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Wind Energy Conversion Systems Based on a Doubly Fed Induction Generator Using Artificial Fuzzy Logic Control

  • Z. ZeghdiEmail author
  • L. Barazane
  • A. Larabi
  • B. Benchama
  • K. Khechiba
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)

Abstract

This paper presents the application of a simulation with a proposed model and control of a (DFIG) associated into a wind energy conversion system with a variable speed wind turbine using Artificial Fuzzy Logic techniques, and we are particularly interested in the application of indirect vector control by stator field orientation of DFIG. Firstly, a mathematical model of the machine written in an appropriate d–q reference frame is proposed to investigate simulations. secondly, and in order to control the power flowing between the stator of the DFIG and the power network, a control law is synthesized using two types of controllers: Proportional-Integral (PI) controller and fuzzy logic based controller. The proposed controller was tested and compared with one other technique, the PI controller. Finally, the obtained results show that the proposed controller exhibits better behaviour in terms of settling time, overshoot, robustness with respect to machine parameters variation, and good tracking references. The simulation was carried out by means of computational simulations in Matlab/Simulink Software.

Keywords

Doubly fed induction machine Wind turbine Proportional-integral Fuzzy logic Vector control 

References

  1. 1.
    Lee, H.H., Dzung, P.Q., Phuong, L.M., Khoa, L.D., Nhan N.H.: A new fuzzy logic approach for control system of wind turbine with doubly fed induction generator. In: International Forum Strategic Technology (IFOST), pp. 135–139 (2010)Google Scholar
  2. 2.
    Pena, R., Clare, J. C., Asher, G. M.: A doubly fed induction generator using back to back converters supplying an isolated load from a variable speed wind turbine. In: IEE Proceeding on Electrical Power Applications vol. 143(September (5)) (1996)CrossRefGoogle Scholar
  3. 3.
    Yao, X., Yi, C., Ying, D., Guo, J., Yang, L.: The grid-side PWM converter of the wind power generation system based on fuzzy sliding mode control. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 973–978 (2008)Google Scholar
  4. 4.
    Rachidi, M., BIdrissi, B.B.: Adaptive nonlinear control of doubly-fed induction machine in wind power generation. J. Theor. Appl. Inf. Technol. 87(1) (2016)Google Scholar
  5. 5.
    Aidoud, M., et al.: A robustification of the two degree-of-freedom controller based upon multivariable generalized predictive control law and robust H control for a doubly-fed induction generator. Trans. Inst. Meas Control 40(3), 1005–1017 (2018)CrossRefGoogle Scholar
  6. 6.
    Khwaldeh, A., Barazane, L., Krishan, M.M.: Robust neural network to improve hybrid control of an induction motor. Electromotion 16(1), 28–37 (2009). ISSN 1223-057XGoogle Scholar
  7. 7.
    Azeem, B., et al. Robust neural network scheme for generator side converter of doubly fed induction generator. In: 2017 IEEE International Symposium on Recent Advances In Electrical Engineering (RAEE) (2017)‏Google Scholar
  8. 8.
    Tapia, A., Tapia, G., Ostolaza, J.X., Sáenz, J.R.: Modeling and control of a wind turbine driven doubly fed induction generator. IEEE Trans. Energy Convers. 18(2), 194–204 (2003)CrossRefGoogle Scholar
  9. 9.
    Abdelmalek, S., et al.: A novel scheme for current sensor faults diagnosis in the stator of a DFIG described by a TS fuzzy model. Measurement 91, 680–691 (2016)CrossRefGoogle Scholar
  10. 10.
    Li, X., Hui, D., Lai, X., Ouyang, M.: Control strategy of wind power output by pith angle control using fuzzy logic. In: 2010 IEEE International Symposium on Industrial Electronics (ISIE), pp. 120–124 (2010)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Z. Zeghdi
    • 1
    Email author
  • L. Barazane
    • 1
  • A. Larabi
    • 1
  • B. Benchama
    • 1
  • K. Khechiba
    • 2
  1. 1.Industrial and Electrical Systems Laboratory (LSEI), Faculty of Electronics and ComputerUniversity of Sciences and Technology Houari BoumedieneAlgiersAlgeria
  2. 2.Department of Electrical Engineering, Faculty of TechnologyDjelfa UniversityDjelfaAlgeria

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