Enhancing hourly heat demand prediction through artificial neural networks: A national level case study

Enhancing hourly heat demand prediction through artificial neural networks: A national level case study

Meeting the goal of zero emissions in the energy sector by 2050 requires accurate prediction of energy consumption, which is increasingly important. However, conventional bottom-up model-based heat demand forecasting methods are not suitable for large-scale, high-resolution, and fast forecasting due...

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Detalhes bibliográficos
Main Authors: Meng Zhang, Michael-Allan Millar, Si Chen, Yaxing Ren, Zhibin Yu, James Yu
Formato: Artigo
Idioma:English
Publicado em: Elsevier 2024-01-01
Colecção:Energy and AI
Assuntos:
Heating demand in buildings
National level forecast
Feature selection
Machine learning
Artificial neural network
Acesso em linha:http://www.sciencedirect.com/science/article/pii/S2666546823000873

Internet

http://www.sciencedirect.com/science/article/pii/S2666546823000873

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