Power System Digital Twins for Distribution Systems | Ning Lu | Smart Grid Seminar

Many countries have set a goal to achieve 100% clean energy by 2035, which has spurred the integration of a large number of distributed energy resources (DERs) into their power grid. To achieve this goal, new power and energy management systems are being developed and tested. Developing and testing these technologies requires emulating a wide variety of unobserved operating scenarios where millions of DERs operate on an ever-changing landscape. In the past, snapshots of operational conditions were used to model a limited number of extreme operation scenarios. However, such approaches will no longer be sufficient for meeting the increasing need for modeling millions of DERs operating on an ever-changing landscape.
In this talk, I will introduce three key technologies that we have been developing over the past five years:
• A high-fidelity power distribution grid digital-twin that can replay actual system operation scenarios.
• GAN-based machine learning tools for synthetic load data and network topology generation.
• A demand response management system for providing power reserves, cold-load pickup, and phase balancing in a microgrid powered by hybrid PV systems.
Finally, I will provide a summary of the emerging challenges and opportunities in electric power distribution system modeling and control.
Bio
Dr. Ning Lu is a Professor in the ECE Department of North Carolina State University. Dr. Lu is an IEEE Fellow and has over 30 years of experience in electric power engineering. She received her Ph.D. degree from Rensselaer Polytechnic Institute in 2002. From 2003 to 2012, Dr. Ning Lu was a senior research engineer with Pacific Northwest National Laboratory. Dr. Lu's research interests include load modeling and control, energy management systems, renewable integration, microgrid modeling and control, real-time and faster-than-real-time large-scale co-simulation systems, and meter data analysis. She has authored more than 200 publications.