An Analytical Model for Spatiotemporal Risk of Grid Infrastructure Under Extreme Events

Accurately quantifying the spatiotemporal risks to power grid infrastructure under extreme events is critical to ensuring system stability and resilience. The recently proposed hazard resistance-based spatiotemporal risk analysis (HRSRA) model addresses a key limitation of the widely used Sequential Monte Carlo method, which tends to overestimate infrastructure damage risk due to repeated sampling in time-series analysis. However, the HRSRA method relies on extensive simulations. This letter proposes an analytical framework and derives closed-form expressions for key statistical metrics to quantify grid infrastructure risk during extreme events. Bypassing the numerical simulations of HRSRA, the proposed analytical method agrees well with power outage observations in Puerto Rico.