An efficient optimisation tool for floating offshore wind support structures. (November 2022) - Faraggiana, E.; Sirigu, M.; Ghigo, A.; Bracco, G.; Mattiazzo, G.
Abstract: Floating offshore wind turbines (FOWTs) are a rapidly developing technology, but still, need to gain economic competitiveness to obtain market acceptance. The reduction of the structural cost of the floating platform represents one of the main targets to reach an optimal design in the initial design process. This paper proposes an efficient optimisation tool that could be applied to any floating wind turbine to optimise the main geometry design parameters. In this study, the OC3 spar buoy concept is considered as an example, where the stability and dynamic performance of the device are verified using hydrostatic and time-domain computations. The numerical simulations are solved using an in-house MATLAB code that uses Salome-Meca to create the mesh and obtain hydrostatic and dynamic properties of the platform, Nemoh to calculate the hydrodynamic coefficients and an aero-hydro-servo Simscape model for the time-domain simulation. The main geometry design parameters of the buoy are optimised using a genetic algorithm in combination with the Kriging surrogate model to minimise the buoy's structural cost while ensuring the spar's performance. The optimal design reduces the cost by two to three times the worst configuration of the design space and there is also a 25% cost reduction between the most and the least restrictive optimal cases. The optimal design results demonstrate the hydrostatic constraints' significance over the dynamic ones as they mostly influence the feasible design area. However, the results of this work could only be specific to the design case considered, and careful consideration should be given to other types of geometries. The optimisation approach presented is particularly important as it is flexible and can be adapted to other platforms. Highlights: An efficient optimisation tool is developed for floating offshore wind platforms. Hydrostatic and dynamic optimisations are compared. Hydrostatic constraints are more significant than dynamic ones. Time-domain simulation is based on computationally efficient look-up tables.