Development of a building information modelling based decision-making framework for green retrofitting of existing buildings

Abstract

In recent years, sustainable development has received more attention in the construction industry along with lowering carbon emissions. As a result, green retrofitting of existing buildings has gained significant attention, which is effective in improving energy optimization and reducing environmental impact. Though there are many advantages and opportunities for implementing green retrofitting in existing buildings, the adoption of these practices remains relatively limited. Building Information Modelling (BIM) has become a game-changing technology in the construction industry and has been widely used for sustainability analysis of buildings and also used for retrofitting of existing buildings. However, the application of BIM for green retrofitting of existing buildings is unexplored. Hence, this paper aims to develop a framework for integrating BIM with green retrofitting to obtain suitable green retrofitting measures for existing buildings. The developed framework integrates sustainable goals with retrofitting strategies and facilitates decision-making on various green retrofitting measures. The developed framework is validated through a case study of an existing building and uses decision-making tools such as a pairwise-comparison matrix and priority matrix for the identification and selection of the best green retrofitting measures. On the application of the developed framework in a case study, 13 green retrofit measures were identified and three suitable retrofit measures were selected. This enabled the reduction of building energy requirements by 37 % and improved water saving by 7.2 %. This framework helps stakeholders, to visualize, analyze, and optimize various retrofit scenarios and make well-informed decisions on suitable retrofitting approaches. The framework can be implemented in any type of existing building and enables the identification of best retrofitting measures.