21 citations · 119 across the 27 of their papers we have counts for
9 papers · 1 filter
Machine Learning Accelerated PDE Backstepping Observers
Yuanyuan Shi, Zongyi Li, Huan Yu +3
State estimation is important for a variety of tasks, from forecasting to substituting for unmeasured states in feedback controllers. Performing real-time state estimation for PDEs…
BEAR: Physics-Principled Building Environment for Control and Reinforcement Learning
Chi Zhang, Yuanyuan Shi, Yize Chen
Recent advancements in reinforcement learning algorithms have opened doors for researchers to operate and optimize building energy management systems autonomously. However, the lac…
Energy Storage Price Arbitrage via Opportunity Value Function Prediction
Ningkun Zheng, Xiaoxiang Liu, Bolun Xu +1
This paper proposes a novel energy storage price arbitrage algorithm combining supervised learning with dynamic programming. The proposed approach uses a neural network to directly…
Carbon-Aware EV Charging
Kai-Wen Cheng, Yuexin Bian, Yuanyuan Shi +1
This paper examines the problem of optimizing the charging pattern of electric vehicles (EV) by taking real-time electricity grid carbon intensity into consideration. The objective…
Stability Constrained Reinforcement Learning for Decentralized Real-Time Voltage Control
Jie Feng, Yuanyuan Shi, Guannan Qu +3
Deep reinforcement learning has been recognized as a promising tool to address the challenges in real-time control of power systems. However, its deployment in real-world power sys…
Robust Online Voltage Control with an Unknown Grid Topology
Christopher Yeh, Jing Yu, Yuanyuan Shi +1
Voltage control generally requires accurate information about the grid's topology in order to guarantee network stability. However, accurate topology identification is a challengin…