IEOR PhD students Julie Mulvaney-Kemp and Salar Fattahi were awarded one of the best conference papers at the 2020 Power & Energy Society General Meeting for their work titled “Load Variation Enables Escaping Poor Solutions of Time-Varying Optimal Power Flow”. Julie and Salar were advised by Prof Javad Lavaei.
Berkeley IEOR congratulates Julie, Salar, and Prof Lavaei! The abstract for the paper can be found below; click here to access the entire paper.
Abstract—This paper analyzes solution trajectories for optimal power low (OPF) with time-varying load. Despite its nonconvexity, it is common to solve time-varying OPF sequentially over time using simple local search algorithms. We aim to understand the local and global optimality behavior of these local solution trajectories. An empirical study on California data shows that local solution trajectories initialized at different points may converge to the time-varying global solution of the data-driven OPF, even if the problem has multiple local solutions throughout time. That is, these trajectories can avoid poor solutions. To explain this phenomenon, we introduce a backward mapping that relates a neighborhood of the time-varying OPF’s global solution at a given time to a set of desirable initial points. We show that this proposed backward mapping could act as a stochastic gradient ascent algorithm on an implicitly convexified formulation of OPF, which justifies the escaping of poor solutions over time.Mulvaney-Kemp, Julie; Fattahi, Salar & Lavaei, Javad. (2019). Load Variation Enables Escaping Poor Solutions of Time-Varying Optimal Power Flow.