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Numerical benchmarking study of a selection of wave energy converters

The aim of this study is to estimate the mean annual power absorption of a selection of eight Wave Energy Converters (WECs) with different working principles. Based on these estimates a set of power performance measures that can be related to costs are derived. These are the absorbed energy per char...

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Bibliographic Details
Published in:Renewable energy 2012-05, Vol.41, p.44-63
Main Authors: Babarit, A., Hals, J., Muliawan, M.J., Kurniawan, A., Moan, T., Krokstad, J.
Format: Article
Language:English
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Summary:The aim of this study is to estimate the mean annual power absorption of a selection of eight Wave Energy Converters (WECs) with different working principles. Based on these estimates a set of power performance measures that can be related to costs are derived. These are the absorbed energy per characteristic mass [kWh/kg], per characteristic surface area [MWh/m 2], and per root mean square of Power Take Off (PTO) force [kWh/N]. The methodology relies on numerical modelling. For each device, a numerical Wave-to-Wire (W2W) model is built based on the equations of motion. Physical effects are modelled according to the state-of-the-art within hydrodynamic modelling practise. Then, the W2W models are used to calculate the power matrices of each device and the mean annual power absorption at five different representative wave sites along the European Coast, at which the mean level of wave power resource ranges between 15 and 88 kW per metre of wave front. Uncertainties are discussed and estimated for each device. Computed power matrices and results for the mean annual power absorption are assembled in a summary sheet per device. Comparisons of the selected devices show that, despite very different working principles and dimensions, power performance measures vary much less than the mean annual power absorption. With the chosen units, these measures are all shown to be of the order of 1. ► 8 Wave Energy Converters with different working principles are calculated. ► Using numerical modelling, their power matrices are estimated. ► Annual energy production and power measures iarecalculated at five different sites. ► Comparison shows that despite very different levels of energy production, power measures are of similar order of magnitudes.
ISSN:0960-1481
1879-0682
DOI:10.1016/j.renene.2011.10.002