Skip to main content
SpringerLink
Log in
Book cover

Wind Power Systems pp 367–382Cite as

Application of TS-Fuzzy Controller for Active Power and DC Capacitor Voltage Control in DFIG-Based Wind Energy Conversion Systems

  • Chapter

Part of the book series: Green Energy and Technology ((GREEN,volume 0))

Abstract

This chapter focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the Doubly Fed Induction Generator (DFIG) based wind generator. The conventional PI control loops for mantaining desired active power and DC capacitor voltage is compared with the TS fuzzy controllers. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings is also investigated. The results from the time domain simulations are presented to elucidate the effectiveness of the TS-fuzzy controller over the conventional PI controller in the DFIG system. The proposed TS-fuzzy con-troller can improve the fault ride through capability of DFIG compared to the conventional PI controller.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Eriksen, P.B., Ackermann, T., Abildgaard, H., Smith, P., Winter, W., Rodriguez Garcia, J.M.: System operation with high wind penetration. IEEE Power Energy Mag 3(6), 65–74 (2005)

    Article  Google Scholar 

  2. Lei, Y., Mullane, A., Lightbody, G., Yacamini, R.: Modeling of the wind turbine with a doubly fed induction generator for grid integration studies. IEEE Transactions on Energy Conversion 21(1), 257–264 (2006)

    Article  Google Scholar 

  3. Mei, F., Pal, B.C.: Modeling snd small signal analysis of a grid connected doubly fed induction generator. In: Proc. of IEEE PES General Meeting, San Francisco, pp. 358–367 (2005)

    Google Scholar 

  4. Mei, F., Pal, B.C.: Modal analysis of grid connected doubly fed induction generator. IEEE Transactions on Energy Conversion 22(3), 728–736 (2007)

    Article  Google Scholar 

  5. Yamamoto, M., Motoyoshi, O.: Active and reactive power control for doubly-fed wound rotor induction generator. IEEE Transactions on Power Electronics 6(4), 624–629 (1991)

    Article  Google Scholar 

  6. Hughes, F.M., Anaya-Lara, O., Jenkins, N., Strbac, G.: Control ofdfig-based wind generation for power network support. IEEE Transactions on Power Systems 20(4), 1958–1966 (2005)

    Article  Google Scholar 

  7. Morren, J., de Haan, S.W.H.: Ride through of wind turbines with doubly-fed induction generator during a voltage dip. IEEE Transactions on Energy Conversions 20(2), 435–441 (2005)

    Article  Google Scholar 

  8. Bansal, R.C.: Bibliography on fuzzy sett theory application to power systems (1994-2001). IEEE Trans. Power Syst. 18(4), 1291–1299 (2003)

    Article  MathSciNet  Google Scholar 

  9. Tomsovic, K., Chow, M.Y. (eds.): Tutorial on Fuzzy Logic Applications in Power Systems. IEEE-PES Winter Meeting, Singapore (January 2000)

    Google Scholar 

  10. Song, Y.H. (ed.): Modern Optimization Techniques in Power Systems. Kluwer Academic Publishers, Netherlands (1999)

    Google Scholar 

  11. Song, Y.H., Johns, A.T.: Applications of Fuzzy Logic in Power Systems: Part 2. Comparison and Integration with Expert Systems, Neural Networks and Genetic Algorithms. IEE Power Engineering Journal 12(4), 185–190 (1998)

    Article  Google Scholar 

  12. Song, Y.H., Johns, A.T.: Applications of Fuzzy Logic in Power Systems: Part 3. Example Applications. IEE Power Engineering Journal 13(2), 97–103 (1999)

    Article  Google Scholar 

  13. Song, Y.H., Dunn, R.: Fuzzy Logic and Hybrid Systems, in Artificial Intelligence Techniques in Power Systems. In: Wardwick, K., Ekwue, A., Aggarwal, R. (eds.) Artificial Intelligence Techniques in Power Systems, London, UK. IEE Power Engineering Series, vol. 22, pp. 68–86 (1997)

    Google Scholar 

  14. Song, Y.H., Johns, A.T.: Applications of Fuzzy Logic in Power Systems: Part 1. General Introduction to Fuzzy Logic. IEE Power Engineering Journal 11(5), 219–222 (1997)

    Article  Google Scholar 

  15. Madan, S., Bollinger, K.E.: Applications of Artificial Intelligence in Power Systems. Electric Power System Research 41(2), 117–131 (1997)

    Article  Google Scholar 

  16. Laughton, M.A.: Artificial Intelligence Techniques in Power Systems. In: Wardwick, K., Ekwue, A., Aggarwal, R. (eds.) Artificial Intelligence Techniques in Power Systems, London, UK. IEE Power Engineering Series, vol. 22, pp. 1–18 (1997)

    Google Scholar 

  17. Mishra, S., Dash, P.K., Panda, G.: TS-fuzzy controller for UPFC in a multi machine power system. In: IEE proceedings on generation, transmission and distribution, January 2000, vol. 147(1), pp. 15–22 (2000)

    Google Scholar 

  18. Ying, H.: Constructing non-linear variable gain controllers via the Takagi-Sugeno fuzzy control. IEEE Trans. Fuzzy Syst. 6(2), 226–235 (1998)

    Article  Google Scholar 

  19. Hughes, F.M., Lara, O.A., Jenkins, N., Strbac, G.: A power system stabilizer for dfig-based wind generation. IEEE Transactions on Power Systems 21(2), 763–772 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The Department of Electrical Engineering, IIT, Delhi, India

    S. Mishra

  2. The School of ITEE, The University of Queensland, Australia and presently also a visiting scholar at The University of Tennessee, Knoxville, TN, USA

    Y. Mishra

  3. The Department of Electrical Engineering, The University of Tennessee, Knoxville, TN, USA

    Fangxing Li

  4. The Department of Electrical Engineering, Hong Kong Polytechnic University, Hong Kong

    Z. Y. Dong

Authors
  1. S. Mishra
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Y. Mishra
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fangxing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Z. Y. Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Texas A&M University, College Station, TX, USA

    Lingfeng Wang  & Chanan Singh  & 

  2. University of Iowa, Iowa City, IA, USA

    Andrew Kusiak

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Berlin Heidelberg

About this chapter

Cite this chapter

Mishra, S., Mishra, Y., Li, F., Dong, Z.Y. (2010). Application of TS-Fuzzy Controller for Active Power and DC Capacitor Voltage Control in DFIG-Based Wind Energy Conversion Systems. In: Wang, L., Singh, C., Kusiak, A. (eds) Wind Power Systems. Green Energy and Technology, vol 0. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13250-6_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-13250-6_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13249-0

  • Online ISBN: 978-3-642-13250-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation