Journal of Power Electronics

The Korean Institute of Power Electronics (전력전자학회)
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Design and Experimental Validation of a Digital Predictive Controller for Variable-Speed Wind Turbine Systems

  • Babes, Badreddine (Automatic Laboratory of Setif (LAS), Department of Electrical Engineering, University of Setif 1) ;
  • Rahmani, Lazhar (Automatic Laboratory of Setif (LAS), Department of Electrical Engineering, University of Setif 1) ;
  • Chaoui, Abdelmadjid (Laboratory of Power Quality in Electrical Networks (QUERE), University of Setif 1) ;
  • Hamouda, Noureddine (Laboratory of Electrical Engineering of Constantine, University of Mentouri Brothers)
  • Received : 2016.07.30
  • Accepted : 2016.11.21
  • Published : 2017.01.20
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Abstract

Advanced control algorithms must be used to make wind power generation truly cost effective and reliable. In this study, we develop a new and simple control scheme that employs model predictive control (MPC), which is used in permanent magnet synchronous generators and grid-connected inverters. The proposed control law is based on two points, namely, MPC-based torque-current control loop is used for the generator-side converter to reach the maximum power point of the wind turbine, and MPC-based direct power control loop is used for the grid-side converter to satisfy the grid code and help improve system stability. Moreover, a simple prediction scheme is developed for the direct-drive wind energy conversion system (WECS) to reduce the computation burden for real-time applications. A small-scale WECS laboratory prototype is built and evaluated to verify the validity of the developed control methods. Acceptable results are obtained from the real-time implementation of the proposed MPC methods for WECS.

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References

  1. A. Beddar, H. Bouzekri, B. Babes, and H. Afghoul, "Experimental enhancement of fuzzy fractional order PI+I controller of grid connected variable speed wind energy conversion system," Energy Conversion and Management, Vol. 123, pp.569-580, Sep. 2016. https://doi.org/10.1016/j.enconman.2016.06.070
  2. R. Melicio, V. M. F. Mendes, and J. P. S. Catalao, "Power converter topologies for wind energy conversion systems: integrated modelling, control strategy and performance simulation," Renewable Energy, Vol. 35, No. 10, pp. 2165-2174, Oct. 2010. https://doi.org/10.1016/j.renene.2010.03.009
  3. L. Tong, X. Zou, S. S. Feng, Y. Chen, Y. Kang, Q. Huang, and Y. Huang, "An SRF-PLL-based sensorless vector control using the predictive deadbeat algorithm for the direct driven permanent magnet synchronous generator," IEEE Trans Power Electron., Vol. 29, No. 6, pp. 2837-2849, Jun. 2014. https://doi.org/10.1109/TPEL.2013.2272465
  4. E. Giraldo and A. Garces, "An adaptive control strategy for a wind energy conversion system based on PWM-CSC and PMSG," IEEE Trans. Power Syst., Vol. 29, No. 3, pp. 1446-1453, May 2014. https://doi.org/10.1109/TPWRS.2013.2283804
  5. F. Delfino, F. Pampararo, R. Procopio, and M. Rossi, "A feedback linearization control scheme for the integration of wind energy conversion systems into distribution grids," IEEE Syst. J., Vol. 6, No. 1, pp.85-93, Mar. 2012. https://doi.org/10.1109/JSYST.2011.2163002
  6. N. A. Gounden, S. A. Peter, H. Nallandula, and S. Krithiga, "Fuzzy logic controller with MPPT using line-commutated inverter for three-phase grid-connected photovoltaic systems," Renewable Energy, Vol. 34, No. 3, pp. 909-915, Mar. 2009. https://doi.org/10.1016/j.renene.2008.05.039
  7. O. Abdel-Rahim, H. Funato, and J. Haruna, "Novel predictive maximum power point tracking techniques for photovoltaic applications," Journal of Power Electronics, Vol. 16, No.1, pp. 277-286, Jan. 2016. https://doi.org/10.6113/JPE.2016.16.1.277
  8. S. Kwak, U.-C. Moon, and J.-C. Park, "Predictive control based direct power control with an adaptive parameter identification technique for improved AFE performance," IEEE Trans Power Electron., Vol. 29, No. 11, pp. 6178-6187, Nov. 2014. https://doi.org/10.1109/TPEL.2014.2298041
  9. Y. Zhang and W. Xie, "Low complexity model predictive control single vector based approach," IEEE Trans Power Electron., Vol. 29, No. 10, pp. 5532-5541, Oct. 2014. https://doi.org/10.1109/TPEL.2013.2291005
  10. S. Kouro, P. Cortes, R. Vargas, U. Ammann, and J. Rodriguez, "Model predictive control simple and powerful method to control power converters," IEEE Trans Ind. Electron., Vol. 56, No. 6, pp. 1826-1838, Jun. 2009. https://doi.org/10.1109/TIE.2008.2008349
  11. P. Antoniewicz and M. P. Kazmierkowski, "Virtual flux based predictive direct power control of AC/DC converters with online inductance estimation," IEEE Trans. Ind. Electron., Vol. 55, No. 12, pp. 4381-4390, Dec. 2008. https://doi.org/10.1109/TIE.2008.2007519
  12. S. Yang, Q. Lei, F. Z. Peng, and Z. Qian, "A robust control scheme for grid connected voltage source inverters," IEEE Trans. Ind. Electron., Vol. 58, No. 1, pp. 202-212, Jan. 2011. https://doi.org/10.1109/TIE.2010.2045998
  13. Z. Song, W. Chen, and C. Xia, "Predictive direct power control for three phase grid connected converters without sector information and voltage vector selection," IEEE Trans. Power Electron., Vol. 29, No. 10, pp. 5518-5531, Oct. 2014. https://doi.org/10.1109/TPEL.2013.2289982
  14. P. Cortes, J. Rodriguez, C. Silva, and A. Flores, "Delay compensation in model predictive current control of a three phase inverter," IEEE Trans. Ind. Electron., Vol. 59, No. 2, pp. 1323-1325, Feb. 2012. https://doi.org/10.1109/TIE.2011.2157284

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