AI-Driven Digital Twin for Energy Optimization in Green Data Centers

Authors

  • Isni Oktria Universitas Gunadarma

DOI:

https://doi.org/10.56127/ijst.v4i2.2249

Keywords:

Artificial Intelligence (AI); Digital Twin; Green Data Center; Energy Optimization; Power Usage Effectiveness (PUE); Carbon Usage Effectiveness (CUE); Sustainable Computing

Abstract

This study proposes the development of an AI-driven digital twin for data centers aimed at improving energy efficiency, reducing carbon footprint, and enhancing operational performance. The digital twin—a virtual replica of the physical data center—will be equipped with real-time AI algorithms to predict thermal loads, analyze cooling requirements, and automatically adjust operations to minimize energy consumption. This paper explores the integration of AI with digital twin architectures, tests its performance in simulated scenarios, and evaluates potential energy savings as well as contributions to Green IT practices.

References

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Sarkar, S., et al. (2024). Sustainability of Data Center Digital Twins with Reinforcement Learning. AAAI Conference (peer-reviewed).

Sarkar, S., et al. (2024). Sustainability of Data Center Digital Twins with Reinforcement Learning — ArXiv preprint (DCRL-Green).

Li, Y., Wen, Y., Guan, K., & Tao, D. (2017). Transforming Cooling Optimization for Green Data Center via Deep Reinforcement Learning. ArXiv preprint.

Boscariol, M. (2025). Review on Green Data Centres: incorporating eco friendly equipment and enhancing operational efficiency. (In press)

TechTarget. (2025, March 6). What is a green data center? — Definitions and best practices.

EE Times. (2024, June 24). Harnessing Digital Twin Technology for Energy Efficient Data Centers.

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Published

2025-07-31

How to Cite

Oktria, I. (2025). AI-Driven Digital Twin for Energy Optimization in Green Data Centers. International Journal Science and Technology, 4(2), 183–191. https://doi.org/10.56127/ijst.v4i2.2249

Issue

Vol. 4 No. 2 (2025): July: International Journal Science and Technology

Section

Articles

License

Copyright (c) 2025 Isni Oktria

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.