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Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation

Abstract : This paper presents a study on dynamic line rating (DLR) forecasting procedure aimed at developing a new methodology able to forecast future ampacity values for rare and extreme events. This is motivated by the belief that to apply DLR network operators must be able to forecast their values and this must be based on conservative approaches able to guarantee the safe operation of the network. The proposed methodology can be summarised as follows: firstly, probabilistic forecasts of conductors' ampacity are calculated with a non-parametric model, secondly, the lower part of the distribution is replaced with a new distribution calculated with a parametric model. The paper presents also an evaluation of the proposed methodology in network operation, suggesting an application method and highlighting the advantages. The proposed forecasting methodology delivers a high improvement of the lowest quantiles' reliability, allowing perfect reliability for the 1% quantile and a reduction of roughly 75% in overconfidence for the 0.1% quantile.
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https://hal-mines-paristech.archives-ouvertes.fr/hal-02889892
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Soumis le : dimanche 5 juillet 2020 - 20:33:55
Dernière modification le : jeudi 24 septembre 2020 - 17:20:18
Archivage à long terme le : : vendredi 25 septembre 2020 - 11:47:41

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Romain Dupin, Laura Cavalcante, Ricardo Bessa, Georges Kariniotakis, Andrea Michiorri. Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation. Energies, MDPI, 2020, 13 (12), pp.3090. ⟨10.3390/en13123090⟩. ⟨hal-02889892⟩

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