2024/04/04 by Hannah Moring, Harsha Nagarajan, Moring, Hannah +7
Computer Science · Engineering · #Distributed and Parallel Computing Systems #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Scheduling and Optimization Algorithms #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2404.03137
openalex publication_date 2024/04/04 · openalex created_date 2024/04/07 · openalex updated_date 2026/07/28
To mitigate the vulnerability of distribution grids to severe weather events, some electric utilities use preemptive de-energization as the primary line of defense, causing significant power outages. In such instances, networked microgrids could improve resiliency and maximize load delivery, though the modeling of three-phase unbalanced network physics and computational complexity pose challenges. These challenges are further exacerbated by an increased penetration of uncertain loads. In this paper, we present a two-stage mixed-integer robust optimization problem that configures and operates networked microgrids, and is guaranteed to be robust and feasible to all realizations of loads within a specified uncertainty set, while maximizing load delivery. To solve this problem, we propose a cutting-plane algorithm, with convergence guarantees, which approximates a convex recourse function with sub-gradient cuts. Finally, we provide a detailed case study on the IEEE 37-bus test system to demonstrate the economic benefits of networking microgrids to maximize uncertain-load delivery.