11 citations · 35 across the 16 of their papers we have counts for
12 papers · 1 filter
Interface Networks for Failure Localization in Power Systems
Chen Liang, Alessandro Zocca, Steven H. Low +1
Transmission power systems usually consist of interconnected sub-grids that are operated relatively independently. When a failure happens, it is desirable to localize its impact wi…
Stability Constrained Reinforcement Learning for Real-Time Voltage Control
Yuanyuan Shi, Guannan Qu, Steven Low +2
Deep reinforcement learning (RL) has been recognized as a promising tool to address the challenges in real-time control of power systems. However, its deployment in real-world powe…
DeepOPF-V: Solving AC-OPF Problems Efficiently
Wanjun Huang, Xiang Pan, Minghua Chen +1
AC optimal power flow (AC-OPF) problems need to be solved more frequently in the future to maintain stable and economic power system operation. To tackle this challenge, a deep neu…
Smoothed Least-Laxity-First Algorithm for EV Charging
Niangjun Chen, Christian Kurniawan, Yorie Nakahira +2
Adaptive charging can charge electric vehicles (EVs) at scale cost effectively, despite the uncertainty in EV arrivals. We formulate adaptive EV charging as a feasibility problem t…
ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging Research
Zachary J. Lee, Sunash Sharma, Daniel Johansson +1
ACN-Sim is a data-driven, open-source simulation environment designed to accelerate research in the field of smart electric vehicle (EV) charging. It fills the need in this communi…
Adaptive Charging Networks: A Framework for Smart Electric Vehicle Charging
Zachary J. Lee, George Lee, Ted Lee +6
We describe the architecture and algorithms of the Adaptive Charging Network (ACN), which was first deployed on the Caltech campus in early 2016 and is currently operating at over…