Grid Modernization in the Age of Artificial Intelligence and Cloud: Synergies Between Grid Modernization, Artificial Intelligence, and Cloud
The electric power grid faces unprecedented challenges as it evolves to meet rising energy demands, integrate renewable sources, and adapt to new technologies. This paper explores how cloud computing and artificial intelligence (AI) are emerging as transformative solutions for grid modernization. Cloud platforms provide the scalable infrastructure and computing power needed to process vast amounts of grid data, while AI enables advanced analytics and decision-making capabilities. Together, these technologies are revolutionizing grid operations across multiple domains. Key applications include intelligent solutions for data center integration, accelerating generator interconnection processes, facilitating distributed energy resource management at scale, enabling data-driven predictive maintenance, enhancing grid resilience and self-healing, optimizing energy generation and distribution, and implementing advanced cybersecurity measures. The article discusses several real-world implementations demonstrating significant operational improvements and cost savings for utilities. It also examines emerging trends like generative AI and multiagent systems that promise to further enhance grid capabilities. While highlighting the immense potential of cloud and AI technologies, the authors emphasize that successful adoption requires a holistic approach encompassing organizational change, workforce development, and regulatory evolution. Looking ahead, the convergence of cloud and AI is poised to create a more intelligent, efficient, and reliable power grid to meet future energy needs. However, realizing this vision will require ongoing collaboration among utilities, technology providers, regulators, and researchers.
Authors
- R. Banerji
- Song Zhang (ORCID: https://orcid.org/0000-0001-9630-185X)
- Amritanshu Pandey (ORCID: https://orcid.org/0000-0002-4431-6889)
- Junhui Zhao (ORCID: https://orcid.org/0000-0002-7090-4297)
- Shaohui Liu (ORCID: https://orcid.org/0000-0002-1810-5412)
- Xiaochuan Luo
- Deepa Pahuja
- Tom Nudell
Institutions
- University of Vermont (US)
- Amazon (United States) (US)
- eIQ Energy (United States) (US)
- FuelCell Energy (United States) (US)
- Eversource Energy (United States)
- Massachusetts Institute of Technology (US)
Publication Details
- Journal
- IEEE Power and Energy Magazine
- Published
- 2025-08-20
- DOI
- https://doi.org/10.1109/mpe.2025.3565467
- Primary Topic
- Advanced Computational Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00