Wind turbine control based on a modified model predictive control scheme for linear parameter-varying systems

Abdelrahman Morsi; Hossam S. Abbas; Abdelfatah M. Mohamed

Wind turbine control based on a modified model predictive control scheme for linear parameter-varying systems

View Fulltext

Author(s): Abdelrahman Morsi¹ ; Hossam S. Abbas¹ ; Abdelfatah M. Mohamed^{1, 2}
- Affiliations: 1: Electrical Engineering Department , Assuit University , Assuit , Egypt ;
  2: Mechatronic and Robotics Department , Egypt and Japan University of Science and Technology , Alexandria , Egypt
Source: Volume 11, Issue 17, 24 November 2017, p. 3056 – 3068
DOI: 10.1049/iet-cta.2017.0426 , Print ISSN 1751-8644, Online ISSN 1751-8652

Received 24/04/2017, Accepted 27/08/2017, Revised 02/08/2017, Published 30/08/2017

This study presents a successful application of a model predictive control (MPC) design approach based on linear parameter-varying (LPV) models subject to input/output constraints to control a utility-scale wind turbine. The control objectives are to allow the wind turbine to extract from the wind the rated power taking into account the wind speed variation, to reduce mechanical loads and power fluctuations and to guarantee the stability of the system for the whole range of operation. A modified min–max MPC-LPV scheme is proposed to compute online the optimal control input at each sampling instant by solving an optimisation problem subject to linear matrix inequality constraints. To reduce the conservatism of the original MPC scheme due to the overbounding associated with affine parameter-dependence, the full block S-procedure with a linear fractional transformation formulation is used. The performance and the efficiency of the proposed MPC-LPV algorithm is validated via simulation and compared with the original scheme and other conventional controllers.

References

1. 1)
  - 29. Hoffmann, C., Hashemi, S.M., Abbas, H.S., et al: ‘Synthesis of LPV controllers with low implementation complexity based on a reduced parameter set’, IEEE Trans. Control Syst. Technol., 2014, 22, (6), pp. 2393–2398.
2. 2)
  - 30. Bianchi, F.D., Battista, H., Mantz, R.J.: ‘Wind turbine control systems: principles, modelling and gain scheduling design’ (Springer-Verlag, London, 2007).
3. 3)
  - 27. Harris, M., Hand, M., Wright, A.: ‘LIDAR for turbine control’. Technical report, National Renewable Energy Laboratory, 2006.
4. 4)
  - 22. Abbas, H.S., Ali, A., Hashemi, S.M., et al: ‘LPV state-feedback control of a control moment gyroscope’, Control Eng. Pract., 2014, 24, pp. 129–137.
5. 5)
  - 21. Rugh, W.J., Shamma, J.S.: ‘Research on gain scheduling’, Automatica, 2000, 36, (10), pp. 1401–1425.
6. 6)
  - 5. Hwas, A., Katebi, R.: ‘Wind turbine control using PI pitch angle controller’. Proc. of IFAC Conf. Advances in PID Control, Brescia, Italy, 2012.
7. 7)
  - 10. Boukhezzar, B., Lupu, H., Siguerdidjane, L., et al: ‘Multivariable control strategy for variable speed, variable pitch wind turbines’, Renew. Energy, 2007, 32, (8), pp. 1273–1287.
8. 8)
  - 6. Wright, A.D., Fingersh, L.J.: ‘Advanced control design for wind turbines Part I: control design, implemenation, and initial tests’. NREL Report, No. Tp-500-42437, National Renewable Energy Laboratory, 2008.
9. 9)
  - 8. Boukhezzar, B., Siguerdidjane, H.: ‘Nonlinear control of variable speed wind turbines without wind speed measurement’. Proc. of the 44th IEEE Conf. Decision and Control, and the European Control Conf., Seville, Spain, December 2005.
10. 10)
  - 20. Lu, Y., Arkun, Y.: ‘Quasi-min-max MPC algorithms for LPV systems’, Automatica, 2000, 36, (4), pp. 527–540.
11. 11)
  - 18. Soliman, M., Malik, O.P., Westwich, D.T.: ‘Multiple model MIMO predictive control for variable speed pitch wind turbines’. Proc. of the IEEE American Control Conf., Baltimore, MD, USA, 2010, pp. 2778–2784.
12. 12)
  - 1. European Wind Energy Association (EWEA), Wind Energy – The Facts, a Guide to the Technology, Economics and Future of Wind Power, Brussels, Belgium. Available at: www.wind-energy-the-facts.org. [last accessed in May 2016].
13. 13)
  - 9. Burkart, R., Margellos, K., Lygeros, J.: ‘Nonlinear control of wind turbines: an approach based on switched linear systems and feedback linearization’. Proc. of the 50th IEEE Conf. Decision and Control and European Control Conf., Orland, FL, USA, 2011, pp. 5485–5490.
14. 14)
  - 3. Bossanyi, E.A.: ‘The design of closed loop controllers for wind turbines’, Wind Energy, 2000, 3, pp. 149–163.
15. 15)
  - 28. Tóth, R.: ‘Modeling and identification of linear parameter- varying systems’ (Springer Science and Business Media, 2010), vol. 403.
16. 16)
  - 23. Abbas, H.S., Tóth, R., Meskin, N., et al: ‘A robust MPC for input-output LPV models’, IEEE Trans. Autom. Control, 2016, PP, (99), pp. 1–1.
17. 17)
  - 14. Lio, W.H., Rossiter, J.A., Jones, B.L.: ‘A review on applications of model predictive control to wind turbines’. Proc. of the UKACC Int. Conf. in Control, Loughborough, 2014, pp. 673–678.
18. 18)
  - 11. Beltran, B., Ali, T.A., Benbouzid, M.: ‘Sliding mode power control of variable-speed wind energy conversion systems’, IEEE Trans. Energy Convers., 2008, 23, (2), pp. 551–558.
19. 19)
  - 31. Besselmann, T., Löfberg, J., Morari, M.: ‘Explicit MPC for LPV systems: stability and optimality’, IEEE Trans. Autom. Control, 2012, 57, (9), pp. 2322–2332.
20. 20)
  - 13. Maciejowski, J.: ‘Predictive control with constraints’ (Prentice-Hall, 2000).
21. 21)
  - 33. Control System Toolbox, the MathWorks, R2013b.
22. 22)
  - 12. Rubio, J.O.M., Aguilar, L.T.: ‘Maximizing the performance of variable speed wind turbine with nonlinear output feedback control’, Procedia Eng., 2012, 35, pp. 31–40.
23. 23)
  - 19. Soltani, M., Wisniewski, R., Brath, P., et al: ‘Load reduction of wind turbines using receding horizon control’. Proc. of the IEEE Int. Conf. Control Applications, Denver, CO, USA, 2011, pp. 852–857.
24. 24)
  - 4. Bossanyi, E.A.: ‘Wind turbine control for load reduction’, Wind Energy, 2003, 6, (3), pp. 229–244.
25. 25)
  - 16. Morsi, A., Abbas, H.S., Mohamed, A.M.: ‘Model predictive control of a wind turbine based on linear parameter-varying models’. Proc. of the IEEE Multi-Conf. Systems and Control, Sydney, Australia, 2015, pp. 318–323.
26. 26)
  - 32. Kouvaritakis, B., Rossiter, J.A., Schuurmans, J.: ‘Efficient robust predictive control’, IEEE Trans. Autom. Control, 2000, 45, (8), pp. 1545–1549.
27. 27)
  - 17. Mirzaei, M., Poulsen, N.K., Niemann, H.H.: ‘Robust model predictive control of a wind turbine’. Proc. of the IEEE American Control Conf., Montreal, QC, 2012, pp. 4393–4398.
28. 28)
  - 26. Scherer, C.W.: ‘LPV control and full block multipliers’, Automatica, 2001, 37, (3), pp. 361–375.
29. 29)
  - 24. Mirzaei, M., Poulsen, N.K., Niemann, H.H.: ‘Model predictive control of a nonlinear system with known scheduling variable’. Proc. of the 17th Nordic process Control Workshop, 2012, pp. 163–168.
30. 30)
  - 25. Apkarian, P., Adams, R.J.: ‘Advanced gain-scheduling techniques for uncertain systems’, IEEE Trans. Control Syst. Technol., 1997, 6, pp. 21–32.
31. 31)
  - 2. Thomsen, S.: ‘Nonlinear control of a wind turbine’. Master's thesis, Technical University of Denmark, 2006.
32. 32)
  - 7. Rocha, R., Martins Filho, L., Bortolus, M.: ‘Optimal multivariable control for wind energy conversion system - a comparison between h2 and h1 controllers’. Proc. of the IEEE Control and Decision Conf. and European Control Conf., 2005, pp. 7906–7911.
33. 33)
  - 15. Henriksen, L.: ‘Model predictive control of a wind turbine’. Master's thesis, Technical University of Denmark, 2007.

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Wind turbine control based on a modified model predictive control scheme for linear parameter-varying systems

References

Related content