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Influence of the power take-off characteristics on the performance of CECO wave energy converter


  • López, M.
  • Taveira-Pinto, F.
  • Rosa-Santos, P.


Previous experimental works proved the ability of CECO to harness wave energy. This wave energy converter (WEC) is presently at Technology Readiness Level (TRL) three, where characterizing the energy conversion stages and evaluating the energy conversion efficiency is crucial. Therefore, in this work Ansys® Aqwa™ was applied to study a CECO unit and to obtain a detailed knowledge of its performance throughout the different energy conversion stages. The numerical model was initially calibrated with results from experimental tests and then used to simulate different configurations of the power take-off (PTO) system under a wide range of regular and irregular wave conditions. For most of the irregular wave conditions tested, CECO can absorb between 10 and 40% of the incident wave power and transmit to the electric generator up to 18%. Although the results reveal a high energy conversion efficiency, there is still scope for improvement of the device by optimizing the PTO. On these grounds, the ideal values of the electric generator damping coefficient are presented for different wave conditions, which allow to define an adequate control strategy in future works.

Suggested Citation

  • López, M. & Taveira-Pinto, F. & Rosa-Santos, P., 2017. "Influence of the power take-off characteristics on the performance of CECO wave energy converter," Energy, Elsevier, vol. 120(C), pages 686-697.
  • Handle: RePEc:eee:energy:v:120:y:2017:i:c:p:686-697
    DOI: 10.1016/

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    References listed on IDEAS

    1. Bret Bosma & Tim Lewis & Ted Brekken & Annette von Jouanne, 2015. "Wave Tank Testing and Model Validation of an Autonomous Wave Energy Converter," Energies, MDPI, Open Access Journal, vol. 8(8), pages 1-16, August.
    2. López, I. & Pereiras, B. & Castro, F. & Iglesias, G., 2014. "Optimisation of turbine-induced damping for an OWC wave energy converter using a RANS–VOF numerical model," Applied Energy, Elsevier, vol. 127(C), pages 105-114.
    3. Iglesias, G. & López, M. & Carballo, R. & Castro, A. & Fraguela, J.A. & Frigaard, P., 2009. "Wave energy potential in Galicia (NW Spain)," Renewable Energy, Elsevier, vol. 34(11), pages 2323-2333.
    4. Folley, Matt & Whittaker, Trevor, 2009. "The cost of water from an autonomous wave-powered desalination plant," Renewable Energy, Elsevier, vol. 34(1), pages 75-81.
    5. Babarit, A. & Hals, J. & Muliawan, M.J. & Kurniawan, A. & Moan, T. & Krokstad, J., 2012. "Numerical benchmarking study of a selection of wave energy converters," Renewable Energy, Elsevier, vol. 41(C), pages 44-63.
    6. Li, Ye & Yu, Yi-Hsiang, 2012. "A synthesis of numerical methods for modeling wave energy converter-point absorbers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4352-4364.
    7. McCabe, A.P. & Aggidis, G.A. & Widden, M.B., 2010. "Optimizing the shape of a surge-and-pitch wave energy collector using a genetic algorithm," Renewable Energy, Elsevier, vol. 35(12), pages 2767-2775.
    8. Iglesias, G. & Carballo, R., 2014. "Wave farm impact: The role of farm-to-coast distance," Renewable Energy, Elsevier, vol. 69(C), pages 375-385.
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    1. repec:eee:appene:v:222:y:2018:i:c:p:717-728 is not listed on IDEAS
    2. repec:eee:energy:v:143:y:2018:i:c:p:833-845 is not listed on IDEAS
    3. repec:eee:energy:v:135:y:2017:i:c:p:303-316 is not listed on IDEAS


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