Verification-Based Assessment of Modelling Assumptions in Discrete-Event Simulation of Operation and Maintenance for Floating Offshore Wind

Abstract. Floating offshore wind offers access to deep-water wind resources but remains challenged by high and uncertain operation and maintenance (O&M) costs. Discrete-event simulation (DES) models are widely used to evaluate O&M strategies, yet variations in modelling assumptions often lead to inconsistent estimates and limit confidence in their use for decision support. This study applies a structured verification framework to examine how key assumptions influence O&M simulation outcomes, using two DES-based models configured with a harmonized deep-water floating wind reference case. While maintenance cost estimates remain broadly consistent across models, substantial differences arise in wind farm availability and in downtime-related revenue losses, which constitute a major share of total O&M costs. These differences are driven primarily by how turbine operational states are represented during maintenance activities, including off-shift periods and tow-to-port operations. Quantifying the influence of these assumptions provides generalizable insight relevant to the wider O&M modelling community, where such choices are implemented inconsistently. Building on the verified modelling foundation, several alternative O&M strategies including service operation vessel–based logistics, floating-to-floating major component replacement, and condition-based maintenance are evaluated, yielding total O&M cost reductions of up to 5 % in the examined case. The findings strengthen model transparency and reproducibility while demonstrating how verified simulation tools can support the assessment of emerging operational concepts in floating offshore wind.