2.1.2. Prediction power requirement in multi-level refrigeration cycle: a single heat source and two heat sinks

For ethylene,

8 Refrigeration

For propylene,

heat sink

For ethylene-propylene cascade cycle,

approach and the new refrigeration model

Table 2. Case data – two heat sources and one sink.

and new shortcut model [3].

power demand, as will be illustrated in the following example.

COPact ¼ 0:741COPid � 0:81 ð4Þ

COPact ¼ 0:758COPid � 0:747 ð5Þ

COPact ¼ 0:596COPid � 0:213 ð6Þ

Temperature (�C) Duty (kW)

The potential benefit of the linear model is that it is the fast and easy evaluating refrigeration

This case explores the use of the new refrigeration model for estimating the power demand in two types of multi-level cycle, with propylene as the refrigerant. The model results will be compared with HYSYS simulation results to demonstrate the usefulness of the model for estimating the net power demand in the complex refrigeration cycles. In this work, the Peng-Robinson equation of state will be used to calculate fluid and thermodynamic properties.

2.1.1. Prediction power requirement in multi-level refrigeration cycle: two heat sources and a single

Heat source 1 �40 3000 Heat source 2 �12.75 3000 Heat sink 30 –

Modelling approach Shaft work (kW) %Error

Table 3. Predicted shaft work requirement for multi-level cycle – two heat sources and a single heat sink using HYSYS

Multi-level cycle (HYSYS) 981 + 2203 = 3184 � Two simple cycles (shortcut model) 1937 + 922 = 2859 10 Two simple cycles (HYSYS) 1943 + 977 = 2920 8

The power demand in the multi-level cycle is estimated, for the case data given in Table 2, by representing the multi-level refrigeration cycle as a two parallel simple cycle, as shown in Figure 2(b). It is clear from the results in Table 3 that the refrigeration model is under predicting

2.1. Case study 1: Evaluation of multi-level refrigeration cycles using decomposition

The single heat source and two heat sinks cycle can also be presented as a two parallel simple cycle, as shown in Figure 4(b). Table 4 shows process data for the analyzed case study. The minimum approach temperature is assumed to be 3C.

The results in Table 5 show that the error between the power demand predicted by the proposed refrigeration model and that predicted by rigorous simulation software is about 4%. This error comes from the mixing effects at the inlet into the throttle valve, as shown in Figure 4(a). However, this scale of error should be acceptable for preliminary estimation of refrigeration power consumption.

In summary, the case study shows that although there is some error associated with the decomposition approach, the refrigeration model still can predict the power demand within reasonable accuracy. The predicted power demand is shown to be within 10% of that of more accurate simulation models. The simplicity of the refrigeration model enables its use for

Figure 4. (a) Multi-level refrigeration cycle—a single heat source and two heat sinks; (b) decomposition into simple cycles.


Table 4. Case data – one heat source and two sink.


Table 5. Predicted shaft work requirement for multi-level cycle – two heat sinks and a single heat source using HYSYS and new shortcut model<sup>1</sup> .

optimizing the design conditions of a complex refrigeration cycle and/or the associated processing conditions, as will be seen in Section 3.
