Modeling and validation of a CO2 refrigeration unit

Modeling

The CO? refrigeration unit model was developed and validated using data from the test facility at EDF France [1]. The schematic of the refrigeration unit is shown in the figure below.

The key components of this refrigeration unit are outlined in the table below.

In this system's control strategy, the HPV regulates the outlet pressure of the gas cooler, the FGV manages the accumulator pressure, and the EV controls the evaporator's superheat. The system includes three compressors, two of which are variable-speed. The activation, deactivation, and speed of the compressors are adjusted to control the glycol outlet temperature.

CO2 compressor manufacturers provide selection software for calculating CO2 refrigeration unit performance. However, this software does not account for heat transfer in heat exchangers (e.g., evaporators, gas coolers, internal heat exchangers). As a result, users must specify fixed values for evaporating temperature and gas cooler outlet temperature to perform calculations, even though these parameters vary during real-world operation. Moreover, the software cannot simulate transient behavior or assess the impact of different control strategies on system performance. To address these limitations, Modelica is employed to develop a CO2 refrigeration unit model. This physics-based model captures heat transfer dynamics and transient behavior, enabling a more comprehensive analysis of CO2 systems.

For the CO? refrigeration model, the following specific inputs are required:

• Glycol flow rate
• Glycol inlet temperature
• Water flow rate
• Water inlet temperature
• Superheat set-point
• Accumulator set-point
• High side pressure set-point
• Glycol outlet temperature set-point

After incorporating these inputs into the model, it can predict the following outputs:

• Power consumption of compressors
• Heat transfer rate of gas cooler and evaporator
• Pressure, temperature, flow rate at various points in the cycle

The inputs and outputs of the CO2 refrigeration unit are illustrated in the figure below:

2. Validation

To validate the accuracy of the developed model, test data from six cases provided by EDF France were utilized [1]. The test data were categorized into inputs and outputs. The inputs are presented in the table below, while the outputs were compared with simulation results for validation, as shown in Table 3.

Where:

• M_g: glycol flow rate
• T_gi: glycol inlet temperature
• M_w: water flow rate
• T_wi: water inlet temperature
• Sup: superheat degree set-point
• Acc: accumulator pressure set-point
• High: high side pressure set-point
• T_go: glycol outlet temperature set-point

Table 3 presents a comparison between the simulation results and the test data. For the selected test cases, the predicted power consumption deviates by less than 10% from the test data. This deviation is partly due to the lack of detailed information on the compressor control strategies in the test report, requiring the use of assumptions in this study. Incorporating the actual control strategies would likely improve the accuracy. Furthermore, the predictions for evaporator capacity and gas cooler outlet temperature show deviations of less than 5%.

3. Further applications of the developed model

The developed model serves as a baseline, providing a foundation for further modifications. These enhancements can include:

Implementation of various control strategies:

• Optimizing the high side pressure set point based on the gas cooler water inlet temperature and other operational parameters.
• Developing strategies for compressor activation and deactivation, as well as adjusting compressor speed ranges.

Adaptation to other configurations:

• Incorporating features such as ejectors, parallel compressors, or multiple evaporating levels.

Reference

[1] A. Paez, B. Ballot-Miguet, B. Michel, P. Tobaly, and R. Revellin, “Experimental investigation of a new CO2 refrigeration system arrangement for supermarket applications,” International Journal of Refrigeration, vol. 162, pp. 245–256, Mar. 2024, doi: 10.1016/j.ijrefrig.2024.03.010.