A Systemic Stochastic Infrastructure Damage Evaluation Framework, Incorporating Fragility Curves, Reinforced by Network Reduction in Distribution Systems

Natural disasters like earthquakes, storms, and floods have an adverse impact on the critical infrastructures operation. The severity of the occurred damages on the infrastructure can be assessed by failure probabilities using fragility curves. In this paper, a S tochastic I nfrastructure D amage E valuation (SIDE) method is proposed. SIDE is a partition-based event tree approach. It estimates cumulative damage from disasters on distribution systems. The system is broken down based on equipment damage levels. SIDE evaluates the probability of damage in each partition. It uses reliability block diagram and the fragility curves of its components. The method improves event tree analysis by using partition-based modeling instead of traditional series equipment sets. Additionally, it enhances analytical efficiency by ignoring unlikely or non-expecting scenarios from the partition-based event trees (PBET). The method was applied to a power distribution system (RBTS4) as a critical infrastructure under an earthquake scenario, with results compared to Monte Carlo simulations (MCS). Finally, the merit of the proposed method is illustrated using sensitivity analysis, considering changing disaster severity and budget. The paper highlights a key observation, where in most budget allocation scenarios, the location of switches often overlaps. This suggests that beyond certain budget, the SIDE method stops adding more switches.