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To be commercially viable, wave energy converters (WECs) will need to be deployed in arrays or “wave farms” to generate significant amounts of energy and to have the costs of these farms minimised. However, when designing a wave farm, there are a number of trade-offs to be made between competing objectives; for example, between the power production potential and installation costs, with the optimal design for one objective not necessarily favourable for the other. In this study, we developed a multi-objective optimisation methodology to allow rigorous evaluation of the trade-offs amongst multiple objectives. We demonstrate the methodology for four objectives: (1) maximising power production, (2) minimising the foundation loads, (3) minimising the number of foundations and (4) minimising the total export cable length required. However, the method is flexible and can be used for optimising a range of other parameters. A case study examining multi-objective optimisation of a wave farm using the developed probability-based evolutionary strategy was conducted for a proposed development site in Albany, Western Australia. The wave farms were composed of 5, 10 and 20 fully submerged cylindrical point-absorber type WECs similar to Carnegie Clean Energy's CETO-6 device. Simulations show that the optimal layouts preferring maximum power formed a single line perpendicular to the predominant wave direction; the optimal layouts preferring minimum cable length and a minimum number of foundations form multiple lines; whereas the optimal layouts preferring minimum foundation loads formed multiple lines in line with the predominant wave direction. By applying a cost model and non-dominated sorting, the methodology allowed us to quantify the trade-offs between power production and cost.
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