Abstract: While increased use of plug-in electric vehicles (PEVs) has environmental and economic benefits, the increased load is expected to strain components of the power delivery infrastructure. Within electric distribution systems, overloading of transformers and underground cables and associated thermal degradation is of particular concern. The current paper estimates the effect of different levels and types of PEV charging on transient heating of underground cables. Transportation survey data is used to estimate travel miles and arrival/departure times for a typical residential neighborhood, which is subsequently used to estimate the electric load curve with different levels of PEV penetration. The estimated load curves are used to perform transient heat transfer computations for a system of three buried cables using an overset grid finite-difference approach, the results of which are used to estimate acceleration of cable thermal degradation. Vehicle charging, even for a modest 30% PEV penetration, is found to nearly double peak temperature rise above ambient at the cable surface, increase the daily variance in cable temperatures, and significantly decrease the estimated time to failure for cables with thermally sensitive insulation.
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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).