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A formal model for verifying the impact of stealthy attacks on optimal power flow in power grids

机译:验证隐形攻击对电网最佳潮流的影响的正式模型

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In modern energy control centers, the Optimal Power Flow (OPF) routine is used to determine individual generator outputs that minimize the overall cost of generation while meeting transmission, generation, and system level operating constraints. OPF relies on the output of another module, namely the state estimator, which computes all the system variables, principally the voltage magnitudes with phase angles, transmission line flows, and the bus (and total system) loads. However, recent works have shown that the widely used weighted least square based state estimation is vulnerable to stealthy attacks wherein an adversary can alter certain measurements to corrupt the estimator's solution, yet remain undetected by the estimator's bad data detection algorithm. Here, we show that an attack on state estimation can compromise the integrity of OPF and undermine the economic and secure system operation. We present a formal verification based framework to systematically investigate the feasibility of such stealthy attacks and their influence on OPF. The proposed approach is described with an illustrative example. We also develop a mechanism to increase the efficiency of executing our model, which is evaluated by running experiments on different IEEE test cases.
机译:在现代能源控制中心中,“最佳功率流”(OPF)例程用于确定单个发电机输出,从而在满足传输,发电和系统级运行约束的同时,将发电的总成本降至最低。 OPF依赖于另一个模块的输出,即状态估计器,该模块计算所有系统变量,主要是具有相角的电压幅度,传输线流量以及总线(和整个系统)负载。但是,最近的工作表明,广泛使用的基于加权最小二乘的状态估计容易受到隐身攻击的攻击,其中对手可以更改某些度量以破坏估计器的解决方案,但仍然无法被估计器的错误数据检测算法检测到。在这里,我们表明对状态估计的攻击可能会损害OPF的完整性并破坏经济和安全的系统运行。我们提出了一个基于正式验证的框架,以系统地调查这种隐身攻击的可行性及其对OPF的影响。通过说明性示例描述了所提出的方法。我们还开发了一种提高执行模型效率的机制,该机制通过在不同的IEEE测试用例上运行实验进行评估。

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