Factoring spatial-temporal demand shifting flexibility of data centers with endogenously formed locational prices

With the booming development of digital information technology, the demand for societal computational power is increasing, and the industrial scale of data centers (DCs) is also growing. DCs serve as flexible and adjustable resources on the load side of the power system. To address this, we propose a collaborative security scheduling strategy for DCs and power system, leveraging their spatial-temporal flexibility. First, we analyze the architectural and operational characteristics of DCs to refine the modelling of their adjustability. Next, a bi-level co-optimization model is developed, considering the autonomy of DCs as independent operators and their impact on system electricity prices. Finally, we conduct a simulation analysis on the IEEE-39 node system. The results demonstrate that the proposed strategy effectively harnesses the spatial-temporal flexibility of DCs, enhances interaction, alleviates the congestion issue, and facilitates renewable energy integration, and significantly improves both DCs and system-wide economic efficiency.

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Publication Details

Journal
IET conference proceedings.
Published
2025-03-01
DOI
https://doi.org/10.1049/icp.2025.0390
Primary Topic
Auction Theory and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Factoring spatial-temporal demand shifting flexibility of data centers with endogenously formed locational prices

Goran Štrbac, Hongru Wang, Yujian Ye, Yizhi Wu et al.
IET conference proceedings.
Auction Theory and Applications
article

Factoring spatial-temporal demand shifting flexibility of data centers with endogenously formed locational prices

Goran Štrbac, Hongru Wang, Yujian Ye, Yizhi Wu, Xi Zhang
article en

Abstract

With the booming development of digital information technology, the demand for societal computational power is increasing, and the industrial scale of data centers (DCs) is also growing. DCs serve as flexible and adjustable resources on the load side of the power system. To address this, we propose a collaborative security scheduling strategy for DCs and power system, leveraging their spatial-temporal flexibility. First, we analyze the architectural and operational characteristics of DCs to refine the modelling of their adjustability. Next, a bi-level co-optimization model is developed, considering the autonomy of DCs as independent operators and their impact on system electricity prices. Finally, we conduct a simulation analysis on the IEEE-39 node system. The results demonstrate that the proposed strategy effectively harnesses the spatial-temporal flexibility of DCs, enhances interaction, alleviates the congestion issue, and facilitates renewable energy integration, and significantly improves both DCs and system-wide economic efficiency.

IET conference proceedings.Vol. 2024(33)
North China Electric Power University (CN), China Electric Power Research Institute, Imperial College London (GB), Southeast University (CN)
Decent work and economic growth
Openalex Percentile: Top 95%
Auction Theory and Applications
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