Multi-objective optimization design for a 15 MW semisubmersible floating offshore wind turbine using evolutionary algorithm

This paper introduces a framework designed to optimize the configuration of a 15 MW floating offshore wind turbine (FOWT) with a focus on the cost. The proposed framework employs a multi-objective evolutionary algorithm, integrating frequency domain (FD) simulations with equilibrium analysis to assess the responses of the floating platform and its mooring system. The objective function of the optimization includes the steel structural mass of the floating platform, the pitch heeling angle, and the motion response amplitude operator (RAO) peak as determined by the FD simulation. Constraints pertinent to these objective functions, alongside the safety of the mooring system and the dynamic response and parameter settings of the FOWT, are meticulously enforced. The resulting optimized designs exhibit substantial improvements in the steel structural mass and pitch heeling angle compare to the initial design parameters. The reliability of this optimization framework is corroborated through time domain (TD) simulations, which elucidate the effects of the pitch heel angle and motion RAO peaks on the time domain response of the optimized structures. These insights offer reference for the future optimization of floating platforms and mooring systems in the realm of offshore wind energy.