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LANS Informal Seminar: Daniel Molzahn
November 16, 2017 @ 10:30 CST
Seminar Title: Recent Progress in Optimal Power Flow: A Survey of Convex Relaxations and an Algorithm for Robust Feasibility
Speaker: Daniel Molzahn, Computational Engineer, ES Division, Argonne National Laboratory
Date/Time: 2017-11-16 10:30
Location: Bldg. 240, Room 1404
Description:
Optimal power flow (OPF) is an important problem in the operation of electric power systems. The solution to an OPF problem provides a minimum cost operating point that satisfies both engineering limits and the power flow equations corresponding to the network physics. Optimal power flow is a non-convex, NP-hard optimization problem that may have multiple local optima. Many recent research efforts have applied convex relaxation techniques to compute bounds on the optimal objective values, certify problem infeasibility, and, in some cases, obtain the globally optimal decision variables of OPF problems. The first part of this presentation surveys the OPF relaxation literature with a focus on recent developments.
With growing penetrations of renewable generation, OPF problems are increasingly influenced by the forecast uncertainty and short-term fluctuations that are inherent to many renewable energy sources. Thus, reliable and efficient operation of power systems requires the solution of OPF problems that incorporate uncertainty. The second part of this presentation describes a recently proposed iterative algorithm for the OPF problem that uses convex relaxation techniques to obtain a solution with robust feasibility guarantees.