Designing Future Energy Systems With Generative AI

作者：Andrew Glaws, Ryan N. King, Patrick Emami, Grant Buster, Brandon Benton, Xiangyu Zhang, Ahmed S. Zamzam, Venkatesh Venkataramanan, Richard Macwan · 发表于：Computing in Science & Engineering · 年份：2025 · DOI：10.1109/mcse.2025.3567208 · 被引用次数：5 · 研究领域：Global Energy and Sustainability Research、Hybrid Renewable Energy Systems

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.