Compared to onshore wind power, floating offshore wind power is a promising renewable energy source due to higher wind speeds and larger suitable available areas. However, costs are still too high compared to onshore wind power. In general, the economic viability of offshore wind technology decreases with greater water depth and distance from shore. Floating wind platforms are more competitive compared to fixed offshore structures above a certain water depth, but there is still great variety and no clear design convergence. Therefore, optimisation of the floating support structure in the preliminary phase of the design process is still of great importance, often up to personal experience and sensibility. It is fundamental that a suitable optimisation approach is chosen to obtain meaningful results at early development stages. This review provides a comparative overview of the methods, numerical tools and optimisation approaches that can be used with respect to the conceptual design of the support structure for Floating offshore wind turbines (FOWT) attempting to detail the limitations preventing the convergence to an optimal floating support structure. This work is intended to be as a reference for any researcher and developer that would like to optimise the support platform for FOWT.

Although sea and ocean waves have been widely acknowledged to have the potential of providing sustainable and renewable energy, the emergence of a self-sufficient and mature industry is still lacking. An essential condition for reaching economic viability is to minimise the cost of electricity, as opposed to simply maximising the converted energy at the early design stages. One of the tools empowering developers to follow such a virtuous design pathway is the techno-economic optimisation. The purpose of this paper is to perform a holistic optimisation of the PeWEC (pendulum wave energy converter), which is a pitching platform converting energy from the oscillation of a pendulum contained in a sealed hull. Optimised parameters comprise shape; dimensions; mass properties and ballast; power take-off control torque and constraints; number and characteristics of the pendulum; and other subcomponents. Cost functions are included and the objective function is the ratio between the delivered power and the capital expenditure. Due to its ability to effectively deal with a large multi-dimensional design space, a genetic algorithm is implemented, with a specific modification to handle unfeasible design candidate and improve convergence. Results show that the device minimising the cost of energy and the one maximising the capture width ratio are substantially different, so the economically-oriented metric should be preferred.