Presenter: James Luedtke, ISE Professor at the University of Wisconsin-Madison 

Seminar Title: Generator Expansion to Improve Power Grid Resiliency and Efficiency: A Case Study in Optimization Under Rare, High-Impact Uncertain Event

Abstract:

We consider the problem of choosing power generator locations in a power grid to yield a system that is both efficient on average and resilient to extreme weather events. This problem is challenging due to the combination of discrete decisions and the need to consider performance of the system under rare high-impact outcomes. We use this problem as a case study to illustrate modeling principles and solution techniques that may be useful more broadly in optimization of systems impacted by rare but extreme events. Specifically, we introduce a stochastic integer programming modeling framework, advocate for a bi-objective modeling approach for balancing efficiency and resiliency, introduce a conditional sampling method for addressing the challenge of low-probability high-impact events, discuss methods for solving the resulting approximation models, and illustrate the importance of modeling spatial dependence of the uncertain parameters in the system.

This is joint work with Ramsey Rossmann, Mihai Anitescu, Julie Bessac, Michael Ferris, Mitchell Krock, and Line Roald.

Bio:

Jim Luedtke is a Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison and a Discovery Fellow at the Wisconsin Institute for Discovery. Luedtke earned his PhD at Georgia Tech and did postdoctoral work at the IBM T.J. Watson Research Center. Luedtke’s research is focused on methods for solving stochastic and mixed-integer optimization problems, as well as applications of such models. Luedtke is a recipient of an NSF CAREER award, was a finalist in the INFORMS JFIG Best Paper competition, and was awarded the INFORMS Optimization Society Prize for Young Researchers. Luedtke serves on the editorial board of Mathematical Programming Computation, is chair of the Mathematical Optimization Society Publications Committee, and serves as Vice-Chair for Optimization under Uncertainty for the INFORMS Optimization Society.