计及负载特性的数据中心微电网双层优化配置
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TM73

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国家自然科学基金资助项目(52177082);国家电网有限公司总部科技项目(5700-202258216A-1-1-ZN)


Bi-level optimal configuration of microgrid in data center considering load characteristics
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    摘要:

    为解决数据中心微电网前期容量规划不合理,无法适应数据中心运行特性的问题,同时为提高数据中心微电网的供电经济性和可再生能源消纳能力,文中提出了计及负载特性的数据中心微电网容量双层优化配置模型。使用基于场景缩减的选择方法应对可再生能源出力的不确定性,同时解决大量场景带来的计算复杂性问题。根据不同负载的特性,考虑其时间维度上的灵活性,制定相应的负载分配策略。采用带有精英策略的非支配排序遗传算法(non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)与 Gurobi结合的方式进行求解,最后利用模糊多属性决策方法获得折衷最优解,合理规划微电网内储能系统、光伏和风机的容量。算例表明,所提方法降低了数据中心微电网建设与运行成本,减少了碳排放,提高了数据中心运营商的满意度。

    Abstract:

    The problem that the early capacity planning of microgrid in data center is unreasonable and cannot adapt to the operation characteristics of data center has not been solved. At the same time,in order to improve the power supply economy and renewable energy consumption capacity of the microgrid in data center,a bi-level optimal configuration model of the microgrid capacity in data center taking into account the load characteristics is proposed in this paper. Scenario reduction-based selection method is used to deal with the uncertainty of renewable energy and the computational complexity caused by a large number of scenarios. The corresponding load scheduling strategies are proposed according to the characteristics of different loads together with their flexibility. The problem of capacity planning for different microgrid resources,including energy storage system,photovoltaic and wind turbine,is solved by using non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) and Gurobi. Finally,the conpromise optimal soulation is obtained by the fuzzy multi-attribute decision-making approach. The simulation results show that the proposed approach can reduce the construction costs,operation costs and carbon emissions of data center microgrids. Besides,the satisfaction of data center operators is improved.

    参考文献
    [1] 冯成,王毅,陈启鑫,等. 能源互联网下的数据中心能量管理综述[J]. 电力自动化设备,2020,40(7):1-9. FENG Cheng,WANG Yi,CHEN Qixin,et al. Review of energy management for data centers in energy Internet[J]. Electric Power Automation Equipment,2020,40(7):1-9.
    [2] 王圆圆,韩丁,白宏坤,等. 能源大数据中心运营管理标准体系框架构建及实践路径[J]. 电力信息与通信技术,2022,20(3):20-25. WANG Yuanyuan,HAN Ding,BAI Hongkun,et al. Construction and practice path of operation management standard system framework of energy big data center[J]. Electric Power Information and Communication Technology,2022,20(3):20-25.
    [3] 张文佺,王晓烨,乔军晶,等. 点亮绿色云端:中国数据中心能耗与可再生能源使用潜力研究[R]. 北京:绿色和平,华北电力大学,2019. ZHANG Wenquan,WANG Xiaoye,QIAO Junjin,et al. Lighting up the green cloud:research on the energy consumption and renewable energy utilization potential of data centers in China[R]. Beijing:Greenpeace,North China Electric Power University,2019.
    [4] 工业信息化部. 新型数据中心发展三年行动计划(2021-2023年). (2021-07-14). https://www.miit.gov.cn/jgsj/txs/wjfb/art/2021/art_12cc04dc9daf4d57a7038811a57383b6.html. Ministry of Industry and Information Technology. Three year action plan for the development of new data center(2021-2023). (2021-07-14). https://www.miit.gov.cn/jgsj/txs/wjfb/art/2021/art_12cc04dc9daf4d57a7038811a57383b6.html.
    [5] 王继业,周春雷,李洋,等. 数据中心关键技术和发展趋势研究综述[J]. 电力信息与通信技术,2022,20(8):1-21. WANG Jiye,ZHOU Chunlei,LI Yang,et al. Review of key technologies and development trend of data center construction[J]. Electric Power Information and Communication Technology,2022,20(8):1-21.
    [6] 余潇潇,马玉草,宋福龙,等. 数据中心能耗建模及能量调节综述[J]. 电力信息与通信技术,2022,20(8):38-49. YU Xiaoxiao,MA Yucao,SONG Fulong,et al. Overview of data center energy consumption modeling and demand response[J]. Electric Power Information and Communication Technology,2022,20(8):38-49.
    [7] YU L,JIANG T,ZOU Y L. Real-time energy management for cloud data centers in smart microgrids[J]. IEEE Access,2016,4:941-950.
    [8] 李彬,杜亚彬,曹望璋,等. 考虑风光储互补与工作负载分配的数据中心优化调度[J]. 现代电力,2022,39(3):356-363. LI Bin,DU Yabin,CAO Wangzhang,et al. Optimal scheduling of data center considering wind-solar-storage complementary and workload distribution[J]. Modern Electric Power,2022,39(3):356-363.
    [9] 吴云芸,方家琨,艾小猛,等. 计及多种储能协调运行的数据中心实时能量管理[J]. 电力自动化设备,2021,41(10):82-89. WU Yunyun,FANG Jiakun,AI Xiaomeng,et al. Real-time energy management of data center considering coordinated operation of multiple types of energy storage[J]. Electric Power Automation Equipment,2021,41(10):82-89.
    [10] DING Z H,XIE L Y,LU Y,et al. Emission-aware stochastic resource planning scheme for data center microgrid considering batch workload scheduling and risk management[C]//IEEE/IAS 54th Industrial and Commercial Power Systems Technical Conference (I&CPS). Niagara Falls,ON,Canada. IEEE,2018:1-9.
    [11] 祁兵,曹望璋,李彬,等. 考虑托管式数据中心负荷调节不确定性的区间优化模型[J]. 电网技术,2022,46(1):39-49. QI Bing,CAO Wangzhang,LI Bin,et al. Interval optimization model considering uncertainty of load regulation for colocation data center[J]. Power System Technology,2022,46(1):39-49.
    [12] NIU T,HU B,XIE K G,et al. Spacial coordination between data centers and power system considering uncertainties of both source and load sides[J]. International Journal of Electrical Power & Energy Systems,2021,124:106358.
    [13] 杨挺,姜含,侯昱丞,等. 基于计算负荷时-空双维迁移的互联多数据中心碳中和调控方法研究[J]. 中国电机工程学报,2022,42(1):164-177. YANG Ting,JIANG Han,HOU Yucheng,et al. Study on carbon neutrality regulation method of interconnected multi-datacenter based on spatio-temporal dual-dimensional computing load migration[J]. Proceedings of the CSEE,2022,42(1):164-177.
    [14] 兰洲,蒋晨威,谷纪亭,等. 促进可再生能源发电消纳和碳减排的数据中心优化调度与需求响应策略[J]. 电力建设,2022,43(4):1-9. LAN Zhou,JIANG Chenwei,GU Jiting,et al. Optimal dispatch and demand response strategies of data centers for promoting accommodation of renewable energy generation and reducing carbon emission[J]. Electric Power Construction,2022,43(4):1-9.
    [15] HADDAD M,COSTA G D,NICOD J M,et al. Combined IT and power supply infrastructure sizing for standalone green data centers[J]. Sustainable Computing:Informatics and Systems,2021,30(7):100505.
    [16] GUO C S,LUO F J,CAI Z X,et al. Integrated planning of Internet data centers and battery energy storage systems in smart grids[J]. Applied Energy,2021,281:116093.
    [17] LYU J W,ZHANG S X,CHENG H Z,et al. Optimal sizing of energy station in the multienergy system integrated with data center[J]. IEEE Transactions on Industry Applications,2021,57(2):1222-1234.
    [18] QI W B,LI J,LIU Y Q,et al. Planning of distributed Internet data center microgrids[J]. IEEE Transactions on Smart Grid,2019,10(1):762-771.
    [19] 张靠社,冯培基,张刚,等. 考虑机会约束的多能源微电网双层优化配置[J]. 太阳能学报,2021,42(8):41-48. ZHANG Kaoshe,FENG Peiji,ZHANG Gang,et al. Bi-level optimization configuration method for multienergy microgrid considering chance constraints[J]. Acta Energiae Solaris Sinica,2021,42(8):41-48.
    [20] 张长云,黄景光,李振兴,等. 极地环境含风氢储混合微电网容量优化配置[J]. 电力工程技术,2022,41(1):108-116. ZHANG Changyun,HUANG Jingguang,LI Zhenxing,et al. Optimal configuration of wind-hydrogen-storage hybrid microgrid capacity in polar environment[J]. Electric Power Engineering Technology,2022,41(1):108-116.
    [21] 高晋坤,余娟,刘珏麟,等. 考虑多时段设备耦合的数据中心能效优化方法[J]. 电力系统自动化,2022,46(15):153-161. GAO Jinkun,YU Juan,LIU Yulin,et,al. Optimization method for energy efficiency of data center considering multi-period equipment coupling[J]. Automation of Electric Power Systems,2022,46(15):153-161.
    [22] CHEN M,GAO C W,SHAHIDEHPOUR M,et al. Internet data center load modeling for demand response considering the coupling of multiple regulation methods[J]. IEEE Transactions on Smart Grid,2021,12(3):2060-2076.
    [23] 丁肇豪,曹雨洁,张素芳,等. 能源互联网背景下数据中心与电力系统协同优化(一):数据中心能耗模型[J]. 中国电机工程学报,2022,42(9):3161-3177. DING Zhaohao,CAO Yujie,ZHANG Sufang,et al. Coordinated operation for data center and power system in the context of energy internet:energy demand management model of data center[J]. Proceedings of the CSEE,2022,42(9):3161-3177.
    [24] 高赐威,吴刚,陈宋宋. 考虑地理分散的数据中心服务器频率调节的电网降损模型[J]. 中国电机工程学报,2019,39(6):1673-1681,1863. GAO Ciwei,WU Gang,CHEN Songsong. A model aimed at reducing power net loss considering frequency scaling of servers in geo-distributed data centers[J]. Proceedings of the CSEE,2019,39(6):1673-1681,1863.
    [25] 李凌,张徐东,钱声攀,等. 数据中心能耗数据实时采集机制的研究与设计[J]. 电力信息与通信技术,2021,19(3):26-33. LI Ling,ZHANG Xudong,QIAN Shengpan,et al. Research and design of real-time collection mechanism of energy consumption data in data center[J]. Electric Power Information and Communication Technology,2021,19(3):26-33.
    [26] 张林锋,武彤,沈庆飞,等. 服务器实际运行功率测试方法研究及应用[J]. 电力信息与通信技术,2021,19(6):64-69. ZHANG Linfeng,WU Tong,SHEN Qingfei,et al. Research and application of server actual operation power test method[J]. Electric Power Information and Communication Technology,2021,19(6):64-69.
    [27] CHEN S M,IRVING S,PENG L. Operational cost optimization for cloud computing data centers using renewable energy[J]. IEEE Systems Journal,2016,10(4):1447-1458.
    [28] 王玚,李鹏,冀浩然,等. 考虑多类型资源的数据中心园区供电协调规划[J]. 电力系统自动化,2022,46(14):19-28. WANG Yang,LI Peng,JI Haoran,et,al. Coordination planning of power supply in data center parks with multiple resources[J]. Automation of Electric Power Systems,2022,46(14):19-28.
    [29] YUAN H T,BI J,ZHOU M C,et al. Biobjective task scheduling for distributed green data centers[J]. IEEE Transactions on Automation Science and Engineering,2021,18(2):731-742.
    [30] 王晓毅,唐忠. 考虑供需自平衡和独立运行能力的并网型 微电网容量优化配置[J]. 太阳能学报,2021,42(5):74-82. WANG Xiaoyi,TANG Zhong. Capacity optimization of grid-connected microgrid considering self-balance and independent operation capability[J]. Acta Energiae Solaris Sinica,2021,42(5):74-82.
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李彬,杜亚彬,曹望璋,祁兵,陈宋宋.计及负载特性的数据中心微电网双层优化配置[J].电力工程技术,2023,42(2):75-83

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  • 收稿日期:2022-08-23
  • 最后修改日期:2022-11-02
  • 录用日期:2022-08-23
  • 在线发布日期: 2023-03-22
  • 出版日期: 2023-03-28
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