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Adaptive PI Controllers for Doubly Fed Induction Generator using B-spline Artificial Neural Networks

by Ruben Tapia-o., Omar Aguilar M., Abel Garcia-b., Omar J. Santos-s.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 80 - Number 16
Year of Publication: 2013
Authors: Ruben Tapia-o., Omar Aguilar M., Abel Garcia-b., Omar J. Santos-s.
10.5120/13956-1949

Ruben Tapia-o., Omar Aguilar M., Abel Garcia-b., Omar J. Santos-s. . Adaptive PI Controllers for Doubly Fed Induction Generator using B-spline Artificial Neural Networks. International Journal of Computer Applications. 80, 16 ( October 2013), 37-42. DOI=10.5120/13956-1949

@article{ 10.5120/13956-1949,
author = { Ruben Tapia-o., Omar Aguilar M., Abel Garcia-b., Omar J. Santos-s. },
title = { Adaptive PI Controllers for Doubly Fed Induction Generator using B-spline Artificial Neural Networks },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 80 },
number = { 16 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 37-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume80/number16/13956-1949/ },
doi = { 10.5120/13956-1949 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:54:44.847207+05:30
%A Ruben Tapia-o.
%A Omar Aguilar M.
%A Abel Garcia-b.
%A Omar J. Santos-s.
%T Adaptive PI Controllers for Doubly Fed Induction Generator using B-spline Artificial Neural Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 80
%N 16
%P 37-42
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents the design and simulation of adaptive PI controllers for doubly fed induction generators using b-spline neural networks. The control structure is based on a back-to-back arrangement where the interest variables are regulated by PI linear controllers. Also, to deal with the nonlinear and uncertain system conditions, we proposed that the control parameters are updated online. The main task is that the power converters operation adapt by itself during the grid changes. Then, the basic problem consists of tuning the PI controllers simultaneously when the system and load are subjected to disturbances. The applicability of the proposal is demonstrated by simulation in a three-node grid, where one end is an infinite bus and the other connects the wind system, between them there are two transmission lines. The results show that the proposed controllers' tuning is comparable to that obtained by a conventional design, without requiring of a detailed model, which enable optimal speed tracking for maximum energy capture from the wind.

References
  1. Hoa M. Nguyen, D. Subbaram Naidu, "Advanced Control Strategies for Wind Energy Systems: An Overview", Proc. IEEE PES Power Systems Conference& Exposition (PSCE), 2011.
  2. S. Niu, K. T. Chau, J. Z. Jiang, and C. Liu, "Design and control of a new double-stator cup-rotor permanent-magnet machine for wind power generation," IEEE Trans. Magnetics, vol. 43, No. 6, pp. 2501-2503, 2007.
  3. Yi Wang, Lie Xu, "Coordinated Control of DFIG and FSIG-Based Wind Farms Under Unbalanced Grid Conditions", IEEE Trans. Power Delivery, vol. 25, No. 1, pp. 367-377, 2010.
  4. F. M. Hughes, O. Anaya-Lara, N. Jenkins, and G. Strbac, "Control of DFIG-based wind generation for power network support," IEEE Trans. Power Systems, vol. 20, No. 4, pp. 1958–1966, 2005.
  5. Mostafa Soliman, O. P. Malik, David T. Westwick, "Multiple Model Predictive Control for Wind Turbines With Doubly Fed Induction Generators", IEEE Trans. Sustainable Energy, vol. 2, No. 3, pp. 215- 225, 2011.
  6. Janeth Alcalá, Víctor Cárdenas, Emanuel Rosas Ciro Núñez, "Control system design for bi-directional power transfer in Single-Phase Back-to-Back converter based on the linear operating region", Proc. IEEE Applied Power Electronics Conference and Exposition (APEC), pp. 1651- 1658, 2010.
  7. Van-Tung Phan, Hong-Hee Lee, "Performance Enhancement of Stand-Alone DFIG Systems With Control of Rotor and Load Side Converters Using Resonant Controllers", IEEE Trans. Industry Applications, vol. 48, No. 1, pp. 199 – 210, 2012.
  8. J. Hu, H. Nian, B. Hu, Y. He, and Z. Q. Zhu, "Direct active and reactive power regulation of DFIG using sliding-mode control approach," IEEE Trans. Energy Conversion, vol. 25, No. 4, pp. 1028–1039, 2010.
  9. H. Camblong, I. M. de Alegria, M. Rodriguez, and G. Abad, "Experimental evaluation of wind turbines maximum power point tracking controllers," Energy Convers. Manage. , vol. 47, pp. 2846–2858, 2006.
  10. M. Sedighizadeh, D. Arzaghi-Harris, and M. Kalantar, "Adaptive PID control of wind energy conversion systems using RASP1 mother wavelet basis function networks," Proc. IEEE Conference in TENCON, vol. C, pp. 524 – 527, 2004.
  11. R. Pena, J. C. J. C Clare, G. M. Asher, "Doubly fed induction generator using back-to-back PWM converters and its application to variable-speed wind-energy generation", IEE Proc. Electric Power Applications, vol. 143, No. 3, pp. 231-241, 1996.
  12. B. Wu, Y. Lang, N. Zargari, S. Kouro, "Power Conversion and Control of Wind Energy Systems", Jonh Wiley and Sons, pp. 25-47, 2011.
  13. Brown, and C. Harris, "Neurofuzzy Adaptive Modelling and Control," Prentice Hall, 1994.
  14. R. C. Baker and B. Charlie, "Nonlinear unstable systems," International Journal of Control, vol. 23, no. 4, pp. 123-145, May 1989.
  15. G. -D. Hong, "Linear controllable systems," Nature, vol. 135, no. 5, pp. 18-27, July 1990.
  16. K. S. Hong and C. S. Kim, "Linear stable sys-tems," IEEE Trans. on Automatic Control, vol. 33, no. 3, pp. 1234-1245, December 1993.
  17. Z. Shiler, S. Filter, and S. Dubowski, "Time op-timal paths and acceleration lines of robotic manipulators," Proc. of the 26th Conf. Decision and Control, pp. 98-99, 1987.
  18. M. Young, The Technical Writer's Handbook, Mill Valley, Seoul, 1989.
  19. W. M. Newmann, R. F. Sproull, Principles of Interactive Computer Graphics, Mc-Graw-Hill, Inc. , 1979.
  20. N. Yadaiah, B. L. Deekshatulu, L. Sivakumar, V. S. H. Rao, Neural network algorithm for parameter identi?cation of dynamical systems involving time delays, Appl. Soft Comput. 7 (3) (2007) 1084–1091
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive PI Controllers B-spline Artificial Neural Network Induction Generators.

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