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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
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    References listed on IDEAS

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    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.
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    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.

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