4.7 Room Temperature Sensors in the Digital Twin

In this bachelor thesis the influence of the position of a temperature sensor on the heating control was investigated. This is important in order to optimize energy consumption and comfort in indoor rooms. To address this question, newly implemented functionality in the simulation tool IDA ICE from EQUA AB was used.

Student: Category: Mentoring: Handed in: Sara Willi Bachelor’s thesis A. Witzig, S. Weber 2020

Temperature sensors in heating systems often measure a combination of air temperature and radiation. In digital planning, the control of thermal comfort in buildings is therefore a demanding task. In this work, indoor climate is investigated by means of detailed physical simulation. The temperature measured by sensors and information relevant for the control are brought together. Furthermore, the findings are to be incorporated into building planning and operation. For this purpose it may be useful to create a digital twin of the building. This digital twin, which is a numerical representation of a real object, contains models with which physical processes can be represented. For example, the temperature distribution in a room due to a ventilation system can be graphically displayed and the control technology can be improved. The theoretical basics of this topic were already established over 20 years ago. It was shown that the position of the temperature sensor can have a significant influence on the energy consumption. [1], [2]. In planning and especially in digital design, however, these correlations are still rarely used today. Simplified models often assume a homogeneously mixed air temperature, which is not suitable to optimize the positioning of temperature sensors. The aim of this work is to process the knowledge in a form useful for the construction industry and to use the processes and tools that are available to a broad user group today. For this purpose, several newly implemented software features of IDA ICE have been used to assess their suitability for mapping thermal comfort and energy consumption in the digital twin.

Figure. Temperature distribution in a hotel room with ventilation. Above: Grid, below: Temperature distribution in vertical cross-section. IDA ICE offers both a 3D solution with finite volumes (using OpenFoam) and a numerically efficient layer model with embedded air flows and plumes [3].

Literature:

[1] B. Magnum und J. Hill, «Thermal Analysis, Human Comfort, Indoor Environments», National Bureau of Standards (U.S.), Washington, D. C., 1977.

[2] P. Riederer, D. Marchio, J. Visier, A. Husaunndee und R. Lahrech, «Room thermal modelling adapted to the test of HVAC control systems,» Elsevier, Building and Environment, ISSN: 0360-1323, 2002

[3] L. Eriksson, G. Grozmann, P. Grozmann, P. Sahlin, M. Vorre and L. Årenius, «CFD-free, Efficient, Micro Indoor Climate Prediction in Buildings, IBPSA Proceedings, UK, 2012