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Power and Capacity Consensus Tracking of Distributed Battery Storage Systems in Modular Microgrids

Author

Listed:
  • Xianyong Zhang

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Yaohong Huang

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Li Li

    (School of Automation, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Wei-Chang Yeh

    (Integration and Collaboration Laboratory, Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 46804804, Taiwan)

Abstract

Conventional microgrids have a specific system configuration and a complex hierarchical control structure, which has resulted in difficulties in their economic development. A modular microgrid based on distributed battery storage has been proposed to realize the rapid economic development of small-to-medium microgrids. Control of modular microgrids is simplified to voltage control within modules and exchange power control among modules. Battery power has great influence on battery performance. Space-time complementary power characteristics among modules help to alleviate power fluctuations, prolong the service life and realize the unified maintenance of distributed batteries. Leader-following consensus theory of multi-agent systems is adopted to realize the power and capacity consensus tracking of distributed battery storage in a modular microgrid. Sufficient and necessary conditions for continuous-time and sampled-data bounded power and capacity consensus tracking of distributed battery storages are deduced by a matrix analytical method. Steady regions of sampling period and sampling delay for sampled-data bounded power and capacity consensus tracking are determined by analytical or numerical solutions. Simulations and experiments on a modular microgrid demonstration project located on DongAo Island (China) show the effectiveness and robustness of the proposed power and capacity consensus tracking strategy for distributed storage systems. The power and capacity consensus tracking strategy determines the exchange power among modules and improves the control technology of modular microgrids.

Suggested Citation

  • Xianyong Zhang & Yaohong Huang & Li Li & Wei-Chang Yeh, 2018. "Power and Capacity Consensus Tracking of Distributed Battery Storage Systems in Modular Microgrids," Energies, MDPI, vol. 11(6), pages 1-25, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1439-:d:150498
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    References listed on IDEAS

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    Cited by:

    1. Yilun Shang, 2018. "Resilient Multiscale Coordination Control against Adversarial Nodes," Energies, MDPI, vol. 11(7), pages 1-17, July.
    2. Srete Nikolovski & Hamid Reza Baghaee & Dragan Mlakić, 2018. "ANFIS-Based Peak Power Shaving/Curtailment in Microgrids Including PV Units and BESSs," Energies, MDPI, vol. 11(11), pages 1-23, October.
    3. Daniele Ferreira & Sidelmo Silva & Waner Silva & Danilo Brandao & Gilbert Bergna & Elisabetta Tedeschi, 2022. "Overview of Consensus Protocol and Its Application to Microgrid Control," Energies, MDPI, vol. 15(22), pages 1-35, November.
    4. Yeh, Wei-Chang & He, Min-Fan & Huang, Chia-Ling & Tan, Shi-Yi & Zhang, Xianyong & Huang, Yaohong & Li, Li, 2020. "New genetic algorithm for economic dispatch of stand-alone three-modular microgrid in DongAo Island," Applied Energy, Elsevier, vol. 263(C).

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