Correlation analysis of building parameters according to ASHRAE Standard 90.1

Abstract

Building energy codes promote efficient energy management in both conventional and eco-friendly buildings. These codes are periodically updated to reduce energy consumption and carbon emissions. However, these updates can induce correlations among building parameters, which could lead to incorrect results when creating or analyzing data sets based on them. This study aims to investigate the impact of correlations in building parameters caused by the trend of updates in building energy codes. The most widely used building energy standard, namely Standard 90.1 of the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), is utilized to understand the trends of energy codes. We confirm that periodic updates to ASHRAE Standard 90.1, representative of numerous energy standards and codes, induce correlations in the input parameters. Moreover, we analyze the problems caused by these correlations through sensitivity analysis and Principal Component Analysis (PCA). Consequently, the sensitivity index of parameters with correlations increases while the importance of parameters without correlations decreases. In the PCA, the number of parameters required to explain more than 95 % of the variance in the raw data changed. This study's findings highlight the need to carefully consider correlations when analyzing building energy code-impacted data and provide insight that enhances the accuracy of the interpreting parameter relation in such data analysis.