Data driven multi-objective optimization of the scheduling for towing a floating offshore wind turbine between assembly port and installation location throughout a year

High demand for the installation of floating offshore wind turbines over the coming years is likely to place significant pressure on ports and installation vessels. Optimization of the routes between ports and farms and the towing schedule when transporting equipment is therefore critical to reducing operation timescales and carbon emissions. This paper presents two series of multi-objective optimizations for minimizing the timescale and carbon emissions for the case of an IEA 15 MW turbine on a VolturnUS-S platform being wet towed through the English Channel to the Celtic Sea. The study makes use of the Maritime Simulation Laboratory (MSL) Ship Simulator to develop an empirical model of the floating offshore wind turbine being towed under different wind conditions. This is then combined with bathymetry data and historical metocean data from the year 2021 to perform the optimizations. The optimization results are used to feed a second optimization that creates a schedule reducing both emissions and cumulated towing time during a whole year for different number of floating offshore wind turbines. • Multi-objective routing of a towed floating offshore wind turbine. • Multi-objective optimization of the schedule for wet towing over a calendar year.