Abstract:

We explore different methods to analyze large and complex datasets related to building integrated photovoltaics (BIPV). Using data from the European RESSOURCES project from the ETNA/B full-scale experimental setups. We show classic data mining methods such as mutual information can be used to better understand the physics behind BIPV systems and highlight discrepancies between different setups. We also use neural networks to model the airflow inside the double-skin facade and quantify its contribution to the buildings cooling and heating.

Dr. Eric Lee received his PhD from the City University of Hong Kong. He is currently an associate professor and the assistant head of architectural engineering in Department of Architecture and Civil Engineering, City University of Hong Kong. His major research areas include building energy analysis and modelling of building systems. He has over 100 articles published in different referred journals and conference proceedings. Dr. Lee is also serving different technical committees of different departments of the Hong Kong SAR Government.