Digital twin (DT) is an innovative concept within the construction sector that utilizes real-world performance data to create a virtual model, enabling optimized decision-making. Building net zero carbon (NZC) retrofitting offers an opportunity to reduce global carbon emissions. However, decision-makers face challenges in making smart and sustainable decisions in NZC retrofitting. DT can improve the smartness and sustainability of the decision-making practice in NZC retrofitting, providing promising solutions. Hence, this study assesses the potential of DT for smart and sustainable decision-making in NZC retrofitting.
This study used a three-stage methodology, which included initial work, systematic review and analysis and discussion. Accordingly, the study investigated 29 relevant academic publications on DT and building retrofitting to NZC, using content analysis as the major analytical approach.
The findings demonstrated the effective application of DT in assessing carbon emissions, energy usage, comfort levels and financial savings within the context of building NZC retrofitting. However, it highlighted a lack of integrated focus on the environmental, social and economic pillars of sustainability in NZC retrofitting. Furthermore, the review identified the technologies utilized in implementing DT for building NZC retrofitting as data-related, modeling-related and model simulation-related technologies. Centered on the identified gaps, the study provides recommendations for building NZC retrofitting.
The identified gaps and proposed directions would guide future researchers interested in implementing DT to make sustainable decisions in building NZC retrofitting.
