Offshore wind energy is a newly rising technology in marine exploration for its rich potential output in the past decades. However, unlike onshore wind farm, the offshore wind farm requires larger installation and O&M cost due to its complicated marine condition, and thus condition monitoring system plays growingly important role in this industry. The high preliminary cost input of condition monitoring system stimulates the cost effectiveness analysis research for the whole system. The O&M cost data are still protected by the wind industry, especially the offshore ones. Failure rate is then significant for modelling the wind turbine conditions and costs. However, there is very little release of the failure rate in the public domain. With some internal cooperation of a large onshore wind farm in the UK, a three-year-period operational data record is used for this research. With wind and wave parameters extracted from the database and being inputs of the cost model, the cost model compares the O&M cost of reactive maintenance and condition based maintenance. The existing cost model uses empirical failure rate based on onshore data in the database. This incurs deviation of the estimation of the analysis output. Therefore, a mathematical translation of failure rate from onshore to offshore is applied to the operational data. The translation renovates the effect caused by the short time occasional fluctuation in the failure rate plot, and provides a smoother curve for a general use. This enhances the reliability of the data translated.
Xi Yu, University of Strathclyde, UK
David Infield, University of Strathclyde, UK
Sami Barbouchi, EDF Energy R&D UK Centre, UK
Redouane Seraoui, EDF R&D STEP, France
Stream: Energy: Renewable Energy and Environmental Solutions
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