Data-driven Optimisation of Offshore Wind Operations & Maintenance

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Offshore Wind (OW) continues to grow globally at a rapid pace, with 57 GW currently installed [1] and growth estimates of 630GW by 2050 [2]. To facilitate this rapid growth costs must continue to be brought down. With turbine manufacturers struggling for further cost reductions [3], reducing operations and maintenance (O&M) costs for wind farms offer opportunities. Currently O&M costs are estimated at 30% of the lifetime costs of a wind farm [4]. With offshore wind farms (OWFs) getting larger, moving further offshore and floating offshore wind becoming more prevalent it is increasingly important to develop and deploy optimised O&M strategies to continue to drive down costs. Furthermore, there is an increased focus on decarbonisation of the supply chain and operational activities of wind farms. To meet the Paris Agreement goals, optimisation of maintenance for a reduction in emissions is essential.Wind farms produce a wealth of data that can be used to develop predictive strategies. The main systems on the wind turbine (WT) are: The Supervisory Control and Data Acquisition (SCADA) system and the condition monitoring system (CMS). These can be combined with maintenance reports; met-ocean data; operational reports; vessel data and stock levels to create a fully optimised maintenance system.