A Novel Assessment Method of Resilient Power System Using Stochastic Geometry

Resilience has been well identified as an essential task for power systems to cope with extreme weather events. Resilience assessment of power systems is the precondition for resilience-oriented planning, operation, and establishing restoration strategies. However, no standardized and well-accepted metrics are available yet. In this paper, an assessment method of a resilient power system based on stochastic geometry is proposed. First, an index measuring the distance features for restoration is established. A Poisson point process is then utilized to model all possible spatial patterns for power systems after extreme weather events. The stochastic distributions of the distances to restore the disconnected components by all possible spatial patterns of the survived sub-systems are analyzed. Finally, a coverage probability index that quantifies the overall performance (i.e., restorability) of the power system is derived. Simulation results conducted on the IEEE 14-bus and 118-bus systems show the feasibility of the proposed method.