Journal of Management Mathematics, doi:10.1093/imaman/dpn012
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© The authors 2008. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

On modelling of grouped reliability data for wind turbines

F. P. A. Coolen{dagger}

Department of Mathematical Sciences, Durham University, Durham DH1 3LE, UK

F. Spinato and D. Venkat

School of Engineering, Durham University, Durham DH1 3LE, UK

{dagger} Email: frank.coolen{at}durham.ac.uk

Received on 23 January 2008. Accepted on 3 June 2008.

Energy generation by wind turbines (WTs) has increased enormously during the last decade, and plans for future expansion, in particular large-scale offshore developments, emphasize the need to study reliability of WTs. Substantial data sets on occurrences of failures in WTs are available, but unfortunately they only provide grouped data with little information on individual turbines or maintenance activities. In this paper, we consider the use of basic non-homogeneous Poisson process models, in particular the power law process, to try to deduce from these data the change, through the years, in reliability of WTs and some critical subsystems. Unfortunately, it turns out that there are major problems that avoid clear conclusions to be drawn, as such the main contribution of this paper is a discussion on choice of the use of either calendar time or total time on test as the key time variable in reliability models, and some advice on future data collection, which will be equally important for a range of industrial activities.

Keywords: calendar time; grouped failure data; non-homogeneous Poisson process; total time on test


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