Abstract: This paper further extends the class of energy hubs that can be modeled with a concise system description and in a computationally efficient optimization framework to permit rapid analysis of multi-energy systems. The new hub models are then embedded in the multi-energy system analysis tool Hubert and solves the multi-period optimal dispatch (MPOD) problem for a broad class of energy hub systems. Specifically, this paper presents recent improvements developed for Hubert, including the use of piece-wise linear modeling to capture nonlinear converter efficiencies, limits on hub component outputs to reflect physical limits of converters, and hub emission limits. These developments enable appropriate modeling of multi-energy micro-grids and cities and are illustrated with a multi-energy model of The University of Vermont's campus under different capital planning scenarios and modeling assumptions. Interestingly, the shortcomings of using a traditional constant-efficiency hub converter model are illustrated with an energy storage sizing application for multi-energy systems. It is shown that the traditional hub models can significantly undersize energy storage as compared to the more accurate piece-wise linear energy hub formulation.
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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).