Adaptable and Scalable Energy Modeling of Ventilation Systems as Part of Building Digital Twins

Digital twins solutions have great potential within a multitude of building applications, but flexible and scalable model backbones are essential for cost-effective large scale distribution within the building sector. In this paper, a flexible component based framework for ventilation system modeling is proposed as part of a scalable digital twin solution. The framework is applied to a case study with limited data availability and the simulated values are compared to measurements. Results show a strong similarity between predictions and data, but it is clear that inaccurate occupancy measurements can cause significant discrepancies. The developed model is used for performance comparison between different ventilation control strategies and a proportional controller is found to slightly outperform the buildings current rule-based controller.