Robust Transmission Expansion Planning

Wednesday, April 20, 2016
7:00 AM to 8:00 AM
MEZ 1.306
Open to ECE graduate students

This presentation addresses the problem of transmission expansion planning under uncertainty in an electric energy system. We consider different sources of uncertainty, including future demand growth and the availability of generation facilities, which are characterized for different regions within the electric energy system. An adaptive robust optimization model is used to derive the investment decisions that minimizes the system's total costs by anticipating the worst case realization of the uncertain parameters within an uncertainty set. The proposed formulation materializes in a mixed-integer three-level optimization problem whose lower-level problem can be replaced by its KKT optimality conditions. The resulting mixed-integer bilevel model is efficiently solved by decomposition using a cutting plane algorithm solely based on primal cuts. A realistic case study is used to illustrate the working of the proposed technique, and to analyze the relationship between the optimal investment plans, the investment budget and the level of supply security at the different regions of the system.

x x


Antonio J. Conejo

Ohio State University

Antonio J. Conejo, professor at The Ohio State University, OH, US, received the B.S from Univ. P. Comillas, Spain, the M.S. from MIT, US and the Ph.D. from the Royal Institute of Technology, Sweden. He has published over 165 papers in SCI journals and is the author or coauthor 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 19 PhD theses. He is an IEEE Fellow.