Speakers: Dr. Daniel Molzahn, Assistant Professor, School of Electrical and Computer Engineering

Seminar Topic: An Overview of Operational Challenges and Related Applications of Convex Optimization Techniques for Future Electric Power Grids

Abstract of Talk: The National Academy of Engineering has classified widespread electrification as one of the greatest engineering accomplishments of the 20th century. The ubiquity of electricity access in much of the world masks the challenges facing electric power systems in the 21st century; reliability and economic efficiency improvements are needed for future electric power systems. This presentation first overviews some of the major challenges facing operators of electric power systems and then discusses recent research that uses convex optimization techniques to address these challenges. In particular, this research relaxes non-convex models of power system networks to more tractable convex formulations that can be embedded within a variety of optimization and control problems. Selected applications include algorithms which globally solve power system optimization problems, certify infeasibility, assure robustness of operating points with respect to certain fluctuations in the power injections, and compute visualizations of the feasible spaces for power system optimization problems.

Biographical Sketches of the Speakers: Daniel Molzahn joined the faculty of the School of Electrical and Computer Engineering at Georgia Tech in Spring 2019. Prior to this position, Dr. Molzahn was a computational engineer at Argonne National Laboratory in the Center for Energy, Environmental, and Economic Systems Analysis (CEEESA), where he currently holds an affiliate position. He was a Dow Postdoctoral Fellow in Sustainability in the Electrical Engineering and Computer Science Department at the University of Michigan. He received the B.S., M.S., and Ph.D. degrees in Electrical Engineering and the Master’s of Public Affairs degree from the University of Wisconsin–Madison, where he was a National Science Foundation Graduate Research Fellow. His research interests are in the development of optimization and control techniques for electric power systems.