Key predictors of annual electricity use in high-rise residential apartments in Dhaka, Bangladesh

Abstract

This paper describes a study that examines the influence of building design and household characteristics on the annual electricity use of apartments in high-rise residential buildings of Dhaka, Bangla-desh. To do this, 342 apartments in different high-rise residential buildings were studied. Their electricity use records were collected and the apartments were also surveyed to collect data of building de-sign characteristics. Data on the building design characteristics in-clude floor level, floor areas of the apartments, effective canyon ratio, window area, shading depth, window-to-wall area ratio (WWR) and window-to-floor area ratio (WFR) and shape coefficient of the apart-ments. Household characteristics include household size and number of air conditioners (ACs). The analysis methods used in this study in-clude descriptive statistics, correlations and linear regression analysis with SPSS. The results show that among the different variables stud-ied, of the design characteristics, total window area and total WFR per apartment are the key predictors of annual electricity if the effect of the influence of household characteristics such as household size and number of ACs are excluded. If household characteristics are included in the linear regression models, effective canyon ratio, household size and number of ACs are the predictors of annual electricity use in addi-tion to total window area and total WFR per apartment.