Studies of arrays of wave energy converters (WECs) with respect to power absorption and array interactions are often performed using linear models. However, nonlinear effects can be important and may change power estimates and optimal array designs. In this study, we have compared linear predictions of the behaviour of a shallowly submerged, buoyant point absorber with predictions from the nonlinear model SWASH with a WEC incorporated (WEC-SWASH). The latter was first comprehensively validated against 1:20 Froude scaled measured data from physical experiments. WEC-SWASH predictions of body motions and mean power absorption were generally in good agreement with measurements (absolute bias within 25%), although some discrepancies were observed in the body motions, especially when the device exhibited motion instabilities. The validated WEC-SWASH model was then compared with a linear frequency-domain model, as the latter is well-known and widely used because of its computational efficiency. Model comparisons were carried out for both an isolated WEC and small arrays (up to 5 devices). The mean power estimates from the linear model and WEC-SWASH for two representative wave farms showed good agreement for mild waves, with a difference of less than 5%. However, for larger waves, the disagreement increased to about 75 to 85% between the models (for the two wave farms tested). We found that array interactions for these arrays depend on wave amplitude and not just wave frequency. Furthermore, we discovered that the power take-off coefficients optimized using the linear model were not the optimum coefficients for the nonlinear model (WEC-SWASH).@en

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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