Predictive model for fatigue evaluation of floating wind turbines validated with experimental data

Abstract

Estimating internal forces and corresponding fatigue damage plays a central role in the definition of operation strategies of any wind turbine, particularly in offshore scenarios. Although strain gauges can be installed to monitor the internal forces at a particular section, it is not feasible to instrument a full wind farm, and new methods are needed that allow to eliminate, or significantly reduce, this type of installation. This paper presents a new physics motivated methodology that incorporates tower top accelerations, available in the monitoring systems of most modern wind turbines, to estimate the tower bending moments and fatigue life consumption, replacing more common data driven approaches based on environmental conditions and/or operation variables by analytical considerations. The expressions derived are validated by numerical simulations, and then applied to experimental data collected at a full scale floating wind turbine, with results systematically better when compared with a data driven approach, often applied in onshore wind turbines. By using a quite rare database, collected in one of the first utility-scale worldwide floating wind turbines, this method presents itself as one of the first data processing methodologies developed explicitly for floating wind turbines, while setting a theoretical background for future developments of monitoring strategies.