The workshop will be hosted in Alexandria, Virginia, on March 5-6 2020. The central goal of the workshop is to examine theoretical and algorithmic advances from the areas of machine learning (ML) and data science (DS) that have the potential to address contemporary challenges in modeling, analysis, operations, and control of power and energy systems (PES). The workshop will provide the opportunity to stakeholders in the power and energy systems area to form collaborations with researchers in the data science and machine learning areas. Furthermore, it will also focus on related technologies pertinent to transportation networks, robotics, and other critical infrastructures that are synergistic with power and energy systems.
The workshop program will include keynote talks, panel discussion sessions with short talks, breakout sessions, and a poster session.
Keynote talks will be scheduled over both days of the workshop, and they will be delivered by world-renowned researchers and stakeholders from academia, industry, and governmental agencies.
These are anticipated to be around 1.5 hours in duration, with 4-5 talks and Q&A. We hope to strike the right mix between methodological and application-oriented panel topics. At the time of this writing, the following panels are anticipated
The breakout sessions will be organized on the second day of the workshop. They will include a 2 hour discussion coupled with a 1.5 hour period reserved for report-back from scribes and discussion leads. The broad theme of the breakout session will be to seek answers to questions posed on the first day of the workshop and also to facilitate brainstorming between participants. The overarching theme will be PES+, i.e., coupling power and energy systems research with a related interdependent infrastructure / enabling methodology. Some examples we wish to highlight of potential discussion areas include:
At the end of day 1, a poster session will be organized to provide all interested participants the opportunity to present their work and spur discussion.