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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]

For a given minimum cost of the electricity dispatch, multiple equivalent dispatch solutions may exist. We explore the sensitivity of networks to these dispatch solutions and their impact on the vulnerability of the network to cascading failure blackouts. It is shown that, depending on the heterogeneity of the network structure, the blackout statistics can be sensitive to the dispatch solution chosen, with the clustering coefficient of the network being a key ingredient. We also investigate mechanisms or configurations that decrease discrepancies that can occur between the different dispatch solutions. [ABSTRACT FROM AUTHOR]

Failures of the complex infrastructures society depends on having enormous human and economic cost that poses the question: Are there ways to optimize these systems to reduce the risks of failure? A dynamic model of one such system, the power transmission grid, is used to investigate the risk from failure as a function of the system size. It is found that there appears to be optimal sizes for such networks where the risk of failure is balanced by the benefit given by the size. [ABSTRACT FROM AUTHOR]

A simple dynamic model of agent operation of an infrastructure system is presented. This system evolves over a long time scale by a daily increase in consumer demand that raises the overall load on the system and an engineering response to failures that involves upgrading of the components. The system is controlled by adjusting the upgrading rate of the components and the replacement time of the components. Two agents operate the system. Their behavior is characterized by their risk-averse and risk-taking attitudes while operating the system, their response to large events, and the effect of learning time on adapting to new conditions. A risk-averse operation causes a reduction in the frequency of failures and in the number of failures per unit time. However, risk aversion brings an increase in the probability of extreme events. [ABSTRACT FROM AUTHOR]

We give an overview of a complex systems approach to large blackouts of electric power transmission systems caused by cascading failure. Instead of looking at the details of particular blackouts, we study the statistics and dynamics of series of blackouts with approximate global models. Blackout data from several countries suggest that the frequency of large blackouts is governed by a power law. The power law makes the risk of large blackouts consequential and is consistent with the power system being a complex system designed and operated near a critical point. Power system overall loading or stress relative to operating limits is a key factor affecting the risk of cascading failure. Power system blackout models and abstract models of cascading failure show critical points with power law behavior as load is increased. To explain why the power system is operated near these critical points and inspired by concepts from self-organized criticality, we suggest that power system operating margins evolve slowly to near a critical point and confirm this idea using a power system model. The slow evolution of the power system is driven by a steady increase in electric loading, economic pressures to maximize the use of the grid, and the engineering responses to blackouts that upgrade the system. Mitigation of blackout risk should account for dynamical effects in complex self-organized critical systems. For example, some methods of suppressing small blackouts could ultimately increase the risk of large blackouts. [ABSTRACT FROM AUTHOR]