Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States

Yigu Liu; Ioannis Semertzis; Alexandru Stefanov; Peter Palensky

doi:10.1145/3470481.3472702

Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States

Yigu Liu^*, Ioannis Semertzis, Alexandru Stefanov, Peter Palensky

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

The security issues of Cyber-Physical power Systems (CPS) have attracted widespread attention from scholars. Vulnerability assessment emerges as an effective method to identify the critical components and thus increase the system resilience. While efforts have been made to study the vulnerability features of power systems under the occurrence of a single, discrete disturbance or failure at a specific time instant, this paper focuses on identifying the critical components of the cyber-physical system considering time-varying operational states. To investigate the potentially ever-changing CPS vulnerability features, in this paper we construct a database of cascading failure chains using quasi-dynamic simulations to capture the vulnerability relationships among components under time-varying operational states. Then, by adopting sequential mining algorithms, we mine the most frequent cascading failure patterns and identify the critical components based on the data mining results. Simulation studies are conducted on IEEE 39-bus and IEEE RTS-96 systems to evaluate the effectiveness of the proposed method for the identification of critical components at both cyber and physical layers.

Original language	English
Title of host publication	9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings
Editors	Peter Palensky, Anurag Srivastava
Place of Publication	New York, NY, USA
Publisher	ACM
Pages	1–7
Number of pages	7
ISBN (Electronic)	978-1-4503-8608-1
DOIs	https://doi.org/10.1145/3470481.3472702
Publication status	Published - 2021
Event	9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems - Virtual Event Duration: 18 May 2021 → 18 May 2021 Conference number: 9

Publication series

Name	9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings

Workshop

Workshop	9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems
Abbreviated title	MSCPES '21
Period	18/05/21 → 18/05/21

Keywords

Cyber-Physical Systems
Data Mining Algorithms
Vulnerability Assessment
Power Systems

Access to Document

10.1145/3470481.3472702

3470481.3472702Final published version, 576 KBLicence: CC BY

Cite this

Liu, Y., Semertzis, I., Stefanov, A., & Palensky, P. (2021). Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States. In P. Palensky, & A. Srivastava (Eds.), 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings (pp. 1–7). Article 3472702 (9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings). ACM. https://doi.org/10.1145/3470481.3472702

Liu, Yigu ; Semertzis, Ioannis ; Stefanov, Alexandru et al. / Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States. 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings. editor / Peter Palensky ; Anurag Srivastava. New York, NY, USA : ACM, 2021. pp. 1–7 (9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings).

@inproceedings{0a2d8fbe0db34f82a878a30bbbb66dcc,

title = "Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States",

abstract = "The security issues of Cyber-Physical power Systems (CPS) have attracted widespread attention from scholars. Vulnerability assessment emerges as an effective method to identify the critical components and thus increase the system resilience. While efforts have been made to study the vulnerability features of power systems under the occurrence of a single, discrete disturbance or failure at a specific time instant, this paper focuses on identifying the critical components of the cyber-physical system considering time-varying operational states. To investigate the potentially ever-changing CPS vulnerability features, in this paper we construct a database of cascading failure chains using quasi-dynamic simulations to capture the vulnerability relationships among components under time-varying operational states. Then, by adopting sequential mining algorithms, we mine the most frequent cascading failure patterns and identify the critical components based on the data mining results. Simulation studies are conducted on IEEE 39-bus and IEEE RTS-96 systems to evaluate the effectiveness of the proposed method for the identification of critical components at both cyber and physical layers. ",

keywords = "Cyber-Physical Systems, Data Mining Algorithms, Vulnerability Assessment, Power Systems",

author = "Yigu Liu and Ioannis Semertzis and Alexandru Stefanov and Peter Palensky",

year = "2021",

doi = "10.1145/3470481.3472702",

language = "English",

series = "9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings",

publisher = "ACM",

pages = "1–7",

editor = "Palensky, {Peter } and Srivastava, {Anurag }",

booktitle = "9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings",

address = "United States",

note = "9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES '21 ; Conference date: 18-05-2021 Through 18-05-2021",

}

Liu, Y , Semertzis, I , Stefanov, A & Palensky, P 2021, Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States. in P Palensky & A Srivastava (eds), 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings., 3472702, 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings, ACM, New York, NY, USA, pp. 1–7, 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, 18/05/21. https://doi.org/10.1145/3470481.3472702

Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States. / Liu, Yigu ; Semertzis, Ioannis ; Stefanov, Alexandru et al.
9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings. ed. / Peter Palensky; Anurag Srivastava. New York, NY, USA: ACM, 2021. p. 1–7 3472702 (9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States

AU - Liu, Yigu

AU - Semertzis, Ioannis

AU - Stefanov, Alexandru

AU - Palensky, Peter

N1 - Conference code: 9

PY - 2021

Y1 - 2021

N2 - The security issues of Cyber-Physical power Systems (CPS) have attracted widespread attention from scholars. Vulnerability assessment emerges as an effective method to identify the critical components and thus increase the system resilience. While efforts have been made to study the vulnerability features of power systems under the occurrence of a single, discrete disturbance or failure at a specific time instant, this paper focuses on identifying the critical components of the cyber-physical system considering time-varying operational states. To investigate the potentially ever-changing CPS vulnerability features, in this paper we construct a database of cascading failure chains using quasi-dynamic simulations to capture the vulnerability relationships among components under time-varying operational states. Then, by adopting sequential mining algorithms, we mine the most frequent cascading failure patterns and identify the critical components based on the data mining results. Simulation studies are conducted on IEEE 39-bus and IEEE RTS-96 systems to evaluate the effectiveness of the proposed method for the identification of critical components at both cyber and physical layers.

AB - The security issues of Cyber-Physical power Systems (CPS) have attracted widespread attention from scholars. Vulnerability assessment emerges as an effective method to identify the critical components and thus increase the system resilience. While efforts have been made to study the vulnerability features of power systems under the occurrence of a single, discrete disturbance or failure at a specific time instant, this paper focuses on identifying the critical components of the cyber-physical system considering time-varying operational states. To investigate the potentially ever-changing CPS vulnerability features, in this paper we construct a database of cascading failure chains using quasi-dynamic simulations to capture the vulnerability relationships among components under time-varying operational states. Then, by adopting sequential mining algorithms, we mine the most frequent cascading failure patterns and identify the critical components based on the data mining results. Simulation studies are conducted on IEEE 39-bus and IEEE RTS-96 systems to evaluate the effectiveness of the proposed method for the identification of critical components at both cyber and physical layers.

KW - Cyber-Physical Systems

KW - Data Mining Algorithms

KW - Vulnerability Assessment

KW - Power Systems

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U2 - 10.1145/3470481.3472702

DO - 10.1145/3470481.3472702

M3 - Conference contribution

AN - SCOPUS:85118101275

T3 - 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings

SP - 1

EP - 7

BT - 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings

A2 - Palensky, Peter

A2 - Srivastava, Anurag

PB - ACM

CY - New York, NY, USA

T2 - 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems

Y2 - 18 May 2021 through 18 May 2021

ER -

Liu Y , Semertzis I , Stefanov A , Palensky P. Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States. In Palensky P, Srivastava A, editors, 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings. New York, NY, USA: ACM. 2021. p. 1–7. 3472702. (9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings). doi: 10.1145/3470481.3472702

Critical Components Identification for Cyber-Physical Power Systems Considering Time-Varying Operational States

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