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Carbon awareness oriented data center location and configuration: An integrated optimization method

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  • Wang, Fengjuan
  • Lv, Chengwei
  • Xu, Jiuping

Abstract

Serving as the information backbone of an increasingly digitalized world and energy-intensive, the data center industry has to seek low-carbon developing way to properly meet the rapidly rising service demand. This paper designs 45 kinds of configuration choices for each decision units by integrating three data centers, three cooling technologies, as well as five energy supply mixes. The model is formulated as a bi objective optimization problem for the decision maker to decide newly established data location and configuration with objective of reducing data center expansion costs and well as minimizing power utilization associated with carbon emissions from a country level. The pilot study in China under the scenarios of different carbon emissions limitation and propagation delay that China can reduce at least 25% of newly established data center related emissions from 2020 to 2023. It further shows that future expansion can be focus on Inner Mongolia and Ningxia for the north, Hubei for the middle, and Yunnan and Guangxi for the south. This paper provides a fresh perspective and makes a valuable attempt at the low-carbon development of data centers.

Suggested Citation

  • Wang, Fengjuan & Lv, Chengwei & Xu, Jiuping, 2023. "Carbon awareness oriented data center location and configuration: An integrated optimization method," Energy, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:c:s0360544223011386
    DOI: 10.1016/j.energy.2023.127744
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    1. 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).

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