Power Grid Faults Classification via Low-Rank Tensor Modeling-Reference-Cited by-同舟云学术

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Power Grid Faults Classification via Low-Rank Tensor Modeling

Published:2023-10-29 Issue: Volume: Page:849-853
ISSN:
Container-title:2023 57th Asilomar Conference on Signals, Systems, and Computers
language:
Short-container-title:

Author:

Repasky Matthew¹,Xie Yao¹,Zhang Yichen²,Qiu Feng³

Affiliation:

1. H. Milton Stewart School of Industrial & Systems Engineering, Georgia Institute of Technology,Atlanta,GA

2. University of Texas at Arlington,Department of Electrical Engineering,Arlington,TX

3. Argonne National Laboratory,Energy Systems and Infrastructure Analysis Division,Lemont,IL

Funder

U.S. Department of Energy

NSF

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10476702/10476779/10476907.pdf?arnumber=10476907

Reference25 articles.

1. Benefits of Synchronized-Measurement Technology for Power-Grid Applications

2. 2020 smart grid system report;Tech. Rep.,2022

3. Overview of Signal Processing and Machine Learning for Smart Grid Condition Monitoring

4. Final report-system distur-bance on 4 november 2006;Maas;Union for the Coordination of Transmission of Electricity in Europe, Tech. Rep,2007

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