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Dynamic modeling of the motions of variable-shape wave energy converters

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  • Shabara, Mohamed A.
  • Abdelkhalik, Ossama

Abstract

In the recently introduced Variable-Shape heaving wave energy converters, the buoy changes its shape actively in response to changing incident waves. In this study, a Lagrangian approach for the dynamic modeling of a spherical Variable-Shape Wave Energy Converter is described. The classical bending theory is used to write the stress–strain equations for the flexible body using Love’s approximation. The elastic spherical shell is assumed to have an axisymmetric vibrational behavior. The Rayleigh–Ritz discretization method is adopted to find an approximate solution for the vibration model of the spherical shell. A novel equation of motion is presented that serves as a substitute for Cummins equation for flexible buoys. Also, novel hydrodynamic coefficients that account for the buoy mode shapes are proposed. The developed dynamic model is coupled with the open-source boundary element method software NEMOH. Two-way and one-way Fluid–Structure Interaction simulations are performed using MATLAB to study the effect of using a flexible shape buoy in the wave energy converter on its trajectory and power production. Finally, the variable shape buoy was able to harvest more energy for all the tested wave conditions.

Suggested Citation

  • Shabara, Mohamed A. & Abdelkhalik, Ossama, 2023. "Dynamic modeling of the motions of variable-shape wave energy converters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
  • Handle: RePEc:eee:rensus:v:173:y:2023:i:c:s1364032122009510
    DOI: 10.1016/j.rser.2022.113070
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    References listed on IDEAS

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    1. Göçmen, Tuhfe & Laan, Paul van der & Réthoré, Pierre-Elouan & Diaz, Alfredo Peña & Larsen, Gunner Chr. & Ott, Søren, 2016. "Wind turbine wake models developed at the technical university of Denmark: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 752-769.
    2. Lander Victor & Peter Troch & Jens Peter Kofoed, 2011. "On the Effects of Geometry Control on the Performance of Overtopping Wave Energy Converters," Energies, MDPI, vol. 4(10), pages 1-27, October.
    3. Li, Guang & Weiss, George & Mueller, Markus & Townley, Stuart & Belmont, Mike R., 2012. "Wave energy converter control by wave prediction and dynamic programming," Renewable Energy, Elsevier, vol. 48(C), pages 392-403.
    4. Clément, Alain & McCullen, Pat & Falcão, António & Fiorentino, Antonio & Gardner, Fred & Hammarlund, Karin & Lemonis, George & Lewis, Tony & Nielsen, Kim & Petroncini, Simona & Pontes, M. -Teresa & Sc, 2002. "Wave energy in Europe: current status and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 6(5), pages 405-431, October.
    5. Tom, N.M. & Lawson, M.J. & Yu, Y.H. & Wright, A.D., 2016. "Development of a nearshore oscillating surge wave energy converter with variable geometry," Renewable Energy, Elsevier, vol. 96(PA), pages 410-424.
    6. Zou, Shangyan & Abdelkhalik, Ossama & Robinett, Rush & Bacelli, Giorgio & Wilson, David, 2017. "Optimal control of wave energy converters," Renewable Energy, Elsevier, vol. 103(C), pages 217-225.
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    1. Liang, Hongjian & Qin, Hao & Su, Haowen & Wen, Zhixuan & Mu, Lin, 2024. "Environmental-Sensing and adaptive optimization of wave energy converter based on deep reinforcement learning and computational fluid dynamics," Energy, Elsevier, vol. 297(C).

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