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MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids

机译:针对智能电网中的溢出输电线路的针对性虚假数据注入网络攻击的MILP建模

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Cyber attacks on transmission lines are one of the main challenges in security of smart grids. These targeted attacks, if not detected, might cause cascading problems in power systems. This paper proposes a bi-level mixed integer linear programming (MILP) optimization model for false data injection on targeted buses in a power system to overflow targeted transmission lines. The upper level optimization problem outputs the optimized false data injections on targeted load buses to overflow a targeted transmission line without violating bad data detection constraints. The lower level problem integrates the false data injections into the optimal power flow problem without violating the optimal power flow constraints. A few case studies are designed to validate the proposed attack model on IEEE 118-bus power system.
机译:传输线上的网络攻击是智能电网安全性的主要挑战之一。如果没有检测到这些有针对性的攻击,则可能导致电力系统中的级联问题。本文针对电力系统目标总线上的虚假数据注入提出了双层混合整数线性规划(MILP)优化模型,以使目标传输线溢出。上层优化问题在目标负载总线上输出优化的错误数据注入,以使目标传输线溢出,而不会违反不良的数据检测约束。较低级别的问题将错误的数据注入集成到最佳潮流问题中,而没有违反最佳潮流约束。设计了一些案例研究来验证在IEEE 118总线电源系统上提出的攻击模型。

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