In the built environment, both daylight performance and human behaviour are highly dynamic aspects. Therefore, they require a dynamic optimization approach to provide humans with the right amount of lighting at the right time of day. Building Information Management (BIM) and Digital Twin (DT) technology can optimize - with the help of Smart lighting systems - lighting used to support human health and well-being as well as the building’s energy performance. Where lighting simulation aims to represent a (static) reality DT technology can provide a dynamic two-way feedback between the physical and virtual environment to optimize the lighting environment using real-time and virtual sensor data. A fully detailed BIM model has the advantage of realism and as-built information but the disadvantage of heaviness and complexity that can slow down the data exchange. On the other hand, a simplified BIM model will be easier to manage and serve the simulation purpose but may oversimplify reality. However, light simulation validations have been done multiple times, but not many studies are performed using DT-driven light evaluation in which not only the realistic representation but also the exchange of information plays a crucial role. Therefore, this study investigated data exchange between a physical and real environment and focused on a scenario in which optimal interaction between daylight and electric light derives an optimized realization of a given light demand curve. Investigation and validation of a DT model was done using a virtual room simulated in the light simulation tool DIALux evo and its physical twin: an existing room equipped with light sensors. Data exchange was optimized for three levels of geometrical complexity (fine, medium, and coarse). The paper will present and discuss results regarding the influence of model complexity and consequences for the speed of information exchange as well as a first strategy for optimized daylight/electric light performance due to interaction between the DT components.