esc 2013 winner

1

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 mono-

ethanol amines, as elaborated in Section 4.8.

2

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: (∆H25C = 206kJ/mol) ----------------- (1)

Water Gas Shift: (∆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 copper-

alumina 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: (∆H25C = -91kJ/mol) --------------- (3)

Modified Stoichiometric Ratio:

-------------------------------------------------------- (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.

3

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

Convection

Section

Radiant

Section Compression Conversion

Pressure ↓ Uncertain Uncertain ↓ ↓

Pre-heat Temperature NA ↓ ↑ Uncertain ↑

Outlet Temperature NA NA ↓ Uncertain ↑

S/C Ratio NA ↓ ↓ ↓ ↑

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].

4

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

pinch analysis together with the steam

reforming heat exchangers.

Figure 1: Schematic for inter-linked effects of varying

parameters – independent variables (black), parameters

affecting cost (shaded pink), calculated parameters (blue)

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].

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.

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

1.51

1.52

1.53

1.54

1.55

1.56

20 25 30 35 40 45 50

An

nu

aliz

ed

Co

sts

(USD

$m

il)

Number of Stages

5

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 dTmin contribution (K)

Condensing/vaporizing 2.5

Liquid 5.0

Gas 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.

6

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 233

oC, Magenta for 244

oC

and multi-colour surface plot for 255oC

4.2 Optimization of Methanol Synthesis Loop

Figure 6 shows that optimal methanol profit

without reforming cost increases with lower

temperature and higher S/C ratio. However, to

ensure that the equilibrium can be achieved,

temperature was constrained to 255oC [23] and

S/C from 9 to 10 [4]. At these conditions, effect of

pressure on cost reaches a plateau at 8900 kPa, as

shown in Figure 7, and this is chosen as the

operating pressure.

Figure 7: Variation of expected profit with Pressure

at reactor temperature of 255C and R=9.063

$3,360.00

$3,370.00

$3,380.00

$3,390.00

$3,400.00

6500 7000 7500 8000 8500 9000 9500

An

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ed

Pro

fit

pe

r M

eth

ano

l, U

SD$

/kg

Pressure, kPa

7

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 Target Current

Heating (MW) 15.9 26.8

Cooling (MW) 13.3 24.2

Total area (m2) 2345 2078

Utility targets

Fired Heater (MW) 32.7 23.4

HPS (MW) 0 0

MPS (MW) 0 3.5

LPS (MW) 0 0.3

HPS generation (MW) 7.3 0

MPS generation (MW) 8.1 7.1

LPS generation (MW) 1.3 0.9

Cooling Water (MW) 13.3 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

Steam Methane Reforming Methanol Synthesis Loop

Temperature 900C 255C

Pressure 2000kPa 8010kPa

(adjusted after heat integration)

S/C Ratio / R Value 2.7 9.035

Utilities Furnace Duty: 22,998kW

Cooling Water: 5493.5kW

MPS Generation: 3,672kW

Cooling Water: 10,732kW

Compression Duty: 4,128kW

Conversion 85.0% Methane Conversion 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.

8

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 % Change in NPV

Methanol Price 25.8

Natural Gas Price -24.3

Hydrogen Price 27.2

Boiler Feed Water Price -0.6

Capital Cost -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:

-40

-30

-20

-10

0

10

20

30

40

0 1 2 3 4 5 6 7 8 9 10 11 12

Cu

mu

lati

ve D

isco

un

ted

Cas

h F

low

(in

M

illio

n E

UR

Os)

Year

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.1 0.2 0.3 0.4 0.5 0.6

Nat

ura

l Gas

Pri

ce, E

UR

O/k

g

Methanol Price, EURO/kg

9

Figure 10: Natural gas prices for 2001 to 2011 from

BP Report

Figure 11: Methanol prices for 2002 to 2013 from

Methanex Report

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

Figure 12: Frequency Distribution of NPVs

generated from random permutations of volatile

parameters

of 40% in production volume [29]. Using these

variations, Monte Carlo simulations were conducted

assuming triangular distribution of parameters

within the assumed fluctuations, to calculate NPV

for each random permutation. Figure 12 displays the

plot of NPV frequency distribution. It can be seen

that, despite the price and volume fluctuations, there

is only a 7.5% chance of making a negative NPV.

This indicates that the cash position of the plant is

safe from the volatility of the market for the given

price fluctuations. Standard deviation of the

distribution in Figure 12 is €22.8mil.

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 Productivity,

m3.CH4/m

3/day

Throughput of

Organic Waste Reference

Corn Silage 181 L/kg.TS 0.73 5400 MT/yr [30]

Corn Grain 300 L/kg.TS 5.4 2600 MT/yr [31]

Wastewater

(Slaughterhouse) 240 L/kg.COD 0.72

150,000 m3/yr

5000 mg.COD/L [32]

Animal Waste

(Chicken Dropping) 207 L/kg.VS 0.37

30,000 MT/yr

40% TS, 85% VS [33]

Pre-treated Wheat

Straw 349L/kg.TS 3.11

1257.8 MT/yr

40% TS, 85% VS [34]

y = -0.0691x2 + 1.7619x + 0.7863 R² = 0.841

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12

USD

$/G

J

Index Time

y = 0.0005x3 - 0.1022x2 + 7.0285x + 120.99 R² = 0.3264 € 0

€ 100

€ 200

€ 300

€ 400

€ 500

€ 600

0 50 100 150

Euro

/MT

Index Time

0%

20%

40%

60%

80%

100%

120%

0

5

10

15

20

25

30

35

40

-15

-6

3

12

21

30

39

48

57

66

75

84

93

10

2

11

1

12

0

Fre

qu

en

cy

NPV, Million Euros

10

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/m

3/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 Option 1 Option 2 Option 3 Option 4 Option 5

Biomethane Produced, KT/yr 0 0.439 2.027 0.439 1.995

Biomethane Cost, USD$/kg 0.4689 0.0981 0.4689 0.0900 0.2714

kg.CO2eq/kg.methanol 0.6587 0.6504 0.6174 0.6180 0.6173

NPV Change, USD$ 0.00 259,732.00 0.00 28,153.00 1,688,303.00

% of -ve NPV 7.52 7.33 7.99 7.72 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.

11

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

Mass Flow 138 MT/day 200 MT/day

Pressure ~ 1 bar 22.2 bar

Temperature ~ 200 °C ~ 200 °C

Composition in Mole Fraction unless otherwise stated Water 0.171 < 600 ppm

CO2 0.0893 > 0.95

Oxygen 0.0175 < 10 ppm

Nitrogen 0.723 < 0.04

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 oxy-

recycle [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

Absorption

(MEA)

Adsorption Membrane

Separation

Cryogenic

Distillation

Energy Usage, GJ/kg.CO2 3.5 3.23 0.605 High Vacuum

High

Refrigeration Cost, €/kg.CO2 28 44 80

Plant Life and Discount Rate 20 yrs, 10% 25 yrs, 7% 25 yrs, 5%

12

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 re-

compression 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 mono-

ethanol 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.

5. 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.

Figure 13: Liquid Absorption via MEA

System

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.

13

A1. APPENDICES

A1.1 Appendix A: Process Flow Diagram and Stream Data Table

A1.2 Appendix B: HYSYS Simulation and Optimization Details

A1.3 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 Optimization Spreadsheet

A4.2 Cost Spreadsheet

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A1.1 APPENDIX A

Stream Number 1 2 3 4 5 6 7 8 9 10

Temperature, C 41.369 76.831 11.995 219.137 218.284 219.951 900.000 484.962 136.754 35.000

Pressure, kPa 7500.000 6750.000 2222.000 2222.000 2222.000 2222.000 1799.820 1619.838 1457.854 956.498

Molar Flow, kmol/h 222.222 222.222 222.222 540.039 263.500 276.539 1177.615 1177.615 1177.615 1177.615

Mass Flow, kg/hr 3876.800 3876.800 3876.800 9730.254 4746.979 4983.275 13607.224 13607.224 13607.224 13607.224

Composition, mol fraction

Methane 9.000E-01 9.000E-01 9.000E-01 1.915E-09 1.915E-09 3.739E-09 3.122E-02 3.122E-02 3.122E-02 3.122E-02

Ethane 1.000E-01 1.000E-01 1.000E-01 1.214E-15 1.214E-15 2.370E-15 7.889E-07 7.889E-07 7.889E-07 7.889E-07

Water 0.000E+00 0.000E+00 0.000E+00 9.999E-01 9.999E-01 9.998E-01 2.395E-01 2.395E-01 2.395E-01 2.395E-01

Hydrogen 0.000E+00 0.000E+00 0.000E+00 5.156E-06 5.156E-06 1.007E-05 5.529E-01 5.529E-01 5.529E-01 5.529E-01

Carbon Monoxide 0.000E+00 0.000E+00 0.000E+00 1.580E-06 1.580E-06 3.086E-06 1.337E-01 1.337E-01 1.337E-01 1.337E-01

Carbon Dioxide 0.000E+00 0.000E+00 0.000E+00 1.026E-04 1.026E-04 2.003E-04 4.273E-02 4.273E-02 4.273E-02 4.273E-02

Methanol 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00

Ethanol 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00 0.000E+00

Stream Number 11 12 13 14 15 16 17 18 19 20

Temperature, C 35.000 206.850 53.000 187.445 105.530 35.000 35.122 255.000 255.000 195.024

Pressure, kPa 956.498 3359.884 3023.896 8010.000 8010.000 956.498 2282.000 7209.000 6488.100 5839.290

Molar Flow, kmol/h 901.077 901.077 901.077 901.077 3253.539 276.539 276.539 4154.626 3765.392 3765.392

Mass Flow, kg/hr 8623.949 8623.949 8623.949 8623.949 18420.662 4983.275 4983.275 27044.836 27044.661 27044.661


Methane 4.080E-02 4.080E-02 4.080E-02 4.080E-02 1.347E-01 3.739E-09 3.739E-09 1.143E-01 1.261E-01 1.261E-01

Ethane 1.031E-06 1.031E-06 1.031E-06 1.031E-06 3.350E-06 2.370E-15 2.370E-15 2.847E-06 3.142E-06 3.142E-06

Water 6.164E-03 6.164E-03 6.164E-03 6.164E-03 2.563E-04 9.998E-01 9.998E-01 1.538E-03 1.293E-02 1.293E-02

Hydrogen 7.226E-01 7.226E-01 7.226E-01 7.226E-01 8.141E-01 1.007E-05 1.007E-05 7.943E-01 7.618E-01 7.618E-01

Carbon Monoxide 1.747E-01 1.747E-01 1.747E-01 1.747E-01 1.893E-02 3.086E-06 3.086E-06 5.272E-02 1.772E-02 1.772E-02

Carbon Dioxide 5.579E-02 5.579E-02 5.579E-02 5.579E-02 2.501E-02 2.003E-04 2.003E-04 3.168E-02 2.373E-02 2.373E-02

Methanol 0.000E+00 0.000E+00 0.000E+00 0.000E+00 6.986E-03 0.000E+00 0.000E+00 5.472E-03 5.772E-02 5.772E-02


Stream Number 21 22 23 24 25 26 27 28 29 30

Temperature, C 169.832 40.000 40.000 40.000 70.000 134.053 64.607 45.923 48.978 42.273

Pressure, kPa 5255.361 4729.825 4729.825 4729.825 365.000 304.955 101.325 101.325 5416.000 5400.000

Molar Flow, kmol/h 3765.392 3765.392 243.102 3522.290 243.102 40.989 198.034 4.079 175.036 93.715

Mass Flow, kg/hr 27044.661 27044.661 7102.405 19942.256 7102.405 738.424 6250.544 113.437 352.873 1168.721


Methane 1.261E-01 1.261E-01 2.330E-03 1.347E-01 2.330E-03 1.203E-30 4.174E-05 1.369E-01 0.000E+00 3.863E-01

Ethane 3.142E-06 3.142E-06 1.179E-07 3.350E-06 1.179E-07 1.656E-73 5.156E-10 7.001E-06 0.000E+00 9.608E-06

Water 1.293E-02 1.293E-02 1.966E-01 2.563E-04 1.966E-01 1.000E+00 3.421E-02 5.244E-03 0.000E+00 7.351E-04

Hydrogen 7.618E-01 7.618E-01 3.064E-03 8.141E-01 3.064E-03 1.433E-30 2.901E-05 1.812E-01 1.000E+00 4.669E-01

Carbon Monoxide 1.772E-02 1.772E-02 1.070E-04 1.893E-02 1.070E-04 3.262E-50 2.260E-06 6.265E-03 0.000E+00 5.429E-02

Carbon Dioxide 2.373E-02 2.373E-02 5.079E-03 2.501E-02 5.079E-03 1.633E-30 2.138E-04 2.923E-01 0.000E+00 7.173E-02

Methanol 5.772E-02 5.772E-02 7.929E-01 6.986E-03 7.929E-01 2.198E-06 9.655E-01 3.781E-01 0.000E+00 2.003E-02


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 <1 mN.s/m2. For the distillation column, a pressure drop of 0.007 bar per tray was estimated together with expected pressure drop from height differences according to the general formula of “ΔP = ρgh”. The reflux pump for the column was sized to make-up for this pressure loss in the reflux stream.

Costing Conventions for Optimization As mentioned, the objective function of each run was characterized by profit. The optimization for steam methane reforming uses the following objective function:

𝑃𝑟𝑜𝑓𝑖𝑡 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑀𝑒𝑡ℎ𝑎𝑛𝑜𝑙 𝑆𝑦𝑛𝑡ℎ𝑒𝑠𝑖𝑠 𝐶𝑜𝑠𝑡 = 𝐶𝑒𝑥𝑝 + 𝐶𝐶𝑜𝑚𝑝 + 𝐶𝐹𝑢𝑟𝑛𝑎𝑐𝑒 + 𝐶𝑉𝑒𝑠𝑠𝑒𝑙 + 𝑅𝑀𝑒𝑡ℎ𝑎𝑛𝑜𝑙

Where, Cexp – Annualized Capital and Operating Cost of Expander Turbine, US$ Ccomp – Annualized Capital and Operating Cost of Make-up Compression Train, US$ Cfurnace – Annualized Capital and Operating Cost of Furnace, US$ CVessel – Annualized Capital and Operating Cost of Water Let Down Vessel, US$ Rmethanol – Revenue for expected methanol conversion from syngas produced, US$

The optimization for the methanol synthesis loop utilizes the following objective function:

𝑃𝑟𝑜𝑓𝑖𝑡 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑅𝑒𝑓𝑜𝑟𝑚𝑖𝑛𝑔 𝐶𝑜𝑠𝑡𝑠= 𝐶𝑅𝑒𝑎𝑐𝑡𝑜𝑟 + 𝐶𝐸𝑥𝑐ℎ𝑎𝑛𝑔𝑒𝑟𝑠 + 𝐶𝐶𝑜𝑚𝑝 + 𝐶𝑀𝑒𝑚𝑏𝑟𝑎𝑛𝑒 + 𝐶𝐷𝑖𝑠𝑡𝑖𝑙𝑙𝑎𝑡𝑖𝑜𝑛 + 𝑅𝑀𝑒𝑡ℎ𝑎𝑛𝑜𝑙 + 𝑅𝐻2

Where, Creactor – Annualized Capital and Operating Cost of Methanol Reactor, US$ Cexchangers – Annualized Capital and Operating Cost of Heat Exchangers in Methanol Synthesis, US$ Ccompressors – Annualized Capital and Operating Cost of Recycle Compressor, US$ CDistillation – Annualized Capital and Operating Cost of Methanol Distillation including knock-out vessel, US$ Rmethanol – Revenue for expected methanol conversion from syngas produced, US$ Rhydrogen – Revenue for expected hydrogen recovered from syngas produced, US$

The formulas used for each cost term consists of a summation of annualized capital costs over 10 years using a discount rate of 10% and annual operating costs. The operating costs are proportional to the respective utility stream used while the capital costs depend on the characteristic parameter used in the modular costing method.

Operating Costs: The utilities used are cooling water, boiler feed water, medium pressure steam, natural gas and electricity. The costs and streams used are shown in “A4.2 Cost Spreadsheet.xlsx” .

Capital Costs: The general formula for capital costing is as such:

𝑃𝑢𝑟𝑐ℎ𝑎𝑠𝑒 𝐶𝑜𝑠𝑡 = 10^ �𝐾1 + 𝐾2lg (A) + 𝐾3�lg (A)�2� ------------------------------- (1)

𝐵𝑎𝑟𝑒 𝑀𝑜𝑑𝑢𝑙𝑒 𝐹𝑎𝑐𝑡𝑜𝑟 1 = 𝐵1 + 𝐵2𝐹𝑀𝐹𝑃 ---------------------------------------------- (2)

𝐵𝑎𝑟𝑒 𝑀𝑜𝑑𝑢𝑙𝑒 𝐹𝑎𝑐𝑡𝑜𝑟 2 = 𝐹𝑀𝐹𝑃 --------------------------------------------------------- (3)

𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝐶𝑜𝑠𝑡 = 𝑃𝑢𝑟𝑐ℎ𝑎𝑠𝑒 𝐶𝑜𝑠𝑡 × 𝐵𝑎𝑟𝑒 𝑀𝑜𝑑𝑢𝑙𝑒 𝐹𝑎𝑐𝑡𝑜𝑟 -------------------------- (4)

𝐹𝑃,𝑉𝑒𝑠𝑠𝑒𝑙 =(P+1)D

2×944×0.9−1.2(P+1)+CA

tmin ------------------------------------------------------------- (5)

Where, K1, K2, K3 – Cost correlation factors B1, B2 – Bare module correlation factors FM – Material Factor FP – Pressure Factor A – Dependent variable

FP,vessel – Pressure Factor for Vessels P – Operating pressure, barg CA – Corrosion Allowance (assumed to be 0.00315), m D – Vessel Diameter, m

Pressure factors for all units except vessels are calculated with a formula of similar form in Equation (1) for the case of high pressures and using pressure in barg as the dependent variable; the value is assumed to be ‘1’ for low pressures or vacuum conditions. For vessels, the pressure factor used is described in Equation (5) using a L/D ratio of 3 and assuming an ellipsoidal head of 2:1 ratio; horizontal vessels are used for volumes larger than 3.8m3. Raw material factors are chosen based on process requirement. Stainless steel is used for any stream containing methanol, alloy steel is used for the furnace, while carbon steel is used for the make-up compressor and steam generation streams. Other constants are obtained from [25] and are summarized in the costing spreadsheet of Section A4. The factor used for annualization of capital costs is:

𝐴𝑛𝑛𝑢𝑎𝑙 𝐶𝑜𝑠𝑡 = 𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝐶𝑜𝑠𝑡 × 𝑟(1+𝑟)𝑛

(1+𝑟)𝑛−1 ----------------------------------------------- (5)

Where, r – Discount rate n – Plant life in number of years

A1.3 APPENDIX C

This appendix provides a clarification for the system boundaries of the options in the biogas substitution case study. These are shown in the diagrams below. The annotation and superscript notes used in these figures are summarized in Table 1.

Table 1: Summary of Annotation and Notes

Superscript Number Description 1 Expressed in terms of potential methane that can be produced from reported kinetics 2 Proportion of feed converted to edible substance 3 Mass of waste 4 Proportion of waste converted to sludge

Figure 1: Option 1 System Boundary

In the base case of Option 1 without biogas substitution, the methanol plant procures natural gas from fossil fuel sources while the potential feedstock for biogas remains in its default treatment procedures. Corn is taken to be used for animal feed and ultimately converted to food; wheat straw and the other organic waste of wastewater and animal waste are assumed to be treated in nearby facilities. The emissions for corn used in animal feed is ignored while the rest were calculated from [39] for the case of energy generation from anaerobic digestion. Methanol production and sludge treatment are ignored as they remain constant across the different options.


Accordingly, routing corn from its default option of animal feed usage to maximize NPV from the high productivity of corn grains would substitute part of the natural gas feedstock from fossil fuels. This results in reduced emissions from fossil fuels, but results in increased emission from transportation of the feedstocks and the biogas treatment procedures. The magnitude of the change in emissions are summed and compared across the options. The subsequent figures elaborate on the last three options.

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