Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control-Reference-Cited by-同舟云学术

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Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control

Published:2024-03 Issue:3 Volume:35 Page:3340-3350
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Zhang Ying¹^ORCID,Yue Meng²^ORCID,Wang Jianhui³^ORCID,Yoo Shinjae⁴^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, USA

2. Interdisciplinary Science Department, Sustainable Energy Division, Brookhaven National Laboratory, Upton, NY, USA

3. Department of Electrical and Computer Engineering, Southern Methodist University, Dallas, TX, USA

4. Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA

Funder

Advanced Grid Modeling Program, Office of Electricity of the U.S. Department of Energy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/5962385/10454107/10413998-aam.pdf

Reference47 articles.

1. Voltage instability in interconnected power systems: a simulation approach

2. A critical review of the state‐of‐art schemes for under voltage load shedding

3. A Hierarchical Data-Driven Method for Event-Based Load Shedding Against Fault-Induced Delayed Voltage Recovery in Power Systems

4. Design of an undervoltage load shedding scheme for the Hydro-Quebec system

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fractional-order transfer Q-learning based on modal decomposition and convolutional neural networks for voltage control of smart grids;Advanced Engineering Informatics;2024-10

2. Leveraging AI for Enhanced Power Systems Control: An Introductory Study of Model-Free DRL Approaches;IEEE Access;2024

3. Optimization of a Cluster-Based Energy Management System Using Deep Reinforcement Learning Without Affecting Prosumer Comfort: V2X Technologies and Peer-to-Peer Energy Trading;IEEE Access;2024

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