A Stackelberg-game based bi-level scheduling model of data center combined with shared energy storage considering price linkage and demand response

Shuo Zhang, Ming Wei, Yingzi Li and Yuanli Chen

Energy, 2025, vol. 336, issue C

Abstract: Data center (DC) is an important component in building the new-type power system and realizing the dual-carbon goals. It is a key issue to motivate the flexible scheduling performance of DC by jointly optimizing SES-DC (DC combined shared energy storage (SES)). To end this, this paper proposes a Stackelberg-game based bi-level scheduling model of SES-DC considering price linkage and demand response (DR). Firstly, the joint scheduling framework for SES-DC is determined by considering their operational characteristics. Secondly, a Stackelberg game model is constructed, with SES as the leader and DC as the follower. SES determines charging and discharging strategies and electricity package price based on the historical electricity consumption of DC. And DC determines its own electricity consumption strategy by combining the DR characteristics of data load. A two-layer algorithm combining genetic algorithm (GA) and CPLEX is applied to solve the model. Finally, through a case study, the rationality and effectiveness of the proposed model are validated. The results show that the proposed joint scheduling model, considering price linkage and DR, can significantly reduce the electricity cost of DC by 7.97 % and bring 193740 CNY to SES. This is of good significance for improving energy utilization efficiency, enhancing load scheduling flexibility, and promoting renewable energy (RE) consumption.

Keywords: Shared energy storage; Data center; Stackelberg game; Demand response; Price linkage (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225041519
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:336:y:2025:i:c:s0360544225041519

DOI: 10.1016/j.energy.2025.138509

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 ().