activity
20172023
most citedEncoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning with Region-of-Interest Active Sampling

117 citations · 266 across the 15 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

eess.SY2022★ 5 cited

DiME and AGVis: A Distributed Messaging Environment and Geographical Visualizer for Large-scale Power System Simulation

Nicholas Parsly, Jinning Wang, Nick West +3

This paper introduces the messaging environment and the geographical visualization tool of the CURENT Large-scale Testbed (LTB) that can be used for large-scale power system closed…

eess.SY2022★ 2 cited

Virtual Inertia Scheduling for Power Systems with High Penetration of Inverter-based Resources

Buxin She, Fangxing Li, Hantao Cui +3

This paper proposes a new concept called virtual inertia scheduling (VIS) to efficiently handle the high penetration of inverter-based resources (IBRs). VIS is an inertia managemen…

eess.SY2022

Impact of Internal Algebraic Variable Treatment on Transient Stability Simulation Performance

Hantao Cui

It is a general notion that, in transient stability simulations, reducing the number of algebraic variables for the differential-algebraic equations (DAE) can improve the simulatio…

eess.SY2022★ 27 cited

Decentralized and Coordinated Vf Control for Islanded Microgrids Considering DER Inadequacy and Demand Control

Buxin She, Fangxing Li, Hantao Cui +4

This paper proposes a decentralized and coordinated voltage and frequency (Vf) control framework for islanded microgrids, with full consideration of the limited capacity of distrib…

eess.SY2022★ 79 cited

Fusion of Model-free Reinforcement Learning with Microgrid Control: Review and Vision

Buxin She, Fangxing Li, Hantao Cui +2

Challenges and opportunities coexist in microgrids as a result of emerging large-scale distributed energy resources (DERs) and advanced control techniques. In this paper, a compreh…

eess.SY2022

Andes_gym: A Versatile Environment for Deep Reinforcement Learning in Power Systems

Hantao Cui, Yichen Zhang

This paper presents Andes_gym, a versatile and high-performance reinforcement learning environment for power system studies. The environment leverages the modeling and simulation c…