IEEE Alaska Section

The (https://alaskasustainableenergy.com/) (ASEC) will be held in Anchorage, Alaska June 3-5, 2025. IEEE Alaska will have an exhibitor booth at the conference. Volunteers are needed to help staff the booth during the course of the conference. If you plan on attending the conference and are willing to spend an hour or two at the IEEE booth, please contact: Ken Pigg, [email protected] to schedule the times you are available. For ASEC agendas and registration, please visit the conference website: https://alaskasustainableenergy.com/ . We hope to see you there! Agenda: https://alaskasustainableenergy.com/agenda/ Bldg: Dena'ina Civic & Convention Center, 600 W 7th Ave, Anchorage, Alaska, United States, 99501

The Open Project Space has been one of the flagship events offered by the IEEE at SBU Student Branch, where students participated in a 5 week long workshop series that built on their software and hardware skills from the very basics. This semester, our executive board planned a miniature version where interested students can vote on a project for the instructors to teach the relevant material on. Once a project was decided, a lecture session was held along with a hands-on technical portion where students can work towards implementing the project with assistance from the instructors. Students were provided hardware kits with all of the required components to complete the activity. Room: 175, Bldg: Light Engineering, 100 Circle Road, Stony Brook, New York, United States, 11790

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 constrol asset loading. What makes this setting intersting is the presence of unique interactions and dependencies among generation assets, which are typically driven by different physical phenoomena and complex constraints such as power flow, degradation and operational limits. In this talk, we will present a unified framework that embeds predictive degration models pertaining to the energy assets within decision optimization models to jointly solve operations and maintenance in variety of energy system settings. We will demonstrate decision making and AI mechanisms to address challenges associated with uncertainty modeling, scalability and privacy. Using classic benchmarks from the IEEE community coupled with real-world sensor data, we will illustrate some of the considerable cost and reliability improvements relative to existing state-of-the art approaches. Speaker(s): Murat Yildirim, Agenda: 7:00 pm - Introduction and Opening remarks 7:10 pm - Presentation starts 8:15 pm - Presentation ends 8:20 pm - Questions & Answers 8:50 pm - Closing remarks 9:00 pm - Meeting ends Virtual: https://events.vtools.ieee.org/m/477621