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arXiv AI By Yunqin Zhu, Feng Qiu, Yao Xie

OutageDiT: A Generative Foundation Model for Power Outage Forecasting and Scenario Simulation

Read the original on arXiv AI →

OutageDiT is a generative foundation model that produces seven‑day power‑outage trajectories at quarter‑hour resolution, trained on nationwide outage and weather data. It uses a condition encoder to process historical context and future covariates, and a shallow flow decoder to generate full trajectories, enabling point forecasting, uncertainty quantification, and conditional event simulation. The model outperforms strong baselines on forecasting benchmarks and can transfer zero‑shot to unseen regions, linking outage simulation to operational planning under uncertainty.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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