4.1. Prediction power requirement in multi-level refrigeration cycle

For the cascaded cycle, the low temperature cycle and the high temperature cycle are treated as individual complex refrigeration cycles. The power demand in the three-level ethylene cycle is estimated by representing the three-level refrigeration cycle as a three parallel simple cycle. The power demand in the high temperature cycle is estimated by representing the two-level refrigeration cycle as a two parallel simple cycle. The refrigerant data in Table 7 are used in the refrigeration model to predict the power demand at each compression stage.

A Simple Approach to Calculate/Minimize the Refrigeration Power Requirements http://dx.doi.org/10.5772/intechopen.69130 13


Table 6. Process stream data for case study 2 [10].

Where W is the net power demand of the refrigeration cycle, Qevap<sup>i</sup> is the cooling duty of ith cooling level, COP<sup>i</sup> is the coefficient of performance which is calculated from the developed shortcut model presented in Section 3, T is the shifted temperature, ΔTmin is the minimum approach temperature, Tevap<sup>i</sup> is the evaporation temperature of ith cooling level, Tcond is the condensing temperature at which the refrigerant being condensed, I is the number of cooling

The main features of this calculation procedure are: (1) using GCC to determine the temperature level and the duty of each stage; (2) the shaft work required of each stage calculated directly without going through the detailed refrigeration calculations or rigorous simulation; and (3) the constrained optimization problem can be solved easily using a simple optimization algorithm, such that available in MATLAB and Excel (i.e., Excel's Solver). The limitations of this approach can be summarized as follows: (1) the advantage of using economizer in minimizing shaft work consumption cannot be explored because the effect of its use cannot be represented in GCC [7], (2) only pure refrigerants are considered, and (3) heat is rejected to external utility rather than process heat sink streams, so the opportunities of the matching refrigeration system with process sink streams—which can provide significant energy savings —are missing. The implementation of the proposed optimization approach for minimizing the overall shaft work requirement of a complex refrigeration cycle is illustrated in Section 4.

This case aims to illustrate how the new refrigeration model can be used to estimate the power demand in a multi-level cascade cycle. A second aim is to illustrate the performance of the

The complex refrigeration cycle in the ethylene-propylene cascade refrigeration cycle from the cold-end process of an ethylene plant is selected for analysis. Case study data are given in Table 6. Figure 6(a) shows the process flow diagram of the ethylene-propylene cascaded refrigeration cycle. Figure 6(b) shows the refrigeration cycle matched against the grand composite curve of the stream data presented in Table 6. Table 7 gives the corresponding cascaded refrigeration cycle details, including two propylene cooling levels in the upper cycle and three

For the cascaded cycle, the low temperature cycle and the high temperature cycle are treated as individual complex refrigeration cycles. The power demand in the three-level ethylene cycle is estimated by representing the three-level refrigeration cycle as a three parallel simple cycle. The power demand in the high temperature cycle is estimated by representing the two-level refrigeration cycle as a two parallel simple cycle. The refrigerant data in Table 7 are used in the

levels, and lb and ub represent the lower and upper bounds, respectively.

12 Refrigeration

4. Case study 2: cold-end process of an ethylene plant

proposed optimization model in minimizing the net power demand.

4.1. Prediction power requirement in multi-level refrigeration cycle

refrigeration model to predict the power demand at each compression stage.

ethylene cooling levels in the lower cycle.

Figure 6. Balanced grand composite curve for case study 1 (a) and its refrigeration cycle (b).


Table 7. Refrigerant data for ethylene-propylene cascade refrigeration cycle.

For the purpose of comparison, the refrigeration cycle was also simulated in HYSYS software. The fluid package chosen in the simulator for determining thermodynamic properties was the Peng-Robinson equation of state. In this case, it is assumed that the compression efficiency is 80% and all the absorbed heat is rejected to cooling water at 23C. Also, for the heat exchangers, a 5C minimum temperature approach is specified, while it is assumed that there is no pressure drop in both heat exchangers and piping [10]. The partition temperature, which is the temperature of the evaporator of the upper cycle, was set at �44�C.

Table 8 presents the results of the predicted power demand for complex cycle using HYSYS and the new refrigeration model. The error between the refrigeration model and HYSYS predictions for net power demand prediction is about 10% in the lower cycle and �2% in the upper cycle. As can be seen from the HYSYS simulation results for the three parallel cycles, this error arises mainly from the mixing effect at the inlet to the compressor.
