Control inteligente para optimizar la extracción de potencia y reducir vibraciones en sistemas eólicos offshore
- Muñoz Palomeque, Eduardo 1
- Sierra García, Jesús Enrique 1
- Santos, Matilde 2
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1
Universidad de Burgos
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2
Universidad Complutense de Madrid
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- Ramón Costa Castelló (coord.)
- Manuel Gil Ortega (coord.)
- Óscar Reinoso García (coord.)
- Luis Enrique Montano Gella (coord.)
- Carlos Vilas Fernández (coord.)
- Elisabet Estévez Estévez (coord.)
- Eduardo Rocón de Lima (coord.)
- David Muñoz de la Peña Sequedo (coord.)
- José Manuel Andújar Márquez (coord.)
- Luis Payá Castelló (coord.)
- Alejandro Mosteo Chagoyen (coord.)
- Raúl Marín Prades (coord.)
- Vanesa Loureiro-Vázquez (coord.)
- 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.