Cost assessment for a semi-submersible floating wind turbine with respect to the hydrodynamic response and tower base bending moments using particle swarm optimisation
International Offshore and Polar Engineering Conference: 419-426 (2016-06)
Contribution to Conference
Cost reduction of a floating wind turbine is crucial for developing wind parks in deep water. Therefore, a study to identify the impact of a number of parameters, such as wind turbine rating, top mass and site conditions, on platform size and support structure cost of a generic semi-submersible was developed. In order to do so, a Python code, which estimates the platform behaviour, was coupled with a Particle Swarm Optimisation (PSO) algorithm. With this, the minimum cost of the support structure could be found which satisfies specified design constraints.
Floating wind turbine
Particle swarm optimisation
Tower base stress
Wind- and wave loads