AI 中文总结
本文针对电力系统频率攻击问题，提出一种选择恶意控制逆变器的方法，通过构建混合整数二次约束规划并设计启发式算法，在WSCC 179节点等系统验证了其能高效找到最优攻击集，可用于分析攻击严重程度的影响因素。
AI 中文摘要
本文研究攻击者如何通过选择基于逆变器的资源（IBRs）中最有效的子集作为恶意控制节点来实施电力系统频率攻击。攻击期间，攻击者控制攻击设备以破坏一组指定目标发电机的稳定性。该攻击通过引入一种不稳定振荡模式来设计，其特征向量在目标发电机处具有大分量，而在受损害的IBRs处具有小分量。我们将最优攻击者选择问题形式化，并提出一个等价的混合整数二次约束规划（MIQCP）。为解决该组合非凸问题，我们通过引入排名度量开发了两种启发式算法。在修改后的WSCC 179节点系统上演示了攻击过程，结果通过非线性动态仿真得到验证。我们表明，所提出的启发式算法在大多数评估场景中能找到最优攻击集，同时显著减少所需的计算时间。来自ACTIVSg500系统的场景被用来进一步支持我们的结果。最后，我们讨论选择不同特征值、目标以及受损害设备数量如何影响攻击的严重程度。
英文摘要
This paper studies how an adversary can execute a power system frequency attack by choosing the most effective subset of inverter-based resources (IBRs) as malicious control nodes. During the attack, the adversary controls the attacking devices to destabilize a group of designated target generators. The attack is designed by introducing an unstable oscillatory mode whose eigenvector has large components at the target generators and small components at the compromised IBRs. We formalize the optimal attacker selection problem and present an equivalent mixed-integer quadratically constrained program (MIQCP). To address this combinatorial nonconvex problem, we develop two heuristic algorithms by introducing a ranking metric. The attack process is demonstrated on a modified WSCC 179-bus system, with results verified through nonlinear dynamic simulations. We show that the proposed heuristics find optimal attacking sets in a majority of evaluated scenarios while significantly reducing the required computational time. Scenarios from the ACTIVSg500 system are used to further support our results. Finally, we discuss how selecting different eigenvalues, targets, and numbers of compromised devices impact the attack's severity.
