An optimization approach for geometry design of multi-axis wave energy converter

The current global energy crisis necessitates a shift to renewable energy sources to mitigate climate change impacts. Wave energy emerges as a promising renewable resource to fulfill increasing energy demands. This energy can be extracted using wave energy converters (WECs), with multi-axis WECs (MA-WECs) being more effective than single-axis versions due to their capacity to harness energy from waves in various directions. The challenge lies in determining the ideal geometric design for MA-WECs, that can be tackled through multiobjective optimization (MOO) techniques. This research focuses on evaluating different MOO algorithms for the optimal geometric design of MA-WECs. To assess the structural response of different geometries and sizes, the study utilized the NEMOH boundary element method solver, aiming to maximize power output, lower the levelized cost of energy (LCOE), and optimize the geometry configuration. Findings indicate that the choice of optimization algorithm considerably influences the MA-WEC's optimal design, enhancing power efficiency, reducing device volume, and cutting costs more effectively than the initial design.