MODELING AND OPTIMIZATION OF A C3MR LNG PLANT EFFICIENCY BY

CHANGE OF MIXED REFRIGERANTS’ COMPONENTS

Hamid Saffari*, Masoud Fasihbeiki°

*°LNG Research Laboratory, School of Mechanical engineering, Iran University of Science and Technology,

Narmak, 16846, Tehran, Iran

*saffari@iust.ac.ir

ABSTRACT

In this paper, we have optimized the energy efficiency of an industrial C3MR LNG base load plant by changing its

refrigerants’ components and their mole fractions in liquefaction and subcooling cycles.

The process is modeled by using the Hysys® software. The PRSV equation of state is used for thermodynamic properties

calculations both for the natural gas and the refrigerants. Two methods for modeling and optimization are explained and the

results are compared. The first optimization method is done by a try and error method, which is based on the use of

temperature vs. enthalpy diagrams or composite curves. In the second method, Hysys® optimizer is used for optimization.

The results show that by optimization of mixed refrigerants, it is possible to decrease the energy demand about 10.4 MW

(5.36 %.)

Key words: Liquefied Natural Gas; C3MR Process; Efficiency; Hysys® software; Cooling Curve

1. INTRODUTION

Natural gas is set to become one of the most important

primary energy sources for the 21st century. Compared with

other fossil fuels, gas is relatively clean with regards to air

pollution and greenhouse gas emissions and has larger

proven reserves. It is expected that the natural gas would

account for about 30% of total electricity generation by 2020

compared with 17% in 2000 [1].

In this paper, we would like to optimize a propane

precooled mixed refrigerant process refrigerants where

precooling is achieved by a multi-stage propane cycle while

liquefaction and subcooling are accomplished by a two-stage

mixed-refrigerant cycles, which is so far the most common

process used since 1972 in 8 different countries. The propane

pre-cooled mixed refrigerant LNG process (C3MR) has been

applied in LNG plants producing from 1 to 5 Mtpa of LNG

per train using steam, gas turbine or electrical drivers, sea

water and air cooling, rich and lean feeds containing a broad

range of nitrogen with and without LPG extraction. The

process has proven to be efficient, flexible, reliable, and cost-

competitive [2]. Propane precooling mixed component

refrigerant process (C3-MR) represents 80 % of that used in

the current base load plants. Large-scale liquefaction of

natural gas takes a large amount of energy. That is why

optimization is necessary to the process at steady state

operation. Because of low efficiency of conversion of fossil

fuels to electricity and consumption of approximately

200MW in electrically driven compressors and main pump of

each train, optimization is advantageous in this case.

There are some differences between the proposed cycle

and a mixed fluid cascade cycle. In a MFC process, A

Mixture of ethylene, ethane, propane and butane is used for

precooling, while almost a pure propane refrigerant is

utilized for precooling in the cycle studies. In addition,

expander will not be used in a C3MR Process and throttling

achieves by throttling valve and precooling is achieved in

three or four stages, while in a MFCP, expander usually is

used for throttling and precooling happens in two stages.

A Mixture of Ethylene, ethane, methane is used for

liquefaction and subcooling in MFCP, while ethylene will

not be used in C3MR Process.

The design, simulation and estimation of natural gas

liquefaction process began from 1970. Shell Corporation has

simulated the cascade, mixed-refrigerant and N2 expander

cycle and analyzed their advantages and disadvantages [3].

Melaaen set up a dynamic model for the natural gas

liquefaction process of base load plant, and carried through

the simulation by DASSL in 1995 [3]. Kikkawa designed the

late model of pre-cooling mixed-refrigerant processes and

expander cycle, and he used CHEMCAD software in his

calculations in 1997 [4]. Terry adopted Hysys® software to

calculate and optimize the typical liquefaction process of

peak shaving plant in 1998 [5]. Gu and his associates have

carried through the simulation and calculation of natural gas

liquefaction process [3]. They also compared the key

parameters of two small-scale natural gas liquefaction

processes using Hysys® software in 2006 [6].

For simulation of a LNG Production process, a reliable

equation of state (EoS) is needed for thermodynamic data

predictions. Several review articles and books cover the

equations of state published in the literature. Most of them

concentrated on cubic EoS's and their mixing rules [7].

Simulation of the process has been conducted using

Hysys® simulator version 3.2 due to many fluid properties

data, Binary coefficients and suitable equations of state. In an

industrial system in which there are many exchangers

requiring refrigerants at many temperature levels, the

simulation of such a system is much simplified if the PFD

contains only real equipment.

The elimination of controllers makes the try and error

method simulation much easier than that of using numerical

convergence standpoint (using Hysys® optimizer). The PFD

consists of only real equipment other than a cluster of non-

equipment items such as controllers and calculators [8].

Large temperature difference and heat exchange load are the

primary reasons of exergy loss in heat exchangers. In this

method, by comparing the consumed work of cycle of each

mole fraction with previous composition, the preferred

composition will be cleared and by comparing the changes in

composite curves formed in main heat exchangers, in each

iteration, the mole fraction of next step will be predicted.

Easily made modeling, rapid countering and close answers to

optimal operation (which will be obtained by Hysys®

optimizer) are the advantages of this method.

2. PROCESS DESCRIPTION:

The process which will be model and optimize is an

industrial process. But, because of some industrial limitation,

the detailed description of simplified process has been

presented in figure 1.

Propane is evaporated at four pressure levels in precooling

cycle (LNG-100, LNG-101, LNG-102 and LNG-103) to

desuperheat the natural gas feed (stream 1) and cool and to

partially condense the main refrigerants mixture (streams 28

and 36 for liquefaction and subcooling respectively) before

they enter to main heat exchangers(LNG-104 and LNG-105).

The heated refrigerant then passes through the separators (V-

100, V-101 and V-102). The remained liquid is used for next

stage of precooling after it passed the valve. The vapor

collects at each pressure levels and enters four compressors

(K-100, K-101, K-102 and K-103).

In liquefaction cycle, mixed refrigerant first enters four

propane precooling heat exchangers identified before. After

cooling to about -30.4ºC at the last heat exchanger (LNG-

103), it passes through the liquefaction main heat exchanger

(LNG-104) and liquefies. After dropping its pressure and

temperature in a throttling valve (VLV-100), the refrigerant

comes back to the heat exchanger and gets heat from hot

composite (natural gas, Subcooling refrigerant and inlet

liquefaction refrigerant). Then it comes back to the

compressor (K-104).

In subcooling cycle, its mixed refrigerant like liquefaction

mixed refrigerant passes propane precooling heat exchangers

(LNG-100, LNG-101, LNG-102 and LNG-103) and

liquefaction main heat exchanger (LNG-104). Then passes

through main subcooling heat exchanger (LNG-105) and is

depressurized in VLV-101 and comes back through the

subcooling heat exchanger to subcooling compressors (K-

105 and K-106).

The natural gas is cooled in the propane precooling cycle

through four heat exchangers (LNG-100, LNG-101, LNG-

102 and LNG-103) to about -30.4ºC. Then by passing

through two main heat exchangers, namely LNG-104 and

LNG-105, the temperature falls to about -162.9ºC and finally

after dropping its pressure to about 0.116 bar releasing most

of its nitrogen contents in separator V-104, it is pumped to receivers.

But there are some differences between the real simplified

process modeled here and the standard C3MR process. For

example in a C3MR Process a mixture of refrigerants is used

for liquefaction and subcooling. In this process, after the

refrigerant passes through the separator, the liquid is used for

liquefaction and the gas is used for subcooling after dropping

its pressure while in the modeled process two distinct

refrigerants are used for liquefaction and subcooling.

3. MODELING AND OPTIMIZATION:

Before the simulation, the required parameters from main

process are specified in Tables 1. As the flow rate of feed gas

is constant, we have used the consumed power instead of

specific power which is normally used in optimization (for

example [6]). Assumed flow rate of natural gas feed is 46

170.25 kg mol/h.

Table 1. Mole fraction of components

Methane

%

Ethane

%

Propane

and

heavier %

Nitrogen

%

Natural gas 89.88% 4.86% 0.18% 5.08%

Precooling

Refrigerant 0.00% 1.81% 98.19% 0.00%

Different equations of state (EoS) have been evaluated at

the cryogenic conditions to choose the most suitable one to

be used in the simulation of the process. Literature says that

PRSV EoS is superior to other examined EoS's [7, 9, 10, 11,

and 12]. Details about these EoS are mentioned in other

works (for example [6]) and are beyond the scope of this

paper.

The simulation, calculation and optimization of Processes

were done using PRSV equation of state through Hysys®

software. PRSV is a modified Peng-Robinson EoS and has

the best adaptation and the least average absolute deviation

with experimental data at cryogenic condition. [7] This

equation is one of the most important Fluid Packages that is

the base of the simulation by Hysys®.

Many factors influence the performance of a certain

process. For instance, they are pressures and temperatures of

the mixed-refrigerants at each stage, temperature of the

refrigerant before expansion, and mole fraction of nitrogen,

methane, ethane, propane, temperature approach between hot

and cold composites in main heat exchangers, etc: As we

would not like to change any physical parameters in the real

process such as thermal surface of heat exchangers by

changing temperature approaches and so on. In this case, the

optimization problem is finding out the optimum mole

fraction of liquefaction and subcooling refrigerant

component values to make the power consumption to its

lowest level. This is some of powers consumed by 7

compressors and 1 pump (see figure 1) and we neglect the

power used for air cooler and other utilities.

We also assume to have 80% adiabatic efficiency in all

units of compressors and pump and this value will not be

changed by changing the mass flow rate of refrigerants.

The process described in the previous section was

simulated using Hysys® flow-sheeting program using PRSV

EoS property package.

Fig.1. The Modeled simplified C3MR Process

4. TRY AND ERROR METHOD FOR OPTIMIZATIOM:

4-1. Concept:

Many parameters can be used for optimization. Suction

and discharge pressure of compressors, the temperature and

pressure of natural gas and refrigerants at each stage may be

uses in an optimization process. As we would liked to apply

the optimization into the main cycle without any physical in

physical components, only composition of mixed refrigerants

and their mass flow rates have been selected as variables in

this work and other properties of refrigerant and natural gas

have been assumed to be constant.

Figure 2. Temperature profiles of the hot and cold (propane) streams

in four precooler heat exchangers of a four-stage precooler of propane

precooled mixed refrigerant natural gas liquefaction process. [13]

Appreciating the variation of temperature of the high and

low pressure streams along the length of the heat exchanger

is the first step in understanding the reason for low exergy

efficiency of the cryogenic refrigerators and liquefiers

operating with pure fluids. Figure 2 shows the temperature

profiles of the hot streams (main refrigerant mixture, natural

gas feed) and the cold stream (propane refrigerant) in four

precooling heat exchangers. The large temperature difference

between the hot and cold streams results in a higher exergy

loss in the propane-precooled process compared to the mixed

refrigerant precooled process (Figure 3) [13].

Figure 3. Temperature profiles in the two main heat exchangers of a

typical precooled mixed refrigerant process [13]

The indicative cooling curve of a natural gas with the

temperature showed in figure 4 profiles two superimposed

routes to liquefaction with pure and mixed refrigerants. For

commercial liquefaction process, the intent is to minimize

the difference between the hot and cold composites in order

to lower the exergy loss and improving thermal efficiency

[14].

As the temperature difference between two curves

declines, the entropy generation and exergy loss decrees.

That is why the designers use mixed combination of

hydrocarbons instead of pure fluids as refrigerant in recently

appeared cycles. Here we are going to optimize the

refrigerants using these cooling curves based on this concept.

In each stage, the preference of selected mixture is

understood by observation of consumed work uses by

compressors and pump and the mole fraction of components

has been changed by observation of the change in cooling

curve produced in main heat exchanger and the predicted

mole fractions were obtained. This operation has been done

for subcooling and liquefaction refrigerant. It is important to

say that in all stages of optimization, the predefined

temperature and pressure of natural gas and refrigerant do

not change.

In optimization of a process by changing its refrigerants

some points should be considered. In this process the

components of refrigerants are the products of this plant. So

availability of refrigerants components should be observed.

At each cycle, selection of components of refrigerants

corresponds with low and high pressure and temperature of

the cycle. For optimal operation all components of

refrigerant must be in two phase at the evaporator and in gas

phase at the inlet of compressors to prevent corrosion. That is

why propane is used for precooling and it is not used for

subcooling and for the same reason nitrogen for subcooling

and not for precooling in the main non-optimized process.

Figure 4. The indicative cooling curve of natural gas and two

superimposed route of liquefaction with pure and mixed refrigerant

[14]

Based on the thermodynamic analysis (first and second

law of thermodynamics), the simulation and calculation of

natural gas liquefaction process in skid-mounted package

were carried through.

4-2.Optimization:

Optimization starts from subcooling refrigerant because

we assumed that the conditions of natural gas is constant at

the inlet and outlet of main Subcooling heat exchanger; and

only the natural gas and subcooling refrigerant passes

through this heat exchanger and we can study the effect of

changing mole fraction and mass flow rate of refrigerant

directly on cooling curve and consumed work. It is

noteworthy to mention that if we liked to start optimization

from liquefaction refrigerant, we should have optimized

composition of Subcooling refrigerant and its optimum flow

rate to have the whole plant optimized.

After changing the refrigerant mole fraction in each stage,

first the mass flow rate of refrigerant modifies to (a) have the

least flow rate and to lower the duty of compressors, and (b)

avoid temperature cross in main heat exchanger. Then the

required mass flow rate for liquefaction and precooling

refrigerants obtained on the basis of two cited constraints and

total duty estimated. Other constraints are as below: (A) Sum

of the mole fractions of mixed-refrigerant is 1 and (B) The

temperature of mixed-refrigerant at the inlet of compressor is

higher than its dew point. It is clear that as the number of

iterations increases, the optimization would become better

and results will converge with by Hysys®

optimization

results. In the diagrams shown in Figure 5 to Figure 13, cold

composite is the backward low-temperature low-pressure

refrigerant and hot composite is sum of other curves formed

in the heat exchanger (natural gas and forward subcooling

refrigerant in subcooling heat exchanger and natural gas and

forward subcooling and liquefaction refrigerant in

liquefaction heat exchanger).

4-3. Results and Analysis of Optimization for Subcooling

Cycle:

As cited before, we could not start optimization from

liquefaction cycle from the beginning of the process. After

specifying the optimized composition and mass flow rate of

refrigerant in Subcooling cycle, and assuming of constant

condition for natural gas and subcooling refrigerant at the

inlet and outlet of main liquefaction heat exchanger, we can

optimize the liquefaction refrigerant as it was done for the

subcooling cycle.

In this refrigerant, we do not have nitrogen because it

stays in the form of gas anywhere in the cycle in operating

pressures and temperatures. Some samples of examined

combination of mole fractions are presented in Table 2. The

relative cooling curves are presented in figures 5-9.

Table 2. Some samples of examined combination of mole fractions

Power

MW

Required

subcooling

mass Flow

rate(kg/h)

Nitrogen

%

Ethane

%

Methane

%

Iteration

no.

193.8 501 134 5 35 60 1

202.4 515 000 5 30 65 2

188.7 500 000 5 40 55 3

191.0 510 000 7 39 54 4

187.1 495 000 3 41 56 5

Note that at iteration no. 5 the temperature approach is about

zero, and these two curves are similar and the consumed

work is minimum value. Because of high demand for heat

transfer area and lack of heat exchanger that could work at

this condition, this iteration will be neglected and iteration

no. 3 is used for continuance of optimization.. More attempts

showed that it is not possible to gather more than two curves

and to decrease the total duty. Optimization in this case is

finished. By using wide range of refrigerants we might

reduce the total consumed power further.

.

Figure 5. Cooling curve for subcooling heat exchanger before optimization– Iteration no. 1

Figure 6. Cooling curve for subcooling heat exchanger – Iteration no. 2

Figure 7. Cooling curve for subcooling heat exchanger – Iteration no. 3

Figure 8. Cooling curve for subcooling heat exchanger – Iteration no. 4

Figure 9. Cooling curve for subcooling heat exchanger – Iteration no. 5

4-4. Results and Analysis of Optimization for

Liquefaction Cycle

The concept of optimization is as explained before. Effect

of changing the concentration of an element on cooling

curves and total duty guided us to modify the mole fraction

of that is the next iteration.

Table 3. Some samples of examined combination of mole fractions

Power

(MW)

Required

subcooling

mass Flow

rate(kg/h)

Nitrogen

%

Ethane

%

Methane

%

Iteration

no.

188.7 790 000 20 70 10 6

196.3 795 000 15 70 15 7

195.9 795 000 10 80 10 8

198.9 815 000 25 50 25 9

184.0 820 000 30 60 10 10

181.7 820 000 35 55 10 11

It is clear that if we like to have a different temperature

approach we can select the related mole fraction of

mentioned cooling curve.

The first iteration in this section is the optimized

condition achieved in the previous part. (Iteration no. 3).

Some samples of examined combination of mole fractions

are presented in Table 3. The relative cooling curves are

presented in figures 10 and 11.

At iteration 11, two curves are too close and this result is

not acceptable like iteration 5. As it is obvious in the previous

figures, when two curves come closer, the demand for work

in this plant will come down.

5. OPTIMIZATION USING HYSYS® OPTIMIZER:

Hysys® contains a multi-variable steady state Optimizer.

Once the flow sheet has been built and a converged solution

has been obtained, the Optimizer can be used to find the

operating conditions which minimize (or maximize) the

objective function. The Optimizer owns its own spreadsheet

Table 4.Optimum component mole fraction obtained by Hysys® optimizer

Methane

%

Ethane

%

Propane

%

Nitrogen

%

Consumed

work

(MW)

Subcooling refrigerant

(before optimization) 60 35 0 5 193.8

Subcooling refrigerant

(optimized) 53.7 41.37 0 4.93 183.4

Liquefaction

refrigerant (before

optimization)

10 70 20 0 193.8

Liquefaction

refrigerant (optimized) 11.93 55.22 32.85 0 183.4

Figure 10. Cooling curve for liquefaction heat exchanger – Iteration no. 6

Figure 11. Cooling curve for liquefaction heat exchanger – Iteration no. 10

Figure 12. Cooling curve for subcooling heat exchanger – optimized by Hysys® optimizer

Figure 13. Cooling curve for liquefaction heat exchanger – optimized by Hysys® optimizer

for defining the objective function, as well as any constraint

expressions to be used. HYSYS has five modes of Optimizer:

Original, Hyprotech SQP, MDC Optim, MDC DataRecon

and Selection Optimization.

As it is not possible to define the mole fraction of

components in each refrigerants, we defined the mass flow

rate of components as optimization variable, which they mix

and generate the refrigerants. For each heat exchanger, an

adjust controller determines the cooling stream flow rate

based on predefined temperature approach (about 3°C in

main and precooling heat exchangers). An imaginary heating

process which consists of a liquid flow controller and a

heater prevents the existence of liquid in compressors

intervals. It is expected that at optimized condition, no heat

should be added to the streams.

Optimum subcooling and liquefaction refrigerants'

components mole fraction obtained by Hysys® optimizer and

predefined values are presented in Table.4. Relative cooling

curves are also present in figures 12 and 13.

Optimization using Hysys® optimizer results in better

answers to optimization. Optimization using this method

could redound in less power consumption and more

convergence of composite curves. By comparing figures 12

and 13 to figures 7 and 11 respectively, the concept of exergy

losses due to definite temperature difference will be clear.

6. CONCLUSIONS

1- As we expected to happen, by closing of two curves in

cooling curve diagrams, we could reduce total duty and

increase the efficiency of LNG production. By changing the

percentage of refrigerants' components and selecting the

optimized ones, we could reduce 5.06 % of preliminary

power (Trial and error method). Besides, we could increase

about 10.53% of base load by spending the original power.

The advantage of this method is that we could achieve these

results without any change in any part of this factory.

2- The mole fraction of refrigerants' composition might be

obtained either by trial and error method based on cooling

curves appeared in the main heat exchangers or using Hysys®

optimizer. In this method, it is possible to decrease the

energy demand about 10.4 MW (5.36 %). Optimization by

Trial and error method needs a simpler flow sheet and gives

leads to rapid and fairly good results, but using Hysys®

optimizer needs some controller elements and time to

converge, even the answer is more accurate.

3- As we know, in pure refrigerants if we assume that the

upstream condition is determined before throttle valve, the

pressure of refrigerants will be calculated when the

temperature is known and vice versa. But while using mixed

refrigerants, A point which should be considered during

modeling is that the pressure is a function of the

composition or the temperature is a function of pressure and

composition and during changing the composition of

refrigerant, the pressure might fall down under atmosphere

pressure if the temperature assumed to be fixed. So fixing the

appropriate variable should be considered.

4- While using EoS in some steam properties, there are some

errors in data prediction. These uncertainties affect the data

and may not lead to real optimum answer. Using restricted

deviation that is more compatible with experiment data,

especially for low temperatures, helps us to become assured

of these results. Surrendering heat leakage to the process,

assuming constant adiabatic efficiency of compressors

(neglecting the effect of stream flow on it) and assuming

constant pressure drop in all streams also lead to less

assurance.

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