IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v382y2025ics0306261924025418.html
   My bibliography  Save this article

Trilayer stackelberg game scheduling of active distribution network based on microgrid group leasing shared energy storage

Author

Listed:
  • Qiao, Jinpeng
  • Mi, Yang
  • Ma, Siyuan
  • Han, Yunhao
  • Wang, Peng

Abstract

―A trilayer stackelberg game (SG) schedule strategy is proposed for an active distribution network based on microgrid group leasing shared energy storage. In the upper-layer, the distribution system operator acts as the leader to determine the trading price considering the power demand of the middle and lower layers, which can realize the safe operation and the peak shaving and valley filling of the active distribution network. In the middle-layer, the shared energy storage operator can serve both as the leader to formulate the leasing price and as the follower to respond the trading price, which can guarantee the reliable charging/discharging and efficient utilization of the shared energy storage. In the lower-layer, the microgrid coalition regards as the follower to formulate leasing capacity and to respond the trading price, which can ensure electricity balance and on-site consumption of the renewable energy. Moreover, in order to solve the trilayer SG model effectively, the existence and uniqueness of the equilibrium solution can be proved by taking advantage of the multi-step backward induction method. Then, a distributed nested iterative algorithm is further exploited to avoid the possible oscillation in iterative optimization, which can improve the computational efficiency. Finally, the effectiveness and rationality of the proposed schedule strategy can be verified through the improved IEEE33 bus system and the extended system.

Suggested Citation

  • Qiao, Jinpeng & Mi, Yang & Ma, Siyuan & Han, Yunhao & Wang, Peng, 2025. "Trilayer stackelberg game scheduling of active distribution network based on microgrid group leasing shared energy storage," Applied Energy, Elsevier, vol. 382(C).
    • Handle: RePEc:eee:appene:v:382:y:2025:i:c:s0306261924025418
    DOI: 10.1016/j.apenergy.2024.125157
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924025418
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.125157?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. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.
    2. Xin-gang, Zhao & Ze-qi, Zhang & Yi-min, Xie & Jin, Meng, 2020. "Economic-environmental dispatch of microgrid based on improved quantum particle swarm optimization," Energy, Elsevier, vol. 195(C).
    3. Ehsan, Ali & Yang, Qiang, 2019. "Scenario-based investment planning of isolated multi-energy microgrids considering electricity, heating and cooling demand," Applied Energy, Elsevier, vol. 235(C), pages 1277-1288.
    4. Walker, Awnalisa & Kwon, Soongeol, 2021. "Analysis on impact of shared energy storage in residential community: Individual versus shared energy storage," Applied Energy, Elsevier, vol. 282(PA).
    5. Hou, Langbo & Tong, Xi & Chen, Heng & Fan, Lanxin & Liu, Tao & Liu, Wenyi & Liu, Tong, 2024. "Optimized scheduling of smart community energy systems considering demand response and shared energy storage," Energy, Elsevier, vol. 295(C).
    6. Kim, Wook-Won & Shin, Je-Seok & Kim, Sung-Yul & Kim, Jin-O., 2017. "Operation scheduling for an energy storage system considering reliability and aging," Energy, Elsevier, vol. 141(C), pages 389-397.
    7. Liu, Yixin & Guo, Li & Wang, Chengshan, 2018. "A robust operation-based scheduling optimization for smart distribution networks with multi-microgrids," Applied Energy, Elsevier, vol. 228(C), pages 130-140.
    8. Cagnano, A. & Caldarulo Bugliari, A. & De Tuglie, E., 2018. "A cooperative control for the reserve management of isolated microgrids," Applied Energy, Elsevier, vol. 218(C), pages 256-265.
    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. Lei Zhang & Yuxing Yuan & Su Yan & Hang Cao & Tao Du, 2025. "Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review," Energies, MDPI, vol. 18(10), pages 1-50, May.

    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. Qiao, Jinpeng & Mi, Yang & Shen, Jie & Lu, Changkun & Cai, Pengcheng & Ma, Siyuan & Wang, Peng, 2025. "Optimization schedule strategy of active distribution network based on microgrid group and shared energy storage," Applied Energy, Elsevier, vol. 377(PD).
    2. Ma, Mingtao & Huang, Huijun & Song, Xiaoling & Peña-Mora, Feniosky & Zhang, Zhe & Chen, Jie, 2022. "Optimal sizing and operations of shared energy storage systems in distribution networks: A bi-level programming approach," Applied Energy, Elsevier, vol. 307(C).
    3. Khojasteh, Meysam & Faria, Pedro & Vale, Zita, 2025. "Adaptive robust strategy for energy and regulation Service Management in Local Energy Communities," Applied Energy, Elsevier, vol. 377(PC).
    4. Sturmberg, B.C.P. & Shaw, M.E. & Mediwaththe, C.P. & Ransan-Cooper, H. & Weise, B. & Thomas, M. & Blackhall, L., 2021. "A mutually beneficial approach to electricity network pricing in the presence of large amounts of solar power and community-scale energy storage," Energy Policy, Elsevier, vol. 159(C).
    5. Di Liu & Junwei Cao & Mingshuang Liu, 2022. "Joint Optimization of Energy Storage Sharing and Demand Response in Microgrid Considering Multiple Uncertainties," Energies, MDPI, vol. 15(9), pages 1-20, April.
    6. Li, Qi & Xiao, Xukang & Pu, Yuchen & Luo, Shuyu & Liu, Hong & Chen, Weirong, 2023. "Hierarchical optimal scheduling method for regional integrated energy systems considering electricity-hydrogen shared energy," Applied Energy, Elsevier, vol. 349(C).
    7. Zhou, Bo & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2019. "Data-adaptive robust unit commitment in the hybrid AC/DC power system," Applied Energy, Elsevier, vol. 254(C).
    8. Hu, Mian & Wang, Yan-Wu & Xiao, Jiang-Wen & Lin, Xiangning, 2019. "Multi-energy management with hierarchical distributed multi-scale strategy for pelagic islanded microgrid clusters," Energy, Elsevier, vol. 185(C), pages 910-921.
    9. Walker, Awnalisa & Kwon, Soongeol, 2021. "Design of structured control policy for shared energy storage in residential community: A stochastic optimization approach," Applied Energy, Elsevier, vol. 298(C).
    10. Kang, Hyuna & Jung, Seunghoon & Lee, Minhyun & Hong, Taehoon, 2022. "How to better share energy towards a carbon-neutral city? A review on application strategies of battery energy storage system in city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    11. Zhu, Jianquan & Xia, Yunrui & Mo, Xiemin & Guo, Ye & Chen, Jiajun, 2021. "A bilevel bidding and clearing model incorporated with a pricing strategy for the trading of energy storage use rights," Energy, Elsevier, vol. 235(C).
    12. Zhaonian Ye & Yongzhen Wang & Kai Han & Changlu Zhao & Juntao Han & Yilin Zhu, 2023. "Bi-Objective Optimization and Emergy Analysis of Multi-Distributed Energy System Considering Shared Energy Storage," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    13. Jani, Ali & Jadid, Shahram, 2023. "Two-stage energy scheduling framework for multi-microgrid system in market environment," Applied Energy, Elsevier, vol. 336(C).
    14. Vedat Kiray, 2025. "A Scenario-Based Simulation Study for Economic Viability and Widespread Impact Analysis of Consumption-Side Energy Storage Systems," Energies, MDPI, vol. 18(2), pages 1-26, January.
    15. 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.
    16. Giaouris, Damian & Papadopoulos, Athanasios I. & Patsios, Charalampos & Walker, Sara & Ziogou, Chrysovalantou & Taylor, Phil & Voutetakis, Spyros & Papadopoulou, Simira & Seferlis, Panos, 2018. "A systems approach for management of microgrids considering multiple energy carriers, stochastic loads, forecasting and demand side response," Applied Energy, Elsevier, vol. 226(C), pages 546-559.
    17. Xuewei Pan & Fan Yang & Peiwen Ma & Yijin Xing & Jinye Zhang & Lingling Cao, 2022. "A Game-Theoretic Approach of Optimized Operation of AC/DC Hybrid Microgrid Clusters," Energies, MDPI, vol. 15(15), pages 1-22, July.
    18. Siqin, Zhuoya & Niu, DongXiao & Li, MingYu & Gao, Tian & Lu, Yifan & Xu, Xiaomin, 2022. "Distributionally robust dispatching of multi-community integrated energy system considering energy sharing and profit allocation," Applied Energy, Elsevier, vol. 321(C).
    19. Wei, Jingdong & Zhang, Yao & Wang, Jianxue & Cao, Xiaoyu & Khan, Muhammad Armoghan, 2020. "Multi-period planning of multi-energy microgrid with multi-type uncertainties using chance constrained information gap decision method," Applied Energy, Elsevier, vol. 260(C).
    20. Khanahmadi, Abbas & Ghaffarpour, Reza, 2022. "A cost-effective and emission-Aware hybrid system considering uncertainty: A case study in a remote area," Renewable Energy, Elsevier, vol. 201(P1), pages 977-992.

    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:382:y:2025:i:c:s0306261924025418. 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.