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Tow-Out Pace and Wet Storage Optimization in Floating Wind Projects
Santiago Bueno, Naval Architect and Offshore Engineer, Seaplace
Abstract
Floating Offshore Wind (FOW) must overcome significant industrialization challenges to meet global deployment targets. Among the most critical bottlenecks are the limited port infrastructure and the mismatch between manufacturing pace and installation campaigns. When these processes are not aligned, wet storage becomes essential to buffer the flow of units between construction and offshore installation. Discrete-Event Simulation (DES) provides a powerful methodology to plan and optimize this balance. By integrating manufacturing pace, resource allocation, weather downtime, and installation windows, DES can identify optimal tow-out sequences, required wet storage capacity, and overall execution time. These simulation models can analyse the construction of floating wind units across different technologies and logistics chains. They enable the evaluation of alternative wet storage methods and the capacity needed, while quantifying their impact on the project. A central premise is that the length of the installation campaign directly drives the number of wet storage positions required. Units completed outside the installation window must be stored to avoid production bottlenecks. Short campaigns consequently require more storage positions, with associated capital expenditure and additional marine operations. Conversely, longer campaigns reduce storage needs but may increase fleet costs unless favourable charter conditions are secured. By integrating metocean data along towing routes and installation sites with operational weather limits, the model estimates achievable monthly installation rates. In a representative case study involving the construction of 50 floating units, from foundation fabrication to wind turbine generator assembly at port, the simulation achieved a 32% reduction in overall project duration. This optimisation also reduced the number of wet storage positions required from 17 to 11, demonstrating the value of DES in balancing infrastructure needs and execution timelines.
