Experimental assessment of a satisfaction based thermal comfort control for a group of occupants

The set point of the Heating, Ventilating and Air Conditioning (HVAC) system is usually given by the Predicted Mean Vote (PMV) model. However, the individual differences in thermal preference often incur dissatisfactions in a group, which indicates that the PMV model may have bias in predicting the thermal comfort for a group of occupants. It has great potential to find a more suitable model to determine room set points. In this paper, a satisfaction based group comfort model is developed based on our previous work. We build an individual comfort model for each person according to their satisfaction and take the convex hull of these comfort zones. Some experiments are implemented for the group under both cooling and heating conditions in an ordinary office environment. The experimental results including indoor environment control, users' acceptance, working efficiency and energy consumption are supporting the presented group model.

[1]  A. P. Gagge,et al.  An Effective Temperature Scale Based on a Simple Model of Human Physiological Regulatiry Response , 1972 .

[2]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[3]  R. Dedear Developing an adaptive model of thermal comfort and preference , 1998 .

[4]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[5]  Zhenjun Ma,et al.  Supervisory and Optimal Control of Building HVAC Systems: A Review , 2008 .

[6]  M. Conner,et al.  Efficacy of the Theory of Planned Behaviour: a meta-analytic review. , 2001, The British journal of social psychology.

[7]  P. O. Fanger,et al.  Thermal comfort: analysis and applications in environmental engineering, , 1972 .

[8]  Zhengwei Li,et al.  Multiplexed optimization for complex air conditioning systems , 2013 .

[9]  Marie Johnston,et al.  Application of the Theory of Planned Behaviour in Behaviour Change Interventions: A Systematic Review , 2002 .

[10]  Koushik Kar,et al.  Building Temperature Control With Active Occupant Feedback , 2014 .

[11]  J A Stolwijk,et al.  MATHEMATICAL MODELS OF THERMAL REGULATION , 1980, Annals of the New York Academy of Sciences.

[12]  Jan A. J. Stolwijk,et al.  Mathematical Model of Thermoregulation , 1970 .

[13]  J. van Hoof Forty years of Fanger's model of thermal comfort: comfort for all? , 2008, Indoor air.

[14]  Hui Zhang,et al.  Thermal sensation and comfort models for non-uniform and transient environments: Part III: whole-body sensation and comfort , 2009 .

[15]  Michael A. Humphreys,et al.  Field Studies of Indoor Thermal Comfort and the Progress of the Adaptive Approach , 2007 .

[16]  Yi Jiang,et al.  Preliminary study of learning individual thermal complaint behavior using one-class classifier for indoor environment control , 2014 .

[17]  Kamel Ghali,et al.  Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm , 2009 .

[18]  Yi Jiang,et al.  A data-driven method to describe the personalized dynamic thermal comfort in ordinary office environment: From model to application , 2014 .

[19]  Yi Jiang,et al.  Experimental study of group thermal comfort model , 2014, 2014 IEEE International Conference on Automation Science and Engineering (CASE).

[20]  Dirk Snelders,et al.  Designing Visual Recognition for the Brand , 2010 .