IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v34y2009i4p994-999.html
   My bibliography  Save this article

Sensor-less maximum power point tracking control for wind generation system with squirrel cage induction generator

Author

Listed:
  • Senjyu, Tomonobu
  • Ochi, Yasutaka
  • Kikunaga, Yasuaki
  • Tokudome, Motoki
  • Yona, Atsushi
  • Muhando, Endusa Billy
  • Urasaki, Naomitsu
  • Funabashi, Toshihisa

Abstract

This paper proposes a technique that determines the optimal windmill operation speed and the optimal rotor flux. Moreover, the position and speed sensor-less wind generation system using the electromotive voltage observer to estimate rotor position and full-order observer to estimate rotor speed and the windmill output torque are proposed. The position and speed sensor-less maximum power point of wind power generation system is controlled by using the above estimated values, optimized windmill operation speed for maximum output power and optimized rotor flux for minimum generator losses. The effectiveness of the position and speed sensor-less maximum power point tracking control for wind power generation system with squirrel cage induction generator is verified by simulations. The simulation results confirm that the proposed method can estimate the operation speed efficiently.

Suggested Citation

  • Senjyu, Tomonobu & Ochi, Yasutaka & Kikunaga, Yasuaki & Tokudome, Motoki & Yona, Atsushi & Muhando, Endusa Billy & Urasaki, Naomitsu & Funabashi, Toshihisa, 2009. "Sensor-less maximum power point tracking control for wind generation system with squirrel cage induction generator," Renewable Energy, Elsevier, vol. 34(4), pages 994-999.
    • Handle: RePEc:eee:renene:v:34:y:2009:i:4:p:994-999
    DOI: 10.1016/j.renene.2008.08.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096014810800311X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2008.08.007?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. 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.
    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. Al-Ghossini, Hossam & Locment, Fabrice & Sechilariu, Manuela & Gagneur, Laurent & Forgez, Christophe, 2016. "Adaptive-tuning of extended Kalman filter used for small scale wind generator control," Renewable Energy, Elsevier, vol. 85(C), pages 1237-1245.
    2. Kurohane, Kyohei & Uehara, Akie & Senjyu, Tomonobu & Yona, Atsushi & Urasaki, Naomitsu & Funabashi, Toshihisa & Kim, Chul-Hwan, 2011. "Control strategy for a distributed DC power system with renewable energy," Renewable Energy, Elsevier, vol. 36(1), pages 42-49.
    3. Mohamed Zribi & Muthana Alrifai & Mohamed Rayan, 2017. "Sliding Mode Control of a Variable- Speed Wind Energy Conversion System Using a Squirrel Cage Induction Generator," Energies, MDPI, vol. 10(5), pages 1-21, May.
    4. Carunaiselvane, C. & Chelliah, Thanga Raj, 2017. "Present trends and future prospects of asynchronous machines in renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1028-1041.
    5. Matija Bubalo & Mateo Bašić & Dinko Vukadinović & Ivan Grgić, 2023. "Hybrid Wind-Solar Power System with a Battery-Assisted Quasi-Z-Source Inverter: Optimal Power Generation by Deploying Minimum Sensors," Energies, MDPI, vol. 16(3), pages 1-24, February.
    6. 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.
    7. Kadri, Ameni & Marzougui, Hajer & Aouiti, Abdelkrim & Bacha, Faouzi, 2020. "Energy management and control strategy for a DFIG wind turbine/fuel cell hybrid system with super capacitor storage system," Energy, Elsevier, vol. 192(C).
    8. Matija Bubalo & Mateo Bašić & Dinko Vukadinović & Ivan Grgić, 2021. "Experimental Investigation of a Standalone Wind Energy System with a Battery-Assisted Quasi-Z-Source Inverter," Energies, MDPI, vol. 14(6), pages 1-17, March.

    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 & 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.
    2. Anto Anbarasu Yesudhas & Young Hoon Joo & Seong Ryong Lee, 2022. "Reference Model Adaptive Control Scheme on PMVG-Based WECS for MPPT under a Real Wind Speed," Energies, MDPI, vol. 15(9), pages 1-17, April.
    3. 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.
    4. 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.
    5. Billy Muhando, Endusa & Senjyu, Tomonobu & Urasaki, Naomitsu & Yona, Atsushi & Kinjo, Hiroshi & Funabashi, Toshihisa, 2007. "Gain scheduling control of variable speed WTG under widely varying turbulence loading," Renewable Energy, Elsevier, vol. 32(14), pages 2407-2423.
    6. Amirsoheil Honarbari & Sajad Najafi-Shad & Mohsen Saffari Pour & Seyed Soheil Mousavi Ajarostaghi & Ali Hassannia, 2021. "MPPT Improvement for PMSG-Based Wind Turbines Using Extended Kalman Filter and Fuzzy Control System," Energies, MDPI, vol. 14(22), pages 1-16, November.
    7. Ram, J.Prasanth & Rajasekar, N. & Miyatake, Masafumi, 2017. "Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1138-1159.
    8. Assareh, Ehsanolah & Biglari, Mojtaba, 2015. "A novel approach to capture the maximum power from variable speed wind turbines using PI controller, RBF neural network and GSA evolutionary algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1023-1037.
    9. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    10. Battisti, L. & Benini, E. & Brighenti, A. & Dell’Anna, S. & Raciti Castelli, M., 2018. "Small wind turbine effectiveness in the urban environment," Renewable Energy, Elsevier, vol. 129(PA), pages 102-113.
    11. Delarue, Ph. & Bouscayrol, A. & Tounzi, A. & Guillaud, X. & Lancigu, G., 2003. "Modelling, control and simulation of an overall wind energy conversion system," Renewable Energy, Elsevier, vol. 28(8), pages 1169-1185.
    12. 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.
    13. Zaragoza, Jordi & Pou, Josep & Arias, Antoni & Spiteri, Cyril & Robles, Eider & Ceballos, Salvador, 2011. "Study and experimental verification of control tuning strategies in a variable speed wind energy conversion system," Renewable Energy, Elsevier, vol. 36(5), pages 1421-1430.
    14. Jurado, Francisco & Saenz, José R, 2002. "Neuro-fuzzy control for autonomous wind–diesel systems using biomass," Renewable Energy, Elsevier, vol. 27(1), pages 39-56.
    15. Tripathi, S.M. & Tiwari, A.N. & Singh, Deependra, 2015. "Grid-integrated permanent magnet synchronous generator based wind energy conversion systems: A technology review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1288-1305.

    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:renene:v:34:y:2009:i:4:p:994-999. 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/renewable-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.