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Integrating ocean wave energy at large-scales: A study of the US Pacific Northwest

Author

Listed:
  • Parkinson, Simon C.
  • Dragoon, Ken
  • Reikard, Gordon
  • García-Medina, Gabriel
  • Özkan-Haller, H. Tuba
  • Brekken, Ted K.A.

Abstract

This paper assesses operational impacts of large-scale ocean wave energy development in the US Pacific Northwest. High-resolution wave power production and forecasting data is synthesized for wave energy arrays spatially-distributed along the region's coast. Geographic diversification is found to limit the rate at which production variability scales with installed capacity, over timescales ranging from minutes to hours. The reduced variability makes it easier to forecast short-term wave generation accurately. When modeled within the operational structure of the region's primary balancing area authority, large-scale wave energy is found to provide a relatively high capacity value and costs less to integrate than equivalent amounts of wind energy.

Suggested Citation

  • Parkinson, Simon C. & Dragoon, Ken & Reikard, Gordon & García-Medina, Gabriel & Özkan-Haller, H. Tuba & Brekken, Ted K.A., 2015. "Integrating ocean wave energy at large-scales: A study of the US Pacific Northwest," Renewable Energy, Elsevier, vol. 76(C), pages 551-559.
    • Handle: RePEc:eee:renene:v:76:y:2015:i:c:p:551-559
    DOI: 10.1016/j.renene.2014.11.038
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    References listed on IDEAS

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    1. Babarit, A. & Hals, J. & Muliawan, M.J. & Kurniawan, A. & Moan, T. & Krokstad, J., 2012. "Numerical benchmarking study of a selection of wave energy converters," Renewable Energy, Elsevier, vol. 41(C), pages 44-63.
    2. Fusco, Francesco & Nolan, Gary & Ringwood, John V., 2010. "Variability reduction through optimal combination of wind/wave resources – An Irish case study," Energy, Elsevier, vol. 35(1), pages 314-325.
    3. Lenee-Bluhm, Pukha & Paasch, Robert & Özkan-Haller, H. Tuba, 2011. "Characterizing the wave energy resource of the US Pacific Northwest," Renewable Energy, Elsevier, vol. 36(8), pages 2106-2119.
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    Cited by:

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    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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    6. Pasquale Contestabile & Vincenzo Ferrante & Diego Vicinanza, 2015. "Wave Energy Resource along the Coast of Santa Catarina (Brazil)," Energies, MDPI, vol. 8(12), pages 1-25, December.
    7. Ponce de León, S. & Orfila, A. & Simarro, G., 2016. "Wave energy in the Balearic Sea. Evolution from a 29 year spectral wave hindcast," Renewable Energy, Elsevier, vol. 85(C), pages 1192-1200.
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    9. Kilcher, Levi & García Medina, Gabriel & Yang, Zhaoqing, 2023. "A scalable wave resource assessment methodology: Application to U.S. waters," Renewable Energy, Elsevier, vol. 217(C).
    10. Reikard, Gordon & Robertson, Bryson & Bidlot, Jean-Raymond, 2015. "Combining wave energy with wind and solar: Short-term forecasting," Renewable Energy, Elsevier, vol. 81(C), pages 442-456.
    11. Humberto Verdejo & Almendra Awerkin & Wolfgang Kliemann & Cristhian Becker & Héctor Chávez & Karina A. Barbosa & José Delpiano, 2019. "A Dynamic Stochastic Hybrid Model to Represent Significant Wave Height and Wave Period for Marine Energy Representation," Energies, MDPI, vol. 12(5), pages 1-15, March.

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