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Research on collaborative control strategy of cold storage and IT workload migration in data center

Author

Listed:
  • Zhu, Yiqun
  • Zhang, Quan
  • Huang, Gongsheng
  • Wang, Jiaqiang
  • Zou, Sikai
  • Ee, Yit Jing
  • Sopian, Kamaruzzaman

Abstract

The rare data communication between IT workload migration and cooling system impedes the optimization and improvement of overall energy efficiency in data center. Therefore, an advanced model predictive control strategy of IT workload migration collaborative cold storage tank and cooling system operation (MPC-WMCS) is developed, which adjusts operating modes and parameters through IT workload migration and cold storage technology to achieve maximum energy efficiency of the cooling system. Firstly, the load migration duration and the proportion of migrated IT workload are determined. And then the load migration process and equipment operating parameters are analyzed. Finally, the influence of annual temperature difference distribution on PUE is explored. Furthermore, to validate the effectiveness of the MPC-WMCS strategy, the Baseline and MPC-CS strategies are set up for comparative analysis. The results indicate that for short-term (S-type), medium-term (M-type), and long-term (L-type) migration of IT workload, 3 h, 5 h, and 7 h respectively are the most suitable. IT workload migration plays a greater role than cold charge/discharge regulation resulting in an 11.1 % increase in the system's COP. The degree of PUE reduction is determined by the outdoor wet-bulb temperature difference between day and night and the number of days the chiller operates. The MPC-WMCS strategy further reduces PUE, and it reduces energy consumption by about 7 % over the entire year compared to the MPC-CS strategy.

Suggested Citation

  • Zhu, Yiqun & Zhang, Quan & Huang, Gongsheng & Wang, Jiaqiang & Zou, Sikai & Ee, Yit Jing & Sopian, Kamaruzzaman, 2025. "Research on collaborative control strategy of cold storage and IT workload migration in data center," Energy, Elsevier, vol. 323(C).
    • Handle: RePEc:eee:energy:v:323:y:2025:i:c:s0360544225014446
    DOI: 10.1016/j.energy.2025.135802
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    References listed on IDEAS

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    2. Xiang, Ke & Tian, Zhiyong & Ma, Ling & Chen, Xinyu & Luo, Yongqiang & Gao, Yafeng & Fan, Jianhua & Wang, Qian, 2025. "Optimization of a free cooling system integrated with cold thermal energy storage in data center based on model predictive control," Energy, Elsevier, vol. 336(C).

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