IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i13p3389-d1689045.html
   My bibliography  Save this article

Multi-Mode Operation and Coordination Control Strategy Based on Energy Storage and Flexible Multi-State Switch for the New Distribution Network During Grid-Connected Operation

Author

Listed:
  • Yuechao Ma

    (Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China
    Inner Mongolia Enterprise Key Laboratory of Smart Grid Simulation of Electrical Power System, Hohhot 010020, China
    Department of Electrical Engineering, Baotou Vocational & Technical College, Baotou 014030, China)

  • Jun Tao

    (Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China
    Inner Mongolia Enterprise Key Laboratory of Smart Grid Simulation of Electrical Power System, Hohhot 010020, China)

  • Yu Xu

    (Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China
    Inner Mongolia Enterprise Key Laboratory of Smart Grid Simulation of Electrical Power System, Hohhot 010020, China)

  • Hongbin Hu

    (Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China
    Inner Mongolia Enterprise Key Laboratory of Smart Grid Simulation of Electrical Power System, Hohhot 010020, China)

  • Guangchen Liu

    (College of Electric Power, Inner Mongolia University of Technology, Hohhot 010080, China)

  • Tao Qin

    (Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China
    Inner Mongolia Enterprise Key Laboratory of Smart Grid Simulation of Electrical Power System, Hohhot 010020, China)

  • Xuchen Fu

    (Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China
    Inner Mongolia Enterprise Key Laboratory of Smart Grid Simulation of Electrical Power System, Hohhot 010020, China)

  • Ruiming Liu

    (College of Electric Power, Inner Mongolia University of Technology, Hohhot 010080, China)

Abstract

For a new distribution network with energy storage and a flexible multi-state switch (FMSS), several problems of multi-mode operation and switching, such as the unbalance of feeder loads and feeder faults, among others, should be considered. This paper forwards a coordination control strategy to address the above challenges faced by the FMSS under grid-connected operations. To tackle the multi-mode operation problem, the system’s operational state is divided into multiple working modes according to the operation states of the system, the positions and number of fault feeders, the working states of the transformers, and the battery’s state of charge. To boost the system’s operational reliability and load balance and extend the power supply time for the fault load, the appropriate control objectives in the coordination control layer and control strategies in the equipment layer for different working modes are established for realizing the above multi-directional control objectives. To resolve the phase asynchrony issue among the fault load and other normal working loads caused by the feeder fault, the off-grid phase-locked control based on the V / f control strategy is applied. To mitigate the bus voltage fluctuation caused by the feeder fault switching, the switching control sequence for the planned off-grid is designed, and the power feed-forward control strategy of the battery is proposed for the unplanned off-grid. The simulation results show that the proposed control strategy can ensure the system’s power balance and yield a high-quality flexible power supply during the grid-connected operational state.

Suggested Citation

  • Yuechao Ma & Jun Tao & Yu Xu & Hongbin Hu & Guangchen Liu & Tao Qin & Xuchen Fu & Ruiming Liu, 2025. "Multi-Mode Operation and Coordination Control Strategy Based on Energy Storage and Flexible Multi-State Switch for the New Distribution Network During Grid-Connected Operation," Energies, MDPI, vol. 18(13), pages 1-29, June.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3389-:d:1689045
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/13/3389/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/13/3389/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cao, Wanyu & Wu, Jianzhong & Jenkins, Nick & Wang, Chengshan & Green, Timothy, 2016. "Operating principle of Soft Open Points for electrical distribution network operation," Applied Energy, Elsevier, vol. 164(C), pages 245-257.
    2. Ge, Pingxu & Tang, Daogui & Yuan, Yuji & Guerrero, Josep M. & Zio, Enrico, 2025. "A hierarchical multi-objective co-optimization framework for sizing and energy management of coupled hydrogen-electricity energy storage systems at ports," Applied Energy, Elsevier, vol. 384(C).
    3. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Ding, Fei & Wu, Jianzhong, 2017. "An enhanced SOCP-based method for feeder load balancing using the multi-terminal soft open point in active distribution networks," Applied Energy, Elsevier, vol. 208(C), pages 986-995.
    4. Cao, Wanyu & Wu, Jianzhong & Jenkins, Nick & Wang, Chengshan & Green, Timothy, 2016. "Benefits analysis of Soft Open Points for electrical distribution network operation," Applied Energy, Elsevier, vol. 165(C), pages 36-47.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Chengshan & Song, Guanyu & Li, Peng & Ji, Haoran & Zhao, Jinli & Wu, Jianzhong, 2017. "Optimal siting and sizing of soft open points in active electrical distribution networks," Applied Energy, Elsevier, vol. 189(C), pages 301-309.
    2. Ji, Haoran & Wang, Chengshan & Li, Peng & Song, Guanyu & Yu, Hao & Wu, Jianzhong, 2019. "Quantified analysis method for operational flexibility of active distribution networks with high penetration of distributed generators," Applied Energy, Elsevier, vol. 239(C), pages 706-714.
    3. Wang, Ke & Xue, Yixun & Zhou, Yue & Li, Zening & Chang, Xinyue & Sun, Hongbin, 2024. "Distributed coordinated reconfiguration with soft open points for resilience-oriented restoration in integrated electric and heating systems," Applied Energy, Elsevier, vol. 365(C).
    4. Gonzalez Venegas, Felipe & Petit, Marc & Perez, Yannick, 2021. "Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    5. Moon, Sangkeun, 2025. "Adaptive distribution topology learning on distributed source energisation and islanding," Energy, Elsevier, vol. 320(C).
    6. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Wu, Jianzhong, 2018. "Quantified flexibility evaluation of soft open points to improve distributed generator penetration in active distribution networks based on difference-of-convex programming," Applied Energy, Elsevier, vol. 218(C), pages 338-348.
    7. Su, Hongzhi & Wang, Chengshan & Li, Peng & Liu, Zhelin & Yu, Li & Wu, Jianzhong, 2019. "Optimal placement of phasor measurement unit in distribution networks considering the changes in topology," Applied Energy, Elsevier, vol. 250(C), pages 313-322.
    8. Aithal, Avinash & Li, Gen & Wu, Jianzhong & Yu, James, 2018. "Performance of an electrical distribution network with Soft Open Point during a grid side AC fault," Applied Energy, Elsevier, vol. 227(C), pages 262-272.
    9. Deakin, Matthew & Sarantakos, Ilias & Greenwood, David & Bialek, Janusz & Taylor, Phil C. & Walker, Sara, 2023. "Comparative analysis of services from soft open points using cost–benefit analysis," Applied Energy, Elsevier, vol. 333(C).
    10. Zhichun Yang & Fan Yang & Huaidong Min & Yu Shen & Xu Tang & Yun Hong & Liang Qin, 2023. "A Local Control Strategy for Voltage Fluctuation Suppression in a Flexible Interconnected Distribution Station Area Based on Soft Open Point," Sustainability, MDPI, vol. 15(5), pages 1-13, March.
    11. Wang, Chunling & Liu, Chunming & Zhou, Xiulin & Zhang, Gaoyuan, 2024. "Flexibility-based expansion planning of active distribution networks considering optimal operation of multi-community integrated energy systems," Energy, Elsevier, vol. 307(C).
    12. Bustos, Cristian & Watts, David & Olivares, Daniel, 2019. "The evolution over time of Distributed Energy Resource’s penetration: A robust framework to assess the future impact of prosumage under different tariff designs," Applied Energy, Elsevier, vol. 256(C).
    13. Bastami, Houman & Shakarami, Mahmoud Reza & Doostizadeh, Meysam, 2021. "A decentralized cooperative framework for multi-area active distribution network in presence of inter-area soft open points," Applied Energy, Elsevier, vol. 300(C).
    14. Shamam Alwash & Sarmad Ibrahim & Azher M. Abed, 2022. "Distribution System Reconfiguration with Soft Open Point for Power Loss Reduction in Distribution Systems Based on Hybrid Water Cycle Algorithm," Energies, MDPI, vol. 16(1), pages 1-22, December.
    15. Eshan Karunarathne & Jagadeesh Pasupuleti & Janaka Ekanayake & Dilini Almeida, 2021. "The Optimal Placement and Sizing of Distributed Generation in an Active Distribution Network with Several Soft Open Points," Energies, MDPI, vol. 14(4), pages 1-20, February.
    16. Escalera, Alberto & Prodanović, Milan & Castronuovo, Edgardo D. & Roldan-Perez, Javier, 2020. "Contribution of active management technologies to the reliability of power distribution networks," Applied Energy, Elsevier, vol. 267(C).
    17. Xiao, Jun & Zu, Guoqiang & Wang, Ying & Zhang, Xinsong & Jiang, Xun, 2020. "Model and observation of dispatchable region for flexible distribution network," Applied Energy, Elsevier, vol. 261(C).
    18. Zhengqi Wang & Haoyu Zhou & Hongyu Su, 2022. "Disturbance Observer-Based Model Predictive Super-Twisting Control for Soft Open Point," Energies, MDPI, vol. 15(10), pages 1-19, May.
    19. Qi, Qi & Wu, Jianzhong & Long, Chao, 2017. "Multi-objective operation optimization of an electrical distribution network with soft open point," Applied Energy, Elsevier, vol. 208(C), pages 734-744.
    20. Li, Peng & Ji, Haoran & Yu, Hao & Zhao, Jinli & Wang, Chengshan & Song, Guanyu & Wu, Jianzhong, 2019. "Combined decentralized and local voltage control strategy of soft open points in active distribution networks," Applied Energy, Elsevier, vol. 241(C), pages 613-624.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jeners:v:18:y:2025:i:13:p:3389-:d:1689045. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.