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Adaptive Gains Control Scheme for PMSG-Based Wind Power Plant to Provide Voltage Regulation Service

Author

Listed:
  • Jianfeng Dai

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Yi Tang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Jun Yi

    (China Electric Power Research Institute, Beijing 100192, China)

Abstract

High-penetration wind power will count towards a significant portion of future power grid. This significant role requires wind turbine generators (WTGs) to contribute to voltage and reactive power support. The maximum reactive power capacity (MRPC) of a WTG depends on its current input wind speed, so that the reactive power regulating ability of the WTG itself and adjacent WTGs are not necessarily identical due to the variable wind speed and the wake effect. This paper proposes an adaptive gains control scheme (AGCS) for a permanent magnet synchronous generator (PMSG)-based wind power plant (WPP) to provide a voltage regulation service that can enhance the voltage-support capability under load disturbance and various wind conditions. The droop gains of the voltage controller for PMSGs are spatially and temporally dependent variables and adjusted adaptively depending on the MRPC which are a function of the current variable wind speed. Thus, WTGs with lower input wind speed can provide greater reactive power capability. The proposed AGCS is demonstrated by using a PSCAD/EMTDC simulator. It can be concluded that, compared with the conventional fixed-gains control scheme (FGCS), the proposed method can effectively improve the voltage-support capacity while ensuring stable operation of all PMSGs in WPP, especially under high wind speed conditions.

Suggested Citation

  • Jianfeng Dai & Yi Tang & Jun Yi, 2019. "Adaptive Gains Control Scheme for PMSG-Based Wind Power Plant to Provide Voltage Regulation Service," Energies, MDPI, vol. 12(4), pages 1-20, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:753-:d:208676
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    References listed on IDEAS

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    1. Pedro G. Lind & Luis Vera-Tudela & Matthias Wächter & Martin Kühn & Joachim Peinke, 2017. "Normal Behaviour Models for Wind Turbine Vibrations: Comparison of Neural Networks and a Stochastic Approach," Energies, MDPI, vol. 10(12), pages 1-14, November.
    2. Zuo, Wei & Wang, Xiaodong & Kang, Shun, 2016. "Numerical simulations on the wake effect of H-type vertical axis wind turbines," Energy, Elsevier, vol. 106(C), pages 691-700.
    3. Yangyang Zhao & Jianyun Chai & Xudong Sun, 2017. "Relative Voltage Control of the Wind Farms Based on the Local Reactive Power Regulation," Energies, MDPI, vol. 10(3), pages 1-13, February.
    4. Cheng Zhong & Lai Wei & Gangui Yan, 2017. "Low Voltage Ride-through Scheme of the PMSG Wind Power System Based on Coordinated Instantaneous Active Power Control," Energies, MDPI, vol. 10(7), pages 1-20, July.
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    Cited by:

    1. Zbigniew Skibko & Grzegorz Hołdyński & Andrzej Borusiewicz, 2022. "Impact of Wind Power Plant Operation on Voltage Quality Parameters—Example from Poland," Energies, MDPI, vol. 15(15), pages 1-16, August.
    2. K. Padmanathan & N. Kamalakannan & P. Sanjeevikumar & F. Blaabjerg & J. B. Holm-Nielsen & G. Uma & R. Arul & R. Rajesh & A. Srinivasan & J. Baskaran, 2019. "Conceptual Framework of Antecedents to Trends on Permanent Magnet Synchronous Generators for Wind Energy Conversion Systems," Energies, MDPI, vol. 12(13), pages 1-39, July.

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