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Machine learning optimises energy efficiency in green buildings
Publication
Machine learning optimises energy efficiency in green buildings
12 September 2024
A machine learning-based model significantly enhances energy efficiency in green buildings by accurately predicting and reducing energy consumption for cooling and heating.
Luca Papapietro
Green building (GB) techniques are vital for reducing energy waste in construction, which consumes nearly 40% of global energy. However, challenges like occupant behavior and energy management gaps often lead to higher-than-expected energy use in GBs.
Building Automation Systems (BAS) are key to improving energy efficiency. This research introduces a machine learning-based predictive model to optimize GB design, focusing on cooling and heating predictions.
The model presented in this study uses advanced ML techniques achieving high accuracy with significant energy savings. The model's success suggests potential for reduced costs, lower carbon footprints, and enhanced sustainability in green buildings.
