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Data-driven transient forecasting for generator digital twin decision support

A calibrated surrogate model for forecasting generator transients was developed to support digital twin decision-making. The model evaluates planned load commands before application using event-conditioned Hankel-DMDc and split-conformal calibration for prediction bands, helping operators ensure voltage and frequency remain within limits.

Why it matters

This approach improves reliability of operational power system management by providing probabilistic assessment of control actions.

Relevant to DT products

Original headline
Data-Driven Generator Transient Prediction for Digital Twin Decision Support
Read the original: arXiv API — полнотекстовый поиск "digital twin"

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