Designing Future Energy Systems With Generative AI

Energy systems are experiencing various changes that impact the distribution, use, and reliability of energy. Local utilities and municipalities must respond and adapt to these changes, moving towards a future energy system with modernized infrastructure and other targeted investments and policy decisions. However, planning for and enacting these advancements requires significant effort from experts and engineers to develop strategies that ensure a reliable and secure energy future. This includes characterizing the current energy infrastructure, identifying areas for development, and engaging with local community members. Emerging generative artificial intelligence techniques can alleviate pain points and help support the development of the next generation of energy systems. In this article, we highlight on-going generative AI work in the areas of atmospheric modeling, building energy management, and distribution network design, and we propose a vision for the role of generative AI that considers opportunities and identifies challenges inherent to this technology.

Authors

Institutions

Publication Details

Journal
Computing in Science & Engineering
Published
2025-05-06
DOI
https://doi.org/10.1109/mcse.2025.3567208
Citations
3
Primary Topic
Global Energy and Sustainability Research
Type
article
Field-Weighted Citation Impact
1.09
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Designing Future Energy Systems With Generative AI

Ahmed S. Zamzam, Brandon Benton, Venkatesh Venkataramanan, Grant Buster et al.
3 citations
Computing in Science & Engineering
Global Energy and Sustainability Research
1.09
article

Designing Future Energy Systems With Generative AI

Ahmed S. Zamzam, Brandon Benton, Venkatesh Venkataramanan, Grant Buster, Patrick Emami, Andrew Glaws, Ryan N. King, Xiangyu Zhang, Richard Macwan
article en
3 citations

Abstract

Energy systems are experiencing various changes that impact the distribution, use, and reliability of energy. Local utilities and municipalities must respond and adapt to these changes, moving towards a future energy system with modernized infrastructure and other targeted investments and policy decisions. However, planning for and enacting these advancements requires significant effort from experts and engineers to develop strategies that ensure a reliable and secure energy future. This includes characterizing the current energy infrastructure, identifying areas for development, and engaging with local community members. Emerging generative artificial intelligence techniques can alleviate pain points and help support the development of the next generation of energy systems. In this article, we highlight on-going generative AI work in the areas of atmospheric modeling, building energy management, and distribution network design, and we propose a vision for the role of generative AI that considers opportunities and identifies challenges inherent to this technology.

Computing in Science & EngineeringVol. 27(4)
National Laboratory of the Rockies (US)
Affordable and clean energy
Openalex Percentile: Top 24%
Global Energy and Sustainability Research
1.09
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Designing Future Energy Systems With Generative AI — Ahmed S. Zamzam, Brandon Benton, et al. · Computing in Science & Engineering (2025) | TGRS Research Map | TGRS