Author
Listed:
- Guo, Haijin
- Yu, Hang
- Wang, Meng
- Liu, Cheng
- Li, Chaoen
Abstract
Workload transfer is a critical and unique strategy for enhancing energy flexibility in data centers. However, existing research has largely focused on the operational cost benefits associated with workload transfer, neglecting its impact on the workloads themselves. To fully investigate the potential of workload transfer for sustainable and positive development in data centers, this study firstly clarifies the interaction between workload and energy. Based on this, an integrated management framework is proposed to simultaneously optimize workload transfer and energy dispatch. A transfer model that considers workload heterogeneity is developed to capture the characteristics of workload transfer and is integrated with the energy system model, enabling cross-sectoral collaboration between Information Technology (IT) and energy sectors. A case study in Shanghai reveals a clear trade-off exists between workload transfer and energy dispatch. The results show that while transferring workloads can reduce operational costs by 7.63 % in summer and 2.81 % in winter, it concurrently increases the average delay rate of workloads by 0.2434 in summer and 0.2028 in winter. The impact of workload transfer on energy systems is not always positive and a sole focus on cost reduction could result in an elevation of the average delay rate. Additionally, the driving forces behind workload transfer include variations in electricity prices, excess renewable energy and optimal operation of the energy system. The structure of workload also significantly affects the workload transfer. Overall, this study integrates modules from both the IT and energy sectors to achieve holistic management of data centers. The results of the case study provide novel and valuable insights for optimizing the operation of data centers during workload transfer processes.
Suggested Citation
Guo, Haijin & Yu, Hang & Wang, Meng & Liu, Cheng & Li, Chaoen, 2025.
"Integrated management of workloads and energy system for data centers,"
Energy, Elsevier, vol. 327(C).
Handle:
RePEc:eee:energy:v:327:y:2025:i:c:s0360544225020420
DOI: 10.1016/j.energy.2025.136400
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