I NDUSTRIAL E NGINEERING AND M ANAGEMENT Master’s Thesis
Condition-based maintenance optimisation of wind power turbines In collaboration with:
Over the past few decades, governments worldwide have attempted to foster growth in renewable energy solutions. Electricity production from wind energy makes a significant contribution to this growth. Globally, the total operational capacity is growing every year, just as the share of wind energy compared to other forms of power generation. Operations and maintenance make up to a third of the total life-cycle costs of a wind turbine. Clever use of data from turbine sensors and advanced modelling techniques can be used to enhance a more proactive and predictive approach to maintenance. This study focuses on the maintenance of an expensive component of Lagerwey wind turbines. We will elaborate on the process of extracting raw data and converting this data into a condition state. From a scientific point of view, this procedure is especially interesting. Existing studies typically assume a certain deterioration process, and only a few studies in literature cope with the process of extracting and converting raw data. Subsequently, we continue to perform analyses on the condition data to model the deterioration process of this component. Lastly, we will simulate this process and determine the costs and downtime of different maintenance policies. Based on these experiments, we will optimise a conditionbased maintenance policy with a preventive maintenance and an opportunistic maintenance threshold. By applying this policy, Lagerwey can reach significant cost reductions and increase the turbine production availability.
AUTHOR B.J.H. (Bram) Klein Kranenbarg - s2405474 F IRST SUPERVISOR
S ECOND SUPERVISOR
dr. B. (Bram) de Jonge
dr. J. (Jasper) Veldman
April 3, 2018