Research on shared energy storage pricing based on Nash gaming considering storage for frequency modulation and demand response of prosumers

被引:0
|
作者
Li, Jinchao [1 ]
Wu, Zijing [1 ]
Lan, Xinyi [1 ]
Yang, Zenan [1 ]
Li, Shiwei [1 ]
Yang, Liunan [1 ]
机构
[1] North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
基金
中国国家自然科学基金;
关键词
Independent Shared Energy Storage (ISES); Prosumer; Nash gaming; Demand response; Frequency modulation market;
D O I
10.1016/j.est.2024.113874
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the continuous development of distributed photovoltaic, the government has accelerated a variety of electricity trading mechanisms as well as energy storage, prosumer participation in the multi-market to promote the consumption of PV. For small aggregations of industrial prosumers, the question of the benefits of interaction with energy storage in complex market environments must be fully considered. This paper presents a comprehensive analysis of the role of energy storage in auxiliary services and the user's demand response market. The concept of Nash equilibrium is employed to develop a model of electric energy interaction and benefit distribution between independent energy storage investment operators and industrial prosumers. The model first derives the internal interaction power through coalition cooperation and then the interaction tariff through an internal game, and uses alternating vector multiplier method to solve it in a distributed way. Compared with the mode of self-built energy storage, an 8.2 %, the three prosumers' cost has decreased by 8.4 %, 7.4 % and 16.0 % respectively, and the energy storage yield was 7.8 %. The calculation example demonstrates that this collaborative model can effectively consume PV, reduce peaks and fill valleys. Such a system has the potential to reduce user costs and, weaken internal competition. Furthermore, it is capable of responding to changes in time-of-use (TOU) tariffs and loads.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Demand-side shared energy storage pricing strategy based on stackelberg-Nash game
    Cui, Jindong
    Zhu, Zengchen
    Qu, Guoli
    Wang, Yuqing
    Li, Ruotong
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2025, 164
  • [2] Research on interval optimization of power system considering shared energy storage and demand response
    Zeng, Linjun
    Gong, Yongguo
    Xiao, Hui
    Chen, Tianjiao
    Gao, Wenzhong
    Liang, Jian
    Peng, Shibo
    JOURNAL OF ENERGY STORAGE, 2024, 86
  • [3] Research on nash game model for user side shared energy storage pricing
    Weijie Qian
    Chao Chen
    Liwu Gong
    Wei Zhang
    Scientific Reports, 13
  • [4] Research on nash game model for user side shared energy storage pricing
    Qian, Weijie
    Chen, Chao
    Gong, Liwu
    Zhang, Wei
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [5] Optimal Configuration of Shared Energy Storage Considering the Incentive-Based Demand Response
    Ma, Lei
    Li, Xiaozhu
    Du, Xili
    Chen, Laijun
    2022 6TH INTERNATIONAL CONFERENCE ON POWER AND ENERGY ENGINEERING, ICPEE, 2022, : 288 - 293
  • [6] Optimization Configuration of Shared Energy Storage Users Considering Demand Response Based on Blockchain
    Sun, Yifan
    Wang, Lin
    Jiang, Yaoxian
    Xu, Ziyun
    Xu, Wenbin
    2022 12TH INTERNATIONAL CONFERENCE ON POWER AND ENERGY SYSTEMS, ICPES, 2022, : 753 - 757
  • [7] Optimal Energy Storage Configuration of Prosumers with Uncertain Photovoltaic in the Presence of Customized Pricing-Based Demand Response
    Pan, Luwen
    Chen, Jiajia
    SUSTAINABILITY, 2024, 16 (06)
  • [8] Shared Energy Storage Planning for Data Center Alliance Considering Demand Response
    Wu Y.
    Fang J.
    Ai X.
    Cui S.
    Xue X.
    Wen J.
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2023, 47 (07): : 42 - 50
  • [9] An evolutionary planning method for distribution networks considering prosumers and shared energy storage
    Han, Jinglin
    Feng, Xichun
    Chen, Zhiyong
    Hu, Ping
    Zhao, Hui
    Chen, Yubing
    Liu, Nian
    FRONTIERS IN ENERGY RESEARCH, 2024, 12
  • [10] Optimized scheduling of smart community energy systems considering demand response and shared energy storage
    Hou, Langbo
    Tong, Xi
    Chen, Heng
    Fan, Lanxin
    Liu, Tao
    Liu, Wenyi
    Liu, Tong
    ENERGY, 2024, 295