Research on Peer-to-peer Transaction Strategy of Cloud Energy Storage Based on Semi-distributed Structured Topology

被引:0
|
作者
Ma Y. [1 ]
Wu C. [1 ]
Lin X. [1 ]
Chen C. [1 ]
Li Z. [1 ]
Wei F. [1 ]
Sui Q. [1 ]
Zhou D. [1 ]
机构
[1] State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Hubei Province, Wuhan
关键词
cloud energy storage; cooperative game; Nash bargaining model; peer-to-peer network;
D O I
10.13334/j.0258-8013.pcsee.211263
中图分类号
学科分类号
摘要
With the growing demand for energy storage resources and the gradual development of peer-to-peer (P2P) technology, cloud energy storage (CES) is expected to become a new business form of user-side energy storage. Aiming at the problems of poor reliability and unbalanced load of centralized topology P2P transactions, poor scalability of fully distributed topology P2P transactions and overload of low bandwidth nodes, this paper proposed a P2P transaction framework for CES based on a semi-distributed structured topology, which closely coupled energy flow, information flow, and business flow to achieve user privacy protection while taking communication efficiency into account. On this basis, in order to solve the problem of difficulty in achieving global optimization under the hierarchical and multi-subject transaction framework, the cooperative game theory was introduced to construct a two-layer P2P two-stage transaction optimization model of CES operator-community-user. In the first stage, with the goal of maximizing the benefits of the cooperative alliance, a CES operator-community-user two-layer energy storage capacity sharing model was established based on the nested alternating direction multiplier method. In the second stage, a Nash bargaining model that considered the differences in the participation of entities and market factors was proposed, and a pricing mechanism for CES leasing fees was formulated to realize the distribution of benefits. Finally, simulations verified the feasibility and superiority of the proposed CES trading strategy and the fairness of the benefit distribution mechanism, providing a new perspective for the development of CES business. © 2022 Chinese Society for Electrical Engineering. All rights reserved.
引用
收藏
页码:7731 / 7745
页数:14
相关论文
共 43 条
  • [1] Zheng LI, CHEN Siyuan, DONG Wenjuan, Low carbon transition pathway of power sector under carbon emission constraints[J], Proceedings of the CSEE, 41, 12, pp. 3987-4000, (2021)
  • [2] SONG Hang, LIU Youbo, LIU Junyong, Intelligent dynamic pricing of electricity retailers considering distributed energy storage interaction on user side[J], Proceedings of the CSEE, 40, 24, pp. 7959-7972, (2020)
  • [3] LI Haibo, LU Zongxiang, QIAO Ying, Assessment on operational flexibility of power grid with grid-connected large-scale wind farms[J], Power System Technology, 39, 6, pp. 1672-1678, (2015)
  • [4] ZHOU Xiaoxin, CHEN Shuyong, LU Zongxiang, Technology features of the new generation power system in China[J], Proceedings of the CSEE, 38, 7, pp. 1893-1904, (2018)
  • [5] KANG Chongqing, LIU Jingkun, ZHANG Ning, A new form of energy storage in future power system:cloud energy storage[J], Automation of Electric Power Systems, 41, 21, pp. 2-8, (2017)
  • [6] LIU Jingkun, ZHANG Ning, KANG Chongqing, Research framework and basic models for cloud energy storage in power system[J], Proceedings of the CSEE, 37, 12, pp. 3361-3371, (2017)
  • [7] LIU Jichun, CHEN Xue, XIANG Yue, Optimal sizing and investment benefit analysis for energy storage of electricity retailers under market mechanisms considering shared mode[J], Power System Technology, 44, 5, pp. 1740-1749, (2020)
  • [8] GUO Yizong, WANG Chutong, SHI Yunhui, Comprehensive optimization configuration of electric and thermal cloud energy storage in regional integrated energy system[J], Power System Technology, 44, 5, pp. 1611-1621, (2020)
  • [9] CHAKRABORTY P,, BAEYENS E, POOLLA K, Sharing storage in a smart grid: a coalitional game approach[J], IEEE Transactions on Smart Grid, 10, 4, pp. 4379-4390, (2019)
  • [10] FENG Bin, GUO Yizong, CHEN Ye, Charging and discharging strategy of cloud energy storage based on GRU multi-step prediction technology[J], Automation of Electric Power Systems, 45, 9, pp. 46-54, (2021)