techno-economic for bioethanol from lignocellulosic

THESIS

TECHNO-ECONOMIC FOR BIOETHANOL FROM

LIGNOCELLULOSIC

MONSIKAN VILAIPAN

GRADUATE SCHOOL, KASETSART UNIVERSITY

Academic Year 2019

THESIS APPROVAL

GRADUATE SCHOOL, KASETSART UNIVERSITY

DEGREE:

Master of Engineering (Sustainable Energy and Resources

Engineering)

MAJOR FIELD: Sustainable Energy and Resources Engineering

FACULTY: Engineering

TITLE: Techno-Economic for Bioethanol from Lignocellulosic

NAME: Miss Monsikan Vilaipan

THIS THESIS HAS BEEN ACCEPTED BY

(Assistant Professor Maythee Saisriyoot, Dr.Techn.)

THESIS ADVISOR

(Associate Professor Thongchai Rohitatisha Srinophakun,

Ph.D.)

GRADUATE COMMITTEE

CHAIRMAN

APPROVED BY THE GRADUATE SCHOOL ON

(Associate Professor Srijidtra Charoenlarpnopparut,

Ph.D.)

DEAN

THESIS

TECHNO-ECONOMIC FOR BIOETHANOL FROM LIGNOCELLULOSIC

MONSIKAN VILAIPAN

A Thesis Submitted in Partial Fulfillment of

the Requirements for the Degree of

Master of Engineering (Sustainable Energy and Resources Engineering)

Graduate School, Kasetsart University

Academic Year 2019

C

ABST RACT Monsikan Vilaipan : Techno-Economic for Bioethanol from Lignocellulosic.

Master of Engineering (Sustainable Energy and Resources Engineering), Major

Field: Sustainable Energy and Resources Engineering, Faculty of Engineering.

Thesis Advisor: Assistant Professor Maythee Saisriyoot, Dr.Techn. Academic Year

2019

The techno-economic analysis of bioethanol production plants from

EFB, OPT and various ratios of EFB:OPT is evaluated in this work. The simulation

model and evaluation of economic feasibility were carried out using Aspen Plus,

Aspen Adsorption, Aspen Economic Analyzer software, and Microsoft Office

Excel. The conditions and results to produce an ethanol base on the preliminary

experiment. The evaluation of mass balance, equipment design, scheduling unit

utilization was performed to assess to accomplish the objective. The bioethanol

production process consists of three sections: Pretreatment, Simultaneous

saccharification and fermentation (SSF), and Purification process. The specified

first pretreatment technology was employed for each feedstock to obtain high

breakdown efficiency of their structure. The highest ethanol yield from OPT and

EFB is 3.311 and 3.4 wt%, respectively. The combination of the distillation and

dehydration is considered as a purification process. Two candidate dehydration

technologies, PV and PSA, are compared in order to determine the suitable

technology for bioethanol plants.

The results represent that the bioethanol production plant with PV gives

better economic results compared with PSA. The bioethanol plants required very

high investment cost to produce 99.5 wt% of ethanol, 10,000 L/day. Therefore, the

small plant capacity with large capital and operating costs results in negative NPV.

The highest NPV is -11,247,848 $ with 0.8831 $/unit for OPT plant with

PV. Therefore, these plants are nonprofitable and not recommended for investment.

To increase NPV to positive, the sensitivity analysts suggest increasing ethanol

concentration in fermentation broth by remaining the same condition.

_________________ _______________________________ ____ / ____ / ____

Student's signature Thesis Advisor's signature

D

ACKNOWLEDGEMENT S

ACKNOWLEDGEMENTS

This thesis becomes a reality with the kind support and help of many

individuals. I would like to extend my sincere thanks to all of them.

First of all, I would like to grateful to my thesis advisor, Assistant Professor Dr.

Maythee Saisriyoot, for time, knowledgeable guidance, encouragement, supporting and

attentiveness on my research. I could not have imagined having a better advisor for my

research.

Besides my advisor, I would like to thank the committee members, Associate

Professor Dr. Penjit Srinophakun, Associate Professor Dr. Thongchai Rohitatisha

Srinophakun, and external committee, Assistant Professor Dr. Veerayut

Lersbamrungsuk, for their encouragement, insightful comment, and point of my

mistake.

In addition, a thank you for the scholarship from faculty of Engineering,

Kasetsart University and Thailand Advanced Institute of Science and Technology and

Tokyo Institute of Technology (TAIST-Tokyo Tech) program, under National Science

and Technology Development Agency (NSTDA) for supporting to complete the

research.

Finally, I owe my deepest gratitude to my lovely family, brother and best friend

for the enthusiasm, support, love, and cheerfulness. They all kept me going, and this

research would not have been possible without them.

Monsikan Vilaipan

TABLE OF CONTENTS

Page

ABSTRACT .................................................................................................................. C

ACKNOWLEDGEMENTS .......................................................................................... D

TABLE OF CONTENTS .............................................................................................. E

LIST OF TABLES ........................................................................................................ H

LIST OF FIGURES ....................................................................................................... J

INTRODUCTION ......................................................................................................... 1

OBJECTIVES ................................................................................................................ 3

SCOPES OF WORK...................................................................................................... 3

LITERATURE REVIEW .............................................................................................. 4

1. Ethanol ................................................................................................................... 4

2. Biomass .................................................................................................................. 4

3. Palm oil residue ..................................................................................................... 4

4. Empty Fruit Bunch (EFB) and Oil palm trunk (OPT) ........................................... 4

5. Lignocellulose ........................................................................................................ 5

6. Bioethanol production ........................................................................................... 6

6.1. Pretreatment process ..................................................................................... 6

6.1.1. Mechanical/physical pretreatment .................................................... 7

6.1.2. Chemical pretreatment ..................................................................... 7

6.1.3. Physico-chemical pretreatment ........................................................ 8

6.1.4. Biological pretreatment .................................................................... 8

6.1.5. Hydrothermal pretreatment .............................................................. 8

6.2. Hydrolysis .................................................................................................... 9

6.3. Fermentation ................................................................................................. 9

6.4. Separate hydrolysis and fermentation and Simultaneous saccharification

and fermentation ....................................................................................... 10

7. Purification .......................................................................................................... 11

F

8. Economic Analysis .............................................................................................. 12

8.1. Cost-benefit analysis .................................................................................. 12

8.1.1. Cost analysis ................................................................................... 12

8.1.2. Benefit analysis .............................................................................. 13

8.2. Total Capital Investment ............................................................................ 13

8.3. Net Present Value (NPV) ........................................................................... 14

8.4. Internal rate of return (IRR) ....................................................................... 14

8.5. Payback Period (PB) .................................................................................. 15

8.6. Salvage Value ............................................................................................. 15

8.7. Depreciation ............................................................................................... 15

9. Literature review .................................................................................................. 16

MATERIALS AND METHODS ................................................................................. 22

Materials .................................................................................................................. 22

Methods ................................................................................................................... 22

1. Concept to produce bioethanol from lignocellulose ...................................... 22

2. Mass balance ................................................................................................. 23

3. Concept to design size of equipment ............................................................. 26

4. Scheduling flow process ................................................................................ 26

5. Simulation process of bioethanol by Aspen Plus software ........................... 26

5.1. Pretreatment process .......................................................................... 27

5.2. Simultaneous saccharification and fermentation (SSF) .................... 28

5.3. Purification ........................................................................................ 28

5.3.1. Dehydration ........................................................................ 29

6. Economic assessment .................................................................................... 31

6.1. Total Capital cost ............................................................................... 31

6.2. Total operating cost .......................................................................... 32

7. Sensitivity Analysis ....................................................................................... 34

7.1. The concentration of ethanol from SSF ............................................ 34

7.2. Chemical cost .................................................................................... 35

G

RESULTS AND DISCUSSION .................................................................................. 36

1. Mass balance calculation ..................................................................................... 36

2. Equipment design ................................................................................................ 36

3. Scheduling ........................................................................................................... 37

4. Simulation model ................................................................................................. 42

4.1. Pretreatment model ..................................................................................... 42

4.2. SSF model .................................................................................................. 43

4.3. Purification model ...................................................................................... 43

4.3.1. Optimize parameter of Distillation column .................................... 44

4.3.2. Dehydration with Pervaporation .................................................... 68

4.3.3. Dehydration with Pressure swing adsorption ................................. 70

5. Economic analysis ............................................................................................... 79

5.1. OPT plant ................................................................................................... 79

5.2. EFB plant .................................................................................................... 84

5.3. Two feedstocks plant .................................................................................. 86

6. Sensitivity ............................................................................................................ 87

7. Conclusion ........................................................................................................... 89

LITERATURE CITED ................................................................................................ 91

APPENDICES ............................................................................................................. 94

CURRICULUM VITAE ............................................................................................ 146

LIST OF TABLES

Page

Table 1 The chemical characteristic of raw material and pretreated EFB ................... 19

Table 2 The composition of OPT in each process ....................................................... 23

Table 3 The composition of EFB in each process ....................................................... 24

Table 4 The composition of the 80:20 ratio of EFB:OPT in each process .................. 24



Table 7 Parameter for economic assessment ............................................................... 34

Table 8 Escalation assumption..................................................................................... 34

Table 9 Mass input and mass output of three plants .................................................... 36

Table 10 The operating time of upstream and SSF and SSF tank utilization for OPT

plant.............................................................................................................................. 39

Table 11 The operating time of upstream and SSF and SSF tank utilization for EFB

and various ratios of feedstocks plants ........................................................................ 41

Table 12 Configuration of a combination of the distillation and pervaporation model

for OPT plant ............................................................................................................... 69

Table 13 Configuration of the combination of distillation and pressure swing

adsorption model for OPT plant .................................................................................. 71


for EFB plant................................................................................................................ 72


for the two feedstocks plant ......................................................................................... 72

Table 16 Configuration of the combination of distillation and pervaporation model for

distillate various ethanol concentrations in fermentation broth to 80 wt% for OPT ... 73





Table 19 The component of total capital cost for the OPT plant ................................. 81

I

Table 20 The component of total operating cost for the OPT plant ............................ 82

Table 21 Economic result for OPT plant ..................................................................... 82

Table 22 The component of total capital cost for EFB plant ....................................... 84

Table 23 The component of total operating cost for EFB plant .................................. 85

Table 24 Economic result for EFB plant ..................................................................... 85

Table 25 The component of total capital cost for two feedstocks plant ...................... 86

Table 26 The component of total operating cost for two feedstocks plant .................. 86

Table 27 Economic result for two feedstocks plant ..................................................... 87

Table 28 Economic result for various Ctec2 price ....................................................... 87

Table 29 Economic result for distillation 4, 6, 8 wt% to 80 wt% ................................ 88



LIST OF FIGURES

Page

Figure 1 Concept for bioethanol production .................................................................. 6

Figure 2 Pretreatment of lignocellulosic materials before bioethanol and biogas

production ...................................................................................................................... 7

Figure 3 The process for ethanol production from lignocellulosic biomass ................ 10

Figure 4 Energy demand .............................................................................................. 16

Figure 5 Multistage pervaporation process .................................................................. 17

Figure 6 The total annual cost in the purification process ........................................... 17

Figure 7 Flow diagram of batch fermentation ............................................................. 20

Figure 8 Flow diagram of continuous fermentation–pervaporation process ............... 20

Figure 9 Flow diagram of steam explosion .................................................................. 21

Figure 10 The scheme of the production process ........................................................ 23

Figure 11 Overview of the bioethanol production process from OPT......................... 27

Figure 12 Overview of the bioethanol production process from EFB ......................... 27

Figure 13 Overview of the bioethanol production process from various ratios of OPT

and EFB ....................................................................................................................... 27

Figure 14 Purification section ...................................................................................... 29

Figure 15 Operating time of the initial SSF tank of OPT plant ................................... 38

Figure 16 Equipment utilization for two consecutive batches for OPT plant .............. 38

Figure 17 Operating time of the initial SSF tank of EFB and two feedstocks plants .. 40

Figure 18 Equipment utilization for two consecutive batches for EFB and two

feedstocks plants .......................................................................................................... 40

Figure 19 Simulation model of the three pretreatment processes for OPT.................. 42

Figure 20 Simulation model of the three pretreatment processes for EFB .................. 42

Figure 21 Simulation model of the media preparing, sterilizing and SSF process ...... 43

Figure 22 Sensitivity number of stages of distillation column for case 1 of OPT plant

with pervaporation technology .................................................................................... 45

K

Figure 23 Sensitivity molar reflux ratio of distillation column for case 1 of OPT plant


Figure 24 Sensitivity distillation to feed of distillation column for case 1 of OPT plant


Figure 25 Sensitivity feed stage of the distillation column for case 1 of OPT plant



























with pressure swing adsorption technology ................................................................. 49



L



Figure 41 Sensitivity feed stage of distillation column for case 1 of OPT plant with

pressure swing adsorption technology ......................................................................... 49

























Figure 54 Sensitivity number of stages of distillation column for EFB plant with

pervaporation technology............................................................................................. 53

Figure 55 Sensitivity molar reflux ratio of distillation column for EFB plant with


Figure 56 Sensitivity distillation to feed of distillation column for EFB plant with


M

Figure 57 Sensitivity feed stage of distillation column for EFB plant with


Figure 58 Sensitivity number of stages of distillation column for 100:0 ratio of EFB

and OPT plant with pervaporation technology ............................................................ 54

Figure 59 Sensitivity molar reflux ratio of distillation column for 100:0 ratio of EFB


Figure 60 Sensitivity distillation to feed of distillation column for 100:0 ratio of EFB


Figure 61 Sensitivity feed stage of distillation column for 100:0 ratio of EFB and OPT

plant with pervaporation technology ........................................................................... 54

























N









Figure 78 Sensitivity number of stages of distillation column for distillate 4 wt% of

fermentation broth to 80 wt% and dehydrate with pervaporation technology............. 59

Figure 79 Sensitivity molar reflux ratio of distillation column for distillate 4 wt% of


Figure 80 Sensitivity distillation to feed of distillation column for distillate 4 wt% of


Figure 81 Sensitivity feed stage of distillation column for distillate 4 wt% of


Figure 82 Sensitivity number of distillation column for distillate 6 wt% of



fermentation broth to 80 wt% and dehydrate with pervaporation technology y.......... 60















O























Figure 102 Sensitivity number o of distillation column for distillate 4 wt% of












P













Figure 114 Relationship of energy demand in dotted line and recovery efficiency in a

solid line with various separation factor and difference inlet concentration applying

the hydrophilic membrane ........................................................................................... 68

Figure 115 Flowsheet for the distillation and dehydration process using PV method 69

Figure 116 Flowsheet of pressure swing adsorption in Aspen Adsorption software .. 70

Figure 117 Flowsheet for the distillation and dehydration process using PSA method

...................................................................................................................................... 71

Figure 118 The simulation model of bioethanol production from OPT by using Aspen

plus with distillation and pervaporation technology .................................................... 75

Figure 119 The simulation model of bioethanol production from OPT by using Aspen

plus with distillation and pressure swing adsorption technology ................................ 76

Figure 120 The simulation model of bioethanol production from EFB by using Aspen

plus with distillation and pervaporation technology .................................................... 77

Figure 121 The simulation model of bioethanol production from two feedstocks by

using Aspen plus with distillation and pervaporation technology ............................... 78

Figure 122 Comparison of the total capital cost of 4 cases ......................................... 83

Figure 123 Comparison of operating costs of 4 cases ................................................. 83

Figure 124 Distribution element of operating costs for OPT plant with 85 wt% in the

overhead stream before dehydrating with PV and PSA ............................................... 83

Figure 125 Distribution chemical costs for OPT plant ................................................ 84

1

INTRODUCTION

The energy consumption in Thailand has increased over the years, and the

world's demand for energy trends to continuously increase with expected population

growth. On the other hand, the supply of fossil fuel, crude oil, and coal is a limited

resource and going to deplete. These fuel sources cause negative effects on the

environment such as the greenhouse effect, global warming. Therefore, renewable

energy from biomass has become a popular alternative energy source to reduce

dependence on fossil fuel, crude oil, and coal. Bioethanol derived from food sources

such as sucrose or starch called first-generation bioethanol has the potential to become

the major source of energy supply to replace fossil fuels. Nevertheless, the main

disadvantage of first-generation is the loss of a food source problem. Therefore,

nonfood sources such as wood, glass, agriculture residual, and lignocellulosic biomass

called second-generation become the promising raw material to produce bioethanol.

Lignocellulosic biomass is considered as promising renewable raw material to

produce energy source. The obvious advantages of lignocellulosic biomass are more

abundant and less expensive than food crops (Derman et al., 2018). Bioethanol

derived from lignocellulosic biomass is an environmentally friendly, clean, and

renewable energy fuel because biomass consumes as much carbon dioxide when it

was growing as it forms during the combustion of bioethanol. Resulting in the net

contribution to the greenhouse effect is zero. Therefore, this work decided to study

about bioethanol derived from lignocellulosic biomass that has a great possibility to

replace fossil fuels.

Ethanol can be produced from lignocellulosic such as corn, cassava, sugar

cane, molasses, oil palm, empty fruit bunch, and rice. They are a mixture of natural

polymers based on cellulose, hemicellulose, and lignin. The sources of cellulose are

generally abundant and available. Therefore, there is a various price of lignocellulose

feedstock. The production cost of bioethanol has increased as well as the price of the

feedstock increase. So, it is important to find out the suitable lignocellulose feedstock

with low feedstock price to produce high ethanol yield. As Thailand is a third-largest

oil palm producer, the Empty fruit bunch (EFB) and oil palm trunk (OPT) are a large

amount of waste from the oil palm extraction and harvesting. Therefore, they were

considered as feedstock to produce bioethanol in this work. However, the

lignocellulose has a strong structure because of covering with lignin as a cell wall. In

order to obtain the product, they must first be breakdown their structure before the

conversion process. The pretreatment process was required to breakdown feedstock’s

structure, and eliminate lignin, which resistant to fermentation ability to increase

yields of fermentable cellulose.

The information to produce the highest ethanol yield from preliminary work

was required. The bioethanol production plant consists of 4 main methods, which are

1) pre-treatment 2) hydrolysis 3) fermentation, and 4) purification. The first step,

EFB, and OPT must be chop to a smaller size, 20×20×5 mm. The small size of two

feedstocks is conveyed to the pretreatment process. In the pretreatment process,

specified first pretreatment techniques are applied for each feedstock. EFB is

2

pretreated with Hot compress water (HCW) at 200oC, 30 bar, 15 min. OPT is

pretreated with Steam explosion (SE) at 210oC, 18.6 bar, 4 min. Then, the treated

OPT and EFB are operated under the same condition and technology. Hot water

washing at 80 oC, 30 minutes, and Hydrogen peroxide digestion (H2O2) at 70oC, 30

minutes are required as second and third pretreatment processes. These processes

have a high potential to destroy the structure and remove the lignin. Pretreatment can

be removing structural and compositional impediments to hydrolysis to improve the

rate of enzyme hydrolysis and increase yields of fermentable. The treated feedstocks

with less amount of lignin are transferred to the simultaneous saccharification and

fermentation (SSF) process. After SSF, most of the cellulose is converted to sugars

and glucose, respectively. The bioethanol from SSF is stored in the buffer tank before

feeding to the purification process. As the SSF process can produce only 3 wt% of

ethanol. Therefore, it must be purified to fuel grade, about 99.5 wt%.

Aspen Plus software V8.8 was performed to simulate the bioethanol

production process from OPT, EFB, and two feedstocks by using the preliminary’s

condition. Aspen Plus is software for simulation in chemical engineering. It can

generate a simulation process and evaluate the total cost investment (TCI) in terms of

equipment and total production cost (TPC). The simulation model was transferred to

Aspen Economic analyzer software to evaluate the utility of the plant.

This work aims to study the technology and evaluate the economic feasibility

of the bioethanol production process from lignocellulose. To accomplish the

objective, the following tasks, including understanding the bioethanol process,

simulation of the bioethanol process and purification process, equipment design,

economic analysis of the bioethanol plant, and a sensitivity analysis was performed in

this work.

3

OBJECTIVES

1. To study and design the bioethanol production process from oil palm trunk (OPT),

Empty fruit bunch (EFB), and various ratios of OPT and EFB.

2. To analyze the economic feasibility of three ethanol production plants.

3. To analyze sensitivity for different concentrations of ethanol before the purification

process and effect of Ctec2 on the production cost of OPT plant.

SCOPES OF WORK

1. Oil palm trunk (OPT) and empty fruit bunch (EFB) are used as a raw material to

produce 10000 liters/day of ethanol.

2. The purity of ethanol is 99.5 wt%

3. Use Aspen Plus software to simulate the production process.

4. Evaluate the total capital investment, total operating cost, the net present value

(NPV), Internal rate of return (IRR), payback period (PB), and production cost per

unit.

4

LITERATURE REVIEW

1. Ethanol

Ethanol is the alcohol and the most promising biofuels for renewable energy.

It is extensively used as fuel in transportation. The physical properties of ethanol are

volatile and colorless. The boiling and melting point of ethanol are 78.5 and -114 °C

at atmospheric pressure (Zaini, 2006). The chemical formula of ethanol is

CH3CH2OH. Ethanol is a polar solvent. Ethanol can be produced by ferment sugar.

For the fermentation process, ethanol and carbon dioxide are produced by fermentable

sugar with yeast or bacteria.

Bioethanol from lignocellulose is produced by using familiar methods, such as

fermentation, and it can be used for transportation systems as fuel. Additional main

two reactions/methods including hydrolysis and fermentation are key processes to

converted to bioethanol from lignocellulose.

2. Biomass

Biomass is one of the most important renewable energy resources. Using

biomass to produce bioethanol can solve the biomass disposal problems from

agricultural industries. Especially, biomass produced from the palm oil industries.

3. Palm oil residue

The palm oil industry especially generates a huge amount of oil palm biomass

residues after harvesting of oil palm fruits, replantation of the trees, and oil palm

processing. The oil palm residues are empty fruit bunches (EFBs), palm oil mill

effluent (POME), palm kernel shell (PKS), oil palm trunks (OPT), oil palm leaves

(OPL), oil palm fronds (OPF) and mesocarp fiber (MF). Disposal of these oil palm

residues is critical for both environmental protection and agricultural profitability.

Therefore, utilizing huge biomass wastes to produce clean and sustainable fuel for the

future is a good solution.

4. Empty Fruit Bunch (EFB) and Oil palm trunk (OPT)

Empty fruit brunch and Oil palm trunk are available and abundance of fibrous

material from biological origin. Empty fruit bunches (EFB), palm oil mill effluent

(POME) and palm kernel shell (PKS) are biomass wastes form palm oil plantation.

They contain a lot of cellulose. Those celluloses in EFB and OPT are the potential to

be converted into sugar and bioethanol, respectively. Cellulose is the major

component of EFB and OPT that can be converted into glucose and bioethanol by

hydrolysis and fermentation process, respectively. They have the highest fiber yield,

and it is the only material utilized commercially for fiber extraction. It is realized as a

promising raw material for bioethanol production due to its potential as a source of

glucose. On the other hand, lignocellulose requires the pretreatment process due to

5

increase yields of fermentable cellulose and eliminate lignin or other resistant

substance in the fermentation process.

5. Lignocellulose

It is the most abundantly available raw material on the Earth for the

production of biofuels. It is composed of cellulose, hemicellulose, and lignin.

Lignocellulosic are promising feedstock because of high yields, low costs, good

suitability for low-quality field, and low environmental impact. These reasons make it

more easily decide to utilize it as raw material for producing energy. Most ethanol

conversion systems have been based on a single feedstock. But considering the

hydrolysis and fermentation process, it is possible to use multiple feedstock types.

This method may even be accomplishing a suitable method for a large scale.

Cellulose contains 40–60% of the dry biomass, is a linear polymer of glucose–

glucose dimer. Cellulose is the major component of the plant. It is a β-1,4- linked

linear polymer of glucose units and is insoluble in water, dilutes acidic solutions, and

dilute alkaline solutions at normal temperatures. The structure is difficult to break due

to the orientation of the linkages, and additional hydrogen bonding makes the polymer

rigid. In the hydrolysis process, the polysaccharide is broken down to free sugar

molecules by the property of water, called saccharification. The glucose, is a six-

carbon sugar or hexose, was produced.

Hemicellulose contains 20–40% of the dry biomass. It consists of short a lot of

branched chains of various sugars such as mainly xylose, and arabinose, galactose,

glucose, and mannose. The degree of polymerization (DP) of hemicellulose is on

average about 100-200 and the molecules can be highly branched called amorphous

structure. Because of the low DP and amorphous structures, hemicellulose is more

easily degraded in dilute acidic than cellulose and easy to hydrolyze. It also contains

smaller amounts of non-sugars such as acetyl groups.

Lignin contains 10–25% of the dry biomass. It is a basic component in all

lignocellulosic biomass. Lignin is one of the most abundant organic polymers in

plants. Therefore, any ethanol production process will have lignin as a residue. It is a

large complex polymer of phenylpropane and methoxy groups, a non-carbohydrate

polyphenolic substance that coat the cell walls and join the cells together. The

chemical properties of lignin include halogenation, nitration, and oxidation reactions.

Lignin is an amorphous thermoplastic polymer, so it has a slight friability under high

temperature. It is degradable by only a few organisms, into higher-value products

such as organic acids, phenols, and vanillin. By using chemical processes valuable

fuel additives may be produced.

6

6. Bioethanol production

The normal concept to produce bioethanol, the bioethanol as the product is

produced from a variety of biomass material. The first step is to mill the biomass to

reduce the size and increase surface area called mechanical pretreatment. It can be

done by dry milling or wet milling. The second step is pretreatment to change the

structure of biomass to make it more accessible for the subsequent process. There are

many types of pretreatment methods, such as chemical, physicochemical, biological

techniques. The third step is the hydrolysis process by using enzymes to convert the

cellulose into glucose and the last step is further fermented to ethanol using glucose-

fermenting microorganisms. After fermentation, ethanol in the mixture is separated

from water called the purification process. There are many methods for purified

ethanol.

Figure 1 Concept for bioethanol production

6.1. Pretreatment process

Pretreatment is an important step for lignocellulosic materials to

produce bioethanol. Lignocellulosic materials contain polysaccharides, such as

cellulose and hemicelluloses. Pretreatment is mainly necessary to change the structure

of cellulosic biomass to make cellulose more accessible to the enzymes that convert

the carbohydrate polymers into fermentable sugars. Pretreatment is an additional

process to produce ethanol. The pretreatment step is considered as the most expensive

processing step or an additional cost in cellulosic biomass-to-fermentable sugars

conversion. So, there are many researchers have focused on this step to make a cost-

effective conversion of cellulose to bioethanol. An effective pretreatment should have

following characteristics (1) maximum cellulose or hemicellulose fractions so that it

can also be converted into fermentable sugar which can further be converted into

ethanol, (2) minimize the formation of inhibitors during pretreatment due to it can be

degradation products, (3) minimize loss of carbohydrate due to it can affect the

conversion of fermentable sugar and (4) minimizing energy input, and the process is

economically efficient as well as cost-effective. To achieve all the criteria mentioned

above should be comprehensively considered as a basis to achieve maximal end

product of interest. Pretreatment technology can be classified into biological,

physical, chemical, and physicochemical pretreatments. However, energy consumed

in the pretreatment process is an important factor to consider.

Pretreatment is the primary process for biomass materials such as EFB

and OPT for improving the cellulose reactivity with cellulase enzymes and for

increasing the yield of fermentable sugars. Pretreatment can increase bioethanol yield

Size

reduction Pretreatment hydrolysis Purification fermentation

7

and productivity significantly. The pretreatment process is required to break down the

lignin structure and disturb the crystalline structure of cellulose. After pretreatment,

the acids or enzymes can easily access the cellulose to hydrolyze into monomers.

Pretreatment allows changing the structure of the lignocelluloses such as increasing

the surface area and porosity of biomass, modifying and removing the lignin, some

part of polymerizes, and removes the hemicelluloses, and reduces the crystallinity of

cellulose. The pretreatment processes or combination can increase the potential to

convert the wastes to biofuel production and increase accessibility to the enzymes

(Behera et al., 2014).

Figure 2 Pretreatment of lignocellulosic materials before bioethanol and biogas

production

Source: Behera et al. (2014)

6.1.1. Mechanical/physical pretreatment

Mechanical pretreatment for lignocellulosic biomass. The

common purpose of mechanical is size reduction processes by using dry milling,

compression milling, vibratory ball milling, and wet milling. Consumption of energy

for size reduction depends on machine variables, rate of feed material, material

properties, moisture content, and initial particle size. Normally, size reduction can be

accomplished by splitting or shearing with sharp knives in which the geometry of

particles is damaged due to impact or compression.

6.1.2. Chemical pretreatment

Chemical pretreatment has considered one of the most

promising methods to increase the biodegradability of cellulose by removing lignin

and hemicelluloses to decrease the degree of polymerization and crystallinity of the

cellulosic component in lignocelluloses. There are many chemicals, which have been

experimented and reported to have a significant effect on the structure of

lignocellulosic biomass. Some chemical does not produce toxic residues after

pretreatment processes.

8

Alkaline hydrogen peroxide pretreatment (AHP), the use of

H2O2 for the pretreatment of lignocellulosic biomass is based on the chemical

reactions that this oxidizing agent undergoes in the alkaline liquid medium. AHP

pretreatments could enhance the enzymatic digestibility by swelling fibers, breaking

ester bonds of lignin-carbohydrate complexes, solubilizing lignin molecules,

increasing the surface area, and providing more cellulose for the accessibility of

enzyme. AHP pretreatment was appealing to the effective degradation of lignin from

lignocellulosic biomass because H2O2 could degrade to oxygen.

6.1.3. Physico-chemical pretreatment

Pretreatments that combine both the chemical and physical

processes are of importance in dissolving hemicellulose and the conversion of lignin

structure. This pretreatment provides improved accessibility of the cellulose for

hydrolytic enzymes.

6.1.4. Biological pretreatment

Biological pretreatment is mostly associated with the action of

fungi that are capable of producing enzymes to degrade lignin, hemicelluloses, and

polyphenols present in the biomass. Biological pretreatment has attracted interest

because of its advantages over physical/chemical pretreatments such as substrate and

reaction specificity, low energy requirements, no generation of toxic compounds, and

high yield of desired products. However, its disadvantages are as possible as its

advantages, due to biological pretreatment is a very slow process and requires

accurate control of growth conditions.

6.1.5. Hydrothermal pretreatment

Pretreatments utilizing primarily steam or liquid water at high

temperatures can efficiently convert biomass to a form that can be easily digested by

enzymes by facilitating autohydrolysis reactions within the biomass. Processes

utilizing hot water or steam as the primary chemical are known as hydrothermal

pretreatments.

Steam explosion (SE) is pretreatment processes that low use of

chemicals and limited energy consumption. With this method, high pressure saturated

steam is injected into a batch or continuous reactor filled with biomass. During the

steam injection, the temperature rises to 160-260 ºC. Subsequently, the pressure is

suddenly reduced, and the biomass goes to an explosive decompression with

hemicellulose degradation and lignin matrix disruption as a result. Results of steam-

explosion pretreatment depend on residence time, temperature, particle size, and

moisture content

9

Hot-compressed water (HCW) pretreatment, which biomass is

exposed to pressured hot water, is a pretreatment method that uses water under

pressure penetrates the cell structure of biomass, hydrates cellulose, and dissolves

hemicellulose and lignin at high temperature (around 200 °C). HCW pretreatment

does not require the addition of any chemical and generates little inhibition to

subsequent hydrolysis and fermentation.

6.2. Hydrolysis

Hydrolysis is the process that converts polysaccharides into

monomeric sugars. The fermentable sugars obtained from hydrolysis can be

fermented into ethanol. Lignocellulose can be hydrolytically broken down into simple

sugars with enzymatically by cellulolytic enzymes or chemically by sulfuric or other

acids. In this process, cellulose is hydrolyzed to glucose, whereas hemicellulose gives

rise to several pentose and hexoses. The advantage of enzymatic hydrolysis is low

toxicity, low utility costs and low corrosion compared to acid or alkaline hydrolysis

The hydrolysis process is hydrolyzed cellulose to glucose by either

acid or enzymatic hydrolysis. The main disadvantage of acid hydrolysis processes is

severely limit for commercial application, which affects the economic feasibility of

dilute acid hydrolysis due to sugar degradation and consequence, low process yields.

Therefore, enzymatic hydrolysis was utilized in this project. Enzymatic hydrolysis of

cellulose is carried out by cellulase enzymes. The utility costs of enzymatic hydrolysis

are low compared to acid or alkaline hydrolysis because enzyme hydrolysis is usually

conducted at conditions (pH 4.8 and temperature 45– 50 °C) and does not have a

corrosion problem (Duff et al., 1996). The products of the hydrolysis are usually

reducing sugars including glucose. Both bacteria and fungi can produce cellulases for

the hydrolysis of lignocellulosic materials.

6.3. Fermentation

The final process for achieving the ethanol production, yeast

fermentation is considered to be an interesting technology, which is improved to gain

the high efficiency due to the traditional yeast fermentations are not ideally suited to

the unique fermentation requirements of cellulose hydrolysates. The fermentation

operates under an anaerobic condition at a temperature of about 32-35 C° and pH

around 4.2-4.5. Fermentable sugar is converted to ethanol as a main product and

carbon dioxide as a by-product. These byproducts need to be removed to obtain pure

ethanol. Batch fermentation, fed-batch, and continuous fermentation are the

commonly adopted industrial methods.

Batch fermentation, all material/substance is introduced into the tank

with fixed volume and retention time for the operation. The sugar in the fermenter is

continuously converting to ethanol until the end of time. After the fermentation, the

residues are taken out from the fermentation tank, then cleaned and sterilized before

10

the next batch of fermentation. Therefore, batch fermentation should be large

scale/volume to operate per time/cycle. On the other hand, the continuous

fermentation never stops. It continues to run for a long period with the addition of

nutrients and collecting the product at regular intervals.

Fed-batch fermentation is an operational technique in biotechnological

processes where one or more nutrients are fed to the reactor during cultivation and in

which the product remains in the bioreactor until the end of the run. The process of

fed-batch fermentation is an effective method in reducing growth inhibition caused by

high substrate concentration. In the fed-batch fermentation process, a suitable feeding

strategy is crucial to achieving both high productivity and yield of the product.

6.4. Separate hydrolysis and fermentation and Simultaneous saccharification

and fermentation

There are two different processes in ethanol production. In the case of

pretreatment, cellulose hydrolysis, fermentation, and product recovery take place in

different reactors, the process is called separate hydrolysis and fermentation (SHF). In

the SHF process, cellulases from the enzyme production are added to the pretreated

material to convert cellulose to glucose, called the hydrolysis process. After

hydrolysis, the microorganism/yeast is added to convert glucose to ethanol, called

fermentation process. All process is separated.

For simultaneous saccharification and fermentation (SSF), enzymatic

cellulose hydrolysis and sugar fermentation are operated in one reactor. Cellulases are

added to the pretreated materials to hydrolyze the cellulose to glucose, while the

microorganism converts glucose into biofuels in the same reactor. Because glucose,

an inhibitor of cellulase, is converted by the microorganism into ethanol. SSF can

efficiently remove or reduce the inhibitory effect of glucose on cellulases, thus

achieving faster biomass hydrolysis rates and higher ethanol yields as compared to

SHF. The SHF and SSF were shown in Figure 3.

Figure 3 The process for ethanol production from lignocellulosic biomass

11

Source: Fan (2014)

7. Purification

After fermentation bioethanol contains a low concentration of ethanol, so it

has to increase concentration by purifying process. The boiling point of water (100

°C) is higher than the ethanol boiling point (78 °C). In this process, ethanol is purified

around 95% because of the azeotropic mixture between water and ethanol. But for

industries require the concentration of ethanol more than 99%. Therefore, the special

process for removal of water is required such as azeotropic distillation, extractive

distillation, and molecular sieve adsorption and pervaporation.

Azeotropic distillation uses a solvent with an intermediate boiling point to

introduce new azeotropes to the mixture and at the same time to generate two liquid

phases that allow, in a combined way, separating ethanol from water. This technique

has lost acceptance due to its poor stability and high energy consumption.

Extractive distillation is a partial vaporization process in the presence of a

non-volatile and high boiling point entrainer which does not form any azeotropes with

the original components of the azeotropic mixture. The extractive distillation requires

entrainer or solvent. The entrainer is much lower than the azeotropic case and

additionally, the quantity of entrainer is lower which affects the diameter of the

columns. It can be observed that the column diameters are smaller in the extractive

distillation systems and also the energy consumption in the columns. On the other

hand, the most important variables used to achieve the desired ethanol concentration

are the entrainer to feed molar ratio and the reflux ratio. The former has a little effect

over the energy consumption compared with the reflux ratio impact on the reboiler

duty.

The molecular sieve dehydration technology utilizes the adsorption

phenomenon, and this is used to produce anhydrous ethanol. These Molecular Sieves

for Ethanol drying is made of popular materials called zeolites. The industrial process

essentially involved passing the vapor form of ethanol through a column of the

molecular sieve, which separates any water present in the vapor form from the ethanol

by trapping its molecules onto its surface while allowing molecules of ethanol to pass

through. Two different subzones of operation are provided within a master transfer

zone so that the two liquids part ways without any further interaction. This process

also does not use any other chemical, hence eliminating the chance of contaminating

ethanol with any other substance completely. The costs of the usage of such chemicals

are also thus automatically eliminated altogether. On the other hand, it recovers higher

alcohol from the process. Therefore, Molecular Sieve Technology offers cost

advantages and higher alcohol recovery rates.

Pressure swing adsorption is a method for the separation of some gas from a

mixture of gases under different pressure levels. It is a widely used technology for the

purification of gases. Specific adsorbent materials such as zeolites, activated carbon,

molecular sieves are used as a trap, preferentially adsorbing the target gas species at

12

high pressure and desorb gas at low pressure. Adsorbents are porous solids, preferably

having a large surface area per unit mass. Since different molecules have different

interactions with the surface of the adsorbent, it is eventually possible to separate

them.

Pervaporation is a membrane process and combines permeation and

vaporization. Pervaporation is used to separate a liquid mixture. The used membrane

is a dense non-porous membrane or a very finely porous ceramic membrane that

depends on what kind of component wants to remove. Specifically, for this process,

the permeating component is converted into an evaporation phase, due to the low

vapor pressure on the permeate-side. This low vapor pressure is normally achieved by

setting a vacuum on the permeate side of the membrane. In most cases, the permeate

is re-condensed. The pervaporation process contains 3 steps (1) Selective sorption in

the membrane on the influent-side, (2) Selective diffusion through the membrane, (3)

Desorption in the gas phase on the permeate-side.

8. Economic Analysis

An economic analysis is a process which makes a clear picture of the existing

economic climate, as it relates to the company’s ability to succeed. There are several

tools for economic evaluation that can be used to gain a comprehensive view of how

the company will manage in the future. The economic analysis takes into account the

opportunity costs of resources employed and attempts to measure in terms of costs

and benefits of a project. The main objective of conducting a project economic

analysis is to help assess the sustainability of investment projects. Therefore, it is best

undertaken at the early stages of the project. The tools for a measure of project worth

including Net Present Value (NPV), Internal Rate of Return (IRR), Payback period

(PB), and production cost per unit.

8.1. Cost-benefit analysis

Cost-benefit analysis in project management is a process used to

analyze decisions. It has been devised to evaluate the costs versus the benefits in the

project proposal. It begins with a list. There is a list of every project expense and what

the benefits will be achieved after successfully executing the project. After that use

these data to calculate total capital investment cost (TCI), net present value (NPV),

internal rate of return (IRR), and the payback period (PB). These variables are used to

determine the worth of the project.

8.1.1. Cost analysis

Investment cost

It includes any expenses during the first step of the project. The

main cost of investment costs is construction costs. To calculate the total investment

13

in addition to the construction, there are many other factors to consider. The costs of

land, machine, installation and equipment costs, water supply, electric fee, telephone

fee, expert employment costs, technical know-how employment.

Operating cost

It is the expenses that are related to the operation of a business,

or the operation of a device, component, piece of equipment or facility. The operation

costs include raw material costs, energy, and water supply for equipment, chemical

costs, consulting costs, worker employment, transportation costs.

Maintenance costs

Maintenance expenses are the costs incurred to keep

equipment, engine, and building in good condition or good working order during the

project life.

8.1.2. Benefit analysis

The benefit of the project is all the outcomes of the project. The

benefit of the project is comprised of direct benefits including goods and services and

indirect benefits.

Direct benefit

Direct benefits are the outcome according to the aim of the

project. Normally, they are profit from goods and services.

Indirect benefit

Indirect benefits are profit beyond the main purpose of the

project.

8.2. Total Capital Investment

Investment is needed as the capital costs to begin product manufacture.

Total Capital Investment (TCI) of a chemical plant includes the purchase of the land,

building, offsite, supporting facilities, utility installation, market research, licensing,

and contractor’s fee. The investment costs are needed to supply the necessary

manufacturing and plant facilities.

Fix capital cost (FCI) is an expense or cost that does not change with

an increase or decrease in the number of goods or services produced or sold. For the

calculation of FCI can be following.

14

FCI = Direct costs + Indirect costs (1)

Direct costs are expenses that directly go into producing goods or

providing service including purchased equipment (Columns, Heat Exchangers,

pumps, tanks), Equipment Installation, Piping (includes insulation), Instruments and

Control, Electrical Equipment, Buildings (Process, Administration, Maintenance

shops), Site Preparation, Service Facilities (steam, water, air, fuel), Waste treatment,

fire control. Offices, Land.

Indirect costs are expenses that keep operating including Engineering

and Supervision (Administrative and Design), Supervision and Inspection,

Construction Expenses, Contractor's fee, Contingency, Start-up expenses.

8.3. Net Present Value (NPV)

The NPV of a project or investment reflects the degree to which cash

inflow, or revenue, equals or exceeds the amount of investment capital required to

fund it. To decide the worth of the project is up to NPV. If the NPV is a positive

value, it is worth to invest. A negative value of NPV is not worth in invest. For the

calculation of NPV, it estimated from cash inflow and outflow. For the calculation of

NPV can be following.

=+

+−= Ti ir

iC

CNPV1

)1(0

(2)

Where r is the discount rate

T is the number of time periods

C0 is Initial Investment

Ci is Cash flow at year i

i is Project start time

8.4. Internal rate of return (IRR)

The internal rate of return (IRR) is a metric used in capital budgeting

to estimate the profitability of potential investments. The internal rate of return is a

discount rate that makes the net present value (NPV) of all cash flows from a

particular project equal to zero. A business needs to look at the IRR as the plan for

future growth and expansion. It is necessary to know the discount rate (r) in the

market. If the market interest rate is lower than IRR, it is worth to invest. If there are

many projects/choices the project with the highest IRR should be considered first. For

the calculation of IRR can be following.

When NPV = 0; =+

= Ti ir

iC

C 1)1(

0 (3)

15

Where r is the discount rate

T is the number of time periods

C0 is Initial Investment

Ci is Cash flow at year i

i is Project start time

If, IRR > r, accept the project

IRR< r, reject the project

8.5. Payback Period (PB)

The payback period is the length of time required to recover the costs

of an investment. The payback period of the investment is an important determinant

of whether to undertake the position or project, as long payback periods are typically

not desirable for investment positions. For the calculation of PB can be the following:

Payback Period = Cost of the investment (4)

Annual net cash inflow

The payback period ignores the time value of money, unlike other

methods. There are two significant problems with this method; it ignores the time

value of money and ignores any benefits that occur after the payback period. So, it

does not measure profitability.

8.6. Salvage Value

Salvage value is the estimated value that paid when the item is sold at

the end of its useful life and is used to determine annual depreciation. It is net cash

obtainable from the sale of used property.

8.7. Depreciation

The monetary value of an asset decreases over time due to use, wear,

and tear or obsolescence. This decrease is measured as depreciation. Types of

depreciation include physical such as wear and tear, corrosion, accidents, age

deterioration, functional, obsolescence and depletion such as loss from materials

consumed and applicable to natural resources (timber, mineral, oil deposits).

Depreciation = Total equipment - Salvage Value (5)

Project Life

16

9. Literature review

Nagy et al. (2015) studied the energy demand of increased concentration for

ethanol solution up to the fuel-grade quality and also discussed how energy

consumption could be reduced by applying the pervaporation (PV) process with the

different operating patterns as showed in Figure 5. All processes were simulated with

Chemcad software and evaluated the energy consumption of each unit. For

distillation, they experimented with various concentrations of ethanol in feed to

achieve 50 wt%, 70 wt%, and 93 wt %. The energy demand strongly increased with

decreasing the ethanol concentration in the feed-in Figure 4.

Figure 4 Energy demand

Source: Nagy et al. (2015)

In the case of PV, the multistage PV had effective due to only one stage of PV

cannot reach the fuel grade product. The 5wt% of ethanol was introduced into

multistage PV to increase concentration up to 99.5% as the product. Process A, the

three-stage membrane, which two hydrophobic and one hydrophilic, can reduce

energy consumption by about 13%. Process B, the two-stage membrane with

hydrophobic and one hydrophilic, can reduce energy consumption by 40% but the

membrane in this process B not available for commercial scale. Moreover, the single

technique and hybrid technique (Distillation+PV) were compared and the result

showed that the hybrid process has efficient higher than a single distillation and one

or multi-stage pervaporation process. Application of pervaporation with hydrophilic

membrane module in a hybrid process can especially be advantageous to further

concentration product of distillation with 50–70 wt% ethanol.

17

Figure 5 Multistage pervaporation process

Source: Nagy et al. (2015)

Valentínyi et al. (2018) studied alternatives for the separation of diluted

ethanol-n-butanol-water mixture that was proposed and simulated in ChemCAD

software. The objective was the minimization of the total annual cost (TAC) to

produce ethanol with a purity of 99.7 wt%. They compared the capital costs and

operating costs between extractive distillation and pervaporation process. The first

distillation column (C1) was the common first step of all alternatives. The 2 wt%

ethanol was fed into the first column (C1). Then ethanol flow to dehydration

including extractive distillation column and pervaporation process to increase

concentration up to 99.7wt%. In the case of pervaporation, alternative separated with

multiple hydrophilic pervaporation modules connected in series, can reduce the

investment costs and operating costs as shown in Figure 6. However, the main

disadvantage is membrane must be replaced every 2.5 years. While extractive

distillation required chemical and high energy consumption to separate ethanol and

water.

Figure 6 The total annual cost in the purification process

Source: Valentínyi et al. (2018)

18

Ebrahimiaqda et al. (2017) studied ethanol production from several varieties

of sweet sorghum (Dale, T-Sugar, M81E, and 350FS). They found that after the

fermentation process, the sweet sorghum fermentation broth has a high-water content.

Therefore, it is necessary to analyze on simulating and optimizing the distillation and

purification processes to achieve 99.8 wt% ethanol as a product. They compared two

methods including extractive distillation and pressure swing adsorption (PSA) with 3

A molecular sieve and also optimized facility sizing, operating conditions, and total

annualized cost. The result showed that applying an extractive distillation method

results in a cost that is, on average, 12% less than that of PSA using molecular sieves.

Comparing the operating and capital costs for each variety shows that the operating

costs for either method were approximately the same. However, the capital costs for

the PSA method was notably higher than the extractive distillation process. Moreover,

the feed entering the distillation column contains small amounts of ethanol and to

obtain a high purity product. A significant amount of energy was required to

concentrate the ethanol to its azeotrope. Therefore, the capital and operating costs of

the first column accounted for between 70 and 80% of the TAC in both methods.

Bastidas et al. (2010) studied and compared the three main ethanol

dehydration technologies including azeotropic, extractive, and adsorption processes,

and also determined the main operating conditions to produce 300 cubic meters per

day of 99.5 mole % ethanol by using Aspen plus. The total cost was implemented

considering the total investment and operating costs of each technology. For

adsorption processes, the final product of the anhydrous ethanol produced is lower

than the obtained in the distillation. This is due to the high ethanol recycle required to

regenerate the second bed. This affects the efficiency of the process importantly and

increases the total energy consumption. The total cost of the three technologies was

azeotropic > adsorption > extractive. This result presents that the equipment costs of

extractive distillation with ethylene glycol was the lowest option to dehydrate ethanol.

The extractive distillation with ethylene glycol represents the most interesting

alternative because the energy consumptions and capital investment costs were

competitive and represent important savings in the final costs of ethanol produced.

Kamarludin et al. (2014) reviewed the mechanical pretreatment of

lignocellulose by focusing mainly on the size reduction technique by grinding process

and they studied combination method, chemical-mechanical pretreatment, was

considered whereby a green ionic liquid (IL) solvent was introduced. The size

reduction of the lignocellulose particles by mechanical pretreatment had been shown

to improve the performance during the subsequent lignocellulose conversion steps due

to the increase in the surface area of the biomass particles and the decrease of

cellulose crystallinity. However, mechanical pretreatment generates costly due to high

energy consumption. Therefore, the combined mechanical and ionic liquid

pretreatment may reduce energy consumption and hence reduce the overall processing

costs.

Pangsang et al. (2018) studied the pretreatment by using Hot compress water

(HCW) for breakdown the structure and eliminate hemicellulose and lignin of oil

palm empty fruit bunch (EFB). The EFB has experienced two different processes

19

including Separate hydrolysis and fermentation (SHF) and simultaneous

saccharification and fermentation (SSF) by Saccharomyces cerevisiae TISTR 5606.

The EFB was pretreated with Hot compress water at the temperature of 200ºC at 30

bars for 15 minutes. Moreover, they experimented by using different temperatures (30

and 35°C) and enzyme loadings (100 and 300 FPU/g dry pretreated EFB) on the

hydrolysis and fermentation process. After Hot compress water pretreatment, they can

increase the cellulose content from 38.50% to 69.27% due to the elimination of

hemicellulose and lignin. As showed in Table 1, the composition of EFB pretreated

with Hot compress water. The best result, with the highest concentration of ethanol

obtained, was at 30°C in terms of both SHF and SSF processes with the range of 53.4-

54.4 g/L ethanol and 0.74-0.75 g/L⋅h.

Table 1 The chemical characteristic of raw material and pretreated EFB

Lignin (%) Cellulose (%) Hemicellulose (%)

EFB 11.63 38.50 26.12

EFB with HCW 3.77 69.27 8.63

(% dry weight)

Source: Pangsang et al. (2018)

Upajak et al. (2018) studied the pretreatment process. The lignocellulosic

biomass was pretreated by Alkaline hydrogen peroxide (AHP). The biomass was

pretreated under a condition with temperatures (30-120°C), H2O2 concentration (2.5-

10%), residence times (1, 2, and 4 h), 10 % (w/v) substrate loading and the initial

pressure was at 20 bars under nitrogen. After the pretreatment, the pretreated solids

were separated using filtration and then thoroughly washed with DI. The optimal

condition for H2O2 pretreatment of biomass was H2O2 concentration of 5% using 60 oC for 2 hours. Under optimal conditions can increase hemicellulose solubilization

into the aqueous phase and also lead to the enhanced glucose yield from enzymatic

hydrolysis and a small amount of formation of inhibitory by-products. After Alkaline

hydrogen peroxide pretreatment, they can increase in surface area, breaking structural

intermolecular bonds between carbohydrates and lignin, disordering the lignin

structure, and isolating lignin from the biomass. Therefore, H2O2 pretreatment led to

higher sugar yield after enzymatic hydrolysis of the pretreated solids.

O’Brien et al. (2000) studied the continuous fermentation process and purify

with the pervaporation method for fuel ethanol production. The data and performance

of membrane-based on previous, a flux of 0.15 kg/m2/h, and a selectivity of 10.3. For

a baseline, membrane cost is $200 per m2. Moreover, they compared the batch

fermentation process as the base case and continuous fermentation–pervaporation

process with the same dehydration method. The advantage of continuous

fermentation–pervaporation may be simplicity, toxicity to fermenting organisms, and

recovery of ethanol, requiring less distillation capacity and energy consumption. As

shown in Figures 7 and 8. They designed the equipment, sized, and costs estimated

for the fermentation, pervaporation, distillation, and dehydration process of a

commercial-scale fuel ethanol plant by using the data from a simulation by Aspen

plus software. The result showed that using commercial organophilic membranes can

20

achieve 42 wt% of ethanol concentration for a continuous fermentation–pervaporation

system. Therefore, the equipment sizes and utility requirements for the continuous

fermentation–pervaporation lower than the base case.

Figure 7 Flow diagram of batch fermentation

Figure 8 Flow diagram of continuous fermentation–pervaporation process

Source: O’Brien et al. (2000)

Medina et al. (2016) studied the effect of the steam explosion (SE)

pretreatment under autocatalytic conditions on EFB. Temperature and reaction time

were the operational variables studied. The SE pretreatment was carried out in a

stainless-steel reactor with a 10 L capacity. Pretreatment was performed with 300 g of

dried EFB, containing 2.0% ± 0.7% moisture. The material was introduced in the

reactor vessel, and saturated steam was fed until reach desired temperature, the

heating time was around 2 minutes. The reaction time was controlled after the

temperature was reached. The sudden decompression released the material into a

cyclone and the vapor was liberated to the atmosphere. The pretreated material was

neutralized with water and solids were recovered by centrifugation. The solids were

21

oven-dried, and a fraction was milled for carbohydrate and lignin analyses. The

process flow diagram is shown in Figure 9. The best pretreatment performance was

obtained at 195oC for 6 min, with an increase of 24% in cellulose and 68% reduction

in hemicellulose.

Figure 9 Flow diagram of steam explosion

Source: Medina et al. (2016)

22

MATERIALS AND METHODS

Materials

1. Personal computer (Lenovo)

1.1 Windows edition: Windows 10 Pro 64-bit Operating System

1.2 System processor: Intel ® Core ™ i5-6200U CPU @ 2.3 GHz

1.3 System installed memory (RAM): 8.00 GB

2. Microsoft Office (Excel) version 2016

3. Simulation software (Aspen Technology)

3.1 Aspen Plus V8.8

3.2 Aspen Economic Analyzer V8.8

3.3 Aspen adsorption V8.8

3.4 Aspen properties V8.8

Methods

In this work, a techno-economic analysis of the three-bioethanol production

plant from lignocellulosic feedstock was performed. Aspen Plus, Aspen Adsorption,

Aspen Economic analyzer, and Microsoft Office Excel carried out the simulation and

the economic evaluation, respectively. The information from a preliminary

experiment was required to simulate the industrial scale of the bioethanol production

process. Temperature, pressure, operating time, composition of feedstock and solid

yield determined from experiment was employed to develop the simulation model by

Aspen plus software.

Three bioethanol plants were designed to produce high purity of bioethanol as

fuel products from different feedstock including OPT, EFB, and various ratios of two

feedstocks. The different kinds of feedstock with different compositions influence the

ethanol yield in SSF process. The methodology to design three bioethanol plants

consists of many steps including understanding the necessary information required to

design the production plant, mass balance calculation, scheduling flow process,

equipment design, simulation plant, and economic assessment.

1. Concept to produce bioethanol from lignocellulose

Lignocellulose is considered as the second generation to produce

biofuel. Its main advantage is noncompetition food raw material. EFB is waste from a

palm oil extraction plant and OPT is waste from replantation that harvested every 25

years. Their component consists of cellulose, hemicellulose, lignin, ash, and other

contents. The composition of OPT and EFB in each process was obtained from

preliminary experiments as determined in Tables 2 and 3. Meanwhile, the

composition of various ratios of two feedstock did not provide. Therefore, eq. 6 was

applied to the calculated mass fraction of various ratios of two feedstocks. The

23

common process to produce ethanol is hydrolysis and fermentation. In order to obtain

high ethanol yield, three pretreatment steps, SSF and purify process were employed in

this work. The scheme of the production process comprised five main processes

including three pretreatment techniques, SSF, and purification, as shown in Figure 10.

Three-section called upstream process covered three-step pretreatment, middle stream

covered after the pretreatment process to SSF, and downstream covered purification

process. In upstream, steam explosion and hot compress water were the suitable first

pretreatment technology to pretreat OPT and EFB, respectively. After that, the same

technology and condition were conducted for both feedstocks. For OPT plant, two

dehydration technologies were studied to determine the suitable technology for

dehydrate the dilute ethanol to fuel grade. The proper technology will be employed

for other plants.

Figure 10 The scheme of the production process

2. Mass balance

Mass balance calculation is elementary work before simulation to

verify the simulation result from Aspen plus. The mass balance template was

developed by Microsoft Office (Excel) version 2016 to follow the distribution of mass

in each process faithfully. The experiment's data including the mass fraction of

cellulose, hemicellulose, lignin, ash, other, total mass recovery, and ethanol yield,

were applied to create mass balance flowsheet. Since there is no information in some

parts, the assumption by a specialist was required. The 6to create the mass balance

flowsheet was presented in Tables 2 to 6.

Table 2 The composition of OPT in each process

OPT SE Hot water H2O2 Neutralize

Composition % dry % dry % dry % dry % dry

Cellulose 0.3867 0.439 0.6176 0.6786 0.7396

Hemicellulose 0.233 0.232 0.041 0.02635 0.0117

Lignin 0.2376 0.116 0.2032 0.16 0.1168

Ash 0.0162 0.0162 0.0116 0.01055 0.0095

Other 0.1265 0.1968 0.1266 0.1245 0.1224

Pretreatment

2nd SSF Purification

Pretreatment

3rd

Pretreatment

1st

Upstream Middlestream Downstream

24

Total 1 1 1 1 1

% recovery 1 0.894 0.791 0.731 0.982

% moisture 0.37 0.82 0.84 0.12

Table 3 The composition of EFB in each process

EFB HCW Hot water H2O2 Neutralize

Composition % dry % dry % dry % dry % dry Cellulose 0.3885 0.5690 0.6927 0.7057 0.7057

Hemicellulose 0.2614 0.1345 0.0863 0.0136 0.0136

Lignin 0.1162 0.1302 0.0377 0.1490 0.1490

Ash 0.014 0.0128 0.0144 0.0178 0.0178

Other 0.2199 0.1532 0.1689 0.1137 0.1137

Total 1 1 1 1 1

% recovery 1 0.908 0.769 0.866 0.997

% moisture 0.37 0.82 0.84 0.12

Because of non-available the composition of the various ratios of two

feedstocks results, eq 6 will be used to calculate mass fraction for each ratio. Tables 4

to 6 show the composition of various ratios of EFB:OPT in each process.

Mass fraction of i = (X × xi) + (Y × yi) (6)

Where X is ratio of EFB

Y is ratio of OPT

xi is the composition i of EFB mass fraction

yi is the composition i of OPT mass fraction

i is the composition of feedstock

Table 4 The composition of the 80:20 ratio of EFB:OPT in each process

EFB OPT HCW SE Hot

water

H2O2 Neutralize

Composition % dry % dry % dry % dry % dry % dry % dry Cellulose 0.3885 0.3885 0.5690 0.439 0.6777 0.7003 0.7125

Hemicellulose 0.2614 0.2614 0.1345 0.232 0.0772 0.0162 0.0133

Lignin 0.1162 0.1162 0.1302 0.116 0.0708 0.1512 0.1426

Ash 0.014 0.014 0.0128 0.0162 0.0138 0.0164 0.0162

25

Other 0.2199 0.2199 0.1532 0.1968 0.1604 0.1159 0.1155

Total 1 1 1 1 1 1 1

% recovery 1 1 0.908 0.894 0.7734 0.839 0.994

% moisture 0.37 0.37 0.82 0.84 0.12


EFB OPT HCW SE Hot

water

H2O2 Neutralize


Hemicellulose 0.2614 0.2614 0.1345 0.232 0.0637 0.0200 0.0127

Lignin 0.1162 0.1162 0.1302 0.116 0.1205 0.1545 0.1329

Ash 0.014 0.014 0.0128 0.0162 0.0130 0.0142 0.0137

Other 0.2199 0.2199 0.1532 0.1968 0.1478 0.1191 0.1181

Total 1 1 1 1 1 1 1

% recovery 1 1 0.908 0.894 0.78 0.7985 0.9895

% moisture 0.37 0.37 0.82 0.84 0.12


EFB OPT HCW SE Hot

water

H2O2 Neutralize


Hemicellulose 0.2614 0.2614 0.1345 0.232 0.0501 0.0238 0.0121

Lignin 0.1162 0.1162 0.1302 0.116 0.1701 0.1578 0.1232

Ash 0.014 0.014 0.0128 0.0162 0.0122 0.0120 0.0112

Other 0.2199 0.2199 0.1532 0.1968 0.1351 0.1223 0.1207

Total 1 1 1 1 1 1 1

% recovery 1 1 0.908 0.894 0.7866 0.758 0.985

% moisture 0.37 0.37 0.82 0.84 0.12

The composition of 100:0 and 0:100 of EFB:OPT is the same as the

composition of EFB and OPT. In this work, mass input was determined 47,208 kg/day

of feedstock for three plants to produce more than 10,000 L/day of 99.5 wt% ethanol.

26

3. Concept to design size of equipment

The basic concept to design the size of equipment was to cover 47,208

kg/day of feedstock. The maximum size of the reactor base on the available maximum

size, 50 m3. Since upstream processes took a shorter time compared with the SSF

process, they could be designed to be a cyclic operation of small units to minimize the

equipment purchasing costs and avoid the bottleneck before feeding to the SSF. The

mass flow in each process was applied to access the size of equipment in each

process. Mass flow in/out and operating time of each process determine the size of the

reactor, which is the main factor impacting the equipment purchasing costs and

directly influences the total capital cost. The concept to design the size of equipment

for the various ratios of OPT and EFB plant was to cover maximum capacity

production for 100:0, 80:20, 50:50, 20:80, 0:100 of EFB:OPT. Most reactors can be

simply a tank e.g. agitated tank, heat jacket tank, mixing heat jacket tank.

4. Scheduling flow process

The operating time of the upstream process was assumed to 30 minutes

excluding the sterilized unit took only 20 minutes. Scheduling aims to avoid the

bottleneck and run a continuous production because of completely different operating

times of the upstream process and individual SSF. The first pretreatment tank was

filled with small pieces of feedstock and then operated for some time. After the

required time has elapsed, the treated feedstock in the reactor was drained out and the

fed to further reactor by a screw pump. Moreover, most processes were batch

operating and neglected time to transfer during the process. Therefore, it is important

to design the size, amount of the reactor, and sequence of unit utilization to avoid the

bottleneck and produce bioethanol more than 10,000 liters every day. As the SSF

process required the longest operating time for 60 hours. So, it was considered as a

bottleneck point and the maximum volume of reactor (50 m3) was employed. Most of

the previous equipment was utilized for shorter periods compared to the SSF process.

Therefore, a new cycle of the first pretreatment step was initiated every 30 minutes.

5. Simulation process of bioethanol by Aspen Plus software

This section describes the condition and required information in the

simulation section. The simulation was performed in Aspen Plus and Adsorption

software to simulate the entire process and PSA performance. Figures 11 to 13

illustrate the framework of three production plants.

27

Figure 11 Overview of the bioethanol production process from OPT

Figure 12 Overview of the bioethanol production process from EFB

Figure 13 Overview of the bioethanol production process from various ratios of OPT

and EFB

5.1. Pretreatment process

The feedstocks were milled to small sizes of about 20×20×5

mm and removed moisture by sundry before pretreatment. In pretreatment focus on 4

techniques including Hot Compress Water (HCW) (at 200oC, 30 bar, 15 min), Steam

explosion (SE) (at 210oC, 18.6 bar, 4 min), Hot water (at 80 oC, 30 min) and hydrogen

peroxide digestion (H2O2) (at 70oC, 30 min). HCW and SE methods were primary

pretreatments for EFB and OPT, respectively. The condition for each pretreatment

step was as follows.

5.1.1. Hot compress water (HCW), 1:10 of OPT:water

was added into a heat jacket agitated vessel and operated under 200 ºC, 30 bar for 15

min.

28

5.1.2. Steam explosion (SE), small particle sizes of EFB

were added into a SE reactor and input hot stream until reached 210 ºC, 18.6 bar and

wait for 4 min.

5.1.3. Hot water washing, 1:8 of OPT:water was added

into a heat jacket agitated vessel and operated under 80ºC for 30 min.

5.1.4. Hydrogen peroxide (H2O2) digestion, the treated

OPT and EFB were added to a digestion vessel containing 10:1 of water:solid,

3.5:10,000 of NaOH:solid and 3:100 of 3 wt% of H2O2:solid. All components were

mixed together and operate under 80ºC for 30 min.

The purpose of the pretreatment process is for enhancing the

cellulose reactivity with cellulase enzymes and increasing the yield of fermentable

sugars. Pretreatment can increase bioethanol yield and productivity significantly.

5.2. Simultaneous saccharification and fermentation (SSF)

SSF is a combination process of hydrolysis and fermentation to

produce ethanol from lignocellulose. The principle of performing is the enzymatic

hydrolysis together with the fermentation, instead of the hydrolysis before

fermentation. The main advantages of SSF are shorter operating times and higher

productivity compared with SHF. On the other hand, disadvantages are the need to

find a suitable condition for both the enzymatic hydrolysis and the fermentation such

as temperature and the difficulty to recycle the yeast and the enzymes.

In SSF process required enzyme Ctec2 10 FPU/g fiber and S.

cerevisiae. They were added together and operated under 40°C. It can produce the

highest ethanol yield of about 34 g/L of ethanol for OPT and 33.11 g/L for EFB at 60

hr. The ethanol yield of various ratios of feedstocks was presented in Table 9.

5.3. Purification

The mixture from SSF, remained a quantity of water, need to

remove impurity and increase ethanol concentration to fuel grade by removing the

water contain. The common method to separated is distillation, involving separation

mixtures of liquids by exploiting differences in the boiling points of the different

components then subsequently condensed back to a liquid phase. The distillation

process works by the different boiling point of the water and ethanol. As ethanol has a

lower boiling point compared to water, the ethanol will become the vapor phase

before the water. It goes up to the top of the column and is condensed and separated.

In this work, the distillation column was represented by the Radfrac model to operate

under vacuum pressure and implemented by Aspen Plus 8.8V. The dilute ethanol

from SSF process was fed to the vacuum distillation column to produce high ethanol

concentration at top of the column called overhead stream. The ethanol concentration

in the overhead stream directly affects the performance and costs of the dehydration

section. Therefore, the 4 cases of various ethanol concentrations in the overhead

29

stream were carried out to determine the suitable concentration with the lowest

production cost per unit. The parameters of the distillation column including molar

reflux ratio, number of stages, feed stage and distillation to feed were optimized to

produce the purpose overhead product e.g. 50, 80, 85, 90 wt% of ethanol for

pervaporation (PV) technology and 80, 85, 90, 94 wt% for pressure swing adsorption

(PSA) technology. The sensitivity of four parameters of the distillation column was

studied to determine the proper values to produce various ethanol concentrations with

minimum energy demand and the quantity of ethanol loss in the waste stream must

lower than 1 kg/hr.

Figure 14 Purification section

5.3.1. Dehydration

Pervaporation

Pervaporation is the methodology to separate the liquid mixture

by property of membrane. The membrane is a dense non-porous polymeric membrane

or inorganic membrane that allow removing specific component to pass through the

membrane. This work, hydrophilic was applied to remove water content less than

ethanol. The water will be evaporated into the vapor phase as a result of the vacuum

pressure on the permeate side, contain a high fraction of water and a few ethanols are

condensed to the liquid phase and pump to distillate as recover stream. The final

products, high ethanol is obtained from the retentate side. The calculation method of

the energy demand of pervaporation was provided in this section. The energy needed

for the evaporation of water per unit of permeated is Q* (MJ/kgw). Hi is the heat of

pervaporation of species i (Et, W denoted Ethanol and water, respectively).

𝑄∗ = 𝐻𝐸𝑡𝐽𝐸𝑡

𝐽𝑊 + 𝐻𝑊 (7)

In the case of vacuum pervaporation, the value of Q* was taken

into account to calculate the specific energy demand related to that of product 1 kg of

ethanol with 𝐶𝑊,𝑜𝑢𝑡𝐿 the concentration of the water inlet phase. The energy required is

calculated as follows eq 8.

PSA Ethanol

99.5 wt%

Ethanol

3 wt%

Dehydration

PV Distillation

Column

Number of stages

Molar reflux ratio

Distillation to feed

Feed stage

30

𝑄 = 𝑄∗(𝐶𝑊,𝑖𝑛

𝐿 − 𝐶𝑊,𝑜𝑢𝑡𝐿 )

𝐶𝐸𝑡,𝑖𝑛𝐿 −(𝐶𝑊,𝑖𝑛

𝐿 − 𝐶𝑊,𝑜𝑢𝑡𝐿 )

𝐽𝐸𝑡𝐽𝑤

(8)

The 𝐽𝑖 is mass transfer or permeation rate of species i, was used

to calculating the specific energy eq 7.

𝐽𝑤

𝐽𝐸𝑡= [

𝐶𝑤

𝐶𝐸𝑡]𝐺 (9)

Eq 9. is a mass transfer ratio that can be rewritten as eq 10.

𝐽𝑤

𝐽𝐸𝑡=

𝐶𝑤−𝐿

𝛼𝐶𝐸𝑡−𝐿 (10)

Where 𝐶𝐸𝑡−𝐿 and 𝐶𝑤

−𝐿 are the logarithmic mean value of ethanol

and water in the feed phase, which can be calculated as follow eq 11.

𝐶𝐸𝑡−𝐿 =

𝐶𝐸𝑡,𝑖𝑛𝐿 − 𝐶𝐸𝑡,𝑜𝑢𝑡

𝐿

𝐼𝑛(𝐶𝐸𝑡,𝑖𝑛𝐿 /𝐶𝐸𝑡,𝑜𝑢𝑡

𝐿 ) (11)

As knowing the ratio of permeation rates of i, the concentration

of liquid permeate can be predicted by eq 12.

𝐶𝐸𝑡𝐺 =

1

1+𝐶𝑤

−𝐿

𝛼𝐶𝐸𝑡−𝐿

(12)

The recovery efficiency of fuel-grade quality (𝜂) can be

calculated by eq 13.

𝜂 = (1 −𝑉𝑝

𝑉𝑖𝑛)

𝐶𝐸𝑡,𝑜𝑢𝑡𝐿

𝐶𝐸𝑡,𝑖𝑛𝐿 (13)

Pressure swing adsorption

Aspen Adsorption was used to simulate the performance of

cyclic PSA. The two columns were considered as absorption and desorption working

in the cycle. The PSA cycle consists of two stages. 1) Adsorption which operates

under high pressure, gases water will be attracted to the adsorbent surface. 2)

Desorption which operates under low pressure to release adsorbed water. The result of

various ethanol concentrations in the overhead stream from Aspen pen software was

transferred to Aspen adsorption software. The overhead stream was fed to the bottom

of the PSA column, packed with Zeolite 3A in the form of spheres with properties as

shown in Table 14. Mathematic Modeling of Pressure swing absorption as follows eq.

14 was used to analyze the ethanol dehydration production process.

31

𝑄𝑖 = 𝐼𝑃1𝑖𝐼𝑃2𝑖𝑃𝑦𝑖

1+Σ𝑘(𝐼𝑃2𝑘𝑃𝑦𝑘) (14)

Where 𝑄𝑖 𝑖𝑠 Amount adsorbed for component i,(kmol/kg

adsorbent), 𝐼𝑃1,2 𝑖𝑠 Isotherm parameters for component i, 𝑃 is Gas Pressure,(bar) and

yi is Gas-phase mole fraction for component i

In this work, three bioethanol production plants were simulated and evaluated

economic feasibility. The first plant was designed for only OPT as feedstock. For

OPT plant, two dehydration technologies including PV and PSA were compared. The

best candidate for technology to purify 3 wt% of the ethanol from OPT plant was

employed for other plants. The second plant was designed for only EFB as feedstock.

EFB has the high potential to produce more ethanol yield according to high cellulose

contain. However, OPT has an obvious limitation in terms of the seasonally harvested

oil palm trunk. So, the third plant was designed for two feedstocks, EFB and OPT.

This plant has more flexibility in operation which can work with various ratios of

EFB and OPT. The period for operating was 7,200 hours/year. The life of the plant

was 20 years with a capacity of more than 10,000 Liters/day of 99.5 wt% ethanol.

6. Economic assessment

The economic evaluation of each alternative bioethanol plant was

calculated in order to determine the feasibility of a project. In this work, Direct fixed

capital (DFC) was represented as the total capital cost. The methodology to calculate

DFC is reported in Petrides (2000). DFC was estimated based on the total equipment

purchasing cost (PC) in a plant. This section showed the element for the calculation of

the total capital cost. The costs of common equipment such as mixing tank, heat

jacket tank, pump were estimated by Vendors' citation. Costs for some equipment

such as cooler, heaters, distillation column were calculated by the Aspen process

economic analyzer V8.8. The total operating cost consists of raw materials, labor,

chemical substance, plant overhead, G and A expenses, utilities, maintenance,

miscellaneous, and membrane/molecular sieve replacement. The detail of total capital

and the operating cost was explained as follows.

6.1. Total Capital cost

The method to calculate total capital cost comprises of 4 main

elements.

1. Total plant direct cost (TPDC) including

1.1 Equipment Purchase Cost (PC) is the major factor in DFC

calculation.

1.2 Installation costs were according to 50 % of PC.

1.3 Piping was according to 40 % of PC. The expense of piping

including purchasing and layout design represented in this part.

32

1.4 Instrumentation costs were estimated at 35 % of PC.

1.5 Insulation is the necessary item for the safety of plant was

estimated at 3 % of PC

1.6 Electrical consists of the infrastructure of the plant such as

lighting, wiring in the plant were estimated at 15 % of PC

1.7 Building costs requires the control room, laboratory, office,

and plant. the costs were estimated at 45 % of PC.

1.8 Land was decided to locate in the south of Thailand where

is the main region for palm production. So, located nearby the feedstock source can

reduce transportation costs. The land value was estimated at 4% of PC, and profit

from land after the end of the plant’s life is 20% per year.

2. Total plant indirect cost (TPIC) including

2.1 Engineering costs including design plant layout, draft and

green print of plant, was estimated at 25 % of TPDC

2.2 Construction costs of the plant were estimated at 35% of

TPDC

3. The contractor’s fee, including during construction and business,

was estimated at 5% of the summation of TPDC and TPIC.

4. A contingency is an expense for a potentially negative event that

may occur in the future, such as natural disasters, economic fluctuation. It was

estimated at 10% of summation of TPDC and TPI

6.2. Total operating cost

In this section, the expenses were divided into 9 elements.

1. Raw materials

The bioethanol plant has a capacity of more than 10,000 L/day

of ethanol. The feedstock, OPT, EFB, and various ratios of OPT and EFB, was

required 47,208 kg/day. The price of OPT is 0.001 $/kg and 0.0015625 $/kg for EFB

which base on the retailer citation in the south region of Thailand.

2. Labor

The operating labor per shift is 12 labors. This plant has 3 shifts

in one day, 8 hours per shift. The local labor costs in the south region of Thailand on

average about 1.2 $/day.

3. Chemical substance

33

The amount of chemical was required to produce bioethanol.

The price of enzyme Ctec2 is 0.53 $/kg, 0.81 $/kg for hydrogen peroxide, 0.09 $/kg

for ammonium sulfate, 0.10 $/kg for urea, 0.20 $/kg for sodium hydroxide, and

S.Cerevisae cultivation was accounted for 10% of total chemical price for one SSF

tank.

4. Plant overhead

Plant Overheads are the charge which cannot directly determine

or traced with any element costs. Plant overhead was estimated at 25% of the

summation of labor and maintenance costs (Goldthorpe et al. 2014).

5. G and A expenses

G and A expenses costs are necessary costs to maintain a

company's daily operations. G and A expenses were accounted for 4 % of summation

of labor, plant overhead, and maintenance costs (Goldthorpe et al. 2014).

6. Utilities

The utility consists of electric city, steam, and water. All utility

prices base on the price in Aspen Plus 8.8V. The electricity is 7.75x10-2 $/kW, water

is 2.12x10-7 $/KJ/hr, and steam which is the main utility of plant is 1.90x10-6 $/KJ/hr.

7. Maintenance

Maintenance costs were accounted for 10% per 8,000 hr of

purchasing equipment costs. This parameter base on the database in Aspen Plus 8.8V.

8. Miscellaneous

Miscellaneous is a special expense excluding the above

element. It was assumed at 1000 $ per year (Diopenes and Laptaned 2009).

9. Membrane/molecular sieve replacement

Membrane and Zeolite 3A were assumed to replace every 5

years. The price of the membrane on average is 200 $/m2 with 100 $ replacement

cost. The price of adsorbent (Zeolite 3A) is 1.3 $/ kg, 4639 kg per one column

(O’Brien et al. 2000).

Table 7 displays the related parameters to evaluate the economic

feasibility of the plant. Discount rate bases on the minimum loan rate of Krungthai

bank (7 Feb 2020). The selling price of the final product was assumed to 0.781$/L

base on the average price of ethanol in Thailand. Depreciation expense with the

straight-line depreciation method bases on Thailand Tax Depreciation Rates. The end

34

of plants’ life, revenue from salvage value of equipment, and profit from land will be

received. Table 8 displays the escalation cost defines as changes in the costs of

product, raw material, labor, and utilities in a given economy over a period (Diopenes

and Laptaned 2009).

Table 7 Parameter for economic assessment

Parameters Values Ref.

Working time 7200 hours N/A

Raw material 1967 kg/hour N/A

Discount rate 5.775% Krungthai bank’s

report

Proposed product price 0.781 $/L N/A

Tax rate 20 %/year Thailand Corporate

Tax Rate

Economic life of the project 20 years N/A

Depreciation method Straight Line N/A

Depreciation Expense 20% Thailand Tax

Depreciation Rates

Land 20% TerraBKK Research

Savage value 20% TerraBKK Research

Table 8 Escalation assumption

Percent/year

Products Escalation 1

Raw Material Escalation 1

Operating and Maintenance Labor Escalation 1

Utility Escalation 1

The parameters represented in Table 7 and 8 were used to calculate cost

analysis, total capital investment (TCI), the net present value (NPV) Internal rate of

return (IRR), and Payback Period (PB) by Microsoft Office Excel 2016 to assess the

feasibility of investment in this project.

7. Sensitivity Analysis

In this section, the sensitivity of two variables was studied for the lowest

production cost of OPT plant. Since the purification was mentioned as the highest

energy consumption part and also generate a high production cost. The costs of

purification strongly rely on ethanol concentration in the feed. Therefore, the various

ethanol concentration in the fermentation broth was assumed and studied in this

section to determine the effect of ethanol concentration on production cost.

7.1. The concentration of ethanol from SSF

• 4 wt% ethanol in a fermentation broth

35



As different ethanol concentrations in the fermentation broth, the various

ethanol concentrations in feed were increased to 80, 85, 90 wt% to determine the

proper ethanol concentration in the overhead stream before feeding to dehydration

section with pervaporation technology.

Moreover, the effect of the highest portion of chemical price was analyzed.

Enzyme Ctec2 was the highest portion accounting for 40 % of the chemical costs. The

price of enzyme Ctec2 was reduced by 15, 30, 45, 60, 75% from the initial price (0.53

$/kg) to calculate the production cost per unit.

7.2. Chemical cost

• 15 % reduction of enzyme Ctec2 price (0.45 $/kg)





.

36

RESULTS AND DISCUSSION

The result of three bioethanol production plants including OPT, EFB, and

various ratios of two feedstocks plants has presented. The first plant focuses on the

determination of the proper technology in the purification section to obtain the lowest

production cost per unit by comparison of the combination of optimized distillation

column with pervaporation (PV) and optimized distillation column with pressure

swing adsorption (PSA). The second (EFB) and third (two feedstocks) plant have

studied the effect on the economic results when utilizing the EFB and various ratios of

two feedstocks by remaining the best candidate for purification technology from OPT

plant.

1. Mass balance calculation

A mass balance flowsheet was developed by Microsoft excel 2016. Mass

balance calculation is essential for verifying the consistency of the compositional

analysis data after the pretreatment and SSF process. The amount of ethanol in the

final process can be estimated by the material balance calculation. The mass transfer

result of each unit was applied to calculate the size, number, and unit utilization of the

reactor in each unit. Table 9 displays the amount of mass input (feedstock), output

(final product), and ethanol concentration from SSF. EFB contains the higher

cellulose fraction with lowers major resistant composition, e.g. lignin compared with

OPT. So, EFB and high EFB ratio in two feedstocks plants can produce a higher

ethanol yield when using the same amount of input (feedstock).

Table 9 Mass input and mass output of three plants

Feedstock Mass input

(kg)

Ethanol

(Liters)

ethanol concentration

(w/v%)

OPT 47,208 11,404.33 3.311

EFB 47,208 13,880.55 3.4

EFB:OPT ratio

100:20 47,208 13,880.55 3.4

80:20 47,208 13,377.41 3.3822

50:50 47,208 12,629.98 3.3555

20:80 47,208 11,891.52 3.3288

0:100 47,208 11,404.33 3.311

2. Equipment design

The mass transfer in each unit determines the size of the rector. The size and

type of main equipment for OPT, EFB, and two feedstock plants were displayed in

Appendix Table A1 to A3, A4, and A5 to A6. The main equipment of various ratios

of feedstocks plant was designed to cover the maximum capacity (100:0 of

EFB:OPT). So, the equipment size of two plants, EFB and various ratios of

feedstocks, was the same.

37

3. Scheduling

The appropriate scheduling can increase productivity without further

investment. Therefore, scheduling is significantly influential to investment costs. As

each plant operates with different sizes and amounts of a reactor, lead to a different

schedule must be designed. The schedule aims to produce bioethanol for more than

10,000 liters every day. Figures 15 and 17 display the equipment utilization to feed

the pretreated feedstock to one SSF tank. EFB and two feedstocks plants can operate

with the same schedule because of utilizing the same size and amount of equipment.

Due to the maximum size of the reactor was 50 m3, 6 and 8 tanks of SSF were

required for OPT and EFB plant to cover 10,000 L of ethanol called a batch. Figures

16 and 18 display the equipment utilization for two consecutive batches. The

operating time of the upstream process is 6 and 5 hours for OPT and EFB plant. This

is the time required to go from the preparation of feedstock until fulfilling the first

SSF tank. Then, the pretreated feedstock in SSF tank was sterilized for 20 minutes

before SSF process, For SSF process required 3 hours to produce the highest ethanol

yield. Therefore, the first SSF tank produced ethanol at 66 hours 20 minutes and 65

hours 20 minutes for OPT and EFB plant. However, since most of the upstream

process was utilized for shorter periods compare with SSF, a new first pretreatment

process is initiated every 30 minutes. Therefore, the next SSF can complete in 3 and 4

hours for OPT and EFB plant.

The upstream process of OPT plant was operated for eight rounds before

feeding to one tank of SSF as presented in Figure 15. One batch demands 6 tanks of

SSF to produced 10,000 L of ethanol as shown in Table 10. For EFB and two

feedstocks plants, upstream processes operated for six rounds before feeding to one

tank of SSF as shown in Figure 17. One batch demands 8 tanks of SSF to produced

10,000 L of ethanol as shown in Table 11. The total processing time is approximately

5,180 minutes to produce the first 10,000 L of ethanol which runs from the first

pretreatment step to the SSF process. The next batch can complete in 24 hr to produce

10,000 L of ethanol. To continue the production process and avoid the bottleneck, 16

and 21 of SSF tanks were required for OPT and EFB plant.

38

Figure 15 Operating time of the initial SSF tank of OPT plant

Figure 16 Equipment utilization for two consecutive batches for OPT plant

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000

Round 1

Round 2

Round 3

Round 4

Round 5

Round 6

Round 7

Round 8

Time (min)

SE

HOT

H2O2

Neutralize

Media

Sterilize

SSF

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000

Round 1

Round 7

Round 13

Round 19

Round 25

Round 31

Round 37

Round 43

Round 49

Round 55

Round 61

Round 67

Round 73

Round 79

Round 85

Round 91

Time (min)

SE

HOT

H2O2

Neutralize

Media

Sterilize

SSF

39

Table 10 The operating time of upstream and SSF and SSF tank utilization for OPT

plant

SSF

tank no.

Upstream SSF

Start (min) End (min) Start (min) End (min)

First batch (10,000 L of ethanol)

1 0 360 360 3980

2 240 600 600 4220

3 480 840 840 4460

4 720 1080 1080 4700

5 960 1320 1320 4940

6 1200 1560 1560 5180

Second batch (10,000 L of ethanol)

7 1440 1800 1800 5420

8 1680 2040 2040 5660

9 1920 2280 2280 5900

10 2160 2520 2520 6140

11 2400 2760 2760 6380

12 2640 3000 3000 6620

Third batch (10,000 L of ethanol)

13 2880 3240 3240 6860

14 3120 3480 3480 7100

15 3360 3720 3720 7340

16 3600 3960 3960 7580

1 3840 4200 4200 7820

2 4080 4440 4440 8060

Fourth batch (10,000 L of ethanol)

3 4320 4680 4680 8300

4 4560 4920 4920 8540

5 4800 5160 5160 8780

6 5040 5400 5400 9020

7 5280 5640 5640 9260

8 5520 5880 5880 9500

Fifth batch (10,000 L of ethanol)

9 5760 6120 6120 9740

10 6000 6360 6360 9980

11 6240 6600 6600 10220

12 6480 6840 6840 10460

13 6720 7080 7080 10700

14 6960 7320 7320 10940

40

Figure 17 Operating time of the initial SSF tank of EFB and two feedstocks plants

Figure 18 Equipment utilization for two consecutive batches for EFB and two

feedstocks plants

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 6,500 7,000

Round 1

Round 6

Round 11

Round 16

Round 21

Round 26

Round 31

Round 36

Round 41

Round 46

Round 51

Round 56

Round 61

Round 66

Round 71

Round 76

Round 81

Round 86

Round 91

Round 96

Time (min)

SE&HCW

Hot water

H2O2

Neutralize

Media

Sterilize

SSF

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000

Round 1

Round 2

Round 3

Round 4

Round 5

Round 6

Time (min)

SE&HCW

Hot water

H2O2

Neutralize

Media

Sterilize

SSF

41

Table 11 The operating time of upstream and SSF and SSF tank utilization for EFB

and various ratios of feedstocks plants

SSF

tank no.

Upstream SSF

Start (min) End (min) Start (min) End (min)

First batch (10,000 L of ethanol)

1 0 300 300 3920

2 180 480 480 4100

3 360 660 660 4280

4 540 840 840 4460

5 720 1020 1020 4640

6 900 1200 1200 4820

7 1080 1380 1380 5000

8 1260 1560 1560 5180

Second batch (10,000 L of ethanol)

9 1440 1740 1740 5360

10 1620 1920 1920 5540

11 1800 2100 2100 5720

12 1980 2280 2280 5900

13 2160 2460 2460 6080

14 2340 2640 2640 6260

15 2520 2820 2820 6440

16 2700 3000 3000 6620

Third batch (10,000 L of ethanol)

17 2880 3180 3180 6800

18 3060 3360 3360 6980

19 3240 3540 3540 7160

20 3420 3720 3720 7340

21 3600 3900 3900 7520

1 3780 4080 4080 7700

2 3960 4260 4260 7880

3 4140 4440 4440 8060

Fourth batch (10,000 L of ethanol)

4 4320 4620 4620 8240

5 4500 4800 4800 8420

6 4680 4980 4980 8600

7 4860 5160 5160 8780

8 5040 5340 5340 8960

9 5220 5520 5520 9140

10 5400 5700 5700 9320

11 5580 5880 5880 9500

42

4. Simulation model

4.1. Pretreatment model

The completed simulation model of three bioethanol production plants

was illustrated in Figures 118 to 121. In the first step, feedstocks were fed to the

crusher machine to reduce the size before the pretreatment method and remove

moisture by sundry. The small pieces of feedstock were introduced to the

pretreatment section, consists of 3 steps to change the structure of the feedstock and

make cellulose more accessible in the subsequent process. Figures 19 and 20 illustrate

the model of the pretreatment section of OPT and EFB plant.

Figure 19 Simulation model of the three pretreatment processes for OPT

Figure 20 Simulation model of the three pretreatment processes for EFB

Three pretreatment units were represented in RYield model in Aspen

Plus 8.8V. The first pretreatment for OPT was a steam explosion (SE), the small

pieces of OPT were added into the reactor and input the hot steam to increase

temperature and pressure to desire condition (210 oC, 18.6 bar), then open the valve to

decrease pressure to atmospheric pressure rapidly. The total operating time of SE

process was assumed to 30 min. The OPT fibers exploded at atmospheric pressure and

the structure of biomass was changed. Meanwhile, small pieces of EFB were

introduced to the high-pressure agitated vessel jacket, operated under high pressure

HCW HOTWATER

HYDROGEN

NEUTRAL

PUMP2 PUMP3PUMP4

CENTRIFU

PUMP1

EFB

WATER1

H2O2

WATER2

NAOHWATER3

WATER

INPUMP3

S17INPUMP5

SE HOTWATER

HYDROGEN

NEUTRAL

PUMP2 PUMP3PUMP4

CENTRIFU

PUMP1

OPT

WATER1

H2O2

WATER2

NAOHWATER3

STEAM

INPUMP2

INPUMP3

S17

S1

INPUMP5

43

and temperature (200 oC, 30 bar, 30 min). The second pretreatment aims to remove

the hemicellulose by washing with hot water at 80 oC for 30 min. The last step was

pretreatment with hydrogen peroxide digestion (H2O2). The 50 wt% of H2O2 solution

was diluted to 3 wt% before fed in the reactor. This step, water, NaOH, and 3 wt% of

H2O2 were added in one reactor and operated at 70 oC for 30 min. The purpose of

H2O2 digestion is removing the lignin which is an inhibitor for hydrolysis and

fermentation process. After pretreatment, the feedstock contains high cellulose

fraction and low hemicellulose, lignin, ash, and other fraction. The next step is to

adjust pH by adding water to neutralize. Since soaked feedstock in the neutralizing

process was centrifuged by the centrifugal machine to remove water form feedstock.

4.2. SSF model

After the pretreatment process, the treated feedstocks were sent to the

mixing tank by screw pump as shown in Figure 21. This process aims to prepare the

suitable surrounding condition for fermentation by adding water, urea, and

ammonium sulfate. These chemicals were mixed together called media. Mixing of

treated feedstock and media was sterilized at 121 oC for 20 min before sending it to

SSF process. In SSF process, enzyme Ctec2 and yeast Saccharomyces cerevisiae were

simultaneously added into the SSF reactor. Simultaneous saccharification and

fermentation (SSF) is one process option to produce ethanol from lignocellulose. The

principal benefits of performing the enzymatic hydrolysis together with the

fermentation, instead of in a separate step after the hydrolysis, are the reduced end-

product inhibition of the enzymatic hydrolysis, and the reduced investment costs.

From our preliminary, the highest ethanol yield from OPT and EFB was 3.311 w/v%

and 3.4 w/v%. The highest ethanol yield can be achieved at 60 hours after this time

the concentration continuously decreases. Plenty of chemical substances were

required for producing 10,000 L/day of ethanol. So, sensitivity analysis of chemical

costs will be concerned in the sensitivity section.

Figure 21 Simulation model of the media preparing, sterilizing and SSF process

4.3. Purification model

For OPT plant, the diluted ethanol (3.311 w/v%) was fed to the

purification section to remove impurity and increase concentration of ethanol to fuel

MIXT ANK SS FAUTOCLAV

PUMP5PUMP6

PUMP7

UREA

AMMONIUM

YE AST

CT EC2

INSS F

INAUTOCL

INPUMP6INPUMP8

INPUMP7

WAT ER4

INPUMP5

44

grade. In purification section carried out the combination of the distillation column

and dehydration technology. The four-parameter of the distillation column was

optimized to produce high ethanol concentration before feeding to the dehydration

process. In the dehydration process, two technologies including pervaporation (PV)

and pressure swing adsorption (PSA) were compared to find out the proper

technology to increase ethanol concentration to 99.5 wt%. The waste stream from the

dehydration model contained dilute ethanol, was recycled to a distillation column to

minimize ethanol loss. The simulation model of OPT plant with pervaporation and

pressure swing adsorption is illustrated in Figure 118 and 119, respectively. The best

candidate for dehydration technology was employed for EFB and two feedstocks

plants due to containing similar ethanol yield in the SSF process.

4.3.1. Optimize parameter of Distillation column

Figures 22 to 113 present the effect of four-parameters on the

mass flow of ethanol, ethanol loss in the waste stream in the blue line ( ) and

ethanol concentration, reboiler duty in the orange line ( ).

The number of stages and molar reflux ratio were increased to

rise purity of the overhead product. The reflux ratio not only increases purity but also

increases the quantity of liquid condensed and returning to the column. Distillation to

feed directly affects the amount of mass flow in the overhead stream. Consequently,

cost increases for reboiler and condenser. Figures 22 to 113 present the effect of 4

parameters on mass fraction, the mass flow rate of ethanol, reboiler duty, and the

mass flow of ethanol in the waste stream. The suitable values ware selected to

produce the purposed ethanol concentration (50-94 wt%) and mass flow with low

reboiler duty and ethanol in the waste stream must less than 1 kg/hr. Radfrac column

was performed to increase ethanol concentration to 50, 80, 85, 90 wt% before sending

to pervaporation model and 80, 85, 90, 94 wt% before pressure swing adsorption

model.

45

4.3.1.1. Sensitivity analysis four-parameter of distillation column for

OPT pant with pervaporation technology

Distillate to 50 wt%


with pervaporation technology







0

0.2

0.4

0.6

0.8

1

0

100

200

300

400

500

4 6 8 10 12

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Numer of stage

0

20

40

60

80

100

120

5.00E+05

5.05E+05

5.10E+05

5.15E+05

4 6 8 10 12

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

1

2

3

4

5

6

7

8

3.70E+05

4.20E+05

4.70E+05

5.20E+05

5.70E+05

6.20E+05

2 2.5 3 3.5 4

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

426

427

428

429

430

431

432

433

434

2 2.5 3 3.5 4

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

0

100

200

300

400

500

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

300

350

400

1.70E+05

4.70E+05

7.70E+05

1.07E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.5

1

1.5

2

2.5

3

5.00E+05

5.05E+05

5.10E+05

5.15E+05

2 3 4 5 6

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

430.5

431

431.5

432

432.5

433

433.5

434

2 3 4 5 6

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

46










0

2

4

6

8

10

12

2.58E+05

2.58E+05

2.58E+05

2.58E+05

2.58E+05

2.58E+05

2.58E+05

2.58E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

0.2

0.4

0.6

0.8

1

376

378

380

382

384

386

388

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

0.2

0.4

0.6

0.8

1

300

320

340

360

380

400

2 2.5 3 3.5 4

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0102030405060708090

2.00E+05

2.20E+05

2.40E+05

2.60E+05

2.80E+05

3.00E+05

2 2.5 3 3.5 4

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

50

100

150

200

1.70E+05

2.70E+05

3.70E+05

4.70E+05

5.70E+05

6.70E+05

7.70E+05

8.70E+05

9.70E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

0

50

100

150

200

250

300

350

400

450

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

2.50E+05

2.52E+05

2.54E+05

2.56E+05

2.58E+05

2.60E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

0

50

100

150

200

250

300

350

400

450

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

47










0

2

4

6

8

10

12

2.61E+05

2.61E+05

2.61E+05

2.61E+05

2.61E+05

2.61E+05

2.61E+05

2.61E+05

2.62E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

376

378

380

382

384

386

388

390

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

50

100

150

200

250

2.50E+05

2.52E+05

2.54E+05

2.56E+05

2.58E+05

2.60E+05

2.62E+05

2.64E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

150

200

250

300

350

400

450

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0102030405060708090100110120

1.90E+05

2.10E+05

2.30E+05

2.50E+05

2.70E+05

2 2.5 3 3.5 4

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

270

290

310

330

350

370

390

410

2 2.5 3 3.5 4

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

60

120

180

1.70E+05

3.70E+05

5.70E+05

7.70E+05

9.70E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

200

250

300

350

400

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


48










0

2

4

6

8

10

2.78E+05

2.78E+05

2.78E+05

2.78E+05

2.78E+05

2.78E+05

2.78E+05

2.78E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.88

0.9

0.92

0.94

0.96

0.98

1

370

372

374

376

378

380

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

10

20

30

40

50

60

70

80

1.90E+05

2.10E+05

2.30E+05

2.50E+05

2.70E+05

2.90E+05

3.10E+05

3 4 5 6

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

270

290

310

330

350

370

390

3 4 5 6

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

30

60

90

120

1.70E+05

3.70E+05

5.70E+05

7.70E+05

9.70E+05

1.17E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

200

250

300

350

400

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

2.70E+05

2.73E+05

2.76E+05

2.79E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

140

190

240

290

340

390

440

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

49

4.3.1.2 Sensitivity analysis four-parameter of distillation column for

OPT pant with pressure swing adsorption technology



with pressure swing adsorption technology






pressure swing adsorption technology

0

10

20

30

40

2.50E+05

3.00E+05

3.50E+05

4.00E+05

2 3 4 5

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

500

510

520

530

540

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0306090120150180210240270300330

1.60E+05

2.60E+05

3.60E+05

4.60E+05

5.60E+05

6.60E+05

7.60E+05

8.60E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

200

250

300

350

400

450

500

550

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

140

190

240

290

340

390

440

490

540

590

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

50

100

150

200

250

300

2.80E+05

2.83E+05

2.86E+05

2.89E+05

2.92E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

1

2

3

4

5

6

2.90E+05

2.90E+05

2.90E+05

2.90E+05

2.90E+05

2.90E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

0.2

0.4

0.6

0.8

1

525

526

527

528

529

530

531

532

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

50










0102030405060708090

2.20E+05

2.70E+05

3.20E+05

3.70E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

420430440450460470480490500510520

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0306090120150180210240270300330

1.60E+05

2.60E+05

3.60E+05

4.60E+05

5.60E+05

6.60E+05

7.60E+05

8.60E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

200

250

300

350

400

450

500

550

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

300

2.70E+05

2.73E+05

2.76E+05

2.79E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

140

190

240

290

340

390

440

490

540

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

2

4

6

8

10

12

14

2.76E+05

2.76E+05

2.76E+05

2.76E+05

2.76E+05

2.76E+05

2.76E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.82

0.85

0.88

0.91

0.94

0.97

1

496

498

500

502

504

506

508

510

512

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

51










0

2

4

6

8

10

3.01E+05

3.01E+05

3.01E+05

3.01E+05

3.01E+05

3.01E+05

3.01E+05

3.01E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.88

0.91

0.94

0.97

1

483484485486487488489490491492493

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

30

60

90

120

2.00E+05

2.50E+05

3.00E+05

3.50E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

350

370

390

410

430

450

470

490

510

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0306090120150180210240270300330

1.60E+05

3.60E+05

5.60E+05

7.60E+05

9.60E+05

1.16E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

200

250

300

350

400

450

500

550

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

140

190

240

290

340

390

440

490

540

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

50

100

150

200

250

300

2.70E+05

2.80E+05

2.90E+05

3.00E+05

3.10E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

52










0

0.5

1

1.5

2

2.5

2.92E+05

2.92E+05

2.92E+05

2.92E+05

25 27 29 31 33 35

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.91

0.94

0.97

1

478.5

479

479.5

480

480.5

481

25 27 29 31 33 35

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

30

60

90

120

150

180

210

2.00E+05

4.00E+05

6.00E+05

8.00E+05

1.00E+06

1.20E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

200

250

300

350

400

450

500

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

30

60

90

120

150

1.90E+05

2.10E+05

2.30E+05

2.50E+05

2.70E+05

2.90E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

310

330

350

370

390

410

430

450

470

490

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

10

20

30

40

50

60

70

80

2.70E+05

2.80E+05

2.90E+05

3.00E+05

5 7 9 11 13 15

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

140

190

240

290

340

390

440

490

540

5 7 9 11 13 15

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

53


EFB pant with pervaporation technology


Figure 54 Sensitivity number of stages of distillation column for EFB plant with

pervaporation technology

Figure 55 Sensitivity molar reflux ratio of distillation column for EFB plant with


Figure 56 Sensitivity distillation to feed of distillation column for EFB plant with


Figure 57 Sensitivity feed stage of distillation column for EFB plant with


0

1

2

3

4

5

6

7

8

3.25E+05

3.26E+05

3.26E+05

3.27E+05

3.27E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.82

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

466

467

468

469

470

471

472

473

474

475

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

5

10

15

20

25

30

2.80E+05

3.00E+05

3.20E+05

3.40E+05

3.60E+05

3.80E+05

3 3.5 4 4.5 5

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

440

450

460

470

480

3 3.5 4 4.5 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

50

100

150

200

2.00E+05

5.00E+05

8.00E+05

1.10E+06

1.40E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

0

100

200

300

400

500

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

300

3.00E+05

3.05E+05

3.10E+05

3.15E+05

3.20E+05

3.25E+05

3.30E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

0

100

200

300

400

500

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

54


100:0 ratio of EFB and OPT plant with pervaporation technology



and OPT plant with pervaporation technology





Figure 61 Sensitivity feed stage of distillation column for 100:0 ratio of EFB and

OPT plant with pervaporation technology

0

1

2

3

4

5

6

7

8

3.25E+05

3.26E+05

3.26E+05

3.27E+05

3.27E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.82

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

466

467

468

469

470

471

472

473

474

475

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

5

10

15

20

25

30

2.80E+05

3.00E+05

3.20E+05

3.40E+05

3.60E+05

3.80E+05

3 3.5 4 4.5 5

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

440

450

460

470

480

3 3.5 4 4.5 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

50

100

150

200

2.00E+05

5.00E+05

8.00E+05

1.10E+06

1.40E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

0

100

200

300

400

500

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

300

3.00E+05

3.05E+05

3.10E+05

3.15E+05

3.20E+05

3.25E+05

3.30E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

0

100

200

300

400

500

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

55












0

2

4

6

8

10

3.10E+05

3.11E+05

3.12E+05

3.13E+05

3.14E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

448449450451452453454455456457458

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

50

100

150

200

2.00E+05

5.00E+05

8.00E+05

1.10E+06

1.40E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

250

300

350

400

450

500

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

300

3.00E+05

3.05E+05

3.10E+05

3.15E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

180

230

280

330

380

430

480

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

30

60

90

120

2.20E+05

2.50E+05

2.80E+05

3.10E+05

3.40E+05

3.70E+05

2 3 4 5

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

330

350

370

390

410

430

450

470

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

56












0

2

4

6

8

10

2.90E+05

2.93E+05

2.96E+05

2.99E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

423

424

425

426

427

428

429

430

431

432

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

50

100

150

200

2.00E+05

5.00E+05

8.00E+05

1.10E+06

1.40E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

250

300

350

400

450

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

300

2.90E+05

2.93E+05

2.96E+05

2.99E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

180

230

280

330

380

430

480

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

30

60

90

120

2.10E+05

2.40E+05

2.70E+05

3.00E+05

3.30E+05

2 3 4 5

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

300

320

340

360

380

400

420

440

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

57












0

1

2

3

4

5

6

7

8

2.80E+05

2.81E+05

2.81E+05

2.82E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

398

399

400

401

402

403

404

405

406

407

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

020406080100120140160180

1.90E+05

4.90E+05

7.90E+05

1.09E+06

0.01 0.06

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

230

280

330

380

430

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

2.70E+05

2.73E+05

2.76E+05

2.79E+05

2.82E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

170

220

270

320

370

420

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

30

60

90

120

2.00E+05

2.30E+05

2.60E+05

2.90E+05

3.20E+05

2 3 4 5

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

290

310

330

350

370

390

410

430

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

58












0

2

4

6

8

10

2.63E+05

2.64E+05

2.64E+05

2.65E+05

2.65E+05

2.66E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

378

380

382

384

386

388

390

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

20

40

60

80

100

120

140

160

1.80E+05

3.80E+05

5.80E+05

7.80E+05

9.80E+05

1.18E+06

0.01 0.06

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

0.2

0.4

0.6

0.8

1

230

250

270

290

310

330

350

370

390

410

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

50

100

150

200

250

2.50E+05

2.53E+05

2.56E+05

2.59E+05

2.62E+05

2.65E+05

2.68E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

0.2

0.4

0.6

0.8

1

150

200

250

300

350

400

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

30

60

90

120

1.90E+05

2.20E+05

2.50E+05

2.80E+05

3.10E+05

2 3 4 5

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

260

280

300

320

340

360

380

400

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

59


distillate 4 wt% of fermentation broth to 80 wt%


fermentation broth to 80 wt% and dehydrate with pervaporation technology







0.7

0.75

0.8

0.85

0.9

0.95

1

504.5

505

505.5

506

506.5

507

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0.7

0.75

0.8

0.85

0.9

0.95

1

420430440450460470480490500510520

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

190

240

290

340

390

440

490

540

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

140

190

240

290

340

390

440

490

540

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

0.5

1

1.5

2

2.5

3.07E+05

3.07E+05

3.07E+05

3.07E+05

3.07E+05

3.07E+05

3.07E+05

3.07E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

20

40

60

80

2.20E+05

2.50E+05

2.80E+05

3.10E+05

3.40E+05

3.70E+05

4.00E+05

4.30E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

50

100

150

200

250

300

1.60E+05

3.60E+05

5.60E+05

7.60E+05

9.60E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

50

100

150

200

250

3.00E+05

3.03E+05

3.06E+05

3.09E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

60



Figure 82 Sensitivity number of distillation column for distillate 6 wt% of



fermentation broth to 80 wt% and dehydrate with pervaporation technology y





0

0.2

0.4

0.6

0.8

1

735

740

745

750

755

760

765

10 12 14 16 18 20

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

0.2

0.4

0.6

0.8

1

750

755

760

765

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

190

290

390

490

590

690

790

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

140

240

340

440

540

640

740

840

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

5

10

15

20

25

3.35E+05

3.35E+05

3.35E+05

3.35E+05

3.36E+05

3.36E+05

10 12 14 16 18 20

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

0.5

1

1.5

2

2.90E+053.20E+053.50E+053.80E+054.10E+054.40E+054.70E+055.00E+055.30E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

70

140

210

280

350

420

490

560

1.40E+05

3.40E+05

5.40E+05

7.40E+05

9.40E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

50

100

150

200

250

300

350

3.20E+05

3.23E+05

3.26E+05

3.29E+05

3.32E+05

3.35E+05

3.38E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

61











0

0.2

0.4

0.6

0.8

1

860

880

900

920

940

960

980

1000

1020

1040

10 12 14 16 18 20

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

0.2

0.4

0.6

0.8

1

1000

1005

1010

1015

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

200

300

400

500

600

700

800

900

1000

1100

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

500

600

700

800

900

1000

1100

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

20

40

60

80

100

120

140

160

3.63E+05

3.64E+05

3.64E+05

3.65E+05

3.65E+05

3.66E+05

3.66E+05

10 12 14 16 18 20

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

2

4

6

8

10

3.50E+05

4.00E+05

4.50E+05

5.00E+05

5.50E+05

6.00E+05

6.50E+05

7.00E+05

7.50E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

100

200

300

400

500

600

700

800

1.50E+05

3.50E+05

5.50E+05

7.50E+05

9.50E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

50

100

150

200

250

300

350

400

3.60E+05

3.61E+05

3.62E+05

3.63E+05

3.64E+05

3.65E+05

3.66E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

62











0.7

0.75

0.8

0.85

0.9

0.95

1

420430440450460470480490500510520

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

200

250

300

350

400

450

500

550

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

140

190

240

290

340

390

440

490

540

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

1

2

3

4

5

6

7

2.90E+05

2.90E+05

2.90E+05

2.90E+05

2.90E+05

2.90E+05

2.90E+05

15 17 19 21 23 25

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

20

40

60

80

2.20E+05

2.50E+05

2.80E+05

3.10E+05

3.40E+05

3.70E+05

4.00E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

70

140

210

280

1.60E+05

3.60E+05

5.60E+05

7.60E+05

9.60E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

50

100

150

200

250

300

2.80E+05

2.85E+05

2.90E+05

2.95E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0.8

0.85

0.9

0.95

1

504

505

506

507

508

509

510

511

512

15 17 19 21 23 25

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

63











0

10

20

2.90E+05

3.20E+05

3.50E+05

3.80E+05

4.10E+05

4.40E+05

4.70E+05

5.00E+05

5.30E+05

2 3 4 5

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

70

140

210

280

350

420

490

1.60E+05

3.60E+05

5.60E+05

7.60E+05

9.60E+05

1.16E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

50

100

150

200

250

300

350

3.80E+05

3.81E+05

3.82E+05

3.83E+05

3.84E+05

3.85E+05

3.86E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

5

10

15

20

25

3.84E+05

3.85E+05

3.85E+05

3.85E+05

3.85E+05

3.85E+05

3.85E+05

3.85E+05

3.85E+05

10 12 14 16 18 20

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.82

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

730

740

750

760

770

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

200

300

400

500

600

700

800

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

140

240

340

440

540

640

740

840

2 4 6 8 10

Eth

anol

conce

ntr

atio

n

(%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0.82

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

740

745

750

755

760

765

770

10 12 14 16 18 20

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

64


distillate 8wt% of fermentation broth to 85 wt%









0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

1008

1010

1012

1014

1016

1018

1020

1022

10 12 14 16 18 20

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

1000

1005

1010

1015

1020

1025

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

200

300

400

500

600

700

800

900

1000

1100

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

500

600

700

800

900

1000

1100

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

2

4

6

8

10

12

4.76E+05

4.76E+05

4.76E+05

4.76E+05

4.76E+05

10 12 14 16 18 20

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

2

4

6

8

10

3.50E+05

4.00E+05

4.50E+05

5.00E+05

5.50E+05

6.00E+05

6.50E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

100

200

300

400

500

600

700

1.50E+05

3.50E+05

5.50E+05

7.50E+05

9.50E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

50

100

150

200

250

300

350

400

4.70E+05

4.71E+05

4.72E+05

4.73E+05

4.74E+05

4.75E+05

4.76E+05

4.77E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

65



Figure 102 Sensitivity number o of distillation column for distillate 4 wt% of








0.7

0.75

0.8

0.85

0.9

0.95

1

350

370

390

410

430

450

470

490

510

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

190

240

290

340

390

440

490

540

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

140

190

240

290

340

390

440

490

540

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

10

20

30

40

50

3.17E+05

3.17E+05

3.18E+05

3.18E+05

3.18E+05

3.18E+05

3.18E+05

3.18E+05

10 12 14 16 18 20

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

20

40

60

80

100

120

140

2.00E+05

2.30E+05

2.60E+05

2.90E+05

3.20E+05

3.50E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

50

100

150

200

250

300

1.60E+05

3.60E+05

5.60E+05

7.60E+05

9.60E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

50

100

150

200

250

300

3.00E+05

3.03E+05

3.06E+05

3.09E+05

3.12E+05

3.15E+05

3.18E+05

3.21E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0.7

0.75

0.8

0.85

0.9

0.95

1

440

450

460

470

480

490

500

10 12 14 16 18 20

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

66











0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

650

670

690

710

730

750

770

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

190

290

390

490

590

690

790

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


0

0.2

0.4

0.6

0.8

1

140

240

340

440

540

640

740

840

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

10

20

30

40

50

60

70

80

3.91E+05

3.91E+05

3.91E+05

3.92E+05

3.92E+05

10 12 14 16 18 20

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0

10

20

30

40

50

60

70

80

2.60E+05

3.00E+05

3.40E+05

3.80E+05

4.20E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0

70

140

210

280

350

420

490

1.80E+05

3.80E+05

5.80E+05

7.80E+05

9.80E+05

1.18E+06

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

50

100

150

200

250

300

350

400

3.80E+05

3.83E+05

3.86E+05

3.89E+05

3.92E+05

3.95E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

660670680690700710720730740750760

10 12 14 16 18 20

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

67











0

0.2

0.4

0.6

0.8

1

500

600

700

800

900

1000

1100

2 4 6 8 10

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Feed stage

0

100

200

300

400

500

600

700

800

1.50E+05

3.50E+05

5.50E+05

7.50E+05

9.50E+05

0.01 0.03 0.05 0.07 0.09

Eth

ano

l w

aste

(k

g/h

r)

Reb

oil

er d

uty

(ca

l/se

c)


0

100

200

300

400

500

4.40E+05

4.43E+05

4.46E+05

4.49E+05

4.52E+05

2 4 6 8 10

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Feed stage

0

10

20

30

40

50

60

70

80

4.48E+05

4.48E+05

4.48E+05

4.49E+05

4.49E+05

4.49E+05

4.49E+05

4.49E+05

4.50E+05

10 12 14 16 18 20

Eth

anol

was

te (

kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Number of stage

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

910

920

930

940

950

960

970

980

990

1000

10 12 14 16 18 20

Eth

anol

conce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Number of stage

0

5

10

15

20

25

30

35

3.20E+05

3.70E+05

4.20E+05

4.70E+05

5.20E+05

5.70E+05

2 3 4 5

Eth

ano

l w

aste

(kg/h

r)

Reb

oil

er d

uty

(ca

l/se

c)

Molar reflux ratio

0.88

0.9

0.92

0.94

0.96

0.98

1

950955960965970975980985990995

1000

2 3 4 5

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)

Molar reflux ratio

0

0.2

0.4

0.6

0.8

1

200

300

400

500

600

700

800

900

1000

1100

0.01 0.03 0.05 0.07 0.09

Eth

ano

l co

nce

ntr

atio

n (

%w

t)

Mas

s fl

ow

of

ethan

ol

(kg/h

r)


68

4.3.2. Dehydration with Pervaporation

The energy consumption and recovery efficiency were

calculated from eq 7. and 13. respectively with a width range of separation factor 50

to 1000 of hydrophilic membrane and plotted graph to show the relation of septation

factor (dotted line) and ethanol concentration in feed (solid line) to recovery

efficiency and energy demand as shown in Figure 114. This graph demonstrated that

higher concentration in feed and high separation factor significantly reduce energy

demand to purify with high recovery efficiency. Moreover, it shows that the

separation factor of more than 300 provided a high percent recovery of almost 100%

of the maximum ethanol concentration in feed (95 wt%) and about 99 % of percent

recovery for 85 and 90 wt%. But membrane with very high separation factor is

unavailable in the commercial. Therefore, the membrane with separation factor lower

than 300 was studied and applied in this work. The ethanol concentration before

feeding to pervaporation model was selected to 50, 80, 85, and 90 wt%.

Figure 114 Relationship of energy demand in dotted line and recovery efficiency in a

solid line with various separation factor and difference inlet concentration applying

the hydrophilic membrane

Four different membrane types, PVA/PAA, PVA, 6FDA-

NDA/DABA, Polyimide (BMTCHDA) from Lee et al., (1995), Li et al., (2006), Le et

al., (2014), and Kim et al., (2000) were selected to dehydrated 50, 80, 85, 90 wt%

ethanol to fuel grade, respectively. The separation factor and permeate rate of each

membrane as shown in Table 12 was applied to calculate the energy demand in

dehydration and membrane area. Figure 115 presents the scheme for the purification

section. As the amount of ethanol loss in the waste stream from the distillation

column was less than 1 kg/hr. Therefore, we can assume that there is an equal

quantity of ethanol in the overhead stream was fed to the dehydration process. The

temperature was increased to 80 oC before passing through the membrane as

suggested in Nagy et al., (2015). The permeate stream from PV model was condensed

and recovered to a distillation column to minimize the ethanol loss.

0.82

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

00.20.40.60.8

11.21.41.61.8

22.22.42.62.8

3

50 200 350 500 650 800 950

reco

ver

y e

ffic

iency

(%

)

The

Ener

gy d

eman

d (

MJ/

kgE

t)

Separation factor

50

60

70

80

85

90

95

50

60

70

80

85

90

95

69

Figure 115 Flowsheet for the distillation and dehydration process using PV method


for OPT plant

Ethanol concentration

in an overhead stream (%)

50 80 85 90

Optimized parameters

of distillation column

Number of stages 10 22 22 22

Feed stage 2 5 6 7

Reflux ratio 3.44 3.22 3.89 5.22

Distillation to feed 0.047 0.02 0.0178 0.0155

Membrane parameter

Type of membrane PVA/PAA PVA 6FDA-NDA/DABA BMTCHDA

Energy demand (MJ/kg eth) 1181.56 226.87 163.09 92.67

Permeate flux (kg/m2.hr) 2.8 1.5 2.7 1.7

Area (m2) 169.64 67.76 28.35 24.84

Table 12 shows the optimized parameters of the distillation

column to produce the purposed overhead product and parameter of the selected

membrane for each case. Different types of membranes were matched for each

concentration. The efficiency to purify relies on not only overhead products but also

the performance of the membrane. High permeated rate and selectivity of the

membrane have more influential to the performance of the membrane, noticeable

from the amount of ethanol loss in the permeated stream and ethanol yield in the

retentate stream. A high separation factor leads to high ethanol recovery efficiency in

the retentate side and low energy consumption to separate. While permeate flux

directly affects the membrane area which mainly causes the investment costs of the

PV model. The distillation column and membrane were integrated and considered as

single technology for purification. In this section, the sensitivity and optimized four-

parameters of distillation were analyzed to obtain the minimum production cost.

70

4.3.3. Dehydration with Pressure swing adsorption

In this section, the cyclic operation of PSA was performed by

Aspen Adsorption V8.8 software as shown in Figure 116. The model is developed

from the original EthanolDehyd in the program by applying Extend Langmuire1

isotherm. The final product was used to purge in the depressurizing step. Therefore,

waste in depressurizes step contained the amount of ethanol. Waste stream needs to

recover to obtain high production efficiency and minimize ethanol loss. The data of

the overhead stream was transferred from Aspen plus to Aspen Adsorption software

to simulate the trapping water in two columns. These columns contained molecular

sieve namely Zeolite 3A. Figure 117 presents the scheme for the purification section

by using two-column to allows the continuous production of high ethanol yield. The

related parameters to simulate and evaluate the costs were presented in Table 13. The

adsorption stage took about 450 seconds for the production stage and purge out 20-

30% of the product at 1.2 bar from the top. The desorption stage operated after the

adsorption stage completed under pressure 0.2 bar. The recovery efficiency of PSA in

the range of 70-78%. Higher ethanol concentration obtained higher percent ethanol

recovery and high purity in the final product. The result from Aspen adsorption was

performed to Aspen plus software to simulate the PSA performance as shown in

Figure 119 to complete the bioethanol production process and evaluate the economics

of this plant.

Figure 116 Flowsheet of pressure swing adsorption in Aspen Adsorption software

71

Figure 117 Flowsheet for the distillation and dehydration process using PSA method

Table 13 Configuration of the combination of distillation and pressure swing

adsorption model for OPT plant



80 85 90 94



Number of stages 22 22 22 30

Feed stage 5 6 7 14

Reflux ratio 2.67 3 4.44 4.83

Distillation to feed 0.0272 0.0235 0.02 0.0179

Adsorb/Desorb column parameter

Adsorbent porosity 0.21

Bed void fraction 0.37

Pressure (bar) 0.2 – 1.2

Bulk density (kg/m3) 750

Particle radius (mm) 2

Dimension of adsorbent(m) 3.5

Height of adsorbent (m) 1.5

Amount of absorbent (kg) 12061

According to, the 85 wt% of the overhead product dehydrated

with pervaporation technology has the lowest production as present in the economic

section. It was considered as the best candidate for purification technology.

Distillation to 85 wt% in the overhead stream and dehydrate with pervaporation was

the best way to purify because of the lowest production cost per unit. This technology

was employed for the other plants because of similar ethanol concentration about 3

wt% in the fermentation broth. The configuration of EFB plant and two feedstock

plants was shown in Tables 14 and 15.

72


for EFB plant

Ethanol concentration in an overhead stream (%) 85



Number of stages 20

Feed stage 6

Reflux ratio 4.1

Distillation to feed 0.0186

Membrane parameter

Type of membrane 6FDA-NDA/DABA

Energy demand (MJ/kg eth) 209.26

Permeate flux (kg/m2.hr) 2.7

Area (m2) 36.21


for the two feedstocks plant

EFB:OPT ratio 100:0 80:20 50:50 20:80 0:100



Number of stages 20 20 20 20 21

Feed stage 6 6 6 6 6

Reflux ratio 4.1 4.1 4.1 4.1 4

Distillation to feed 0.0186 0.0183 0.0182 0.0181 0.0178

Membrane parameter


Energy demand (MJ/kg eth) 209.26 194.79 185.63 176.42 163.13

Permeate flux (kg/m2.hr) 2.7 2.7 2.7 2.7 2.7

Area (m2) 36.21 33.80 32.19 30.57 28.35

In the sensitivity section, the ethanol concentration in the

fermentation broth was increased to study the effect of various ethanol concentrations

on production cost. The various ethanol concentration in the fermentation broth was

assumed to 4, 6, 8 wt% and distilled to 80, 85, 90 wt% to find out the suitable ethanol

concentration in the overhead stream. Then best candidate for the dehydration section,

the pervaporation technology, was employe to increase ethanol concentration to 99.5

wt%.

Tables 16 to 18 display the optimized distillation and

membrane parameters for various ethanol concentrations in the fermentation broth

distilled to 80, 85, 90 wt% for OPT plant. These parameters will be applied in the

sensitivity analysis section to explain the relationship between concentration in feed

and production cost.

73

Table 16 Configuration of the combination of distillation and pervaporation model

for distillate various ethanol concentrations in fermentation broth to 80 wt% for OPT


of fermentation broth

4 6 8



Number of stages 18 17 15

Feed stage 4 4 4

Reflux ratio 3.2

2.2 1.7

Distillation to feed 0.0265 0.04 0.054

Membrane parameter


Energy demand (MJ/kg eth) 303.65 454.17 614.32

Permeate flux (kg/m2.hr) 1.5 1.5 1.5

Area (m2) 79.93 119.57 183.15





4 6 8




Feed stage 6 6 6

Reflux ratio 3.33 3.32 3.31


Membrane parameter




Area (m2) 38.86 58.22 75.59

74





4 6 8




Feed stage 7 8 8

Reflux ratio 4.8 4.2 3.65


Membrane parameter




Area (m2) 33.17 48.99 67.18

75

Fig

ure

118 T

he

sim

ula

tion m

od

el o

f bio

ethanol

pro

duct

ion f

rom

OP

T b

y usi

ng A

spen

plu

s w

ith d

isti

llati

on a

nd p

erva

pora

tion t

echnolo

gy

SE

HO

TW

AT

ER

HY

DR

OG

EN

NE

UT

RA

LM

IXT

AN

KS

SF

CE

NT

RIF

2

ST

OR

AG

E

SEP

2

ME

MB

RA

NE

CO

LUM

N

AU

TO

CL

AV

MIX

ER

PU

MP

11

HX

1

CO

OLE

R1

PU

MP

12

PU

MP

2P

UM

P3

PU

MP

5P

UM

P6

PU

MP

8

PU

MP

9

PU

MP

4

CE

NT

RIF

U

PU

MP

10

PU

MP

1

PU

MP

7O

PT

WA

TE

R1

H2

O2

WA

TE

R2

NA

OH

WA

TE

R3

UR

EA

AM

MO

NIU

M

WA

TE

R4

YE

AS

T

CT

EC

2

SO

LID

WA

S

ST

EA

M

PE

RM

EA

TE

PR

OD

UC

T

WA

ST

EC

OL

INS

SF

INA

UT

OC

LIN

MIX

ER

INC

OLU

MN

RE

CY

CL

E

INP

UM

P3

INP

UM

P5

INP

UM

P6

INP

UM

P8

S1

7IN

PU

MP

10

INP

UM

P7

S2

76

Fig

ure

119 T

he

sim

ula

tion m

od

el o

f bio

ethanol

pro

duct

ion f

rom

OP

T b

y usi

ng A

spen

plu

s w

ith d

isti

llati

on a

nd p

ress

ure

sw

ing

adso

rpti

on t

echnolo

gy

SE

HO

TW

AT

ER

HY

DR

OG

EN

NE

UT

RA

LM

IXT

AN

KS

SF

CE

NT

RIF

2

ST

OR

AG

E

AU

TO

CLA

VP

UM

P2

PU

MP

3P

UM

P5

PU

MP

6P

UM

P8

PU

MP

9

PU

MP

4

CE

NT

RIF

U

PU

MP

10

DE

SO

RB

AD

SO

RB

CO

LU

MN

OP

T

WA

TE

R1

H2

O2

WA

TE

R2

NA

OH

WA

TE

R3

UR

EA

AM

MO

NIU

M

WA

TE

R4

YE

AS

T

CT

EC

2

SO

LID

WA

S

ST

EA

M

INS

SF

INA

UT

OC

LIN

MIX

ER

INP

UM

P2

INP

UM

P3

INP

UM

P5

INP

UM

P6

INP

UM

P8

INP

UM

P9

INP

UM

P4

S1

7IN

PU

MP

10

RE

CY

CLE

S8

ET

H99

PR

OD

UC

T

S1

1S

1S

19

S3

WA

ST

E

77

Fig

ure

120 T

he

sim

ula

tion m

od

el o

f bio

ethanol

pro

duct

ion f

rom

EF

B b

y usi

ng A

spen

plu

s w

ith d

isti

llati

on a

nd p

erva

pora

tion t

echnolo

gy

HC

WH

OT

WA

TE

R

HY

DR

OG

EN

NE

UT

RA

LM

IXT

AN

KS

SF

CE

NT

RIF

2

ST

OR

AG

E

SEP

2

ME

MB

RA

NE

CO

LUM

N

AU

TO

CL

AV

MIX

ER

PU

MP

11

HX

1

CO

OLE

R1

PU

MP

12

PU

MP

2P

UM

P3

PU

MP

5P

UM

P6

PU

MP

8

PU

MP

9

PU

MP

4

CE

NT

RIF

U

PU

MP

10

PU

MP

1

PU

MP

7E

FB

WA

TE

R1

H2

O2

WA

TE

R2

NA

OH

WA

TE

R3

UR

EA

AM

MO

NIU

M

WA

TE

R4

YE

AS

T

CT

EC

2

SO

LID

WA

S

WA

TE

R

PE

RM

EA

TE

PR

OD

UC

T

WA

ST

EC

OL

INS

SF

INA

UT

OC

LIN

MIX

ER

INC

OLU

MN

RE

CY

CL

E

INP

UM

P3

INP

UM

P5

INP

UM

P6

INP

UM

P8

S1

7IN

PU

MP

10IN

PU

MP

7

78

Fig

ure

121 T

he

sim

ula

tion m

od

el o

f bio

ethanol

pro

duct

ion f

rom

tw

o f

eedst

ock

s by

usi

ng A

spen

plu

s w

ith d

isti

llati

on a

nd p

erva

pora

tion

tech

nolo

gy

SE

HO

TWA

TER

HY

DR

OG

EN

NE

UTR

AL

ME

DIA

SS

FS

TOR

AG

E

SE

P2

PE

RV

AP

OR

CO

LUM

N

AU

TOC

LA

VC

EN

TRIF

U

CE

NTR

IF2

WA

TER

2

H2O

2

WA

TER

3

NA

OH

WA

TER

4

PE

PT

ON

E

BU

FF

ER

YE

AS

T

CTE

C2

PR

OD

UC

T

OP

TEF

B

S10

RE

CY

CLE

B1

S2

HC

W

STE

AM

WA

TER

1

S7

79

5. Economic analysis

The preliminary economic evaluation of a project for production plant usually

associates with the estimation of capital investment, operating costs, and analysis of

profitability. The economic evaluation was performed in order to determine the

feasibility of each project. When the parameter and assumptions to calculate regarding

Table 7. The economic results of three bioethanol production plants were presented in

Table 19 to 27. The simulation model of bioethanol production in the Aspen Plus

software was transferred to the Aspen Process Economic Analyzer program to

calculate the utility costs and some equipment price. The economic result and

production cost per unit are helpful information for project decisions.

5.1. OPT plant

The distribution capital costs and operating costs of 4 cases for PV and

PSA were presented in Tables 19 and 20 respectively. The calculation of total capital

investment (TCI) found that plants dehydrated with pervaporation (PV) use less of

total capital investment (TCI) compared with pressure swing absorption (PSA). As a

result of higher equipment purchasing cost of PSA cause higher investment costs. The

total capital cost for OPT plants is in the range of 22x106$ to 24x106$. The equipment

purchasing costs affected the total capital cost significantly because the various

elements of total capital cost are estimated based on the total equipment purchase

costs (PC) by using several multipliers as shown in the economic assessment section.

The graph for the comparison of the total capital cost of 4 cases showed in Figure

122. Detailed definitions of the main equipment can be found in Appendix Table A1

to A3. The operating costs to run a bioethanol plant are the sum of all expenses

including raw materials, labor, chemical substance, plant overhead, G and A

expenses, utilities, maintenance, miscellaneous, membrane/molecular sieve

replacement. Figure 124 illustrated that utility cost is the highest element, accounted

for 32%, contributed to operating cost. The bioethanol plant with PSA technology

consumes higher utility costs to produce high purity of ethanol. Therefore, the

operating costs of PSA higher than PV for all cases, except case 1 because case 1 of

OPT plant with PV had more amount of mass flow in the overhead stream. The mass

flow in the overhead stream directly impacts to energy demand in distillation and

dehydration. The graph for the comparison of the operating costs of 4 cases showed in

Figure 123. From these results, we can state that the bioethanol plant with

pervaporation seems to dominate dehydration because of lower production cost in all

cases compared with pressure swing absorption. Moreover, the result demonstrated

that increasing dilute ethanol to 85 wt% in the overhead stream before dehydrating

with PV and PSA have more economically effective. The pervaporation technology

was the best candidate for dehydration technology because of the lowest production

cost per unit. So, we can conclude that distillate dilute ethanol to 85 wt% before

feeding to Polyimide (BMTCHDA) membrane to dehydrate and produce 99.5wt% of

ethanol is the best way for purification.

However, these projects required large investment costs to produce a small

capacity plant that can produce the final product only 10,000 L/day. It resulted in

80

NPV of all cases was a negative value. It means this project is not suitable for

investment. Table 21 provides a summary of the economic result for the OPT plant.

Tables A12 to A27 in Appendix show the annual cash flow and the net present value

of the OPT plant.

81

Tab

le 1

9 T

he

com

ponen

t of

tota

l ca

pit

al c

ost

for

the

OP

T p

lant

P

V

PS

A

Eth

an

ol

con

cen

trati

on

in o

ver

hea

d s

trea

m (

%)

50

80

85

90

80

85

90

94

Equip

men

t purc

has

e co

st

4224522

4248147

4240364

42399

63

4464556

4463356

4464756

4496856

Inst

alla

tion

2112261

2124074

2120182

21199

81

2232278

2231678

2232378

2248428

Pro

cess

pip

ing

1689809

1699259

1696146

16959

85

1785822

1785342

1785902

1798742

Inst

rum

enta

tion

1478583

1486852

1484128

14839

87

1562595

1562175

1562665

1573900

Insu

lati

on

126736

127444

127211

12719

9

133937

133901

133943

134906

Ele

ctri

cal

633678

637222

636055

63599

4

669683

669503

669713

674528

Buil

din

gs

1901035

1911666

1908164

19079

83

2009050

2008510

2009140

2023585

Lan

d

168981

169926

169615

16959

9

178582

178534

178590

179874

Tota

l p

lan

t d

irec

t co

st (

TP

DC

) 12335605

12404590

12381864

12380

691

13036503

13032999

13037087

13130819

Engin

eeri

ng

3083901

3101148

3095466

30951

73

3259126

3258250

3259272

3282705

Con

stru

ctio

n

4317462

4341607

4333652

43332

42

4562776

4561550

4562980

4595787

Tota

l p

lan

t in

dir

ect

cost

(T

PIC

)

7401363

7442754

7429118

74284

14

7821902

7819799

7822252

7878491

Tota

l p

lan

t co

st (

TP

C)

19736968

19847344

19810983

19809

105

20858405

20852798

20859339

21009310

Con

trac

tor’

s fe

e 986848

992367

990549

99045

5

1042920

1042640

1042967

1050466

Con

tingen

cy

1973697

1984734

1981098

19809

11

2085840

2085280

2085934

2100931

Tota

l ca

pit

al

cost

22697513

22824446

22782630

22780

471

23987165

23980718

23988240

24160707

82

Tab

le 2

0 T

he

com

ponen

t of

tota

l oper

atin

g c

ost

fo

r th

e O

PT

pla

nt

P

V

PS

A

50

80

85

90

80

85

90

94

Raw

mat

eria

ls

14162

14162

14162

14162

14162

14162

14162

14162

Lab

or

259200

259200

259200

259200

259200

259200

259200

259200

Chem

ical

subst

ance

456183

456183

456183

456183

456183

456183

456183

456183

Pla

nt

over

hea

d

159852

160383

160208

160199

165253

165226

165257

165979

G a

nd A

Expen

ses

31970

32077

32042

32040

33051

33045

33051

33196

Uti

liti

es

646549

585139

585877

589463

617726

612499

616496

613218

Mai

nte

nan

ce

380207

382333

381633

381597

401810

401702

401828

404717

Mis

cell

aneo

us

1000

1000

1000

1000

1000

1000

1000

1000

Tota

l op

erati

ng c

ost

1949123

1890477

1890305

1893844

1948385

1943016

1947177

1947655

Tab

le 2

1 E

conom

ic r

esult

for

OP

T p

lant

P

V

PS

A

50

80

85

90

80

85

90

94

NP

V (

$)

-11,8

13,9

44

-11,2

95,4

41

-1

1,2

47,8

48

-11,2

75,5

04

-1

2,9

18,5

08

-12,8

90,9

11

-12,9

10,6

45

-1

4,0

39,9

17

IRR

(%

) -0

.08%

0.2

4%

0.2

5%

0.2

3%

-0

.31%

-0

.30%

-0

.31%

-0

.99%

PB

(yea

r)

N/A

N

/A

N/A

N

/A

N/A

N

/A

N/A

N

/A

Pro

duct

ion

cost

per

unit

($/u

nit

)

0.8

99

0.8

8355

0.8

831

0.8

84

0.9

190

0.9

184

0.9

1879

0.9

209

83

Figure 122 Comparison of the total capital cost of 4 cases

Figure 123 Comparison of operating costs of 4 cases

Figure 124 Distribution element of operating costs for OPT plant with 85 wt% in the

overhead stream before dehydrating with PV and PSA

2.2E+07

2.2E+07

2.3E+07

2.3E+07

2.4E+07

2.4E+07

2.5E+07

case 1 case 2 case 3 case 4

To

tal

ca

pit

al

cost

($

)

PV

PSA

1.80E+06

1.84E+06

1.88E+06

1.92E+06

1.96E+06

2.00E+06

case 1 case 2 case 3 case 4

To

tal

op

erat

ing c

ost

($

/yea

r) PV

PSA

1%

13-14%

23%

8%

2%

31-32%

21%

0%

Raw Materials

Labor

Chamical supstance

Plant Overhead

G and A Expenses

Utilities

maintenance

Miscellaneous

84

Figure 125 Distribution chemical costs for OPT plant

As a result of the highest portion of operating costs is utility costs account for

32 % and chemical costs account for 23 % of total operating cost. In this work, the

best candidate plant, OPT plant with PV technology, will be studied the sensitivity of

the highest element contributed to the chemical costs. Figure 125 shows the highest

element contributed to chemical costs was enzyme Ctec2, accounted for 47%. The

additional information about the raw material and chemical costs of OPT plant can be

found in Appendix Table A7.

5.2. EFB plant

The best way to purification of OPT plant was employed to other

plants. Tables 22 to 24 provide the economic results of EFB plant with PV

technology. The dilute ethanol in the fermentation broth was increased to 85 wt% by

the Radfrac column and remove the water in an overhead stream by PV technology to

achieve 99.5 wt% of ethanol.

Table 22 The component of total capital cost for EFB plant



85

Equipment purchase cost 5503432

Installation 2751716

Process piping 2201373

Instrumentation 1926201

Insulation 165103

Electrical 825515

Buildings 2476544

Land 220137

Total plant direct cost (TPDC) 16070020

Engineering 4017505

Construction 5624507

47%

3%

25%

2%

15%

0%8%

CTec2

H2O2

Ammonium sulfate

S. cerevisiae

Urea

NaOH

Water

85

Total plant indirect cost (TPIC) 9642012

Total plant cost (TPC) 25712033

Contractor’s fee 1285602

Contingency 2571203

Total capital cost 29568837

Table 23 The component of total operating cost for EFB plant


in the overhead stream (%)

85

Raw materials 22129

Labor 259200

Chemical substance 536537

Plant overhead 188627

G and A Expenses 37725

Utilities 707048

Maintenance 495309

Miscellaneous 1000

Total operating cost 2247574

Table 24 Economic result for EFB plant


in the overhead stream (%)

85

NPV ($) -14,762,153

IRR (%) 0.18%

PB (year) N/A

Production cost per unit ($/unit) 0.892

For EFB plant, it had a high potential to produce bioethanol because of the

highest ethanol yield compared with OPT as shown in Table 9. OPT had more lignin

fraction and caused less efficiency in ethanol conversion. Therefore, EFB plant can

produce more products and obtain higher incomes. But there is the main disadvantage

of EFB plant that is it must operate under high pressure (30 bar) in the first

pretreatment process. It results in the requirement of high equipment purchasing costs

for the high-pressure agitated vessel in a hot compress water process (HCW). The

total equipment costs of EFB plant are 30 % more than OPT plant. Even though

higher annual income but EFB plant had a higher production cost compare with OPT

plant. The Net Present Value (NPV) of EFB plant is negative, meaning not suitable

for investment. The detailed definitions of the main equipment, additional information

on raw material and chemical costs, and annual cash flow and net present value of

EFB plant can be found in Appendix, Tables A4, A8, and A27 to A28.

86

5.3. Two feedstocks plant

The distribution of capital costs, operating costs and economic results

of various ratios of two feedstocks plants were present in Tables 25 to 27.

Table 25 The component of total capital cost for two feedstocks plant

EFB:OPT ratio 100:0 80:20 50:50 20:80 0:100

Equipment purchase cost 5553432 5552726 5536729 5536096 5555868

Installation 2776716 2776363 2768364 2768048 2777934

Process piping 2221373 2221090 2214692 2214439 2222347

Instrumentation 1943701 1943454 1937855 1937634 1944554

Insulation 166603 166582 166102 166083 166676

Electrical 833015 832909 830509 830414 833380

Buildings 2499044 2498727 2491528 2491243 2500141

Land 222137 222109 221469 221444 222235

Total plant

direct cost

(TPDC)

16216020 16213959 16167248 16165401 16223134

Engineering 4054005 4053490 4041812 4041350 4055783

Construction 5675607 5674886 5658537 5657890 5678097

Total plant

indirect cost

(TPIC)

9729612 9728376 9700349 9699241 9733880

Total plant

cost (TPC)

25945633 25942335 25867597 25864642 25957014

Contractor’s fee 1297282 1297117 1293380 1293232 1297851

Contingency 2594563 2594233 2586760 2586464 2595701

Total capital cost 29837477 29833685 29747737 29744338 29850566

Table 26 The component of total operating cost for two feedstocks plant

EFB:OPT ratio 100:0 80:20 50:50 20:80 0:100

Raw materials 22129 20535 18146 15756 14162

Labor 259200 259200 259200 259200 259200

Chemical substance 536537 521454 497393 471975 454346

Plant overhead 189752 189736 189376 189362 189807

G and A Expenses 37950 37947 37875 37872 37961

Utilities 707048 706751 674441 640704 602530

Maintenance 499809 499745 498306 498249 500028

Miscellaneous 1000 1000 1000 1000 1000

Total operating cost 2253424 2236370 2175737 2114118 2059035

87

Table 27 Economic result for two feedstocks plant

EFB:OPT

ratio

100:0 80:20 50:50 20:80 0:100

NPV ($) -15,038,365 -16,080,237 -17,072,550 -18,267,834 -19,053,929

IRR (%) 0.12% -0.32% -0.77% -1.29% -1.61%

PB (year) N/A N/A N/A N/A N/A

Production

Cost per

unit ($/unit)

0.897 0.926 0.960 1.004 1.036

For two feedstocks plant, the main unit operations were designed to cover the

maximal capacity, 100:0 of EFB:OPT. So, the equipment purchasing costs of all

ratios were approximately the same except for the equipment in the purification

process. SSF process produces different ethanol yield. The fermentation broth

released from the SSF units in each ratio of two feedstocks had different ethanol

yield, therefore the purification process had to operate under different conditions to

produce the same quality of the final product. The two feedstocks plant had the

highest equipment purchasing costs compared with OPT and EFB plant because of

two technologies in the first pretreatment process. The total capital cost of all ratio

was approximately the same. While a high EFB ratio provides high operating costs

because of higher mass flow in the process. The highest ethanol yield was produced

from the production plant with EFB:OPT equal to 100:0 yielding the lowest

production cost per unit. Meanwhile, the production plant with EFB:OPT equal to

0:100 produced the lowest ethanol yield contributing to the highest production cost

per unit compared with other plants. The result indicated that the Net Present Value

(NPV) of all ratios of two feedstocks plant was negative. The detailed definitions of

the main equipment, additional information on raw material and chemical costs, and

annual cash flow and net present value of EFB plant can be found in Appendix,

Tables A5, A6 to A11, and A30 to A39.

6. Sensitivity

In the last section, sensitivity analysis has studied the effect of two variables

on production cost for the best candidate of OPT plant with PV method. As

considered in the operation portion, Figure 125 shows that enzyme Ctec2 was the

main factor contributed to the total chemical costs. So, the various Ctec2 price

including 0.53, 0.45, 0.37, 0.29, 0.21, 0.13 $ was studied. The result indicated that

decreasing Ctec2 price by 70% provides a lower 7.4% of production cost per unit as

shown in Table 28.

Table 28 Economic result for various Ctec2 price Ctec2 price

($/kg)

0.53 0.45 0.37 0.29 0.21 0.13

NPV ($) -

11,247,9

21

-

10,943,6

86

-

10,639,4

50

-

10,335,2

15

-

10,030,9

80

-

9,726,7

45

88

IRR (%) 0.25 0.41 0.57 0.73 0.89 1.05

PB (year) N/A N/A N/A N/A N/A N/A

Production

Cost per

unit ($/unit)

0.8831

0.8736

0.8641

0.8546

0.8452

0.8357

Moreover, the ethanol concentration released from SSF strongly influenced to

the purification section. The various ethanol concentration in fermentation broth has

studied the effect on production cost. In this section, the bioethanol concentration was

varied between 4 to 8 wt%. The same amount of feedstock, 47,208 kg/day, was fed

into the process to produce various ethanol concentrations in the SSF process.

Moreover, the various ethanol concentration in the overhead stream has studied to

determine the proper concentration for each ethanol concentration in the fermentation

broth. The various ethanol concentration was distilled to 80, 85, 90 wt% before

feeding to PV model. The parameter for various ethanol concentration plants was

shown in Table 18. The economic result of various ethanol concentrations was

presented in Tables 29 to 31. These results demonstrated that a higher concentration

can be purified with a lower number of stages. Therefore, capital costs and operating

costs consistently decreased. For 4 to 8 wt%, distillates to 85 wt% provide the lowest

production cost per unit with the highest NPV. It requited the lowest total capital and

operating cost compared with 80 and 90 wt%. The 6 and 8 wt% had a positive value

of NPV. Therefore, we can conclude that the high concentration in the fermentation

broth is preferable to minimize production cost for bioethanol plants. The annual cash

flow and the net present value of sensitivity analysis were shown in the Appendix,

Tables A40 to A57.

Table 29 Economic result for distillation 4, 6, 8 wt% to 80 wt%

Ethanol concentration (wt%) 4 6 8

NPV ($) -2,868,446 14,638,350 31,936,117

IRR (%) 4.45% 11.93% 18.48%

PB (year) 16.66 9.97 5.45

Production

Cost per

unit ($/unit)

0.6743 0.45241 0.34210



NPV ($) -2,825,501 14,733,890 32,231,073

IRR (%) 4.47% 11.99% 18.65%

PB (year) 15.29 8.01 5.4

Production

Cost per

unit ($/unit)

0.6739 0.4523 0.3420

89



NPV ($) -2,942,067 14,674,717 32,223,988

IRR (%) 4.42% 11.95% 18.64%

PB (year) 15.38 8.01 5.41

Production

Cost per

unit ($/unit)

0.6762 0.4530 0.3417

7. Conclusion

This study evaluated the economic feasibility of bioethanol production from

OPT, EFB, and various ratios of two feedstocks to produce 99.5 wt% of ethanol,

10000 L/day. The specified first pretreatment technology was employed for each

feedstock to produce the highest ethanol yield. The Hot compressor water (HCW),

Steam explosion (SE) were used to destroy feedstock’s structure, then hot water

washing, and hydrogen peroxide digestion process were used to increase cellulose

fraction for both feedstocks before feeding to simultaneous saccharification

fermentation (SSF) process. SSF was considered as the conversion process to produce

ethanol about 3 wt%. The dilute ethanol must be raised purity by purification. In

purification, PV and PSA were performed to increase 3 wt% of ethanol to fuel grade,

99.5 wt%. The mass balance throughout the bioethanol production plant was

calculated by developing the mass flow sheet in Microsoft excel 2016. The economic

evaluation was performed by Aspen Process Economic Analyzer and Microsoft excel

2016 to evaluate the price of some equipment, utility of the plant, and evaluated the

economic result. The economic result including NPV, IRR, PB, production cost per

unit was selected as the indicator for an investment decision. The sensitivity analysis

of various ethanol concentrations in the fermentation broth was studied.

The result showed that large investment costs were required to produce a small

capacity of bioethanol products, resulting in high production cost per unit, and NPV is

negative. Even though EFB can produce higher ethanol yield but the HCW, the first

pretreatment step, required the expensive equipment. It causes higher investment costs

and production cost per unit. Therefore, OPT plant pretreated with SE is promising

bioethanol production plant to produce bioethanol with lower production cost. The

economic analyst demonstrated that the best candidate for OPT plant with

pervaporation (PV) technology needs the total capital investment (TCI) equal to

22,782,630 $ and total operating cost equal to 1,890,305 $ with 0.8831 $/unit of

production cost per unit. While the best candidate for OPT plant with pressure swing

adsorption technology needs the total capital investment (TCI) equal to 23,980,718 $

and total operating cost equal to 1,943,016 $ with 0.9184 $/unit of production cost per

unit. EFB plant needs the total capital investment equal to 29,568,837 $ and total

operating costs equal to 2,247,474 $ with 0.892 $/unit of production cost per unit.

And the highest ethanol yield from two feedstocks, 100:0 of EFB:OPT needs the total

capital investment (TCI) equal to 29,837,477 $ and total operating cost equal to

2,253,424 $ with 0.897 $/unit of production cost per unit. This result confirms that all

projects are not feasible and nonprofitable because of net present worth is negative,

90

the internal rate of return is lower than the interest rate. Therefore, the bioethanol

plants were not recommended to develop. The sensitivity analysis suggested that the

NPV became positive when ethanol concentration in the fermentation broth was

increased higher than 6 wt% by remaining the same amount of input and conditions to

produce bioethanol.

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APPENDICES

95

Table A1 List of main equipment for OPT plant

Model Type of equipment Unit Volume

(m3)

Price

per

unit

(USD)

Total

price

(USD)

Crusher Woodchipper machine 1 - 13000 13000

SE HP jacketed tank 1 3 50000 50000

Hot water Agitated vessel jacket 1 10 40000 40000

H2O2 Agitated vessel jacket 1 12 48000 48000

Neutralize Agitated vessel jacket 1 14 56000 56000

Centrifuge Horizontal Spiral

Centrifuge

2 - 15,400 30800

Media tank Agitated vessel 1 6 24000 24000

Storage tank Vertical vessel 1 50 20000

0

200000

SSF tank Agitated vessel jacket 16 50 20000

0

320000

0

Dilute tank Agitated vessel 1 3 12000 12000

Yeast cultivation

tank

Agitated vessel 16 5 20000 320000

Yeast cultivation

tank

Agitated vessel 16 0.5 2000 32000

Yeast cultivation

tank


Yeast cultivation

tank

Small vessel 16 0.005 20 320

Table A2 List of equipment cost in pervaporation technology for OPT plant

Model Unit Case 1 Case 2 Case 3 Case 4

Distillation column 1 133200 178900 179000 179900

Membrane 1 33927 13552 5669 4968

Cooler 1 1 10400 8700 8700 8100

Hx 1 1 8100 8100 8100 8100

Vacuum pump 1 2500 2500 2500 2500

Pump 2 2000 2000 2000 2000

Screw pump 7 5075 5075 5075 5075

Table A3 List of equipment cost in pressure swing adsorption technology for OPT

plant

Model Unit Case 1 Case 2 Case 3 Case 4

Distillation column 1 179900 179800 181300 225700

Adsorb column 1 100000 100000 100000 100000

Desorb column 1 100000 100000 100000 100000

Zeolite 3A 2 12061 12061 12061 12061

Cooler 1 1 8700 8700 8700 8600

96

Cooler 2 1 8900 8800 8700 8700

Cooler 3 1 8700 8700 8700 8600

Hx 1 1 9900 8900 8900 8800

Pump 4 2000 2000 2000 2000

Screw pump 7 5075 5075 5075 5075

Table A4 List of equipment for EFB plant


(m3)

Price

per

unit

(USD)

Total

price

(USD)

Crusher Woodchipper machine 1 N/A 13000 13000

HCW HP jacketed tank 1 12 17760

0

177600





Centrifuge

2 N/A 15400 30800



0

200000


0

420000

0


Yeast cultivation

tank


Yeast cultivation

tank


Yeast cultivation

tank


Yeast cultivation

tank

Small vessel 16 0.005 20 420

Distillation column 1 N/A 18580

0

185800

Membrane 1 N/A 7237 7237

Cooler 1 1 N/A 8700 8700

Hx 1 1 N/A 8100 8100

Vacuum pump 1 N/A 2500 2500

Pump 4 N/A 500 2000

Screw pump 7 N/A 725 5075

97

Table A5 List of equipment for two feedstocks plant


(m3)

Price

per

unit

(USD)

Total

price

(USD)

Crusher Woodchipper machine 1 N/A 13000 13000

SE 1 3 50000 50000

HCW HP jacketed tank 1 12 17760

0

177600





Centrifuge

2 N/A 15400 30800



0

200000


0

420000

0


Yeast cultivation

tank


Yeast cultivation

tank


Yeast cultivation

tank


Yeast cultivation

tank

Small vessel 16 0.005 20 420

Table A6 List of equipment cost in pervaporation technology for two feedstocks plant

Model Unit EFB:OPT

100:0 80:20 50:50 20:80 0:100

Distillation column 1 185800 185600 170000 169700 176800

Membrane 1 7237 6731 6434 6101 5673

Cooler 1 1 8700 8700 8600 8600 8700

Hx 1 1 8100 8100 8100 8100 8100

Vacuum pump 1 2500 2500 2500 2500 2500

Pump 2 2000 2000 2000 2000 2000

Screw pump 7 5075 5075 5075 5075 5075

98

Table A7 Additional information for raw material and chemical substance for OPT

plant and 100:0 EFB:OPT plant

Chemical substance Unit/hr Cost/unit Total

cost

($/hr)

Total cost

($/year)

OPT 1967 0.001 2 14162

Enzyme Ctec2

H2O2 50 wt%

Ammonium sulfate

Saccharomyces cerevisiae

Urea

Sodium hydroxide (NaOH)

Water

55.94 0.53 63.36 456183

2.50 0.81

190.19 0.09

1084.08 0.00094

95.10 0.10

0.49 0.20

9985 0.00049

Table A8 Additional information for raw material and chemical substance for EFB

plant and 0:100 EFB:OPT plant


cost ($/hr)

Total cost

($/year)

EFB 1967 0.0016 3 22129

Enzyme Ctec2

H2O2 50 wt%

Ammonium sulfate


Urea


Water

66.43 0.53 74 532928

2.47 0.81

225.88 0.09

1287.49 0.00094

112.94 0.10

0.48 0.20 11858 0.00049

Table A9 Additional information for raw material and chemical substance for 80:20

EFB:OPT plant


cost ($/hr)

Total cost

($/year)

OPT

EFB

393

1574

0.0010

0.0016

0.4

2.5

2832

17703

Enzyme Ctec2

H2O2 50 wt%

Ammonium sulfate


Urea


Water

64.34 0.53 72 521454

2.48 0.81

218.75 0.09

1246.86 0.00094

109.37 0.10

0.48 0.20

11858 0.00049


EFB:OPT plant

Chemical substance Unit/hr Cost/unit Total Total cost

99

cost

($/hr)

($/year)

OPT

EFB

984

984

0.0010

0.0016

0.4

2.5

2832

17703

Enzyme Ctec2

H2O2 50 wt%

Ammonium sulfate


Urea


Water

61.43 0.53 69 497393

2.50 0.81

208.85 0.09

1190.46 0.00094

104.43 0.10

0.49 0.20

10965 0.00049


EFB:OPT plant


cost

($/hr)

Total cost

($/year)

OPT

EFB

1574

393

0.0010

0.0016

0.4

2.5

2832

17703

Enzyme Ctec2

H2O2 50 wt%

Ammonium sulfate


Urea


Water

58.18 0.53 66 471975

2.50 0.81

197.83 0.09

1127.61 0.00094

98.91 0.10

0.49 0.20 10386 0.00049

100

Tab

le A

12 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

1 o

f O

PT

pla

nt

wit

h p

ervap

ora

tion t

echn

olo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,6

97,5

13

-

2

2,6

97,5

13

1

2

,681,4

35

1

,949,1

23

732,3

12

112,6

66

619,6

46

- 2

2,0

77,8

67

2

2

,708,2

49

1

,958,3

22

749,9

27

116,1

89

633,7

38

- 2

1,4

44,1

30

3

2

,735,3

31

1

,967,6

13

767,7

18

119,7

48

647,9

71

- 2

0,7

96,1

59

4

2

,762,6

85

1

,976,9

97

785,6

88

123,3

41

662,3

46

- 2

0,1

33,8

12

5

2

,790,3

12

2

,037,3

66

752,9

46

116,7

93

636,1

53

- 1

9,4

97,6

59

6

2

,818,2

15

1

,996,0

48

822,1

67

130,6

37

691,5

30

- 1

8,8

06,1

29

7

2

,846,3

97

2

,005,7

16

840,6

81

134,3

40

706,3

41

- 1

8,0

99,7

88

8

2

,874,8

61

2

,015,4

81

859,3

80

138,0

80

721,3

00

- 1

7,3

78,4

88

9

2

,903,6

09

2

,025,3

44

878,2

66

141,8

57

736,4

09

- 1

6,6

42,0

80

10

2

,932,6

46

2

,086,1

96

846,4

50

135,4

94

710,9

56

- 1

5,9

31,1

23

11

2

,961,9

72

2

,045,3

66

916,6

06

149,5

25

767,0

81

- 1

5,1

64,0

42

12

2

,991,5

92

2

,055,5

27

936,0

64

153,4

17

782,6

48

- 1

4,3

81,3

95

13

3

,021,5

08

2

,065,7

91

955,7

17

157,3

47

798,3

70

- 1

3,5

83,0

25

14

3

,051,7

23

2

,076,1

56

975,5

66

161,3

17

814,2

49

- 1

2,7

68,7

76

15

3

,082,2

40

2

,137,5

17

944,7

23

155,1

48

789,5

75

- 1

1,9

79,2

01

16

3

,113,0

62

2

,097,2

00

1

,015,8

62

169,3

76

846,4

86

- 1

1,1

32,7

15

101

Tab

le A

13 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

1 o

f O

PT

pla

nt

wit

h p

erv

apora

tion t

echn

olo

gy (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3

,144,1

93

2

,107,8

80

1

,036,3

13

1

73,4

66

862,8

47

- 1

0,2

69,8

68

18

3

,175,6

35

2

,118,6

67

1

,056,9

68

1

77,5

98

879,3

71

- 9

,390,4

97

19

3

,207,3

91

2

,129,5

61

1

,077,8

30

1

81,7

70

896,0

60

- 8

,494,4

37

20

3

,239,4

65

2

,140,5

65

1

,098,9

01

1

85,9

84

8

,236,1

43

- 258,2

94

NP

V

-1

1,8

13,9

44

102

Tab

le A

14 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

2 o

f O

PT

pla

nt

wit

h p

ervap

ora

tion t

echn

olo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,8

24,4

46

-2

2,8

24,4

46

1

2,6

80,6

80

1,8

90,4

77

790,2

02

124,0

55

666,1

47

-22,1

58,2

99

2

2,7

07,4

86

1,8

99,0

62

808,4

24

127,7

00

680,7

24

-21,4

77,5

74

3

2,7

34,5

61

1,9

07,7

33

826,8

28

131,3

80

695,4

48

-20,7

82,1

27

4

2,7

61,9

07

1,9

16,4

91

845,4

16

135,0

98

710,3

18

-20,0

71,8

08

5

2,7

89,5

26

1,9

45,6

64

843,8

62

134,7

87

709,0

74

-19,3

62,7

34

6

2,8

17,4

21

1,9

34,2

70

883,1

52

142,6

45

740,5

07

-18,6

22,2

27

7

2,8

45,5

95

1,9

43,2

92

902,3

03

146,4

75

755,8

28

-17,8

66,4

00

8

2,8

74,0

51

1,9

52,4

06

921,6

46

150,3

44

771,3

02

-17,0

95,0

98

9

2,9

02,7

92

1,9

61,6

10

941,1

82

154,2

51

786,9

31

-16,3

08,1

67

10

2,9

31,8

20

1,9

91,2

35

940,5

85

154,1

32

786,4

53

-15,5

21,7

14

11

2,9

61,1

38

1,9

80,2

96

980,8

42

162,1

83

818,6

59

-14,7

03,0

55

12

2,9

90,7

49

1,9

89,7

79

1,0

00,9

71

166,2

09

834,7

62

-13,8

68,2

93

13

3,0

20,6

57

1,9

99,3

57

1,0

21,3

00

170,2

75

851,0

25

-13,0

17,2

68

14

3,0

50,8

64

2,0

09,0

31

1,0

41,8

33

174,3

81

867,4

51

-12,1

49,8

16

15

3,0

81,3

72

2,0

39,1

30

1,0

42,2

43

174,4

63

867,7

79

-11,2

82,0

37

16

3,1

12,1

86

2,0

28,6

69

1,0

83,5

16

182,7

18

900,7

98

-10,3

81,2

39

103

Tab

le A

15 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

2 o

f O

PT

pla

nt

wit

h p

erv

apora

tion t

echn

olo

gy (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,1

43,3

08

2,0

38,6

36

1,1

04,6

71

186,9

49

917,7

22

-9,4

63,5

17

18

3,1

74,7

41

2,0

48,7

03

1,1

26,0

38

191,2

22

934,8

15

-8,5

28,7

01

19

3,2

06,4

88

2,0

58,8

70

1,1

47,6

18

195,5

38

952,0

80

-7,5

76,6

22

20

3,2

38,5

53

2,0

69,1

39

1,1

69,4

14

199,8

98

8,3

33,6

97

757,0

75

NP

V

-1

1,2

95,4

41

104

Tab

le A

16 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

3 o

f O

PT

pla

nt

wit

h p

ervap

ora

tion t

echn

olo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

82,6

30

-2

2,7

82,6

30

1

2,6

80,0

02

1,8

90,3

05

789,6

97

124,0

17

665,6

81

-22,1

16,9

49

2

2,7

06,8

02

1,8

98,8

97

807,9

05

127,6

58

680,2

47

-21,4

36,7

03

3

2,7

33,8

70

1,9

07,5

75

826,2

94

131,3

36

694,9

58

-20,7

41,7

44

4

2,7

61,2

08

1,9

16,3

40

844,8

68

135,0

51

709,8

17

-20,0

31,9

27

5

2,7

88,8

20

1,9

33,6

97

855,1

23

137,1

02

718,0

22

-19,3

13,9

05

6

2,8

16,7

09

1,9

34,1

34

882,5

74

142,5

92

739,9

82

-18,5

73,9

23

7

2,8

44,8

76

1,9

43,1

65

901,7

11

146,4

19

755,2

91

-17,8

18,6

31

8

2,8

73,3

25

1,9

52,2

86

921,0

38

150,2

85

770,7

54

-17,0

47,8

78

9

2,9

02,0

58

1,9

61,4

98

940,5

60

154,1

89

786,3

71

-16,2

61,5

07

10

2,9

31,0

78

1,9

79,3

07

951,7

72

156,4

31

795,3

40

-15,4

66,1

67

11

2,9

60,3

89

1,9

80,2

00

980,1

89

162,1

15

818,0

74

-14,6

48,0

93

12

2,9

89,9

93

1,9

89,6

91

1,0

00,3

02

166,1

37

834,1

64

-13,8

13,9

28

13

3,0

19,8

93

1,9

99,2

78

1,0

20,6

15

170,2

00

850,4

15

-12,9

63,5

13

14

3,0

50,0

92

2,0

08,9

60

1,0

41,1

32

174,3

04

866,8

29

-12,0

96,6

84

15

3,0

80,5

93

2,0

27,2

43

1,0

53,3

50

176,7

47

876,6

03

-11,2

20,0

81

16

3,1

11,3

99

2,0

28,6

15

1,0

82,7

83

182,6

34

900,1

50

-10,3

19,9

32

105

Tab

le A

17 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

3 o

f O

PT

pla

nt

wit

h p

erv

apora

tion t

echn

olo

gy (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,1

42,5

13

2,0

38,5

91

1,1

03,9

22

186,8

61

917,0

60

-9,4

02,8

71

18

3,1

73,9

38

2,0

48,6

66

1,1

25,2

72

191,1

31

934,1

40

-8,4

68,7

31

19

3,2

05,6

77

2,0

58,8

42

1,1

46,8

35

195,4

44

951,3

91

-7,5

17,3

40

20

3,2

37,7

34

2,0

69,1

20

1,1

68,6

14

199,8

00

8,3

19,5

03

802,1

63

NP

V

-1

1,2

47,8

48

106

Tab

le A

18 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

4 o

f O

PT

pla

nt

wit

h p

ervap

ora

tion t

echn

olo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

80,4

71

-2

2,7

80,4

71

1

2,6

80,4

81

1,8

93,8

44

786,6

36

123,4

08

663,2

29

-22,1

17,2

42

2

2,7

07,2

86

1,9

02,4

73

804,8

13

127,0

43

677,7

70

-21,4

39,4

72

3

2,7

34,3

58

1,9

11,1

87

823,1

71

130,7

15

692,4

57

-20,7

47,0

15

4

2,7

61,7

02

1,9

19,9

89

841,7

13

134,4

23

707,2

90

-20,0

39,7

25

5

2,7

89,3

19

1,9

36,3

30

852,9

89

136,6

78

716,3

11

-19,3

23,4

14

6

2,8

17,2

12

1,9

37,8

57

879,3

55

141,9

51

737,4

04

-18,5

86,0

10

7

2,8

45,3

84

1,9

46,9

25

898,4

59

145,7

72

752,6

87

-17,8

33,3

23

8

2,8

73,8

38

1,9

56,0

85

917,7

54

149,6

31

768,1

23

-17,0

65,2

01

9

2,9

02,5

77

1,9

65,3

35

937,2

41

153,5

29

783,7

13

-16,2

81,4

88

10

2,9

31,6

02

1,9

82,1

30

949,4

73

155,9

75

793,4

98

-15,4

87,9

90

11

2,9

60,9

18

1,9

84,1

15

976,8

03

161,4

41

815,3

62

-14,6

72,6

28

12

2,9

90,5

28

1,9

93,6

46

996,8

82

165,4

57

831,4

25

-13,8

41,2

03

13

3,0

20,4

33

2,0

03,2

72

1,0

17,1

61

169,5

12

847,6

48

-12,9

93,5

55

14

3,0

50,6

37

2,0

12,9

95

1,0

37,6

42

173,6

09

864,0

34

-12,1

29,5

21

15

3,0

81,1

44

2,0

30,2

66

1,0

50,8

78

176,2

56

874,6

22

-11,2

54,8

99

16

3,1

11,9

55

2,0

32,7

32

1,0

79,2

22

181,9

25

897,2

98

-10,3

57,6

02

107

Tab

le A

19 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

4 o

f O

PT

pla

nt

wit

h p

erv

apora

tion t

echn

olo

gy (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,1

43,0

74

2,0

42,7

50

1,1

00,3

25

186,1

45

914,1

80

-9,4

43,4

22

18

3,1

74,5

05

2,0

52,8

67

1,1

21,6

38

190,4

08

931,2

30

-8,5

12,1

92

19

3,2

06,2

50

2,0

63,0

85

1,1

43,1

65

194,7

13

948,4

52

-7,5

63,7

40

20

3,2

38,3

13

2,0

73,4

06

1,1

64,9

07

199,0

62

8,3

15,8

37

752,0

97

NP

V

-1

1,2

75,5

04

108

Tab

le A

20 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

1 o

f O

PT

pla

nt

wit

h p

ress

ure

sw

ing a

dso

rpti

on t

echnolo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

3,9

87,1

65

-2

3,9

87,1

65

1

2,6

75,8

92

1,9

48,3

85

727,5

07

109,7

85

617,7

22

-23,3

69,4

43

2

2,7

02,6

51

1,9

57,2

95

745,3

55

113,3

55

632,0

01

-22,7

37,4

43

3

2,7

29,6

77

1,9

66,2

95

763,3

82

116,9

60

646,4

22

-22,0

91,0

21

4

2,7

56,9

74

1,9

75,3

85

781,5

88

120,6

01

660,9

87

-21,4

30,0

34

5

2,7

84,5

44

1,9

96,6

27

787,9

16

121,8

67

666,0

50

-20,7

63,9

84

6

2,8

12,3

89

1,9

93,8

39

818,5

50

127,9

94

690,5

56

-20,0

73,4

28

7

2,8

40,5

13

2,0

03,2

05

837,3

08

131,7

45

705,5

63

-19,3

67,8

65

8

2,8

68,9

18

2,0

12,6

64

856,2

54

135,5

34

720,7

20

-18,6

47,1

45

9

2,8

97,6

07

2,0

22,2

17

875,3

90

139,3

62

736,0

28

-17,9

11,1

16

10

2,9

26,5

83

2,0

43,9

27

882,6

56

140,8

15

741,8

41

-17,1

69,2

75

11

2,9

55,8

49

2,0

41,6

12

914,2

37

147,1

31

767,1

06

-16,4

02,1

69

12

2,9

85,4

08

2,0

51,4

55

933,9

52

151,0

74

782,8

78

-15,6

19,2

91

13

3,0

15,2

62

2,0

61,3

97

953,8

65

155,0

56

798,8

08

-14,8

20,4

83

14

3,0

45,4

14

2,0

71,4

38

973,9

76

159,0

79

814,8

98

-14,0

05,5

85

15

3,0

75,8

68

2,0

93,6

40

982,2

28

160,7

29

821,4

99

-13,1

84,0

86

16

3,1

06,6

27

2,0

91,8

22

1,0

14,8

05

167,2

45

847,5

60

-12,3

36,5

26

109

Tab

le A

21 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

1 o

f O

PT

pla

nt

wit

h p

ress

ure

sw

ing a

dso

rpti

on t

echnolo

gy

(co

nti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,1

37,6

93

2,1

02,1

67

1,0

35,5

26

171,3

89

864,1

37

-11,4

72,3

88

18

3,1

69,0

70

2,1

12,6

16

1,0

56,4

54

175,5

74

880,8

80

-10,5

91,5

09

19

3,2

00,7

61

2,1

23,1

69

1,0

77,5

92

179,8

02

897,7

90

-9,6

93,7

19

20

3,2

32,7

69

2,1

33,8

28

1,0

98,9

40

184,0

72

8,6

54,1

94

-1,0

39,5

25

NP

V

-1

2,9

18,5

08

110

Tab

le A

22 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

2 o

f O

PT

pla

nt

wit

h p

ress

ure

sw

ing a

dso

rpti

on t

echnolo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

3,9

80,7

18

-2

3,9

80,7

18

1

2,6

72,7

06

1,9

43,0

16

729,6

89

110,2

31

619,4

58

-23,3

61,2

60

2

2,6

99,4

33

1,9

51,8

75

747,5

58

113,8

05

633,7

53

-22,7

27,5

07

3

2,7

26,4

27

1,9

60,8

22

765,6

05

117,4

14

648,1

91

-22,0

79,3

16

4

2,7

53,6

91

1,9

69,8

59

783,8

32

121,0

60

662,7

73

-21,4

16,5

44

5

2,7

81,2

28

1,9

91,0

47

790,1

81

122,3

29

667,8

52

-20,7

48,6

92

6

2,8

09,0

40

1,9

88,2

04

820,8

36

128,4

60

692,3

76

-20,0

56,3

16

7

2,8

37,1

31

1,9

97,5

15

839,6

16

132,2

16

707,4

00

-19,3

48,9

16

8

2,8

65,5

02

2,0

06,9

18

858,5

84

136,0

10

722,5

74

-18,6

26,3

43

9

2,8

94,1

57

2,0

16,4

16

877,7

41

139,8

41

737,9

00

-17,8

88,4

43

10

2,9

23,0

99

2,0

38,0

69

885,0

29

141,2

99

743,7

30

-17,1

44,7

13

11

2,9

52,3

30

2,0

35,6

97

916,6

33

147,6

20

769,0

13

-16,3

75,7

00

12

2,9

81,8

53

2,0

45,4

83

936,3

70

151,5

67

784,8

03

-15,5

90,8

97

13

3,0

11,6

72

2,0

55,3

66

956,3

06

155,5

54

800,7

51

-14,7

90,1

45

14

3,0

41,7

88

2,0

65,3

48

976,4

40

159,5

81

816,8

59

-13,9

73,2

86

15

3,0

72,2

06

2,0

87,4

91

984,7

15

161,2

36

823,4

79

-13,1

49,8

07

16

3,1

02,9

28

2,0

85,6

13

1,0

17,3

16

167,7

56

849,5

59

-12,3

00,2

48

111

Tab

le A

23 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

2 o

f O

PT

pla

nt

wit

h p

ress

ure

sw

ing a

dso

rpti

on t

echnolo

gy

(co

nti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,1

33,9

57

2,0

95,8

97

1,0

38,0

60

171,9

05

866,1

55

-11,4

34,0

92

18

3,1

65,2

97

2,1

06,2

85

1,0

59,0

12

176,0

96

882,9

17

-10,5

51,1

76

19

3,1

96,9

50

2,1

16,7

76

1,0

80,1

74

180,3

28

899,8

46

-9,6

51,3

30

20

3,2

28,9

20

2,1

27,3

72

1,1

01,5

47

184,6

03

8,6

54,1

90

-997,1

40

NP

V

-1

2,8

90,9

11

112

Tab

le A

24 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

3 o

f O

PT

pla

nt

wit

h p

ress

ure

sw

ing a

dso

rpti

on t

echnolo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

3,9

88,2

40

-2

3,9

88,2

40

1

2,6

75,5

54

1,9

47,1

77

728,3

77

109,9

57

618,4

20

-23,3

69,8

20

2

2,7

02,3

10

1,9

56,0

76

746,2

34

113,5

29

632,7

05

-22,7

37,1

15

3

2,7

29,3

33

1,9

65,0

64

764,2

69

117,1

36

647,1

34

-22,0

89,9

81

4

2,7

56,6

26

1,9

74,1

41

782,4

85

120,7

79

661,7

06

-21,4

28,2

75

5

2,7

84,1

93

1,9

95,3

70

788,8

23

122,0

46

666,7

76

-20,7

61,4

99

6

2,8

12,0

35

1,9

92,5

69

819,4

65

128,1

75

691,2

90

-20,0

70,2

09

7

2,8

40,1

55

2,0

01,9

22

838,2

33

131,9

29

706,3

05

-19,3

63,9

04

8

2,8

68,5

56

2,0

11,3

68

857,1

89

135,7

20

721,4

69

-18,6

42,4

35

9

2,8

97,2

42

2,0

20,9

08

876,3

34

139,5

49

736,7

85

-17,9

05,6

50

10

2,9

26,2

14

2,0

42,6

05

883,6

10

141,0

04

742,6

06

-17,1

63,0

44

11

2,9

55,4

77

2,0

40,2

76

915,2

00

147,3

22

767,8

78

-16,3

95,1

66

12

2,9

85,0

31

2,0

50,1

06

934,9

25

151,2

67

783,6

58

-15,6

11,5

07

13

3,0

14,8

82

2,0

60,0

34

954,8

48

155,2

52

799,5

96

-14,8

11,9

11

14

3,0

45,0

31

2,0

70,0

61

974,9

70

159,2

76

815,6

94

-13,9

96,2

17

15

3,0

75,4

81

2,0

92,2

49

983,2

32

160,9

28

822,3

03

-13,1

73,9

14

16

3,1

06,2

36

2,0

90,4

17

1,0

15,8

19

167,4

46

848,3

73

-12,3

25,5

41

113

Tab

le A

25 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

3 o

f O

PT

pla

nt

wit

h p

ress

ure

sw

ing a

dso

rpti

on t

echnolo

gy

(co

nti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,1

37,2

98

2,1

00,7

48

1,0

36,5

50

171,5

92

864,9

58

-11,4

60,5

83

18

3,1

68,6

71

2,1

11,1

82

1,0

57,4

89

175,7

80

881,7

09

-10,5

78,8

74

19

3,2

00,3

58

2,1

21,7

21

1,0

78,6

37

180,0

09

898,6

27

-9,6

80,2

46

20

3,2

32,3

61

2,1

32,3

65

1,0

99,9

96

184,2

81

8,6

55,3

87

-1,0

24,8

59

NP

V

-1

2,9

10,6

45

114

Tab

le A

26 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

4 o

f O

PT

pla

nt

wit

h p

ress

ure

sw

ing a

dso

rpti

on t

echnolo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

4,1

60,7

07

-2

4,1

60,7

07

1

2,6

77,2

59

1,9

47,6

55

729,6

04

109,9

46

619,6

58

-23,5

41,0

49

2

2,7

04,0

32

1,9

56,5

21

747,5

11

113,5

27

633,9

83

-22,9

07,0

66

3

2,7

31,0

72

1,9

65,4

76

765,5

96

117,1

44

648,4

52

-22,2

58,6

14

4

2,7

58,3

83

1,9

74,5

20

783,8

63

120,7

98

663,0

65

-21,5

95,5

48

5

2,7

85,9

66

1,9

95,7

15

790,2

52

122,0

75

668,1

76

-20,9

27,3

72

6

2,8

13,8

26

1,9

92,8

80

820,9

46

128,2

14

692,7

32

-20,2

34,6

40

7

2,8

41,9

64

2,0

02,1

98

839,7

67

131,9

78

707,7

88

-19,5

26,8

52

8

2,8

70,3

84

2,0

11,6

09

858,7

75

135,7

80

722,9

95

-18,8

03,8

57

9

2,8

99,0

88

2,0

21,1

14

877,9

73

139,6

20

738,3

54

-18,0

65,5

04

10

2,9

28,0

79

2,0

42,7

76

885,3

03

141,0

86

744,2

17

-17,3

21,2

86

11

2,9

57,3

60

2,0

40,4

11

916,9

48

147,4

15

769,5

34

-16,5

51,7

53

12

2,9

86,9

33

2,0

50,2

05

936,7

29

151,3

71

785,3

58

-15,7

66,3

95

13

3,0

16,8

02

2,0

60,0

96

956,7

07

155,3

66

801,3

40

-14,9

65,0

55

14

3,0

46,9

71

2,0

70,0

86

976,8

84

159,4

02

817,4

82

-14,1

47,5

73

15

3,0

77,4

40

2,0

92,2

37

985,2

03

161,0

66

824,1

37

-13,3

23,4

35

16

3,1

08,2

15

2,0

90,3

67

1,0

17,8

47

167,5

95

850,2

53

-12,4

73,1

82

115

Tab

le A

27 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

case

4 o

f O

PT

pla

nt

wit

h p

ress

ure

sw

ing a

dso

rpti

on t

echnolo

gy

(co

nti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,1

39,2

97

2,1

00,6

60

1,0

38,6

37

171,7

52

866,8

84

-11,6

06,2

98

18

3,1

70,6

90

2,1

11,0

56

1,0

59,6

34

175,9

52

883,6

82

-10,7

22,6

16

19

3,2

02,3

97

2,1

21,5

56

1,0

80,8

41

180,1

93

900,6

48

-9,8

21,9

69

20

3,2

34,4

21

2,1

32,1

61

1,1

02,2

60

184,4

77

8,7

13,1

00

-1,1

08,8

69

NP

V

-1

3,0

46,7

71

116

Tab

le A

28 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

EF

B p

lant

wit

h p

erv

apora

tion t

echnolo

gy

Y

ears

R

even

ue

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

9,5

68,8

37

-2

9,5

68,8

37

1

3,2

62,2

30

2,2

47,6

35

1,0

14,5

95

158,8

92

855,7

04

-28,7

13,1

34

2

3,2

94,8

52

2,2

57,5

18

1,0

37,3

34

163,4

39

873,8

94

-27,8

39,2

39

3

3,3

27,8

01

2,2

67,5

01

1,0

60,3

00

168,0

32

892,2

67

-26,9

46,9

72

4

3,3

61,0

79

2,2

77,5

83

1,0

83,4

95

172,6

72

910,8

24

-26,0

36,1

48

5

3,3

94,6

89

2,2

98,6

28

1,0

96,0

61

175,1

85

920,8

76

-25,1

15,2

72

6

3,4

28,6

36

2,2

98,0

52

1,1

30,5

85

182,0

89

948,4

95

-24,1

66,7

77

7

3,4

62,9

23

2,3

08,4

40

1,1

54,4

83

186,8

69

967,6

14

-23,1

99,1

63

8

3,4

97,5

52

2,3

18,9

31

1,1

78,6

20

191,6

97

986,9

24

-22,2

12,2

39

9

3,5

32,5

27

2,3

29,5

28

1,2

02,9

99

196,5

72

1,0

06,4

27

-21,2

05,8

12

10

3,5

67,8

53

2,3

51,0

93

1,2

16,7

60

199,3

25

1,0

17,4

36

-20,1

88,3

77

11

3,6

03,5

31

2,3

51,0

41

1,2

52,4

91

206,4

71

1,0

46,0

20

-19,1

42,3

57

12

3,6

39,5

67

2,3

61,9

58

1,2

77,6

08

211,4

94

1,0

66,1

14

-18,0

76,2

43

13

3,6

75,9

62

2,3

72,9

85

1,3

02,9

77

216,5

68

1,0

86,4

09

-16,9

89,8

34

14

3,7

12,7

22

2,3

84,1

23

1,3

28,5

99

221,6

92

1,1

06,9

07

-15,8

82,9

27

15

3,7

49,8

49

2,4

06,2

33

1,3

43,6

16

224,6

96

1,1

18,9

20

-14,7

64,0

07

16

3,7

87,3

48

2,4

06,7

32

1,3

80,6

15

232,0

96

1,1

48,5

20

-13,6

15,4

87

117

Tab

le A

29 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

EF

B p

lant

wit

h p

erv

apora

tion t

echnolo

gy (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,8

25,2

21

2,4

18,2

07

1,4

07,0

14

237,3

75

1,1

69,6

38

-12,4

45,8

49

18

3,8

63,4

73

2,4

29,7

97

1,4

33,6

77

242,7

08

1,1

90,9

69

-11,2

54,8

80

19

3,9

02,1

08

2,4

41,5

02

1,4

60,6

06

248,0

94

1,2

12,5

12

-10,0

42,3

68

20

3,9

41,1

29

2,4

53,3

25

1,4

87,8

05

253,5

33

10,7

74,4

92

732,1

24

NP

V

-1

4,7

62,1

53

118

Tab

le A

30 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

100:0

of

EF

B:O

PT

plan

t

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

9,8

37,4

77

-2

9,8

37,4

77

1

3,2

63,5

82

2,2

53,4

24

1,0

10,1

57

157,6

04

852,5

53

-28,9

84,9

24

2

3,2

96,2

17

2,2

63,3

08

1,0

32,9

09

162,1

54

870,7

55

-28,1

14,1

69

3

3,3

29,1

79

2,2

73,2

91

1,0

55,8

89

166,7

50

889,1

39

-27,2

25,0

31

4

3,3

62,4

71

2,2

83,3

73

1,0

79,0

98

171,3

92

907,7

06

-26,3

17,3

25

5

3,3

96,0

96

2,3

04,4

11

1,0

91,6

85

173,9

09

917,7

75

-25,3

99,5

49

6

3,4

30,0

57

2,3

03,8

41

1,1

26,2

16

180,8

16

945,4

00

-24,4

54,1

50

7

3,4

64,3

58

2,3

14,2

29

1,1

50,1

28

185,5

98

964,5

30

-23,4

89,6

20

8

3,4

99,0

01

2,3

24,7

21

1,1

74,2

80

190,4

29

983,8

51

-22,5

05,7

68

9

3,5

33,9

91

2,3

35,3

18

1,1

98,6

73

195,3

07

1,0

03,3

66

-21,5

02,4

02

10

3,5

69,3

31

2,3

56,8

76

1,2

12,4

56

198,0

64

1,0

14,3

92

-20,4

88,0

10

11

3,6

05,0

24

2,3

56,8

30

1,2

48,1

94

205,2

11

1,0

42,9

83

-19,4

45,0

28

12

3,6

41,0

75

2,3

67,7

48

1,2

73,3

26

210,2

38

1,0

63,0

89

-18,3

81,9

39

13

3,6

77,4

85

2,3

78,7

75

1,2

98,7

10

215,3

15

1,0

83,3

96

-17,2

98,5

43

14

3,7

14,2

60

2,3

89,9

12

1,3

24,3

48

220,4

42

1,1

03,9

06

-16,1

94,6

38

15

3,7

51,4

03

2,4

12,0

16

1,3

39,3

87

223,4

50

1,1

15,9

37

-15,0

78,7

01

16

3,7

88,9

17

2,4

12,5

22

1,3

76,3

95

230,8

51

1,1

45,5

43

-13,9

33,1

58

119

Tab

le A

31 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

100:0

of

EF

B:O

PT

plan

t (c

onti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,8

26,8

06

2,4

23,9

97

1,4

02,8

09

236,1

34

1,1

66,6

75

-12,7

66,4

83

18

3,8

65,0

74

2,4

35,5

86

1,4

29,4

88

241,4

70

1,1

88,0

18

-11,5

78,4

65

19

3,9

03,7

25

2,4

47,2

92

1,4

56,4

33

246,8

59

1,2

09,5

74

-10,3

68,8

91

20

3,9

42,7

62

2,4

59,1

14

1,4

83,6

48

252,3

02

10,8

58,2

42

489,3

50

NP

V

-1

5,0

38,3

65

120

Tab

le A

32 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

80:2

0 o

f E

FB

:OP

T pl

ant

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

9,8

33,6

85

-2

9,8

33,6

85

1

3,1

44,1

03

2,2

36,3

70

907,7

33

137,1

25

770,6

09

-29,0

63,0

77

2

3,1

75,5

44

2,2

46,2

35

929,3

10

141,4

40

787,8

70

-28,2

75,2

07

3

3,2

07,3

00

2,2

56,1

98

951,1

02

145,7

99

805,3

03

-27,4

69,9

04

4

3,2

39,3

73

2,2

66,2

61

973,1

11

150,2

00

822,9

11

-26,6

46,9

93

5

3,2

71,7

67

2,2

86,5

21

985,2

45

152,6

27

832,6

18

-25,8

14,3

75

6

3,3

04,4

84

2,2

86,6

91

1,0

17,7

94

159,1

37

858,6

57

-24,9

55,7

18

7

3,3

37,5

29

2,2

97,0

59

1,0

40,4

70

163,6

72

876,7

98

-24,0

78,9

20

8

3,3

70,9

04

2,3

07,5

30

1,0

63,3

74

168,2

53

895,1

21

-23,1

83,7

99

9

3,4

04,6

13

2,3

18,1

07

1,0

86,5

06

172,8

79

913,6

27

-22,2

70,1

72

10

3,4

38,6

60

2,3

38,8

85

1,0

99,7

74

175,5

33

924,2

41

-21,3

45,9

31

11

3,4

73,0

46

2,3

39,5

78

1,1

33,4

68

182,2

72

951,1

96

-20,3

94,7

35

12

3,5

07,7

77

2,3

50,4

75

1,1

57,3

01

187,0

38

970,2

63

-19,4

24,4

72

13

3,5

42,8

54

2,3

61,4

81

1,1

81,3

73

191,8

53

989,5

20

-18,4

34,9

52

14

3,5

78,2

83

2,3

72,5

97

1,2

05,6

86

196,7

15

1,0

08,9

70

-17,4

25,9

81

15

3,6

14,0

66

2,3

93,9

20

1,2

20,1

45

199,6

07

1,0

20,5

38

-16,4

05,4

43

16

3,6

50,2

06

2,3

95,1

64

1,2

55,0

43

206,5

87

1,0

48,4

56

-15,3

56,9

87

121

Tab

le A

33 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

80:2

0 o

f E

FB

:OP

T pl

ant

(conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,6

86,7

08

2,4

06,6

16

1,2

80,0

92

211,5

97

1,0

68,4

95

-14,2

88,4

92

18

3,7

23,5

76

2,4

18,1

84

1,3

05,3

92

216,6

57

1,0

88,7

35

-13,1

99,7

56

19

3,7

60,8

11

2,4

29,8

67

1,3

30,9

45

221,7

67

1,1

09,1

77

-12,0

90,5

79

20

3,7

98,4

19

2,4

41,6

67

1,3

56,7

53

226,9

29

10,7

55,4

96

-1,3

35,0

83

NP

V

-1

6,0

80,2

37

122

Tab

le A

34 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

50:5

0 o

f E

FB

:OP

T pl

ant

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

9,7

47,7

37

-2

9,7

47,7

37

1

2,9

79,6

66

2,1

75,7

37

803,9

29

116,4

92

687,4

37

-29,0

60,3

00

2

3,0

09,4

63

2,1

85,2

55

824,2

08

120,5

48

703,6

60

-28,3

56,6

40

3

3,0

39,5

57

2,1

94,8

68

844,6

89

124,6

44

720,0

45

-27,6

36,5

95

4

3,0

69,9

53

2,2

04,5

77

865,3

76

128,7

81

736,5

94

-26,9

00,0

01

5

3,1

00,6

52

2,2

24,0

34

876,6

18

131,0

30

745,5

88

-26,1

54,4

13

6

3,1

31,6

59

2,2

24,2

88

907,3

71

137,1

80

770,1

91

-25,3

84,2

22

7

3,1

62,9

75

2,2

34,2

91

928,6

84

141,4

43

787,2

41

-24,5

96,9

81

8

3,1

94,6

05

2,2

44,3

95

950,2

11

145,7

48

804,4

62

-23,7

92,5

19

9

3,2

26,5

51

2,2

54,5

99

971,9

52

150,0

97

821,8

56

-22,9

70,6

63

10

3,2

58,8

17

2,2

74,5

56

984,2

60

152,5

58

831,7

02

-22,1

38,9

61

11

3,2

91,4

05

2,2

75,3

15

1,0

16,0

90

158,9

24

857,1

66

-21,2

81,7

95

12

3,3

24,3

19

2,2

85,8

29

1,0

38,4

90

163,4

04

875,0

86

-20,4

06,7

09

13

3,3

57,5

62

2,2

96,4

47

1,0

61,1

15

167,9

29

893,1

86

-19,5

13,5

24

14

3,3

91,1

38

2,3

07,1

72

1,0

83,9

65

172,4

99

911,4

66

-18,6

02,0

58

15

3,4

25,0

49

2,3

27,6

56

1,0

97,3

94

175,1

85

922,2

09

-17,6

79,8

49

16

3,4

59,3

00

2,3

28,9

45

1,1

30,3

54

181,7

77

948,5

77

-16,7

31,2

72

123

Tab

le A

35 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

50:5

0 o

f E

FB

:OP

T pl

ant

(conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,4

93,8

93

2,3

39,9

95

1,1

53,8

97

186,4

86

967,4

12

-15,7

63,8

60

18

3,5

28,8

31

2,3

51,1

56

1,1

77,6

76

191,2

41

986,4

35

-14,7

77,4

26

19

3,5

64,1

20

2,3

62,4

28

1,2

01,6

92

196,0

45

1,0

05,6

48

-13,7

71,7

78

20

3,5

99,7

61

2,3

73,8

12

1,2

25,9

49

200,8

96

10,6

22,9

94

-3,1

48,7

84

NP

V

-1

7,0

72,5

50

124

Tab

le A

36 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

20:8

0 o

f E

FB

:OP

T pl

ant

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

9,8

14,1

85

-2

9,8

14,1

85

1

2,8

01,2

82

2,1

15,6

39

685,6

43

92,7

36

592,9

07

-29,2

21,2

77

2

2,8

29,2

95

2,1

24,7

95

704,5

00

96,5

07

607,9

92

-28,6

13,2

85

3

2,8

57,5

88

2,1

34,0

44

723,5

44

100,3

16

623,2

28

-27,9

90,0

57

4

2,8

86,1

64

2,1

43,3

84

742,7

80

104,1

63

638,6

16

-27,3

51,4

40

5

2,9

15,0

25

2,1

61,9

70

753,0

55

106,2

18

646,8

37

-26,7

04,6

03

6

2,9

44,1

76

2,1

62,3

47

781,8

29

111,9

73

669,8

56

-26,0

34,7

47

7

2,9

73,6

17

2,1

71,9

70

801,6

47

115,9

37

685,7

10

-25,3

49,0

37

8

3,0

03,3

54

2,1

81,6

90

821,6

63

119,9

40

701,7

23

-24,6

47,3

14

9

3,0

33,3

87

2,1

91,5

07

841,8

80

123,9

83

717,8

97

-23,9

29,4

17

10

3,0

63,7

21

2,2

10,5

75

853,1

46

126,2

37

726,9

10

-23,2

02,5

07

11

3,0

94,3

58

2,2

11,4

37

882,9

21

132,1

91

750,7

30

-22,4

51,7

77

12

3,1

25,3

02

2,2

21,5

52

903,7

50

136,3

57

767,3

93

-21,6

84,3

85

13

3,1

56,5

55

2,2

31,7

67

924,7

87

140,5

65

784,2

23

-20,9

00,1

62

14

3,1

88,1

20

2,2

42,0

85

946,0

35

144,8

14

801,2

21

-20,0

98,9

41

15

3,2

20,0

02

2,2

61,6

58

958,3

43

147,2

76

811,0

67

-19,2

87,8

74

16

3,2

52,2

02

2,2

63,0

32

989,1

70

153,4

41

835,7

29

-18,4

52,1

45

125

Tab

le A

37 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

20:8

0 o

f E

FB

:OP

T pl

ant

(conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,2

84,7

24

2,2

73,6

62

1,0

11,0

61

157,8

20

853,2

42

-17,5

98,9

03

18

3,3

17,5

71

2,2

84,3

99

1,0

33,1

72

162,2

42

870,9

30

-16,7

27,9

73

19

3,3

50,7

46

2,2

95,2

43

1,0

55,5

03

166,7

08

888,7

95

-15,8

39,1

77

20

3,3

84,2

54

2,3

06,1

96

1,0

78,0

58

171,2

19

10,5

26,2

20

-5,3

12,9

57

NP

V

-1

8,3

43,3

49

126

Tab

le A

38 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

0:1

00

of

EF

B:O

PT

plan

t

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

9,8

50,5

66

-2

9,8

50,5

66

1

2,6

78,6

72

2,0

59,0

35

619,6

37

79,4

80

540,1

57

-29,3

10,4

10

2

2,7

05,4

59

2,0

67,7

94

637,6

65

83,0

86

554,5

79

-28,7

55,8

31

3

2,7

32,5

13

2,0

76,6

41

655,8

73

86,7

28

569,1

45

-28,1

86,6

86

4

2,7

59,8

38

2,0

85,5

75

674,2

63

90,4

06

583,8

57

-27,6

02,8

29

5

2,7

87,4

37

2,1

03,0

71

684,3

66

92,4

26

591,9

40

-27,0

10,8

89

6

2,8

15,3

11

2,1

03,7

14

711,5

97

97,8

72

613,7

24

-26,3

97,1

64

7

2,8

43,4

64

2,1

12,9

20

730,5

44

101,6

62

628,8

82

-25,7

68,2

82

8

2,8

71,8

99

2,1

22,2

18

749,6

81

105,4

89

644,1

92

-25,1

24,0

90

9

2,9

00,6

18

2,1

31,6

09

769,0

09

109,3

55

659,6

54

-24,4

64,4

36

10

2,9

29,6

24

2,1

49,5

64

780,0

60

111,5

65

668,4

95

-23,7

95,9

41

11

2,9

58,9

20

2,1

50,6

73

808,2

48

117,2

03

691,0

45

-23,1

04,8

96

12

2,9

88,5

10

2,1

60,3

48

828,1

62

121,1

85

706,9

76

-22,3

97,9

20

13

3,0

18,3

95

2,1

70,1

20

848,2

75

125,2

08

723,0

67

-21,6

74,8

53

14

3,0

48,5

79

2,1

79,9

90

868,5

89

129,2

71

739,3

18

-20,9

35,5

35

15

3,0

79,0

64

2,1

98,4

30

880,6

35

131,6

80

748,9

55

-20,1

86,5

80

16

3,1

09,8

55

2,2

00,0

27

909,8

29

137,5

19

772,3

10

-19,4

14,2

71

127

Tab

le A

39 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

0:1

00 o

f E

FB

:OP

T pl

ant

(conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

3,1

40,9

54

2,2

10,1

95

930,7

58

141,7

05

789,0

54

-18,6

25,2

17

18

3,1

72,3

63

2,2

20,4

66

951,8

97

145,9

33

805,9

65

-17,8

19,2

52

19

3,2

04,0

87

2,2

30,8

39

973,2

48

150,2

03

823,0

45

-16,9

96,2

07

20

3,2

36,1

28

2,2

41,3

16

994,8

12

154,5

15

10,4

71,4

15

-6,5

24,7

92

NP

V

-1

9,0

53,9

29

128

Tab

le A

40 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 4

wt%

to 8

0 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

52,0

93

2

2,7

52,0

93

1

3,5

15,3

16

1,8

96,6

64

1,6

18,6

53

289,8

53

1,3

28,8

00

-21,4

23,2

94

2

3,5

50,4

69

1,9

05,3

26

1,6

45,1

43

295,1

51

1,3

49,9

92

-20,0

73,3

02

3

3,5

85,9

74

1,9

14,0

76

1,6

71,8

99

300,5

02

1,3

71,3

96

-18,7

01,9

05

4

3,6

21,8

34

1,9

22,9

12

1,6

98,9

22

305,9

07

1,3

93,0

15

-17,3

08,8

91

5

3,6

58,0

52

1,9

55,8

16

1,7

02,2

36

306,5

70

1,3

95,6

66

-15,9

13,2

25

6

3,6

94,6

33

1,9

40,8

52

1,7

53,7

81

316,8

79

1,4

36,9

02

-14,4

76,3

22

7

3,7

31,5

79

1,9

49,9

56

1,7

81,6

23

322,4

47

1,4

59,1

76

-13,0

17,1

47

8

3,7

68,8

95

1,9

59,1

52

1,8

09,7

43

328,0

71

1,4

81,6

72

-11,5

35,4

75

9

3,8

06,5

84

1,9

68,4

39

1,8

38,1

44

333,7

51

1,5

04,3

93

-10,0

31,0

82

10

3,8

44,6

50

2,0

01,7

99

1,8

42,8

51

334,6

93

1,5

08,1

58

-8,5

22,9

23

11

3,8

83,0

96

1,9

87,2

94

1,8

95,8

02

345,2

83

1,5

50,5

19

-6,9

72,4

04

12

3,9

21,9

27

1,9

96,8

63

1,9

25,0

64

351,1

35

1,5

73,9

29

-5,3

98,4

75

13

3,9

61,1

46

2,0

06,5

28

1,9

54,6

19

357,0

46

1,5

97,5

73

-3,8

00,9

03

14

4,0

00,7

58

2,0

16,2

89

1,9

84,4

69

363,0

16

1,6

21,4

53

-2,1

79,4

50

15

4,0

40,7

65

2,0

50,1

26

1,9

90,6

39

364,2

50

1,6

26,3

89

-553,0

61

16

4,0

81,1

73

2,0

36,1

05

2,0

45,0

68

375,1

36

1,6

69,9

32

1,1

16,8

70

129

Tab

le A

41 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 4

wt%

to 8

0 w

t% (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

4,1

21,9

85

2,0

46,1

62

2,0

75,8

23

381,2

87

1,6

94,5

36

2,8

11,4

06

18

4,1

63,2

05

2,0

56,3

20

2,1

06,8

85

387,5

00

1,7

19,3

85

4,5

30,7

91

19

4,2

04,8

37

2,0

66,5

79

2,1

38,2

58

393,7

74

1,7

44,4

84

6,2

75,2

75

20

4,2

46,8

85

2,0

76,9

41

2,1

69,9

44

400,1

11

9,1

10,6

69

15,3

85,9

44

NP

V

-2

,868,4

46

130

Tab

le A

42 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 6

wt%

to 8

0 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,8

45,1

94

2

2,8

45,1

94

1

5,2

71,3

88

1,9

10,3

11

3,3

61,0

77

638,1

99

2,7

22,8

78

-20,1

22,3

16

2

5,3

24,1

02

1,9

19,0

90

3,4

05,0

12

646,9

86

2,7

58,0

26

-17,3

64,2

91

3

5,3

77,3

43

1,9

27,9

56

3,4

49,3

86

655,8

61

2,7

93,5

25

-14,5

70,7

65

4

5,4

31,1

16

1,9

36,9

12

3,4

94,2

05

664,8

25

2,8

29,3

80

-11,7

41,3

86

5

5,4

85,4

27

1,9

81,8

27

3,5

03,6

00

666,7

04

2,8

36,8

96

-8,9

04,4

90

6

5,5

40,2

82

1,9

55,0

92

3,5

85,1

90

683,0

22

2,9

02,1

68

-6,0

02,3

22

7

5,5

95,6

84

1,9

64,3

18

3,6

31,3

66

692,2

57

2,9

39,1

09

-3,0

63,2

13

8

5,6

51,6

41

1,9

73,6

37

3,6

78,0

04

701,5

85

2,9

76,4

19

-86,7

93

9

5,7

08,1

58

1,9

83,0

49

3,7

25,1

08

711,0

06

3,0

14,1

03

2,9

27,3

09

10

5,7

65,2

39

2,0

28,4

27

3,7

36,8

13

713,3

46

3,0

23,4

66

5,9

50,7

76

11

5,8

22,8

92

2,0

02,1

57

3,8

20,7

35

730,1

31

3,0

90,6

04

9,0

41,3

80

12

5,8

81,1

21

2,0

11,8

54

3,8

69,2

66

739,8

37

3,1

29,4

29

12,1

70,8

09

13

5,9

39,9

32

2,0

21,6

48

3,9

18,2

83

749,6

41

3,1

68,6

43

15,3

39,4

52

14

5,9

99,3

31

2,0

31,5

41

3,9

67,7

91

759,5

42

3,2

08,2

49

18,5

47,7

00

15

6,0

59,3

24

2,0

77,4

03

3,9

81,9

22

762,3

68

3,2

19,5

53

21,7

67,2

54

16

6,1

19,9

18

2,0

51,6

23

4,0

68,2

95

779,6

43

3,2

88,6

52

25,0

55,9

06

131

Tab

le A

43 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 6

wt%

to 8

0%

(co

nti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

6,1

81,1

17

2,0

61,8

15

4,1

19,3

02

789,8

44

3,3

29,4

58

28,3

85,3

63

18

6,2

42,9

28

2,0

72,1

09

4,1

70,8

19

800,1

48

3,3

70,6

72

31,7

56,0

35

19

6,3

05,3

57

2,0

82,5

05

4,2

22,8

52

810,5

54

3,4

12,2

98

35,1

68,3

33

20

6,3

68,4

11

2,0

93,0

06

4,2

75,4

05

821,0

65

10,8

25,2

14

45,9

93,5

47

NP

V

1

4,6

38,3

50

132

Tab

le A

44 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 8

wt%

to 8

0 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,8

66,7

73

2

2,8

66,7

73

1

7,0

00,9

51

1,9

19,7

87

5,0

81,1

64

982,1

09

4,0

99,0

55

-18,8

18,7

27

2

7,0

70,9

60

1,9

28,6

45

5,1

42,3

15

994,3

39

4,1

47,9

76

-14,6

70,7

51

3

7,1

41,6

70

1,9

37,5

91

5,2

04,0

79

1,0

06,6

92

4,1

97,3

87

-10,4

73,3

64

4

7,2

13,0

86

1,9

46,6

27

5,2

66,4

59

1,0

19,1

68

4,2

47,2

92

-6,2

26,0

72

5

7,2

85,2

17

2,0

04,2

40

5,2

80,9

78

1,0

22,0

71

4,2

58,9

06

-1,9

67,1

66

6

7,3

58,0

69

1,9

64,9

71

5,3

93,0

99

1,0

44,4

96

4,3

48,6

03

2,3

81,4

37

7

7,4

31,6

50

1,9

74,2

80

5,4

57,3

70

1,0

57,3

50

4,4

00,0

20

6,7

81,4

57

8

7,5

05,9

67

1,9

83,6

83

5,5

22,2

84

1,0

70,3

33

4,4

51,9

51

11,2

33,4

08

9

7,5

81,0

26

1,9

93,1

80

5,5

87,8

47

1,0

83,4

45

4,5

04,4

01

15,7

37,8

10

10

7,6

56,8

37

2,0

51,2

58

5,6

05,5

79

1,0

86,9

92

4,5

18,5

87

20,2

56,3

97

11

7,7

33,4

05

2,0

12,4

59

5,7

20,9

46

1,1

10,0

65

4,6

10,8

81

24,8

67,2

78

12

7,8

10,7

39

2,0

22,2

44

5,7

88,4

95

1,1

23,5

75

4,6

64,9

21

29,5

32,1

98

13

7,8

88,8

46

2,0

32,1

26

5,8

56,7

20

1,1

37,2

20

4,7

19,5

01

34,2

51,6

99

14

7,9

67,7

35

2,0

42,1

07

5,9

25,6

28

1,1

51,0

01

4,7

74,6

26

39,0

26,3

25

15

8,0

47,4

12

2,1

00,6

75

5,9

46,7

38

1,1

55,2

23

4,7

91,5

14

43,8

17,8

39

16

8,1

27,8

86

2,0

62,3

70

6,0

65,5

16

1,1

78,9

79

4,8

86,5

37

48,7

04,3

77

133

Tab

le A

45 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 8

wt%

to 8

0 w

t% (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

8,2

09,1

65

2,0

72,6

53

6,1

36,5

12

1,1

93,1

78

4,9

43,3

34

53,6

47,7

10

18

8,2

91,2

57

2,0

83,0

40

6,2

08,2

17

1,2

07,5

19

5,0

00,6

98

58,6

48,4

08

19

8,3

74,1

69

2,0

93,5

30

6,2

80,6

39

1,2

22,0

04

5,0

58,6

35

63,7

07,0

43

20

8,4

57,9

11

2,1

04,1

25

6,3

53,7

86

1,2

36,6

33

12,5

11,4

47

76,2

18,4

91

NP

V

3

1,9

36,1

17

134

Tab

le A

46 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 4

wt%

to 8

5 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

45,0

34

-

22,7

45,0

34

1

3,5

17,1

47

1,8

96,5

59

1,6

20,5

88

290,2

51

1,3

30,3

37

-21,4

14,6

97

2

3,5

52,3

19

1,9

05,2

22

1,6

47,0

96

295,5

52

1,3

51,5

44

-20,0

63,1

53

3

3,5

87,8

42

1,9

13,9

72

1,6

73,8

70

300,9

07

1,3

72,9

63

-18,6

90,1

90

4

3,6

23,7

20

1,9

22,8

09

1,7

00,9

11

306,3

15

1,3

94,5

96

-17,2

95,5

94

5

3,6

59,9

57

1,9

43,3

93

1,7

16,5

65

309,4

46

1,4

07,1

19

-15,8

88,4

75

6

3,6

96,5

57

1,9

40,7

50

1,7

55,8

07

317,2

95

1,4

38,5

13

-14,4

49,9

63

7

3,7

33,5

23

1,9

49,8

55

1,7

83,6

68

322,8

67

1,4

60,8

01

-12,9

89,1

61

8

3,7

70,8

58

1,9

59,0

51

1,8

11,8

07

328,4

94

1,4

83,3

13

-11,5

05,8

49

9

3,8

08,5

66

1,9

68,3

39

1,8

40,2

28

334,1

79

1,5

06,0

49

-9,9

99,8

00

10

3,8

46,6

52

1,9

89,3

78

1,8

57,2

74

337,5

88

1,5

19,6

86

-8,4

80,1

13

11

3,8

85,1

19

1,9

87,1

94

1,8

97,9

24

345,7

18

1,5

52,2

06

-6,9

27,9

07

12

3,9

23,9

70

1,9

96,7

64

1,9

27,2

06

351,5

74

1,5

75,6

32

-5,3

52,2

76

13

3,9

63,2

09

2,0

06,4

29

1,9

56,7

80

357,4

89

1,5

99,2

91

-3,7

52,9

84

14

4,0

02,8

41

2,0

16,1

91

1,9

86,6

51

363,4

63

1,6

23,1

87

-2,1

29,7

97

15

4,0

42,8

70

2,0

37,7

08

2,0

05,1

62

367,1

65

1,6

37,9

96

-491,8

01

16

4,0

83,2

99

2,0

36,0

08

2,0

47,2

90

375,5

91

1,6

71,6

99

1,1

79,8

98

135

Tab

le A

47 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 4

wt%

to 8

5 w

t% (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

4,1

24,1

32

2,0

46,0

66

2,0

78,0

66

381,7

46

1,6

96,3

19

2,8

76,2

18

18

4,1

65,3

73

2,0

56,2

24

2,1

09,1

49

387,9

63

1,7

21,1

86

4,5

97,4

04

19

4,2

07,0

27

2,0

66,4

84

2,1

40,5

43

394,2

42

1,7

46,3

01

6,3

43,7

05

20

4,2

49,0

97

2,0

76,8

46

2,1

72,2

51

400,5

83

9,1

10,2

26

15,4

53,9

31

NP

V

-2

,825,5

01

136

Tab

le A

48 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 6

wt%

to 8

5 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

34,1

35

-

22,7

34,1

35

1

5,2

77,4

82

1,9

18,9

75

3,3

58,5

07

637,8

51

2,7

20,6

57

-20,0

13,4

79

2

5,3

30,2

57

1,9

27,8

64

3,4

02,3

93

646,6

28

2,7

55,7

65

-17,2

57,7

14

3

5,3

83,5

59

1,9

36,8

43

3,4

46,7

17

655,4

93

2,7

91,2

24

-14,4

66,4

90

4

5,4

37,3

95

1,9

45,9

11

3,4

91,4

84

664,4

46

2,8

27,0

38

-11,6

39,4

52

5

5,4

91,7

69

1,9

72,5

35

3,5

19,2

34

669,9

96

2,8

49,2

38

-8,7

90,2

15

6

5,5

46,6

87

1,9

64,3

21

3,5

82,3

66

682,6

22

2,8

99,7

43

-5,8

90,4

71

7

5,6

02,1

53

1,9

73,6

64

3,6

28,4

90

691,8

47

2,9

36,6

42

-2,9

53,8

29

8

5,6

58,1

75

1,9

83,1

00

3,6

75,0

75

701,1

64

2,9

73,9

10

20,0

81

9

5,7

14,7

57

1,9

92,6

31

3,7

22,1

25

710,5

74

3,0

11,5

51

3,0

31,6

32

10

5,7

71,9

04

2,0

19,7

23

3,7

52,1

82

716,5

86

3,0

35,5

96

6,0

67,2

28

11

5,8

29,6

23

2,0

11,9

80

3,8

17,6

43

729,6

78

3,0

87,9

65

9,1

55,1

94

12

5,8

87,9

20

2,0

21,8

00

3,8

66,1

20

739,3

73

3,1

26,7

47

12,2

81,9

40

13

5,9

46,7

99

2,0

31,7

18

3,9

15,0

81

749,1

66

3,1

65,9

16

15,4

47,8

56

14

6,0

06,2

67

2,0

41,7

35

3,9

64,5

32

759,0

56

3,2

05,4

76

18,6

53,3

32

15

6,0

66,3

29

2,0

69,3

17

3,9

97,0

12

765,5

52

3,2

31,4

61

21,8

84,7

93

16

6,1

26,9

93

2,0

62,0

70

4,0

64,9

22

779,1

34

3,2

85,7

89

25,1

70,5

81

137

Tab

le A

49 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 6

wt%

to 8

5 w

t% (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

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ax

C

ash

flo

w

17

6,1

88,2

63

2,0

72,3

91

4,1

15,8

72

789,3

24

3,3

26,5

48

28,4

97,1

29

18

6,2

50,1

45

2,0

82,8

15

4,1

67,3

30

799,6

15

3,3

67,7

15

31,8

64,8

44

19

6,3

12,6

47

2,0

93,3

43

4,2

19,3

04

810,0

10

3,4

09,2

94

35,2

74,1

38

20

6,3

75,7

73

2,1

03,9

76

4,2

71,7

97

820,5

09

10,7

86,3

30

46,0

60,4

69

NP

V

1

4,7

33,8

90

138

Tab

le A

50 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 8

wt%

to 8

5 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

79,6

71

-2

2,7

79,6

71

1

7,0

36,9

63

1,9

41,9

66

5,0

94,9

97

985,0

81

4,1

09,9

16

-18,6

69,7

55

2

7,1

07,3

33

1,9

51,0

76

5,1

56,2

57

997,3

33

4,1

58,9

24

-14,5

10,8

31

3

7,1

78,4

06

1,9

60,2

77

5,2

18,1

29

1,0

09,7

07

4,2

08,4

22

-10,3

02,4

09

4

7,2

50,1

90

1,9

69,5

70

5,2

80,6

21

1,0

22,2

06

4,2

58,4

15

-6,0

43,9

94

5

7,3

22,6

92

2,0

01,6

33

5,3

21,0

59

1,0

30,2

93

4,2

90,7

66

-1,7

53,2

28

6

7,3

95,9

19

1,9

88,4

35

5,4

07,4

84

1,0

47,5

78

4,3

59,9

06

2,6

06,6

78

7

7,4

69,8

78

1,9

98,0

09

5,4

71,8

69

1,0

60,4

55

4,4

11,4

14

7,0

18,0

92

8

7,5

44,5

77

2,0

07,6

79

5,5

36,8

98

1,0

73,4

61

4,4

63,4

37

11,4

81,5

29

9

7,6

20,0

23

2,0

17,4

46

5,6

02,5

77

1,0

86,5

97

4,5

15,9

80

15,9

97,5

09

10

7,6

96,2

23

2,0

49,9

89

5,6

46,2

35

1,0

95,3

28

4,5

50,9

06

20,5

48,4

15

11

7,7

73,1

85

2,0

37,2

74

5,7

35,9

12

1,1

13,2

64

4,6

22,6

48

25,1

71,0

63

12

7,8

50,9

17

2,0

47,3

36

5,8

03,5

81

1,1

26,7

98

4,6

76,7

83

29,8

47,8

47

13

7,9

29,4

26

2,0

57,5

00

5,8

71,9

27

1,1

40,4

67

4,7

31,4

60

34,5

79,3

07

14

8,0

08,7

21

2,0

67,7

65

5,9

40,9

56

1,1

54,2

73

4,7

86,6

83

39,3

65,9

90

15

8,0

88,8

08

2,1

00,8

10

5,9

87,9

98

1,1

63,6

81

4,8

24,3

17

44,1

90,3

07

16

8,1

69,6

96

2,0

88,6

04

6,0

81,0

92

1,1

82,3

00

4,8

98,7

92

49,0

89,0

99

139

Tab

le A

51 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 8

wt%

to 8

5 w

t% (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

8,2

51,3

93

2,0

99,1

80

6,1

52,2

13

1,1

96,5

24

4,9

55,6

89

54,0

44,7

88

18

8,3

33,9

07

2,1

09,8

61

6,2

24,0

45

1,2

10,8

91

5,0

13,1

55

59,0

57,9

43

19

8,4

17,2

46

2,1

20,6

50

6,2

96,5

96

1,2

25,4

01

5,0

71,1

95

64,1

29,1

38

20

8,5

01,4

18

2,1

31,5

47

6,3

69,8

72

1,2

40,0

56

12,4

79,5

50

76,6

08,6

88

NP

V

3

2,2

31,0

73

140

Tab

le A

52 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 4

wt%

to 9

0 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

66,3

23

-

22,7

66,3

23

1

3,5

13,6

31

1,9

03,0

03

1,6

10,6

28

288,2

27

1,3

22,4

01

-21,4

43,9

22

2

3,5

48,7

67

1,9

11,7

26

1,6

37,0

41

293,5

10

1,3

43,5

31

-20,1

00,3

91

3

3,5

84,2

55

1,9

20,5

37

1,6

63,7

18

298,8

45

1,3

64,8

73

-18,7

35,5

17

4

3,6

20,0

97

1,9

29,4

35

1,6

90,6

63

304,2

34

1,3

86,4

29

-17,3

49,0

89

5

3,6

56,2

98

1,9

48,3

73

1,7

07,9

25

307,6

86

1,4

00,2

39

-15,9

48,8

50

6

3,6

92,8

61

1,9

47,4

99

1,7

45,3

62

315,1

74

1,4

30,1

88

-14,5

18,6

61

7

3,7

29,7

90

1,9

56,6

67

1,7

73,1

23

320,7

26

1,4

52,3

97

-13,0

66,2

64

8

3,7

67,0

88

1,9

65,9

27

1,8

01,1

61

326,3

34

1,4

74,8

28

-11,5

91,4

37

9

3,8

04,7

59

1,9

75,2

79

1,8

29,4

80

331,9

97

1,4

97,4

83

-10,0

93,9

54

10

3,8

42,8

06

1,9

94,6

76

1,8

48,1

31

335,7

27

1,5

12,4

03

-8,5

81,5

51

11

3,8

81,2

34

1,9

94,2

65

1,8

86,9

70

343,4

95

1,5

43,4

75

-7,0

38,0

76

12

3,9

20,0

47

2,0

03,9

00

1,9

16,1

47

349,3

31

1,5

66,8

16

-5,4

71,2

60

13

3,9

59,2

47

2,0

13,6

32

1,9

45,6

15

355,2

24

1,5

90,3

91

-3,8

80,8

69

14

3,9

98,8

40

2,0

23,4

61

1,9

75,3

79

361,1

77

1,6

14,2

01

-2,2

66,6

68

15

4,0

38,8

28

2,0

43,3

40

1,9

95,4

88

365,1

99

1,6

30,2

89

-636,3

79

16

4,0

79,2

16

2,0

43,4

16

2,0

35,8

01

373,2

62

1,6

62,5

39

1,0

26,1

60

141

Tab

le A

53 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 4

wt%

to 9

0 w

t% (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

4,1

20,0

09

2,0

53,5

43

2,0

66,4

66

379,3

95

1,6

87,0

71

2,7

13,2

32

18

4,1

61,2

09

2,0

63,7

71

2,0

97,4

38

385,5

89

1,7

11,8

49

4,4

25,0

81

19

4,2

02,8

21

2,0

74,1

02

2,1

28,7

19

391,8

45

1,7

36,8

74

6,1

61,9

55

20

4,2

44,8

49

2,0

84,5

35

2,1

60,3

14

398,1

64

9,1

07,5

77

15,2

69,5

31

NP

V

-2

,942,0

67

142

Tab

le A

54 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 6

wt%

to 9

0 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

89,7

72

-

22,7

89,7

72

1

5,2

78,2

01

1,9

21,1

93

3,3

57,0

08

637,4

68

2,7

19,5

40

-20,0

70,2

32

2

5,3

30,9

83

1,9

30,0

92

3,4

00,8

90

646,2

44

2,7

54,6

46

-17,3

15,5

86

3

5,3

84,2

92

1,9

39,0

81

3,4

45,2

11

655,1

09

2,7

90,1

03

-14,5

25,4

84

4

5,4

38,1

35

1,9

48,1

60

3,4

89,9

76

664,0

62

2,8

25,9

14

-11,6

99,5

70

5

5,4

92,5

17

1,9

72,0

27

3,5

20,4

89

670,1

64

2,8

50,3

25

-8,8

49,2

45

6

5,5

47,4

42

1,9

66,5

90

3,5

80,8

52

682,2

37

2,8

98,6

15

-5,9

50,6

30

7

5,6

02,9

16

1,9

75,9

44

3,6

26,9

72

691,4

61

2,9

35,5

11

-3,0

15,1

19

8

5,6

58,9

45

1,9

85,3

91

3,6

73,5

54

700,7

77

2,9

72,7

77

-42,3

42

9

5,7

15,5

35

1,9

94,9

33

3,7

20,6

02

710,1

87

3,0

10,4

15

2,9

68,0

74

10

5,7

72,6

90

2,0

19,2

68

3,7

53,4

22

716,7

51

3,0

36,6

71

6,0

04,7

45

11

5,8

30,4

17

2,0

14,3

03

3,8

16,1

14

729,2

89

3,0

86,8

24

9,0

91,5

69

12

5,8

88,7

21

2,0

24,1

34

3,8

64,5

87

738,9

84

3,1

25,6

03

12,2

17,1

73

13

5,9

47,6

09

2,0

34,0

63

3,9

13,5

45

748,7

75

3,1

64,7

70

15,3

81,9

42

14

6,0

07,0

85

2,0

44,0

92

3,9

62,9

93

758,6

65

3,2

04,3

28

18,5

86,2

70

15

6,0

67,1

55

2,0

68,9

19

3,9

98,2

37

765,7

14

3,2

32,5

23

21,8

18,7

93

16

6,1

27,8

27

2,0

64,4

51

4,0

63,3

76

778,7

42

3,2

84,6

35

25,1

03,4

28

143

Tab

le A

55 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 6

wt%

to 9

0 w

t% (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

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Inco

me

bef

ore

tax

T

ax

In

com

e aft

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ax

C

ash

flo

w

17

6,1

89,1

05

2,0

74,7

83

4,1

14,3

22

788,9

31

3,3

25,3

91

28,4

28,8

19

18

6,2

50,9

96

2,0

85,2

18

4,1

65,7

78

799,2

22

3,3

66,5

56

31,7

95,3

75

19

6,3

13,5

06

2,0

95,7

58

4,2

17,7

48

809,6

16

3,4

08,1

32

35,2

03,5

07

20

6,3

76,6

41

2,1

06,4

04

4,2

70,2

38

820,1

14

10,8

03,1

17

46,0

06,6

23

NP

V

1

4,6

74,7

17

144

Tab

le A

56 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 8

wt%

to 9

0 w

t%

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

0

2

2,7

98,0

42

-

22,7

98,0

42

1

7,0

31,1

00

1,9

35,5

89

5,0

95,5

11

985,1

56

4,1

10,3

55

-18,6

87,6

87

2

7,1

01,4

11

1,9

44,6

31

5,1

56,7

80

997,4

10

4,1

59,3

70

-14,5

28,3

17

3

7,1

72,4

25

1,9

53,7

64

5,2

18,6

62

1,0

09,7

86

4,2

08,8

75

-10,3

19,4

42

4

7,2

44,1

50

1,9

62,9

87

5,2

81,1

62

1,0

22,2

87

4,2

58,8

76

-6,0

60,5

66

5

7,3

16,5

91

1,9

92,4

60

5,3

24,1

31

1,0

30,8

80

4,2

93,2

51

-1,7

67,3

15

6

7,3

89,7

57

1,9

81,7

12

5,4

08,0

45

1,0

47,6

63

4,3

60,3

82

2,5

93,0

66

7

7,4

63,6

55

1,9

91,2

15

5,4

72,4

39

1,0

60,5

42

4,4

11,8

97

7,0

04,9

64

8

7,5

38,2

91

2,0

00,8

13

5,5

37,4

78

1,0

73,5

50

4,4

63,9

28

11,4

68,8

92

9

7,6

13,6

74

2,0

10,5

08

5,6

03,1

67

1,0

86,6

87

4,5

16,4

79

15,9

85,3

71

10

7,6

89,8

11

2,0

40,4

55

5,6

49,3

55

1,0

95,9

25

4,5

53,4

30

20,5

38,8

01

11

7,7

66,7

09

2,0

30,1

88

5,7

36,5

21

1,1

13,3

58

4,6

23,1

63

25,1

61,9

64

12

7,8

44,3

76

2,0

40,1

75

5,8

04,2

01

1,1

26,8

94

4,6

77,3

06

29,8

39,2

71

13

7,9

22,8

20

2,0

50,2

63

5,8

72,5

57

1,1

40,5

65

4,7

31,9

91

34,5

71,2

62

14

8,0

02,0

48

2,0

60,4

52

5,9

41,5

96

1,1

54,3

73

4,7

87,2

23

39,3

58,4

85

15

8,0

82,0

68

2,0

90,8

99

5,9

91,1

69

1,1

64,2

88

4,8

26,8

81

44,1

85,3

66

16

8,1

62,8

89

2,0

81,1

36

6,0

81,7

53

1,1

82,4

05

4,8

99,3

49

49,0

84,7

14

145

Tab

le A

57 A

nnual

cas

h f

low

and n

et p

rese

nt

val

ue

for

dis

till

atio

n 8

wt%

to 9

0 w

t% (

conti

nues

)

Yea

rs

Rev

enu

e

Exp

end

itu

re

Inco

me

bef

ore

tax

T

ax

In

com

e aft

er t

ax

C

ash

flo

w

17

8,2

44,5

18

2,0

91,6

33

6,1

52,8

85

1,1

96,6

31

4,9

56,2

54

54,0

40,9

68

18

8,3

26,9

63

2,1

02,2

35

6,2

24,7

28

1,2

11,0

00

5,0

13,7

28

59,0

54,6

96

19

8,4

10,2

33

2,1

12,9

44

6,2

97,2

89

1,2

25,5

12

5,0

71,7

77

64,1

26,4

74

20

8,4

94,3

35

2,1

23,7

59

6,3

70,5

76

1,2

40,1

69

12,4

86,0

68

76,6

12,5

42

NP

V

3

2,2

23,9

88

CURRICULU M VITAE

CURRICULUM VITAE

NAME Monsikan Vilaipan

DATE OF BIRTH 18 July 1996

BIRTH PLACE Mahasarakam province

ADDRESS 64 Village no. 6, Udon-Nongkai Road, Kudsa Sub-district,

Mueang District, Udonthani

EDUCATION 2018 B.Eng (Industrial engineering-Logistic), Kasetsart

University Kamphaeng Saen, Nakhon pathom

SCHOLARSHIP Faculty of Engineering, Kasetsart University

Thailand Advanced Institute of Science and

Technology and Tokyo Institute of

Technology (TAIST TokyoTech)

National Science and Technology

Development Agency (NSTDA)

techno-economic for bioethanol from lignocellulosic

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