Congratulations to Meng Zhang, Zhihui Li, and Professor Zhibin Yu on their latest paper, “Machine Learning-based regional cooling demand prediction with Optimised dataset partitioning“, published in Energy and Buildings, Volume 344 (1 October 2025).
Meng is a key contributor to Work Package 3: Heat Digital Twin within the Ensign project, and this publication marks an exciting step forward in energy-efficient building research.
As global temperatures rise, even cooler regions like the UK are seeing increased demand for cooling — especially in urban areas like London. This study introduces a generalised framework for developing high-resolution LSTM and GRU networks using physical model-based summer cooling demand data. These predictive models are essential for improving energy management and maintaining efficiency in domestic buildings.
Fantastic work by the team!
