Asynchronous Traveling Wave-based Distribution System Protection with Graph Neural Networks-Reference-Cited by-同舟云学术

Asynchronous Traveling Wave-based Distribution System Protection with Graph Neural Networks

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Kansas Power and Energy Conference (KPEC)
language:
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Author:

Jimenez-Aparicio Miguel¹,Reno Matthew J.¹,Wilches-Bernal Felipe¹

Affiliation:

1. Electric Power Systems Research Sandia National Laboratories,Albuquerque,USA

Funder

Office of Energy

National Nuclear Security Administration

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9813728/9814709/09814818.pdf?arnumber=9814818

Reference18 articles.

1. Accurate Two-Terminal Transmission Line Fault Location Using Traveling Waves

2. Multi-Resolution Analysis Algorithm for Fast Fault Classification and Location in Distribution Systems;jiménez aparicio;International Conference on Smart Energy Grid Engineering (SEGE),2021

3. An Algorithm for Fast Fault Location and Classification Based on Mathematical Morphology and Machine Learning;wilches-bernal;2022 IEEE Innovative Smart Grid Technologies North America (ISGT NA),2022

4. A Machine Learning-based Method using the Dynamic Mode Decomposition for Fault Location and Classification;wilches-bernal;Thirteenth Conference on Innovative Smart Grid Technologies (ISGT),2022

5. Fast Fault Location Method for a Distribution System with High Penetration of PV

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1. Micro Random Forest: A Local, High-Speed Implementation of a Machine-Learning Fault Location Method for Distribution Power Systems;2023 IEEE Power & Energy Society General Meeting (PESGM);2023-07-16

2. Local, Single-Ended, Traveling-Wave Fault Location on Distribution Systems Using Frequency and Time-Domain Data;IEEE Access;2023

3. Protection Analysis of a Traveling-Wave, Machine-Learning Protection Scheme for Distributions Systems With Variable Penetration of Solar PV;IEEE Access;2023

4. Evaluating the use of Shapelets in Traveling Wave based Fault Detection and Classification in Distribution Systems;IEEE Transactions on Industry Applications;2023

5. Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks;Energies;2022-10-20