Supermarket refrigeration systems
Developments applied to at least four CO2 supermarket refrigeration systems with heat recovery.
CO2 refrigeration systems
Currently, four demonstration cases are planned. All four cases are CO2 supermarket refrigeration systems involving different features, e.g. heat recovery. The refrigeration systems are installed in Danish supermarkets such as SuperBrugsen and Fakta.
Figure 1: Simplified flow sheet of a CO2 supermarket refrigeration system with heat recovery.
The supermarket refrigeration systems consist of various subsystems such as a compressor rack, display cabinets, an outdoor unit, and potentially a heat recovery unit. For the different subsystems, the amount of knowledge about the system varies. This accounts for both the information about the specific construction as well as data associated with the operation of the units. Thus, this aspect requires different modelling approaches to exploit the resources most optimally while providing the required services.
Figure 2: Display cabinets (left) and compressor rack (right) from the Fakta store located in Otterup, Denmark.
Digital twin-based services
The supermarket refrigeration systems are crucial for the supermarkets, although there is a limited focus and understanding from the supermarket owner associated with the refrigeration systems. Therefore, many supermarkets are collaborating with service providers such as AK-Centralen, who specializes in monitoring and optimizing refrigeration systems during operation.
Until now, the monitoring, the set-point tuning, and the alarm handling are to a wide extent based on manual inputs. The idea is to develop methods, which are able to support and improve the respective services.
The advanced system monitoring may predict performances, support functionality, and performance tests of newly installed systems as well as provide performance benchmarking and constitute soft sensors.
Furthermore, digital twins may be used to continuously optimize the set-points in order to reach the highest energy performances. In a subsequent step, the systems may be optimized with respect to flexible electricity tariffs and include scheduling of downtime.
In addition, the advanced models will provide the possibility to detect and diagnose fault mechanisms before or at an early stage of their occurrence. This will enable predictive measures as well as a reduction of downtime.