Forecasting thermal parameters for ultra‐high voltage transformers using long‐ and short‐term time‐series network with conditional mutual information

Abstract Precise forecasting of the thermal parameters is a critical factor for the safe operation and fault incipient warning of the ultra‐high voltage (UHV) transformers. In this work, a novel multi‐step forecasting method based on the long‐ and short‐term time‐series network (LSTNet) with the con...

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Bibliografiske detaljer

Principais autores:	Weiqing Lin, Xiren Miao, Jing Chen, Sa Xiao, Yanzhen Lu, Hao Jiang
Format:	Artigo
Sprog:	Inglês
Udgivet:	Wiley 2022-05-01
Serier:	IET Electric Power Applications
Fag:	conditional mutual information (CMI) forecasting method long‐ and short‐term time‐series network (LSTNet) top oil temperature UHV transformers winding temperature
Online adgang:	https://doi.org/10.1049/elp2.12175
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