Adjusting onshore failure rate data for cost effectiveness analysis of wind turbine condition monitoring offshore

Yu, Xi and Infield, David and Barbouchi, Sami and Seraoui, Redouane; (2015) Adjusting onshore failure rate data for cost effectiveness analysis of wind turbine condition monitoring offshore. In: ACSEE 2015, The Asian Conference on Sustainability, Energy and the Environment. UNSPECIFIED.

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Abstract

Offshore wind energy is a fast growing technology within the marine energy sector. In contrast to onshore, offshore wind farms require larger installation and incur higher O&M costs due to the challenges of the marine environment. In this context condition monitoring systems have an important role to play in reducing maintenance costs. The high initial cost of condition monitoring systems motivates this analysis of the cost effectiveness of such technology O&M cost data are commercially sensitive and generally protected by the wind industry, especially for offshore operations. Component failure rates are essential for modelling wind turbine O&M costs but very little offshore failure rate data available in the public domain. With cooperation of the operator of the largest onshore wind farm in the UK and that of a large Swedish offshore wind farm, three years of operational data records have been made available for this research. With wind and wave parameters extracted from the database and set as inputs to a cost model is has been possible to compare the O&M cost of reactive maintenance with condition based maintenance. The cost model available uses empirical failure rate based on onshore data and so will not fully represent the offshore situation as failure rates are expected to be affected by offshore operational conditions. To overcome this limitation, a mathematical translation of failure rate from onshore to offshore is applied to the operational data. The way this translation is calculated is sensitive to the way the relevant probability distributions are represented and improved curve fitting approaches have been explored.

ORCID iDs

Yu, Xi ORCID logoORCID: https://orcid.org/0000-0001-9547-5962, Infield, David, Barbouchi, Sami and Seraoui, Redouane;
CORE (COnnecting REpositories)