Robust Partitioning and Operation for Maximal Uncertain-Load Delivery in Distribution Grids
<|reference_start|>Robust Partitioning and Operation for Maximal Uncertain-Load Delivery in Distribution Grids: 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.<|reference_end|>
@article{moring2024robust,
    title={Robust Partitioning and Operation for Maximal Uncertain-Load Delivery in
  Distribution Grids},
    author={Hannah Moring, Harsha Nagarajan, Kshitij Girigoudar, David M. Fobes,
  Johanna L. Mathieu},
    journal={arXiv preprint arXiv:2404.03137},
    year={2024},
    number={LA-UR-23-32237},
    archivePrefix={arXiv},
    eprint={2404.03137},
    primaryClass={math.OC cs.SY eess.SY}
}