15 citations · 23 across the 12 of their papers we have counts for
5 papers · 1 filter
Finite-Sample Probabilistic Safety Certification for AI-Based Grid-Edge Coordination
Yihong Zhou, Hanbin Yang, Thomas Morstyn
Coordinating large population of flexible grid-edge devices can alleviate the need for time-consuming and capital-intensive network upgrades, and AI-based control methods such as m…
Decision-Focused Scenario Generation and Selection for Efficient and Robust Grid Dispatch
Yangze Zhou, Yihong Zhou, Thomas Morstyn +1
The increasing uncertainty from flexible demand and renewable generation has made distributionally robust optimization (DRO) an important tool for robust power system dispatch. DRO…
Supervised Reinforcement Learning for the Coordination of Distributed Energy Resources
Haoyuan Deng, Yihong Zhou, Thomas Morstyn +1
The increasing integration of distributed energy resources (DERs) is crucial for power system decarbonization, yet unlocking DERs' flexibility is challenged by their inherent uncer…
JAX-Based Batched AC Power Flow for GPU Acceleration and AI Ecosystem Integration
Yihong Zhou, Dylan Cope, Jakob Foerster +1
Coordinating growing grid flexibility under uncertainty is becoming increasingly important for efficient and reliable power-system operation. A core computational requirement is th…
GradMAP: Gradient-Based Multi-Agent Proximal Learning for Grid-Edge Flexibility
Yihong Zhou, Hongtai Zeng, Thomas Morstyn
Coordinating large populations of grid-edge devices requires learning methods that remain fully decentralised in deployment while still respecting three-phase AC distribution-netwo…