A Multiple Model Predictive Control for Maximum Energy Extraction from Variable Speed Wind Power Systems

Authors

ferdowsi university of mashad

Abstract

Due to concerns about the environment pollution caused by the burning of fossil fuels, and its continually diminishing reserves, the use of wind power for generating electricity has been increasing over last few decades. Nowadays, controller design for a variable speed wind turbine is one of the most challenges for engineers. In this paper, a control strategy based on multiple model predictive control techniques for the control of variable speed wind turbines in the below rated wind speed regime is proposed. In this region control objectives are mainly to maximize energy capture, and to reduce dynamic loads. This has the effect of increasing the efficiency and the lifetime of the wind energy conversion system (WECS). Furthermore, in this control structure the constraints on the system variables in the controller design are considered and a multiple model structure to deal with the nonlinearities in the system is used. A 2MW wind turbine is considered to show the good performances brought by the proposed approach by presenting and discussing the simulation results.

Keywords

References

[1]    Lucy Y. Pao and Kathryn E. Johnson , “A Tutorial on the Dynamics and Control of Wind Turbines and Wind Farms”, American Control Conference, June pp. 10-12, 2009.
[2]   Yazhou Lei, Alan Mullane, Gordon Lightbody, and Robert Yacamini, “Modeling of the Wind Turbine With a Doubly Fed Induction Generator for Grid Integration Studies”, IEEE Transactions on Energy Conversion, Vol. 21, No. 1, pp. 257-264,  March 2006.
[3]   A. Mirecki, X. Roboam, F. Richardeau, “Comparative Study of Maximum Power Strategy in Wind Turbines”, Industrial Electronics, IEEE, 2004. 
[4]   Quincy Wang, , and Liuchen Chang, “An Intelligent Maximum Power Extraction Algorithm for Inverter-Based Variable Speed Wind Turbine Systems”, IEEE Transactions on Power Electronics, Vol. 19, No. 5, pp. 1242-1249, September 2004.
[5]   R. Esmaili, L. Xu, and D. K. Nichols ,” A New Control Method of Permanent Magnet Generator for Maximum Power Tracking in Wind Turbine Application” , Power Engineering Society General Meeting, IEEE, 2005.
[6]   A. Miller, E. Muljadi and D. S. Zinger, "A variable speed wind turbine power control," IEEE Transacton on Energy Convers, Vol. 12, 1997.
[7]   P. Novak, T. Ekelund, I. Jovik and B. Schmidtbauer, "Modeling and control of variable-speed wind-turbine drive-system dynamics," IEEE Control Syst. Mag., Vol. 15, pp. 28-38, 08. 1995.
[8]   Xuemei Zheng, Lin Li, Dianguo Xu, Jim Platts, “Sliding Mode MPPT Control of Variable Speed Wind Power System”, 978-1-4244-2487-0, IEEE, 2009.
[9]   Nadhira Khezami, Naceur Benhadj Braiek Xavier Guillaud,  “Wind turbine power tracking using an improved multimodel quadratic approach”. ISA Transactions 49, pp. 326-334, 2010.
[10]  M.Soliman, O.P.Malik, D.T.Westwick, “Multiple Model Predictive Control for Wind Turbines with Doubly Fed Induction Generators”, IEEE Transactions on Sustainable Energy, Vol. 2, No. 3, pp. 215-225, 2011.
[11]  Eduardo F.Camacho, Carlos Bordons, “Model Predictive Control”, Springer, 1999.
[12]  A. Bemporad, M. Morari and N.L. Ricker, “Model Predictive Control Toolbox, for Use with MATLAB”. The Mathworks, 2005.
[13]  Boštjan Pregelj, and Samo Gerkšic, “Multiple Model Approach to Multi-Parametric Model Predictive Control of a Nonlinear Process – simulation case study, http://as.utia.cas.cz/files/113.pdf, 2006.
[14]  Francesco Borrelli, Manfred Morari, "Offset Free Model Predictive Control", Proceedings of the 46th IEEE Conference on Decision and Control, New Orleans, LA, USA, 2007.
 

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History

  • Receive Date: 23 November 2016
  • Revise Date: 18 January 2017
  • Accept Date: 23 November 2016

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