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Vulnerability analysis of secondary control system when microgrid suffering from sequential denial‐of‐service attacks
Author(s) -
Wang Bingyu,
Sun Qiuye,
Wang Rui,
Dong Chaoyu
Publication year - 2022
Publication title -
iet energy systems integration
Language(s) - English
Resource type - Journals
ISSN - 2516-8401
DOI - 10.1049/esi2.12026
Subject(s) - vulnerability (computing) , denial , microgrid , denial of service attack , computer security , service (business) , computer science , control (management) , business , psychology , artificial intelligence , world wide web , psychotherapist , the internet , marketing
The objective of the microgrid secondary control system (MSCS) is to regulate frequency and voltage and allocate active and reactive power among distributed generations in the microgrid. Sequential denial‐of‐service (DoS) attacks have a lasting impact that reduce the vulnerability of the MSCS. A vulnerability assessment method is proposed for when the microgrid experiences DoS attacks. The sequence model of attack actions and N–1 contingency actions are proposed to find the traversal expression. With the traversal method, vulnerable factors of the microgrid can be interpreted by the proposed comprehensive vulnerability metric, which provides an intuitive and easy way to understand the vulnerability of the MSCS. The metric is composed of four basic indicators concerning not only final states of the microgrid when a DoS attack ends, but also the dynamic process of the microgrid. To test the proposed metric, two mitigation methods with the purpose of mitigating the impact on the physical system caused by DoS attacks are proposed: the self‐adaptive coefficient method and the fault‐tolerance method. Finally, a 33‐node microgrid platform with eight distributed generations has been built to test the proposed vulnerability assessment method. From the analysis results, nodes with a high cyber‐degree are vulnerable and the fault‐tolerance method can provide a better mitigation result with an average metric of 9.41 compared with the self‐adaptive coefficient method with a metric of 9.03.

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