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This paper delineates a novel analytical and computational approach to fault location for power transmission grids. The proposed methodology involves an online and an offline stage. The online stage is based solely on the utilization of the time-of-arrival (ToA) measurements of traveling waves propagating from the fault-occurrence point to synchronized wide-area monitoring devices installed at strategically selected substations. The captured waveforms are processed together at the time of fault in order to identify the location of the fault under study. The overall performance of the developed technique is demonstrated using Alternative Transients Program (ATP) simulations of fault transients and postprocessing the faulted waveform data via discrete wavelet transform. The applicability of the algorithm is independent of the fault type and can readily be extended to transmission grids of any size.

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Increased interconnection between critical infrastructure networks, such as electric power and communications systems, has important implications for infrastructure reliability and security. Others have shown that increased coupling between networks that are vulnerable to internetwork cascading failures can increase vulnerability. However, the mechanisms of cascading in these models differ from those in real systems and such models disregard new functions enabled by coupling, such as intelligent control during a cascade. This paper compares the robustness of simple topological network models to models that more accurately reflect the dynamics of cascading in a particular case of coupled infrastructures. First, we compare a topological contagion model to a power grid model. Second, we compare a percolation model of internetwork cascading to three models of interdependent power-communication systems. In both comparisons, the more detailed models suggest substantially different conclusions, relative to the simpler topological models. In all but the most extreme case, our model of a “smart” power network coupled to a communication system suggests that increased power-communication coupling decreases vulnerability, in contrast to the percolation model. Together, these results suggest that robustness can be enhanced by interconnecting networks with complementary capabilities if modes of internetwork failure propagation are constrained.

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