An Ontology-Based Framework for Building Energy Simulation in the Operation Phase

Buildings account for a large proportion of energy consumption, and improving building energy efficiency during the operation phase has attracted increasing research attention to achieve the carbon neutrality goal. Building energy simulation is a powerful tool to predict and manage building energy performance during the operation phase. Decision making can be informed by timely and reliable simulation results. However, building energy simulation requires various data and information including building geometries, thermal properties of constructions, Heating, Ventilation, and Air-conditioning (HVAC) systems, etc. Collecting these data and information from different sources (e.g., Building Information Modeling (BIM), Building Management Systems (BMS)) can be a tedious and time-consuming job, which limits a timely prediction and decision-making. This study proposes an ontology-based framework which can integrate data for building energy simulation from different data sources. Firstly, we collect and integrate four types of data (i.e., weather, building, internal heat gain, and HVAC system) from different sources. Ontology models are designed by integrating existing ontology models Brick Schema and Building Topology Ontology (BOT). An inference rule for thermal zoning is proposed. Secondly, a group of rooms in a campus building are selected as a case study to demonstrate the implementation of the models and the inference rule. The proposed models reduce the efforts needed to collect and integrate data for building energy simulation during the operation phase. Using the proposed model, data needed for building energy simulation can be obtained promptly and accurately, which strongly supports building energy management towards energy efficiency.