Survivability and reciprocal altruism: Two strategies for intelligent infrastructure with applications to power grids
Intelligent Infrastuctures, , 133-150, 2010
Abstract: While electric power grids are generally robust to small failures and thus provide a fairly high level of reliability, they are notably vulnerable to large, spectacular cascading failures. Single component failures rarely impede the ability of a power grid to serve its customers. But larger sets of concurrent outages can produce blackouts with sizes that are highly improbable from the perspective of Gaussian statistics. Because of the number of components in a power grid it is impossible to plan for and mitigate all sets of failures. Maintaining a high level of reliability in the midst of this risk is challenging. As market forces, variable sources (e.g., wind and solar power) and new loads (e.g., electric cars) increase stress on electricity infrastructure, the challenge of managing grid reliability and costs will certainly increase. Therefore we need strategies that enable the most important services that depend on electricity infrastructure to continue in the midst of risks. This chapter discusses two strategies for enabling the most important services that depend on electricity continue in the midst of significant systemic vulnerability. The first, as proposed by Talukdar et al.  is survivability, in which backup electricity sources provide a very high level of reliability for services that are economically and socially vital. The second, as proposed by Hines et al. , is Reciprocal Altruism, under which agents that manage the infrastructure are encouraged to align personal goals with those of the system as a whole.
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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).