A Data-Driven Model for Simulating the Evolution of Transmission Line Failure in Power Grids

Cascading failures in a power grid result in successive failures of power transmission lines that may eventually affect large portions of a grid. In this paper, a parametric model is proposed that represents the propagation of transmission line failures in the power grid. At first, by optimal DC power-flow simulations of the IEEE 118 bus system, different types of data on the transmission line failures are collected, which can capture the time evolution of the cascade. The probability that a line of a given capacity fails is found to be well approximated by a power-law (the higher is the capacity the lower the probability). Then based on these data, a discrete-time parametric model is proposed to keep track of the failures of lines of different capacities during a cascading failure event. The convergence of the evolution of line failures to the steady state is analyzed. Finally, when compared to real-world data, the model is shown to be capable of reproducing similar trends for the time evolution of the failure dynamics.