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The study of energy filtering management process for microgrid based on the dynamic response model of vanadium redox flow battery

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  • Ni, Jing-Wei
  • Li, Ming-Jia
  • Ma, Teng

Abstract

For the efficient application of vanadium redox flow battery (VRB) in microgrid containing the clean renewable energy and advanced coal-fired power system such as the supercritical carbon dioxide (S-CO2) Brayton cycle power plant, a feasible energy filtering optimization process is proposed in this paper. A coupled dynamic response model of VRB and an optimized load distribution algorithm are covered in the process. First, the Ustack-Ibattery-SOC curves are fitted based on the coupled calculation model of VRB. The equivalent resistance of the simplified equivalent circuit model is further calculated. The dynamic response model is refined for the fast calculation of real-time efficiencies. Second, a basic operation scheme and an optimized operation scheme based on the moving average filtering method are selected as the load distribution algorithms. An energy filtering optimization management process that includes a configuration optimization design part and a load distribution part is further constructed. Finally, a case application is carried out to verify the feasibility of the proposed energy management process. The relevant results are presented as follows. First, the combination of the experimental data and the fitted curves can be used to calculate the equivalent resistance of the dynamic response model. The maximum Ustack of 86.14 V is obtained at the SOC of 0.99 and Ibattery of 10A when charging. Second, when applying the optimized operation scheme, the time average efficiency of VRB is operating at an efficient level of 82.75%. The change frequency of load command for each equipment and its dynamic response characteristic can be well matched. Finally, compared to the case where the basic operation scheme is selected in the experimental system, the time average efficiency of VRB is increased from 69.50% to 82.13%., the time average efficiency of S-CO2 power plant is increased from 39.79% to 40.02%. The application of energy filtering optimization management process for the actual microgrid is feasible. The study can provide the operation scheme and case application for VRB energy storage system in the actual microgrid.

Suggested Citation

  • Ni, Jing-Wei & Li, Ming-Jia & Ma, Teng, 2023. "The study of energy filtering management process for microgrid based on the dynamic response model of vanadium redox flow battery," Applied Energy, Elsevier, vol. 336(C).
    • Handle: RePEc:eee:appene:v:336:y:2023:i:c:s0306261923002313
    DOI: 10.1016/j.apenergy.2023.120867
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    References listed on IDEAS

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    1. Li, Ming-Jia & Tao, Wen-Quan, 2017. "Review of methodologies and polices for evaluation of energy efficiency in high energy-consuming industry," Applied Energy, Elsevier, vol. 187(C), pages 203-215.
    2. Qingwu Gong & Jiazhi Lei, 2017. "Design of a Bidirectional Energy Storage System for a Vanadium Redox Flow Battery in a Microgrid with SOC Estimation," Sustainability, MDPI, vol. 9(3), pages 1-15, March.
    3. Wang, Tao & Fu, Jiahui & Zheng, Menglian & Yu, Zitao, 2018. "Dynamic control strategy for the electrolyte flow rate of vanadium redox flow batteries," Applied Energy, Elsevier, vol. 227(C), pages 613-623.
    4. Ma, Teng & Li, Ming-Jia & Xu, Jin-Liang & Cao, Feng, 2019. "Thermodynamic analysis and performance prediction on dynamic response characteristic of PCHE in 1000 MW S-CO2 coal fired power plant," Energy, Elsevier, vol. 175(C), pages 123-138.
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    Cited by:

    1. Zhang, Teng & Li, Ming-Jia & Ni, Jing-Wei & Qian, Cun-Cun, 2024. "Study of dynamic performance of PEMFC-based CCHP system in a data center based on real-time load and a novel synergistic control method with variable working conditions," Energy, Elsevier, vol. 300(C).
    2. Ma, Teng & Li, Ming-Jia & Xu, Hang, 2024. "Thermal energy storage capacity configuration and energy distribution scheme for a 1000MWe S–CO2 coal-fired power plant to realize high-efficiency full-load adjustability," Energy, Elsevier, vol. 294(C).
    3. Ouyang, Tiancheng & Zhang, Mingliang & Qin, Peijia & Tan, Xianlin, 2024. "Flow battery energy storage system for microgrid peak shaving based on predictive control algorithm," Applied Energy, Elsevier, vol. 356(C).

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