Forecasting of Short-Term Load Using the MFF-SAM-GCN Model

Short-term load forecasting plays a significant role in the operation of power systems. Recently, deep learning has been generally employed in short-term load forecasting, primarily in the extraction of the characteristics of digital information in a single dimension without taking into account of t...

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Bibliographic Details
Main Authors:	Feng, W. (Author), Li, J. (Author), Zhang, J. (Author), Zou, Y. (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Attention mechanisms Bi-directional bi-directional long short-term memory Bi-directional long short-term memory Brain Convolution Convolutional networks Convolutional neural network Convolutional neural networks Electric load forecasting Electric power plant loads Extraction graph convolutional network Graph convolutional network Long short-term memory Multi-feature fusion One-dimensional one-dimensional convolutional neural network One-dimensional convolutional neural network Short term load forecasting short-term load forecasting
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Forecasting of Short-Term Load Using the MFF-SAM-GCN Model

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