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Augmenting effectiveness of control loops of a PMSG (permanent magnet synchronous generator) based wind energy conversion system by a virtually adaptive PI (proportional integral) controller

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  • Alizadeh, Mojtaba
  • Kojori, Shokrollah Shokri

Abstract

Offering substantial features, PMSG (permanent magnet synchronous generator) based WECS (wind energy conversion system) is definitely one of the most reliable and efficient ways of extracting electrical power from the wind. Like other WECSs, PMSG-based WECS (PMSG_WECS) encompasses two main control loops, each equipped with PI (proportional integral) controller, to control speed and currents of the system. This work develops a virtually adaptive PI controller to enhance the performance of both main control loops of a PMSG_WECS. A WNN (wavelet neural network) is proposed to be added to each closed control loop in series with PI controller. Due to having a cascade connection, the transfer function of the WNN, which is a pure gain in each time step, is multiplied by PI gains. Therefore, the value of transfer function of the WNN, and consequently, both parameters of PI controller can be changed in each time step by online training of the WNN, resulting in a virtually adaptive PI controller. The performance of the proposed controller in improving efficacy of both current and speed control loops is evaluated by simulation studies and is also compared to that of PI controller, WNNC (wavelet neural network controller), and QNNC (quantum neural network controller).

Suggested Citation

  • Alizadeh, Mojtaba & Kojori, Shokrollah Shokri, 2015. "Augmenting effectiveness of control loops of a PMSG (permanent magnet synchronous generator) based wind energy conversion system by a virtually adaptive PI (proportional integral) controller," Energy, Elsevier, vol. 91(C), pages 610-629.
  • Handle: RePEc:eee:energy:v:91:y:2015:i:c:p:610-629
    DOI: 10.1016/j.energy.2015.08.047
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    1. Abdullah, M.A. & Yatim, A.H.M. & Tan, C.W. & Saidur, R., 2012. "A review of maximum power point tracking algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3220-3227.
    2. Mohamed, Amal Z. & Eskander, Mona N. & Ghali, Fadia A., 2001. "Fuzzy logic control based maximum power tracking of a wind energy system," Renewable Energy, Elsevier, vol. 23(2), pages 235-245.
    3. Li, H. & Chen, Z., 2009. "Design optimization and site matching of direct-drive permanent magnet wind power generator systems," Renewable Energy, Elsevier, vol. 34(4), pages 1175-1184.
    4. Hong, Chih-Ming & Ou, Ting-Chia & Lu, Kai-Hung, 2013. "Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system," Energy, Elsevier, vol. 50(C), pages 270-279.
    5. Lin, Whei-Min & Hong, Chih-Ming & Cheng, Fu-Sheng, 2010. "Fuzzy neural network output maximization control for sensorless wind energy conversion system," Energy, Elsevier, vol. 35(2), pages 592-601.
    6. Ganjefar, Soheil & Ghassemi, Ali Akbar & Ahmadi, Mohamad Mehdi, 2014. "Improving efficiency of two-type maximum power point tracking methods of tip-speed ratio and optimum torque in wind turbine system using a quantum neural network," Energy, Elsevier, vol. 67(C), pages 444-453.
    7. González, L.G. & Figueres, E. & Garcerá, G. & Carranza, O., 2010. "Maximum-power-point tracking with reduced mechanical stress applied to wind-energy-conversion-systems," Applied Energy, Elsevier, vol. 87(7), pages 2304-2312, July.
    8. Lin, Whei-Min & Hong, Chih-Ming, 2010. "Intelligent approach to maximum power point tracking control strategy for variable-speed wind turbine generation system," Energy, Elsevier, vol. 35(6), pages 2440-2447.
    9. Kot, R. & Rolak, M. & Malinowski, M., 2013. "Comparison of maximum peak power tracking algorithms for a small wind turbine," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 29-40.
    10. Baroudi, Jamal A. & Dinavahi, Venkata & Knight, Andrew M., 2007. "A review of power converter topologies for wind generators," Renewable Energy, Elsevier, vol. 32(14), pages 2369-2385.
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    1. Mahdy, Ahmed & Hasanien, Hany M. & Helmy, Waleed & Turky, Rania A. & Abdel Aleem, Shady H.E., 2022. "Transient stability improvement of wave energy conversion systems connected to power grid using anti-windup-coot optimization strategy," Energy, Elsevier, vol. 245(C).
    2. Fantino, Roberto & Solsona, Jorge & Busada, Claudio, 2016. "Nonlinear observer-based control for PMSG wind turbine," Energy, Elsevier, vol. 113(C), pages 248-257.
    3. Phan, Dinh-Chung & Yamamoto, Shigeru, 2016. "Rotor speed control of doubly fed induction generator wind turbines using adaptive maximum power point tracking," Energy, Elsevier, vol. 111(C), pages 377-388.
    4. Yang, Bo & Yu, Tao & Shu, Hongchun & Zhang, Yuming & Chen, Jian & Sang, Yiyan & Jiang, Lin, 2018. "Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine," Renewable Energy, Elsevier, vol. 119(C), pages 577-589.

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