Modelling the impact of the environment on offshore wind turbine failure rates

For offshore wind turbines to become an economical energy generation option it is vital that the impact of the offshore environment on reliability is understood. This paper aims to model the impact of the wind speed and the external humidity and temperature. This is achieved using reliability data comprising of two modern, large scale wind farm sites consisting of approximately 380 wind turbine years of data. Weather data comes from a nearby weather station and an onsite met mast. A model is developed, using the reliability data, which calculates weather dependant failure rates and downtimes which are used to populate a Markov Chain. Monte Carlo simulation is then exercised to simulate the lifetime of a large scale wind farm which is subjected to controlled weather conditions. The model then calculates wind farm availability and component seasonal failure rates. Results show that offshore, the wind speed will have the biggest impact on component reliability, increasing the wind turbine failure rate by approximately 61%. The components affected most by this are the control system and the drive train. The higher offshore wind speeds appear to cause a higher proportion of major failures than experienced onshore. Research from this paper will be of interest to operators and wind turbine manufacturers who are interested in maintenance costs and logistics.