יום שישי, 31 ביולי 2026 LIVE
AI־INFO

כתבה arXiv cs.AI ·

Enabling Scalable Topology Inference in Distribution Systems via Constrained Multi-Source Inference

תקציר מקורי באנגליתarXiv:2607.20480v1 Announce Type: new Abstract: Accurate distribution system topology is essential for outage localization, voltage analytics, and operation of distribution grids, yet maintaining reliable connectivity records remains challenging in practice due to heterogeneous and imperfect utility data. Existing topology identification methods often rely primarily on electrical similarity or spatial records alone, which become unreliable in dense feeders and under inconsistent metadata conditions. This paper formulates distribution topology identification as a constrained inference problem that refines a utility-provided base topology using heterogeneous evidence while enforcing spatial feasibility and physical operational constraints. Instead of reconstructing connectivity from scratch,
קרא במקור המקורי