Energy Portfolio Optimization of Data Centers

被引:65
作者
Ghamkhari, Mahdi [1 ]
Wierman, Adam [2 ]
Mohsenian-Rad, Hamed [1 ]
机构
[1] Univ Calif Riverside, Dept Elect & Comp Engn, Riverside, CA 92521 USA
[2] CALTECH, Dept Comp & Math Sci, Pasadena, CA 91125 USA
基金
美国国家科学基金会;
关键词
Data centers; energy portfolio; day-ahead and real-time markets; reserve; renewable generation; energy storage; PIECEWISE-LINEAR-APPROXIMATION; GREEN DATA CENTERS; OPTIMAL POWER; CONVEX; MANAGEMENT; RISK; DEMAND;
D O I
10.1109/TSG.2015.2510428
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];
摘要
Data centers have diverse options to procure electricity. However, the current literature on exploiting these options is very fractured. Specifically, it is still not clear how utilizing one energy option may affect selecting other energy options. To address this open problem, we propose a unified energy portfolio optimization framework that takes into consideration a broad range of energy choices for data centers. Despite the complexity and nonlinearity of the original models, the proposed analysis boils down to solving tractable linear mixed-integer stochastic programs. Using experimental electricity market and Internet workload data, various insightful numerical observations are reported. It is shown that the key to link different energy options with different short-and long-term profit characteristics is to conduct risk management at different time horizons. Also, there is a direct relationship between data centers' service-level agreement parameters and their ability to exploit certain energy options. The use of on-site storage and the deployment of geographical workload distribution can particularly help data centers in utilizing high-risk energy choices, such as offering ancillary services or participating in wholesale electricity markets.
引用
收藏
页码:1898 / 1910
页数:13
相关论文
共 63 条
[1]
[Anonymous], IEEE SYST J IN PRESS
[2]
[Anonymous], LOAD PART ERCOT NOD
[3]
[Anonymous], P IEEE WCSP HANGZH C
[4]
[Anonymous], 2014, INPROC INT GREENCOMP
[5]
[Anonymous], IEEE COMMUN IN PRESS
[6]
[Anonymous], 2003, ORNLTM200319
[7]
[Anonymous], 2003, Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management
[8]
[Anonymous], 2010, EPRINT ARXIV
[9]
[Anonymous], PJM HOURLY REAL TIME
[10]
[Anonymous], PJM CAPACITY MARKET