Bio: Antonio J. Conejo received the M.S. degree from MIT, Cambridge, Massachusetts, in 1987, and the Ph.D. degree from the Royal Institute of Technology, Stockholm, Sweden, in 1990. He is currently a professor at the Integrated System Engineering and the Electrical & Computer Engineering Departments, The Ohio State University, Columbus, Ohio. He has published over 200 papers in SCI journals and is the author or co-author of books published by Springer, John Wiley, McGraw-Hill and CRC. He has been the principal investigator of many research projects financed by public agencies and the power industry and has supervised 20 Ph.D. theses. He is an IEEE Fellow for contributions to analytical techniques for power system scheduling. His research interests include control, operations, planning, economics and regulation of electric energy systems, statistics, and optimization theory and its applications.

Abstract: This seminar presents a technique to solve efficiently a Robust Security- Constrained Optimal Power Flow (R-SCOPF) problem. A bilevel max-min optimization model is proposed to find the worst contingencies while representing Alternating Current (AC) power flow equations and considering corrective actions. The objective is to minimize the total generation cost while satisfying operation and security constraints. The upper-level problem allows representing contingencies using binary variables. The lower-level problem represents the AC optimal power flow problem using a second-order cone relaxed formulation. Duality is then used to merge the upper- and lower-level problems into a single- level one. The resulting mixed-integer second-order conic problem can be efficiently solved. Two case studies are presented as applications of this technique.