Optimisation of offshore wind farm maintenance.
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SINHA, Y. 2016. Optimisation of offshore wind farm maintenance. Robert Gordon University, PhD thesis.
The installed capacity of European Offshore Wind Turbines (OWT) is likely to rise from the 2014 value of 7GW to 150GW in 2030. However maintenance of OWT is facing unprecedented challenges and cost 35% of lifetime costs. This will be equivalent to £14billion/year by 2030 if current OWT maintenance schemes are not changed. However the complexities around OWT operation require tools and systems to optimise OWT maintenance. The design of optimal OWT maintenance requires failure analysis of over 10,000 components in OWT for which there is little published work relating to performance and failure. In this work, inspection reports of over 400 wind turbine gearboxes (source: Stork Technical Services) and SCADA data (source: Shetland Aerogenerators Ltd) were studied to identify issues with performance and failures in wind turbines. A modified framework of Failure Mode Effects and Criticality Analysis (i.e. FMECA+) was designed to analyse failures according to the unique requirements of OWT maintenance planners. The FMECA+ framework enables analysis and prediction of failures for varied root causes, and determines their consequences over short and long periods of time. A software tool has been developed around FMECA+ framework that enables prediction of component level failures for varied root causes. The tool currently stores over 800 such instances. The need to develop a FMECA+ based Enterprise Resource Planning tool has been identified and preliminary results obtained from its development have been shown. Such a software package will routinely manage OWT data, predict failures in components, manage resources and plan an optimal maintenance. This will solve some big problems that OWT maintenance planners currently face. This will also support the use of SCADA and condition monitoring data in planning OWT maintenance, something which has been difficult to manage for a long time.