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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. Gacitua, L. & Gallegos, P. & Henriquez-Auba, R. & Lorca, Á. & Negrete-Pincetic, M. & Olivares, D. & Valenzuela, A. & Wenzel, G., 2018. "A comprehensive review on expansion planning: Models and tools for energy policy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 346-360.
    2. Habibi Khalaj, Ali & Scherer, Thomas & Siriwardana, Jayantha & Halgamuge, Saman K., 2015. "Multi-objective efficiency enhancement using workload spreading in an operational data center," Applied Energy, Elsevier, vol. 138(C), pages 432-444.
    3. Wu, Feng & Huang, Ningyu & Zhang, Fan & Niu, Lulu & Zhang, Yali, 2020. "Analysis of the carbon emission reduction potential of China's key industries under the IPCC 2 °C and 1.5 °C limits," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    4. Gupta, Rohit & Moazamigoodarzi, Hosein & MirhoseiniNejad, SeyedMorteza & Down, Douglas G. & Puri, Ishwar K., 2020. "Workload management for air-cooled data centers: An energy and exergy based approach," Energy, Elsevier, vol. 209(C).
    5. Faiz, Tasnim Ibn & Noor-E-Alam, Md, 2019. "Data center supply chain configuration design: A two-stage decision approach," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 119-135.
    6. Xie, Li & Li, Zexin & Ye, Xiuhua & Jiang, Yanru, 2021. "Environmental regulation and energy investment structure: Empirical evidence from China's power industry," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    7. 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).
    8. de Sousa Jabbour, Ana Beatriz Lopes & Jabbour, Charbel Jose Chiappetta & Foropon, Cyril & Godinho Filho, Moacir, 2018. "When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 18-25.
    9. Ni, Jiacheng & Bai, Xuelian, 2017. "A review of air conditioning energy performance in data centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 625-640.
    10. Kwon, Soongeol, 2020. "Ensuring renewable energy utilization with quality of service guarantee for energy-efficient data center operations," Applied Energy, Elsevier, vol. 276(C).
    11. Depoorter, Victor & Oró, Eduard & Salom, Jaume, 2015. "The location as an energy efficiency and renewable energy supply measure for data centres in Europe," Applied Energy, Elsevier, vol. 140(C), pages 338-349.
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