The silver lining: Utilising curtailment in offshore wind as an opportunity for operation and maintenance

Opportunistic maintenance strategies for offshore wind may provide significant reductions in operational costs and downtime for turbines. The utilisation of favourable periods to complete maintenance in past literature has often focused on internal factors, where the replacement of components allows preventive maintenance to be completed on other components that are approaching failure, in order to extend useful remaining life. In this paper, an offshore wind opportunistic maintenance model is created, that simulates the operations of a wind farm over it's lifetime. The research conducted produces a model that utilises both internal opportunity and also external opportunity by incorporating periods of curtailment as opportunities to complete maintenance. By completing preventive maintenance during periods of curtailment, in which the wind farm is being paid to switch off turbines, the lost production costs often associated with other maintenance periods are nullified. A cost benefit analysis is utilised to determine if completing maintenance during curtailment is financially beneficial to the wind farm. Other constraints within the model include vessel accessibility limits, resource limitations, preventive maintenance thresholds and weather windows for repair. Outputs for the model include a breakdown of the repair, transport, lost revenue and staff costs, as well as other key metrics such as availability and energy production. A case study for an offshore wind farm was conducted to validate the model considering both internal and external opportunities for maintenance against two other maintenance strategies; a corrective strategy and an opportunistic strategy that considers only internal opportunity for maintenance. Operational costs are reduced by 50% using the curtailment opportunistic strategy in comparison to the corrective strategy, whereas using only the internal opportunistic strategy has 20% reduction in costs compared to the corrective strategy. Sensitivity analyses are conducted for three of the model inputs namely, number of technicians, distance from shore and failure distribution values, to determine the impact and importance of the various inputs into the model.