Several challenging optimization problems in power networks involve operational decisions, non-linear models of the underlying physics described by the network as well as uncertainty in the system parameters. However, these networks exhibit a nice structure. This talk provides an overview of approaches that combine recent advances in robust optimization and conic relaxations of polynomial optimization problems along with exploiting the structure of the underlying problem. These approaches are demonstrated on applications arising in power networks.

Bio: Bissan Ghaddar is a David G. Burgoyne Faculty Fellow and an Associate Professor of Management Science at the Ivey Business School working on problems at the intersection of smart cities and nonconvex optimization models. Her research mainly focuses on developing strong conic relaxations and efficient algorithms for solving non-convex polynomial optimization problems with application to energy, transportation, and telecommunication networks. She received her Ph.D. degree in operations research from the University of Waterloo, Canada. Prior to joining Ivey Business School, she was as an Assistant Professor at the Department of Management Sciences at the University of Waterloo. She has also worked at IBM Research and at the Centre for Operational Research and Analysis, Department of National Defence Canada. Her work has been published in prestigious journals such as Mathematical Programming, INFORMS Journal on Computing, SIAM Journal on Optimization, among others. Her research has been supported by national and international grants including OCE, NSERC, Cisco, H2020, and FP7 IIF European Union Grant. She is a Balsillie School of International Affairs Fellow, a member of the Waterloo Institute of Sustainable Energy, and a member of the Affordable Energy for Humanity. She currently serves as an Associate Editor of the EURO Journal of Computational Optimization.