AI Workshops Advance Smarter, More Resilient Power Grids with Foundation Models and Privacy-Preserving Techniques

AI Helps Build Smarter, More Resilient Power Grids LEMONTE, Ill.–(BUSINESS WIRE)–As society's dependency on electricity continues to grow, artificial intelligence (AI) is revolutionizing the way we manage and optimize power grids. Recently, the U.S. Department of Energy’s Argonne National Laboratory hosted a workshop that convened top experts from national labs, universities, government agencies, and industry to explore the transformative potential of AI foundation models in electric grid management. The three-day event, titled "Foundational Models for Electric Grids," organized by Argonne researchers Kibaek Kim, Emil M. Constantinescu, and Adrian Maldonado, marked the third installment in a series that has gained significant traction. Co-sponsored by IBM, Hydro-Québec, and the National Rural Electric Cooperative Association (NRECA), the workshop fostered collaboration aimed at developing smarter, more adaptive power grids. Kibaek Kim observed the growing interest in the field, noting, “Attendance has surged from around 25 participants at our first workshop to well over 100 this time. This increase highlights the rapid progress in AI and the critical need for innovative solutions in electric grid management.” The workshop emphasized practical applications through a combination of technical sessions, panel discussions, live demonstrations, and structured networking opportunities. Participants shared insights and best practices, with industry leaders showcasing cutting-edge AI technologies. These innovations range from advanced forecasting models to automated distribution systems that enhance both performance and resilience. Argonne’s Valerie Taylor and Henry Huang delivered keynotes, highlighting the lab’s pivotal role in this domain. Huang emphasized, “Advanced analytics and AI are crucial for modernizing power systems, making them more resilient and efficient.” A significant focus of the workshop was on foundation models—AI systems trained on large datasets and fine-tuned to address specific grid challenges. Adrian Maldonado explained, “Our foundation model is an AI engine pre-trained on extensive datasets covering multiple aspects of power grid functions. It’s capable of handling tasks from forecasting to operations, offering a holistic approach to modern grid management.” Emil M. Constantinescu underscored the predictive capabilities of these models: “They can identify subtle signals that traditional methods often overlook, enabling us to forecast and prevent outages before they disrupt services.” Privacy-preserving federated learning (PPFL) was another key topic. This approach allows AI models to be trained on sensitive energy data without compromising privacy. Kim elaborated, “As we incorporate more distributed energy resources into the grid, such as natural gas generators and geothermal plants, PPFL will help us manage increasingly complex operations with greater accuracy and security.” Constantinescu further emphasized the practical application of their work: “Our objective extends beyond mere theory. We are actively integrating foundation models into operational workflows to ensure they are effective in real-world scenarios.” Argonne continues to lead in advancing AI-driven energy resilience. The insights gained from this workshop will fuel future research projects and bolster industry collaborations, aiming to create secure, efficient, and adaptive power systems. Addressing the challenges ahead, Constantinescu stated, “We are tackling two primary issues: technological limitations in grid modeling and broader resilience concerns affecting modern power systems. This is just the beginning. We are laying the groundwork for a future where AI-driven models play a central role in managing and optimizing our power grids.”