Principal component analysis and long-term building energy simulation correlation

Abstract

The objective was to investigate whether energy use in buildings from simulation could be correlated with a new composite climatic index, which would account for the influences of major climatic variables such as temperature, humidity and solar radiation. Principal component analysis of prevailing weather conditions in sub-tropical Hong Kong was conducted, and a new climatic index Z determined. Multi-year (1979–2007) building energy simulations were carried out for a generic office building. It was found that Z exhibited daily and seasonal variations similar to the simulated cooling load and building energy use. Regression models were developed to correlate the simulated daily cooling load and building energy use with the corresponding daily Z. Error analysis indicated that annual building energy use from the regression models were very close to the simulated values; the difference was less than 2%. Difference in individual daily energy use, however, could be up to 6%. It was also found that both the simulated annual building energy use and the new climatic variable Z appeared to show an increasing trend during the 29-year period, indicating a subtle, but gradual change of climatic conditions that might affect energy use in buildings in future years.