Unlocking potentials of building energy systems' operational efficiency: Application of digital twin design for HVAC systems

Abstract

Building energy systems are complex because of their nonlinear behaviour and stochastic environmental interactions. Thus, their efficiency depends on both component design and control strategy. Aiming for high efficiencies over the whole lifecycle, we apply Product Lifecycle Management and Digital Twin Design to HVAC systems, initially using an energy recovery ventilation (ERV) simulation model. We develop a Digital Twin Prototype in Modelica of the ERV unit to predict physical system behaviour. Verifying functionality and suitability, we set up a Digital Twin Instance (DTI) by calibrating the model against measurement data of the physical twin. DTI and physical twin communicate via MQTT interfaces with each other. The approach enables DTIs to calculate predictions for different scenarios per instance, which increases systems' efficiency significantly. In conclusion, this framework allows an application of innovative and predictive control and maintenance strategies to HVAC systems.