A PARAMETRIC ENERGY EVALUATION OF PUBLIC HOUSING DESIGN IN SINGAPORE

Abstract

Over 80% of the population in Singapore lives in public housing. Of the total energy consumption in Singapore, the residential sector contributes to 20% with air-conditioning and lighting as two major components. The generation of energy would imply additional C02 production leading to global warming, given the increasing population growth in Singapore and the world. This dissertation seeks to understand various design factors or parameters of housing and their associated energy demand within the building and urban scale, through the use of Sustainable Urban Neighborhoods Tool (SUNTOOL) software, during the initial schematic design phase. The software allows architects to evaluate their designs without the tedious resolution of the building details. In summary, this dissertation comprises of 2 major stages: 1. [Building stage] Different typologies of housing block types are derived by varying the building depth and the orientation of the building, whilst keeping the floor plan area and Gross floor area (GFA) consistent. They are then evaluated for energy demand. 2. [Urban stage] Various Urban layouts of varying the block heights and block separations, whilst keeping the density or Floor Area Ratio (FAR) and number of housing blocks consistent. The most energy efficient building types for each different orientation are selected from the previous stage and placed in 3 distinct urban precinct layouts to be evaluated for energy demand Case studies of 5 selected housing blocks design from 5 consecutive decades of Singapore's public housing respectively are evaluated. Optimizations from the urban simulation studies are also applied to 2 different housing precincts in Boonlay and Punggol. From the numerous simulation cases, it is discovered that the surface to volume ratio of 1:4 would yield optimum energy demand for all generic block types tested. And among the urban simulated cases, the staggered precinct layout is the best performing arrangement. Although from the studies, higher density implies higher energy demand, nonetheless the existing housing design can be improved by efficient placement housing blocks in future estates.