Multivariable regression analysis to assess energy consumption and CO2 emissions in the early stages of offices design in Chile

Abstract

The reduction of energy consumption and CO2 emissions in buildings has become an essential field of study in the recent years. Simplified design tools, used in the first design stages, can be of great help in adopting concrete decisions that will, at the end, allow these to be reduced. This paper presents a new predictive model for office buildings in Chile. Starting from the 1,386,000 study cases pursuant the ISO 13790:2008 standard, 18 multivariable regression models have been generated, 9 for energy consumption and 9 for CO2 emissions., They have been adapted to each climatic zone in Chile. In these case studies, 8 fundamental variables have been considered to cover the design parameters. This research considers number of stories (NS), floor area (FA), form ratio (FR), window-to-wall ratio (WWR), coefficient of performance (COP), Energy efficiency ratio (EER), heating emission factors (HEF) and cooling emission factors (CEF). The models generate an R2 between 91.81% and 98.05% for energy consumption and between 96.83% and 99.56% for CO2 emissions, with the results of this research being incorporated into future regulations and into the first stages of design for office buildings in Chile. As an expected outcome, the model will contribute to reduce, or at least contain, energy consumption and CO2 emissions associated with office buildings in the future.