Abstract: This paper is a result of ongoing activity carried out by Understanding, Prediction, Mitigation and Restoration of Cascading Failures Task Force under IEEE Computer Analytical Methods Subcommittee (CAMS). The task force's previous papers are focused on general aspects of cascading outages such as understanding, prediction, prevention and restoration from cascading failures. This is the second of two new papers, which extend this previous work to summarize the state of the art in cascading failure risk analysis methodologies and modeling tools. The first paper reviews the state of the art in methodologies for performing risk assessment of potential cascading outages. This paper describes the state of the art in cascading failure modeling tools, documenting the view of experts representing utilities, universities and consulting companies. The paper is intended to constitute a valid source of information and references about presently available tools that deal with prediction of cascading failure events. This effort involves reviewing published literature and other documentation from vendors, universities and research institutions. The assessment of cascading outages risk evaluation is in continuous evolution. Investigations to gain even better understanding and identification of cascading events are the subject of several research programs underway aimed at solving the complexity of these events that electrical utilities face today. Assessing the risk of cascading failure events in planning and operation for power transmission systems require adequate mathematical tools/software.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).