Fault-tolerant economic model predictive control for wind turbines
Résumé
The operational cost of wind turbines (WT) is remarkably incurred in fatigue loads induced by torsional vibration within the drive-train subsystem and fore-aft bending of the tower subsystem. Under closed-loop control configuration, actuator faults in pitch subsystem and converter subsystem proliferate these fatigue loads, thereby, severely affect the economic operation of WT. In this paper, we present a novel active fault-tolerant control(FTC) methodology for WT, which minimizes the economic cost of WT by achieving the two broad objectives: power maximization and fatigue reduction, possibly under the effect of torque bias faults in converters. The proposed FTC system is composed of two modules: fault diagnosis(FD),and controller reconfiguration (CR). We develop the CR module using a model-predictive control(MPC) technique where the primary issue is that the constraint set is not convex in decision variables. The novelty of the proposed scheme lies in transforming the original non-convex optimization problem into a convex problem using some new decision variables. We also develop the FD module using an unknown-input-residual generator and a suitably designed estimation filter to extract the complete information of the fault. This fault information is subsequently used to reconfigure in real-time the constraints of the MPC to ensure system availability. The effectiveness of the developed scheme is demonstrated on a 2MW WT system.