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Improving the assessment of wave energy resources by means of coupled wave-ocean numerical modeling

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  • Barbariol, Francesco
  • Benetazzo, Alvise
  • Carniel, Sandro
  • Sclavo, Mauro

Abstract

Sea waves energy represents a renewable and sustainable energy resource, that nevertheless needs to be further investigated to make it more cost-effective and economically appealing. A key step in the process of Wave Energy Converters (WEC) deployment is the energy resource assessment at a sea site either measured or obtained through numerical model analysis. In these kind of studies, some approximations are often introduced, especially in the early stages of the process, viz. waves are assumed propagating in deep waters without underneath ocean currents. These aspects are discussed and evaluated in the Adriatic Sea and its northern part (Gulf of Venice) using locally observed and modeled wave data. In particular, to account for a “state of the art” treatment of the Wave–Current Interaction (WCI) we have implemented the Simulating WAves Nearshore (SWAN) model and the Regional Ocean Modeling System (ROMS), fully coupled within the Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) system. COAWST has been applied to a computational grid covering the whole Adriatic Sea and off-line nested to a high-resolution grid in the Gulf of Venice. A 15-year long wave data set collected at the oceanographic tower “Acqua Alta”, located approximately 15 km off the Venice coast, has also been analyzed with the dual purpose of providing a reference to the model estimates and to locally assess the wave energy resource. By using COAWST, we have quantified for the first time to our best knowledge the importance of the WCI effect on wave power estimation. This can vary up to 30% neglecting the current effect. Results also suggest the Gulf of Venice as a suitable testing site for WECs, since it is characterized by periods of calm (optimal for safe installation and maintenance) alternating with severe storms, whose wave energy potentials are comparable to those ordinarily encountered in the energy production sites.

Suggested Citation

  • Barbariol, Francesco & Benetazzo, Alvise & Carniel, Sandro & Sclavo, Mauro, 2013. "Improving the assessment of wave energy resources by means of coupled wave-ocean numerical modeling," Renewable Energy, Elsevier, vol. 60(C), pages 462-471.
    • Handle: RePEc:eee:renene:v:60:y:2013:i:c:p:462-471
    DOI: 10.1016/j.renene.2013.05.043
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    1. Vicinanza, D. & Contestabile, P. & Ferrante, V., 2013. "Wave energy potential in the north-west of Sardinia (Italy)," Renewable Energy, Elsevier, vol. 50(C), pages 506-521.
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    3. Gunn, Kester & Stock-Williams, Clym, 2012. "Quantifying the global wave power resource," Renewable Energy, Elsevier, vol. 44(C), pages 296-304.
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    2. Hong, Ji-Seok & Moon, Jae-Hong & Kim, Taekyun & Cho, Il-Hyoung & Choi, Jongsu & Park, Ji Yong, 2021. "Response of wave energy to tidal currents in the western sea of Jeju Island, Korea," Renewable Energy, Elsevier, vol. 172(C), pages 564-573.
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    6. Lewis, M.J. & Neill, S.P. & Hashemi, M.R. & Reza, M., 2014. "Realistic wave conditions and their influence on quantifying the tidal stream energy resource," Applied Energy, Elsevier, vol. 136(C), pages 495-508.
    7. Hashemi, M. Reza & Neill, Simon P. & Robins, Peter E. & Davies, Alan G. & Lewis, Matt J., 2015. "Effect of waves on the tidal energy resource at a planned tidal stream array," Renewable Energy, Elsevier, vol. 75(C), pages 626-639.
    8. Liang, Bingchen & Fan, Fei & Liu, Fushun & Gao, Shanhong & Zuo, Hongyan, 2014. "22-Year wave energy hindcast for the China East Adjacent Seas," Renewable Energy, Elsevier, vol. 71(C), pages 200-207.
    9. Beya, Ignacio & Buckham, Bradley & Robertson, Bryson, 2021. "Impact of tidal currents and model fidelity on wave energy resource assessments," Renewable Energy, Elsevier, vol. 176(C), pages 50-66.
    10. Liang, Bingchen & Shao, Zhuxiao & Wu, Yajie & Shi, Hongda & Liu, Zhen, 2017. "Numerical study to estimate the wave energy under Wave-Current Interaction in the Qingdao coast, China," Renewable Energy, Elsevier, vol. 101(C), pages 845-855.
    11. Guillou, Nicolas & Chapalain, Georges, 2015. "Numerical modelling of nearshore wave energy resource in the Sea of Iroise," Renewable Energy, Elsevier, vol. 83(C), pages 942-953.
    12. Webb, A. & Waseda, T. & Kiyomatsu, K., 2020. "A high-resolution, long-term wave resource assessment of Japan with wave–current effects," Renewable Energy, Elsevier, vol. 161(C), pages 1341-1358.
    13. Rute Bento, A. & Martinho, Paulo & Guedes Soares, C., 2015. "Numerical modelling of the wave energy in Galway Bay," Renewable Energy, Elsevier, vol. 78(C), pages 457-466.
    14. Hashemi, M. Reza & Neill, Simon P., 2014. "The role of tides in shelf-scale simulations of the wave energy resource," Renewable Energy, Elsevier, vol. 69(C), pages 300-310.
    15. Shi, Xueli & Li, Shaowu & Liang, Bingchen & Zhao, Jianchun & Liu, Ye & Wang, Zhenlu, 2023. "Numerical study on the impact of wave-current interaction on wave energy resource assessments in Zhoushan sea area, China," Renewable Energy, Elsevier, vol. 215(C).
    16. Robins, Peter E. & Neill, Simon P. & Lewis, Matt J., 2014. "Impact of tidal-stream arrays in relation to the natural variability of sedimentary processes," Renewable Energy, Elsevier, vol. 72(C), pages 311-321.
    17. Foteinis, Spyros, 2022. "Wave energy converters in low energy seas: Current state and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    18. Hung-Ju Shih & Chih-Hsin Chang & Wei-Bo Chen & Lee-Yaw Lin, 2018. "Identifying the Optimal Offshore Areas for Wave Energy Converter Deployments in Taiwanese Waters Based on 12-Year Model Hindcasts," Energies, MDPI, vol. 11(3), pages 1-21, February.

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