Since wind turbines have become one of the prevailing sources of electrical energy, their reliability and availability are of enormous importance. Predictive maintenance is a strategy for keeping both factors high and thus heavily under research. Maintenance based on the actual condition of a turbine would be the ideal way in the field of tension between benefit and effort. However, determining the condition of machine parts and elements traditionally requires the expensive application of measurement techniques and inspections. In many cases load-based maintenance – powered by few simple sensors and a model-based derivation of the condition from the history of loads – would be a good compromise. This paper presents a novel method for modeling wind turbines with minimal data requirements for the purpose of calculating inner loads and deriving the condition of machine elements. The applicability is demonstrated in the form of a remaining useful lifetime estimation of gearbox bearings.

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The share of wind energy in the public electricity supply in Europe is constantly growing, so that reliability and availability of wind turbines are becoming increasingly important. High availability is ensured by continuous condition monitoring, because it allows long downtimes to be avoided by reacting immediately to (imminent) failures. This paper presents a portable and real-time capable simulation model for determining internal loads on components in the mechanical drivetrain. The loads are apt for being utilized for a subsequent generation of a system reliability index in the scope of a decision support tool for demand- and degradation-oriented adjustments of the operational management. Thus, the work contributes to ensuring reliability. By determining the state of degradation of similarly loaded plants, under- or overloading of individual turbines can be proactively prevented. The analysis of the influence of individual model parameters is of particular importance here and provides evidence that even with a restricted parameter set the outputs of the load calculation model are accurate enough as inputs for a reliability calculation.

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