The Levelized Cost of Energy for floating offshore wind must decrease significantly to be competitive with fixed offshore wind projects or even with onshore wind projects. This study focuses on the design optimization of cylindrical buoyancy bodies for floating substructures of offshore wind turbines. The presented work is based on a previously studied buoyancy body design that allows an efficient manufacturing process and integration into different substructures. In this study, an optimization framework based on genetic algorithm is developed to parameterize the buoyancy body’s geometry and optimize its design in terms of cost, considering loads acting on the structure as well as manufacturing and floater specific dimension restrictions. The implementation of the optimization process is detailed, and tested for a given study case. Two structurally different genetic algorithms are considered in order to compare the results obtained and asses the performance of the presented optimization framework.

The Levelized Cost of Energy for floating offshore wind must decrease significantly to be competitive with fixed offshore wind projects or even with onshore wind projects. This study focuses on the design optimization of cylindrical buoyancy bodies for Floating Offshore Wind Turbine substructures. The presented work is based on a previously studied buoyancy body design that allows an efficient manufacturing process and integration into different substructures. In this study, an optimization framework using a particular Genetic Algorithm is developed to parameterize the cylindrical geometry of the buoyancy body and optimize its design in terms of cost, considering loads acting on the structure as well as manufacturing and floater specific dimension restrictions. In this paper, the specific characteristics of this particular buoyancy body are highlighted and the implementation of the optimization process is detailed. Preliminary results for a given study case are presented and discussed before pointing out potential cost reductions and future improvements to be made with regards to the presented optimization work.