A 'big data' approach to the application of building performance simulation to improve the operational performance of large estates

This paper derives from the ‘Hit2Gap’ project, funded under the European Union’s Horizon 2020 R&D programme (Hit2Gap 2015). The aim of the project is to reduce the gap between design intent and the operational performance of large building estates. To this end, a data exchange platform is being prototyped and tested, able to collect and store data from disparate sources and deliver subsets of these data to a range of applications (services) and end users. The ultimate aim is to identify physical interventions that could alleviate operational problems and so reduce the performance gap. This paper deals with the application of building performance simulation (BPS) within the context of data exchange platform and specifically, the delivery of an input model, its automated calibration and use in areas such as HVAC system fault detection and diagnosis, upgrade options appraisal, indoor environment quality improvement, demand reduction, renewable energy systems integration, control system refinement, and regulatory compliance. The paper summarises the Hit2Gap architecture, the procedure for the automatic calibration of BPS models and automated performance assessments.