evaluation of a gas refinery using exergy-based methods · evaluation of a gas refinery using...

Evaluation of a gas refinery using exergy-based methods

vorgelegt von M. Sc.

Mehrnoosh Sarcheshmehpoor

von der Fakultät III – Prozesswissenschaften der Technischen Universität Berlin

zur Erlangung des akademischen Grades

Doktor der Ingenieurwissenschaften -Dr.-Ing.-

genehmigte Dissertation

Promotionsausschuss

Vorsitzender: Gutachterin: Gutachter:

Prof. Dr. Aleksander Gurlo Prof. Dr. Tetyana Morozyuk Prof. Dr. Predrag Raskovic

Tag der wissenschaftlichen Aussprache: 27. März 2019

Berlin 2019

Dedicated to

the pure sole of my father for all his love and kindness and

to my lovely mother for all her sacrifices

ACKNOWLEDGMENT

This work has been done in institute of energy engineering and environment protection at

the Technical university of Berlin. Finishing my thesis, I would like to take this opportunity

to express my deep gratitude to all the people that helped, supported and encouraged me

to finish this work.

I would like to express my sincere appreciation and gratitude to my supervisor, Professor

Tetyana Morozyuk who with her valuable knowledge, great guidance skills and her positive

energy supported me to complete my work. Without her great and excellent support,

completing this thesis was not possible. You create hope in my life, Thank you!

I am also deeply thankful to Professor George Tsatsaronis for his precious knowledge, time

and patience to provide me several sessions of fruitful technical discussions. His

remarkable encouragements will never be forgotten.

Furthermore, Professor Gurlo is highly appreciated for his willingness to chair my defense.

I would like to extend my sincere gratitude to my external examiner Professor Predrag

Raskovic for reviewing my thesis and for his precise and useful advices. I deeply thank him

for his kind cooperation and his valuable time to help me to improve my thesis.

I thank my colleague in institute of energy engineering, Mathias Penkuhn for answering my

question at any time.

I would like to appreciate several friends that helped me and supported me in any way that

they could do it: My oldest friend; Naghmeh Babaalizadeh, my supportive and kind

neighbor; Farzaneh, my lovely friends; Anne-Lise Papillon, Valérie Faure and her husband

Bernhard, Asal Mansouri and her husband Amirhossein, George Saade and my youngest

friend Joy Nader.

This work was not possible without the support and accompanying of my lovely husband,

Athanasios. Your sacrifices, supporting and encouragement have been the most important

and powerful motivator to my work. I would like to express my honest and eternal

gratitude towards you for your understanding, help and patience during the last years. I

i

never forget your encouragement and strong back at all levels. There is no word to say for

all your kindness except that: You are the loveliest!

Lastly but not least, I would dedicate my special thanks to my beloved parents, My father,

Hossein for encouraging and giving hope to me always and my mother, Zari, without her

sacrifices, I could not be in this position that I am today. My beautiful sisters; Mahnaz and

Mojdeh, my lovely brother; Mohsen, and my little niece; Raha, thank you all for your

encouragements and your jokes to make me laugh during my challenging time. When it

comes to family, hardly I find words to express my feelings. I love you all!!!

At the end, I wish for my beautiful and blessed country, Iran to stand again from his ashes.

ABSTRACT Processing of natural gas as one of the main resources of energy has been always in the

center of focus to boost production of high commercial value products such as ethane,

propane, butane and condensate for different applications. In this work, some operation

units of a natural gas refinery are assessed based on thermodynamic efficiency and

economic feasibility and from environmental impacts point of view.

Exergy analysis is used for evaluation of considered gas refinery in some major units of

operation such as condensate stabilization, dehydration and mercury guard, ethane

recovery unit, NGL fractionation unit, propane refrigeration, export gas compression unit

and sour water treatment unit. Other units of operation have been considered as black

boxes and only the interactions with the main units have been taken into account. The aim

of this study is to improve the process by identifying the location and magnitude of

thermodynamic inefficiencies in studied gas refinery and by making appropriate actions for

improvement.

In addition, to have a more precise evaluation; an economic analysis has been conducted

and the results has been combined with exergy analysis. This methodology known as -

Exergoeconomic analysis - reveals equipment with highest priority of improvement,

considering a trade-off between thermodynamic inefficiencies and cost of equipment. In

addition to exergoeconomic analysis, the plant has been also evaluated by exergoeconomic

diagnostic to reveal the influential components for replacement after the calculated life

time of the plant.

In analogy with exergoeconomic, the plant also has been assessed by exergoenvironmental

analysis and results associated with environmental impacts obtained.

Lastly, the most influential components in the system based on highest rate of exergy

destruction have been selected and analyzed with advanced exergy-based analyses.

Among examined components, obtained results from exergoeconomic show dryers’

regeneration furnace (104-H1) and second stage refrigerant compressor (111-K6) total

iv

cost is related to exergy destruction and require improvement by reducing the destructed

exergy costing which lead to apply better process design or technology. On the other hand,

export gas compressor (106-K7), and depropanizer column (107-C4) could be improved by

using a moderate technology to reduce the equipment cost rate.

The results obtained from exergoeconomic diagnostic urge the system, to replace the

dryers’ regeneration furnace (104-H1) and export gas compressor (106-K7), as the cost of

destruction is quiet high in these components. In addition, the results of

exergoenvironmental analysis, shows that dryers’ regeneration furnace (104-H1) and

export gas compressor (106-K7) are the main contributors to the environmental impacts of

exergy destruction. Therefore, by applying better technology margins, the corresponding

environmental impact is reduced.

Lastly, the advanced exergy-based analyses results show that among analyzed components,

treated gas compressor (105-K4), export gas compressor (106-K7) and cold box (105-E8)

have the highest rate of avoidable exergy destruction and corresponding cost and

environmental impacts, which can influence the overall system efficiency from

thermodynamic and cost and environmental concerns.

Table of Contents

1 Introduction ........................................................................................................................................................ 1

1.1 Natural gas overview .............................................................................................................................. 1

1.2 Natural gas processing plants ............................................................................................................. 8

1.3 Thesis outlines ....................................................................................................................................... 11 2 State of the art ................................................................................................................................................. 14 3 Methodology of exergy-based analyses ................................................................................................. 38

3.1 Exergy analysis ...................................................................................................................................... 39

3.1.1 Exergy............................................................................................................................................... 39

3.1.2 Conventional exergy analysis ................................................................................................. 41

3.2 Exergy and economics ......................................................................................................................... 43

3.2.1 Economic analysis ....................................................................................................................... 43

3.2.2 Exergoeconomic analysis ......................................................................................................... 48

3.2.3 Exergoeconomic diagnostic ..................................................................................................... 51

3.3 Exergy and environmental impacts ............................................................................................... 53

3.3.1 Life Cycle Assessment (LCA) ................................................................................................... 53

3.3.2 Exergoenvironmental analysis ............................................................................................... 55

3.4 Advanced exergy-based analyses ................................................................................................... 58

3.4.1 Advanced exergy analysis ........................................................................................................ 58

3.4.2 Advanced exergoeconomic analysis ..................................................................................... 59

3.4.3 Advanced exergoenvironmental analysis .......................................................................... 59 4 Process description and simulation ........................................................................................................ 61

4.1 Introduction ............................................................................................................................................ 61

4.1.1 Gas processing units ................................................................................................................... 64

4.1.2 Hydrocarbon Liquid processing units ................................................................................. 68

4.2 Process simulation and assumptions ............................................................................................ 70

4.2.1 Applied software for simulation ............................................................................................ 70 5 Application of exergy-based analyses to the plant ............................................................................ 73

5.1 Exergy analysis ...................................................................................................................................... 73

5.2 Economic analysis................................................................................................................................. 74

5.2.1 Total capital investment (TCI) estimation ......................................................................... 74

5.2.2 Total revenue requirement (TRR) estimation ................................................................. 77

vi

5.3 Exergoeconomic analysis ................................................................................................................... 78

5.4 Exergoeconomic diagnostic .............................................................................................................. 79

5.5 Exergoenvironmental analysis ........................................................................................................ 80

5.6 Advanced exergy-based analysis for selected components ................................................. 80 6 Results and discussions ............................................................................................................................... 83

6.1 Results of conventional exergy analysis ...................................................................................... 83

6.2 Results of economic analysis ............................................................................................................ 87

6.3 Results of exergoeconomic analysis .............................................................................................. 91

6.4 Results of exergoeconomic diagnostic .......................................................................................... 95

6.5 Results of exergoenvironmental analysis .................................................................................... 96

6.6 Results of advanced exergy-based analysis ................................................................................ 97 7 Summary and conclusions ........................................................................................................................ 107

7.1 Conventional exergy analysis ......................................................................................................... 107

7.2 Economic and exergoeconomic analysis ................................................................................... 108

7.3 Exergoeconomic diagnostic ............................................................................................................ 108

7.4 Exergoenvironmental analysis ...................................................................................................... 109

7.5 Advanced exergy-based analysis .................................................................................................. 109

7.6 Summary of the future work .......................................................................................................... 109 References .......................................................................................................................................................... 113 APPENDIX A-Equipment list and process flow diagrams ................................................................ 126

A.1 Equipment list ...................................................................................................................................... 126

A.2 Process flow diagrams ...................................................................................................................... 128 APPENDIX B-Detail Stream information ................................................................................................. 138 APEENDIX C-Purchased Equipment Costs (PEC) estimation ......................................................... 171

C.1 Pumps ...................................................................................................................................................... 171

C.2 Compressors ......................................................................................................................................... 172

C.3 Air coolers .............................................................................................................................................. 173

C.3.1 Estimation of required shaft power for air coolers ...................................................... 177

C.4 Furnace ................................................................................................................................................... 178

C.5 Slug catcher ........................................................................................................................................... 179

C.6 Separators .............................................................................................................................................. 179

C.6.1 Vessel sizing ................................................................................................................................. 179

C.6.2 Estimation of purchased cost ................................................................................................ 183

C.7 Heat exchangers .................................................................................................................................. 184

C.7.1 Heat exchanger sizing .............................................................................................................. 184

C.7.2 Estimation of purchased cost ................................................................................................ 185

C.8 Columns .................................................................................................................................................. 185

C.8.1 Sizing of columns ....................................................................................................................... 186

C.8.2 Sizing of columns heat exchangers ..................................................................................... 187

C.8.3 Estimation of purchased cost of columns ........................................................................ 190

C.9 Dryers and Mercury Guard.............................................................................................................. 193

C.10 “Black boxes” units .......................................................................................................................... 195

C.11 Summary of PEC estimation ......................................................................................................... 196

APPENDIX D-Stream cost information .............................................................................................. 204

List of Figures Fig. 1.1 Gas consumption by sector ................................................................................................................ 3 Fig. 1.2 Fuel shares of electricity generation (1973-2014) .................................................................. 4 Fig. 1.3 Distribution of proved reserves in 1996, 2006 and 2016-Percentage ............................. 5 Fig. 1.4 Natural gas production by region (billion cubic meters) ...................................................... 6 Fig. 1.5 United States energy consumption by fuel .................................................................................. 7 Fig. 1.6 Average wholesale Natural Gas prices by region 2016 .......................................................... 8 Fig. 3.1 General structure of the Eco-indicator 99 ................................................................................ 54 Fig. 4.1 Block flow diagram of a typical gas refinery ............................................................................ 63 Fig. 6.1 Overview of exergy destruction within plant .......................................................................... 84 Fig. 6.2 Exergy destruction within productive components ............................................................. 85 Fig. 6.3 Exergy destruction within units ................................................................................................... 86 Fig. 6.4 Exergy destruction within dissipative components ............................................................. 87 Fig. 6.5 Overview of cost rate values .......................................................................................................... 88 Fig. 6.6 Cost rates distribution in productive components................................................................ 89 Fig. 6.7 Cost rates distribution in units...................................................................................................... 90 Fig. 6.8 Cost rates distribution in dissipative components ................................................................ 90 Fig. 6.9 Cost rate of exergy destruction for productive components ............................................. 93 Fig. 6.10 (CD,K+ZK)Values for productive components ......................................................................... 94 Fig. 6.11 Exergy destruction cost rate of productive components(Exergoeconomic

diagnostic) ................................................................................................................................................... 96 Fig. 6.12 Exergy destruction environmental impact rate of productive components ........... 97 Fig. 6.13 Avoidable and unavoidable exergy destruction in selected components (best case

scenario, if applicable) ............................................................................................................................ 98 Fig. 6.14 Avoidable and unavoidable exergy destruction in selected components (worst

case scenario, if applicable) ................................................................................................................ 100 Fig. 6.15 Avoidable and unavoidable cost rate of exergy destruction within selected

productive components (best case scenario, if applicable) ................................................... 101 Fig. 6.16 Avoidable and unavoidable cost rate of exergy destruction within selected

productive components (worst case scenario, if applicable) ................................................ 102 Fig. 6.17 Environmental impact rate of exergy destruction (best case scenario) .................. 103 Fig. 6.18 Environmental impact rate of exergy destruction (worst case scenario) ............... 105 Fig. A.1 Overall Process Flow Diagram of studied gas refinery...................................................... 128 Fig. A.2 Process flow diagram for receiving facilities and gas treatment black box (Unit 100

&101) .......................................................................................................................................................... 129

ix

Fig. A.3 Process flow diagram for condensate stabilization (Unit 103) ...................................... 130 Fig. A.4 Process flow diagram for dehydration and mercury guard (Unit 104) ...................... 131 Fig. A.5 Process flow diagram for ethane extraction (Unit 105) ................................................... 132 Fig. A.6 Process flow diagram for NGL fractionation (Unit 107) ................................................... 133 Fig. A.7 Process flow diagram for sales gas compression (Unit 106) .......................................... 134 Fig. A.8 Process flow diagram for propane refrigeration cycle (Unit 111) ............................... 135 Fig. A.9 Process flow diagram for sour water treatment (Unit 109) ........................................... 136 Fig. A.10 Process flow diagram for black box units; propane, butane and ethane treatment

and drying (Units 114/115/116) ..................................................................................................... 137 Fig. C.1 Optimum bundle depth .................................................................................................................. 174 Fig. C.2 Surface per fan horse power ........................................................................................................ 177 Fig. C.3 Design vapor velocity factor for vertical vapor-liquid separators ................................ 180

x

List of Tables Table 3.1 Breakdown of Total Capital Investment (TCI) .................................................................... 44 Table 4.1 Feed gas composition ................................................................................................................... 61 Table 4.2 Products composition ................................................................................................................... 61 Table 4.3 Non-conventional components properties .......................................................................... 71 Table 5.1 Parameters and initial assumptions used in economic analysis ................................. 76 Table 7.1 The four most influential components as ranked by each analysis .......................... 107 Table A.1 Equipment list and assigned tag numbers ......................................................................... 126 Table B.1 Streams data .................................................................................................................................. 138 Table B.2 Definition of the exergy of fuel and exergy of product at component level .......... 155 Table B.3 Cost balances and auxiliary equations ................................................................................. 160 Table B.4 Results of conventional exergy and exergoeconomic for productive components

....................................................................................................................................................................... 164 Table B.5 Results of Diagnostic exergoeconomic for productive components ....................... 167 Table B.6 Results of exergoenvironmental for productive components .................................... 168 Table B.7 Results of advanced exergy-based analyses for selected compressors .................. 169 Table B.8 Results of advanced exergy-based analyses for selected productive components

....................................................................................................................................................................... 169 Table B.9 Results of advanced exergy-based analyses for selected units .................................. 169 Table B.10 Results of advanced exergy analysis for selected dissipative components ........ 170 Table C.1 Purchased cost of pumps .......................................................................................................... 172 Table C.2 Purchased cost of compressors .............................................................................................. 173 Table C.3 Estimating factors- 1” outer diameter tube × 2 3/8” triangular spacing ............... 174 Table C.4 Purchased equipment cost of air coolers ............................................................................ 175 Table C.5 Estimation of outlet air temperature in air coolers (British units) .......................... 176 Table C.6 Estimation of heat transfer area in air coolers ................................................................. 176 Table C.7 Estimation of required fan power for air coolers ............................................................ 177 Table C.8 Estimation of air mass flow rate for air coolers ............................................................... 178 Table C.9 Purchased cost of fired heater ................................................................................................ 179 Table C.10 Purchased cost of Slug catcher, ............................................................................................ 179 Table C.11 Sizing of vertical vessels ......................................................................................................... 182 Table C.12 Sizing of horizontal vessels .................................................................................................... 182 Table C.13 Purchased cost of vessels ....................................................................................................... 183 Table C.14 Calculated area of heat exchangers .................................................................................... 184 Table C.15 Calculated area of Cold box .................................................................................................... 185 Table C.16 Purchased cost of heat exchangers ..................................................................................... 185 Table C.17 DSTWU calculation methods ................................................................................................. 186

xi

Table C.18 Estimation of columns’ specifications ............................................................................... 187 Table C.19 Estimation of reboilers’ area ................................................................................................. 188 Table C.20 Estimation of deethanizer’s condenser area ................................................................... 188 Table C.21 Estimation of outlet air temperature in air cooled columns’ condensers (British

units) ........................................................................................................................................................... 189 Table C.22 Estimation of heat transfer area in air cooled columns’ condensers (SI units) 189 Table C.23 Purchased cost of columns (without accessories) ........................................................ 191 Table C.24 Purchased equipment cost of columns’ trays ................................................................. 191 Table C.25 Purchased equipment cost of columns’ air-cooled condensers .............................. 192 Table C.26 Purchased equipment cost of columns’ reboilers ......................................................... 192 Table C.27 Purchased cost of columns (including all accessories) ............................................... 193 Table C.28 Sizing of packed towers ........................................................................................................... 194 Table C.29 Purchased cost of packed towers (without absorbent) .............................................. 194 Table C.30 Purchased cost of absorbents ............................................................................................... 195 Table C.31 Purchased cost of towers (including absorbent) .......................................................... 195 Table C.32 Purchased cost of “black boxes”........................................................................................... 196 Table C.33 Purchased cost of “black box” gas sweetening unit...................................................... 196 Table C.34 Purchased equipment costs (PEC) ...................................................................................... 197 Table C.35 Assumptions and detail information for (TCI) estimation ........................................ 199 Table C.36 Estimation of TCI ....................................................................................................................... 200 Table C.37 Estimation of Total Revenue Requirement (TRR) ........................................................ 201 Table C.38 Estimation of cost rates ........................................................................................................... 202 Table C.39 Estimation of cost rates (cont.) ............................................................................................ 203 Table D.1 Streams cost rates data of exergoeconomic analysis ..................................................... 204 Table D.2 Streams cost rates data of exergoeconomic analysis (cont.) ...................................... 205 Table D.3 Stream cost rates data for exergoeconomic diagnostic ................................................ 206 Table D.4 Stream cost rates data for exergoeconomic diagnostic (cont.) .................................. 207 Table D.5 Impact rate of streams for exergoenvironmental analysis .......................................... 208 Table D.6 Impact rate of streams for exergoenvironmental analysis (cont.) ........................... 209

xii

Nomenclature A - area, m2 b - environmental impact per unit of exergy, Pts J-1

�� - environmental impact rate associated with exergy stream, Pts hr-1

c - cost per unit of exergy, $ J-1

cp - specific heat capacity at constant pressure, J kg−1 K−1 𝐶 - cost, $ �� - cost rate associated with an exergy stream, $ hr-1

D - diameter, m e - mass-specific exergy, J kg-1 �� - mole-specific exergy, kJ kmol−1 �� - exergy flow rate, MW ��D - rate of exergy destruction, MW ��L - rate of exergy loss, MW

f - factor, - g - constant, - h - mass-specific enthalpy, kJ kg−1

ieff - effective interest rate, - I - irreversibility, J k - constant, - L - characteristic length, m 𝑚 - mass, kg �� - mass flow rate, kg s-1 𝑁 - number of exergy streams, -

p - pressure, bar

�� - heat flow rate, W r - relative cost difference, - rb - relative environmental impact difference, - rFC - annual escalation rate for fuel cost, % 𝑅� - universal gas constant, kJ kmol−1 K−1 s - mass-specific entropy, kJ kg−1 K-1

xiii

T - temperature;

thermodynamic temperature, K; Celsius temperature, °C

u - speed, m s−1 U - overall coefficient of heat transfer, W m-2 K-1 �� - volume flow rate, m3 s-1 V - volume, m3 �� - mechanical or electrical power, J s-1 x - mole fraction, - xvap - vapor fraction, - X - variable expressing capacity or size of a component, - yD - exergy destruction ratio, % �� - component-related environmental impact rate, Pts hr-1 �� - cost rate associated with capital investment, $ hr-1

Abbreviation

AFUDC - Allowance for Funds Used During Construction bcm - billion cubic meters bcf/d - billion cubic meters per day CC - Carrying Charges CCS - Carbon Capture and Storage CELF - Constant Escalation Levelization Factor CEPCI - Chemical Engineering Plant Cost Index CRF - Capital Recovery Factor CNG - Compressed Natural Gas DC - Direct Costs EES - Engineering Equation Solver EIA - Energy Information Administration ELCA - Exergetic Life Cycle Assessment FA - Face Area FC - Fuel Cost FCI - Fixed Capital Investment FPSO - Floating Production Storage and Offload FV - Face Velocity IC - Indirect Costs

xiv

IEA - International Energy Agency IGCC - Integrated Gasification Combined Cycle HHV - Higher Heating Value HP - High Pressure LCA - Life Cycle Assessment LHV - Lower Heating Value LMTD - Log Mean Temperature Differences LNG - Liquefied Natural Gas LP - Low Pressure LPG - Liquefied Petroleum Gas MDEA - Monodethanolamine MEG - Monoethylene Glycol NG - Natural Gas NGL - Natural Gas Liquids NGV - Natural Gas Vehicles OFSC - Offsite Costs OMC - Operating and Maintenance Costs ONSC - Onsite Costs PEC - Purchased Equipment Cost PFBC - Pressurised Fluidised Bed Combustion PFI - Plant Facility Investment RVP - Reid Vapor Pressure SUC - Startup Costs SUR - Surface area TCI - Total Capital Investment TRR - Total Revenue Requirement USD - United States Dollar WC - Working Capital yr - year Greek Symbols α - capacity exponent, - D - increment, - ε - exergy efficiency, %

xv

k - unit exergy consumption, -

ρ - mass density, kg m−3 τ - annual operating hours, hr Subscripts (⋅)0 - conditions of the thermodynamic environment

(⋅)air - air (⋅)B - base cost (⋅)BM - bare module cost (⋅)b - exergoenvironmental factor (⋅)bt - bare tube (⋅)c - cold (⋅)Coll Y - collected year (⋅)d - design factor (⋅)diss - dissipative component (⋅)F - fuel (⋅)FC - fuel cost (⋅)FG - fuel gas (⋅)h - hot (⋅)i - index of numbering (⋅)in - inlet (⋅)j - j-th material stream (⋅)k - k-th component (⋅)L - levelized cost (⋅)Liq - liquid (⋅)OMC - operating and maintenance cost (⋅)out - outlet (⋅)m - material factor (⋅)mix gas - mixed ideal gases (⋅)n - plant economic life (⋅)NG - Natural Gas (⋅)p - pressure factor (⋅)P - product

xvi

(⋅)PEC - purchased equipment cost (⋅)PR - process fluid (⋅)q - specific cost of heat of low pressure/high pressure steam (⋅)Q - exergy of heat (⋅)Ref Y - reference year (⋅)T - temperature factor (⋅)tot - total system (⋅)V - vapor (⋅)vap max - maximum vapor velocity (⋅)w - electricity Superscripts (⋅)AV - avoidable exergy (⋅)CH - chemical exergy (⋅)n - plant economic life (⋅)PF - Pollutant Formation (⋅)PH - physical exergy (⋅)real - real status (⋅)tot - total system (⋅)UN - unavoidable exergy

xvii

CHAPTER 1

1 Introduction

1.1 Natural gas overview

Natural gas is the gas obtained from natural underground reservoirs either as free gas or

gas associated with crude oil. It generally contains large amounts of methane (CH4) along

with other hydrocarbons. Impurities such as H2S, N2, and CO2 are often found with the gas.

Generally it also comes saturated with water vapor [1].

Natural gas is the number three fuel, reflecting 24 % of global primary energy and it is the

most energy-efficient fossil fuel; it offers important energy-saving benefits when it is used

instead of oil or coal. Although the primary use of natural gas is as a fuel, it is also a source

of hydrocarbons for petrochemical feedstock. Its popularity as an energy source is expected

to grow substantially in the future because natural gas can help achieve two important

energy goals for the twenty-first century: providing the sustainable energy supplies and

services needed for social and economic development and reducing adverse impacts on

global climate and the environment. It is good to know that Carbon Dioxide, the greenhouse

gas linked to global warming, is produced from oil and coal at a rate approximately 1.4 to

1.75 times higher than production from natural gas. Moreover, both oil and coal contain

Nitrogen compounds which are not present in natural gas in large amount. Nitrogen Oxides

(NOx), as other greenhouse gases which are formed from burning natural gas, are

approximately 20 % of those produced when oil or coal is burned. Emerging innovative

technologies in gas sector could give the possibility to position itself as a renewable energy

and dramatically change the role of gas in the energy transition. It should be added that

there is significant downside risk for gas if it doesn’t succeed to innovate and develop new

technologies making it “cleaner” and increasingly “renewable”. The share of gas in power

generation would especially be at risk in the absence of commercially viable Carbon

Capture and Storage (CCS) and the economic viability of new technologies like biogas or

power to gas is a challenge for gas evolving towards a renewable energy source. Actually,

the potential of biogas remains significant but there are technical and economic barriers.

1

Chapter 1- Introduction

Nevertheless, the experience of Germany with nearly 2,000 projects shows that biogas

cannot be written off [2-4].

Natural gas is used extensively in residential, commercial, industrial and power generation

applications. The industrial sector uses natural gas as a source of process heat, as a fuel for

the generation of steam and as a feedstock in the production of petrochemicals and

fertilizers. The electric power generation sector also uses natural gas to produce electricity.

Natural gas is also used as an alternative fuel in the transportation sector. Natural gas,

which has been used to fuel vehicles since the 1930's, is increasingly popular as a vehicle

fuel. Most Natural Gas Vehicles (NGVs) operate using Compressed Natural Gas (CNG)

or Liquefied Natural Gas (LNG). CNG is more popular in light-duty passenger vehicles,

while LNG is favored in heavy-duty applications such as transit buses or locomotives.

Natural gas is also used by the natural gas industry itself. For example, producers use

Natural gas as a fuel in processing facilities, while pipeline companies use natural gas to

fuel the compressors which push the natural gas along the pipeline [5].

Fig. 1.1 shows the share of gas consumption by different sectors. As it is clear; the largest

contribution to consumption growth comes from the industrial sector followed by power.

This growth continues with the same trend till 2035.

2


Fig. 1.1 Gas consumption by sector [6]

According to World Energy Council report; natural gas is the second energy source in

power generation, representing a 22 % share in 2014 [4]. International Energy Agency

made a comparison of using natural gas in producing electricity in 1973 and 2014 which is

shown in Fig. 1.2:

3


Fig. 1.2 Fuel shares of electricity generation (1973-2014) [7]

As can be seen from Fig. 1.2, Natural Gas consumption in electricity generation has been

increased by 78 % in last decades. Moreover, it is predicted that Natural Gas will continue

to increase its share of the global energy mix, growing at 2 % per year until 2020 and

continuing expansion of supplies of Liquefied Natural Gas (LNG), increasing the availability

of gas globally [6, 7].

It should be mentioned that the role of gas will be closely linked with developments in the

power. Global electricity demand is expected to double by 2060 and the power sector offers

the highest growth potential for natural gas. An increasing market share in power

generation will be the main driver of gas demand growth [8].

Proved natural gas reserves were estimated in 2016 to be around 186.6 trillion cubic

meters, a 33.8 % and 15.2 % increase over 1996 and 2006 levels, respectively. The

distribution of proved natural gas reserves in 1996, 2006 and 2016 has been shown in Fig.

1.3 As it is indicated in this graph, global proved gas reserves in 2016 raised slightly

comparing 1996 and 2006. In addition, by region, the Middle East holds the largest proved

reserves (42.5 % of the global total). A majority of these proved reserves are in Iran, Russia

and Qatar, with 18 %, 17.3 % and 13 % of total world reserves, respectively [9].

4


Fig. 1.3 Distribution of proved reserves in 1996, 2006 and 2016-Percentage [9]

Natural gas reserves face even less risk, as demand in 2040 is expected to increase

comparing the demand in 2016 under the “2 °C Scenarios of global warming” [10].

On the other hand, according to World Energy Resources report in 2016, natural gas

production grew at an average rate of 3.3 % per annum. from 2009-2013, however with the

collapse in oil and gas prices in the last half of 2014, production growth has slowed,

reaching a 2.2 % increase over 2014 production levels [4].

However, according to British Petroleum latest report published in 2017, the largest

producers of natural gas globally are United States, Russia, Iran, Qatar and Canada with

(21.1 %), (16.3 %), (5.7 %), (5.1 %) and (4.3 %) of world total production, respectively.

Fig. 1.4 provides an overview of natural gas production worldwide by region in 1991-2016.

As it is shown in this figure, North America and Europe/Eurasia have the highest

contribution in natural gas production [9].

5


Fig. 1.4 Natural gas production by region (billion cubic meters) [9]

Regarding the market of natural gas, it should be mentioned that natural gas markets have

historically operated in three major regional markets: North America, Europe and Asia.

This market structure was driven by the regional pipeline trade, which reflects more than

90 % of global natural gas trade. North America is both a large consumer and producer of

natural gas, and is dominated by United States supply and demand dynamics. The United

States is currently the world’s largest producer and consumer of natural gas globally [11].

As the major consumer of natural gas, it is good to know that natural gas plays an

extremely important role in the United States and accounts for approximately 23 % of the

total energy used. Fig. 1.5 shows the relationship among energy sources in the United

States, as well as projected growth through 2025. As indicated in graphs, gas is presently

second only to petroleum, and the difference in demand for gas over coal is expected to

increase substantially with time. Of interest is the prediction that energy from nuclear and

hydroelectric sources will be flat, and non-hydroelectric renewable are not expected to

play a significant role through 2025 [3].

6


Fig. 1. 5 United States energy consumption by fuel [3]

On the other hand, natural gas market in Europe characterized by both intra-regional

supplies (~40 %) and substantial imports of pipeline gas and LNG (~60 %). Europe was

the world’s top interregional natural gas importer in 2014. More than 60 % of all imported

gas came from Russia via pipeline and 73 % of LNG imports were imported from Algeria

and Qatar [11]. Moreover, European Union demand for natural gas and therefore

dependence on the imported sources is set to rise. According to International Energy

Agency (IEA), by 2035 the European Union’s primary natural gas demand may rise by

almost 20 % compared to demand 2008 [7]. Natural gas contributed to 14 % of the

production of primary energy in the European Union in 2015 [12]. Lastly, Asia has

historically relied on oil and coal for energy, but in recent years, it has become the

dominant LNG importing region, accounting for (~75 %) of all LNG imports in 2014 [11]. It

is the matter of interest to know that based on categorizing by country, United States,

Russia, China and Iran with (22 %), (11 %), (5.9 %) and (5.7 %) of total world consumption

of 3543 bcm, include the highest consumption rate of natural gas in 2016 [9].

7


As a result of the regional nature of global natural gas markets, there is wide difference in

wholesale natural gas prices across regions, with importing regions, especially Asia Pacific

and Europe, paying higher prices than resource rich regions as indicated in Fig. 1.6:

Fig. 1.6 Average wholesale Natural Gas prices by region 2016 [13]

Wholesale prices can obviously vary significantly from year to year, but both Asia and Asia

Pacific had average prices around 6 $. Prices in Europe, which has the next largely share,

were almost 1 $ lower than in the Asian regions. Prices in North America in 2016 were

below the average for Latin America and even Africa. Prices have fallen back sharply in the

Former Soviet Union, in $ terms, reflecting the continued currency weakness, especially for

the Ruble, to lower levels than in the Middle East [13].

1.2 Natural gas processing plants

Processing of natural gas is in many respects less complicated than the processing and

refining of crude oil, but it is equally necessary before its use by end users. Natural gas

produced at the wellhead contains contaminants and Natural Gas Liquids (NGL1), which

must be processed and cleaned, before it can be safely delivered to the high-pressure, long-

distance pipelines since the principal market for natural gas is achieved via transmission

lines that distribute natural gas to different consuming centers such as; industrial,

commercial, and domestic. Natural gas that is not within certain specific gravities,

1 The term Natural Gas Liquids (NGL) is a general term which applies to liquids recovered from Natural Gas and refers to Ethane and heavier products.

8


pressures, or water content levels will cause operational problems, pipeline deterioration,

or can even cause pipeline rupture. Thus, field processing operations are enforced to treat

the natural gas in order to meet the requirements and specifications set by the gas

transmission companies. Natural gas processing consists of separating all of the various

hydrocarbons and fluids from the pure natural gas to produce what is known as ‘pipeline

quality’ dry natural gas [1] [14,15]. In other words, gas processing plants bring natural gas

to pipeline quality levels and recover marketable products like condensate, NGL, Liquefied

Petroleum Gas (LPG), and sulfur. It should be taken into consideration that the important

factors that usually determine the extent of gas processing plant include; the processing

objectives, the type or source of the gas and the location and size of the gas fields [2].

In addition, natural gas plants are flexible both in technical and economic terms, so they

can react quickly to demand peaks, and are ideally twinned with intermittent renewable

options such as wind power. They are low-risk (technically and financially) and lower-

carbon relative to other fossil fuels and can be built relatively quickly in around two

years, unlike nuclear facilities, which can take much longer [7].

As mentioned before, United States is an important producer of natural gas worldwide.

Therefore, it is useful to know about number of existing natural gas processing plants and

the approximate investment in this country.

In 2012, the Energy Information Administration (EIA) reported that United States had 516

active natural gas processing plants with a total processing capacity of 64.7 bcf/d. On

average, these plants processed about 44.4 bcf/d in 2012 (operating at about 69 percent of

capacity). In 2014, U.S. Department of Energy’s analysis estimated that there was 83 bcf/d

of gas processing capacity which has been expected to increase by 12 bcf/d by the end of

2017. From another point of view, IHS and ICF (research firms) estimated total required

gas processing investments from 2014 through 2025 at 32 $billion and 14 $billion,

respectively [16]. In addition, ExxonMobil has reported that significant investments will be

needed to meet global demand for oil and Natural Gas based on new policies scenario by

International Energy Agency which estimates cumulative oil and natural gas investment

may reach approximately 21 $trillion between 2017 and 2040 [10].

9


There are plenty of projects around the world for developing gas processing plants for

different purposes, either as national targets or international aims which some of them is

brought as following.

In 2013, it has been reported that Saudi Arabia would like to increase natural gas

production capacity. Although Saudi Arabia holds the sixth largest reserves of natural gas

in the world, the country was continuously suffering of shortage due to expansion of

petrochemicals and power generation sectors. In addition, the widening gap between the

crude oil price and the gas price was motivating Saudi Arabia to convert the use of crude oil

and naphtha as feed stock into cheaper natural gas and condensate. In this context, Saudi

Arabia is aiming at producing 15 bcf/d of natural gas in 2018. In this program the main

challenge relies on the high sulfur content of gas with the consequences to increase the

production costs and to cause delay. At the same time, Abu Dhabi National Oil Company

was mandate to increase the natural gas production by all means considering the gas

shortage in Abu Dhabi to meet the continuously growing consumption. In this regard, EPC

companies submitted commercial offers with an estimated budget of 500 $million capital

expenditure.

In the same region, in 2015, Iran and Oman planned a subsea gas pipeline with 260 km

distance with capacity of 10 billion cubic meters per year and estimated 1 $billion capital

expenditure.

Russian company (LUKOIL) in 2016 started a project in Uzbekistan to process gas

condensate. It is LUKOIL’s biggest investment project in Uzbekistan with the value of 3.3

$million. The complex is expected to be completed by the second half of 2018 and will be

fully operational by 2019.

In Europe, in 2012, European companies signed a contract for developing Azerbaijan

Natural Gas pipeline, with an estimated budget of 2 $billion capital expenditure. Moreover;

in 2015, Cyprus Island started developing Aphrodite gas field with USA and Israel based

companies. This gas field has been estimated to hold 4.5 trillion cubic feet of natural gas

[17].

10

https://www.2b1stconsulting.com/saudi-arabia-to-increase-natural-gas-production-capacity/

https://www.2b1stconsulting.com/saudi-arabia-to-increase-natural-gas-production-capacity/

https://www.2b1stconsulting.com/natural-gas/

https://www.2b1stconsulting.com/natural-gas/


With all the description in this chapter, it is concluded that there is worldwide motivation

towards increasing the application of natural gas. Therefore, the necessity of optimizing the

production process is clear. By minimizing the energy consumption for processing natural

gas, the profit associated with the process will be increased. Moreover, in order to reduce

the operating costs of a gas processing plant, much effort is put to find the optimal design

condition of the process through further studies. In this thesis, the main units of operations

in a typical gas processing facilities will be assessed from thermodynamic, economic and

environmental points of view.

The method used for the evaluation of the plant is based on exergy principles. An exergy

analysis is the first step in evaluating the natural gas processing system, identifying the

source and cause of thermodynamic inefficiencies. The combination of an exergy analysis

with an economic and environmental impact assessment analyses constitutes the

exergoeconomic and exergoenvironmental analyses, i.e. exergy-based analyses. With

conventional exergy-based analyses, information about improvements of the process is

revealed. Monetary costs are assigned to all exergy streams of the plant, as well as to the

exergy destruction incurred within each plant component, exposing appropriate

compromises among thermodynamic and economic considerations. In analogy with

exergoeconomic analysis, the environmental impact assessment associated with exergy

destruction is estimated. To have a more detail overview, the most influential components

with high exergy destruction are selected and by advanced exergy-based analysis, the

avoidable and unavoidable exergy destruction within these components are estimated to

reveal the potential of improvement inside plant.

1.3 Thesis outlines

After the brief introduction about energy status in the world and the role of natural gas in

this context, the need of review of processing natural gas with an innovative

thermodynamic approach seems necessary to cover the increasing demand by suggesting

some improvement in the process. In this thesis, the following outlines have been

addressed:

11


Chapter 2 provides an overview on main research topics which have been conducted

during recent years in Technical university of Berlin, with the approach on exergy-based

methods in different industries. In addition, this part is followed by literature review of

researches which have assessed the individual units of processing natural gas and similar

processing facilities; such as petroleum refineries, offshore platforms, petrochemical

plants, etc. from thermodynamic, economic and environmental aspects applying exergy-

based methodologies. This chapter highlights also the motivation of applying the exergy-

based methods to a gas refinery.

Chapter 3 presents the concept of exergy-based methodology for evaluation of the gas

refinery. In this chapter, exergy, exergoeconomic, diagnostic exergoeconomic,

exergoenvironmental and advanced exergy-based analyses are described.

Chapter 4 provides a detailed description of refining process and relevant process flow

diagrams in a gas plant which is considered in this study to be investigated by exergy-based

methodology. In addition, the software for performing the simulation and the assumptions

which have been applied in simulation of the system are presented.

Chapter 5 presents detailed information and required assumptions for the application of

exergy-based analyses to the simulated system. In this chapter, in the first step, the

application of conventional exergy analysis, the economic analysis and the life cycle

assessment of the simulated system are presented. The second step is followed by

application of exergoeconomic, exergoeconomic diagnostic, exergoenvironmental analyses.

Lastly, the associated advanced exergy analyses for selected critical components are done.

The exergy balances and results of all abovementioned analyses are obtained and

presented in appendices.

Chapter 6 discusses the results obtained for all exergy analyses that have been applied to

the simulated gas plant. The critical components from exergetic, economic and

environmental points of view are depicted and discussed. The avoidable and unavoidable

part of exergy destruction for most important components are estimated by advanced

exergy-based analysis and presented.

12


Chapter 7 provides the conclusions from this research and with the focus on main

contributors to the thermodynamics, economic and environmental deficiencies outlines the

future potentials for improvement to the process.

Lastly, supplementary data such as overall process flow diagram, stream data, equipment

cost estimations and additional detailed information and assumption used in this study are

presented in appendices.

13

CHAPTER 2

2 State of the art Refining processes are complex and highly integrated, thus, a thermodynamic, economic

and environmental evaluation of gas plants is of great importance to indicate the actual

efficiency of production of several fuels such as propane, butane, and condensate. In this

regards, the proposed method for evaluation of the plant is based on exergy principles.

As mentioned in previous chapter, an exergy analysis is the first step in evaluating an

energy conversion system or a chemical process, identifying the location, the magnitude

and the causes of thermodynamic inefficiencies and pinpoints the components with high

irreversibility. With conventional exergy-based analysis, information about improvements

of a chemical process system is revealed. The combination of an exergy analysis with an

economic analysis constitutes the exergoeconomic analysis. Monetary costs are assigned to

all exergy streams of the plant. Using an exergoeconomic analysis we can calculate the total

cost associated with a component, i.e. the sum of the capital investment cost, the operating

and maintenance expenses, and the cost of the exergy destruction [18,19]. In addition to

exergoeconomic analysis, exergoeconomic diagnostic was developed to identify the

degradation of the components behavior of a thermal system and to assess and quantify

their effects in terms of additional fuel plant consumption [20].

In addition to above-mentioned analyses, the environmental impact assessment of a plant

can be done by Life Cycle Assessment (LCA) and accordingly, the results of exergy analysis

are combined with LCA of the plant and the concept of exergoenvironmental analysis is

established. This analysis basically aims to modify the exergoeconomic analysis to convert

the problem from involving an economic assessment to involving an ecological evaluation

[21, 22].

The main objective of the implementation of an exergy-based approach is to find

appropriate trade-offs between fuel cost and investment cost or environmental impact, in

order to improve a process. Nonetheless, the conventional exergy-based analyses,

Chapter 2- State of the art

mentioned above, have some significant limitations and do not provide information about

real potential for improvement. To address the shortcomings of the conventional methods,

advanced exergy, exergoeconomic and exergoenvironmental analyses were developed. In

advanced exergy-based analyses, the thermodynamic inefficiencies, costs and

environmental impacts associated with important plant components are split into

avoidable/unavoidable parts [23].

During the last decades, exergy analysis concept has been undertaken to numerous sectors

such as; thermal systems and chemical process plants like petroleum refineries,

petrochemical plants, offshore platforms and more relevant to this research to some

individual processing units in gas refineries.

In Technical University of Berlin, Institute of Energy Engineering - as one of the pioneers in

exergy concept development - exergy analyses have been applied extensively to a wide

variety of industries.

Due to importance of improving the efficiency and possibilities on reduction the cost of

generated power and associated environmental impacts, special attention has been given

to the power plants sector and several researches have been conducted in Berlin as well,

which some of the most recent ones are mentioned below.

Petrakopoulou made a comparative evaluation of power plants with CO2 capture by using

the conventional and advanced exergy analyses from three main areas of concern:

thermodynamics, economic and environmental aspects [24].

Erlach has applied the exergy and exergoeconomic analyses to the hydrothermal

carbonization plant design. Exergy analyses revealed the most significant source of exergy

destruction in all the analyzed processes generating solid biofuels and potentials for

reduction the biocoal production costs [25].

In another research, a solid-oxide fuel cell - as a source of electricity generation- in

combination with an internal combustion engine has been proposed by Lee and the

performance of the new system from thermodynamics, economic and environmental points

of view have been evaluated using exergy-based method. At the end, performance of a

15


conventional simple Solid-oxide fuel-cell system and the combined one with an internal

engine hybrid system has been also compared [26].

In other effort, Sorgenfrei has applied the advanced exergy analysis to an integrated

gasification combined cycle technology including carbon capture; with considering an

efficient and flexible electric power generation [27].

Wang also has investigated the pulverized-coal power plants by advanced exergy analysis.

In addition, a new approach of calculating endogenous exergy destruction has been

introduced and a modern ultra-supercritical coal-fired power plant was evaluated

comprehensively [28].

To facilitate the application of the exergoeconomic analysis to the power plants, a

computer program based on SPECO methodology was developed by Zhao. Despite of

improving the degree of accuracy of computer program, application of that to the complex

energy system showed appropriate results [29].

In addition to above-mentioned applications of exergy-based analyses to the power

generation industries in energy engineering institute of technical university of Berlin, these

analyses recently have been used also in other sectors such as cement industry, aircraft

industry, production of carbon black and industrial bakery [30-33].

Recently, due to the importance of methanol as the feedstock to the chemical and

petrochemical industries, Blumberg studied different processes for production of methanol

from natural gas and analyzed them with advanced exergy and exergoeconomic to reveal

the main sources and the magnitude of the irreversibilities and their associated costs in

component level [34].

In a similar approach of chemical processing of natural gas, Tesch also used the exergy-

based methods to analyze the integrated LNG regasification into an air separation unit. In

the LNG receiving terminal, LNG is regasified with direct or indirect heat transfer which

leads to destroying of low-temperature exergy of LNG. This regasification process can be

integrated to power plant or other chemical related systems to have an improvement from

thermodynamics point of view. In this study, Tesch with the help of advanced exergy based

methods concluded that by using the low exergy of LNG regasification for air separation

unit, the power consumption and total capital investment in air separation unit would be

16


decreased by 50 % and 25 %, respectively, which consequently resulted in lower specific

product costs up to 60 % [35].

In this research the application of exergy analyses would be mentioned only for some

sectors which are similar to gas refining industry and reviewing of other researches on

thermal systems are excluded.

There are few researches that have been conducted for a whole refinery. Dincer et al.

applied exergy analysis to a petroleum refinery and they reviewed the separation, heating

and cooling processes. Finally the overall availability efficiency of 5.9 % of the refinery has

been predicted [36]. In another work, Rivero provided the integrated results of previous

works done in different projects of Mexican Petroleum Institute for petroleum refineries

and petrochemical plants with exergy concept considering economy and ecology

assessments and concluded that exergy based techniques would continue to be used for the

improvement of energy use in industry to help in reducing energy degradation in a

technically feasible, costly effective and ecologically sustainable way [37]. In 2016,

Vilarinho et al. used exergy analysis for an aromatic plant of a refinery in Portugal. It was

found out that the plant had an overall energy yield of 0.81 % and an exergy efficiency of

65.9 %. The equipment with higher energy losses were the condensers, air coolers and

furnaces with 25.9 %, 15.4 % and 14.7 % of total energy losses; while irreversibilities

observed in the condensers and air coolers were equivalent to 1.61 % and 0.86 % of the

total plant irreversibility and furnaces stand out above the irreversibilities analysis with

14.5 % of the total. Therefore, furnaces showed the highest potential of energetic and

exergetic performance improving [38].

In some other researches, exergy analysis has been used for the assessment of some

processing units in petroleum refineries like crude combined distillation unit, hydrogen

production unit and fluid catalytic cracking unit. In 2008, Cruz et al. evaluated a hydrogen

production unit with 550,000 m3 per day of hydrogen production capacity; in an oil

refinery by exergy and cost estimation. They have calculated the overall exergy efficiency of

the plant as 66.6 % as well as hydrogen production cost as 1.18 $ kg-1. It was concluded

that obviously there were thermodynamics performance limitations for reforming natural

gas to produce hydrogen [39]. In another work for hydrogen production unit in an oil

17


refinery in Turkey, Dilmaç et al. applied exergy analysis to a natural gas steam reforming

process of this unit and they obtained the energy and exergy efficiencies of the steam

reformer as 94.33 % and 78.23 %, respectively and the lowest exergy efficiency was belong

to steam generator as 66.81 % [40]. Nuhu et al. reviewed Fluid Catalytic Cracking Unit

(FCCU) in Kaduna Refining and Petrochemical Company in Nigeria. They found out that the

maximum energy lost was in the fractionators’ columns with the value of 67 % of the input

energy, following by condensers with 5 %, 2.4 % for all other components and less than

1 % for absorbers. In addition, the calculated second law and exergy efficiencies of the

system were 24.77 % and 61.20 %, respectively which showed the improvement potential

in the quality of heat input to the system to improve the second law efficiency of the unit,

consequently [41].

In addition to above-mentioned applications, Yang et al. applied advanced exergy analysis

to evaluate the performance of an oil shale retorting process. The obtained results revealed

an exergy efficiency of 34.17 % and the total exergy destruction is 442.62 MW, of which

45.50 % is unavoidable and, therefore, cannot be reduced [42].

In other works, exergy and exergoeconomic analyses have been done on crude-oil

refineries’ single components such as distillation columns. Distillation system is an

important and energy consuming unit operation in petroleum industry, therefore, it has

been focused by several researchers to locate the inefficiencies and to be optimized. Rivero

et al. evaluated the different distillation columns in petroleum refinery. In 1999, they

calculated the physical and chemical exergies for mixtures of crude oils and their fractions

by the help of computer programs and simulation codes. Later, having applied the

methodology to a mixture of Mexican crude oils, they evaluated a crude oil combined

distillation column. The exergy analysis of the unit indicated that the atmospheric

distillation section represents 69 % of the exergy losses, the vacuum distillation section

7 % and the crude oil preheating section 5 %. The remaining sections represent together

13 % [43]. In 2005, Al-Muslim et al. studied crude oil distillation system with energy and

exergy analysis and they concluded almost similar results as Rivero and his team. They

found out that the highest exergy losses happened in atmospheric distillation column by

56 % as the main separation occurred in this column, followed by vacuum distillation and

18


heaters with 26 % and 18 %, respectively. They reported that 6.2 % of losses were due to

chemical exergy losses and the rest was belonged to physical exergy losses because of

temperature difference [44].

In 2001, Rivero, conducted a detailed exergy analysis of a distillation system with adiabatic

and diabatic rectification and stripping columns and then compared the results. He

determined the distribution of exergy losses inside the column and the optimal distribution

of heat to be transferred inside the column in order to produce the minimum overall exergy

losses. The maximum of exergy losses was located at the tray with the largest composition

differences; which for stripping column maximum losses occurred in the lower part of the

column, whereas in the rectification case was along the column [45]. In another work,

Koeijer and Rivero compared a diabatic and adiabatic distillation column by exergy

analysis and they discovered that diabatic column lost 39 % less exergy than the adiabatic

column which also was verified by an experimental confirmation [46]. To allocate the total

production cost to the different product streams, Rivero et al. conducted exergy and

exergoeconomic analyses to the crude oil combined distillation column in a petroleum

refinery in Mexico. Obtained results revealed that blocks presenting the highest exergy

losses, exergy improvement potential and exergoeconomic improvement potential are the

distillation systems, integrated by fired heaters, columns and condensers. To solve the

problem, they proposed to investigate more for the application of crude oil progressive

diabatic distillation. They also discovered that the most important factor affecting the costs

of the products was the cost of the crude oil fed to the plant [47]. Following the proposed

recommendation in previous research by Rivero et al., he and his coworkers applied a

diabatic distillation to a depentanizer tower of a tertiary amyl methyl ether product unit of

a crude oil refinery and they compared the results of exergy analysis with adabatic

distillation. This application enabled the process to approach equilibrium condition and

consequently reduce the exergy losses and increased the exergy effectiveness. By

implementation of diabatic distillation in the depentanizer section, losses due to

irreversibilities have been reduced by 18.10 %. They conducted an economic analysis and

found out that the cost of the diabatic column was about 20 % higher than the cost of the

adiabatic column. The investment of the diabatic tower is three times higher than that of

19


the conventional adiabatic tower, but the reduction in the investment costs of the reboiler

and condenser compensated the higher tower investment. Finally, they proposed further

detail review and pilot plant experience [48].

As distillation column optimal design is very vital in oil refinery, more efforts and analyses

have been performed over optimization of it and the tool of this approach was exergy

analysis. Costa et al. developed a program to calculate the exergy efficiency of distillation

columns and they concluded that exergy analysis was vital to find out energy deficiencies in

the industrial processes and it could be used not only for process synthesis but also for

process optimization activities [49]. In another effort in 2010, Khoa et al., proposed a new

exergy graphical method for optimal design of distillation column with minimum exergy

lost. By the help of this graphical method, the simulation required fewer efforts and

enabled engineering to have a better visual overview of columns operation condition [50].

In another investigation about distillation columns, Tarigholeslami et al. applied exergy

analysis as a tool to provide exergy loss profile of atmospheric distillation column in Tabriz

refinery of Iran. Due to increasing the capacity of the plant, the influence of the new blend

of feed stock on operating condition of column would have been analyzed. By application of

the exergy loss profile, the best retrofit option has been identified with 17.16 % reduction

in exergy losses, and consequently 3.6 % reduction of primary fuel demand [51].

In addition to above works, Silva et al. compared several methods for calculation of

separation processes’ exergy efficiency in petroleum refinery, based on different

properties. Their results showed that the method which was dependent only on the

entropies of the streams was the most accurate [52]. In 2014, Izyan and Shuhaimi also

applied exergy analysis to the furnace and crude preheat train in a crude distillation unit to

investigate more over fuel reduction strategies. They presented some strategies to reduce

the exergy loss (equivalent to exergy destruction in the terminology used in this thesis)

through process modification. The results showed that the highest exergy loss occurred at

the inlet furnace with contribution of 86 % of total exergy loss. They have extracted some

fuel reduction strategies from exergy composite curve. The proposed fuel reduction

strategies were the reduction of heat loss from furnace stack and overall cleaning schedule

of crude preheat train. To assess the feasibility of these options, they conducted an

20


economic analysis as well. From the results of economic analysis they have concluded that

overall cleaning schedule of crude preheat train contributed to the highest energy saving of

5.6 %, while the reduction of heat loss from furnace stack is the highest cost saving by

about 6.4 % [53].

In another publication on exergy and economic analyses over distillation units, Odejobi also

evaluated a distillation unit by exergy and economic analyses. The reported exergy analysis

results showed that distillation unit had lowest exergy efficiency 52.1 %, followed by pre-

flash drum and furnace with 74.1 % and 75.1 %, respectively. By application of economic

analysis, it was found out that the optimization of the number of column trays should be

considered [54].

To identify the potential for energy savings in distillation processes, Wei et al. proposed

some methods for splitting the exergy destructions and investment costs into

avoidable/unavoidable for distillation columns, and hot-utility/cold-utility heat exchangers

(reboiler/condenser) in a case study of light-ends separation plant. The authors assumed

the estimation of unavoidable exergy destruction through the minimum reflux ratio, and

the unavoidable investment cost, based on condition of total reflux with minimum

theoretical stage number. For the utility heat exchangers, the unavoidable exergy

destruction has been estimated through the minimum possible temperature difference, and

the unavoidable investment cost corresponds to the maximum allowed temperature

difference that is related to practical applications. The results showed that the exergy-

savings potential enables comparisons of energy-savings potentials, and the value of the

cost-savings potential pointed out the cost that could be avoided in today’s technological

and economic environment [55].

Recently, in 2017, to have a more precise assessment of distillation unit, Osuolale and

Zhang proposed a new methodology for optimizing the exergy efficiency of atmospheric

distillation unit without any trading off of product qualities and process throughput. The

new methodology was based on modeling the exergy efficiency by neural network and

therefore, finding the most efficient condition [56].

21


Having described the extensive application of exergy analysis, it is good to be familiar with

other applications of this methodology in industries similar to gas refineries. In other

application of exergetic methodology, some researches evaluated the utility issues by

applying exergy analysis. Rosen et al. examined the feasibility of substituting the steam for

other energy sources of heating in industry and they found out that by this replacement

resulted in higher exergy efficiency of the process and they recommended exergy analysis

as a tool for optimization of process where extensive use of steam was contemplated. They

compared the different configuration of steam supply system in an industrial plant [57]. In

other works, utility consumption in refinery has been assessed based on exergy and

exergoeconomic. Khodaei et al. have investigated the steam network of Tehran oil refinery.

They had simulated and optimized the steam network and selected the best scenario with

considering minimum total annualized cost and carbon dioxide reduction. Exergy analysis

has been applied and the results showed that the main exergy losses occurred in boilers

and heat recovery steam generator in existing and optimized scenarios, respectively.

However, amount of the destructed exergy in optimized scenario was 13.5 % less than the

existing one [58]. In another effort, Silva et al. also reviewed the utilities production plant

of a Brazilian petroleum refinery. In their work, they have applied exergy analysis to

evaluate the performance of refinery’s utility plant and exergoeconomic analysis to identify

the exergy unit cost. The analysis showed that the equipment where attention should be

given; were the boilers followed by the gas turbine, that together, were responsible for

80 % of total exergy destruction in the utilities plant. The obtained total exergy efficiency

was about 35 % and more than 280 MW of exergy was destructed in the utilities processes

[59].

In addition to above, some researches have been undertaken for the evaluation of offshore

platforms separation processes by exergy analysis. Oliveira et al. carried out an exergy

analysis over a Brazilian offshore platform and they quantified the value of destructed

exergy and the exergetic efficiencies of involved equipment as well as overall platform

performance. Obtained results showed that the main contributors of exergy consumption

were the heating and compressing operations. However, the separation process had the

22


lowest value of exergetic efficiency of 22 % and the overall exergetic efficiency of plant was

calculates as 97 % [60].

Besides the Brazilian platform, Nguyen et al. performed several researches for assessment

of thermodynamic performance of North Sea oil and gas platforms by exergy analysis. In

one work, they assessed the energy systems in offshore platforms. They discovered that

62–65 % of the total exergy destruction of an offshore platform was attributable to the

power generation and waste heat recovery system, and 35–38 % to the oil and gas

processing. Moreover, the rejection of high-temperature gases from the utility and flaring

systems was introduced to be the major contributor to the exergy losses [61]. In another

study, Nguyen et al. focused on four offshore processing plants with different working

conditions and designs. Several approaches of exergy efficiency definition have been

presented and applied to the four cases which resulted in low sensitivity to performance

improvement and gave inconsistent results. In this regard, they suggested an alternative

approach which called component-by-component exergy efficiency which relied on the

decomposition of the exergy flows at the level of the chemical compounds that used for

comparisons of separation systems, and provided potentials of improvements. The

performance of the offshore platforms under study varied between 1.7 % and 29.6 %.

Consequently, they offered splitting exergy destruction to avoidable and unavoidable for

more precise evaluation [62]. In another work, Voldsund et al. continued this investigation

and compared the source of exergy destructions and losses in the same four offshore

platforms and they found out that 27 %–57 % of the exergy destruction took place in the

gas treatment sections, 13 %–29 % took place in the gas recompression sections and 10–

24 % occurred in the production manifolds and exergy losses with flaring belonged to two

platforms [63]. Prior to this work, Volsund et al. also carried out exergy analysis for one

offshore platform in a real day production and they identified the sub-processes with most

exergy destruction which were the production manifold (4600 kW), the recompression

train (4150 kW) and the reinjection trains (10400 kW) [64]. In addition to above, Teixeira

and his coworkers reviewed MEG Recovery Unit (MRU) of an offshore platform by exergy

analysis. They assessed three type of MEG recovery processes; traditional process (TP),

full-stream process (FS) and slip-stream process (SS), considering two different

23

https://www.sciencedirect.com/science/article/pii/S036054421400718X%23!

https://www.sciencedirect.com/science/article/pii/S036054421400718X%23!


approaches for reference environment reservoir (RER). From the comparison of results of

exergy and energy analysis, they found out that TP had the highest exergy efficiency and

lowest energy consumption, while FS exhibited the lowest exergy efficiency and highest

energy consumption [65].

In addition to evaluation of offshore platforms processes, some studies have been

performed on Floating Production Storage and Offload (FPSO) ship by exergy analysis.

Gallo et al. applied exergy methodology for reviewing the compression system including its

prime movers in a FPSO unit with three conditions of well fluid composition and mass flow.

They also assessed the process in part load operation and it has been found out that there

are equipment clearly oversized for most part of FPSO operation [66]. In another study,

Silva et al. used exergy costing analysis for oil and gas produced on a FPSO along the

lifespan of the well. Distribution of exergy costs for the oil and gas revealed that the exergy

cost of oil varied from 1.0 kJ kJ-1 to 3.2 kJ kJ-1 along the well lifespan and for the gas varied

from 1.0 kJ kJ-1 to 2.4 kJ kJ-1. The average emission of CO2 for the natural gas ranges from

19 gCO2 MJ-1 to 19.8 g CO2 MJ-1 while for the oil it ranges from 19.4 g CO2 MJ-1 to

26.8 g CO2 MJ-1 [67].

Having described wide ranges of exergy applications to processes similar to gas refineries,

it is the time to go forward to application of this concept to gas refineries.

Panjeshahi et al. conducted an exergy analysis on a gas refinery but details of analysis and

results have not been reported extensively for refining processes. According to the

obtained results, the most exergy losses occurred in Amine Recovery Column, Absorption

Column, Air Coolers, Recovery Column Reboilers, Glycol Flash Drums, Incinerator of

Sulphur Recovery Unit, Boilers and finally Gas Turbines of Power Production Unit and Gas

Turbines of Gas Pressure Compression Unit. Because of the significant exergy losses in the

gas turbines of both units, they focused on these units’ equipment and analyzed them from

exergetic and economic points of view. Since the gas plant needed high pressure steam and

to reduce exergy losses in these equipment, they investigated converting the boiler feed

water to a high pressure steam by using high temperature gases emitted from the turbines.

Applying these improvements, exergy efficiency of a gas turbine of both units were

increased from 23 % to 37 % for Gas Turbines of Power Production Unit and 26 % to 46 %,

24


for Gas Turbines of Gas Pressure Compression Unit. In addition, their thermal efficiency

improved about 14 %. Hence, by avoiding fuel consumption in boilers for providing this

amount of produced high pressure steam in these modified units; about 618,418 $ and

379,288 $ would be saved yearly in units Gas Turbines of Power Production Unit and Gas

Turbines of Gas Pressure Compression Unit, respectively. It has also been shown that high-

pressure steam can be raised using turbine exhaust heat. This modification can save energy

by 997,700 $ yr-1, while the required investment will be paid back in about 3 years [68].

Few researches have been conducted for some individual units in gas refinery; such as

condensate stabilization unit. Montelongo et al. evaluated a simple condensate stabilization

unit by exergy analysis as case study. The overall exergetic efficiency of the unit was

calculated as 99.2 %. It revealed that even an idealized model of a process accounts for

some of the exergy destruction in the process [69]. Kianfar et al., combined pinch and

exergy techniques and they reviewed electricity consumption in condensate stabilization

unit. A potential of saving 1.1 MW electricity and reducing operating costs by 522,240 $ yr-1

has been reported [70]. Tahouni et al. studied the debottlenecking of the heat exchangers

network in condensate stabilization unit of a gas refinery. The authors have also evaluated

the consequences of increasing throughput to the unit. Finally, they discovered that this

retrofit study resulted in final energy saving of 99,478 $ yr-1 which can be returned within

2.4 years and will reduce CO2 emission about 8608 kg hr-1 [71].

Another unit of operation in gas refinery that has been analyzed by exergy concept was

Sulphur Recovery Unit (SRU). Khademsamimi et al. carried out an exergy analysis for SRU

in a gas refinery plant. Since SRU is involved with high temperature processes, it is

associated with remarkable potential of thermodynamic losses. The results showed that

the exergetic efficiency could be improved in incinerator and Claus reaction furnace from

9.9 % and 11.2 % to 12.6 % and 14.9 %, respectively [72].

In another study of gas refinery units, an exergy analysis has been applied by Banat et al.

for a natural gas sweetening unit. The results showed that highest exergy destruction have

been occurred in absorber by 3 MW, sweet gas air cooler by 2.7 MW and flasher unit by 2.2

MW, respectively. Estimation of exergy efficiencies showed that absorber was the most

efficient equipment with 98 %, however; flasher with 27 %, air cooler with 24 % and

25


pressure recovery turbine with 31 % revealed to be under performance [73]. In 2016,

Suleiman et al. compared the performance of sweetening process using triethanolamine

(TEA) and diethanolamine (DEA) as gas sweeteners with exergy and economic analysis,

with the target of 99 % of natural gas purification. The results showed that TEA process

configuration was more efficient than the DEA process from both energy and exergy

analyses, as the TEA system had about 58 % lower exergy destruction than DEA and higher

exergetic efficiency of 98.91 % in addition to low energy requirement of 5.75 MW. On the

other hand, from economic point of view, the DEA process configuration indicated better

economic performance but trade- off conducted between energy, exergy and economic

analyses resulted in TEA based system configuration was the most preferred gas sweetener

system [74].

Some attempts have been made to apply exergy or exergoeconomic analyses for ethan

recovery unit and its refrigeration cycle. Because of the high energy consumption of

refrigeration systems and the vital role of the economic issues in the industry, it is

important to find out the location of inefficiencies and the potential for improvement. Shin

et al. applied exergy analysis for assessment of most common process flow diagram of

ethan recovery unit. Moreover, they compared the results of exergy analysis with two other

modifications in this process flow sheet, different condition of the feed to this unit and

increasing the number of stages in demethanizer column. The results showed that main

exergy losses happened in compressor and demethanizer column and in most cases the

value of exergy losses has been decreased. It should be mentioned that by increasing the

number of stages in the column, the ethan recovery factor increased but this can happen at

the expense of capital investment of the column. The assessment did not include any cost

analysis and have been proposed as future work [75] In other work, Mehrpooya et al.

carried out an exergy analysis for a natural gas Liquid recovery unit and its refrigeration

cycle of an industrial NGL plant in south of Iran. They showed that the exergetic efficiency

of the refrigeration cycle is about 26 %, which indicates a great potential for improvements.

They also found out that the air coolers and chilling sections had the lowest exergetic

efficiencies among other components of the cycle [76]. Later, they investigated more detail

on refrigeration cycle with focus on of compression and condensation section of the

26


mentioned plant by thermoeconomic approach and the effect of the component

inefficiencies on the fuel consumption, and on the rest of the components were quantified

[77]. In this regard, Tirandazi et al. also carried out an exergy analysis for C2+ recovery

plant in a petrochemical plant and its multistage refrigeration cycle with Propane

refrigerant. The exergetic efficiency of the refrigeration cycle was determined to be

43.45 % indicating a great potential for improvements. The results revealed that the

exergetic efficiencies of the heat exchanger and expansion sections had the lowest value

comparing other compartments of refrigeration cycle. Also, the effects of pressure drop

and temperature on the exergy efficiency and coefficient of performance of the cycle have

been investigated and concluded that adjustments of these parameters can improve the

cycle performance [78].

Ghorbani et al. combined the exergy analysis with pinch technology and evaluated the

refrigeration cycle of NGL recovery unit. This combined analysis deal with both energy

recovery systems and shaft works. They assessed the refrigeration cycle and in the last part

of analysis, another refrigerant was applied which resulted in the reduction of work of

compressor and refrigerant mass flow rate by about 570 kw and 11.5 %, respectively [79].

In another work, Ghorbani and his coworker applied both exergy and exergoeconomic

analyses on two units of operations in a natural gas processing facility. They reviewed

ethane recovery and NGL fractionation units. Obtained results from exergy analysis

showed that highest exergy losses happened in distillation columns by 64 % of total exergy

losses and followed by heat exchangers and compressions with 15 % and 13 % of total

values, respectively. On the other hand, exergoeconomic analysis indicated that increases

in the unit thermoeconomic costs of the compression and the demethanizer were the

highest. Finally, the cost based information has been taken into consideration for potential

improvement of the system [80]. Tahmasebi et al. investigated the effect of different feed

conditions on the performance of the NGL recovery unit by using exergy analysis. The

results of this study showed that increasing heavy contents of feed cause higher duty

requirement for heat exchangers and lower compression duty for compressors [81].

Mehrpooya et al. also studied an ethane recovery process and Propane refrigeration cycle

by advanced exergy analysis. Exergetic efficiency of the refrigeration cycle has been

27


reported by 33.9 % which shows a high potential for improvements. The advanced exergy

analysis results revealed that 59.61 % of the exergy destruction is unavoidable and

compressors contribute to 25.47 % of the exergy destruction [82].

In another application of exergy analysis, integrated LNG-NGL process configurations have

been assessed to discover the potentials of improvement. The newest integrated processes

have been introduced and analyzed by Vatani and Mehrpooya. High ethane recovery

(90 %+), low specific power, simple design and using reliable configuration in refrigerant

systems and NGL recovery section were the advantages of these processes [83,84]. Later in

2017, these novel processes have been further assessed by Ansarinasab and Ghorbani in

two different works. Ghorbani et al. carried out exergy and exergoeconomic analyses for

these integrated processes. The highest exergy efficiency was related to the air coolers,

multi stream heat exchangers and compressors, with the values of 92 %, 91 % and 83 %,

respectively. The results of exergoeconomic analysis revealed that highest exergoeconomic

factor was related to compressor with 92.92 %. Demethanizer column as a vital component

had small exergoeconomic factor and high exergy destruction, which showed that column

efficiency should be increased in the cost of increasing investment cost [85]. Ansarinasab et

al. also evaluated these processes with advanced exergoeconomic analysis and with two

different refrigeration systems. Their results showed that based on the avoidable cost of

exergy destruction compressors should be modified first. Cost of exergy destruction and

investment in most of the process components were endogenous. So interactions among

the components in these processes were not significant. On the other hand, investment cost

of turbo expander and compressors were unavoidable due to technological and economic

limits while air coolers and heat exchangers had potential for improvement. Cost of exergy

destruction of the air coolers and heat exchangers were unavoidable while turbo expander

and compressors were avoidable [86]. In another work, Ghorbani et al. have investigated

these integrated processes but this time with a novelty of using absorption refrigeration

system instead of pre-cooling stage of mixed fluid cascade refrigeration system. Due to the

removal of a stage of the compression system, energy consumption in these units reduced

and additionally the absorption refrigeration system could utilize the waste thermal

energy. They have conducted economic and exergy analyses for this process and the results

28


illustrated that the highest exergy destruction occurred in the air coolers before and after

installation of the new absorption refrigeration cycle with the values of 56.21 % and

42.72 %, respectively. They also carried out a sensitivity analysis for assessment of

economic parameters considering utilities price as well as effect of products price on the

market [87].

Regarding the evaluation of liquefaction of natural gas (LNG), Bin Omar has conducted his

doctoral thesis in this sector by assessing several LNG processes thermodynamically and

economically. The thermodynamic assessment was performed based on exergy concept. In

cold production, the physical exergy has been splitted into physical and mechanical exergy

values and sensitivity analysis has been done. Among the examined processes, it has been

concluded that the most efficient processes were those working with the mixed-refrigerant

technology. The outcome of the economic analysis was that main cryogenic multi-flow heat

exchangers contributed to the highest priced compared to other critical components in

their fixed capital investments [88].

In another relevant research, Primabudi implemented the exergy based analyses to obtain

optimal operation condition for Propane pre-cooled mixed refrigerant process. Genetic

algorithm has been used for optimization of LNG process with the aid of exergy-based

methods. It is shown that Genetic algorithm produced better results when performed

sequentially by carefully selecting the design variables according to the results of exergy

and exergoeconomic analyses [89].

By combining the pinch technology concept with advanced exergy analysis (so-called

CPEA), Mehdizadehfard et al. also evaluated Heat Exchanger Network (HEN) of a natural

gas refinery. The CPEA method has been used to optimize both the utility consumption and

the total exergy destruction of the HEN, by minimization of the total annual cost. Results

showed that the potential of improvement on both the utility consumption and the heat

recovery were about 36.09 % and 42.65 %, respectively. The optimized HEN reduced

exergy destruction about 26 % relative to existing network. In addition, considering

unavoidable exergy loss in the retrofitted network, it was clear that the CPEA method led to

the exergetic efficiency of 88.27 % in comparison with 49.45 % of the existing network. In

other words, there was a huge potential for improvement about 78 % in energy

29


consumption of the plant, by investment in the HEN for installation of the new heat

exchangers [90].

Despite of extensive and varied applications of exergy and exergoeconomic and

corresponding advanced analyses in industries similar to gas refinery (petroleum refinery,

offshore platforms …), till now no research has been done with exergoeconomic diagnostic

in these sectors. For the first time, exergoeconomic diagnostic (thermoeconomic diagnosis

methodology) has been presented by Lozano et al. in 1994 and applied to a coal fired

power plant sited in Spain [20]. Later, Valero hat al. as applied the exergy cost theory in

CGAM project [91]. In another research, Schwarz et al. applied diagnostic exergoeconomic

to a Pressurized Fluidized Bed Combustor power plant (PFBC) [92]. In 1997, Valero et al.

developed the on-line diagnostic thermoeconomic which was general enough to be

implemented in complex energy systems. They applied this method to an Integrated

Gasification Combined Cycle (IGCC) [93]. In addition, Verda in his PhD thesis applied

diagnostic exergoeconomic to an urban district heating system based on cogenerative

steam and gas turbines [94]. In another research, Verda et al. reviewed the effects of

regulation on the thermoeconomic diagnostic of a power plant [95].

Torres et al. proposed some new advances to the diagnostic exergoeconomic methodology,

which contains the information related with the plant inefficiencies and their effects on

each component and on the whole plant [96]. On the other hand, Valero et al. applied the

new proposed advances in an actual coal fired power plant in Spain and the impact of the

component inefficiencies on the fuel plant consumption, and the effect of a component

inefficiency on the rest of the plant components have been analyzed and quantified [97].

In the same direction, in 2004, TADEUS project was initiated and the procedure of

exergoeconomic diagnostic has been applied to it to reveal the energy utility system

malfunctions and inefficiencies. This paper showed at which level of detail the analysis of

physical and technical characteristics of the plant should be performed, how to develop a

design and off-design model suitable for malfunction analysis, how to analyze and define

component malfunctions and how to interpret and use thermoeconomic variables and

indexes [98]. Similar to these applications, in 2007, Zhang et al. has applied the

exergoeconomic diagnostic to a 300 MW pulverized coal fire power plant in China and they

30


found out this methodology as a promising tool for diagnosis of complex energy system and

a great prospect for thermal power plant optimizations [99]. By installing a

thermoeconomic diagnosis system in a coal fire power plant, its operation during a time

span of more than 6 years has been analyzed and the effects of variations in components

(degradation, repairing and substitution), fuel quality, ambient conditions and operation

strategy, have been quantified. Obtained results showed that the diagnosis method

provided addressing the source of inefficiency for about 70 % of the cases with an accuracy

of ±3 % [100].

In another application, Ommen and Elmegaard applied exergoeconomic diagnostic in a

commercial transcritical/subcritical booster refrigeration system installed in Danish

supermarkets. Thermoeconomic theory has been used to establish the cost of cooling at

each individual temperature level based on the operating costs and with the objective of

cost and power consumption reduction, a general solution for malfunctioning equipment in

operation has been considered [101].

Having reviewed the exergy concept in combination with cost, now the application of

exergy associating with environmental impact assessment will be discussed. To have an

overview of environmental impact assessment, Life Cycle Assessment (LCA) is used. LCA

has been extensively applied to various sectors like energy conversion and chemical

processes and buildings e.g., steam methane reforming, biodiesel production processes,

waste water treatment, hydrogen production [102-105], power plants [24, 26], buildings

[106, 107], nuclear industry [108], biorefinery [109], and it covers the environmental

impacts from fuel consumption as well as from construction, maintenance and disposal of

plant components.

In similar industries to gas refineries, there are several researches that carried out LCA. In

2011, Clark et al., by using LCA; published a report to draw the attention to environmental

impacts of shale gas production. They compared the results of emissions of greenhouse

gases with conventional natural gas production’s emissions. The results showed that shale

gas life-cycle emissions are 6 % lower than those of conventional natural gas. However, the

range in values for shale and conventional gas overlapped and it could be the results of a

31


statistical uncertainty regarding whether shale gas emissions were indeed lower than

conventional gas emissions [110].

In another work in similar industries to gas refinery, an LCA of petroleum processing

activities in the United Kingdom has been performed by O'Born, with the approach of “from

ground to gate”, to identify the refining emissions associated with different fuel types at

both process and country level [111].

Morales et al. performed an LCA to a gasoline production facility in Chile. As gasoline was

the second most consumed fuel in Chile in transportation related activities and Chilean

refineries processed more than 97 % of the total gasoline commercialized in the national

market, therefore, reviewing the environmental impact of this process seemed necessary.

For this purpose, LCA has been selected as a useful methodology to assess the ecological

burdens derived from fuel-based systems. The results showed that the main hotspots were

the refining activities as well as the tailpipe emissions from car use. When detailing by

impact category, climate change was mainly affected by the combustion emissions derived

from the gasoline use and refining activities. Refinery was also remarkable in toxicity

related categories due to heavy metals emissions. In ozone layer and mineral depletion,

transport activities played an important role. Refinery was also predominant in

photochemical oxidation and water depletion. In terms of terrestrial acidification and

marine eutrophication, the combustion emissions from gasoline use accounted for large

contributions [112].

Recently, Morsali reviewed the environmental impacts of oil refineries with using the

technique of LCA. In this work, only the material production phase of the bitumen (one of

oil refineries’ products) life cycle has been considered and to improve the quality of the

LCA, a regionalized Life Cycle Inventory (LCI) database for the oil refineries and

commercial LCI databases were used for validating and modeling of unit processes with

LCA software.

The obtained results showed that in typical oil refineries, the most damage occurred in

resources category with 156900mPt units per one ton bitumen production. It has been

identified that from extraction step to distribution bitumen in markets the most released

emissions to the air were; nitrogen oxides, sulfur oxides, carbon dioxide, nickel and

32


methane which all have negative effects on human health category, and in this category

respiratory inorganics subcategory has the highest effect. In addition, in respiratory

inorganic subcategory using of diesel in diesel generators represented the most negative

impact on environment with spreading nitrogen oxides to the air [113].

In gas refineries sector, Bahmannia has applied an LCA to a gas refinery in south of Iran. In

order to quantify the emissions of greenhouse gases, as well as other major environmental

consequences (resource consumption, and energy use) for measuring the sustainability

development activities, material and energy balances were performed in cradle-to-grave

manner on the operations required to transfer raw materials in to useful products [114].

For optimization of the energy consumption in a natural gas refinery, Akbari et al.

conducted a Life Cycle Energy analysis, whose application was highly dependent on

technologies studied in Life Cycle Assessment. In this work, an LCA, with gate to gate

approach has been employed [115].

In another application, supply chain of natural gas from Canada to Europe has been

evaluated by both techno-economic and LCA. It is important for Canada to deliver the

natural gas with a competitive price and lower greenhouse gases emissions. The results

showed that the delivered cost of Canadian LNG (including recovery, processing,

transmission, liquefaction, and shipping cost) to Europe was 8.9–12.9 $ GJ-1, depending on

the resources and pathway and the total well-to-port greenhouse gases emissions

(including emissions from recovery, processing, transportation, liquefaction, shipping and

regasification at the destination port) from the Canadian production sites to Europe

reported as 22.9–42.1 CO2 g MJ-1, depending on the resources and pathway followed [116].

Besides the exergy and exergoeconomic methods, a combination of exergy analysis and

LCA principles is a relatively new method to evaluate the environmental impacts of energy

conversion systems. In the last years the method of implementing the exergoeconomic

theory to the life cycle environmental impact allocation was presented by Tsatsaronis and

his research group for component-level energy systems [21, 22] [117].

Boyano et al. applied exergoenvironmental method to assess the environmental aspects of

steam methane reforming. This work emphasized the importance of thermodynamic

33


efficiency in reducing environmental impacts [102]. Similar approach has used by Peiró et

al. to assess the life cycle of biodiesel obtained from methyl transesterification of used

cooking oil. The process was evaluated by LCA to account environmental impacts and by an

Exergetic Life Cycle Assessment (ELCA) to measure the exergy input to the system. The

results showed that transesterification was the most impacting stage of the system and the

major exergy inputs were associated to uranium and natural gas for electricity production

[118]. In another application, Ozbilen et al. applied Exergetic Life Cycle Assessment (ELCA)

with LCA to a hydrogen production process. Exergy efficiencies and air pollution emissions

were evaluated for all process steps. The parametric studies indicated that the effect of

plant lifetime on environmental impact per kg hydrogen production diminished at large-

scale production capacities. The author concluded that ExLCA was a beneficial addition to

LCA for introducing thermodynamic analysis throughout the life cycle analysis of the

system [119]. Banerjee and Tierney have assessed the environmental impacts of different

energy systems for rural communities in developing countries. Ten systems were

proposed, modeled, and assessed by five exergoenvironmental methods. It was found that

the method combining a standard environmental impact indicator – the ReCiPe – with

exergy analysis was the most effective due to using a well-established and updated

environmental impact metric [120].

Koroneos and Tsarouhis combined methods of LCA and exergy analysis to evaluate the

performance of solar systems for space heating, cooling and hot water production in

domestic scale. The results showed that the solar cooling system had the greatest

environmental impact followed by the system of solar space heating. Moreover, exergy

analysis showed a relatively low efficiency for the renewable energy systems but

environmental impacts were also very low [121].

Restrepo et al. applied exergy and environmental analysis to a pulverized coal power plant

in Brazil and quantified the exergy destruction and the environmental impacts. The

analyses showed that the highest degree of environmental impact occurred during the

combustion process [122].

Petrakopoulou et al. performed an advanced exergoenvironmental analysis to a combined-

cycle power plant. The obtained results showed that combustion chamber with highest

34


exergy destruction rate, caused most of the environmental impact within the plant, 68 % of

which was found to be unavoidable [123].

Sahraie et al. optimized an aromatic plant with considering three concepts of exergy,

economy and environmental impacts. The author concluded that, unlike the power plants,

implementing exergy and environmental optimization simultaneously, for a process system

with reactors, could not necessary led to this point that reducing exergy destruction would

definitely decrease the environmental impacts of the plant [124].

Khoshgoftar Manesh et al. proposed a new procedure for optimal design of cogeneration

systems with the aid of advanced exergoeconomic and exergoenvironmental and they

applied the new procedure into Iran LNG cogeneration plant, which showed that the

proposed methodology can be applied to any cogeneration systems systematically,

graphically and elegantly which can led to optimal design of systems [125].

In 2015, Jensen et al. conducted conventional and advanced exergoenvironmental analyses

to an ammonia-water hybrid absorption-compression heat pump. The advanced

exergoenvironmental analysis showed that the highest avoidable environmental impact

belongs to the compressor, followed by the absorber. Further, it is found that the initial

environmental impact of the studied heat pump was negligible compared to the

operational environmental impact [126].

Morosuk et al. reviewed the effect of characterization indicator which was obtained

through LCA and used in exergoenvironmental analysis. The authors found out that

contribution of the component-related environmental impact can be neglected in the

exergoenvironmental evaluation, and that only the environmental impact associated with

the exergy destruction should be considered in the analysis. For the case study, they have

performed the exergoenvironmental analysis to a compression refrigeration machine and

the conclusions from evaluation showed independency from employed environmental

indicator [127].

A novel solar-driven combined cooling, heating, and power, has been evaluated with

exergoenvironmental and exergoeconomic analyses, by Rahmatian et al. The outcomes of

the analyses reveal that increments in turbine inlet pressure and mass flow rate of the

35


vapor generator were associated in the lower environmental impact of system products as

well as the total product cost rate in both summer and winter seasons. The optimum value

of daily exergy efficiency, total product environmental impact rate, and total product cost

rate indicate improvements by 2.5 %, 15.7 %, and 15.3 % respectively in summer and

36.3 %, 7.4 %, and 4.9 % ,respectively in winter, relative to the base point [128].

In another application of exergy-based analyses (exergoeconomic, exergoenvironmental

and advanced analyses) Mergenthaler et al. studied a carbon black production facility with

these concepts. They recognized that burners contributed to the highest exergy destruction

among all components of the total plant, but, neither had the highest impact on cost

generation caused by exergy destruction, nor the highest impact on the

exergoenvironmental values. The largest cost generation took place within the boilers' heat

exchangers and the most important components for the exergoenvironmental analysis

were the reactors [129].

Jelihi et al. proposed a process integration of a conventional oil refinery hydrotreatment

unit and renewable hydrogen production and then they studied the effect of this

integration to reduction of costs and greenhouse gases emissions by exergoeconomic and

exergoenvironmental analyses. finally, it has been concluded that this integration yielded

to the considered reductions in cost and environmental impacts. The exergy analysis

showed that reactor, distillation column and separator contributed to energy losses

between 334-1100 MW. On the other hand, life cycle analysis through Eco indicator-99

method revealed the apparent damage effects to human health of greenhouse gases

emission from burning fuel gas for fired heater and reboiler, which corresponded to

953mPts yr-1. However, the impact of SO2 emission from burning excess H2S in the flaring

system to atmosphere was minor and could be neglected [130].

Finally, it is evident that from all the reported works until now, none of them performed

exergy, exergoeconomic, exergoeconomic diagnostic and exergoenvironmental analyses for

the integrated major units in gas refinery. Therefore, thesis aims to evaluate a typical gas

refinery main processing units of operation, taking into account thermodynamic, economic

and environmental aspects. In this regards, exergy, exergoeconomic, exergoeconomic

diagnostic and exergoenvironmental and corresponding advanced analyses are applied to

36


some major units of operation in order to identify the bottlenecks of exergy destruction

and to propose recommendations for system improvement by considering economic and

environmental factors as well. The units which will be analyzed in detail include: reception

facilities, condensate stabilization, dehydration and mercury guard, ethane recovery unit,

NGL fractionation unit, propane refrigeration unit, gas compression unit and sour water

treatment unit. Other units of operation, due to patented technology, have been considered

as black boxes and only the interactions with the main units have been taken into account.

37

CHAPTER 3

3 Methodology of exergy-based analyses A process designer is expected to optimize an objective measure of a system such as cost of

product, profit or return on investment, subject to certain constraints imposed for legal,

environmental or economic reasons. The options open to the designer include choice of

different process parameters and choice of a process flow sheet.

Many decisions are made by considering results obtained from energy analysis based on

the first law of thermodynamics only. An energy balance focuses on the quantity of energy

and fails to account for the quality of energy. The true thermodynamic value (quality) of an

energy resource is expressed by its potential to cause a change that is “to do something

useful”; such as heat a room, compress a gas, or promote an endothermic chemical reaction.

Kinetic, potential, mechanical, and electric energy can be fully converted in an ideal process

to any other form of energy, whereas the quality of thermal and chemical energy depends

on parameters (temperature, pressure, and chemical composition) of the energy carrier

and of the environment. Electricity clearly has a greater quality than low-pressure steam or

a cooling water stream in an energy conversion plant. The energy analysis does not

measure rationally the effectiveness with which fuels and resources are put to use and does

not allow the comparison of dissimilar systems.

On the contrary an analysis based on the first and second laws of thermodynamics (exergy

analysis) accurately identifies and evaluates the dissipations (exergy destructions) in a

plant and the efficiency of each system component. In thermodynamics, the quality of a

given quantity of energy is characterized by its exergy.

The second law of thermodynamics complements and enhances an energy balance by

enabling calculation of both the true thermodynamic value of an energy carrier, and the

real thermodynamic inefficiencies in processes or systems. The concept of exergy is

extremely useful for this purpose. The real inefficiencies of a system are exergy destruction,

occurring within the system boundaries, and exergy losses, which are exergy transfers out

38

Chapter 3- Methodology

of the system that are not further used in the overall installation. Some of the common

causes for exergy destruction include chemical reaction, heat transfer across a finite

temperature difference, fluid friction, throttling of flow, and mixing of dissimilar fluids.

The exergy analysis of a system is closely related to its economic indicators. It is exergy, not

energy, for which we pay. The exergy destruction in a system is not only a measure of the

efficiency; it also shows how much a particular inefficiency costs the operation of the

system. The economically optimal selection of a process (or a component) can be made by

comparing the costs of exergy destruction together with other capital and operating costs

for different technical solutions.

Moreover, in addition to the economic analysis used to calculate the cost of exergy

destruction, an assessment of the environmental impacts associated with a product over its

lifetime can provide information about the influence of thermodynamic inefficiencies in the

environment and can be led to a more environmental friendly design of a plant.

3.1 Exergy analysis

3.1.1 Exergy

Exergy is the maximum theoretical useful work (shaft work or electrical work) obtained

from a thermal system as it is brought into thermodynamic equilibrium with the

environment while interacting with the environment only. Alternatively, exergy is the

minimum theoretical work (shaft work or electrical work) required to form a quantity of

matter from substances present in environment and to bring the matter to a specified state.

The environment is a large equilibrium system in which the state variables (T0 ,p0) and the

chemical potential of the chemical components contained in it remain constant, when, in a

thermodynamic process, heat and materials are exchanged between another system and

the environment. It is important that no chemical reaction can take place between the

chemical components of the environment. The environment is free of irreversibilities, and

the exergy of the environment is equal to zero. The environment is part of surroundings of

any thermal system.

39


By considering only physical and chemical exergy values, the rate of total exergy ��jtotof the

j-th material stream is then (3.1):

��jtot = ��jPH + ��jCH (3.1)

where

• Physical exergy (��jPH) is the maximum theoretical useful work obtainable as the

system passes from its initial state (T, p, x) to the restricted dead state (T0, p0, x) while heat

transfer takes place only between the system and the environment. The rate of physical

exergy (��jPH) associated with the j-th material stream is defined according to (3.2):

��jPH = �� × 𝑒jPH = ��[�ℎj − ℎ0� − 𝑇0�𝑠j − 𝑠0�] (3.2)

Here �� is the mass flow rate, while e, h and s denote the specific exergy, enthalpy and

entropy, respectively, of the j-th material stream. The subscript 0 refers to the property

values of the same mass flow rate at temperature T0 and pressure p0 of the reference state,

and;

• Chemical exergy (��jCH) is the maximum theoretical useful work obtainable as the

system having the temperature and pressure of the reference environment is brought into

chemical equilibrium with this environment while interacting only with this environment.

The chemical exergy of an ideal mixture of N ideal gases is:

�� mix gasCH = �𝑥j

N

j=1

��jCH + 𝑅�𝑇0�𝑥j

N

j=1

𝑙𝑛(𝑥j) (3.3)

Here ��jCH is the standard molar chemical exergy of the j-th substance, and 𝑥j is the mole

fraction of the j-th substance in the system at T0. The rate of chemical exergy of the j-th

material stream is calculated as:

��jCH = �� × ��jCH (3.4)

40


3.1.2 Conventional exergy analysis

All thermodynamic processes are governed by the laws of conservation of mass and

energy. These conservation laws state that mass and energy can neither be created nor

destroyed in a process. Exergy, however, is not conserved but is destroyed by

irreversibilities within a system. Consequently, an exergy balance must contain a

destruction term, which vanishes only in a reversible process. Furthermore, exergy is lost,

in general, when a material or energy stream is rejected to the environment.

In order to conduct an exergy analysis, the specific exergies and exergy rates of each

stream have to be calculated.

In the past, the exergy analysis was conducted in terms of “exergy inlet (��in) / exergy outlet

(��out)”:

��in = ��out + ��D + ��L (3.5)

However, it is more appropriate and convenient for an exergy balance to be formulated in

terms of “exergy of fuel (��F) / exergy of product (��P)”:

��F = ��P + ��D + ��L (3.6)

In Eqs. (3.5) and (3.6), ��D is the exergy destruction due to irreversibilities within a system

(the k-th component), and ��L is the exergy losses, i.e. exergy transfer to the system

surroundings. This exergy transfer is not further used in the installation being considered.

For simplification, we can assume that the system boundary for each component has the

temperature and the pressure of the environment (T0, p0). Then, the exergy loss for the k-th

component is zero: ��L,k = 0.

Finally, the exergetic balance for the k-th component is:

��F,k = ��P,k + ��D,k (3.7)

where

��P −exergy of product is the desired result, expressed in exergy terms, achieved by the

system (the k-th component) being considered and ��F −exergy of fuel is the exergetic

resources expended to generate the exergy of the product.

41


The exergetic efficiencies of k-th component- as the ratio between product and fuel is

defined by Eq. (3.8):

ℰk =��P,k

��F,k= 1 −

��D,k

��F,k (3.8)

General guidelines for the definition of exergetic efficiencies have been formulated [131].

Improving an energy conversion system according to the results from an exergy analysis

means improving components with the highest values of the exergy destruction ED .or the

It should be mentioned that within a thermal system, there are components where exergy

is destroyed or transferred to the environment without obtaining something useful in the

same component. Such components are called dissipative components. No meaningful

exergetic purpose exists when these dissipative components are considered in isolation. No

exergetic efficiency can, therefore, be defined for these plant components, which often

serve another component or assist in reducing the investment cost in the overall system. In

these cases, the thermodynamic inefficiencies should be calculated for each dissipative

component. The value of the exergy destruction within a dissipative component is

calculated from (3.9) [18] [131]:

��D,kdiss = ��in,k − ��out,k (3.9)

With the exergy analysis the main sources of thermodynamic irreversibilities within a plant

are identified. If necessary, modifications to the plant can then be applied, in order to

reduce these inefficiencies. Since the adoption and/or the development of systems are

mainly driven by economics and in most cases considering less environmental impacts, the

thermodynamically optimal design can be used as the starting point for cost minimization

and designing plants with lower environmental impacts.

The methodologies of an economic analysis and environmental impact assessment (which

will be performed by LCA approach) as well as the combinations with an exergy analysis,

which are called exergoeconomic and exergoenvironmental analyses, respectively, are

described in next sections.

42


3.2 Exergy and economics

3.2.1 Economic analysis

Through an economic analysis, the economic feasibility of the construction and operation,

as well as the cost of the generated product of a facility can be estimated. With proper cost

estimations through the project design, important basis for decision making can be

achieved. To conduct an economic analysis, different approaches can be used. In this thesis

the total revenue requirement (TRR) method is used. Under the TRR method, the cost of

the product can be calculated through the following four steps: (a) Estimation of the total

capital investment (TCI), (b) Determination of the economic, financial, operating, and

market input parameter for the detailed cost calculation, (c) Calculation of the total

revenue requirement (TRR), (d) Calculation the levelized cost of products.

The TCI of a plant is counted as a one-time cost, while the cost of fuel or operating and

maintenance costs are categorized as the continuous expenses. Hence, TCI comprises of

two main components: Fixed Capital Investment (FCI) and Other Outlays.

Table 3.1 shows a general list of the items to be considered in the estimation of TCI for a

new system [18].

As per Table 3.1; cost estimates for FCI consists of two cost parts: Direct and Indirect costs.

Direct costs are the costs of all permanent equipment, materials, labor and other resources

involved in fabrication, erection and installation of the permanent facilities. Indirect costs

do not become a permanent part of the facilities but are required for the orderly

completion of the project. Lastly, other outlays consist of start-up costs, working capital,

cost of licensing, research and development, and allowance for funds used during

construction (interest incurred during construction).

The first step and the main challenge in an economic analysis is the estimation of the

purchased equipment cost (PEC) of plant components, where the value of each cost

component is estimated based on the (PEC) of the equipment, by multiplying them with

appropriate factors.

43


Table 3.1 Breakdown of Total Capital Investment (TCI)

I. Fixed-Capital Investment (FCI) A. Direct costs(DC) A.1. Onsite Costs (ONSC) Purchased-equipment cost (PEC) PEC Purchased-equipment installation 20-90 % PEC Piping 10-70 % PEC Instrumentation and controls 6-40 % PEC Electrical equipment and materials 10-15 % PEC A.2. Offsite Costs (OFSC) Land 0-10 % PEC Civil, structural and architectural work 15-90 % PEC Service facilities 30-100 % PEC Total direct costs (DC) =(ONSC)+(OFSC) B. Indirect Costs (IC) B.1. Engineering and supervision 25-75 % PEC B.2. Construction costs 15 % DC B.3. Contingencies 8-25 % sum of above

t Total indirect costs (IC) Total Fixed Capital Investment (FCI)=(DC)+(IC) Plant Facility Investment (PFI)=(FCI)-cost of land II. Other Outlays

Startup costsa 5-12 % FCI Working capitalb 10-20 % TCI Costs of licensing, research and developmentc - Allowance for funds used during constructiond 15 % FCI Total Capital Investment (TCI)=(FCI)+(Other Outlays)

a) Startup costs (SC) are mainly associated with design changes that have to be made after completion of construction but before the system can operate at design conditions. Here, the costs are assumed to be the sum of 1) one month of fixed operating and maintenance costs, 2) one month of variable operating costs calculated at full load, 3) one week of fuel at full load, and 4) 2 % of plant-facilities investment. The fixed (OMC) costs are composed of costs for operating labor, maintenance labor, maintenance materials, overhead, administration and support, distribution and marketing, and so forth. The variable operating costs depend on operating time of system and consist of the costs for operating supplies other than fuel costs (e.g., raw water and limestone), catalysts, chemicals, and disposing of waste material. b) The working capital (WC) represents the funds required to sustain plant operation, that is, to pay for the operating expenses before payment is received through the sale of the plant products. In here, the WC is assumed to be the sum of 1) two months of fuel cost at full load, 2) two months of variable operating cost at full load, 3) three months of labor costs, and 4) contingency of 25 % of the above three items. c ) Licensing and R&D costs are not considered in this thesis. d) Allowance for funds used during construction (AFUDC) represents the time value of money during construction periods; sometimes it is called interest during construction. In this thesis, it is calculated taking the required annual return of each financing into account; 8 % of interest rate is used for common equity while 6 % is used for debt.

44


The type of equipment and its size, the range of operation, and the construction materials

have been determined during the flow diagram development. The best cost estimates for

purchased equipment can be obtained directly through vendors’ quotations. The next best

source of cost estimates is cost values from past purchase orders, quotations from

experienced professional cost estimators, or calculations using the extensive cost databases

often maintained by engineering companies or company engineering departments. If the

two most preferred options are not obtainable, the purchased equipment cost can be also

estimated via available charts in the literature. In this project, approximate costs have been

estimated based on latest method.

The charts are usually built using the help of a high volume of data in cost and design.

When parameters necessary to get values from the charts are known, such as heat

exchanger’s heat transfer area or compressor’s power, it is easily possible to study the

charts for the desired cost of the equipment. The charts also allow effects of the equipment

characteristics to be taken into account, for example temperature and pressure. The

equipment base cost (CB) which obtainable from the charts is corrected by having these

effects as factors such as material factor (fm), temperature factor (fT), design factor (fd) or

pressure factor (fp). Furthermore, bare module factors (fBM) can be included as well to the

equipment final module cost of, as shown in (3.10):

𝐶BM = 𝐶B𝑓d𝑓m𝑓p𝑓T𝑓BM (3.10)

However, in general, there are very limited cost data of different sizes or capacities;

therefore, an exponential rule is used according to (3.11):

𝐶PEC,2 = 𝐶PEC,1(𝑋2𝑋1

)𝛼 (3.11)

Where; 𝐶PEC,2 is the purchased equipment cost at given capacity(𝑋2); which can be

obtained in case that 𝐶PEC,1 and 𝑋1 are known values. The exponent, α, is a constant within

a given size range and it is usually lower than unity. In the absence of specific information,

an exponent value of 0.6 may be used.

45


When the costs of the all equipment are known, they must be brought to the same

reference year; that is used as the base year for all cost calculations. This conversion can be

made using cost indices such as; Chemical Engineering Plant Cost Indices (CEPCI) based on

(3.12):

𝑃𝐸𝐶Ref Y = 𝑃𝐸𝐶Coll Y �𝐶𝐸𝑃𝐶𝐼Ref Y𝐶𝐸𝑃𝐶𝐼Coll Y

� (3.12)

From the PEC, the cost rate ��kof each component k, is estimated using (3.13):

��k =𝐶𝐶 + 𝑂𝑀𝐶𝑃𝐸𝐶tot × 𝜏

× 𝑃𝐸𝐶k (3.13)

Here, τ represents the annual operating hours and OMC the operating and maintenance

costs of the plant. The carrying charges are calculated subtracting the fuel and operating

and maintenance costs of the plant from its TRR.

The calculated cost rates are used as input for the exergoeconomic analysis [18].

The annual total revenue requirement (TRR, total product cost) for a system is the revenue

that must be collected in a given year through the sale of all products to compensate the

system operating company for all expenditures incurred in the same year and to ensure

sound economic plant operation. It consists of two parts: carrying charges and expenses.

Carrying charges are a general designation for charges that are related to capital

investment whereas expenses are used to define costs associated with the operation of a

plant. Carrying charges (CC) include the following: total capital recovery; return on

investment for debt, preferred stock and common equity; income taxes; and other taxes

and insurance. Examples for expenses are fuel cost (FC) and operating and maintenance

costs (OMC).

All annual carrying charges and expenses have to be estimated for each year over the entire

economic life of a plant.

The series of annual costs associated with carrying charges CCn and expenses (FCn and

OMCn) for the n − th year of plant operation is not uniform. When taxes are not considered,

the levelized carrying charges can be calculated as (3.14):

46


𝐶𝐶L = 𝑇𝐶𝐼 × 𝐶𝑅𝐹 (3.14)

In (3.14) is assumed that each money transaction occurs at the end of each year. The

capital-recovery factor CRF is given by (3.15):

𝐶𝑅𝐹 =𝑖eff (1 + 𝑖eff)n

(1 + 𝑖eff)n − 1

(3.15)

Here 𝑖eff is the average annual effective discount rate (cost of money), and 𝑛 denotes the

plant economic life expressed in years.

If the series of payments for the annual fuel cost (FCn) is uniform over time except for a

constant escalation 𝑟FC (i.e., FCn = FC0(1 + 𝑟FC)n), then the levelized value FCL of the

series can be calculated by multiplying the fuel expenditure FC0 at the beginning of the first

year by the constant escalation levelization factor CELF as per (3.16):

𝐹𝐶L = 𝐹𝐶0 × 𝐶𝐸𝐿𝐹 = 𝐹𝐶0𝑘FC(1− 𝑘FCn )

(1− 𝑘FC)𝐶𝑅𝐹

(3.16)

where

𝑘FC =1 + 𝑟FC1 + 𝑖eff

(3.17)

and 𝑟FC = const.

The terms 𝑟FC and CRF denote the annual escalation rate for the fuel cost and the capital-

recovery factor, respectively.

Accordingly, the levelized annual operating and maintenance costs OMCL are given by

(3.18):

𝑂𝑀𝐶L = 𝑂𝑀𝐶0 × 𝐶𝐸𝐿𝐹 = 𝑂𝑀𝐶0𝑘FC(1− 𝑘FCn )

(1− 𝑘FC)𝐶𝑅𝐹

(3.18)

where

𝑘OMC =1 + 𝑟OMC1 + 𝑖eff

(3.19)

47


and 𝑟OMC = const. and it is the nominal escalation rate for the operating and maintenance

costs.

Finally, the levelized total revenue requirement (TRRL) is obtained from (3.20):

𝑇𝑅𝑅L = 𝐶𝐶L + 𝐹𝐶L + 𝑂𝑀𝐶L (3.20)

The major difference between a conventional economic analysis and an economic analysis

conducted as part of an exergoeconomic analysis is that later is done at the plant

component level.

Finally, the non-uniform annual monetary values associated with the investment,

operating, maintenance, and fuel costs of the system being analyzed are levelized, that is

they are converted to an equivalent series of constant payments (annuities).

3.2.2 Exergoeconomic analysis

An exergoeconomic analysis is an appropriate combination of an exergy analysis with

economic principles. This is achieved through exergy costing, by which a specific cost c is

assigned to each exergy stream of the plant. The specific cost of stream j, 𝑐j , multiplied by

the exergy of the same stream, ��j , provides the cost rate ��j associated with stream j:

��j = 𝑐 × ��j (3.21)

To perform an exergoeconomic analysis on a plant, cost balances are stated at the

component level resulting in a system of balance equations. A cost balance shows that the

sum of cost rates associated with all exiting exergy streams equals the sum of cost rates of

all entering exergy streams plus the appropriate charges (cost rates) due to capital

investment as well as to operating and maintenance expenses. The cost balance can be

written in terms of inlet/outlet exergy as per (3.22):

∑ ��out,k = ∑ ��in,k + ��k (3.22)

or in terms of exergy of fuel and exergy of product:

��P,k = ��F,k + ��k (3.23)

or

48


𝑐P,k��P,k = 𝑐F,k��F,k + ��k (3.24)

��P,k and ��F,k are the cost rates associated with product exergy ��P,k and fuel exergy ��F,k , and

𝑐P,k and 𝑐F,k represent the costs per unit of exergy associated with product and fuel,

respectively.

If the number of exergy streams exiting the component (𝑁out) is higher that 1 (𝑁out > 1),

we need to formulate (𝑁out − 1) auxiliary equations, to be able to calculate the costs

associated with the exiting streams when the costs associated with all entering streams are

known. The P-principle (on the product side) and the F-principle (on the fuel side) are used

to determine the auxiliary equations. The P-principle states that the cost per unit of exergy

is supplied to all streams that belong to the definition of the product of the component at

the same cost. The F-principle states that the cost, associated with the exergy removed

from a considered component, has the same specific cost as the exergy supplied to the

upstream components [18] [131].

With the aid of cost balances and auxiliary equations, the cost rate and the cost per unit of

exergy are calculated for each exergy stream in the overall system. In this way, we

associate with each stream not only mass, energy, entropy and exergy but also cost. This is

the first step in understanding the cost formation process and the real cost sources and,

thus, in making a well-informed decision for improving the cost effectiveness of an energy

conversion system.

When the necessary balance equations are stated and solved, the exergoeconomic

evaluation follows. Through the evaluation iterative step to improve and finally optimize

the considered system are revealed. An important outcome of the exergoeconomic analysis

is the relation of exergy destruction with costs:

��D,k = 𝑐F,k��D,k (3.25)

where, 𝑐F,k is the specific cost of fuel of component k.

The calculation of the cost of exergy destruction facilitates the evaluation of plant

components and allows comparison between cost of exergy destruction and investment

cost. The components are first ranked and evaluated based on their total costs ��k + ��D,k.

49


The higher the costs are, the more significant the effect of the component to the overall

plant.

The contribution of the capital cost, ��k , to the sum of costs is expressed by exergoeconomic

factor, 𝑓k , defined by (3.26):

𝑓k =��k

��k + ��D,k (3.26)

Exergoeconomic factor provides information for evaluating the performance of a

component. It is necessary to know the relative significance of contribution of non-exergy-

related and exergy destruction costs.

A low value of the exergoeconomic factor suggests that cost savings in the entire system

might be achieved by improving the component efficiency (reducing the exergy

destruction) even if the capital investment for this component will increase. A high value of

this factor suggests a decrease in the investment costs of this component at the expense of

its exergetic efficiency. Depending on the calculated values, trade-offs between exergy

destruction and investment costs are suggested. The goal is to improve the overall plant

from both the thermodynamic and the economic viewpoints.

Another important variable of the exergoeconomic evaluation is the relative cost

difference, 𝑟k. For a given component k, the difference between the specific cost of product,

𝑐P,k, and the specific cost of fuel, 𝑐F,k ,depends on the cost of exergy destruction, ��D,k ,and

the related ��k:

𝑟k =𝑐P,k − 𝑐F,k

𝑐F,k=��D,k + ��k𝑐F,k��P,k

(3.27)

Information about compromises between the cost of exergy destruction and the

investment cost of components, resulting from the exergoeconomic evaluation, can be used

for the iterative design improvement of the plant. The objective is to reduce the cost

associated with the product of the overall plant.

50


3.2.3 Exergoeconomic diagnostic

This section introduces a methodology, based on thermoeconomics, to the operation

diagnosis of energy systems. Diagnosis is always performed through comparison of at least

two states: the actual state of the plant, which is to be examined, and a reference state,

which is a condition without any anomalies. The presence of anomalies in the actual state

determines deviations in some of the measured quantities with respect to the reference

values. In general, thermoeconomic diagnosis’ objective is detection of the efficiency

deviation, the location of the main causes and the quantification of its effects in terms of

additional fuel consumption or economic impact.

The methodology consists of the following steps:

• Identification of components and degradation symptoms,

• Clear description of the symptoms to allow simple problem recognition,

• Evaluation of the deterioration mechanisms and the root causes, and

• Validation and conclusions.

As a result, a diagnostic procedure should yield those specific recommendations to change

operating strategies, maintenance actions and components replacement.

Moreover, it is very difficult to locate and to find the real causes of all effects that can

simultaneously occur. This is due to the high complexity of interrelations among

components. A successful interpretative procedure will reduce the non-accountable losses

to a minimum, and will put forward the ultimate causes of component degradation.

Thermoeconomic diagnosis is a Second Law based technique oriented to operation

analysis. The exergy balance of an installation allows us to allocate and calculate

irreversibilities in the production process and to identify the equipment which affects

overall efficiency and the reasons thereof. This information, although useful, has proved

not to be enough. In practice, when attempting to achieve energy savings in an installation,

we must consider that not all irreversibility can be avoided. The potential exergy saving is

limited by technical and economic constraints. Thus, the technical possibilities for exergy

savings, which is called technical exergy saving, are always lower than the theoretical limit

of thermodynamic exergy losses.

51


Therefore, the additional fuel consumption can be expressed as the difference between the

resources consumption of the plant in operation and the resources consumption for a

reference or design condition, with the same production objectives, i.e. with the same total

plant product.

∆��F,tot = ��F,tot(𝑋)− ��F,tot(𝑋0) (3.28)

It can be broken up into the sum of the irreversibilities (=exergy destruction) of each

component:

∆��F,tot = ∆𝐼tot = �(𝐼j(𝑋)− 𝐼j(𝑋0)N

j=1

) = �∆𝐼j

N

j=1

(3.29)

However, the local exergy savings which can be achieved in the different units or processes

of an installation are not equivalent. The same decrease in the local irreversibility of two

different components leads, in general, to different variations of the total plant energy

consumption. It is shown in the fuel impact formula that expresses the increase of

resources consumption in the plant, as a function of the marginal exergy consumption of

each individual component of the plant:

∆��F,tot = ��𝑐Pj

N

j=0

�N

i=1

(𝑋)∆𝜅𝑗𝑖� ��Pi(𝑋0) + 𝑐Pj𝛥��Pi,out (3.30)

The variation of the marginal exergy consumption of each component increases its

resources consumption and then its irreversibilities in a quantity ∆𝜅ji��Pi ,which is called,

malfunction. Consequently, it implies an additional consumption of the external resources

given by 𝑐Pj∆𝜅𝑗𝑖��Pi, which is called the malfunction cost. Therefore, the total fuel impact can

be written as the sum of the fuel impact or malfunction cost of each component, as shown

in (3.30). In order to analyze the impact on resource consumption of a plant, we need to

know the design and operation values of the irreversibilities, product, unit exergy cost for

design and operation, and the increase of the marginal exergy consumption of each

component of the plant [20] [96] [132,133].

52


3.3 Exergy and environmental impacts

3.3.1 Life Cycle Assessment (LCA)

In the last decades, industrial activities resulted in an increase of pollutants’ emissions and

growth in depletion of natural resources; which can be assessed by methods using a life

cycle assessment (LCA). LCA, as internationally standardized method, has been developed

for assessing the responsibility of each component of a system to overall environmental

impact and identifying the source of impacts. LCA analyses the consumption and emission

of material flows from all process steps within the life cycle.

The LCA process consists of several steps including: goal definition and scoping (defining

the system under consideration), inventory analysis (identifying and quantifying the

consumption and release of materials), and interpretation (evaluation of the results). Based

on the inventory data and different methodologies, the environmental impacts caused by

depletion and emissions of a natural resource can be quantified. In this regard,

damage-oriented impact analysis method, Eco-indicator 99 is applied because it considers

many environmental aspects and uses average European data [102].

Eco-indicator 99 comprises of three categories of damage: damage to human health,

ecosystem and natural resources. After calculating the environmental effects of the

different categories, the values are optionally normalized, weighted and the result is

expressed in Eco-indicator points (Pts). Higher values of the Eco-indicator are associated

with higher damage [117].

The structure and the considered environmental aspects of Eco-indicator 99 are displayed

in Fig. 3.1.

The standard Eco-indicator 99 inventory values are available for the production and

processing of a large number of materials, transport processes, disposal scenarios, etc. The

impact is calculated with reference to the annual environmental impact of a European

inhabitant. The scale is chosen in such a way that the value of 1 Point is representative for

one thousandth of the yearly environmental load of one average European inhabitant (this

value is calculated by dividing the total environmental load in Europe by the number of

inhabitants and multiplying it by 1,000) [134].

53


Fig. 3.1 General structure of the Eco-indicator 99 [134]

54


Depending on the attitude and perspective of different societies, during characterization,

normalization, and weighting, subjective choices are unavoidable. There are three

Archetypes: Individualists focus on the present, neglecting long term effects and take only

proven effects into account. Egalitarians weigh the effect on future generations and take all

possible effects into account, even with minimal scientific proof. Hierarchists keep a

balance between short and long-term perspectives and take environmental damages into

account based on consensus [24].

In this thesis, the ‘hierarchists' perspective is selected for impact assessment.

The application of an LCA assists in understanding the formation of environmental impacts

associated with the components. The influence of thermodynamic inefficiencies in the

environmental impact can be analyzed by performing an exergoenvironmental analysis

[117].

3.3.2 Exergoenvironmental analysis

An exergoenvironmental analysis is an appropriate combination of an exergy analysis and

a life cycle assessment. The whole procedure of an exergoenvironmental analysis is very

similar to that of an exergoeconomic analysis. In analogy to the exergy costing in

exergoeconomic analysis, environmental impact value is assigned to each exergy stream in

an exergoenvironmental analysis, as formulated in (3.31):

��j = 𝑏j × ��j (3.31)

where, specific environmental impact 𝑏j, is assigned to each exergy stream ��j, and is

associated with the environmental impact rate ��j.

To calculate the value for environmental impact flow of each exergy stream as well as the

output streams, balance equations are formulated at component level [93], considering the

functional relations of each incoming and outgoing streams [117].

The environmental impact balance for the k-th component states that the sum of the

environmental impact associated with all input streams of the component equals the sum

of the environmental impact associated with all output streams of the same component as

per (3.32):

55


��in,k + ��k + ��kPF� = ��out,k (3.32)

Here, ��in/out = 𝑏in/out��in/out (b: specific environmental impact of inlet and outlet streams,

∑ ��in,k is the sum of the environmental impacts associated with the steams entering

component k, ∑ ��out,k is the sum of the environmental impacts associated with the streams

leaving component k and ��kPF is the impact of pollutant formation. Eq. (3.32) need to be

rearranged to reflect the exergetic characteristics of each component and can be

formulated as shown in (3.30):

��F,k + (��k + ��kPF) = ��P,k (3.33)

Here, ��F,k indicates the environmental impact rate of exergy of fuel while ��P,k means the

environmental impact rate of exergy of product and ��k is component-related

environmental impact of component k, which is obtained in LCA considering the entire life

cycle of the component.

To solve a number of balance equations for the entire system, auxiliary equations are

necessary if the number of unknown variables in (3.32) or (3.33) is greater than one [102].

In this thesis, the same approach used in the SPECO method [131] is adaptively applied to

formulate the auxiliary equations.

The ��kPF is the component-related pollutant formation, which is calculated from (3.34):

��kPF = �𝑏jPF(��j,out − ��j,in) (3.34)

Here, ��in and ��out are the mass flow rates of pollutants entering and exiting component k,

respectively. 𝑏jPF is the environmental impact per unit mass of j-th pollutant chemical

substances which are emitted to the environment; the value can be obtained directly

through an LCA.

Pollutant formation is meaningful only when a chemical reaction occurs within the

component; in any other case, it is zero [24]. In this thesis, only pollutants which are finally

emitted to the environment are taken into account, for example CO2, CO, and NOx [102].

The environmental impact caused by the exergy destruction occurring within the k-th

component, ��D,k , is calculated as:

56


��D,k = 𝑏F,k × ��D,k (3.35)

Here, 𝑏F,k is the specific environmental impact of the exergetic-fuel of component k, which

is calculated based on the exergy of fuel and product defined in the exergy analysis.

By comparing ��D,k and ��k of each component, it can be determined which component and

how is mostly responsible for the environmental impact of the whole system.

To conduct exergoenvironmental evaluations, exergoenvironmental variables are defined

and applied: exergoenvironmental factor and relative environmental impact difference.

The exergoenvironmental factor is defined as (3.36), which indicates the contribution of

the component-related environmental impact on the total environmental impact.

𝑓b,k =��k

��k + ��D,k

(3.36)

In components showing a high value of 𝑓b,k , the construction, operating and maintenance,

and disposal stage have greater effect on the total impact than that of the system operation.

Therefore the use of environmentally friendly materials and manufacturing process have

great importance, even they cause a decrease in efficiency in other words increase in

exergy destruction. A relatively low value of 𝑓b,k implies that exergy destruction dominates

the environmental impact of the k-th component. In this case, an efficiency increase

(decrease in exergy destruction) is of importance. If the assumption of ��k = 0 is applied,

then (3.36) is not meaningful.

Another important variable for the exergoenvironmental evaluation is the relative

environmental impact difference, 𝑟b,k , which is defined by (3.37). Comparison of value

identifies the components with the highest relative increase between𝑏F,k and 𝑏P,k :

𝑟b,k =��k + ��D,k

𝑏F,k��P,k=𝑏F,k − 𝑏P,k

𝑏F,k

(3.37)

The environmental impact difference of component k, 𝑟b,k , depends on the impact of its

exergy destruction and its component-related impact. Thus, it is an indicator of the

reduction potential of the component.

57


3.4 Advanced exergy-based analyses

With conventional exergy-based analyses, the locations, magnitudes and causes of

irreversibilities, costs and environmental impacts are identified, and a general direction for

improvement is indicated. However, none of the conventional analyses are able to reveal

estimate the real potential for improvement. Advanced exergy-based analyses attempt to

address this shortcoming.

3.4.1 Advanced exergy analysis

Thermodynamic improvement (optimization) of the energy conversion system means, in

general, decreasing the irreversibilities (exergy destruction) within the overall system.

However, the conventional exergy analysis cannot answer the following questions that are

in the focus of interest in practical applications: by how much can the irreversibility within

the k-th component be decreased? Therefore, the limitations of the conventional exergy

analysis are: we cannot estimate the real potential for improving the system components.

These limitations contributed in the past to the fact that an exergy analysis was not very

popular among energy practitioners. To answer these questions, the advanced exergy

analysis has been developed and applied for different exergy-conversion systems [23]

[135-140].

In an advanced exergy analysis, the exergy destruction in each component is split into

avoidable and unavoidable parts. This splitting provides the designer and operator of the

studied system with unambiguous and valuable detailed information with respect to

options for improving the overall efficiency.

The exergy destruction rate that cannot be reduced due to technological limitations such as

availability and cost of materials and manufacturing methods is the unavoidable ��D,kUN part

of the exergy destruction. The remaining part represents the avoidable ��D,kAN part of the

exergy destruction

��D,k = ��D,kUN + ��D,k

AN (3.38)

58


For calculating the unavoidable exergy destruction ��D,kUN within each system component, the

conditions that just cannot be realized in the foreseeable future should be assumed. The

value of the unavoidable exergy destruction within the k-th component is calculated as:

��D,kUN = ��P,k �

��D,k

��P,k�UN

(3.39)

where the value ��D,k��P,k

�UN

should be calculated for the k-th component using the process with

unavoidable irreversibilities. The approach developed by Tsatsaronis and Park in 2002, was

used: Each component with unavoidable irreversibilities should be simulated in isolation

from the overall system [136].

3.4.2 Advanced exergoeconomic analysis

In advanced exergoeconomic analysis, depending on whether the costs of exergy

destruction can be avoided or not, is applied and the cost rate of exergy destruction is

splitted into the unavoidable cost rate of exergy destruction ��D,kUN and accordingly,

avoidable cost rate of exergy destruction ��D,kAN within component k:

��D,k = ��D,kUN + ��D,k

AV (3.40)

The value of the unavoidable cost rate of exergy destruction within the k-th component is

calculated based on (3.41):

��D,kUN = 𝑐F,k

real × ��D,kUN (3.41)

where, ��D,kUN is the unavoidable part of exergy destruction rate that has been calculated in an

advanced exergy analysis with considering the most favorable operating conditions that

result in the lowest possible exergy destruction. Specific cost of fuel 𝑐F,kreal of component k

has been also calculated in exergoeconomic analysis of the component k in real condition of

the component.

3.4.3 Advanced exergoenvironmental analysis

In advance exergoenvironmental analysis, the focus is rather on the impacts related to the

exergy destruction and pollutant formation [102]. Like the exergy destruction, the

59


environmental impact associated with exergy destruction is separated into

avoidable/unavoidable as:

��D,k = ��D,kUN + ��D,k

AV (3.42)

The unavoidable environmental impact rate, ��kUN due to exergy destruction is calculated

via (3.43):

��D,kUN = 𝑏F,k

real × ��D,kUN (3.43)

where 𝑏F,kreal has been calculated by exergoenvironmental analysis and ��D,k

UN also is obtained

by advanced exergoeconomic analysis.

Unavoidable environmental impact rate related to pollutant formation is calculated as:

��kPF,UN = �𝑏jPF(��j,out − ��j,in) (3.44)

Since pollutant formation process was not evaluated in this thesis, further description of

the associated methodology is not meaningful.

60

CHAPTER 4

4 Process description and simulation

4.1 Introduction

This section covers the overall process description of a typical onshore gas refinery. Raw

gas from an offshore platform is transferred to gas refinery via sea line. Onshore facilities

include all processing units, utilities, offsite and infrastructure necessary to produce sales

gas to domestic gas network, ethane gas as feed to petrochemical plants, commercial grade

of propane and butane for export, solidified sulphur and stabilized condensate for export.

The composition of feed gas and the specification of refinery’s products are summarized in

Tables 4.1 and 4.2, respectively:

Table 4.1 Feed gas composition

Components Molar ( %) Components Molar( %) H2O 1.56 C3 1.86 N2 3.31 iC4 0.43 CO2 1.74 nC4 0.69 H2S 0.66 iC5 0.30 C1 80.95 nC5 0.30 C2 5.17 C6~C20 cut 3.03

Table 4.2 Products composition

Product Composition purity Sales gas Min 80 % C1 Condensate Min 76 % C6~C20 Ethane Min 98 % C2 Propane Min 98 % C3 Butane Min 97.5 % C4

61

Chapter 4- Process Description and Simulation In general, the overall process can be summarized as follows1:

Receiving facilities for HP separation of raw gas and condensate/water (unit 100)

Condensate stabilization producing stabilized condensate for export (unit 103)

Gas treatment facilities producing sales gas, gaseous ethane and NGL and consist of:

- H2S removal from gas / CO2 partial removal from gas (unit 101)

- Dehydration and mercury guard (unit 104)

- Ethane extraction unit producing sales gas, gaseous ethane and NGL (unit 105)

NGL fractionation facilities to sour liquid butane and propane (unit 107)

Gaseous ethane cut treatment for CO2 removal and drying for export (unit 116)

Propane and butane treatment and drying for export (units 114 & 115)

Export gas compression to export pipeline pressure (unit 106)

MEG regeneration and injection unit (unit 102)

Sulphur recovery producing liquid sulphur for solidification and export (unit 108)

Propane refrigeration cycle (unit 111)

Sour water treatment unit (unit 109)

In this research, some major units of operation have been studied, and some units

(101,114,115&116) due to patented technology have been considered as black boxes. Units

102, 108, 113 are patented technology as well and common between some other refineries

or units, therefore, due to lack of data and intermittent operation are excluded from this

study. Studied units are 100,103,104,105,106,107,109 and 111 and detailed in following

section.

A typical block diagram of units in plant is shown in Fig. 4.1.

1 Text description contains the basic component of the plant that are presented in Fig. 4.1 while some more details descriptions are presented in the Figures in Appendix A.

62

Chapter 4- Process Description and Simulation

Fig. 4.1 Block flow diagram of a typical gas refinery

63

Chapter 4- Process Description and Simulation 4.1.1 Gas processing units

The processes associated with the gas stream are discussed in this section and then the

required processes for treatment on hydrocarbon liquid will be explained in next section.

A mixture of gas, condensate and glycolated water with temperature of 25 ⁰C and pressure

of 75 bar and mass flow rate of 50900 kmole hr-1, from offshore platform via sea line is first

transferred to the Receiving facilities and HP separator (Unit 100 in Fig. 4.1). Mixture first

enters the slug catcher (100-L1 in Fig. A.2) in onshore gas refinery.

Slug catcher is finger type and consists of six 46” fingers. This component separates gas,

condensate, and glycolated water and for this purpose has been designed in four sections

as: Gas-Liquid separation section with a slope of 1:20; Intermediate section which is

located downstream of the gas outlet of the separation section; Storage section with a slope

of 1:100 which is connected to main header of the gas outlet from separation section, and

Liquid-Liquid separation section which collects the liquid from separation section.

Then, HP raw gas flows to the HP separator (100-D1 in Fig. A.2); where final separation of

liquid from gas takes place. Overhead gas from the HP Separators is routed to the gas

treating unit (Unit 101 in Fig. 4.1) through a gas heater (100-E1 in Fig. A.2), which heats the

gas up, in order to avoid hydrates formation. This gas heater may be by-passed during

summer time.

In gas treating unit (Unit 101 in Fig. 4.1), H2S and CO2 from the inlet sour feed gas are

removed. Selective H2S removal from the sour gas is based on the use of generic MDEA

treatment process which is a licenced technology. The removed sulphur from gas is sent to

sulphur recovery unit (Unit 108 in Fig. 4.1).

The sweet gas from gas treating unit (Unit 101 in Fig. 4.1) is routed to dehydration and

mercury guard unit (Unit 104 in Fig. 4.1) to remove water and recover any mercury from

the sweet gas before feeding the ethane recovery unit (Unit 105 in Fig. 4.1). Therefore, the

sweet gas is firstly cooled in the wet gas / treated gas exchanger (104-E5 in Fig. A.4), and

then will be further cooled by vaporization of propane refrigerant in the wet gas chiller

(104-E6 in Fig. A.4). These cooling processes maximize the amount of condensed water and

consequently minimize the required adsorption capacity of the dehydration beds. The

64

Chapter 4- Process Description and Simulation water condensed in the chiller is separated from the gas in the dryer’s inlet separator (104-

D8 in Fig. A.4) and the gas is sent to the dryers (104-R1 A/B/C in Fig. A.4)and the water is

sent to sour water stripper feed drum (109-D13 in Fig. A.9) of sour water treatment unit

(Unit 109 in Fig. 4.1).

The dehydration and mercury guard unit (Unit 104 in Fig. 4.1) consists of 3 dryers’ bed

(104-R1 A/B/C in Fig. A.4), two of them being operated in adsorption mode, while the third

one being regenerated. In adsorption phase, as the gas passes downward through the

dryers, the water is absorbed by the molecular sieves. The dry gas exiting the bottom of the

dryers, passes through the dryer’s filters in order to remove the molecular sieve fines, and

then flows to the heat exchanger (104-E7 in Fig. A.4) and finally to mercury guard reactor

(104-R2 in Fig. A.4), leading to mercury sulfide formation. A split of dry gas is then heated

in the dryer’s regeneration furnace (104-H1 in Fig. A.4) to be used as regeneration gas

returning to dryers. The gas is heated to 250 °C in the dryers’ regeneration furnace (104-

H1 in Fig. A.4) and passes through the molecular sieve beds in an upward direction. The

design assumes a temperature drop of 20 °C in the transfer line, i.e. a regeneration gas

temperature of 230 °C entering the dryers (104-R1 A/B/C in Fig. A.4).

The wet and hot effluent gas is cooled in regeneration gas air cooler (104-A4 in Fig. A.4).

Condensed water is removed in the regeneration gas separator (104-D9 in Fig. A.4) and

sent to the sour water stripper feed drum (109-D13 in Fig. A.9) of sour water treatment

unit (Unit 109 in Fig. 4.1). The recovered gas is then compressed in the dryer’s

regeneration compressors (104-K3 A/B in Fig. A.4) and recycled back to the wet

gas/treated gas exchanger (104-E5 in Fig. A.4). After H2S removal, dehydration and

mercury removal, the dry sweet gas is routed to the ethane recovery unit (Unit 105 in Fig.

4.1), where the gas is processed to produce “Sales gas” which will be exported through the

Export Gas Compression unit (Unit 106 in Fig. 4.1), and Ethane cut to be used as a

petrochemical feed.

The gas is then cooled down to -35 °C in the cold box (105-E8 in Fig. A.5) in contact with:

a propane stream at medium pressure (propane at 19.3 °C),

65

Chapter 4- Process Description and Simulation

The cold sales gas coming from demethanizer column (105-C2 in Fig. A.5) & Cold

box (105-E8 in Fig. A.5) at -87.3 °C and going to the Gas/Gas exchanger (104-E5 in

Fig. A.4) at 16.8 °C,

a withdrawal stream from and to lower section of demethanizer (105-C2 in Fig.

A.5) which entering and leaving cold box (105-E8 in Fig.A.5) at 12.6 °C and 18.5 °C,

a propane stream at low pressure (propane at -4.3 °C),

a withdrawal stream from and to medium section of demethanizer (105-C2 in Fig.

A.5), which entering and leaving cold box (105-E8 in Fig. A.5) at -37.1 °C and

-11.9 °C).

At -35 °C a major portion of the butane and heavier components are condensed. The liquid

phase also contains significant amounts of methane and ethane which must be removed.

The two phases flow is separated in feed flash KO drum (105-D10 in Fig. A.5) and liquid is

sent to demethanizer (105-C2 in Fig. A.5) while the exiting gas is split into two streams:

One side stream is sent to cold box (105-E8 in Fig. A.5) and the other stream feeds the feed

gas expander (105-X1 in Fig. A.5) before feeding the demethanizer (105-C2 in Fig. A.5).

Demethanizer (105-C2 in Fig. A.5) is a stripper-absorber column that produces sales gas as

an overhead product and a wide-range liquid as a bottom product. Between the bottom

trays and the feed tray, light components are stripped out of the liquid phase and heavy

components are absorbed from the gas phase. Between the feed tray and the top tray,

heavier compounds are removed from the gas phase being absorbed by the liquid reflux

coming from the demethanizer exchanger. To minimize the amount of light component in

the liquid, a stripping action is provided by means of low pressure steam used as a heating

medium in the demethanizer reboiler. To lower demethanizer reboiler duty and to balance

heat input to the column, intermediate withdrawals are provided. They are reheated in the

cold box (105-E8 in Fig. A.5) by cooling feed to the demethanizer (105-C2 in Fig. A.5).

The gas leaving the top of the demethanizer (105-C2 in Fig. A.5) feeds the treated gas

compressor (105-K4 in Fig. A.5) to increase the gas pressure up to 33.4 bar before being

exported to the export gas compression unit (Unit 106 in Fig. 4.1).

Gas is first routed to the export gas compressor suction drum (106-D14 in Fig. A.7) where

any entrained liquids are separated. The gas feeds the export gas compressor (106-K7 in

66

Chapter 4- Process Description and Simulation Fig. A.7) at 33 bar and is recompressed by compressor to 93.5 bar and then is air-cooled in

the cooler (106-A8 in Fig. A.7) down to 58 °C before being exported. Then export gas is

routed to pipeline via the metering system at 90.8 bar.

On the other hand, the bottom liquid product of demethanizer (105-C2 in Fig. A.5) is sent to

deethanizer (105-C3 in Fig. A.5) by means of demethanizer transfer pump (105-P3 in Fig.

A.5). The function of this column is to remove ethane as an overhead vapor stream and a

bottom product containing all the propane and heavier components. The ethane stream

exiting the deethanizer (105-C3 in Fig. A.5) is heated up by means of liquid propane in

ethane heater (105-E9 in Fig. A.5).

The liquid hydrocarbons recovered at the deethanizer (105-C3 in Fig. A.5) bottom (C3+

cut) are sent to the NGL fractionation unit (Unit 107 in Fig. 4.1), where liquid propane cut,

liquid butane cut and C5+ cut are produced. Liquid hydrocarbons are routed to

depropanizer column (107-C4 in Fig. A.6). The function of this distillation column is to

produce a propane stream as an overhead liquid stream which is sent by the propane feed

pump (107-P4 in Fig. A.6) to the propane treatment unit (Unit 114 in Fig. 4.1), where the

mercaptans are removed and propane is sent for storage and export. This column is

equipped with a depropanizer reboiler, which uses LP saturated steam as heating medium.

The bottom product, containing butane and heavier components, feeds the debutanizer

distillation column (107-C5 in Fig. A.6). The overhead gas of the column is condensed in the

condenser and sent to butane feed pump (107-P6 in Fig. A.6) and cooled by sea water in the

butane cooler (107-E10 in Fig. A.6). Cooled butane then is routed to butane treatment unit

(Unit 115 in Fig. 4.1) for the removal of sulfur compounds, mercaptans and water prior to

sending the butane cut to storage and export. The debutanizer (107-C5 in Fig. A.6) bottom

liquid is pumped by condensate circulation pumps (107-P5 in Fig. A.6) before to be air-

cooled by condensate cooler (107-A5 in Fig. A.6). Then the liquid is sent to the condensate

stabilization unit (Unit 103 in Fig. 4.1) to be mixed with stabilized condensates.

It should be added that for the low-temperature cooling requirements of the dehydration

and mercury guard unit (Unit 104 in Fig. 4.1), and the ethane recovery unit (Unit 105 in Fig.

4.1) a refrigerant cycle shall be provided. The vapor from the deethanizer (105-C2 in Fig.

A.5) condenser and from the low-temperature part of the cold box (105-E8 in Fig. A.5) are

67

Chapter 4- Process Description and Simulation mixed and routed to the first stage suction drum (111-D11 in Fig. A.8) - where any

entrained liquids are separated from gas - and feeds the first stage of the refrigerant

compressor (111-K5 in Fig. A.8) at 4 bar. The vapor from the wet gas chiller (104-E6 in Fig.

A.4) and cold box (105-E8 in Fig. A.5) are mixed and routed to the second stage suction

drum (111-D12 in Fig. A.8), where any entrained liquids are separated. Then the gas feeds

the second stage of the refrigerant compressor (111-K6 in Fig. A.8) at 8 bar. The total gas

leaves the refrigerant compressor of propane refrigeration cycle unit (Unit 111 in Fig. 4.1)

and is totally condensed in the refrigerant condenser (111-A6 in Fig. A.8). Then the liquid

flows to the ethane treatment unit (Unit 116 in Fig. 4.1) after being sub cooled of 4.3 °C in

the ethane heater (105-E9 in Fig. A.5).

4.1.2 Hydrocarbon Liquid processing units

After the gas treating processes description, the required processes for treatment of the

hydrocarbon liquid extracting from HP separator (100-D1 in Fig. A.2) is discussed in the

following.

Liquid hydrocarbon and glycolated water are routed to condensate stabilization unit (Unit

103 in Fig.4.1). The function of this unit is to remove the lightest components from the raw

feed and to perform a liquid product, which after mixing with the C5+ from NGL

fractionation unit (Unit 107 in Fig. 4.1), will give a stabilized condensate having a Reid

Vapor Pressure (RVP) of 10 psia in summer and 12 psia in winter.

The stream of liquid hydrocarbon and glycolated water is mixed with liquid from the HP

separators (100-D1 in Fig. A.2) and is preheated in condensate pre flash heater (103-E2 in

Fig. A.3) with the stabilised condensate. The total mixture flows to the pre flash drum (103-

D2 in Fig. A.3) which is a three phase separator.

Having separated the gas from liquid, the flash gas is sent to the second stage off gas

compressor suction drum (103-D6 in Fig. A.3). Gas is further compressed in second stage

compressor (103-K1/K2 in Fig. A.3), cooled in second stage off gas compressor after cooler

(103-A3 in Fig. A.3), and sent to the HP separators (100-D1 in Fig. A.2). The glycolated

water is sent to the MEG regeneration unit (Unit 102 in Fig. 4.1) for recovery and lean

Glycol is sent back to offshore platform. Hydrocarbon liquid is then pumped by desalter

68

Chapter 4- Process Description and Simulation feed pump (103-P1 in Fig. A.3) to the condensate desalter (103-D3 in Fig. A.3) to remove

the free aqueous phase from the hydrocarbon. Operating temperature in the desalter shall

be held at about 71.6 °C to ensure an efficient separation of glycolated water from

condensate. To prevent the flashing of light components, the desalter operating pressure is

set above condensate bubble point with sufficient margin.

For an efficient separation of glycolated water from condensate, the fluid is heated in the

condensate desalter pre heater (103-E3 in Fig. A.3) by heat exchange with stabilized

condensate.

The separated water phase is sent to sour water treatment unit (Unit 109 in Fig. 4.1) and

the raw condensate enters the condensate stabilizer column (103-C1 in Fig. A.3) to be

treated at pressure 10 barg. In this column, lighter components are removed as vapor

overhead product. The stabilizer (103-C1 in Fig. A.3) overhead vapor is compressed by a

two-stages reciprocating compressor (103-K1/K2 in Fig. A.3) and cooled by first and

second off gas compressor after coolers (103-A2 and 103-A3 in Fig. A.3), and vapor-liquid

separated at the inter stage drums; first stage off gas compressor suction drum (103-D4 in

Fig. A.3), first stage off gas compressor discharge drum (103-D5 in Fig. A.3) and second

stage off gas compressor suction drum (103-D6 in Fig. A.3). Any condensate water is

collected and sent to the sour water treatment unit (Unit 109 in Fig. 4.1).

The stabilized condensate from the bottom of the stabilizer column (103-C1 in Fig. A.3) is

further cooled by side reboiler (103-E4 in Fig. A.3), condensate desalter pre heater (103-E3

in Fig. A.3), stabilized condensate air cooler (103-A1 in Fig. A.3) and condensate pre flash

heater (103-E2 in Fig. A.3). Subsequently the C5+ product from NGL fractionation unit

(Unit 107 in Fig.4.1) is mixed with stabilized condensate, before entering the condensate

degassing drum (103-D7 in Fig. A.3). On-spec condensate is then sent to storage and

ultimately shipped out.

Lastly, the sour water streams from all units are routed to the sour water treatment unit

(Unit 109 in Fig. 4.1) and firstly is transferred to first sour water stripper feed drum (109-

D13 in Fig. A.9), operating at the low pressure flare back pressure. This drum is a three-

phase separator designed to remove oil from the inlet water streams. The vapor phase is

vented from the feed drum to the LP flare.

69

Chapter 4- Process Description and Simulation Oil is pumped to burn pits or off-spec tanks and the water is pumped via sour water

stripper feed pump (109-P7 in Fig. A.9) and sent to the sour water stripper (109-C6 in Fig.

A.9). The stripper reboiler is kettle type, heated by LP saturated steam.

The stripper overhead acid gas is sent to the LP flare and treated water as bottom product

of sour water stripper (109-C6 in Fig. A.9) is pumped by first sour water stripper bottom

pump (109-P8 in Fig. A.9) and air cooled by first sour water stripper bottom cooler (109-

A7 in Fig. A.9) and is sent to mayor water treatment facility.

Overall process flow diagram and relevant process flow diagram of the each processing

unit are presented in Fig. A.1 to Fig. A.10 in Appendix A. In addition, the complete

equipment list and associated tag numbers is provided in Table A.1 in Appendix A.

4.2 Process simulation and assumptions

4.2.1 Applied software for simulation

Simulation of the gas refinery processes were performed using Aspen Plus [141] and based

on flow sheet and heat and material balance from [142]. Aspen is a software suite

composed of several chemical and thermodynamic process simulators. The main platform

of this package is Aspen Plus, which contains an extensive library of chemical and

thermodynamic property data, as well as a wide array of unit operations. Calculations in

Aspen Plus are performed by unit operation blocks. The Aspen Plus Model Library contains

several standard unit operations such as heat exchangers, separators, pumps, compressors,

and reactors. In addition, Aspen Plus allows for the capability to build custom unit

operation models. Unit operation blocks are connected by material, heat, and work

streams.

Simulating a process involves three main steps. The first step requires setup of the flow

sheet, in which the unit operation blocks are laid out and connected by desired streams.

The second step consists of defining the chemical components of the simulation and

specifying the temperature, pressure, flow, and composition of streams. Finally, the

operating conditions of the unit operation blocks are defined.

In Aspen plus, components are classified as either conventional or non-conventional.

Conventional components are ones with property data contained in the Aspen component

70

Chapter 4- Process Description and Simulation database. Nonconventional components are non-homogeneous substances that do not have

a consistent composition and are not contained in the Aspen component database. In

studied gas plant, as per feed specification in Table 4.1, there are some components which

are classified as nonconventional. It includes heavy hydrocarbons (C6~C20) which are

defined by their normal boiling point, specific gravity and molecular weight as available

information. Hence, Aspen plus could be able to calculate other required properties of

those components. The applied data for definition of nonconventional components is

summarized in Table 4.3.

In addition, for simulating gas plant, Soave-Redlich-Kwong –Lee Kesler (SRK-LK) has been

considered as equation of state. According to Aspen Property Method Assistant

recommendation, SRK-LK is a suitable equation of state for prediction of properties in

refineries, gas processing plants and petrochemicals, as it can calculate the enthalpy and

entropy values of the process streams and it is appropriate for a mixture of non-polar or

mildly-polar, consistent even in the critical region, and reasonable results can be found at

all pressures and temperature [141].

Table 4.3 Non-conventional components properties

Component Molecular Weight/kg kmole-1 Boiling Point/°C Specific Gravity

C6 CUT 84 67.74 0.690 C7 CUT 96 95.65 0.727 C8 CUT 107 118.8 0.749 C9 CUT 121 145.8 0.768 C10 CUT 134 167.7 0.782 C11 CUT 147 184 0.793 C12 CUT 161 200 0.804 C13 CUT 175 214.3 0.815 C14 CUT 190 232.7 0.826 C15 CUT 206 252.9 0.836 C16 CUT 222 271.7 0.843 C17 CUT 237 288.9 0.851 C18 CUT 251 303.9 0.856 C19 CUT 263 316.5 0.861 C20 CUT 385 417.2 0.850

71

Chapter 4- Process Description and Simulation For each material stream, according to heat and material balance, mass flow rate,

composition, temperature and pressure have been set in Aspen Plus. Having set this

information; physical exergy of each stream is calculated by Aspen Plus. The reference state

temperature and pressure have been defined as 25 °C and 1.013 bar, respectively.

For chemical exergy values, higher heating value (HHV) of all streams have been calculated

by Aspen and based on state of stream (liquid or vapor), a percentage of HHV is considered

as chemical exergy value [18].

By providing thermodynamic properties of inlet and outlet streams, equipment

specifications can be estimated as well. Detail information about streams properties have

been shown in Appendix B.

72

CHAPTER 5

5 Application of exergy-based analyses to the plant This chapter includes details and particularities of the application of exergy-based

analyses; including conventional and advanced exergy analyses, economic and

exergoeconomic analyses, and exergoenvironmental analysis.

5.1 Exergy analysis

As explained before; for each material stream, mass flow rate, composition, temperature

and pressure have been set in Aspen Plus. Having set this information; physical exergy of

each stream is calculated by Aspen Plus. The reference conditions are defined as:

temperature 25 °C and pressure 1.013 bar.

Since the higher heating value (HHV) is the main contributor of the chemical exergy of a

fossil fuel, for simplification of calculation of chemical exergy, in this thesis it has been

assumed, - depend on the state of the fuel (liquid or vapor)-, a percentage of HHV is

considered as chemical exergy value [18]. In this thesis; 98.5 % of HHV for gaseous state

and 99 % of HHV for liquid state have been considered as chemical exergies’ values. The

total exergy rates associated with each material stream as well as the physical and chemical

terms are given in Table B.1. The statements of the exergy rates are carried out based on

the SPECO approach [131].

In this research, major units of operations; including units 100,103,104,105,106,107,109

and 111 have been analyzed by exergy analysis and other units (101,114,115&116) that

they are designed based on a patented technology, they have been considered as black

boxes and only the interactions with major units have been taken into account. In these

black boxes units, only destructed exergy is calculated based on difference of total exergy

values of input and output streams. Moreover, other units such as (102, 108 &113) are also

designed on patented technology and they are common between other refineries or units

and they are excluded from this study.

73

Chapter 5- Application of exergy – based analyses to the plant

For some equipment (columns, for example), to have a better and precise understanding of

exergy analysis, the definitions of fuel and product are achieved through separate

considering physical and chemical exergies. However, for demethanizer column (105-C2),

as far as the number of input and output streams are quiet high, the definition of fuel and

product exergies cannot be achieved easily. Therefore, in this case, only destructed exergy

has been calculated based on the difference of total exergy values of input and output.

It should be added that phase separators and coolers are considered as dissipative

components and only the destructed exergy is calculated. In addition, the components such

as mixers and throttling valves are neglected in this study. Then in general, it can be said

that the components are categorized in three parts: productive components, units and

dissipative components.

Regarding the definition of the exergy of the fuel and exergy of products of the entire

system; as there are streams that enter or leave the system and are distributed to other

trains of other refineries. Therefore, these values are not defined.

The equations regarding definitions of fuel and product exergies are illustrated in Table

B.2. Moreover, the results of exergy analysis are displayed in Table B.4, and are analyzed in

detail in Chapter 6.

5.2 Economic analysis

As explained in Chapter 3, to calculate the total capital investment (TCI), the first step is to

estimate the purchased equipment costs (PEC) and other parameters will be defined as a

percentage of (PEC). Following the TCI estimation, by economic analysis, total revenue

requirement (TRR) will be calculated. Lastly, Total capital investment cost (TCI) and total

revenue requirement (TRR) for gas plant are estimated and levelized and consequently

cost rate of equipment would be evaluated as an input for exergoeconomic.

5.2.1 Total capital investment (TCI) estimation

According to flow sheet and required specifications, the characteristic values for the

equipment are obtained from the simulation. Then various sources of literatures are

combined and all purchased equipment costs (PEC) have been obtained. Finally, these

reference costs are updated by CEPCI according to today’s costs. Detail of assumption and

74


procedures for estimation of PEC is available in Appendix C. As shown in Table C.34, the

total PEC is 60.151 M$ inclusive the appropriate cost indexes. It should be noted that in this

thesis all calculations are carried out based on USD currency and year 2017 is used for the

reference year.

Having estimated the PEC value, it is possible to estimate the Fixed Capital Investment

(FCI) by considering some assumptions. The assumptions are indicated in Table C.35 and

FCI of the plant has been estimated as 189.394 M$.

As explained in Chapter 3, to be able to estimate TCI, “other outlays, including; start up cost

(SUC), working capital (WC), cost of licensing, research and development and Allowance for

Funds Used During Construction (AFUDC)” shall be calculated and added to Plant Facility

Index (PFI). However, in this thesis, cost of land is ignored; therefore, the PFI value is equal

to (FCI). It should be added that costs of licensing, research and development is excluded as

well.

Assumptions should be made considering the economic, financial, operating, and market

condition of the country, where the plant should operate. Table 5.1 summarizes the main

assumptions and parameters used in this thesis, which reflect the current economic

situation in USA.

The evaluation of other outlays is given in detail in below part based on economic analysis

assumptions of Table 5.1. As shown in this table, the economic lifetime for all equipment

and for the overall system is assumed as 20 years, and plant operates with 90 % of capacity

factor (approximately 8,000 hr yr-1).

In studied gas refinery, the fuel of the system is considered as natural gas which comes

from wellhead for further treatment in plant. The average unit price of natural gas in USA is

considered as 3.05 $ GJ-1 for middle of year 2017. The mass flow rate of gas entering the

facilities is 308 kg s-1 and the LHV of it is 47.7 MJ kg-1. Therefore, the annual fuel cost (FC)

is:

FC = (0.003) × (47.7) × (308) × (8000) × (3600) = 1,162 M$ yr-1 for Mid-2017.

To calculate the annual fuel costs for the first year of commercial operation (Mid-2020),

this number at an annual escalation rate of 2.5 % for natural gas should be escalated:

75


FC = 1,162 × (1.025)3 = 1,251 M$ yr-1 for Mid-2020.

Moreover, fixed and variable operating and maintenance costs are estimated based on

direct labor cost as mentioned in Table 5.1.

Table 5.1 Parameters and initial assumptions used in economic analysis

Parameters (units) Values Average general inflation rate/% 2 Average nominal escalation rate/% 2 Average nominal escalation rate for Natural gas/% 2.5 Beginning of design and construction period 2018 Date of commercial operation 2020 Plant economic life/yr 20 Plant financing fractions and required returns on capital

Type of financing Common Equity Debt

Financing fraction/% 50 50 Required annual return/% 8 6 Average cost of money/% 7 Average capacity factor/% 90 Contingencies/% 25 labor positions for operating and maintenance 15 Assumed average labor rate/$ hr-1 25 Average number of working hours per labor position/hr yr-1 2080 Annual direct labors costs/$ yr-1

Fixed OMC (2.18 times of annual direct labor cost)/$ 780 ×103

1.7×106

Variable OMC (0.2 times of annual direct labor cost)/$ 156×103 Unit cost of fuel/$ GJ-1

3.05

Allocation of plant facilities investment to the Individual years of design and construction,%

Jan.1- Dec.31.2018 40 Jan.1- Dec.31.2019 60

Having calculated the fuel cost (FC) and estimating operating and maintenance costs

(OMC), the startup costs (SUC) and the working capital (WC) can be estimated. As shown in

Table 3.1, the startup costs (SUC) is assumed to be the sum of the following unescalated

76


costs: (a) one month of fixed OMC, (b) one month of variable operating costs calculated at

full load, (c) one week of full-load fuel, and (d) 2 % of the plant facilities investment (PFI).

Thus;

SUC = (1.7×106)/12 + (156×103) (0.9)/12 + (1.162×109)/52+ (0.02) (189.394×106) =26.277 M$.

This value is for Mid-year of 2017. Having escalated this value, the startup cost for Mid-year

2019 is: (SUC) = 27.338 M$.

Similarly, the working capital (WC) is the sum of the unescalated expenses representing

2 months of fuel and variable operating costs at full load, and 3 months of labor costs plus a

contingency of 25 % of the total of the above three items. Then for Mid-year 2017:

WC = [(2×1.162×109/12) + (2×156×103/12) + (3×780 ×103/12)] × (1+0.25) = 242.25 M$;

or escalated value for End-year 2019 is: WC = 254.54 M$.

The plant-facilities investment (PFI) for this project is estimated as 189.394 M$ for mid-

2017 which is the same value as (FCI) due to neglecting cost of land. According to

assumption of Table 5.1, 40 % of this amount must be escalated at an annual rate of 2 % to

the middle of 2018, when it is expended, whereas the remaining 60 % of the PFI must be

escalated to the middle of 2019. In addition, the Allowance for Funds Used During

Construction (AFUDC) is also calculated separately for each type of financing using the

corresponding returns on investment.

Finally, the total capital investment (TCI) is then calculated as 490.644 M$. Details of all

results are summarized in Table C.36.

5.2.2 Total revenue requirement (TRR) estimation

For estimating of TRR, the levelized fuel cost (FC), the levelized operating and maintenance

costs (OMC) and the levelized carrying charges (CC) during the life time of the plant should

be calculated.

Considering 20 years of plant operation and assuming constant dollar value, the levelized

carrying charges, levelized fuel cost and levelized operation and maintenance cost are

estimated at 46.3, 1550.4 and 2.3 M$, respectively. As the corresponding values show, the

highest contribution to the levelized cost comes from the fuel cost, by almost 96.96 %,

77


followed by the carrying charges of about 2.9 % and 0.14 % for operation and maintenance

costs. Detailed data is shown in Table C.37 for the gas plant.

5.3 Exergoeconomic analysis

To conduct an exergoeconomic analysis, monetary values are allocated to the exergy

streams, including material and energy streams; such an allocation is based on the so-

called exergy-costing principle; the SPECO method [131] which is used in this thesis. The

exergoeconomic analysis consists of a group of linear equations stated at the component

level. The sum of all costs entering a component (cost of incoming streams plus investment

cost of the component) must be equal to the cost of the streams exiting the component.

All cost balance equations and auxiliary equations, used in the exergoeconomic calculation

of the studied units in gas refinery, are summarized in Table B.3. For some equipment such

as distillation columns, the cost rate is divided into two parts, chemical and physical, since

the exergy analysis takes such splits into account for more precise investigation. Moreover,

in columns; cost of reboilers and condensers has been summed with cost of column vessel

pressure and one cost rate has been applied in balances.

In addition to the above-explained balance equations and auxiliary equations, appropriate

boundary conditions for all incoming streams must be used; for example, the cost of the

supplied fuel, water, air, steam and electricity must be specified. As shown in Table 5.1, the

specific cost of fuel (natural gas) is considered as 3.05$ GJ-1 which is used in the calculation.

The cost of waste water coming from caustic regeneration or MEG regeneration units (out

of scope of study) to waste water treatment unit, have been considered as zero.

For all equipment where electric power is supplied (pumps, and compressors), the specific

cost of electricity has been assigned as cw=20.14 $ GJ-1 for USA [143]. Moreover, low

pressure (LP) steam with T=155 oC and p= 4.3 bar is used in reboliers of some columns

(demethanizer, deethanizer, debutanizer and sour water stripper) as heating medium. The

price of LP steam is calculated by following rough equation [144]:

Total Steam Cost ($ MMBtu-1) = Fuel Cost ($ MMBtu-1) × 130 %

78


Therefore, by having cost of fuel as 3.05 $ GJ-1, the specific price of low pressure steam is

calculated as 4.17 $ GJ-1.

On the other hand, High Pressure (HP) steam with T=260 oC and p=40 bar is used in

reboilers of condensate stabilizer and depropanaizer. Due to lack of detail information, it is

assumed that HP steam is 20 % more expensive than LP steam; by value of: 5.004 $ GJ-1.

Dissipative components (e.g., air coolers, air cooled condensers, flash separators and slug

catcher) serve productive components in a system, facilitating an overall effective

operation, cost reduction or achievement of required emission standards. Thus, costs

associated with purchasing and operating a dissipative component is usually charged

either to the component(s) served by it or to the final product(s) of the system [131]. In

this thesis, the costs related to dissipative equipment are charged to the final products.

The cost balances and the auxiliary equations for all equipment were formulated and

solved by EES software. The specific cost of each material stream is calculated and the

results are reported in Table D.1.

The specific costs per unit of exergy of the product (𝑐P) and fuel (𝑐F) were calculated and

depend on them; the cost rate of the exergy destruction ��D.

Cost rate ��k of each group of components also has been calculated and the results are

available in Table C.38. Accordingly ��D,k + ��k within each productive component is

obtained. Results of exergoeconomic analysis for productive components are available in

Table B.4 and are discussed more in detail in Chapter 6.

5.4 Exergoeconomic diagnostic

In exergoeconomic diagnostic, similar approach to exergoeconomic analysis is applied. The

difference is in considering cost rates of all components: ��k = 0. The set of equations for all

the system is solved and results of streams specific costs(𝑐), costs per unit of exergy of the

product (𝑐P) and fuel (𝑐F) and consequently, cost rate of the exergy destruction ��D for all

productive components are calculated.

79


The specific costs and cost rates of each material stream are available in Table D.3, and the

results of analysis for productive components are shown in Table B.5. Interpretation of

results is available in Chapter 6.

5.5 Exergoenvironmental analysis

A lifetime of 20 years and 8000 working hours per year is assumed. During operation, the

consumption of natural gas, electricity, HP and LP steam are considered.

The environmental impact of natural gas is considered as 35 mPts kg-1 which for unit

consistency is converted as below to environmental impact per unit of exergy [102]:

bNG = 35 / 0.0477 = 733.7 mPts GJ-1. The environmental impact per unit of exergy of waste

water coming from caustic regeneration or MEG regeneration units (out of scope of study)

to waste water treatment unit, is neglected. The environmental impact of electricity per

unit of exergy is assigned as bw =7500 mPts GJ-1 [102]. Lastly, environmental impact per

unit of exergy for LP and HP steam is considered as environmental impact per unit of

exergy of heat as bLP = bHP =5,300 mPts GJ-1.

Similar to approach taken into consideration in exergoeconomic diagnostic, component-

related environmental impact has been considered as zero (Yk =0).

Environmental impact per unit of exergy of the product (𝑏P) and fuel (𝑏F) and

consequently, environmental impact of exergy destruction ��D,k is calculated for all

productive components. ��D,k value is used to identify the most important components from

the viewpoint of formation of environmental impacts due to exergy destruction within the

component. The results of exergoenvironmental for productive components are available

in Table B.6 and further discussed in Chapter 6. In addition, environmental impacts per

unit of exergy for streams are also reported in Table D.5.

5.6 Advanced exergy-based analysis for selected components

In addition to a conventional exergy analysis, an advanced exergy analysis was applied to

the selected components of the plant. To conduct the advanced exergy analysis, the

unavoidable conditions for the components were defined. For the calculation of the

unavoidable exergy destruction, the best possible operating conditions are considered for

80


the component. These calculations regard each component in isolation. The exergy

destruction within these components is split into unavoidable and avoidable.

For selected compressors, the assumption is the isentropic efficiency as 90 %. Current

value of isentropic efficiency for compressors is 73 %. For multi stream heat exchanger and

selected distillation columns some expedient researches are used to simplify the analysis.

As the structure of these components and interaction between corresponding streams are

quiet complex, based on results of some other similar researches, a range for unavoidable

exergy destruction rate has been chosen and accordingly the avoidable exergy destruction

rate is obtained [55] [145]. For multi stream heat exchanger (cold box, 105-E8), as it is

explained in [145], the parameter which identifies the technological limitations is the

minimal temperature difference in heat exchanger. Therefore, this minimum value was

assumed to be equal to 0 K. For multi stream heat exchanger, from the obtained results

from this research, it is assumed that in best case scenario 30 % and in worst case scenario

60 % of destructed exergy is unavoidable. Based on this information, the avoidable and

unavoidable exergy destruction rate and consequently, corresponding cost and

environmental impact of these two scenarios have been estimated and reported in Table

B.8.

Regarding selected columns, as described in [55], a procedure has been defined for the

estimating the unavoidable exergy destruction within distillation columns. In this

procedure, the minimum reflux ratio (the minimum energy requirement) and the total

reflux (the minimum theoretical stage number) are used to estimate the unavoidable

exergy destruction and the unavoidable investment cost of a distillation column,

respectively.

With the same approach used for cold box, from the obtained results of this research, it is

assumed that in best and worst case scenarios, 65-75 % of exergy destruction is

unavoidable, respectively. Consequently, the cost rates and environmental impact rate

associated with unavoidable exergy destruction are estimated. Results are presented in

Table B.8 and further discussed in Chapter 6.

The next investigated productive component is dryers’ regeneration furnace (104-H1),

which in general it is assumed that most of the destructed exergy is unavoidable.

81


Corresponding cost rate and environmental impact rate of unavoidable exergy destruction

within furnace are shown in Table B.8 and discussed in detail in Chapter 6.

In the next assessment, units with patented technology are analyzed by advance exergy

analysis. The manufacturers of these units always try to improve their package by applying

the highest technology and material and considering lower costs. Therefore, it is assumed

that in best case scenario 70 % and in worst case scenario 90 % of destructed exergy is

unavoidable. Due to lack of precise information, cost rate and environmental impact rate

concepts are not applicable in case of dissipative components. Results are presented in

Table B.9.

Lastly, for coolers as dissipative components, it is assumed that most of the destructed

exergy is not avoidable. Therefore, by assuming 90 % of total exergy destructed as

unavoidable exergy value, the avoidable exergy destruction rate is calculated. It should be

mentioned that cost rate and environmental impact rate concepts are not applicable in case

of dissipative components. Results are presented in Table B.10.

Now, with all above-mentioned assumptions, it is possible to calculate the unavoidable and

avoidable exergy destruction rate for selected components. The results of avoidable and

unavoidable exergy destruction for all the selected components, (for both scenarios, if any)

are graphically shown in Fig. 6.13 and Fig. 6.14.

Further investigation is done by assigning cost and environmental impacts data to

unavoidable and avoidable exergy destruction and unavoidable cost rate of destructed

exergy and unavoidable environmental impact rate per unit of exergy destruction are

estimated for productive components. It should be mentioned that advanced analysis

results are integrated to the cost information obtained by exergoeconomic diagnostic.

Results of advanced exergoeconomic diagnostic and exergoenvironmental are available in

Table B.8 and discussed in detail in Chapter 6. In addition, the corresponding charts for

productive components for both considered scenarios are presented in Fig. 6.15 to Fig.

6.18.

82

CHAPTER 6

6 Results and discussions In this chapter the results obtained from exergy analysis as well as economic and

exergoeconomic, exergoenvironmental and advanced exergy-based analysis are presented

and discussed.

6.1 Results of conventional exergy analysis

As mentioned in chapter 5, by simulation the gas plant in Aspen plus, values of physical and

chemical exergies have been calculated and components in main operation units have been

analyzed based on fuel and product concept.

The components of the plant have been categorized in three groups: Productive

components, Units and Dissipative components. The results of the conventional exergy

analysis are tabulated in Table B.4. It is clear from Table B.4 that the highest exergy

destruction in productive components group occurs in the export gas compressor (106-K7)

by 3.8 MW followed by depropanizer column (107-C4) with 3.2 MW. Accordingly, in units

group of components, within demethanizer (105-C2) and propane treatment unit (114-B2),

5.3 MW and 3.05 MW of exergy are destroyed, respectively. Lastly, in dissipative

components group the highest rates of exergy destruction belong to export gas air cooler

(106-A8) by 4.8 MW, and refrigerant condenser (111-A6) by 2.1 MW.

As shown in Table B.4, the exergetic efficiency value is only can be considered for

productive components. The exergy efficiency of condensate stabilizer (103-C1), Gas heater

(100-E1), wet gas chiller (104-E6), gas/gas exchanger (104-E5), dry gas heater (104-E7),

ethane heater (105-E9), dryers regeneration furnace (104-H1), first and second stage

refrigerant compressor (111-K5/K6) are calculated to be very high, and amounts to 99.9 %,

while the condensate desalter pre-heater (103-E3) shows the lowest exergetic efficiency by

29.3 %, followed by sour water stripper (109-C6), with 34.3 % and debutanizer (107-C5)

with 43.7 %. In addition, among compressors -as important components-, first and second

stage offgas compressor (103-K1/K2), represents approximately 54 % for exergy

Chapter 6-Results and discussions

efficiency. The exergy values for the pumps are very small; therefore, the exergetic

efficiency of the pumps has no technical significance.

To have a better overview of exergy destruction within gas plant, Fig. 6.1 illustrates the

breakdown of each group of components in exergy destruction within the whole system.

Fig. 6.1 Overview of exergy destruction within plant

As it is depicted in this graph, productive components group with 21.3 MW has the highest

rate of exergy destruction inside the plant, while the units group and dissipative

components group represent almost similar destructed exergy values with approximately

14.7 MW. In other words, productive components group represents 42 % of total exergy

destruction and is followed by units group and dissipative components group, each 29 % of

total exergy destruction.

To get more into detail of exergy destruction within each individual component, the results

have been graphically shown for each group of components in Fig. 6.2 to Fig. 6.4.

In productive components, as it is indicated in Fig. 6.2, highest exergy destruction occurs in

export gas compressor (106-K7) and depropanizer column (107-C4), with the value of

3.8 MW and 3.2 MW, respectively. Only these two components are responsible for 33 % of

exergy destruction in their corresponding group.

42%

29%

29%

Productive components (21.3 MW)

Black-box Units (14.8 MW)

Dissipative components (14.7 MW)

84


Fig. 6.2 Exergy destruction within productive components

Other significant components with approximately equal shares in producing exergy

destruction are: deethanizer (105-C3) with 1.9 MW, cold box (105-E8) with 1.8 MW,

debutanizer (107-C5) with 1.7 MW, dryer’s regeneration furnace (104-H1) with 1.3 MW,

and treated gas compressor (105-K4) and its gas turbine drive (105-X1) , each with almost

1 MW. These components accounts for approximately 41 % of total exergy destruction

within productive components. The remaining components with lower rate of exergy

destruction have been integrated in one part and shown as “Other”, which accounts for 26

% of the total exergy destruction within productive components group.

Next group of components are units. In units group, due to lack of precise information, a

real assessment is limited. However, by considering exergy rate of inlet and outlet streams,

the destructed exergy has been estimated and displayed in each individual unit in Fig. 6.3.

Therefore, black boxes including Gas sweetening unit (101-B1), C3 treatment unit (114-

B2), C4 treatment unit (115-B3),treatment unit (116-B4), slug catcher (100-L1), dryers

(104-R1), and Mercury guard (104-R2) have been considered as units in grouping of

components. In addition, since the number of inlet streams an outlet streams to

demethanaizer (105-C2) is a lot, defining fuel and product exergy is quiet complicated.

Therefore, this component also has been considered as a unit.

20%

17%

17%10%

9%

9%

7%

6%5% 106-K7 (3.81 MW)

Other (3.29 MW)

107-C4 (3.23 MW)

105-C3 (1.94 MW)

105-E8 (1.77 MW)

107-C5 (1.73 MW)

104-H1 (1.28 MW)

105-K4 (1.07 MW)

105-X1 (0.95 MW)

85


As it is apparent in Fig. 6.3, the bigger contributor of exergy destruction within units group,

is demethanizer column (105-C2) with 5.4 MW accounting for almost 36 % of total exergy

destruction in this category of components.

Fig. 6.3 Exergy destruction within units

After that, propane treatment unit (114-B2), with approximately 3 MW, and slug catcher

with 2.7 MW are other two main contributors to exergy destruction in units group, which

represents the 39 % of total exergy destruction rate. Gas sweetening unit (101-B1) and

butane treatment unit (115-B3) has equal share in destructing the exergy, each, with

approximately 1.5 MW. Remaining units including dryers (104-R1) with 0.4 MW, mercury

guard reactor (104-R2) with 0.3 MW and ethane treatment unit (116-B4) with 0.1 MW; do

not have significant exergy destruction rate in units group.

Lastly, exergy destruction within dissipative components has been estimated by difference

of exergy of input and output streams. Fig. 6.4 shows the amount of exergy destruction

inside dissipative components. As it is obvious from the graph, export gas air cooler (106-

A8) represents for 34 % of total exergy destructed inside dissipative components.

Refrigerant condenser (111-A6) and regeneration gas air cooler (104-A4) are other main

components with high exergy destruction of 2.1 MW and 1.9 MW, respectively and appear

to be equally important with approximately 15 % of exergy destruction ratio per each in

this group of components. Stabilizer side reboiler (103-E4) and stabilized condensate air

34%

20%17%

9%

9%

5%3% 2% 1% 105-C2 (5,36 MW)

114-B2 (3.05 MW)

100-L1 (2.71 MW)

101-B1 (1.43 MW)

115-B3 (1.37 MW)

Other (0.86 MW)

104-R1 (0.45 MW)

104-R2 (0.28 MW)

116-B4 (0.12 MW)

86


cooler (103-A1) with 1.5 MW and 1.1 MW of exergy destruction rate, accounting for 11 %

and 8 % of total exergy destruction within dissipative components.

On the other hand, comparing above-mentioned equipments, all other remaining

equipment (almost 20 components) represents for only 18 % of total exergy destruction

within dissipative components group, which is quiet low share in exergy destruction rate in

group of dissipative components.

Fig. 6.4 Exergy destruction within dissipative components

From the perspective of an exergy analysis, the greater the exergy destruction in a

component, the higher the priority for improvement is. Hence, high priority should be

given to the order of demethanizer (105-C2) with 5.3 MW, export gas air cooler (106-A8)

with 4.8 MW, export gas compressor (106-K7) with 3.8 MW and the depropanizer (107-C4)

with 3.2 MW. However, the exergy analysis only investigates the components from

thermodynamic point of view. The results of economic and consequently, exergoeconomic

are discussed in detail further.

6.2 Results of economic analysis

From economic analysis, the Fixed Capital Investment (FCI), Total Capital Investment (TCI)

and Total Revenue Requirement (TRR) of the gas plant have been estimated as 189.3 M$,

490.6 M$ and 1599.1 M$, respectively. In addition, different sources of literature have been

34%

18%15%

14%

11%

8%106-A8 (4.79 MW)

OTHER (2.49 MW)

111-A6 (2.10 MW)

104-A4 (1.90 MW)

103-E4 (1.48 MW)

103-A1 (1.14 MW)

87


used and Purchased Equipment Cost (PEC) of all components has been calculated as

60.1 M$. With this information, now it is possible to calculate the levelized cost rate (��k) of

equipment and recognize which component has the highest cost rate to the system. On the

other hand, the estimated levelized cost rates are used as input to exergoeconomic analysis.

The results of cost rates of components are presented in Table C.38. Gas sweetening unit

(Unit 101-B1) and export gas compressor (106-K7) represent the highest cost rates of the

system by 1545 $ hr-1 and 1285 $ hr-1, respectively. In addition to these two components,

the other two most costly components are ethane treatment unit (Unit 116-B4) with

315.9 $ hr-1 and dryers (104-R1) with 302.2 $ hr-1.

By providing an overview of share of each category of components in total cost rate of the

system, the costly group of component is recognized. The overview of cost rates is shown in

Fig. 6.5.

Fig. 6.5 Overview of cost rate values (��k)

It can be noticed from Fig. 6.5, that the share of productive component (including 30 single

components) with 44 % of total cost rates of the plant, is nearly close to share of units

group (including 8 units) with 42 % of total cost rates, while the dissipative components

are only responsible for 14 % of total cost rate of the system. To have a more detail

44%

42%

14% Productive components (2691 $ hr-1)

Black-box Units (2569 $ hr-1)

Dissipative components (818 $ hr-1)

88


understanding, each group of components, is graphically presented. Firstly, the cost rates

within productive components are discussed.

Fig. 6.6 Cost rates (��k) distribution in productive components

As can be seen from Fig. 6.6, the highest cost rate within productive components group,

belong to export gas compressor (106-K7) with 1285 $ hr-1, accounting for 48 %. All the

other components are appeared to be equally important and are assigned for very small

percentage of cost rate, almost 3~8 %, comparing the export gas compressor.

Secondly, the units’ component group is analyzed. In assessment of cost rate among units

group of components, it should be taken into consideration that there are patented units

which comprises of several single equipment units.

Within the units group of components, as it is clear in Fig. 6.7, gas sweetening unit (101-B1)

is the main contributor to the cost rates’ values in this group with approximately 60 % of

total cost rate, and followed by dryers (104-R1) and ethane treatment unit (116-B4), with

the same cost rate share of 12 %. Other units like slug catcher (100-L1), demethanizer

column (105-C2), mercury guard (104-R2) and butane treatment unit (115-B4), have

approximately similar trend of 2~4 % of share in cost rate of this group of components.

48%

8%7%

7%

6%

5%

5%

5%3% 3% 3% 106-K7 (1285 $ hr-1)

OTHER (209.8 $ hr-1)111-K6 (189.3 $ hr-1)104-H1 (177 $ hr-1)105-C3 (159.1 $ hr-1)103-K2 (148.8 $ hr-1)105-K4 (135.2 $ hr-1)107-C4 (132.6 $ hr-1)105-X1 (90.6 $ hr-1)105-E8 (82.5 $ hr-1)

89


Fig. 6.7 Cost rates (��k) distribution in units

It should be mentioned that regarding the units which considered like black boxes, as they

are built based on several equipmentinside with confidential technology and material; it is

not easy to judge about the cost rate and compare it with individual components.

Lastly, the cost rates within dissipative components group is illustrated in Fig. 6.8.

Fig. 6.8 Cost rates distribution (Zk) in dissipative components

Among dissipative components, as it is apparent in corresponding graph, two components

significantly contribute to the highest cost rates: HP separator (100-D1) and dryers’ inlet

60%

12%

12%

4%4%

3% 3% 2% 101-B1 (1545 $ hr-1)

116-B4 (315.9 $ hr-1)

104-R1 (302.2 $ hr-1)

114-B2 (108.1 $ hr-1)

105-C2 (100.5 $ hr-1)

115-B3 (73.5 $ hr-1)

104-R2 ( 68.3 $ hr-1)

100-L1 (55.8 $ hr-1)

21%

21%

15%

13%

10%

7%

6%4% 3% 100-D1 (173.6 $ hr-1)

104-D8 (173.6 $ hr-1)OTHER (117.3 $ hr-1)103-D3 (102.3 $ hr-1)105-D10 (80.2 $ hr-1)106-D14 (59.2 $ hr-1)103-D2 (51.6 $ hr-1)111-A6 (33.8 $ hr-1)106-A8 (27.0 $ hr-1)

90


separator (104-D8) with cost rate of 173.6 $ hr-1, which accounts for approximately 21 %

of share in total cost rate within this group of components. Therefore, only 42 % of the cost

rates belong to two separators. The next higher value is assigned to “Other” which

represents 16 components together and they are responsible for 15 % of total cost rates

here.

In addition, second stage compressor suction drum (103-D3) and feed flash KO drum (105-

D10), with cost rate of 102.3 $ hr-1 and 80.2 $ hr-1, accounts for 13 % and 10 % of cost rates

shares within dissipative components.

Having assessed all the components groups in detail, it can be noticed that gas sweetening

unit (101-B1) with 1544.8 $ hr-1, export gas compressor (106-K7) with 1284.7$ hr-1,

ethane treatment unit (116-B4) with 315.8 $ hr-1 and dryers (104-R1) with 302.2 $ hr-1

imposed highest cost rates to the whole system.

6.3 Results of exergoeconomic analysis

The results of cost streams are presented in Table D.1. The cost rate of the internal streams

increases through the addition of capital investment related costs and the costs of exergy.

Through the recirculation of exergy, and the associated recirculation of cost, relatively high

cost rates are observed on some internal flows.

Meanwhile, the highest specific cost per unit of exergy is assigned to streams no.141,

141A,142,142A,143,144,145,146,146A,147,147A,148,148B and 149 with approximately

73 $ GJ-1. This ranking followed by streams no. 37,38,38A,39,39A,40,41 and 42 with about

55 $ GJ-1. The specific cost of raw natural gas coming from wellhead is considered as

3.05 $ GJ-1, and the specific costs per unit of exergy of generated products of the system are

calculated.

The stream no.21B is condensate product, with specific cost per unit of exergy of

4.07 $ GJ-1, stream no.72 is sales gas with 10.16 $ GJ-1, stream no. 63C is ethane with

10.37 $ GJ-1, stream 161A is propane with 10.3 $ GJ-1 and stream171B is butane with

10.2 $ GJ-1 specific cost per unit of exergy.

According to [143], the average whole price of propane in 2017 (reference year for

calculation), was 1.28 $ gal-1 which is equal to 13.25 $ GJ-1. Therefore, the price of propane

91


is estimated correctly and within the market margins. As per [143], the price of butane has

the same trend as propane. Therefore, it can be perceived that the specific cost of butane

also, is nearly close to what it has been estimated in this thesis. Regarding the ethane and

condensate specific price, the validation of results is complicated. Depends on the amount

of processing, demand of the market and location, the prices are different and cannot be

judged.

In this research, the exergoeconomic analysis is only performed for productive components

group. Having estimated the specific cost of streams, the costs per unit of exergy of the

product (𝑐P) and fuel (𝑐F) were calculated for each component. An important outcome of

the exergoeconomic analysis is the correlation of exergy destruction with costs. The cost

rate of exergy destruction (��D,k) is calculated at the component level and it is then

compared to the respective investment cost rates. The components are then ranked

depending on their total cost rate, which consists of their investment and exergy

destruction cost rates (��D,k + ��k). The higher this total cost, the higher the influence of the

component on the overall plant and thus, the more significant the component is considered.

This cost ranking exposes the components that should have improvement priority, in order

to improve the cost effectiveness of the overall plant.

The results of exergoeconomic analysis at component level are summarized in Table B.4.

Firstly, the cost rates of exergy destruction (��D,k) within the productive components are

discussed. As it is shown in Fig.6. 9, two components significantly contribute to the

increasing of cost rate of exergy destruction: export gas compressor (106-K7), with

275.9 $ hr-1, reflecting 21 % of share in exergy destruction cost rate within productive

components, and dryers’ regeneration furnace (104-H1), with 252.7 $ hr-1, representing of

19 % of exergy destruction cost rate.

92


Fig. 6.9 Cost rate of exergy destruction (��D,k ) for productive components

These components are followed by second stage refrigerant compressor (111-K6) with

211.4 $ hr-1 or 16 % of total exergy destruction cost rate. Moreover, the depropanizer

column (107-C4) is ranked as fourth costly component within productive components

group, with 99.5 $ hr-1. The remaining components exergy destruction cost rates is

relatively low amounts (3 %~7 %) and do not have significant effect on system costs.

To make complete the exergoeconomic analysis, now the sum of exergy destruction cost

rate with component cost rate (��D,k + ��k) should be taken into consideration. The

distribution of this parameter is shown in Fig. 6.10.

As it is clear in Fig. 6.10, export gas compressor (106-K7) is the first component in the

highest ranking of (��D,k + ��k) parameter. It is assigned for 1560.9 $ hr-1 or in other word

39 % of total exergy destruction and component investment cost rates. This result was

expected from previous assessment, while it has the highest cost rate of exergy destruction

and simultaneously carries on the highest component investment cost rate.

Other two critical components with high (��D,k + ��k) parameter are dryers’ regeneration

furnace (104-H1) and second stage refrigerant compressor (111-K6), with approximately

10 % of total cost rates of exergy destruction and component, which assigned for

429.7 $ hr-1and 400.7 $ hr-1, respectively. Depropanizer column (107-C4) with 232.1 $ hr-1,

21%

19%

16%7%

7%

6%

5%

5%

4%4% 3% 3% 106-K7 (275.9 $ hr-1)

104-H1 (252.7 $ hr-1)111-K6 (211.4 $ hr-1)107-C4 (99.5 $ hr-1)OTHER (95.9 $ hr-1)105-K4 (77.7 $ hr-1)105-E8 (73.6 $ hr-1)103-K2 (61.2 $ hr-1)111-K5 (58.0 $ hr-1)105-C3 (51.2 $ hr-1)

93


occupied the fourth ranking place and treated gas compressor (105-K4), second stage

offgas compressor (103-K2) and demethanizer column (105-C3) occupy the same ranking

place, with approximately 210 $ hr-1 of total cost rate.

Fig. 6.10 (��D,k + ��k) Values for productive components

“Other” category represents 17 individual components. These components are imposing

341 $ hr-1 or 9 % share in (��D,k + ��k) parameter, which is quiet low influence to total cost

rate of system. The remaining of components including; first stage refrigerant compressor

(111-K5), cold box(105-E8), and gas turbine driver (105-X1) has the share of 3 % to 4 % of

the (��D,k + ��k) parameter.

High values of the exergoeconomic factor 𝑓k for components with high total cost suggest

that a reduction of the investment cost should be considered. On the other hand, low values

of the factor suggest that a reduction in the exergy destruction should be considered, even

if this would increase the investment cost of the component. The low exergoeconomic

factors 𝑓k of the ethane heater (105-E9), dry gas heater (104-E7), first stage offgas

compressor (103-K1), dryers’ regeneration furnace (104-H1), condensate desalter pre-

heater (103-E3)and second stage refrigerant compressor (111-K6) show that most of the

component’s total cost is related to exergy destruction. On the other hand, high

exergoeconomic factors 𝑓k calculated for the condensate stabilizer column (103-C1), dryers

39%

11%10%

9%

6%

5%

5%

5%4%

3% 3% 106-K7 (1560.9 $ hr-1)104-H1 (429.7 $ hr-1)111-K6 (400.7 $ hr-1)OTHER (341.0 $ hr-1)107-C4 (232.1 $ hr-1)105-K4 (212.9 $ hr-1)105-C3 (210.3 $ hr-1)103-K2 (210.0 $ hr-1)105-E8 (156.1 $ hr-1)111-K5 (139.1 $ hr-1)

94


regeneration compressor (104-K3), export gas compressor (106-K7), and deethanizer

column (105-C3), and all the pumps, suggesting that a decrease in the investment cost of

these components (if less expensive materials could be integrated) should be considered in

an attempt to improve the cost effectiveness of the plant. In the remaining components, the

average exergoeconomic factor is seen, which shows that the cost of exergy destruction is

in balance with investment cost rate of component.

Lastly, it can be concluded that from exergoeconomic point of view, high priority shall be

give to improve the export gas compressor (106-K7), dryers’ regeneration furnace (104-

H1), second stage refrigerant compressor (111-K6) and depropanizer column (107-C4).

6.4 Results of exergoeconomic diagnostic

Exergoeconomic diagnostic has been performed for productive components, by assuming

that the cost rate of components of the plant is equal to zero. Now, with considering

constant values for specific cost of natural gas and electricity and steam, and ��k = 0, the

results of exergoeconomic diagnostic at component level are obtained and reported in

Table B.5. The specific cost of streams also is available in Table D.3.

As depicted in Table D.3, the highest specific cost per unit of exergy is assigned to streams

37,38,38A,39,39A,40,41 and 42 with about 100 $ GJ-1. These high costs of the streams are

resulted from high corresponding costs of exergy of streams.

The results of Table B.5 are illustrated in Fig. 6.11. The breakdown of cost rates associated

with exergy destruction (��D) of exergoeconomic diagnostic within productive components

is shown. As it is clear in this graph, dryers’ regeneration furnace (104-H1) is the most

influential component in high exergy destruction cost rate of almost 458.9 $ hr-1 which

represents of 29 % of the total value of exergy destruction costs within productive

components.

The next important component is the export gas compressor (106-K7); which with 17 % of

share in total exergy destruction cost rate, is placed in second ranking and followed by

depropanizer (107-C4), with 9 % of share of exergy destruction cost rate. The second

refrigerant compressor (111-K6) and cold box (105-E8) occupied the same ranking place

with equal share of 7 % of exergy destruction cost.

95


Fig. 6.11 Exergy destruction cost rate (��D,k ) of productive components(Exergoeconomic diagnostic)

“Other” category of components is representative for 19 components. They imposed the

exergy destruction cost rate of 156.4 $ hr-1 or 10 % of total exergy destruction cost rate.

Remaining component including, deethanizer column (105-C3), treated gas compressor

(105-K4), second stage off gas compressor (103-K2), debutanizer column (107-C5), and

gas turbine driver (105-X1) account for exergy destruction cost rates of 3 % to 6 %, which

is quiet negligible.

Lastly, the specific costs per unit of exergy of generated products of the system are

calculated. The stream no.21B is condensate product, with specific cost per unit of exergy

of 4.8 $ GJ-1, stream no.72 is sales gas with 15.8 $ GJ-1, stream no. 63C is ethane with

15.83 $ GJ-1, stream 161A is propane with 15.9 $ GJ-1 and stream171B is butane with

15.87 $ GJ-1 specific cost per unit of exergy.

6.5 Results of exergoenvironmental analysis

The results are presented in Table B.6 and shown in Fig. 6.12. As it is apparent from Fig.

6.12, the highest exergy destruction environmental impact rate corresponds to the dryers’

regeneration furnace (104-H1), with 183130 mPts hr-1, accounting for 29 % of total share

among productive components’ exergy destruction environmental impact rate.

29%

17%

10%9%

7%

7%

6%

5%4%

3% 3% 104-H1 (458.9 $ hr-1)106-K7 (275.9 $ hr-1)OTHER (156.4 $ hr-1)107-C4 (146.5 $ hr-1)111-K6 (114.2 $ hr-1)105-E8 (104.1 $ hr-1)105-C3 (94.3 $ hr-1)105-K4 (77.7 $ hr-1)103-K2 (61.2 $ hr-1)105-X1 (53.6 $ hr-1)

96


Other two major contributors in exergy destruction environmental impacts are export gas

compressor (106-K7) and depropanizer column (107-C4) with 16 % and 10 %,

respectively. Moreover, the second stage refrigerant compressor (111-K6) is found to be

placed in next high ranking of environmental impacts due to exergy destruction, with the

share of 7 % of total value. The remaining components exergy destruction environmental

impact is not considerable values, contribute between 2~4 %, which is quiet negligible

values.

Fig. 6.12 Exergy destruction environmental impact rate (��D,k) of productive components

6.6 Results of advanced exergy-based analysis

The results obtained from the advanced exergy analysis of the selected components are

given in Table B.7 to Table B.10, correspond to component groups. It should be mentioned

that advanced exergoeconomic diagnostic and exergoenvironmental analysis have been

performed only for productive components. The main variable used to evaluate the

potential for improvement of a plant is the avoidable exergy destruction, ��D,kAV . Larger

values of avoidable exergy destruction indicate significant improvement potential.

29%

16%

10%7%

6%

6%

5%

4%

4%4%

3%2%2%2% 104-H1 (183130 mPts hr-1)106-K7 (102762 mPts hr-1)107-C4 (66475 mPts hr-1)111-K6 (42530 mPts hr-1)105-E8 (38777 mPts hr-1)105-C3 (38086 mPts hr-1)OTHER (31435 mPts hr-1)105-K4 (28944 mPts hr-1)107-C5 (26215 mPts hr-1)103-K2 (22815 mPts hr-1)105-X1 (19973 mPts hr-1)103-K1 (13122 mPts hr-1)109-C6 (12154 mPts hr-1)111-K5 (11674 mPts hr-1)

97


The results obtained from advanced exergy analysis with considering the best case

scenario (lower limit of unavoidable exergy destruction) for some components (columns

and black boxes units) are shown in Fig. 6.13.

Fig. 6.13 Avoidable and unavoidable exergy destruction in selected components

(best case scenario, if applicable)

As it is clear from this figure, highest rate of unavoidable exergy destruction corresponds to

104-H1, 103-A1, 106-A8 103-E4, and 111-A6, by approximately 90 % of total exergy

destruction rate. Then by only 10 % of avoidable exergy destruction it is concluded that

these components due to technology limitation cannot be improved. This values show that

high priorities shall be given for improvement of these components, if overcome to

technologies’ limitation is possible.

2.59

1.34

0.92

0.83

0.81

0.71

0.48

0.48

0.43

0.43

0.41

0.21

0.15

0.13

0.11

0.04

1.21

4.02

2.14

0.24

2.42

1.06

1.45

4.31

1.30

1.01

0.96

1.89

1.34

1.15

1.03

0.09

0.00 1.00 2.00 3.00 4.00 5.00 6.00

106-K7

105-C2

114-B2

105-K4

107-C4

105-E8

105-C3

106-A8

107-C5

101-B1

115-B3

111-A6

103-E4

104-H1

103-A1

116-B4ED-AV(MW) ED-UN(MW)

98


The list is followed by units; 101-B1, 114-B2, 115-B3, 116-B4 by 70 % unavoidable exergy

destruction, as it was assumed before. As far as these units developed under patented

technology, hardly the exergy destruction can be avoided, as already they are upgraded.

As assumed before, in columns, 105-C2, 105-C3, 107-C4 and 107-C5, in best case scenario,

65 % of exergy destruction is unavoidable. For example, for column 107-C4, from 3.2 MW,

in this scenario, as per our assumption, 65 % is unavoidable, which is about 2.1 MW.

Therefore, improvement cannot be easily introduced, but the need of more detail

investigation and development still exists.

For cold box (105-E8), as also has been assumed, best case scenario, 30 % of exergy

destruction is unavoidable. In other word, 70 % of exergy destruction is avoidable, which

shows the potential of improvement is high and requires further studies.

Lastly, the selected compressors are investigated. As the results show in Table B.7, and it is

apparent in Fig. 6.13, for 105-K4, approximately 22 % of destructed exergy is unavoidable.

However, 78 % of exergy destruction within this compressor could be avoided. For

compressor 106-K7, as it is illustrated in Table B.7, from 3.8 MW exergy destruction rate,

only 1.2 MW is unavoidable and 2.6 MW is avoidable exergy destruction. In other word,

31 % of exergy destruction is unavoidable, while 69 % is avoidable. Therefore, there is a

great potential of improvement of this component as well.

In general, it is clear that within assessed components by advanced exergy analysis, the

great potential of improvement belongs to selected compressors and cold box. Moreover,

the total value of avoidable exergy destruction in selected components in best case scenario

(which is applicable for columns and cold box) is about 11.8 MW.

As it has been explained before, for columns and cold box, there is another scenario

considered as “worst case scenario”, with higher percentage of unavoidable exergy

destruction rate. The results are given in Table B.8 and graphically shown in Fig. 6.14.

As it is shown, the same trend for the avoidable and unavoidable exergy destruction is

seen. For example, for column 107-C4, from 3.2 MW, in this scenario, as per our

assumption, 75 % is unavoidable, which is about 2.4 MW. Accordingly, other columns are

also subjected to this approach and therefore, less exergy destruction is estimated in

99


general as avoidable. In addition, comparing with the previous scenario, the total avoidable

exergy destruction within selected components corresponds for 10.07 MW which shows

avoidable exergy destruction rate is reduced by 15 %.

Fig. 6.14 Avoidable and unavoidable exergy destruction in selected components

(worst case scenario, if applicable)

Having estimated the unavoidable and avoidable exergy destruction enables us to go more

forward and developed the exergoeconomic and exergoenvironmental advanced analyses.

As it has been explained before, the results of advanced exergy analysis for productive

components have been integrated into results of exergoeconomic diagnostic and advanced

exergoeconomic diagnostic results are obtained and presented in Table B.7 and Table B.8.

The results also are shown graphically in Fig. 6.15 to Fig. 6.16, considering both scenarios

for columns and cold box.

2.59

1.88

1.24

1.13

0.92

0.83

0.68

0.61

0.48

0.43

0.41

0.21

0.15

0.13

0.11

0.04

1.21

3.49

0.53

2.10

2.14

0.24

1.26

1.13

4.31

1.01

0.96

1.89

1.34

1.15

1.03

0.09

0.00 1.00 2.00 3.00 4.00 5.00 6.00

116-B4

106-K7

107-C4

114-B2

111-A6

103-A1

105-C2

105-K4

107-C5

115-B3

103-E4

106-A8

101-B1

105-E8

105-C3

104-H1ED-AV(MW) ED-UN(MW)

100


Firstly, the results of considering best case scenario for columns and cold box in

combination with the remaining selected productive components are discussed.

The cost rate of exergy destruction within the selected components has been splitted to

unavoidable and avoidable cost rates.

As it is clear in Fig. 6.15, cost of exergy destruction within 104-H1, with 458.9 $ hr-1 is

significantly larger than other components, of which 90 % is unavoidable exergy

destruction cost rate. Moreover, it is obvious that other component like 105-C3, 107-C4,

107-C5, the unavoidable cost rate of exergy destruction is about 65 % of total value for cost

of exergy destruction. However, it can be seen that the cost of unavoidable exergy

destruction within 105-E8, 105-K4 and 106-K7, comparing the cost of avoidable exergy

destruction is quiet lower and most of the cost of exergy destruction in these components

can be avoided.

In best case scenario, for 105-E8, the cost rate of exergy destruction is 104.1 $ hr-1, which

31.2 $ hr-1 is unavoidable but 72.9 $ hr-1 is estimated to be avoidable, which accounts for

70 % of total cost rate.

Fig. 6.15 Avoidable and unavoidable cost rate of exergy destruction within selected productive components

(best case scenario, if applicable)

188.05

72.89

60.40

51.29

45.89

33.01

18.37

87.90

31.24

17.33

95.25

413.05

61.31

34.11

0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00 400.00 450.00 500.00

106-K7

105-E8

105-K4

107-C4

104-H1

105-C3

107-C5 CD-AV($ hr-1) CD-UN($ hr-1)

101


For compressor 105-K4, the cost rate of exergy destruction is about 77.7 $ hr-1, of which

17.3 $ hr-1 is unavoidable and 60.4 $ hr-1 is avoidable, which represents for 78 % of total

cost rate of exergy destruction within this compressor that can be avoided. The same trend

is valid for compressor 106-K7, that the total cost of exergy destruction is 275.9 $ hr-1, and

from this cost, 188 $ hr-1 or 69 % can be avoided.

In worst case scenario, most of the components followed the same trend as in best case

scenario, but with higher cost rate of exergy destruction.

As it is obvious in Fig. 6.16, in columns 105-C3, 107-C4, 107-C5, the unavoidable cost rate

of exergy destruction is about 75 % of total value for cost of exergy destruction. However, it

can be seen that the cost of unavoidable exergy destruction within 105-E8 is significant

here, about 60 % of total exergy destruction cost rate, and the cost of avoidable exergy

destruction is quiet lower comparing the best case scenario, with reduction about 42 %.

Fig. 6.16 Avoidable and unavoidable cost rate of exergy destruction within selected productive components (worst case scenario, if applicable)

In worst case scenario, for 105-E8, the cost rate of exergy destruction is 104.1 $ hr-1, which

62.4 $ hr-1 is unavoidable but 41.6 $ hr-1 is estimated to be avoidable, which accounts for

40 % of total cost rate.

188.05

60.40

45.89

41.65

36.63

23.58

13.12

87.90

17.33

413.05

62.47

109.90

70.74

39.36

0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00 400.00 450.00 500.00

106-K7

105-K4

104-H1

105-E8

107-C4

105-C3

107-C5CD-AV($ hr-1) CD-UN($ hr-1)

102


It is apparent from Fig. 6.16 that same as best case scenario, the highest unavoidable cost of

exergy destruction belongs to 104-H1, with 90 % of its total exergy destruction cost, and

followed by 107-C4, 105-C3 and 107-C5, with 75 % of unavoidable exergy destruction cost.

Finally, it can be concluded that in general the 105-K4, and 106-K7, and lastly 105-E8 with

high avoidable exergy cost rates have the potential of cost reduction of exergy destruction.

As explained before, the results of advanced exergy analysis can be integrated to

exergoenvironmental analysis and it can be seen in selected productive components, how

much of environmental impacts due to exergy destruction is avoidable. The results are

presented in Table B.7 and Table B.8 and graphically shown in Fig. 6.17 and Fig. 6.18 for

both considered scenarios for columns and cold box.

In best case scenario, whose results shown in Fig. 6.17, it is clear that two critical

components which have the highest rate of environmental impact due to exergy

destruction, include 104-H1 and 106-K7. However, most of environmental impacts of

exergy destruction within 104-H1 is not avoidable, which accounts for 90 % of total value.

Fig. 6.17 Environmental impact rate of exergy destruction (best case scenario)

70029.2

27143.9

23266.2

22491.2

18313.0

13330.0

9175.3

32732.8

11633.1

43,208.7

6452.8

164817.4

24755.8

17039.8

0.0 20000.0 40000.0 60000.0 80000.0 100000.0 120000.0 140000.0 160000.0 180000.0 200000.0

106-K7

105-E8

107-C4

105-K4

104-H1

105-C3

107-C5 BD-AV (mPts hr-1) BD-UN (mPts hr-1)

103


However, in 106-K7, from 102762 mPts hr-1, 70029 mPts hr-1 of environmental impacts

due to exergy destruction is avoidable, which corresponds to approximately, 68 % of total

value.

As can be seen from Fig. 6.17 the component with highest rate of avoidable environmental

impacts associated with exergy destruction, is 105-K4, which is the highest rate of

avoidable environmental impact among investigated components. Approximately, 77.7 %

of total environmental impact of exergy destruction within this component is avoidable.

The next component, which has the high avoidable environmental impacts of exergy

destruction is 105-E8, which from 38777 mPts hr-1, 27144 mPts hr-1 is avoidable and

accounts for 70 % of total value of environmental impact rate of exergy destruction.

The unavoidable environmental impact of exergy destruction within columns including

105-C3, 107-C4 and 107-C5, as has been assumed for unavoidable exergy destruction, is

about 65 % of total value. Therefore, the most of environmental impact of these

components cannot be avoided.

In worst case scenario considered for columns and cold box, unavoidable exergy

destruction rate has been considered 75 % and 60 %. As it is shown in Fig. 6.18, in analogy

with unavoidable exergy destruction, 75 % of environmental impact associated with exergy

destruction in columns and 60 % of it for 105-E8 is not avoidable. However, with the

similar trend to best case scenario, the highest rate of avoidable environmental impact rate

belongs to compressors 105-K4 and 106-K7, with 77.7 % and 68.4 % of total values for

environmental impacts of exergy destruction.

104


Fig. 6.18 Environmental impact rate of exergy destruction (worst case scenario)

From Fig. 6.18, it can be understood that the highest potential for reducing the

environmental impact of exergy destruction belongs to 106-K7, with 70029 mPts hr-1,

followed by 105-K4, with 22491 mPts hr-1.

70029.2

22491.2

18313.0

16618.7

15510.8

9521.4

6553.8

32732.8

6452.8

164817.4

49856.2

23266.2

28564.3

19661.3

0.0 20000.0 40000.0 60000.0 80000.0 100000.0 120000.0 140000.0 160000.0 180000.0 200000.0

106-K7

105-K4

104-H1

107-C4

105-E8

105-C3

107-C5BD-AV (mPts hr-1) BD-UN (mPts hr-1)

105

CHAPTER 7

7 Summary and conclusions In this thesis, major units of operations in a gas refinery have been analyzed using

exergy-based analyses, i.e. conventional and advanced exergetic, exergoeconomic,

exergoeconomic diagnostic and exergoenvironmental analyses. The components have been

categorized in three groups: productive components, units and dissipative components.

The conventional exergy analysis has been applied for all the groups of components, while

the exergoeconomic, exergoeconomic diagnostic, exergoenvironmental and advanced

analyses have been applied only for productive components. The most influential

components in each analysis have been ranked in Table 7.1.

Table 7.1 The four most influential components as ranked by each analysis

A. Conventional analyses (Based on exergy destruction / costs and total environmental impact)

B. Advanced analyses (Based on avoidable exergy destruction / cost and environmental impact)

A1. Exergetic

A2. Exergoeconomic

A3. Diagnostic Exergoeconomic

A4. Exergoenvironmental

B1. Exergetic

B2. Exergoeconomic

B3. Diagnostic Exergoeconomic

B4. Exergoenvironmental

105-C2 106-K7 104-H1 104-H1 105-K4 - 105-K4 105-K4 106-A8 104-H1 106-K7 106-K7 106-K7 - 106-K7 106-K7 106-K7 111-K6 107-C4 107-C4 105-E8 - 105-E8 105-E8 107-C4 107-C4 111-K6/105-E8 111-K6 - - - -

In conventional exergy-based analyses, except for conventional exergy analysis, the main

four components are the same in all the other conventional analyses, with a bit different

ranking. However, in advanced exergy analyses, the main components are the same, and in

the same ranking. A short summary of the main results from each analysis is presented

below.

7.1 Conventional exergy analysis

Through the exergy analysis, the location, magnitude and sources of thermodynamic

inefficiencies in the gas refinery are identified. In addition, from the perspective of an

exergy analysis, the greater the exergy destruction in a component, the higher the priority

for improvement is. Hence, high priority should be given to the order of demethanizer

(105-C2) with 5.3 MW, export gas air cooler (106-A8) with 4.8 MW, export gas compressor

Chapter 7-Summary and conclusions

(106-K7) with 3.8 MW and the depropanizer (107-C4) with 3.2 MW of exergy destruction

rate.

7.2 Economic and exergoeconomic analysis

Through the exergoeconomic analysis, the information of the cost in gas plant has been

assessed in terms not only of the capital investment but also of the cost of exergy. Based on

the results of the exergoeconomic analysis, components can be categorized into three

groups; each group needs individually-characterized effort for cost reduction. For the first

group, showing a high exergoeconomic factor, the exergy destruction and the relevant cost

of exergy destruction need to be reduced; these efforts may contribute the overall cost

reduction. For the second group, showing a lower exergoeconomic factor, investment cost

need to be reduced even if a reduction of the component efficiency must be accepted. For

the third group, showing intermediate values of the exergoeconomic factor, a closer

investigation is needed. However, based on total cost of exergy destruction and component

investment cost rates, it can be concluded that from exergoeconomic point of view, high

priority shall be give to improve the export gas compressor (106-K7), dryers’ regeneration

furnace (104-H1), second stage refrigerant compressor (111-K6) and depropanizer column

(107-C4).

7.3 Exergoeconomic diagnostic

With considering constant values for specific cost of natural gas and electricity and steam,

and assuming (��k = 0) in exergoeconomic analysis, the results of exergoeconomic

diagnostic at component level are obtained. The results show that the most influential

component is dryers’ regeneration furnace (104-H1), which is followed by export gas

compressor (106-K7). The depropanizer (107-C4) is placed in ranking order of third

influential components and the second refrigerant compressor (111-K6) and cold box

(105-E8) occupied the same ranking place hereafter.

108


7.4 Exergoenvironmental analysis

In exergoenvironmental analysis, the component-related environmental impact is

neglected and only the exergy destruction corresponding environmental impacts have been

calculated for productive components. The obtained results show that highest exergy

destruction environmental impact rate corresponds to the dryers’ regeneration furnace

(104-H1), followed by export gas compressor (106-K7). The depropanizer (107-C4) and

second stage refrigerant compressor (111-K6) occupied the third and fourth ranking place

in environmental impacts associated with exergy destruction.

7.5 Advanced exergy-based analysis

In advanced exergy-based analysis, the components with high rate of exergy destruction

have been selected and analyzed from exergetic, economic and environmental point of

view. The exergy destruction, corresponding cost and environmental impacts of most

important components have been splitted to avoidable and unavoidable parts. The

components in each category with highest avoidable part have the highest potential of

improvement. In this regards, the treated gas compressor (105-K4), export gas compressor

(106-K7) and cold box (105-E8) have the highest rate of avoidable exergy destruction, and

consequently avoidable cost of exergy destruction and avoidable environmental impact

associated with exergy destruction, and they can be improved.

7.6 Summary of the future work

In this thesis, major units of a gas refinery have been analyzed by exergy-based analyses

and the component which are corresponding to improve the system, in each analysis have

been identified.

As far as the interaction of all system components are quiet complex, therefore, considering

smaller boundary limits enables us to split the exergy destruction into endogenous and

exogenous in order to discover the interrelations between the plant components. In this

case, estimating the avoidable endogenous exergy destruction is a good factor for

justification of components with high improvement potential.

Moreover, it is recommended that the flaring network (as a source of heat loss) to be

optimized. In this regard, the different process design to reduce the flaring could be

109


examined through energetic and exergetic analyses. By having this data, the heat of flaring

can be used in different part of the plant to produce useful product like steam which results

in saving money and consequently less environmental emissions.

Other challenging components in this research were recognized as distillation columns. By

reviewing of the possibility of improving the distillation columns to the new technology

options (like heat integrated distillation columns or vapor recompression columns) and

performing the exergy-based analyses, the effect of improvement can be assessed. The

distillation columns like demethanizer and depropanizer as the contributors to the highest

exergy destruction can be re-designed and re-assessed thermodynamically and

economically. Moreover, reducing the operating pressure in columns, without affecting the

product specification and column flooding, is a potential improvement of columns.

Reduction in column pressure will reduce the column bottom temperature which

considerably reduces the energy loss. On the other hand, at lower column pressure,

separation efficiency is higher which consequently reduce the reflux and energy

consumption. This option can be examined through exergy analysis.

Another proposed improvement for future design of gas processing plant is the heat

integration between columns’ reboilers and compressors’ discharge gas. During the

compression, process fluid will be heated to a high temperature which normally is cooled

by air. On the other side, the gas plant fractionators requires high amount of heat for re-

boiling at almost low temperature. This heat can be integrated and the integrated process

to be assessed by exergy analysis.

Fired heaters (furnaces) also can be used as distillation columns reboilers. A pump is

required to circulate the columns bottoms through heat transfer tubes in the furnace. The

required heat for fired heater reboilers can be provided by fuel gas or fuel oil. However, the

reduction in exergy destruction should be assessed considering the cost of fired heaters

and associated pumps.

Another design improvement which can be considered and evaluated as gas plant energy

saving option, is preheating the dryers’ regeneration gas in a preheater before sending the

regeneration gas to dryers’ regeneration furnace. Normally, regeneration gas is cooled by

air and this heat can be recovered in mentioned preheater. This alternative also can be

evaluated by exergy-based analyses.

110


Lastly, the information provided in this thesis should be used to realize improved designs

of the plant structures. This will provide a helpful guide on how environmental and

economic considerations interact and new design modification of the plant can be obtained

to have a less costly and environmental friendly plant.

111

References

References

[1] Abdel-Aal HK, Aggour MA, Fahim MA (2015) Petroleum and Gas Field Processing. CRC Press

[2] Mokhatab S, Poe W (2012) Handbook of natural gas transmission and processing, 2nd edn. Gulf Professional Publishing. https://doi.org/10.1016/C2010-0-66115-3

[3] Kidnay AJ, Parrish WR (2006) Fundamentals of Natural Gas Processing. CRC Press.

[4] World Energy Council (2017). https://www.worldenergy.org/. Accessed 01 June 2017

[5] Natural Resources Canada (2017). https://www.nrcan.gc.ca/home.

[6] British Petroleum (2017) Energy Outlook. https://safety4sea.com/wp-content/uploads/2017/01/BP-Energy-Outlook-2017_01.pdf

[7] International Energy Agency (2017). https://www.iea.org. Accessed 29 May 2017

[8] World Energy Council (2017) World Energy Perspectives, The role of Natural Gas, Executive Summary. https://www.worldenergy.org/wp-content/uploads/2017/11/WEC-Executive-Summary-Gas-Report-WEB.pdf

[9] British Petroleum (2017) Statistical Review of World Energy, 66th edn. https://www.bp.com/content/dam/bp-country/de_ch/PDF/bp-statistical-review-of-world-energy-2017-full-report.pdf

[10] ExxonMobil (2017) 2018 Energy & Carbon Summary-Positioning for a Lower-Carbon Energy Future. https://corporate.exxonmobil.com/-/media/Global/Files/energy-and-carbon-summary/2018-Energy-and-Carbon-Summary_archive.pdf

[11] World Energy Resources (2016) Natural Gas. https://www.worldenergy.org/wp-content/uploads/2016/10/World-Energy-Resources-Full-report-2016.10.03.pdf

[12] Eurostat (2017) Energy, transport and environment indicators. https://ec.europa.eu/eurostat/documents/3217494/8435375/KS-DK-17-001-EN-N.pdf/18d1ecfd-acd8-4390-ade6-e1f858d746da

[13] International Gas Union (2017) Wholesale gas price survey. http://www.igu.org/sites/default/files/node-document-field_file/IGU_Wholesale %20Gas %20Price %20Survey %202017 %20Digital_0.pdf

113

https://doi.org/10.1016/C2010-0-66115-3

https://www.worldenergy.org/

https://www.nrcan.gc.ca/home

https://safety4sea.com/wp-content/uploads/2017/01/BP-Energy-Outlook-2017_01.pdf

https://safety4sea.com/wp-content/uploads/2017/01/BP-Energy-Outlook-2017_01.pdf

https://www.iea.org/

https://www.worldenergy.org/wp-content/uploads/2017/11/WEC-Executive-Summary-Gas-Report-WEB.pdf

https://www.worldenergy.org/wp-content/uploads/2017/11/WEC-Executive-Summary-Gas-Report-WEB.pdf

https://www.bp.com/content/dam/bp-country/de_ch/PDF/bp-statistical-review-of-world-energy-2017-full-report.pdf

https://www.bp.com/content/dam/bp-country/de_ch/PDF/bp-statistical-review-of-world-energy-2017-full-report.pdf

https://corporate.exxonmobil.com/-/media/Global/Files/energy-and-carbon-summary/2018-Energy-and-Carbon-Summary_archive.pdf

https://corporate.exxonmobil.com/-/media/Global/Files/energy-and-carbon-summary/2018-Energy-and-Carbon-Summary_archive.pdf

https://www.worldenergy.org/wp-content/uploads/2016/10/World-Energy-Resources-Full-report-2016.10.03.pdf

https://www.worldenergy.org/wp-content/uploads/2016/10/World-Energy-Resources-Full-report-2016.10.03.pdf

https://ec.europa.eu/eurostat/documents/3217494/8435375/KS-DK-17-001-EN-N.pdf/18d1ecfd-acd8-4390-ade6-e1f858d746da

https://ec.europa.eu/eurostat/documents/3217494/8435375/KS-DK-17-001-EN-N.pdf/18d1ecfd-acd8-4390-ade6-e1f858d746da

http://www.igu.org/sites/default/files/node-document-field_file/IGU_Wholesale%20Gas%20Price%20Survey%202017%20Digital_0.pdf

http://www.igu.org/sites/default/files/node-document-field_file/IGU_Wholesale%20Gas%20Price%20Survey%202017%20Digital_0.pdf

References

[14] Natural Gas (2013) Processing Natural Gas. http://naturalgas.org/naturalgas/processing-ng/

[15] Partho SR, Amin MR (2011) Aspen-HYSYS Simulation of Natural Gas Processing Plant. J Chem Eng 26 (1): 62-65. http://dx.doi.org/10.3329/jce.v26i1.10186

[16]

Energy (2017) Natural gas infrastructure. https://www.energy.gov/sites/prod/files/2015/06/f22/Appendix %20B- %20Natural %20Gas_1.pdf

[17] 2b1st consulting (2015) Cyprus Aphrodite gas field to benefit from Isarel Leviathan delays. https://www.2b1stconsulting.com/cyprus-aphrodite-gas-field-to-benefit-from-israel-leviathan-delays/

[18] Bejan A, Tsatsaronis G, Moran M (1996) Thermal design and optimization. Wiley, New York

[19] Tsatsaronis G, Cziesla F (2002) Thermoeconomics. In: Encyclopedia of physical science and technology. Academia Press, New York, p 659-680

[20] Lozano MA, Bartolome JL, Valero A, Reini M (1994) Thermoeconomic Diagnosis of Energy. In: Flowers 94: Florence World Energy Research Symposium, Florence

[21] Tsatsaronis G, Morosuk T (2008) A general exergy-based method for combining a cost analysis with an environmental impact analysis: Part I — Theoretical development. In: ASME International Mechanical Engineering Congress and Exposition, Boston. http://dx.doi.org/10.1115/IMECE2008-67218

[22] Tsatsaronis G, Morosuk T (2008) A general exergy-based method for combining a cost analysis with an environmental impact analysis: Part II – Application to a cogeneration system. In: ASME International Mechanical Engineering Congress and Exposition, Boston. http://dx.doi.org/10.1115/IMECE2008-67219

[23] Tsatsaronis G, Bejan A, Mamut E (eds) (1999) Strengths and limitations of exergy analysis. In: Thermodynamic Optimization of Complex Energy Systems. Kluwer Academic Publishers, Dordrecht, p 93-100.

[24] Petrakopoulou F (2011) Comparative Evaluation of Power Plants with CO2 Capture: Thermodynamic, Economic and Environmental Performance. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-2717

[25] Erlach B (2014) Biomass upgrading technologies for carbon-neutral and carbon-negative electricity generation. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-4224

[26] Lee YD (2015) Thermodynamic, Economic and Environmental Evaluation of Solid-Oxide Fuel-Cell Hybrid Power-Generation Systems. Dissertation, Technical

114

http://naturalgas.org/naturalgas/processing-ng/

http://dx.doi.org/10.3329/jce.v26i1.10186

https://www.energy.gov/sites/prod/files/2015/06/f22/Appendix%20B-%20Natural%20Gas_1.pdf

https://www.energy.gov/sites/prod/files/2015/06/f22/Appendix%20B-%20Natural%20Gas_1.pdf

https://www.2b1stconsulting.com/cyprus-aphrodite-gas-field-to-benefit-from-israel-leviathan-delays/

https://www.2b1stconsulting.com/cyprus-aphrodite-gas-field-to-benefit-from-israel-leviathan-delays/

http://dx.doi.org/10.1115/IMECE2008-67218

http://dx.doi.org/10.1115/IMECE2008-67219

http://dx.doi.org/10.14279/depositonce-4224

References

University of Berlin. http://dx.doi.org/10.14279/depositonce-4546

[27] Sorgenfrei M (2016) Analysis of IGCC-based plants with carbon capture for an efficient and flexible electric power generation. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-5073

[28] Thermo-economic evaluation, optimization and synthesis of large-scale coal-fired power plants http://dx.doi.org/10.14279/depositonce-5451

[29] Zhao P (2015) A Computer Program for the Exergoeconomic Analysis of Energy Conversion Plants. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-4890

[30] John JP (2017) An Investigation for Energy Sustainability in Cement Industries in Tanzania: The Case of Mbeya Cement. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-5810

[31] Bender D (2018) Exergy-Based Analysis of Aircraft Environmental Control Systems and its Integration into Model-Based Design. Dissertation, Technical University of Berlin.


[32] Mergenthaler P (2018) Exergetische Untersuchung einer Carbon Black Anlage. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-8614

[33] Jado AHK (2018) Evaluation and Improvement of Energy Management in Industrial Baking Ovens. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-8419

[34] Blumberg TD (2018) Comparative evaluation of methanol production processes using natural gas: A thermodynamic and economic assessment. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-7771

[35] Tesch SJ (2018) Exergy-based methods applied to the processes of LNG regasification integrated into air separation units. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-8134

[36] Dincer S, Erkan D (1986), Available energy analysis of a petroleum refinery operation. Appl Energy 22:157–163. https://doi.org/10.1016/0306-2619(86)90079-6

[37] Rivero R (2002) Application of the exergy concept in the petroleum refining and petrochemical industry. J Energy Convers Manage 43:1199–1220.

115







https://doi.org/10.1016/0306-2619(86)90079-6

References

https://doi.org/10.1016/S0196-8904(02)00008-0

[38] Vilarinho AN, Campos JBLM, Pinho C (2016) Energy and exergy analysis of an aromatics plant. Case Stud Therm Eng 8:115–127. https://doi.org/10.1016/j.csite.2016.06.003

[39] Cruz FE, Oliveira S (2008) Petroleum Refinery Hydrogen Production Unit: Exergy and Production cost evaluation. Int J Thermodyn 11:187-193.

[40] Dilmac OF, Ozkan SK (2008) Energy and exergy analyses of a steam reforming process for hydrogen production. Int J Exergy 5:241-248. http://dx.doi.org/10.1504/IJEX.2008.016678

[41] Nuhu M, Olawale AS, Salahudeen N, Yusuf AZ, Mustapha Y (2012) Exergy and Energy Analysis of Fluid Catalytic Cracking Unit in Kaduna Refining and Petrochemical Company. Int J Chem Eng Appl 3:441–445. http://dx.doi.org/10.7763/IJCEA.2012.V3.239

[42] Yang Q, Qian Y, Kraslawski A, Zhou H, Yang S (2016) Advanced exergy analysis of an oil shale retorting process. Appl Energy 165:405-415. https://doi.org/10.1016/j.apenergy.2015.12.104

[43] Rivero R, Rendon C, Monroy L (1999) The Exergy of Crude Oil Mixtures and Petroleum Fractions:Calculation and Application. Int J App Thermodyn 2:115-123 http://dx.doi.org/10.5541/ijot.19

[44] Al-Muslim H, Dincer I (2005) Thermodynamic analysis of crude oil distillation systems. Int J Energy Res 29:637–655. https://doi.org/10.1002/er.1097

[45] Rivero R (2001) Exergy simulation and optimization of adiabatic and diabatic binary distillation. J Energy 26:561–593. https://doi.org/10.1016/S0360-5442(01)00020-2

[46] Koeijer G, Rivero R (2003) Entropy production and exergy loss in experimental distillation columns. Chem Eng Sci 58:1587–1597. https://doi.org/10.1016/S0009-2509(02)00627-9

[47] Rivero R, Rendon C, Gallegos S (2004) Exergy and exergoeconomic analysis of a crude oil combined distillation unit. J Energy 29:1909–1927. https://doi.org/10.1016/j.energy.2004.03.094

[48] Rivero R, Garcia M, Urquiza J (2004) Simulation, exergy analysis and application of diabatic distillation to thertiary amyl methyl ether production unit of a crude oil refinery. J Energy 29:467-489. https://doi.org/10.1016/j.energy.2003.10.007

[49] Costa CTOG, Queiroz EM, Pessoa FLP (2009) A software for the calculation of the exergetic efficiency in distillation columns. Comput Aided Chem Eng 27:1005-1010. https://doi.org/10.1016/S1570-7946(09)70388-8

116

https://doi.org/10.1016/S0196-8904(02)00008-0

https://doi.org/10.1016/j.csite.2016.06.003

http://dx.doi.org/10.7763/IJCEA.2012.V3.239

https://doi.org/10.1016/j.apenergy.2015.12.104

http://dx.doi.org/10.5541/ijot.19

https://doi.org/10.1002/er.1097

https://doi.org/10.1016/S0360-5442(01)00020-2

https://doi.org/10.1016/S0009-2509(02)00627-9

https://doi.org/10.1016/j.energy.2004.03.094


https://doi.org/10.1016/S1570-7946(09)70388-8

References

[50] Khoa TD, Shuhaimi M, Hashim H, Panjeshahi MH (2010) Optimal design of distillation column using three dimensional exergy analysis curves. J Energy 35:5309–5319. https://doi.org/10.1016/j.energy.2010.07.032

[51] Tarighaleslami AH, Omidkhah MR, Ghannadzadeh A, Hesas RH (2012) Thermodynamic evaluation of distillation columns using exergy loss profiles: a case study on the crude oil atmospheric distillation column. Clean Technol. Environ. Policy 14:381–387. https://doi.org/10.1007/s10098-012-0465-6

[52] Silva JAM, Oliveira SD, Pulgarín J, et al (2015) On the Exergy Determination for Petroleum Fractions and Separation Processes Efficiency. Heat Transfer Eng 36:974–983. https://doi.org/10.1080/01457632.2015.972752

[53] Izyan ZN, Shuhaimi M (2014) Exergy analysis for fuel reduction strategies in crude distillation unit. J Energy 66:891–897. http://dx.doi.org/10.1016/j.energy.2014.01.026

[54] Odejobi OJ (2015) Exergy and economic analyses of crude oil distillation unit. Afr J Eng Res 3(2): 44-55.

[55] Wei Z, Zhang B, Wu S, et al (2012) Energy-use analysis and evaluation of distillation systems through avoidable exergy destruction and investment costs. J Energy 42:424–433. http://dx.doi.org/10.1016/j.energy.2012.03.026

[56] Osuolale FN, Zhang J (2017) Thermodynamic optimization of atmospheric distillation unit. Comp Chem Eng 103:201–209. https://doi.org/10.1016/j.compchemeng.2017.03.024

[57] Rosen MA, Dincer I (2004) A study of industrial steam process heating through exergy analysis. Int J Energy Res 28:917–930. https://doi.org/10.1002/er.1005

[58] Khodaei H, Seresht RT, Arghandeh R (2009) Exergy analysis of the steam network in Tehran oil refinery and evaluation with new scenario. In: proceeding of 31st Industrial Energy Technology Conference, New Orleans, 2009

[59] Silva JAM, Pellegrini LF, Plaza C, Rucker C, Oliveira S (2010) Exergy and Exergoeconomic Analysis of a Petroleum Refinery Utilities Plant Using the Condensing to Power Method. In:13th Brazilian Congress of Thermal Sciences and Engineering, Uberlandia, 2010 https://bdpi.usp.br/item/002141816

[60] Oliveira S, Hombeeck MV (1997) Exergy analysis of petroleum separation processes in offshore platforms. Energy Convers Manage 38:1577–1584. https://doi.org/10.1016/S0196-8904(96)00219-1

[61] Nguyen TV, Pierobon L, Elmegaard B, et al (2013) Exergetic assessment of energy

117


https://doi.org/10.1007/s10098-012-0465-6

https://doi.org/10.1080/01457632.2015.972752

http://dx.doi.org/10.1016/j.energy.2014.01.026


https://doi.org/10.1016/j.compchemeng.2017.03.024


https://bdpi.usp.br/item/002141816

https://doi.org/10.1016/S0196-8904(96)00219-1

References

systems on North Sea oil and gas platforms. J Energy 62:23–36. https://doi.org/10.1016/j.energy.2013.03.011

[62] Nguyen TV, Voldsund M, Elmegaard B, et al (2014) On the definition of exergy efficiencies for petroleum systems: Application to offshore oil and gas processing. J Energy 73:264–281. https://doi.org/10.1016/j.energy.2014.06.020

[63] Voldsund M, Nguyen TV, Elmegaard B, et al (2014) Exergy destruction and losses on four North Sea offshore platforms: A comparative study of the oil and gas processing plants. J Energy 74:45–58. https://doi.org/10.1016/j.energy.2014.02.080

[64] Voldsund M, Ertesvåg IS, He W, Kjelstrup S (2013) Exergy analysis of the oil and gas processing on a North Sea oil platform a real production day. J Energy 55:716–727. https://doi.org/10.1016/j.energy.2013.02.038

[65] Teixeira AM, Medeiros JL, Araújo OQF (2015) Exergy Analysis of Monoethylene Glycol (MEG) Recovery Systems. Comp Aided Chem Eng 37:533-538 https://doi.org/10.1016/B978-0-444-63578-5.50084-0

[66] Gallo WLR, Gallego AG, Acevedo VL, et al (2017) Exergy analysis of the compression systems and its prime movers for a FPSO unit. J Nat Gas Sci Eng 44:287–298. https://doi.org/10.1016/j.jngse.2017.04.023

[67] Silva JAM, Oliveira S (2018) Unit exergy cost and CO2 emissions of offshore petroleum production. J Energy 147:757–766. https://doi.org/10.1016/j.energy.2018.01.100

[68] Panjeshahi MH, Harati F, Nouzari MM (2010) Improving Energy efficiency in Natural Gas Refineries, using Exergy Analysis. J Chem Eng Trans 21:121-126. https://doi.org/10.3303/CET1021021

[69] Montelongo-Luna JM, Svrcek WY, Young BR (2007) An exergy calculator tool for process simulation. Asia-Pac J Chem Eng 2:431–437. https://doi.org/10.1002/apj.76

[70] Kianfar E, Tayebinejad E (2014) Energy Optimization of Ilam Gas Refinery Unit 100(stabilization) by using HYSYS REFINERY Software. Int Res J Basic Appl Sci 8(9): 1265-1270.

[71] Tahouni N, Khoshchehreh R, Panjeshahi MH (2014) Debottlenecking of condensate stabilization unit in a gas refinery. J Energy 77:742–751. https://doi.org/10.1016/j.energy.2014.09.047

[72] Khadem Samimi A, Fard SS, Abyaneh MZ (2014) Minimizing thermodynamic losses in sulfur recovery unit: An exergy analysis approach. J Pet Coal 56:74-78.

[73] Banat F, Younas O, Didarul I (2014) Energy and exergical dissection of a natural gas sweetening plant using methyldiethanol amine (MDEA) solution. J Nat Gas Sci Eng 16:1–7.

118





https://doi.org/10.1016/B978-0-444-63578-5.50084-0

https://doi.org/10.1016/j.jngse.2017.04.023


https://doi.org/10.3303/CET1021021

https://doi.org/10.1002/apj.76


References

http://dx.doi.org/10.1016/j.jngse.2013.10.005

[74] Suleiman B, Abdulkareem A, Abdulsalam Y, et al (2016) Thermo-economic analysis of natural gas treatment process using triethanolamine (TEA) and diethanolamine (DEA) as gas sweeteners. J Nat Gas Sci Eng 36:184–201. http://dx.doi.org/10.1016 %2Fj.jngse.2016.10.023

[75] Shin J, Yoon S, Kim J (2015) Application of exergy analysis for improving energy efficiency of natural gas liquids recovery processes. J App Therm Eng 75:967–977. http://dx.doi.org/10.1016/j.applthermaleng.2014.10.042

[76] Mehrpooya M, Jarrahian A, Pishvaie MR (2006) Simulation and exergy-method analysis of an industrial refrigeration cycle used in NGL recovery units. Int J Energy Res 30:1336–1351. http://dx.doi.org/10.1002/er.1256

[77] Mehrpooya M, Gharagheizi F, Vatani A (2009) Thermoeconomic analysis of a large industrial propane refrigeration cycle used in NGL recovery plant. Int J Energy Res 33:960–977. https://doi.org/10.1002/er.1523

[78] Tirandazi B, Mehrpooya M, Vatani A, Moosavian SMA (2011) Exergy analysis of C2+ recovery plants refrigeration cycles. Chem Eng Res Des 89:676–689. http://dx.doi.org/10.1016/j.cherd.2010.10.006

[79] Ghorbani B, Salehi GR, Ghaemmaleki H, et al (2012) Simulation and optimization of refrigeration cycle in NGL recovery plants with exergy-pinch analysis. J Nat Gas Sci Eng 7:35–43. https://doi.org/10.1016/j.jngse.2012.03.003

[80] Ghorbani B, Salehi G, Amidpour M, Hamedi M (2012) Exergy and exergoeconomic evaluation of gas separation process. J Nat Gas Sci Eng 9:86–93. https://doi.org/10.1016/j.jngse.2012.05.001

[81] Tahmasebi S, Abbasabadi AB, Ghasemi N, et al (2015) Investigation of various feed conditions on NGL recovery plant energy and exergy performance: A case study. J Nat Gas Sci Eng 22:83–89. http://dx.doi.org/10.1016/j.jngse.2014.11.019

[82] Mehrpooya M, Lazemzade R, Sadaghiani MS, Parishani H (2016) Energy and advanced exergy analysis of an existing hydrocarbon recovery process. Energy Convers Manage 123:523–534. http://dx.doi.org/10.1016/j.enconman.2016.06.069

[83] Vatani A, Mehrpooya M, Tirandazi B (2013) A novel process configuration for co-production of NGL and LNG with low energy requirement. Chem Eng Process 63:16–24. https://doi.org/10.1016/j.cep.2012.10.010

[84] Mehrpooya M, Hossieni M, Vatani A (2014) Novel LNG-Based Integrated Process Configuration Alternatives for Coproduction of LNG and NGL. Ind Eng Chem Res

119


http://dx.doi.org/10.1016%2Fj.jngse.2016.10.023

http://dx.doi.org/10.1016/j.applthermaleng.2014.10.042

http://dx.doi.org/10.1002/er.1256


http://dx.doi.org/10.1016/j.cherd.2010.10.006




http://dx.doi.org/10.1016/j.enconman.2016.06.069

https://doi.org/10.1016/j.cep.2012.10.010

References

53:17705–17721. https://doi.org/10.1021/ie502370p

[85] Ghorbani B, Mehrpooya M, Hamedi M-H, Amidpour M (2017) Exergoeconomic analysis of integrated natural gas liquids (NGL) and liquefied natural gas (LNG) processes. Appl Therm Eng 113:1483–1495. https://doi.org/10.1016/j.applthermaleng.2016.11.142

[86] Ansarinasab H, Mehrpooya M (2017) Evaluation of novel process configurations for coproduction of LNG and NGL using advanced exergoeconomic analysis. App Therm Eng 115:885–898. http://dx.doi.org/10.1016/j.applthermaleng.2017.01.019

[87] Ghorbani B, Shirmohammadi R, Mehrpooya M (2018) A novel energy efficient LNG/NGL recovery process using absorption and mixed refrigerant refrigeration cycles – Economic and exergy analyses. Appl Therm Eng 132:283–295. http://dx.doi.org/10.1016/j.applthermaleng.2017.12.099

[88] Bin Omar MN (2015) Thermodynamic and Economic Evaluation of Existing and Prospective Processes for Liquefaction of Natural Gas in Malaysia. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-5565

[89] Primabudi E (2019) Evaluation and Optimization of Natural Gas Liquefaction Process with Exergy-Based Methods: A Case Study for C3MR. Dissertation, Technical University of Berlin. http://dx.doi.org/10.14279/depositonce-8519

[90] Mehdizadeh-Fard M, Pourfayaz F, Mehrpooya M, Kasaeian A (2018) Improving energy efficiency in a complex natural gas refinery using combined pinch and advanced exergy analyses. Appl Therm Eng 137:341–355. http://dx.doi.org/10.1016/j.applthermaleng.2018.03.054

[91] Valero A, Lozano MA, Serra L, Torres C (1994) Application of the exergetic cost theory to the CGAM problem. J Energy 19(3):365–381. https://doi.org/10.1016/0360-5442(94)90116-3

[92] Schwarz P, Lozano MA, Von Spakovsky MR, Valero A (1997) Diagnostic analysis of a PFBC power plant using a thermoeconomic methodology. In:TAIES’97 Proceedings of International Conference June 10-13, Beijing

[93] Valero A., Correas L., Serra L. (1999) On-Line Thermoeconomic Diagnosis of Thermal Power Plants. In: Bejan A., Mamut E. (eds) Thermodynamic Optimization of Complex Energy Systems. NATO Science Series (Series 3. High Technology), Vol 69. Springer, Dordrecht, pp 117–136

[94] Verda V (2001) Thermoeconomic Diagnosis of an Urban District Heating System Based on Cogenerative Steam and Gas Turbines. Dissertation, Politecnico di Torino and University of Zaragoza. https://core.ac.uk/reader/11428694

120

https://doi.org/10.1021/ie502370p

https://doi.org/10.1016/j.applthermaleng.2016.11.142






https://doi.org/10.1016/0360-5442(94)90116-3

https://core.ac.uk/reader/11428694

References

[95] Verda V, Serra L, Valero A (2001) The effects of the regulation system on the thermoeconomic diagnosis of a power plant, Part I: The diagnosis procedure; Part II: Application to a gas turbine based cogeneration plant. In: International Conference ECOS, Istanbul, 2001

[96] Torres C, Valero A, Serra L, Royo J (2002) Structural theory and thermoeconomic diagnosis, Part 1: on malfunction and dysfunction analysis. Energy Convers Manage 43(9-12):1503–1518. https://doi.org/10.1016/S0196-8904(02)00032-8

[97] Valero A, Lerch F, Serra L, Royo J (2002) Structural theory and thermoeconomic diagnosis, Part II: Application to an actual power plant. Energy Convers Manage 43:1519–1535. http://dx.doi.org/10.1016/S0196-8904(02)00033-X

[98] Valero A, Correas L, Zaleta A, Lazzaretto A, et al (2004) On the thermoeconomic approach to the diagnosis of energy system malfunctions, Part 1: the TADEUS problem. J Energy 29(12-15):1875–1887. https://doi.org/10.1016/j.energy.2004.04.053

[99] Zhang C, Chen S, Zheng C, Lou X (2007) Thermoeconomic diagnosis of a coal fired power plant. Energy Convers Manage 48(2):405–419. http://dx.doi.org/10.1016/j.enconman.2006.07.001

[100] Usón S, Valero A, Correas L (2010) Energy efficiency assessment and improvement in energy intensive systems through thermoeconomic diagnosis of the operation. Appl Energy 87(6):1989–1995. http://dx.doi.org/10.1016/j.apenergy.2009.12.004

[101] Ommen T, Elmegaard B (2012) Numerical model for thermoeconomic diagnosis in commercial transcritical /subcritical booster refrigeration systems. Energy Convers Manage 60:161–169. http://dx.doi.org/10.1016/j.enconman.2011.12.028

[102] Boyano A, Blanco-Marigorta A, Morosuk T, Tsatsaronis G (2011) Exergoenvironmental analysis of a steam methane reforming process for hydrogen production. Energy, Int J 36:2202–2214. https://doi.org/10.1016/j.energy.2010.05.020

[103] Faleh N, Khila Z, Wahada Z, et al (2018) Exergo-environmental life cycle assessment of biodiesel production from mutton tallow transesterification. Renew Energy J 127:74–83. http://dx.doi.org/10.1016/j.renene.2018.04.046

[104] Sena M, Hicks A(2018) Life cycle assessment review of struvite precipitation in wastewater treatment. Resour Conserv Recy 139:194–204. https://doi.org/10.1016/j.resconrec.2018.08.009

[105] Petrescu L, Müller CR, Cormos CC (2014) Life Cycle Assessment of Natural Gas-based Chemical Looping for Hydrogen Production. Energy Procedia 63:7408–7420.

121

https://doi.org/10.1016/S0196-8904(02)00032-8

http://dx.doi.org/10.1016/S0196-8904(02)00033-X



http://dx.doi.org/10.1016/j.apenergy.2009.12.004



http://dx.doi.org/10.1016/j.renene.2018.04.046

https://doi.org/10.1016/j.resconrec.2018.08.009

References

https://doi.org/10.1016/j.egypro.2014.11.777

[106] Ingrao C, Messineo A, Beltramo R, et al (2018) How can life cycle thinking support sustainability of buildings? Investigating life cycle assessment applications for energy efficiency and environmental performance. J Clean Prod 201:556–569. http://dx.doi.org/10.1016/j.jclepro.2018.08.080

[107] Negishi K, Tiruta-Barna L, Schiopu N, et al (2018) An operational methodology for applying dynamic Life Cycle Assessment to buildings. Building and Environment 144:611–621. http://dx.doi.org/10.1016/j.buildenv.2018.09.005

[108] Farjana SH, Huda FN, Mahmud MAP, Lang C (2018) Comparative life-cycle assessment of uranium extraction processes. J Clean Prod 202:666–683. http://dx.doi.org/10.1016/j.jclepro.2018.08.105

[109] Rahimi V, Karimi K, Shafiei M, et al (2018) Well-to-wheel life cycle assessment of Eruca Sativa-based biorefinery. Renew Energy J 117:135–149. http://dx.doi.org/10.1016/j.renene.2017.10.035

[110] Clark C, Han J, Burnham A, Dunn JB, Wang M (2012) Life-cycle analysis of shale gas and natural gas. http://dx.doi.org/10.2172/1044520

[111] O'Born R (2012) From Ground to Gate: A life cycle assessment of petroleum processing activities in the United Kingdom. Dissertation, Norwegian University of Science and Technology. https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/234869

[112] Morales M, García SG , Aroca G, Moreira MT (2015) Life cycle assessment of gasoline production and use in Chile. Int J Life Cycle Ass 505:833-843. https://doi.org/10.1016/j.scitotenv.2014.10.067

[113] Morsali S (2017) Damage Assessment of Bitumen Refineries Using Simapro (LCA) Inventory Data. J Pet Environ Biotechnol 8(1). https://dx.doi.org/10.4172/2157-7463.1000317

[114] Bahmannia G (2008) Life Cycle Assessment (LCA) In Oil And Gas Industries As an Effective Sustainability Development Measure: Case Study. Sarkhoon Gas Treating Plant. In: 19th World Petroleum Congress, Madrid, 2008

[115] Akbari A, Mousavi E, Mhdizade F, Sarcheshmehpoor M, et al (2008) Life Cycle Energy Analysis of a Natural Gas Refinery. In: International Conference on Energy Security and Climate Change: Issues, Strategies, and Options, Bangkok, 2008

[116] Sapkota K, Oni AO, Kumar A (2018) Techno-economic and life cycle assessments of the natural gas supply chain from production sites in Canada to north and southwest Europe. J Nat Gas Sci Eng 52:401–409. https://doi.org/10.1016/j.jngse.2018.01.048

[117] Meyer L, Tsatsaronis G, Buchgeister J, Schebek L (2009) Exergoenvironmental analysis for evaluation of the environmental impact of energy conversion systems.

122

https://doi.org/10.1016/j.egypro.2014.11.777

http://dx.doi.org/10.1016/j.jclepro.2018.08.080


http://dx.doi.org/10.1016/j.renene.2017.10.035

http://dx.doi.org/10.2172/1044520

https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/234869

https://doi.org/10.1016/j.scitotenv.2014.10.067

https://dx.doi.org/10.4172/2157-7463.1000317


References

Energy Int J 34:75–89. https://doi.org/10.1016/j.energy.2008.07.018

[118] Peiró LT, Lombardi L, Méndez GV, Durany XGI (2010) Life cycle assessment (LCA) and exergetic life cycle assessment (ELCA) of the production of biodiesel from used cooking oil (UCO). J Energy 35(2):889–893. https://doi.org/10.1016/j.energy.2009.07.013

[119] Ozbilen A, Dincer I, Rosen MA (2012) Exergetic life cycle assessment of a hydrogen production process. Int J Hydrog Energy 37(7):5665–5675. http://dx.doi.org/10.1016/j.ijhydene.2012.01.003

[120] Banerjee A, Tierney M (2011) Comparison of five exergoenvironmental methods applied to candidate energy systems for rural villages in developing countries. J Energy 36(5):2650–2661. http://dx.doi.org/10.1016/j.energy.2011.02.006

[121] Koroneos C, Tsarouhis M (2012) Exergy analysis and life cycle assessment of solar heating and cooling systems in the building environment. J Clean Prod 32(4):52–60. http://dx.doi.org/10.1016/j.jclepro.2012.03.012

[122] Restrepo Á, Miyake R, Kleveston F, Bazzo E (2012) Exergetic and environmental analysis of a pulverized coal power plant. J Energy 45(1):195–202. http://dx.doi.org/10.1016/j.energy.2012.01.080

[123] Petrakopoulou F, Tsatsaronis G, Morosuk T, Paitazoglou C (2012) Environmental evaluation of a power plant using conventional and advanced exergy-based methods. J Energy 45(1):23–30. http://dx.doi.org/10.1016/j.energy.2012.01.042

[124] Sahraei MH, Farhadi F, Boozarjomehry RB (2013) Analysis and interaction of exergy, environmental and economic in multi-objective optimization of BTX process based on evolutionary algorithm. J Energy 59:147–156. http://dx.doi.org/10.1016/j.energy.2013.06.029

[125] Manesh MHK, Navid P, Marigorta AMB, et al (2013) New procedure for optimal design and evaluation of cogeneration system based on advanced exergoeconomic and exergoenvironmental analyses. J Energy 59:314–333. http://dx.doi.org/10.1016/j.energy.2013.06.017

[126] Jensen JK, Markussen WB, Reinholdt L, Elmegaard B(2015) Conventional and advanced exergoenvironmental analysis of an ammonia-water hybrid absorption-compression heat pump. In: 28th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS), Pau,2015

[127] Morosuk T, Tsatsaronis G, Koroneos C (2016) Environmental impact reduction using exergy-based methods. J Clean Prod 118:118–123. https://doi.org/10.1016/j.jclepro.2016.01.064

123



http://dx.doi.org/10.1016/j.ijhydene.2012.01.003







https://doi.org/10.1016/j.jclepro.2016.01.064

References

[128] Rahmatian M, Boyaghchi FA (2016) Exergo-environmental and exergo-economic analyses and multi-criteria optimization of a novel solar-driven CCHP based on Kalina cycle. Energy Equip Sys 4(2): 225-244. https://dx.doi.org/10.22059/ees.2016.23040

[129] Mergenthaler P, Schinkel AP, Tsatsaronis G (2017) Application of exergoeconomic, exergoenvironmental, and advanced exergy analyses to Carbon Black production. J Energy 137:898–907. http://dx.doi.org/10.1016/j.energy.2017.03.107

[130] Jelihi P, Wasserman T, Zondervan E(2018) Process Integration as an Effective Route Towards Sustainable Oil Refinery Development. In: 28th European Symposium on Computer Aided Process Engineering, Graz, 2018

[131] Lazzaretto A, Tsatsaronis G (2006) SPECO: A systematic and general methodology for calculating efficiencies and costs in thermal systems. J Energy 31:1257–1289. http://dx.doi.org/10.1016/j.energy.2005.03.011

[132] Lozano MA, Valero A, Serra L (1996) Local optimization of energy system. In: Proceedings of the ASME Advanced Energy System Division, AES, Vol 36. Atlanta, 1996

[133] Torres C, Valero A (2004) Thermoeconomics, PhD Course. University of Zaragoza

[134] Goedkoop M, Spriensma R (2000) The Eco-indicator 99: a damage oriented method for life cycle impact assessment, Methodology report. Amersfoort http://teclim.ufba.br/jsf/indicadores/holan %20ecoindicator %2099.pdf

[135] Tsatsaronis G, Bejan A, Mamut E (eds) (1999) Design optimization using exergoeconomics. In: Thermodynamic Optimization of Complex Energy Systems. Kluwer Academic Publishers, Dordrecht, p 101-117.

[136] Tsatsaronis G, Park MH (2002) On avoidable and unavoidable exergy destructions and investment costs in thermal systems. Energy Convers Manage 43:1259–1270. http://dx.doi.org/10.1016/S0196-8904(02)00012-2

[137] Cziesla F, Tsatsaronis G, Gao Z (2006) Avoidable thermodynamic inefficiencies and costs in an externally fired combined cycle power plant. J Energy 31:1472–1489. http://dx.doi.org/10.1016/j.energy.2005.08.001

[138] Tsatsaronis G (2008) Recent developments in exergy analysis and exergoeconomics. Int J Exergy 5(5):489-499. http://dx.doi.org/10.1504/IJEX.2008.020822

[139] Tsatsaronis G, Morosuk T (2008) A general exergy-based method for combining a cost analysis with an environmental impact analysis. In: Proceedings of the ASME International Mechanical Engineering Congress and Exposition, Boston, 2008

[140] Morosuk T, Tsatsaronis G (2009) Advanced Exergy Analysis for Chemically Reacting Systems – Application to a Simple Open Gas-Turbine System. Int J Thermodynamics 12(3):105-111. http://dx.doi.org/10.5541/ijot.245

124

https://dx.doi.org/10.22059/ees.2016.23040



http://teclim.ufba.br/jsf/indicadores/holan%20ecoindicator%2099.pdf

http://dx.doi.org/10.1016/S0196-8904(02)00012-2


http://dx.doi.org/10.1504/IJEX.2008.020822

http://dx.doi.org/10.5541/ijot.245

References

[141] AspenTech V8.4 (2016). http://www.aspentech.com. Accessed on 2017.

[142] Hamedni N, Sadatiyeh SRM (2008) Description of process units and facilities of gas refineries of south Pars. Jahad daneshgahi, Tehran.

[143] U.S. Energy Information Administration (2017). https://www.eia.gov/

[144] Thermaxx Jackets (2017). https://www.thermaxxjackets.com

[145] Tesch S, Morosuk T, Tsatsaronis G (2016) Advanced exergy analysis applied to the process of regasification of LNG (liquefied natural gas) integrated into an air separation process. J Energy 117:550–561. https://doi.org/10.1016/j.energy.2016.04.031

[146] Turton R, Baillie RC, Whiting WB, Shaeiwitz JA(2009) Analysis, synthesis and design of chemical processes. 3rd edn. Prentice Hall, Boston

[147] Ulrich GD, Vasudevan PT (2004) Chemical engineering –process design and economics, a practical guide. 2nd edn. Process Pub, Durham NH

[148] Ludwig E (2004) Applied process design for chemical and petrochemical plants, vol 3. 3rd edn. Gulf professional publishing, Houston

[149] Branan C (2002) Rules of thumb for chemical engineers, 3rd edn. Gulf professional publishing, Houston

[150] Baasel W (1990) Preliminary chemical engineering plant design. 2nd edn. Van Nostrand Reinhold, New York

[151] ISIS Steam (2017). http://www.isissteam.com/. Accessed on 2017.

[152] Engineers edge (2017). www.engineersedge.com. Accessed on 2017.

[153] Process associates (2017). www.processassociates.com. Accessed on 2017.

[154] Couper JR, Penney WR, Fair JR, Walas SM (2012) Chemical Process Equipment; Selection and Design. 3rd edn. Butterworth-Heinemann, Waltham

[155] Rhinesmith RB, Archer PJ, Watson SJ (2001) Carbonyl Sulfide (COS) removal from Propane. Pearl development company. Available via https://www.scribd.com/document/120122769/Carbonyl-Sulfide-COS-Removal-from-Propane-GPA

[156] Ochieng R, Berrouk AS, Peters CJ, Slagle J (2012) Amine processes outperform in sweetening LNG plant. Oil & Gas Journal 110(12): 108-115.

125

http://www.aspentech.com/

https://www.eia.gov/

https://www.thermaxxjackets.com/


http://www.isissteam.com/

http://www.engineersedge.com/

http://www.processassociates.com/

https://www.scribd.com/document/120122769/Carbonyl-Sulfide-COS-Removal-from-Propane-GPA

https://www.scribd.com/document/120122769/Carbonyl-Sulfide-COS-Removal-from-Propane-GPA

Appendices

APPENDIX A- Equipment list and process flow diagrams

A.1 Equipment list

Table A. 1 Equipment list and assigned tag numbers

Tag No. Equipment name

103-A1 Stabilized condensate air cooler

103-A2 1st Stage Off gas Compressor After cooler

103-A3 2nd Stage Off gas Compressor After cooler

104-A4 Regeneration gas air cooler

107-A5 Condensate cooler

111-A6 Refrigerant condenser

109-A7 Sour water stripper bottom cooler

106-A8 Export gas compressor after cooler

100-D1 HP separator

103-D2 Pre-flash drum

103-D3 Condensate desalter

103-D4 1st Stage compressor suction drum

103-D5 1st Stage compressor discharge drum

103-D6 2nd Stage compressor suction drum

103-D7 Condensate degassing drum

104-D8 Dryers inlet separator

104-D9 Regeneration gas separator

105-D10 Feed flash K.O. drum

111-D11 1st Stage suction drum

111-D12 2nd Stage suction drum

109-D13 Sour water stripper drum

106-D14 Export gas compressor suction drum

103-P1 Desalter feed pump

103-P2 Stabilized condensate export pump

105-P3 Deethanaiser transfer pump

107-P4 Propane feed pump

107-P5 Condensate circulation pump

107-P6 Butane feed pump

109-P7 Sour water stripper feed pump

126

Appendices

Tag No. Characteristics

109-P8 Sour water stripper bottom pump

100-E1 Gas heater

103-E2 Condensate pre-flash heater

103-E3 Condensate desalter pre heater

103-E4 Stabilizer side reboiler

104-E5 Gas/Gas exchanger

104-E6 Wet gas chiller

104-E7 Dry gas heater

105-E8 Cold box

105-E9 Ethane heater

107-E10 Butane cooler

103-K1 1st Stage off gas compressor

103-K2 2nd Stage off gas compressor

104-K3 Dryers regeneration compressors

105-K4 Treated gas compressor

111-K5 1st Stage refrigerant compressor

111-K6 2nd Stage refrigerant compressor

106-K7 Export gas compressor

105-X1 Gas turbine driver

104-R1 A/B/C Dryers 104-R2 Mercury guard reactor 104-H1 Dryers regeneration furnace 100-L1 Slug catcher 103-C1 Condensate stabilizer 105-C2 Demethaniser 105-C3 Deethaniser 107-C4 Depropaniser 107-C5 Debutaniser 109-C6 Sour water stripper Unit 101-B1 Gas sweetening unit

Unit 114-B2 Propane treatment unit

Unit 115-B3 Butane treatment unit

Unit 116-B4 Ethane treatment unit

127

Appendices

A.2 Process flow diagrams

Fig. A.1 Overall Process Flow Diagram of studied gas refinery

104-R2

104-E7

105-C3

105-E8

105 K4

10 5-X1

105-D10

105-C2

105-P3

105-E9COMPRESSI ON SEC TION IDENTI CAL T O ABOVE SEC TION

106-D14K7

106-A8

COMPRESSI ON SEC TION IDENTI CAL T O ABOVE SEC TION

106-D-201

106-D-301 106- K-301

106- K-201

106- A-301

106- A-201


106-D-401 106- K-401 106- A-401


106-D-501 106- K-501 106- A-501


106-D-601 106- K-601 106- A-601


106-D-701 106- K-701 106- A-701

07-C4

107-C5

107-A5

107-E10107-P6

03-D3103-C1

103-E4

103-D4 103-D6103-A2

1 03-A3

103 -D5

103 -K11st

S TAGE103- K2

2nd STAGE

1 00- L1

103 -D7

103- P2

103- D2

103-P1

103-A1

103-E3 1103-E2

100-D1 100-E1

111-A6

111-D11

111-D12

111-K5

NNF

111-K6

NN

F

107-P41

146

147A 148B 149 141

104-R1 A/B/C

104 - D8

104-D9

104-A4

104 - K3

104 - E6

104-E5

146A

142A333A

144

4

A4

2

142

3334 3557

43A

247

52

248

256

55

53

250

249

261

246

244

37

38

104 - H1 40

40

41

39A

39

43C43B

33336A3656

146

51143

145

54

59

63

63A

63B

141

63C

142

141A

701

57

701C

701A

72A

UNIT 116-B 4

UNIT 116-B 4

UNIT 116-B 4

ToUNIT 101-B 1

ToUN

IT 1

01-

B1

ACID

GAS

SRU(

108)

58

62

56

43

3BL2BL

1BL

4B

1

2A

27

2B

10

20

12A13A 13

14A 17

12

19 18

15B14

15

2411

16

24A25 25B 25C

26C

26B26F

2628A26A

27A

101D

29

13B

26E

27

101

101A

101C

102A

104

107

108108A

109

21

31

3OA

3OB

28

161A

161B

161

64A

8584 07-P51

91

86

90 93

31

64

81

85A 86A

89

92

171

171A

171B

171C

M

106-

M

Thre a te d g a sfrom

105-K-301


105-K-401

C3/C4From uni t 114/115

phase 19 A

C3/C4From uni t 114/115

phase 19 B


105-K-201

Lean gasto export

UNIT 115-B3

Caustic regeneration

UNIT

Treated Butane

Sour washingbutane cut

H ydroca rbonsfrom

Tra in 3 UN IT 105

Treated ButaneGas fromOffshore

Stabilized condensatefor export

HC liquid fromUNIT 104

Second Gas Train

Sour wa te rof MEG UN IT

FIRST STAGE SECOND STAGE

109-D13

109-P7

109-P8

109-C6

109-A7Water

Treatment

UNIT1 1 4 -B2

TreatedProp ane

Ca usticRe ge ne ra tion

UN IT

128

Appendices

Fig. A.2 Process flow diagram for receiving facilities and gas treatment black box (Unit 100 &101)

129

Appendices

Fig. A.3 Process flow diagram for condensate stabilization (Unit 103)

130

Appendices

Fig. A.4 Process flow diagram for dehydration and mercury guard (Unit 104)

131

Appendices

Fig. A.5 Process flow diagram for ethane extraction (Unit 105)

132

Appendices

Fig. A.6 Process flow diagram for NGL fractionation (Unit 107)

133

Appendices

Fig. A.7 Process flow diagram for sales gas compression (Unit 106)

134

Appendices

Fig. A.8 Process flow diagram for propane refrigeration cycle (Unit 111)

135

Appendices

Fig. A.9 Process flow diagram for sour water treatment (Unit 109)

136

Appendices

Fig. A.10 Process flow diagram for black box units; propane, butane and ethane treatment and drying (Units 114/115/116)

137

Appendices APPENDIX B-Detail Stream information Table B.1 Streams data

Str. No. 1 1BL 2 2A 2B 2BL 3 3BL 4

Composition/kg s-1

H2O 4.0 0.1 0.1 0.1 3.7 0.0 0.2 0.1 0.1

N2 13.1 6.6 13.0 0.1 0.0 0.0 13.1 6.6 13.1

CO2 10.8 5.4 10.2 0.6 0.0 3.1 10.8 2.3 10.8

H2 3.2 1.6 2.8 0.3 0.0 1.6 3.2 0.0 3.2

CH4 183.7 91.9 180.5 3.3 0.0 0.0 183.8 91.9 183.7

C2H6 22.0 11.0 20.6 1.4 0.0 0.0 22.0 11.0 22.0

C3H8 12.0 6.0 10.1 1.8 0.0 0.0 12.0 6.0 12.0

i−C4H10 3.4 1.5 2.5 0.9 0.0 0.0 3.0 1.5 3.0

n−C4H10 5.7 2.3 3.9 1.8 0.0 0.0 4.5 2.3 4.5

i−C5H12 2.9 0.8 1.5 1.4 0.0 0.0 1.7 0.8 1.7

n−C5H12 2.9 0.8 1.4 1.5 0.0 0.0 1.5 0.8 1.5

C6~C20 44.4 1.9 3.5 40.9 0.0 0.1 3.8 1.8 3.7 ṁ/kg s −1 308.1 129.7 250.2 54.2 3.7 4.7 259.5 125.0 259.4

T/°C 25 24 25 25 25 25 25 45 24

p/bar 75 67 75 75 75 67 70 67 69

xvap/- 0.9 1.0 1.0 0.0 0.0 0.0 1.0 1.0 1.0

h/kJ kg −1 −4019 −4218 −4246 −2317 −15870 −6382 −4220 −4093 −4221

s/MJ kg −1 K −1 −0.006 −0.006 −0.006 −0.007 −0.009 −0.001 −0.006 −0.006 −0.006

eCH/MJ kg −1 47.682 49.023 49.091 44.291 2.476 5.844 49.018 50.657 49.023

ePH/MJ kg −1 0.458 0.522 0.540 0.061 0.010 0.178 0.526 0.534 0.5243

��tot/MW 14831.2 6425.0 12416.0 2403.2 9.3 28.5 12854.8 6396.4 12850.647

Continuation on next page

138

Appendices

Str. No. 4A 4B 10 11 12 12A 12B 13 13A

Composition/kg s-1

H2O 0.0 0.1 3.8 0.0 3.8 3.8 3.8 0.0 3.8

N2 0.0 13.1 0.1 0.0 0.1 0.1 0.1 0.0 0.0

CO2 0.0 10.8 0.6 0.0 0.6 0.6 0.6 0.3 0.0

H2 0.0 3.2 0.3 0.0 0.3 0.3 0.3 0.2 0.0

CH4 0.0 183.7 3.3 0.0 3.3 3.3 3.3 0.8 0.0

C2H6 0.0 22.0 1.4 0.0 1.4 1.4 1.4 0.8 0.0

C3H8 0.0 12.0 1.8 0.0 1.8 1.8 1.8 1.4 0.0

i−C4H10 0.0 3.0 0.9 0.0 0.9 0.9 0.9 0.8 0.0

n−C4H10 0.0 4.5 1.8 0.0 1.8 1.8 1.8 1.7 0.0

i−C5H12 0.0 1.7 1.4 0.0 1.4 1.4 1.4 1.3 0.0

n−C5H12 0.0 1.5 1.5 0.0 1.5 1.5 1.5 1.5 0.0

C6~C20 0.1 3.7 40.9 0.1 41.0 41.0 41.1 41.0 0.0 ṁ/kg s −1 0.1 259.4 57.9 0.1 58.0 58.0 58.2 49.8 3.8

T/°C 24 25 21 23 47 21 47 47 47

p/bar 69 68.68 30 30 29 30 29 28 28

xvap/- 0.0 1.0 0.1 0.1 0.2 0.1 0.2 0.0 0.0

h/kJ kg −1 −4809 −4218 −3191 −4809 −3122 −3194 −3119 −2078 −15754

s/MJ kg −1 K −1 −0.007 −0.006 −0.007 −0.007 −0.007 −0.007 −0.007 −0.007 −0.009

eCH/MJ kg −1 38.196 49.023 41.593 38.196 41.588 41.588 41.609 44.022 2.572

ePH/MJ kg −1 0.063 0.5244 0.046 0.056 0.047 0.046 0.047 0.018 0.007

��tot/MW 3.7 12850.6 2411.8 3.7 2415.6 2415.6 2425.3 2192.1 9.9


139

Appendices

Str. No. 13B 14 14A 14B 15 15B 15C 16 17

Composition/kg s-1

H2O 3.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CO2 0.0 0.3 0.3 0.3 0.3 0.3 0.0 0.0 0.0

H2 0.0 0.2 0.2 0.2 0.2 0.2 0.0 0.0 0.0

CH4 0.0 0.8 0.8 0.8 0.8 0.8 0.0 0.0 0.0

C2H6 0.0 0.8 0.8 0.8 0.9 0.8 0.0 0.0 0.0

C3H8 0.0 1.4 1.4 1.4 1.7 1.4 0.0 0.0 0.0

i−C4H10 0.0 0.8 0.8 0.8 0.9 0.8 0.0 0.4 0.4

n−C4H10 0.0 1.7 1.7 1.7 1.8 1.7 0.0 1.2 1.2

i−C5H12 0.0 1.3 1.3 1.3 1.4 1.3 0.0 1.2 1.2

n−C5H12 0.0 1.5 1.5 1.5 1.6 1.5 0.0 1.4 1.4

C6~C20 0.0 41.0 41.0 41.0 41.3 41.0 0.0 40.8 40.8 ṁ/kg s −1 3.9 49.8 49.8 49.8 51.0 49.8 0.0 45.0 45.0

T/°C 41 72 49 72 68 73 0.0 198 155

p/bar 22 37 38 35 11 35 0.0 11 10

xvap/- 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0

h/kJ kg −1 −15530 −2030 −2076 −2030 −2030 −2021 0.0 −1576 −1706

s/MJ kg −1 K −1 −0.009 −0.006 −0.007 −0.006 −0.006 −0.006 0.0 −0.006 −0.006

eCH/MJ kg −1 3.304 44.022 44.022 44.022 44.131 44.022 0.0 43.803 43.803

ePH/MJ kg −1 0.002 0.025 0.019 0.025 0.020 0.025 0.0 0.093 0.060

��tot/MW 12.9 2192.5 2192.2 2192.5 2252.0 2192.5 0.0 1976.4 1974.9


140

Appendices

Str. No. 18 19 20 21 21B 24 24A 24B 25

Composition/kg s-1

H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CO2 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.3 0.3

H2 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.2 0.2

CH4 0.0 0.0 0.0 0.0 0.0 0.8 0.0 0.8 0.8

C2H6 0.0 0.0 0.0 0.0 0.0 0.9 0.0 0.9 0.9

C3H8 0.0 0.0 0.0 0.0 0.0 1.7 0.0 1.7 1.7

i−C4H10 0.4 0.4 0.4 0.4 0.4 0.5 0.0 0.5 0.5

n−C4H10 1.2 1.2 1.2 1.2 1.2 0.7 0.0 0.7 0.7

i−C5H12 1.2 1.2 1.2 2.8 2.8 0.2 0.0 0.2 0.2

n−C5H12 1.4 1.4 1.4 2.9 2.9 0.2 0.0 0.2 0.2

C6~C20 40.8 40.8 40.8 44.2 44.2 0.5 0.0 0.5 0.5 ṁ/kg s −1 45.0 45.0 45.0 51.5 51.5 5.9 0.063 5.9 5.9

T/°C 132 73 29 35 35 63 63 62 62

p/bar 10 9 8 1 8 10 10 9 9

xvap/- 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0 1.0

h/kJ kg −1 -1757 -1904 -1998 -2006 -2005 -2849 -2104 -2849 -2849

s/MJ kg −1 K −1 -0.006 -0.006 -0.007 -0.007 -0.007 -0.005 -0.007 -0.005 -0.005

eCH/MJ kg −1 43.803 43.803 43.803 44.455 44.455 46.591 47.300 46.591 46.591

ePH/MJ kg −1 0.037 0.012 0.001 0.000 0.001 0.151 0.011 0.144 0.144

��tot/MW 1973.9 1972.7 1972.3 2290.4 2290.5 276.7 3.0 276.6 276.6


141

Appendices

Str. No. 25A 25B 25C 26 26A 26B 26C 26E 26F

Composition/kg s-1

H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0

CO2 0.0 0.3 0.3 0.6 0.3 0.0 0.0 0.0 0.0

H2 0.0 0.2 0.2 0.3 0.2 0.0 0.0 0.0 0.0

CH4 0.0 0.8 0.8 3.3 0.8 0.0 0.0 0.0 0.0

C2H6 0.0 0.9 0.9 1.4 0.8 0.1 0.0 0.0 0.0

C3H8 0.0 1.7 1.7 1.8 1.4 0.3 0.0 0.0 0.0

i−C4H10 0.0 0.5 0.5 0.5 0.4 0.1 0.0 0.0 0.0

n−C4H10 0.0 0.7 0.7 0.6 0.5 0.2 0.0 0.0 0.0

i−C5H12 0.0 0.2 0.2 0.2 0.1 0.1 0.0 0.0 0.0

n−C5H12 0.0 0.2 0.2 0.2 0.1 0.1 0.0 0.0 0.0

C6~C20 0.0 0.5 0.5 0.3 0.1 0.3 0.0 0.0 0.0 ṁ/kg s −1 0.0 5.9 5.9 9.3 4.7 1.2 0.0 0.0 0.0

T/°C 0.0 136 60 52 60 60 0.0 0.0 0.0

p/bar 0.0 28 27 27 27 27 0.0 0.0 0.0

xvap/- 0.0 1.0 0.9 1.0 1.0 0.0 0.0 0.0 0.0

h/kJ kg −1 0.0 -2723 -2945 -3540 -3069 -2480 0.0 0.0 0.0

s/MJ kg −1 K −1 0.0 -0.005 -0.006 -0.005 -0.005 -0.007 0.0 0.0 0.0

eCH/MJ kg −1 0.0 46.591 46.591 47.055 46.174 48.164 0.0 0.0 0.0

ePH/MJ kg −1 0.0 0.242 0.200 0.295 0.229 0.057 0.001 0.0 0.0

��tot/MW 0.0 277.2 277.0 440.2 217.1 59.9 9.5 0.0 0.0


142

Appendices

Str. No. 27 27A 28 28A 29 30A 30B 31 32

Composition/kg s-1 H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 N2 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 7.0

CO2 0.6 0.6 0.3 0.6 0.0 0.0 0.0 0.0 2.5

H2 0.3 0.3 0.1 0.3 0.0 0.0 0.0 0.0 0.0

CH4 3.3 3.3 2.5 3.3 0.0 0.0 0.0 0.0 98.8

C2H6 1.4 1.4 0.6 1.4 0.1 0.0 0.0 0.0 11.8

C3H8 1.8 1.8 0.4 1.8 0.3 0.0 0.0 0.0 6.4

i−C4H10 0.5 0.5 0.1 0.5 0.1 0.0 0.0 0.0 1.6

n−C4H10 0.6 0.6 0.2 0.6 0.2 0.0 0.0 0.0 2.4

i−C5H12 0.2 0.2 0.1 0.2 0.1 0.0 0.0 1.6 0.9

n−C5H12 0.2 0.2 0.1 0.2 0.1 0.0 0.0 1.5 0.8

C6~C20 0.3 0.3 0.1 0.3 0.3 0.1 0.1 3.4 1.9 ṁ/kg s −1 9.3 9.3 4.6 9.3 1.2 0.1 0.1 6.5 134.2

T/°C 81 133 47 52 39 19 19 60 22

p/bar 70 71 28 27 11 30 30 13 64

xvap/- 1.0 1.0 1.0 1.0 0.2 0.1 0.2 0.0 1.0

h/kJ kg −1 −3531 −3401 −4018 −3541 −2480 −2360 −2347 −2219 −4150

s/MJ kg −1 K −1 −0.006 −0.005 −0.006 −0.005 −0.007 −0.007 −0.007 −0.007 −0.007

eCH/MJ kg −1 47.055 47.055 47.947 47.055 48.164 47.855 47.854 48.974 50.663

ePH/MJ kg −1 0.374 0.403 0.366 0.295 0.054 0.045 0.049 0.008 0.528

��tot/MW 441.0 441.2 223.2 440.2 59.9 4.8 4.8 318.3 6871.7


143

Appendices

Str. No. 33 34 35 36 36A 36B 37 38 38A

Composition/kg s-1

H2O 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 0.0 6.6 6.6 6.6 6.6 0.5 0.5 0.5

CO2 0.0 0.0 2.3 2.3 2.3 2.3 0.2 0.2 0.2

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 0.0 0.0 91.9 91.9 91.9 91.9 6.9 6.9 6.9

C2H6 0.0 0.0 11.0 11.0 11.0 11.0 0.8 0.8 0.8

C3H8 0.0 0.0 6.0 6.0 6.0 6.0 0.4 0.4 0.4

i−C4H10 0.0 0.0 1.5 1.5 1.5 1.5 0.1 0.1 0.1

n−C4H10 0.0 0.0 2.3 2.3 2.3 2.3 0.2 0.2 0.2

i−C5H12 0.0 0.0 0.8 0.8 0.8 0.8 0.1 0.1 0.1

n−C5H12 0.0 0.0 0.8 0.8 0.8 0.8 0.1 0.1 0.1

C6~C20 0.1 0.0 1.7 1.7 1.7 1.7 0.1 0.1 0.1 ṁ/kg s −1 0.1 0.3 124.8 124.8 124.8 124.8 9.4 9.4 9.4

T/°C 22 22 23 23 28 28 23 280 280

p/bar 64 64 64 63 63 62 64 61 60

xvap/- 0.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

h/kJ kg −1 −2360 −15867 −4142 −4142 −4129 −4127 −4143 −3456 −3456

s/MJ kg −1 K −1 −0.007 −0.009 −0.007 −0.007 −0.007 −0.007 −0.007 −0.005 −0.005

eCH/MJ kg −1 47.855 2.467 50.688 50.688 50.688 50.688 50.688 50.688 50.688

ePH/MJ kg −1 0.052 0.008 0.527 0.526 0.527 0.524 0.528 0.714 0.712

��tot/MW 4.8 0.7 6390.4 6390.3 6390.4 6390.1 481.0 482.8 482.7


144

Appendices

Str. No. 39 39A 40 41 42 43 43A 43B

Composition/kg s-1

H2O 0.3 0.3 0.3 0.0 0.0 0.1 0.4 0.4

N2 0.5 0.5 0.0 0.5 0.5 6.6 7.0 7.0

CO2 0.2 0.2 0.0 0.2 0.2 2.3 2.5 2.5

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 6.9 6.9 0.0 6.9 6.9 91.9 98.8 98.8

C2H6 0.8 0.8 0.0 0.8 0.8 11.0 11.8 11.8

C3H8 0.4 0.4 0.0 0.4 0.4 6.0 6.4 6.4

i−C4H10 0.1 0.1 0.0 0.1 0.1 1.5 1.6 1.6

n−C4H10 0.2 0.2 0.0 0.2 0.2 2.3 2.4 2.4

i−C5H12 0.1 0.1 0.0 0.1 0.1 0.8 0.9 0.9

n−C5H12 0.1 0.1 0.0 0.1 0.1 0.8 0.8 0.8

C6~C20 0.1 0.1 0.0 0.1 0.1 1.8 1.9 1.9 ṁ/kg s −1 9.7 9.7 0.3 9.4 9.4 125.0 134.6 134.6

T/°C 60 279 60 60 71 44 45 35

p/bar 59 60 59 59 67 65 65 65

xvap/- 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0

h/kJ kg −1 −4379 −3743 −15716 −4083 −4061 −4093 −4112 −4137

s/MJ kg −1 K −1 −0.006 −0.005 −0.009 −0.006 −0.006 −0.006 −0.006 −0.007

eCH/MJ kg −1 49.255 49.255 2.467 50.500 50.500 50.657 50.556 50.556

ePH/MJ kg −1 0.515 0.710 0.016 0.525 0.542 0.530 0.530 0.530

��tot/MW 481.7 483.6 0.6 481.1 481.3 6396.0 6877.9 6877.8


145

Appendices

Str. No. 43C 51 52 53 54 55 56 57 58

Composition/kg s-1

H2O 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 7.0 6.6 6.6 0.1 4.6 0.1 6.6 6.6 0.0

CO2 2.5 2.3 2.3 0.1 1.5 0.1 1.7 1.7 0.6

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 98.8 91.9 91.9 2.0 63.5 2.0 91.8 91.8 0.0

C2H6 11.8 11.0 11.0 1.2 6.9 1.2 3.8 3.8 7.2

C3H8 6.4 6.0 6.0 1.7 3.0 1.7 0.2 0.2 5.8

i−C4H10 1.6 1.5 1.5 0.7 0.6 0.7 0.0 0.0 1.5

n−C4H10 2.4 2.3 2.3 1.3 0.7 1.3 0.0 0.0 2.2

i−C5H12 0.9 0.8 0.8 0.6 0.1 0.6 0.0 0.0 0.8

n−C5H12 0.8 0.8 0.8 0.6 0.1 0.6 0.0 0.0 0.8

C6~C20 1.9 1.7 1.7 1.6 0.1 1.6 0.0 0.0 1.7 ṁ/kg s −1 134.6 124.8 124.8 9.9 81.1 9.9 104.1 104.1 20.7

T/°C 22 28 −35 −35 −67 −48 16 30 39

p/bar 64 62 61 61 30 30 29 28 30

xvap/- 1.0 1.0 1.0 0.0 1.0 0.3 1.0 1.0 0.0

h/kJ kg −1 −4171 −4127 −4318 −3291 −4448 −3291 −4401 −4369 −2936

s/MJ kg −1 K −1 −0.007 −0.007 −0.007 −0.008 −0.007 −0.008 −0.006 −0.006 −0.007

eCH/MJ kg −1 50.556 50.688 50.688 50.047 50.744 50.047 51.023 51.023 49.006

ePH/MJ kg −1 0.529 0.523 0.545 0.244 0.511 0.231 0.483 0.480 0.146

��tot/MW 6877.7 6389.9 6392.7 500.4 4158.0 500.2 5360.5 5360.2 1017.4


146

Appendices

Str. No. 59 62 62A 62B 62C 62D 63 63A 63B

Composition/kg s-1

H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 6.6 6.6 13.1 13.1 26.2 0.0 0.0 0.0

CO2 0.6 1.7 1.7 3.4 3.4 6.8 0.6 0.6 0.6

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 0.0 91.8 91.8 183.7 183.7 367.3 0.0 0.0 0.0

C2H6 7.2 3.8 3.8 7.6 7.6 15.2 7.2 7.2 0.0

C3H8 5.8 0.2 0.2 0.3 0.3 0.6 0.0 0.0 0.0

i−C4H10 1.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n−C4H10 2.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

i−C5H12 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n−C5H12 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C6~C20 1.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ṁ/kg s −1 20.7 104.1 104.1 208.2 208.2 416.3 7.9 7.9 0.6

T/°C 39 45 45 45 46 45 7 43 72

p/bar 31 33 33 33 33 33 30 30 30

xvap/- 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

h/kJ kg −1 −2936 −4338 −4338 −4337 −4336 −4337 −3393 −3307 −8923

s/MJ kg −1 K −1 −0.007 −0.006 −0.006 −0.006 −0.006 −0.006 −0.006 −0.006 0.000

eCH/MJ kg −1 49.006 51.023 51.023 51.024 51.025 51.025 47.861 47.861 0.000

ePH/MJ kg −1 0.146 0.503 0.502 0.502 0.503 0.502 0.256 0.255 0.185

��tot/MW 1017.4 5362.6 5362.5 10725.4 10726.2 21451.4 378.8 378.8 0.1


147

Appendices

Str. No. 63C 64 64A 72 72A 81 84 85 85A

Composition/kg s-1

H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 0.0 0.0 5.2 5.2 0.0 0.0 0.0 0.0

CO2 0.0 0.0 0.0 1.4 1.4 0.0 0.0 0.0 0.0

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 0.0 0.0 0.0 73.5 73.5 0.0 0.0 0.0 0.0

C2H6 7.2 0.0 0.0 3.0 3.0 0.0 0.0 0.0 0.0

C3H8 0.0 5.8 5.8 0.1 0.1 11.6 0.0 0.1 11.5

i−C4H10 0.0 1.5 1.5 0.0 0.0 3.0 0.2 2.9 0.1

n−C4H10 0.0 2.2 2.3 0.0 0.0 4.5 0.4 4.5 0.0

i−C5H12 0.0 0.8 0.8 0.0 0.0 1.7 0.0 1.7 0.0

n−C5H12 0.0 0.8 0.8 0.0 0.0 1.5 0.0 1.5 0.0

C6~C20 0.0 1.7 1.7 0.0 0.0 3.4 0.0 3.4 0.0 ṁ/kg s −1 7.3 12.8 12.8 83.3 83.3 25.7 0.6 14.1 11.6

T/°C 72 108 108 58 57 93 40 138 61

p/bar 30 31 31 93 91 23 9 23 22

xvap/- 1.0 0.0 0.0 1.0 1.0 0.2 0.0 0.0 0.0

h/kJ kg −1 −2756 −2342 −2352 −4353 −4353 −2347 −2548 −2142 −2631

s/MJ kg −1 K −1 −0.007 −0.007 −0.007 −0.007 −0.007 −0.007 −0.008 −0.006 −0.007

eCH/MJ kg −1 51.963 49.709 49.708 51.025 51.025 49.708 49.425 49.172 50.359

ePH/MJ kg −1 0.589 0.093 0.078 0.646 0.643 0.089 0.044 0.064 0.127

��tot/MW 381.0 638.8 638.9 4302.3 4302.0 1277.8 30.3 692.5 585.4


148

Appendices

Str. No. 86 86A 89 90 90A 91 92 93 100

Composition/kg s-1

H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4.0

N2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CO2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C2H6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C3H8 0.1 0.1 0.1 0.0 0.0 11.5 0.1 0.0 0.0

i−C4H10 3.1 3.1 3.1 0.0 0.0 0.1 3.1 0.0 0.0

n−C4H10 4.9 4.8 4.8 0.0 0.0 0.0 4.8 0.0 0.0

i−C5H12 1.7 0.1 0.1 1.6 1.6 0.0 0.1 1.6 0.0

n−C5H12 1.5 0.0 0.0 1.5 1.5 0.0 0.0 1.5 0.0

C6~C20 3.4 0.0 0.0 3.4 3.4 0.0 0.0 3.4 0.0 ṁ/kg s −1 14.7 8.2 8.2 6.5 6.5 11.6 8.2 6.5 4.0

T/°C 93 61 62 133 133 65 40 60 83

p/bar 9 8 20 9 14 38 20 13 27

xvap/- 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

h/kJ kg −1 −2159 −2486 −2482 −2033 −2032 −2625 −2540 −2219 −15619

s/MJ kg −1 K −1 −0.006 −0.007 −0.007 −0.006 −0.006 −0.007 −0.007 −0.007 −0.008

eCH/MJ kg −1 49.183 49.348 49.348 48.974 48.974 50.359 49.348 48.974 2.476

ePH/MJ kg −1 0.052 0.048 0.050 0.041 0.043 0.131 0.046 0.006 0.023

��tot/MW 722.6 404.0 404.0 318.5 318.5 585.5 404.0 318.3 10.0


149

Appendices

Str. No. 101 101A 101B 101C 101D 102A 103 104 107

Composition/kg s-1

H2O 7.8 8.4 0.0 8.4 0.5 8.4 0.0 8.4 0.008

N2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CO2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C2H6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C3H8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

i−C4H10 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n−C4H10 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

i−C5H12 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n−C5H12 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C6~C20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ṁ/kg s −1 7.9 8.4 0.0 8.4 0.5 8.4 0.0 8.4 0.008

T/°C 64 60 0.0 61 39 61 0.0 61 61.2

p/bar 22 22 0.0 22 59 29 0.0 2 2.1

xvap/- 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

h/kJ kg −1 −15575 −15589 0.0 −15584 −15797 −15583 0.0 −15583 −15583

s/MJ kg −1 K −1 −0.009 −0.009 0.0 −0.009 −0.009 −0.009 0.0 −0.009 −0.009

eCH/MJ kg −1 2.884 2.857 0.0 2.857 2.467 2.857 0.0 2.857 2.857

ePH/MJ kg −1 0.012 0.009 0.0 0.009 0.005 0.009 0.0 0.009 0.009

��tot/MW 22.9 24.2 0.0 24.2 1.3 24.2 0.0 24.2 24.2


150

Appendices

Str. No. 108 108A 109 141 141A 142 142A 143 144

Composition/kg s-1

H2O 8.4 8.4 8.4 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CO2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C2H6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C3H8 0.0 0.0 0.0 56.5 56.5 49.2 49.2 7.3 15.3

i−C4H10 0.0 0.0 0.0 0.5 0.5 0.4 0.4 0.1 0.2

n−C4H10 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.0 0.0

i−C5H12 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n−C5H12 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C6~C20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ṁ/kg s −1 8.4 8.4 8.4 57.1 57.1 49.8 49.8 7.4 15.5

T/°C 90.0 115.2 115.2 60 57 20 20 19 3

p/bar 0.7 1.7 4.2 22 21 8 8 8 5

xvap/- 1.0 0.0 0.0 0.0 0.0 0.3 0.6 0.3 0.1

h/kJ kg −1 −13211 −15373 −15372 −2634 −2645 −2645 −2553 −2645 −2754

s/MJ kg −1 K −1 −0.002 −0.008 −0.008 −0.007 −0.007 −0.007 −0.007 −0.007 −0.008

eCH/MJ kg −1 2.861 2.857 2.857 50.362 50.362 50.362 50.362 50.362 50.356

ePH/MJ kg −1 0.431 0.048 0.048 0.126 0.125 0.115 0.113 0.117 0.115

��tot/MW 0.03 24.5 24.5 2883.8 2883.7 2511.3 2511.2 371.9 783.2


151

Appendices

Str. No. 145 146 146A 146B 147 147A 148 148A 148B

Composition/kg s-1

H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CO2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C2H6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C3H8 5.2 5.2 20.5 0.0 20.5 20.5 36.0 0.0 56.5

i−C4H10 0.1 0.1 0.3 0.0 0.3 0.3 0.2 0.0 0.5

n−C4H10 0.0 0.0 0.1 0.0 0.1 0.1 0.0 0.0 0.1

i−C5H12 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

n−C5H12 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

C6~C20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ṁ/kg s −1 5.3 5.3 20.8 0.0 20.8 20.8 36.3 0.0 57.1

T/°C −4 −3 −5 0.0 −5 27 19 0.0 22

p/bar 4 4 4 0.0 4 8 8 0.0 8

xvap/- 0.2 1.0 1.0 0.0 1.0 1.0 1.0 0.0 1.0

h/kJ kg −1 −2754 −2430 −2434 0.0 −2434 −2392 −2407 0.0 −2401

s/MJ kg −1 K −1 −0.008 −0.007 −0.007 0.0 −0.007 −0.007 −0.007 0.0 −0.007

eCH/MJ kg −1 50.356 50.356 50.356 0.0 50.356 50.356 50.365 0.0 50.362

ePH/MJ kg −1 0.113 0.077 0.077 0.0 0.077 0.109 0.109 0.0 0.109

��tot/MW 268.3 268.1 1050.7 0.0 1050.7 1051.4 1831.4 0.0 2882.8


152

Appendices

Str. No. 149 161 161A 161B 171 171A 171B 171C 244

Composition/kg s-1

H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6.5

CO2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.2

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 89.8

C2H6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 9.8

C3H8 56.5 11.5 11.5 0.0 0.1 0.0 0.1 0.0 4.3

i−C4H10 0.5 0.1 0.1 0.0 3.1 0.2 2.9 0.0 0.8

n−C4H10 0.1 0.0 0.0 0.0 4.8 0.4 4.5 0.0 1.0

i−C5H12 0.0 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.2

n−C5H12 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1

C6~C20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 ṁ/kg s −1 57.1 11.6 11.6 0.0 8.2 0.6 7.5 0.0 114.8

T/°C 77 65 65 65 40 40 40 40 −35

p/bar 22 38 38 38 18 16 16 16 61

xvap/- 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0

h/kJ kg −1 −2336 −2625 −2630 −915 −2540 −2551 −2548 −952 −4406

s/MJ kg −1 K −1 −0.007 −0.007 −0.007 −0.002 −0.007 −0.008 −0.008 −0.003 −0.007

eCH/MJ kg −1 50.362 50.359 50.359 25.752 49.348 49.474 49.485 26.052 50.744

ePH/MJ kg −1 0.160 0.131 0.124 0.047 0.045 0.049 0.050 0.039 0.564

��tot/MW 2885.7 585.5 585.4 0.0 404.0 30.2 372.6 1.2 5891.5


153

Appendices

Str. No. 246 246A 247 248 249 250 256 261A 333 333A 701 701A 701C

Composition/ kg s-1

H2O 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

N2 1.9 4.6 1.9 6.6 0.0 0.0 0.0 0.0 0.0 0.0 5.2 5.2 5.2

CO2 0.6 1.5 0.6 1.7 2.2 1.9 2.2 1.9 0.0 0.0 1.4 1.4 1.4

H2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CH4 26.4 63.5 26.4 91.8 0.5 3.5 0.5 3.5 0.0 0.0 73.5 73.5 73.5

C2H6 2.9 6.9 2.9 3.8 12.3 10.9 12.3 10.9 0.0 0.0 3.0 3.0 3.0

C3H8 1.3 3.0 1.3 0.2 6.9 6.5 6.9 6.5 7.3 28.7 0.1 0.1 0.1

i−C4H10 0.2 0.6 0.2 0.0 1.6 1.5 1.6 1.5 0.1 0.2 0.0 0.0 0.0

n−C4H10 0.3 0.7 0.3 0.0 2.4 2.3 2.4 2.3 0.0 0.0 0.0 0.0 0.0

i−C5H12 0.1 0.1 0.1 0.0 0.8 0.8 0.8 0.8 0.0 0.0 0.0 0.0 0.0

n−C5H12 0.0 0.1 0.0 0.0 0.8 0.8 0.8 0.8 0.0 0.0 0.0 0.0 0.0

C6~C20 0.0 0.1 0.0 0.0 1.7 1.7 1.7 1.7 0.0 0.0 0.0 0.0 0.0 ṁ/kg s −1 33.7 81.1 33.7 104.1 29.2 30.0 29.2 30.0 7.4 28.9 83.3 83.3 83.3

T/°C −35 −35 −84 −87 13 −40 19 −12 20 20 45 45 155

p/bar 61 61 60 30 30 30 30 30 8 8 33 33 94

xvap/- 1.0 1.0 0.0 1.0 0.0 0.0 0.1 0.3 1.0 1.0 1.0 1.0 1.0

h/kJ kg −1 −4406 −4406 −4756 −4664 −3381 −3632 −3345 −3509 −2405 −2406 −4337 −4336 −4090

s/MJ kg −1 K −1 −0.007 −0.007 −0.009 −0.007 −0.007 −0.008 −0.007 −0.007 −0.007 −0.007 −0.006 −0.006 −0.006

eCH/MJ kg −1 50.744 50.744 50.744 51.023 47.085 48.141 47.085 48.141 50.362 50.366 51.025 51.025 51.025

ePH/MJ kg −1 0.564 0.564 0.711 0.565 0.183 0.258 0.182 0.232 0.110 0.111 0.503 0.502 0.702

��tot/MW 1729.2 4162.3 1734.1 5369.0 1378.7 1449.7 1378.6 1448.9 371.8 1459.7 4290.4 4290.3 4307.0

154

Appendices

Table B.2 Definition of the exergy of fuel and exergy of product at component level

Tag No. Equations

103-C1 ��F = ��QC1 + ��24A�𝑒15PH − 𝑒24APH � + ��16�𝑒15CH − 𝑒16CH� ��P = ��24�𝑒24PH − 𝑒15PH�+ ��16�𝑒16PH − 𝑒15PH� + ��24�𝑒24CH − 𝑒15CH� + ��24A�𝑒24ACH − 𝑒15CH�

105-C3 ��F = ��QC3 + ��64�𝑒59PH − 𝑒64PH� + ��63�𝑒59CH − 𝑒63CH� ��P = ��64�𝑒64CH − 𝑒59CH� + ��63�𝑒63PH − 𝑒59PH�

107-C4 ��F = ��QC4 + ��85�𝑒81 − 𝑒85� 𝐸P = ��85A�𝑒85A − 𝑒81�

107-C5 ��F = ��QC5 + ��86A�𝑒86PH − 𝑒86APH � + ��90(𝑒86PH − 𝑒90PH) + ��90�𝑒86CH − 𝑒90CH� ��P = ��86A�𝑒86ACH − 𝑒86CH�

109-C6 ��F = ��QC6+��108�𝑒104CH − 𝑒108CH � ��P = ��107(𝑒107PH − 𝑒104PH ) + ��108(𝑒108PH − 𝑒104PH ) + ��107�𝑒107CH − 𝑒104CH �

100-E1 ��F = ��Q1 + ��4 ��P = ��4B

103-E2 ��F = ��19 − ��20 + ��12A ��P = ��12

103-E3 ��F = ��17 − ��18 ��P = ��14 − ��14𝐴

104-E5 ��F = ��43A + ��56 − ��43B ��P = ��57


155

Appendices

Tag No. Equations

104-E6 ��F = ��43B + ��142 − ��142A ��P = ��43C

104-E7 ��F = ��Q2 + ��36 ��P = ��36A

105-E8 ��F = (��145 − ��146 )+(��250 − ��261𝐴 )+(��248 − ��56)+(��249 − ��256)+(��143 − ��333) ��P = ��247 − ��246� + (��52 − ��51)

105-E9 ��F = ��63 + ��141 − ��141𝐴 ��P = ��63𝐴

104-H1 ��F = ��QH1 + ��37 ��P = ��38

103-K1 ��F = ��K1 ��P = ��25B − ��25

103-K2 ��F = ��K2 ��P = ��27A − ��26

104-K3 ��F = ��K3 ��P = ��42 − ��41

105-K4 ��𝐹 = ��𝐾4 ��𝑃 = ��62 − ��57


156

Appendices

Tag No. Equations

111-K5 ��F = ��K5 + ��147 ��P = ��147A

111-K6 ��F = ��K6 + ��148B ��P = ��149

106-K7 ��F = ��K7 ��P = ��701C − ��701A

103-P1 ��F = ��P1 ��P = ��14A − ��13

103-P2 ��F = ��P2 ��P = ��21B − ��21

105-P3 ��F = ��P3 ��P = ��59 − ��58

107-P4 ��F = ��P4 ��P = ��91 − ��85A

107-P5 ��F = ��P5 ��P = ��90A − ��90

107-P6 ��F = ��P6 ��P = ��89 − ��86A


157

Appendices

Tag No. Equations

109-P7 ��F = ��P7 ��P = ��102A − ��101C

109-P8 ��F = ��P8 ��P = ��108A − ��108

105-X1 ��F = ��246A − ��54 ��P = ��X1

Units

101-B1 ��D = (��1BL + ��B1)− (��2BL + ��3BL)

114-B2 ��D = (��161 + ��B2) − (��161A + ��161B)

115-B3 ��D = (��171 + ��B3) − (��171A + ��171B + ��171C)

116-B4 ��D = (��63A + ��B4) − (��63B + ��63C)

104-R1 ��D = (��32 + ��38)− (��38A + ��35 + ��37)

104-R2 ��D = ��36A − ��36B

105-C2 ��D = (��256 + ��54 + ��261A + ��247 + ��55 + ��QC2)− (��248 + ��250 + ��249 + ��58)

100-L1 ��D = ��1 − (��2A + ��2B + ��2)


158

Appendices

Dissipative components

103-A1 ��D = ��A1 + ��18 − ��19 103-A2 ��D = ��A2 + ��25B − ��25C 103-A3 ��D = ��A3 + ��27A − ��27 104-A4 ��D = ��A4 + ��39A − ��39 107-A5 ��D = ��A5 + ��90A − ��93 111-A6 ��D = ��A6 + ��149 − ��141 109-A7 ��D = ��A7 + ��108A − ��109 106-A8 ��D = ��A8 + ��701C − ��72 100-D1 ��D = ��3 − (��4 + ��4A) 103-D2 ��D = ��12B − (��13 + ��13A + ��28) 103-D3 ��D = ��14 − ��15B 103-D4 ��D = ��24 − ��25 103-D5 ��D = ��25C − (��26B + ��26A) 103-D6 ��D = ��28A − ��26 103-D7 ��D = (��20 + ��31)− ��21 104-D8 ��D = ��43C − (��32 + ��33 + ��34) 104-D9 ��D = ��39 − (��40 + ��41) 105-D10 ��D = ��52 − (��53 + ��244) 111-D11 ��D = ��146A − ��147 111-D12 ��D = (��333 + ��333A)− ��148 109-D13 ��D = ��101A − ��101C 106-D14 ��D = ��701 − ��701A 103-E4 ��D = ��16 − ��17 107-E10 ��D = ��89 − ��92

159

Appendices

Table B.3 Cost balances and auxiliary equations

Tag No. Cost balance Auxiliary equations

Productive components

103-C1 𝑐15��15 + 𝑐qHP��QC1 + ��C1 = 𝑐24��24 + 𝑐24A��24A + 𝑐16��16 𝑐15 = 𝑐16 = 𝑐24 = 𝑐24A

105-C3 𝑐qLP��QC3 + 𝑐59��59 + ��C3 = 𝑐63��63 + 𝑐64��64 𝑐63 = 𝑐64

107-C4 𝑐qHP��QC4 + 𝑐81��81 + ��C4 = 𝑐85A��85A + 𝑐85��85 𝑐85 = 𝑐81

107-C5 𝑐qLP��QC5 + 𝑐86��86 + ��C5 = 𝑐86A��86A + 𝑐90��90 𝑐90 = 𝑐86A

109-C6 𝑐qLP��QC6 + 𝑐104��104 + ��C6 = 𝑐107��107 + 𝑐108��108 𝑐107 = 𝑐108

100-E1 𝑐4 ��4 + 𝑐qLP��Q1 + ��E1 = 𝑐4B ��4B N/A

103-E2 𝑐12A ��12A + 𝑐19 ��19 + ��E2 = 𝑐20 ��20 + 𝑐12 ��12 c19 = c20

103-E3 𝑐17 ��17 + 𝑐14A ��14A + ��E3 = 𝑐18 ��18 + 𝑐14 ��14 𝑐17 = 𝑐18

104-E5 𝑐43A��43A + 𝑐56��56 + ��E5 = 𝑐57��57 + 𝑐43B��43B 𝑐43A = 𝑐43B

104-E6 𝑐43B��43B + 𝑐142��142 + ��E6 = 𝑐43C��43C + 𝑐142A��142A 𝑐43C = 𝑐43B

104-E7 𝑐36��36 + 𝑐qLP��Q2 + ��E7 = 𝑐36A��36A N/A

105-E8 𝑐250��250 + 𝑐145��145 + 𝑐249��249 + 𝑐143��143 + 𝑐248��248 + 𝑐51��51 + 𝑐246��246 + ��E8 = 𝑐146��146 + 𝑐261A��261A + 𝑐56��56 + 𝑐247��247 + 𝑐52��52 + 𝑐256��256 + 𝑐333��333

𝑐51 = 𝑐52 , 𝑐51 = 𝑐56 𝑐247 = 𝑐246 , 𝑐145 = 𝑐146 𝑐250 = 𝑐261A, 𝑐249 = 𝑐256

105-E9 𝑐63��63 + 𝑐141��141 + ��E9 = 𝑐63A��63A + 𝑐141A��141A 𝑐141 = 𝑐141A

104-H1 𝑐FG��QH1 + ��H1 + 𝑐37��37 = 𝑐38��38 N/A


160

Appendices


103-K1 𝑐w ��K1 + 𝑐25 ��25 + ��K1 = 𝑐25B ��25B N/A

103-K2 𝑐w ��K2 + ��K2 + 𝑐26 ��26 = 𝑐27A ��27A N/A

104-K3 𝑐41��41 + 𝑐w��K3 + ��K3 = 𝑐42��42 N/A

105-K4 𝑐w��K4 + 𝑐57��57 + ��K4 = 𝑐62��62 N/A

111-K5 𝑐w��K5 + ��K5 + 𝑐147��147 = 𝑐147A��147A N/A

111-K6 𝑐w��K6 + ��K6 + 𝑐148B��148B = 𝑐149��149 N/A

106-K7 𝑐w��K7 + ��K7 + 𝑐701A��701A = 𝑐701C��701C N/A

103-P1 𝑐w ��P1 + 𝑐13 ��13 + ��P1 = 𝑐14A ��14A N/A

103-P2 𝑐w ��P2 + ��P2 + 𝑐21 ��21 = 𝑐21B ��21B N/A

105-P3 𝑐w ��P3 + 𝑐58��58 + ��P3 = 𝑐59 ��59 N/A

107-P4 𝑐w ��P4 + ��P4 + 𝑐85A��85A = 𝑐91 ��91 N/A

107-P5 𝑐w ��P5 + ��P5 + 𝑐90��90 = 𝑐90A��90A N/A

107-P6 𝑐w ��P6+��P6 + 𝑐86A��86A = 𝑐89��89 N/A

109-P7 𝑐w ��P7 + 𝑐101C��101C + ��P7 = 𝑐102A ��102A N/A

109-P8 𝑐w ��P8 + 𝑐108��108 + ��P8 = 𝑐108A ��108A N/A

105-X1 𝑐246A��246A + ��X1 = 𝑐54��54 + 𝑐w��X1 N/A


161

Appendices


Units

101-B1 𝑐1BL ��1BL + 𝑐w ��B1 + ��B1 = 𝑐2BL ��2BL + 𝑐3BL ��3BL 𝑐2BL = 𝑐3BL

114-B2 𝑐161 ��161 + 𝑐w ��B2 + ��B2 = 𝑐161A ��161A + 𝑐161B ��161B 𝑐161A = 𝑐161B

115-B3 𝑐171 ��171 + 𝑐w ��B3 + ��B3 = 𝑐171A ��171A + 𝑐171B ��171B + 𝑐171C ��171C 𝑐171A = 𝑐171B = 𝑐171C

116-B4 𝑐63A��63A + 𝑐w��B4 + ��B4 = 𝑐63B��63B + 𝑐63C��63C 𝑐63B = 𝑐63C

104-R1 𝑐32��32 + 𝑐38��38 + ��R1 = 𝑐38A��38A + 𝑐35��35 + 𝑐37��37 c38 = c38A

104-R2 𝑐36A��36A + ��R2 = 𝑐36B��36B N/A

105-C2 𝑐256A��256A + 𝑐54��54 + 𝑐261A��261A + 𝑐247��247 + 𝑐55��55 + 𝑐qLP��QC2 + ��C2

= 𝑐248��248 + 𝑐250��250 + 𝑐249��249 + 𝑐58��58 𝑐248 = 𝑐249 = 𝑐250 = 𝑐58

100-L1 𝑐1��1 + ��L1 = 𝑐2A��2A + 𝑐2B��2B + 𝑐2��2 𝑐1 = 𝑐2 = 𝑐2A = 𝑐2B

Dissipative components

103-A1 ��DA1 = 𝑐w��A1 + 𝑐18 ��18 − 𝑐19 ��19 + ��A1 𝑐18 = 𝑐19

103-A2 ��DA2 = 𝑐w��A2 + 𝑐25B ��25B − 𝑐25C ��25C + ��A2 𝑐25B = 𝑐25C

103-A3 ��DA3 = 𝑐w��A3 + 𝑐27A ��27A − 𝑐27 ��27 + ��A3 𝑐27A = 𝑐27

104-A4 ��DA4 = 𝑐w��A4 + 𝑐39A ��39A − 𝑐39 ��39 + ��A4 𝑐39A = 𝑐39

107-A5 ��DA5 = 𝑐w��A5 + 𝑐90A ��90A − 𝑐93 ��93 + ��A5 𝑐90A = 𝑐93

111-A6 ��DA6 = 𝑐w��A6 + 𝑐149 ��149 − 𝑐141 ��141 + ��A6 𝑐149 = 𝑐141

109-A7 ��DA7 = 𝑐w��A7 + 𝑐108A��108A − 𝑐109 ��109 + ��A7 𝑐109 = 𝑐108A


162

Appendices


106-A8 ��DA8 = 𝑐w��A8 + 𝑐701C��701C − 𝑐72 ��72 + ��A8 𝑐72 = 𝑐701C

100-D1 ��DD1 = 𝑐3��3 − (𝑐4��4 + 𝑐4A��4A) + ��D1 𝑐3 = 𝑐4 = 𝑐4A

103-D2 ��DD2 = 𝑐12B��12B − (𝑐13��13 + 𝑐13A��13A + 𝑐28��28) + ��D2 𝑐13 = 𝑐28

103-D3 ��DD3 = 𝑐14��14 − 𝑐15B��15B + ��D3 N/A

103-D4 ��DD4 = 𝑐24��24 − 𝑐25��25 + ��D4 N/A

103-D5 ��DD5 = 𝑐25C��25C − (𝑐26B��26B + 𝑐26A��26A) + ��D5 𝑐26A = 𝑐26B

103-D6 ��DD6 = 𝑐28A��28A − 𝑐26��26 + ��D6 N/A

103-D7 ��DD7 = (𝑐20��20 + 𝑐31��31) − 𝑐21��21 + ��D7 N/A

104-D8 ��DD8 = 𝑐43C��43C − (𝑐32��32 + 𝑐33��33 + 𝑐34��34) + ��D8 𝑐32 = 𝑐33 = 𝑐34

104-D9 ��DD9 = 𝑐39��39 − (𝑐40��40 + 𝑐41��41) + ��D9 𝑐40 = 𝑐41

105-D10 ��DD10 = 𝑐52��52 − �𝑐53��53 + 𝑐244��244� + ��D10 𝑐53 = 𝑐244

111-D11 ��DD11 = 𝑐146A��146A − 𝑐147��147 + ��D11 N/A

111-D12 𝐶DD12 = (𝑐333��333 + 𝑐333A��333A) − 𝑐148��148 + ��D12 N/A

109-D13 ��DD13 = 𝑐101A��101A − 𝑐101C��101C + ��D13 N/A

106-D14 ��DD14 = 𝑐701��701 − 𝑐701A��701A + ��D14 N/A

103-E4 ��DE4 = 𝑐16 ��16 − 𝑐17��17 + ��E4 𝑐16 = 𝑐17

107-E10 ��DE10 = 𝑐89 ��89 − 𝑐92 ��92 + ��E10 𝑐89 = 𝑐92

163

Appendices

Table B.4 Results of conventional exergy and exergoeconomic for productive components

Tag No. ��𝐅,𝐤 / MW

��𝐏,𝐤 / MW

��𝐃,𝐤 / MW

𝜺𝐤 / %

��𝐃,𝐤 / GJ hr-1

��𝐤 / $ hr-1

𝒄𝐅,𝐤 / $ GJ-1

𝒄𝐏,𝐤 / $ GJ-1

��𝐃,𝐤 / $ hr-1

��𝐃,𝐤 + ��𝐤 / $ hr-1

𝒓𝐤 / -

𝒇𝐤 / -

Productive components 103-C1 18.87 18.85 0.02 99.92 0.05 25.13 3.51 3.90 0.19 25.32 0.11 0.99

105-C3 11.82 9.88 1.94 83.60 6.98 159.10 7.35 13.25 51.28 210.38 0.80 0.76

107-C4 11.21 7.98 3.23 71.17 11.64 132.60 8.56 16.64 99.54 232.14 0.95 0.57

107-C5 3.08 1.35 1.73 43.78 6.24 39.69 4.15 17.64 25.86 65.55 3.26 0.61

109-C6 0.97 0.33 0.64 34.38 2.29 11.86 4.17 22.00 9.56 21.42 4.28 0.55

100-E1 12850.93 12850.69 0.24 100.00 0.87 6.76 4.17 78.31 3.65 10.41 17.78 0.65

103-E2 2416.04 2415.65 0.39 99.98 1.41 13.52 3.05 3.05 4.29 17.81 0.00 0.76

103-E3 1.04 0.31 0.74 29.34 2.65 6.90 3.10 16.83 8.22 15.12 4.43 0.46

104-E5 5360.55 5360.23 0.32 99.99 1.16 12.58 10.00 10.00 11.55 24.13 0.00 0.52

104-E6 6877.90 6877.67 0.24 100.00 0.85 12.17 6.77 6.77 5.73 17.90 0.00 0.68

104-E7 6390.79 6390.38 0.41 99.99 1.46 8.11 9.97 9.97 14.53 22.65 0.00 0.36

105-E8 9.54 7.77 1.77 81.48 6.36 82.50 11.59 312.30 73.65 156.15 25.96 0.53

105-E9 378.86 378.75 0.10 99.97 0.36 1.15 10.06 10.07 3.66 4.81 0.00 0.24

104-H1 484.04 482.76 1.28 99.74 4.60 177.00 54.98 55.22 252.75 429.75 0.00 0.41

103-K1 1.07 0.58 0.49 54.41 1.75 24.34 20.14 48.67 35.24 59.58 1.42 0.41

103-K2 1.85 1.00 0.85 54.25 3.04 148.80 20.14 78.37 61.27 210.07 2.89 0.71

104-K3 0.21 0.16 0.05 78.37 0.16 18.26 20.14 56.81 3.26 21.52 1.82 0.85

105-K4 3.41 2.33 1.07 68.53 3.86 135.20 20.14 45.49 77.72 212.92 1.26 0.63

111-K5 1051.61 1051.39 0.22 99.98 0.79 81.14 73.27 73.31 58.03 139.17 0.00 0.58


164

Appendices




𝜺𝐤 / %


��𝐤 / $ hr-1

𝒄𝐅,𝐤 / $ GJ-1

𝒄𝐏,𝐤 / $ GJ-1

��𝐃,𝐤 / $ hr-1

��𝐃,𝐤 + ��𝐤 / $ hr-1

𝒓𝐤 / -

𝒇𝐤 / -

111-K6 2886.53 2885.73 0.80 99.97 2.89 189.30 73.22 73.26 211.40 400.70 0.00 0.47

106-K7 20.50 16.69 3.81 81.43 13.70 1285.00 20.14 46.41 275.95 1560.95 1.30 0.82

103-P1 0.10 0.06 0.04 63.64 0.13 8.06 20.14 67.19 2.61 10.67 2.34 0.76

103-P2 0.06 0.06 0.00 95.16 0.01 4.34 20.14 41.59 0.22 4.56 1.07 0.95

105-P3 0.00 0.00 0.00 74.07 0.00 1.63 20.14 254.10 0.07 1.71 11.62 0.96

107-P4 0.07 0.05 0.02 78.26 0.05 6.40 20.14 58.67 1.09 7.49 1.91 0.85

107-P5 0.01 0.01 0.00 77.78 0.01 1.90 20.14 102.80 0.15 2.04 4.10 0.93

107-P6 0.03 0.02 0.01 69.70 0.04 3.59 20.14 72.30 0.73 4.32 2.59 0.83

109-P7 0.01 0.00 0.01 12.13 0.03 2.16 20.14 764.90 0.51 2.66 36.98 0.81

109-P8 0.00 0.00 0.00 68.30 0.00 1.27 20.14 205.70 0.07 1.34 9.21 0.95

105-X1 4.35 3.41 0.95 78.28 3.40 90.61 9.98 20.14 33.96 124.57 1.02 0.73 Units

101-B1 6426.36 6424.92 1.439 - 5.180 1545.0 - - - - - -

114-B2 588.47 585.419 3.055 - 10.998 108.1 - - - - - -

115-B3 405.39 404.019 1.373 - 4.943 73.58 - - - - - -

116-B4 381.26 381.132 0.125 - 0.45 315.9 - - - - - -

104-R1 7354.46 7354.006 0.454 - 1.634 302.2 - - - - - -

104-R2 6390.38 6390.1 0.283 - 1.019 68.37 - - - - - -

105-C2 9220.12 9214.756 5.364 - 19.3104 100.5 - - - - - -

100-L1 14831.20 14828.493 2.707 - 9.745 55.8 - - - - - -


165

Appendices




𝜺𝐤 / %


��𝐤 / $ hr-1

𝒄𝐅,𝐤 / $ GJ-1

𝒄𝐏,𝐤 / $ GJ-1

��𝐃,𝐤 / $ hr-1

��𝐃,𝐤 + ��𝐤 / $ hr-1

𝒓𝐤 / -

𝒇𝐤 / -

Dissipative Components 103-A1 1973.893 1972.746 1.147 - 4.129 10.55 - - - - - - 103-A2 277.213 276.962 0.251 - 0.903 9.20 - - - - - - 103-A3 441.242 440.972 0.27 - 0.972 8.52 - - - - - - 104-A4 483.643 481.741 1.902 - 6.847 10.01 - - - - - - 107-A5 318.507 318.267 0.24 - 0.864 8.52 - - - - - - 111-A6 2885.879 2883.778 2.101 - 7.563 33.81 - - - - - - 109-A7 24.524 24.18 0.344 - 1.238 9.60 - - - - - - 106-A8 4307.05 4302.26 4.79 - 17.244 27.05 - - - - - - 100-D1 12854.839 12854.386 0.453 - 1.631 173.60 - - - - - - 103-D2 2425.3 6391.902 0.073 - 0.263 51.58 - - - - - - 103-D3 2192.496 1050.723 0.012 - 0.043 102.3 - - - - - - 103-D4 276.672 1831.428 0.045 - 0.162 2.55 - - - - - - 103-D5 276.962 24.207 0.043 - 0.154 4.13 - - - - - - 103-D6 440.24 4290.286 0.004 - 0.014 4.13 - - - - - - 103-D7 2290.562 2425.227 0.118 - 0.424 9.77 - - - - - - 104-D8 6877.665 2192.484 0.4 - 1.440 173.60 - - - - - - 104-D9 481.741 276.627 0.029 - 0.104 6.50 - - - - - - 105-D10 6392.717 276.919 0.815 - 2.934 80.22 - - - - - - 111-D11 1050.724 440.236 0.001 - 0.004 4.61 - - - - - - 111-D12 1831.492 2290.444 0.064 - 0.230 9.70 - - - - - - 109-D13 24.208 6877.265 0.001 - 0.004 8.57 - - - - - - 106-D14 4290.389 481.712 0.103 - 0.371 59.16 - - - - - - 103-E4 1976.401 1974.914 1.487 - 5.353 6.83 - - - - - - 107-E10 404.026 403.986 0.04 - 0.144 4.06 - - - - - -

166

Appendices

Table B.5 Results of Diagnostic exergoeconomic for productive components




𝜺𝐤 / %


��𝐤 / $ hr-1

𝒄𝐅,𝐤 / $ GJ-1

𝒄𝐏,𝐤 / $ GJ-1

��𝐃,𝐤 / $ hr-1

��𝐃,𝐤 + ��𝐤 / $ hr-1

𝒓𝐤 / -

𝒇𝐤 / -

103-C1 18.87 18.85 0.02 99.92 0.05 0.00 3.50 3.52 0.19 0.19 0.00 0.00 105-C3 11.82 9.88 1.94 83.60 6.98 0.00 13.51 16.14 94.32 94.32 0.19 0.00 107-C4 11.21 7.98 3.23 71.17 11.64 0.00 12.59 17.70 146.53 146.53 0.41 0.00 107-C5 3.08 1.35 1.73 43.78 6.24 0.00 8.41 19.21 52.48 52.48 1.28 0.00 109-C6 0.97 0.33 0.64 34.38 2.29 0.00 4.17 12.13 9.56 9.56 1.91 0.00 100-E1 12850.93 12850.69 0.24 100.00 0.87 0.00 4.17 30.15 3.65 3.65 6.23 0.00 103-E2 2416.04 2415.65 0.39 99.98 1.41 0.00 3.05 3.05 4.29 4.29 0.00 0.00 103-E3 1.04 0.31 0.74 29.34 2.65 0.00 3.09 10.52 8.19 8.19 2.41 0.00 104-E5 5360.55 5360.23 0.32 99.99 1.16 0.00 15.78 15.78 18.24 18.24 0.00 0.00 104-E6 6877.90 6877.67 0.24 100.00 0.85 0.00 9.84 9.84 8.32 8.32 0.00 0.00 104-E7 6390.79 6390.38 0.41 99.99 1.46 0.00 15.76 15.76 22.98 22.98 0.00 0.00 105-E8 9.54 7.77 1.77 81.48 6.36 0.00 16.38 365.70 104.12 104.12 21.33 0.00 105-E9 378.86 378.75 0.10 99.97 0.36 0.00 15.79 15.80 5.74 5.74 0.00 0.00 104-H1 484.04 482.76 1.28 99.74 4.60 0.00 99.83 100.10 458.95 458.95 0.00 0.00 103-K1 1.07 0.58 0.49 54.41 1.75 0.00 20.14 37.02 35.24 35.24 0.84 0.00 103-K2 1.85 1.00 0.85 54.25 3.04 0.00 20.14 37.12 61.27 61.27 0.84 0.00 104-K3 0.21 0.16 0.05 78.37 0.16 0.00 20.14 25.70 3.26 3.26 0.28 0.00 105-K4 3.41 2.33 1.07 68.53 3.86 0.00 20.14 29.39 77.72 77.72 0.46 0.00 111-K5 1051.61 1051.39 0.22 99.98 0.79 0.00 39.58 39.59 31.35 31.35 0.00 0.00 111-K6 2886.53 2885.73 0.80 99.97 2.89 0.00 39.56 39.57 114.21 114.21 0.00 0.00 106-K7 20.50 16.69 3.81 81.43 13.70 0.00 20.14 24.89 275.95 275.95 0.24 0.00 103-P1 0.10 0.06 0.04 63.64 0.13 0.00 20.14 31.65 2.61 2.61 0.57 0.00 103-P2 0.06 0.06 0.00 95.16 0.01 0.00 20.14 21.16 0.22 0.22 0.05 0.00 105-P3 0.00 0.00 0.00 74.07 0.00 0.00 20.14 27.19 0.07 0.07 0.35 0.00 107-P4 0.07 0.05 0.02 78.26 0.05 0.00 20.14 25.73 1.09 1.09 0.28 0.00

167

Appendices




𝜺𝐤 / %


��𝐤 / $ hr-1

𝒄𝐅,𝐤 / $ GJ-1

𝒄𝐏,𝐤 / $ GJ-1

��𝐃,𝐤 / $ hr-1

��𝐃,𝐤 + ��𝐤 / $ hr-1

𝒓𝐤 / -

𝒇𝐤 / -

107-P5 0.01 0.01 0.00 77.78 0.01 0.00 20.14 27.62 0.15 0.15 0.37 0.00

Table B.6 Results of exergoenvironmental for productive components




𝜺𝐤 / %


��𝐤 / mPts hr-

1

𝒃𝐅,𝐤 / mPts GJ-1

𝒃𝐏,𝐤 / mPts GJ-1

��𝐃,𝐤 / mPts hr-

��𝐃,𝐤 + ��𝐤 / mPts hr-1

𝒓𝐛,𝐤 / -

𝒇𝐛,𝐤 / -

103-C1 18.87 18.85 0.02 99.92 0.05 0.00 1735 1741 94 94 0.00 0.00 105-C3 11.82 9.88 1.94 83.60 6.98 0.00 5456 6519 38086 38086 0.19 0.00 107-C4 11.21 7.98 3.23 71.17 11.64 0.00 5713 8028 66475 66475 0.41 0.00 107-C5 3.08 1.35 1.73 43.78 6.24 0.00 4202 9597 26215 26215 1.28 0.00 109-C6 0.97 0.33 0.64 34.38 2.29 0.00 5300 15416 12154 12154 1.91 0.00 100-E1 12850.93 12850.69 0.24 100.00 0.87 0.00 5300 38323 4636 4636 6.23 0.00 103-E2 2416.04 2415.65 0.39 99.98 1.41 0.00 734 734 1033 1033 0.00 0.00 103-E3 1.04 0.31 0.74 29.34 2.65 0.00 754 2572 2002 2002 2.41 0.00 104-E5 5360.55 5360.23 0.32 99.99 1.16 0.00 5877 5878 6792 6792 0.00 0.00 104-E6 6877.90 6877.67 0.24 100.00 0.85 0.00 3475 3475 2940 2940 0.00 0.00 104-E7 6390.79 6390.38 0.41 99.99 1.46 0.00 5869 5869 8557 8557 0.00 0.00 105-E8 9.54 7.77 1.77 81.48 6.36 0.00 6099 136183 38777 38777 21.33 0.00 105-E9 378.86 378.75 0.10 99.97 0.36 0.00 5889 5891 2141 2141 0.00 0.00 104-H1 484.04 482.76 1.28 99.74 4.60 0.00 39835 39941 183130 183130 0.00 0.00 103-K1 1.07 0.58 0.49 54.41 1.75 0.00 7500 13784 13122 13122 0.84 0.00 103-K2 1.85 1.00 0.85 54.25 3.04 0.00 7500 13825 22815 22815 0.84 0.00 104-K3 0.21 0.16 0.05 78.37 0.16 0.00 7500 9571 1215 1215 0.28 0.00 105-K4 3.41 2.33 1.07 68.53 3.86 0.00 7500 10945 28944 28944 0.46 0.00 111-K5 1051.61 1051.39 0.22 99.98 0.79 0.00 14739 14743 11674 11674 0.00 0.00 111-K6 2886.53 2885.73 0.80 99.97 2.89 0.00 14730 14734 42530 42530 0.00 0.00 106-K7 20.50 16.69 3.81 81.43 13.70 0.00 7500 9268 102762 102762 0.24 0.00 103-P1 0.10 0.06 0.04 63.64 0.13 0.00 7500 11786 972 972 0.57 0.00 103-P2 0.06 0.06 0.00 95.16 0.01 0.00 7500 7881 81 81 0.05 0.00 105-P3 0.00 0.00 0.00 74.07 0.00 0.00 7500 10125 27 27 0.35 0.00 107-P4 0.07 0.05 0.02 78.26 0.05 0.00 7500 9583 405 405 0.28 0.00 107-P5 0.01 0.01 0.00 77.78 0.01 0.00 7500 10286 54 54 0.37 0.00 107-P6 0.03 0.02 0.01 69.70 0.04 0.00 7500 10761 270 270 0.43 0.00 109-P7 0.01 0.00 0.01 12.13 0.03 0.00 7500 61837 189 189 7.24 0.00 109-P8 0.00 0.00 0.00 68.30 0.00 0.00 7500 10981 27 27 0.46 0.00 105-X1 4.35 3.41 0.95 78.28 3.40 0.00 5871 7500 19973 19973 0.28 0.00

168

Appendices

Table B.7 Results of advanced exergy-based analyses for selected compressors




��𝐃,𝐤 / $ hr-1

��𝐃,𝐤 / mPts hr-1

��𝐃,𝐤𝐔𝐍 /

MW ��𝐃,𝐤𝐀𝐕 /

MW ��𝐃,𝐤𝐔𝐍 /

$ hr-1 ��𝐃,𝐤𝐀𝐕 /

$ hr-1 ��𝐃,𝐤𝐔𝐍 /

mPts hr-1 ��𝐃,𝐤𝐀𝐕 /

mPts hr-1 105-K4 3.406 2.334 1.07 77.72 28944 0.24 0.83 17.33 60.40 6452.82 22491.18 106-K7 20.495 16.689 3.81 275.95 102762 1.21 2.59 87.90 188.05 32732.78 70029.22

Table B.8 Results of advanced exergy-based analyses for selected productive components

Real operation Best case scenario Worst case scenario




��𝐃,𝐤 / $ hr-1

��𝐃,𝐤 / mPts hr-

1

��𝐃,𝐤𝐔𝐍 /



$ hr-1 ��𝐃,𝐤𝐀𝐕 /

$ hr-1 ��𝐃,𝐤𝐔𝐍 /


mPts hr-1 ��𝐃,𝐤𝐔𝐍 /



$ hr-1 ��𝐃,𝐤𝐀𝐕 /

$ hr-1 ��𝐃,𝐤𝐔𝐍 /


mPts hr-1

105-C3 11.823 9.884 1.939 94.32 38086 1.26 0.68 33.33 17.95 24755.75 13330.02 1.45 0.48 38.46 12.82 28564.33 9521.44

107-C4 11.21 7.978 3.232 146.53 66475 2.10 1.13 64.70 34.84 43208.70 23266.22 2.42 0.81 74.65 24.88 49856.19 16618.73

107-C5 3.083 1.35 1.733 52.48 26215 1.13 0.61 16.81 9.05 17039.79 9175.27 1.30 0.43 19.39 6.46 19661.29 6553.76

105-E8 9.537 7.771 1.766 104.12 38777 0.53 1.24 22.10 51.56 11633.10 27143.90 1.06 0.71 44.19 29.46 23266.20 15510.80

104-H1 484.037 482.76 1.277 458.95 183130 1.15 0.13 227.48 25.28 164817.44 18313.05 - - - - - -

Table B.9 Results of advanced exergy-based analyses for selected units

Unit Real operation Best case scenario Worst case scenario

��𝐢𝐧,𝐤 /MW ��𝐨𝐮𝐭,𝐤 /MW ��𝐃,𝐤 /MW

��𝐃,𝐤𝐔𝐍 /MW ��𝐃,𝐤

𝐀𝐕 /MW

��𝐃,𝐤𝐔𝐍 /MW ��𝐃,𝐤

𝐀𝐕 /MW

101-B1 6426.36 6424.92 1.439 1.01 0.43 1.30 0.14 114-B2 588.474 585.419 3.055 2.14 0.92 2.75 0.31 115-B3 405.392 404.019 1.373 0.96 0.41 1.24 0.14 116-B4 381.257 381.132 0.125 0.09 0.04 0.11 0.01 105-C2 9220.12 9214.756 5.364 3.49 1.88 4.02 1.34

169

Appendices

Table B.10 Results of advanced exergy analysis for selected dissipative components

Tag No. ��𝐢𝐧,𝐤 /MW ��𝐨𝐮𝐭,𝐤/MW ��𝐃,𝐤 /MW ��𝐃,𝐤𝐔𝐍 /MW ��𝐃,𝐤

𝐀𝐕 /MW

103-A1 1973.893 1972.746 1.147 1.03 0.11

111-A6 2885.879 2883.778 2.101 1.89 0.21

106-A8 4307.05 4302.26 4.79 4.31 0.48

103-E4 1976.401 1974.914 1.487 1.34 0.15

170

Appendices

APEENDIX C-Purchased Equipment Costs (PEC) estimation

The purpose of this appendix is to present the assumption and methodology of cost

estimation of available equipmentor units in gas refinery.

C.1 Pumps

To estimate the purchased cost of pumps, based on [146], required shaft power and type of

pump shall be specified. The material of construction of all pumps has been considered as

Carbon Steel. Considering the volumetric flow rate of handled fluid and pressure, the type

of all pumps has been considered as “centrifugal pumps”.

To estimate the shaft power, required pressure ratio has been set in ASPEN for all pumps.

Based on this data and volumetric flow rate of handled fluid, shaft power has been

calculated by ASPEN. The efficiency of all pumps has been assumed as 75 %.

Applying above mentioned data in (C.1), will result in estimation of base cost of pumps:

log10 𝐶B = 𝑔1 + 𝑔2 𝑙𝑜𝑔10(𝑋) + 𝑔3 [𝑙𝑜𝑔10(𝑋)]2 (C.1)

Where; 𝐶B and X are the base cost and size (or capacity) parameter (here; shaft power),

respectively. g values are constants and have been extracted for centrifugal pumps from

relevant table.

It should be added that the calculated shaft power is in the range proposed for g values.

Therefore, it is not necessary to consider scaling factor in this case.

The material factor for carbon steel centrifugal pump is considered as fm=1.8 which has

been read from relevant graph.

The pressure factor, fp, is given by (C.2):

𝑙𝑜𝑔10 𝑓p = 𝑔1 + 𝑔2 𝑙𝑜𝑔10(𝑝) + 𝑔3 [𝑙𝑜𝑔10(𝑝)]2 (C.2)

Where p is the operating pressure of equipment. The values of constants (g1, g2 and g3) in

above equation, depending on type of equipment, have been extracted from relevant table.

Lastly, the bare module cost is given by (C.3):

171

Appendices

𝐶BM = 𝐶B(𝑔1 + 𝑔2𝑓p𝑓m) (C.3)

Where the values of constants (g1 and g2) have been extracted from relevant table.

The reference year for cost is 2001; therefore, all costs have been brought to 2017 by

Chemical Engineering Cost Index (CEPCI).

Finally, by dividing CBM to module factor for pumps, proposed by Guthrie, with value of

“1.3”, the purchased costs of pumps have been obtained. Table C.1 summarized the results

for all pumps:

Table C.1 Purchased cost of pumps

Tag. No. 𝒑𝐨𝐮𝐭𝒑𝐢𝐧

/- ��/m3 s-1 �� /kW 𝑪𝐁,𝟐𝟎𝟎𝟏/$ 𝑪𝐁,𝟐𝟎𝟏𝟕/$ fp /- fm /- CBM, 2017 /$ PEC2017 /$

103-P1 1.35 0.075 99.20 12,861 17,341 1.68 1.80 103,677 79,752

103-P2 7.43 0.069 62.50 9,583 12,921 1.00 1.80 55,819 42,938

105-P3 1.01 0.050 2.70 2,760 3,722 1.55 1.80 21,022 16,171

107-P4 1.78 0.031 69.00 10,182 13,729 1.69 1.80 82,365 63,357

107-P5 1.62 0.013 9.60 3,893 5,249 1.13 1.80 24,383 18,757

107-P6 2.69 0.017 33.50 6,740 9,088 1.32 1.80 46,232 35,563

109-P7 1.32 0.008 8.24 3,692 4,979 1.51 1.80 27,734 21,334

109-P8 2.46 0.008 2.92 2,802 3,778 1.00 1.80 16,321 12,555

C.2 Compressors

To estimate the purchased cost of compressors, based on [147], required fluid power and

type of compressors shall be specified. The material of construction of all compressors has

been considered as Carbon Steel. Considering the volumetric flow rate of handled fluid and

pressure ratio, the type of all compressors has been considered as “centrifugal

compressors”.

To estimate the fluid power, required pressure ratio and efficiency have been set in ASPEN

for all compressors. Based on provided data, required shaft power and fluid power have

been calculated by ASPEN. Fluid power is the result of multiplying shaft power in efficiency.

The efficiency of all compressors has been assumed as 75 %.

172

Appendices

By obtaining fluid power and assuming type of compressors, from provided graphs in

[146], the purchased cost of compressors in 2004 has been evaluated. As far as, the cost of

drivers has been excluded, they should be estimated by relevant graphs. Depends on

required shaft power, all drivers have been assumed as electrical motors. Other two drivers

are gas turbine, one based on process flow diagram of refinery and the other is an

outsource gas turbine which provides electricity from outside of plant.

For estimation of shaft power of drivers, as a practice in industries, 10 % more that

required shaft power of compressor have been used as first evaluation.

Lastly, all costs have been updated by CEPCI of 2017. Table C.2 summarized the results of

PEC estimation for all compressors:

Table C.2 Purchased cost of compressors

Tag. No. 𝒑𝐨𝐮𝐭𝒑𝐢𝐧

/- �� /kW PEC2004 /$ PEC2017 /$ PEC2017 (incl. driver)/$

103-K1 3.22 1067.00 80,000 107,060 240,885 Electric motor ------- 1173.70 100,000 133,825 103-K2 2.67 1848.00 900,000 1,204,425 1,472,075 Electric motor ------- 2032.80 200,000 267,650 104-K3 1.12 208.70 100,000 133,825 180,664 Electric motor ------- 229.57 35,000 46,839 105-X1 0.50 3406.00 670,000 896,628

2,234,878 105-K4 1.16 3170.00 1,000,000 1,338,250 111-K5 1.98 884.00 500,000 669,125 802,950 Electric motor ------- 972.40 100,000 133,825 111-K6 2.80 3730.00 1,000,000 1,338,250 1,873,550 Electric motor ------- 4103.00 400,000 535,300 106-K7 2.80 20495.00 8,500,000 11,375,125

12,713,375 Gas Turbine ------- 22544.50 1,000,000 1,338,250

C.3 Air coolers

For estimating the purchased cost of air coolers - based on [146]- required area of air

coolers shall be calculated. The type of air coolers is considered as forced draft with carbon

steel material.

As in ASPEN, the shortcut model of air cooler has been selected; therefore, there is no

information available for air side of air cooler. Hence, procedure described in [148] has

173

Appendices

been used to calculate the air specifications (outlet air temperature, mass flow rate and

required shaft work for motor of air cooler).

In ASPEN, by setting the outlet temperature of process fluid the heat duty of exchangers

has been determined. Inlet air temperature assumed to be ambient temperature as 25 °C.

The next step is to select overall heat transfer coefficient of bare tubes surface. As [149]

includes U values for extensive applications, the values have been extracted from this

reference based on service of air cooler.

According to design procedure proposed by [148], the next step is to calculate:

𝑇PR,in − 𝑇air,in

𝑈bt (C.4)

Here; TPR,in is the inlet process fluid temperature. By having this value and using below

graph, optimum bundle tube row depth can be obtained.

Fig. C.1 Optimum bundle depth [148]

From Table C.3, typical standard air face velocity, and ratio of surface area to face area have

been selected for obtained bundle depth:

Table C.3 Estimating factors- 1” outer diameter tube × 2 3/8” triangular spacing [148]

12 10 8 6 4 Depth, tube rows

405 445 490 540 595 Typical standard FV/ft min-1

15.20 12.64 10.08 7.60 5.04 𝐒𝐮𝐫 𝐅𝐀

/ft2 ft-2

174

Appendices

Next step is to assume air temperature rise�𝑇air,out − 𝑇air,in�; where; 𝑇air,out is the air outlet

temperature. By replacing air temperature rise in below equation, face area is obtained:

𝐹𝐴 =��

�𝑇air,out − 𝑇air,in�𝐹𝑉(1.08) (C.5)

Where; FA is the total face area and FV is the face velocity.

By having outlet temperature of air, ∆𝑇LMTD can be calculated. Consequently, required bare

tube area can be estimated by using (C.6):

𝐴 =��

𝑈 × ∆𝑇LMTD

(C.6)

Now, again face area would be calculated by (C.7):

𝐹𝐴2 = 𝐴

�𝑆𝑢𝑟 𝐹𝐴 �

= 𝐹𝐴1 (from Table C. 3)

(C.7)

Where subscript 2 refers to second or check calculation, and 1 refers to original trial. If

FA2 =FA1, then the assumed air temperature rise is assumed correct. Otherwise, these steps

should be repeated again till convergence of (C.7).

By obtaining, outlet air temperature, required surface area of air cooler would be estimated

by (C.6) and purchased equipment cost can be calculated accordingly.

The results of air cooler design and estimating for purchased cost of equipment have been

summarized through Tables C.4 to C.6. It should be noted that all units of measurement in

Ludwig are British units.

Table C.4 Purchased equipment cost of air coolers

Tag No. A/m2 PEC2004 /$ PEC2017 /$

103-A1 331 78,000 104,384

103-A2 84 68,000 91,001

103-A3 59 63,000 84,310

104-A4 269 74,000 99,031

175

Appendices

107-A5 55 63,000 84,310

111-A6 1,335 250,000 334,563

109-A7 94 71,000 95,016

106-A8 1,121 200,000 267,650

Table C.5 Estimation of outlet air temperature in air coolers (British units)

Tag No. ��/ Btu hr-1

U/ Btu hr-1 ft-2.°F-1

TPR,in / °F

TPR,out / °F

𝑻𝐚𝐢𝐫,𝐢𝐧/ °F

𝑻𝐏𝐑,𝐢𝐧 − 𝑻𝐚𝐢𝐫,𝐢𝐧

𝑼𝐛𝐭 Bundle

depth FV/ ft min-1

103-A1 22,636,148 80 270.3 164.12 77 2.42 8 490

103-A2 4,466,493 60 277.3 140.00 77 3.34 8 490 103-A3 4,111,631 75 271.2 177.80 77 2.59 8 490 104-A4 21,018,792 60 533.6 140.00 77 7.61 12 405 107-A5 4,138,928 85 271.9 140.00 77 2.29 6 540 111-A6 57,972,286 65 170.1 140.00 77 1.43 4 595 109-A7 6,653,676 95 239.3 140.00 77 1.71 6 540 106-A8 74,725,902 75 311.7 136.40 77 3.13 8 490

Tag No. 𝐒𝐮𝐫 𝐅𝐀

/ ft2 ft-2

𝑻𝐚𝐢𝐫,𝐨𝐮𝐭 − 𝑻𝐚𝐢𝐫,𝐢𝐧 / °F

FA1/ ft2

A/ ft2

FA2/ ft2

𝑻𝐚𝐢𝐫,𝐨𝐮𝐭/ °F

∆𝑻𝐋𝐌𝐓𝐃/ °F

𝐒𝐮𝐫 𝐅𝐀

/ ft2 ft-2

103-A1 10.08 121 354 3560 353 198 79.49 10.08 103-A2 10.08 94 90 899 89 171 82.77 10.08 103-A3 10.08 121.5 64 638 63 198.5 85.99 10.08 104-A4 15.20 250 192 2897 191 327 120.91 15.20 107-A5 7.60 91 78 595 78 168 81.79 7.60 111-A6 5.04 32 2819 14368 2851 109 62.08 5.04 109-A7 7.60 86 133 1008 133 163 69.47 7.60 106-A8 10.08 123.5 1143 12061 1196 200.5 82.61 10.08 Table C.6 Estimation of heat transfer area in air coolers

Tag No. ��/ kW U/Wm-2°C-1 TPR,in /°C TPR,out /°C 𝑻𝐚𝐢𝐫,𝐢𝐧/°C 𝑻𝐚𝐢𝐫,𝐨𝐮𝐭/°C ∆𝑻𝐋𝐌𝐓𝐃/°C A/m2

103-A1 6634 454.3 132.40 73.4 25 92.22 44.16 331 103-A2 1309 340.7 136.27 60 25 77.22 45.98 84 103-A3 1205 425.9 132.88 81 25 92.50 47.77 59 104-A4 6160 340.7 278.66 60 25 163.88 67.17 269 107-A5 1213 482.7 133.32 60 25 75.55 45.44 55 111-A6 16990 369.1 76.75 60 25 42.77 34.49 1,335 109-A7 1951 539.4 115.20 60 25 72.77 38.60 94 106-A8 21900 425.9 155.38 58 25 93.61 45.89 1,121

176

Appendices

C.3.1 Estimation of required shaft power for air coolers

To estimate required shaft work of air cooler fan can be evaluated by:

�� = 𝐴𝑡𝑜𝑡𝐴

𝐻𝑜𝑟𝑠𝑒 𝑝𝑜𝑤𝑒𝑟 (C.8)

Where the “ 𝐴Horse power

” is read from below graph:

Fig. C.2 Surface per fan horse power [148]

The results of estimation of required fan power for air coolers are summarized in below

Table C.7:

Table C.7 Estimation of required fan power for air coolers

Tag No. 𝑨/ft2 𝑨

𝑯𝒐𝒓𝒔𝒆 𝒑𝒐𝒘𝒆𝒓 /ft2hp-1 ��/hp ��/kW

103-A1 3,560 120 29.66 22.10

103-A2 899 120 7.49 5.58

103-A3 638 120 5.31 3.96

104-A4 2,897 180 16.10 11.99

107-A5 595 90 6.61 4.93

111-A6 14,368 70 205.25 152.91

109-A7 1,008 90 11.20 8.35

106-A8 12,061 120 100.51 74.88 In addition; by extracting values for overall heat transfer for finned tube, and selecting

average value for heat capacity of air, the mass flow rate of air can be obtained from below

equation:

177

Appendices

�� = ��air𝑐pair�𝑇air,out − 𝑇air,in� (C.9)

Finally, results are reported in Table C.8:

Table C.8 Estimation of air mass flow rate for air coolers

Tag No. ��/Btu hr-1 𝑻𝐚𝐢𝐫,𝐨𝐮𝐭 − 𝑻𝐚𝐢𝐫,𝐢𝐧 /°F 𝒄𝐩𝐚𝐢𝐫 /Btu lb-1°F-1 ��𝒂𝒊𝒓/lb hr-1 ��𝒂𝒊𝒓/kg s-1

103-A1 22,636,148 121 0.24 779,482 97.44

103-A2 4,466,493 94 0.24 197,983 24.75

103-A3 4,111,631 121.5 0.24 141,002 17.63

104-A4 21,018,792 250 0.24 350,313 43.79

107-A5 4,138,928 91 0.24 189,511 23.69

111-A6 57,972,286 32 0.24 7,548,475 943.56

109-A7 6,653,676 86 0.24 322,368 40.3

106-A8 74,725,902 123.5 0.24 2,521,117 315.14

C.4 Furnace

For estimating the PEC of “Dryers Regeneration Furnace” which is a fired heater; by

providing the outlet temperature of fluid, ASPEN calculated the required heat duty. Based

on [146]; by applying general (C.1) and considering heat duty as the capacity parameter

and extracting g-value constant for furnace/fired heaters from relevant table; the based

cost for fired heater is estimated. Furthermore, by replacing fluid pressure in (C.2), the

pressure factor, fp , is obtained.

To calculate the bare module cost of furnace, (C.10) shall be used:

𝐶BM = 𝐶B𝑓BM𝑓p𝑓T (C.10)

In this equation, fT, is the temperature factor which is fT =1 for furnaces. Bare module factor

in above equation for fired heater is obtained from relevant graph as fBM =2.2. It should be

added that the material of construction of fired heater has been assumed as carbon steel.



178

Appendices

Finally, by dividing CBM to module factor for furnace, proposed by Guthrie, with value of

“1.3”, the purchased costs of fired heater have been estimated. Table C.9 summarized the

results for fired heater:

Table C.9 Purchased cost of fired heater

Tag No. ��/kW logCB/- CB, 2001 /$ CB, 2017 /$ log fp/- fp/- fBM/- CBM,2017/$ PEC2017/$

104-H1 6448.80 5.85 704,242 949,573 0.037368 1.09 2.20 2,276,769 1,751,360

C.5 Slug catcher

Slug catcher has been assumed as 46"(1.17 m) pipeline with approximate length of 100 m

and made of steel material. By having the approximate density of steel, mass of slug catcher

has been calculated. With having unit price of steel material per mass, price of slug catcher

has been obtained. Results are summarized in Table C.10:

Table C.10 Purchased cost of Slug catcher,

Tag No. D/m L/m V/m3 ρ /kg m-3 m /kg C per m,2017 /$ kg-1 PEC2017 /$

100-L1 1.17 100 107 7850 843,550 0.655 552,526

C.6 Separators

C.6.1 Vessel sizing

In this research, two types of process vessels are available: vertical and horizontal. To

estimate the purchased cost of vessels based on [146], the volume of vessels shall be

calculated as the criteria for cost estimation. Therefore, the vessels depending on

orientation and function shall be sized. First the methodology for sizing of vertical vessels

will be discussed and after, the horizontal vessels.

Vertical vessels size estimation

179

Appendices

To have a rough estimation of vessel size, the methodology proposed by [149] has been

used. For vapor/liquid separators, this is usually expressed in terms of maximum velocity

which is related to the difference in liquid and vapor densities. The standard equation is:

𝑢vap max = 𝑔[𝜌Liq − 𝜌V

𝜌V]0.5 (C.11)

where

u = Velocity/ft s-1

ρ = Density of vapor or liquid/lb ft-3

g = System constant

System constant g, is obtained from below graph by calculating the separation factor

=(��Liq/��V �𝜌V𝜌Liq

�0.5

); while �� is the liquid or vapor flow rate/lb s-1.

Fig. C.3 Design vapor velocity factor for vertical vapor-liquid separators [149]

The next step is to calculate the minimum vessel cross section , A , by volumetric flow rate

of vapor, ��V ,and vapor velocity as estimated before. Accordingly, by obtaining cross section

of vessel, the approximate diameter of vessel can be estimated. By assuming the ratio of

length to diameter of vessel, L/D, equal to 3, the approximate length of vessel would be

calculated. With these assumptions, the diameter and length of vessels obtained which

result in estimation of volume of vessels. The results have been summarized in Table C.11.

It should be added that in case of lack of information for g in graph, recommended value

g=0.295 from [150] has been used.

180

Appendices

Horizontal vessels size estimation

Horizontal vessel normally will be used when no or very small gas flow exists. Therefore,

Hold-Up time is the criteria for sizing of this type of vessel to provide enough time of

separation of any gas from liquid. In this section, Hold-Up time assumed to be 15 minutes

and the ratio of length to diameter of vessel, L/D, considered as 3. Moreover, it is assumed

that the vessel is full of liquid.

By above-mentioned assumption and having liquid flow rate and hold up time, volume of

vessel is estimated and consequently, diameter and length is calculated. Results are

available in Table C.12.

181

Appendices

Table C.11 Sizing of vertical vessels

Tag No. ��𝐋𝐢𝐪 / lb s-1

��𝐕/ lb s-1

𝝆𝐋𝐢𝐪/ lb ft-3

𝝆𝐕 / lb ft-3 ��𝐋𝐢𝐪/��𝐕 �

𝝆𝐕𝝆𝐋𝐢𝐪

�𝟎.𝟓

/ g/ -

u / ft s-1

��V / ft3 s-1

A/ ft2

D/ ft

L/ ft

D/ m

L/ m

V/ m3

100-D1 0.11 285.90 41.98 3.91 0.0001 0.295 0.92 73.14 79.44 10.06 30.18 3.0 9.0 63.6

103-D4 1.30 13.04 62.40 0.75 0.0110 0.320 2.90 17.39 5.99 2.76 8.29 1.0 3.0 2.4

103-D5 2.75 10.14 33.20 2.37 0.0725 0.420 1.51 4.30 2.84 1.90 5.70 1.0 3.0 2.4

103-D6 2.05 20.50 62.40 1.81 0.0170 0.395 2.29 11.35 4.96 2.51 7.54 1.0 3.0 2.4

104-D8 0.85 295.80 40.01 3.56 0.0009 0.295 0.94 82.9 87.82 10.58 31.73 3.0 9.0 63.6

104-D9 0.55 20.76 45.82 2.68 0.0064 0.420 1.69 7.70 4.57 2.41 7.24 1.0 3.0 2.4

105-D10 21.80 253.00 31.21 4.84 0.0339 0.400 0.93 52.20 55.91 8.44 25.32 2.6 7.8 41.4

111-D11 4.58 45.85 62.40 0.50 0.0089 0.300 3.34 83.35 24.96 5.64 16.91 1.7 5.1 11.6

111-D12 7.98 79.80 62.40 1.06 0.0130 0.330 2.51 76.14 30.33 6.22 18.65 1.9 5.7 16.2

106-D14 18.30 183.56 62.40 1.37 0.0148 0.330 2.20 132.40 60.11 8.75 26.25 2.6 7.8 41.4

Table C.12 Sizing of horizontal vessels

Tag No. ��Liq /m3 hr-1 Hold Up /min V/m3 D/m L/m

103-D2 254.3 15 63.6 3.0 9.0

103-D3 308.7 15 77.2 3.2 9.6

103-D7 254.3 15 63.6 3.0 9.0

109-D13 30.6 15 7.7 1.5 4.4

182

Appendices

C.6.2 Estimation of purchased cost

Having calculated the volume of vessels, now it is possible to estimate the purchased cost of

them. The methodology in [146] has been applied to calculate the bare cost of vessels.

By applying general (C.1) and considering volume as the capacity parameter and extracting

g-value constant for vertical and horizontal vessels from relevant table; the based costs for

vessels have been estimated.



The material of all vessels has been assumed to be carbon steel; therefore, the material

factor would be equal to 1 (fm=1). Pressure factor (fp) and bare module cost (CBM) have

been estimated based on equations (C.2) and (C.3), respectively and constant values for

vertical and horizontal vessels have been extracted from relevant tables. To evaluate the

purchased cost of vessels, the bare costs have been divided by modular factor proposed by

Guthrie, which for vessels is 1.5. The results are summarized in Table C.13:

Table C.13 Purchased cost of vessels

Tag No. V/m3 log CB/- CB,2001/$ CB,2017/$ p/bar fp /- fm /- CBM,2017/$ PEC2017 /$

100-D1 63.60 4.66 45,198 60,943 82.56 22 1 2,577,286 1,718,191 103-D2 63.60 4.53 34,022 45,874 33.60 10 1 765,639 510,426 103-D3 77.20 4.59 39,048 52,651 55.80 18 1 1,518,974 1,012,649 103-D4 2.40 3.68 4,776 6,439 10.32 2 1 37,927 25,285 103-D5 2.40 3.68 4,776 6,439 32.40 4 1 61,366 40,910 103-D6 2.40 3.68 4,776 6,439 32.16 4 1 61,366 40,910 103-D7 63.60 4.53 34,022 45,874 1.26 1 1 145,054 96,703 104-D8 63.60 4.66 45,198 60,943 75.96 22 1 2,577,286 1,718,191 104-D9 2.40 3.68 4,776 6,439 70.08 7 1 96,524 64,349 105-D10 41.40 4.50 31,845 42,939 71.40 14 1 1,190,706 793,804 111-D11 11.60 4.10 12,460 16,801 3.60 1 1 68,380 45,587 111-D12 16.20 4.20 15,698 21,167 8.40 3 1 143,935 95,956 109-D13 7.70 3.98 9,533 12,854 26.6 4.2 1 127,182 84,788 106-D14 41.40 4.50 31,845 42,939 38.40 10 1 878,108 585,405

183

Appendices

C.7 Heat exchangers

C.7.1 Heat exchanger sizing

For evaluating of purchased cost of heat exchangers, the area is the main criteria which

shall be specified. Therefore, in this section, the procedure which has been applied to

evaluate the area of heat exchangers will be explained.

Amongst of all type of exchangers, shell and tube exchangers are most commonly used heat

exchange equipment. The simplest and cheapest type of shell and tube exchanger is with

fixed tube sheet design. Therefore, in this research, this type of heat exchanger has been

assumed. Furthermore, material of construction of these heat exchangers has been

assumed as carbon steel.

The areas of heat exchangers have been calculated by (C.6). The thermodynamic

specification of fluids, heat duty of each exchanger have been calculated by ASPEN.

Depending on type of fluids inside shell and tube, typical overall heat transfer values have

been extracted from manufacturers’ information [151]. Calculated area for each heat

exchanger is reported in Table C.14.

Table C.14 Calculated area of heat exchangers

Tag No. ��/ kW Th,in/°C Th,out/°C Tc,in/°C Tc,out/°C DTLMTD/°C U/Wm-2°C-1 A/m2 100-E1 933.8 155.0 152.0 24.3 25.0 128.9 30 241.5

103-E2 4205 73.4 29.2 20.9 47.1 15.6 100 2694.3

103-E3 2300 155.0 132.0 48.9 72.0 83.0 100 276.9

103-E4 4679 190.0 155.0 112.0 133.0 49.7 369 255.2

104-E5 3337 45.0 35.0 16.0 30.0 16.9 100 1972.1

104-E6 4605 35.3 22.0 19.6 19.8 7.0 426 1539.7

104-E7 1614 155.0 148.0 22.7 28.1 126.1 30 426.7

105-E9 682 60.0 56.5 7.2 43.0 30.3 483 46.6

107-E10 473 62.4 40.0 34.0 39.0 12.8 426 86.9

Among heat exchangers, there is a “Cold box” which is a multi-stream heat exchanger. This

type of heat exchangers normally is finned plate type and assessing the required heat

transfer area is a complex procedure. By adjusting the thermodynamic specification of

184

Appendices

streams in ASPEN, heat duty and UA parameter have been estimated. The proposed overall

heat transfer values for this type of heat exchangers in literature [152] are in the limit of

1000-4000 Wm-2°C-1. Therefore, to consider the maximum required area, the minimum

value has been considered. Results are available in Table C.15.

Table C.15 Calculated area of Cold box

Tag No. ��/kW DTLMTD/°C UA/kW °C-1 U/W m-2°C-1 A/m2

105-E8 36000 6.4 5625 1000 5625

C.7.2 Estimation of purchased cost

Based on area calculated for each heat exchanger in previous part, the purchased

equipment cost of them has been evaluated by available graphs in [147]. All costs have

been updated by CEPCI for 2017 and reported in Table C.16.

Table C.16 Purchased cost of heat exchangers

Tag No. A/m2 PEC2004/$ PEC2017/$ 100-E1 241.5 50,000 66,913

103-E2 2694.3 100,000 133,825

103-E3 276.9 51,000 68,251

103-E4 255.2 50,500 67,582

104-E5 1972.1 93,000 124,457

104-E6 1539.7 90,000 120,443

104-E7 426.7 60,000 80,295

105-E8 5625.0 610,000 816,333

105-E9 46.6 8,500 11,375

107-E10 86.9 30,000 40,148

C.8 Columns

In this section, the sizing procedure and purchased cost of columns and trays are described.

For condenser (Air-cooled type) and reboiler of each column, the same procedure of air

cooler and heat exchanger has been applied respectively. Finally, the total cost of columns

185

Appendices

is the sum of cost of columns (based on volume of column), cost of trays (based on area of

trays) and cost of reboiler and air-cooled condensers (based on heat transfer area).

C.8.1 Sizing of columns

For sizing of columns, ASPEN has been used. There are some shortcut models in ASPEN

that enables the users to have a first estimation of columns specifications. DSTWU is the

shortcut model which has been selected here. For a specified product recovery (both light

and heavy), the DSTWU column first estimates the minimum number of stages and the

minimum reflux ratio, and then it calculates the either the required reflux ratio or the

required number of theoretical stages based on the user input. This column completes

calculations using Gilliland’s, Winn’s, and Underwood’s methods for calculations of stages

and reflux ratios as indicated in Table C.17.

Table C.17 DSTWU calculation methods

Shortcut Method Calculates For:

Winn Minimum number of stages

Underwood Minimum reflux ratio

Gilliland

Required reflux ratio for a specified number of stages or required number of stages for a specified reflux ratio

In this research, by adjusting the products recovery and number of stages, reflux ratio is

calculated by ASEPN for each column. Having estimated the primary specification of

columns, diameter of columns can be calculated by ASPEN as well. By replacing (RadFrac)

model of columns with (DSTWU), diameters of columns have been obtained. This

distillation unit completes much more rigorous calculations comparing the previous one.

Simulated columns have been assumed to be tray columns (valve type). Heuristic values for

tray spacing has been considered to be 0.6 m. By multiplying this value in number of stages

and adding assumed value of 1.8 m in reboiler section and 1.2m in condenser section, the

height and consequently volume of columns have been estimated. To calculate the tray

area, it has been assumed that tray diameter is equal to column diameter and therefore,

area can be calculated accordingly. The results have been shown in Table C.18.

186

Appendices

Table C.18 Estimation of columns’ specifications

Tag No. No. of actual trays Molar Reflux Ratio D/m L/m V/m3 Tray A/m2

103-C1 10 0.005 2.3 9 37.37 4.15 105-C2 17 0.177 3.7 13.2 141.86 10.75 105-C3 30 2.334 3 21 148.37 7.07 107-C4 34 2.979 3 23.4 165.32 7.07 107-C5 24 1.943 2 17.4 54.64 3.14 109-C6 10 89.75 1 9 7.07 0.79

C.8.2 Sizing of columns heat exchangers

With simulation of columns in ASPEN; as explained in previous section; and by specifying

the temperature and pressure of products, required heat duty of reboilers and condensers

have been reported by ASPEN. The temperature and pressure of inlet and outlet

hydrocarbon stream into reboiler and condenser is known. However, in this research the

second streams thermodynamic properties are not known and should be estimated. With

having this information, DTLMTD of heat exchangers can be evaluated and accordingly the

area could be obtained. It should be added that overall heat transfer coefficient with

considering fluid in contact have been obtained from literature [153].

For reboilers, the medium for heating the hydrocarbon stream is either high pressure (HP)

or low pressure (LP) steam whose temperatures are known. For outlet temperature of

condensed steam, it has been assumed that the outlet temperature is 10 degree lower than

inlet temperature of steam.

On the other hand, the cooling medium in condensers is air. Therefore, by applying the

same procedure as air cooler the outlet temperature of air can be estimated.

C.8.2.1 Sizing of reboilers

As described in previous section, the results of area estimation of reboilers have been

summarized in Table C.19. The kettle type reboilers have been selected as most common

type.

187

Appendices

Table C.19 Estimation of reboilers’ area

Tag No. Heating Medium ��/kW Tc,in/°C Tc,out/°C Th,in/°C Reboiler of 103-C1 HP STEAM 11,400 160.8 197.7 260 Reboiler of 105-C2 LP STEAM 2,810 28.32 38.6 155 Reboiler of 105-C3 LP STEAM 8,974 98 108.3 155 Reboiler of 107-C4 HP STEAM 11,710 128.1 138.3 260 Reboiler of 107-C5 LP STEAM 5,747 122 132.7 155 Reboiler of 109-C6 LP STEAM 3,500 113.5 115.1 155 Tag No. Th,out/°C DTLMTD/ °C U /W m-2°C-1 A /m2 Reboiler of 103-C1 250 75 567 268.3 Reboiler of 105-C2 145 117 567 42.5 Reboiler of 105-C3 145 47 567 337.8 Reboiler of 107-C4 250 122 567 169.6 Reboiler of 107-C5 145 23 567 447.5

C.8.2.2 Sizing of condensers

As explained in previous section, the condenser type is air cooled and therefore, the same

procedure of air coolers would be applied for sizing of them. It should be noted that

demethanizer column (105-C2) does not have any condenser and cooling of top product

would be done by some withdrawal streams from cold box (105-E8).

It should be added that cooling medium of condenser of deethanaizer column (105-C3) is

Propane. Due to lack of information of propane stream temperatures, for estimation the

required area of condenser, UA value has been estimated by ASPEN. Consequently, DTLMTD

value is estimated according to (C.6). Having assumed a value for overall heat transfer

coefficient U; required area is obtained.

Results of estimation of heat transfer area for condensers are reported through Tables C.20

to C.22.

Table C.20 Estimation of deethanizer’s condenser area

Tag No. ��/kW UA/kW °C-1 DTLMTD/°C U/Wm2°C-1 A/m2

Condenser of 105-C3 (Propane cooling medium)

4944 100 49.44 490 204.1

188

Appendices

Table C.21 Estimation of outlet air temperature in air cooled columns’ condensers (British units)

Tag No. ��/Btu hr-1 U/Btu hr-1ft-2°F-1 TPR,in /°F TPR,out /°F 𝑻𝐚𝐢𝐫,𝐢𝐧/°F 𝑻𝐏𝐑,𝐢𝐧 − 𝑻𝐚𝐢𝐫,𝐢𝐧

𝑼𝐛𝐭 Bundle depth FV/ft min-1

Condenser of 103-C1 600,537 90 167 145 77 1.00 4 595

Condenser of 107-C4 41,379,042 100 144 141 77 0.67 3 595

Condenser of 107-C5 25,945,925 90 150 141 77 0.81 3.5 595

Condenser of 109-C6 5,817,701 110 200 194 77 1.1 5 595

Tag No. 𝐒𝐮𝐫

𝐅𝐀/ft2 ft-2 𝑻𝐚𝐢𝐫,𝐨𝐮𝐭 − 𝑻𝐚𝐢𝐫,𝐢𝐧 /°F FA1/ft2 A/ft2 FA2/ft2 𝑻𝐚𝐢𝐫,𝐨𝐮𝐭/°F DTLMTD/°F

Condenser of 103-C1 5 40 23 114 23 117 59

Condenser of 107-C4 5 36 1,789 9,020 1,790 113 46

Condenser of 107-C5 5 35 1,150 5,800 1,151 112 50

Condenser of 109-C6 5 70 129 656 130 147 80.6

Table C.22 Estimation of heat transfer area in air cooled columns’ condensers (SI units)

Tag No. ��/kW U/Wm-2°C-1 TPR,in /°C TPR,out /°C 𝑻𝐚𝐢𝐫,𝐢𝐧/ °C 𝑻𝐚𝐢𝐫,𝐨𝐮𝐭/°C DTLMTD/ °C A/m2

Condenser of 103-C1 176 511 74.93 63 25 47.2 33 10.6

Condenser of 107-C4 12127 567 62.4 60.78 25 45 25 838.9

Condenser of 107-C5 7604 511 65.3 60.75 25 44.5 28 539.1

Condenser of 109-C6 1705 625 93.2 89.95 25 63.8 45 60.8

189

Appendices

C.8.3 Estimation of purchased cost of columns

As explained before, purchased cost of columns includes: cost of pressure vessel, cost of

trays, cost of reboiler and cost of condenser. The sum of these costs provides us the total

purchased cost of a column. All above mentioned costs has been estimated by applying

[146] methodology, except for purchased cost of reboilers, while some of reboilers’

calculated areas were not in the range proposed in [148]. Therefore, Couper has been used

for cost estimation of reboilers.

However, the reboilers cost have been estimated by following equations:

𝐶 = 1.218 × 𝑓d × 𝑓m × 𝑓p × 𝐶B (C.12)

where

𝐶B = 𝑒𝑥𝑝 (8.821 − 0.30863(𝑙𝑛 𝐴) + 0.0681(𝑙𝑛𝐴)2 (C.13)

𝑓p = 0.7771 + 0.04981 (𝑙𝑛 𝐴)

𝑓p = 1.0305 + 0.07140 (𝑙𝑛 𝐴)

100-300 Psig (C.14)

300-600 Psig

𝑓m = 𝑔1 +𝑔2(𝑙𝑛 𝐴) (C.15)

where g1=0.8603, g2= 0.23296.

The bare module costs of pressure vessels, trays and condensers have been obtained by

using equations in previous sections. It should be added that material of construction for all

accessories and pressure vessels has been considered as carbon steel, except for reboilers

which has been considered as stainless steel 316. Having calculated the bare module costs,

by using Guthrie factors, all PECs have been calculated. Moreover, all the costs have been

updated to year 2017. Results are available in Tables C.23 to C.27, respectively.

190

Appendices

Table C.23 Purchased cost of columns (without accessories)

Tag No. V/m3 log CB/- CB, 2001/$ CB, 2017/$ fp/- fm/- CBM, 2017/$ PEC2017/ $

103-C1 37.37 4.47 29,396 39,652 3 1 118,955 79,304

105-C2 141.86 4.96 91,162 122,965 8 1 983,722 655,814

105-C3 148.37 4.98 94,973 128,106 13 1 1,665,372 1,110,248

107-C4 165.32 5.02 104,914 141,515 7.8 1 1,103,816 735,878

107-C5 54.64 4.60 39,892 53,809 2 1 107,617 71,745

109-C6 7.07 3.96 9,029 12,180 1.1 1 13,397 8,932

Table C.24 Purchased equipment cost of columns’ trays

Tag No. Tray A/ m2 log CB/- CB, 2001/$ CB, 2017/$ fd/- fBM/- CBM, 2017/$ PEC2017/ $

103-C1 4.15 3.76 5,789 7,809 1.64 1 128,105 98,542

105-C2 10.75 4.20 15,716 21,199 1.14 1 410,047 315,421

105-C3 7.07 3.99 9,786 13,200 1 1 395,985 304,604

107-C4 7.07 3.99 9,786 13,200 1 1 448,783 345,218

107-C5 3.14 3.66 4,544 6,129 1 1 147,094 113,149

109-C6 0.79 3.29 1,928 2,601 1.64 1 42,664 32,819

191

Appendices

Table C.25 Purchased equipment cost of columns’ air-cooled condensers

Tag No. A/m2 log CB/- CB, 2001/$ CB, 2017/$ fm/- fp/- CBM, 2017/$ PEC2017/ $

Condenser of 103-C1 10.57 4.33 21,155 28,524 1 1 28,524 28,524

Condenser of 105-C3 204.08 4.84 69,101 93,173 1 1 93,173 93,173

Condenser of 107-C4 838.90 5.14 138,957 187,365 1 1 187,365 187,365

Condenser of 107-C5 539.08 5.04 110,647 149,192 1 1 149,192 149,192

Condenser of 109-C6 60.8 4.61 40,686 54,859 1 1 54,859 54,859

Table C.26 Purchased equipment cost of columns’ reboilers

Tag No. A/m2 fm/- fp/- fd/- CB/$ C2003/$ C2017/$ PEC2017/$

Reboiler of 103-C1 268.27 2.16 1.06 1.35 10,144 38,086 50,715 42,263

Reboiler of 105-C2 42.53 1.73 1.30 1.35 5,549 20,538 27,348 22,790

Reboiler of 105-C3 337.83 2.22 1.45 1.35 11,302 59,576 79,331 66,109

Reboiler of 107-C4 169.58 2.06 1.40 1.35 8,360 39,485 52,578 43,815

Reboiler of 107-C5 447.53 2.28 1.08 1.35 13,021 52,828 70,345 58,621

Reboiler of 109-C6 69.4 1.85 1.00 1.35 6,227 18,924 25,199 20,999

192

Appendices

Table C.27 Purchased cost of columns (including all accessories)

Tag No. Items Accessories PEC2017 /$ Column PEC2017/$ 103-C1 Pressure vessel 79,304 248,633

Condenser of 103-C1 28,524 Reboiler of 103-C1 42,263 Trays 98,542

105-C2 Pressure vessel 655,814 994,025

Condenser of 105-C2 0 Reboiler of 105-C2 22,790 Trays 315,421

105-C3 Pressure vessel 1,110,248 1,574,135


107-C4 Pressure vessel 735,878 1,312,276

Condenser of 107-C4 187,365 Reboiler of 107-C1-101 43,815 Trays 345,218





C.9 Dryers and Mercury Guard

The dehydration unit consists of 3 dryers’ bed (104-R1 A/B/C), two of them being operated

in adsorption mode, the third one being regenerated. In addition, there is a packed tower

which its function is to operate as mercury guard. To calculate the cost of these items, the

cost of vertical towers (vessels) and the cost of packing shall be estimated. In first step, for

the cost of vessels, vessels shall be sized based on vertical vessels’ procedure mentioned in

193

Appendices

section C.6.1. The only different assumption is L/D ratio which here has been assumed to

be L/D=2. Results of sizing the towers are summarized in Table C.28.

Table C.28 Sizing of packed towers

Tag No. ��𝐋𝐢𝐪 /lb s-1 ��𝐕/lb s-1 𝝆𝐋𝐢𝐪/lb ft-3 𝝆𝐕 /lb ft-3 ��𝐋𝐢𝐪/��𝐕 �𝝆𝐕𝝆𝐋𝐢𝐪

�𝟎.𝟓

/- g/-

104-R1A/B/C 0.15 295.8 62.40 3.55 0.0001 0.29

104-R2 27.5 275.1 62.40 3.34 0.0231 0.42

Tag No. u /ft s-1 ��V /ft3 s-1 A/ft2 D/ft D/ m L/m V/m3

104-R1A/B/C 1.20 84.23 70.12 9.45 3 6 42.4

104-R2 1.76 82.4 46.65 7.71 2.5 5 24.5

The purchased costs of these equipment have been estimated based on [146] and the

results have been reported in Table C.29:

Table C.29 Purchased cost of packed towers (without absorbent)

Tag No. V/m3 log CB/- CB, 2001/$ CB, 2017/$ p/bar 104-R1 A/B/C 42.4 4.51 32,480 43,795 64

104-R2 24.5 4.32 21,287 28,703 62

Tag No. fp/- fm/- CBM, 2017/$ PEC2017/$ 104-R1 A/B/C 15 1 1,294,153 2,588,306

104-R2 15 1 848,159 565,439

The material of construction has been considered as carbon steel.

To estimate the cost of absorbent with having the inside diameter of vessel and bed height-

can be obtained. In this regard, based on [154], bed heights are usually limited to 8-12 ft

(2.5-3.6 m). For these towers, the packing bed height assumed to be 2.5 m. Therefore, the

costs of absorbent could be estimated. Finally, the total cost of towers and their packing

have been reported. Results are available in Tables C.30 and C.31, respectively.

194

Appendices

Table C.30 Purchased cost of absorbents

Tag No. Packing bed height/m PEC2004/$ PEC2017/$ 104-R1 A/B/C 2.50 300,000 401,625 104-R2 2.5 83,000 111,116 Table C.31 Purchased cost of towers (including absorbent)

Tag No. PEC2017/$ 104-R1 A/B/C 2,989,931 104-R2 676,556

C.10 “Black boxes” units

In this research, there are four units that have been considered as black boxes. They are:

Propane treatment unit (unit 114-B2)

Butane treatment unit (unit 115-B3)

Ethane treatment unit (unit 116-B4)

Gas sweetening unit (unit 101-B1)

Assessing the cost of equipment involved in these units is very complex process; due to lack

of accurate information and patented technology. However, there are some reports from

some companies available in internet for some of the above mentioned units.

In 2001, “Pearl Development Company” [155] has published a report about Propane

treatment. In this report, different technologies have been presented and economic

analyses for two design flow rate of treated Propane (50,000 and 300,000 gallon per day)

have been conducted. Among described technologies, “UOP, RK-29II: Dehydration and

Adsorption- Case B2”, due to similarity to popular process in gas refineries for treatment of

Propane, has been selected, where It is used for the removal of hydrogen sulfide, methyl

mercaptans and carbonyl sulfide.

Selected capacity is 300,000 gallon per day; as it is close to value of stream which enters in

this black box in ASPEN simulated process (Stream 161 – with 693348 gallon per day).

Scaling has been applied to this capacity to adapt the cost of equipment for desired range

based on well-known equation (3.11).

195

Appendices

Due to lack of information for butane and ethane treatment units and operation similarity

of these units with propane treatment unit, the same procedure has been applied for

purchased equipment cost evaluation of these units.

Result of purchased cost of equipment (based on UOP technology) for these units have

been shown in Table C.32:

Table C.32 Purchased cost of “black boxes”

Unit Name ��-treated C3/gpd UOP ��-treated C3/gpd UOP -PEC2001/$ PEC2001/$ PEC2017/$

UNIT 114-B2- C3 treatment unit

693,348 300,000 476,274 787,326 1,069,813


365,120 300,000 476,274 535,853 728,113


4,140,537 300,000 476,274 2,300,478 3,125,872

Lastly for gas sweetening unit PEC estimation, based on [156] publication, Fixed Capital

Investment (FCI) has been reported for conventional Monodethanolamine (MDEA)

technology for gas sweetening process. By having FCI, and assuming that PEC is 15 % of the

FCI, purchased equipment costs has been evaluated for gas sweetening unit. The costs have

been updated for year 2017. Results are available in Table C.33:

Table C.33 Purchased cost of “black box” gas sweetening unit

Unit Name FCI/$ PEC2000/$ PEC2017/$ UNIT101-B1- Gas Sweetening unit 75,000,000 11,250,000 15,286,412

C.11 Summary of PEC estimation

Main criteria for adjusting the costs, final costs of equipment and total (PEC) values are

summarized in Table C.34.

196

Appendices

Table C.34 Purchased equipment costs (PEC)

Tag No. Characteristics Prices ($)

103-A1 Heat Transfer area 104,384








100-D1 Volume of vessel 1,718,191

103-D2 Volume of vessel 510,426













103-P1 Shaft power 79,752








197

Appendices

Tag No. Characteristics Prices ($)


100-E1 Heat Transfer area 66,913










103-K1 Fluid power 240,885

103-K2 Fluid power 1,472,075


105-K4 Fluid power 1,338,250


111-K6 Fluid power 1,873,550

106-K7 Fluid power 12,713,375

105-X1 Fluid power 896,628

104-R1 A/B/C Volume/ Packing height 2,989,931

104-R2 Volume/ Packing height 676,556

104-H1 Heat duty 1,751,360

100-L1 Length 552,526

103-C1 Volume of vessel/Trays area/ Heat duty for reboiler and condenser 248,633


105-C3 Volume of vessel/Trays area/ Heat duty for reboiler and condenser 1,574,135

107-C4 Volume of vessel/Trays area/ Heat duty for reboiler and condenser 1,312,276



Unit 101-B1 Scaling with reference plant 15,286,412


Unit 115-B3 Scaling with reference plant 728,113


PECtot 60,151,803 Consequently, assumptions for estimating (TCI) have been summarized in Table C.35.

198

Appendices

Table C.35 Assumptions and detail information for (TCI) estimation

I. Fixed-Capital Investment (FCI) A. Direct costs(DC) Assumption Value/M$ A.1. Onsite Costs (ONSC) Purchased-equipment cost (PEC) PEC 60.151 Purchased-equipment installation 33 % PEC 19.850 Piping 35 % PEC 21.053 Instrumentation and controls 12 % PEC 7.218 Electrical equipment and materials 13 % PEC 7.819 A.2. Offsite Costs (OFSC) Land 0 0 Civil, structural and architectural work 21 % PEC 12.631 Service facilities 35 % PEC 21.053 Total direct costs (DC) =(ONSC)+(OFSC) 149.777 B. Indirect Costs (IC) B.1. Engineering and supervision 8 % DC 11.982 B.2. Construction costs 15 % DC 22.466 B.3. Contingencies 15 % of total costs 5.167 Total indirect costs (IC) 39.616 Fixed Capital Investment (FCI)=(DC)+(IC) 189.394 Plant Facility Investment (PFI)=(FCI) − cost of land 189.394 II. Other Outlays Startup costs Based on assumption Working capital Based on assumption Costs of licensing, research and development - Allowance for funds used during construction (AFUDC) Based on assumption Total Capital Investment (TCI)=(FCI)+(Other Outlays)

199

Appendices

Table C.36 Estimation of TCI

Plant-Facilities Investment (PFI)/ M$ Year Allocated FCI Value of escalation Escalated Investment Common equity Debt 2018 75.757 1.515 77.272 38.636 38.636 2019 113.637 4.591 118.228 59.114 59.114 Sum 189.394 6.106 195.500 97.750 97.750 Start-up costs (SUC)/ M$ Middle 2017 26.277 Middle 2019 27.338 Escalated values for Operating and Maintenance Costs (OMC)/ M$ Fixed OPEX 1.804 Variable OPEX 0.149 Sum 1.953 Working Capital (WC)/ M$ Middle 2017 242.247 End 2019 254.542 Total net outlay/ M$ Escalated PFI 195.500 SUC 27.338 WC 254.542 Sum 477.380 Total Allowance for Funds During Construction (AFUDC)/ M$ AFUDC for PFI Common equity Debt Mid 2018 4.728 3.528 Mid 2019 2.320 1.748 AFUDC for SUC (middle year 2015) 0.536 0.404 Sum 7.584 5.680 Total AFUDC 13.264 Total Capital Investment/ M$ Total net outlay 477.380 Total AFUDC 13.264 TCI 490.644

200

Appendices

Table C.37 Estimation of Total Revenue Requirement (TRR)

Levelized values − 20 Years for the Plant

Item k CELF CRF Current dollars/M$ Rel. Contr/ %

Carrying Charges (CC) − − 0.0944 46.30 2.90

Fuel cost (FC) 0.958 1.24 − 1550.47 96.96

Operating and maintenance cost (OMC) 0.953 1.19 − 2.32 0.14

TRR − − − 1599.1 100

201

Appendices

Table C.38 Estimation of cost rates

Tag No. PEC/$ PEC/PECtot ��/$ yr-1 ��/$ hr-1 Productive components 103-C1 248,633 0.00413 201,011 25.13 105-C3 1,574,135 0.02617 1,272,630 159.10 107-C4 1,312,276 0.02182 1,060,927 132.60 107-C5 392,706 0.00653 317,489 39.69 109-C6 117,608 0.00196 95,082 11.86 100-E1 66,913 0.00111 54,096 6.76 103-E2 133,825 0.00222 108,193 13.52 103-E3 68,251 0.00113 55,178 6.90 104-E5 124,457 0.00207 100,619 12.58 104-E6 120,443 0.00200 97,373 12.17 104-E7 80,295 0.00133 64,916 8.11 105-E8 816,333 0.01357 659,975 82.50 105-E9 11,375 0.00019 9,196 1.15 104-H1 1,751,360 0.02912 1,415,911 177.00 103-K1 240,885 0.00400 194,747 24.34 103-K2 1,472,075 0.02447 1,190,119 148.80 104-K3 180,664 0.00300 146,060 18.26 105-K4 1,338,250 0.02225 1,081,926 135.20 111-K5 802,950 0.01335 649,156 81.14 111-K6 1,873,550 0.03115 1,514,697 189.30 106-K7 12,713,375 0.21135 10,278,299 1285.00 103-P1 79,752 0.00133 64,476 8.06 103-P2 42,938 0.00071 34,714 4.34 105-P3 16,171 0.00027 13,074 1.63 107-P4 63,357 0.00105 51,222 6.40 107-P5 18,757 0.00031 15,164 1.90 107-P6 35,563 0.00059 28,751 3.59 109-P7 21,334 0.00035 17,248 2.16 109-P8 12,555 0.00021 10,150 1.27 105-X1 896,628 0.01491 724,891 90.61 Units 101-B1 15,286,412 0.25413 12,358,505 1545 114-B2 1,069,813 0.01779 864,904 108.1 115-B3 728,113 0.01210 588,652 73.58 116-B4 3,125,872 0.05197 2,527,153 315.9 104-R1 2,989,931 0.04971 2,417,250 302.2 104-R2 676,556 0.01125 546,971 68.37 105-C2 994,025 0.01653 803,633 100.5 100-L1 552,526 0.00919 446,697 55.84

202

Appendices

Table C.39 Estimation of cost rates (cont.)

Tag No. PEC/$ PEC/PECtot ��/$ yr-1 ��/$ hr-1 Dissipative components 103-A1 104,384 0.00174 84,390 10.55 103-A2 91,001 0.00151 73,571 9.196 103-A3 84,310 0.00140 68,161 8.52 104-A4 99,031 0.00165 80,063 10.01 107-A5 84,310 0.00140 68,161 8.52 111-A6 334,563 0.00556 270,482 33.810 109-A7 95,016 0.00158 76,817 9.602 106-A8 267,650 0.00445 216,385 27.048 100-D1 1,718,191 0.02856 1,389,094 173.6 103-D2 510,426 0.00849 412,660 51.58 103-D3 1,012,649 0.01683 818,690 102.3 103-D4 25,285 0.00042 20,442 2.555 103-D5 40,910 0.00068 33,075 4.134 103-D6 40,910 0.00068 33,075 4.134 103-D7 96,703 0.02856 1,389,094 9.773 104-D8 1,718,191 0.00107 52,024 173.6 104-D9 64,349 0.01320 641,761 6.503 105-D10 793,804 0.00076 36,855 80.22 111-D11 45,587 0.00160 77,577 4.607 111-D12 95,956 0.00068 33,075 9.697 109-D13 84,788 0.00141 68,548 8.568 106-D14 585,405 0.00973 473,279 59.16 103-E4 67,582 0.00112 54,637 6.83 107-E10 40,148 0.00067 32,458 4.057 Total PEC 60,151,803 Sum of levelized OMC and CC costs 48,630,533

203

Appendices

APPENDIX D-Stream cost information Table D.1 Streams cost rates data of exergoeconomic analysis

Str. No. ��/GJ hr-1 c/$ GJ-1 C/$ hr-1 Str. No. ��/GJ hr-1 c/$ GJ-1 C/$ hr-1 1 53392.5 3.050 162847.0 25C 997.1 3.202 3192.6 1BL 23130.0 3.060 70777.9 26 1584.8 3.142 4979.6 2 44697.6 3.050 136327.7 26A 781.4 3.207 2506.0 2A 8651.5 3.050 26387.2 26B 215.5 3.207 691.0 2B 33.4 3.050 102.0 26C 0.0 0.000 0.0 2BL 102.6 3.130 321.0 26E 0.0 0.000 0.0 3 46277.4 3.060 141608.9 26F 0.0 0.000 0.0 3BL 23027.1 3.130 72075.0 27 1587.5 3.313 5259.4 4 46262.3 3.060 141562.7 27A 1588.5 3.313 5262.6 4A 13.5 3.060 41.2 28 803.5 3.074 2470.0 4B 46262.5 3.060 141563.2 28A 1584.9 3.140 4976.5 10 8682.6 3.051 26490.6 29 215.5 3.270 704.6 11 13.5 3.060 41.2 30A 17.4 6.777 118.1 12 8696.3 3.053 26549.9 30B 17.5 6.777 118.3 12A 8696.0 3.051 26531.5 31 1145.8 10.080 11549.7 12B 8731.2 3.068 26787.4 32 24738.3 6.777 167651.4 13 7891.7 3.074 24259.0 33 17.4 6.777 118.2 13A 35.5 3.074 109.2 34 2.6 6.777 17.6 13B 46.3 3.083 142.7 35 23005.3 9.969 229340.2 14 7893.0 3.078 24294.6 36 23004.9 9.969 229336.2 14A 7891.9 3.076 24275.4 36A 23005.4 9.970 229363.7 14B 7892.9 3.078 24294.4 36B 23004.4 9.973 229422.5 15 8107.2 3.094 25083.6 36C 0.0 0.000 0.0 15B 7892.9 3.091 24397.1 37 1731.6 55.300 95759.0 15C 0.0 0.000 0.0 38 1737.9 55.220 95968.8 16 7115.0 3.100 22056.6 38A 1737.7 55.220 95956.9 17 7109.7 3.100 22040.0 39 1734.3 55.120 95592.7 18 7105.9 3.100 22028.4 39A 1741.1 55.120 95967.9 19 7101.9 3.100 22015.8 40 2.2 55.130 123.7 20 7100.1 3.100 22010.4 41 1731.9 55.130 95480.7 21 8245.6 4.071 33567.8 42 1732.5 55.130 95513.1 21B 8245.8 4.072 33576.9 43 23025.5 3.130 72069.7 24 996.0 3.104 3091.6 43A 24760.3 6.768 167577.8 24A 10.8 3.093 33.5 43B 24760.1 6.768 167576.7 24B 995.9 3.104 3091.1 43C 24759.6 6.770 167622.5 25 995.9 3.107 3094.1 51 23003.7 9.973 229415.9 25A 0.0 0.000 0.0 52 23013.8 9.976 229585.5 25B 997.9 3.202 3195.4 53 1801.4 9.981 17979.6

204

Appendices

Table D.2 Streams cost rates data of exergoeconomic analysis (cont.)

Str. No. ��/GJ hr-1 c/$ GJ-1 C/$ hr-1 Str. No. ��/GJ hr-1 c/$ GJ-1 C/$ hr-1 54 14968.8 9.981 149403.4 108A 88.3 4.918 434.1 55 1800.9 9.981 17974.7 109 87.0 4.918 428.1 56 19297.8 9.999 192958.9 141 10381.6 73.260 760556.2 57 19296.8 10.000 192968.2 141A 10381.3 73.260 760535.6 58 3662.7 9.999 36623.2 142 9040.7 73.270 662408.8 59 3662.7 10.000 36626.9 142A 9040.4 73.270 662386.9 62 19305.2 10.020 193438.3 143 1338.7 73.270 98089.9 62D 77225.0 10.020 773794.9 144 2819.4 73.270 206574.3 63 1363.5 10.050 13703.6 145 966.0 73.270 70778.8 63A 1363.5 10.070 13730.6 146 965.3 73.270 70728.4 63B 0.4 10.370 4.3 146A 3782.6 73.310 277302.8 63C 1371.7 10.370 14224.1 146B 0.0 0.000 0.0 64 2299.8 10.050 23113.3 147 3782.6 73.310 277302.8 64A 2300.0 10.050 23115.0 147A 3785.0 73.310 277477.9 72 15488.1 10.160 157359.5 148 6593.1 73.280 483145.2 72A 15487.2 10.160 157350.3 148A 0.0 0.000 0.0 81 4600.2 10.050 46231.9 148B 10378.1 73.290 760609.3 84 109.1 0.000 0.0 149 10388.6 73.260 761070.0 85 2492.9 10.050 25053.3 161 2107.8 10.140 21373.1 85A 2107.6 10.140 21371.2 161A 2107.5 10.300 21707.3 86 2601.4 10.050 26143.9 161B 0.001 10.300 0.0 86A 1454.4 10.076 14654.6 171 1454.3 10.080 14659.8 89 1454.5 10.079 14659.8 171A 108.8 10.200 1109.3 90 1146.6 10.080 11557.5 171B 1341.3 10.200 13680.8 90A 1146.6 10.080 11557.8 171C 4.5 10.200 45.5 91 2107.8 10.140 21373.2 244 21209.5 9.981 211691.6 92 1454.4 10.080 14659.9 246 6225.0 9.981 62131.9 93 1145.8 10.080 11549.3 246A 14984.4 9.981 149559.7 100 36.1 0.000 0.0 247 6242.9 10.000 62428.6 101 82.4 3.083 254.1 248 19328.4 9.999 193265.1 101A 87.1 4.536 395.3 249 4963.2 9.999 49627.2 101B 0.0 0.000 0.0 250 5218.8 9.999 52183.0 101C 87.1 4.635 403.9 256 4963.1 9.999 49625.9 101D 4.8 29.240 141.2 261A 5216.1 9.999 52155.4 102A 87.1 4.666 406.6 333 1338.6 73.270 98077.3 103 0.0 0.000 0.0 333A 5254.8 73.270 385019.1 104 87.1 4.666 406.6 701 15445.4 10.020 154762.9 107 0.1 4.902 0.5 701A 15445.0 10.020 154759.2 108 88.2 4.902 432.6 701C 15505.1 10.160 157531.9

205

Appendices

Table D.3 Stream cost rates data for exergoeconomic diagnostic

Str. No. ��/GJ hr-1 c/$ GJ-1 C/$ hr-1 Str. No. ��/GJ hr-1 c/$ GJ-1 C/$ hr-1 1 53392.5 3.050 162847.0 25C 997.1 3.160 3150.7 1BL 23130.0 3.056 70685.4 26 1584.8 3.119 4943.1 2 44697.6 3.050 136327.7 26A 781.4 3.160 2469.3 2A 8651.5 3.050 26387.2 26B 215.5 3.160 680.9 2B 33.4 3.050 102.0 26C 0.0 0 0.0 2BL 102.6 3.059 313.8 26E 0.0 0 0.0 3 46277.4 3.056 141423.8 26F 0.0 0 0.0 3BL 23027.1 3.059 70440.0 27 1587.5 3.196 5073.7 4 46262.3 3.056 141377.7 27A 1588.5 3.196 5076.7 4A 13.5 3.056 41.1 28 803.5 3.079 2474.0 4B 46262.5 3.056 141378.1 28A 1584.9 3.119 4943.2 10 8682.6 3.051 26490.6 29 215.5 3.160 680.9 11 13.5 3.056 41.1 30A 17.4 9.836 171.5 12 8696.3 3.051 26532.5 30B 17.5 9.836 171.7 12A 8696.0 3.051 26531.5 31 1145.8 15.800 18103.7 12B 8731.2 3.078 26874.7 32 24738.3 9.836 243325.9 13 7891.7 3.079 24298.4 33 17.4 9.836 171.5 13A 35.5 3.079 109.4 34 2.6 9.836 25.6 13B 46.3 3.084 142.8 35 23005.3 15.760 362564.1 14 7893.0 3.080 24310.4 36 23004.9 15.760 362557.7 14A 7891.9 3.079 24299.1 36A 23005.4 15.760 362564.8 14B 7892.9 3.080 24310.2 36B 23004.4 15.760 362548.8 15 8107.2 3.083 24994.4 36C 0.0 0 0.0 15B 7892.9 3.080 24310.3 37 1731.6 100.400 173855.4 15C 0.0 0 0.0 38 1737.9 100.100 173967.3 16 7115.0 3.086 21957.0 38A 1737.7 100.100 173945.8 17 7109.7 3.086 21940.5 39 1734.3 99.910 173270.5 18 7105.9 3.086 21928.9 39A 1741.1 99.910 173950.5 19 7101.9 3.086 21916.4 40 2.2 99.920 224.1 20 7100.1 3.086 21911.0 41 1731.9 99.920 173053.4 21 8245.6 4.853 40015.9 42 1732.5 99.890 173060.2 21B 8245.8 4.854 40025.2 43 23025.5 3.059 70434.9 24 996.0 3.089 3076.7 43A 24760.3 9.834 243492.9 24A 10.8 3.083 33.4 43B 24760.1 9.834 243491.3 24B 995.9 3.089 3076.2 43C 24759.6 9.835 243510.7 25 995.9 3.089 3076.2 51 23003.7 15.760 362538.2 25A 0.0 0 0.0 52 23013.8 15.760 362697.3 25B 997.9 3.160 3153.5 53 1801.4 15.770 28407.8

206

Appendices

Table D.4 Stream cost rates data for exergoeconomic diagnostic (cont.)

Str. No. ��/GJ hr-1 c/$ GJ-1 C/$ hr-1 Str. No. ��/GJ hr-1 c/$ GJ-1 C/$ hr-1 54 14968.8 15.770 236057.6 108A 88.3 5.876 518.6 55 1800.9 15.770 28400.1 109 87.0 5.876 511.5 56 19297.8 15.780 304519.6 141 10381.6 39.570 410800.0 57 19296.8 15.780 304503.9 141A 10381.3 39.570 410788.9 58 3662.7 15.780 57797.2 142 9040.7 39.570 357738.7 59 3662.7 15.780 57797.3 142A 9040.4 39.570 357726.9 62 19305.2 15.790 304829.5 143 1338.7 39.570 52974.2 62D 77225.0 15.790 1219383.4 144 2819.4 39.580 111590.1 63 1363.5 15.790 21530.4 145 966.0 39.580 38234.3 63A 1363.5 15.800 21543.5 146 965.3 39.580 38207.1 63B 0.4 15.830 6.6 146A 3782.6 39.600 149791.2 63C 1371.7 15.830 21713.4 146B 0.0 0 0.0 64 2299.8 15.790 36314.3 147 3782.6 39.600 149791.2 64A 2300.0 15.790 36317.1 147A 3785.0 39.590 149847.9 72 15488.1 15.820 245022.3 148 6593.1 39.580 260956.5 72A 15487.2 15.820 245008.1 148A 0.0 0 0.0 81 4600.2 15.790 72637.0 148B 10378.1 39.580 410764.3 84 109.1 0 0.0 149 10388.6 39.570 411077.5 85 2492.9 15.790 39362.3 161 2107.8 15.810 33324.4 85A 2107.6 15.810 33321.4 161A 2107.5 15.920 33551.6 86 2601.4 15.790 41075.9 161B 0.001 15.920 0.0 86A 1454.4 15.799 22978.2 171 1454.3 15.800 22978.6 89 1454.5 15.800 22981.0 171A 108.8 15.870 1725.9 90 1146.6 15.800 18116.0 171B 1341.3 15.870 21285.7 90A 1146.6 15.800 18116.4 171C 4.5 15.870 70.8 91 2107.8 15.810 33324.5 244 21209.5 15.770 334473.2 92 1454.4 15.800 22978.8 246 6225.0 15.770 98168.6 93 1145.8 15.800 18103.0 246A 14984.4 15.770 236304.6 100 36.1 0 0.0 247 6242.9 15.780 98512.3 101 82.4 3.084 254.1 248 19328.4 15.780 305002.8 101A 87.1 5.781 503.8 249 4963.2 15.780 78319.5 101B 0.0 0 0.0 250 5218.8 15.780 82353.0 101C 87.1 5.781 503.8 256 4963.1 15.780 78317.6 101D 4.8 51.680 249.6 261A 5216.1 15.780 82309.5 102A 87.1 5.788 504.4 333 1338.6 39.570 52967.4 103 0.0 0 0.0 333A 5254.8 39.580 207984.9 104 87.1 5.788 504.4 701 15445.4 15.790 243882.9 107 0.1 5.874 0.6 701A 15445.0 15.790 243877.0 108 88.2 5.874 518.4 701C 15505.1 15.820 245290.8

207

Appendices

Table D.5 Impact rate of streams for exergoenvironmental analysis

Str. No. ��/GJ hr-1 b/mPts GJ-1 ��/mPts hr-1 Str. No. ��/GJ hr-1 b/mPts GJ-1 ��/mPts hr-1 1 53392.5 733.7 39,174,056 25C 997.1 786.9 784,590 1BL 23130.0 736.1 17,026,019 26 1584.8 765.8 1,213,677 2 44697.6 733.7 32,794,633 26A 781.4 787 614,984 2A 8651.5 733.7 6,347,628 26B 215.5 787 169,584 2B 33.4 733.7 24,534 26C 0.0 0 0 2BL 102.6 737.3 75,624 26E 0.0 0 0 3 46277.4 735.9 34,055,551 26F 0.0 0 0 3BL 23027.1 737.3 16,977,917 27 1587.5 795.4 1,262,698 4 46262.3 735.9 34,044,449 27A 1588.5 795.4 1,263,459 4A 13.5 735.9 9,902 28 803.5 745 598,610 4B 46262.5 736.1 34,053,806 28A 1584.9 765.7 1,213,531 10 8682.6 733.9 6,372,166 29 215.5 787 169,574 11 13.5 735.9 9,900 30A 17.4 3475 60,576 12 8696.3 734 6,383,101 30B 17.5 3475 60,663 12A 8696.0 733.9 6,381,986 31 1145.8 5900 6,760,232 12B 8731.2 745 6,504,752 32 24738.3 3475 85,965,571 13 7891.7 745 5,879,285 33 17.4 3475 60,586 13A 35.5 745 26,467 34 2.6 3475 9,038 13B 46.3 746.3 34,554 35 23005.3 5869 135,018,326 14 7893.0 745.6 5,885,009 36 23004.9 5869 135,015,951 14A 7891.9 745.3 5,881,822 36A 23005.4 5869 135,018,591 14B 7892.9 745.6 5,884,967 36B 23004.4 5870 135,035,628 15 8107.2 746.8 6,054,441 36C 0.0 0 0 15B 7892.9 745.6 5,884,979 37 1731.6 40082 69,407,074 15C 0.0 0 0 38 1737.9 39941 69,414,858 16 7115.0 754.5 5,368,301 38A 1737.7 39941 69,406,275 17 7109.7 754.5 5,364,260 39 1734.3 39867 69,139,972 18 7105.9 754.5 5,361,428 39A 1741.1 39867 69,411,316 19 7101.9 754.5 5,358,374 40 2.2 39869 89,422 20 7100.1 754.5 5,357,058 41 1731.9 39869 69,049,890 21 8245.6 1470 12,121,033 42 1732.5 39859 69,056,019 21B 8245.8 1470 12,121,343 43 23025.5 737.3 16,976,672 24 996.0 759.6 756,577 43A 24760.3 3475 86,042,072 24A 10.8 745.7 8,085 43B 24760.1 3475 86,041,513 24B 995.9 759.6 756,453 43C 24759.6 3475 86,039,613 25 995.9 759.6 756,453 51 23003.7 5870 135,031,692 25A 0.0 0 0 52 23013.8 5870 135,090,932 25B 997.9 786.9 785,284 53 1801.4 5871 10,575,932

208

Appendices

Table D.6 Impact rate of streams for exergoenvironmental analysis (cont.)

Str. No. ��/GJ hr-1 b/mPts GJ-1 ��/mPts hr-1 Str. No. ��/GJ hr-1 b/mPts GJ-1 ��/mPts hr-1 54 14968.8 5871 87,881,688 108A 88.3 2023 178,547 55 1800.9 5871 10,573,048 109 87.0 2023 176,097 56 19297.8 5877 113,413,270 141 10381.6 14734 152,962,523 57 19296.8 5878 113,426,728 141A 10381.3 14734 152,958,389 58 3662.7 5877 21,525,615 142 9040.7 14737 133,232,131 59 3662.7 5877 21,525,658 142A 9040.4 14737 133,227,723 62 19305.2 5880 113,514,718 143 1338.7 14737 19,729,091 62D 77225.0 5880 454,083,235 144 2819.4 14738 41,551,680 63 1363.5 5887 8,027,189 145 966.0 14738 14,236,910 63A 1363.5 5891 8,032,463 146 965.3 14738 14,226,770 63B 0.4 5903 2,446 146A 3782.6 14746 55,778,307 63C 1371.7 5903 8,096,913 146B 0.0 0 0 64 2299.8 5887 13,539,095 147 3782.6 14746 55,778,305 64A 2300.0 5887 13,540,121 147A 3785.0 14743 55,802,156 72 15488.1 5892 91,256,093 148 6593.1 14738 97,169,686 72A 15487.2 5892 91,250,790 148A 0.0 0 0 81 4600.2 5887 27,081,308 148B 10378.1 14740 152,972,864 84 109.1 0 0 149 10388.6 14734 153,065,862 85 2492.9 5887 14,675,491 161 2107.8 5917 12,471,882 85A 2107.6 5916 12,468,661 161A 2107.5 5956 12,552,328 86 2601.4 5887 15,314,356 161B 0.001 5956 7 86A 1454.4 5899.784 8,580,702 171 1454.3 5900 8,580,630 89 1454.5 5900.061 8,581,596 171A 108.8 5926 644,460 90 1146.6 5900 6,764,826 171B 1341.3 5926 7,948,277 90A 1146.6 5900 6,764,993 171C 4.5 5926 26,435 91 2107.8 5917 12,471,916 244 21209.5 5871 124,520,748 92 1454.4 5900 8,580,673 246 6225.0 5871 36,547,100 93 1145.8 5900 6,759,986 246A 14984.4 5871 87,973,648 100 36.1 0 0 247 6242.9 5876 36,683,023 101 82.4 746.3 61,501 248 19328.4 5877 113,593,231 101A 87.1 1835 159,918 249 4963.2 5877 29,168,811 101B 0.0 0 0 250 5218.8 5877 30,670,998 101C 87.1 1835 159,911 256 4963.1 5877 29,168,083 101D 4.8 20378 98,422 261A 5216.1 5877 30,654,823 102A 87.1 1838 160,179 333 1338.6 14737 19,726,560 103 0.0 0 0 333A 5254.8 14738 77,445,214 104 87.1 1838 160,179 701 15445.4 5880 90,818,964 107 0.1 2022 200 701A 15445.0 5879 90,801,334 108 88.2 2022 178,441 701C 15505.1 5892 91,356,099

209

evaluation of a gas refinery using exergy-based methods · evaluation of a gas refinery using...

Documents