Data-driven fatigue-oriented MPC applied to wind turbines Individual Pitch Control

David Collet (1, 2) , Mazen Alamir (2) , Domenico Di Domenico (1) , Guillaume Sabiron (1)

1 IFPEN - IFP Energies nouvelles
2 GIPSA-MODUS - GIPSA - Modelling and Optimal Decision for Uncertain Systems

Horizontal Axis Wind Turbine (HAWT) rotor is a system whose components are particularly exposed to fatigue damage, due to non-uniform winds and the rotating nature of the rotor. Individual Pitch Control (IPC) can help alleviating the fatigue loads on the rotor blades by rotating the blades independently from each other on their longitudinal axis. However, reducing the blades fatigue damage is often compensated by an increase in pitch activity, damaging the blade pitch actuators. An IPC regulator must thus optimize a trade-off between the fatigue damage of the blades and blade pitch actuators. This paper presents the derivation and implementation of a fatigue-oriented adaptive Model Predictive Control (MPC) IPC regulator using a data-driven fatigue-oriented cost function. This MPC allows to efficiently optimize the IPC fatigue trade-off and significantly reduce the expectancy of an HAWT rotor economic fatigue cost, compared to a finely tuned non-adaptive MPC. The methodology used for the derivation of the presented MPC allows to efficiently reduce an economic fatigue cost, while limiting the sensitivity to controller tuning.

Mots clés: Fatigue; Optimal control; Model Predictive Control; Individual Pitch Control

Domaines: Ingénierie de l'environnement

David Collet, Mazen Alamir, Domenico Di Domenico, Guillaume Sabiron. Data-driven fatigue-oriented MPC applied to wind turbines Individual Pitch Control. Renewable Energy, 2021, 170, pp.1008-1019. ⟨10.1016/j.renene.2021.02.052⟩. ⟨hal-03169150⟩