Rapid assessment, visualization, and mitigation of cascading failure risk in power systems
System Sciences (HICSS), 2015 48th Hawaii International Conference on, , 2748-2758, 2015
Abstract: This paper describes a new approach, using "Random Chemistry" sampling, to estimate the risk of large cascading blackouts triggered by multiple contingencies. On a 2383 bus test case the new approach finds the expected value of large-blackout sizes (a measure of risk) two orders of magnitude faster than Monte Carlo sampling, without introducing measurable bias. We also derive a method to compute the sensitivity of blackout risk to individual component-failure probabilities, allowing one to quickly identify low-cost strategies for reducing risk. For example, we show how a 1.9% increase in operational costs reduced the overall risk of cascading failure in a 2383-bus test case by 61%. An examination of how risk changes with load yielded a surprising decrease in cascading failure risk at the highest loadings, due to increased locality in generation and less long-distance transmission. Finally, this paper proposes new visualizations of spatio-temporal patterns in cascading failure risk that could provide valuable guidance to system planners and operators.
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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).