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

机译:MILP建模针对性的假负载数据注入网络攻击才能溢出智能电网中的传输线

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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:对传输线的网络攻击是智能电网安全性的主要挑战之一。如果未检测到,则这些目标攻击可能会导致电力系统中的级联问题。本文提出了一种用于在电力系统中的目标总线上的假数据喷射的双级混合整数线性编程(MILP)优化模型,以溢出目标传输线。上层优化问题输出目标负载总线上的优化假数据喷射,以溢出目标传输线而不违反数据检测约束。较低级别的问题将假数据喷射集成到最佳功率流问题中而不违反最佳功率流量限制。一些案例研究旨在验证IEEE 118总线电力系统的建议攻击模型。

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