Presentations

Abstract

This paper presents a digital twin framework for offshore wind turbines to track damage accumulation of turbine components by calculating load time series based on measured inflow conditions. The inflow conditions are measured using a nacelle-mounted scanning LiDAR and provided to an aero-servo-hydro-elastic simulation model of a deployed wind turbine. The simulation model provides load time series for analytical damage estimation methods. Fatigue damage is estimated for the blade roots, the pitch bearing and the main bearing and provides decision support for O&M strategies. The model can be used to identify the most detrimental operational and inflow conditions or track the accumulated damage over a turbine's lifetime. The functionality of the simulation framework is presented for a bottom fixed and a floating offshore wind turbine. The bottom fixed model represents a deployed turbine in the Belgian North Sea and the necessary modelling and validation process is explained. The simulation model is based on a scaled reference turbine and is calibrated based on field measurements. The floating model represents the deployed bottom fixed turbine on a scaled research floater. The work showcases the use of digital twin frameworks for the reduction of O&M costs of offshore wind turbines.