Bridging the environmental and energy performance gap in buildings through simulation, measurement and data analysis

Buildings during operation are dynamic environments where changes to control strategies and space usage regularly occur. As a result of these and other issues a performance gap between design intent and actual building performance emerges. This paper seeks to address the operational performance gap and optimise building performance by identifying inconsistencies in building operation. This is achieved through the combined use of a calibrated simulation model output data and the implementation of a breakout detection algorithm based on measured time-series building data. A number of alternative breakout detection algorithms are reviewed in comparison to the chosen technique in this paper. This paper outlines a statistically robust methodology to identify breakouts for measured time-series building performance data. Time-series data from the sports centre within University College Dublin (UCD) swimming pool hall were analysed. Unintended shifts in swimming pool return humidity levels above an acceptable level of 70% were identified by the breakout detection algorithm. A calibrated simulation model is referred to and the building system or zone set-point is reset to the recommended optimal value. The engineering value of this process is that it can be run in real time, as time-series data is produced, to accurately identify shifts in performance for building managers and reduce the performance gap.