Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

Jiménez-Aparicio, Miguel; Hernández-Alvidrez, Javier; Montoya, Armando Y.; Reno, Matthew J.

doi:10.3390/en15207785

Title: Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

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Abstract

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playbackmore »« less

Authors:

; Hernández-Alvidrez, Javier;

;

Publication Date:: Thu Oct 20 00:00:00 EDT 2022

Sponsoring Org.:: USDOE

OSTI Identifier:: 1894159

Grant/Contract Number:: Laboratory Directed Research and Development program

Resource Type:: Published Article

Journal Name:: Energies

Additional Journal Information:: Journal Name: Energies Journal Volume: 15 Journal Issue: 20; Journal ID: ISSN 1996-1073

Publisher:: MDPI AG

Country of Publication:: Switzerland

Language:: English

Citation Formats


                    Jiménez-Aparicio, Miguel, Hernández-Alvidrez, Javier, Montoya, Armando Y., and Reno, Matthew J. Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks.  Switzerland: N. p., 2022. 
Web.  doi:10.3390/en15207785.

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                    Jiménez-Aparicio, Miguel, Hernández-Alvidrez, Javier, Montoya, Armando Y., & Reno, Matthew J. Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks.  Switzerland.  https://doi.org/10.3390/en15207785

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                    Jiménez-Aparicio, Miguel, Hernández-Alvidrez, Javier, Montoya, Armando Y., and Reno, Matthew J. Thu .  
"Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks".  Switzerland.  https://doi.org/10.3390/en15207785.

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@article{osti_1894159,

  title        = {Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks},

  author       = {Jiménez-Aparicio, Miguel and Hernández-Alvidrez, Javier and Montoya, Armando Y. and Reno, Matthew J.},

  abstractNote = {This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.},

  doi          = {10.3390/en15207785},

  journal      = {Energies},

  number       = 20,

  volume       = 15,

  place        = {Switzerland},

  year         = {Thu Oct 20 00:00:00 EDT 2022},

  month        = {Thu Oct 20 00:00:00 EDT 2022}

}

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