Thermal-comfort analysis and simulation for various low-energy cooling-technologies applied to an office building in a subtropical climate

Simulation of buildings' thermal-performances is necessary to predict comfort of the occupants in buildings and to identify alternate cooling control-systems for achieving better indoor thermal environments. An analysis and prediction of thermal-comfort using DesignBuilder, based on the state-of-the-art building performance simulation software EnergyPlus, is carried out in an air-conditioned multi-storeyed building in the city of Rockhampton in Central Queensland, Australia. Rockhampton is located in a hot humid-region; therefore, indoor thermal-comfort is strongly affected by the outdoor climate. This study evaluates the actual thermal conditions of the Information Technology Division (ITD) building at Central Queensland University during winter and summer seasons and identifies the thermal comfort level of the occupants using low-energy cooling technologies namely, chilled ceiling (CC), economiser usages and pre-cooling. The Fanger comfort-model, Pierce two-node model and KSU two-node model were used to predict thermal performance of the building. A sophisticated building-analysis tool was integrated with the thermal comfort models for determining appropriate cooling-technologies for the occupants to be thermally comfortable while achieving sufficient energy savings. This study compares the predicted mean-vote (PMV) index on a seven-point thermal-sensation scale, calculated using the effective temperature and relative humidity for those cooling techniques. Simulated results show that systems using a chilled ceiling offer the best thermal comfort for the occupants during summer and winter in subtropical climates. The validity of the simulation results was checked with measured values of temperature and humidity for typical days in both summer and winter. The predicted results show a reasonable agreement with the measured data.

[1]  Standard Ashrae Thermal Environmental Conditions for Human Occupancy , 1992 .

[2]  Abdullah Yildiz,et al.  Energy and exergy analyses of space heating in buildings , 2009 .

[3]  A. H. Taki,et al.  An investigation into thermal comfort in the summer season of Ghadames, Libya , 2001 .

[4]  A. Auliciems,et al.  THERMAL COMFORT CRITERIA FOR INDOOR DESIGN TEMPERATURES IN THE AUSTRALIAN WINTER , 1977 .

[5]  Noriko Umemiya,et al.  Seasonal Difference of Neutral Temperature Based on the Measured Metabolic Rate , 2001 .

[6]  S. Roaf,et al.  Standards for Thermal Comfort: Indoor air temperature standards for the 21st century , 1995 .

[7]  R. Dedear,et al.  Validation of the predicted mean vote model of thermal comfort in six Australian field studies , 1985 .

[8]  I. Budaiwi,et al.  An approach to investigate and remedy thermal-comfort problems in buildings , 2007 .

[9]  T. Frank,et al.  Climate change impacts on building heating and cooling energy demand in Switzerland , 2005 .

[10]  Stephen Sharples,et al.  Will energy regulations in the Gulf States make buildings more comfortable - A scoping study of residential buildings , 2009 .

[11]  Hiroshi Yoshino,et al.  Indoor thermal environment of urban residential buildings in China: winter investigation in five major cities , 2004 .

[12]  Povl Ole Fanger,et al.  Turbulence and draft , 1989 .

[13]  Joseph Andrew Clarke,et al.  Predicting adaptive responses - simulating occupied environments , 2006 .

[14]  P. Fanger Moderate Thermal Environments Determination of the PMV and PPD Indices and Specification of the Conditions for Thermal Comfort , 1984 .

[15]  S. Karjalainen Gender differences in thermal comfort and use of thermostats in everyday thermal environments , 2007 .

[16]  A. Auliciems,et al.  Airconditioning in Australia I – human thermal factors , 1986 .

[17]  L. Berglund,et al.  A standard predictive index of human response to the thermal environment , 1986 .