Real-Time Decision Making Seminar

A Critical Review of Chance-constrained Optimization and Applications to Power Systems

Chance-constrained optimization is one of the major approaches for decision making in uncertain environments. Motivated by the uncertainties from deepening penetration of renewable energy resources in power systems, we provide a critical review of three major solutions to chance-constrained optimization problems: (1) scenario approach; (2) sample average approximation; and (3) convex approximation. We evaluate each solution in three aspects: (1) optimality; (2) conservativeness; and (3) complexity. Case studies based on power system problems (DC optimal power flow, optimal reactive power dispatch) are provided to examine the performance of each solution.

Anyone who would like to give one of the weekly seminars on the RTDM program can fill in the survey at https://goo.gl/forms/Li5jQ0jm01DeYZVC3.