Wind Turbine Pitch Control First Approach Based on Reinforcement Learning
- J. Enrique Sierra-García 1
- Matilde Santos 2
-
1
Universidad de Burgos
info
-
2
Universidad Complutense de Madrid
info
- Cesar Analide (ed. lit.)
- Paulo Novais (ed. lit.)
- David Camacho (ed. lit.)
- 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
Any de publicació: 2020
Títol del volum: Part II
Volum: 2
Pàgines: 260-268
Congrés: Intelligent Data Engineering and Automated Learning – IDEAL (21. 2020. Guimarães)
Tipus: Aportació congrés
Resum
The control strategy defined for a wind turbine (WT) aims to achieve the highest energy efficiency and at the same time to ensure safe operation under all wind conditions. The goal of the pitch control of a WT is to stabilize the output power around its nominal (rated) value by means of the position of the rotor blades with respect to the wind. In this work, a pitch control strategy based on reinforcement learning (RL) is proposed. The control system consists of a state estimator, a reward mechanism, a policy table and policy update algorithm. Different reward strategies and policy update algorithms for the RL controller have been tested and compared with a PID regulator. The proposed controller stabilizes the output power of the wind turbine around the rated power more accurately and with smaller overshoot than the traditional one.
Els documents de l'Observatori s'actualitzen diàriament. Aquesta data fa referència a l'actualització de la informació relacionada amb l'estructura de l'Observatori (persones, grups d'investigació, unitats organitzatives, projectes, etc.).