The Departmental Seminar Series is open to all. U-M Industrial and Operations Engineering graduate students and faculty are especially encouraged to attend.

The seminar will be followed by a reception in the IOE Commons (Room 1709) from 4 p.m. to 5 p.m.

Title:
Stochastic Hierarchical Planning: A Win-Win Paradigm for Power System Operations

Abstract:
Driven by ambitious renewable portfolio standards, variable energy resources (such as wind and solar) are expected to impose unprecedented levels of uncertainty to power system operations. The current practice of planning operations with deterministic optimization tools may be ill-suited for a future where uncertainty is abundant. To overcome the reliability challenges associated with the large-scale inclusion of renewable resources, we present a stochastic hierarchical planning (SHP) framework. This framework captures operations at day-ahead, short-term and hour-ahead timescales, as well as the interactions between decisions and stochastic processes across these timescales. While stochastic counterparts of individual optimization problems (e.g., unit commitment, economic dispatch etc.) have been studied previously, this presentation is built around a comprehensive computational treatment of planning frameworks that are stitched together in a hierarchical setting. Computational experiments conducted with the NREL118 dataset reveal that, relative to its deterministic counterpart, the SHP framework significantly reduces unmet demand, and can lead to substantial savings in costs and greenhouse gas emissions. Such a "Win-Win" paradigm is only possible through new approaches which combine OR and Data Science through Stochastic Programming.

Joint work with S. Atakan (formerly USC, and currently at Amazon) and H. Gangammanavar (SMU).

Bio:
Suvrajeet Sen is Professor at the Daniel J. Epstein Department of Industrial and Systems Engineering at the University of Southern California. Prior to joining USC, he was a Professor at Ohio State University (2006-2012), and University of Arizona (1982-2006). He has also served as the Program Director of OR as well as Service Enterprise Systems at the National Science Foundation. Professor Sen’s research is devoted to many categories of optimization models, and he has published over one hundred papers, with the vast majority of them dealing with models, algorithms and applications of Stochastic Programming problems. He has served on several editorial boards, including Operations Research as Area Editor for Optimization and as Associate Editor for INFORMS Journal on Computing, Journal of Telecommunications Systems, Mathematical Programming B, and Operations Research. He also serves as an Advisory Editor for several newer journals. Professor Sen was instrumental in founding the INFORMS Optimization Society in 1995, and recently served as its Chair (2015-16). Except for his years at NSF, he has received continuous extramural research funding from NSF and other basic research agencies, totaling over ten million dollars as PI over his career. He and his colleagues were jointly recognized by the INFORMS Computing Society for “seminal work” on Stochastic Mixed-Integer Programming. Professor Sen is also a Fellow of INFORMS.