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Hybrid Intelligent Control for Maximum Power Point Tracking of a Floating Wind Turbine

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Hybrid Artificial Intelligent Systems (HAIS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14001))

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Abstract

Floating Offshore Wind Turbines (FOWTs) are surrounded by an environment with random phenomena (wind and waves) that disturb the ideal operation of these devices. In addition, its non-linear dynamics make the control of power generation more complex. In order to face these disturbances, achieving the maximum energy production and reducing as much as possible the vibrations of the turbine, in this work a control action is designed and applied in the Maximum Power Point Tracking (MPPT) operation region of a 5MW FOWT. A hybrid control architecture composed of intelligent and conventional regulators is defined. The intelligent controller is an unsupervised radial basis function neural network (RBNN), which is responsible for adjusting the electromagnetic torque to achieve optimal speed and power output. The conventional controller that complements the NN is a PID that seeks to reduce the movements of the tower. This control approach is incorporated into the Direct Speed Control (DSC) framework which determines the reference speed to follow. Control parameters have been optimized using genetic algorithms. This hybrid methodology is validated against the OpenFAST software torque control strategy, providing greater efficiency in terms of better power generation and vibration reduction.

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Acknowledgments

This work has been partially supported by the Spanish Ministry of Science and Innovation under project MCI/AEI/FEDER number PID2021-123543OB-C21.

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Authors and Affiliations

  1. Systems Engineering and Automation, University of Burgos, Burgos, Spain

    Eduardo Muñoz-Palomeque & J. Enrique Sierra-García

  2. Institute of Knowledge Technology, Complutense University of Madrid, Madrid, Spain

    Matilde Santos

Authors
  1. Eduardo Muñoz-Palomeque
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  2. J. Enrique Sierra-García
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  3. Matilde Santos
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Corresponding author

Correspondence to Eduardo Muñoz-Palomeque .

Editor information

Editors and Affiliations

  1. University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of Leon, León, Spain

    Hilde Pérez García

  3. University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  4. Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  5. Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  6. University of Burgos, Burgos, Spain

    Álvaro Herrero

  7. University of A Coruña, Ferrol - Coruña, Spain

    José Luis Calvo Rolle

  8. University of A Coruña, Ferrol - Coruña, Spain

    Héctor Quintián

  9. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Muñoz-Palomeque, E., Sierra-García, J.E., Santos, M. (2023). Hybrid Intelligent Control for Maximum Power Point Tracking of a Floating Wind Turbine. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_42

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  • DOI: https://doi.org/10.1007/978-3-031-40725-3_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-40724-6

  • Online ISBN: 978-3-031-40725-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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