Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2025 , Vol. 59 >Issue 9: 1327 - 1337

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2023.528

New Type Power System and the Integrated Energy

Capacity Planning and Operational Optimization for Low-Carbon Data Center Integrated Energy System Considering Exergy Efficiency

  • LIN Jiayu ,
  • HAN Juntao ,
  • WANG Yongzhen ,
  • HAN Kai ,
  • HAN Yibo ,
  • LI Jian
Expand
  • 1 School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100083, China
    2 Innovation Center in Chongqing, Beijing Institute of Technology, Chongqing 401120, China

Received date: 2023-10-20

  Revised date: 2023-12-17

  Accepted date: 2024-02-06

  Online published: 2024-02-22

Fold

Abstract

With the rapid development of the digital economy, the energy consumption and carbon emissions of data centers (DCs) have significantly increased. In recent years, the construction of data center integrated energy systems (DC-IES) has emerged as one of the critical trends in energy conservation and emission reduction for DCs under the global net-zero emission initiative. To support the planning and construction of low-carbon DC-IES, this paper proposes a multi-objective optimization model for capacity allocation and operational planning of DC-IES, integrating energy and economic considerations with a focus on low-carbon performance. Based on the “quality” analysis method of exergy from the second law of thermodynamics, the model proposed comprehensively accounts for the dynamic exergy efficient characteristics of energy conversion devices under varying load conditions, revealing the energy flow distribution characteristics of DC-IES under different objectives. The computational results indicate that compared with the optimization scheme assuming constant equipment efficiency, the scheme considering dynamic equipment efficiency reduces energy loss rate, economic cost, and carbon emissions by 2.6%, 1.9%, and 4.8%, respectively, demonstrating clear advantages. Moreover, compared with the economically optimal scheme, the multi-objective optimization scheme significantly reduces carbon emissions and energy loss rate of the DC-IES by 22.72% and 20.73%, respectively. Furthermore, compared to the scheme scenarios with the minimum exergy loss rate and lowest carbon emissions, the multi-objective optimization scheme reduces economic costs by 54.54% and 60.78%, respectively. Compared with the scheme relying solely on grid electricity supply, the multi-objective optimization scheme that regards the DC as an integrated energy system can reduce carbon emissions by 40.97%.

Key words： data center (DC); integrated energy system (IES); exergy efficiency; computational power; energy performance

Cite this article

LIN Jiayu , HAN Juntao , WANG Yongzhen , HAN Kai , HAN Yibo , LI Jian . Capacity Planning and Operational Optimization for Low-Carbon Data Center Integrated Energy System Considering Exergy Efficiency[J]. Journal of Shanghai Jiaotong University, 2025 , 59(9) : 1327 -1337 . DOI: 10.16183/j.cnki.jsjtu.2023.528

References

[1] 中国信息通信研究院, 开放数据中心委员会. 数据中心白皮书(2023年)[M]. 北京: 中国信息通信研究院, 2023: 4.
  China Academy of Information and Communication Research, Open Data Center Committee. Data center white paper (2023)[M]. Beijing: China Academy of Information and Communication Research, 2023: 4.
[2] IEA. Data centres & networks[EB/OL].[2023-02-15]. https://www.iea.org/fuels-and-technologies/data-centres-networks.
[3] ANDERS S G, TOMAS E. On global electricity usage of communication technology: Trends to 2030[J]. Challenges, 2015, 6(1): 117-157.
[4] 王永真, 沈俊, 韩恺, 等. 算力-电力-热力协同: 数据中心综合能源技术发展白皮书[M]. 北京: 北京理工大学, 2023: 12.
  WANG Yongzhen, SHEN Jun, HAN Kai. et al. Arithmetic-power-thermal synergy data center integrated energy technology development white paper[M]. Beijing: Beijing Institute of Technology, 2023: 12.
[5] LI X L, WU T, LIN S F. Flexible and optimized operation of integrated energy systems based on exergy analysis and pipeline dynamic characteristics[J]. Frontiers in Energy Research, 2023, 11: 1203720.
[6] 王永真, 赵军. 综合能源系统的发展历程、典型形态及未来趋势[J]. 太阳能学报, 2021, 42(8): 84-95.
  WANG Yongzhen, ZHAO Jun. Development history, typical form and future trend of integrated energy system[J]. Acta Energiae Solaris Sinica, 2021, 42(8): 84-95.
[7] WANG Y Z, ZHANG L L, SONG Y, et al. State-of-the-art review on evaluation indicators of integrated intelligent energy from different perspectives[J]. Renewable and Sustainable Energy Reviews, 2024, 189(A): 113835.
[8] 王丹, 周天烁, 李家熙, 等. 面向能源转型的高?综合能源系统理论与应用[J]. 电力系统自动化, 2022, 46(17): 114-131.
  WANG Dan, ZHOU Tianshuo, LI Jiaxi, et al. Theory and application of high-exergy integrated energy system for energy transition[J]. Automation of Electric Power Systems, 2022, 46 (17): 114-131.
[9] 李家熙, 王丹, 贾宏杰. 面向综合能源系统的?流机理与分析方法[J]. 电力系统自动化, 2022, 46(12): 163-173.
  LI Jiaxi, WANG Dan, JIA Hongjie. Exergy flow mechanism and analysis method for integrated energy system[J]. Automation of Electric Power Systems, 2022, 46 (12): 163-173.
[10] NORANI M, DEYMI D M. Energy, exergy and exergoeconomic optimization of a proposed CCHP configuration under two different operating scenarios in a data center: Case study[J]. Journal of Cleaner Production, 2022, 342: 130971.
[11] 黄菲菲. 计及(火用)效率的综合能源系统多目标规划优化研究[D]. 北京: 华北电力大学, 2022.
  HUANG Feifei. Research on multi-objective planning and optimization of integrated energy system considering exergy efficiency[D]. Beijing: North China Electric Power University, 2022.
[12] WANG D X, XIE C H, WU R J, et al. Energy scheduling for data center with energy nets including CCHP and demand response[J]. IEEE Access, 2021, 9: 6137-6151.
[13] 范斐斐, 尼米智. 环境约束下数据中心综合能源系统优化配置方法[J]. 电工技术, 2021 (3): 20-23.
  FAN Feifei, NI Mizhi. Optimal configuration method of date center integrated energy system under environmental constraints[J]. Electric Engineering, 2021(3): 20-23.
[14] LIU J H, XU Z B, WU J, et al. Optimal planning of internet data centers decarbonized by hydrogen-water-based energy systems[J]. IEEE Transactions on Automation Science and Engineering, 2023, 20(3): 1577-1590.
[15] XIE Y L, CUI Y, WU D J, et al. Economic analysis of hydrogen-powered data center[J]. International Journal of Hydrogen Energy, 2021, 46(55): 27841-27850.
[16] 张诚, 檀志恒, 晁怀颇. “双碳” 背景下数据中心氢能应用的可行性研究[J]. 太阳能学报, 2022, 43(6): 327-334.
  ZHANG Cheng, TAN Zhiheng, CHAO Huaipo. Feasibility study of hydrogen energy application on data center under “carbon peaking and neutralization” background[J]. Acta Energiae Solaris Sinica, 2022, 43(6): 327-334.
[17] QI W, QIANG Y, LI D, et al. Modular modeling method and power supply capability evaluation for integrated hydrogen production stations of DC systems[J]. Energy Reports, 2022, 8(6): 130-137.
[18] GUPTA R, ASGARI S, MOAZAMIGOODARZI H, et al. Exergy and computing efficiency based data center workload and cooling management[J]. Applied Energy, 2021, 299: 117050.
[19] ALI K, JOAQUíN N, ADRIáN M. Energy, exergy and environmental (3E) analysis of a compound ejector-heat pump with low GWP refrigerants for simultaneous data center cooling and district heating[J]. International Journal of Refrigeration, 2022, 133: 61-72.
[20] MEHRAN A, MAHDI D, MOSTAFA A. Investigation of energy, exergy, and economy of co-generation system of solar electricity and cooling using linear parabolic collector for a data center[J]. Energy, 2023, 279: 128076.
[21] 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.
[22] 吕佳炜, 张沈习, 程浩忠, 等. 集成数据中心的综合能源系统能量流-数据流协同规划综述及展望[J]. 中国电机工程学报, 2021, 41(16): 5500-5521.
  Lü Jiawei, ZHANG Shenxi, CHENG Haozhong, et al. Review and prospect on coordinated planning of energy flow and workload flow in the integrated energy system containing data centers[J]. Proceedings of the CSEE, 2021, 41(16): 5500-5521.
[23] ASHRAE. Thermal guidelines for data processing environments[M]. 5th ed. Georgia, USA: ASHRAE, 2021: 10-40.
[24] 耿圣杰, 贾燕冰, 江坷滕, 等. 电网数据中心服务器容量及其综合供能系统联合规划策略研究[J]. 电网技术, 2022, 46(9): 3281-3292.
  GENG Shengjie, JIA Yanbing, JIANG Keteng, et al. Joint planning strategy of grid data center server capacity and its integrated energy supply system[J]. Power System Technology, 2022, 46(9): 3281-3292.
[25] LI X, LI T X, LIU L, et al. Operation optimization for integrated energy system based on hybrid CSP-CHP considering power-to-gas technology and carbon capture system[J]. Journal of Cleaner Production, 2023, 391: 136119.
[26] CHEN L T, XIAO K, HU F, et al. Performance evaluation and optimization design of integrated energy system based on thermodynamic, exergoeconomic, and exergoenvironmental analyses[J]. Applied Energy, 2022, 326: 119987.
[27] WANG J J, JING Y Y, ZHANG C F. Optimization of capacity and operation for CCHP system by genetic algorithm[J]. Applied Energy, 2010, 87(4): 1325-1335.
[28] ZHANG Y B, SHAN K, LI X M, et al. Research and technologies for next-generation high-temperature data centers-state-of-the-arts and future perspectives[J]. Renewable & Sustainable Energy Reviews, 2023, 171: 112991.
[29] 荆有印, 白鹤, 张建良. 太阳能冷热电联供系统的多目标优化设计与运行策略分析[J]. 中国电机工程学报, 2012, 32(20): 82-87.
  JING Youyin, BAI He, ZHANG Jianliang. Multi-objective optimization design and operation strategy analysis of a solar combined cooling heating and power system[J]. Proceedings of the CSEE, 2012, 32(20): 82-87.
[30] 程浩忠, 胡枭, 王莉, 等. 区域综合能源系统规划研究综述[J]. 电力系统自动化, 2019, 43(7): 2-13.
  CHENG Haozhong, HU Xiao, WANG Li, et al. Review on research of regional integrated energy system planning[J]. Automation of Electric Power Systems, 2019, 43(7): 2-13.
[31] 李建林, 田立亭, 程林, 等. 考虑变工况特性的微能源系统优化规划. (一) 基本模型和分析[J]. 电力系统自动化, 2018, 42(19): 18-26.
  LI Jianlin, TIAN Liting, CHENG Lin, et al. Optimal planning of micro-energy systems considering off-design performance. Part One: General model and analysis[J]. Automation of Electric Power Systems, 2018, 42(19): 18-26.
[32] 刘晓鸥, 葛少云. 区域综合能源系统的能效定义及其相关性分析[J]. 电力系统自动化, 2020, 44(8): 8-18.
  LIU Xiaoou, GE Shaoyun. Definition and correlation analysis on energy utilization efficiency of regional integrated energy system[J]. Automation of Electric Power Systems, 2020, 44(8): 8-18.
[33] 胡枭. 考虑能量品质的区域综合能源系统优化规划研究[D]. 上海: 上海交通大学, 2020
  HU Xiao. Research on the optimal planning of regional integrated energy system considering energy quality[D]. Shanghai: Shanghai Jiao Tong University, 2020.
[34] 徐赫彤. 基于热力学?分析的复合型冷源机柜传热优化与节能研究[D]. 长春: 中国科学院大学, 2020.
  XU Hetong. Research on heat transfer optimization and energy saving of server cabinet with combined cold sources based on thermodynamic exergy analysis[D]. Changchun: University of Chinese Academy of Sciences, 2020.
[35] JING R, WANG M, ZHANG Z H, et al. Comparative study of posteriori decision-making methods when designing building integrated energy systems with multi-objectives[J]. Energy and Buildings, 2019, 194: 123-139.
[36] 朱海南, 王娟娟, 陈兵兵, 等. 考虑经济性与碳排放的电-气综合能源系统多目标规划[J]. 上海交通大学学报, 2023, 57(4): 422-431.
  ZHU Hainan, WANG Juanjuan, CHEN Bingbing, et al. Multi-objective planning of power-gas integrated energy system considering economy and carbon emission[J]. Journal of Shanghai Jiao Tong University, 2023, 57(4): 422-431.
Options
Outlines

/

〈 〉