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Adaptive Virtual Impedance Droop Control Based on Consensus Control of Reactive Current

Author

Listed:
  • Zhilin Lyu

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China)

  • Qing Wei

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China)

  • Yiyi Zhang

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China)

  • Junhui Zhao

    (Department of Electrical and Computer Engineering & Computer Science, University of New Haven, West Haven, CT 06516, USA)

  • Emad Manla

    (Department of Electrical and Computer Engineering & Computer Science, University of New Haven, West Haven, CT 06516, USA)

Abstract

It is difficult to achieve accurate distribution of reactive power based on conventional droop control due to the line impedance mismatch in an islanded microgrid. An adaptive virtual impendence method based on consensus control of reactive current is proposed in this paper. A distributed control structure without the central controller has been established. In this structure, each distributed generation unit (DG) is an independent agent, one-way communication is used between the adjacent DGs, and the reactive power sharing is equivalent to a problem of reactive power current consensus. It has been proven that the system is asymptotically stable under the proposed control strategy. When the adjacent DG’s reactive power is not proportionally distributed, the current weight error term will generate a virtual impedance correction term through the proportional-integral controller based on the reactive current consensus control strategy, thus introducing adaptive virtual impedance to eliminate mismatches in output impedance between DGs. Reactive power auto-proportional distribution can be achieved without knowing the line impedance. At the same time, the power control loop is simplified and the virtual impedance compensation angle is employed to compensate the decreased reference voltage magnitude and varied phase angle due to the introduction of the virtual impedance, so the stability of the system can be improved. Finally, the correctness and effectiveness of the proposed strategy are verified by modeling analysis and microgrid simulations.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1801-:d:157092
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    References listed on IDEAS

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    1. Jiefeng Liu & Hanbo Zheng & Yiyi Zhang & Hua Wei & Ruijin Liao, 2017. "Grey Relational Analysis for Insulation Condition Assessment of Power Transformers Based Upon Conventional Dielectric Response Measurement," Energies, MDPI, vol. 10(10), pages 1-16, October.
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    3. Roh Chan & Sangshin Kwak, 2018. "Improved Finite-Control-Set Model Predictive Control for Cascaded H-Bridge Inverters," Energies, MDPI, vol. 11(2), pages 1-27, February.
    4. Bin Li & Lin Zhou, 2017. "Power Decoupling Method Based on the Diagonal Compensating Matrix for VSG-Controlled Parallel Inverters in the Microgrid," Energies, MDPI, vol. 10(12), pages 1-13, December.
    5. Henan Dong & Shun Yuan & Zijiao Han & Zhiyuan Cai & Guangdong Jia & Yangyang Ge, 2018. "A Comprehensive Strategy for Accurate Reactive Power Distribution, Stability Improvement, and Harmonic Suppression of Multi-Inverter-Based Micro-Grid," Energies, MDPI, vol. 11(4), pages 1-16, March.
    6. Seung-Jin Yoon & Ngoc Bao Lai & Kyeong-Hwa Kim, 2018. "A Systematic Controller Design for a Grid-Connected Inverter with LCL Filter Using a Discrete-Time Integral State Feedback Control and State Observer," Energies, MDPI, vol. 11(2), pages 1-20, February.
    7. Yiyi Zhang & Jiefeng Liu & Hanbo Zheng & Hua Wei & Ruijin Liao, 2017. "Study on Quantitative Correlations between the Ageing Condition of Transformer Cellulose Insulation and the Large Time Constant Obtained from the Extended Debye Model," Energies, MDPI, vol. 10(11), pages 1-17, November.
    8. Demin Li & Bo Zhao & Zaijun Wu & Xuesong Zhang & Leiqi Zhang, 2017. "An Improved Droop Control Strategy for Low-Voltage Microgrids Based on Distributed Secondary Power Optimization Control," Energies, MDPI, vol. 10(9), pages 1-18, September.
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    Cited by:

    1. Jose R Sicchar & Carlos T. Da Costa & Jose R. Silva & Raimundo C. Oliveira & Werbeston D. Oliveira, 2018. "A Load-Balance System Design of Microgrid Cluster Based on Hierarchical Petri Nets," Energies, MDPI, vol. 11(12), pages 1-30, November.
    2. Mohamed Keddar & Mamadou Lamine Doumbia & Karim Belmokhtar & Mohamed Della Krachai, 2022. "Enhanced Reactive Power Sharing and Voltage Restoration Based on Adaptive Virtual Impedance and Consensus Algorithm," Energies, MDPI, vol. 15(10), pages 1-19, May.
    3. Xiangwu Yan & Yang Cui & Sen Cui, 2019. "Control Method of Parallel Inverters with Self-Synchronizing Characteristics in Distributed Microgrid," Energies, MDPI, vol. 12(20), pages 1-20, October.
    4. Jiawei Dong & Chunyang Gong & Jun Bao & Lihua Zhu & Yuanjun Hou & Zhixin Wang, 2022. "Secondary-Frequency and Voltage-Regulation Control of Multi-Parallel Inverter Microgrid System," Energies, MDPI, vol. 15(22), pages 1-25, November.
    5. Biyun Chen & Haoying Chen & Yiyi Zhang & Junhui Zhao & Emad Manla, 2019. "Risk Assessment for the Power Grid Dispatching Process Considering the Impact of Cyber Systems," Energies, MDPI, vol. 12(6), pages 1-18, March.
    6. Mohammed Ali Khan & Ahteshamul Haque & Frede Blaabjerg & Varaha Satya Bharath Kurukuru & Huai Wang, 2021. "Intelligent Transition Control between Grid-Connected and Standalone Modes of Three-Phase Grid-Integrated Distributed Generation Systems," Energies, MDPI, vol. 14(13), pages 1-21, July.
    7. Zhilin Lyu & Xiao Yang & Yiyi Zhang & Junhui Zhao, 2020. "Bi-Level Optimal Strategy of Islanded Multi-Microgrid Systems Based on Optimal Power Flow and Consensus Algorithm," Energies, MDPI, vol. 13(7), pages 1-19, March.
    8. 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.
    9. Qian Sun & Qiuye Sun & Dehao Qin, 2018. "Adaptive Fuzzy Droop Control for Optimized Power Sharing in an Islanded Microgrid," Energies, MDPI, vol. 12(1), pages 1-23, December.
    10. Yousef Asadi & Mohsen Eskandari & Milad Mansouri & Andrey V. Savkin & Erum Pathan, 2022. "Frequency and Voltage Control Techniques through Inverter-Interfaced Distributed Energy Resources in Microgrids: A Review," Energies, MDPI, vol. 15(22), pages 1-29, November.

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