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Adaptability of a generic wave energy converter to different climate conditions

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  • de Andres, A.
  • Guanche, R.
  • Vidal, C.
  • Losada, I.J.

Abstract

This study evaluates the influence of wave climate tunability on the performance of a generic Wave Energy Converter (WEC) for different climate scenarios. The generic WEC is assumed to be composed of an array of heaving, floating cylinders. In this study, two natural periods for the cylinders of 4 s and 8 s (typical of enclosed seas and the mean Atlantic swell, respectively) and a location-tunable cylinder are considered to evaluate the influence of tuning on the power performance of the cylinder. The WEC power matrix is computed using a frequency domain model, and the performance of the WEC is evaluated along the global coasts; the met-ocean data originated from the global reanalysis database (GOW) from Reguero et al. (2012). The performance of the WEC is evaluated using two parameters: the capture width ratio (CWR), which evaluates the efficiency of the converter at each location, and the kW/Ton (KWT) parameter, which evaluates the efficiency of the converter using “economic” terms. Tuning a converter for each location displayed a positive CWR; however, the KWT was low after WEC tuning because of the weight of the structures required to tune the converter that experiences high peak periods.

Suggested Citation

  • de Andres, A. & Guanche, R. & Vidal, C. & Losada, I.J., 2015. "Adaptability of a generic wave energy converter to different climate conditions," Renewable Energy, Elsevier, vol. 78(C), pages 322-333.
  • Handle: RePEc:eee:renene:v:78:y:2015:i:c:p:322-333
    DOI: 10.1016/j.renene.2015.01.020
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    References listed on IDEAS

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    1. Goggins, Jamie & Finnegan, William, 2014. "Shape optimisation of floating wave energy converters for a specified wave energy spectrum," Renewable Energy, Elsevier, vol. 71(C), pages 208-220.
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    2. Wang, Yingguang & Wang, Lifu, 2018. "Towards realistically predicting the power outputs of wave energy converters: Nonlinear simulation," Energy, Elsevier, vol. 144(C), pages 120-128.
    3. Reguero, B.G. & Losada, I.J. & Méndez, F.J., 2015. "A global wave power resource and its seasonal, interannual and long-term variability," Applied Energy, Elsevier, vol. 148(C), pages 366-380.
    4. He, Zechen & Ning, Dezhi & Gou, Ying & Zhou, Zhimin, 2022. "Wave energy converter optimization based on differential evolution algorithm," Energy, Elsevier, vol. 246(C).
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    7. Robertson, Bryson & Bailey, Helen & Leary, Matthew & Buckham, Bradley, 2021. "A methodology for architecture agnostic and time flexible representations of wave energy converter performance," Applied Energy, Elsevier, vol. 287(C).
    8. Lavidas, George & Venugopal, Vengatesan, 2017. "A 35 year high-resolution wave atlas for nearshore energy production and economics at the Aegean Sea," Renewable Energy, Elsevier, vol. 103(C), pages 401-417.
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    10. Adrian De Andres & Jéromine Maillet & Jørgen Hals Todalshaug & Patrik Möller & David Bould & Henry Jeffrey, 2016. "Techno-Economic Related Metrics for a Wave Energy Converters Feasibility Assessment," Sustainability, MDPI, vol. 8(11), pages 1-19, October.
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    12. Garcia-Teruel, Anna & Forehand, David I.M., 2022. "Manufacturability considerations in design optimisation of wave energy converters," Renewable Energy, Elsevier, vol. 187(C), pages 857-873.
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    14. Pasquale Contestabile & Enrico Di Lauro & Mariano Buccino & Diego Vicinanza, 2016. "Economic Assessment of Overtopping BReakwater for Energy Conversion (OBREC): A Case Study in Western Australia," Sustainability, MDPI, vol. 9(1), pages 1-28, December.
    15. Garcia-Teruel, A. & Forehand, D.I.M., 2021. "A review of geometry optimisation of wave energy converters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
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