5 papers
Quantum Learning and Estimation for Coordinated Operation between Distribution Networks and Energy Communities
Yingrui Zhuang, Lin Cheng, Yuji Cao +4
Price signals from distribution networks (DNs) guide energy communities (ECs) in adjusting their energy usage, enabling effective coordination for reliable power system operation.…
Prediction-Specific Design of Learning-Augmented Algorithms
Sizhe Li, Nicolas Christianson, Tongxin Li
Algorithms with predictions} has emerged as a powerful framework to combine the robustness of traditional online algorithms with the data-driven performance benefits of machine-lea…
System-Level Performance and Communication Tradeoff in Networked Control with Predictions
Yifei Wu, Jing Yu, Tongxin Li
Distributed control of large-scale systems is challenging due to the need for scalable and localized communication and computation. In this work, we introduce a Predictive System-L…
Learning-Augmented Control: Adaptively Confidence Learning for Competitive MPC
Tongxin Li
We introduce Learning-Augmented Control (LAC), an approach that integrates untrusted machine learning predictions into the control of constrained, nonlinear dynamical systems. LAC…
Out-of-Distribution-Aware Electric Vehicle Charging
Tongxin Li, Chenxi Sun
We tackle the challenge of learning to charge Electric Vehicles (EVs) with Out-of-Distribution (OOD) data. Traditional scheduling algorithms typically fail to balance near-optimal…