Virtual Seminar: Leveraging Sensor-Based Degradation Analytics for Scalable Integration of Asset Prognostics and Operations in Energy Systems
All dates for this event occur in the past.
Seminar by Dr. Murat Yildirim
Assistant Professor
Department of Industrial and Systems Engineering
Wayne State University
Sensor-driven maintenance and operations scheduling in energy systems revolves around coordinating fleet-level electricity production with sensing and asset monitoring to help support maintenance decisions and control asset loading. What makes this setting interesting is the presence of unique interactions and dependencies among generation assets, which are typically driven by different physical phenomena and complex constraints such as power flow, degradation, and operational limits. In this talk, I will present a unified framework that embeds predictive degradation models pertaining to the generation assets within mixed integer programming to jointly solve operations and maintenance in a variety of energy system settings. I will demonstrate robust and decentralized optimization techniques to address challenges associated with uncertainty modeling, scalability, and privacy. Using classic benchmarks from the IEEE community coupled with real-world vibration data, I will illustrate some of the considerable cost and reliability improvements relative to existing state-of-the-art approaches.
Dr. Murat Yildirim is an Assistant Professor in the Department of Industrial and Systems Engineering at Wayne State University. Prior to joining Wayne State, he worked as a postdoctoral fellow at the Georgia Institute of Technology (2016-2018). He obtained a PhD degree in Industrial Engineering, MS degree in Operations Research, and BS degrees in Electrical and Industrial Engineering from Georgia Institute of Technology. Dr. Yildirim's research interest lies in advancing the integration of mathematical programming and data analytics in various application domains. Specifically, he focuses on the modeling and the computational challenges arising from the integration of real-time inferences generated by advanced data analytics and simulation into large-scale mathematical programming models used for optimizing and controlling networked systems.
Join Zoom Meeting
https://osu.zoom.us/j/99692141888?pwd=ODYrY1B6L0x0VTJXU25UMVVTcm9HUT09
Meeting ID: 996 9214 1888
Password: 640649