Increase in Demand for Electricity Due to Rapid Increase in Data Centers to Support AI and Role of V2G in Supporting this Growth

Authors

  • Pawan Kumar

DOI:

https://doi.org/10.47941/ijce.2431

Keywords:

Artificial Intelligence, Electricity Demand, Vehicle-to-Grid (V2G), Renewable Energy, Electric Vehicles, Smart Grid

Abstract

Purpose: The rapid proliferation of artificial intelligence (AI) technologies has led to unprecedented growth in data center infrastructure, significantly increasing global electricity demand. This study examines how Vehicle-to-Grid (V2G) technology can mitigate the energy challenges associated with AI-driven data center expansion.

Methodology: This paper employs a literature review of technological advancements, policy frameworks, and case studies to explore the interplay between AI-driven data center growth, electricity consumption, and the potential of V2G technology. Strategic insights are drawn to evaluate V2G’s role in energy management and grid stabilization.

Findings: V2G technology provides a promising solution for peak demand management, renewable energy integration, and grid stabilization by leveraging electric vehicles as mobile energy storage units. Key findings highlight V2G's capacity to support sustainable energy practices in data centers, with examples from real-world implementations.

Unique Contribution to Theory, Policy, and Practice: This paper contributes to the understanding of V2G’s transformative potential in addressing energy challenges posed by AI-driven data center expansion. It emphasizes the need for collaborative efforts in technological development, policy-making, and adoption strategies to build a resilient, sustainable infrastructure for the future.

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Published

2024-12-31

How to Cite

Kumar, P. (2024). Increase in Demand for Electricity Due to Rapid Increase in Data Centers to Support AI and Role of V2G in Supporting this Growth. International Journal of Computing and Engineering, 6(7), 27–39. https://doi.org/10.47941/ijce.2431

Issue

Vol. 6 No. 7 (2024)

Section

Articles

License

Copyright (c) 2024 Pawan Kumar

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

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.