Data Center Aggregators' Optimal Bidding and Benefit Allocation Strategy Considering the Spatiotemporal Transfer Characteristics

被引:16
|
作者
Lu, Xiaoxing [1 ,2 ,3 ]
Zhang, Peng [1 ,2 ,3 ]
Li, Kangping [4 ]
Wang, Fei [1 ,2 ,3 ]
Li, Zhengshuo [5 ]
Zhen, Zhao [4 ]
Wang, Tieqiang [6 ]
机构
[1] North China Elect Power Univ, Dept Elect Engn, Baoding 071003, Peoples R China
[2] North China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R China
[3] North China Elect Power Univ, Hebei Key Lab Distributed Energy Storage & Microg, Baoding 071003, Peoples R China
[4] Fsinghua Univ, Dept Electri Cal Engn, Beijing 100084, Peoples R China
[5] Shandong Univ, Sch Elect Engn, Jinan 250061, Peoples R China
[6] State Grid Hebei Elect Power Co Ltd, Dispatch & Control Ctr, Shijiazhuang 050022, Hebei, Peoples R China
基金
国家重点研发计划;
关键词
Data centers; Batteries; Generators; Power systems; Companies; State of charge; Spatiotemporal phenomena; Benefit allocation; data center aggregators (DCAs); demand response (DR); optimal bidding; Shapley value; ELECTRICITY SPOT PRICES; DEMAND-RESPONSE; ENERGY; MANAGEMENT; COALITION; CHINA;
D O I
10.1109/TIA.2021.3090342
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The aggregator, an emerging entity in the electricity market, gathers and creates market power for the small flexible resources, which traditionally contain distributed generation, electric storage, and flexible load. Recently, the exploding growth of information technology demand gives rise to the data centers, whose participation in demand response (DR) is becoming increasingly significant for its remarkable performance in spatiotemporal transfer characteristics compared to conventional facilities. The high-quality DR potential of data centers provides a new opportunity for the profit-seeking data center aggregators (DCAs) to optimize their bidding plans in the day-ahead electricity market. Therefore, this article targets the formulation of the optimal bidding strategy of demand response aggregators (DRAs) to achieve the maximization of the joint benefit of both DCA and data centers. A spatiotemporal transfer characteristics-based optimization strategy is formulated to obtain the electricity purchasing scheme and arrangement of data centers. Meanwhile, the Shapley value method is introduced to design the appropriate and equitable DR reward mechanism that each DCA should compensate its customers, which would serve as a guarantee to ensure data centers' active participation in DR events and lay a solid foundation for the implementation of the DCA's optimal bidding strategy. Numerical tested results demonstrate the effectiveness of the proposed optimal bidding model and the benefit allocation mechanism, which profit both DRA and data centers when participating in DR programs while preserving their daily power demand.
引用
收藏
页码:4486 / 4499
页数:14
相关论文
共 50 条
  • [1] Optimal Bidding Strategy for Electric Vehicle Aggregators in Electricity Markets
    Vagropoulos, Stylianos I.
    Bakirtzis, Anastasios G.
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2013, 28 (04) : 4031 - 4041
  • [2] Optimal strategy for energy allocation and bidding decision of generators considering generation adequacy
    Li, Yating
    He, Chuan
    Liu, Xinyi
    Tang, Jiajun
    Zhang, Zhi
    Li, Jing
    Wang, Kai
    Zhang, Weishi
    Jiang, Hailong
    Yang, Li
    Lin, Zhenzhi
    ENERGY REPORTS, 2021, 7 : 75 - 80
  • [3] Optimal Bidding Strategy for Energy Hub Incorporating Data Center Flexibility
    Fu, Chenchen
    Wang, Jianxiao
    Li, Gengyin
    Zhou, Ming
    Wang, Xuanyuan
    Liu, Zhen
    2021 POWER SYSTEM AND GREEN ENERGY CONFERENCE (PSGEC), 2021, : 139 - 144
  • [4] Scenario Tree Generation Using Data Reconciliation for Aggregators Bidding Strategy
    Afkousi-Paqaleh, Mohammad
    Nouri, Alireza
    Keane, Andrew
    2023 IEEE BELGRADE POWERTECH, 2023,
  • [5] Exact relaxation of complementary constraints for optimal bidding strategy for electric vehicle aggregators
    Chen, Dapeng
    Jing, Zhaoxia
    Li, Zhigang
    Xu, Hedong
    Ji, Tianyao
    IET RENEWABLE POWER GENERATION, 2022, 16 (12) : 2493 - 2507
  • [6] Bi-level optimal bidding strategy of an aggregator in competition with rival aggregators
    Abbasi, Mohammad Hossein
    Taki, Mehrdad
    Zhang, Jiangfeng
    IET SMART GRID, 2020, 3 (06) : 898 - 905
  • [7] Optimal Bidding/Offering Strategy for EV Aggregators under a Novel Business Model
    Chen, Dapeng
    Jing, Zhaoxia
    Tan, Huijuan
    ENERGIES, 2019, 12 (07)
  • [8] Network-Constrained Decentralised Bidding Strategy of DR Aggregators Considering Customer Behaviour
    Afkousi-Paqaleh, Mohammad
    Rigoni, Valentin
    Keane, Andrew
    2021 IEEE PES INNOVATIVE SMART GRID TECHNOLOGY EUROPE (ISGT EUROPE 2021), 2021, : 660 - 665
  • [9] Robust Bidding Strategy and Profit Allocation for Cooperative DSR Aggregators With Correlated Wind Power Generation
    Li, Bosong
    Wang, Xu
    Shahidehpour, Mohammad
    Jiang, Chuanwen
    Li, Zhiyi
    IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2019, 10 (04) : 1904 - 1915
  • [10] Optimal allocation of photovoltaic and storage capacity in low carbon data center considering load transfer demand response
    Liu Y.
    Xiang Y.
    Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2024, 44 (07): : 149 - 155