IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v91y2015icp610-629.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544215011226
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2015.08.047?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ganjefar, Soheil & Ghasemi, Ali Akbar, 2014. "A novel-strategy controller design for maximum power extraction in stand-alone windmill systems," Energy, Elsevier, vol. 76(C), pages 326-335.
    2. 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.
    3. Dixon, Christopher & Reynolds, Steve & Rodley, David, 2016. "Micro/small wind turbine power control for electrolysis applications," Renewable Energy, Elsevier, vol. 87(P1), pages 182-192.
    4. Kumar, Dipesh & Chatterjee, Kalyan, 2016. "A review of conventional and advanced MPPT algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 957-970.
    5. Mokhtari, Yacine & Rekioua, Djamila, 2018. "High performance of Maximum Power Point Tracking Using Ant Colony algorithm in wind turbine," Renewable Energy, Elsevier, vol. 126(C), pages 1055-1063.
    6. Melício, R. & Mendes, V.M.F. & Catalão, J.P.S., 2011. "Comparative study of power converter topologies and control strategies for the harmonic performance of variable-speed wind turbine generator systems," Energy, Elsevier, vol. 36(1), pages 520-529.
    7. 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.
    8. Dargahi, Vahid & Sadigh, Arash Khoshkbar & Pahlavani, Mohammad Reza Alizadeh & Shoulaie, Abbas, 2012. "DC (direct current) voltage source reduction in stacked multicell converter based energy systems," Energy, Elsevier, vol. 46(1), pages 649-663.
    9. Mahela, Om Prakash & Shaik, Abdul Gafoor, 2016. "Comprehensive overview of grid interfaced wind energy generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 260-281.
    10. Ganjefar, Soheil & Mohammadi, Ali, 2016. "Variable speed wind turbines with maximum power extraction using singular perturbation theory," Energy, Elsevier, vol. 106(C), pages 510-519.
    11. Fathabadi, Hassan, 2016. "Novel high-efficient unified maximum power point tracking controller for hybrid fuel cell/wind systems," Applied Energy, Elsevier, vol. 183(C), pages 1498-1510.
    12. Yin, Minghui & Yang, Zhiqiang & Xu, Yan & Liu, Jiankun & Zhou, Lianjun & Zou, Yun, 2018. "Aerodynamic optimization for variable-speed wind turbines based on wind energy capture efficiency," Applied Energy, Elsevier, vol. 221(C), pages 508-521.
    13. Feng, Yi & Lin, Heyun & Ho, S.L. & Yan, Jianhu & Dong, Jianning & Fang, Shuhua & Huang, Yunkai, 2015. "Overview of wind power generation in China: Status and development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 847-858.
    14. Belmokhtar, K. & Doumbia, M.L. & Agbossou, K., 2014. "Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator)," Energy, Elsevier, vol. 76(C), pages 679-693.
    15. Belkacem Belabbas & Tayeb Allaoui & Mohamed Tadjine & Mouloud Denai, 2019. "Comparative study of back-stepping controller and super twisting sliding mode controller for indirect power control of wind generator," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(6), pages 1555-1566, December.
    16. Marwa Hassan & Alsnosy Balbaa & Hanady H. Issa & Noha H. El-Amary, 2018. "Asymptotic Output Tracked Artificial Immunity Controller for Eco-Maximum Power Point Tracking of Wind Turbine Driven by Doubly Fed Induction Generator," Energies, MDPI, vol. 11(10), pages 1-25, October.
    17. Nasiri, M. & Milimonfared, J. & Fathi, S.H., 2015. "A review of low-voltage ride-through enhancement methods for permanent magnet synchronous generator based wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 399-415.
    18. Yu, Jie & Chen, Kuilin & Mori, Junichi & Rashid, Mudassir M., 2013. "A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction," Energy, Elsevier, vol. 61(C), pages 673-686.
    19. Golnary, Farshad & Moradi, Hamed, 2022. "Identification of the dynamics of the drivetrain and estimating its unknown parts in a large scale wind turbine," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 50-69.
    20. Mohd Zin, Abdullah Asuhaimi B. & Pesaran H.A., Mahmoud & Khairuddin, Azhar B. & Jahanshaloo, Leila & Shariati, Omid, 2013. "An overview on doubly fed induction generators′ controls and contributions to wind based electricity generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 692-708.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:91:y:2015:i:c:p:610-629. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.