IMI Interdisciplinary Mathematics InstituteCollege of Arts and Sciences

Ninth Annual Graduate Student Mini-conference in Computational Mathematics
Speaker

Keynote
Mihai Anitescu
Argonne National Laboratory
http://www.mcs.anl.gov/~anitescu/

Dr. Mihai Anitescu, is a Senior Computational Mathematician in the Mathematics and Computer Science Division at Argonne National Laboratory and a Professor in the Department of Statistics at the University of Chicago. Dr. Anitescu is one of the leaders in the research area of uncertainty quantification and numerical optimization. He is best known for the work of computational mathematics in nuclear engineering, electricity grid, and materials science. He has co-authored more than 100 peer-reviewed papers in scholarly journals, book chapters, and conference proceedings, and he is on the editorial board of Mathematical Programming A and B, SIAM Journal on Optimization, Optimization Methods and Software, SIAM Journal on Scientific Computing, and SIAM/ASA Journal on Uncertainty Quantification.


Talk

Mathematical and computational challenges in energy systems

  • Feb. 17, 2018
  • 9 a.m.
  • LeConte 412

The electrical power grid (the electricity transmission and distribution system) is one of the most complex engineering achievements of the 20th century. It is also at the center of massive changes in the way we create and consume energy. A distinguishing feature of power grid applications is that optimization is ubiquitous and that it must accommodate simultaneously multiple complexity drivers. These include not only discrete variables, nonconvexity, or stochasticity but also ordinary and, with the increased usage of natural gas, partial differential equations. We outline a number of existing and emerging fundamental research challenges and discuss some recent promising avenues in the area. We will discuss in some detail the issue of long-horizon dynamic optimization problems that appear in planning problems and stochastic optimization problems that accommodate the uncertainty stemming from massive penetration of renewable resources.

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