(445a) Multi-Objective Optimization of the Dual Independent Expander Gas-Phase Refrigeration Process for Lng

Many chemical processes require refrigeration over a broad range of low-temperatures. One of the most common processes is the liquefaction of natural gas (LNG). In this process, natural gas is converted into liquid by cooling it from ambient to a temperature of approximately -160 °C. The refrigeration and liquefaction sections of an LNG plant are very important as they account for almost 35% of the capital investment of the overall plant. There are many commercial processes available for the liquefaction of natural gas, for example, single mixed refrigeration (SMR), and cascade refrigeration. In the SMR process, a mixture of hydrocarbons is used as the refrigerant rather than a pure refrigerant. The composition of the refrigerant is selected in such a way that the refrigerant evaporates over a temperature range to match the process being cooled. On the other hand, in the cascade refrigeration system, natural gas is cooled down using a cascade of refrigeration cycles. Each cycle uses a different pure refrigerant. However, the mixed refrigerant systems require careful selection of refrigerant compositions; whereas, the cascade systems are expensive to build and maintain.

Alternatively, gas phase refrigeration systems can provide cooling down to cryogenic temperatures. Such systems rely on rotary expansion devices like turbo-expanders to cool the refrigerant gas through near-isentropic expansion. Shaftwork is supplied in the compressors and, simultaneously, recovered from the expanders. The operating costs of the refrigeration systems are dominated by the shaftwork supplied to the compressors.

Foglietta (2004) proposed a dual independent expander refrigeration system to liquefy natural gas using the feed gas to provide cooling to an intermediate temperature level, and then nitrogen refrigerant to subcool the liquefied gas. Shah and Hoadley (2007) studied a multistage gas phase refrigeration process based on the method proposed by Foglietta. A shaftwork targeting method was developed for these multistage refrigeration systems. It was found that the expansion/compression pressure ratio and the heat exchanger ΔT_min were the key parameters affecting energy efficiency as well as the capital cost.

In this work, a multi-objective optimization study has been carried out to optimize the gas phase refrigeration process by varying the parameters such as the ΔT_min and pressure ratio. A 1000 kmol/h natural gas stream at 5.5 MPa and ambient temperature consisting of 96.929 mol% methane, 2.938 mol% ethane, 0.059 mol% propane, 0.01 mol% n-butane and 0.064 mol% nitrogen is liquefied using natural gas as a refrigerant, and subcooled using N2 as a refrigerant. The two objective functions optimized simultaneously are the capital cost and the energy efficiency.

A Multi-Platform, Multi-Language Environment was used as an interface to optimize the process simulated in HYSYS (Bhutani et al., 2007), and a Non-dominated Sorting Genetic Algorithm (NSGA-II, Deb et al., 2002) was used to generate the Pareto optimal front. Firstly, the user supplies the values of the genetic algorithm parameters like mutation and crossover probabilities, number of generations, and population size to the Visual Basic interface, which are then passed to the NSGA-II code. A set of decision variables is generated and passed back to the HYSYS simulation through the VB interface. The given objectives are evaluated in the HYSYS spreadsheet and sent back to NSGA-II. After a series of operations like selection, crossover and mutation, a new set of decision variables is generated and supplied back to the VB interface. The procedure continues until it reaches the maximum number of generations, or until the specified convergence criterion is met.

An interesting aspect of the optimisation is the use of a superstructure flowsheet for the process simulation in order to allow for different number of refrigeration stages (from 2 to 8 stages). In this work, natural gas has been used as a refrigerant to liquefy the process natural gas stream. The number of natural gas stages (n_NG) is limited to four. Nitrogen has been used for the subcooling of the liquefied natural gas stream. The number of nitrogen stages (n_N2) is also limited to four. Therefore, the maximum number of stages can only be eight. Sixteen flowsheets have been created in HYSYS by considering all the possible combinations of n_NG and n_N2. During the optimization, the number of stages (natural gas and nitrogen refrigeration stages) is calculated based on the value of pressure ratio and the final refrigeration temperature, T_n, selected. Depending upon the values of n_NG and n_N2, a HYSYS flowsheet is selected and the objectives are then evaluated.

In the present multi-objective optimization study, an extended range of process parameters such as heat exchanger ΔT_min, pressure ratio in the natural gas as well as the nitrogen refrigeration loop, and the number of refrigeration stages have been tested. The results show that three natural gas stages are favored over one or two stages, because one or two stages often involve internal pinching in heat exchangers, resulting in very high heat transfer area. In the case of nitrogen refrigeration, one or two refrigeration stages are favored.

The combination of a flowsheet simulator and the NSGA-II optimizer is a very flexible and powerful tool, which could be applied to many other chemical engineering problems.

References

Bhutani, N., Tarafder, Rangaiah, G. P. and Ray, A. K. (2007), A Multi-Platform, Multi-Language Environment for Process Modeling, Simulation and Optimization, International Journal of Computer Applications in Technology, In press.

Deb, K., Pratap, A., Agarwal, A. and Meyarivan, T. (2002), A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6 (2), pp. 182-197.

Foglietta, J. H. (2004), Consider Dual Independent Expander Refrigeration for LNG Production, Hydrocarbon Processing, 83, pp. 39.

Shah, N. M. and Hoadley, A. F. A. (2007), A Targeting Methodology for Multistage Gas-Phase Auto Refrigeration Processes, Ind. Eng. Chem. Res. In Press