We consider a robust optimization problem in an electric power system under uncertain demand and availability of renewable energy resources. Solving the deterministic alternating current optimal flow (ACOPF) has been considered challenging since 1960s due to its nonconvexity. Linear approximation AC sees pervasive use, but does not guarantee physically feasible configuration. In recent years, v...

In this paper, an optimization problem with uncertain objective function coefficients is considered. The uncertainty specified by providing a discrete scenario set containing possible realizations of the coefficients. concept belief in traditional and possibilistic setting applied to define admissible probability distributions over set. generalized Hurwicz criterion then used compute solution. ...

We develop a general methodology for deriving probabilistic guarantees solutions of robust optimization problems. Our analysis applies broadly to any convex compact uncertainty set and c...

Over the last two decades, robust optimization has emerged as a popular means to address decision-making problems affected by uncertainty. This includes single-stage and multi-stage involving real-valued and/or binary decisions exogenous (decision-independent) endogenous (decision-dependent) uncertain parameters. Robust techniques rely on duality theory potentially augmented with approximations...