Data-driven Performance Evaluation of Ventilated Photovoltaic Double-skin Facades in the Built Environment

In this paper we present a collaborative data science project bringing together experts from the fields of physical and information sciences to tackle to challenges and opportunities of analysing large and rich datasets obtained from the monitoring of building integrated PV systems operating in the built environment. We present data mining analysis techniques to classify data according to environmental conditions and system performance, to distinguish between nominal and anomalous behaviour, and to identify instrumentation faults. These methods were implemented using data from the RESSOURCES project to construct evaluate the performance of a PV envelope, and to validate a simplified physical model to predict thermal and aerodynamic behaviour.