MAE Seminar Series

Transforming towards a Sustainable Future: Artificial Intelligence in Next Generation Energy Systems Sensing, Modeling, and Optimization

Cong Feng.

Cong Feng

Postdoctoral Fellow, Sensing & Predictive Analysis Group, National Renewable Energy Laboratory

Friday, May 5, 2023| 11:30 a.m. | 206 Furnas Hall

Abstract

Power and energy systems are transiting from fossil-based systems to systems with large amounts of renewable energy. Compared to the traditional power system configuration, future power systems will integrate more renewable resources, manageable loads, energy storage systems, electric vehicles, and other energy efficient technologies. These new technologies will also bring more uncertainty and vulnerability to the power systems. Delivering reliable, resilient, clean, and affordable power and energy with large penetrations of renewable energy remains to be a challenging problem. Artificial intelligence (AI) has been applied to tackle these challenges by promoting power system decision intelligence. This talk will mainly cover the research of applying artificial intelligence to the sensing of the next generation energy systems: Meteorology-informed AI for Solar Sensing. We will demonstrate how to use deep learning, computer vision, and sky camera to enhance solar visibility and predictability. This talk will also briefly introduce other research in learning-enabled energy system modeling and optimization. At last, this talk will briefly describe future research plan and services beyond research in this field. 

Bio

Dr. Cong Feng is a Director’s Postdoctoral Fellow in the Sensing and Predictive Analysis Group at the National Renewable Energy Laboratory (NREL). Dr. Feng obtained a Ph.D. in 2020 at the University of Texas at Dallas and a B.S. degree from Wuhan University, China. His research focuses on enhancing the sustainability, reliability, resilience, and security of power and energy systems by promoting decision intelligence through cutting-edge technologies, such as artificial intelligence (AI) and big data. He is a principal investigator of multiple federal- or lab-funded projects. His research has result in over 40 peer-reviewed journal and conference papers with more than 12,00 citations. His main research awards include a SAS/IIF (International Institute of Forecasters) award, a Director’s award from NREL, two best paper awards from IEEE and big data conferences, and two fellowship awards. He is active in synergistic activities and was recognized as the Outstanding Reviewer for the IEEE Transactions on Sustainable Energy journal in three consecutive years. He is also a session chair and organizer of international conferences, an IEA Wind Stream Task Leader, and an editorial board member of multiple journals.

Event Date: May 5, 2023