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Maximum mechanical power extraction from wind turbines using novel proposed high accuracy single-sensor-based maximum power point tracking technique

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  • Fathabadi, Hassan

Abstract

A novel high accuracy single-sensor-based maximum power point tracking (MPPT) technique is proposed to extract maximum mechanical power from wind turbines. The technique uses only one wind speed sensor to regulate turbine speed to its optimum value, i.e., there is no need for any shaft speed sensor (tachometer), shaft power meter, shaft torque meter, etc. Instead of using a shaft speed sensor, the instant angular speed of the turbine is precisely extracted from the output voltage of the generator coupled to the turbine. A wind energy conversion system has been built to evaluate the technique performance. The proposed MPPT technique is compared with the state-of-the-art MPPT techniques, it is experimentally verified that not only the MPPT efficiency of the method is 98.04%, which is significantly more than that of others, but also its convergence time is only 18 ms, which is the shortest convergence time compared to others. Very simple structure, low cost, and very good response to sudden variations in wind speed are the other advantages. The proposed MPPT technique is novel because it provides the highest MPPT efficiency along with the shortest tracking convergence time compared to the state-of-the-art MPPT techniques for extracting maximum mechanical power from wind turbines.

Suggested Citation

  • Fathabadi, Hassan, 2016. "Maximum mechanical power extraction from wind turbines using novel proposed high accuracy single-sensor-based maximum power point tracking technique," Energy, Elsevier, vol. 113(C), pages 1219-1230.
  • Handle: RePEc:eee:energy:v:113:y:2016:i:c:p:1219-1230
    DOI: 10.1016/j.energy.2016.07.081
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    Cited by:

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    3. Fathabadi, Hassan, 2016. "Novel highly accurate universal maximum power point tracker for maximum power extraction from hybrid fuel cell/photovoltaic/wind power generation systems," Energy, Elsevier, vol. 116(P1), pages 402-416.
    4. Mahmoud F. Elmorshedy & Umashankar Subramaniam & Jagabar Sathik Mohamed Ali & Dhafer Almakhles, 2023. "Energy Management of Hybrid DC Microgrid with Different Levels of DC Bus Voltage for Various Load Types," Energies, MDPI, vol. 16(14), pages 1-32, July.
    5. 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.
    6. 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).
    7. Maheshwari, Zeel & Kengne, Kamgang & Bhat, Omkar, 2023. "A comprehensive review on wind turbine emulators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).

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