Currently, around 1500 offshore wind turbines are operating in the UK, for a total of 5.4GW, with further 3GW under construction, and 13GW consented. Until now, the focus of the research on offshore wind turbines has been mainly on how to minimise the CAPEX, but Operation and maintenance (O&M) can represent up to 39% of the lifetime costs of an offshore wind farm, due mainly to the high cost of the assets and the harsh environment, limiting the access to these assets in a safe mode.
The present work is a part of a larger project, called HOME Offshore (www.homeoffshore.org), and it has as aim an advanced interpretation of the fault mechanisms through a holistic multiphysics modelling of the wind farm.
The first step (presented here) toward achieving this aim consists of two main tasks: first of all, to identify and rank the most relevant failure modes within a wind farm, identifying the component, its mode of failure, and the relative environmental conditions. Then, to assess (for each failure mode) how the full-order, nonlinear model of dynamics used to represent the dynamics of the wind turbine can be reduced in order, such that is less computationally expensive (and therefore more suitable to be scaled up to represent multiple wind turbines), but still able to capture and represent the relevant dynamics linked with the inception of the chosen failure mode.
A methodology to rank the failure modes is presented, followed by an approach to reduce the order of the Aero-Hydro-Servo-Elastic (AHSE) model of dynamics adopted. The results of the proposed reduced-order models are discussed, comparing it against the full-order coupled model, and taking as case study a fixed offshore wind turbine (monopile) in gearbox failure condition.