Offset-Free Model Predictive Control for Wind Power Generation Systems

Xiao Lan Wang; Li Sha Ye

doi:10.4028/www.scientific.net/AMR.724-725.495

Paper Titles

Development of a Wind Power Generation Experiment Device
p.476

Improve the Forecast of Surface-Layer Wind in Wind Power Farm with WRF-3DVAR
p.480

Mechanism of Large Scale Cascading Trip-Off of Wind Turbine Generators
p.485

Modeling and Simulation of the Brushless Double Rotor Motor for the Novel Wind Power Generation System
p.491

Offset-Free Model Predictive Control for Wind Power Generation Systems
p.495

Study on Different Impacts on the Reliability of Grid Connecting with the Offshore and Onshore Wind Farms
p.501

The Dynamic Interactional Model of SVC and DFIG to Maintain Grid Voltage
p.506

The Wind Power Industry in China: Status and Issues
p.512

Vibration Analysis on the Megawatt-Class Wind Turbine Based on the Rigid-Flexible Coupling Model
p.517

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 724-725Offset-Free Model Predictive Control for Wind...

Offset-Free Model Predictive Control for Wind Power Generation Systems

Abstract:

Due to wind power generation system (WGS) is strongly nonlinear, multi-input multi-output and with high turbulent disturbance, we build a offset-free model considering system noise and measurement noise and its predictive controller for all operating area from cut-in speed to the cut-out wind speed. Finally we predict the optimum generator torque and pitch control signal. By add damping mode in drive train using torque control, the purpose of smoother power and less torsional torque pulsation on drive train are achieved. Simulation results shows that this predictive controller is able to reduce the impact of noise and interference on the system, ensuring constant power output and reducing the torque pulsation.

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Periodical:

Advanced Materials Research (Volumes 724-725)

Pages:

495-500

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.724-725.495

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Online since:

August 2013

Authors:

Xiao Lan Wang, Li Sha Ye

Keywords:

Multiple Model, Predictive Control, State Space, Torque Pulsation, Wind Power Generation

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References

[1] Shridhar Rahul, Cooper, Douqlas J. Tuning strategy for unconstrained multivariable model predictive control. Industrial and Engineering Chemistry Research, v 37, n 10, pp.4003-4016, Oct 1998.

DOI: 10.1021/ie980202s

Google Scholar

[2] Wei Wang.. A Direct Method of Generalized Predictive Adaptive Control. Acta Automatica Sinica.1996, 22(3), pp.270-277. (In Chinese).

Google Scholar

[3] N. Nanayakkara, M. Nakamura, H. Hatazaki. Predictive control of wind turbines in small power system at high turbulent wind speeds. Control Eng. Practice, 1997, Vol. 5, No. 8, pp.1063-1069.

DOI: 10.1016/s0967-0661(97)00097-x

Google Scholar

[4] N.P.G van Deelen, A. Jokic, et. Exploiting inertia of wind turbines in power network frequency control: a model predictive control approach. IEEE International Conference on Control Applications, USA, September 28-30, 2011.

DOI: 10.1109/cca.2011.6044490

Google Scholar

[5] Damien Castaignet, Niels K. Poulsen, Thomas Buhl& Jens Jakob Wedel-Heinen. Model Predictive Control of Trailing Edge Flaps on a Wind Turbine blade. 2011 American Control Conference San Francisco, CA, USA, 2011.

DOI: 10.1109/acc.2011.5991111

Google Scholar

[6] Alan D. Wright. Modern Control Design for Flexible Wind Turbines. Springfield: U.S. Department of Energy Office of Energy Efficiency and Renewable Energy, 2004.

Google Scholar

[7] J. Jonkman, S. Butterfield, et al．Definition of a 5-MW Reference Wind Turbine for Offshore System Development. Technical Report NREL/TP-500-3- 8060 February 2009.

DOI: 10.2172/947422

Google Scholar