IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v285y2023ics036054422302916x.html
   My bibliography  Save this article

Cooperative online schedule of interconnected data center microgrids with shared energy storage

Author

Listed:
  • Xiao, Jiang-Wen
  • Yang, Yan-Bing
  • Cui, Shichang
  • Wang, Yan-Wu

Abstract

The rapid increasing of data centers calls for an efficient method to reduce high operation costs and carbon emissions. This paper proposes a cooperative online schedule framework for local interconnected data centers considering shared energy storage. A time-average optimization problem is built to reduce the overall operation cost with essential operational constraints. Multiple randomness and the temporal coupling constraints of energy system levels make it challenging to solve the stochastic problem. Adapting the Lyapunov optimization theory with relaxation and perturbation technique, an online algorithm is proposed to find an acceptable solution to the problem to achieve both good service coordination and efficient energy coordination. The algorithm does not require prediction of random parameters, and has a fast convergence rate. Especially, the theoretical conditions for convergence and the distance between the acceptable and real optimal solution are derived in a closed form. Simulation studies show that the algorithm can effectively reduce operation cost of data centers, carbon emissions, and dependence on the main grid.

Suggested Citation

  • Xiao, Jiang-Wen & Yang, Yan-Bing & Cui, Shichang & Wang, Yan-Wu, 2023. "Cooperative online schedule of interconnected data center microgrids with shared energy storage," Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:energy:v:285:y:2023:i:c:s036054422302916x
    DOI: 10.1016/j.energy.2023.129522
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422302916X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.129522?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Fengjuan & Lv, Chengwei & Xu, Jiuping, 2023. "Carbon awareness oriented data center location and configuration: An integrated optimization method," Energy, Elsevier, vol. 278(C).
    2. MansourLakouraj, Mohammad & Shahabi, Majid & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Optimal market-based operation of microgrid with the integration of wind turbines, energy storage system and demand response resources," Energy, Elsevier, vol. 239(PB).
    3. Sermsuk, Maytungkorn & Sukjai, Yanin & Wiboonrat, Montri & Kiatkittipong, Kunlanan, 2022. "Feasibility study of a combined system of electricity generation and cooling from liquefied natural gas to reduce the electricity cost of data centres," Energy, Elsevier, vol. 254(PA).
    4. Lian, Yicheng & Li, Yuanzheng & Zhao, Yong & Yu, Chaofan & Zhao, Tianyang & Wu, Lei, 2023. "Robust multi-objective optimization for islanded data center microgrid operations," Applied Energy, Elsevier, vol. 330(PB).
    5. Liu, Wenyu & Yan, Yuejun & Sun, Yimeng & Mao, Hongju & Cheng, Ming & Wang, Peng & Ding, Zhaohao, 2023. "Online job scheduling scheme for low-carbon data center operation: An information and energy nexus perspective," Applied Energy, Elsevier, vol. 338(C).
    6. Wang, Jiangjiang & Deng, Hongda & Liu, Yi & Guo, Zeqing & Wang, Yongzhen, 2023. "Coordinated optimal scheduling of integrated energy system for data center based on computing load shifting," Energy, Elsevier, vol. 267(C).
    7. Jin, Chaoqiang & Bai, Xuelian & Yang, Chao & Mao, Wangxin & Xu, Xin, 2020. "A review of power consumption models of servers in data centers," Applied Energy, Elsevier, vol. 265(C).
    8. Huang, Pei & Copertaro, Benedetta & Zhang, Xingxing & Shen, Jingchun & Löfgren, Isabelle & Rönnelid, Mats & Fahlen, Jan & Andersson, Dan & Svanfeldt, Mikael, 2020. "A review of data centers as prosumers in district energy systems: Renewable energy integration and waste heat reuse for district heating," Applied Energy, Elsevier, vol. 258(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lei Su & Wenxiang Wu & Wanli Feng & Junda Qin & Yuqi Ao, 2024. "Collaborative Planning of Distribution Network, Data Centres and Renewable Energy in the Power Distribution IoT via Interval Optimization," Energies, MDPI, vol. 17(15), pages 1-26, July.
    2. Han, Ouzhu & Ding, Tao & Yang, Miao & Jia, Wenhao & He, Xinran & Ma, Zhoujun, 2024. "A novel 4-level joint optimal dispatch for demand response of data centers with district autonomy realization," Applied Energy, Elsevier, vol. 358(C).
    3. Zare Ghaleh Seyyedi, Abbas & Akbari, Ehsan & Mahmoudi Rashid, Sara & Nejati, Seyed Ashkan & Gitizadeh, Mohsen, 2024. "Application of robust optimized spatiotemporal load management of data centers for renewable curtailment mitigation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
    4. Weijian Ding & Behzad Ebrahimi & Byoung-Do Kim & Connie L. Devenport & Amy E. Childress, 2024. "Analysis of Anthropogenic Waste Heat Emission from an Academic Data Center," Energies, MDPI, vol. 17(8), pages 1-20, April.
    5. Gupta, Rohit & Asgari, Sahar & Moazamigoodarzi, Hosein & Down, Douglas G. & Puri, Ishwar K., 2021. "Energy, exergy and computing efficiency based data center workload and cooling management," Applied Energy, Elsevier, vol. 299(C).
    6. Chen, Sirui & Li, Peng & Ji, Haoran & Yu, Hao & Yan, Jinyue & Wu, Jianzhong & Wang, Chengshan, 2021. "Operational flexibility of active distribution networks with the potential from data centers," Applied Energy, Elsevier, vol. 293(C).
    7. Liu, Xiaoou, 2024. "Research on collaborative scheduling of internet data center and regional integrated energy system based on electricity-heat-water coupling," Energy, Elsevier, vol. 292(C).
    8. He, Wei & Ding, Su & Zhang, Jifang & Pei, Chenchen & Zhang, Zhiheng & Wang, Yulin & Li, Hailong, 2021. "Performance optimization of server water cooling system based on minimum energy consumption analysis," Applied Energy, Elsevier, vol. 303(C).
    9. Li, Haoran & Hou, Juan & Hong, Tianzhen & Nord, Natasa, 2022. "Distinguish between the economic optimal and lowest distribution temperatures for heat-prosumer-based district heating systems with short-term thermal energy storage," Energy, Elsevier, vol. 248(C).
    10. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    11. Mohammadnia, Ali & Iov, Florin & Rasmussen, Morten Karstoft & Nielsen, Mads Pagh, 2024. "Feasibility assessment of next-generation smart district heating networks by intelligent energy management strategies," Energy, Elsevier, vol. 296(C).
    12. Wang, Fengjuan & Lv, Chengwei & Xu, Jiuping, 2023. "Carbon awareness oriented data center location and configuration: An integrated optimization method," Energy, Elsevier, vol. 278(C).
    13. Ashouri, Mahyar & Chhokar, Callum & Bahrami, Majid, 2024. "A novel microgroove-based absorber for sorption heat transformation systems: Analytical modeling and experimental investigation," Energy, Elsevier, vol. 307(C).
    14. Pauli Hiltunen & Sanna Syri, 2020. "Highly Renewable District Heat for Espoo Utilizing Waste Heat Sources," Energies, MDPI, vol. 13(14), pages 1-21, July.
    15. Han, Ouzhu & Ding, Tao & Zhang, Xiaosheng & Mu, Chenggang & He, Xinran & Zhang, Hongji & Jia, Wenhao & Ma, Zhoujun, 2023. "A shared energy storage business model for data center clusters considering renewable energy uncertainties," Renewable Energy, Elsevier, vol. 202(C), pages 1273-1290.
    16. Cheng Liu & Hang Yu, 2021. "Evaluation and Optimization of a Two-Phase Liquid-Immersion Cooling System for Data Centers," Energies, MDPI, vol. 14(5), pages 1-21, March.
    17. Fathy, Ahmed & Ferahtia, Seydali & Rezk, Hegazy & Yousri, Dalia & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal adaptive fuzzy management strategy for fuel cell-based DC microgrid," Energy, Elsevier, vol. 247(C).
    18. Aguado, José A. & Paredes, Ángel, 2023. "Coordinated and decentralized trading of flexibility products in Inter-DSO Local Electricity Markets via ADMM," Applied Energy, Elsevier, vol. 337(C).
    19. Borkowski, Mateusz & Piłat, Adam Krzysztof, 2022. "Customized data center cooling system operating at significant outdoor temperature fluctuations," Applied Energy, Elsevier, vol. 306(PB).
    20. Peng Yin & Yang Guo & Man Zhang & Jiaqiang Wang & Linfeng Zhang & Da Feng & Weike Ding, 2024. "Performance Analysis of Lake Water Cooling Coupled with a Waste Heat Recovery System in the Data Center," Sustainability, MDPI, vol. 16(15), pages 1-21, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:285:y:2023:i:c:s036054422302916x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.