Enabling Scalable Topology Inference in Distribution Systems via Constrained Multi-Source Inference
Leveraging constrained inference to automate and verify complex power grid connectivity with 95% accuracy.
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 ide...
ArXiv CS.AI
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This research bridges the gap between unreliable utility data and grid stability by using constrained inference to automate complex topology mapping. By prioritizing physical feasibility, the model allows power operators to maintain grid observability with significantly higher precision and lower computational overhead.
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