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An Analysis of Variable-Speed Wind Turbine Power-Control Methods with Fluctuating Wind Speed

Author

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  • Yun-Su Kim

    (School of Electrical Engineering and Computer Science, Seoul National University, Seoul 151-742, Korea)

  • Il-Yop Chung

    (School of Electrical Engineering, Kookmin University, Seoul 136-702, Korea)

  • Seung-Il Moon

    (School of Electrical Engineering and Computer Science, Seoul National University, Seoul 151-742, Korea)

Abstract

Variable-speed wind turbines (VSWTs) typically use a maximum power-point tracking (MPPT) method to optimize wind-energy acquisition. MPPT can be implemented by regulating the rotor speed or by adjusting the active power. The former, termed speed-control mode (SCM), employs a speed controller to regulate the rotor, while the latter, termed power-control mode (PCM), uses an active power controller to optimize the power. They are fundamentally equivalent; however, since they use a different controller at the outer control loop of the machine-side converter (MSC) controller, the time dependence of the control system differs depending on whether SCM or PCM is used. We have compared and analyzed the power quality and the power coefficient when these two different control modes were used in fluctuating wind speeds through computer simulations. The contrast between the two methods was larger when the wind-speed fluctuations were greater. Furthermore, we found that SCM was preferable to PCM in terms of the power coefficient, but PCM was superior in terms of power quality and system stability.

Suggested Citation

  • Yun-Su Kim & Il-Yop Chung & Seung-Il Moon, 2013. "An Analysis of Variable-Speed Wind Turbine Power-Control Methods with Fluctuating Wind Speed," Energies, MDPI, vol. 6(7), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:7:p:3323-3338:d:26966
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    References listed on IDEAS

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    1. Llorente Iglesias, Rosario & Lacal Arantegui, Roberto & Aguado Alonso, Mónica, 2011. "Power electronics evolution in wind turbines—A market-based analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4982-4993.
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    Cited by:

    1. Wei Sun & Mohan Liu & Yi Liang, 2015. "Wind Speed Forecasting Based on FEEMD and LSSVM Optimized by the Bat Algorithm," Energies, MDPI, vol. 8(7), pages 1-23, June.
    2. Yun-Su Kim & Il-Yop Chung & Seung-Il Moon, 2015. "Tuning of the PI Controller Parameters of a PMSG Wind Turbine to Improve Control Performance under Various Wind Speeds," Energies, MDPI, vol. 8(2), pages 1-20, February.
    3. Zhiqiang Yang & Minghui Yin & Yan Xu & Zhengyang Zhang & Yun Zou & Zhao Yang Dong, 2016. "A Multi-Point Method Considering the Maximum Power Point Tracking Dynamic Process for Aerodynamic Optimization of Variable-Speed Wind Turbine Blades," Energies, MDPI, vol. 9(6), pages 1-16, May.
    4. Dejian Yang & Moses Kang & Eduard Muljadi & Wenzhong Gao & Junhee Hong & Jaeseok Choi & Yong Cheol Kang, 2017. "Short-Term Frequency Response of a DFIG-Based Wind Turbine Generator for Rapid Frequency Stabilization," Energies, MDPI, vol. 10(11), pages 1-14, November.
    5. Zhiqiang Yang & Minghui Yin & Yan Xu & Yun Zou & Zhao Yang Dong & Qian Zhou, 2016. "Inverse Aerodynamic Optimization Considering Impacts of Design Tip Speed Ratio for Variable-Speed Wind Turbines," Energies, MDPI, vol. 9(12), pages 1-15, December.

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