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• W3100365247 abstract "Developing attack models is the first step to understand cyberattacks in smart grids and develop countermeasures. In this article, a three-level nonlinear programming formulation is proposed for false data injection (FDI) cyberattacks that could result in multiple transmission line congestions without being detected by conventional bad data detection (BDD) algorithms. The model is then converted to a mixed integer linear programming (MILP) formulation to guarantee a global optimum exists. A detection framework based on recursive least-square estimation (RLSE) is developed that can successfully detect the stealthy FDIs. The developed model with the detection framework is validated through various case studies in IEEE 118-bus benchmark." @default.
• W3100365247 created "2020-11-23" @default.
• W3100365247 creator A5041147963 @default.
• W3100365247 date "2021-05-01" @default.
• W3100365247 modified "2023-10-16" @default.
• W3100365247 title "Stealthy Cyberattacks on Loads and Distributed Generation Aimed at Multi-Transmission Line Congestions in Smart Grids" @default.
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• W3100365247 doi "https://doi.org/10.1109/tsg.2020.3038045" @default.
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