Energy consumption in higher education buildings: bridging the performance gap using digital twin technology - Peinturier, L; Wallom, D (European Council for an Energy-Efficient Economy, 2024)
Limiting global warming to 1.5°C necessitates a significant reduction in energy demand and increase in energy efficiency, particularly in the building sector, responsible for 26 % of global energy-related emissions and 25 % of UK emissions in 2022. Among UK buildings, higher education institutions (HEIs) rank second in energy intensity, due to their diverse array of activities, spaces, and age. To reduce this elevated energy demand, new methodologies are required to analyse HEIs energy use and uncover potential performance gaps. Well understood digital twin energy simulations are valuable for this purpose, to identify the causes of these gaps and allowing interventions to be tested virtually before modifying buildings’ controls or equipment. The Andrew Wiles Building (AWB), home to the Mathematical Institute at the University of Oxford, serves as a case study to demonstrate the effectiveness of digital twin energy simulations in closing performance gaps during the operational phase of a recently constructed building. Several control and equipment failures have caused the AWB’s energy consumption to exceed expectations. A digital twin has been built using DesignBuilder with two different configurations. The first is derived from construction documentation and originally intended operations. The second configuration is calibrated to reflect the AWB’s metered consumption and operational methodologies. Differences in simulated energy consumption between the first and second configurations are used to understand the building’s performance gaps Proposed interventions result in a 22 % reduction in electricity usage for the year 2022, aligning the AWB’s energy performance with best practice standards according to the 2021 CIBSE TM46 benchmarks. This study highlights the value of accurate digital twin energy simulations to allow building operators to gain understanding of intervention impacts prior to implementation.