A novel two-objective optimization computational framework for a two-body heaving wave energy converter

Abstract

The present research introduces a novel two-objective optimization computational framework, named H∞ optimization criterion-constrained Two-Objective Optimization Genetic Algorithm (H∞ − cTOOGA). Within this optimization framework, the objectives considered are: (i) the sprung mass isolation, and (ii) the wave energy extraction of a heaving buoy coupled with a sprung (overlying) mass. In such a two-body heaving wave energy converter (WEC), the satisfaction of both objectives is pursued by proper selection of the buoy geometry (i.e., radius r and draft Dr) and the characteristics of the power take-off (PTO). The interrelation among potential buoy geometries and PTO characteristics is performed on the basis of a critical condition. The critical condition refers to the formation of equal double peaks in the sprung mass acceleration response curve and is imposed as the sprung mass acceleration limit that is not allowed to be exceeded throughout the entire frequency range of interest. The two-objective optimization is realized with r, Dr and the tuning ratio δOPT being the decision variables. The value of δOPT is constrained by the value of the critical tuning ratio δcrit, that is, δOPT <δcrit. This ensures the minimization of the maximum sprung mass acceleration response. Then, the Pareto-optimal solutions result to optimal wave energy extraction.