4 papers
Scaling Laws of Machine Learning for Optimal Power Flow
Xinyi Liu, Xuan He, Yize Chen
Optimal power flow (OPF) is one of the fundamental tasks for power system operations. While machine learning (ML) approaches such as deep neural networks (DNNs) have been widely st…
FREESH: Fair, Resource- and Energy-Efficient Scheduling for LLM Serving on Heterogeneous GPUs
Xuan He, Zequan Fang, Jinzhao Lian +3
The ever-increasing computation and energy demand for LLM and AI agents call for holistic and efficient optimization of LLM serving systems. In practice, heterogeneous GPU clusters…
Vertex-Guided Redundant Constraints Identification for Unit Commitment
Xuan He, Yuxin Pan, Yize Chen +1
Power systems Unit Commitment (UC) problem determines the generator commitment schedule and dispatch decisions to realize the reliable and economic operation of power networks. The…
Is Locational Marginal Price All You Need for Locational Marginal Emission?
Xuan He, Danny H. K. Tsang, Yize Chen
Growing concerns over climate change call for improved techniques for estimating and quantifying the greenhouse gas emissions associated with electricity generation and transmissio…