Control inteligente para optimizar la extracción de potencia y reducir vibraciones en sistemas eólicos offshore

  1. Muñoz Palomeque, Eduardo 1
  2. Sierra García, Jesús Enrique 1
  3. Santos, Matilde 2
  1. 1 Universidad de Burgos
    info

    Universidad de Burgos

    Burgos, España

    ROR https://ror.org/049da5t36

  2. 2 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Llibre:
XLIV Jornadas de Automática: libro de actas: Universidad de Zaragoza, Escuela de Ingeniería y Arquitectura, 6, 7 y 8 de septiembre de 2023, Zaragoza
  1. Ramón Costa Castelló (coord.)
  2. Manuel Gil Ortega (coord.)
  3. Óscar Reinoso García (coord.)
  4. Luis Enrique Montano Gella (coord.)
  5. Carlos Vilas Fernández (coord.)
  6. Elisabet Estévez Estévez (coord.)
  7. Eduardo Rocón de Lima (coord.)
  8. David Muñoz de la Peña Sequedo (coord.)
  9. José Manuel Andújar Márquez (coord.)
  10. Luis Payá Castelló (coord.)
  11. Alejandro Mosteo Chagoyen (coord.)
  12. Raúl Marín Prades (coord.)
  13. Vanesa Loureiro-Vázquez (coord.)
  14. Pedro Jesús Cabrera Santana (coord.)

Editorial: Servizo de Publicacións ; Universidade da Coruña

ISBN: 9788497498609

Any de publicació: 2023

Pàgines: 174-179

Congrés: Jornadas de Automática (44. 2023. Zaragoza)

Tipus: Aportació congrés

Resum

This research analyzes the performance of a hybrid control strategy in the maximum power point tracking (MPPT) region and the effect on structural vibration reduction in a 5MW floating offshore wind turbine (FOWT). In these wind systems, different disturbance sources influence the stability of the wind turbine. These elements that alter the efficient operation of the wind turbine, include the non-linear nature of the machine, turbulent winds, and waves that change the structural stability of the device. The controller in this study uses an adaptive radial basis function neural network (RBNN) to regulate the electromagnetic torque, which influences the speed and output power. In addition, this torque is complemented by incorporating a conventional PID control that focuses on reducing the tower motion. The controller is optimized with the use of a genetic algorithm. The performance of the controller is validated against the OpenFast torque controller, achieving a higher output power and at the same time a decrease in the effect of vibrations.