An ontology-based framework for automatic building energy modeling with thermal zoning

Abstract

Building Energy Modeling (BEM) has wide application in building design and operation stages. Developing BEM requires numerous data from multiple sources, and therefore is time consuming and expertise demanding. Building Information Modeling can provide information needed for BEM, but a seamless transfer of BIM to BEM is not available yet. This study proposes an ontology-based automatic framework aimed at integrating multiple data sources and automatically generating BEM models, in which the ontology model could integrate data from weather, building, internal heat gain, and Heating, Ventilation, and Air Conditioning system. We developed a cross-domain and rule-based reasoning method for thermal zoning, and an automatic ontology model to BEM model translation method using instance-based mapping and dynamic data conversion. We demonstrated our approach by developing a BEM model for one floor of a campus building. The results showed that the proposed framework could automatically generate the model that has the potential to reduce the modeling time by over 99% comparing with manual modeling.