Optimal Pricing Strategy for Data Center Considering Demand Response and Renewable Energy Source Accommodation

被引:9
|
作者
Jiang, Chenwei [1 ,2 ]
Tseng, Chung-Li [3 ]
Wang, Yizheng [1 ,2 ]
Lan, Zhou [2 ]
Wen, Fushuan [4 ,5 ]
Chen, Fei [2 ]
Liang, Liang [6 ]
机构
[1] Zhejiang Univ, Sch Elect Engn, Hangzhou 310027, Peoples R China
[2] State Grid Zhejiang Elect Power Co Ltd, Econ & Technol Res Inst, Hangzhou 310000, Peoples R China
[3] Univ New South Wales, UNSW Business Sch, Sydney, Australia
[4] Tallinn Univ Technol, Dept Elect Power Engn & Mechatron, Tallinn, Estonia
[5] Zhejiang Univ, Coll Elect Engn, Hangzhou, Peoples R China
[6] State Grid Zhejiang Elect Power Co Ltd, Jiaxing Power Supply Co, Jiaxing 314000, Peoples R China
基金
中国国家自然科学基金;
关键词
Servers; Pricing; Costs; Sensitivity; Power systems; Energy consumption; Renewable energy sources; Data center (DC); demand response (DR); pricing strategy; renewable energy source (RES); Stackelberg game; MANAGEMENT;
D O I
10.35833/MPCE.2021.000130
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
With the continuous development of information technology, data centers (DCs) consume significant and ever-growing amounts of electrical energy. Renewable energy sources (RESs) can act as clean solutions to meet this requirement without polluting the environment. Each DC serves numerous users for their data service demands, which are regarded as flexible loads. In this paper, the willingness to pay and time sensitivities of DC users are firstly explored, and the user-side demand response is then devised to improve the overall benefits of DC operation. Then, a Stackelberg game between a DC and its users is proposed. The upper-level model aims to maximize the profit of the DC, in which the time-varying pricing of data services is optimized, and the lower-level model addresses user's optimal decisions for using data services while balancing their time and cost requirements. The original bi-level optimization problem is then transformed into a single-level problem using the Karush-Kuhn-Tucker optimality conditions and strong duality theory, which enables the problem to be solved efficiently. Finally, case studies are conducted to demonstrate the feasibility and effectiveness of the proposed method, as well as the effects of the time-varying data service price mechanism on the RES accommodation.
引用
收藏
页码:345 / 354
页数:10
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