Assessment of the Resilience of the Power System Operating Under Systematic Terrorist Attacks

Power system resilience, defined as its readiness to fulfill society’s electricity needs, is analyzed by examining differing approaches to its assessment in peaceful and wartime conditions. It is noted that periodic massive attacks on power systems lead to their gradual degradation and eventual collapse. The circumstances influencing the scale of power system bombings during 20th-century wars are examined, and the current vulnerability of power systems in Eastern European countries is highlighted. The consequences of systematic missile and drone attacks on Ukraine’s power system in 2024 are assessed, and the destroyed facilities are categorized by the extent of their damage. Restoration efforts are characterized by the duration of repair works. The characteristics of power facility destruction and the duration of repair work are incorporated into an equation modeling the dynamics of generating units available for use in the current period. To assess the resilience of Ukraine’s power system, a cluster model for load modes of power facilities was applied. In this model, similar power facilities were grouped into clusters, and instead of traditional binary variables, integer variables were used to describe discrete states of startup, loading, and shutdown. Using the proposed cluster model enabled the reproduction of hourly load modes of the main types of generating equipment in Ukraine’s power system throughout 2024 and the evaluation of its resilience on a monthly basis. The presented modeling results demonstrate the adequacy of the cluster model of Ukraine’s power system when compared to actual data obtained from open publications. Key challenges in assessing the resilience of power systems functioning under systematic large-scale attacks are outlined, including anticipated attack strategies—their periodicity, scale, and targeting—dynamics of air defense system effectiveness in protecting power facilities, scheduled commissioning of protective structures with varying levels of protection, dynamics of the effectiveness of backup mechanisms, and the sufficiency of resources for repair work. The proposed cluster model is capable of addressing these pressing challenges.