Research on collaborative control strategy of cold storage and IT workload migration in data center
Yiqun Zhu,
Quan Zhang,
Gongsheng Huang,
Jiaqiang Wang,
Sikai Zou,
Yit Jing Ee and
Kamaruzzaman Sopian
Energy, 2025, vol. 323, issue C
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.
Keywords: Data center; IT workload migration; Model predictive control (MPC); Water storage; Energy conservation (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225014446
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:323:y:2025:i:c:s0360544225014446
DOI: 10.1016/j.energy.2025.135802
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().