2023
DOI: 10.48550/arxiv.2301.02651
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A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow

Abstract: In this paper, we propose a robust data-driven process model whose hyperparameters are robustly estimated using the Schweppe-type generalized maximum likelihood estimator. The proposed model is trained on recorded time-series data of voltage phasors and power injections to perform a time-series stochastic power flow calculation. Power system data are often corrupted with outliers caused by large errors, fault conditions, power outages, and extreme weather, to name a few. The proposed model downweights vertical… Show more

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References 28 publications
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