11 citations · 35 across the 16 of their papers we have counts for
6 papers · 1 filter
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…
A Spectral Representation of Power Systems with Applications to Adaptive Grid Partitioning and Cascading Failure Localization
Alessandro Zocca, Chen Liang, Linqi Guo +2
Transmission line failures in power systems propagate and cascade non-locally. This well-known yet counter-intuitive feature makes it even more challenging to optimally and reliabl…
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…
Conditions for Exact Convex Relaxation and No Spurious Local Optima
Fengyu Zhou, Steven H. Low
Non-convex optimization problems can be approximately solved via relaxation or local algorithms. For many practical problems such as optimal power flow (OPF) problems, both approac…
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…