1. Introduction

Refrigeration systems are commonly used to provide cooling to sub-ambient processes. The most common refrigeration system in use today is the vapor compression refrigeration cycle [1]. Heat is extracted from a lower temperature heat source and pumped to a higher temperature by means of the work of the compressor. This higher temperature might be to an

external cooling utility (e.g., cooling water), a heat sink within the process or to another refrigeration system [2]. The power demand of the cycle depends strongly on the temperature at which cooling is required, the temperature at which the refrigerant is condensed, as well as the type of refrigerant being used [3].

Generally, a simple refrigeration cycle (i.e., a single-stage compression cycle) cannot be used to provide cooling at very low temperature due to industrial limitation of refrigerant [4] and a complex cycle (e.g., a multi-stage cycle) or cascaded is used as an alternative. Complex refrigeration system that utilizes a multi-stage compressor presents lower energy consumption when compared to the simple cycle [2]. Although complex cycle reduces power consumption, the design and optimization of this cycle are challenging because there are a large number of design alternatives and, consequently, their design fundamental interaction.

Branan [5] presented graphs that help prediction of power requirements for simple and multilevel refrigeration cycles at various temperature ranges using propane, propylene, ethane, or ethylene as the refrigerant. In preliminary design stage and in optimization where evaluation of a large number of cycles may be required, shortcut methods may be preferred because they allow faster evaluation without needing detailed specification of refrigeration design parameters (e.g., refrigerant mass flow rate, cooling duty, and the partition temperature in cascaded cycle). A shortcut method to predict the coefficient of performance (COP) of simple vapor compression cycles for pure refrigerants under the assumption of isentropic compression was proposed by Shelton and Grossman [6]. The shortcut model predicted the COP by using system temperatures and thermodynamic data of refrigerant (i.e., specific heat capacity and molar latent heat of vaporization). This chapter proposes a new refrigeration model to predict the net power demand for various design options (refrigerants and configuration) of the refrigeration cycle. The new proposed model predicts the actual coefficient of performance as function of the ideal performance (i.e., the Carnot cycle). This chapter also addresses refrigeration integration with sub-ambient process streams and provides a systematic methodology required for operational optimization of refrigeration cycles. Inputs to the optimization model include process stream data and initial estimate of operating conditions. The outputs of optimization are evaporation temperatures and cooling duties of each level and shaft work of each stage. The proposed optimization is less complicated than recently published work of Montanez-Morantes et al. [7]. Also, it is very useful for students who do not have strong mathematical background.

This chapter is organized in the following way: first, an introduction that outlines the basic configurations on which the model is based and that illustrates how the complex cycles can be decomposed into an associated simple cycles is presented. Then, the approach that is used to develop new refrigeration models is presented. After that, two examples are introduced to illustrate the effectiveness of the new refrigeration model for predicting the power demand in multi-level refrigeration cycles. Section 3 introduces a systematic methodology for the optimization of operating conditions in multi-level refrigeration cycles. A case study is presented in Section 4 to demonstrate the benefit of the use of the optimization method proposed in this chapter. Finally, the conclusions of the chapter and the recommendations for future work are presented in Section 5.
