Assessing the utility of live data streams across existing and planned university buildings - Markiewicz, William; Wilczynski, Vince; Dorsey, Julie; Wilson, Duncan; Elwell, Clifford (Frontiers in Energy Efficiency, 2025)
This study provides a theoretical and practical assessment of the potential benefits of live data streams, as used in digital twins, relating to a building’s running cost and carbon emissions. This is a significant issue, as there is a rise in the demand of digital twins and smart buildings in industry, and the energy savings that could be achieved should be assessed, as it relates to building automation and function. The study considers theoretical assessments based on existing standards and practical assessments on university buildings in London, United Kingdom and New Haven, Connecticut, United States, and is particularly focused on how data-driven controls can improve the energy efficiency of the buildings considered. Using data from the building’s building management systems and energy monitoring software, operational building data analysis was carried out on buildings in London and New Haven. Informed by the studies of both buildings, an assessment against ISO 52120-1:2021 was carried out for the existing building in New Haven, and a planned new university complex in New Haven. The comparative study between the London and New Haven building found that 29% of noteworthy cases identified for the London building were also observed in New Haven. The most significant energy saving opportunities, such as signs of overcooling and not adhering to scheduled shutdowns, were found to be present in both buildings. From a baseline state of low building automation, three states of increasing Building Automation and Control capability were defined as “must have”, “should have”, and “could have”. The mean expected energy savings for these were 5%, 7%, and 9% respectively. The implications of this study are that energy savings can be achieved in existing and planned education buildings, and that opportunities can be identified using enhanced building automation described in ISO 52120-1:2021. It also highlights the challenges with using ISO 52120 to fully quantify the energy savings due to enhanced automation and live data streams, especially for buildings with laboratory areas, which are not covered by ISO 52120, and which typically make up a much higher proportion of a building’s energy footprint than office areas.