UTD Researchers Develop AI Model for Self-Healing Electrical Grids
The University of Texas at Dallas researchers, in collaboration with engineers from the University at Buffalo in New York, have devised an artificial intelligence (AI) model capable of swiftly rerouting electricity within milliseconds, potentially averting power outages in electrical grids. Published in Nature Communications, this pioneering "self-healing grid" technology autonomously detects and rectifies issues like storm-induced damage to power lines without human intervention, addressing challenges in efficiently distributing electricity to consumers within the vast and intricate North American grid. Led by Dr. Jie Zhang, associate professor of mechanical engineering at UT Dallas, the research team leveraged machine learning algorithms to map the complex relationships within power distribution networks, enabling rapid identification of alternative routes for electricity delivery. Dr. Yulia Gel, professor of mathematical sciences at UT Dallas and study co-author, highlighted the interdisciplinary collaboration's significance, combining expertise in power systems, mathematics, and machine learning to enhance outage management and resilience across diverse complex systems.
UTD Researchers Develop AI Model for Self-Healing Electrical Grids
