Publications
Packetized Plug-in Electric Vehicle Charge Management
IEEE Transactions on Smart Grid, 5, 642-640, 2014
Status: Published
Citations: 11
Cite: [bibtex]

Abstract: Plug-in electric vehicle (PEV) charging could cause significant strain on residential distribution systems, unless technologies and incentives are created to mitigate charging during times of peak residential consumption. This paper describes and evaluates a decentralized and ‘packetized’ approach to PEV charge management, in which PEV charging is requested and approved for time-limited periods. This method, which is adapted from approaches for bandwidth sharing in communication networks, simultaneously ensures that constraints in the distribution network are satisfied, that communication bandwidth requirements are relatively small, and that each vehicle has fair access to the available power capacity. This paper compares the performance of the packetized approach to an optimization method and a first-come, first- served (FCFS) charging scheme in a test case with a constrained 500 kVA distribution feeder and time-of-use residential electricity pricing. The results show substantial advantages for the packetized approach. The algorithm provides all vehicles with equal access to constrained resources and attains near optimal travel cost performance, with low complexity and communication requirements. The proposed method does not require that vehicles report or record driving patterns, and thus provides benefits over optimization approaches by preserving privacy and reducing computation and bandwidth requirements.
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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.
Continuous Self-Modeling. Science 314, 1118 (2006). [Journal Page]

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).