Green Cloud Computing: A Technical and Policy Framework for the AI Era
DOI:
https://doi.org/10.21467/proceedings.8.1.3Keywords:
Data center energy, green computing, AI workloadsAbstract
The global adoption of artificial intelligence is causing an unsustainable increase in the energy consumption of data centers, threatening to reverse a decade of efficiency gains. While legacy green computing strategies held power consumption steady through the 2010s, the unique, high-intensity nature of Al workloads renders these measures insufficient. Projections now indicate that data center electricity demand could triple by 2030, consuming a significant share of global electricity. This paper provides a framework for this challenge by reassessing legacy measures and examining four critical domains: advanced thermal management, security and data sovereignty, AI as a tool for energy optimization, and the economic and policy landscape. The analysis concludes that the exponential scaling of AI, which pushes server rack power densities from 15 kW to over 100 kW, requires a paradigm shift toward new infrastructure like liquid cooling and on-site clean power. Actionable recommendations are provided for industry and policymakers to ensure the AI revolution can proceed sustainably.
References
1. International Energy Agency, ”Energy and AI,” IEA, Paris, France, 2024. https://www.iea.org/reports/energy-and-ai
2. M. Kandemir, ”Why AI uses so much energy, and what we can do about it,” Penn State University, Institutes of Energy and the Environment, Apr. 2025.
3. McKinsey & Company, ”How data centers and the energy sector can sate Al’s hunger for power,” 2024.
4. Dell’Oro Group, ”Dell’Oro Group raises market forecast for data center liquid cooling and rack power distribution,” Press Release, Feb. 5, 2025.
5. W. Wang, et al., ”Immersion cooling technology development status of data center,” Sci. Technol. Energy Transit., 2024.
6. A. Shehabi, S. Smith, D. Sartor, R. Brown, and M. Herrlin, ”United States data center energy usage report,” Lawrence Berkeley National Laboratory, Berkeley, CA, 2016.
7. A. Shehabi, et al., ”2024 United States data center energy usage report,” Lawrence Berkeley National Laboratory, Berkeley, CA, Rep. LBNL-2001637, Dec. 2024.
8. U.S. Department of Energy, Grid Deployment Office, ”Clean energy resources to meet data center electricity demand.”
9. U.S. Environmental Protection Agency, ”Virtualize Servers,” ENERGY STAR.
10. Uptime Institute, ”Global data center survey 2024,” 2024.
11. CoolIT Systems, ”Energy efficiency in the data center with direct liquid cooling,” White Paper, 2024.
12. J. D. Michels, C. Millard, I. Walden, and U. Wuermeling, ”Cloud sovereignty and the GDPR, part one: US government access to European data,” SSRN Electron. J., 2024.
13. G. La Scala, ”United States and European Union clash over data protection,” Fordham Int. Law J. Online, 2019.
14. A. A. Solanke, ”Sovereign cloud implementation: Technical architectures for data residency and regulatory compliance,” Int. J. Sci. Res. Arch., vol. 11, no. 2, pp. 2136-2147, 2024.
15. E. Gamble and J. Gao, ”Safety-first Al for autonomous data centre cooling and industrial control,” Google DeepMind, 2018.
16. Gartner, Inc., ”GenAI boom: Datacenter spending forecast raised again,” The Next Platform, Jan. 23, 2025.
17. European Union, ”Directive (EU) 2023/1791 of the European Parliament and of the Council of 13 September 2023 on energy efficiency,” Official Journal of the European Union, L 249, Oct. 2023.
18. U.S. Congress, Inflation Reduction Act of 2022, H.R.5376, 117th Congress, 2022.
19. Vertiv, ”Quantifying data center PUE when introducing liquid cooling,” White Paper.
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