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Title: Maintenance optimisation for wind turbines.
Authors: Andrawus, Jesse A.
Supervisors: Watson, John
Kishk, Mohammed
Keywords: Wind turbines
Maintenance optimisation
Condition-based maintenance
Issue Date: Apr-2008
Publisher: The Robert Gordon University
Citation: ANDRAWUS, J., WATSON, J. and KISHK, M. 2006. Asset management processes in the wind energy industry. In: Proceedings of the 2nd Joint International Conference on Sustainable Energy and Environment (SEE 2006), 21-23 November 2006. Bangkok, Thailand. pp. 269-274
ANDRAWUS, J., WATSON, J., KISHK, M. and ADAM, A. 2006. Determining an appropriate condition-based maintenance strategy for wind turbines. In: Proceedings of the 2nd Joint International Conference on Sustainable Energy and Environment (SEE 2006). 21-23 November 2006. Bangkok, Thailand. pp. 275-280
ANDRAWUS, J., WATSON, J., KISHK, M. and ADAM, A., 2006. The selection of a suitable maintenance strategy for wind turbines. International Journal of Wind Engineering, 30 (6), pp. 471-486
ANDRAWUS, J., WATSON, J. and KISHK, M., 2007. Wind turbine maintenance optimisation: principles of quantitative maintenance optimisation. International Journal of Wind Engineering, 31 (2), pp. 101-110
ANDRAWUS, J., WATSON, J. and KISHK, M. 2007. Maintenance optimisation of wind turbines : lessons for the built environment. In: Proceedings of the 23rd Annual ARCOM Conference. 3-5 September 2007. Belfast. pp. 893-902
ANDRAWUS, J., WATSON, J. and KISHK, M., 2007. Modelling system failures to optimise wind turbine maintenance. International Journal of Wind Engineering, 31 (6), pp. 503-522
Abstract: Wind is becoming an increasingly important source of energy for countries that ratify to reduce the emission of greenhouse gases and mitigate the effects of global warming. Investments in wind farms are affected by inter-related assets and stakeholders’ requirements. These requirements demand a well-founded Asset Management (AM) frame-work which is currently lacking in the wind industry. Drawing from processes, tools and techniques of AM in other industries, a structured model for AM in the wind industry is developed. The model divulges that maintenance is indispensable to the core business objectives of the wind industry. However, the common maintenance strategies applied to wind turbines are inadequate to support the current commercial drivers of the wind industry. Consequently, a hybrid approach to the selection of a suitable maintenance strategy is developed. The approach is used in a case study to demonstrate its practical application. Suitable Condition-Based Maintenance activities for wind turbines are determined. Maintenance optimisation is a means to determine the most cost-effective maintenance strategy. Field failure and maintenance data of wind turbines are collected and analysed using two quantitative maintenance optimisation techniques; Modelling System Failures (MSF) and Delay-Time Maintenance Model (DTMM). The MSF permits the evaluation of life-data samples and enables the design and simulation of a system’s model to determine optimum maintenance activities. Maximum Likelihood Estimation is used to estimate the shape (β) and scale (η) parameters of the Weibull distribution for critical components and subsystems of the wind turbines. Reliability Block Diagrams are designed using the estimated β and η to model the failures of the wind turbines and of a selected wind farm. The models are simulated to assess and optimise the reliability, availability and maintainability of the wind turbine and the farm. The DTMM examines equipment failure patterns by taking into account failure consequences, inspection time and cost in order to determine optimum inspection intervals. Defects rate (α) and mean delay-time (1/γ) of components and subsystems within the wind turbine are estimated. Optimal inspection intervals for critical subsystems of the wind turbine are then determined.
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