Development of a Novel Positive Sequence Contactor Model Using Deep Neural Networks

Sameer Nekkalapu; Vijay Vittal; John Undrill; Bo Gong; Kenneth Brown

doi:10.1109/TPWRS.2023.3296096

Development of a Novel Positive Sequence Contactor Model Using Deep Neural Networks

Sameer Nekkalapu, Vijay Vittal, John Undrill, Bo Gong, Kenneth Brown

Engineering, Ira A. Fulton Schools of (IAFSE)

Research output: Contribution to journal › Article › peer-review

Abstract

In this work, a novel positive sequence (PS) contactor model for the protection of the 'motorc' model Lesieutre et al. 2008 has been developed using a detailed novel methodology, using linear regression and deep neural networks (DNNs). This model has been developed to identify and incorporate the critical tripping and reconnection characteristics of a newly developed 24 V electromagnetic transient (EMT) contactor Nekkalapu et al. 2022 from an EMT simulator (PSCAD) into a positive sequence simulator (GE PSLF). The impact of the accurate EMT contactor model on the motor stalling phenomenon, to accurately estimate fault induced delayed voltage recovery (FIDVR) type phenomenon for single-line to ground (SLG) faults, is also accurately captured using the proposed methodology.

Original language	English (US)
Pages (from-to)	3182-3195
Number of pages	14
Journal	IEEE Transactions on Power Systems
Volume	39
Issue number	2
DOIs	https://doi.org/10.1109/TPWRS.2023.3296096
State	Published - Mar 1 2024

Keywords

Contactors
DNNs
EMT
FIDVR
GE PSLF
POW
PSCAD
SPHIMS
load modeling
motors
regression
stalling

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1109/TPWRS.2023.3296096

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title = "Development of a Novel Positive Sequence Contactor Model Using Deep Neural Networks",

abstract = "In this work, a novel positive sequence (PS) contactor model for the protection of the 'motorc' model Lesieutre et al. 2008 has been developed using a detailed novel methodology, using linear regression and deep neural networks (DNNs). This model has been developed to identify and incorporate the critical tripping and reconnection characteristics of a newly developed 24 V electromagnetic transient (EMT) contactor Nekkalapu et al. 2022 from an EMT simulator (PSCAD) into a positive sequence simulator (GE PSLF). The impact of the accurate EMT contactor model on the motor stalling phenomenon, to accurately estimate fault induced delayed voltage recovery (FIDVR) type phenomenon for single-line to ground (SLG) faults, is also accurately captured using the proposed methodology.",

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Development of a Novel Positive Sequence Contactor Model Using Deep Neural Networks

Abstract

Keywords

ASJC Scopus subject areas

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