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浙江大学学报(工学版)
计算机科学     
智能电网下数据中心能耗费用优化综述
黄焱, 王鹏, 谢高辉, 安俊秀
1. 中国科学院成都计算机应用研究所, 四川 成都 610041; 
2. 中国科学院大学, 北京 100049;
3. 西南民族大学, 四川 成都 610225; 
4. 广州五舟科技股份有限公司技术研究院, 广东 广州 510000;
5. 成都信息工程大学, 四川 成都 610225
Data center energy cost optimization in smart grid: a review
HUANG Yan, WANG Peng, XIE Gao hui, AN Jun xiu
1. Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu 610041, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China; 
3. Southwest University for Nationalities, Chengdu 610225, China; 
4. Academy of Technology, Guangzhou Wuzhou Technology Corporation, Guangzhou 510000, China; 
5. Chengdu University of Information Technology, Chengdu 610225, China
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摘要:

在电价随时间和地理位置波动的智能电网环境下,分布式数据中心运营商在满足各种内外部约束条件下,根据外部负载类型和负载量的变化,通过负载分配、节点状态控制、使用能量存储设备等方法对能耗费用优化目标以及碳排放量、网络带宽费用、响应时间、电网稳定性等协同优化目标进行优化.介绍数据中心的能耗构成和能耗费用优化问题的基本模型,从调整运行节点数、动态电压频率调整(DVFS)、负载分配、部分执行、使用不间断电源(UPS)、使用可再生能源、与电网交互、虚拟化8个方面对数据中心能耗费用优化方法和研究进展进行分类、总结、对比;未来的研究热点包括多目标优化、数据中心需求响应、节点级UPS、可再生能源发电设施、在线优化算法、能源互联网等.

Abstract:

Electricity price varies with time and geographic position in smart grid. According to the chage of external load type and loading capacity, data center operators optimize data center energy cost, carbon emission, network cost, response time, grid stability through load distribution, node state controling and using energy storage to meet internal and external constraints. Energy structure of data center was analyzed; a basic model of data center energy cost optimization problem was proposed. Specially, a taxonomy, comparison and peroration of the latest researchs in data center energy cost optimization problem were provided from eight key perspectives: dynamic running node number adjustment, dynamic voltage and frequency scaling (DVFS), load distribution, partial execution, using uninterruptible power supply (UPS), using renewable energy, interaction with smart grid, virtualization. Further research hotspots include multi-objective optimization, data center demand response, distributed UPS, renewable energy generating plants, online algorithm, energy internet.

出版日期: 2016-12-08
:  TP 393  
基金资助:

国家自然科学基金资助项目(60702075);广东省科技厅高新技术产业化科技攻关资助项目(2011B010200007);四川省青年科学基金资助项目(09ZQ026068);成都市创新发展战略研究资助项目(11RKYB016ZF);四川省高校重点实验室开放基金资助项目(MSSB-2015-9).

通讯作者: 王鹏,男,教授,博导. ORCID: 0000-0002-8551-921X.     E-mail: yunzjs@163.com
作者简介: 黄焱(1982—),男,博士生,从事智能优化算法研究. ORCID: 0000-0003-3896-5636. E-mail: hep128@qq.com
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黄焱, 王鹏, 谢高辉, 安俊秀. 智能电网下数据中心能耗费用优化综述[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2016.12.020.

HUANG Yan, WANG Peng, XIE Gao hui, AN Jun xiu. Data center energy cost optimization in smart grid: a review. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2016.12.020.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2016.12.020        http://www.zjujournals.com/eng/CN/Y2016/V50/I12/2386

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