DESIGN OF METHANOL PLANT EURECHA Student Contest Problem Competition 2013 Chan Wei Nian,
[email protected] Fang You,
[email protected] Department of Chemical & Biomolecular Engineering, National University of Singapore, Engineering Drive 4, Singapore 117576, Republic of Singapore
EXECUTIVE SUMMARY This report presents a techno-economic analysis of setting up a methanol plant with a capacity of 50,000 MT/yr from natural gas feedstock of 31,000 MT/yr and 90% methane. This is performed in the European context with due considerations for environmental sustainability. The plant is designed assuming 10-year plant life and 8000 hours of operation per annum. The methanol process was developed according to open literature and industry standard, as described in Section 2; it consists of 5 units/sections: steam methane reformer, compression trains, methanol synthesis reactor, hydrogen separation and methanol distillation. These were grouped into two main segments of steam methane reforming and methanol synthesis, and were independently optimized in Sections 3.1 and 3.2 using Aspen HYSYS v7.2 by varying important process parameters within reported ranges. This is followed by a plant-wide heat integration study with Aspen Energy Analyzer v7.2, described in Sections 3.3 and 4.3. Operating conditions favouring better overall process profit of the order of USD$106 are reported in Sections 4.1 and 4.2 for the ideal case ignoring operating constraints, and the base case for economic analysis was chosen based on practical industry constraints; the reforming section utilizes an excess steam to carbon ratio of 2.7, inlet pressure of 2000 kPa and furnace outlet temperature of 900°C and while the methanol synthesis loop employs a reactor temperature of 255°C, compressor discharge pressure of 8010 kPa and a stoichiometric ratio of 9.035, as summarized in Section 4.4. The fixed capital investment, cost of manufacturing and revenue for the base case is €31,562,300, €29,520,600 and €43,952,670 respectively. The payback period is 3.2 years and the net present value (NPV) of the investment is €32,840,270. The breakeven price for methanol is €0.3285/kg and the discounted cash flow rate of return is 26.02%. The former is most sensitive to natural gas, hydrogen and methanol prices, as shown in Section 4.5. In Section 4.6, Monte Carlo simulations performed according to expected price fluctuations of natural gas and methanol obtained in the past 10 years reported a 7.5% probability of making an overall investment loss. The feasibility of substituting biogas for natural gas was analyzed for the given feedstocks in Section 4.7. Several options were explored, and the highest savings in net present value of €1,299,770 as well as reduction of 2074 MT/yr of CO2 emissions were obtained for the case of utilizing the non-liquid feeds. Options to capture carbon emissions from the plant as well as other carbon sources were explored, and the most suitable technology for the plant was found to be absorption using monoethanol amines, as elaborated in Section 4.8.
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1.
INTRODUCTION
Methanol demand in the global market is burgeoning with a 23% increase from 2010 to 2012 to 61 million tons and an expected increase to 137 million tons in 2022 [1]. However, its raw material: natural gas faces both supply limitation and volatility; as a non-renewable resource, natural gas is expected to deplete as early as 37 years depending on the level of conservativeness [2] while gas infrastructure in Europe is fragmented and inconsistent [3]. At the same time, environmental concerns for carbon emissions necessitate the integration of carbon capturing technologies. These usher a new age of sustainable design in this age-old process, and it will be reviewed in this report. A base case for the methanol synthesis was developed and optimized, followed by case studies on biogas substitution and alternative carbon capture opportunities. 2.
PROCESS DESCRIPTION
For the base case, the methanol synthesis is generally split into steam reforming, methanol synthesis, hydrogen separation and methanol purification, which are described in this section. Steam reforming: This is an overall endothermic reaction involving catalytic conversion of methane and steam into syngas at high temperatures above 800oC [4], medium pressures of 15-30 bar [5] and steam to carbon (S/C) ratio of 2 to 4 using nickel catalysts. Steam reforming is limited by equilibrium [6], and higher conversion is achieved by increasing temperature, lowering pressure and higher S/C ratio. It usually occurs in nickel catalyst-packed tubes located in the radiant section of a furnace. Steam Reforming: Water Gas Shift:
(∆H25C = 206kJ/mol) ----------------- (1) (∆H25C = -41kJ/mol) ----------------- (2)
Methanol Synthesis: Syngas can be catalytically converted to methanol via an overall exothermic reaction at medium temperatures of 210-270˚C and high pressures of 50-100 bar [7], over copperalumina catalysts. The presence of the water-gas shift reaction necessitates the use of a modified stoichiometric ratio defined below, and it is typically in the range of 9-10 [4]. Methanol Synthesis: Modified Stoichiometric Ratio:
(∆H25C = -91kJ/mol) --------------- (3) -------------------------------------------------------- (4)
Methanol synthesis reactors are designed to remove reaction heat via cooling service fluids such as unheated reactants or boiler feed water as well as feed quenching [8]. Isothermal cooling in shell and reactor tube setups was modeled under conditions known to approach equilibrium [4], and it can achieve higher conversions with lower temperatures, higher pressures and stoichiometric ratios. Methanol Purification: Methanol synthesis products containing methanol and syngas are flashed to separate unconverted light ends and crude methanol. Crude methanol is distilled to separate remaining light-ends, methanol at 98%wt and water, in an atmospheric column with a partial condenser. Hydrogen Separation: The flashed light-ends contain excess hydrogen; to avoid recycle accumulation, these must be purged for furnace fueling or purified for hydrogen credit via pressure swing adsorption, cryogenic distillation or membrane separation [9] with the latter being cheaper at the low recoveries and purities required [10]. For this, polyimide membranes are fabricated as hollow fiber tubes in a shell, and separation is achieved by partial pressure differences. 2
3.
METHODOLOGY
The process was simulated using Aspen HYSYS v7.2, and individual units were designed to sufficient detail for costing based on the module factor approach [11]. Expected revenue from methanol (€0.413/kg [12]) and hydrogen (€8.04/kg [13]) sales was factored in for a plant-wide optimization. The methodology for design and costing for each unit for the optimization is elaborated below. 3.1 Steam Reforming Section Optimization This section focuses on the reformer furnace with the reaction modeled to reach equilibrium and the costing based on energy used. This is independent of downstream synthesis and is optimized separately. The variables affecting this section are the pressure, furnace temperatures (i.e., pre-heat and outlet temperatures) and S/C ratio; these affect costs of individual sections/units, and their expected effect on profit is shown in Table 1. Table 1: Expected effect of increase in design variables on profit due to costs of individual sections/units Design Variable
Energy Recovery from Natural Gas Pressure ↓ Pre-heat Temperature NA Outlet Temperature NA S/C Ratio NA
Convection Section Uncertain ↓ NA ↓
Radiant Section Uncertain ↑ ↓ ↓
Compression Conversion ↓ Uncertain Uncertain ↓
↓ ↑ ↑ ↑
Energy Recovery: Natural gas is expected to be delivered at 75 bar within European pipelines [3] and must be expanded via a valve or turbine for energy recovery to the desired pressure; the latter can be achieved with radial gas turbines at 75-88% efficiency [14] together with a minimum motor generator efficiency of 95% mandated by EU Directive 640/2009 [15]. The turbine was priced based on energy recovery rate and capital costs. Steam Reformer Furnace: Natural gas is mixed with steam and preheated in the convection section before reaction in the radiant section. The duties are summed, and used for furnace capital and energy costs. Catalyst life is assumed to be within industrial norm, and is priced based on USD$0.55 per kilo mole of natural gas processed [16]. A 95% approach to equilibrium was found to best match industrial data from [17], and this was used in the reactor simulations Water Let-Down Vessel: Excess steam is condensed and removed from the reformer products, in a knock-out vessel to ensure dryness for the compression train. The design is based on the water throughput to allow for 7.5 min of residence time, and the vessel volume is used for capital costing. The condensate is pumped up to process pressure and reheated as recycle steam to the reformer. Make-up Compressor: A separate compression train for syngas products (i.e., fresh feed) is designed because it has less variability than the recycle compressor and so requires less capacity allowance. For the discharge pressure of 50-100 bar and required flow of about 0.410 m3/s, reciprocating compressors are suitable and are used for costing at 75% efficiency. To avoid adiabatic temperature rise beyond the maximum temperature of 480 K [14], two-stage compression is used with inter-stage cooling. This cooler is designed using heat transfer area obtained using typical overall heat transfer coefficients and log mean temperature difference for cooling water service [18].
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3.2 Methanol Synthesis Section Optimization Due to low equilibrium conversion to methanol, recycle of syngas is necessary. The effect of reactor temperature, pressure and stoichiometric ratio of reactants on profitability of this section is shown in Figure 1. For modeling and optimization purposes, common reaction conditions of 210-270°C and 5-10 MPa were used. Costs involved for cooling reactant products in the crude methanol flash, pre-heating for distillation and column duties are calculated based on a preliminary setup, and optimized later using Figure 1: Schematic for inter-linked effects of varying pinch analysis together with the steam parameters – independent variables (black), parameters affecting cost (shaded pink), calculated parameters (blue) reforming heat exchangers. Methanol Synthesis Reactor: The recycle and fresh syngas streams are heated to the reaction temperature with reaction heat and an optional pre-heating or cooling; this is possible in shell and tube reactors [19]. The reactor was sized based on heat transfer area [20]. Catalyst cost, based on its replacement norms, is USD$0.0513 per kilo mole methanol, for isothermal reactors [4].
Annualized Costs (USD$mil)
Methanol Purification: The crude methanol flash vessel was sized similar to the water let-down vessel, and the distillation column was optimized based on typical feed of 78-80%mol methanol at 70oC. Trade-off between reflux ratio and number of stages was analysed by costing the column, condenser, reboiler, reflux drum and reflux pump, and the optimum number stages was found to be 27 for reflux ratio from 0.4 to 0.6 (Figure 2). This design is deemed optimal and used for all runs in the optimization study. 1.56 1.55 1.54 1.53 1.52 1.51 20
25
30
35
40
45
50
Number of Stages
Figure 2: Local optimization for distillation column
Figure 3: Hollow Fiber Membrane Separation Module Source: [21]
Hollow Fiber Membrane Module: Hydrogen separation is as shown in Figure 3 to recover hydrogen from the purge stream. Feed to permeate pressure ratio of 6 was used to minimize recompression of hydrogen [9], and this sets the limit for hydrogen recovery to 95%. The annualized capital cost increase is calculated to be in the range of USD$2,442.9 for a 0.01 fraction increase in recovery, whereas the gain in revenue was USD$365,600 for the same increase. As such, hydrogen recovery was maximized at 95% for each optimization run. With the hydrogen flux constant, only the membrane cost will vary 4
according to required membrane area (USD$21/m2 [22]) obtained from changes in log mean pressure difference as a result of changing reactor pressure levels for each run. Recycle Compressor: The recycle compressor was designed for approximately 0.495 m3/s of flow with reciprocating compressors as the suitable choice [14]. Due to a smaller pressure difference, single stage compression is sufficient, and the compressor was priced using duty and 75% efficiency. 3.3 Heat Integration In order to improve the energy efficiency of the methanol plant, heat integration is performed to recover process heat, using Aspen Energy Analyzer (AEA) v7.2 coupled with the Aspen HYSYS v7.2 simulation of the methanol process. The Utility Composite Curve from pinch analysis is shown in Figure 4 with minimum approach temperature (dTmin) contribution for various streams listed in Table 2. From Figure 4, the shifted process pinch temperature is 135.3°C and the overall heating and cooling targets are 15.9 MW and 13.3 MW respectively. The area target returned by AEA is 2345 m2 for 1 shell pass and 2-tube pass heat exchangers. Due to the lower price of natural gas compared to steam, AEA program recommends generating high amounts of steam from the fired heater as seen in Figure 4. However, the credit from exporting steam may be diminished if there is lack of demand for steam. Hence, the plant will not generate excess steam from natural gas.
Figure 4: Utility Composite Curve for Methanol Plant Process Table 2: dTmin Contribution for Each of the Stream Types Stream Type Condensing/vaporizing Liquid Gas
dTmin contribution (K) 2.5 5.0 7.5
Subsequently, a Heat Exchanger Network (HEN) is designed with the following operating constraints: (1) HP steam for SMR is to be generated in the furnace to ensure a steady supply of feed for the process; (2) the reforming heat of reaction must be supplied by a furnace to maintain optimal reaction temperature as process heat exchange potentially introduces fluctuations; and (3) crude methanol distillation column condenser and reboiler are to be serviced by utilities to ensure controllability of column operations. 5
4.
RESULTS AND DISCUSSION
Simulations were run for variations in operating parameters beyond the practical constraints applied in industry; this was to explore the potential cost savings from surpassing operating constraints. Data was extracted and costed according to Section 3 with detailed calculations in Section A4.2. The optimal process was then chosen after applying the appropriate constraints and the heat integration study was conducted to obtain the base case. 4.1 Optimization of Steam Methane Reforming Methanol profit excluding methanol synthesis costs was found to increase with higher temperature, lower S/C ratio and pressure while pre-heat temperature was found to have negligible impact (Figure 5). The results show that significant savings are possible in the magnitude of USD 106/yr if equilibrium conversion can be achieved at the extreme ends of the optimization range. Constraints of temperature at 900oC due to mechanical strength limits of tubes [5], pressure at 20 bar and S/C at 2.7 to prevent excessive coking [4] constrains the reforming section to operate at these limits and these are chosen as the base case conditions.
Figure 5: Variation of expected profit with S/C and temperature
Figure 6: Variation of methanol profit with pressure and R: Red surface plot for reaction temperature of 211oC; Green dots for 222oC, Red for 233oC, Magenta for 244oC and multi-colour surface plot for 255oC
Annualized Profit per Methanol, USD$/kg
4.2 Optimization of Methanol Synthesis Loop Figure 6 shows that optimal methanol profit $3,400.00 without reforming cost increases with lower $3,390.00 temperature and higher S/C ratio. However, to $3,380.00 ensure that the equilibrium can be achieved, $3,370.00 temperature was constrained to 255oC [23] and $3,360.00 S/C from 9 to 10 [4]. At these conditions, effect of 6500 7000 7500 8000 8500 9000 9500 Pressure, kPa pressure on cost reaches a plateau at 8900 kPa, as shown in Figure 7, and this is chosen as the Figure 7: Variation of expected profit with Pressure operating pressure. at reactor temperature of 255C and R=9.063 6
4.3 Heat Integration Results Following the practical considerations for heat integration, the HEN shown in Appendix A1.1 is proposed. The heat recovered from the hot syngas is used to preheat methanol reactor feed as well as to vaporize recycled water/condensate for steam reforming reaction. However, natural gas preheating for the SMR reactor is not subjected to process heat exchange as this will cause difficulty in achieving steady state during start up; hence the duty will be provided by LPS. Crude methanol feed to the distillation column is preheated using LPS as the methanol reactor effluent stream is used to generate MPS and LPS for plant-wide heating purposes and there are no other hot process streams in close proximity for process heat exchange. The performance of the proposed HEN is summarized in Table 3. The targets are not fully met due to the operating constraints stated in Section 3.3 as well as practical considerations for process heat exchange due to the physical location of the streams, in which case utility steam is generated for energy recovery. Table 3: HEN Performance Summary Overall targets Heating (MW) Cooling (MW) Total area (m2) Utility targets Fired Heater (MW) HPS (MW) MPS (MW) LPS (MW) HPS generation (MW) MPS generation (MW) LPS generation (MW) Cooling Water (MW)
Target 15.9 13.3 2345
Current 26.8 24.2 2078
32.7 0 0 0 7.3 8.1 1.3 13.3
23.4 0 3.5 0.3 0 7.1 0.9 16.2
4.4 Base Case Plant The integrated results from the process optimization and pinch analysis are summarized in Table 4 and the equipment schedule is shown in Section A4 with the PFD and stream data for the base case in Appendix A1.1. Table 4: Base Case Conditions for Methanol Plant Temperature
Steam Methane Reforming 900C
Pressure
2000kPa
S/C Ratio / R Value
2.7
Utilities
Furnace Duty: 22,998kW Cooling Water: 5493.5kW
Conversion
85.0% Methane Conversion
Methanol Synthesis Loop 255C 8010kPa (adjusted after heat integration) 9.035 MPS Generation: 3,672kW Cooling Water: 10,732kW Compression Duty: 4,128kW 93.7% Syngas Conversion
With the capital and utility costs, additional direct, general and fixed manufacturing costs were factored using multiplication factors on the process data [24]. Grassroots cost were used to account for off-site and auxiliary costs. A straight line depreciation method typical of Europe [25] was used in generating the cash flow diagram. Detailed calculations can be found in Section A4.2.
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Natural Gas Price, EURO/kg
Cumulative Discounted Cash Flow (in Million EUROs)
40 30 20 10 0 -10
0
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10 11 12
-20 -30 -40
0.7 0.65 0.6 0.55 0.5 0.45 0.4 0.35 0.3 0.25 0.2 0.1
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Methanol Price, EURO/kg
Year
Figure 8: Cumulative discounted cash flow for 10% discount, 30% tax and 10 years plant life
Figure 9: Breakeven methanol price for different price of natural gas
The fixed capital investment required is €31,562,300, and cost of manufacturing is €29,520,590 for natural gas price of €0.361/kg [26]. Taking methanol price to be €0.413/kg and hydrogen price €8.04/kg, the revenue is €43,952,670. The payback period for the base case is 3.2 years from the time of plant start-up after 2 years of allocated construction time. The net present value (NPV) of the investment is €32,840,270, as shown in the cash flow diagram in Figure 8. The breakeven price for methanol is €0.3285/kg holding other prices constant and discount rate at 10%. 4.5 Sensitivity Analysis To understand the susceptibility of profits to the various parameters affecting the plant costs, a sensitivity analysis was conducted. 10% changes in key parameters were made, and the change in NPV was measured as a percentage of the NPV reported above; these results are reported in Table 5. Table 5: Sensitivity of NPV to 10% changes in key parameters 10% Change in Methanol Price Natural Gas Price Hydrogen Price Boiler Feed Water Price Capital Cost
% Change in NPV 25.8 -24.3 27.2 -0.6 -7.98
As observed, the production costs are most susceptible to changes in the methanol, hydrogen and natural gas prices as expected. It is much less sensitive to the raw material price of boiler feed water since it represents a smaller portion of overall costs, and capital cost changes have a smaller effect because of its diluted effect over the plant life. 4.6 Economic Analysis From cost calculations of the base case, a range of breakeven prices for the given discount rate can be calculated for each variation in natural gas price. This is summarized in Figure 9. To understand the impact of market volatility in natural gas and methanol, price trends were obtained from BP and Methanex market surveys for the past 10 years [27] [28]. The price fluctuations were quantified by performing a polynomial regression on the data points and determining the deviations from the expected trend. Figure 10 and Figure 11 show the regression data:
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14
€ 600
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€ 500 Euro/MT
USD$/GJ
10 8 6 y=
4
-0.0691x2 +
1.7619x + 0.7863 R² = 0.841
€ 400 € 300 € 200 € 100
2
y = 0.0005x3 - 0.1022x2 + 7.0285x + 120.99 R² = 0.3264
€0
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Index Time
Figure 11: Methanol prices for 2002 to 2013 from Methanex Report
Figure 10: Natural gas prices for 2001 to 2011 from BP Report
-15 -6 3 12 21 30 39 48 57 66 75 84 93 102 111 120
Frequency
Although, price estimation involves a more complex interaction of supply and demand, these plots provide a statistical estimate for the expected volatility for initial projections. From these, natural gas was determined to fluctuate from 16.6% to -19.7%; for methanol, 17% to -22%. To estimate the range of variation in sales volume, the world methanol capacity was taken as an index to obtain a fluctuation of 40% in production volume [29]. Using these 40 120% variations, Monte Carlo simulations were conducted 35 100% assuming triangular distribution of parameters 30 80% 25 within the assumed fluctuations, to calculate NPV 20 60% for each random permutation. Figure 12 displays the 15 40% 10 plot of NPV frequency distribution. It can be seen 20% 5 that, despite the price and volume fluctuations, there 0 0% is only a 7.5% chance of making a negative NPV. NPV, Million Euros This indicates that the cash position of the plant is safe from the volatility of the market for the given Figure 12: Frequency Distribution of NPVs price fluctuations. Standard deviation of the generated from random permutations of volatile distribution in Figure 12 is €22.8mil. parameters 4.7 Case 1: Biogas substitution To investigate the impact of biogas, yield, productivity and throughput data for the available food waste were obtained from the literature, and these are summarized in Table 6: Table 6: Biogas Kinetic Data Organic Load
Methane Yield
Corn Silage Corn Grain Wastewater (Slaughterhouse) Animal Waste (Chicken Dropping) Pre-treated Wheat Straw
181 L/kg.TS 300 L/kg.TS
Productivity, m3.CH4/m3/day 0.73 5.4
240 L/kg.COD
0.72
207 L/kg.VS
0.37
349L/kg.TS
3.11
9
Throughput of Organic Waste 5400 MT/yr 2600 MT/yr 150,000 m3/yr 5000 mg.COD/L 30,000 MT/yr 40% TS, 85% VS 1257.8 MT/yr 40% TS, 85% VS
Reference [30] [31] [32] [33] [34]
These data represent an average of the relative crop rates; actual values are scattered about these estimates [34] [35]. Corn grain is clearly more productive, which allows the reactor size to be smaller. This effect on capital cost was calculated with costing exponential factor of 0.7 taken from [36] for the reactor and auxiliary facility costs as well as compression requirements and storage. The operating cost would vary with the amount of load transported and the travel duration [37] while heating costs were neglected due to surplus heat streams from the main process. The costs were annualized across the plant life and an average cost for each kg of biomethane is calculated. From this, it was concluded that wastewater is unprofitable to use in isolation because the transportation of the dilute organic load is uneconomical; the final cost of biomethane from such production is 3 times the natural gas price (€10.09/kg vs €0.361/kg). For solid waste, the savings in transportation allows biogas to be produced at a lowest possible productivity value of 0.118 m3 of CH4/m3/day while maintaining biogas cost to be comparable to natural gas price; this productivity is easily achieved in industry and literature. Economic Analysis: From Table 6, several options to utilize the available waste for biogas production were analysed to maintain positive NPV as shown in Table 7. Option 1 is the base case without any biogas, Option 2 maximizes NPV by only utilizing the corn grain, Option 3 maximizes the production of biogas, Option 4 maximizes NPV with a substitute for corn of plant origin, and Option 5 is the scenario where all solid waste was processed to take advantage of the cheaper transport. The effect of each biogas substitution option on the Monte Carlo simulated probability of earning a negative NPV is also reported. This was done by reducing the variability and price of natural gas as a result of partial substitution by biogas and assuming biogas does not fluctuate in price. As seen in Table 2, the biogas substitution is economically justified, and the best improvement in NPV is from Option 5. Table 7: Biogas Production Scenarios Description Biomethane Produced, KT/yr Biomethane Cost, USD$/kg kg.CO2eq/kg.methanol NPV Change, USD$ % of -ve NPV
Option 1 0 0.4689 0.6587 0.00 7.52
Option 2 0.439 0.0981 0.6504 259,732.00 7.33
Option 3 2.027 0.4689 0.6174 0.00 7.99
Option 4 0.439 0.0900 0.6180 28,153.00 7.72
Option 5 1.995 0.2714 0.6173 1,688,303.00 6.53
Environmental Analysis: The carbon emissions data for each of the above options was also analyzed to consider their environmental impact. This was developed by defining the system boundary to include the natural gas production facility from fossil fuels, the treatment facilities of the respective organic wastes, the alternative biogas production facilities for each respective organic wastes and the effect of transportation. The effect of post-digestion sludge as well as the methanol plant was deemed to stay constant for all scenarios. Greenhouse gas emission data were adapted from life cycle assessment studies from [38] and [39] with global warming potential equivalency taken from [40]. Appendix A1.3 provides an elaborate write-up on the environmental analysis. As seen in Table 7, Options 3 and 5 are the scenarios with the most carbon reduction. Choice of Biogas Substitution Option: The best option is clearly Option 5. It yields the highest NPV increase, has a lower probability of making a loss and has superior levels of carbon reduction. This is because the transportation of solid wastes is both economical and environmentally sustainable, and hence it should be capitalized. 10
Food for Energy: Corn has the best productivity and yield, and maximizing its use in biogas production for Option 2 also yields some carbon reduction. However, its competition for arable land may cause overall poorer performance in other life cycle parameters such as human health, ecosystem quality and resource depletion [41]. This also spills over to market pressures to increase food price. This should and can be avoided with readily available alternatives such as straw, fruits and vegetable waste or plant residues [42]. For example, wheat straw pre-treated with alkaline can achieve very high productivity similar to that of corn [34]; accordingly, Options 2 and 4 clearly show a similar performance to the high productivity of corn grain. Alternatively, co-digestion of fruits and vegetable waste with manure or slaughterhouse wastewater can yield up to 51.5% increase in biogas yield [43]. Co-digestion of wheat straw and chicken manure is also possible [44]. Therefore, these options of direct substitution and co-digestion are viable alternatives. 4.8 Case 2: Carbon Capture Technology The methanol production process leads to carbon dioxide effluents from its purge stream (which can be routed to flare systems or into the furnace for additional fuel) and from furnace flue gas stream. These must be effectively captured to the desired flow of 200 MT/day required for the production rate enhancement. Table 8 summarizes the effluents specifications for re-use. Table 8: Flue Gas and Target Composition Available Flue Gas Composition Target Feed Composition 138 MT/day 200 MT/day Mass Flow ~ 1 bar 22.2 bar Pressure ~ 200 °C ~ 200 °C Temperature Composition in Mole Fraction unless otherwise stated 0.171 < 600 ppm Water 0.0893 > 0.95 CO2 0.0175 < 10 ppm Oxygen 0.723 < 0.04 Nitrogen
An additional 62 MT/day of CO2 is necessary, and this can be obtained from fossil-fuel firing units; these include power plants or other chemical plants in neighbouring complexes depending on transport constraints. The CO2 effluent stream would need to be purified to prevent introducing excess inert gases such as nitrogen that would strain the recycle loop; to conform to certain standards, the IPCC standard will be used [45]. The purification can be setup as a pre-combustion, post-combustion or oxyrecycle [46]. The post-combustion method was chosen due to its flexibility of installation, suitability over the oxy-recycle method specifically for natural gas fuels in the furnace as well as the need to preserve carbon within the syngas flow for process purposes. For this method, CO2 is removed after it leaves the furnace and options for performing the purification can be chosen as shown in Table 9. Table 9: Summary of Different Carbon Dioxide Purification Technologies; See Text for References
Energy Usage, GJ/kg.CO2 Cost, €/kg.CO2 Plant Life and Discount Rate
Absorption (MEA) 3.5 28 20 yrs, 10%
Adsorption 3.23 44 25 yrs, 7%
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Membrane Separation 0.605 80 25 yrs, 5%
Cryogenic Distillation High Vacuum High Refrigeration
Cryogenic distillation is generally taken to be too expensive due to its extreme conditions [46]. Data for membrane separation from [47] reports the lowest energy, unlike the excessive heating or recompression in liquid absorption and pressure swing adsorption (PSA); however, it is most expensive due to the need for multi-stage membrane modules and compression for the low pressure carbon dioxide feed. PSA energy usage reported in [48] is slightly better than that from absorption via monoethanol amine (MEA) [49] despite the reported cost for the latter [50] to be cheaper than the former as shown by [51]. From this, it is evident that there is a trade-off between profitability and energy use. In consideration of economics and environmental energy concerns, liquid absorption with MEA is ideal. This is due to it being the cheapest technology and most convenient to integrate in terms of energy use; it only requires once-through compression as opposed to cycles in adsorption, and its heating duty can be easily provided from the excess heat in the plant, hence mitigating its energy penalty. In addition, membrane operation is inherently more prone to aging and poisoning issues such as membrane wetting or plugging [52], therefore it is also superior in technical robustness. With this in mind, the liquid absorption method was chosen.
Figure 13: Liquid Absorption via MEA System
5.
Figure 13 shows the schematic representation of the chosen carbon dioxide purification system. Flue gas is pressurized as required, CO2 is absorbed by lean MEA solvent, and then it is boiled off in the regenerator column to release the high pressure CO2 as feed to the steam reforming section. Steam required for regeneration/ reboiler is readily available from the main process steam facilities.
CONCLUSIONS
As shown in this preliminary process development, the base case for methanol production is profitable to a company setting up operations within the European context. Furthermore, the traditional process of methanol production holds potential for increased cost savings if operating constraints in reactor design can be overcome to achieve equilibrium at more extreme conditions. In the context of sustainable development, options to substitute the traditional natural gas feed with renewable biogas as well as carbon capture were evaluated and shown to be economically justified while reducing carbon emissions for the plant. This supports the relevance of the traditional methanol production process in a modern technical, economic and environmental perspective. In this study on methanol process development and design, steam methane reforming, methanol synthesis, distillation and absorption of carbon dioxide are well-established technologies that can be designed and implemented readily. On the other hand, hydrogen separation using membrane technology is a relatively newer technology, and biogas generation requires further testing on the specific feedstock to affirm the suitability of the feed. Further work on these is recommended before implementing the proposed methanol process with biogas substitution for part of the natural gas feed.
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A1.
APPENDICES
A1.1 A1.2 A1.3
Appendix A: Process Flow Diagram and Stream Data Table Appendix B: HYSYS Simulation and Optimization Details Appendix C: Biogas Life Cycle System Boundary and Details
A2.
METHANOL PLANT SIMULATION FILE
A3.
AEA HEAT INTEGRATION FILE
A4.
MS EXCEL SPREADSHEETS
A4.1 A4.2
Optimization Spreadsheet Cost Spreadsheet
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15
A1.1
APPENDIX A
1 Stream Number Temperature, C 41.369 Pressure, kPa 7500.000 Molar Flow, kmol/h 222.222 Mass Flow, kg/hr 3876.800 Composition, mol fraction Methane 9.000E-01 Ethane 1.000E-01 Water 0.000E+00 Hydrogen 0.000E+00 Carbon Monoxide 0.000E+00 Carbon Dioxide 0.000E+00 Methanol 0.000E+00 Ethanol 0.000E+00 11 Stream Number Temperature, C 35.000 Pressure, kPa 956.498 Molar Flow, kmol/h 901.077 Mass Flow, kg/hr 8623.949 Composition, mol fraction Methane 4.080E-02 Ethane 1.031E-06 Water 6.164E-03 Hydrogen 7.226E-01 Carbon Monoxide 1.747E-01 Carbon Dioxide 5.579E-02 Methanol 0.000E+00 Ethanol 0.000E+00
2 76.831 6750.000 222.222 3876.800
3 11.995 2222.000 222.222 3876.800
4 219.137 2222.000 540.039 9730.254
5 218.284 2222.000 263.500 4746.979
6 219.951 2222.000 276.539 4983.275
7 900.000 1799.820 1177.615 13607.224
8 484.962 1619.838 1177.615 13607.224
9 136.754 1457.854 1177.615 13607.224
10 35.000 956.498 1177.615 13607.224
9.000E-01 1.000E-01 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00
9.000E-01 1.000E-01 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00
1.915E-09 1.214E-15 9.999E-01 5.156E-06 1.580E-06 1.026E-04 0.000E+00 0.000E+00
1.915E-09 1.214E-15 9.999E-01 5.156E-06 1.580E-06 1.026E-04 0.000E+00 0.000E+00
3.739E-09 2.370E-15 9.998E-01 1.007E-05 3.086E-06 2.003E-04 0.000E+00 0.000E+00
3.122E-02 7.889E-07 2.395E-01 5.529E-01 1.337E-01 4.273E-02 0.000E+00 0.000E+00
3.122E-02 7.889E-07 2.395E-01 5.529E-01 1.337E-01 4.273E-02 0.000E+00 0.000E+00
3.122E-02 7.889E-07 2.395E-01 5.529E-01 1.337E-01 4.273E-02 0.000E+00 0.000E+00
3.122E-02 7.889E-07 2.395E-01 5.529E-01 1.337E-01 4.273E-02 0.000E+00 0.000E+00
12 206.850 3359.884 901.077 8623.949
13 53.000 3023.896 901.077 8623.949
14 187.445 8010.000 901.077 8623.949
15 105.530 8010.000 3253.539 18420.662
16 35.000 956.498 276.539 4983.275
17 35.122 2282.000 276.539 4983.275
18 255.000 7209.000 4154.626 27044.836
19 255.000 6488.100 3765.392 27044.661
20 195.024 5839.290 3765.392 27044.661
4.080E-02 1.031E-06 6.164E-03 7.226E-01 1.747E-01 5.579E-02 0.000E+00 0.000E+00
4.080E-02 1.031E-06 6.164E-03 7.226E-01 1.747E-01 5.579E-02 0.000E+00 0.000E+00
4.080E-02 1.031E-06 6.164E-03 7.226E-01 1.747E-01 5.579E-02 0.000E+00 0.000E+00
1.347E-01 3.350E-06 2.563E-04 8.141E-01 1.893E-02 2.501E-02 6.986E-03 0.000E+00
3.739E-09 2.370E-15 9.998E-01 1.007E-05 3.086E-06 2.003E-04 0.000E+00 0.000E+00
3.739E-09 2.370E-15 9.998E-01 1.007E-05 3.086E-06 2.003E-04 0.000E+00 0.000E+00
1.143E-01 2.847E-06 1.538E-03 7.943E-01 5.272E-02 3.168E-02 5.472E-03 0.000E+00
1.261E-01 3.142E-06 1.293E-02 7.618E-01 1.772E-02 2.373E-02 5.772E-02 0.000E+00
1.261E-01 3.142E-06 1.293E-02 7.618E-01 1.772E-02 2.373E-02 5.772E-02 0.000E+00
21 Stream Number Temperature, C 169.832 Pressure, kPa 5255.361 Molar Flow, kmol/h 3765.392 Mass Flow, kg/hr 27044.661 Composition, mol fraction Methane 1.261E-01 Ethane 3.142E-06 Water 1.293E-02 Hydrogen 7.618E-01 Carbon Monoxide 1.772E-02 Carbon Dioxide 2.373E-02 Methanol 5.772E-02 Ethanol 0.000E+00
22 40.000 4729.825 3765.392 27044.661
23 40.000 4729.825 243.102 7102.405
24 40.000 4729.825 3522.290 19942.256
25 70.000 365.000 243.102 7102.405
26 134.053 304.955 40.989 738.424
27 64.607 101.325 198.034 6250.544
28 45.923 101.325 4.079 113.437
29 48.978 5416.000 175.036 352.873
30 42.273 5400.000 93.715 1168.721
1.261E-01 3.142E-06 1.293E-02 7.618E-01 1.772E-02 2.373E-02 5.772E-02 0.000E+00
2.330E-03 1.179E-07 1.966E-01 3.064E-03 1.070E-04 5.079E-03 7.929E-01 0.000E+00
1.347E-01 3.350E-06 2.563E-04 8.141E-01 1.893E-02 2.501E-02 6.986E-03 0.000E+00
2.330E-03 1.179E-07 1.966E-01 3.064E-03 1.070E-04 5.079E-03 7.929E-01 0.000E+00
1.203E-30 1.656E-73 1.000E+00 1.433E-30 3.262E-50 1.633E-30 2.198E-06 0.000E+00
4.174E-05 5.156E-10 3.421E-02 2.901E-05 2.260E-06 2.138E-04 9.655E-01 0.000E+00
1.369E-01 7.001E-06 5.244E-03 1.812E-01 6.265E-03 2.923E-01 3.781E-01 0.000E+00
0.000E+00 0.000E+00 0.000E+00 1.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00
3.863E-01 9.608E-06 7.351E-04 4.669E-01 5.429E-02 7.173E-02 2.003E-02 0.000E+00
A1.2
APPENDIX B
This appendix provides additional details and assumptions of the simulations in Section A2 to support the main features discussed in the main report regarding process development and optimization procedures in Sections 3.1, 3.2, 4.1 and 4.2. General Simulation and Optimization Assumptions For the simulations, HYSYS files used were developed according to a generic heat exchange network. The core assumption is that the effect of heat integration presents a similar effect to all simulations. In addition, HYSYS files used for optimization in each segment were separately developed to minimize convergence errors across segments. The core assumption in this was that minor process parameters, apart from the main factors discussed in Section 3, have marginal effect on the overall process performance. In the process development, pressure drops across heat exchangers and reactors was taken to be 10% of inlet pressure for gases, 60 kPa for liquids of viscosity 1-10 mN.s/m2 and 35 kPa for
