Community Energy Cooperation With the Presence of Cheating Behaviors

被引:76
作者
Cui, Shichang [1 ,2 ]
Wang, Yan-Wu [1 ,2 ]
Shi, Yang [3 ,4 ]
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, Key Lab Image Proc & Intelligent Control, Minist Educ, Wuhan 430074, Peoples R China
[3] Univ Victoria, Dept Mech Engn, Victoria, BC V8W 3P6, Canada
[4] Univ Victoria, Inst Integrated Energy Syst, Victoria, BC V8W 3P6, Canada
关键词
Optimization; Games; Energy storage; Renewable energy sources; Investment; Economics; Computational modeling; Photovoltaic prosumer; community energy storage; energy cooperation; Nash bargaining; cheating behavior; STORAGE; MANAGEMENT; PV;
D O I
10.1109/TSG.2020.3022792
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This article investigates the energy cooperation between photovoltaic prosumers and community energy storage (CES) to improve community energy efficiency. The optimal energy sharing profiles between prosumers and CES are firstly derived by solving the energy optimization problem minimizing social energy cost. To guarantee the incentives for prosumers and CES to participate in the energy cooperation, a Nash bargaining based benefits sharing model is presented to determine the energy sharing payments. Two implementation modes, i.e., Data-Centric and Prosumers-to-CES mode, are developed to protect privacy for both prosumers and CES. Cheating behaviors in benefits sharing, the critical yet challenging matter, are analyzed; a cheating equilibrium based solution is proposed and achieved by a relaxation algorithm for a stable cooperation. In addition, the alternating direction method of multipliers with adaptive parameter selection is introduced to solve the formulated problems in a distributed way. Numerical simulation tests show the efficiency of the novel models.
引用
收藏
页码:561 / 573
页数:13
相关论文
共 34 条
  • [1] 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
  • [2] [Anonymous], 2011, P ACM SIGMETRICS JOI
  • [3] [Anonymous], 2017, P IEEE POW EN SOC GE
  • [4] 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
  • [5] 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
  • [6] 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
  • [7] An Agent-Based Hierarchical Bargaining Framework for Power Management of Multiple Cooperative Microgrids
    Dehghanpour, Kaveh
    Nehrir, Hashem
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (01) : 514 - 522
  • [8] Evaluating the limits of solar photovoltaics (PV) in traditional electric power systems
    Denholm, Paul
    Margolis, Robert M.
    [J]. ENERGY POLICY, 2007, 35 (05) : 2852 - 2861
  • [9] Optimal Design of Community Battery Energy Storage Systems With Prosumers Owning Electric Vehicles
    El-Batawy, Shady A.
    Morsi, Walid G.
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (05) : 1920 - 1931
  • [10] Bargaining-based cooperative energy trading for distribution company and demand response
    Fan, Songli
    Ai, Qian
    Piao, Longjian
    [J]. APPLIED ENERGY, 2018, 226 : 469 - 482