Optimal Power Flow (OPF) is a crucial part of the Energy Management System (EMS) as it determines individual generator outputs that minimize generation cost while satisfying transmission, generation, and system level operating constraints. OPF relies on a core EMS routine, namely state estimation, which computes system states, principally bus voltages/phase angles at the buses. However, state estimation is vulnerable to false data injection attacks in which an adversary can alter certain measurements to corrupt the estimator's solution without being detected. It is also shown that such a stealthy attack on state estimation can increase the OPF cost. However, the impact of stealthy attacks on the economic and secure operation of the system cannot be comprehensively analyzed due to the very large size of the attack space. In this paper, we present a hybrid framework that combines formal analytics with Simulink-based system modeling to investigate the feasibility of stealthy attacks and their influence on OPF in a time-efficient manner. The proposed approach is illustrated on synthetic case studies demonstrating the impact of stealthy attacks in different attack scenarios. We also evaluate the impact analysis time by running experiments on standard IEEE test cases and the results show significant scalability of the framework.

中文翻译：

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隐形攻击对最佳潮流的影响：Simulink 驱动的形式分析

最佳潮流 (OPF) 是能源管理系统 (EMS) 的关键部分，因为它决定了在满足输电、发电和系统级运行约束的同时，最大限度地降低发电成本的单个发电机输出。OPF 依赖于核心 EMS 程序，即状态估计，它计算系统状态，主要是总线上的总线电压/相角。然而，状态估计容易受到虚假数据注入攻击，在这种攻击中，对手可以改变某些测量值来破坏估计器的解决方案而不会被发现。还表明，这种对状态估计的隐蔽攻击会增加 OPF 成本。然而，由于攻击空间非常大，隐身攻击对系统经济和安全运行的影响无法综合分析。在本文中，我们提出了一个混合框架，将形式分析与基于 Simulink 的系统建模相结合，以一种省时的方式研究隐蔽攻击的可行性及其对 OPF 的影响。所提出的方法在综合案例研究中进行了说明，展示了隐身攻击在不同攻击场景中的影响。我们还通过在标准 IEEE 测试用例上运行实验来评估影响分析时间，结果表明该框架具有显着的可扩展性。