An optimized method for short-term load forecasting based on feature fusion and ConvLSTM-3D neural network

An optimized method for short-term load forecasting based on feature fusion and ConvLSTM-3D neural network

As renewable energy continues to penetrate modern power systems, accurate short-term load forecasting is crucial for optimizing power generation resource allocation and reducing operational costs. Traditional forecasting methods often overlook key factors such as holiday load variations and differen...

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Bibliographic Details
Main Authors: Xiaofeng Yang, Shousheng Zhao, Kangyi Li, Wenjin Chen, Si Zhang, Jingwei Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Energy Research
Subjects:
short-term load forecasting
fused features
prophet algorithm
SHAP algorithm
convlstm-3D model
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2024.1501963/full
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