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Flexible Droop Coefficient-Based Inertia and Voltage Cascade Control for Isolated PV-Battery DC Microgrid

Author

Listed:
  • Zhilong Yin

    (Xi’an Dynamic Inspection and Testing Co., Ltd., Xi’an 710000, China)

  • Shuilian Xue

    (Xi’an Dynamic Inspection and Testing Co., Ltd., Xi’an 710000, China)

  • Zhiguo Wang

    (Xi’an Dynamic Inspection and Testing Co., Ltd., Xi’an 710000, China)

  • Feng Yu

    (School of Electrical Engineering, Nantong University, Nantong 226019, China)

  • Hailiang Chen

    (Nanjing Moral Testing and Certification Co., Ltd., Nanjing 211106, China)

Abstract

To realize the coordinated distribution of power in the multi-source system, maintain the charging balance among energy storage units, and improve the anti-interference capability of the bus voltage, a cascade control for an isolated PV-battery DC microgrid is proposed in this paper. First, to provide inertia for the microgrid so that it can cope with external disturbance, the parameters of the droop curve were adjusted by correlating the bus voltage variation rate, which improved the conventional droop control. Secondly, a nonsingular terminal sliding mode control was proposed to track voltage and current references and, thus, enhance the robustness of the DC microgrid. Moreover, the high-frequency chattering of the sliding mode control was inhibited with the exponential reaching law, and the Lyapunov function was utilized to verify the stability of the proposed nonsingular terminal sliding mode control method. Both the simulated and experimental results verified the correctness and effectiveness of the proposed method.

Suggested Citation

  • Zhilong Yin & Shuilian Xue & Zhiguo Wang & Feng Yu & Hailiang Chen, 2022. "Flexible Droop Coefficient-Based Inertia and Voltage Cascade Control for Isolated PV-Battery DC Microgrid," Energies, MDPI, vol. 15(24), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9318-:d:997865
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    References listed on IDEAS

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    1. Okech Emmanuel Okwako & Zhang-Hui Lin & Mali Xin & Kamaraj Premkumar & Alukaka James Rodgers, 2022. "Neural Network Controlled Solar PV Battery Powered Unified Power Quality Conditioner for Grid Connected Operation," Energies, MDPI, vol. 15(18), pages 1-18, September.
    2. Ratnam, Kamala Sarojini & Palanisamy, K. & Yang, Guangya, 2020. "Future low-inertia power systems: Requirements, issues, and solutions - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
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