arXiv:2607.06958v2 Announce Type: replace Abstract: The rapid growth of artificial intelligence workloads is increasing the scale and concentration of data center demand, creating new concerns for power system resilience under disruptive events. This paper extends a validated multi-time-step DC optimal power flow framework to evaluate the impact of aggregated data center demand on contingency-induced unserved energy. Using an IEEE 30-bus system with flexible resources, we replace a conventional load at a contingency-exposed bus with an energy-matched constant data center load and examine two capacity-growth levels under generator derating, transmission line derating, and coupled derating. The results show that data center capacity growth substantially increases both system-level and data-center-bus unserved energy under transmission-constrained contingencies. Under coupled derating, the high-growth case increases total unserved energy from 3.203 MWh in the energy-matched case to 22.891 MWh. A supplementary energy-matched coincident-demand case further increases total unserved energy by 34.4%, indicating that temporally concentrated data center demand can amplify resilience impacts even without increasing total energy consumption.