This event will be held virtually.
Speaker: Yuxuan Yuan, ECpE Graduate Student
Advisor: Zhaoyu Wang
Title: Power Distribution System Outage Detection and Location Using Deep Learning and Graph Theory
Abstract: Outage detection and location is a challenging problem in power systems, especially in distribution networks where the majority of outage events take place. The annual economic loss of power outages across the U.S. approximately ranges from 22 to 135 billion. Smart meters have capacitors that can generate last-gasp signals to report outages down to laterals, offering a great opportunity to improve outage detection. However, most utilities cannot have full SM coverage due to budgetary limitations. This presentation will present two novel data-driven approaches using deep learning and graph theory to enable rapid and accurate outage detection in partial observable distribution systems.
Bio: Yuxuan Yuan received the B.S. degree in Electrical & Computer Engineering from Iowa State University, Ames, IA, in 2017. He is currently pursuing the Ph.D. degree at Iowa State University. His research interests include distribution system state estimation, synthetic networks, data analytics, and machine learning.
Webinar Link: https://iastate.webex.com/iastate/j.php?MTID=mb7aa8adce57263c5d7b49ad6286310f7
Recording: https://iastate.webex.com/iastate/ldr.php?RCID=58205bbb8aad46719779b4afc0287dc0