Hull geometry optimisation of wave energy converters: On the choice of the optimisation algorithm and the geometry definition.

It is key in the development of wave energy systems to aim at designing economically competitive solutions that enable maximal annual energy production. Previous studies identify the Wave Energy Converter (WEC) structure, i.e. the hull, to have one of the largest cost reduction potentials. Due to this potential, geometry optimisation of WECs has been previously considered, however, most of these studies have been limited by the simplicity of the employed geometrical shapes and the lack of accurate cost models. It is, therefore, important to include an adaptable geometry definition capable of generating diverse WEC shapes, and to account for other factors that can have an effect on costs. These considerations result in a more challenging optimisation problem, and a more complex objective function. The goal of this study is to address the challenge of finding a suitable and efficient optimisation method for WEC geometry design. In this paper, different geometry definitions, such as using simple shapes or B-spline surfaces, and different meta-heuristic optimisation algorithms, such as genetic algorithms or particle swarm optimisation are applied to this problem to find the most suitable choices. Results show an improvement in final objective function values of up to 224% when using an adaptable geometry definition and up to 11% when employing the most suitable optimisation algorithm compared to previous results. In conclusion, the choice of the different elements of the optimisation formulation have a large impact on the quality of the optimisation results and should be based on preliminary studies as presented here. • A comprehensive optimisation method is required for wave energy converter design. • The main elements for wave energy converter geometry optimisation were studied. • Meta-heuristic algorithms are suitable for WEC geometry optimisation. • Genetic and particle swarm optimisation algorithms suit different study cases. • Geometry definitions based on bicubic B-splines achieve better optimisation results. [ABSTRACT FROM AUTHOR]