Spatial-Temporal Residential Short-Term Load Forecasting via Graph Neural Networks

• Published in: IEEE transactions on smart grid Vol. 12; no. 6; pp. 5373 - 5384
• Main Authors: Lin, Weixuan, Wu, Di, Boulet, Benoit
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.11.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Convolution; Correlation; Electric load forecasting; Electric power grids; Electrical loads; Forecasting; Graph neural networks; Houses; Load; Load forecasting; Load modeling; Machine learning; Neural networks; Predictive models; Residential energy; Spatial dependencies; spatial-temporal

Electric load forecasting, especially short-term load forecasting, is of significant importance for the safe and efficient operation of power grids. With the wide adoption of advanced smart meters, more attention has been paid to short-term residential load forecasting. Most of the existing load for...