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Asilomar Conference on Signals, Systems, and Computers (Oct. 26th - Oct. 29th, 2025)
Welcome
Welcome
This special session con Oct 27th, 2025 at Asilomar Conference 2025 invites innovative research at the intersection of machine learning (ML) and physics-based modeling to address critical challenges in modern power systems. The focus is on the design and implementation of innovative methodologies that integrate power system fundamentals (e.g., power flow equations, stability constraints, or equipment dynamics) with data-driven techniques to improve sustainability, resilience, and efficiency. Submissions may cover applications in renewable energy integration, grid optimization, demand forecasting, real-time control, and computational acceleration of power system workflows.
Invited Talks and Speakers
Robert Ferrando
University of Arizona
Christine Chen
UBC
Daniel Arnold
LLNL
Shaohui Liu
MIT
DecisionISO: An Agile, Physics-Informed Decision-Flow Platform for Real-Time Power-Market Operations
Robert Ferrando, Laurent Pagnier, Michael Chertkov, University of Arizona, United States
Estimating Load Coincidence Factors for Optimal DER Dispatch in Radial Distribution Networks
Estimating Load Coincidence Factors for Optimal DER Dispatch in Radial Distribution Networks
Yanqing Weng, Andrew Musgrave, Christine Chen, University of British Columbia, Canada
A Co-Simulation Framework for Distribution System Power Flow with Smart Inverter Dynamics
A Co-Simulation Framework for Distribution System Power Flow with Smart Inverter Dynamics
Daniel Arnold, Lawrence Livermore National Laboratory, United States
Inferring Maximum Flexibility in Large Loads for Resilient Grid Operations
Inferring Maximum Flexibility in Large Loads for Resilient Grid Operations
Shaohui Liu, Anne Gvozdjak, Deepjyoti Deka, Sungho Shin, Massachusetts Institute of Technology, United States
Organizers
Organizers
Yuanyuan Shi (University of California San Diego)
Yize Chen (University of Alberta)
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