Efficient Residential Electric Load Forecasting via Transfer Learning and Graph Neural Networks

The accurate short-term electric load forecasting (STLF) is critical for the safety and economical operation of modern electric power systems. Recently, the graph neural network (GNN) has been applied in STLF and achieved impressive success via utilizing spatial dependency between residential househ...

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Bibliographic Details
Published in:	IEEE transactions on smart grid 2023-05, Vol.14 (3), p.1-1
Main Authors:	Wu, Di, Lin, Weixuan
Format:	Article
Language:	English
Subjects:	Convolution Correlation Data models Domains Electric load forecasting Electric power systems Electrical loads Forecasting Graph neural networks Households Learning Load forecasting Load modeling Mathematical models Neural networks Predictive models Residential areas Training transfer learning
Citations:	Items that this one cites Items that cite this one
Online Access:	Get full text
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