An analysis of future building energy use in subtropical Hong Kong

Principal component analysis of prevailing weather conditions in subtropical Hong Kong was conducted, and a new climatic index Z (as a function of the dry-bulb temperature, wet-bulb temperature and global solar radiation) determined for past (1979–2008, measurements made at local meteorological station) and future (2009–2100, predictions from general circulation models) years. Multi-year (1979–2008) building energy simulations were carried out for a generic office building. It was found that Z exhibited monthly and seasonal variations similar to the simulated cooling/heating loads and building energy use. Regression models were developed to correlate the simulated monthly building cooling loads and total energy use with the corresponding Z. Error analysis indicated that annual building energy use from the regression models were very close to the simulated values; the difference was about 1%. Difference in individual monthly cooling load and energy use, however, could be up to 4%. It was also found that both the DOE-simulated results during 1979–2008 and the regression-predicted data during 2009–2100 indicated an increasing trend in annual cooling load and energy use and a gradual reduction in the already insignificant heating requirement in cooling-dominated office buildings in subtropical climates.

[1]  H. Storch,et al.  Statistical Analysis in Climate Research , 2000 .

[2]  A HC van Paassen,et al.  Weather data generator to study climate change on buildings , 2002 .

[3]  Tony N.T. Lam,et al.  Principal component analysis and long-term building energy simulation correlation , 2010 .

[4]  Jn Hacker,et al.  Constructing design weather data for future climates , 2005 .

[5]  Danny H.W. Li,et al.  Long term ambient temperature analysis and energy use implications in Hong Kong , 2004 .

[6]  R Aguiar,et al.  Climate change impacts on the thermal performance of Portuguese buildings. Results of the SIAM study , 2002 .

[7]  C. Lam On Climate Changes Brought About by Urban Living , 2006 .

[8]  Lisa Guan,et al.  Preparation of future weather data to study the impact of climate change on buildings , 2009 .

[9]  Masson-Delmotte,et al.  The Physical Science Basis , 2007 .

[10]  Dennis M. Driscoll,et al.  A Comparison of Objective and Subjective Means of Weather Typing: An Example from West Texas , 1980 .

[11]  Donald L. Hadley,et al.  Daily variations in HVAC system electrical energy consumption in response to different weather conditions , 1993 .

[12]  Tony N.T. Lam,et al.  Long-term trends of heat stress and energy use implications in subtropical climates , 2010 .

[13]  Alexei G. Sankovski,et al.  Special report on emissions scenarios , 2000 .

[14]  Geoff Levermore,et al.  New algorithm for generating hourly temperature values using daily maximum, minimum and average values from climate models , 2007 .

[15]  Joseph C. Lam Building envelope loads and commercial sector electricity use in Hong Kong , 1995 .

[16]  L. Kalkstein,et al.  An Evaluation of Three Clustering Procedures for Use in Synoptic Climatological Classification , 1987 .

[17]  John F. B. Mitchell,et al.  THE WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research , 2007 .

[18]  Liu Yang,et al.  Principal component analysis of electricity use in office buildings , 2008 .

[20]  Joseph C. Lam,et al.  An analysis of climatic influences on chiller plant electricity consumption , 2009 .

[21]  Jacob N. Hacker,et al.  Climate Change and the Indoor Environment: Impacts and Adaptation , 2005 .

[22]  Geoff Levermore,et al.  A review of the IPCC Assessment Report Four, Part 1: the IPCC process and greenhouse gas emission trends from buildings worldwide , 2008 .

[23]  J. C. Lam,et al.  Seasonal variations in residential and commercial sector electricity consumption in Hong Kong , 2008 .

[24]  L O Degelman Which came first – building cooling loads or global warming? – a cause and effect examination , 2002 .

[25]  Joseph C. Lam,et al.  Energy analysis of commercial buildings in subtropical climates , 2000 .

[26]  J. C. Lam,et al.  Energy consumption in Hong Kong , 1994 .

[27]  R. Cess,et al.  Regional Cloud Cover Change Associated with Global Climate Change: Case Studies for Three Regions of the United States. , 1999 .