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Real time hybrid modeling for ocean wave energy converters

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  • Börner, Thomas
  • Alam, Mohammad-Reza

Abstract

Accurate modeling of ocean wave energy converters is limited mainly due to the reciprocating nature of the exciting force and consequent complications, particularly in the fluid domain. Direct simulation is usually computationally expensive, and experiments are constrained by scaling rules that cannot be satisfied simultaneously, and of course, by the costs. Many modeling problems, including several in ocean wave energy, can be divided into sub-domains that for each, one modeling scheme (e.g. numerical simulation or experiment) is practical and preferred. The idea behind hybrid simulation is to solve each sub-domain using the preferred method, while sub-domains communicate with each other at their common boundaries via sensors and actuators, with the prime objective of solving the main problem as a whole. We are particularly interested in the set of problems in which the subdomains are strongly coupled and hence significantly influence each other. The challenge is when one of the subproblems is to be modeled experimentally and therefore as a result the entire hybrid simulation modeling has to be carried out in real time. We review here the background and details of the real time hybrid simulation scheme with the specific focus on the modeling of ocean wave energy devices. We elaborate major challenges via a case study of a newly proposed seabed mounted pressure-differential wave energy converter called “Wave Carpet”. We find the optimum parameters of the power takeoff units as well as their optimal positioning in order to achieve the highest overall efficiency of the Wave Carpet.

Suggested Citation

  • Börner, Thomas & Alam, Mohammad-Reza, 2015. "Real time hybrid modeling for ocean wave energy converters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 784-795.
  • Handle: RePEc:eee:rensus:v:43:y:2015:i:c:p:784-795
    DOI: 10.1016/j.rser.2014.11.063
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    References listed on IDEAS

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    1. Painuly, J.P, 2001. "Barriers to renewable energy penetration; a framework for analysis," Renewable Energy, Elsevier, vol. 24(1), pages 73-89.
    2. Zhang, Dahai & Li, Wei & Lin, Yonggang, 2009. "Wave energy in China: Current status and perspectives," Renewable Energy, Elsevier, vol. 34(10), pages 2089-2092.
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    Cited by:

    1. Hashim, Roslan & Roy, Chandrabhushan & Motamedi, Shervin & Shamshirband, Shahaboddin & Petković, Dalibor, 2016. "Selection of climatic parameters affecting wave height prediction using an enhanced Takagi-Sugeno-based fuzzy methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 246-257.
    2. Foteinis, S. & Tsoutsos, T., 2017. "Strategies to improve sustainability and offset the initial high capital expenditure of wave energy converters (WECs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 775-785.
    3. Ubaldo Jasso-Ruiz & Juan Ramón Rodríguez-Rodríguez & Edgar Mendoza & Carlos Echeverría & Nadia Maria Salgado-Herrera, 2024. "Real-Time Co-Simulation and Grid Integration of PMSG-Based Hydrokinetic Energy Conversion Systems via Power-Hardware-in-the-Loop Technics," Energies, MDPI, vol. 17(11), pages 1-20, May.
    4. Cuadra, L. & Salcedo-Sanz, S. & Nieto-Borge, J.C. & Alexandre, E. & Rodríguez, G., 2016. "Computational intelligence in wave energy: Comprehensive review and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1223-1246.

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