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Hybrid Neural Fuzzy Design-Based Rotational Speed Control of a Tidal Stream Generator Plant

Author

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  • Khaoula Ghefiri

    (Laboratory of Research in Automatic Control—LA.R.A, National Engineering School of Tunis (ENIT), University of Tunis El Manar, BP 37, Le Belvédère, 1002 Tunis, Tunisia
    Automatic Control Group—ACG, Department of Automatic Control and Systems Engineering, Engineering School of Bilbao, University of the Basque Country, 48012 Bilbao, Spain)

  • Izaskun Garrido

    (Automatic Control Group—ACG, Department of Automatic Control and Systems Engineering, Engineering School of Bilbao, University of the Basque Country, 48012 Bilbao, Spain)

  • Soufiene Bouallègue

    (Laboratory of Research in Automatic Control—LA.R.A, National Engineering School of Tunis (ENIT), University of Tunis El Manar, BP 37, Le Belvédère, 1002 Tunis, Tunisia)

  • Joseph Haggège

    (Laboratory of Research in Automatic Control—LA.R.A, National Engineering School of Tunis (ENIT), University of Tunis El Manar, BP 37, Le Belvédère, 1002 Tunis, Tunisia)

  • Aitor J. Garrido

    (Automatic Control Group—ACG, Department of Automatic Control and Systems Engineering, Engineering School of Bilbao, University of the Basque Country, 48012 Bilbao, Spain)

Abstract

Artificial Intelligence techniques have shown outstanding results for solving many tasks in a wide variety of research areas. Its excellent capabilities for the purpose of robust pattern recognition which make them suitable for many complex renewable energy systems. In this context, the Simulation of Tidal Turbine in a Digital Environment seeks to make the tidal turbines competitive by driving up the extracted power associated with an adequate control. An increment in power extraction can only be archived by improved understanding of the behaviors of key components of the turbine power-train (blades, pitch-control, bearings, seals, gearboxes, generators and power-electronics). Whilst many of these components are used in wind turbines, the loading regime for a tidal turbine is quite different. This article presents a novel hybrid Neural Fuzzy design to control turbine power-trains with the objective of accurately deriving and improving the generated power. In addition, the proposed control scheme constitutes a basis for optimizing the turbine control approaches to maximize the output power production. Two study cases based on two realistic tidal sites are presented to test these control strategies. The simulation results prove the effectiveness of the investigated schemes, which present an improved power extraction capability and an effective reference tracking against disturbance.

Suggested Citation

  • Khaoula Ghefiri & Izaskun Garrido & Soufiene Bouallègue & Joseph Haggège & Aitor J. Garrido, 2018. "Hybrid Neural Fuzzy Design-Based Rotational Speed Control of a Tidal Stream Generator Plant," Sustainability, MDPI, vol. 10(10), pages 1-26, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3746-:d:176362
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    References listed on IDEAS

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    1. Khaoula Ghefiri & Soufiene Bouallègue & Izaskun Garrido & Aitor J. Garrido & Joseph Haggège, 2017. "Complementary Power Control for Doubly Fed Induction Generator-Based Tidal Stream Turbine Generation Plants," Energies, MDPI, vol. 10(7), pages 1-23, June.
    2. Fernández, Luis M. & Jurado, Francisco & Saenz, José Ramón, 2008. "Aggregated dynamic model for wind farms with doubly fed induction generator wind turbines," Renewable Energy, Elsevier, vol. 33(1), pages 129-140.
    3. Zhou, Zhibin & Benbouzid, Mohamed & Frédéric Charpentier, Jean & Scuiller, Franck & Tang, Tianhao, 2013. "A review of energy storage technologies for marine current energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 390-400.
    4. Rizzo, Santi Agatino & Scelba, Giacomo, 2015. "ANN based MPPT method for rapidly variable shading conditions," Applied Energy, Elsevier, vol. 145(C), pages 124-132.
    5. Segura, E. & Morales, R. & Somolinos, J.A. & López, A., 2017. "Techno-economic challenges of tidal energy conversion systems: Current status and trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 536-550.
    6. Myers, L. & Bahaj, A.S., 2005. "Simulated electrical power potential harnessed by marine current turbine arrays in the Alderney Race," Renewable Energy, Elsevier, vol. 30(11), pages 1713-1731.
    7. Bryden, Ian G. & Couch, Scott J., 2006. "ME1—marine energy extraction: tidal resource analysis," Renewable Energy, Elsevier, vol. 31(2), pages 133-139.
    8. Bahaj, A.S. & Molland, A.F. & Chaplin, J.R. & Batten, W.M.J., 2007. "Power and thrust measurements of marine current turbines under various hydrodynamic flow conditions in a cavitation tunnel and a towing tank," Renewable Energy, Elsevier, vol. 32(3), pages 407-426.
    9. 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.
    10. Kalogirou, Soteris A., 2001. "Artificial neural networks in renewable energy systems applications: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 5(4), pages 373-401, December.
    11. Marzband, Mousa & Azarinejadian, Fatemeh & Savaghebi, Mehdi & Pouresmaeil, Edris & Guerrero, Josep M. & Lightbody, Gordon, 2018. "Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations," Renewable Energy, Elsevier, vol. 126(C), pages 95-106.
    12. Grabbe, Mårten & Lalander, Emilia & Lundin, Staffan & Leijon, Mats, 2009. "A review of the tidal current energy resource in Norway," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1898-1909, October.
    13. Bilgili, Mehmet & Sahin, Besir & Yasar, Abdulkadir, 2007. "Application of artificial neural networks for the wind speed prediction of target station using reference stations data," Renewable Energy, Elsevier, vol. 32(14), pages 2350-2360.
    14. Dounis, Anastasios I. & Kofinas, Panagiotis & Alafodimos, Constantine & Tseles, Dimitrios, 2013. "Adaptive fuzzy gain scheduling PID controller for maximum power point tracking of photovoltaic system," Renewable Energy, Elsevier, vol. 60(C), pages 202-214.
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    1. Khaoula Ghefiri & Aitor J. Garrido & Eugen Rusu & Soufiene Bouallègue & Joseph Haggège & Izaskun Garrido, 2018. "Fuzzy Supervision Based-Pitch Angle Control of a Tidal Stream Generator for a Disturbed Tidal Input," Energies, MDPI, vol. 11(11), pages 1-21, November.
    2. Ramin Alipour & Roozbeh Alipour & Seyed Saeid Rahimian Koloor & Michal Petrů & Seyed Alireza Ghazanfari, 2020. "On the Performance of Small-Scale Horizontal Axis Tidal Current Turbines. Part 1: One Single Turbine," Sustainability, MDPI, vol. 12(15), pages 1-25, July.

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