Development of a knowledge-based decision support system for optimising passive design strategy selection in buildings

Realisation of net-zero energy targets is correlated with optimising building-related activities, owing to their contributions to global energy consumption and greenhouse gas emissions. The enormous amounts of energy drawn by active systems such as HVACs for cooling and heating have gradually shifted the research paradigm towards exploring passive design strategies in recent years. However, selecting the most sustainable passive energy consumption optimisation strategy for buildings involves considering several criteria, including technical, economic, and social ones, making it complex and challenging for practitioners. The complexity of the process is further compounded by the lack of standardised methodologies for identifying relevant criteria and alternatives, as well as limited comprehension of passive strategies by decision-makers during building design and refurbishment. In this study, rapid evidence assessment (REA) was initially used to systematically collate relevant criteria for passive designs in buildings, followed by the development of a knowledge-based decision support tool (KB-DST) that enables automatic assessment in real-time, based on a novel MADM algorithm that hybridises evaluation based on distance from average solution (EDAS) and criteria importance through inter-criteria correlation (CRITIC) methods. This tool has the potential to significantly alleviate the difficulty of selecting passive strategies for practitioners.