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Lookup NU author(s): Da HuoORCiD
This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2020.
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The dramatic increase of cyber-attacks on energy systems can cause huge losses, which has drawn extensive attention due to the fast integration of information communication technologies (ICTs). This issue is becoming worse with the integration of electricity and gas systems (IEGS), facilitated by gas generation and new coupling technologies. This paper investigates the risk and mitigation strategies for IEGS under false data injection attacks (FDIA) in a hierarchical two-stage framework. The FDIA on both electricity and gas systems are modelled through injecting falsified data by adversaries. To mitigate the adverse impacts, a novel two-stage distributionally robust optimization (DRO) is proposed: i) day-ahead operation to determine initial operation scheme and ii) real-time corrective operation with the realization of FDIA and renewable generation uncertainties. A semidefinite programming is formulated for the original problem and it is then solved by a convex optimization- based algorithm. A typical IEGS is used for demonstration, which shows that the proposed model is effective in mitigating the risks caused by potential FDIA and renewable uncertainties, by optimal coordinating energy infrastructures and load shedding. This work provides system operators with a powerful tool to operate the IEGS with enhanced security against malicious cyber-attacks while accommodating increasing renewable energy. The method can also be easily extended to operating IEGS against other natural attacks.
Author(s): Zhao P, Gu C, Huo D
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Power Systems
Print publication date: 01/09/2020
Online publication date: 13/04/2020
Acceptance date: 04/04/2020
Date deposited: 07/04/2020
ISSN (print): 0885-8950
ISSN (electronic): 1558-0679
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