IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v336y2023ics0306261923002313.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923002313
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.120867?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohamed Elhefnawy & Ahmed Ragab & Mohamed-Salah Ouali, 2023. "Polygon generation and video-to-video translation for time-series prediction," Journal of Intelligent Manufacturing, Springer, vol. 34(1), pages 261-279, January.
    2. Xu, Yang & Li, Ming-Jia & Zheng, Zhang-Jing & Xue, Xiao-Dai, 2018. "Melting performance enhancement of phase change material by a limited amount of metal foam: Configurational optimization and economic assessment," Applied Energy, Elsevier, vol. 212(C), pages 868-880.
    3. Zeng, Zhichen & Ni, Dong & Xiao, Gang, 2022. "Real-time heliostat field aiming strategy optimization based on reinforcement learning," Applied Energy, Elsevier, vol. 307(C).
    4. Si, Tong & Wang, Chunbo & Liu, Ruiqi & Guo, Yusheng & Yue, Shuang & Ren, Yujie, 2020. "Multi-criteria comprehensive energy efficiency assessment based on fuzzy-AHP method: A case study of post-treatment technologies for coal-fired units," Energy, Elsevier, vol. 200(C).
    5. Sun, Jie & Zheng, Menglian & Yang, Zhongshu & Yu, Zitao, 2019. "Flow field design pathways from lab-scale toward large-scale flow batteries," Energy, Elsevier, vol. 173(C), pages 637-646.
    6. Wang, Kun & He, Ya-Ling & Zhu, Han-Hui, 2017. "Integration between supercritical CO2 Brayton cycles and molten salt solar power towers: A review and a comprehensive comparison of different cycle layouts," Applied Energy, Elsevier, vol. 195(C), pages 819-836.
    7. Ma, Zhao & Li, Ming-Jia & Zhang, K. Max & Yuan, Fan, 2021. "Novel designs of hybrid thermal energy storage system and operation strategies for concentrated solar power plant," Energy, Elsevier, vol. 216(C).
    8. 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.
    9. Jefimowski, Włodzimierz & Szeląg, Adam & Steczek, Marcin & Nikitenko, Anatolii, 2020. "Vanadium redox flow battery parameters optimization in a transportation microgrid: A case study," Energy, Elsevier, vol. 195(C).
    10. Shouguang Yao & Xiaofei Sun & Min Xiao & Jie Cheng & Yaju Shen, 2019. "Equivalent Circuit Model Construction and Dynamic Flow Optimization Based on Zinc–Nickel Single-Flow Battery," Energies, MDPI, vol. 12(4), pages 1-17, February.
    11. de la Rue du Can, Stephane & Pudleiner, David & Pielli, Katrina, 2018. "Energy efficiency as a means to expand energy access: A Uganda roadmap," Energy Policy, Elsevier, vol. 120(C), pages 354-364.
    12. Lenore Newman & Robert Newell & Colin Dring & Alesandros Glaros & Evan Fraser & Zsofia Mendly-Zambo & Arthur Gill Green & Krishna Bahadur KC, 2023. "Agriculture for the Anthropocene: novel applications of technology and the future of food," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 15(3), pages 613-627, June.
    13. Salvatori, Simone & Benedetti, Miriam & Bonfà, Francesca & Introna, Vito & Ubertini, Stefano, 2018. "Inter-sectorial benchmarking of compressed air generation energy performance: Methodology based on real data gathering in large and energy-intensive industrial firms," Applied Energy, Elsevier, vol. 217(C), pages 266-280.
    14. Alexander Melnik & Irina Naoumova & Kirill Ermolaev & Jerome Katrichis, 2021. "Driving Innovation through Energy Efficiency: A Russian Regional Analysis," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
    15. Amir Abolhassani & Gale Boyd & Majid Jaridi & Bhaskaran Gopalakrishnan & James Harner, 2023. "“Is Energy That Different from Labor?” Similarity in Determinants of Intensity for Auto Assembly Plants," Energies, MDPI, vol. 16(4), pages 1-35, February.
    16. Zhao, Tian & Li, Hang & Li, Xia & Sun, Qing-Han & Fang, Xuan-Yi & Ma, Huan & Chen, Qun, 2024. "A frequency domain dynamic simulation method for heat exchangers and thermal systems," Energy, Elsevier, vol. 286(C).
    17. Hassan, Taimoor & Song, Huaming & Khan, Yasir & Kirikkaleli, Dervis, 2022. "Energy efficiency a source of low carbon energy sources? Evidence from 16 high-income OECD economies," Energy, Elsevier, vol. 243(C).
    18. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    19. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2022. "Institutional quality and its spatial spillover effects on energy efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    20. Marco Briceño-León & Dennys Pazmiño-Quishpe & Jean-Michel Clairand & Guillermo Escrivá-Escrivá, 2021. "Energy Efficiency Measures in Bakeries toward Competitiveness and Sustainability—Case Studies in Quito, Ecuador," Sustainability, MDPI, vol. 13(9), pages 1-20, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:336:y:2023:i:c:s0306261923002313. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.