Skip to main content
SpringerLink
Log in

Distinguishability analysis of controller parameters with applications to DFIG based wind turbine

  • Progress of Projects Supported by NSFC
  • Published:
Science China Technological Sciences Aims and scope Submit manuscript

Abstract

The power system controllers normally have more than one parameter. The distinguishability analysis of the controller parameters is to identify whether the optimal set of the parameters of the controllers is unique. It is difficult to obtain the analytic relationship between the objective of the optimization and the controller parameters, which means that the analytical method is not suitable for the distinguishability analysis. Therefore, a trajectory sensitivity based numerical method for the distinguishability analysis of the controller parameters is proposed in this paper. The relationship between the distinguishability and the sensitivities of the parameters is built. The magnitudes of the sensitivities are used to identify the key parameters, while the phase angles of the sensitivities are used to analyze the distinguishability of the key parameters. The distinguishability of the controller parameters of wind turbine with DFIG is studied using the proposed method, and dynamic simulations are performed to verify the results of the distinguishability analysis.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Yu Y X, Luan W P. Smart grid and its implementations (in Chinese). Proc CSEE, 2009, 29(34): 1–8

    MATH  Google Scholar 

  2. Li N H, Ni Y X, Sun S J, et al. Survey on smart grid and relevant key technologies (in Chinese). Southern Power Syst Technol, 2010, 4(3): 1–7

    Article  MATH  Google Scholar 

  3. Lu Q, Sheng C Y, Chen Y. Coordinated autonomous control strategy for power systems with large-scale wind power plants (in Chinese). Control Theory Appl, 2011, 28(10): 1491–1495

    Google Scholar 

  4. Cheung W K, Zhao E, Yao M, et al. Smart dispatch for large grid operations with integrated renewable resources (in Chinese). Energy Technol Econom, 2011, 23(11): 1–7

    Google Scholar 

  5. Dai X Z, Zhang K F, Zang Q. Nonlinear decentralized control method of power systems based on component structural model (in Chinese). Proc CSEE, 2008, 28(22): 15–28

    Google Scholar 

  6. Zhang X M, Mei S W, Su X Y, et al. Multi-level multi-area hybrid automatic voltage control system and its trial operation in Northeast China Grid. Sci China Tech Sci, 2011, 54(9): 2501–2510

    Article  MATH  Google Scholar 

  7. Zhang J Y, Ju P, Yu Y P, et al. Responses and stability of power system under small Gauss type random excitation. Sci China Tech Sci, 2012, 55(7): 1873–1880

    Article  Google Scholar 

  8. Wang W J, Li D H, Gao Q, et al. A two-degree-of-freedom PID controller tuning method (in Chinese). J Tsinghua Univ (Science and Technology), 2008, 48(11): 1786–1790

    Google Scholar 

  9. Chen J G, Hhuang L, Zhang J G, et al. A method for consolidated optimizing and quantitative setting under multi-index constraint (in Chinese). Ordnance Indus Autom, 2012, 31(2): 47–56

    Google Scholar 

  10. Zhou S L, Zhang P, Liu Y Y. Parameters tuning for primary controller of steam generator level control system based on H-loop shaping method (in Chinese). Atom Energy Sci Technol, 2011, 45(10): 1236–1241

    MathSciNet  Google Scholar 

  11. Shao L W, Liao X Z, Zhang Y H. Parameter tuning of active disturbance-rrejection controller for induction motor based on time scale (in Chinese). Contl Theor Appl, 2008, 25(2): 205–209

    Google Scholar 

  12. Wang W, Zhang J T, Chai T Y. A survey of advanced PID parameter tuning methods (in Chinese). Acta Autom Sin, 2000, 26(3): 347–355

    Google Scholar 

  13. Zhang C, Zhou X X, Jiang L, et al. The adjustment of the parameters of power system non-linear controller by learning algorithms (in Chinese). Proc CSEE, 2000, 20(4): 2–5

    Google Scholar 

  14. Liu Z, Jiang X Z, Li D H. Overview of the tuning methods of the PID controller parameters (in Chinese). Autom Elec Power Syst, 1997, 21(8): 79–83

    MATH  Google Scholar 

  15. Yang L, Yang G Y, Xu Z, et al. Optimal controller design of a doubly-fed induction generator wind turbine system for small signal stability enhancement. IET Gen Transm Distr, 2010, 4(5): 579–597

    Article  Google Scholar 

  16. Zhou X F, Chen C, Song Z Q, et al. Optimal design for HVDC PI controllers based on improverd PSO algorithm (in Chinese). High Volt Eng, 2009, 35(2): 408–414

    Google Scholar 

  17. Qin R C, Li T, Zhang Y. Controller parameter tuning method based on immune theory (in Chinese). J Univ Electronic Sci Technol China, 2009, 38(7): 609–612

    Google Scholar 

  18. Wu F, Zhang X P, Godferey K, et al. Small signal stability analysis and optimal control of a wind turbine with doubly fed induction generator. IET Gen Transm Distr, 2007, 1(5): 751–760

    Article  Google Scholar 

  19. Xie H L, Ju P, Luo J Y, et al. Identifiability analysis of load parameters based on sensitivity calculation (in Chinese). Autom Elec Power Syst, 2009, 33(7): 17–21

    Google Scholar 

  20. Sun J Q, Fang D Z, Zhou B R. Study on preventive control algorithm for dynamic security of power systems based on trajectory sensitivity method (in Chinese). Power System Technol, 2004, 28(21): 26–30

    Google Scholar 

  21. Ma J, Wang J G, He R M. Sensitivity analysis of power system dynamic simulation (in Chinese). Autom Elec Power Syst, 2005, 29(17): 20–27

    Google Scholar 

  22. Hiskens I A, Alseddiqui J. Sensitivity, approximation, and uncertainty in power system dynamic simulation. IEEE T Power Syst, 2006, 21(4): 1808–1820

    Article  Google Scholar 

  23. Ju P, Qin C, Wu F, et al. Load modeling for wide area power system. Elec Power Energy Syst, 2011, 33(4): 909–917

    Article  Google Scholar 

  24. Ju P. Theories and Methodologies of Power System Modeling. Beijing: Science Press, 2010

    Google Scholar 

  25. Li J F, Cai F B, Qiao L M, et al. China Wind Power Outlook. Beijing: China Environmental Science Press, 2012

    Google Scholar 

  26. Shi P F. Present situations and development trends of global wind power (in Chinese). Power System and Clean Energy, 2008, 24(1): 3–5

    Google Scholar 

  27. Luo R Y, Lin Y, Qian Y. The development and prospects of world wind power industry (in Chinese). Renew Energy Resou, 2010, 28(2): 14–7

    Google Scholar 

  28. Lei Y Z, Gordon L. An introduction on wind power grid code and dynamic simulation (in Chinese). Power System Technol, 2005, 25(12): 27–32

    Google Scholar 

  29. He D S, Liu Y Q, Wang Ya. Study of the shunt — connected wind power generation system (in Chinese). High Volt Eng, 2008, 34(1): 142–147

    Google Scholar 

  30. Wang W, Kiani M, Fahimi B. Optimal design of doubly fed induction generators using field reconstruction method. IEEE T Magn, 2010, 46(8): 3453–3456

    Article  Google Scholar 

  31. Pena R, Clear J C, Asher G M. Doubly fed induction generator using back-to-back PWM converters and its application to variablespeed wind energy generation. IEE Proc: Elec Power Appl, 1996, 143(3): 231–241

    Article  Google Scholar 

  32. Lei Y, Mullane A, Lightbody G, et al. Modeling of the wind turbine with a doubly fed induction generator for grid integration studies. IEEE T Energy Conv, 2006, 21(1): 257–264

    Article  Google Scholar 

  33. Ostadi A, Yadani A, Varma R K. Modeling and stability analysis of a DFIG-based wind-power generator interfaced with a series-compen-sated line. IEEE T Power Deliver, 2009, 24(3): 1504–1514

    Article  Google Scholar 

  34. Yamamoto M, Motoyoshi O. Active and reactive power control for doubly-fed wound rotor induction generator. IEEE T Power Elec, 1991, 6(33): 624–629

    Article  Google Scholar 

  35. Kundur P. Power System Stability and Control. New York: McGraw-Hill, 1994

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Energy and Electrical Engineering, Hohai University, Nanjing, 210098, China

    Chuan Qin, Ping Ju & Feng Wu

  2. Research Center for Renewable Energy Generation Engineering of Ministry of Education, Hohai University, Nanjing, 210098, China

    Chuan Qin, Ping Ju, Feng Wu & Lei Liu

  3. College of Science, Hohai University, Nanjing, 210098, China

    Lei Liu

Authors
  1. Chuan Qin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ping Ju
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Feng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chuan Qin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Qin, C., Ju, P., Wu, F. et al. Distinguishability analysis of controller parameters with applications to DFIG based wind turbine. Sci. China Technol. Sci. 56, 2465–2472 (2013). https://doi.org/10.1007/s11431-013-5324-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-013-5324-0

Keywords

Search

Navigation