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Comparison of maximum peak power tracking algorithms for a small wind turbine

Author

Listed:
  • Kot, R.
  • Rolak, M.
  • Malinowski, M.

Abstract

This paper reviews maximum power point tracking (MPPT) algorithms dedicated for small wind turbines (SWTs). Many control strategies with different features are available and it is very important to select proper one in order to achieve best performance and low cost. Three most widely used algorithms are discussed. Two are based on turbine static parameters such as power versus rotational speed characteristic Pm(ω) and optimum tip-speed ratio λopt. Third one, which seems to be most promising, iteratively searches for optimum operating point and it does not require prior knowledge of the turbine. This work attempts to summarize and compare these algorithms. Detailed description of each one is made with most significant qualities emphasized. Discussion is supported by the simulation studies using Synopsys Saber software. Results for 5kW SWT with diode rectifier and DC/DC boost converter are shown and commented.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:matcom:v:91:y:2013:i:c:p:29-40
    DOI: 10.1016/j.matcom.2013.03.010
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    Citations

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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. 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.
    3. 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.
    4. 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.
    5. Makeen, Peter & Ghali, Hani A. & Memon, Saim & Duan, Fang, 2023. "Smart techno-economic operation of electric vehicle charging station in Egypt," Energy, Elsevier, vol. 264(C).
    6. Junji Kondoh & Hidetoshi Mizuno & Takuji Funamoto, 2019. "Fault Ride-Through Characteristics of Small Wind Turbines," Energies, MDPI, vol. 12(23), pages 1-12, December.
    7. Tania García-Sánchez & Arbinda Kumar Mishra & Elías Hurtado-Pérez & Rubén Puché-Panadero & Ana Fernández-Guillamón, 2020. "A Controller for Optimum Electrical Power Extraction from a Small Grid-Interconnected Wind Turbine," Energies, MDPI, vol. 13(21), pages 1-16, November.
    8. 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.
    9. Yin, Xiu-xing & Lin, Yong-gang & Li, Wei & Gu, Hai-gang, 2016. "Hydro-viscous transmission based maximum power extraction control for continuously variable speed wind turbine with enhanced efficiency," Renewable Energy, Elsevier, vol. 87(P1), pages 646-655.
    10. Andrzej Bogdan Kasprowicz & Oleksandr Husev & Ryszard Strzelecki, 2022. "Induction Generator with Direct Control and a Limited Number of Measurements on the Side of the Converter Connected to the Power Grid," Energies, MDPI, vol. 16(1), pages 1-23, December.
    11. 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.

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