Intelligent Fuzzy Optimized Control for Energy Extraction in Large Wind Turbines

  1. Carlos Serrano-Barreto 1
  2. Matilde Santos 1
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Libro:
Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference: Guimarães, Portugal; November 4–6, 2020. Proceedings
  1. Cesar Analide (ed. lit.)
  2. Paulo Novais (ed. lit.)
  3. David Camacho (ed. lit.)
  4. Hujun Yin (ed. lit.)

Editorial: Springer International Publishing AG

ISBN: 978-3-030-62362-3,  978-3-030-62361-6,  978-3-030-62364-7,  978-3-030-62365-4

Año de publicación: 2020

Título del volumen: Part II

Volumen: 2

Páginas: 269-276

Congreso: Intelligent Data Engineering and Automated Learning – IDEAL (21. 2020. Guimarães)

Tipo: Aportación congreso

DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

In this paper an intelligent controller is designed to obtain themaximum power of a large floating offshore wind turbine. The control of these turbines is more complex due to the strong loads they are subjected to and the uncertainty that comes from the environment, mainly wind and waves, and from its non-linear dynamics. In this case, the control goal is tomaximize the output power of the wind turbine by controlling the rotor speed. An incremental PD-type fuzzy controller has been implemented; it generates the pitch angle reference. The performance of this control scheme on the NREL 5 MW floating offshore wind turbine has been compared with the internal control that is provided within the FAST software. Results are encouraging, showing that the intelligent control strategy is able to produce more energy.

Fuente de los datos: Dialnet