Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact

Anika Tabassum; Nils Stenvig; Sangkeun Lee; Supriya Chinthavali

doi:10.1109/BigData55660.2022.10020680

Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact

Anika Tabassum, Nils Stenvig, Sangkeun Lee, Supriya Chinthavali

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

Abstract

Power system components are crucial based on various complex connections inter-connections among them. Crucial power system components cause the vulnerability in the network. Any minor disturbance on one of few crucial power components can lead to massive outages and hence can cripple the entire nation. Traditional power contingency analysis tools are expensive to identify the crucial components. Also, such analysis are not scalable to measure vulnerability at national-scale. In this paper, we develop a real-time scoring module which provides a metric to represent the cruciality of a power system component. Through a case-study in a disaster impacted regions, we show that our scoring module is better than traditional and popular network-centrality measure techniques.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022
Editors	Shusaku Tsumoto, Yukio Ohsawa, Lei Chen, Dirk Van den Poel, Xiaohua Hu, Yoichi Motomura, Takuya Takagi, Lingfei Wu, Ying Xie, Akihiro Abe, Vijay Raghavan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6815-6817
Number of pages	3
ISBN (Electronic)	9781665480451
DOIs	https://doi.org/10.1109/BigData55660.2022.10020680
State	Published - 2022
Event	2022 IEEE International Conference on Big Data, Big Data 2022 - Osaka, Japan Duration: Dec 17 2022 → Dec 20 2022

Publication series

Name	Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022

Conference

Conference	2022 IEEE International Conference on Big Data, Big Data 2022
Country/Territory	Japan
City	Osaka
Period	12/17/22 → 12/20/22

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a non-exclusive, paid up, irrevocable, world-wide license to publish or reproduce the published form of the manuscript, or allow others to do so, for U.S. Government purposes. The DOE will provide public access to these results in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

criticality measure
power system network
rule-based model

Access to Document

10.1109/BigData55660.2022.10020680

Cite this

Tabassum, A., Stenvig, N., Lee, S., & Chinthavali, S. (2022). Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact. In S. Tsumoto, Y. Ohsawa, L. Chen, D. Van den Poel, X. Hu, Y. Motomura, T. Takagi, L. Wu, Y. Xie, A. Abe, & V. Raghavan (Eds.), Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022 (pp. 6815-6817). (Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData55660.2022.10020680

Tabassum, Anika ; Stenvig, Nils ; Lee, Sangkeun et al. / Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact. Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022. editor / Shusaku Tsumoto ; Yukio Ohsawa ; Lei Chen ; Dirk Van den Poel ; Xiaohua Hu ; Yoichi Motomura ; Takuya Takagi ; Lingfei Wu ; Ying Xie ; Akihiro Abe ; Vijay Raghavan. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 6815-6817 (Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022).

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title = "Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact",

abstract = "Power system components are crucial based on various complex connections inter-connections among them. Crucial power system components cause the vulnerability in the network. Any minor disturbance on one of few crucial power components can lead to massive outages and hence can cripple the entire nation. Traditional power contingency analysis tools are expensive to identify the crucial components. Also, such analysis are not scalable to measure vulnerability at national-scale. In this paper, we develop a real-time scoring module which provides a metric to represent the cruciality of a power system component. Through a case-study in a disaster impacted regions, we show that our scoring module is better than traditional and popular network-centrality measure techniques.",

keywords = "criticality measure, power system network, rule-based model",

author = "Anika Tabassum and Nils Stenvig and Sangkeun Lee and Supriya Chinthavali",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Big Data, Big Data 2022 ; Conference date: 17-12-2022 Through 20-12-2022",

year = "2022",

doi = "10.1109/BigData55660.2022.10020680",

language = "English",

series = "Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "6815--6817",

editor = "Shusaku Tsumoto and Yukio Ohsawa and Lei Chen and {Van den Poel}, Dirk and Xiaohua Hu and Yoichi Motomura and Takuya Takagi and Lingfei Wu and Ying Xie and Akihiro Abe and Vijay Raghavan",

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Tabassum, A , Stenvig, N , Lee, S & Chinthavali, S 2022, Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact. in S Tsumoto, Y Ohsawa, L Chen, D Van den Poel, X Hu, Y Motomura, T Takagi, L Wu, Y Xie, A Abe & V Raghavan (eds), Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022. Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022, Institute of Electrical and Electronics Engineers Inc., pp. 6815-6817, 2022 IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, 12/17/22. https://doi.org/10.1109/BigData55660.2022.10020680

Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact. / Tabassum, Anika ; Stenvig, Nils ; Lee, Sangkeun et al.
Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022. ed. / Shusaku Tsumoto; Yukio Ohsawa; Lei Chen; Dirk Van den Poel; Xiaohua Hu; Yoichi Motomura; Takuya Takagi; Lingfei Wu; Ying Xie; Akihiro Abe; Vijay Raghavan. Institute of Electrical and Electronics Engineers Inc., 2022. p. 6815-6817 (Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022).

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

TY - GEN

T1 - Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact

AU - Tabassum, Anika

AU - Stenvig, Nils

AU - Lee, Sangkeun

AU - Chinthavali, Supriya

PY - 2022

Y1 - 2022

N2 - Power system components are crucial based on various complex connections inter-connections among them. Crucial power system components cause the vulnerability in the network. Any minor disturbance on one of few crucial power components can lead to massive outages and hence can cripple the entire nation. Traditional power contingency analysis tools are expensive to identify the crucial components. Also, such analysis are not scalable to measure vulnerability at national-scale. In this paper, we develop a real-time scoring module which provides a metric to represent the cruciality of a power system component. Through a case-study in a disaster impacted regions, we show that our scoring module is better than traditional and popular network-centrality measure techniques.

AB - Power system components are crucial based on various complex connections inter-connections among them. Crucial power system components cause the vulnerability in the network. Any minor disturbance on one of few crucial power components can lead to massive outages and hence can cripple the entire nation. Traditional power contingency analysis tools are expensive to identify the crucial components. Also, such analysis are not scalable to measure vulnerability at national-scale. In this paper, we develop a real-time scoring module which provides a metric to represent the cruciality of a power system component. Through a case-study in a disaster impacted regions, we show that our scoring module is better than traditional and popular network-centrality measure techniques.

KW - criticality measure

KW - power system network

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DO - 10.1109/BigData55660.2022.10020680

M3 - Conference contribution

AN - SCOPUS:85147910761

T3 - Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022

SP - 6815

EP - 6817

BT - Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022

A2 - Tsumoto, Shusaku

A2 - Ohsawa, Yukio

A2 - Chen, Lei

A2 - Van den Poel, Dirk

A2 - Hu, Xiaohua

A2 - Motomura, Yoichi

A2 - Takagi, Takuya

A2 - Wu, Lingfei

A2 - Xie, Ying

A2 - Abe, Akihiro

A2 - Raghavan, Vijay

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Big Data, Big Data 2022

Y2 - 17 December 2022 through 20 December 2022

ER -

Tabassum A , Stenvig N , Lee S , Chinthavali S. Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact. In Tsumoto S, Ohsawa Y, Chen L, Van den Poel D, Hu X, Motomura Y, Takagi T, Wu L, Xie Y, Abe A, Raghavan V, editors, Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 6815-6817. (Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022). doi: 10.1109/BigData55660.2022.10020680

Rule-based Quantification to Identify Crucial Power System Components for Mitigating Disaster Impact

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