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Evaluation of the PRICO liquefaction process using exergy-based methods
Journal of Natural Gas Science and Engineering xxx (2015) 1e9
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Journal of Natural Gas Science and Engineering journal homepage: www.elsevier.com/locate/jngse
Evaluation of the PRICO liquefaction process using exergy-based methods T. Morosuk*, S. Tesch, A. Hiemann, G. Tsatsaronis, N. Bin Omar €t Berlin, Marchstrasse 18, KT 1, TU Berlin, 10587 Berlin, Germany1 Institute for Energy Engineering, Technische Universita
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 October 2014 Received in revised form 5 February 2015 Accepted 7 February 2015 Available online xxx
The PRICO process is a single mixed-refrigerant process used for small-scale LNG plants, including offshore terminals. The working fluid (refrigerant) is a mixture of methane, ethane, butane and nitrogen. The behavior of the mixture in processes such as cooling, heating, compression, evaporation and condensation depends on its composition and on the part of the chemical constituents of the mixture that are in the gas and liquid phases. The state-of-the art for the evaluation and optimization of the PRICO process is discussed. Exergy-based analyses, i.e. exergetic, exergoeconomic and exergoenvironmental analyses, are applied to the evaluation of the PRICO liquefaction process of natural gas. The purpose of the paper is to identify options for improving the PRICO process and to demonstrate the application of exergy-based methods to the improvement of an LNG plant. The perspectives from the thermodynamic, economic and environmental impact points of view are discussed. © 2015 Elsevier B.V. All rights reserved.
Keywords: LNG PRICO process Exergy analysis Exergoeconomic analysis Exergoenvironmental analysis
1. Introduction Liquefaction of natural gas is the most energy-intensive and cost-intensive part of the overall chain “natural gas LNG e natural gas”. At the same time, liquefaction has also the largest potential for improvement. Therefore, different LNG production processes have been developed and are used in export terminals in many parts of the world. The PRICO process, which is one of them, is also known as a single mixed refrigerant (SMR) process. This process has been developed by the Black&Veatch Company, and the industrial applications of PRICO started in the year 1955, when it was applied to one of the first LNG plants. Three U.S./international patents cover the PRICO process. At present at least 21 LNG plants use this process while 16 more plants are in the design and/or construction phase. The PRICO process is popular for LNG peak-shaving units. In the year 2010, 25% of the LNG plants in the U.S. used this process. In the year 2012, design and construction for the world's first offshore LNG project started (Black&Veatch). The following advantages are associated with the PRICO process (Roberts et al., 2004):
* Corresponding author. E-mail addresses: [email protected] (T. Morosuk), [email protected]. de (S. Tesch), [email protected] (A. Hiemann), [email protected] (G. Tsatsaronis), [email protected] (N. Bin Omar). 1 URL: www.ebr.tu-berlin.de; www.energietechnik.tu-berlin.de.
Proven process that achieves the promised performance Relative simple operation Minimal refrigerant inventory Reduced number of equipment items Low capital cost and operating cost High flexibility High reliability Rapid startup
There are not many research publications dealing with liquefaction processes; however the PRICO (SMR) process recently became quite popular among researchers. Four processes for small-scale LNG plants were evaluated by Remeljeja and Hoadley, 2006. The PRICO process was selected there as a reference process. An exergy analysis was performed in a simple way and only relative data are given. The exergy destructions (thermodynamic inefficiencies) are distributed as follows: 21% within both compressors, 30% e within both coolers, 46% e within a heat exchanger, and 3% - within the throttling valve. The paper concluded that the SMR process has among all studied processes the lowest exergy consumption for the compressors, and that the main difference between the processes was caused by efficiency differences of the expander-driven compressors. Jensen and Skogestad, 2009 discussed eight compositions of the mixed refrigerant that can be used for the PRICO process; the effect of properties of the mixed refrigerant to the main characteristics of
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Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
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T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
the PRICO process were reported. The authors demonstrated that increasing the concentration of nitrogen within the mixed refrigerant leads to an improvement in the heat-transfer characteristics of all heat exchangers. An application of the gradient-free optimization-simulation method to processes modeled with the simulator Aspen HYSYS is reported by Aspelund et al., 2010. The PRICO process was selected as an academic example for the optimization for two reasons: Firstly this process is a simple LNG process with seven independent variables (selected by the authors). This number is too large for the optimization routine, but small enough to be optimized with an optimization-simulation tool. The second reason is that it is possible to verify the results by investigating the hot and cold composite curves. The paper focused on the number of iterations required to get an optimal concentration of the mixed refrigerant. Mokarizadeh Haghighi Shirazi and Mowla (2010) discussed the simulation of SMR concepts and the properties that are used in MATLAB to generate the objective function. A genetic algorithm was used for optimization. The energy consumption of the process was minimized. Depending on the concentration of the refrigerant, the specific energy consumption can be reduced from 1485 kJ/kgLNG to 1186.6 kJ/kgLNG or from 1126.7 kJ/kgLNG to 1092.4 kJ/kgLNG. The smaller values were taking from Lee, 2001 (as a reference publication). The authors applied also an exergy analysis, in order to calculate the values of the exergy destruction within the components: 31% within both compressors, 33% e within both coolers, 27% e within the heat exchanger, and 9% - within the throttling valve. Hiemann, 2011 conducted a detailed exergy analysis of the PRICO process. Here the approach “exergy of fuel/exergy of product” has been used taking into account a splitting of the physical exergy into thermal and mechanical parts. Marmolejo-Correa and Gundersen, 2012 selected the PRICO process as an academic example to demonstrate the effect of using different approaches in the exergy analysis (“inlet exergy/outlet exergy” versus “exergy of fuel/exergy of product” as well as splitting of the physical exergy into thermal and mechanical parts) on the obtained results. The authors assumed the operation conditions without necessarily a reference to real plants. Xu et al., 2013 reported the results of the optimization of the concentration of the refrigerant as a function of the inlet temperature to the heat exchanger (263.15 K through 313.15 K). For the optimization, a genetic algorithm coupled with the process simulation software Aspen Plus has been used. The results show that when the ambient temperature increases, the concentrations of methane, ethylene and propane should decrease, while the concentration of isopentane should increase. In this way the overall exergetic efficiency can be increased from 30% (calculated by the authors for the commercial concentration of the refrigerant) up to 39.6e42.3%. In this paper the exergetic efficiency is a function of COP and of a “correlation factor”. In a follow-up paper (Xu et al., 2013), the effect of concentration for each working fluid within the mixed refrigerant was investigated, in order to minimize the specific power consumption (the value of 1003.6 kJ/kgLNG was reached), i.e. maximize the values of COP and exergetic efficiency. The reported value of COP ¼ 0.782 is surprisingly high in comparison with results reported in other publications; however, the definition of COP is not given. The exergetic efficiency was calculated as 43.9%, which is in the range of other available data for the PRICO process. The distribution of the exergy destruction within the components is as follows: 36% within both compressors, 27% e within both coolers, 26% e within the heat exchanger, and 11% - within the throttling valve. Sequential quadratic programming was also applied to the optimization of the PRICO process (Morin A. et al., 2011). The research focused on the method used for optimization. The optimization results related to the liquefaction process itself were
discussed very briefly for the two study cases, in which the mixed refrigerant is with and without pentane. Through the energetic optimization, the specific energy supply decreases by 3.12%. Again the same optimization procedure for the PRICO process was reported by Wahl et al., 2013. The optimal composition of the mixed refrigerant was a function of the composition of natural gas (so called “lean natural gas” and “rich natural gas”). The heat-transfer characteristics for the multi-flow heat exchanger are also discussed. The main goal of the authors was to get the results of the optimization within a short period of execution time (5 min) in comparison with the optimization procedure discussed by Aspelund et al., 2010 that required 12 h. Castillo and Dorao, 2012, discussed economic issues related to LNG processes. They reported the application of Decision-Making (using a Genetic Algorithm binary coding and Nash-GA) for the PRICO process. The LNG markets were also implemented in the optimization of the PRICO process. Only relative economic data are reported, for example, the cost of the multi-flow heat exchanger is approximately 10e15% of the total investment cost and the cost associated with the compression process is always the dominating factor for all approaches used in the optimization. Khan et al., 2012 discussed the optimal composition of the mixed refrigerant for the SMR process from the energetic point of view, i.e. through the minimization of energy consumption for the compression process (from 1600 to 1528 kJ/kgLNG). The log mean temperature difference within multi-flow heat exchanger is 7.8 K. The SMR process was modeled in the UniSim Design simulator, and the model was optimized with nonlinear programming. The exergy analysis was implemented into the described optimization methodology (Khan et al., 2013) and more complex mixed refrigerant processes were optimized. Heldt, 2011 developed and tested a mathematical model for control strategies, in order for the SMR processes to operate at optimal conditions. High attention was given to the modeling of the multi-flow heat exchanger based on industrial experimental data. The literature review for the evaluation of the PRICO (SMR) process shows that mainly energetic optimizations were discussed using different methods for the mathematical optimization and corresponding algorithms. Sometimes the selected method for optimization and its improvement/robustness were more important to the authors that the obtained results related to the PRICO process. The objective function of the optimization refers mainly to the composition of the mixed refrigerant. An economic analysis is not very common for the evaluation of the PRICO liquefaction process, and environmental issues have not been discussed yet. The goal of this paper is to evaluate the PRICO process from the exergetic, economic, and environmental viewpoints for a given composition of the mixed refrigerant, in order to assist in developing an optimal strategy for designing and operating such a plant. 2. Exergy-based methods Exergy is defined as the maximum theoretical useful work (shaft work or electrical work) obtainable from an energy conversion system as this is brought into thermodynamic equilibrium with the thermodynamic environment while interacting only with this environment (Tsatsaronis, 2007). An exergetic analysis identifies the location, magnitude, and causes of thermodynamic inefficiencies, which are the exergy destruction (due to irreversibilities within each system component), and the exergy loss (exergy transfer to the environment). In an exergetic analysis, we calculate the exergy associated with each energy carrier (stream) in the overall system, the exergy destruction within each system component and process, and the exergetic efficiency (for each process, component, or system) (for example, Bejan et al., 1996).
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
Modern exergetic analyses use the concept of fuel and product introduced almost 30 years ago (Tsatsaronis, 1984) and generalized by Lazzaretto and Tsatsaronis, 2006: The exergy of product is the desired result (expressed in exergy terms) achieved by the system (e.g., the kth component) being considered, and the exergy of fuel represents the exergetic resources expended to generate the exergy of the product. These concepts are used in a consistent way in all exergy-based analyses (Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006; Meyer et al., 2009; Tsatsaronis and Morosuk, 2012) that include the exergoeconomic and the exergoenvironmental analyses. The exergy balance for the overall system (subscript tot) is
E_ F;tot ¼ E_ P;tot þ
X
E_ D;k þ E_ L;tot
(2)
where E_ F , E_ P , E_ D and E_ L are the exergy rates of fuel, product, destruction and losses, respectively. The variables used for the conventional exergetic evaluation of the kth component in a system include the following: Exergy destruction rate that is calculated from the exergy balance Exergetic efficiency
εk ¼
E_ P;k E_ D;k ¼1 E_ E_ F;k
(3)
F;k
Exergy destruction ratio
yk ¼
E_ D;k E_ F;tot
(4)
Exergoeconomic analysis (for example, Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006) is a unique combination of exergy analysis and cost analysis conducted at the component level, to provide the designer or operator of an energy conversion system with information crucial to the design or operation of a costeffective system. The same information cannot be provided by any other approaches. A complete exergoeconomic analysis consists of (a) an exergetic analysis, (b) an economic analysis, and (c) an exergoeconomic evaluation. The exergoeconomic model for an energy conversion system consists of cost balances written for the kth component, and of auxiliary equations based on the so-called F and P rules (Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006). The cost balances can be written as
C_ P;k ¼ C_ F;k þ Z_ k
(5a)
or
cP;k E_ P;k ¼ cF;k E_ F;k þ Z_ k where
C_ D;k ¼ cF;k $E_ D;k
(5b)
(7)
and for the overall system
C_ D;tot ¼ cF;tot $
and for the kth component (subscript k)
(6)
Here C_ P;k and C_ F;k are the cost rates associated with the exergy of product and fuel, respectively; cP,k and cF,k are the specific costs per unit of exergy associated with the exergy of product and fuel, respectively; Z_ k is the cost rate that represents the sum of the capital CI OM investment cost Z_ k and operating and maintenance expenses Z_ k . The cost rate associated with exergy destruction within the kth component is
(1)
k
E_ F;k ¼ E_ P;k þ E_ D;k
CI OM Z_ k ¼ Z_ k þ Z_ k
3
X
E_ D;k
(8)
An exergoeconomic evaluation is based on the following variables: C_ D;k , Z_ k , the sum ðC_ D;k þ Z_ k Þ, the relative cost difference rk, and the exergoeconomic factor fk
rk ¼
cP;k cF;k 1 εk Z_ k ¼ þ cF;k εk cF;k E_ P;k
fk ¼
Z_ k _ Z k þ C_ D;k
(9)
(10)
In an exergoenvironmental analysis (Meyer et al., 2009), the environmental impacts obtained by Life Cycle Assessment (LCA) are apportioned to the exergy streams and the exergy destruction streams, thus identifying the system components with the highest environmental impact and possible improvements associated with these components. Finally, exergoenvironmental variables are calculated, and an exergoenvironmental evaluation is carried out. Life cycle assessment is a technique for assessing the environmental aspects associated with a product over its life cycle. The LCA process consists of goal definition and scoping (defining the system under consideration), inventory analysis (identifying and quantifying the consumption and release of materials), and interpretation (evaluation of the results). Any of the recently introduced metrics (environmental indicators) can be used for LCA, for example, EcoIndicator 99 (Goedkoop and Spriensma, 2000). The exergoenvironmental model for an energy conversion system consists of environmental impact balances written for the kth component and auxiliary equations based on the F and P rules. The environmental impact balances can be written as
PF B_ P;k ¼ B_ F;k þ Y_ k þ B_ k
(11a)
or
PF bP;k E_ P;k ¼ bF;k E_ F;k þ Y_ k þ B_ k
(11b)
Here B_ P;k and B_ F;k are the environmental impact rates associated with the exergy of product and fuel, respectively; cP,k and cF,k are the specific environmental impacts per unit of exergy associated with CO the exergy of product and fuel, respectively; construction, Y_ k , OM DI operation & maintenance, Y_ k , and disposal, Y_ k constitute the component-related environmental impact associated with the kth component Y_ k : CO OM DI Y_ k ¼ Y_ k þ Y_ k þ Y_ k
(12)
To simplify the discussion, we assume that the value of Y_ k is CO mainly associated with Y_ k
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
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T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
To account for pollutant formation within the k th component, PF PF the variable B_ k is used (Boyano et al., 2012). The term B_ k is zero when no pollutants are formed within a process, i.e. for processes without a chemical reaction such as compression, expansion, heat transfer, etc. The environmental impact associated with the exergy destruction within the kth component B_ D;k is given by
B_ D;k ¼ bF;k E_ D;k
(13)
and within the overall system by
B_ D;tot ¼ bF;tot $
X
E_ D;k
(14)
To identify the most important components from the viewpoint of formation of environmental impacts, the sum of environmental PF impacts ðY_ k þ B_ k þ B_ D;k Þ is used together with two other variables in analogy with the exergoeconomic analysis, i.e. the relative difference
rb;k ¼
bP;k bF;k bF;k
(15)
Y_ k PF Y_ k þ B_ k þ B_ D;k
The simulation data are given in Tables 2 and 3. The purpose of this paper is to evaluate the PRICO process, therefore the drivers for the compressors have not been considered in the simulation, and the energy and exergy analyses. 3.1. Energy and exergy analyses The results obtained from the energy analysis include the following: The power required for the compressors is _ _ W ¼ 44:70 MW and W ¼ 46:51 MW. In the case of oneCM1
and the exergoenvironmental factor
fb;k ¼
Inlet characteristics of natural gas: T8 ¼ 38 С and p8 ¼ 67 bar (Venkatarathnam, 2008) The pressure drop within the heat exchanger is 3 bar for all three streams The minimum temperature difference within the cooler and the condenser is 3 K The isentropic efficiency for both compressors is assumed to be equal to 80% The compositions of refrigerant and natural gas are given in Table 1. Note that n- butane is lumped with butane.
(16)
However, the application of the exergoenvironmental analysis to different energy conversion processes (for example, Meyer et al., 2009; Boyano et al., 2011, 2012; Tsatsaronis and Morosuk, 2012; Morosuk et al., 2012) demonstrated that the value of environmental impact associated with the exergy destruction B_ D;k is always much higher than the component-related environmental impact Y_ k PF (if the value of B_ is not considered for the k th component). In this k
way, and for simplifying the analysis without affecting the conclusions, Y_ k can be neglected; then, fb,k is not used. These methods were used to evaluate power plants (for example, Tsatsaronis and Morosuk, 2008, 2012; Petrakopoulou at el. 2011), refrigeration processes (for example, Morosuk and Tsatsaronis, 2012) and chemical processes (for example, Meyer et al., 2009; Boyano et al., 2011, 2012). 3. PRICO process The flow diagram of the PRICO (SMR) process is shown in Fig. 1. The working fluid (refrigerant) is a mixture of methane, ethane, butane and nitrogen (Table 1). The refrigerant is compressed from state 1 to state 4 using a two-stage compression process (CM1 and CM2) with interstage cooling (COL), and is subsequently condensed (CD). The heat exchanger HE is a three-flow heat exchanger, where the stream 5-6 of refrigerant is cooled down, while the stream 7-1 of refrigerant is vaporized, and the stream 8-9 of natural gas is cooled and liquefied. In general, due to the relative small pressure ratio, a single-stage compression process could be sufficient. However, a two-stage compression process with interstage cooling is more appropriate, in order to decrease the total power required for the compressors. For the simulation of the PRICO process the software Aspen Plus (2011) was used, and the PengeRobinson equation of state was selected. This approach can handle any combination of nonpolar or mildly polar mixtures; examples are hydrocarbons and light gases. The following assumptions were used for the simulation: The ambient temperature is 25 C, and the ambient pressure is 1.013 bar
CM2
stage compression process, additional 5.6 MW would be required. The heat rates transferred to the environment are ¼ 36:38 MW and Q_ ¼ 93:57 MW. The heat rate within the Q_ COL
CD
heat exchanger is Q_ HE ¼ 336:95 MW. The T DH_ diagram for the heat exchanger is shown in Fig. 2. The log-mean temperature difference within the exchanger is equal to 7 K. The coefficient of performance of the PRICO process defined by _ _ COP ¼ ðH_ H_ Þ=ðW þW Þ is equal to 0.44 under the 8
9
CM1
CM2
assumed operation conditions and concentration of the refrigerant, whereas the specific energy consumption amounts to 1824 kJ/ kgLNG. The exergetic analysis was conducted using the approach “exergy of fuel/exergy of product” (Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006). The physical exergy of the material streams in the PRICO process must be split into thermal and mechanical parts (Morosuk and Tsatsaronis, 2005) for processes below the ambient temperature and every time this temperature is crossed. The reference values for the exergetic analysis (state 0) for each material stream are given in Table 2. The exergy of fuel and exergy of product for each system component are defined as follows: Compressor 1 (CM 1)
M _ _T _ _ M þ E_ T _ E_ F;CM1 ¼ W CM1 þ E1 and EP;CM1 ¼ E 2 E1 2 Cooler (COL) is a dissipative component (Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006), therefore E_ D;COL ¼ E_ 2 E_ 3 Compressor 2 (CM 2)
_ _ _ _ E_ F;CM2 ¼ W CM2 and EP;CM2 ¼ E 4 E3 Condenser (CD) is a dissipative component, E_ D;CD ¼ E_ 4 E_ 5 Heat exchanger (HE)
M M M T T M M M E_ F;HE ¼ E_ 7 E_ 1 þ E_ 7 E_ 1 þ E_ 8 E_ 9 þ E_ 5 E_ 6 T T þ E_ 5 þ E_ 8 and E_ P;HE T ¼ E6T þ E_ 9
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
5
Fig. 1. Flow diagram of the PRICO process: CM 1 e Compressor 1; COL e Cooler; CM 2 e Compressor 2; CD e Condenser; HE e Heat exchanger; TV e Throttling Valve.
Table 1 Compositions of natural gas and refrigerant. Component
Formula
Refrigerant (% mol)a
Natural gasb (% mol)
Methane Ethane Propane Butane Nitrogen
CH4 C2H6 C3H8 C4H10 N2
0.30 0.30 e 0.25 0.15
0.88 0.08 0.02 e 0.02
a b
Table 3 Detailed thermodynamic data of each chemical component in the streams within mixed refrigerant. Stream
1
2
3
4
5
6
7
8
9
0.148 0.277 0.000 0.446 0.129
0.148 0.277 0.000 0.446 0.129
0.144 0.249 0.000 0.224 0.128
e e e e e
0.003 0.000 0.000 0.000 0.057
0.786 0.134 0.049 0.000 0.031
e e e e e
e e e e e
e e e e e
0.004 0.028 0.000 0.222 0.001
0.148 0.277 0.000 0.446 0.129
0.145 0.277 0.000 0.446 0.072
e e e e e
0.786 0.134 0.049 0.000 0.031
2.40 2.40 e 2.00 1.20
6.60 6.60 e 5.50 3.30
7.69 7.10 e 3.31 3.91
e e e e e
0.43 0.00 e 0.00 5.57
58.96 5.36 1.34 e 1.34
e e e e e
Mass fraction (kg/kg) Vapor Methane 0.148 0.148 Ethane 0.277 0.277 Propane 0.000 0.000 Butane 0.446 0.446 Nitrogen 0.129 0.129 Liquid Methane e e Ethane e e Propane e e Butane e e Nitrogen e e Partial pressure (bar) Methane 0.90 2.40 Ethane 0.90 2.40 Propane e e Butane 0.75 2.00 Nitrogen 0.45 1.20
Jensen and Skogestad, 2009. Mokhatab and Economides, 2006.
Throttling valve (TV)
M M T T E_ F;TV ¼ E_ 6 E_ 7 and E_ P;TV ¼ E_ 7 E_ 6
Overall system (without considering the drivers for the compressors)
M _ _ _ _M _T _T _ E_ F;tot ¼ W CM1 þ W CM2 þ E8 E 9 ; and EP;tot ¼ E9 E8
example, Bejan et al., 1996). For the economic analysis the bare module cost for each component was estimated, and the remaining cost contributors are calculated based on these values (Table 5). Since the location of the evaluated LNG plant is unknown, office costs were not taken into consideration. Because no economic data for the PRICO process are available in the open sources and because cost estimation data for the lowtemperature and cryogenic equipment is not reported in detail in the literature, as it is the case for chemical and power plants, the bare module cost for each component of the PRICO process was
The results obtained from the exergetic analysis are shown in Table 4. 3.2. Economic analysis An economic analysis of the PRICO process was carried out based on the Total Revenue Requirement (TRR) method (for
Table 2 Thermodynamic, exergetic, cost and environmental impact data for the material streams. Stream Material stream Thermodynamic data m_
1 2 3 4 5 6 7 0a 8 9 0a a
Refrigerant
p
x
(Kg/s) (ºC)
(Bar)
(Kg/kg) (kJ/kg)
475
3 8 8 22 22 19 6 1.013 67 64 1.013
e e e e 0.84 0 0.07
Natural gas 50
T
Exergetic analysis
15 71 30 91 30 159 162 25 38 159 25
e 0
h
s
T
e
M
e
Exergoeconomic analysis PH
e
T
c
(kJ/kg K) (kJ/kg) (kJ/kg) (kJ/kg) ($/GJ)
2446 5.16 2352 5.10 2429 5.34 2331 5.28 2532 5.90 3156 8.94 3156 8.92 2426 4.81 4188 6.83 4998 10.92 4141 4.81
0.3 6.1 0.1 16.8 0.2 291.2 362.3
81.5 153.3 153.3 218.2 218.2 210.0 132.5
81.8 159.4 153.4 235.0 218.4 501.2 494.8
50.07 18.06 18.06 17.67 17.67 57.49 50.07
0.7 417.0
555.1 549.7
555.8 966.7
0 57.49
M
Exergoenvironmental analysis
c
c
bT
bM
bPH
($/GJ)
($/GJ)
(Pts/GJ)
(Pts/GJ)
(Pts/GJ)
17.87 17.96 17.96 17.87 17.87 17.87 17.87
67.94 36.02 36.02 35.54 35.54 75.36 67.94
39.06 14.54 14.54 14.29 14.29 44.76 39.06
14.42 14.48 14.48 14.42 14.42 14.42 14.42
53.48 29.01 29.01 28.71 28.71 59.18 53.48
0 57.49
3.75 44.76
3.75 3.75
7.51 48.52
0 0
PH
Reference state for the exergetic analysis.
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
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T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9 Table 5 Estimation of the fixed-capital investment (in mil US$ for the year 2014). Direct costs (DC)
Onsite costs (bare module cost, CBM) Compressor CM1 Compressor CM2 Cooler Condenser Heat exchanger Throttling valve Offsite costs
Total direct costs Indirect costs (IC)
Engineering and supervision (8% of DC) Construction costs (15% of DC) Contingencies (15% of the sum DC and ID) Total indirect costs Fixed-capital investment
Fig. 2. T DH_ diagram for the heat exchanger.
pressure factors were assumed to be equal to one. However, for the intensification of heat-transfer characteristics, the material of tube is assumed to be brass (material of shell is carbon steel). Therefore the material factor is 2.4. The bare module factor is equal to 3.17. The heat exchanger is a three-flow, low temperature heat exchanger. Such a heat exchanger is considered as quite challenging due to its special design. Only few companies in the world produce such heat exchangers for LNG applications; therefore the data required for the economic analysis are confidential and not available in the open literature. The overall heat transfer coefficient was estimated as UHE ¼ 2000 W/m2K (Kakac and Hongtan, 1998), therefore ACOL ¼ 3865 m2. For the economic analysis, the data reported by Ulrich and Vasudevan, 2002 were used with the following adjustments corresponding to the low-temperature operation conditions: fm ¼ 2.3 and fT ¼ 1.5. The bare module factor is equal to 3.5. A simple throttling valve used for the simulation, represents in reality a throttling valve station (many throttling valves with corresponding safety/control equipment, used in parallel).
estimated using the following equation:
CBM;k ¼ CM;k fd fm fT fp fBM;k
87.6 39.3 40.5 1.7 1.4 3.9 0.8 0 87.6 7.0 13.1 16.1 36.2 123.8
(17)
where CBM,k bare module cost of the k th component, CM module cost of the k th component, fd e design-type factor, fm e material factor, fT e temperature factor, fp e pressure factor, and fBM e bare module factor of the k th component. The term CM fd fm fT fp is the purchased-equipment cost. Data from the chemical industry were used to calculate the bare module cost and the factors. The following assumptions were made and results were obtained for the economic analysis: Centrifugal type of turbo compressors was selected. The information from Waren et al., 2004 was used for the economic analysis of the compressors. For the estimation of the module _ ) is used as a sizing factor. cost, the net required power (W k Based on the data given for the year 2004, the recalculated specific cost is 878 US$2014/kW. Since the operation conditions for the two compressors are in the range of regular application, the design-type, material, temperature and pressure factors were assumed to be equal to one. The bare module factor is equal to 2.15. The cooler and condenser were assumed to be shell-and-tube heat exchangers. The UA values of the cooler and condenser were obtained from the Aspen PLUS simulation software and the overall heat transfer coefficients (U) were taken from Kakac and Hongtan, 1998, i.e., UCOL ¼ 500 W/m2K and UCD ¼ 1000 W/ m2K. Finally, the heat transfer surfaces amount to ACOL ¼ 2600 m2 and ACD ¼ 2198 m2. For the economic analysis, the data reported by Waren et al., 2004 were used. Since the operation conditions for the cooler and condenser are also in the range of regular application, the design-type, temperature, and
Based on the estimated fixed-capital investment and the assumptions for the economic, financial, operating, and market input variables, the total revenue requirement is calculated. The nonuniform annual monetary values associated with the investment (carrying charges, CC), operation & maintenance (OMC), and fuel costs (FC) of the system being analyzed are levelized, that is they are converted into an equivalent series of constant payments (annuities). The levelized carrying charges are calculated as
CCL ¼ ðTotal Capital InvestmentÞ CRF
(18)
where the capital-recovery factor (CRF) (Bejan et al., 1996) is given by
Table 4 Results obtained from the exergetic, exergoeconomic and exergoenvironmental analyses. Component
CM1 COL CM2 CD HE TV Overall system
Exergetic analysis
Exergoeconomic analysis
Exergoenvironmental analysis
E_ F;k
E_ P;k
E_ D;k
εk
yk
cF,k
cP,k
Z_ k
C_ D;k
Z_ k þ C_ D;k
r
f
bF,k
bP,k
B_ D;k
rb
(MW)
(MW)
(MW)
(%)
(%)
($/GJ)
($/GJ)
($/h)
($/h)
($/h)
(%)
(%)
(mPts/GJ)
(mPts/GJ)
(mPts/h)
(%)
44.84 e 46.51 e 200.50 36.77 91.48
37.00 e 38.83 e 159.20 33.73 20.82
7.84 2.86 7.71 7.89 41.31 3.04 70.66
82.5 e 83.5 e 79.4 91.7 22.7
8.6 3.1 8.5 8.6 45.1 3.3 77.2
31.99 97.28 31.67 96.17 120.42 48.32 31.58
48.76 e 47.84 e 151.89 52.89 178.35
1330 56 1373 48 131 26 2965
188 370 182 1009 6759 196 1654
1518 426 1555 1057 6890 222 4619
171.1 e 170.9 e 26.4 10.2 948.1
87.6 13.3 88.3 4.6 1.9 11.8 64.2
12.00 384.63 11.91 204.02 35.54 14.42 11.89
14.54 e 14.29 e 55.82 15.72 52.24
338 3946 332 5791 5284 158 3024
21.2 e 20.0 e 57.1 9.0 339.5
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T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
n ieff 1 þ ieff CRF ¼ n 1 þ ieff 1
(19)
Here ieff is the average annual effective discount rate (cost of money), and n denotes the plant economic life expressed in years. For the fuel we calculate the constant escalation levelization factor (CELF).
FCL ¼ FC0 CELF ¼ FC0
kFC 1 knFC CRF ð1 kFC Þ
kOMC 1 knOMC CRF OMCL ¼ OMC0 CELF ¼ OMC0 ð1 kOMC Þ
TRRL ¼ CCL þ FCL þ OMCL
(21)
(22)
The LNG plant operates with a 100% capacity during 7446 h per year (capacity factor ¼ 85%) The average cost of money is ieff ¼ 10%. The plant economic life is n ¼ 20 years. The average general inflation rate is rn ¼ 2.5% The operating and maintenance costs are assumed to be 4% of the CC.
3.3. Exergoeconomic analysis An exergoeconomic analysis is based on cost balances written for the k th component and auxiliary costing equations (if required): T M M T Compressor 1: C_ 1 þ C_ W;CM1 þ Z_ CM1 ¼ C_ 2 C_ 1 þ C_ 2 and one auxiliary costing equation according to the P-rule, M M M M cT2 ðC_ 2 C_ 1 Þ=ðE_ 2 E_ 1 Þ M M T T Compressor 2: C_ W;CM2 þ Z_ CM2 ¼ C_ 4 C_ 3 þ C_ 4 C_ 3 , and according to the P rule M M T T M M T T ðC_ C_ Þ=ðE_ E_ Þ ðC_ C_ Þ=ðE_ E_ Þ. The values of 3
4
3
4
3
2
COL
3
Diff;COL
T T M M condenser is C_ 4 C_ 5 þ C_ 4 C_ 5 þ Z_ CD ¼ C_ Diff ;CD with the asM _ sumptions cT4 ¼ cT5 and cM 4 ¼ c5 . The values of C Diff;COL and _ are considered in the calculation of the cost associated C
with the product of the overall system. The cost rates associated with the exergy of fuel and the exergy of product for the overall system are T T C_ P ¼ C_ 9 C_ 8 þ C_ Diff;CD þ C_ Diff;COL and C_ F M
The following assumptions have been made for the economic analysis:
4
2
M sumptions cT2 ¼ cT3 and cM 2 ¼ c3 , and the cost balance for the
M
¼ C_ W;CM1 þ C_ W;CM2 þ C_ 8 C_ 9 respectively:
with kOMC ¼ 1 þ rOMC =1 þ ieff and rOMC ¼ const, where rOMC is the average annual nominal escalation rate for the operating and maintenance costs. Finally, the levelized total revenue requirement (TRRL) is obtained from
3
Cooler and condenser are dissipative components, therefore the cost balances should be written in a different way taking into account that the specific cost of each stream passed through these components remains constant, i.e. the cost balance for the T T M M cooler is C_ C_ þ C_ C_ þ Z_ ¼ C_ with the as-
Diff;CD
(20)
with kFC ¼ 1 þ rFC =1 þ ieff and rFC ¼ const. The term rFC denotes the average annual nominal escalation rate for fuel cost. The levelized annual operating and maintenance costs OMCL are given by
4
7
3
_ C_ W;CM1 and C_ W;CM2 are calculated as C_ W;CM1 ¼ W CM1 cW and _ _ C W;CM2 ¼ W CM2 cW , respectively
T M M M M M M Heat Exchanger: C_ 5 þ C_ 8 C_ 9 þ C_ 5 C_ 6 þ C_ 7 C_ 1 þ T T T T T T T T C_ 7 C_ 1 þ Z_ HE ¼ C_ 9 þ C_ 6 , according to the P-rule C_ 9 =E_ 9 ¼ C_ 6 =E_ 6 M M M M M , and according to the F rule: cM 8 ¼ c9 , c5 ¼ c6 , c7 ¼ c1 and
cT7 ¼ cT1 . M M T T Throttling Valve: C_ 6 C_ 7 þ Z_ TV ¼ C_ 7 C_ 6 , according to the F M M rule, c6 ¼ c7
The value of cW was calculated using the cost balance applied to the overall open-cycle gas-turbine system LM 6000 used as a driver for both compressors: C_ fuel þ Z_ GT ¼ C_ W . Based on data reported by General Electric for the LM 6000 system (Gas Turbine World, 2006), the following initial data were obtained, and the corresponding results were calculated: The overall energetic efficiency of the LM 6000 system is equal to 44.5%; therefore the fuel (natural gas) consumption is calculated as 4.43 kg/s; The specific investment cost of the gas-turbine system for the year 2010 was estimated as 296 US$/kW, which leads to the value of Z_ GT ¼ 1073 $/h. Assuming that the price of natural gas is 4.5 US$/GJLHV, the specific cost of power supplied from the driver to both compressors is calculated as cW ¼ 14.37 $/GJ. Tables 2 and 4 show the results obtained from the exergoeconomic analysis.
3.4. Exergoenvironmental analysis An exergoenvironmental analysis is based on environmental impact balances written for the k th component and auxiliary equations (if required). The environmental impact balances are formulated in analogy to the cost balances written for the corresponding exergoeconomic analysis. For the evaluation of the PRICO process, we assumed that the component-related environmental impact can be neglected (Yk¼0), therefore no component-related LCA was conducted. The Eco-Indicator 99 was applied. Note that for the exergoenvironmental analysis of the PRICO process with compressors driven by a gas-turbine power system, two different values of the environmental impact associated with natural gas were used: For natural gas that should be liquefied (stream 8), Pts ¼ 3:90 Pts , and bCH4 ¼ 0:14 Nm 3 GJLHV For natural gas that is used in a gas-turbine system (driver), bCH4 ¼ 5:30 GJPts . This value is higher than the first one because it LHV includes the generation of pollutants during the combustion process. Charging the potential pollutants to the fuel is an approach that simplifies the analysis because there is then no PF need to calculate the value of B_ k for Eq. (11). For the calculation of the environmental impact associated with the power supplied to the compressors, an analogous methodology to the
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T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
exergoeconomic analysis was applied. Finally the environmental impact associated with the power for the compressors is bW ¼ 11.91 Pts/GJ. Tables 2 and 4 show the results obtained from the exergoenvironmental analysis. 4. Results and discussions The values of COP ¼ 0.44 and specific energy consumption of 1824 kJ/kgLNG are relatively low compared to the corresponding ones from the publications mentioned in the introduction. The value of the exergetic efficiency of 22.7% cannot be compared with the data reported by others because, as it was already noted, the exergy analysis was conducted in terms of “exergy of fuel/exergy of product” and not of “inlet/outlet exergy” as used by other authors. However, the distribution of the exergy destruction among the components (Table 4) has a good correlation with the earlier reported results (Mokarizadeh Haghighi Shirazi and Mowla, 2010; Xu et al., 2013): 22% associated with the compression process (E_ D;CM1 þ E_ D;CM2 ¼ 15:55 MW); 15% associated with the cooler and condenser (E_ D;COL þ E_ D;CD ¼ 10:75 MW) e within both coolers, 58% e within the heat exchanger (E_ D;HE ¼ 41:31 MW), and 5.7% - within the throttling valve (E_ D;TV ¼ 3:04 MW). The rate of exergy destruction within the heat exchanger (yHE) shows that 45% of the exergy of the fuel supplied to the overall system is destroyed through the inefficiencies within this component. The exergetic efficiency for each of the productive components (compressors, heat exchanger and throttling valve) is high (in the range of 80e90%). This means that the evaluated PRICO system has a relatively low potential of efficiency improvement as long as the composition of the mixed refrigerant remains unchanged. The economic analysis (Tables 4 and 5) shows that 91% of the total capital investment associated with the two compressors (that is fully confirmed by data reported by Castillo and Dorao, 2012.), 5% with the heat exchanger, 3% with the cooler and condenser and 1% with the throttling valve. If cost optimization would be based on the investment costs, then the conclusion is obvious: a reduction in the cost of both compressors will significantly reduce the total cost of the PRICO plant. Let us discuss the conclusions that have been obtained from the exergoeconomic analysis (Table 4). The value of the exergoeconomic factor (64.2%) for the overall system demonstrates (based on recommendation from Bejan et al., 1996), that the analyzed PRICO process has no design error from the cost point of view. The component-by-component analyses show, that the value of the total cost associated with the component, i.e., the sum ðC_ D;k þ Z_ k Þ, is the highest for the heat exchanger because of the cost of the exergy destruction within this component. The very low value of the exergoeconomic factor (fHE ¼ 1:9%) suggests the direction for cost improvement: The heat exchanger should be improved from the thermodynamic point of view, i.e. the exergy destruction should be reduced, and the exergetic efficiency increased. This will lead to a decrease in the cost of the exergy destruction. At the same time, the capital investment cost of this component will increase. However, the cost of the final product will definitely decrease. Both compressors have the highest capital investment cost but very low cost associated with the exergy destruction. The high value of the exergoeconomic factor (around 88%) for the compressors indicates that the overall LNG cost could be reduced if less expensive compressors would be used, even if these would have a lower efficiency. The data obtained from the exergoenvironmental analysis demonstrate that the highest environmental impact is associated with the exergy destruction within the heat exchanger. In order to
reduce this value, the thermodynamic efficiency of the heat exchanger should be increased. The exergy-based evaluation of the PRICO process shows that the most important component from the thermodynamic, economic and environmental points of view is the heat exchanger. Thermodynamically improving this component (decreasing the temperature differences during heat transfer and the pressure drops), would significantly improve the performance of the PRICO process. 5. Conclusions In this paper the PRICO process (operated with compressors driven by a gas-turbine system) for the liquefaction of natural gas has been evaluated using exergy-based analyses. The results obtained from these analyses confirmed that this process is, in general, well designed from the thermodynamic and economic points of view. Since all LNG processes are not only energy-intensive but also cost- and environmental-impact-intensive, the design of the heat exchanger should be a central focus of such LNG plants, especially the heat transfer characteristics. Despite the fact that the investment cost of the heat exchanger is relatively high due to the large heat transfer surface and to a complex and unique design, decreasing the inefficiencies within this component and accepting higher investment cost will finally lead to a decrease in the overall cost of the generated LNG. References Aspelund, A., Gundersen, T., Myklebust, J., Nowak, M.P., Tomasgard, A., 2010. An optimization-simulation model for a simple LNG process. Comput. Chem. Eng. 34, 1606e1617. Aspen Plus V7.1, 2011. The Software is a Proprietary Product of AspenTech. http:// www.aspentech.com. Bejan, A., Tsatsaronis, G., Moran, M., 1996. Thermal design and Optimization. Wiley, New York, NY. Black&Veatch, www.bv.com. Boyano, A., Blanco-Marigorta, A.M., Morosuk, T., Tsatsaronis, G., 2011. Exergoenvironmental analysis of a steam methane reforming process for hydrogen production. Energy Int. J. 36 (4), 2202e2214. Boyano, A., Morosuk, T., Blanco-Marigorta, A.M., Tsatsaronis, G., 2012. Conventional and advanced exergoenvironmental analysis of a steam methane reforming reactor for hydrogen production. J. Clean. Prod. 20, 152e160. Castillo, L., Dorao, C.A., 2012. Consensual decision-making model based on game theory for LNG processes. Energy Conv. Manag. 64, 387e396. Gas Turbine World, 2006. Handbook. Pequot Publishing Inc., USA. General Electric, Gas turbine catalog, www.ge.com. Goedkoop, M., Spriensma, R., 2000. The Eco-indicator 99: a Damage Oriented Method for Life Cycle Impact Assessment. Methodology Report. Amersfoort, Netherlands. http://www.pre.nl. Heldt, S., 2011. Near-optimal Operation of LNG Liquefaction Processes by Means of €t Berlin, Germany. Regulation. Ph.D. Thesis. Technische Universita Hiemann, A., 2011. Energy and Exergy Analysis of a Single Mixed Refrigerant Process for the Liquefaction of Natural Gas. Student Research Project. Technische Universit€ at Berlin, Germany. Jensen, J.B., Skogestad, S., 2009. Single cycle mixed-liquefied LNG process Part I: optimal design. In: Alfadala, H.E., Reklaitis, G.V., El-Halwagi, M.M. (Eds.), Proceedings of the 1st Annual Gas Processing Symposium. Elsevier, UK, pp. 211e218. Kakac, S., Hongtan, L., 1998. Heat Exchangers: Selection, Rating, and Thermal Design. CRC Press, Boca Raton. Khan, M.S., Lee, S., Lee, M., 2012. Optimization of single mixed refrigerant natural gas liquefaction plant with nonlinear programming. Asia-Pac J. Chem. Eng. 7, 62e70. Khan, M.S., Lee, S., Rangaiah, G.P., Lee, M., 2013. Knowledge based decision making method for the selection of mixed refrigerant systems for energy efficient LNG processes. Appl. Energy 111, 1018e1031. Lazzaretto, A., Tsatsaronis, G., 2006. SPECO: a systematic and general methodology for calculating efficiencies and costs in thermal systems. Energy Int. J. 31, 1257e1289. Lee, G., 2001. Optimal Design and Analysis of Refrigeration Systems for Low Temperature Processes. PhD Thesis. UMIST, Manchester, UK. Marmolejo-Correa, D., Gundersen, T., 2012. A comparison of exergy efficiency definitions with focus of low temperature process. Energy Int. J. 44, 477e489. Meyer, L., Tsatsaronis, G., Buchgeister, J., Schebek, L., 2009. Exergoenvironmental analysis for evaluation of the environmental impact of exergy conversion
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T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9 systems. Energy Int. J. 34, 75e89. Mokarizadeh Haghighi Shirazi, M., Mowla, D., 2010. Energy optimization for liquefaction process of natural gas in peak shaving plant. Energy Int. J. 35, 2878e2885. Mokhatab, S., Economides, M.J., 2006. Process selection is critical to onshore LNG economics. Glob. LNG Rep. 227 (2). Morin, A., Wahl, P.E., Mølnvik, M.J., 2011. Using evolutionary search to optimize the energy consumption for natural gas liquefaction. Chem. Eng. Res. Des. 89, 2428e2441. Morosuk, T., Tsatsaronis, G., 2005. Graphical models for splitting physical exergy. In: Kjelstrup, S., Hustad, J.E., Gundersen, T., Rosjorde, A., Tsatsaronis, G. (Eds.), Shaping Our Future Energy Systems, vol. 1, pp. 377e384. Morosuk, T., Tsatsaronis, G., 2012. 3-D exergy-based methods for improving energyconversion systems. Int. J. Thermodyn. 15 (4), 201e213. Morosuk, T., Tsatsaronis, G., Koroneos, C., 2012. On the effect of eco-indicator selection on the conclusions obtained from an exergoenvironmental analysis. In: Proceedings of ECOS 2012-the 25th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems June 26e29, 2012, Perugia, Italy. CD-ROM: 275-1 e; 275e13. Petrakopoulou, F., Boyano, A., Cabrera, M., Tsatsaronis, G., 2011. Exergoeconomic and exergoenvironmental analyses of a combined cycle power plant with chemical looping technology. Int. J. Greenh. Gas Control 5, 475e482. Remeljeja, C.W., Hoadley, A.F.A., 2006. An exergy analysis of small-scale liquefied natural gas (LNG) liquefaction processes. Energy Int. J. 31, 2005e2019.
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Roberts, M.J., Liu, Y.-N., Bronfenbrenner, J.C., Solomon, J., 2004. Hydrocarbon Engineering. May, pp. 81e84. Tsatsaronis, G., 1984. Combination of exergetic and economic analysis in energyconversion processes, energy economics and management in Industry. In: Proceedings of the European Congress, Algarve, Portugal, April 2e5, 1984, vol. 1. Pergamon Press, Oxford, England, pp. 151e157. Tsatsaronis, G., 2007. Definitions and nomenclature in exergy analysis and exergoeconomics. Energy Int. J. 32, 249e253. Tsatsaronis, G., Morosuk, T., 2008. A general exergy-based method for combining a cost analysis with an environmental impact analysis. In: Proceedings of the ASME International Mechanical Engineering Congress and Exposition, Boston, Massachusetts, USA, 2008 files IMECE2008e67218 and IMECE2008-67219. Tsatsaronis, G., Morosuk, T., 2012. Understanding and improving energy conversion systems with the aid of exergy-based methods. Int. J. Exergy 11, 518e542. Ulrich, G.D., Vasudevan, P.T., 2002. Chemical Engineering: Process Design and Economics. A Practical Guide. Process Publishing, Durham, Now Hampshire. Venkatarathnam, G., 2008. Cryogenic Mixed Refrigerant Processes. Springer. Wahl, P.E., Løvseth, S.W., Mølnvik, M.J., 2013. Optimization of a simple LNG process using sequential quadratic programming. Comput. Chem. Eng. 56, 27e36. Waren, D., Seider, J.D., Lewin, D.R., 2004. Product & Process Design Principles: Synthesis, Analysis and Evaluation, second ed. John Wiley. Xu, X., Liu, J., Jiang, C., Cao, L., 2013. The correlation between mixed refrigerant composition and ambient conditions in the PRICO LNG process. Appl. Energy 102, 1127e1136.
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Evaluation of the PRICO liquefaction process using exergy-based methods T. Morosuk*, S. Tesch, A. Hiemann, G. Tsatsaronis, N. Bin Omar €t Berlin, Marchstrasse 18, KT 1, TU Berlin, 10587 Berlin, Germany1 Institute for Energy Engineering, Technische Universita
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 October 2014 Received in revised form 5 February 2015 Accepted 7 February 2015 Available online xxx
The PRICO process is a single mixed-refrigerant process used for small-scale LNG plants, including offshore terminals. The working fluid (refrigerant) is a mixture of methane, ethane, butane and nitrogen. The behavior of the mixture in processes such as cooling, heating, compression, evaporation and condensation depends on its composition and on the part of the chemical constituents of the mixture that are in the gas and liquid phases. The state-of-the art for the evaluation and optimization of the PRICO process is discussed. Exergy-based analyses, i.e. exergetic, exergoeconomic and exergoenvironmental analyses, are applied to the evaluation of the PRICO liquefaction process of natural gas. The purpose of the paper is to identify options for improving the PRICO process and to demonstrate the application of exergy-based methods to the improvement of an LNG plant. The perspectives from the thermodynamic, economic and environmental impact points of view are discussed. © 2015 Elsevier B.V. All rights reserved.
Keywords: LNG PRICO process Exergy analysis Exergoeconomic analysis Exergoenvironmental analysis
1. Introduction Liquefaction of natural gas is the most energy-intensive and cost-intensive part of the overall chain “natural gas LNG e natural gas”. At the same time, liquefaction has also the largest potential for improvement. Therefore, different LNG production processes have been developed and are used in export terminals in many parts of the world. The PRICO process, which is one of them, is also known as a single mixed refrigerant (SMR) process. This process has been developed by the Black&Veatch Company, and the industrial applications of PRICO started in the year 1955, when it was applied to one of the first LNG plants. Three U.S./international patents cover the PRICO process. At present at least 21 LNG plants use this process while 16 more plants are in the design and/or construction phase. The PRICO process is popular for LNG peak-shaving units. In the year 2010, 25% of the LNG plants in the U.S. used this process. In the year 2012, design and construction for the world's first offshore LNG project started (Black&Veatch). The following advantages are associated with the PRICO process (Roberts et al., 2004):
* Corresponding author. E-mail addresses: [email protected] (T. Morosuk), [email protected]. de (S. Tesch), [email protected] (A. Hiemann), [email protected] (G. Tsatsaronis), [email protected] (N. Bin Omar). 1 URL: www.ebr.tu-berlin.de; www.energietechnik.tu-berlin.de.
Proven process that achieves the promised performance Relative simple operation Minimal refrigerant inventory Reduced number of equipment items Low capital cost and operating cost High flexibility High reliability Rapid startup
There are not many research publications dealing with liquefaction processes; however the PRICO (SMR) process recently became quite popular among researchers. Four processes for small-scale LNG plants were evaluated by Remeljeja and Hoadley, 2006. The PRICO process was selected there as a reference process. An exergy analysis was performed in a simple way and only relative data are given. The exergy destructions (thermodynamic inefficiencies) are distributed as follows: 21% within both compressors, 30% e within both coolers, 46% e within a heat exchanger, and 3% - within the throttling valve. The paper concluded that the SMR process has among all studied processes the lowest exergy consumption for the compressors, and that the main difference between the processes was caused by efficiency differences of the expander-driven compressors. Jensen and Skogestad, 2009 discussed eight compositions of the mixed refrigerant that can be used for the PRICO process; the effect of properties of the mixed refrigerant to the main characteristics of
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T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
the PRICO process were reported. The authors demonstrated that increasing the concentration of nitrogen within the mixed refrigerant leads to an improvement in the heat-transfer characteristics of all heat exchangers. An application of the gradient-free optimization-simulation method to processes modeled with the simulator Aspen HYSYS is reported by Aspelund et al., 2010. The PRICO process was selected as an academic example for the optimization for two reasons: Firstly this process is a simple LNG process with seven independent variables (selected by the authors). This number is too large for the optimization routine, but small enough to be optimized with an optimization-simulation tool. The second reason is that it is possible to verify the results by investigating the hot and cold composite curves. The paper focused on the number of iterations required to get an optimal concentration of the mixed refrigerant. Mokarizadeh Haghighi Shirazi and Mowla (2010) discussed the simulation of SMR concepts and the properties that are used in MATLAB to generate the objective function. A genetic algorithm was used for optimization. The energy consumption of the process was minimized. Depending on the concentration of the refrigerant, the specific energy consumption can be reduced from 1485 kJ/kgLNG to 1186.6 kJ/kgLNG or from 1126.7 kJ/kgLNG to 1092.4 kJ/kgLNG. The smaller values were taking from Lee, 2001 (as a reference publication). The authors applied also an exergy analysis, in order to calculate the values of the exergy destruction within the components: 31% within both compressors, 33% e within both coolers, 27% e within the heat exchanger, and 9% - within the throttling valve. Hiemann, 2011 conducted a detailed exergy analysis of the PRICO process. Here the approach “exergy of fuel/exergy of product” has been used taking into account a splitting of the physical exergy into thermal and mechanical parts. Marmolejo-Correa and Gundersen, 2012 selected the PRICO process as an academic example to demonstrate the effect of using different approaches in the exergy analysis (“inlet exergy/outlet exergy” versus “exergy of fuel/exergy of product” as well as splitting of the physical exergy into thermal and mechanical parts) on the obtained results. The authors assumed the operation conditions without necessarily a reference to real plants. Xu et al., 2013 reported the results of the optimization of the concentration of the refrigerant as a function of the inlet temperature to the heat exchanger (263.15 K through 313.15 K). For the optimization, a genetic algorithm coupled with the process simulation software Aspen Plus has been used. The results show that when the ambient temperature increases, the concentrations of methane, ethylene and propane should decrease, while the concentration of isopentane should increase. In this way the overall exergetic efficiency can be increased from 30% (calculated by the authors for the commercial concentration of the refrigerant) up to 39.6e42.3%. In this paper the exergetic efficiency is a function of COP and of a “correlation factor”. In a follow-up paper (Xu et al., 2013), the effect of concentration for each working fluid within the mixed refrigerant was investigated, in order to minimize the specific power consumption (the value of 1003.6 kJ/kgLNG was reached), i.e. maximize the values of COP and exergetic efficiency. The reported value of COP ¼ 0.782 is surprisingly high in comparison with results reported in other publications; however, the definition of COP is not given. The exergetic efficiency was calculated as 43.9%, which is in the range of other available data for the PRICO process. The distribution of the exergy destruction within the components is as follows: 36% within both compressors, 27% e within both coolers, 26% e within the heat exchanger, and 11% - within the throttling valve. Sequential quadratic programming was also applied to the optimization of the PRICO process (Morin A. et al., 2011). The research focused on the method used for optimization. The optimization results related to the liquefaction process itself were
discussed very briefly for the two study cases, in which the mixed refrigerant is with and without pentane. Through the energetic optimization, the specific energy supply decreases by 3.12%. Again the same optimization procedure for the PRICO process was reported by Wahl et al., 2013. The optimal composition of the mixed refrigerant was a function of the composition of natural gas (so called “lean natural gas” and “rich natural gas”). The heat-transfer characteristics for the multi-flow heat exchanger are also discussed. The main goal of the authors was to get the results of the optimization within a short period of execution time (5 min) in comparison with the optimization procedure discussed by Aspelund et al., 2010 that required 12 h. Castillo and Dorao, 2012, discussed economic issues related to LNG processes. They reported the application of Decision-Making (using a Genetic Algorithm binary coding and Nash-GA) for the PRICO process. The LNG markets were also implemented in the optimization of the PRICO process. Only relative economic data are reported, for example, the cost of the multi-flow heat exchanger is approximately 10e15% of the total investment cost and the cost associated with the compression process is always the dominating factor for all approaches used in the optimization. Khan et al., 2012 discussed the optimal composition of the mixed refrigerant for the SMR process from the energetic point of view, i.e. through the minimization of energy consumption for the compression process (from 1600 to 1528 kJ/kgLNG). The log mean temperature difference within multi-flow heat exchanger is 7.8 K. The SMR process was modeled in the UniSim Design simulator, and the model was optimized with nonlinear programming. The exergy analysis was implemented into the described optimization methodology (Khan et al., 2013) and more complex mixed refrigerant processes were optimized. Heldt, 2011 developed and tested a mathematical model for control strategies, in order for the SMR processes to operate at optimal conditions. High attention was given to the modeling of the multi-flow heat exchanger based on industrial experimental data. The literature review for the evaluation of the PRICO (SMR) process shows that mainly energetic optimizations were discussed using different methods for the mathematical optimization and corresponding algorithms. Sometimes the selected method for optimization and its improvement/robustness were more important to the authors that the obtained results related to the PRICO process. The objective function of the optimization refers mainly to the composition of the mixed refrigerant. An economic analysis is not very common for the evaluation of the PRICO liquefaction process, and environmental issues have not been discussed yet. The goal of this paper is to evaluate the PRICO process from the exergetic, economic, and environmental viewpoints for a given composition of the mixed refrigerant, in order to assist in developing an optimal strategy for designing and operating such a plant. 2. Exergy-based methods Exergy is defined as the maximum theoretical useful work (shaft work or electrical work) obtainable from an energy conversion system as this is brought into thermodynamic equilibrium with the thermodynamic environment while interacting only with this environment (Tsatsaronis, 2007). An exergetic analysis identifies the location, magnitude, and causes of thermodynamic inefficiencies, which are the exergy destruction (due to irreversibilities within each system component), and the exergy loss (exergy transfer to the environment). In an exergetic analysis, we calculate the exergy associated with each energy carrier (stream) in the overall system, the exergy destruction within each system component and process, and the exergetic efficiency (for each process, component, or system) (for example, Bejan et al., 1996).
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
Modern exergetic analyses use the concept of fuel and product introduced almost 30 years ago (Tsatsaronis, 1984) and generalized by Lazzaretto and Tsatsaronis, 2006: The exergy of product is the desired result (expressed in exergy terms) achieved by the system (e.g., the kth component) being considered, and the exergy of fuel represents the exergetic resources expended to generate the exergy of the product. These concepts are used in a consistent way in all exergy-based analyses (Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006; Meyer et al., 2009; Tsatsaronis and Morosuk, 2012) that include the exergoeconomic and the exergoenvironmental analyses. The exergy balance for the overall system (subscript tot) is
E_ F;tot ¼ E_ P;tot þ
X
E_ D;k þ E_ L;tot
(2)
where E_ F , E_ P , E_ D and E_ L are the exergy rates of fuel, product, destruction and losses, respectively. The variables used for the conventional exergetic evaluation of the kth component in a system include the following: Exergy destruction rate that is calculated from the exergy balance Exergetic efficiency
εk ¼
E_ P;k E_ D;k ¼1 E_ E_ F;k
(3)
F;k
Exergy destruction ratio
yk ¼
E_ D;k E_ F;tot
(4)
Exergoeconomic analysis (for example, Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006) is a unique combination of exergy analysis and cost analysis conducted at the component level, to provide the designer or operator of an energy conversion system with information crucial to the design or operation of a costeffective system. The same information cannot be provided by any other approaches. A complete exergoeconomic analysis consists of (a) an exergetic analysis, (b) an economic analysis, and (c) an exergoeconomic evaluation. The exergoeconomic model for an energy conversion system consists of cost balances written for the kth component, and of auxiliary equations based on the so-called F and P rules (Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006). The cost balances can be written as
C_ P;k ¼ C_ F;k þ Z_ k
(5a)
or
cP;k E_ P;k ¼ cF;k E_ F;k þ Z_ k where
C_ D;k ¼ cF;k $E_ D;k
(5b)
(7)
and for the overall system
C_ D;tot ¼ cF;tot $
and for the kth component (subscript k)
(6)
Here C_ P;k and C_ F;k are the cost rates associated with the exergy of product and fuel, respectively; cP,k and cF,k are the specific costs per unit of exergy associated with the exergy of product and fuel, respectively; Z_ k is the cost rate that represents the sum of the capital CI OM investment cost Z_ k and operating and maintenance expenses Z_ k . The cost rate associated with exergy destruction within the kth component is
(1)
k
E_ F;k ¼ E_ P;k þ E_ D;k
CI OM Z_ k ¼ Z_ k þ Z_ k
3
X
E_ D;k
(8)
An exergoeconomic evaluation is based on the following variables: C_ D;k , Z_ k , the sum ðC_ D;k þ Z_ k Þ, the relative cost difference rk, and the exergoeconomic factor fk
rk ¼
cP;k cF;k 1 εk Z_ k ¼ þ cF;k εk cF;k E_ P;k
fk ¼
Z_ k _ Z k þ C_ D;k
(9)
(10)
In an exergoenvironmental analysis (Meyer et al., 2009), the environmental impacts obtained by Life Cycle Assessment (LCA) are apportioned to the exergy streams and the exergy destruction streams, thus identifying the system components with the highest environmental impact and possible improvements associated with these components. Finally, exergoenvironmental variables are calculated, and an exergoenvironmental evaluation is carried out. Life cycle assessment is a technique for assessing the environmental aspects associated with a product over its life cycle. The LCA process consists of goal definition and scoping (defining the system under consideration), inventory analysis (identifying and quantifying the consumption and release of materials), and interpretation (evaluation of the results). Any of the recently introduced metrics (environmental indicators) can be used for LCA, for example, EcoIndicator 99 (Goedkoop and Spriensma, 2000). The exergoenvironmental model for an energy conversion system consists of environmental impact balances written for the kth component and auxiliary equations based on the F and P rules. The environmental impact balances can be written as
PF B_ P;k ¼ B_ F;k þ Y_ k þ B_ k
(11a)
or
PF bP;k E_ P;k ¼ bF;k E_ F;k þ Y_ k þ B_ k
(11b)
Here B_ P;k and B_ F;k are the environmental impact rates associated with the exergy of product and fuel, respectively; cP,k and cF,k are the specific environmental impacts per unit of exergy associated with CO the exergy of product and fuel, respectively; construction, Y_ k , OM DI operation & maintenance, Y_ k , and disposal, Y_ k constitute the component-related environmental impact associated with the kth component Y_ k : CO OM DI Y_ k ¼ Y_ k þ Y_ k þ Y_ k
(12)
To simplify the discussion, we assume that the value of Y_ k is CO mainly associated with Y_ k
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4
T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
To account for pollutant formation within the k th component, PF PF the variable B_ k is used (Boyano et al., 2012). The term B_ k is zero when no pollutants are formed within a process, i.e. for processes without a chemical reaction such as compression, expansion, heat transfer, etc. The environmental impact associated with the exergy destruction within the kth component B_ D;k is given by
B_ D;k ¼ bF;k E_ D;k
(13)
and within the overall system by
B_ D;tot ¼ bF;tot $
X
E_ D;k
(14)
To identify the most important components from the viewpoint of formation of environmental impacts, the sum of environmental PF impacts ðY_ k þ B_ k þ B_ D;k Þ is used together with two other variables in analogy with the exergoeconomic analysis, i.e. the relative difference
rb;k ¼
bP;k bF;k bF;k
(15)
Y_ k PF Y_ k þ B_ k þ B_ D;k
The simulation data are given in Tables 2 and 3. The purpose of this paper is to evaluate the PRICO process, therefore the drivers for the compressors have not been considered in the simulation, and the energy and exergy analyses. 3.1. Energy and exergy analyses The results obtained from the energy analysis include the following: The power required for the compressors is _ _ W ¼ 44:70 MW and W ¼ 46:51 MW. In the case of oneCM1
and the exergoenvironmental factor
fb;k ¼
Inlet characteristics of natural gas: T8 ¼ 38 С and p8 ¼ 67 bar (Venkatarathnam, 2008) The pressure drop within the heat exchanger is 3 bar for all three streams The minimum temperature difference within the cooler and the condenser is 3 K The isentropic efficiency for both compressors is assumed to be equal to 80% The compositions of refrigerant and natural gas are given in Table 1. Note that n- butane is lumped with butane.
(16)
However, the application of the exergoenvironmental analysis to different energy conversion processes (for example, Meyer et al., 2009; Boyano et al., 2011, 2012; Tsatsaronis and Morosuk, 2012; Morosuk et al., 2012) demonstrated that the value of environmental impact associated with the exergy destruction B_ D;k is always much higher than the component-related environmental impact Y_ k PF (if the value of B_ is not considered for the k th component). In this k
way, and for simplifying the analysis without affecting the conclusions, Y_ k can be neglected; then, fb,k is not used. These methods were used to evaluate power plants (for example, Tsatsaronis and Morosuk, 2008, 2012; Petrakopoulou at el. 2011), refrigeration processes (for example, Morosuk and Tsatsaronis, 2012) and chemical processes (for example, Meyer et al., 2009; Boyano et al., 2011, 2012). 3. PRICO process The flow diagram of the PRICO (SMR) process is shown in Fig. 1. The working fluid (refrigerant) is a mixture of methane, ethane, butane and nitrogen (Table 1). The refrigerant is compressed from state 1 to state 4 using a two-stage compression process (CM1 and CM2) with interstage cooling (COL), and is subsequently condensed (CD). The heat exchanger HE is a three-flow heat exchanger, where the stream 5-6 of refrigerant is cooled down, while the stream 7-1 of refrigerant is vaporized, and the stream 8-9 of natural gas is cooled and liquefied. In general, due to the relative small pressure ratio, a single-stage compression process could be sufficient. However, a two-stage compression process with interstage cooling is more appropriate, in order to decrease the total power required for the compressors. For the simulation of the PRICO process the software Aspen Plus (2011) was used, and the PengeRobinson equation of state was selected. This approach can handle any combination of nonpolar or mildly polar mixtures; examples are hydrocarbons and light gases. The following assumptions were used for the simulation: The ambient temperature is 25 C, and the ambient pressure is 1.013 bar
CM2
stage compression process, additional 5.6 MW would be required. The heat rates transferred to the environment are ¼ 36:38 MW and Q_ ¼ 93:57 MW. The heat rate within the Q_ COL
CD
heat exchanger is Q_ HE ¼ 336:95 MW. The T DH_ diagram for the heat exchanger is shown in Fig. 2. The log-mean temperature difference within the exchanger is equal to 7 K. The coefficient of performance of the PRICO process defined by _ _ COP ¼ ðH_ H_ Þ=ðW þW Þ is equal to 0.44 under the 8
9
CM1
CM2
assumed operation conditions and concentration of the refrigerant, whereas the specific energy consumption amounts to 1824 kJ/ kgLNG. The exergetic analysis was conducted using the approach “exergy of fuel/exergy of product” (Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006). The physical exergy of the material streams in the PRICO process must be split into thermal and mechanical parts (Morosuk and Tsatsaronis, 2005) for processes below the ambient temperature and every time this temperature is crossed. The reference values for the exergetic analysis (state 0) for each material stream are given in Table 2. The exergy of fuel and exergy of product for each system component are defined as follows: Compressor 1 (CM 1)
M _ _T _ _ M þ E_ T _ E_ F;CM1 ¼ W CM1 þ E1 and EP;CM1 ¼ E 2 E1 2 Cooler (COL) is a dissipative component (Bejan et al., 1996; Lazzaretto and Tsatsaronis, 2006), therefore E_ D;COL ¼ E_ 2 E_ 3 Compressor 2 (CM 2)
_ _ _ _ E_ F;CM2 ¼ W CM2 and EP;CM2 ¼ E 4 E3 Condenser (CD) is a dissipative component, E_ D;CD ¼ E_ 4 E_ 5 Heat exchanger (HE)
M M M T T M M M E_ F;HE ¼ E_ 7 E_ 1 þ E_ 7 E_ 1 þ E_ 8 E_ 9 þ E_ 5 E_ 6 T T þ E_ 5 þ E_ 8 and E_ P;HE T ¼ E6T þ E_ 9
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
5
Fig. 1. Flow diagram of the PRICO process: CM 1 e Compressor 1; COL e Cooler; CM 2 e Compressor 2; CD e Condenser; HE e Heat exchanger; TV e Throttling Valve.
Table 1 Compositions of natural gas and refrigerant. Component
Formula
Refrigerant (% mol)a
Natural gasb (% mol)
Methane Ethane Propane Butane Nitrogen
CH4 C2H6 C3H8 C4H10 N2
0.30 0.30 e 0.25 0.15
0.88 0.08 0.02 e 0.02
a b
Table 3 Detailed thermodynamic data of each chemical component in the streams within mixed refrigerant. Stream
1
2
3
4
5
6
7
8
9
0.148 0.277 0.000 0.446 0.129
0.148 0.277 0.000 0.446 0.129
0.144 0.249 0.000 0.224 0.128
e e e e e
0.003 0.000 0.000 0.000 0.057
0.786 0.134 0.049 0.000 0.031
e e e e e
e e e e e
e e e e e
0.004 0.028 0.000 0.222 0.001
0.148 0.277 0.000 0.446 0.129
0.145 0.277 0.000 0.446 0.072
e e e e e
0.786 0.134 0.049 0.000 0.031
2.40 2.40 e 2.00 1.20
6.60 6.60 e 5.50 3.30
7.69 7.10 e 3.31 3.91
e e e e e
0.43 0.00 e 0.00 5.57
58.96 5.36 1.34 e 1.34
e e e e e
Mass fraction (kg/kg) Vapor Methane 0.148 0.148 Ethane 0.277 0.277 Propane 0.000 0.000 Butane 0.446 0.446 Nitrogen 0.129 0.129 Liquid Methane e e Ethane e e Propane e e Butane e e Nitrogen e e Partial pressure (bar) Methane 0.90 2.40 Ethane 0.90 2.40 Propane e e Butane 0.75 2.00 Nitrogen 0.45 1.20
Jensen and Skogestad, 2009. Mokhatab and Economides, 2006.
Throttling valve (TV)
M M T T E_ F;TV ¼ E_ 6 E_ 7 and E_ P;TV ¼ E_ 7 E_ 6
Overall system (without considering the drivers for the compressors)
M _ _ _ _M _T _T _ E_ F;tot ¼ W CM1 þ W CM2 þ E8 E 9 ; and EP;tot ¼ E9 E8
example, Bejan et al., 1996). For the economic analysis the bare module cost for each component was estimated, and the remaining cost contributors are calculated based on these values (Table 5). Since the location of the evaluated LNG plant is unknown, office costs were not taken into consideration. Because no economic data for the PRICO process are available in the open sources and because cost estimation data for the lowtemperature and cryogenic equipment is not reported in detail in the literature, as it is the case for chemical and power plants, the bare module cost for each component of the PRICO process was
The results obtained from the exergetic analysis are shown in Table 4. 3.2. Economic analysis An economic analysis of the PRICO process was carried out based on the Total Revenue Requirement (TRR) method (for
Table 2 Thermodynamic, exergetic, cost and environmental impact data for the material streams. Stream Material stream Thermodynamic data m_
1 2 3 4 5 6 7 0a 8 9 0a a
Refrigerant
p
x
(Kg/s) (ºC)
(Bar)
(Kg/kg) (kJ/kg)
475
3 8 8 22 22 19 6 1.013 67 64 1.013
e e e e 0.84 0 0.07
Natural gas 50
T
Exergetic analysis
15 71 30 91 30 159 162 25 38 159 25
e 0
h
s
T
e
M
e
Exergoeconomic analysis PH
e
T
c
(kJ/kg K) (kJ/kg) (kJ/kg) (kJ/kg) ($/GJ)
2446 5.16 2352 5.10 2429 5.34 2331 5.28 2532 5.90 3156 8.94 3156 8.92 2426 4.81 4188 6.83 4998 10.92 4141 4.81
0.3 6.1 0.1 16.8 0.2 291.2 362.3
81.5 153.3 153.3 218.2 218.2 210.0 132.5
81.8 159.4 153.4 235.0 218.4 501.2 494.8
50.07 18.06 18.06 17.67 17.67 57.49 50.07
0.7 417.0
555.1 549.7
555.8 966.7
0 57.49
M
Exergoenvironmental analysis
c
c
bT
bM
bPH
($/GJ)
($/GJ)
(Pts/GJ)
(Pts/GJ)
(Pts/GJ)
17.87 17.96 17.96 17.87 17.87 17.87 17.87
67.94 36.02 36.02 35.54 35.54 75.36 67.94
39.06 14.54 14.54 14.29 14.29 44.76 39.06
14.42 14.48 14.48 14.42 14.42 14.42 14.42
53.48 29.01 29.01 28.71 28.71 59.18 53.48
0 57.49
3.75 44.76
3.75 3.75
7.51 48.52
0 0
PH
Reference state for the exergetic analysis.
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
6
T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9 Table 5 Estimation of the fixed-capital investment (in mil US$ for the year 2014). Direct costs (DC)
Onsite costs (bare module cost, CBM) Compressor CM1 Compressor CM2 Cooler Condenser Heat exchanger Throttling valve Offsite costs
Total direct costs Indirect costs (IC)
Engineering and supervision (8% of DC) Construction costs (15% of DC) Contingencies (15% of the sum DC and ID) Total indirect costs Fixed-capital investment
Fig. 2. T DH_ diagram for the heat exchanger.
pressure factors were assumed to be equal to one. However, for the intensification of heat-transfer characteristics, the material of tube is assumed to be brass (material of shell is carbon steel). Therefore the material factor is 2.4. The bare module factor is equal to 3.17. The heat exchanger is a three-flow, low temperature heat exchanger. Such a heat exchanger is considered as quite challenging due to its special design. Only few companies in the world produce such heat exchangers for LNG applications; therefore the data required for the economic analysis are confidential and not available in the open literature. The overall heat transfer coefficient was estimated as UHE ¼ 2000 W/m2K (Kakac and Hongtan, 1998), therefore ACOL ¼ 3865 m2. For the economic analysis, the data reported by Ulrich and Vasudevan, 2002 were used with the following adjustments corresponding to the low-temperature operation conditions: fm ¼ 2.3 and fT ¼ 1.5. The bare module factor is equal to 3.5. A simple throttling valve used for the simulation, represents in reality a throttling valve station (many throttling valves with corresponding safety/control equipment, used in parallel).
estimated using the following equation:
CBM;k ¼ CM;k fd fm fT fp fBM;k
87.6 39.3 40.5 1.7 1.4 3.9 0.8 0 87.6 7.0 13.1 16.1 36.2 123.8
(17)
where CBM,k bare module cost of the k th component, CM module cost of the k th component, fd e design-type factor, fm e material factor, fT e temperature factor, fp e pressure factor, and fBM e bare module factor of the k th component. The term CM fd fm fT fp is the purchased-equipment cost. Data from the chemical industry were used to calculate the bare module cost and the factors. The following assumptions were made and results were obtained for the economic analysis: Centrifugal type of turbo compressors was selected. The information from Waren et al., 2004 was used for the economic analysis of the compressors. For the estimation of the module _ ) is used as a sizing factor. cost, the net required power (W k Based on the data given for the year 2004, the recalculated specific cost is 878 US$2014/kW. Since the operation conditions for the two compressors are in the range of regular application, the design-type, material, temperature and pressure factors were assumed to be equal to one. The bare module factor is equal to 2.15. The cooler and condenser were assumed to be shell-and-tube heat exchangers. The UA values of the cooler and condenser were obtained from the Aspen PLUS simulation software and the overall heat transfer coefficients (U) were taken from Kakac and Hongtan, 1998, i.e., UCOL ¼ 500 W/m2K and UCD ¼ 1000 W/ m2K. Finally, the heat transfer surfaces amount to ACOL ¼ 2600 m2 and ACD ¼ 2198 m2. For the economic analysis, the data reported by Waren et al., 2004 were used. Since the operation conditions for the cooler and condenser are also in the range of regular application, the design-type, temperature, and
Based on the estimated fixed-capital investment and the assumptions for the economic, financial, operating, and market input variables, the total revenue requirement is calculated. The nonuniform annual monetary values associated with the investment (carrying charges, CC), operation & maintenance (OMC), and fuel costs (FC) of the system being analyzed are levelized, that is they are converted into an equivalent series of constant payments (annuities). The levelized carrying charges are calculated as
CCL ¼ ðTotal Capital InvestmentÞ CRF
(18)
where the capital-recovery factor (CRF) (Bejan et al., 1996) is given by
Table 4 Results obtained from the exergetic, exergoeconomic and exergoenvironmental analyses. Component
CM1 COL CM2 CD HE TV Overall system
Exergetic analysis
Exergoeconomic analysis
Exergoenvironmental analysis
E_ F;k
E_ P;k
E_ D;k
εk
yk
cF,k
cP,k
Z_ k
C_ D;k
Z_ k þ C_ D;k
r
f
bF,k
bP,k
B_ D;k
rb
(MW)
(MW)
(MW)
(%)
(%)
($/GJ)
($/GJ)
($/h)
($/h)
($/h)
(%)
(%)
(mPts/GJ)
(mPts/GJ)
(mPts/h)
(%)
44.84 e 46.51 e 200.50 36.77 91.48
37.00 e 38.83 e 159.20 33.73 20.82
7.84 2.86 7.71 7.89 41.31 3.04 70.66
82.5 e 83.5 e 79.4 91.7 22.7
8.6 3.1 8.5 8.6 45.1 3.3 77.2
31.99 97.28 31.67 96.17 120.42 48.32 31.58
48.76 e 47.84 e 151.89 52.89 178.35
1330 56 1373 48 131 26 2965
188 370 182 1009 6759 196 1654
1518 426 1555 1057 6890 222 4619
171.1 e 170.9 e 26.4 10.2 948.1
87.6 13.3 88.3 4.6 1.9 11.8 64.2
12.00 384.63 11.91 204.02 35.54 14.42 11.89
14.54 e 14.29 e 55.82 15.72 52.24
338 3946 332 5791 5284 158 3024
21.2 e 20.0 e 57.1 9.0 339.5
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
n ieff 1 þ ieff CRF ¼ n 1 þ ieff 1
(19)
Here ieff is the average annual effective discount rate (cost of money), and n denotes the plant economic life expressed in years. For the fuel we calculate the constant escalation levelization factor (CELF).
FCL ¼ FC0 CELF ¼ FC0
kFC 1 knFC CRF ð1 kFC Þ
kOMC 1 knOMC CRF OMCL ¼ OMC0 CELF ¼ OMC0 ð1 kOMC Þ
TRRL ¼ CCL þ FCL þ OMCL
(21)
(22)
The LNG plant operates with a 100% capacity during 7446 h per year (capacity factor ¼ 85%) The average cost of money is ieff ¼ 10%. The plant economic life is n ¼ 20 years. The average general inflation rate is rn ¼ 2.5% The operating and maintenance costs are assumed to be 4% of the CC.
3.3. Exergoeconomic analysis An exergoeconomic analysis is based on cost balances written for the k th component and auxiliary costing equations (if required): T M M T Compressor 1: C_ 1 þ C_ W;CM1 þ Z_ CM1 ¼ C_ 2 C_ 1 þ C_ 2 and one auxiliary costing equation according to the P-rule, M M M M cT2 ðC_ 2 C_ 1 Þ=ðE_ 2 E_ 1 Þ M M T T Compressor 2: C_ W;CM2 þ Z_ CM2 ¼ C_ 4 C_ 3 þ C_ 4 C_ 3 , and according to the P rule M M T T M M T T ðC_ C_ Þ=ðE_ E_ Þ ðC_ C_ Þ=ðE_ E_ Þ. The values of 3
4
3
4
3
2
COL
3
Diff;COL
T T M M condenser is C_ 4 C_ 5 þ C_ 4 C_ 5 þ Z_ CD ¼ C_ Diff ;CD with the asM _ sumptions cT4 ¼ cT5 and cM 4 ¼ c5 . The values of C Diff;COL and _ are considered in the calculation of the cost associated C
with the product of the overall system. The cost rates associated with the exergy of fuel and the exergy of product for the overall system are T T C_ P ¼ C_ 9 C_ 8 þ C_ Diff;CD þ C_ Diff;COL and C_ F M
The following assumptions have been made for the economic analysis:
4
2
M sumptions cT2 ¼ cT3 and cM 2 ¼ c3 , and the cost balance for the
M
¼ C_ W;CM1 þ C_ W;CM2 þ C_ 8 C_ 9 respectively:
with kOMC ¼ 1 þ rOMC =1 þ ieff and rOMC ¼ const, where rOMC is the average annual nominal escalation rate for the operating and maintenance costs. Finally, the levelized total revenue requirement (TRRL) is obtained from
3
Cooler and condenser are dissipative components, therefore the cost balances should be written in a different way taking into account that the specific cost of each stream passed through these components remains constant, i.e. the cost balance for the T T M M cooler is C_ C_ þ C_ C_ þ Z_ ¼ C_ with the as-
Diff;CD
(20)
with kFC ¼ 1 þ rFC =1 þ ieff and rFC ¼ const. The term rFC denotes the average annual nominal escalation rate for fuel cost. The levelized annual operating and maintenance costs OMCL are given by
4
7
3
_ C_ W;CM1 and C_ W;CM2 are calculated as C_ W;CM1 ¼ W CM1 cW and _ _ C W;CM2 ¼ W CM2 cW , respectively
T M M M M M M Heat Exchanger: C_ 5 þ C_ 8 C_ 9 þ C_ 5 C_ 6 þ C_ 7 C_ 1 þ T T T T T T T T C_ 7 C_ 1 þ Z_ HE ¼ C_ 9 þ C_ 6 , according to the P-rule C_ 9 =E_ 9 ¼ C_ 6 =E_ 6 M M M M M , and according to the F rule: cM 8 ¼ c9 , c5 ¼ c6 , c7 ¼ c1 and
cT7 ¼ cT1 . M M T T Throttling Valve: C_ 6 C_ 7 þ Z_ TV ¼ C_ 7 C_ 6 , according to the F M M rule, c6 ¼ c7
The value of cW was calculated using the cost balance applied to the overall open-cycle gas-turbine system LM 6000 used as a driver for both compressors: C_ fuel þ Z_ GT ¼ C_ W . Based on data reported by General Electric for the LM 6000 system (Gas Turbine World, 2006), the following initial data were obtained, and the corresponding results were calculated: The overall energetic efficiency of the LM 6000 system is equal to 44.5%; therefore the fuel (natural gas) consumption is calculated as 4.43 kg/s; The specific investment cost of the gas-turbine system for the year 2010 was estimated as 296 US$/kW, which leads to the value of Z_ GT ¼ 1073 $/h. Assuming that the price of natural gas is 4.5 US$/GJLHV, the specific cost of power supplied from the driver to both compressors is calculated as cW ¼ 14.37 $/GJ. Tables 2 and 4 show the results obtained from the exergoeconomic analysis.
3.4. Exergoenvironmental analysis An exergoenvironmental analysis is based on environmental impact balances written for the k th component and auxiliary equations (if required). The environmental impact balances are formulated in analogy to the cost balances written for the corresponding exergoeconomic analysis. For the evaluation of the PRICO process, we assumed that the component-related environmental impact can be neglected (Yk¼0), therefore no component-related LCA was conducted. The Eco-Indicator 99 was applied. Note that for the exergoenvironmental analysis of the PRICO process with compressors driven by a gas-turbine power system, two different values of the environmental impact associated with natural gas were used: For natural gas that should be liquefied (stream 8), Pts ¼ 3:90 Pts , and bCH4 ¼ 0:14 Nm 3 GJLHV For natural gas that is used in a gas-turbine system (driver), bCH4 ¼ 5:30 GJPts . This value is higher than the first one because it LHV includes the generation of pollutants during the combustion process. Charging the potential pollutants to the fuel is an approach that simplifies the analysis because there is then no PF need to calculate the value of B_ k for Eq. (11). For the calculation of the environmental impact associated with the power supplied to the compressors, an analogous methodology to the
Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007
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T. Morosuk et al. / Journal of Natural Gas Science and Engineering xxx (2015) 1e9
exergoeconomic analysis was applied. Finally the environmental impact associated with the power for the compressors is bW ¼ 11.91 Pts/GJ. Tables 2 and 4 show the results obtained from the exergoenvironmental analysis. 4. Results and discussions The values of COP ¼ 0.44 and specific energy consumption of 1824 kJ/kgLNG are relatively low compared to the corresponding ones from the publications mentioned in the introduction. The value of the exergetic efficiency of 22.7% cannot be compared with the data reported by others because, as it was already noted, the exergy analysis was conducted in terms of “exergy of fuel/exergy of product” and not of “inlet/outlet exergy” as used by other authors. However, the distribution of the exergy destruction among the components (Table 4) has a good correlation with the earlier reported results (Mokarizadeh Haghighi Shirazi and Mowla, 2010; Xu et al., 2013): 22% associated with the compression process (E_ D;CM1 þ E_ D;CM2 ¼ 15:55 MW); 15% associated with the cooler and condenser (E_ D;COL þ E_ D;CD ¼ 10:75 MW) e within both coolers, 58% e within the heat exchanger (E_ D;HE ¼ 41:31 MW), and 5.7% - within the throttling valve (E_ D;TV ¼ 3:04 MW). The rate of exergy destruction within the heat exchanger (yHE) shows that 45% of the exergy of the fuel supplied to the overall system is destroyed through the inefficiencies within this component. The exergetic efficiency for each of the productive components (compressors, heat exchanger and throttling valve) is high (in the range of 80e90%). This means that the evaluated PRICO system has a relatively low potential of efficiency improvement as long as the composition of the mixed refrigerant remains unchanged. The economic analysis (Tables 4 and 5) shows that 91% of the total capital investment associated with the two compressors (that is fully confirmed by data reported by Castillo and Dorao, 2012.), 5% with the heat exchanger, 3% with the cooler and condenser and 1% with the throttling valve. If cost optimization would be based on the investment costs, then the conclusion is obvious: a reduction in the cost of both compressors will significantly reduce the total cost of the PRICO plant. Let us discuss the conclusions that have been obtained from the exergoeconomic analysis (Table 4). The value of the exergoeconomic factor (64.2%) for the overall system demonstrates (based on recommendation from Bejan et al., 1996), that the analyzed PRICO process has no design error from the cost point of view. The component-by-component analyses show, that the value of the total cost associated with the component, i.e., the sum ðC_ D;k þ Z_ k Þ, is the highest for the heat exchanger because of the cost of the exergy destruction within this component. The very low value of the exergoeconomic factor (fHE ¼ 1:9%) suggests the direction for cost improvement: The heat exchanger should be improved from the thermodynamic point of view, i.e. the exergy destruction should be reduced, and the exergetic efficiency increased. This will lead to a decrease in the cost of the exergy destruction. At the same time, the capital investment cost of this component will increase. However, the cost of the final product will definitely decrease. Both compressors have the highest capital investment cost but very low cost associated with the exergy destruction. The high value of the exergoeconomic factor (around 88%) for the compressors indicates that the overall LNG cost could be reduced if less expensive compressors would be used, even if these would have a lower efficiency. The data obtained from the exergoenvironmental analysis demonstrate that the highest environmental impact is associated with the exergy destruction within the heat exchanger. In order to
reduce this value, the thermodynamic efficiency of the heat exchanger should be increased. The exergy-based evaluation of the PRICO process shows that the most important component from the thermodynamic, economic and environmental points of view is the heat exchanger. Thermodynamically improving this component (decreasing the temperature differences during heat transfer and the pressure drops), would significantly improve the performance of the PRICO process. 5. Conclusions In this paper the PRICO process (operated with compressors driven by a gas-turbine system) for the liquefaction of natural gas has been evaluated using exergy-based analyses. The results obtained from these analyses confirmed that this process is, in general, well designed from the thermodynamic and economic points of view. Since all LNG processes are not only energy-intensive but also cost- and environmental-impact-intensive, the design of the heat exchanger should be a central focus of such LNG plants, especially the heat transfer characteristics. Despite the fact that the investment cost of the heat exchanger is relatively high due to the large heat transfer surface and to a complex and unique design, decreasing the inefficiencies within this component and accepting higher investment cost will finally lead to a decrease in the overall cost of the generated LNG. References Aspelund, A., Gundersen, T., Myklebust, J., Nowak, M.P., Tomasgard, A., 2010. An optimization-simulation model for a simple LNG process. Comput. Chem. Eng. 34, 1606e1617. Aspen Plus V7.1, 2011. The Software is a Proprietary Product of AspenTech. http:// www.aspentech.com. Bejan, A., Tsatsaronis, G., Moran, M., 1996. Thermal design and Optimization. Wiley, New York, NY. Black&Veatch, www.bv.com. Boyano, A., Blanco-Marigorta, A.M., Morosuk, T., Tsatsaronis, G., 2011. Exergoenvironmental analysis of a steam methane reforming process for hydrogen production. Energy Int. J. 36 (4), 2202e2214. Boyano, A., Morosuk, T., Blanco-Marigorta, A.M., Tsatsaronis, G., 2012. Conventional and advanced exergoenvironmental analysis of a steam methane reforming reactor for hydrogen production. J. Clean. Prod. 20, 152e160. Castillo, L., Dorao, C.A., 2012. Consensual decision-making model based on game theory for LNG processes. Energy Conv. Manag. 64, 387e396. Gas Turbine World, 2006. Handbook. Pequot Publishing Inc., USA. General Electric, Gas turbine catalog, www.ge.com. Goedkoop, M., Spriensma, R., 2000. The Eco-indicator 99: a Damage Oriented Method for Life Cycle Impact Assessment. Methodology Report. Amersfoort, Netherlands. http://www.pre.nl. Heldt, S., 2011. Near-optimal Operation of LNG Liquefaction Processes by Means of €t Berlin, Germany. Regulation. Ph.D. Thesis. Technische Universita Hiemann, A., 2011. Energy and Exergy Analysis of a Single Mixed Refrigerant Process for the Liquefaction of Natural Gas. Student Research Project. Technische Universit€ at Berlin, Germany. Jensen, J.B., Skogestad, S., 2009. Single cycle mixed-liquefied LNG process Part I: optimal design. In: Alfadala, H.E., Reklaitis, G.V., El-Halwagi, M.M. (Eds.), Proceedings of the 1st Annual Gas Processing Symposium. Elsevier, UK, pp. 211e218. Kakac, S., Hongtan, L., 1998. Heat Exchangers: Selection, Rating, and Thermal Design. CRC Press, Boca Raton. Khan, M.S., Lee, S., Lee, M., 2012. Optimization of single mixed refrigerant natural gas liquefaction plant with nonlinear programming. Asia-Pac J. Chem. Eng. 7, 62e70. Khan, M.S., Lee, S., Rangaiah, G.P., Lee, M., 2013. Knowledge based decision making method for the selection of mixed refrigerant systems for energy efficient LNG processes. Appl. Energy 111, 1018e1031. Lazzaretto, A., Tsatsaronis, G., 2006. SPECO: a systematic and general methodology for calculating efficiencies and costs in thermal systems. Energy Int. J. 31, 1257e1289. Lee, G., 2001. Optimal Design and Analysis of Refrigeration Systems for Low Temperature Processes. PhD Thesis. UMIST, Manchester, UK. Marmolejo-Correa, D., Gundersen, T., 2012. A comparison of exergy efficiency definitions with focus of low temperature process. Energy Int. J. 44, 477e489. Meyer, L., Tsatsaronis, G., Buchgeister, J., Schebek, L., 2009. Exergoenvironmental analysis for evaluation of the environmental impact of exergy conversion
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Please cite this article in press as: Morosuk, T., et al., Evaluation of the PRICO liquefaction process using exergy-based methods, Journal of Natural Gas Science and Engineering (2015), http://dx.doi.org/10.1016/j.jngse.2015.02.007