A robust individual pitch control strategy is presented to deal with periodic load disturbances on wind turbines under operating point variation. The asymmetric loads are mainly caused by the tower shadow and wind shear effects. Multi-blade coordinate (MBC) transformation is utilized to model the turbine dynamics under various operating points. The coupling dynamics of the multi-input multi-output (MIMO) system are considered to reveal high harmonic frequency peak reduction. The stability and robustness performance of the system under uncertainties are guaranteed by robust control design. The performance of the synthesized controller is compared with a collective controller and a PI individual controller. The results show significant load mitigation in periodic frequencies.
For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.
In this research, a disturbance observer based (DOB) control scheme is illustrated to reject the unknown low frequency disturbances to wind turbines. Specifically, we aim at maintaining the constant output power but achieving better generator speed regulation when the wind turbine is operated at time-varying and turbulent wind field. The disturbance observer combined with a filter is designed to asymptotically reject the persistent unknown time-varying disturbances. The proposed algorithm is tested in both linearized and nonlinear NREL offshore 5-MW baseline wind turbine. The application of this DOB pitch controller achieves improved power and speed regulation in Region 3 compared with a baseline gain scheduling PID collective controller both in linearized and nonlinear plant.
In this research, model reference adaptive control is examined for the pitch control of wind turbines that may suffer from reduced life owing to extreme loads and fatigue when operated under a high wind speed. Specifically, we aim at making a trade-off between the maximum energy captured and the load induced. The adaptive controller is designed to track the optimal generator speed and at the same time to mitigate component loads under turbulent wind field and other uncertainties. The proposed algorithm is tested on the NREL offshore 5-MW baseline wind turbine, and its performance is compared with that those of the gain scheduled proportional integral (GSPI) control and the disturbance accommodating control (DAC). The results show that the blade root flapwise load can be reduced at a slight expense of optimal power output. The generator speed regulation under adaptive controller is better than DAC.