Fairly Extreme: Minimizing Outages Equitably

Speaker: Kaarthik Sundar, Los Alamos National Laboratory

Abstract: This talk will focus on the problem of minimizing the outages due to extreme events on the power grid equitably among all customers of the grid. In particular, we shall examine two ways of incorporating fairness into the existing formulations that seek to minimize the total outage in the power grid. The first method is motivated by existing literature on incorporating fairness in optimization problems and this is done by modifying the problem’s objective function. The second method introduces a novel notion of fairness, termed ε-fairness, that can be incorporated into existing problem formulations through a single second-order cone constraint. Both these methods are very general and can be used to incorporate fairness in existing planning and operational optimization problems in the power grid and beyond. Extensive computational case studies that examine the effectiveness of both these methods to characterize fairness will also be presented. The talk will conclude with an overview of some ongoing work on incorporating fairness in vehicle routing applications. 

Bio: Kaarthik Sundar is a scientist in the Information Systems and Modeling Group at Los Alamos National Laboratory (LANL). At LANL, he is also a part of the Advanced Network Science Initiative. He obtained his Doctoral and Master's degrees in Mechanical and Electrical engineering, respectively, both from Texas A&M University, College Station. His research interests lie at the intersection of optimization, control, and learning applied to complex systems. In particular, his expertise lies in the areas of mathematical programming, large-scale deterministic and stochastic optimization, optimal control, heuristics, approximation algorithms, and reinforcement learning. He applies these techniques to solve problems that arise in the domains of pipeline infrastructure systems, transportation systems, decarbonization of energy infrastructure systems, improving the resiliency of infrastructure systems in the face of climate impacts, robotics, and autonomous systems.

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