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A tool for combined WEC-site selection throughout a coastal region: Rias Baixas, NW Spain

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  • Carballo, R.
  • Sánchez, M.
  • Ramos, V.
  • Castro, A.

Abstract

The selection of the appropriate wave energy converter (WEC) and site is the basis for the installation of a wave farm in a region. For this purpose, the estimation of the energy that any WEC would produce at any location of interest is fundamental. Despite all its importance, this information or the elements required for obtaining it are currently available only at specific coastal locations or areas of interest. This work develops a tool for computing the energy that any WEC would generate at any coastal location within the Rias Baixas Region (NW Spain). With this aim, a methodology which allows the consideration of almost all the total energy available is used to characterize the coastal resource with a high spatial resolution. Then, a matlab-based application called WEDGE (Wave Energy Diagram GEnerator) is implemented for easy access to the stored data and automatic reconstruction of the resource at any coastal site in terms of a high-resolution characterization matrix (or energy diagram). As a result, the information required for accurate energy production computation throughout the region is available whereby a combined WEC-site selection can be conducted. Finally, the tool is used to compute the energy production of a total of 23 WEC-site combinations in an area within this region where a wave farm has been recently proposed. The results will underline the importance of a combined WEC-site selection for proper decision-making regarding wave energy exploitation.

Suggested Citation

  • Carballo, R. & Sánchez, M. & Ramos, V. & Castro, A., 2014. "A tool for combined WEC-site selection throughout a coastal region: Rias Baixas, NW Spain," Applied Energy, Elsevier, vol. 135(C), pages 11-19.
    • Handle: RePEc:eee:appene:v:135:y:2014:i:c:p:11-19
    DOI: 10.1016/j.apenergy.2014.08.068
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    4. Rusu, Eugen & Onea, Florin, 2016. "Estimation of the wave energy conversion efficiency in the Atlantic Ocean close to the European islands," Renewable Energy, Elsevier, vol. 85(C), pages 687-703.
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    6. Appendini, Christian M. & Urbano-Latorre, Claudia P. & Figueroa, Bernardo & Dagua-Paz, Claudia J. & Torres-Freyermuth, Alec & Salles, Paulo, 2015. "Wave energy potential assessment in the Caribbean Low Level Jet using wave hindcast information," Applied Energy, Elsevier, vol. 137(C), pages 375-384.
    7. Abaei, Mohammad Mahdi & Arzaghi, Ehsan & Abbassi, Rouzbeh & Garaniya, Vikram & Penesis, Irene, 2017. "Developing a novel risk-based methodology for multi-criteria decision making in marine renewable energy applications," Renewable Energy, Elsevier, vol. 102(PB), pages 341-348.
    8. Kamranzad, Bahareh & Hadadpour, Sanaz, 2020. "A multi-criteria approach for selection of wave energy converter/location," Energy, Elsevier, vol. 204(C).
    9. Carballo, R. & Arean, N. & Álvarez, M. & López, I. & Castro, A. & López, M. & Iglesias, G., 2019. "Wave farm planning through high-resolution resource and performance characterization," Renewable Energy, Elsevier, vol. 135(C), pages 1097-1107.
    10. Raúl Cascajo & Emilio García & Eduardo Quiles & Francisco Morant & Antonio Correcher, 2020. "Wave Energy Assessment at Valencia Gulf and Comparison of Energy Production of Most Suitable Wave Energy Converters," IJERPH, MDPI, vol. 17(22), pages 1-16, November.
    11. Liang, Bingchen & Shao, Zhuxiao & Wu, Guoxiang & Shao, Meng & Sun, Jinwei, 2017. "New equations of wave energy assessment accounting for the water depth," Applied Energy, Elsevier, vol. 188(C), pages 130-139.
    12. Kamranzad, Bahareh & Lin, Pengzhi & Iglesias, Gregorio, 2021. "Combining methodologies on the impact of inter and intra-annual variation of wave energy on selection of suitable location and technology," Renewable Energy, Elsevier, vol. 172(C), pages 697-713.

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