Mitigating power grid impact from proactive data center workload shifts: A coordinated scheduling strategy integrating synergistic traffic - data - power networks

Yuanshi Zhang, Bokang Zou, Xu Jin, Yifu Luo, Meng Song, Yujian Ye, Qinran Hu, Qirui Chen and Antonio Carlos Zambroni

Applied Energy, 2025, vol. 377, issue PD, No S0306261924020804

Abstract: The widespread adoption of cloud computing has markedly escalated the demand for Internet services, rendering Internet Data Centers (IDCs) a critical component in the consideration for demand response (DR) initiatives and grid energy management. This work proposes a flexible scheduling strategy integrating data, traffic, and power networks (DN-TN-PN) to mitigate the impact of proactive IDC workload transfers on power system balance. The spatial-temporal transfer characteristics of EV charging and discharging loads are utilized to track the proactive spatial-temporal transfer of IDC workloads. Considering the influence of weather factors and traffic congestion on EV travel time, an incentive pricing model for EV users is introduced to alleviate bus load fluctuation and line congestion in the distribution network. Numerical simulations demonstrate that the proposed EV pricing strategy, which accounts for the coupled DN-TN-PN, reduces IDC-induced load fluctuations by over 20 % and decreases transmission line occupancy by approximately 15 %, opening up more opportunities for the implementation of DR programs.

Keywords: Congestion management; Pricing strategy; Traffic - data - power networks; Datacenter; Electric vehicle (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2024.124697

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