Hybrid Model of Cascading Failure in Power Systems using Trajectory Sensitivity-based Classification

Sai Gopal Vennelaganti; Nilanjan Ray Chaudhuri

doi:10.1109/PESGM40551.2019.8973813

Hybrid Model of Cascading Failure in Power Systems using Trajectory Sensitivity-based Classification

Sai Gopal Vennelaganti, Nilanjan Ray Chaudhuri

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

A new hybrid model of cascading failure is proposed, which employs a detailed dynamic model to identify and correct the cascade propagation path of QSS model. At every event or failure, trajectory sensitivities for a few seconds following that failure are computed using the detailed dynamic model. Classification based on computed sensitivities reveal the accuracy of QSS model's prediction. If necessary, corrections are made by simulating the detailed dynamic model for a sufficient time. The proposed hybrid model along with a review of trajectory sensitivity is presented. The effectiveness of the proposed model is validated through case studies on IEEE 4-machine and 16-machine systems.

Original language	English (US)
Title of host publication	2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Publisher	IEEE Computer Society
ISBN (Electronic)	9781728119816
DOIs	https://doi.org/10.1109/PESGM40551.2019.8973813
State	Published - Aug 2019
Event	2019 IEEE Power and Energy Society General Meeting, PESGM 2019 - Atlanta, United States Duration: Aug 4 2019 → Aug 8 2019

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2019-August
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Country/Territory	United States
City	Atlanta
Period	8/4/19 → 8/8/19

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Nuclear Energy and Engineering
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/PESGM40551.2019.8973813

Cite this

@inproceedings{db3a8c63cc2c48a19a0439a42016f783,

title = "Hybrid Model of Cascading Failure in Power Systems using Trajectory Sensitivity-based Classification",

abstract = "A new hybrid model of cascading failure is proposed, which employs a detailed dynamic model to identify and correct the cascade propagation path of QSS model. At every event or failure, trajectory sensitivities for a few seconds following that failure are computed using the detailed dynamic model. Classification based on computed sensitivities reveal the accuracy of QSS model's prediction. If necessary, corrections are made by simulating the detailed dynamic model for a sufficient time. The proposed hybrid model along with a review of trajectory sensitivity is presented. The effectiveness of the proposed model is validated through case studies on IEEE 4-machine and 16-machine systems.",

author = "Vennelaganti, {Sai Gopal} and Chaudhuri, {Nilanjan Ray}",

note = "Funding Information: ACKNOWLEDGMENT This work was supported by funding from NSF Award ECCS 1836827. Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Power and Energy Society General Meeting, PESGM 2019 ; Conference date: 04-08-2019 Through 08-08-2019",

year = "2019",

month = aug,

doi = "10.1109/PESGM40551.2019.8973813",

language = "English (US)",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE Computer Society",

booktitle = "2019 IEEE Power and Energy Society General Meeting, PESGM 2019",

address = "United States",

}

Vennelaganti, SG & Chaudhuri, NR 2019, Hybrid Model of Cascading Failure in Power Systems using Trajectory Sensitivity-based Classification. in 2019 IEEE Power and Energy Society General Meeting, PESGM 2019., 8973813, IEEE Power and Energy Society General Meeting, vol. 2019-August, IEEE Computer Society, 2019 IEEE Power and Energy Society General Meeting, PESGM 2019, Atlanta, United States, 8/4/19. https://doi.org/10.1109/PESGM40551.2019.8973813

Hybrid Model of Cascading Failure in Power Systems using Trajectory Sensitivity-based Classification. / Vennelaganti, Sai Gopal; Chaudhuri, Nilanjan Ray.
2019 IEEE Power and Energy Society General Meeting, PESGM 2019. IEEE Computer Society, 2019. 8973813 (IEEE Power and Energy Society General Meeting; Vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Hybrid Model of Cascading Failure in Power Systems using Trajectory Sensitivity-based Classification

AU - Vennelaganti, Sai Gopal

AU - Chaudhuri, Nilanjan Ray

PY - 2019/8

Y1 - 2019/8

N2 - A new hybrid model of cascading failure is proposed, which employs a detailed dynamic model to identify and correct the cascade propagation path of QSS model. At every event or failure, trajectory sensitivities for a few seconds following that failure are computed using the detailed dynamic model. Classification based on computed sensitivities reveal the accuracy of QSS model's prediction. If necessary, corrections are made by simulating the detailed dynamic model for a sufficient time. The proposed hybrid model along with a review of trajectory sensitivity is presented. The effectiveness of the proposed model is validated through case studies on IEEE 4-machine and 16-machine systems.

AB - A new hybrid model of cascading failure is proposed, which employs a detailed dynamic model to identify and correct the cascade propagation path of QSS model. At every event or failure, trajectory sensitivities for a few seconds following that failure are computed using the detailed dynamic model. Classification based on computed sensitivities reveal the accuracy of QSS model's prediction. If necessary, corrections are made by simulating the detailed dynamic model for a sufficient time. The proposed hybrid model along with a review of trajectory sensitivity is presented. The effectiveness of the proposed model is validated through case studies on IEEE 4-machine and 16-machine systems.

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U2 - 10.1109/PESGM40551.2019.8973813

DO - 10.1109/PESGM40551.2019.8973813

M3 - Conference contribution

AN - SCOPUS:85097574029

T3 - IEEE Power and Energy Society General Meeting

BT - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019

PB - IEEE Computer Society

T2 - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019

Y2 - 4 August 2019 through 8 August 2019

ER -

Hybrid Model of Cascading Failure in Power Systems using Trajectory Sensitivity-based Classification

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

UN SDGs

Access to Document

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Cite this