Deep Learning-Based Short-Term Load Forecasting for Transformers in Distribution Grid

Deep Learning-Based Short-Term Load Forecasting for Transformers in Distribution Grid

Load of transformer in distribution grid fluctuates according to many factors, resulting in overload frequently which affects the safety of power grid. And short-term load forecasting is considered. To improve forecasting accuracy, the input information and the model structure are both considered. F...

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Bibliographic Details
Main Authors:	Renshu Wang, Jing Zhao
Format:	Article
Language:	English
Published:	Springer 2020-11-01
Series:	International Journal of Computational Intelligence Systems
Subjects:	Load forecasting convolutional neural network (CNN) Long short-term memory (LSTM) Inception structure Residual connection
Online Access:	https://www.atlantis-press.com/article/125945649/view

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