The focus of improving the economic performance of the oscillating-body wave energy converters (WECs) is the optimization of the float shape. A combination of heuristic algorithms, panel-based hydrodynamic simulations and geometric parameterization forms a potential method to address this challenge. However, previous studies have shown that the optimal float shape depends on the choice of the optimization algorithm and the objective function. To give further insights into the method's effect on the optimal results and enhance its efficiency, the optimization of an oscillating-body WEC with three degrees of freedom (surge, pitch and heave) is considered herewith. The optimization parameters are selected using B-spline surfaces to describe the float geometry in the form of a matrix of control points. Multiple strategies with different heuristic algorithms and objective functions are employed to iteratively optimize the float shape subject to irregular waves. The time-domain boundary element method is used to simulate the interaction between waves and WECs. The numerical and experimental results show that this optimization method can significantly improve the power capture efficiency of the oscillating-body WEC, and both the algorithm setting and the objective function have a great impact on the optimization results.


Various concepts of the oscillating-body WECs have been proposed over the past few decades with the ultimate goal of selecting the most economically competitive designs. In these concepts, the float structure serves as the interface between the incident waves and the power take off (PTO) systems of WECs, whose hydrodynamic response determines the efficiency of the wave energy conversion to the mechanical energy of WECs. The float geometry has been found to be a key factor affecting the hydrodynamic performance of the float, and thus the economic performance of the WEC (Shi et al., 2019).

Optimizing the float shape of the oscillating-body WECs has been a research focus. At present, the design and optimization of the float shape are mostly based on a local intuitive method (Rodríguez et al., 2020), which take a few typical parameters or simple shapes as variables and evaluate a couple of possible solutions on a limited range. However, this method can be largely influenced by human intervention and preconceived ideas, and the result is not the global optimal solution.

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