Resilient Cyber-Physical Power Protection Systems Using Transient Kinetic Energy Method

The integration of remote control and digitalization in intelligent power systems has introduced significant cybersecurity risks, particularly from malicious attacks targeting protection systems, which can lead to operational disruptions and line outages. However, such outages may also arise from system faults, protection failures, or circuit breaker malfunctions. To address this challenge, this article introduces a novel methodology based on waveform analysis. The proposed approach leverages transient kinetic energy analysis and real-time circuit breaker monitoring to differentiate between cyber-attacks and other causes of line outages. By analyzing waveform data from circuit breaker (CB) coil current and contact travel, the method extracts timing features to assess CB health. Probability distribution curves are generated for each feature, enabling new measurements to be compared within these distributions to evaluate CB conditions. Numerical simulations on a modified IEEE 39-bus test system, supported by experimental tests, reveal a key finding: during power system faults, a distinct time delay occurs between abrupt changes in transient kinetic energy and the initiation of line outages. In contrast, this delay is absent in cases of cyber-attacks and circuit breaker failures. This innovative method can be seamlessly integrated into supervisory control and data acquisition systems, enabling real-time identification of the root causes of outages and significantly enhancing the cybersecurity of power systems.

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Publication Details

Journal
IEEE Transactions on Industrial Informatics
Published
2025-05-07
DOI
https://doi.org/10.1109/tii.2025.3563547
Citations
1
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
1.21
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article

Resilient Cyber-Physical Power Protection Systems Using Transient Kinetic Energy Method

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1 citations
IEEE Transactions on Industrial Informatics
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article

Resilient Cyber-Physical Power Protection Systems Using Transient Kinetic Energy Method

Hamid Reza Shabani, Navid Razmjooy, Chun‐Lien Su, Seyed Hossein Rouhani, Mostafa Esmaeili Shayan, Saleh Mobayen, Cheng‐Shing Chiang, J. C. Yu
article en
1 citations

Abstract

The integration of remote control and digitalization in intelligent power systems has introduced significant cybersecurity risks, particularly from malicious attacks targeting protection systems, which can lead to operational disruptions and line outages. However, such outages may also arise from system faults, protection failures, or circuit breaker malfunctions. To address this challenge, this article introduces a novel methodology based on waveform analysis. The proposed approach leverages transient kinetic energy analysis and real-time circuit breaker monitoring to differentiate between cyber-attacks and other causes of line outages. By analyzing waveform data from circuit breaker (CB) coil current and contact travel, the method extracts timing features to assess CB health. Probability distribution curves are generated for each feature, enabling new measurements to be compared within these distributions to evaluate CB conditions. Numerical simulations on a modified IEEE 39-bus test system, supported by experimental tests, reveal a key finding: during power system faults, a distinct time delay occurs between abrupt changes in transient kinetic energy and the initiation of line outages. In contrast, this delay is absent in cases of cyber-attacks and circuit breaker failures. This innovative method can be seamlessly integrated into supervisory control and data acquisition systems, enabling real-time identification of the root causes of outages and significantly enhancing the cybersecurity of power systems.

IEEE Transactions on Industrial InformaticsVol. 21(8)
University of Cagliari (IT), National University of Kaohsiung (TW), Iran University of Science and Technology (IR), National Yunlin University of Science and Technology (TW), Saveetha University (IN)
Affordable and clean energy
Openalex Percentile: Top 22%
Smart Grid Security and Resilience
1.21
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