Presentations

Abstract

The project focused on developing a quantitative risk assessment model for offshore wind farm decommissioning, addressing the limited experience and high uncertainty surrounding this emerging phase of the project lifecycle. The methodology builds on the ISO 31000 risk management framework and utilizes Monte Carlo simulations to capture both systematic uncertainty and discrete risk events. A catalogue of 15 discrete events was parameterized using PERT distributions, enabling the generation of probabilistic delay profiles across hundreds of iterations. In parallel, a weather risk module integrates historical metocean data with vessel-specific operational limits, quantifying the impact of waiting-on-weather time on overall project schedules. This model was then applied to a reference 400 MW offshore wind farm in the German North Sea, demonstrating how decommissioning durations can increase by over 20% due to process risks, with weather further compounding delays. The results highlight the dominance of availability risks and foundation removal challenges, and they provide a transparent framework for sensitivity analysis and scenario evaluation. By quantifying uncertainty with greater precision than more holistic approaches, the model contributes a decision-support tool for developers and contractors, enabling improved scheduling, resource planning, and cost control in future offshore wind decommissioning campaigns.