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eess.SY2026
Geometric Pareto Control: Physics-Supervised Pareto Representation Learning via Riemannian Energy-Gradient Flow
Tong Wu, Anna Scaglione
We study multi-objective sequential control problems in physical systems whose dynamics and operational constraints are known or can be represented by accurate physics-based models…
eess.SY2025
Universal Graph Learning for Power System Reconfigurations: Transfer Across Topology Variations
Tong Wu, Anna Scaglione, Sandy Miguel +1
This work addresses a fundamental challenge in applying deep learning to power systems: developing neural network models that transfer across significant system changes, including…
eess.SY2024★ 66 cited
A Review of Safe Reinforcement Learning Methods for Modern Power Systems
Tong Su, Tong Wu, Junbo Zhao +2
Given the availability of more comprehensive measurement data in modern power systems, reinforcement learning (RL) has gained significant interest in operation and control. Convent…