Economic Storage Sharing Framework: Asymmetric Bargaining-Based Energy Cooperation

被引:66
作者
Cui, Shichang [1 ,2 ]
Wang, Yan-Wu [1 ,2 ]
Liu, Xiao-Kang [1 ,2 ]
Wang, Zhuo [1 ,2 ]
Xiao, Jiang-Wen [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Minist Educ, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Energy storage; Games; Renewable energy sources; Informatics; Economics; Resource management; Standards; Asymmetric bargaining; distributed optimization; energy cooperation; energy storage providers (ESPs); prosumers; GAME; BUILDINGS; NETWORKS; PV;
D O I
10.1109/TII.2021.3053296
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, we propose an economic storage sharing framework for prosumers and energy storage providers (ESPs) to promote renewable energy utilization cooperatively. The optimal shared capacities of ESPs and the energy sharing profiles of prosumers are first derived via minimizing social energy costs. Then the storage sharing profits of ESPs and the energy sharing payments of prosumers are successively determined by the asymmetric bargaining-based benefits sharing model. Specifically, the prosumer group bargains with the ESPs with the nominal required capacity and the shared capacities as their bargaining power to share the storage sharing benefits. Then prosumers bargain with each other to share the energy sharing benefits with their bargaining power quantified by a nonlinear energy sharing mapping method. Therefore, the benefits sharing model based on the contributions of prosumers and ESPs is fair enough for the participants. Numerical simulation tests verify the efficiency of the proposed framework.
引用
收藏
页码:7489 / 7500
页数:12
相关论文
共 36 条
  • [1] Abdulla Khalid, 2018, IEEE Transactions on Smart Grid, V9, P2086, DOI [10.1109/PESGM.2017.8273930, 10.1109/TSG.2016.2606490]
  • [2] A Distributed and Resilient Bargaining Game for Weather-Predictive Microgrid Energy Cooperation
    An, Lu
    Duan, Jie
    Chow, Mo-Yuen
    Duel-Hallen, Alexandra
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (08) : 4721 - 4730
  • [3] [Anonymous], 2020, ELECT PRICE TABLE SH ELECT PRICE TABLE SH
  • [4] [Anonymous], 2017, PVWATTS CALCULATOR
  • [5] [Anonymous], 2017, Southern California Edison Company's Department of Defense Vehicle-to-grid Final Report
  • [6] Community energy storage: A smart choice for the smart grid?
    Barbour, Edward
    Parra, David
    Awwad, Zeyad
    Gonzalez, Marta C.
    [J]. APPLIED ENERGY, 2018, 212 : 489 - 497
  • [7] Distributed optimization and statistical learning via the alternating direction method of multipliers
    Boyd S.
    Parikh N.
    Chu E.
    Peleato B.
    Eckstein J.
    [J]. Foundations and Trends in Machine Learning, 2010, 3 (01): : 1 - 122
  • [8] On the convergence of the direct extension of ADMM for three-block separable convex minimization models with one strongly convex function
    Cai, Xingju
    Han, Deren
    Yuan, Xiaoming
    [J]. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2017, 66 (01) : 39 - 73
  • [9] Coalitional Game-Based Cost Optimization of Energy Portfolio in Smart Grid Communities
    Chis, Adriana
    Koivunen, Visa
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (02) : 1960 - 1970
  • [10] Peer-to-Peer Energy Sharing Among Smart Energy Buildings by Distributed Transaction
    Cui, Shichang
    Wang, Yan-Wu
    Xiao, Jiang-Wen
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (06) : 6491 - 6501