Reliability-based leading edge erosion maintenance strategy selection framework

Abstract

Leading edge erosion has become one of the most prevailing failure modes of wind turbines. Its effects can evolve from an aerodynamic modification of the properties of the blade to a potential structural failure of the leading edge. The first produces a reduction of energy production and the second can produce a catastrophic failure of the blade. Considering the uncertainties and constraints involved in the design of optimal operation and maintenance (O&M) strategies for offshore assets and the influence of site-specific parameters on the dynamics of this particular failure mode, the task becomes complex. In this study, a framework to evaluate the influence of different maintenance strategies considering uncertainties in weather, material behaviour and repair success is presented. Monte Carlo Simulation (MCS) is used alongside a computational framework for Leading Edge Erosion (LEE) degradation to evaluate the lifetime cost distribution and probability of failure of the chosen maintenance strategies. The use of the framework is demonstrated in a case study considering a 5-MW offshore wind turbine located in the north of Germany. The influence of the modification of the maintenance interval or time between repairs and the comparison with maintenance activities executed only during months with milder weather is analysed in terms of cost and reliability. A Pareto front plot considering the probability of failure and the median of the cost is used to jointly compare strategies considering both aspects to provide a tool for risk-informed maintenance selection. Finally, the potential benefits of condition-based maintenance and autonomous decision-making systems are discussed. The case of study shows the benefits of repairs during summer months and the importance of the relation risk/O&M cost for different maintenance strategies.