IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i18p4614-d1478282.html
   My bibliography  Save this article

Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

Author

Listed:
  • Zheng Shi

    (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China)

  • Lu Yan

    (Yingda Chang’an Insurance Brokers Co., Ltd., Taiyuan 030021, China)

  • Yingying Hu

    (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China)

  • Yao Wang

    (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China)

  • Wenping Qin

    (Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China)

  • Yan Liang

    (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China
    Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Haibo Zhao

    (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China)

  • Yongming Jing

    (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China)

  • Jiaojiao Deng

    (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China)

  • Zhi Zhang

    (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030021, China)

Abstract

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%.

Suggested Citation

  • Zheng Shi & Lu Yan & Yingying Hu & Yao Wang & Wenping Qin & Yan Liang & Haibo Zhao & Yongming Jing & Jiaojiao Deng & Zhi Zhang, 2024. "Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective," Energies, MDPI, vol. 17(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:18:p:4614-:d:1478282
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/18/4614/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/18/4614/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dong, Haiyan & Fu, Yanbo & Jia, Qingquan & Wen, Xiangyun, 2022. "Optimal dispatch of integrated energy microgrid considering hybrid structured electric-thermal energy storage," Renewable Energy, Elsevier, vol. 199(C), pages 628-639.
    2. Xu, Jiazhu & Yi, Yuqin, 2023. "Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: A Nash bargaining approach," Energy, Elsevier, vol. 263(PB).
    3. Ma, Xiaochen & Pan, Yanchun & Zhang, Manzi & Ma, Jianhua & Yang, Wen, 2024. "Impact of carbon emission trading and renewable energy development policy on the sustainability of electricity market: A stackelberg game analysis," Energy Economics, Elsevier, vol. 129(C).
    4. Nie, Yonghui & Qiu, Yu & Yang, Annan & Zhao, Yan, 2024. "Risk-limiting dispatching strategy considering demand response in multi-energy microgrids," Applied Energy, Elsevier, vol. 353(PA).
    5. Rodriguez, Mauricio & Arcos–Aviles, Diego & Martinez, Wilmar, 2023. "Fuzzy logic-based energy management for isolated microgrid using meta-heuristic optimization algorithms," Applied Energy, Elsevier, vol. 335(C).
    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. Yuchen Liu & Zhenhai Dou & Zheng Wang & Jiaming Guo & Jingwei Zhao & Wenliang Yin, 2024. "Optimal Configuration of Electricity-Heat Integrated Energy Storage Supplier and Multi-Microgrid System Scheduling Strategy Considering Demand Response," Energies, MDPI, vol. 17(21), pages 1-23, October.
    2. Rodriguez, Mauricio & Arcos-Aviles, Diego & Guinjoan, Francesc, 2024. "Simple fuzzy logic-based energy management for power exchange in isolated multi-microgrid systems: A case study in a remote community in the Amazon region of Ecuador," Applied Energy, Elsevier, vol. 357(C).
    3. Félix González & Paul Arévalo & Luis Ramirez, 2025. "Game Theory and Robust Predictive Control for Peer-to-Peer Energy Management: A Pathway to a Low-Carbon Economy," Sustainability, MDPI, vol. 17(5), pages 1-23, February.
    4. Sulman Shahzad & Muhammad Abbas Abbasi & Hassan Ali & Muhammad Iqbal & Rania Munir & Heybet Kilic, 2023. "Possibilities, Challenges, and Future Opportunities of Microgrids: A Review," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    5. Li, He & Wang, Pengyu & Fang, Debin, 2024. "Differentiated pricing for the retail electricity provider optimizing demand response to renewable energy fluctuations," Energy Economics, Elsevier, vol. 136(C).
    6. Ziming Zhou & Zihao Wang & Yanan Zhang & Xiaoxue Wang, 2024. "Nash Bargaining-Based Coordinated Frequency-Constrained Dispatch for Distribution Networks and Microgrids," Energies, MDPI, vol. 17(22), pages 1-27, November.
    7. Wu, Biao & Zhang, Shaohua & Yuan, Chenxin & Wang, Xian & Wang, Fei & Zhang, Shengqi, 2024. "Cooperative energy and reserve trading strategies for multiple integrated energy systems based on asymmetric nash bargaining theory," Energy, Elsevier, vol. 313(C).
    8. Ge, Haotian & Zhu, Yu & Zhong, Jiuming & Wu, Liang, 2024. "Day-ahead optimization for smart energy management of multi-microgrid using a stochastic-robust model," Energy, Elsevier, vol. 313(C).
    9. Wanting Yu & Xin Zhang & Mingli Cui & Tiantian Feng, 2024. "Construction and Application of the Double Game Model for Direct Purchase of Electricity by Large Consumers under Consideration of Risk Factors," Energies, MDPI, vol. 17(8), pages 1-24, April.
    10. Yiyun Liu & Jun Wu & Jianjun Li & Jingjing Huang, 2023. "The Diffusion Rule of Demand-Oriented Biogas Supply in Distributed Renewable Energy System: An Evolutionary Game-Based Approach," Sustainability, MDPI, vol. 15(19), pages 1-16, September.
    11. Li, Yiran & Chang, Weiguang & Yang, Qiang, 2025. "Deep reinforcement learning based hierarchical energy management for virtual power plant with aggregated multiple heterogeneous microgrids," Applied Energy, Elsevier, vol. 382(C).
    12. Hu, Chunbin & Wang, Honglei & Li, Chengjiang & Yuan, Xufeng, 2025. "Multi-microgrid cooperative modeling based on power router and time-space interconnection scheduling strategy," Energy, Elsevier, vol. 320(C).
    13. Wei Li & Ruixin Jin & Xiaoyong Ma & Guozun Zhang, 2023. "Capacity Optimal Allocation Method and Frequency Division Energy Management for Hybrid Energy Storage System Considering Grid-Connected Requirements in Photovoltaic System," Energies, MDPI, vol. 16(10), pages 1-16, May.
    14. Hu, Fanshuai & Zhou, Dequn & Pan, Yinghao & Sun, Jinghe & Zhu, Qingyuan, 2025. "Impacts of overlapping regulation on the electricity market concerning renewable portfolio standards and carbon emission trading," Renewable Energy, Elsevier, vol. 238(C).
    15. Abdellatif Soussi & Enrico Zero & Alessandro Bozzi & Roberto Sacile, 2024. "Enhancing Energy Systems and Rural Communities through a System of Systems Approach: A Comprehensive Review," Energies, MDPI, vol. 17(19), pages 1-43, October.
    16. Zhang, Yue & Zhao, Xin-gang & Zhou, Ying & Wang, Hui, 2025. "Impact of combined environmental policies on carbon emission reduction: A system dynamics analysis," Utilities Policy, Elsevier, vol. 94(C).
    17. Liang, Ziwen & Mu, Longhua, 2024. "Multi-agent low-carbon optimal dispatch of regional integrated energy system based on mixed game theory," Energy, Elsevier, vol. 295(C).
    18. Lefeng Cheng & Pengrong Huang & Mengya Zhang & Ru Yang & Yafei Wang, 2025. "Optimizing Electricity Markets Through Game-Theoretical Methods: Strategic and Policy Implications for Power Purchasing and Generation Enterprises," Mathematics, MDPI, vol. 13(3), pages 1-90, January.
    19. Xia, Xiqiang & Li, Jiangwen & Wei, Wei & Benkraiem, Ramzi & Abedin, Mohammad Zoynul, 2025. "Emission reduction levels of manufacturers under carbon trading policies," Energy Economics, Elsevier, vol. 141(C).
    20. Mohtavipour, Seyed Saeid, 2024. "Convex relaxation of two-stage network-constrained stochastic programming for CHP microgrid optimal scheduling," Energy, Elsevier, vol. 308(C).

    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:17:y:2024:i:18:p:4614-:d:1478282. 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.