Analyzing vulnerability of electricity distribution networks to DER disruptions

Shelar, Devendra; Amin, Saurabh

doi:10.1109/acc.2015.7171101

Cited by 11 publications

(2 citation statements)

References 13 publications

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“…These features, which will be described in the text, include callbacks for in-memory bidirectional communication with branch-and-bound solvers, automatic differentiation of user-defined nonlinear functions, and easy-to-develop add-ons for specialized problem classes such as robust optimization. JuMP's unique mix of functionality has driven growing adoption by researchers [7,34,49,72,46], and JuMP and has been used for teaching in courses in at least 10 universities (e.g., [25]). In this paper, we will highlight both the important technical and usability aspects of JuMP, including how JuMP itself uses the advanced features of Julia.…”

mentioning

confidence: 99%

JuMP: A Modeling Language for Mathematical Optimization

Dunning¹,

Huchette²,

Lubin³

2017

SIAM Rev.

1,330

774

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Abstract.JuMP is an open-source modeling language that allows users to express a wide range of optimization problems (linear, mixed-integer, quadratic, conic-quadratic, semidefinite, and nonlinear) in a high-level, algebraic syntax. JuMP takes advantage of advanced features of the Julia programming language to offer unique functionality while achieving performance on par with commercial modeling tools for standard tasks. In this work we will provide benchmarks, present the novel aspects of the implementation, and discuss how JuMP can be extended to new problem classes and composed with state-of-the-art tools for visualization and interactivity.

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mentioning

confidence: 99%

JuMP: A Modeling Language for Mathematical Optimization

Dunning¹,

Huchette²,

Lubin³

2017

SIAM Rev.

1,330

774

View full text Add to dashboard Cite

show abstract

“…For this, theoretical constructs from Stackelberg games are applied. Although Stackelberg games have been used in the literature in the context of energy management [17] and vulnerability analysis [18], this is the first time these are being effectively utilized for attack planning.…”

Section: A Attack Planning Via Stackelberg Gamesmentioning

confidence: 99%

A Novel Distributed and Stealthy Attack on Active Distribution Networks and a Mitigation Strategy

Srikantha

Liu

Samarabandu

2020

IEEE Trans. Ind. Inf.

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Rapid advances in smart devices tremendously facilitate our day-to-day lives. However, these can be exploited remotely via existing cyber vulnerabilities to cause disruption at the physical infrastructure level. In this paper, we discover a novel distributed and stealthy attack that uses malicious actuation of a large number of small-scale loads residing within a distribution network (DN). This attack is capable of cumulatively violating the underlying operational system limits, leading to widespread and prolonged disruptions. A key element of this attack is the efficient use of attack resources, planned via Stackelberg games. To mitigate this type of an attack, we propose a countermeasure strategy which adaptively suppresses adverse effects of the attack when detected in a timely manner. The effectiveness of the proposed mitigation strategy is demonstrated via theoretical convergence studies, practical evaluations and comparisons with the state-of-the-art using realistic load flow and DN infrastructure models.

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Distributed Attack and Mitigation Strategies for Active Power Distribution Networks

Liu

Srikantha

2020

Security of Cyber-Physical Systems

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Analyzing vulnerability of electricity distribution networks to DER disruptions

Cited by 11 publications

References 13 publications

JuMP: A Modeling Language for Mathematical Optimization

JuMP: A Modeling Language for Mathematical Optimization

A Novel Distributed and Stealthy Attack on Active Distribution Networks and a Mitigation Strategy

Distributed Attack and Mitigation Strategies for Active Power Distribution Networks

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