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Modeling and fuzzy control of a wind energy system based on double-fed asynchronous machine for supply of power to the electrical network

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Abstract

The present paper proposes a model of fuzzy logic control of a doubly fed asynchronous machine (DFAM). First, a mathematical model of DFAM, written in an appropriate d-q reference frame, is established to investigate the results of simulations. In order to control the rotor currents of DFAM, a torque tracking control law is synthesized using PI controllers; the stator side power factor is controlled at a unity level. Then, artificial intelligent controls, such as fuzzy logic control, are applied. The simulated performances are then compared to those of a classical PI controller. Results obtained, in Matlab/Simulink environment, show that the fuzzy control is more robust i.e. has a superior dynamic performance and, hence, is found to be a suitable replacement of the conventional PI controller for a high performance drive applications.

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References

  • Arul I, Karthikeyan M, Krishnan N, Muthukumar S (2012) A design and modeling techniques for maximum power optimization on wind electrical power system with variable speed generation using neuro fuzzy. Int J Emerg Technol Adv Eng, 2(9):272–277

  • Barbade SA, Kasliwal P (2012) Neural network based control of doubly-fed induction generator in wind power generation. IOSR J Electr Electron Eng, IOSRJEEE 1(6):35–40

    Article  Google Scholar 

  • Brekken TKA (2005) A novel control scheme for a doubly-fed induction wind generator under unbalanced grid voltage condition

  • Chaiba A, Abdessemed R, Bendaas ML, Dendouga A (2005) Performances of torque tracking control for doubly fed asynchronous motor using PI and fuzzy logic controllers. J Electr Eng, JEE 5(2):25–30

    Google Scholar 

  • Eisenhut C, Krug F, Schram C, Klockl B (2007) Wind turbine model for system simulations. Near cut-in wind speed. IEEE Trans, Energy Convers 22:414–420

    Article  Google Scholar 

  • Hanseen AD (2004) Generator and power electronics for wind turbine. In: Ackermann T (ed) Wind power in power systems. Wiley, Chichester

    Google Scholar 

  • Hellendoorn H (1990) Closure properties of the compositional rule of inference. Fuzzy Sets Syst 35:163–183

    Article  MathSciNet  MATH  Google Scholar 

  • Nait-kaci B, Doumbia ML (2009) Active and reactive power control of a doubly fed induction generator for wind applications, IEEE

  • Peterson A (2005) Analysis, modeling and control of doubly fed induction generators for wind turbines. In: Energy and environment. PhD Dissertation thesis, Chalmers University of Technology, Goteborg

  • Protsenko K, Xu D (2008) Modeling and control of brushless doubly-fed induction generators in wind energy applications. Department of Electrical and Computer Engineering Ryerson University, Toronto

  • Qingding G, Lime W, Rueful L (1997) Robust fuzzy variable structure control of PMLSM servo system, In: IEEE international conference on intelligent processing systems, Beijing, pp 675–679

  • Runkler TA (1997) Selection of appropriate defuzzification methods using application specific properties. IEEE Trans Fuzzy Syst 5:72–79

    Article  Google Scholar 

  • Shen B, Mwinyiwiwa B, Zhang Y, Obi B-T (2009) Sensor less maximum power point tracking of wind by DFIG using rotor position phase lock loop (PLL). IEEE Trans Power Electron 24(4):942–951

    Article  Google Scholar 

  • Takagi T, Surgeon M (1983) Derivation of fuzzy control rules from human operator’s control actions. In Proceedings IFAC symposium on fuzzy information, knowledge representation and decision analysis, pp 55–60

  • Tapia A, Tapia G, Ostolaza JX (2003) Modeling and control of a wind turbine driven doubly fed induction generator. IEEE 18(2):194–204

    Google Scholar 

  • Xu WC (1995) Torque and reactive power control of a doubly-fed induction machine by position sensor less scheme. IEEE Trans Ind Appl 31(3):636–642

    Article  Google Scholar 

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Correspondence to Abdel Karim Guediri.

Annexure

Annexure

Wound rotor induction machine parameters:

Nominal power \(P_{n}\) = 1.5 MW

Stator frequency \(f_{s}\) = 50 Hz

Stator resistance \(R_{s}\) = 0.12 Ω

Stator inductance \(L_{s}\) = 0.0205 H

Rotor resistance \(R_{r}\) = 0.021 Ω

Rotor inductance \(L_{r}\) = 0.0204 H

Mutual inductance \(L_{m}\) = 0.0169 H

Inertia constant J = 1000 kg m−2

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Guediri, A.K., Ben Attous, D. Modeling and fuzzy control of a wind energy system based on double-fed asynchronous machine for supply of power to the electrical network. Int J Syst Assur Eng Manag 8 (Suppl 1), 353–360 (2017). https://doi.org/10.1007/s13198-015-0367-1

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  • DOI: https://doi.org/10.1007/s13198-015-0367-1

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