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Many complex infrastructure systems, such as electric power transmission grids, display characteristics of a critical or near critical behavior with a risk of large cascading failures. Understanding this risk and its relation to the system state as it evolves could allow for a more realistic risk assessment and even for mitigation measures. We use the OPA model of cascading blackouts and grid evolution to describe and quantify regimes of criticality of the power grid. [ABSTRACT FROM AUTHOR]

Cascading blackouts can be thought of as initiating events followed by propagating events that progressively weaken the power system. We briefly discuss the implications for assessing cascading risk by proper sampling from the various sources of uncertainty and for mitigating cascading risk by reducing both the initiating events and their propagation. [ABSTRACT FROM AUTHOR]

We show how to use standard transmission line outage historical data to obtain the network topology in such a way that cascades of line outages can be easily located on the network. Then we obtain statistics quantifying how cascading outages typically spread on the network. Processing real outage data is fundamental for understanding cascading and for evaluating the validity of the many different models and simulations that have been proposed for cascading in power networks. [ABSTRACT FROM PUBLISHER]

• Many nodes on realistic electric grid networks can be simplified allowing faster calculations. • Solving the potential on the nodes in place of the current can sparsify the simplex matrix. • Accurate WECC model is less sensitive to the dispatch due to its low clustering coefficient. The social and economic costs of large blackouts in power transmission networks make it critical to properly understand their dynamics. The OPA model was developed with this objective in mind and has previously been applied to power grids of small and medium size, some of them properly modeling realistic cases such as the simplified WECC network, covering the Western region of the US. The bulk of the OPA model's computational cost comes from the repeated solution of a linear programming problem using the Simplex method which is difficult to parallelize. In this paper we introduce important improvements to the modeling part of the linear problem, accelerating the previous implementation by a factor of up to 200, depending on the network. These improvements make it possible, from a practical point of view, to simulate the largest, most detailed, WECC network consisting of 19,402 nodes, reducing the wall-clock time of the simulation from two years to only 10 days. The first simulations show an interesting result: the detailed 19,402 nodes network displays a reduced sensitivity of the dynamics to the dispatch, when compared to the previously used simplified WECC models containing only 1553 and 2504 nodes. [ABSTRACT FROM AUTHOR]