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...

Full description

Bibliographic Details
Main Authors: Meng Zhang, Michael-Allan Millar, Si Chen, Yaxing Ren, Zhibin Yu, James Yu
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Energy and AI
Subjects:
Heating demand in buildings
National level forecast
Feature selection
Machine learning
Artificial neural network
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546823000873

Internet

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

Similar Items