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Model Predictive Control of a Wind Turbine


A. Jain

Semester Thesis, FS13 (10250)

In solving the challenges of increasing demands for renewable energy, wind power continues to show its dominance. Thus, maximizing power while still being able to produce it at an economical price remain important topics of research. This prompts for efficient active control systems for the wind turbines. This report investigates the efficacy of linear Model Predictive Control (MPC) in achieving this objective in comparison to a conventional controller. MPC has been implemented in closed loop with a nonlinear 3-bladed, horizontal axis, variable speed wind turbine model. The formulation uses a linearized plant model at each time step; the linearization calculated depending upon the prediction of wind disturbance at that step. Tuning of MPC is also discussed with respect to the problem at hand. The performance of this controller is compared to a torque based controller in region 2 and a PID controller in region 3. The eff ect of varying quality of wind predictions on MPC performance has also been studied. In region 2, MPC doesn't o ffer any signifi cant advantages. In region 3, MPC with perfect preview has been validated to perform better, both in power maximization and reduction in drivetrain twist, which is also a implicit measure of cost of wind power. MPC without preview delivers comparable performance to a PID controller in achieving these objectives.


Type of Publication:

(13)Semester/Bachelor Thesis

G. Schildbach

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2013:IFA_4628
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