Energy-Constrained Optimization of Data Center Layouts: An Integer Linear Programming Approach

Jing Liang (), Donglin Chen and Shangying Xu
Additional contact information
Jing Liang: School of Economics, Wuhan University of Technology, Wuhan 430070, China
Donglin Chen: School of Economics, Wuhan University of Technology, Wuhan 430070, China
Shangying Xu: School of Economics, Wuhan University of Technology, Wuhan 430070, China

Energies, 2025, vol. 18, issue 18, 1-20

Abstract: Optimizing the layout of data centers is important for the rapid development of digital infrastructure, while also addressing the issues of energy consumption, environmental sustainability, and geographic resource distribution. Traditional strategies usually focus only on the distance to demand centers and ignore the energy and environmental costs of data centers in densely populated areas. In this paper, we propose a layout optimization model based on energy consumption constraints that combines integer linear programming with binary decision variables. The model combines energy efficiency, renewable resource availability, and regional characteristics to balance economic benefits and environmental impacts, consistent with the “East data, West computing” project. The experimental results showed that the energy efficient scenario consistently reduced costs, from ¥3.68 × 10 8 to ¥3.08 × 10 8 without energy constraints, and from ¥4.08 × 10 8 to ¥3.47 × 10 8 under energy consumption constraints. Additionally, energy constraints increased the number of required data centers from two to three. The results of the study emphasized the importance of strategic siting, especially in low electricity price areas, in order to optimize the layout and improve sustainability.

Keywords: data center layout optimization; energy consumption constraints; integer linear programming; binary decision variables; east data (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/18/5040/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/18/5040/ (text/html)

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:gam:jeners:v:18:y:2025:i:18:p:5040-:d:1755187

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().