Article pubs.acs.org/IECR
Technoeconomic Feasibility Study of Monoethanolamine-Based CO2 Capture System Deployment to be Retrofitted to an Existing Utility System in a Chemical Plant Heewon Hwang,† Jee-Hoon Han,*,‡ and In-Beum Lee†,§ †
Department of Chemical Engineering, POSTECH, Pohang, Korea 780-784 Department of Chemical and Biological Engineering, University of Wisconsin−Madison, Madison, Wisconsin 53706, United States § Graduate School of Engineering Mastership, POSTECH, Pohang, Korea 780-784 ‡
S Supporting Information *
ABSTRACT: Most chemical plants have their own utility systems (UtSys) to produce utilities (e.g., steam, electricity, water) required for manufacturing chemical products, and the UtSy discharges a considerable amount of flue gases. A monoethanolamine (MEA) based CO2 capture system (CCSy) is a promising solution to separate CO2 from the flue gases, but it can lead to a loss in utility generation by the UtSy, because of utility requirements for recovering the MEA solvent. A technoeconomic feasibility study to deploy CCSy at an existing UtSy as an integrated process should be performed for chemical plants. Thus, we design three process integration configurations to combine the UtSy and CCSy and then develop each process optimization model. Lastly, our technoeconomic analysis determines the one among three configurations that minimizes the total cost of configurations.
1. INTRODUCTION Most chemical plants use utilities (e.g., electricity, steam, water, and air) to produce their chemical products. The utility requirements of a chemical plant can be satisfied by its own utility system (UtSy), which consists of equipment such as boilers, gas turbines, steam turbines, deaerators, pumps, and heat exchangers.1 This equipment can usually be combined in many feasible configurations that can supply the required utilities.1 For example, boilers can generate heat (steam) by burning fossil fuels, which contribute significantly to operating cost of the UtSy.2 Gas turbines can produce electricity, and hot exhaust gases are passed to boilers to be used as preheated air and consequently to reduce fuel consumption in the boiler.1 Several studies have considered how to identify minimum-cost UtSy configurations and how to determine operating conditions (e.g., temperature, pressure, and flow rate) of UtSy equipment that satisfy the required utility demand.1,3−12 Levels of CO2 emissions are highly correlated with levels of fuel use, especially in electricity and heat generation within the UtSy.13,14 Most research focuses on optimal design and technoeconomic performance analysis of monoethanolamine (MEA)-based CO2 capture systems (CCSys) for removing CO2 from exhaust flue gases of fossil-fuel power plants.15,16 The CCSy consists of equipment such as an absorber, a regenerator, heat exchangers, and compressors.17 Running this equipment requires a considerable amount of utilities, especially steam for releasing CO2 and recovering the MEA solvent in the regenerator, and these utilities contribute significantly to operating cost of the CCSy.17 The equipment of CCSy can be combined with the equipment of UtSy in many feasible configurations that can reduce the utility requirements for removing CO2 from exhaust flue gases of UtSy. Despite the large number of optimal designs for individual UtSy and CCSy or heat integration studies for © 2013 American Chemical Society
different industrial energy systems utilizing waste heat that have been presented in the literature,18−22 few studies have been conducted to (1) develop an integrated design of UtSy and CCSy with (2) a simultaneous technoeconomic performance analysis and comparison of various system configurations. Accordingly, the aim of this paper is to accomplish these goals. In section 2, we present a broad overview of the technologies to develop the integrated process design of UtSy and CCSy. In section 3, we design three process configurations and develop each process simulation model. In section 4, we present an optimization of each configuration and an economic evaluation of configurations. Thus, we can suggest the best process integration design of an existing utility system in a chemical plant to be retrofitted with an MEA-based CO2 capture system.
2. TECHNOLOGY OVERVIEW AND RESEARCH BACKGROUND Our strategy combines two subsystems for (1) flue gas emission as well as utility generation from fossil fuels in a UtSy1 and (2) separation of CO2 from flue gas in a CCSy.17 Papoulias and Grossmann1 developed an optimal UtSy (Figure 1). A gas turbine uses fossil fuels and air to produce electricity required for a chemical plant. The hot air discharged from the gas turbine is used to convert pressurized water to high pressure steam in a boiler with an additional use of fossil fuels. A portion of the high pressure steam is distributed to meet the chemical plant’s requirements, and the remaining steam can be converted to lower pressure steam (medium or low pressure steam) through a steam turbine (or letdown valve) for Received: Revised: Accepted: Published: 18334
August 26, 2013 November 19, 2013 December 2, 2013 December 2, 2013 dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
Figure 1. Flowsheet of utility system. Components and processes are described in the text.
Figure 2. Flowsheet of MEA-based CO2 capture system. Components and processes are described in the text.
absorber loaded with MEA solvent. In the absorber, CO2 in the flue gas is absorbed by the MEA, then the exhaust gas is released into the atmosphere. The CO2-rich solvent stream containing a high quantity of ionic forms of CO2 is pressurized using a pump before being passed through a heat exchanger. The CO2-rich and CO2-lean solvent streams are crossed in the heat exchanger. The hot CO2-rich solvent discharged from the heat exchanger enters a regenerator, which releases CO2 gas and water vapor by boiling the CO2-rich solvent in a reboiler. The top gas of the regenerator is cooled using a cooler to
use in the chemical plant. The converting energy between steams can be used to produce electricity in the steam turbine. The remaining low pressure steam is transferred to a deaerator to preheat the makeup water. The preheated makeup water is pressurized using a pump and then provided to the boiler. Here, it must be noted that a considerable amount of flue gas is emitted by the gas turbine and boiler. CO2 in the flue gas can be separated in a CCSy assessed by Rao et al.17 (Figure 2). First, the flue gas is cooled using a cooler and pressurized using a blower before entering an 18335
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
Figure 3. Reference configuration, in which utility system and CO2 capture system are operated individually.
Figure 4. Integrated process configuration 1, in which a utility system provides utilities for a CO2 capture system.
separate CO2 gas and water vapor in the flash. The liquefied water is returned to the regenerator, while the CO2 product gas is sent to a compressor to reduce its volume before it is transported to CO2 storage sites. At the bottom of the regenerator, most of the regenerated CO2-lean solvent is pumped to the heat exchanger. Before entering the absorber, the CO2-lean solvent is cooled using a cooler and mixed with the fresh MEA solvent. The CCSy requires a considerable amount of heating in the reboiler, whereas most UtSys in chemical plants simply vent unused heat (or steam) into the air.2 If the UtSy can supply the
vented heat to the CCSy, its heat requirement will be significantly reduced. However, the amount of reduction depends on the amount of previously unused heat. Furthermore, the hot flue gas emitted by the gas turbine and boiler of the UtSy must be cooled before it is sent into the CCSy. To maximize heat recovery we can perform heat integration, which facilitates transfer of heat from the hot flue gas streams to process streams of the reboiler. However, this transfer can increase the fuel consumption in the gas turbine and boiler because the hot flue gas stream, which is used for 18336
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
Figure 5. Integrated process configuration 2, in which the hot gas discharged from the gas turbine provides regeneration heat for a reboiler directly.
Figure 6. Integrated process configuration 3, in which the hot gas discarged from the gas turbine provides regeneration heat for a reboiler indirectly.
exchange utilities or CO2. In configuration 1 (Figure 4), the UtSy supplies utilities (e.g., steam and power) required for the CCSy. The boiler produces additional low pressure steam required for the reboiler of CCSy, thus when additional fuel is consumed in the boiler additional CO2 emissions result. The CCSy also requires electricity to pressurize CO2 product gas, flue gas, and solvent streams. The gas turbine generates additional electricity required for the CCSy, thus when additional fuel is consumed in the gas turbine additional CO2 emissions result. To avoid this consequence, a power import is
generating utilities required for the chemical plant, is used instead to heat the CCSy. Thus, in the following sections we will design alternative system configurations and evaluate their energy efficiency and cost.
3. PROCESS DEVELOPMENT 3.1. Process Design Description. We designed three process configurations (conf. 1−3) and compared their unit costs to that of a reference configuration (refer to Figure 3) in which the UtSy and CCSy are operated individually, i.e., do not 18337
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
introduced for each configuration except for the reference configuration. The direct contact cooler (DCC) in the CCSy requires some water to cool the flue gas stream discharged from the boiler, and the CCSy also requires some water to cool the CO2 product gas and CO2-lean solvent streams. The water used for the DCC in the CCSy returns to the deaerator in the UtSy to reduce the quantity of makeup water required. Configurations 2 and 3 differ according to heat resource utilization of flue gas stream. In configuration 2 (Figure 5), the heat of the hot gas stream discharged from the gas turbine provides all heat requirements for the reboiler in the CCSy. Additional low pressure steam is not required for to fulfill the heat requirement, but the hot gas stream has greater volume than the low pressure steam used in the reboiler, so the reboiler in configuration 2 should be larger than the reboiler in configuration 1. Configuration 3 (Figure 6) uses the heat of the hot gas discharged from the gas turbine to make additional low pressure steam used in the reboiler; thus this configuration employs a multiple heat exchanger (MHE) instead of a DCC. There is no large change of the size of the reboiler compared to configuration 1. 3.2. Process Model Formulation. To develop the UtSy, we used the unit performance models (e.g., a cooler, a gas turbine) of Aspen Utilities Model Library23 built in the ASPEN Custom Modeler,24 based on an optimized configuration and data1 except that the present study considered LNG as a fuel; whereas, a literature source1 used kerosene. The unit performance models for the CCSy were developed using ASPEN Custom Modeler based on the literature.17 Because the unit performance models in the literature were developed for individual UtSys and CCSys, we will present the development of material and energy balance models for the integrated process, which can link the unit performance models. Equations 1−12 are the material and energy balances of the CCSy. Equations 1 and 2 are the overall material balances of gas streams. The CO2 capture efficiency divides the flow rates of exhaust gas and CO2 product gas from the flow rate of the flue gas discharged from the UtSy. Equations 3−7 are the mass balances of each component in the gas streams. Especially, the removal efficiency of each acid gas determines its composition in the exhaust gas.
G (1 −
m yCO η /100) 2 CO2
m GmyCO (1 2
=
− ηCO /100) = 2
m Gexmyex,SO X
m m GmyNO (1 − ηNO /100) = Gexmyex,NO X
X
=
For the process configuration 2, eqs 13 and 14 are the material and energy balances of the hot flue gas stream as a heat source required for the reboiler.
X
(14)
m m Fsw,in = Flps,out
(15)
m m Fhfg,in = Fhfg,out
(16)
m m m m Fsw,in Hsw,in − Flps,out Hlps,out = Fhfg,in Hhfg,in − Fhfg,in Hhfg,out
(17) m Fcw,in
m Fsw,out
(18)
m m Fcfg,in = Fcfg,out
(19)
=
m m m m Fcw,in Hcw,in − Fsw,out Hsw,out = Fcfg,in Hcfg,in − Fcfg,in Hcfg,out
(20)
reference objective function low pressure steam flow of the CCSy (t/h) 36.5 decision variables lean solvent CO2 loading (mol CO2/mol MEA) 0.34 MEA weight percent (%) 40 conf 1 conf 2 conf 3
(6) (7)
m Sinm = Sout
lean solvent CO2 loading (mol CO2/mol MEA) MEA weight percent (%) power generation of the gas turbine (MW)
(8)
−
m Q = FinmHhfg,in − Fout Hhfg,out
For the process configuration 3, eqs 15−20 are the material and energy balances of the cooling water and saturated water required for the MHE.
For the process configurations 1 and 3, eqs 8 and 9 are the material and energy balances of the steam required for the reboiler of CCSy.
Q=
(13)
operating cost ($/h)
m Gexmyex,O 2
SinmHsteam,in
m m Fhfg,in = Fhfg,out
(3)
(5)
GmyOm 2
(12)
Table 1. Summary of Optimizations
(4)
X
m m m m Fcw,in Hcw,in − Fcw,out Hcw,out = Fcfg,in Hcfg,in − Fcfg,in Hcfg,out
(2)
2
− ηSO /100) =
(11)
m Gexmyex,CO 2
m GmySO (1 X
2
m m Fcfg,in = Fcfg,out
(1)
m m GmyCO ηCO /100 = Gpmyp,CO 2
(10)
Gexm
2
2
m m Fcw,in = Fcw,out
Equations 21−25 are the unit performance models for the CCSy of Rao et al.17 Here, eq 21 determines the ratio of the molar flow rates between the flue gas and the MEA solvent under the given conditions, which include the mole fraction of CO2 in the flue gas, the CO2-lean solvent loading, the CO2 capture efficiency, the weight percent of MEA to water, and the flue gas temperature. Similarly, eq 22 determines the ratio of the regeneration heat to the molar flow rate of the MEA
m GmyCO ηCO /100 = Gpm
m
For the process configurations 1 and 2, eqs 10−12 are the material and energy balances of the cooling water required for the coolers of CCSy.
m Sout Hsteam,out
steam flow transferred to the deaerator (t/h)
(9) 18338
objective function 3921 3950 decision variables 0.34 0.34
range
0.05−0.34 15−40 range
3966 0.34
0.05−0.34
40 24.9
40 23.8
15−40 10−40
constraints 0.01 0.01
0.01
0.01−25.6
40 23.9
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
Table 2. Specifications of Baseline Case
Table 4. Results of an Economic Study for CO2 Capture Systems
Conditions Common to All Configurations flue gas condition flue gas pressure (kPa)17 flue gas temperature (°C)17 CCSy CO2-lean solvent loading (mol CO2/mol MEA)17 MEA (wt %)17 CO2 capture efficiency (%)17 reboiler inlet solvent temperature in the reboiler (°C) reboiler outlet solvent temperature in the reboiler (°C) utility supply system steam demand (t/h)1 high pressure (69 bar and 661 K) medium pressure (17.2 bar and 600 K) low pressure (3.5 bar and 411K) electricity demand (MW)1 Conditions Specific to Configurations ref
1
configuration 101.6 48 0.34 40 90 111 119
flue gas condition flue gas mass flow (t/h) 357.5 274.8 flue gas composition (wt %) N2 74.52 73.70 CO2 8.87 11.78 O2 9.35 4.89 H2O 7.26 9.64 NOx 0.00014 0.00019 utility supply system bolier feedwater temperature 176 168 (°C)
273.7
74.00 10.73 6.50 8.78 0.00017
73.81 11.39 5.48 9.32 0.00018
208
189
2
[adj R = 0.92]
Ecompr =
(21)
(22)
(23)
m 100ecompGpmyp,CO 2
ηcomp
(24)
v
E blower =
G ΔPfg 360ηblower
electricity price ($/MWh)
3.13
6.03
6.38
9.13
9.63
44.3 56.3 68.3
49 54 58
50 55 59
50 55 60
48 54 61
48 54 60
4. RESULTS AND DISCUSSIONS This section is divided into two parts. Section 4.1 presents a baseline case definition and the optimization of each process configuration. Section 4.2 presents an economic evaluation and discussion of the results. 4.1. Baseline Case Definition and Optimization. A utility system1 servicing a petroleum refinery of 200 000 barrels per stream day (BPSD) capacity was selected as a reference. We suggest the best process integration design of the existing utility system in a petroleum refinery to be retrofitted with an MEA-based CO2 capture system. The baseline case optimization was performed using the ASPEN custom modeler, and the summary of optimization was showed (Table 1). Equation 26 was an objective function of reference configuration to minimize the thermal energy requirements of the reboiler, and eqs 28 and 29 were decision variables and ranges of the reference configuration. Equation 27 was an objective function of the configurations 1−3 to minimize the operating cost of the utility system, and eqs 28−30 were decision variables and ranges of configurations 1−3. Also eq 31 was a constraint of configurations 1−3. Baseline cases (Table 2) were defined for each process configuration. The utility supply contribution of an internal UtSy and an external source to a CCSy were obtained (Table 3; details show in Table A.1 in the Appendix). All integrated process configurations yielded significant cooling utility savings (0.38 GJ/T CO2) compared to the reference configuration; the cooling requirements were reduced to 4.06 GJ/T CO2,
2
Lv ΔPsolvent 360ηpump
24.67 10.10 12.33 215 57 32
Configuration 1 is superior except where numbers appear in italic, in which case configuration 2 is superior.
Q /L = exp( −2.4452 − 0.0037yCO − 6.2743 × ϕlean
Epump =
23.76 9.89 12.04 215 56 26
a
2
2
[adj R = 0.96]
3
23.00 9.64 11.72 214 55 43
3
L /G = exp( − 1.4352 + 0.1239yCO + 3.4863ϕlean + 0.0174ηCO
+ 0.0254C)/1000
2
23.67 15.48 17.62 214 82 38
avoid cost at
286.1
2
1
total capital investment (M$) total operating cost (M$/y) total annual cost (M$/y) avoided CO2 emissions (kt/y) cost of CO2 avoided ($/t CO2) load of the boiler (%)
natural gas price ($/GJ)
solvent. Equations 23−25 calculate the electricity requirements of the pumps, compressor, and blower in the CCSy.
− 0.0397C + 0.0027Tfg,in)
ref
Table 5. Cost of CO2 Avoided ($/t CO2) with Varying Economical Parametersa
0 120.5 188.6 47.4 2
quantity
(25)
Table 3. Utility Supply Contribution (GJ/t CO2) of the Internal UtSy and External Source to CCSya Configuration source
ref E
internal UtSy external total a
C
1 H
E
C
2 H
E
C
4.44 8.88
3.89
1.35
4.06 5.74
E
C
−0.52
0.32 0.55
3 H
1.79
4.06 5.33
H −0.27
1.72
4.06 5.50
E: electricity. C: cooling. H: heating. 18339
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
Table A.1. Detailed Optimization Results with Associated Stream Data of All Equipment Units ref fuel consumption of the boiler (t/h) fuel consumption of the gas turbine (t/h) overall fuel consumption (t/h) high pressure steam to the first letdown valve (t/h) high pressure steam to the first steam turbine (t/h) overall high pressure steam generation (t/h) medium pressure steam from the first letdown valve (t/h) medium pressure steam from the first steam turbine (t/h) medium pressure steam from the first waste heat boiler (t/h) medium pressure steam to a heat exchanger (t/h) medium pressure steam to the second letdown valve (t/h) medium pressure steam to the second steam turbine (t/h) medium pressure steam demand (t/h) overall medium pressure steam generation (t/h) low pressure steam from the second letdown valve (t/h) low pressure steam from the second steam turbine (t/h) low pressure steam from the second waste heat boiler (t/h) low pressure steam from a multiple heat exchanger (t/h)
conf 1
conf 2
conf 3
2.1
4.6
3.7
4.2
9.4
7.2
7.5
7.1
11.5 3.2
11.8 3.2
11.2 3.2
11.3 3.2
80.4
90.2
54.8
67.8
83.6
93.4
58.0
71.0
3.2
3.2
3.2
3.2
80.4
90.2
54.8
67.8
213.0
213.0
213.0
213.0
12.4
12.4
12.4
12.4
14.7
14.7
14.7
14.7
149.0
158.8
123.4
136.4
120.5
120.5
120.5
120.5
296.6
306.4
271.0
284.0
14.7
14.7
14.7
14.7
149.0
158.8
123.4
136.4
50.5
50.5
50.5
50.5
0.0
0.0
0.0
21.1
ref low pressure steam to the deaerator (t/h) low pressure steam to the CO2 capture system (t/h) low pressure steam demand (t/h) overall low pressure steam generation (t/h) cooling water of the CO2 capture system (t/h) makeup water of the deaerator (t/h) condensed return of the deaerator (t/h) blowdown water before entering the feedwater pump (t/h) blowdown water of the boiler (t/ h) power from the gas turbine (MW) power from the first steam turbine (MW) power from the second steam turbine (MW) power demand of the CO2 capture system (MW) power demand of the utility system (MW) overall power generation (MW) power imports (MW) air for the gas turbine (t/h) flue gas (t/h) exhaust gas (t/h) CO2 product gas (t/h) CO2 emissions (t/h)
(26)
m min z = PNGFNG + PelecE import
(27)
0.05 ≤ ϕlean ≤ 0.34
(28)
15 ≤ C ≤ 40
(29)
10 ≤ EGT ≤ 40
(30)
m 0.01 ≤ SDA,in ≤ 25.6
(31)
conf 2
conf 3
0.0
0.0
0.0
0.0
35.4
0.0
34.1
188.6 214.2
188.6 224.0
188.6 188.6
188.6 222.8
3018.1
2816.3
2671.7
2713.9
459.2
459.7
457.9
458.5
120.1
120.1
120.1
120.1
265.8
265.8
265.8
265.8
4.4
4.9
3.1
3.7
31.4
23.9
24.9
23.8
5.1
5.8
3.5
4.3
10.9
11.6
9.0
10.0
4.4
4.5
4.4
4.4
47.4
47.4
47.4
47.4
47.4 0.0 346.0 357.5 329.0 28.6 3.2
41.2 10.7 263.0 274.8 245.7 29.1 3.2
37.4 14.3 275.0 286.1 258.5 27.6 3.1
38.1 13.7 262.4 273.7 245.7 28.1 3.1
Analyzer25 (Table A.2 in the Appendix). After that, the total capital investment (CAPEX) was calculated based on the
compared to the reference (4.44 GJ/t CO2), because the hot stream discharged from DCC or MHE passed to a deaerator to be used as preheated water instead of being sent to a cooling tower. Meanwhile, all integrated process configurations yielded significant heating utility savings (3.57−4.41 GJ/t CO2) and significant electricity imports (0.8−1.23 GJ/t CO2). Because more electricity was imported, less CO2 was emitted from the gas turbine, Configuration 2 had the lowest value of the total utility supply (5.33 GJ/t CO2), then it was best option for energy savings. But an economic evaluation should be performed, because it was expected that the reboiler of configuration 2 had a larger equipment cost than that of other configurations. min z = Sinm
conf 1
25.6
Table A.2. Overview of the Cost of Equipment cost (M$) type of equipment
ref
conf 1
conf 2
conf 3
absorber CO2 compressor cooler heat exchanger lean pump rich pump condenser condenser tank reboiler reflux pump stripper direct contact cooler multiple heat exchanger total
0.711 4.248 0.052 0.272 0.010 0.012 0.034 0.011 0.147 0.004 0.186 0.092
0.608 4.248 0.051 0.225 0.009 0.011 0.035 0.011 0.142 0.004 0.186 0.084
0.624 4.248 0.051 0.274 0.009 0.011 0.034 0.011 0.265 0.004 0.186 0.081
0.608 4.248 0.049 0.352 0.009 0.011 0.035 0.011 0.137 0.004 0.186
5.777
5.613
5.798
0.372 6.022
detailed model of Abu-Zahra et al.,16 and then, the total operating cost (OPEX) was estimated with the economic parameters (Figures A.1−A.3 and Tables A.3−A.5 in the Appendix). On the basis of the CAPEX and OPEX, we calculated a total annual cost (TAC) and then determined a cost of CO2 avoided
4.2. Economic Evaluation. In this study, the technoeconomic potential of the proposed process was evaluated, assuming that a MEA-based CCSy could be retrofitted to an existing UtSy in a chemical plant. Unit equipment costs of CCSy were estimated using Aspen Process Economic 18340
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
out of three configurations: it had the lowest total annual cost (TAC), the lowest cost of CO2 avoided and a reasonable load on the boiler (current amount of high pressure steam generation divided by the designed (affordable) amount of high pressure steam generation before optimization1). We performed sensitivity analyses on various key economical parameters (Table 5). We could consider natural gas price and electricity price as key economical parameters, because both parameters had a significant influence on the TAC. Trade-offs occurred between configurations 1 and 2 with the range of two economical parameters. As the natural gas prices (NGP) increase ($ 9.13/GJ), configuration 2 became preferable to ($ 48−61/t CO2) configuration 1. Furthermore, if we use novel solvents (MDEA, Carbonate) which typically have lower regeneration energy requirements than MEA,26 a trade-off of the determined cost of CO2 avoided between configurations 1 and 2 occurs at relatively low NGP, because lower regeneration energy requirements with the novel solvents results in lower fuel consumption and capacity of the reboiler which means that the gap of TAC is reduced between configurations 1 and 2.
Figure A.1. Overview of purchased equipment costs for each configuration.
that corresponds to the TAC divided by avoided CO2 emissions (Table 4). Configuration 1 was the best configuration
Figure A.2. Overview of CAPEX values for each configuration.
Figure A.3. Overview of OPEX values for each configuration. 18341
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
operated individually without exchanging utilities or CO2. After process integrations, we obtained significant cooling utility savings (0.38 GJ/t CO2) and heating utility savings (3.57−4.41 GJ/t CO2) in all process configurations, compared to the reference configuration, but we obtained significant electricity imports (0.8−1.23 GJ/t CO2). We showed that configuration 1 was the best configuration out of three configurations and has the lowest cost of CO2 avoided ($55/t CO2), using the current economical parameters. However, our sensitivity analysis showed that configuration 2 might be better ($48−61/t CO2) than configuration 1 if the natural gas price is high ($9.13/GJ).
Table A.3. Economic Evaluation Assumptions project life (y)16 equipment salvage value16 construction period (y)16 plant operating (h/y)16 interest rate (%)16 MEA degradation rate (kg/t CO2)16 MEA price ($/t)16 natural gas price (median, $/t)27 low pressure steam price ($/GJ)28 water price ($/t)28 electricity price (median, $/MW h)29
25 0 3 7500 8 1.5 1000 282 14.05 0.0148 56.3
■
APPENDIX Tables A.1−A.5 and Figures A.1−A.3 as mentioned previously in the text.
Table A.4. CO2 Capture System Total Capital Investment (CAPEX) cost (M$) percentage of purchased cost ISBL purchased equipment purchased equipment installation instrumentation and control piping electrical OSBL building and building services yard improvements services facilities land total direct cost engineering construction expenses contractor’s fee contingency total indirect cost fixed capital investment
ref
direct cost 12.77 100.0%16 5.78 50.0%16
2.89
conf 2
conf 3
12.41 5.61
12.81 5.80
13.31 6.02
2.81
2.90
1.16
1.12
1.16
1.20
40.0%16 11.0%16
2.31 0.64 2.60 0.58
2.25 0.62 2.53 0.56
2.32 0.64 2.61 0.58
2.41 0.66 2.71 0.60
0.58 1.16 0.29 15.37 indirect cost 10.0%16 0.58 10.0%16 0.58
0.56 1.12 0.28 14.93
0.58 1.16 0.29 15.42
0.60 1.20 0.30 16.02
0.56 0.56
0.58 0.58
0.60 0.60
0.03 0.95 2.11 17.04
0.03 0.99 2.17 17.60
0.03 1.02 2.26 18.28
10.0%16 10.0%16 20.0%16 5.0%16
16
0.5% 17.0%16
0.03 0.98 2.17 17.53
100.0%16 25.0%16 10.0%16
Table A.5. CO2 Capture System Total Operating Cost (OPEX) cost (M$/y) specification production cost fixed charge (FC) local tax insurance direct production cost (DPC) Natural gas cost (NGC) steam cost electricity cost makeup water cooling water MEA makeup maintenace (M) operating labor (OL) supervision and support labor (S) operating supplies laboratory charges plant overhead cost (POC) general expenses (GE) administrative cost distribution and marketing RD cost total operating cost (OPEX)
3.01
20.0%16
percentage of FCI fixed capital investment working investment startup cost + MEA cost total capital investment (CAPEX)
conf 1
cost (M$) 17.53 4.38 1.75 23.67
17.04 4.26 1.70 23.00
17.60 4.40 1.76 23.76
18.28 4.57 1.83 24.67
2% of FCI16 1% of FCI16
ref 15.73 0.51 0.34 0.17 14.23
282 $/t27
conf 1 conf 2
conf 3
9.01 0.51 0.34 0.17 7.51
9.28 0.53 0.35 0.18 7.75
9.47 0.55 0.37 0.18 7.90
0.49
−0.79
−0.41
14.05 $/GJ28 56.3 $/MW h 0.0148 $/t28 0.0148 $/t28 1000 $/t, 1.5 kg/t CO216 4% of FCI16 $45 1/h, two job per shift16 30% of (OL + S)16
8.66 1.86 0.05 0.34 0.32 0.68 0.68
4.51 0.05 0.31 0.33 0.68 0.68
6.04 0.05 0.30 0.31 0.70 0.68
5.77 0.05 0.30 0.32 0.73 0.68
0.29
0.29
0.29
0.29
15% of M16 10% of OL16 60% of (M + OL + S)16
0.10 0.07 0.99
0.10 0.07 0.99
0.11 0.07 1.00
0.11 0.07 1.02
1.01
0.63
0.64
0.65
0.10 0.08
0.10 0.05
0.10 0.05
0.10 0.05
0.83 16.74
0.48 9.63
0.49 9.93
0.50 10.12
15% of OL16 0.5% of OPEX16 5% of OPEX16
Notation
C = MEA weight percent, % Eblower = blower electricity requirement, MW ecomp = CO2 compression unit energy requirement, MW h/t CO2 Ecompr = compressor electricity requirement, MW EGT = electricity generated from the gas turbine, MW Eimport = electricity imports, MW Epump = pump electricity requirement, MW Fm hfg,in = hot flue gas inlet mass flow rate, t/h Fm hfg,out = hot flue gas outlet mass flow rate, t/h Fm cw,in = cooling water inlet mass flow rate, t/h Fm cw,out = cooling water outlet mass flow rate, t/h
5. CONCLUSIONS We developed three process integration configurations, which combines UtSy and CCSy, according to how to supply thermal energy required for the CCSy: configuration 1 the UtSy produces additional low-pressure steam; configuration 2 the hot gas discharged from a gas turbine in the UtSy is used directly; and configuration 3 the hot gas discharged from a gas turbine in the UtSy indirectly with an MHE that generates additional low pressure steam. As a standard for comparison we also optimized a reference configuration in which the UtSy and CCSy are 18342
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
■
Fm cfg,in = cold flue gas inlet mass flow rate, t/h Fm cfg,out = cold flue gas outlet mass flow rate, t/h Fm lps,out = low pressure steam outlet mass flow rate, t/h Fm NG = total fuel mass flow rate, t/h Fm sw,in = saturated water inlet mass flow rate, t/h Fmsw,out = Saturated water outlet mass flow rate t/h G = flue gas molar flow rate, kmol/h Gm = flue gas mass flow rate, t/h Gm ex = exhaust gas mass flow rate, t/h Gm p = product CO2 gas mass flow rate, t/h Gv = flue gas volume flow rate, m3/h Hhfg,in = hot flue gas inlet mass enthalpy, GJ/t Hhfg,out = hot flue gas outlet mass enthalpy, GJ/t Hsteam,in = inlet low pressure steam mass enthalpy for the reboiler, GJ/t Hsteam,out = outlet low pressure steam mass enthalpy for the reboiler, GJ/t Hcfg,in = Hot flue gas inlet mass enthalpy, GJ/t Hcfg,out = hot flue gas outlet mass enthalpy, GJ/t Hcw,in = cooling water inlet mass enthalpy for the reboiler, GJ/t Hcw,out = cooling water outlet mass enthalpy for the reboiler, GJ/t Hsw,in = saturated water inlet mass enthalpy for the reboiler, GJ/t Hsw,out = saturated water outlet mass enthalpy for the reboiler, GJ/t Hlps,out = low pressure steam outlet mass enthalpy for the MHE, GJ/t L = lean solvent molar flow rate, kmol/h Lv = lean solvent volume flow rate, m3/h PElec = electricity price, $/MW h PNG = natural gas price, $/t Q = total heat requirement for solvent regeneration, GJ/h Sm DA,in = steam mass flow rate transferred to the deaerator, t/h Sm in = inlet low pressure steam mass flow rate for the reboiler, t/h Sm out = outlet low pressure steam mass flow rate for the reboiler, t/h Tfg,in = flue gas temperature before entering the absorber, °C yCO2 = flue gas CO2 mol percent, % ym CO2 = flue gas CO2 mass fraction ym ex,CO2 = exhaust gas CO2 mass fraction ym ex,NOX = exhaust gas NOX mass fraction ym ex,O2 = exhaust gas O2 mass fraction ym ex,SOX = exhaust gas SOX mass fraction ym NOX = flue gas NOX mass fraction ym O2 = flue gas O2 mass fraction ym p,CO2 = CO2 product gas CO2 mass fraction ym SOX = flue gas SOX mass fraction
AUTHOR INFORMATION
Corresponding Author
*Tel.: +82-54-279-2950. Fax: +82-54-279-5528. E-mail address:
[email protected]. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS This work was supported by Research Institute of Industrial Science & Technology (RIST) as part of Green Science Program (No. RIST 2010H084).
■
REFERENCES
(1) Papoulias, S. A.; Grossmann, I. E. A structural optimization approach in process synthesis-I. Utility systems. Comput. Chem. Eng. 1983, 7 (6), 695−706. (2) Kim, S. H.; Yoon, S. G.; Chae, S. H.; Park, S. Economic and environmental optimization of a multi-site utility network for an industrial complex. J. Environ. Manage. 2010, 91 (3), 690−705. (3) Clark, J. K., Jr.; Helmick, N. E. How to Optimize the Design of Steam Systems. Chem. Eng. 1980, 87 (5), 116−128. (4) Khoshgonftar Manesh, M. H.; Motevallian, S. J.; Amidpour, M.; Mazhari, V. Optimization of steam network through MINLP method: Application to utility of KHARK island NGL recovery project, 2009; 2009; pp 225−230. (5) Petroulas, T.; Reklaitis, G. V. Computer-Aided Synthesis and Design of Plant Utility Systems. AIChE J. 1984, 30 (1), 69−78. (6) Savola, T.; Fogelholm, C. J. MINLP optimization model for increased power production in small-scale CHP plants. Appl. Thermal Eng. 2007, 27 (1), 89−99. (7) Gupta, A.; Manousiouthakis, V. Minimum utility cost of mass exchange networks with variable single component supplies and targets. Ind. Eng. Chem. Res. 1993, 32 (9), 1937−1950. (8) Jeong Hwan, K.; Han, C. Short-term multiperiod optimal planning of utility systems using heuristics and dynamic programming. Ind. Eng. Chem. Res. 2001, 40 (8), 1928−1938. (9) Tina, G. M.; Passarello, G. Short-term scheduling of industrial cogeneration systems for annual revenue maximisation. Energy 2012, 42 (1), 46−56. (10) Jeong, S. J.; Kim, K. S.; Park, J. W.; Lim, D. s.; Lee, S. m. Economic comparison between coal-fired and liquefied natural gas combined cycle power plants considering carbon tax: Korean case. Energy 2008, 33 (8), 1320−1330. (11) Agha, M. H.; Thery, R.; Hetreux, G.; Hait, A.; Le Lann, J. M. Integrated production and utility system approach for optimizing industrial unit operations. Energy 2010, 35 (2), 611−627. (12) Luo, X.; Zhang, B.; Chen, Y.; Mo, S. Modeling and optimization of a utility system containing multiple extractions steam turbines. Energy 2011, 36 (5), 3501−3512. (13) Han, J.-H.; Lee, I.-B. Development of a scalable infrastructure model for planning electricity generation and CO2 mitigation strategies under mandated reduction of GHG emission. Appl. Energy 2011, 88 (12), 5056−5068. (14) Chae, S. H.; Kim, S. H.; Yoon, S.-G.; Park, S. Optimization of a waste heat utilization network in an eco-industrial park. Appl. Energy 2010, 87 (6), 1978−1988. (15) Abu-Zahra, M. R. M.; Schneiders, L. H. J.; Niederer, J. P. M.; Feron, P. H. M.; Versteeg, G. F. CO2 capture from power plants. Part I. A parametric study of the technical performance based on monoethanolamine. Int. J. Greenhouse Gas Control 2007, 1 (1), 37−46. (16) Abu-Zahra, M. R. M.; Niederer, J. P. M.; Feron, P. H. M.; Versteeg, G. F. CO2 capture from power plants. Part II. A parametric study of the economical performance based on mono-ethanolamine. Int. J. Greenhouse Gas Control 2007, 1 (2), 135−142. (17) Rao, A. B.; R, E. S.; Berkenpas, M. B. An Integrated Modeling Framework for Carbon Management. In Vol. 1−Technical Documentation: Amine Based CO2 Capture and Storage Systems for Fossil Fuel Power
Greek Symbols
ΔPfg = flue gas blowing head, bar ΔPsolvent = solvent pumping head, bar ηblower = blower percent efficiency, % ηCO2 = CO2 capture efficiency, % ηcomp = compression percent efficiency, % ηNOX = NOX capture efficiency, % ηpump = pump percent efficiency, % ηSOX = SOX capture efficiency, % ϕlean = lean solvent CO2 loading, mol CO2/mol MEA
■
Article
ASSOCIATED CONTENT
S Supporting Information *
Supporting Tables A.1−A.8 and Figure A.1. This material is available free of charge via the Internet at http://pubs.acs.org. 18343
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
Industrial & Engineering Chemistry Research
Article
Plant; Center for Energy and Environmental Studies, C.M.U., Pittsburgh, PA, 2004. (18) Sandberg, J.; Larsson, M.; Wang, C.; Dahl, J.; Lundgren, J. A new optimal solution space based method for increased resolution in energy system optimization. Appl. Energy 2012, 92, 583−592. (19) Han, J. H.; Ahn, Y. C.; Lee, I. B. A multi-objective optimization model for sustainable electricity generation and CO2 mitigation (EGCM) infrastructure design considering economic profit and financial risk. Appl. Energy 2012, 95, 186−195. (20) Vuarnoz, D.; Kitanovski, A.; Gonin, C.; Borgeaud, Y.; Delessert, M.; Meinen, M.; Egolf, P. W. Quantitative feasibility study of magnetocaloric energy conversion utilizing industrial waste heat. Appl. Energy 2012, 100, 229−237. (21) Rudberg, M.; Waldemarsson, M.; Lidestam, H. Strategic perspectives on energy management: A case study in the process industry. Appl. Energy 2013, 104, 487−496. (22) Karlsson, M. The MIND method: A decision support for optimization of industrial energy systems - Principles and case studies. Appl. Energy 2011, 88 (3), 577−589. (23) AspenUtilitiesModelLibraryV7.3, Aspen Technology Inc.: Cambridge, 2011. (24) ASPENcustommodelerV7.3, Aspen Technology Inc.: Cambridge, 2011. (25) AspenProcessEconomicAnalyzerV7.3, Aspen Technology Inc.: Cambridge, 2011. (26) Lu, Y.; Rostam-Abadi, M.; Ye, X.; Zhang, S.; Djukardi, T. Development and Evaluation of a Novel Integrated Vacuum Carbonate Absorption Process; University of Illinois, 2012. (27) U.S. Energy Information Administration, Natural Gas Price http://www.eia.gov/dnav/ng/hist/n3035us3A.htm (accessed 2013). (28) Sen, S. M.; Alonso, D. M.; Wettstein, S. G.; Gürbüz, E. I.; Henao, C. A.; Dumesic, J. A.; Maravelias, C. T. A sulfuric acid management strategy for the production of liquid hydrocarbon fuels via catalytic conversion of biomass-derived levulinic acid. Energy Environ. Sci. 2012, 5 (12), 9690−9697. (29) U.S. Energy Information Administration, Eelectricity Price http://www.eia.gov/electricity/data.cfm#sales (accessed 2013).
18344
dx.doi.org/10.1021/ie4028044 | Ind. Eng. Chem. Res. 2013, 52, 18334−18344
