Research on an hourly heat load forecasting model for district heating systems based on heterogeneous model fusion

Research on an hourly heat load forecasting model for district heating systems based on heterogeneous model fusion

Accurate load forecasting for district heating systems (DHS) is crucial for ensuring efficient production, distribution, and energy utilization. Although artificial neural networks have been widely used for DHS thermal load forecasting, their capacity to capture long-term dependencies remains limite...

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Bibliographic Details
Main Authors: Tieliu Jiang, Wenyue Liu, Jianqing Lin, Xu Jin, Zhongyan Liu
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Case Studies in Thermal Engineering
Subjects:
District heating systems
Thermal load forecasting
Bi-Mamba2
State space model
Temporal convolutional network
Kolmogorov-arnold network
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X25007609
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