Assessing wind farm reliability using weather dependent failure rates

G Wilson, D McMillan

Research output: Contribution to journalConference Contributionpeer-review

19 Citations (Scopus)
194 Downloads (Pure)


Using reliability data comprising of two modern, large scale wind farm sites and wind data from two onsite met masts, a model is developed which calculates wind speed dependant failure rates which are used to populate a Markov Chain. Monte Carlo simulation is then exercised to simulate three wind farms which are subjected to controlled wind speed conditions from three separate potential UK sites. The model then calculates and compares wind farm reliability due to corrective maintenance and component failure rates influenced by the wind speed of each of the sites. Results show that the components affected most by changes in average daily wind speed are the control system and the yaw system. A comparison between this model and a more simple estimation of site yield is undertaken. The model takes into account the effects of the wind speed on the cost of operation and maintenance and also includes the impact of longer periods of downtime in the winter months and shorter periods in the summer. By taking these factors into account a more detailed site assessment can be undertaken. There is significant value to this model for operators and manufacturers.
Original languageEnglish
Article number012181
Number of pages11
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 10 Jun 2014
EventThe Science of Making Torque from Wind - Technical University of Denmark, Copenhagen, Denmark
Duration: 17 Jun 201420 Jun 2014


  • wind farm
  • reliability
  • weather dependent
  • failure rates
  • instrumentation and measurement
  • earth sciences


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