89 citations · 194 across the 13 of their papers we have counts for
6 papers · 1 filter
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…
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…
Adam-based Augmented Random Search for Control Policies for Distributed Energy Resource Cyber Attack Mitigation
Daniel Arnold, Sy-Toan Ngo, Ciaran Roberts +3
Volt-VAR and Volt-Watt control functions are mechanisms that are included in distributed energy resource (DER) power electronic inverters to mitigate excessively high or low voltag…
Improving Robustness of Reinforcement Learning for Power System Control with Adversarial Training
Alexander Pan, Yongkyun Lee, Huan Zhang +2
Due to the proliferation of renewable energy and its intrinsic intermittency and stochasticity, current power systems face severe operational challenges. Data-driven decision-makin…
Understanding the Safety Requirements for Learning-based Power Systems Operations
Yize Chen, Daniel Arnold, Yuanyuan Shi +1
Recent advancements in machine learning and reinforcement learning have brought increased attention to their applicability in a range of decision-making tasks in the operations of…
A Convex Neural Network Solver for DCOPF with Generalization Guarantees
Ling Zhang, Yize Chen, Baosen Zhang
The DC optimal power flow (DCOPF) problem is a fundamental problem in power systems operations and planning. With high penetration of uncertain renewable resources in power systems…