Modeling Cascading Failures in Coupled Smart Grid Networks

Salehpour, Aliasghar; Al‐Anbagi, Irfan; Yow, Kin Choong; Cheng, Xiaolin

doi:10.1109/access.2022.3194989

Cited by 9 publications

(4 citation statements)

References 50 publications

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“…This model partially captures the dynamics of cascading failures in the power grid but does not analyze the point of no return (PNR) or global instability, which is the focus of our work. Multiple recent studies have been conducted to model and analyze cascading failures in smart grids [24], [25] based on power flow analysis. Such studies analyze the impact of line overloads or loss of equipment, but do not capture the dynamics of the fast-cascading failure mechanism.…”

Section: State-of-the-art and Contributionsmentioning

confidence: 99%

Dynamical Analysis of Power System Cascading Failures Caused by Cyber Attacks

Rajkumar,

Ştefanov,

Rueda Torres

et al. 2024

IEEE Trans. Ind. Inf.

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Cascading failures in power systems are extremely rare occurrences caused by a combination of multiple, low probability events. The looming threat of cyberattacks on power grids, however, may result in unprecedented large-scale cascading failures, leading to a blackout. Therefore, new analysis methods are needed to study such cyber induced phenomena. In this article, we propose a data-driven method for dynamical analysis of power system cascading failures caused by cyberattacks. We provide experimental proof on how attacks may accelerate the cascading failure mechanism, in comparison to historically observed blackouts. Using a dynamic power grid model, consisting of multiple, coordinated protection schemes, we define and analyze the point of no return in a cascading failure sequence by applying the Hilbert-Huang transform for time-frequency analysis. Numerical results indicate, cyberattacks may accelerate cascading failures at least by a factor of 3x. This is due to the excitation and non-damping of multiple frequency modes greater than 1 Hz in a short time span. The proposed method is tested using time domain simulations conducted through a modified IEEE 39-bus test system, which can simulate cascading outages using coordinated protection schemes.

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Section: State-of-the-art and Contributionsmentioning

confidence: 99%

Dynamical Analysis of Power System Cascading Failures Caused by Cyber Attacks

Rajkumar,

Ştefanov,

Rueda Torres

et al. 2024

IEEE Trans. Ind. Inf.

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“…Interconnected and reliant on information technology, these areas are vulnerable, potentially causing operational disruptions, data issues, privacy breaches, and physical harm. Cyberattacks can also trigger cascading effects, disrupting control systems, communication networks, device operations, data integrity, and DER stability, possibly leading to a chain of attacks [190,191]. These cascades underscore the need for comprehensive cybersecurity measures that address interdependencies to ensure the overall resilience and security of the smart grid system.…”

Section: Vulnerable Components and Cascading Consequences Of Cyberatt...mentioning

confidence: 99%

Cyberattacks in Smart Grids: Challenges and Solving the Multi-Criteria Decision-Making for Cybersecurity Options, Including Ones That Incorporate Artificial Intelligence, Using an Analytical Hierarchy Process

Bouramdane

2023

JCP

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Smart grids have emerged as a transformative technology in the power sector, enabling efficient energy management. However, the increased reliance on digital technologies also exposes smart grids to various cybersecurity threats and attacks. This article provides a comprehensive exploration of cyberattacks and cybersecurity in smart grids, focusing on critical components and applications. It examines various cyberattack types and their implications on smart grids, backed by real-world case studies and quantitative models. To select optimal cybersecurity options, the study proposes a multi-criteria decision-making (MCDM) approach using the analytical hierarchy process (AHP). Additionally, the integration of artificial intelligence (AI) techniques in smart-grid security is examined, highlighting the potential benefits and challenges. Overall, the findings suggest that “security effectiveness” holds the highest importance, followed by “cost-effectiveness”, “scalability”, and “Integration and compatibility”, while other criteria (i.e., “performance impact”, “manageability and usability”, “compliance and regulatory requirements”, “resilience and redundancy”, “vendor support and collaboration”, and “future readiness”) contribute to the evaluation but have relatively lower weights. Alternatives such as “access control and authentication” and “security information and event management” with high weighted sums are crucial for enhancing cybersecurity in smart grids, while alternatives such as “compliance and regulatory requirements” and “encryption” have lower weighted sums but still provide value in their respective criteria. We also find that “deep learning” emerges as the most effective AI technique for enhancing cybersecurity in smart grids, followed by “hybrid approaches”, “Bayesian networks”, “swarm intelligence”, and “machine learning”, while “fuzzy logic”, “natural language processing”, “expert systems”, and “genetic algorithms” exhibit lower effectiveness in addressing smart-grid cybersecurity. The article discusses the benefits and drawbacks of MCDM-AHP, proposes enhancements for its use in smart-grid cybersecurity, and suggests exploring alternative MCDM techniques for evaluating security options in smart grids. The approach aids decision-makers in the smart-grid field to make informed cybersecurity choices and optimize resource allocation.

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“…Cascading failures in smart power grids are a growing concern due to rapid digitalisation energy transition. Various modelling approaches for understanding the mechanisms behind cascading failures in power grids are discussed in [20]. The authors investigated the impact of different factors such as node connectivity, load distribution, and protection schemes on the likelihood of cascading failures.…”

Section: B Cascading Failure Researchmentioning

confidence: 99%

Cyber Attacks on Power Grids: Causes and Propagation of Cascading Failures

Rajkumar,

Ştefanov,

Presekal

et al. 2023

IEEE Access

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Cascading effects in the power grid involve an uncontrolled, successive failure of elements. The root cause of such failures is the combined occurrence of multiple, statistically rare events that may result in a blackout. With increasing digitalisation, power systems are vulnerable to emergent cyber threats. Furthermore, such threats are not statistically limited and can simultaneously occur at multiple locations. In the absence of real-world attack information, however, it is imperative to investigate if and how cyber attacks can cause power system cascading failures. Hence, in this work we present a fundamental analysis of the connection between the cascading failure mechanism and cyber security. We hypothesise and demonstrate how cyber attacks on power grids may cause cascading failures and a blackout. To do so, we perform a systematic survey of major historic blackouts caused by physical disturbances, and examine the cascading failure mechanism. Subsequently, we identify critical cyber-physical factors that can activate and influence it. We then infer and discuss how cyber attack vectors can enable these factors to cause and accelerate cascading failures. A synthetic case-study and software-based simulation results prove our hypothesis. This analysis enables future research into cyber resilience of power grids.

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Modeling Cascading Failures in Coupled Smart Grid Networks

Cited by 9 publications

References 50 publications

Dynamical Analysis of Power System Cascading Failures Caused by Cyber Attacks

Dynamical Analysis of Power System Cascading Failures Caused by Cyber Attacks

Cyberattacks in Smart Grids: Challenges and Solving the Multi-Criteria Decision-Making for Cybersecurity Options, Including Ones That Incorporate Artificial Intelligence, Using an Analytical Hierarchy Process

Cyber Attacks on Power Grids: Causes and Propagation of Cascading Failures

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