Measures of power grid vulnerability are often assessed by the amount of damage an adversary can exact on the network. However, the cascading impact of such attacks is often overlooked, even though cascades are one of the primary causes of large-scale blackouts. This paper explores modifications of transmission line protection settings as candidates for adversarial attacks, which can remain undetectable as long as the network equilibrium state remains unaltered. This forms the basis of a black-box function in a Bayesian optimization procedure, where the objective is to find protection settings that maximize network degradation due to cascading. Notably, our proposed method is agnostic to the choice of the cascade simulator and its underlying assumptions. Numerical experiments reveal that, against conventional wisdom, maximally misconfiguring the protection settings of all network lines does not cause the most cascading. More surprisingly, even when the degree of misconfiguration is limited due to resource constraints, it is still possible to find settings that produce cascades comparable in severity to instances where there are no resource constraints.

翻译：电力网络脆弱性的度量通常通过攻击者对网络造成的损害程度来评估。然而，此类攻击的级联效应常常被忽视，尽管级联是大规模停电的主要原因之一。本文探索了将输电线路保护装置设置的修改作为潜在的对抗攻击途径——只要网络平衡状态不变，这些修改即可保持不可检测性。这构成了贝叶斯优化过程中黑箱函数的基础，其目标是寻找能够通过级联效应最大程度降低网络性能的保护设置。值得注意的是，我们提出的方法对级联仿真器的选择及其底层假设保持中立。数值实验表明，与传统认知相反，将全网线路保护装置设置进行最大程度错误配置并不会导致最严重的级联效应。更令人惊讶的是，即使因资源限制而限制错误配置程度，仍可能找到与无资源限制情形下严重程度相当的级联设置。