Enhancing Short-Term Load Forecasting Through K-Shape Clustering and Deep Learning Integration

Enhancing Short-Term Load Forecasting Through K-Shape Clustering and Deep Learning Integration

Short-term load forecasting (STLF) is essential for the efficient operation and management of modern power grids, impacting dispatch and trading strategies in electricity markets. However, accurately forecasting short-term loads remains challenging due to the difficulty in categorizing diverse opera...

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Bibliographic Details
Main Authors: Wentao Zhang, Meng Cheng, Qianliang Xiang, Qinmiao Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Short-term load forecasting (STLF)
K-shape clustering
deep learning
NBEATSx
power system operation
Online Access:https://ieeexplore.ieee.org/document/10883988/

Internet

https://ieeexplore.ieee.org/document/10883988/

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