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A Reactive Power-Voltage Control Strategy of an AC Microgrid Based on Adaptive Virtual Impedance

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  • Yao Liu

    (School of Electric Power, South China University of Technology, Guangzhou 510640, China
    Zhuhai Power Supply Bureau of Guangdong Power Grid Corporation, Zhuhai 519000, China)

  • Lin Guan

    (School of Electric Power, South China University of Technology, Guangzhou 510640, China)

  • Fang Guo

    (School of Automation Foshan University, Foshan 528225, China)

  • Jianping Zheng

    (Development Department of Guangdong Power Grid Corporation, Guangzhou 510030, China)

  • Jianfu Chen

    (Zhuhai Power Supply Bureau of Guangdong Power Grid Corporation, Zhuhai 519000, China)

  • Chao Liu

    (Zhuhai Power Supply Bureau of Guangdong Power Grid Corporation, Zhuhai 519000, China)

  • Josep M. Guerrero

    (Department of Energy Technology, Aalborg University, DK-9220 Aalborg East, Denmark)

Abstract

As an effective carrier of distributed generation, a microgrid is an effective way to ensure that distributed power can be reasonably utilized. However, due to the property of line impedance and other factors in a microgrid, reactive power supplied by distributed generation units cannot be shared rationally. To efficiently improve reactive power sharing, this paper proposes a reactive power-voltage control strategy based on adaptive virtual impedance. This method changes the voltage reference value by adding an adaptive term based on the traditional virtual impedance. Meanwhile, a voltage recovery mechanism was used to compensate the decline of distributed generation (DG) output voltage in the process. MATLAB/Simulink simulations and experimental results show that the proposed controller can effectively improve the steady state performance of the active and reactive power sharing. Finally, the feasibility and effectiveness of the proposed control strategy were verified.

Suggested Citation

  • Yao Liu & Lin Guan & Fang Guo & Jianping Zheng & Jianfu Chen & Chao Liu & Josep M. Guerrero, 2019. "A Reactive Power-Voltage Control Strategy of an AC Microgrid Based on Adaptive Virtual Impedance," Energies, MDPI, vol. 12(16), pages 1-15, August.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3057-:d:255906
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    References listed on IDEAS

    as
    1. Morteza Afrasiabi & Esmaeel Rokrok, 2018. "An Improved Centralized Control Structure for Compensation of Voltage Distortions in Inverter-Based Microgrids," Energies, MDPI, vol. 11(7), pages 1-13, July.
    2. Song, Dongran & Fan, Xinyu & Yang, Jian & Liu, Anfeng & Chen, Sifan & Joo, Young Hoon, 2018. "Power extraction efficiency optimization of horizontal-axis wind turbines through optimizing control parameters of yaw control systems using an intelligent method," Applied Energy, Elsevier, vol. 224(C), pages 267-279.
    3. Chang Yuan & Peilin Xie & Dan Yang & Xiangning Xiao, 2018. "Transient Stability Analysis of Islanded AC Microgrids with a Significant Share of Virtual Synchronous Generators," Energies, MDPI, vol. 11(1), pages 1-19, January.
    4. Song, Dongran & Yang, Jian & Dong, Mi & Joo, Young Hoon, 2017. "Model predictive control with finite control set for variable-speed wind turbines," Energy, Elsevier, vol. 126(C), pages 564-572.
    5. Liang Zhang & Kang Chen & Ling Lyu & Guowei Cai, 2019. "Research on the Operation Control Strategy of a Low-Voltage Direct Current Microgrid Based on a Disturbance Observer and Neural Network Adaptive Control Algorithm," Energies, MDPI, vol. 12(6), pages 1-17, March.
    6. Zhilin Lyu & Qing Wei & Yiyi Zhang & Junhui Zhao & Emad Manla, 2018. "Adaptive Virtual Impedance Droop Control Based on Consensus Control of Reactive Current," Energies, MDPI, vol. 11(7), pages 1-17, July.
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