A new zone temperature predictive modeling for energy saving in buildings

Hao Huang*, Lei Chen, Morteza Mohammadzaheri, Eric Hu

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

28 Citations (Scopus)


Currently in most buildings, the heating, ventilation and air conditioning (HVAC) systems are controlled by the present temperature in the building. If the predictions for future temperature in the building or a zone were available, the building management system (BMS) could use both present and future temperatures to control HVAC systems, the energy consumed by HAVC systems could then be minimised. Therefore, a lot of research effort has been devoted to develop accurate temperature prediction models using various approaches, e.g. traditional thermodynamic, artificial neural networks (ANN), generic algorithms (GA) and fuzzy logic approaches. When the historical data of the building is available, the ANN approach is thought to be the most cost-effective method. Most of previous studies of ANN modelling of building temperature, have either focused on single-zone examination or assumed that zones' temperatures were the same throughout the building. In this study, a more realistic multi-zone scenario in a large building is proposed in the developing of the ANN temperature predictive model. The coupled effects between zones caused by the temperature difference are considered in the model. The results of a case study show that the new ANN model that considers the temperatures of the neighbouring zones, achieves more accurate results. The proposed modelling methodology can be extended to include other inputs, besides neighboring zones' temperatures, usage pattern of the building, so that the better intelligent control strategies can be developed for energy saving purposes, based on the more accurate predicted temperatures form the new model.

Original languageEnglish
Pages (from-to)142-151
Number of pages10
JournalProcedia Engineering
Publication statusPublished - 2012
Externally publishedYes
EventEvolving Energy-International Energy Foundation International Energy Congress, IEF-IEC 2012 - Sydney, NSW, Australia
Duration: Sept 1 2012Sept 1 2012


  • Artificial neural networks (ANN)
  • HVAC
  • Multi-zone

ASJC Scopus subject areas

  • General Engineering


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