IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i5p887-d211866.html
   My bibliography  Save this article

A Dynamic Stochastic Hybrid Model to Represent Significant Wave Height and Wave Period for Marine Energy Representation

Author

Listed:
  • Humberto Verdejo

    (Department of Electrical Engineering, Universidad de Santiago de Chile, Santiago 9170124, Chile
    These authors contributed equally to this work.)

  • Almendra Awerkin

    (Department of Electrical Engineering, Universidad de Santiago de Chile, Santiago 9170124, Chile
    These authors contributed equally to this work.)

  • Wolfgang Kliemann

    (Department of Mathematics, Iowa State University, Ames, IA 50011, USA)

  • Cristhian Becker

    (Department of Electrical Engineering, Universidad de Santiago de Chile, Santiago 9170124, Chile
    These authors contributed equally to this work.)

  • Héctor Chávez

    (Department of Electrical Engineering, Universidad de Santiago de Chile, Santiago 9170124, Chile
    These authors contributed equally to this work.)

  • Karina A. Barbosa

    (Department of Electrical Engineering, Universidad de Santiago de Chile, Santiago 9170124, Chile
    These authors contributed equally to this work.)

  • José Delpiano

    (School of Engineering and Applied Sciences, Universidad de los Andes, Santiago 7620001, Chile
    Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390212, Chile)

Abstract

This paper presents a methodology to represent ocean wave power generation based on real data observation for significant wave height (SWH or H s ) and wave period (WP or T ). This technique is based on a hybrid model, which considers Fourier series and stochastic differential equations, allowing a continuous time representation of the random changes in the parameters associated with wave power generation ( H s and T ). The methodology is explained, including estimation methods and a validation procedure. The data series generated by the models erre used to create simulated wave power output applying a transformed matrix and a theoretical model. The results validate the utilization of this technique, when the objective is to obtain a robust dynamic representation of a random process, oriented to linear studies.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:887-:d:211866
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/5/887/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/5/887/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mustapa, M.A. & Yaakob, O.B. & Ahmed, Yasser M. & Rheem, Chang-Kyu & Koh, K.K. & Adnan, Faizul Amri, 2017. "Wave energy device and breakwater integration: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 43-58.
    2. 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.
    3. Wu, Shuping & Liu, Chuanyu & Chen, Xinping, 2015. "Offshore wave energy resource assessment in the East China Sea," Renewable Energy, Elsevier, vol. 76(C), pages 628-636.
    4. Pinson, P. & Reikard, G. & Bidlot, J.-R., 2012. "Probabilistic forecasting of the wave energy flux," Applied Energy, Elsevier, vol. 93(C), pages 364-370.
    5. Pelc, Robin & Fujita, Rod M., 2002. "Renewable energy from the ocean," Marine Policy, Elsevier, vol. 26(6), pages 471-479, November.
    6. O'Hagan, A.M. & Lewis, A.W., 2011. "The existing law and policy framework for ocean energy development in Ireland," Marine Policy, Elsevier, vol. 35(6), pages 772-783, December.
    7. Lehmann, Marcus & Karimpour, Farid & Goudey, Clifford A. & Jacobson, Paul T. & Alam, Mohammad-Reza, 2017. "Ocean wave energy in the United States: Current status and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1300-1313.
    8. Tedd, James & Peter Kofoed, Jens, 2009. "Measurements of overtopping flow time series on the Wave Dragon, wave energy converter," Renewable Energy, Elsevier, vol. 34(3), pages 711-717.
    9. Rusu, Liliana & Onea, Florin, 2017. "The performance of some state-of-the-art wave energy converters in locations with the worldwide highest wave power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1348-1362.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Milad Shadman & Mateo Roldan-Carvajal & Fabian G. Pierart & Pablo Alejandro Haim & Rodrigo Alonso & Corbiniano Silva & Andrés F. Osorio & Nathalie Almonacid & Griselda Carreras & Mojtaba Maali Amiri &, 2023. "A Review of Offshore Renewable Energy in South America: Current Status and Future Perspectives," Sustainability, MDPI, vol. 15(2), pages 1-34, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tunde Aderinto & Hua Li, 2018. "Ocean Wave Energy Converters: Status and Challenges," Energies, MDPI, vol. 11(5), pages 1-26, May.
    2. Tunde Aderinto & Hua Li, 2019. "Review on Power Performance and Efficiency of Wave Energy Converters," Energies, MDPI, vol. 12(22), pages 1-24, November.
    3. Hugo Mendonça & Rosa M. De Castro & Sergio Martínez & David Montalbán, 2017. "Voltage Impact of a Wave Energy Converter on an Unbalanced Distribution Grid and Corrective Actions," Sustainability, MDPI, vol. 9(10), pages 1-16, October.
    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.
    5. Milad Shadman & Corbiniano Silva & Daiane Faller & Zhijia Wu & Luiz Paulo de Freitas Assad & Luiz Landau & Carlos Levi & Segen F. Estefen, 2019. "Ocean Renewable Energy Potential, Technology, and Deployments: A Case Study of Brazil," Energies, MDPI, vol. 12(19), pages 1-37, September.
    6. Choupin, O. & Pinheiro Andutta, F. & Etemad-Shahidi, A. & Tomlinson, R., 2021. "A decision-making process for wave energy converter and location pairing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    7. Zhang, Yongxing & Zhao, Yongjie & Sun, Wei & Li, Jiaxuan, 2021. "Ocean wave energy converters: Technical principle, device realization, and performance evaluation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    8. Galparsoro, I. & Korta, M. & Subirana, I. & Borja, Á. & Menchaca, I. & Solaun, O. & Muxika, I. & Iglesias, G. & Bald, J., 2021. "A new framework and tool for ecological risk assessment of wave energy converters projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    9. Jahangir, Mohammad Hossein & Hosseini, Seyed Sina & Mehrpooya, Mehdi, 2018. "A detailed theoretical modeling and parametric investigation of potential power in heaving buoys," Energy, Elsevier, vol. 154(C), pages 201-209.
    10. Américo S. Ribeiro & Maite deCastro & Liliana Rusu & Mariana Bernardino & João M. Dias & Moncho Gomez-Gesteira, 2020. "Evaluating the Future Efficiency of Wave Energy Converters along the NW Coast of the Iberian Peninsula," Energies, MDPI, vol. 13(14), pages 1-15, July.
    11. Nasrollahi, Sadaf & Kazemi, Aliyeh & Jahangir, Mohammad-Hossein & Aryaee, Sara, 2023. "Selecting suitable wave energy technology for sustainable development, an MCDM approach," Renewable Energy, Elsevier, vol. 202(C), pages 756-772.
    12. Bertram, D.V. & Tarighaleslami, A.H. & Walmsley, M.R.W. & Atkins, M.J. & Glasgow, G.D.E., 2020. "A systematic approach for selecting suitable wave energy converters for potential wave energy farm sites," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    13. Choupin, O. & Têtu, A. & Del Río-Gamero, B. & Ferri, F. & Kofoed, JP., 2022. "Premises for an annual energy production and capacity factor improvement towards a few optimised wave energy converters configurations and resources pairs," Applied Energy, Elsevier, vol. 312(C).
    14. deCastro, M. & Rusu, L. & Arguilé-Pérez, B. & Ribeiro, A. & Costoya, X. & Carvalho, D. & Gómez-Gesteira, M., 2024. "Different approaches to analyze the impact of future climate change on the exploitation of wave energy," Renewable Energy, Elsevier, vol. 220(C).
    15. Martić, Ivana & Degiuli, Nastia & Grlj, Carlo Giorgio, 2024. "Scaling of wave energy converters for optimum performance in the Adriatic Sea," Energy, Elsevier, vol. 294(C).
    16. 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).
    17. Carrelhas, A.A.D. & Gato, L.M.C. & Falcão, A.F.O. & Henriques, J.C.C., 2021. "Control law design for the air-turbine-generator set of a fully submerged 1.5 MW mWave prototype. Part 2: Experimental validation," Renewable Energy, Elsevier, vol. 171(C), pages 1002-1013.
    18. Sánchez, Antonio Santos & Rodrigues, Diego Arruda & Fontes, Raony Maia & Martins, Márcio Fernandes & Kalid, Ricardo de Araújo & Torres, Ednildo Andrade, 2018. "Wave resource characterization through in-situ measurement followed by artificial neural networks' modeling," Renewable Energy, Elsevier, vol. 115(C), pages 1055-1066.
    19. Alireza Shadmani & Mohammad Reza Nikoo & Riyadh I. Al-Raoush & Nasrin Alamdari & Amir H. Gandomi, 2022. "The Optimal Configuration of Wave Energy Conversions Respective to the Nearshore Wave Energy Potential," Energies, MDPI, vol. 15(20), pages 1-29, October.
    20. Xu, Xinxin & Robertson, Bryson & Buckham, Bradley, 2020. "A techno-economic approach to wave energy resource assessment and development site identification," Applied Energy, Elsevier, vol. 260(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:887-:d:211866. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.