A Decision-Support Framework for Opportunistic Tactical Scheduling of Offshore Wind Maintenance Campaigns

Abstract In offshore wind operations, favourable weather and access conditions create opportunities to perform maintenance more efficiently. This study presents a modelling framework to identify and characterize such weather-based opportunity windows for yearly tactical planning. The framework integrates method statements, resource constraints, and multi-year hindcast metocean data within the TNO UWiSE discrete-event simulation model, evaluating all possible campaign start weeks. A historical blade repair campaign conducted in 2022 at the Offshore Wind Farm Egmond aan Zee is used for validation. The model reproduces most weather days accurately, though total campaign duration is overestimated by approximately 14%, likely due to conservative repair duration assumptions. As a proof of concept, a hypothetical future campaign is simulated, identifying an optimal window between calendar weeks 13 and 28, where cost, transfers, downtime, and duration are minimized. The best week shows approximately 15% lower total cost compared to the least favourable week. Sensitivity analysis indicates that uncertainties in task duration affect both the timing and width of opportunity windows, particularly for weather-critical activities. The framework enables operators and maintenance service providers to quantitatively assess maintenance scheduling performance across a year, accounting for seasonal and interannual variability. It is applicable to a wide range of maintenance activities, with future work focusing on integration with planning workflows, asset-condition models, and weather forecasting, as well as multi-objective optimization for automated scheduling.