IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i22p8626-d975735.html
   My bibliography  Save this article

A Cooperative Game-Based Sizing and Configuration of Community-Shared Energy Storage

Author

Listed:
  • Yuzhe Xie

    (State Grid Ningbo Power Supply Company, Ningbo 315000, China)

  • Yan Yao

    (Ningbo Electric Power Design Institute Company, Ningbo 315000, China)

  • Yawu Wang

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 201100, China)

  • Weiqiang Cha

    (State Grid Ningbo Power Supply Company, Ningbo 315000, China)

  • Sheng Zhou

    (State Grid Ningbo Power Supply Company, Ningbo 315000, China)

  • Yue Wu

    (State Grid Ningbo Power Supply Company, Ningbo 315000, China)

  • Chunyi Huang

    (Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 201100, China)

Abstract

Sizing and configuring community-shared energy storage according to the actual demand of community users is important for the development of user-side energy storage. To solve this problem, this paper first proposes a community energy storage cooperative sharing mode containing multiple transaction types and then establishes a sizing and configuration model of community-shared energy storage based on a cooperative game among community users and energy storage operators, in which the loss caused by the capacity decay of energy storage is quantified by a dynamic power loss cost factor. To improve the solving efficiency, a distributed and cooperating solving method based on ADMM is used to solve the sizing and configuration model. On this basis, the bilateral Shapley method is used to allocate the total annual cost according to the marginal expected cost brought by each user. Compared with existing strategies, this paper calculates the economic benefits of community-shared energy storage based on several typical days of each year and quantifies the capacity decay of energy storage by a dynamic power loss cost factor which increases year by year to be closer to the real situation. Finally, the simulation verifies that the model proposed in this paper can be used for the sizing and configuration of community-shared energy storage. Compared with the original annual cost, the total annual cost of the community is reduced by 3.92%, and the annual operation cost of the community which equals annual electricity purchasing cost minus annual electricity selling income plus annual power loss cost is reduced by 25.6%.

Suggested Citation

  • Yuzhe Xie & Yan Yao & Yawu Wang & Weiqiang Cha & Sheng Zhou & Yue Wu & Chunyi Huang, 2022. "A Cooperative Game-Based Sizing and Configuration of Community-Shared Energy Storage," Energies, MDPI, vol. 15(22), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8626-:d:975735
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/22/8626/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/22/8626/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Longxi Li, 2020. "Optimal Coordination Strategies for Load Service Entity and Community Energy Systems Based on Centralized and Decentralized Approaches," Energies, MDPI, vol. 13(12), pages 1-22, June.
    2. Chen, Weidong & Wang, Junnan & Yu, Guanyi & Chen, Jiajia & Hu, Yumeng, 2022. "Research on day-ahead transactions between multi-microgrid based on cooperative game model," Applied Energy, Elsevier, vol. 316(C).
    3. Mohamed El-Hendawi & Zhanle Wang & Xiaoyue Liu, 2022. "Centralized and Distributed Optimization for Vehicle-to-Grid Applications in Frequency Regulation," Energies, MDPI, vol. 15(12), pages 1-22, June.
    4. Kan Xie & Weifeng Zhong & Weijun Li & Yinhao Zhu, 2019. "Distributed Capacity Allocation of Shared Energy Storage Using Online Convex Optimization," Energies, MDPI, vol. 12(9), pages 1-15, April.
    5. Junpei Nan & Jieran Feng & Xu Deng & Chao Wang & Ke Sun & Hao Zhou, 2022. "Hierarchical Low-Carbon Economic Dispatch with Source-Load Bilateral Carbon-Trading Based on Aumann–Shapley Method," Energies, MDPI, vol. 15(15), pages 1-17, July.
    6. Dini, Anoosh & Hassankashi, Alireza & Pirouzi, Sasan & Lehtonen, Matti & Arandian, Behdad & Baziar, Ali Asghar, 2022. "A flexible-reliable operation optimization model of the networked energy hubs with distributed generations, energy storage systems and demand response," Energy, Elsevier, vol. 239(PA).
    7. Uyikumhe Damisa & Nnamdi I. Nwulu, 2022. "Blockchain-Based Auctioning for Energy Storage Sharing in a Smart Community," Energies, MDPI, vol. 15(6), pages 1-12, March.
    8. Parra, David & Norman, Stuart A. & Walker, Gavin S. & Gillott, Mark, 2017. "Optimum community energy storage for renewable energy and demand load management," Applied Energy, Elsevier, vol. 200(C), pages 358-369.
    9. Seyedfarzad Sarfarazi & Marc Deissenroth-Uhrig & Valentin Bertsch, 2020. "Aggregation of Households in Community Energy Systems: An Analysis from Actors’ and Market Perspectives," Energies, MDPI, vol. 13(19), pages 1-37, October.
    10. Hannie Zang & JongWon Kim, 2021. "Reinforcement Learning Based Peer-to-Peer Energy Trade Management Using Community Energy Storage in Local Energy Market," Energies, MDPI, vol. 14(14), pages 1-18, July.
    11. Li, Dongsen & Gao, Ciwei & Chen, Tao & Guo, Xiaoxuan & Han, Shuai, 2021. "Planning strategies of power-to-gas based on cooperative game and symbiosis cooperation," Applied Energy, Elsevier, vol. 288(C).
    12. Huang, Chunyi & Zhang, Mingzhi & Wang, Chengmin & Xie, Ning & Yuan, Zhao, 2022. "An interactive two-stage retail electricity market for microgrids with peer-to-peer flexibility trading," Applied Energy, Elsevier, vol. 320(C).
    13. Barbour, Edward & Parra, David & Awwad, Zeyad & González, Marta C., 2018. "Community energy storage: A smart choice for the smart grid?," Applied Energy, Elsevier, vol. 212(C), pages 489-497.
    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. Wang He & Min Liu & Chaowen Zuo & Kai Wang, 2023. "Massive Multi-Source Joint Outbound and Benefit Distribution Model Based on Cooperative Game," Energies, MDPI, vol. 16(18), pages 1-19, September.

    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. 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. Obara, Shin'ya & Hamanaka, Ryo & El-Sayed, Abeer Galal, 2019. "Design methods for microgrids to address seasonal energy availability – A case study of proposed Showa Antarctic Station retrofits," Applied Energy, Elsevier, vol. 236(C), pages 711-727.
    3. Christian van Someren & Martien Visser & Han Slootweg, 2023. "Sizing Batteries for Power Flow Management in Distribution Grids: A Method to Compare Battery Capacities for Different Siting Configurations and Variable Power Flow Simultaneity," Energies, MDPI, vol. 16(22), pages 1-19, November.
    4. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
    5. Gährs, Swantje & Knoefel, Jan, 2020. "Stakeholder demands and regulatory framework for community energy storage with a focus on Germany," Energy Policy, Elsevier, vol. 144(C).
    6. 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).
    7. Scheller, Fabian & Burkhardt, Robert & Schwarzeit, Robert & McKenna, Russell & Bruckner, Thomas, 2020. "Competition between simultaneous demand-side flexibility options: the case of community electricity storage systems," Applied Energy, Elsevier, vol. 269(C).
    8. Roberts, Mike B. & Bruce, Anna & MacGill, Iain, 2019. "Impact of shared battery energy storage systems on photovoltaic self-consumption and electricity bills in apartment buildings," Applied Energy, Elsevier, vol. 245(C), pages 78-95.
    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. Koirala, Binod Prasad & van Oost, Ellen & van der Windt, Henny, 2018. "Community energy storage: A responsible innovation towards a sustainable energy system?," Applied Energy, Elsevier, vol. 231(C), pages 570-585.
    11. Parra, David & Patel, Martin K., 2019. "The nature of combining energy storage applications for residential battery technology," Applied Energy, Elsevier, vol. 239(C), pages 1343-1355.
    12. Berg, Kjersti & Rana, Rubi & Farahmand, Hossein, 2023. "Quantifying the benefits of shared battery in a DSO-energy community cooperation," Applied Energy, Elsevier, vol. 343(C).
    13. Dong, Siyuan & Kremers, Enrique & Brucoli, Maria & Rothman, Rachael & Brown, Solomon, 2020. "Improving the feasibility of household and community energy storage: A techno-enviro-economic study for the UK," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    14. 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).
    15. Fabian Scheller & Robert Burkhardt & Robert Schwarzeit & Russell McKenna & Thomas Bruckner, 2020. "Competition between simultaneous demand-side flexibility options: The case of community electricity storage systems," Papers 2011.05809, arXiv.org.
    16. Sofiane Kichou & Nikolaos Skandalos & Petr Wolf, 2020. "Evaluation of Photovoltaic and Battery Storage Effects on the Load Matching Indicators Based on Real Monitored Data," Energies, MDPI, vol. 13(11), pages 1-20, May.
    17. Pia Szichta & Ingela Tietze, 2020. "Sharing Economy in der Elektrizitätswirtschaft: Treiber und Hemmnisse [Title sharing economy in the electricity sector: drivers and barriers]," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 28(3), pages 109-125, December.
    18. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    19. 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).
    20. Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).

    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:15:y:2022:i:22:p:8626-:d:975735. 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.