Optimization of indoor air temperature set-point for centralized air-conditioned spaces in subtropical climates

Kwok Wai Mui, Ling Tim Wong, Nai Kong Fong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)


Current Building Management System (BMS) does not integrate well with real-time occupant response. In order to fine-tune the system to meet individual demands and to maximize the occupant acceptance of indoor thermal environment, a new notion of Bayesian control algorithm was developed in this study. Control parameters of a weighting function for air temperature control (namely, the control temperature constant kTand the probable acceptance of the air temperature set-point λ) and two prior distribution functions of air temperature set-point, namely the uniform prior and the expert's prior, were examined. Optimum air temperature set-points of air-conditioning systems obtained from certain Hong Kong offices were then used to demonstrate the applicability of the new algorithm for controlling an example air temperature set-point ranged between 0.2 °C and 1 °C. This algorithm would be useful for adaptive thermal comfort control in a large, post-occupied air-conditioned space.
Original languageEnglish
Pages (from-to)709-713
Number of pages5
JournalAutomation in Construction
Issue number6
Publication statusPublished - 1 Oct 2010


  • Air temperature set-point
  • Building Management System (BMS)
  • Occupant perception
  • Thermal comfort

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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