DanRETwin: A Digital Twin Solution for Optimal Energy Retrofit Decision-Making and Decarbonization of the Danish Building Stock

The current trend in renovating existing buildings is to perform retrofits on a case-by-case basis without a systematic assessment, using static tools with broad assumptions and generic inputs. As a result, only about 1% of the building stock undergoes energy renovations each year. To address this issue, new approaches and modern tools are necessary to enhance and expedite energy retrofits in Danish buildings. While there were a few initiatives and projects exploring the implementation of digital twins in building applications, the focus is primarily on newly constructed, highly energy-efficient buildings with integrated building information models (BIM). Conversely, existing and older buildings often lack any form of digital modeling, making it challenging to implement digital twins in those contexts. This paper presents an innovative digital twin solution, ‘DanRETwin’, which will provide decision-making support, retro-commissioning, and data-driven performance optimization for non-residential existing buildings. The proposed solution will utilize building operational data, employing machine learning and artificial intelligence techniques to develop scalable data-driven models of building energy. Additionally, clamp-on IoT sensors will be used for data collection, enabling a fully automated and flexible solution. By utilizing DanRETwin, building owners will enjoy higher energy efficiency and improved comfort in their retrofitted buildings; facility managers will have an advanced monitoring solution that enables systematic retro-commissioning of their newly retrofitted buildings, eliminating faults and reducing losses; consultants will have a potential solution to retrofit, enhance, and optimize their clients’ building performance, allowing them to make informed, data-driven decisions and interventions; and city planners will have an effective, scalable, and adaptable tool to expand retrofit efforts and evaluate various scenarios.