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Ocean wave energy is a source of renewable energy that has gained muchattention for its potential to contribute significantly to meeting the globalenergy demand. In this research, we investigate the problem of maximising theenergy delivered by farms of wave energy converters (WEC's). We considerstate-of-the-art fully submerged three-tether converters deployed in arrays.The goal of this work is to use heuristic search to optimise the power outputof arrays in a size-constrained environment by configuring WEC locations andthe power-take-off (PTO) settings for each WEC. Modelling the complexhydrodynamic interactions in wave farms is expensive, which constrains searchto only a few thousand model evaluations. We explore a variety of heuristicapproaches including cooperative and hybrid methods. The effectiveness of theseapproaches is assessed in two real wave scenarios (Sydney and Perth) with farmsof two different scales. We find that a combination of symmetric local searchwith Nelder-Mead Simplex direct search combined with a back-trackingoptimization strategy is able to outperform previously defined searchtechniques by up to 3\%.

A Hybrid Evolutionary Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters