RETROFIT DESIGN OF HEAT-INTEGRATED CRUDE OIL DISTILLATION SYSTEMS A thesis submitted to the University of Manchester Institute of Science and Technology for the degree of Doctor of Philosophy by Mamdouh Ayad Gadalla Under the direction of Prof. Robin Smith Dr. Megan Jobson Department of Process Integration University of Manchester Institute of Science and Technology P.O. Box 88, Sackville Street Manchester M60 1QD January 2003
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RETROFIT DESIGN OF HEAT-INTEGRATED CRUDE OIL
DISTILLATION SYSTEMS
A thesis submitted to the
University of Manchester Institute of Science and Technology
for the degree of
Doctor of Philosophy
by
Mamdouh Ayad Gadalla
Under the direction of
Prof. Robin Smith
Dr. Megan Jobson
Department of Process Integration
University of Manchester Institute of Science and Technology
P.O. Box 88, Sackville Street
Manchester M60 1QD
January 2003
i
Declaration
No portion of the work referred to in this thesis has been submitted in support of an
application for another degree or qualification of this or any other university or other
institution of learning.
Mamdouh Gadalla
ii
To my Mum ‘Neamat’ and my Brother ‘Nabil’, who
continuously gave me the courage, inspiration and the love in
doing this work, but did not live to see it. Now, your memories
will last forever through this work. To Susana Arnal, for her
being with me, encouraging and supporting me. To my dad,
brothers and my whole family, for being always supportive.
iii
ACKNOWLEDGMENTS
Although words and space are not enough, I would like to deeply express my gratitude
to both my supervisors, Prof. Robin Smith and Dr. Megan Jobson, for their guidance,
encouragement and support throughout my research and study. I found invaluable their
contribution and inspiration which put me in the right direction towards accomplishing
my research. I specially thank Dr. Megan Jobson for her great cooperation during the
stage of writing-up.
Special thanks to the Department of Process Integration for giving me the opportunity
and the sponsorship to study at UMIST and the chance to meet many people.
Throughout my study, I spent a pleasant time with so many wonderful people from
different parts of the globe and of many different cultures; I found one common thing
they all have and share that is kindness.
My sincere thanks go to all staffs at the department of Process Integration, for their help
and support whenever needed. I would like to thank Chris for his help in the
programming part of my research; he really deserves a very big thank. Special thanks to
Steve for his valuable discussion and explanations during my research work.
I am also grateful to all students at the department. Thanks to them for creating a
friendly atmosphere and making a great time in which I spent and worked. Many
colleagues and friends left and new ones came, but they will always stay in my memory.
I cannot name them all because they are too many; I can only say that they are those
people whom I met since I arrived at the department.
I would like lastly to thank all people unmentioned and no longer exist who were at the
background of my life but their effects reach so deep up to the front. I would like to
continuously send deep thanks and love to my mum, Neamat and my brother, Nabil; I
wish they could be here to share and touch their dream. Special thanks go to Susana
Arnal, for being with me when I needed. I also thank my father, my brothers and the
whole family for their support and remembrance.
Last but not least, I give unlimited thanks to the Lord who provides all I need and ask.
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ABSTRACT
Heat-integrated crude oil distillation systems are energy and capital intensive, and have a very complex structure with strong interactions between the individual units. Retrofit of these systems is of major interest to petroleum refiners. Retrofit objectives are various and preferably achieved with minimum capital expenditure, while equipment constraints are met.
Traditional approaches to retrofit design of crude oil distillation systems identify promising modifications based on experience or pinch analysis. Later, sequential approaches to retrofit design were developed, in which distillation and heat recovery units are modified individually. Recent approaches considered simultaneously the distillation column and heat integration targets, rather than the existing heat recovery system. That shortcut models for retrofit design of distillation columns are not available is an additional limitation of established methodologies.
In this thesis, a new approach is presented for retrofit design of heat-integrated crude oil distillation systems. Shortcut models are developed for distillation retrofit, including reboiled and steam-stripped columns. These models are based on the Underwood equation and are appropriate for retrofit design of simple columns and various complex column arrangements. Models are also proposed for exchanger network retrofit, addition of new columns to the existing distillation unit, modifying column internals, enhancing heat transfer in exchanger tubes and for evaluating CO2 emissions in existing crude oil distillation units.
The retrofit design methodology is optimisation-based, and considers the existing distillation process simultaneously with the details of the associated heat recovery system. Existing equipment limitations, such as the hydraulic capacity of the distillation column, exchanger network pressure drop and bottlenecked exchangers, are accounted for. The approach considers various structural modifications and design options resulting in significant benefits. Examples of these are the installation of preflash and prefractionator units to the existing column configuration, replacement of column internals with packing, enhancement of exchanger heat transfer and integration of a gas turbine with an existing furnace.
The optimisation framework comprises column and exchanger network retrofit models, cost models and suitable objective functions. The approach optimises all operating conditions of the existing distillation process and any new columns to minimise or maximise a specified objective function, while satisfying existing constraints. The objective function is flexible and varies according to retrofit objectives. Several objectives are taken into account, such as reducing energy consumption and overall cost, increasing capacity, improving profit and reducing CO2 emissions. The approach allows these objectives to be met by considering several design alternatives.
The new retrofit approach is applied to different industrial cases of crude oil distillation units, for energy and total cost savings, throughput enhancement, product yield changes, profit increase and emissions reduction. Typical results conclude that retrofit goals can be achieved with substantial savings in energy and total cost, and improved profit with minimal capital investment.
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Table of contents Chapter 1: Introduction 1
1.1. Retrofit of heat-integrated crude oil distillation systems 2
1.2. Motivation and objective of the work 4
1.3. Overview of the thesis 5
Chapter 2: Literature review 7
2.1. Introduction 7
2.2. Grassroots design of heat-integrated crude oil distillation systems 8
2.3. Shortcut models for design of distillation columns 10
2.4. Retrofit design of heat-integrated crude oil distillation systems 16
Figure 6.6: Preheat train structure of existing crude oil distillation unit 169
Figure 6.7: Simulated stage diameter for current operation (stages from
top of column to bottom) (tray sizing using HYSYS) 170
Figure 6.8: FUA plot for existing distillation column (column stages:
top-bottom) 170
Figure 6.9: Simulated stage diameter for maximum capacity increase (stages
from column top-down) (tray sizing using HYSYS) 171
Figure 6.10: Temperature profile for existing unit with preflash 172
Figure 6.11: Crude oil stream routing in existing HEN with preflash 183
Figure 6.12: Location of preflash vapour to enter main column 184
Figure 6.13: Temperature profile for optimum unit with preflash 185
Figure 6.14: Column diameter for base case and unit with preflash (stages from
top to bottom of the column) (tray sizing using HYSYS) 187
Figure 6.15: Column diameter for 38% capacity increase of unit with
preflash, compared with existing unit and base case (stages:
top-bottom) 188
Figure 6.16: Reconfiguration of existing crude oil distillation tower with
installed prefractionator 190
Figure 6.17: Location of installed prefractionator in existing preheat train 191
Figure 6.18: FUA curve for unit with prefractionator (stages from column
top-down) 197
Figure 6.19: Simulated column diameter for 59% increased throughput to unit
with prefractionator (number of stages is top-down) (tray sizing
using HYSYS) 198
Figure B.1: Exchanger cost data from various sources (45 and 35% represent
the ratios of the installation cost of exchangers to their purchase
costs as recommended by Peters and Timmerhaus, 1980) 225
Figure B.2: Exchanger cost curve, showing model regression parameters
(data used for regressions are in Table B.1) 226
Figure C.2.1: Retrofit curve and data regression for existing exchanger network
(Aret: area obtained from retrofit study, Amodel: area obtained
from regressed model) 230
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Figure C.2.2: Relocation of exchanger 4 in existing HEN (points 2, 2′) 231
Figure C.2.3: Relocation of exchanger 9 in existing HEN (points 3, 3′) 231
Figure C.2.4: Relocation of exchanger 10 in existing HEN (points 4, 4′) 231
Figure C.2.5: Introduction of new exchanger in existing HEN (points 5, 5′) 231
Figure C.4.1: Relocation of exchanger 4 for network pinch approach results 234
Figure D.1: Modifications to existing heat exchanger network 236
Figure E.2.1: Modifications to existing heat exchanger network for optimum unit
with 20% capacity increase 241
Figure E.3.1: Retrofit curve and data regression (Aret: area obtained from
retrofit study, Amodel: area obtained from regressed model) 244
Figure E.3.2: Relocation of exchanger 1 in existing HEN (points 2, 2′) 245
Figure E.3.3: Relocation of exchanger 9 in existing HEN (points 3, 3′) 245
Figure E.3.4: Introduction of new exchanger in existing HEN (points 4, 4′) 245
Figure E.3.5: Relocation of exchanger 3 in existing HEN (points 5, 5′) 245
Figure E.3.6: Comparison of retrofit model of unit with 20% increased
throughput with existing throughput (vertical dotted line
represents existing energy demand) 246
Figure E.4.1: Modifications to existing heat exchanger network for optimum
unit with 20% capacity increase 247
Figure F.2.1: Relocation of exchanger 4 for optimum network (with integrated
gas turbine) 251
Figure F.3.2: Relocation of exchanger 4 for optimum network 252
Figure H.1: Relocation of exchanger 8 for optimum unit with preflash 261
Figure H.2: FUA curve for existing unit with preflash (stages from column
top to bottom) 261
Figure I.1: Redistribution of stages into sections of decomposed column
sequence of main distillation column 262
Figure I.2: Heat exchanger network for unit with prefractionator (see Table I.2,
for stream references) 264
Figure I.3: Relocation of exchanger 7 in existing for optimum unit
with prefractionator 270
Figure I.4: Stage diameter of unit with prefractionator (stages from column
top to bottom) 270
Figure J.1: Existing exchangers to be enhanced, crude oil is split into 2
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branches 273
Figure J.2: Retrofit curve and data regression for existing HEN with heat
transfer enhancement (HTE) (horizontal dotted line represents
the existing exchanger total area) 276
Figure J.3: Retrofit modifications to existing preheat train, showing types
of exchanger additional area 278
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List of tables Table 3.1: Typical degrees of freedom for design of reboiled distillation
columns 39
Table 3.2: Feed data and column specifications 40
Table 3.3: Retrofit shortcut and rigorous model results (HYSYS) 41
Table 3.4: Typical degrees of freedom for design of fully thermally
coupled sequences of reboiled distillation columns 45
Table 3.5: Column specifications for thermally coupled 46
Table 3.6: Retrofit shortcut and rigorous model results 46
Table 3.7: Retrofit shortcut and rigorous model results 49
Table 3.8: Data for column with a prefractionator 53
Table 3.9: Results for column with prefractionator 54
Table 3.10: Typical degrees of freedom for steam-stripped distillation columns 60
Table 3.11: Feed mixture data and column specifications 61
Table 3.12: Retrofit shortcut and rigorous simulation (HYSYS) results 61
Table 3.13: Column and product specifications 65
Table 3.14: Retrofit shortcut and rigorous model results 65
Table 3.15: Retrofit shortcut and rigorous model results 68
Table 3.16: Typical degrees of freedom for atmospheric crude oil tower 69
Table 3.17: Crude oil assay data 71
Table 3.18: Key components for the separation of each pair of products 72
Table 3.19: Feed composition of crude oil mixture (derived from assay data) 72
Table 3.20: Specifications of atmospheric crude oil distillation column 73
Table 3.21: Results of atmospheric crude oil distillation column 74
Table 4.1: Preflash column results 95
Table 4.2: Product flow rates of an existing crude oil unit 99
Table 6.1: Crude oil assay data 148
Table 6.2: Key components for separation of crude oil products
(recoveries are presented in Table 6.4) 148
Table 6.3: Number of stages and existing diameters of distillation tower
sections 148
Table 6.4: Operating conditions of base case for crude oil distillation tower 148
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Table 6.5: Optimisation variables for crude oil distillation tower 150
Table 6.6: Optimum values of operating conditions 151
Table 6.7: Energy consumption and operating costs for optimum unit 152
Table 6.8: Comparison of new approach results with previous work 156
Table 6.9: Comparison of additional area to existing exchanger 156
Table 6.10: Products income and operating costs of existing unit 158
Table 6.11: Retrofit results of optimum unit with maximum profit 159
Table 6.12: Optimum values of operating conditions for maximum profit 159
Table 6.13: Comparison of energy reduction and increasing profit optimum
cases 160
Table 6.14: Energy consumption, operating costs and profit for base case 162
Table 6.15: Column diameter required for base case and actual diameter 162
Table 6.16: Column diameter for 20% increase in throughput on base case 163
Table 6.17: Process requirements for 20% increase in throughput 163
Table 6.18: Optimisation results for optimum unit with 20% increase in
capacity 165
Table 6.19: Optimum values of operating conditions for 20% capacity increase 166
Table 6.20: Column diameter for optimum unit with 20% capacity increase 166
Table 6.21: Number of stages and existing diameters of distillation tower
sections 168
Table 6.22: CO2 emissions from base case of crude oil distillation tower 172
Table 6.23: CO2 emissions from optimised unit with integrated gas turbine 173
Table 6.24: CO2 emissions from optimum unit without integrated gas turbine 175
Table 6.25: Product yields of base case 176
Table 6.26: Key components of separation for product yield changes 176
Table 6.27: Product yields of new unit with yield changes 177
Table 6.28: Energy consumption and operating costs for new product yield
units 177
Table 6.29: Retrofit results for base case with preflash 180
Table 6.30: Energy consumption and operating costs for optimum unit with
preflash 181
Table 6.31: Energy consumption and operating costs for optimum unit with
preflash 184
Table 6.32: Comparison of results of unit with different locations of preflash
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vapours 185
Table 6.33: Retrofit results for existing unit with prefractionator 192
Table 6.34: Optimum results of unit with prefractionator 194
Table 6.35: Optimum results of unit with prefractionator (all operating
conditions) 195
Table 6.36: Energy and cost requirement and profit for maximum capacity
increase 198
Table 6.37: Optimisation results of optimum unit with maximum capacity
increase 199
Table 6.38: Retrofit approach results for optimum unit with heat
transfer enhancement (HTE) 201
Table 6.39: Case studies comparison 202
Table B.1: Exchanger area and cost data 226
Table C.1.1: Feed composition of crude oil mixture 227
Table C.1.2: Utility, stripping steam and exchanger unit costs 227
Table C.1.3: Energy consumption and operating costs for existing unit 228
Table C.1.4: Heat exchanger data 228
Table C.1.5: Process and utility stream data for existing unit 229
Table C.2.1: Retrofit data for 229
Table C.3.1: Product flow rates of optimum unit 232
Table C.3.2: Key component recoveries of products for optimum unit 232
Table C.3.3: Process stream data for optimum unit 232
Table C.3.4: Additional area and cost for case study 6.1 233
Table C.4.1: Additional area and cost for network pinch approach (no
modifications to column operating conditions) 234
Table C.4.2: Comparison of optimisation results with minimum energy approach
of Bagajewicz (1998) 234
Table C.4.3: Additional area and cost for energy-based approach 235
Table D.1: Product value and crude oil price 236
Table D.2: Additional area and capital cost 237
Table D.3: Process stream data for optimum unit of maximum profit 237
Table D.4: Key component recoveries of products for maximum profit 238
Table E.1.1: Operating conditions of base case 239
Table E.1.2: Heat exchanger data 239
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Table E.1.3: Process and utility stream data for base case 240
Table E.2.1: Operating conditions of 20% capacity increase on base case 241
Table E.2.2: Additional area and cost for 20% increase on base case 242
Table E.2.3: Process and utility stream data for 20% increase of base case
capacity 243
Table E.3.1: Retrofit data 243
Table E.4.1: Operating conditions of optimum unit with 20% capacity increase 246
Table E.4.2: Additional area and cost for optimum unit with 20% capacity
increase 247
Table E.4.3: Process stream data for optimum unit with 20% capacity increase 248
Table F.1.1: Data of hot utilities for case study 249
Table F.1.2: Data for heating fuels in CO2 emissions 249
Table F.2.1: CO2 emissions from optimum unit with integrated gas turbine 249
Table F.2.2: Cost and economic parameters for CO2 emissions calculation 250
Table F.2.3: Optimum values of operating conditions 250
Table F.2.4: Additional area and cost for optimum unit 251
Table F.2.5: Process stream data for optimum unit 251
Table F.3.1: Optimum values of operating conditions 252
Table F.3.2: Additional area and cost for optimum unit 252
Table F.3.3: Process stream data for optimum unit 253
Table G.1: Operating conditions for new product yields 254
Table G.2: Additional area and cost for unit with new product yields 254
Table G.3: Process stream data for unit with new product yields 255
Table G.4: Optimum operating conditions for unit with new product yields 255
Table G.5: Additional area and cost for optimum unit with new product yields 256
Table G.6: Process stream data for optimum unit with new product yields 256
Table H.1: Process stream data for base case with preflash 257
Table H.2: Additional area and cost for base case with preflash 257
Table H.3: Optimum operating conditions for unit with preflash drum 258
Table H.4: Process stream data for optimum unit with preflash 258
Table H.5: Additional area and cost for optimum unit with preflash 259
Table H.6: Optimum operating conditions for unit with preflash drum 259
Table H.7: Product flow rates of optimum unit with preflash 259
Table H.8: Additional area and cost for optimum unit with preflash 260
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Table H.9: Process stream data for optimum unit with preflash 260
Table I.1: Number of stages and of main distillation tower sections 262
Table I.2: Design specifications of prefractionator column 262
Table I.3: Operating conditions of main column of unit with prefractionator 263
Table I.4: Product flow rates of unit with prefractionator 263
Table I.5: Key component recoveries of products for unit with
prefractionator 263
Table I.6: Process streams for base case and unit with prefractionator 264
Table I.7: Process stream data for unit with prefractionator 265
Table I.8: Additional area and cost for unit with prefractionator 265
Table I.9: Operating conditions of main column of optimum
unit with prefractionator 266
Table I.10: Product flow rates of optimum with prefractionator 266
Table I.11: Key component recoveries for optimum unit with prefractionator 266
Table I.12: Process stream data for optimum unit with prefractionator 267
Table I.13: Additional area and cost for optimum unit with prefractionator 267
Table I.14: Optimum operating conditions for unit with prefractionator 268
Table I.15: Product flow rates of optimum with prefractionator 268
Table I.16: Key component recoveries for optimum unit with prefractionator 268
Table I.17: Process stream data for optimum unit with prefractionator 269
Table I.18: Additional area and cost for optimum unit with prefractionator 269
Table I.19: Optimum operating conditions for unit with prefractionator
(59% increase) 270
Table I.20: Optimum design specifications of unit with prefractionator
(59% increase) 271
Table I.21: Product flow rates of optimum with prefractionator (59% increase) 271
Table I.22: Recoveries of products for unit with prefractionator (59% increase) 271
Table I.23: Additional area for optimum unit with prefractionator
(59% increase) 272
Table I.24: Process stream data for optimum unit with prefractionator
(59% increase) 272
Table J.1: Data for exchanger units 273
Table J.2: Maximum area for heat transfer enhancement 273
Table J.3: Calculations of model parameters for retrofit with enhancement 274
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Table J.4: Calculations of model parameters for retrofit with enhancement 274
Table J.5: Optimum operating conditions for unit with heat transfer
enhancement 276
Table J.6: Product flow rates of optimum unit with enhancement 277
Table J.7: Key component recoveries of products for optimum unit
with enhancement 277
Table J.8: Additional and enhancement area for optimum unit with
enhancement 277
Table J.9: Process stream data for optimum unit with heat transfer
enhancement 278
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Nomenclature and abbreviation a1, a2 Constant parameters for equation 4.51 A Exchanger area (m2) Aen Enhanced exchanger area (m2) Aex, Bex, Cex Cost parameters in equation 5.1 ($, $/m2, dimensionless) Aexist Existing area of heat exchanger network (m2) Ao, Bo, Co Constant parameters for flooding limits in equation 4.1 Areq Additional exchanger area for retrofit (m2) Aret Retrofit exchanger area given by equation 4.9 (m2) b0, b1, b2, b3 Retrofit model parameters of polynomial form in equation 4.8 B Molar flow rate of bottom product (kmol/h) c1, c2 Cost parameters in equation 5.2 ($, $/m2) C% Carbon mass percent in fuel CC Composite curve CGCC Column grand composite curve CO2 Emiss Carbon dioxide emissions (kg/h) CostFInst Installed cost of preflash ($) CostGT Capital cost of gas turbines (k$) Costpack Installed cost of packed section ($) CostPower
GT Cost of power generated by gas turbines ($/h) CostPrShell Shell installed cost of prefractionator column ($) CostPrStages Stages installed cost of prefractionator column ($) CP Specific heat capacity of flue gases (kJ/kg oC) CSB Souder and Brown flooding constant (capacity factor) (ft/s) d Tube diameter in Appendix A (m) D Molar flow rate of top product (kmol/h) DC Ratio of down-comer area to cross sectional area of stage (≈12%) de Tube bundle equivalent diameter in Appendix A (m) DFlash Diameter of preflash (m) di Molar flow rate of component i in top product (kmol/h) Dpack Diameter of packing (ft) DPrColumn Diameter of prefractionator column (m) (DR)HK Distribution ratio of heavy key component (DR)i Distribution ratio of component i DT Stage diameter (ft) E Energy consumption of existing HEN (MW) EnCostex Cost of enhancement material ($) f Fraction of flooding velocity (0.5 to 0.7) F Molar flow rate of feed (kmol/h) FLV Flow parameter Fm Correction factor for column material of construction in equation
4.20 Fp Correction factor for column pressure in equation 4.20 Fpack Packing factor (ft2/ft3) Fpd Dry-bed packing factor (ft-1) FUA Fractional of utilised area FuelFact Fuel factor defined in equation 4.26 f{f×uo} Actual velocity function defined (calculated from equation 4.64)
xxii
f{uo} Flooding velocity function defined in equation 4.64 f{µL} Liquid viscosity correction factor given by equation 4.67 f{ρL} Liquid density correction factor given by equation 4.66 g0, g1, g2, g3, g4 Regression parameters in equation 4.66 g Acceleration due to gravity (32.2 ft/s2) GT Gas turbine h0, h1, h2, h3, h4 Regression parameters in equation 4.64 HColumn Enthalpy of crude oil before entering distillation tower (kW) HD Heavy distillate product HETP Height equivalent to a theoretical plate (ft) HF Enthalpy of crude oil before preflash exchanger (kW) HFI Enthalpy of crude oil before entering preflash column (kW) HFlash Height of preflash (m) HK Light key component HL Enthalpy of bottom liquid from preflash (kW) HV Enthalpy of top vapour from preflash (kW) Hmix Enthalpy of vapour mixture (kW) HN Heavy naphtha product Hn Enthalpy of vapour from column n (kW) HP High pressure HPrColumn Height of prefractionator column (m) hProc Enthalpy of steam delivered to process (kJ/kg) hshell Shell side heat transfer coefficient (W/ m2 oC) hshell
exist Shell side heat transfer coefficient in parallel arrangement (W/ m2
oC) HTE Heat transfer enhancement htube
exist Tube side heat transfer coefficient in parallel arrangement (W/ m2
oC) htube
en Enhanced tube side heat transfer coefficient (W/ m2 oC) HXCostNex Capital cost of heat exchanger ($) K Scaling parameter for penalty function in equation 5.3 K1, K2 Parameters for pressure drops (equations 4.49, 4.50) k1, k2, k3 Parameters for pressure drop correlation in Appendix A k′1, k′2, k′3 Parameters for pressure drop correlation in Appendix A L Flow rate of liquid (kmol/h) (only in equation 4.2, units are kg/h) LD Light distillate product LF Gas loading factor in Robbins correlation (lb/h ft2) LFlash Molar flow rate of bottom liquid from preflash (kmol/h) Lflux Mass flow rate of liquid flux (lb/h ft2) LK Light key component LN Light naphtha product m0, m1 Retrofit model parameters in equation 5.4 (m2/MW,
m2.h/MW.kmol) m, c Retrofit model parameters of power form in equation 4.7
(m2/MW, -) m', c' Retrofit model parameters of power form in equation 4.48
(m2/MW, -) MFG Flow rate of flue gas (kg/s) MINLP Mixed integer non-linear programming
xxiii
MSIndex Marshall and Swift index for equipment costs scaling up (1094.3 for the year 2001)
n0, n1 Retrofit model parameters in equation 5.4 (-, h/kmol) N Total number of theoretical stages NActual Actual total number of stages in distillation column NHV Fuel net heating value (kJ/kg) NLP Non-linear programming Nmin Minimum number of stages at total reflux NOVLDTray Number of overloaded (bottlenecked) trays NR Number of theoretical stages in rectifying section NRActual Number of actual stages in rectifying section NS Number of theoretical stages in stripping section NSActual Number of actual stages in stripping section NSpacing Stage spacing (m) (≈ 0.60) NTP Number of theoretical plates P Pressure (Pa) PA Pump-around PCKVcost Cost of packing per unit volume ($/ft3) Penalty Value of penalty function Pmix Pressure of vapour mixture (Pa) Pn Pressure of vapour from column n (Pa) Pr Prandtl Number in Appendix A Pt Tube pinch in Appendix A (m) PUnitCost Unit cost of power produced in gas turbines ($/kW h) p, z Pressure drop model constant parameters (Pa/MW, -) q1, q2 Constants in Robbins correlation given by equation 4.70, 4.71 q Liquid fraction of feed at feed stage conditions Q Heat load of heat exchanger (kW) QFuel Amount of fuel burnt in utility devices (kW) QPreflash Heat duty of required for preflash column (kW) QPreheat Heat duty of furnace (kW) QProc Heat duty required by process (kJ/kg) QFuel
Furn Amount of fuel consumed in a furnace (kW) QFuel
GT Amount of fuel consumed in a gas turbine (MW) QFuel
PS Reduction in fuel consumption at a power station (kW) QFurn Process heat duty provided by a furnace (kW) QGT Process heat duty provided by a gas turbine (kW) r Split ratio for the new to existing shell branches R Reflux ratio RES Residue product RFlash Ratio of height to diameter of preflash RHK Recovery of heavy key component to bottom product RLK Recovery of light key component to top product Rmin Minimum reflux ratio SS Side-stripper TBP True boiling point (oC) TExhaust Exhaust gas temperature from a gas turbine (oC) TFTB Flue gases flame temperature in boilers (oC) TFTF Flue gases flame temperature in furnaces (oC)
xxiv
Tinlet Inlet temperature to the gas turbine (combustion temperature) (oC)
To Ambient temperature (oC) Toutlet Outlet temperature from the gas turbine (flue gas temperature)
(oC) TStack Stack temperature (oC) U Overall heat transfer coefficient for existing exchanger (W/ m2
oC) Udes Design velocity “actual velocity” (ft/s) Uen Overall heat transfer coefficient for enhanced exchanger (W/ m2
oC) Umax Flooding velocity (ft/s) uo Flooding velocity in a packed column (ft/s) Uratio Ratio of design velocity to flooding velocity (70-80%) V Flow rate of vapour (kmol/h) (only in equation 4.2, units are
kg/h) VF Gas loading factor in Robbins correlation (lb/h ft2) VFlash Molar flow rate of top vapour from preflash (kmol/h) Vflux Mass flow rate of liquid flux (lb/h ft2) VL Volumetric flow rate of flashed liquid (m3/s) Vmin Minimum molar vapour flow rate in top section (kmol/h) V′min Minimum molar vapour flow rate at bottom pinch (kmol/h) Vmin,top: Minimum molar vapour flow rate in top section (kmol/h) Vmix Flow rate of vapour mixture (kmol/h) Vn Flow rate of vapour from column n (kmol/h) VS Volumetric flow rate in shell side in Appendix A (m3/s) VT Volumetric flow rate in tube side in Appendix A (m3/s) VV Volumetric flow rate of vapour (ft3/s)) WGT Power produced in a gas turbine (kW) X Molar composition of bottom liquid from preflash xbLK Mole fraction of light key component in bottom product xdHK Mole fraction of heavy key component in top product xdLK Mole fraction of light key component in top product xf,i Mole fraction of component i in feed xfHK Mole fraction of heavy key component in feed xfLK Mole fraction of light key component in feed xHKFS Liquid mole fraction of heavy key component on feed stage xi Dependent variable in optimisation, equation 5.3 xLKFS Liquid mole fraction of light key component on feed stage xi,lim Constrained value for variable in optimisation, equation 5.3 x, y Number of carbon and hydrogen atoms respectively in equation
4.24 XX Location of entering vapours from preflash to distillation column Y Molar composition of top vapour from preflash Ymix Molar composition of vapour mixture Yn Molar composition of vapour from column n Z Molar composition of feed to preflash
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Greek letters
α Ratio of molar masses of carbon dioxide and carbon (=3.67) αHK Volatility of heavy key component relative to a reference
component αi Volatility of component i relative to a reference component αLK Volatility of light key component relative to a reference
component ∆A Additional area to an existing exchanger unit (m2) ∆Amax Maximum area that can be achieved by enhancing an exchanger
(m2) ∆Atotal
max Total maximum area that can be achieved by enhancing a HEN (m2)
∆HPrColumn Extra height added to prefractionator column (m) ∆P Pressure drop for a plain tube (Pa) ∆PC.O. Pressure drop for the crude oil stream in preheat train (Pa) ∆Pen Pressure drop for an enhanced exchanger (Pa) ∆Pshell Pressure drop on shell side (Pa) ∆Pshell
exist Pressure drop of existing shell (Pa) ∆Pshell
new Pressure drop of new shell (Pa) ∆Pshell
total Total pressure drop of existing and new shells (Pa) ∆Pflood Pressure drop in a packed bed at flooding (in. H2O/ft height) ∆Ppack Pressure drop in a packed bed (in. H2O/ft height) ∆Ptube Pressure drop in tube sides (Pa) ∆T Temperature drop through pump-around (oC) ∆TLM Logarithmic mean temperature difference (oC) ∆Tmin Minimum difference temperature approach (oC) φ Roots of Underwood equation φFensk Fenske term given by equation 3.6 to simplify equation 3.5 φKirk Kirkbride term given by equation 3.17 to simplify equation 3.16 Φ Friction factor in Appendix A ηC Carnot Factor of gas turbine ηFurn Furnace efficiency ηGT Gas turbine heat recovery efficiency ηOP Overall plate efficiency ηOTray Overall tray efficiency of distillation column ηRTray Tray efficiency of rectifying section ηSTray Tray efficiency of stripping section κ, υ Constants in Coker correlation for pressure drop in Appendix A λ Thermal conductivity in Appendix A (W/m2 K) λProc Latent heat of steam delivered to process in Appendix A (kJ/kg) µ Viscosity (kg/m s) µF,avg Average viscosity of feed at section temperature and pressure
(cP) µL Liquid viscosity (cP) θR Residence time in preflash (s) ρ Density in Appendix A (kg/m3)
OHρ 2 Density of water (62.4 lb/ft3)
xxvi
ρL Mass density of liquid (kg/m3) (in equations 4.74, 4.75 only, units are lb/ft3)
ρV Mass density of vapour (kg/m3) (in equations 4.72, 4.73 only, units are lb/ft3)
ϕSteam Stripping steam term given by equation 3.31 to simplify equation 3.30
σ Surface tension (dyne/cm) ξ Term defined by equations 2.8, 3.9 and 3.34 ψGill Gilliland term in equations 3.7, 3.32
Subscripts and superscripts
C Carnot factor C.O. Crude oil stream des Design en Heat transfer enhanced exist Existing unit F,avg Feed average property FG Flue gases Fensk Fenske equation flood Flooding condition Furn Furnace Gill Gilliland equation GT Gas turbine HK Heavy key component Kirk Kirkbride correlation lim Limiting value for a variable LK Light key component LM Logarithmic mean max Maximum condition min Minimum condition mix Mixture property OP Overall plate property OTray Overall tray property OVLDTray Overloaded or bottlenecked trays Pack Packed section Proc Distillation process PS Central power station R Residence time, Rectifying section RActual Rectifying actual trays req Required ret Retrofit design RTray Rectifying tray section S Stripping section SActual Stripping actual trays SB Souder and Brown constant shell Shell-side Steam Stripping steam STray Stripping tray section tube Tube-side
Chapter 1 Introduction
1
Chapter 1: Introduction
Crude oil distillation is a process of major importance in the refining industry. This
process is energy and capital intensive. An existing crude oil distillation unit is a
complex structure with highly interlinked columns. The crude oil distillation column has
strong connections with the associated heat recovery system, i.e. the distillation column
is integrated with the heat recovery system. The operating variables of the distillation
temperature drop, etc.) in new column design to be exploited to maximise the energy
efficiency of a refinery distillation process, based on heat integration targets (i.e. area
and energy targets obtained from pinch analysis). It was found in this work that
optimising the operating conditions of crude oil distillation column reduces the energy
target significantly for given minimum temperature approach. The shortcut models
developed in this work for grassroots design of crude oil distillation columns will be
presented in Section 2.3.
Very recently, work was carried out by Bagajewicz and co-workers on grassroots design
of crude oil distillation units, addressing various design options and extending the
design methodology and insights of Liebmann et al. (1998). Bagajewicz and Ji (2001)
present a rigorous targeting methodology to design conventional atmospheric crude
fractionation units for processing different types of crude oil (from heavy to light crude
oil) at optimal conditions. This work uses heat demand-supply diagrams, which account
for the contribution of each process stream or pump-around to the utility consumption,
as a tool guiding the design to result in the optimal condenser and pump-around duties.
Bagajewicz and Soto (2001) proposed a model to design a multipurpose heat exchanger
network to process various crude oils. This exchanger network is capable of providing
the process heat requirements for the different types of crude oils processed in the
design obtained by the method of Bagajewicz and Ji (2001).
Ji and Bagajewicz (2002a) presented a rigorous procedure to obtain cooling and heating
energy targets for grassroots design of crude oil fractionation with preflash and
prefractionator columns. This procedure is based on rigorous calculations and combined
with heat integration. The work pointed out that the optimum temperature of the flash
drum, the location of the flash vapour to the distillation column and the optimum
prefractionator feed temperature need to be studied. The work concluded that the
introduction of a preflash drum into a heat exchanger network design reduces the
number of exchanger units and reduce the utility consumption.
Ji and Bagajewicz (2002b; c) extended their previous work (2002a) to design both
conventional crude oil atmospheric towers and stripping-type distillation columns plants
with vacuum units and multipurpose heat exchanger networks. In stripping-type
Chapter 2 Literature review
10
columns, the crude oil is heated to a relative low temperature (about 150 oC) and fed at
the top of the column, and then the crude oil goes down the column and heated
consecutively in three heaters. Two design options were considered upstream of the
atmospheric tower in the design, design with a preflash drum and design with a
prefractionator column. It was found that the introduction of a vacuum tower affects the
conventional and preflash designs, and hence changes the heat distribution among the
pump-around circuits. The work results in energy targets for the different types of
column designs considered. Then, these energy targets obtained for different types of
crude oils are used to develop a multipurpose heat exchanger network that can handle
the process requirements for a range of crude oils.
The presented grassroots design methodologies for crude oil distillation systems provide
basis and insights for retrofit design situations; however, they cannot be applied directly
for such a problem. The reason is as mentioned above that the challenges and problem
nature of retrofit design are conceptually different from those of grassroots design. In
addition, most these design methods use rigorous simulations which cannot be applied
in retrofit situations to account for the complexities of an existing crude oil distillation
unit and the associated heat exchanger network. In this case, shortcut models would be
valuable. The next section summaries the existing shortcut models for grassroots design
of distillation columns, since they are relevant to the work of this thesis.
2.3. Shortcut models for design of distillation columns
Shortcut models for grassroots design of distillation columns are well established and
have been widely applied. The best known shortcut method for distillation design is the
Underwood method (Underwood, 1948). This method is based on two limiting
assumptions, constant molar overflow within each column section, and constant relative
volatilities throughout the column. It is easy to use, with only recoveries of two key
components and thermal condition of feed needing to be specified. This method is
applicable to simple conventional distillation columns, i.e. single-feed two-product
columns with a single condenser and a single reboiler. The minimum condenser and
reboiler duties and also the minimum vapour flow rates in column sections are obtained
from the calculations. The method gives good results for distillation systems with
relatively ideal mixtures. However, for multicomponent mixtures and for systems with
non-ideal vapour-liquid equilibrium behaviour, the molar overflow is not constant and
Chapter 2 Literature review
11
the relative volatilities change through the column (Seader and Henley, 1998; Suphanit,
1999). Where the underlying assumptions are not valid, the accuracy of the results will
be compromised. Even in these cases, however, the estimation of minimum vapour flow
rates is good in regions of constant composition (pinch zones) (King, 1980: p. 418;
Kister, 1992: p. 313). Some improvements (King, 1980; Nandakumar et al., 1981; Rev,
1990; Suphanit, 1999) to the Underwood method have been suggested to extend its
applicability.
Based on the Underwood equation, many researchers have proposed shortcut models for
grassroots design of non-conventional distillation columns. The Fenske-Underwood-
Gilliland (FUG) model is the most popular shortcut model for design. Petlyuk et al.
(1965) and Stupin and Lockhart (1972) used this model to analyse the energy
consumption of fully thermally coupled distillation arrangements, compared with
conventional columns. Cerda and Westerberg (1981) developed shortcut models for the
design of various complex distillation configurations. Glinos and Malone (1985)
developed a shortcut procedure for design of a distillation column with a side-stripper.
Carlberg and Westerberg (1989b) and Triantafyllou and Smith (1992) applied the
Underwood equation to a three-column model for the design and analysis of fully
thermally coupled distillation columns. Suphanit (1999) developed shortcut models for
grassroots design of distillation columns using reboilers and stripping steam. Various
complex distillation column configurations, including side-strippers and side-rectifiers
are considered. The model of Suphanit (1999) is applicable for crude oil distillation
columns.
The design model of Suphanit (1999) is presented in some details, as it is highly
relevant to the work of this thesis. This model is an improvement to the standard FUG
method. The improvements concentrate on the limiting assumptions of the FUG
method, i.e. constant molar overflow within each column section and constant relative
volatilities throughout the column. The relative volatility of each component is taken to
be the geometric mean of that at different locations in the column, i.e. top section,
bottom section and feed stage. Enthalpy balances around column sections are carried
out to accommodate the changes in vapour flow rates at both minimum and actual reflux
conditions. The modified shortcut design procedure at the minimum reflux conditions is
as follows:
Chapter 2 Literature review
12
1. Use the Underwood equation to estimate the minimum vapour flow rates at the top
and bottom pinch zones.
2. An enthalpy balance around the top section is performed to calculate the minimum
condenser duty and the minimum vapour flow rate at the top of the column. Then,
the corresponding reboiler duty is calculated by an overall enthalpy balance.
3. The minimum vapour flow rate at the bottom of the column is calculated by
enthalpy balance around the reboiler.
At the actual reflux condition, the vapour flow rate in the top section is calculated by
material balance around the condenser, assuming a reasonable value for the reflux ratio.
Then, the vapour flow rate in the bottom section is calculated by an enthalpy balance
around the reboiler.
Based on these improvements to the FUG method, Suphanit (1999) developed a
shortcut model for grassroots design of reboiled distillation columns, including different
column configurations, such as columns with side-strippers, side-rectifiers and side-
exchangers. For a given feed and required product specifications, the model calculates
the number of theoretical stages in each section, assuming a value for the reflux ratio.
The basic model equations of the shortcut model are presented for simple distillation
columns with reboilers, as follows:
The Underwood equation at the feed stage can be written as:
qx
i
ifi −=−
Σ 1,
φαα
(2.1)
The minimum vapour flow rate (Vmin) and distribution of components with volatilities
between those of the key components at the top pinch location is given by:
minVd
i
ii =−
Σφα
α (2.2)
The minimum vapour flow rate at the bottom pinch (V'min) location is then calculated as
follows:
FqVV )1(minmin −−=′ (2.3)
Chapter 2 Literature review
13
The minimum reflux (Rmin) ratio is then calculated:
1)/( min,min −= DVR top (2.4)
The Fenske equation (Fenske, 1932) is used to determine the minimum number of
stages (Nmin) at total reflux (Cited in Seader and Henley, 1998; Chapter 9):
[ ]HKLK
HKHK
LKLK
RRRR
Nαα /ln
/)1()1/(ln
min
−
−
= (2.5)
To achieve a specified separation between two key components, the actual reflux ratio
and the number of stages must be greater than their minimum values. The actual reflux
ratio is generally chosen, by economic considerations, as some multiple of minimum
reflux. The corresponding number of stages is then determined by suitable graphical
methods or by an empirical correlation. The most successful and simplest graphical
correlation for the number of stages was developed by Gilliland (1940) and slightly
modified later by Robinson and Gilliland (1950). Seader and Henley (1998) reviewed
the various equations for the Gilliland correlation and presented a comparison of
rigorous calculations with the Gilliland correlation. The Gilliland correlation relates the
number of stages to the minimum number of stages, and minimum and actual reflux
ratios. The data of this correlation are based on plant data. Molokanov et al. (1972)
represented these data by a line with the following equation:
−
++
−=+
−5.0
min 12.11711
4.541exp11 ξ
ξξξ
NNN
(2.6)
where,
1min
+−
=R
RRξ (2.7)
After calculating the total number of theoretical stages (N) inside the column, the
location of the feed stage can be identified using the empirical equation of Kirkbride
(1944) (Cited in Seader and Henley, 1998; Chapter 9):
206.02
=
dHK
bLK
fLK
fHK
S
R
xx
xx
DB
NN (2.8)
Chapter 2 Literature review
14
Following the calculations of the total number of stages and the feed location, an energy
balance is carried out to calculate the condenser and reboiler duties (Seader and Henley,
1998).
For distillation columns using stripping steam, the separation characteristics, such as
temperature profile and vaporisation mechanism, are different from those of reboiled
columns. The stage temperature in reboiled columns decreases continuously from the
reboiler to the condenser as the vapour is created in the reboiler, where the temperature
is the highest in the column. In steam-stripped columns, the vapour phase in the column
is generated in the stripping section by the reduction in the partial pressure of the liquid
caused by the stripping steam; the liquid itself supplies the heat of vaporisation. The
liquid temperature reduces from the feed stage towards the bottom of the column.
Therefore, the temperature profile of the steam-stripped columns shows a peak value at
the feed stage. Suphanit (1999) developed a shortcut model for grassroots design of
steam-stripped distillation columns. This model is applicable for simple and complex
configurations of steam-stripped distillation columns, including columns with side-
strippers, side-rectifiers, and side-exchangers. In this model, the Underwood equation
and enthalpy balance are applied to estimate the minimum vapour flow rate in each
section, and the minimum reflux ratio and the condenser duty. At actual reflux, the
vapour flow rate in the top section is calculated by material balance around the
condenser, assuming a reasonable value for the reflux ratio. An enthalpy balance around
the top section calculates the condenser duty; while an overall enthalpy balance finds
the enthalpy of the bottom product. The dew point temperature is calculated for the top
product for a partial condenser; the bubble point temperature is calculated for a total
condenser. The temperature of the bottom product is calculated by bubble point
calculation with known enthalpy. Then, the vapour flow rate at the bottom of the
column is calculated by an overall enthalpy balance.
The number of stages is calculated separately for each section of the column. In the
rectifying section, the Fenske equation is applied to determine the minimum number of
stages at total reflux condition:
[ ]HKLK
HKFSLKFS
dHKdLK
xxxx
Nαα /ln
//
ln
min
= (2.9)
Chapter 2 Literature review
15
Then, the Gilliland correlation determines the number of stages in this section.
In the stripping section, the vapour flow rate profile is non-linear. The changes in
vapour flow rate are restricted by enthalpy balance. Thus, to obtain a good prediction of
the number of stages, consecutive flash calculations are performed from the bottom
stage towards the feed stage. The number of stages is counted from the bottom stage
until the stage vapour flow rate reaches or exceeds the vapour flow rate below the feed
stage. The vapour flow rate below the feed stage is assumed to be the minimum vapour
flow rate at the bottom pinch of the column.
Although much attention has been paid to the development of shortcut models for
grassroots design of distillation columns, no shortcut models are published for retrofit
design; only rigorous models are applied in the commercial simulation packages. In all
the above design models, the number of theoretical stages, reflux ratio, heating and
cooling duties, etc. are calculated for a given set of operating conditions (e.g. column
pressure, reflux ratio, stripping steam flow rate, etc.), feed data and product
specifications. However, to carry out a retrofit study on heat-integrated distillation
systems (e.g. crude oil distillation), retrofit models are necessary to fix the existing
distillation design, i.e. column configuration, number of real stages, locations of
reboilers, condensers, side-exchangers and side-strippers.
Established rigorous models do not provide multivariable optimisation. Shortcut models
are quicker to solve, do not have convergence problems and are more robust than
rigorous models for column optimisation. In particular, shortcut models for retrofit
would be valuable for evaluating retrofit design options, to improve the performance of
an existing heat-integrated distillation system and can be combined with detailed heat
exchanger network models for optimising the overall distillation system.
Nevertheless, these grassroots design models are valuable and can be modified to be
applicable for retrofit design. In particular, the shortcut models developed by Suphanit
(1999) are significantly useful, since they overcome the underlying limitations of most
conventional models and considered both reboiled and steam-stripped distillation
columns, as is the case in crude oil distillation units.
Chapter 2 Literature review
16
2.4. Retrofit design of heat-integrated crude oil distillation systems
Research work, reports and industrial experience mainly focused on heat-integrated
crude oil distillation systems, not necessarily accounting for the existing heat recovery
systems. The heat recovery system, however, are approximated by heat integration
targets (area and energy targets) provided by pinch analysis. The opportunities for heat
recovery that may result from the consideration of the existing heat recovery system are
not analysed. Interactions between the two individual units, i.e. distillation column and
heat recovery system, are not exploited.
The previous work on heat-integrated crude oil distillation systems and their evaluation
are summarised as follows:
2.4.1. Modifications-based retrofit methods
Retrofit design of crude oil distillation columns was initially carried out based on
modifications suggested by research studies or engineering experience. These
modifications may include structural modifications to the distillation column or the heat
exchanger network and changes to the process conditions of the distillation column.
Sittig (1978) suggested a number of modifications in order to improve the energy
efficiency of distillation systems, such as:
1. Installation of new internals with higher efficiency.
2. Use of intermediate reboilers on crude oil distillation towers.
3. Selection of optimum balance between number of stages and reflux.
4. Use of tower side draws.
5. Minimisation of entrainment and optimisation of tray efficiency.
6. Use of optimum column control.
7. Reduction of column pressure.
8. Choice of best feed location and condition.
The recommendations to improve the energy efficiency are given without a proposed
Chapter 2 Literature review
17
procedure on which order and how these modifications can be applied.
Bannon and Marple (1978) recommended other column modifications for retrofit of
crude oil distillation columns. These modifications include the installation of pump-
arounds at the right location in the tower and adjusting the cooling duty for each pump-
around. The energy consumption in the associated heat recovery system is expected to
reduce. However, these modifications incur large capital investment, do not account for
the hydraulic capacity limitations of distillation columns and may require major changes
to the existing design of the exchanger network.
Harbert (1978) advised that the installation of preflash units or prefractionator columns
to existing crude oil distillation unit saves energy and allows the increase of the
throughput of the distillation unit. The location of the additional units in the preheat
train was not addressed, as well as the consequences of changing the preflash vapour
feed to the distillation column.
The increase in the production capacity of distillation unit is achieved by the installation
of additional equipment together with changing the existing distillation equipment and
the heat exchanger networks (McConnel and Royer, 1988). No detailed
recommendations or systematic design procedure were given on how the capacity can
be increased or how the exchanger network is to be modified and the capital cost
requirements.
Rivero and Anaya (1990) suggested the use of more trays in existing distillation towers
and strippers as well as the installation of a reboiler in stripping columns are suggested
for improving the performance of crude oil distillation towers. These recommendations
did not account for the physical constraints of the existing distillation towers, such as
existing diameter limitations and column space, and the large capital investment
incurred by these modifications.
Golden (1997) concluded in his research that preflash drums should be used to
debottleneck an existing crude oil distillation unit. This work concentrates on the
operational problems and troubleshooting of preflash drums. He advised that if a
preflash drum is undersized, and entrains flashed crude oil to the crude distillation
column, severe problems will occur, such as black distillate products (product
contaminants). Increasing the flash drum operating temperature can reduce the heat
Chapter 2 Literature review
18
input to the atmospheric column. Two important issues were not considered, the
optimum temperature of the preflash drum and the location of the preflash vapour to the
distillation column. However, the proposal of the proper sizing of the preflash drum is
valuable.
Although the above retrofit methods recommended process modifications for energy
saving and throughput increase, they have not provided a systematic procedure of
applying the proposed modifications or have not accounted for the capital requirements.
The capital costs of process modifications are very large (e.g. additional columns) and
impractical (e.g. more trays) in some cases without the efficient reuse of the existing
equipment. In addition, the modified distillation process may have infeasible operation
because the hydraulic capacity limitations have not been taken into account during the
retrofit design procedure. Methods that considered retrofit with preflash drums have not
addressed the issues of the location of the flash drum in the preheat train or the location
of flash vapour to the distillation column. Also, the optimum preflash operating
temperature has not been studied. None of these retrofit methods addressed the potential
of changing the operating conditions of the distillation process (e.g. feed preheating
temperature, stripping steam flow rate, pump-around flow rate and duty) for reducing
energy demand and increasing processing capacity or for other objectives, such as
reducing CO2 emissions.
Among the above retrofit design methodologies, changing the existing structure of
crude oil distillation unit has not been dealt with systematically. When a preflash drum
or a prefractionator column is added, the optimum operating temperature, the location of
the unit in the preheat train and the location of the flash drum vapour to the distillation
column need to be addressed.
However, some insights and design options can be taken into account and studied
further in retrofit design of heat-integrated crude oil distillation systems. These insights
and design options include adding a preflash drum or a prefractionator column upstream
of an existing crude oil distillation column for energy saving and throughput
enhancement. The location of preflash vapour feed and the optimum preflash
temperature can be explored for better performance. Also, the preflash drum needs to be
properly sized to avoid operational problems.
Chapter 2 Literature review
19
2.4.2. Pinch analysis-based retrofit approaches
The concept of distillation column targeting (Dhole and Linnhoff, 1993a) provides
column modifications relevant to reduction in energy demand. The column targets (Heat
loads and temperature) are based on the “Column Grand Composite Curve” (CGCC),
which determines the scope for appropriate modifications and sets the temperature
targets for these modifications. The CGCC is obtained from converged simulations.
This CGCC is then used to identify beneficial column modifications; appropriate
column process modifications are those which result in reducing energy demand and
improving the temperature-quality of heat sources. These modifications include
appropriate feed location, reflux ratio modifications, feed conditioning and using side
condensing or reboiling. The difficulty in using this design procedure is that it is based
on graphical representations and it considers only two key components as a basis for the
calculations. The proposed modifications do not account for the diameter constraints of
the distillation column or the existing stages; a large number of stages is required to
accommodate some particular modifications.
Dhole and Buckingham (1994) published a methodology for retrofit of refinery
distillation columns. In this methodology, energy saving and debottlenecking objectives
were considered. The approach uses three stages, column modifications using CGCC,
design modifications for energy saving and design modifications for debottlenecking.
Several techniques for saving energy and debottlenecking were involved in this
approach, such as (1) increasing the heat recovery in the heat exchanger network (HEN)
in order to reduce the utility consumption, which consequently may provide opportunity
for debottlenecking, and (2) revamping the utility system for higher duty and
correspondingly modify the column and the HEN for throughput increase. The
limitation of this approach is that it is a sequential approach, i.e. the column is modified,
and then the implications on the heat exchanger network are determined. When
modifications are suggested, the details of the existing exchanger network are not
considered. The hydraulic limitations of the distillation column are not accounted for;
therefore, the modified column may have bottlenecks.
Liebmann (1996) proposed a two-step (sequential) approach for grassroots and retrofit
designs of crude oil distillation systems. This approach uses pinch analysis and rigorous
simulation to analyse the existing column configuration and to propose column
Chapter 2 Literature review
20
modifications that result in reduced energy consumption and enhanced throughput
capabilities. The retrofit procedure identifies the interactions between the column
modifications and the energy targets. The retrofit procedure is divided into three levels.
Simple and inexpensive modifications are proposed first. If these modifications do not
achieve the retrofit objectives, more complex modifications with higher investment are
considered. The shortcoming of this approach is that it decomposes the problem into
two stages, i.e. the distillation column and the heat exchanger network are not
considered at the same time. In addition, the details of the heat exchanger network,
including, exchanger matches, area, heat loads, and existing structure, are not accounted
for. Therefore, the capital costs required by the HEN are not evaluated. The proposed
changes to the operating conditions are sequential and are not considered
simultaneously. The modified distillation column is different from the existing design;
this requires extensive structure modifications and huge capital costs. Some column
modifications are impractical, such as redistributing the existing number of stages and
changing the locations of the side-draws and pump-arounds. Furthermore, the modified
distillation column may have infeasible operation, because the hydraulic capacity
limitations are not taken into account.
Bagajewicz (1998) adopted and extended the approach of Liebmann (1996) for
optimising an existing crude oil distillation column based on pinch analysis principles
and rigorous model-based simulation. This approach applies for reducing energy
consumption and atmospheric emissions. Pinch analysis is used to calculate energy
target for the process conditions of the distillation column. The approach changes the
operating parameters of the distillation process to minimise energy consumption or
atmospheric emissions. This work concluded that the simultaneous consideration of the
process conditions of an existing crude oil distillation unit can reduce the minimum
utility consumption. This approach overcomes two shortcomings involved in the work
by Liebmann (1996); the approach changes the operating conditions of the distillation
column at the same time and considers the energy target simultaneously with the
distillation process. However, no capital-energy trade-off is considered in the
optimisation. In addition, the approach does not account for the details and the structure
of the existing heat exchanger network and the hydraulic capacity constraints of the
distillation column. This may lead to bottlenecked distillation column and result in
modified heat exchanger network with significant structure changes (e.g. change
Chapter 2 Literature review
21
exchanger matches, large additional areas, bottlenecked exchanger units). In addition,
the approach does not explore the benefits of changing the structure of the existing
distillation column (e.g. adding a preflash or a prefractionator) or the heat exchanger
network (e.g. integrating a gas turbine with process furnace, enhancing heat transfer) for
better energy and hydraulic performances. Only two objectives for retrofit design are
considered in this work; however, more objectives need to be addressed, such as
processing new crude oil feedstocks and changing product yields.
Group of researchers have dealt with particular retrofit problems; they proposed
modifications and applied previous approaches to specific problems to achieve certain
retrofit objective. Briones et al. (1999) considered revamping the crude oil distillation
unit of a Mexican refinery for reducing the energy consumption. A number of
modifications and suggestions, based on pinch analysis and the approach of Liebmann
(1996), were proposed, such as integrating the atmospheric and vacuum distillation
units, adding pump-arounds and using stripping steam instead of reboilers in the side-
strippers. Fraser and Sloley (2000) considered retrofit of a crude oil distillation unit to
increase the vacuum gas oil production. The revamp modifications were concentrated in
the vacuum unit and its feed preheating system. These modifications include adding
pump-arounds and reducing the operating pressure, increasing the preflash overhead
vapour, modifying the vacuum stripping section trays and optimising the flow rate of
stripping steam. These researchers (i.e. Briones et al., 1999; Fraser and Sloley, 2000)
have not provided general procedures for proposing or applying the retrofit
modifications; they rather applied previous approaches. These modifications are strictly
suitable for particular cases to which they were applied. They recommended expensive
structural modifications without exploiting the potential of changing the operating
conditions of the overall system for better performance.
It can be seen that the previous retrofit approaches have not considered the existing
distillation column and the details of the associated heat recovery system at the same
time, but in a sequential manner. Most methods suggested column modifications, which
possibly will require large capital costs without full exploitation of the existing
distillation equipment. Practical constraints, such as hydraulic limitations of the existing
distillation column or allowable pressure drop for the crude oil feed stream, have not
been taken into account. This may lead to unfeasible operational designs, i.e. hydraulic
bottleneck in the distillation column or bottleneck in the exchanger network. Many
Chapter 2 Literature review
22
approaches used rigorous simulations, which are time consuming and do not provide
multivariable optimisation. Retrofit approaches that dealt with particular cases of crude
oil distillation units cannot be generalised since they do not provide systematic
procedure for applying the proposed modifications to other cases.
2.5. Retrofit design of crude oil distillation systems
This section includes previous work on crude oil distillation systems, not necessarily
accounting for the heat integration aspects; this includes increasing capacity of
distillation columns, reducing atmospheric emissions and using heat transfer
enhancement. Liu (2000) proposed a graphical method to analyse the hydraulic
performance of an existing simple distillation column (i.e. single column with single
feed, and single reboiler and condenser) for throughput enhancement. The FUA
(fraction of utilised area) is obtained for an existing distillation column to determine the
potential for increasing the production capacity and identify modifications for
debottlenecking. This method is accompanied by guidelines to identify modifications to
increase capacity. The proposed modifications include changing the operating
conditions, changing the feed condition and using side condensers or reboilers. The
objective in this work was capacity-related and no opportunities for heat recovery were
considered. Although the retrofit tool presented by Liu (2000) is valid for simple
distillation columns and did not consider the opportunities for heat recovery, it can
systematically be extended to crude oil distillation columns, where there are varied
column diameters. Moreover, the retrofit modifications and insights given in this work
for increasing capacity and identifying column bottlenecks can still be used for crude oil
distillation units.
Smith and Delaby (1991) presented an approach for targeting flue gas emissions (i.e.
relating minimum energy consumption to emissions) from utility systems for a given
process with fixed conditions. They introduced a new term for the global accounting of
the CO2 emissions; these emissions are the sum of the emissions from the utilities on a
site together with those from outside the factory boundary. Furthermore, Delaby and
Smith (1995) proposed a design methodology to minimise the flue gas emissions.
Design options include changing fuels, changing the utility system design, process
changes, improved heat recovery and chemical treatment of flue gases. They also
presented a method which identifies the best combination of these techniques to achieve
Chapter 2 Literature review
23
a target for emissions reduction with minimum cost. The models proposed by Delaby
and co-workers are valuable to consider the atmospheric emissions aspect in retrofit of
heat-integrated crude oil distillation systems, although they did not consider any
existing design details (e.g. distillation column and HEN).
Manninen and Zhu (1999) presented a methodology for integrating a gas turbine with an
existing site to cut down the flue gas emissions and reduce the operational costs. This
methodology involves operational optimisation to achieve the best economic
performance. Also, Townsend and Linnhoff (1983a, b) and Dhole and Linnhoff (1993b)
developed graphical tools to analyse the integration of gas turbine to an existing process
and estimate the size of the gas turbine required for process requirements. On the other
hand, Chew (2001) extended previous work developed on overall refinery optimisation
to account for reducing the CO2 emissions from refineries. The work aimed at
exploiting the interactions between the major networks in a refinery, i.e. material
processing units, hydrogen network and utility system (H2, heat, power, fuel, steam), to
reduce the CO2 emissions using optimisation. These works on CO2 emissions did not
consider the details of the existing designs of the crude oil distillation column and heat
recovery system, as well as the operating conditions of the distillation column.
However, the models proposed for integrating a gas turbine by Manninen and Zhu
(1999) can be extended to retrofit design of crude oil distillation column and heat
exchanger network, where the two individual units can be considered at the same time
together with their practical constraints.
Heat transfer enhancement has proved to be useful for retrofit design of heat exchanger
networks and process integration (Polley et al., 1992). Zhu et al. (2000) developed a
targeting procedure for using heat transfer enhancement in retrofit of heat exchanger
networks This procedure determines which exchangers are suitable for using heat
transfer enhancement, what level of enhancement is required and which enhancement
technique is most suitable. By applying heat transfer enhancement to an existing
exchanger unit, additional exchanger area will become available for heat transfer; this
additional area can be estimated as follows:
existtube
shell Ahh
A
−=∆ 1
21
max (2.10)
Chapter 2 Literature review
24
Where ∆Amax is the maximum area that can be achieved by using enhancement, hshell and
htube are the shell and tube-side film heat transfer coefficients, and Aexist is the existing
exchanger area. Nie and Zhu (1999) extended the work of Zhu et al. (2000) by
considering pressure drop limitations in retrofit with heat transfer enhancement. The
motivation is that heat transfer enhancement techniques have a significant impact on
pressure drops. They developed models, based on those proposed by Polley et al.
(1990), to account for pressure drop when applying heat transfer enhancement. The
models for heat transfer enhancement can be used to consider heat transfer enhancement
as a design option in retrofit of heat-integrated crude oil distillation systems.
As seen, the design methodologies presented in this section apply only for specific
issues in retrofit design of crude oil distillation systems, including debottlenecking an
existing distillation column, reducing CO2 emissions and using heat transfer
enhancement. These methodologies do not consider the process conditions of the
distillation column simultaneously while considering the different retrofit issues or the
existing distillation process and the associated heat exchanger network simultaneously.
Nevertheless, the proposed models and retrofit insights (e.g. Polley et al., 1990; Smith
and Delaby, 1991; Nie and Zhu, 1999; Zhu et al., 2000; Liu, 2000) can be extended to
be applicable for retrofit design of the crude oil distillation unit and the heat recovery
systems simultaneously for debottlenecking existing distillation columns, reducing CO2
emissions and using heat transfer enhancement.
2.6. Retrofit design of heat recovery systems
Another group of researchers concentrated on improving the performance of the heat
recovery systems, irrespective of the background process, in this case the distillation
process. The literature is rich in methods and approaches for retrofit design of heat
exchanger networks (e.g. Linnhoff and Hindmarsh, 1983; Tjoe and Linnhoff, 1986;
Silangwa, 1986; Ciric and Floudas, 1989; Yee and Grossmann, 1991; Shokoya, 1992;
Carlsson et al., 1993; Asante and Zhu, 1997; Jos et al., 1998; Sharma et al., 1999;
Varbanov and Klemes, 2000; Zhu et al., 2000). Asante (1996) provided a
comprehensive review for most of the retrofit methods and approaches of heat
exchanger networks (HEN). We only review some of these approaches.
Chapter 2 Literature review
25
Pinch analysis principles, which were initially developed for grassroots design, were
extensively used to redesign existing heat exchanger networks for energy savings. The
most important rule of the pinch analysis is that there should not be heating (using hot
utilities) below the process pinch and no cooling (using cold utilities) above the process
pinch. A large number of researchers extended the application of pinch analysis to
retrofit situations. Tjoe and Linnhoff (1986) developed a graphical tool (i.e. graph that
relate the minimum exchanger area required for retrofit to the minimum energy
consumption) to illustrate the constant area efficiency targeting method, which is one of
the earlier retrofit approaches. Area efficiency is defined as the ratio between the
minimum area required and that actually used to achieve a specific heat recovery. This
retrofit method used the rules and guidelines defined in the pinch design method
(Linnhoff and Hindmarsh, 1983), together with some additional rules, especially those
applicable to the retrofit design task, such as it is not good retrofit design to add more
exchanger area and the associated energy demand increases or to waste the purchased
area for reducing energy demand (Tjoe, 1986). This method assumes that the area
efficiency of the retrofit network is equal to that of the existing exchanger network. The
retrofit design procedure decomposes the exchanger network retrofit problem around
the pinch. Any exchanger that lies on both sides of the pinch is removed as it conflicts
with the fundamental pinch analysis rule. The design is conducted separately for regions
above and below the pinch. Finally, introducing new units into the network as required
completes the retrofit design. These retrofit approaches (e.g. Tjoe and co-workers,
Linnhoff and co-workers) do not consider the distillation process in the retrofit design.
The process conditions of the distillation column (e.g. feed preheating temperature,
reflux ratio, pump-around flow rates, etc.) are also not exploited.
Silangwa (1986) proposed that the incremental area efficiency (i.e. the retrofit area
efficiency is greater than the original network efficiency) targeting procedure should be
used instead of constant area efficiency method in retrofit cases where the area
efficiency of the original network is very low (less than 0.6). This method assumes that
any retrofit area added to the existing network has an efficiency greater than that of the
original HEN. Similar limitations as for the above approaches are involved in this
retrofit approach. The only advantage over the previous approaches (e.g. Tjoe and co-
workers, Linnhoff and co-workers) is that the additional area has an efficiency of new
area which is rather realistic than the efficiency of the original network.
Chapter 2 Literature review
26
Recently, with advances in computers, a number of researchers directed their retrofit
research to mathematical programming methods. Retrofit design of the heat exchanger
network is modelled mathematically as an optimisation problem; the objective is to
identify the lowest retrofit design costs.
In 1989, Ciric and Floudas decomposed the HEN retrofit design problem into a two-
stage approach consisting of a match selection stage and an optimisation stage. The
match selection stage selects process stream matches, and matches exchangers for the
retrofit problem, while the optimisation stage optimises the exchanger matches. Then,
the two stages are combined into a single stage approach. The limitation of this
approach is that it is assumed that the heat recovery to be achieved is fixed by
experience and hence there is no method proposed to initialise the heat recovery to be
achieved. In addition, the repiping cost is independent of the stream involved. There is
no user interaction to select from the proposed modifications or to impose practical
constraints.
Asante and Zhu (1997) introduced a new powerful approach for retrofit design of heat
exchanger networks. This approach combines the strength of both the mathematical
optimisation techniques with thermodynamic analysis and practical engineering. This
retrofit approach is built based on the observation that certain exchanger matches
thermodynamically limit the heat recovery in an existing exchanger network. The new
method uses a two-stage approach to HEN retrofit, a diagnosis stage and an
optimisation stage. The first stage selects a minimum number of promising HEN
topology modifications, which achieve the required heat recovery target. In the second
stage, the modified network is optimised (i.e. redistributing heat loads) using non-linear
optimisation techniques to minimise the cost of additional exchanger area.
The approach of Asante and Zhu (1997) defines concepts in retrofit of heat exchanger
network, which are network pinch and pinching matches. The pinching matches are
exchanger matches for which the temperature approach between the hot and cold
streams tends towards a limiting value as the heat recovery in the HEN increases; these
matches act as a bottleneck to the heat recovery. The pinching matches identify the
locations of the network pinch or the bottlenecks of the existing heat exchanger
network. To increase the heat recovery beyond the limits caused by the pinching
Chapter 2 Literature review
27
matches, the network topology must be changed by relocating existing exchanger units,
adding new matches or creating stream splits.
Network pinch analysis can be applied to retrofit a heat exchanger network for energy
saving or capacity increase. The application starts with fixing the structure of the
existing heat exchanger network. Then, the pinching matches are identified and the
network pinch is located. The retrofit approach then proposes a set of structural
modifications which overcome the bottlenecks caused by pinching matches. These
modifications incur minimum capital expenditure for maximum energy savings.
The significance of network pinch approach is that it provides alternative design options
for the same level of energy saving. These modifications can be screened according to
any practical limitations or constraints involved in the existing HEN. It also allows a
user interaction, so that any retrofit decision can be examined.
Other researchers worked on retrofit of particular heat exchanger networks associated
with existing crude oil distillation columns by applying previous approaches and using
new techniques, such as heat transfer enhancement. Examples of these research results
are given by Jos et al. (1998), Sharma et al. (1999), Klemes and Varbanov (2000), and
Zhu et al. (2000).
The common feature between most retrofit methods of heat recovery systems is that
these methods did not consider the background process (distillation process) in the
overall retrofit procedure, and assumed fixed process conditions for the distillation unit.
Therefore, the interactions between the distillation process and the associated heat
recovery systems are not exploited. These interactions and process conditions have
proven useful for increasing heat recovery opportunities in previous research on heat-
integrated crude oil distillation systems. Nevertheless, some of the reviewed
approaches, in particular network pinch (Asante and Zhu (1997) can be used in the
overall retrofit of heat-integrated crude oil distillation systems.
2.7. Concluding remarks
It can be seen that although various approaches and design methodologies have been
proposed for retrofit design of crude oil distillation units and heat recovery systems,
there is still no simultaneous approach that can address the two individual unit
Chapter 2 Literature review
28
operations. The literature shows that exploiting the operating conditions of the existing
crude oil distillation columns can improve heat recovery opportunities. Modifying the
existing structure (e.g. adding a preflash or a prefractionator, integrating a gas turbine,
etc.) of the crude oil distillation units can reduce energy demand, allow processing more
throughout and reduce atmospheric emissions. Also, many shortcut models have been
proposed for grassroots design of distillation columns. The limitations of the presented
approaches and design models can be then summarised as follows:
1. No shortcut models are published for retrofit design of distillation columns.
2. The details of the existing heat recovery system are not considered simultaneously
with the crude oil distillation column.
3. The existing equipment constraints and process limitations, such as distillation
hydraulic capacity, pressure drop in heat recovery system and bottlenecked
exchanger units, are not accounted for during optimisation in the simultaneous
retrofit approaches.
4. The process conditions (operating parameters) of the crude oil distillation column
and the design options (e.g. adding preflash, prefractionator and gas turbine units,
modifying existing column and heat exchanger network internals) are not considered
at the same time.
5. Retrofit column modifications (e.g. more trays, new pump-arounds, new columns,
etc.) require large capital expenditure and may require severe changes to the existing
column design.
6. Optimum results from retrofit approaches (e.g. Liebmann and co-workers,
Bagajewicz and co-workers) may lead to an infeasible (hydraulically bottlenecked)
column operation.
7. Only a few retrofit objectives are tackled. However, many other retrofit purposes are
industrially relevant, including improving profit, changing product yields and
processing new crude oil feedstocks.
8. No systematic method is available for retrofit with structural modifications to
existing crude oil distillation units. These modifications may include adding preflash
Chapter 2 Literature review
29
drums or prefractionator columns, replacing column internals with packing,
integrating a gas turbine and enhancing exchanger tubes.
The above shortcomings of established retrofit design methods and the perceived needs
of industry motivate the present work and form the fundamental goal of this study.
Consequently, the principal aim is to develop a new approach for retrofit design of heat-
integrated crude oil distillation systems. The need for shortcut models for retrofit design
of distillation columns is addressed; these models need to be applicable for crude oil
distillation units. The retrofit approach needs to consider the distillation column
simultaneously with the details of the existing heat recovery system. It is essential to
consider all operating conditions of distillation unit simultaneously. Furthermore, the
design methodology has to account for existing equipment and process limitations.
Various retrofit objectives need to be addressed and preferably achieved with reduced
operating costs and minimum capital expenses. The retrofit approach needs to consider
structural modifications and design options in a systematic way.
Chapter 3 Shortcut models for retrofit design of distillation columns
30
Chapter 3: Shortcut models for retrofit design of distillation columns
In this chapter, new shortcut models are developed for retrofit design of distillation
columns, including both reboiled and steam-stripped columns. The models are primarily
based on those models developed by Suphanit (1999), for grassroots design of
distillation columns. The retrofit shortcut models will be presented firstly for simple
distillation columns, and then followed by models for sequences of simple columns and
various configurations of complex distillation columns, such as columns with side-
strippers, side-rectifiers, and prefractionators. Illustrative examples are presented for
various distillation configurations, showing a comparison of the results with those of
existing rigorous models
3.1. Introduction
Distillation is certainly the most widely used separation technology. However, it is
energy and capital intensive. Distillation generally requires heat to carry out separation.
Reboilers provide this heat to distillation processes in most industrial applications, such
as petrochemicals, naphtha fractionation, etc. Other distillation applications, such as
crude oil distillation, use live steam to supply the required heat.
Industrial distillation applications use various column configurations. These
configurations vary from simple to complex column sequences. For crude oil
distillation, the conventional complex column configuration that is extensively used is a
main tower with a set of side-strippers and pump-arounds. Other column configurations
also exist, such as a progressive distillation sequence. Progressive distillation is a recent
energy-efficient development, and was first installed at Mider refinery, Leuna,
Germany. It consists of a main tower with a side-stripper, and uses two successive
prefractionators (Rhode, 1997).
Retrofit projects of these distillation column configurations aim to reuse the existing
equipment more efficiently in order to increase the profit. To carry out a retrofit study
on a given distillation column, retrofit models are necessary to fix the existing
distillation design. Shortcut models are well established for grassroots design of
distillation columns and have been broadly applied. However, no shortcut models are
Chapter 3 Shortcut models for retrofit design of distillation columns
31
published for retrofit; only rigorous models are applied in the commercial simulation
packages. Established rigorous models are time consuming and have convergence
problems. Furthermore, they fail to consider all design parameters simultaneously in the
optimisation of heat integrated distillation columns. In contrast, shortcut models are
quicker to solve, do not have significant convergence problems, and are more robust
than rigorous models for column optimisation. In particular, shortcut models for retrofit
would be valuable for evaluating retrofit design options, for improving the performance
of existing distillation systems (distillation columns and heat recovery systems).
Furthermore, shortcut models can be combined with detailed heat exchanger network
models for optimising existing heat-integrated distillation processes, as will be seen in
Chapters 4 and 5.
3.2. Retrofit models for design of reboiled distillation columns
In this section, shortcut models for retrofit design of reboiled distillation columns are
developed. These models are an extension of those for grassroots design (Suphanit,
1999) that are presented in Chapter 2. The retrofit models account for the change in the
molar overflow and relative volatilities throughout the distillation column. The relative
volatility of each component is calculated as the geometric mean of that at different
locations in the column, while the constant molar overflow is corrected by enthalpy
balances around the column sections. Initially, a shortcut model is developed for retrofit
design of simple distillation columns. Thereafter, a retrofit model is proposed for design
of complex distillation configurations. The section also presents a number of examples
to illustrate the applications of the retrofit models, and to validate these models for
applications in the design of distillation columns using reboilers.
3.2.1. Retrofit shortcut model for simple reboiled distillation columns
For retrofit design of simple distillation columns with reboilers, a shortcut model is
developed. The basic model equations for grassroots design are rewritten for existing
simple distillation columns with reboilers. Then, these equations are solved
simultaneously with the material balance equations in order to calculate the product
compositions and flow rates for a fixed number of existing stages and given operating
conditions.
Chapter 3 Shortcut models for retrofit design of distillation columns
32
Figure 3.1 shows an existing simple distillation column with a reboiler; the number of
stages in the top and bottom sections is NR and NS respectively.
Figure 3.1: Simple distillation column with reboiler
Material balances are carried out around the column for the light and heavy key
components. Light key (LK) component material balance results in:
( ) BxRFx bLKLKfLK =−1 (3.1)
( )B
RFxx LKfLK
bLK
−=
1 (3.2)
Heavy key (HK) component material balance gives the following equations:
( ) DxRFx dHKHKfHK =−1 (3.3)
( )D
RFxx HKfHK
dHK
−=
1 (3.4)
For an existing simple distillation column with a reboiler, the Fenske equation is
rewritten in a new form in order to give the recovery of the key components as a
function of the minimum number of stages, as follows:
FenskHK
HK
LK
LK
RR
RR
φ=
−
− 11
(3.5)
where
Feed
Top product
Bottom product
NR
NS
Chapter 3 Shortcut models for retrofit design of distillation columns
33
minN
HK
LKFensk
=
αα
φ (3.6)
The relative volatilities of the key components, which are substituted in equation 3.6,
are calculated as the geometric mean of the values at the top and bottom of the column
and the feed stage. The compositions of these streams are given as a function of the
component recoveries.
From the existing total number of stages inside the distillation column and for given
operating conditions, the minimum number of stages Nmin, that is required to calculate
the term φFensk is calculated from a new form of the Gilliland correlation, as follows:
( ) GillGillNN ψψ −−= 1min (3.7)
where
−
++
−= 5.0
12.11711
4.541exp1ξξ
ξξψ Gill (3.8)
1min
+−
=R
RRξ (3.9)
The number of theoretical stages N in equation 3.7 is related to the actual total number
of stages in the distillation column NActual by the overall tray efficiency, as given by:
ActualOTray NN η= (3.10)
The tray efficiency is provided from the design data available for the distillation
column. However, when no data are available the efficiency can be calculated from
correlations found in many textbooks such as Seader and Henley (1998), Peters and
Timmerhaus (1980), and Kister (1992). Note that in the examples presented in this
chapter, the tray efficiency is set to 100%.
In the calculation of the minimum reflux, the change in the vapour flow rate in the
column is accounted for by applying the procedure of Suphanit (1999). So, the
Underwood equation estimates the minimum vapour flow rates at the top and bottom
pinch zones (King, 1980: p. 418; Kister, 1992: p. 313). Then, by enthalpy balances
Chapter 3 Shortcut models for retrofit design of distillation columns
34
around the column sections, the minimum vapour flow rates at the top and the bottom of
the column are obtained.
Equations 3.7, 3.8 and 3.9 were developed by Molokanov et al. (1972) to represent the
data of the Gilliland correlation. Although Molokanov equation is not the only equation
that describes the Gilliland correlation, it is a good representation of the Gilliland data
including very low values of ξ (King, 1980; p. 430). However, any other suitable
equations can be substituted. These equations may include those of Eduljee (King,
1980; p. 428), Erbar and Maddox (King, 1980; p. 430) and Robinson and Gilliland
(1950; p. 347-350).
Eduljee (1975) proposed a similar equation to represent the Gilliland correlation, as
follows:
5668.0min
1min75.075.0
1
+−
−=+
−R
RRN
NN (3.11)
The latter equation is not an accurate representation of the Gilliland correlation for all
operating conditions, as it does not fulfil the minimum condition since it results in N >
Nmin, as R ≈ Rmin (King, 1980).
The Kirkbride correlation is rearranged for an existing simple distillation column, with
known number of existing stages in each column section. The new form gives the ratio
of the product compositions of key components, as a function of the number of existing
stages in each section.
854.42
=
S
R
fLK
fHK
dHK
bLK
NN
xx
DB
xx
(3.12)
Similarly, the numbers of theoretical stages in the rectifying and stripping sections are
related to the existing stages in each section, as follows:
RActualRTrayR NN η= (3.13)
SActualSTrayS NN η= (3.14)
Dividing equation 3.2 by equation 3.4, the ratio of the key component mole fractions
can be obtained:
Chapter 3 Shortcut models for retrofit design of distillation columns
35
−−
=
HK
LK
fHK
fLK
dHK
bLK
RR
BD
xx
xx
11
(3.15)
By substituting equation 3.15 into equation 3.12, the recovery of the key components
can be related to the number of existing stages in each section:
KirkHK
LK
RR
φ=−−
11 (3.16)
where
427.22/1
=
S
R
fLK
fHKKirk N
Nxx
DBφ (3.17)
Equation 3.16 fixes the split of the two key components for existing distillation columns
with given number of stages in each section. The term, φKirk can be calculated for the
existing distillation column, where the number of existing stages in each section is given
and the top and bottom product molar flow rates and the mole fractions of the key
components are known.
Equation 3.16 is rearranged in order to be solved with equation 3.5:
( ) KirkHKLK RR φ−=− 11 (3.18)
( ) KirkHKLK RR φ−−= 11 (3.19)
( )( ) KirkHK
KirkHK
LK
LK
RR
RR
φφ
−−−
=− 1
111
(3.20)
Then, equation 3.5 is rearranged as follows:
−
=−
FenskLK
LK
HK
HK
RR
RR
φ1
11 (3.21)
Equations 3.20 and 3.21 are solved simultaneously to calculate the recovery of the
heavy key component as follows:
( )( ) FenskHKKirk
HKKirk
HK
HK
RR
RR
φφφ 1
1111−−−
=− (3.22)
Chapter 3 Shortcut models for retrofit design of distillation columns
36
( ) ( ) 01111 2 =−−+−FenskKirk
HK
FenskHKHKHK
RRRRφφφ
(3.23)
( ) ( ) 01111111 2 =−
+−+
−−
KirkFenskKirkFenskFenskHK
FenskHK RR
φφφφφφ (3.24)
Equation 3.24 is quadratic, in one unknown, RHK, as a function of various constants. The
equation is rearranged to the form: aX2 + bX + c = 0, where X = 1 - RHK. The constants
a, b and c can be extracted from equation 3.24. The two roots of the quadratic equation
area
acbbX2
42
1−+−
= , a
acbbX2
42
2−−−
= . Since the recovery of the heavy key
component, RHK must be positive and less than unity, the variable X must be positive.
Therefore, only the positive root of the solution is acceptable.
Thus, the solution to equation 3.24 is:
( )( ) ( )
( )( )12
11
114
1 1FenskKirk
Kirk
1/2
FenskKirk
2
FenskKirk
Kirk
−+
+
−+
−
+−=
φφφ
φφφφφ
HKR (3.25)
This equation calculates the recovery of the heavy key component, given the values of
the terms φKirk and φFensk. Then, the recovery of the light key component can be
estimated from equations 3.19 and 3.25, as follows:
( )( ) ( )
( )( )12
1114
1 1Fensk
Kirk
1/2
Fensk
Kirk
2
Fensk
Kirk
−+
+
−+
−+
−=φφ
φφ
φφ
LKR (3.26)
After calculating the key component recoveries, the product key compositions (mole
fractions) can be calculated from equations 3.2 and 3.4, and hence the key component
flow rates. On the other hand, the recoveries of the non-key components are calculated
as follows:
1. For the components lighter than the light key, they are assumed to appear
completely in the distillate and at zero mole fractions in the bottom product.
Similarly, the components heavier than the heavy key appear completely in the
bottom product and at zero mole fractions in the distillate (King, 1980; p. 325).
Chapter 3 Shortcut models for retrofit design of distillation columns
37
2. The Underwood equation is used to determine the distribution of non-key
components with volatilities between those of the key components in the top and
bottom sections at minimum reflux.
3. After calculating the minimum number of stages Nmin, the Fenske equation is
used in another form to calculate the distribution of intermediate-boiling non-
key components at total reflux as follows (King, 1980; p. 426):
( ) ( )minN
HK
iHKi DRDR
=
αα
(3.27)
Where (DR)i is defined as the distribution ratio of component i and is equal to the ratio
of the recovery of the component i between the top and bottom products. The
distribution ratio of the heavy key component can be obtained, providing the recovery to
the top and bottom products obtained previously.
4. Then, the distribution of the non-key components for the given operating
condition can be obtained by linear interpolation between their distributions at
minimum and total reflux as suggested by Treybal (1979) and King (1980; p.
434) (Suphanit, 1999). The recovery of non-key components can then be
calculated from the distributions.
5. The mole fractions of the non-key components in the top and bottom products
can then be calculated from similar relationships to those in equations 3.2 and
3.4, for the calculated recoveries from the previous steps. Hence, the non-key
components flow rates are then calculated.
The temperatures of the products are calculated by carrying out bubble and dew point
calculations. Then, an enthalpy balance around the various column sections calculates
the condenser and reboiler duties.
The retrofit shortcut model for simple reboiled distillation columns is represented
through the equations 3.6 to 3.10, 3.13, 3.14, 3.17, and 3.25 to 3.27.
In the application of the shortcut model for retrofit design of simple reboiled distillation
columns, the model equations mentioned above are solved simultaneously. Note that
equation 3.17 requires initial values for the key component recoveries to initialise the
calculations of the top and bottom product flow rates required in the calculation of the
Chapter 3 Shortcut models for retrofit design of distillation columns
38
term φKirk. The product flow rates are obtained for the initial recovery values by
applying the grassroots shortcut model of Suphanit (1999). The input data to the retrofit
model are the feed specifications (i.e. flow rate, temperature, pressure, composition),
and the number of existing stages in each section, as well as the operating conditions
(i.e. reflux ratio, column temperature, column pressure). The model output includes the
product compositions, temperatures and flow rates, and the heat duties of the condensers
and reboilers. The procedure of applying the retrofit shortcut model in simulations of
existing simple distillation columns with reboilers can be outlined as follows:
1. The feed composition, flow rate, temperature and pressure are specified. An
initial value is provided for the key component recoveries in the products.
2. The number of existing stages in the top and bottom sections is fixed.
3. The retrofit model calculates the product compositions (key and non-key
component mole fractions) and flow rates, for given operating conditions
including reflux ratio, and column pressure and temperature.
4. Bubble and dew point calculations determine the product temperatures.
5. Enthalpy balances calculate the condensing and reboiling duties.
The retrofit shortcut model is also applicable for design of sequences of simple
distillation columns with reboilers, including those shown in Figure 3.2. These
sequences may also include the combination of direct and indirect simple column
configurations. These column configurations are used to separate one feed mixture into
more than two products. As seen in these configurations, the simple columns are
connected in direct or indirect sequences. The connection between columns in the
indirect configurations is the top product streams of the upstream columns. In the direct
configurations, this connection is the bottom product streams of the upstream columns.
In these configurations, the downstream columns have no direct or indirect influence on
the upstream columns. Therefore, the retrofit shortcut model can be applied directly and
sequentially to each simple column in the sequences, starting with the first columns.
Thus, the sequence configurations and the number of stages in each section of each
column are fixed. The model calculates the product compositions, temperatures and
flow rates and the various duties of the condensers and reboilers, for given operating
conditions.
Chapter 3 Shortcut models for retrofit design of distillation columns
39
(a) Indirect sequence (b) Direct sequence
Figure 3.2: Sequences of two simple reboiled distillation columns
3.2.1.1. Degrees of freedom for simple reboiled distillation columns
To design a reboiled distillation column, four independent variables must be set, after
the feed and column pressure have been specified (King, 1980; p. 793). Therefore, to
describe a distillation problem, four degrees of freedom are available. The variables,
which might be used, are those listed in Table 3.1. However, any or all of the four listed
variables could be replaced with other independent variables in which we are more
interested. When using the retrofit shortcut models in design, the independent variables
that need to be set reduce to three. This results from the fact that the ratio between the
key component recoveries is specified by the Kirkbride correlation and is given as
equation 3.13. Thus, this relationship indirectly sets the fourth independent variable.
Table 3.1: Typical degrees of freedom for design of reboiled distillation columns
Rigorous model Retrofit shortcut model 1 Number of stages in top section Number of stages in top section 2 Number of stages in bottom section Number of stages in bottom section 3 Reflux ratio Reflux ratio 4 Distillate flow rate RLK/RHK = f (NR, NS) (equation 3.16)
3.2.1.2. Illustrative example – a simple reboiled distillation column
An existing simple reboiled distillation column separates a mixture of aromatic
hydrocarbons into two products. The feed mixture data and column specifications are
given in Table 3.2. The task of the distillation column is to separate the benzene from
Chapter 3 Shortcut models for retrofit design of distillation columns
40
toluene with 99% recovery of both components. The physical and thermodynamic
properties of feed and the product streams are calculated by the Peng Robinson model.
HYSYS simulation program (HYSYS, 1999) is used to provide results from a rigorous
model for comparison to validate the retrofit shortcut model results. A reflux ratio of
2.082 is calculated in HYSYS simulation to separate the given feed mixture in the
existing distillation column into the top product with the required specifications, i.e.
99% recovery of benzene to top product and 99% recovery of toluene to bottom
product. A hundred stages are used to calculate the minimum reflux ratio in the rigorous
3. The retrofit shortcut model for simple reboiled distillation columns is directly
applied to column 1. The top and bottom product flow rates, compositions and
flow rates are calculated, as well as the condensing and reboiling duties. The top
and bottom product streams feed columns 2 and 3 respectively.
4. Then, the same retrofit model is applied to columns 2 and 3 simultaneously. A
middle key component needs to be specified for the product specifications at the
bottom of column 2 and at the top of column 3, in addition to the normal key
components for the top and bottom products.
5. Since the bottom section of column 2 is connected to the top section of column 3
in the real main column, a vapour flow constraint is therefore necessary in the
design using the three-column model. In this case, the vapour flow rate in the
bottom section of column 2 and that in the top section of column 3 are set to be
equal (Suphanit, 1999).
6. Finally, the retrofit model results in the top, bottom and middle product flow
rates, temperatures and compositions, and the various heat duties, for a fixed
number of stages and given operating conditions.
The retrofit model for Petlyuk columns is similar to that for columns with
prefractionators. In this case, the retrofit shortcut model for thermally coupled
sequences is applied simultaneously to the three columns of the equivalent three-column
configuration. The same vapour flow constraint is applied. Eleven degrees of freedom
exist for design of Petlyuk columns; six for the existing stages; one for the reflux ratio;
three for the ratio RLK/RHK = f (NR, NS) in each column.
Chapter 3 Shortcut models for retrofit design of distillation columns
53
It is also possible that side-exchangers can be installed at the top and bottom of the
prefractionator column. The resulting column configuration represents the condition
between columns with prefractionators and Petlyuk columns. In this case, the retrofit
model includes those retrofit models for partially thermally coupled sequences. The
degrees of freedom in this case increase to fifteen; by adding four degrees of freedom (2
variables × 2 side-exchangers) to the eleven for Petlyuk columns.
3.2.2.6. Illustrative example – a reboiled distillation column with a prefractionator
An existing complex distillation column using a prefractionator (see Figure 3.7(a)) is
used to separate the feed mixture given in Table 3.2, into three products. The existing
stages for the prefractionator and main column, the key component recoveries and the
operating conditions are given in Table 3.8. The Peng Robinson model calculates the
physical and thermodynamic properties of the feed and all product streams.
Table 3.8: Data for column with a prefractionator
Parameter Prefractionator Main column Stages in top section 11 12 Stages in bottom section 11 24 Stages in top of middle section 8 Stages in bottom of middle section 18 Top recovery of benzene (%) 99.5 99.0 Bottom recovery of ethyl benzene (%) 99.5 99.0 Middle recovery of toluene (%) 99.0 Column pressure (bar) 2.0 2.0 Reflux ratio 1.243 3.904
The existing distillation unit is simulated using both the retrofit shortcut model and
rigorous model simulation (HYSYS). The simulation results of both models are
summarised in Table 3.9.
One can observe that the results of the retrofit shortcut model compare very well with
those obtained from the rigorous simulation.
3.2.3. Summary
Retrofit models have been developed for designing reboiled distillation columns. The
models apply to various column configurations; many column configurations are
considered. The column configurations include simple columns, sequences of simple
columns, columns with side-strippers and side-rectifiers, columns with side-exchangers,
Chapter 3 Shortcut models for retrofit design of distillation columns
54
columns with prefractionators and Petlyuk columns. These retrofit models account for
the change in molar overflow and relative volatilities through the distillation columns.
In all applications, the retrofit model calculates the product stream flow rates,
temperature and compositions, and the various heating and cooling duties, for a fixed
column configuration and stages, and given operating conditions. Very good agreement
is observed between the retrofit shortcut models and the rigorous simulation results for
well-behaved mixtures of hydrocarbons. The applicability of the shortcut models is
restricted to well-behaved systems.
Table 3.9: Results for column with prefractionator
Parameter Rigorous model
Retrofit shortcut model
Prefractionator column Top recovery of benzene (%) 99.5* 99.8 Bottom recovery of ethyl benzene (%) 99.5* 99.8 Condenser duty (kW) 2527 2466 Reboiler duty (kW) 4945 4855 Reflux ratio 1.243 1.243* Main column Top recovery of benzene (%) 99.0* 99.7 Middle recovery of toluene (%) 99.0* 99.6 Bottom recovery of ethyl benzene (%) 99.0* 99.5 Reflux ratio 3.904 3.904* Condenser duty (kW) 7915 7974 Reboiler duty (kW) 6009 6106 Top product flow (kmol/h) 198.1 198.6 Top product temperature (oC) 104.3 104.3 Middle product flow (kmol/h) 102.6 100.7 Middle product temperature (oC) 135.7 136.1 Bottom product flow (kmol/h) 399.4 399.8 Bottom product temperature (oC) 166.7 166.8
*: specified
3.3. Retrofit models for design of steam-stripped distillation columns
Some distillation applications, including crude oil distillation, use stripping steam as a
vaporisation mechanism. Live steam is injected directly into the bottom of the column
as a stripping agent. Steam is condensed in the condenser and can be separated from
liquid hydrocarbons at the top of the crude oil column because it is immiscible with
most hydrocarbons.
Chapter 3 Shortcut models for retrofit design of distillation columns
55
As discussed in Chapter 2 (Section 2.3), the separation characteristics of steam-stripped
columns, such as temperature profile and vaporisation mechanism, are different from
those of reboiled column. Therefore, the retrofit shortcut models for reboiled distillation
columns cannot be applied directly to steam-stripped distillation columns.
In this section, shortcut models are developed for retrofit design of steam-stripped
distillation columns, based on the grassroots models of Suphanit (1999). The new
retrofit models overcome the main drawbacks of the standard FUG method; constant
molar overflows and relative volatilities. The relative volatility of each component is the
geometric mean of the values at the top section, bottom section and the feed stage.
Enthalpy balances around column sections are performed to correct the constant vapour
flow rates at both minimum and actual reflux conditions. Firstly, a retrofit shortcut
model for simple distillation columns is built. Then, retrofit models are proposed for
different complex configurations of steam-stripped distillation columns. Illustrative
examples are also presented to show the application of the retrofit models, and to
validate these models for the design of steam-stripped distillation columns.
3.3.1. Retrofit shortcut model for simple steam-stripped distillation columns
In simple steam-stripped distillation columns, the column is divided into two sections,
the rectifying and stripping sections, as shown in Figure 3.9. The retrofit modelling for
such columns is carried out separately for each column section. For the rectifying
section with a given number of stages, solving new forms of the basic equations of the
grassroots model, simultaneously with material balance equations, builds the retrofit
shortcut model.
A material balance is carried out around the column for the light key component,
resulting in:
DxFRx dLKLKfLK = (3.28)
DFRx
x LKfLKdLK = (3.29)
Chapter 3 Shortcut models for retrofit design of distillation columns
56
Figure 3.9: Simple distillation column using stripping steam
The Fenske equation is rewritten for an existing distillation column to give the
composition of the key components in the distillate as a function of the minimum
number of stages, as follows:
SteamdHK
dLK
xx
ϕ= (3.30)
where
minN
HK
LK
HKFS
LKFSSteam x
x
=
αα
ϕ (3.31)
To account for the change in the volatility, the volatility of the key components is
calculated as the geometric mean of the values at the top and bottom of the column and
the feed stage.
The minimum number of stages in the rectifying section can be calculated from the
Gilliland correlation represented by the equation of Molokanov et al. (1972), given the
existing number of stages and operating conditions:
( ) GillGillRNN ψψ −−= 1min (3.32)
where
−
++
−= 5.0
12.11711
4.541exp1ξξ
ξξψ Gill (3.33)
Top product
Bottom product
NR
NS Steam
Water
Feed
Chapter 3 Shortcut models for retrofit design of distillation columns
57
1min
+−
=R
RRξ (3.34)
The number of theoretical stages in the rectifying section NR is obtained from the actual
stages in that section by a similar relationship to that in equation 3.13.
As mentioned previously, the vapour flow rate is not constant throughout the column,
especially for multicomponent systems. Thus, to account for this aspect, the procedure
of Suphanit (1999) is applied. The vapour flow rates at the top and bottom pinch zones
are calculated by the Underwood equation for multicomponent systems as suggested by
King (1980). Then, the vapour flow rate at the top of the column is calculated by
enthalpy balance around the top section. Thus, the minimum reflux ratio required in
equation 3.31 can be calculated.
By solving equations 3.29 and 3.30, the recovery of the light key component can be
calculated as a function of the existing stages in the rectifying section and the bottom
composition:
FxDx
RfLK
SteamdHKLK
ϕ= (3.35)
The retrofit shortcut model for the rectifying sections is represented through equations
3.31 to 3.35. The model calculates the recovery of the light key component for a given
number of existing stages in the rectifying section.
For the stripping section, the retrofit model is based on the consecutive flash
calculations presented in Chapter 2 (Section 2.3). The retrofit model is shown in Figure
3.10; it determines the bottom product composition for a given number of stages in the
stripping section and steam flow rate. The model calculation starts by assuming a
bottom product composition, in terms of a heavy key component recovery. Then, in an
iterative procedure, consecutive flash calculations are carried out from the bottom stage
towards the feed stage. In each step, the number of stages is counted from the bottom
stage to the feed stage. Then, the bottom product composition, which is related to the
heavy key component recovery, is updated through a linear relation with the previous
bottom composition. The new recovery value of the heavy key component is equal to
the old value of the heavy key component recovery minus a recovery difference. This
recovery difference is directly proportional to the ratio of the difference of the existing
Chapter 3 Shortcut models for retrofit design of distillation columns
58
number of stages and the current number of stages to the difference of the current
number of stages and the number of stages from the previous iteration. At the first
iteration, the recovery difference is assumed to be small value. The iterations terminate
when the calculated number of stages and existing number of stages are identical.
Hence, the correct bottom product composition is obtained.
Figure 3.10: Retrofit algorithm for stripping sections
The retrofit shortcut models for the rectifying and stripping sections comprise the model
for simple steam-stripped distillation columns. The model for the rectifying section
determines the light key component recovery, while the retrofit algorithm for the
stripping section calculates the recovery of the heavy key component. Thus, the
distribution of the key components (flow rates) in the distillate and bottom products can
be determined. On the other hand, the distribution of the non-key components is
calculated as follows:
1. For the components lighter than the light key, they are assumed to appear
completely in the distillate and at zero mole fractions in the bottom product.
Similarly, the components heavier than the heavy key are to appear completely
in the bottom product and at zero mole fractions in the distillate (King, 1980; p.
325).
Assume bottom composition
Carry out consecutive flash calculations from bottom stage towards feed stage
Number of stages is counted until stage vapour flow ≥ vapour below feed stage
Existing stages (NS) εNN SS ≤−′
Correct bottom composition
Yes
No
Update new bottom composition
Chapter 3 Shortcut models for retrofit design of distillation columns
59
2. The Underwood equation is applied to calculate the distribution of intermediate-
boiling non-key components in the top and bottom sections at minimum reflux.
3. After calculating the minimum number of stages Nmin in equations 3.32 to 3.34,
the Fenske equation is used to calculate the distribution of intermediate-boiling
non-key components at total reflux (King, 1980; p. 426).
4. Then, the distribution of the non-key components for the given operating
condition can be obtained by linear interpolation between their distributions at
minimum and total reflux as suggested by Treybal (1979) and King (1980; p.
434) (Suphanit, 1999). Thus, the recovery of the non-key components can then
be calculated from their distributions.
5. The mole fractions of the non-key components in the top and bottom products
can then be calculated from similar relationships to those in equations 3.2 and
3.4, for the calculated recoveries from the previous steps. Hence, the non-key
components flow rates are then calculated.
The temperature of the distillate is calculated by carrying out bubble and dew point
calculations. The temperature of the bottom product is calculated by performing
enthalpy balance. Then, an enthalpy balance around the condenser calculates the
condenser duty.
In the application of the retrofit model, the shortcut model for rectifying section is
solved simultaneously with that for stripping sections. Overall, the model fixes the
number of stages in each section and, for the given operating conditions and steam flow
rate, it calculates the product stream flow rates, temperatures and compositions, and the
condenser duty.
(a) Indirect sequence (b) Direct sequence
Figure 3.11: Sequences of direct and indirect simple steam-stripped distillation columns
Chapter 3 Shortcut models for retrofit design of distillation columns
60
The same retrofit model is applicable for sequences of simple steam-stripped columns
(e.g. Figure 3.11). As shown, the link between each pair of columns in the indirect
sequence is the top product stream from the upstream column to the downstream
column. In the direct sequence, the bottom product from the upstream column feeds the
downstream column. These configurations consist of simple columns connected with no
thermal coupling. Thus, the retrofit model for simple steam-stripped columns is applied
directly and sequentially to each simple column in these configurations, starting with
the first column.
3.3.1.1. Degrees of freedom for simple steam-stripped distillation columns
In the design of steam-stripped distillation columns, there are four degrees of freedom,
as for reboiled distillation columns. Thus in the design of such columns, four
independent design variables need to be specified. Table 3.10 lists examples of these
design variables for both the rigorous and shortcut models. The listed variables can be
replaced by any other design variables of interest.
Table 3.10: Typical degrees of freedom for steam-stripped distillation columns
Rigorous model Retrofit shortcut model 1 Number of stages in top section Number of stages in top section 2 Number of stages in bottom section Number of stages in bottom section 3 Reflux ratio Reflux ratio 4 Steam flow rate Steam flow rate
3.3.1.2. Illustrative example – a simple steam-stripped distillation column
An equimolar C8-C23 mixture of normal paraffins is separated into two products by a
simple distillation column using stripping steam. The feed data and column
specifications are given in Table 3.11. Superheated steam at 160 oC and 3 bar is used as
a stripping agent. The task of the distillation column is to recover 95% of n-C14 to the
top product and 95% of n-C19 to the bottom product.
The existing distillation column is simulated using both the retrofit shortcut model and
rigorous simulation (HYSYS). Both models use the Peng Robinson model for the
physical and thermodynamic property calculations of the feed and product streams. In
the rigorous simulation, a steam flow rate of 1540 kmol/h and a reflux ratio of 0.411 are
predicted to separate the given feed in the existing column into the required
specifications. When using the retrofit shortcut model, the number of stages in each
Chapter 3 Shortcut models for retrofit design of distillation columns
61
section and the column operating conditions are fixed. The steam flow rate and reflux
ratio, which are obtained from the rigorous simulation, are specified. Then, the model
calculates the product flow rates and temperatures, the key component recoveries (or
flow rates) and the duty of condenser. The results are summarised in Table 3.12, and
compared with the rigorous simulation results.
As seen in the table, there is a very good agreement between the results of the retrofit
shortcut model and the rigorous simulation. The deviation in product flow rates does not
exceed 1%; however, the key component (n-C14) flow rate in the top product shows a
deviation of 3.5%. The condenser duty shows approximately the same results for both
models. The maximum temperature difference of the various product streams is less
than 1.5 oC
Table 3.11: Feed mixture data and column specifications
Feed specifications C8-C23 mixture Flow rate (kmol/h) 1000 Pressure (bar) 3.0 Temperature (oC) 300 Column specifications Rectifying stages 6 Stripping stages 8 Column pressure (bar) 3.0 Flow rate of n-C14 in top product (kmol/h) (95% recovery)
59.4
Flow rate of n-C19 in bottom product (kmol/h) (95% recovery)
59.4
Table 3.12: Retrofit shortcut and rigorous simulation (HYSYS) results
Parameter Rigorous model
Retrofit shortcut model
n-C14 in top product (kmol/h) 59.4* 61.5 n-C14 in top product (kmol/h) 59.4* 59.9 Top product flow (kmol/h) 564.6+ 564.0 Top product temp. (oC) 130.4 131.4 Condenser duty (MW) 40.0 40.4 Bottom product flow (kmol/h) 435.4+ 435.9 Bottom product temp. (oC) 224.6 225.8 Steam flow (kmol/h) 1540 1540* Reflux ratio 0.411 0.411*
*: specified +: water-free basis
Chapter 3 Shortcut models for retrofit design of distillation columns
62
3.3.2. Retrofit shortcut model for complex configurations of steam-stripped distillation columns
Complex distillation configurations may use steam stripping for vaporisation rather than
using reboilers. Using steam stripping is more economical than using reboilers due to
the lower cost required for steam and its availability. The shortcut models for simple
steam-stripped distillation columns cannot be applied directly to retrofit these column
configurations.
In this section, retrofit modelling of complex configurations of steam-stripped
distillation columns is presented. Different complex configurations are considered, such
as columns with side-strippers, side-rectifiers, side-exchangers and thermal coupling.
The configurations considered are alternatives to simple columns for separating a single
feed mixture into more than two products.
3.3.2.1. Complex distillation columns with side-strippers or side-rectifiers
Retrofit modelling of these complex configurations is carried out by using the column
decomposition approach. The complex configurations are decomposed into
thermodynamically equivalent sequences of simple columns with thermal coupling.
This step makes the retrofit design easier. Then, a retrofit model, based on that for
simple steam-stripped distillation columns, is proposed.
The equivalent sequences to complex columns with side-strippers and side-rectifiers are
shown in Figure 3.12. These sequences are fully thermally coupled simple columns in
direct or indirect link. As seen in the indirect coupled sequence, the thermal coupling
connection is the vapour feed to the downstream column from the upstream column and
the liquid stream from the downstream column to the upstream column. The condenser
of the second column provides reflux for both columns. In the direct coupled sequence,
the downstream column receives its feed from the bottom liquid of the upstream column
and returns a vapour stream to the upstream column. The reboiler of the second column
provides vapour for both columns.
Chapter 3 Shortcut models for retrofit design of distillation columns
63
Figure 3.12: Decompositions of steam-stripped complex columns, showing
distribution of existing number of stages (full thermal coupling)
The retrofit shortcut for modelling complex steam-stripped columns with side-strippers
and side-rectifiers is summarised as follows:
1. The complex columns are decomposed into the thermodynamically equivalent
sequences of simple columns with thermal coupling connections.
2. The existing stages of the main column are distributed into the first column and
the top section of the second column, while the existing stages of the side-
stripper or side-rectifier are distributed into the bottom section of the second
column (Figure 3.12).
3. The retrofit shortcut model for simple columns is applied to each column in the
sequences, starting with the first column. For each simple column, the retrofit
NR1
NS1
NS2
NR2 NR1
NS1
NS2
NR2
NR2
NR1
NS1
NS2
NR1
NS1
NR2
NS2
Column with side stripper Indirect sequence
Equivalent simple sequences Complex columns
Column with side-rectifier Direct sequence
Chapter 3 Shortcut models for retrofit design of distillation columns
64
model calculates the product stream flow rates, temperatures and compositions,
and the duties of the reboilers and condensers.
4. Due to the thermal coupling connections, an iterative procedure is carried out.
The iterations start with the simulation results obtained in step 3. New recoveries
for key components are updated in each iteration step through a linear relation
with the previous recoveries. The iterations terminate when the calculated
number of stages and the existing stages are identical.
5. For the thermally coupled sequences, the iterative procedure results in the
product compositions, flow rates and temperatures, the flow rates of the liquid
and vapour streams of the thermal coupling connection, and the duties of the
reboilers and condensers.
In design of columns with side-strippers or side-rectifiers (equivalent to two thermally
coupled columns), there are eight degrees of freedom, four for each column. These
degrees of freedom are four for the existing stages in the rectifying and stripping
sections for the two columns; two for the steam flow rates to each column; one for the
reflux ratio of the second column; and one for the liquid flow rate between the two
columns.
3.3.2.2. Illustrative example – a steam-stripped distillation column with side-stripper
In this example, the same hydrocarbon feed mixture, specifications for which are given
in Table 3.11, is separated into three products using a steam-stripped distillation column
with a side-stripper (equivalent to the thermally coupled indirect sequence of two steam-
stripped columns). The specifications for each column are given in Table 3.13,
including the flow rates of stripping steam and the key components. Stripping steam
used for both columns is at 160 oC and 3 bar.
The existing distillation column is first rigorously simulated using HYSYS. A reflux
ratio of 2.59 is calculated to give the required specifications, for the given number of
stages and steam flow rates. When using the retrofit model, the column specifications
and the operating conditions, including the reflux ratio and steam flow rates, are
specified. Then, the model calculates the product stream flow rates and temperatures,
the key component flow rates and the condenser cooling duty. The results are
Chapter 3 Shortcut models for retrofit design of distillation columns
65
summarised in Table 3.14, and compared with those results obtained from the rigorous
simulation. Both models use the Peng Robinson model for the calculation of the
physical and thermodynamic properties of the feed and product streams.
The retrofit shortcut and rigorous simulation results show good agreement. Some
deviation is observed between the results of the retrofit shortcut model and rigorous
simulation. This deviation is due to the complexity in the column configuration, the
presence of the stripping steam and the large number of components. Temperature
differences of up to 7.6 oC and flow rate differences of products of up to 3.7 % are
observed. However, a very good agreement can be observed between the results of the
Table 3.14: Retrofit shortcut and rigorous model results
Parameter Rigorous model
Retrofit shortcut model
Column 1 Bottom product flow (kmol/h) 454.5+ 448.1 Bottom product temperature (oC) 236.5 237.3 n-C19 flow in bottom product (kmol/h) 59.4* 59.48* Steam flow (kmol/h) 1100* 1100* Thermal coupling Vapour flow (kmol/h) 1940 1875 Liquid flow (kmol/h) 261 224 Column 2 Top product flow (kmol/h) 277.5+ 273.4 Top product temperature (oC) 127.8 128.7 n-C10 flow in top product (kmol/h) 59.4* 59.3 Bottom product flow (kmol/h) 268.5+ 278.5 Bottom product temperature (oC) 228.1 235.7 Condenser duty (MW) 30.7 30.8 Steam flow (kmol/h) 100* 100* n-C13 flow in botoom product (kmol/h) 57.8 61.2 Reflux ratio 2.59 2.59*
*: specified +: water-free basis
1
2 Top 2
Bottom 2
Bottom 1
Feed
Vapour
Liquid
Steam
Steam
Chapter 3 Shortcut models for retrofit design of distillation columns
66
3.3.2.3. Complex distillation columns with side-exchangers
Similar to reboiled distillation columns, side-exchangers may be added to steam-
stripped complex distillation columns. A side-cooler is added at the upper section of a
complex column with a side-stripper, while a side-heater is added at the lower section of
a complex column with a side-rectifier. This condition, which is called partial thermal
coupling, represents a condition between the uncoupled sequences and the fully
thermally coupled sequences. Figure 3.13 shows complex columns with side-
exchangers (partially thermally coupled), versus fully thermally coupled sequences. In
the partially thermally coupled sequences, some of the duty of the condenser or the
reboiler of the second column is shifted to the side-exchanger. In fully thermally
coupled sequences, the side-exchanger duty is zero, i.e. no side-exchanger exists.
(a) Partial thermal coupling (b) Full thermal coupling
Figure 3.13: Thermal coupled complex columns with steam (direct and indirect sequences)
A similar retrofit model to that for fully thermally coupled sequences is proposed for
complex columns with side-exchangers, i.e. partially thermally coupled sequences. This
model is based on the shortcut model for simple steam-stripped distillation columns and
the model of Suphanit (1999), for the calculation of side-exchanger duties. The retrofit
model uses the column decomposition approach, and has an iterative procedure. For
fixed existing stages and given operating conditions, the retrofit model calculates the
Chapter 3 Shortcut models for retrofit design of distillation columns
67
various product stream flow rates, temperatures and compositions, the duties of the
condensers and side-exchangers, and the flow rate of the liquid through the side-
exchangers.
There are ten degrees of freedom in design of these column configurations; two are
added, for the side-exchangers, to those eight degrees for fully thermally coupled
sequences.
3.3.2.4. Illustrative example – a steam stripped distillation column with a side-stripper and a pump-around
An existing steam-stripped distillation column with a side-stripper and a pump-around
is used to separate the same hydrocarbon feed mixture given in Table 3.11, into three
products. The column specifications, including the existing stages and column pressure,
are the same as in example 3.3.2.2. The pump-around has a cooling duty of 3056 kW
and a temperature drop of 20 oC.
The retrofit shortcut model simulates the existing distillation unit. The results are
summarised in Table 3.15, and compared with results from rigorous simulation. The
physical and thermodynamic properties of the various streams are predicted using the
Peng Robinson model.
One can note that the shortcut model predicts results in good agreement with those of
the rigorous simulation. The maximum error in the product flow rates and the condenser
duty is less than 4%. The temperatures of the products, predicted by the shortcut model,
deviate from those of the rigorous simulation by up to 9.5 oC.
3.3.3. Summary
New shortcut models have been developed for retrofit design of steam-stripped
distillation columns. The retrofit models overcome the main drawbacks of the
Underwood-based models: constant molar overflow and constant relative volatilities.
The models account for different column configurations such as simple columns,
sequences of simple columns, and columns with side-strippers, side-rectifiers and side-
exchangers. Good agreement is found between the results of the shortcut and the
rigorous models.
Chapter 3 Shortcut models for retrofit design of distillation columns
68
Table 3.15: Retrofit shortcut and rigorous model results
Parameter Retrofit shortcut model
Rigorous model
Column 1 Bottom product flow (kmol/h) 453.6 465.1+ Bottom product temperature (oC) 233.2 242.8 n-C19 flow in bottom product (kmol/h) 59.4* 59.4* Steam flow (kmol/h) 900* 900* Temperature drop across pump-around (oC) 20.0* 21.0 Pump-around duty (kW) 3056* 3056* Liquid flow through pump-around (kmol/h) 842.4 842.4* Thermal coupling Vapour flow (kmol/h) 1566 1544 Liquid flow (kmol/h) 120 118 Column 2 Top product flow (kmol/h) 271.5 262.4+ Top product temperature (oC) 128.7 127.6 n-C10 flow in top product (kmol/h) 59.4* 58.6 Bottom product flow (kmol/h) 274.9 270.5+ Bottom product temperature (oC) 222.9 214.4 Condenser duty (MW) 26.99 25.77 Steam flow (kmol/h) 150* 150* n-C13 flow in botoom product (kmol/h) 61.0 59.0 Reflux ratio 2.179 2.179*
*: specified +: water-free basis
3.4. Retrofit modelling for design of refinery distillation columns
Crude oil distillation is a process of great importance in the refining industry. The
process is both energy and capital intensive. Retrofit of these units is a common design
activity aiming to increase profit by using the existing equipment more efficiently.
Established crude oil distillation units use a combination of steam-stripped and reboiled
columns. For retrofit design of such configurations, the new shortcut models developed
for reboiled columns and steam-stripped columns can be applied sequentially.
Conventionally, the design of crude oil distillation units is carried out by the
specification of the cut point and temperature gap, or product flow rates (Watkins,
1979). Rigorous model-based simulations apply this conventional method for design of
crude oil distillation systems; i.e. the simulators specify the cut point and temperature
gap for separation products. Conventional shortcut models (e.g. FUG method) require
the specification of key components for the required separation. In crude oil distillation
columns, pseudo-components are specified for each pair of successive products when
Chapter 3 Shortcut models for retrofit design of distillation columns
69
using the shortcut models in design. Real components can be specified as the key
components for the separation of the light ends.
Various column configurations exist for distillation of crude oil in refineries. A tower
with three side-strippers and pump-arounds is a configuration that is typical of
atmospheric distillation towers used worldwide. This column configuration mostly uses
steam for stripping in the main tower and in the first side-stripper; it is equivalent to
four thermally coupled columns with three pump-arounds. In the design of such
configurations, there are twenty-two degrees of freedom. Summary of these degrees of
freedom, when using the retrofit shortcut model is given in Table 3.16.
Table 3.16: Typical degrees of freedom for atmospheric crude oil tower
Number of degrees of freedom
Retrofit shortcut model
8 2 (stages in top and bottom sections) × 4 (columns) 3 Product flow rate for first three columns 2 Steam flow rate for first two columns 6 2 (∆T, duty of pump-around) × 3 (pump-arounds) 1 Reflux ratio 2 RLK/RHK = f (NR, NS) for last two columns
Total 22
In retrofit design of crude oil distillation units, the column configurations, number of
stages in each section, locations of pump-arounds and side-strippers are fixed. Then for
given operating conditions, including the steam flow rates, the retrofit models for
reboiled columns and those for stripped columns are applied sequentially to each
corresponding column. The models calculate the various process stream flow rates,
temperatures and compositions, the different heating and cooling duties of reboilers,
condensers and pump-arounds.
The significance of these retrofit models is that they are applicable for any column
configurations of crude oil distillation units, and they provide reliable results.
3.4.1. Illustrative example – an atmospheric crude oil distillation column
An atmospheric crude oil distillation unit processes 100,000 barrels/day (2610 kmol/h)
of crude oil at 25 oC and 3 bar into five products: light naphtha (LN), heavy naphtha
(HN), light distillate (LD), heavy distillate (HD), and residue (RES). Superheated steam
at 260 oC and 4.5 bar is used as a stripping agent.
Chapter 3 Shortcut models for retrofit design of distillation columns
70
The true boiling point data (crude assay) of the crude oil are shown in Table 3.17; these
data are based on a textbook example (Watkins, 1979). The crude assay is represented
using 25 pseudo-components, using the oil characterisation technique embedded within
a rigorous simulation package (HYSYS, 1999). The physical and thermodynamic
properties of each pseudo-component (e.g. molecular weight, vapour pressure, boiling
temperature, critical properties, etc.) are calculated using the Peng Robinson model, and
are then extracted from HYSYS. The key components for the separation of each pair of
products are shown in Table 3.18. The composition of the feed in terms of the pseudo-
components and their boiling temperatures and flow rates are given in Table 3.19.
The distillation column configuration is shown in Figure 3.14, which also shows the
equivalent sequence of four-thermally coupled columns. Table 3.20 gives the existing
stages in each section of the column, the operating conditions, the steam flow rates, and
the pump-around temperature differences and the cooling duties
The existing atmospheric unit is simulated using the retrofit shortcut model. In the
calculations, the existing stages in the rectifying and stripping sections are fixed, as are
the operating conditions, including the steam flow rates. The reflux ratio, the
temperature drops along the pump-arounds, and the pump-around duties are then
specified. The retrofit model calculates the product flow rates and temperatures, the
flow rates of the liquid recycled through the pump-arounds, the duties of the condenser
and reboilers, and the key component flow rates. The results are summarised in Table
3.21, and are then used to initialise the calculations of the rigorous simulation
(HYSYS), for the same column and feed specifications, and the operating conditions.
The rigorous simulation results are then compared with those from the retrofit shortcut
model in Table 3.21.
The table shows that the results predicted by the retrofit shortcut model are in good
agreement with those obtained from the rigorous simulations; no significant deviations
are observed. The maximum temperature difference is 10 oC, and the deviations in all
flow rates are within 7%. However, the other variables have very close results.
As seen, the distillation column configuration is very complex with many side-strippers
and pump-arounds; moreover it has a large number of components (25 pseudo-
components + water). So this good agreement is an important result for such column
complexity and large component numbers. The good agreement illustrates the adequacy
Chapter 3 Shortcut models for retrofit design of distillation columns
71
of the retrofit shortcut model and supports the application of the new model for retrofit
studies.
In refinery distillation products, the product composition and the true boiling curves are
of great importance since these features determine the product specifications and hence
the product qualities to meet the market requirements. Figures 3.15 to 3.19 show the
product compositions obtained from the retrofit shortcut models and compare them with
results from rigorous simulation. The figures are plotted as the pseudo-component mole
fraction in the product against the pseudo-component number. As shown, the retrofit
models predict product compositions in good agreement with rigorous simulation.
Furthermore, in Figures 3.20 to 3.24, the true boiling curves (TBP curves) of the various
products for the retrofit model and the rigorous simulation are shown. The true boiling
curves are obtained from HYSYS by inputting the product stream data (temperature,
pressure, component mole fractions) that are predicted by the shortcut models. It is clear
that there is good agreement between the results.
A conclusion can be drawn from this example that the retrofit shortcut models
developed for design of crude oil distillation columns are reliable for applications with
good accuracy compared with rigorous models. The models predict product separations
with comparable specifications and qualities with those obtained by using rigorous
simulations. The predicted results include flow stream rates, compositions, duties and
true boiling curves. In addition, the models can initialise rigorous calculations.
Figure 4.13: Regression of viscosity data from Seader and Henley (1998)
3. For given packing material, and fluid flow rates and properties, the flooding
velocity can then be calculated from equations 4.63, 4.64. The correction factors
for the liquid properties are obtained from equations 4.65 and 4.66.
4. Then, a fraction of flooding f is selected (usually from 0.5 to 0.7) (Seader and
Henley, 1998). The diameter of the packed section is then calculated from:
5.04
=
Vopack fu
VDπρ
(4.67)
5. Check that the calculated diameter is at least 8 times the packing size. If not,
select a smaller packing and repeat the procedure till reasonable diameter is
obtained (Robbins, 1991).
6. The pressure drop at flooding through packed beds is strongly dependent on the
packing factor Fpack, and can be calculated by (Kister, 1992):
701150 .packflood F.P =∆ (4.68)
Seader and Henley (1998) suggested that the pressure drop at flooding for all packing
ranges from 2.5 to 3 in. of water head per foot packing (2.044 to 2.453 kPa/m of
Chapter 4 Modelling for retrofit of heat-integrated crude oil distillation systems
119
packing).
7. The pressure drop ∆Ppack can then be linearly interpolated at the values of the
flow parameter, f{uo) and f{f×uo). Where f is a fraction of the flooding velocity
(0.5 – 0.7) (Seader and Henley, 1998). Alternatively, it can be calculated from
Robbins’ correlation (1991):
421
1.02
1 )10(000,20
4.010 22 FF LqF
FLqFpack VqLVqP
+=∆ (4.69)
where:
( ) 81 104.7 −=q (4.70)
( ) 52 107.2 −=q (4.71)
atm 1.0P for F
VV pd
VfluxF ≤
=
5.05.0
20075.0ρ
(4.72)
atm 1.0 P for F
VV Vpd
VfluxF >
= ρ
ρ3.0
5.05.0
1020
075.0 (4.73)
15 F for F
LL pdLpd
LfluxF ≥
= 1.0
5.0
204.62 µ
ρ (4.74)
15 F for F
LL pdLpdL
fluxF <
= 1.0
5.0204.62 µ
ρ (4.75)
Fpd is dry-bed packing factor and can be obtained from Kister (1992; p. 500), for
various packing materials. Coker (1991) developed a more simple correlation for
pressure drop calculation (see Appendix A.3). He also suggested that the design
pressure drop for fractionators is in the range 0.40 - 0.80 in. H2O/ft height (0.327 -
0.654 kPa/m of packing).
The cost of the packing materials is evaluated after determining the diameter and height.
Costs of packing materials per unit volume PCKVcost can be found in Douglas (1988; p.
576), Perry (1974; p. 18.54) and Peters and Timmerhaus (1980; p. 770), for different
types and sizes. The installed cost of a packed section can then be calculated,
Chapter 4 Modelling for retrofit of heat-integrated crude oil distillation systems
120
providing the diameter and height, as follows: an installation cost of 75% of the packing
purchase cost is assumed (Peters and Timmerhaus, 1980; p. 169):
( ) ( )cost2
475.1 PCKVDCost packpack
π= (4.76)
The model for designing packed sections is combined with those in Section 4.1 for
retrofit, to account for the use of packing materials in retrofit. The model can evaluate
the potential for removing hydraulic bottlenecks and increasing throughput of a crude
oil distillation column using packing.
4.8. Summary and conclusions
Modelling of heat-integrated crude oil distillation systems for retrofit design has been
presented. Column retrofit models can specify an existing design of crude oil distillation
unit, by fixing the existing stages in each section and the column configuration. The
hydraulic capacity limitations of distillation columns can be accounted for through the
calculation of the stage diameters required for separation. HEN retrofit model considers
the details of the existing preheat train and relates the exchanger area required to the
energy consumption, for all possible topology modifications. Practical constraints such
as pressure drop and limited number of modifications are taken into account.
The installation of preflash and prefractionator columns for throughput enhancement
and energy saving are modelled. The models determine the required number of trays,
diameters and capital investment for a given separation in prefractionators. For preflash
units, the dimensions and the capital costs are determined. Various options of
configuring the preflash with the distillation column are addressed.
Replacing bottlenecked trays with packing for increasing throughput and
debottlenecking is also modelled, including selection, sizing and costing. In addition,
the use of heat transfer enhancement in preheat trains, for retrofit, is presented. Models
incorporate the effect of enhancing existing exchangers in retrofit design and
accommodate pressure drop implications.
Furthermore, the environmental impact of existing refinery distillation processes on
atmospheric pollution, in particular the CO2 emissions, is modelled. CO2 emissions are
evaluated from various sources and for different types of fuels. Integration of gas
Chapter 4 Modelling for retrofit of heat-integrated crude oil distillation systems
121
turbines with refinery distillation processes is also addressed.
The proposed models form the basis for retrofit of heat-integrated crude oil distillation
processes in order to achieve various objectives, while fulfilling existing constraints and
limitations. The retrofit objectives may include increasing throughput, reducing energy
demands and operating costs, minimising flue gas emissions, increasing profit and
changing product specifications. Thus, the models will be used in Chapter 5 to fix
existing designs of crude oil distillation unit and preheat train and accommodate the
various aspects mentioned above for retrofit design.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
122
Chapter 5: Retrofit design of heat-integrated crude oil distillation systems
This chapter presents a new approach for retrofit of heat-integrated crude oil distillation
systems. This approach is optimisation based, and uses the shortcut models developed
in Chapter 3 for distillation columns and those of Chapter 4 for different aspects of
retrofit design. The approach considers both the distillation column and the exchanger
network at the same stage. It is applicable for different retrofit design objectives
including throughput increase, energy saving, emissions reduction and new feed/product
specifications. The retrofit approach concentrates on the efficient reuse of existing
equipment without major modifications; however, it also accounts for changing the
structure of the distillation column and the exchanger network.
The chapter starts with an introduction to the retrofit design problem of heat-integrated
crude oil distillation systems. The retrofit philosophy followed in this work is presented.
The effect of the distillation column design parameters on the performance of the
overall system is also discussed. Then, a retrofit approach for heat-integrated crude oil
distillation systems is presented. A procedure for different applications of the retrofit
approach is also outlined.
5.1. Features of heat-integrated crude oil distillation systems
In the refining industry, crude oil distillation units consist of many interlinked columns,
use side-coolers and side-heaters, and contain different types of energy inputs such as
stripping steam and reboilers. In addition to the complex structure, the existing columns
are directly connected to an existing heat recovery system (preheat train or exchanger
network). The crude oil feed is heated to an intermediate temperature in the exchanger
network in which the distillation heat sources reject heat to heat sinks. Then, the feed is
heated further to the processing temperature in furnace or fired heater. The heat sources
in crude oil distillation columns include the top vapour product, the hot recycled liquids
in pump-arounds, and the hot distillation product streams. On the other hand, the heat
sinks are the crude oil feed, the stripping steam, the cold recycled liquids in side-heaters
and the reboilers. The product streams are cooled to their target (or storage)
temperatures by heating the crude oil feed or generating steam. Similarly, the hot
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
123
recycled liquids through pump-arounds are cooled against the crude oil feed. The top
vapour is condensed by providing heat to the crude oil feed and other cold streams in
the process.
Figure 5.1 illustrates a typical heat-integrated crude oil distillation unit. In this unit, the
crude oil is heated in a set of exchanger units and a furnace before entering the
atmospheric distillation tower in which it is separated into various products. The top
vapour from the atmospheric tower is sent to the naphtha stabiliser to be then separated
into naphtha and gasoline in subsequent processes. The residue of the atmospheric
tower is heated in a furnace and then is processed in the vacuum tower. The side
products obtained in the side-strippers are stored for marketing or further processing.
The features of the heat-integrated crude oil distillation systems can be summarised as:
(a) systems have complex structure and consist of various units; each has its capacity
limitations and structure constraints, (b) strong interactions exist between distillation
processes and heat recovery systems, (c) wide range of energy-related products are
produced, (d) systems consume large amounts of energy; typically, energy consumption
in atmospheric towers is about 2% of crude oil distilled (Rhode, 1997), (e) existing
systems are expensive to modify, and economically and environmentally challenged. As
a result, retrofit of such systems is of major importance to refining industry.
The amount of energy exchanged between the heat sources and heat sinks is a measure
of the energy efficiency of the distillation process and the exchanger network. Systems
with high energy efficiency consume less utility and have low operating costs, while
systems with low energy efficiency have high operating costs.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
124
Atmospheric tower
Vacuum tower
Stabiliser
Flash
Furnace
Furnace
Flash
DesalterCrude oil
Figure 5.1: Heat-integrated crude oil distillation system including
atmospheric and vacuum towers and naphtha splitter
The crude oil distillation column and the heat recovery system have strong interactions
between them; these interactions are represented by the operating conditions of the
distillation columns. The operating conditions include the feed preheating temperature,
the reflux ratio, the steam flow rates, the degree of thermal coupling between the
different column sections, and the flow rates and temperature changes of the recycled
liquids in the pump-arounds and side-heaters. The operating parameters play a key role
in the retrofit design of the overall system, i.e. the distillation column and the heat
recovery system. Any changes in these operating parameters individually or
simultaneously may influence the quality and quantity of the heat sources and heat
sinks, and therefore affect the energy efficiency of the overall systems. In addition,
these changes alter the vapour-liquid flow rates inside the column. Consequently, they
may affect opportunities for enhancing the production capacity.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
125
5.2. Retrofit design philosophy in refinery distillation systems
Retrofit design of heat-integrated crude oil distillation systems aims to reuse the existing
equipment more efficiently in order to achieve various objectives. Objectives for retrofit
design include increasing production capacity, reducing utility consumption, minimising
CO2 emissions, and processing new feedstocks or changing product specifications.
These objectives are achieved most preferably by minor modifications to the existing
equipment. While retrofit objectives are achieved, existing equipment constraints must
be met. As pointed out in Chapter 2, the modifications suggested by previous
approaches change the structure of existing equipment; therefore, a large capital needs
to be invested. In this work, we follow another retrofit philosophy in which the existing
equipment is efficiently reused before considering any major modifications. The details
of existing equipment together with its physical constraints are taken into account.
Furthermore, the benefits of modifying the structure of the existing equipment, e.g.
changing column internals, adding preflash drums, etc., are also considered. When
structural modifications to existing equipment are made, a large capital investment is
needed. Therefore, a trade-off between capital investment and operating cost saving
exists. The retrofit approach established in this work concentrates on those column
modifications which require little or no capital investment.
As reviewed earlier in Chapter 2, the conventional retrofit approaches for refinery
distillation systems were carried out sequentially, in which the distillation column is
initially retrofitted. Then, the additional area and modification requirements for the
exchanger network are determined. In these approaches, any benefits of the interactions
between the distillation columns and the exchanger networks have been lost.
Furthermore, the approaches result in column modifications without efficient reuse of
the existing equipment. An example of such an approach is that proposed by Liebmann
(1996). This approach has two steps and requires manual iterations; it does not
simultaneously account for system interactions. In addition, the approach considers
pinch analysis insights for heat integration and not the existing heat recovery system,
nor does it account for hydraulic capacity limitations. As summarised previously, very
few researchers have looked simultaneously at the distillation columns and the heat
recovery systems. As yet, none has considered the details of the heat recovery system or
taken the distillation hydraulic constraints into account. Alternatively, the heat recovery
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
126
opportunities, determined by pinch analysis, were maximised. In these approaches, such
that of Bagajewicz (1998), the details of the existing heat recovery system are not
accounted for. Besides, the hydraulic capacity limitations of the distillation columns are
not taken into consideration. Consequently, the retrofit design may result in bottlenecks
in both the distillation column and the heat recovery system.
In the retrofit approach presented in this chapter, the details of the heat recovery
systems and the distillation columns are considered at the same stage. The hydraulic
capacity constraints of the distillation columns are incorporated.
5.3. Interactions between distillation operating conditions, heat recovery potential and column hydraulics
As discussed above, the interactions (operating conditions) affect the performance of the
overall refinery distillation system, i.e. crude distillation column and heat recovery
system. Therefore, retrofit design of such systems is highly dependent on these
interactions. For existing designs of crude distillation columns and exchanger networks,
the effect of the operating conditions on the performance of the overall system will be
investigated in terms of both the heat recovery and the hydraulic performance of the
distillation columns:
1. When the feed preheating temperature in a reboiled column increases, the hot utility
required in the reboiler reduces. This will create a heat sink at a lower temperature
than that in the reboiler, and hence this will benefit the heat recovery. In addition,
the vapour-liquid traffic below the feed stage will decrease. Thus, the required
diameter in this section is reduced. However, this effect will incur heat load
penalties due to higher total cooling and heating requirements. In this case, the
diameter required in the upper sections is increased.
In the case of steam-stripped columns, increasing the temperature of the feed
preheating will require less stripping steam for the same separation, and hence the
bottom product temperature increases. This creates more opportunities for
recovering heat at a higher temperature and saves hot utility requirements. At the
same time, the diameter required in the bottom section is reduced, while that in the
upper sections is increased.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
127
2. Generally, as the reflux ratio in the distillation column increases, larger energy
consumption is expected because the condenser and reboiler duties increase. As a
result, the vapour and liquid loads inside the column sections increase, and hence
this will require larger diameters. On the other hand, the stripping steam flow rate
needs to be increased as the condenser duty and the reflux ratio increase. This will
lead to a reduced bottom product temperature, and therefore poorer opportunities for
heat recovery exist.
3. Increasing the flow rate of the stripping steam leads to a decrease in the bottom
product temperature and an increase in the vapour and liquid traffic in the column
section. This means a larger diameter is needed and poorer heat recovery
opportunities are expected. On the other hand, with a smaller steam flow rate, heat
recovery opportunities improve because of the higher temperature of the bottom
product, and also the required column section diameter is reduced. In order to keep
the separation performance fixed, other operating variables need to be changed. This
leads to trade-offs between the effects of the different operating variables, and hence
the problem becomes more complex.
4. As explained in Chapter 3, the retrofit modelling of complex distillation columns is
carried out with the equivalent sequence of simple columns connected with thermal
coupling. So, by increasing the degree of thermal coupling of two simple reboiled
columns from partial to full thermal coupling, the reboiler duty of the downstream
column will reduce, while the condenser duty of the downstream column will
increase. As a net result, the total heating and cooling duties of the structure are
reduced, but the quality of the heat source (pump-around) will be degraded since the
pump-around duty is shifted completely to the condenser of the downstream column
which operates at a lower temperature level.
In the case of using stripping steam in both columns, less steam is needed by the
downstream column as a result of increasing the degree of thermal coupling. The
condenser duty of the downstream column will become higher because of shifting
the pump-around duty. Therefore, a higher quality heat source is created at the
bottom of the downstream column, while the degradation of the pump-around
stream leads to poorer heat recovery opportunities.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
128
5. The pump-arounds reject heat at temperatures higher than that of the condenser, and
hence the opportunities for heat recovery are improved. They can also reduce the
vapour and liquid traffic in the column section. Therefore, this can enhance the
throughput of the distillation columns. When the temperature difference across the
pump-around decreases, the flow rate of the recycled liquid will be larger for a fixed
cooling duty. This increases the liquid traffic inside the column, and hence a larger
diameter is required around the pump-around. However, the pump-around will
operate at a higher temperature level, which improves heat recovery opportunities.
On the other hand, if the pump-around duty increases for a fixed liquid flow rate, the
temperature difference across the pump-around will increase. Therefore, the pump-
around outlet stream will operate at a lower temperature level reducing the vapour
traffic around the pump-around due to more condensation. This leads to a reduced
required diameter on the trays near the pump-around; however, the quality of the
heat source for heat recovery is now lower.
In the case of using side-heaters in the distillation columns, if the temperature
difference across the side-heater decreases, the flow rate of the recycled liquid will
increase for a fixed heating duty. This requires a larger diameter around the side-
heater; however, a heat sink at a lower temperature level is created which benefits
the heat recovery potential. Similarly, increasing the temperature difference across
the side-heater for a fixed heat duty will result in a reduced diameter requirement,
while a heat sink at a higher temperature level is created which consumes more hot
utility.
From the above discussion, a conclusion can be drawn that the interactions between the
distillation column and exchanger network affect significantly the heat recovery
opportunities of the overall structure and that the operating conditions affect the
hydraulic performance of distillation column. Some changes benefit the heat recovery in
the exchanger network, while others can enhance the processing capacity of the crude
oil distillation column. These interactions can be, however, exploited to remove column
bottlenecks where exist. Therefore, the interactions represented by the operating
conditions of the distillation processes need to be considered simultaneously in an
optimisation approach for retrofit design. In the following sections, the retrofit approach
developed for heat-integrated crude oil distillation systems will be explained in detail.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
129
5.4. New approach for retrofit of heat-integrated crude oil distillation systems
The retrofit design of heat-integrated crude oil distillation systems is carried out by
incorporating the distillation column retrofit and the heat recovery system retrofit
models into an optimisation framework simultaneously. The optimisation strategy for
retrofit design of the distillation column and heat recovery system needs then to be
selected.
There exist two different modelling strategies for optimisation of chemical processes,
sequential modular and equation-oriented strategies (Biegler et al., 1997). In the
sequential modular strategy, each unit is modelled individually as a subsystem.
Therefore, it is easier to construct each unit model. The design models and
thermodynamic (physical properties) model are then solved simultaneously from
upstream to downstream units of the process. This strategy is robust for non-linear
process calculations, since only one unit is handled at a time. It is also easier to initialise
the problem variables. However, this strategy consumes a substantial calculation effort.
On the other hand, the equation-oriented strategy combines the unit models and the
thermodynamic model into a large set of equations, and solves them simultaneously.
Therefore, it converges faster than the sequential modular approach, and requires less
computational time. It is, however, difficult to construct and initialise the problem. This
strategy is generally selected for the systems with simple design models (Suphanit,
1999).
For the retrofit design of heat-integrated crude oil distillation systems, the retrofit
shortcut models developed for distillation columns in Chapter 3 and the design models
for exchanger networks and modelling the various aspects of refinery distillation
systems are highly non-linear. Moreover, the Peng Robinson thermodynamic model for
the physical properties calculation (HYSYS, 1999) is highly non-linear. Therefore, it
will be difficult to solve these models simultaneously using the equation-oriented
strategy. Hence, the sequential modular approach is more appropriate for solving the
retrofit design models.
In the next sections, the retrofit approach established in this work will be explained, as
well as the formulation of the optimisation framework and procedure, and the possible
applications.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
130
5.4.1. Retrofit design strategies for heat-integrated crude oil distillation systems
As reviewed in Chapter 2, previous researchers approached the retrofit problem of heat-
integrated crude oil distillation systems by considering the heat integration constraints
of the heat recovery system. They did not include the details of the heat recovery system
in their works, and only involved the minimum utility consumption provided from pinch
analysis.
In this work, however, the details of the existing heat recovery system are considered at
the same stage as the distillation column in a simultaneous optimisation strategy. The
retrofit design strategy can be carried out in two different ways. The first strategy is to
consider the superstructure of the existing heat recovery system in the optimisation
framework of the entire system. In this strategy, the superstructure will be included in
addition to the structure of the distillation column. The retrofit problem is then
formulated as a mixed-integer non-linear programming (MINLP). The advantage of this
strategy is that it accounts for the capital cost details of the structural modifications and
the structure of the heat recovery system in the optimisation. In addition, this strategy
accounts for the change in the process conditions of the distillation column during the
optimisation. However, the problem is a rather complex and becomes too difficult to
formulate (e.g. with structural decisions such as preflash, prefractionator, etc.) and solve
for large processes, particularly when the system is highly non-linear such as crude oil
distillation.
Alternatively, the details of the existing heat recovery system can be approximated by
using the retrofit model proposed in Chapter 4. In this strategy, the existing heat
recovery system is studied in isolation for retrofit design and then the retrofit model
(equations 4.7 or 4.8 and 4.9; Chapter 4) is obtained. This model accounts for the
structure of the network, the exchanger areas and duties and the energy consumption.
The overall retrofit problem is then formulated as a non-linear programming (NLP)
problem. The advantages of this strategy over the previous one are that the complexity
of the problem reduces and it is quicker to solve. This strategy is selected as the retrofit
strategy proposed in this work.
The design strategy for retrofit of heat-integrated distillation systems is proposed in
Figure 5.2. In this retrofit strategy, the existing designs of the crude oil distillation
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
131
column and the associated heat recovery system are accounted for simultaneously. The
shortcut models developed in Chapter 3 are appropriate for distillation column retrofit,
and they are included in the retrofit approach to fix the existing design. The existing
design details include the column configuration, the number of real stages in each
column section, and the locations of reboilers, condensers, side-exchangers and side-
strippers. On the other hand, the structure and the details of the heat recovery systems
are incorporated into the approach and represented by the model proposed in Chapter 4.
Hence, the exchanger matches, existing areas and duties, and utility heat loads are
considered. Moreover, the models of Chapter 4 that account for different issues in
refinery distillation systems are included within the retrofit approach. These issues
include CO2 emissions, installation of preflash and prefractionator units, heat transfer
enhancement and pressure drop consideration and replacement of trays with packing.
The overall retrofit model is formulated by combining the various models mentioned
above, and hence the retrofit problem is a non-linear programming problem since the
individual models are non-linear.
The successive quadratic programming (SQP) algorithm is selected as the optimisation
solver for the retrofit of heat-integrated distillation systems. In particular, the
optimisation subroutine E04UCF of the NAG FORTRAN library (NAG, 1990) is used
to implement the Quasi-Newton method (Dennis and Schnabel, 1983) in the solution.
The SQP method is a popular procedure for process optimisation. It requires fewer
iterations than the reduced gradient method and is suitable for black-box models that
involve few variables. The details of the SQP algorithm are explained in Biegler et al.
(1997).
The retrofit strategy shown in Figure 5.2 involves no structural design decisions; in
other words, the flowsheet structure is fixed throughout the optimisation and no
structural changes may be made. However, structural modifications can be applied to
the retrofit strategy as retrofit options prior to the optimisation. The structural
modifications considered in this work focus on the installation of preflash drums or
prefractionator columns, the replacement of trays with packing, and the integration of
gas turbines with process furnaces.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
132
Figure 5.2: Simultaneous retrofit strategy for heat-integrated distillation systems
5.4.2. Objective functions for optimisation of heat-integrated crude oil distillation systems
The purpose of the optimisation is to minimise or maximise a specified objective
function. The objective function depends on the retrofit objectives. In this work, the
objective functions take the form of the total annualised cost of the expenses incurred
less the profit. The process expenses include the operating costs of stripping steam, hot
utilities and cold utilities, and the price of crude oil feed and the capital costs of process
modifications. In this work, the costs for minor modifications that do not incur capital
expenditure (e.g. downtime, labour, consumables, etc.) are not accounted for. However,
if these cost components are available, they can be incorporated into the model The
costs for new equipment are taken into account. The process modifications may contain
preflash drums, prefractionator columns, gas turbines and exchanger network
modifications. On the other hand, the process profit includes the value of products and
the value of power generated. Having defined the objective function, the appropriate
issues of the refinery distillation systems are involved through using the relevant
models. Then, the necessary cost components for the particular retrofit objective can be
Existing distillation column design
Existing heat recovery system design
NLP Optimisation
Optimum existing heat-integrated distillation
process design
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
133
evaluated. For instance if the aim of the retrofit is to minimise the total annualised cost
with a preflash installed, the model that considers preflash drum in an existing system
will be included. Hence, the capital cost of the preflash is evaluated and added to the
objective function. The calculation of cost components required for the various
objective functions will be explained in the following sections.
5.4.2.1. Objective function in retrofit for energy reduction
When the retrofit is applied to reduce the energy consumption of the crude oil
distillation unit, the objective function will be the operating costs of the utility
consumption and the stripping steam, and the capital costs of the additional area
required by exchangers of new units and of network modifications. As seen in Section
4.2, the HEN retrofit model relates the area required by existing units, new exchangers
and network modifications with the energy demand of the existing network. Therefore,
the amount of additional area required is determined from the retrofit model based on
the level of energy consumption. Then, the capital cost associated with each required
area can be evaluated. The capital cost of exchanger area is calculated from cost
correlations, as function of the area required:
exCretexexNex ABAHXCost += (5.1)
Where, the parameters Aex, Bex and Cex can be found in different sources, such as
Douglas (1988) and Nasr and Polley (2000). In this work, different cost data are
collected from Douglas (1988), Peters and Timmerhaus (1980) and SPRINT (2002).
The data are plotted and then regressed to determine the average cost parameters for the
cost model, as: Aex ($) = 0, Bex ($/m2) = 1530, Cex = 0.63 (see Appendix B.1, for details).
The parameter, Aex, is given a reasonable value for the installation costs of the new
exchanger units; for example this value may be $13,000 (Nie, 1998).
On the other hand, the utility costs are calculated knowing the cost per energy unit and
the heat load of each utility. Similarly, the cost of stripping steam is calculated
providing the unit cost and the flow rate. Therefore, the total annual costs of the energy
and capital investment can be evaluated during the course of the optimisation.
If heat transfer enhancement is applied to the existing exchanger network, the cost for
the enhancement material (as mentioned earlier, labour cost is not accounted for) is
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
134
therefore added. This cost can be obtained by knowing the amount of the enhanced area
as mentioned in Chapter 4, as follows:
enex AccEnCost 21 += (5.2)
The cost parameters c1, c2 are dependent on the type of the enhancement material and
can be obtained from enhancement providers. For instance, these parameters for the
type of coiled wire 5.5 are 0 ($) and 60 ($/m2) respectively (Nie, 1998).
If preflash drum or prefractionator column is installed in an existing system to reduce
the energy consumption, the capital cost, calculated from the relevant models of Chapter
4, will be added to the objective function.
5.4.2.2. Objective function in retrofit for throughput enhancement
In case of increasing the production capacity of the existing unit, the objective function
will include the value of the products and cost of the crude oil feed in addition to the
costs of the energy and stripping steam and the HEN capital investment. The value of
the products and cost of crude oil feed can be determined knowing the unit prices and
the production flow rates.
If installing a preflash drum or a prefractionator column is to be selected for increasing
capacity, the capital costs of the modifications will be added to the objective function.
Similarly, when column trays are to be replaced, the cost of the packing is added. In
these cases, the models proposed in Chapter 4 for calculating the costs of the
modifications are used.
5.4.2.3. Objective function in retrofit for profit increase
For a fixed flow rate of crude oil feed, process profit can be maximised. This can be
done by allowing product flow rates to change; hence, the value of products will
increase. In this case, the objective function includes the value of products and cost of
crude oil feed, in addition to the operating costs and the network modification costs.
Moreover, profit can be maximised for a given crude oil distillation unit with structural
modification, such as preflash or prefractionator. The modification cost will be then
added to the objective function where applicable.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
135
5.4.2.4. Objective function in retrofit for CO2 emissions reduction
If the goal of the retrofit project is to minimise the emissions from the existing refinery
distillation system, the objective function must account for the emissions tax or
investment in emissions-abatement infrastructure. Therefore, the cost penalties of
meeting the environmental regulations are taken into account. Two approaches are used
to consider emissions; one is to consider the carbon tax imposed by the government.
The other is to add the capital invested for reducing the emissions. In the first scenario,
the carbon tax is added to the operating costs and the capital cost of the HEN
modifications. The flow rate of the CO2 is evaluated in the existing system; hence, the
total tax can be determined, knowing the penalty value (tax) per unit mass of CO2.
In the second scenario, the capital investment for emissions reduction is determined
prior to optimisation. This task can be done by carrying out a separate study on the
existing crude distillation unit in order to reduce the emissions. Various retrofit
modifications may be performed, such as modifying the distillation column or the
exchanger network, and using different fuels in combustion. The possible modifications
to the distillation column include firstly changing the operating conditions; these
changes have cost implications on the existing network. Then, adding a preflash drum
or prefractionator column may be made. In addition, the existing network may be
modified and a gas turbine can be integrated with the process. Therefore, the capital
investment required for each reduction in the emissions can be evaluated. Then, the data
of the investment can be plotted against the flow rate of the CO2 (Figure 5.3). As
shown, the plot can be divided into intervals of energy consumption, for which the slope
of the curve can be estimated as shown by the dotted lines. The inverse of these slopes
indicates the investment per unit mass of CO2, and it can represent the costs required for
reducing the emissions for a given range. The objective function is then the summation
of the emissions reduction investment and the operating costs. Alternatively, the curve
can be regressed to obtain a model that correlates the capital investment to the flow rate
of the CO2 emissions. Then, this model can be incorporated into the overall retrofit
model to estimate the investment for a given emission level.
When a gas turbine is integrated with the process furnace, the capital and power costs of
the gas turbines need to be added to the objective function. Therefore, the models of
Chapter 4 that calculate the capital and power costs are employed.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
136
CO2 flow(kg/h)
Investment ($)
Existing processEmissionsreduction curve
Slope =kg/h$
Decreasingenergy demand
Figure 5.3: CO2 emissions reduction strategy for refinery distillation systems
As seen above, although the retrofit objectives are presented for individual purposes,
multiple objectives can also be accommodated, such as reducing total cost together with
improving profit, or increasing capacity and reducing emissions. In this case, the
objective function will be the summation of the total annualised cost of all objectives
involved. This may allow the retrofit design and modifications options to be explored
for several objectives at the same time, e.g. gas turbine and prefractionator can be added
for reducing emissions and increasing production capacity.
5.4.3. Optimisation procedure for existing heat-integrated crude oil distillation systems
Figure 5.4 shows the optimisation framework for retrofit design of heat-integrated
distillation systems. In this framework, column retrofit models, HEN model, cost
models and other models accounting for structural modifications are solved
simultaneously within a black-box. Column retrofit models account for the details of an
existing column design including column configuration, number of actual stages and
existing column diameter. HEN retrofit model takes the details of the existing heat
exchanger network into account. The optimisation variables are the operating conditions
of the distillation process, including feed preheat temperature, preflash prefractionator
temperatures, steam flow rates, reflux and reboiling ratios, and side-exchanger
temperature drops and flow rates. The lower and upper boundaries of the optimisation
variables need to be set. These boundaries may depend on practical experience or they
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
137
can be imposed as constraints. For instance, the feed preheating temperature of crude oil
should not exceed a certain limit depending on the crude oil origin to avoid unwanted
thermal decomposition (Watkins, 1979). Similarly, the pump-around temperature
differences may have constrained values. Any practical constraints in the existing
system can be applied in the optimisation framework. SQP is used as the NLP
optimisation solver.
The optimisation is applied to any existing crude oil distillation column with its
associated exchanger network. Throughout the optimisation, the given column structure
is fixed, as are the number of actual stages in each section and the locations of the
condensers, reboilers and side-exchangers. In addition, the stage diameter is calculated
as discussed in Chapter 4, and hence the existing diameter of the distillation column can
act as a constraint throughout the optimisation. On the other hand, the details of the
existing heat recovery systems are taken into account using the area retrofit model. The
operating conditions of the distillation processes are changed simultaneously for the
fixed system design to minimise or maximise an objective function.
Figure 5.4: Simultaneous retrofit strategy for heat-integrated distillation systems
The optimisation starts with the calculation of the energy consumption and total
exchanger area of the existing distillation unit. Then, in every iteration, the heating
Column retrofit model HEN retrofit model
Cost model Other models
NLP optimiser (SQP)
Existing distillation column
Existing heat recovery system
Objective: Minimise or maximise
objective function
Optimum existing heat-integrated distillation process
Parameter boundaries
Practical constraints
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
138
demand at each temperature level, associated with available utilities, is calculated for
the new process stream data using the process grand composite curve (Smith, 1995).
This is done by forming a linear programming (LP) problem based on the problem table
algorithm of Linnhoff et al. (1982) to determine the optimum use of available utilities
given their unit costs (Parker, 1989). The HEN model provides the exchanger additional
area required for retrofit at each heating demand level.
The drawback of the approach is that the model for the heat exchanger network retrofit
is obtained for fixed process conditions. However, during the optimisation, these
process conditions change. As a result, the capital-energy trade-off given by this retrofit
model does not account for the changes in process conditions and the retrofit
requirements to the existing heat exchanger network. This shortcoming can be
overcome by repeatedly applying the optimisation approach to the existing system.
After each optimisation run, a new retrofit model is obtained for the optimum process
conditions. Then, this model is used for the next optimisation step. The optimisation
runs end when there is no scope for a better solution to be obtained. Overall, a retrofit
model is obtained which relates the capital-energy trade-off in the existing heat
exchanger network and the process changes.
As mentioned, various objective functions can be handled. Thus, according to the
objective function employed, the appropriate aspects of the refinery distillation systems
are involved through applying the relevant models. This means that, for instance, if the
retrofit objective is to minimise the CO2 emissions, the emissions will be calculated and
the corresponding objective function will be evaluated.
During the course of the optimisation, practical constraints can be applied. The practical
constraints considered in this work include: (1) hydraulic capacity limitations of the
distillation column, (2) allowable pressure drop for crude oil feed in heat recovery
system, (3) maximum heat duty of pump-arounds or side-heaters and duties of the
condenser and reboilers, (4) product component recoveries and (5) product flow rates. If
a constraint is violated, a penalty value will be added to the value of the objective
function. A square penalty function is used in the optimisation framework, as follows:
( )2lim,ii xxKPenalty −= if xi ≤ xi,lim (5.3)
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
139
The values of the dependent variables, xi, are obtained from the appropriate retrofit
models presented in Chapters 3 and 4, while the limiting values of these variables, xi,lim,
are specified. For example, if the pump-around duty is to be constrained, the duty will
be calculated from the column retrofit models during the course of optimisation. Then,
the value will be compared with the maximum duty and therefore a penalty value will
be imposed where the duty is violated.
The results of the optimisation will be the optimum design of the existing crude oil
distillation column and the associated heat recovery system. The optimum operating
conditions of the distillation process are obtained. On the other hand, the total additional
exchanger area, the type of network modifications and the the energy consumption of
the optimum distillation unit can also be obtained. However, the detailed network
requirements, including the additional area to the individual exchanger units, the
modification implications for the existing design and the utility consumption, are
determined by applying the optimum process conditions to the existing exchanger
network.
5.5. Implementation of retrofit models and applications of retrofit approach
The column retrofit models, the exchanger network model, and the other models
accounting for the various aspects in refinery distillations are coded in FORTRAN
(FTN77) and then embedded within COLOM software (2002). The physical property
model of Peng Robinson with zero interaction parameters (Suphanit, 1999) is also
included. The overall procedure for applying the retrofit approach to an existing heat-
integrated crude oil distillation system is illustrated in Figure 5.5, and can be
summarised as follows:
1. The crude oil mixture is specified in HYSYS software (HYSYS, 1999) using the
crude assay data. Then, the crude oil is cut into a number of pseudo-components,
each with known physical properties such as molecular weight, vapour pressure,
boiling temperature, critical properties, etc. HYSYS has a built-in facility to break
down a given crude oil mixture into a specified number of pseudo-components. In
addition to the pseudo-components, chemical components, such as light ends, can
also be specified.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
140
2. The physical property parameters of all existing components in the oil mixture are
extracted from HYSYS. A macro interface namely Expcmpn was written by
Suphanit (1999) for data extraction to transfer the physical property parameters from
HYSYS to COLOM software.
3. The structure of the existing distillation column is specified in the form of the
decomposed sequence of columns, as are the number of actual stages and the actual
diameter in each column section, and the product specifications. Moreover, the
current operating conditions including feed temperature, steam flow rates, reflux
ratio, pump-around flow rates, etc. need to be specified. The cost of crude oil feed
per unit barrel and the unit value of products need to be specified.
4. The existing exchanger network is represented using the retrofit model, and thus the
model parameters need to be specified. On the other hand, the utility consumption
and the total exchanger area are specified. The unit cost of each utility and the
exchanger model cost parameters are also specified.
5. The optimisation variables are then selected. The lower and upper boundaries of the
optimisation variables are set.
6. Existing practical constraints such as hydraulic limitations, pressure drop, maximum
duties, etc. are specified.
7. The optimisation can then be performed for a user-defined retrofit objective.
8. The results of the optimisation will be the optimum operating conditions for the
specified retrofit objective, and the optimum energy consumption and the network
retrofit requirements.
The optimum process changes to the distillation column do not require any capital
investment because they are only changes to the operating conditions. The HEN
retrofit requirements include the total additional exchanger area and the type of
network modifications, which can be determined from the optimum energy
consumption and the HEN retrofit curve.
9. The detailed retrofit implications including the additional area to each exchanger
unit can be determined by reconsidering the existing HEN and the optimum process
conditions.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
141
As known, for non-linear optimisation problems, global solutions cannot be guaranteed
(Edgar and Himmelblau, 1998). Hence, the optimisation with different initial values of
the optimisation variables may reveal the direction of the global solution and improve
the optimum solutions obtained. This procedure can be carried out repeatedly till a
satisfactory solution is obtained.
Figure 5.5: Overall procedure for heat-integrated crude oil distillation systems
The overall retrofit procedure can be applied to any crude oil distillation column and the
associated heat recovery system for various objectives, as will be explained in the next
sections.
5.5.1. Retrofit for energy reduction
Applying the retrofit approach can reduce energy consumption of existing crude oil
distillation units. The objective is therefore to minimise the total annualised cost of
utility consumption, stripping steam, and exchanger network modifications. The
optimisation results in the optimum process changes of the distillation column and the
minimum total of utility consumption and modification costs of the existing exchanger
network. The energy consumption can be further reduced by installing preflash or
prefractionator units, and using heat transfer enhancement. In these cases, the selected
modification is applied to the existing unit, and then the retrofit approach is applied.
Therefore, the objective is to minimise the total annualised cost including the cost of the
installed units and the operating costs and the network modification costs. The results of
Retrofit shortcutmodels
PA3
LD
HN
LNWater
PA2
HD
Steam1RES
PA1
Feed
Steam2
HEN
Column decomposition
Optimiser(SQP)
Existing HEN retrofit model
Optimum existing system
Water
LN
HN
LD
Steam2
HD
Steam1
RES
PA3
PA2
Feed
PA1
Existing system
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
142
the approach will include the optimum location and the sizing of the installed unit. The
location of the installed unit in the existing preheat train is determined by the optimum
temperature of the feed entering these units.
5.5.2. Retrofit for throughput enhancement
Increasing the throughput of existing crude distillation column is limited by the
hydraulic capacity limitations and the maximum heat load of the process furnace. Each
column has an actual diameter which cannot be exceeded. When the diameter required
for separation is smaller than the actual one, the column can allow the throughput to be
increased. The maximum throughput increase can be determined from the information
of the required diameter for separation and the actual diameter. This can be done by
using the FUA technique (Liu, 2000). Alternatively, it can be determined from the
hydraulic analysis evaluation, as discussed in Chapter 4. The retrofit approach is applied
for increasing the throughput of an existing crude oil distillation unit. In this case, the
feed flow rate is, therefore, an optimisation variable. The HEN retrofit model needs to
be modified to include the effect of throughput increase. The procedure of Section 4.2 is
thus applied for different feed flow rates. Therefore, the retrofit model may have the
form of equation 5.4, taking into account the effect of feed flow rate. The form of
equation 5.4 was found suitable for the data obtained. The equation has power form, and
relates the retrofit exchanger area with both the feed flow rate and energy demand. The
objective in these retrofit situations is to maximise the profit by changing the crude oil
feed flow rate. The maximum throughput increase, as well as the optimum operating
conditions can be determined from the optimisation results. The network retrofit
requirements are also obtained.
( )( ) Fnnreq EFmmA 10
10++= (5.4)
On the other hand, by modifying the structure of the existing distillation flowsheet,
throughput can be increased further. The modifications are the installation of a preflash
drum or a prefractionator column to the existing distillation column, and the
replacement of column trays with packing. Similarly, the retrofit approach is then
applied to the existing unit with the modifications for increasing the throughput.
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
143
5.5.3. Retrofit for profit increase
In the case of reducing energy consumption, the product flow rates are kept constant.
However, product flow rates can be allowed to change in order to maximise profit for a
given feed flow rate. In this case, the retrofit approach is applied to increase the net
value of the products through changing the flow rates, and reduce the process expenses;
hence the profit is maximised. The results in this situation are the maximum profit
together with the optimum product flow rate distribution. The optimum operating
conditions and the heat exchanger network modifications are also resulted.
5.5.4. Retrofit for CO2 emissions reduction
The retrofit approach can be applied to reduce the environmental impact of an existing
crude oil distillation unit. The objective is to minimise the total annualised cost of the
carbon tax, and the operating costs and the network modification costs. The
optimisation results will be the optimum operating conditions and the network
modifications. On the other hand, a gas turbine can be integrated to reduce the CO2
emissions further. The results in this case include the optimum operating conditions, the
optimum size of the gas turbine and its load, and the heat exchanger network
modifications.
5.5.5. Retrofit for product/feed specification changes
Due to the change in the market demands and the specifications of the crude oil,
refineries may process new feed specifications or change the product specifications.
Changes in product specifications include the increase of a specific product at the
expense of another one. The retrofit approach can be applied for these situations, in
which the new product specifications (key component recoveries) need to be specified.
The retrofit approach results in the optimum operating conditions required for the new
changes to the feed or the product specifications. The required exchanger network
modifications are also obtained.
5.6. Summary and conclusions
In this chapter, an optimisation-based approach for retrofit design of heat-integrated
crude oil distillation systems has been developed. The distillation columns and the
Chapter 5 Retrofit design of heat-integrated crude oil distillation systems
144
associated heat recovery systems are considered simultaneously. The column retrofit
models consider the existing designs of distillation columns, while the HEN model
accounts for the details of the exchanger networks. The hydraulic limitations of the
distillation columns are also taken into account. The effects of the interactions between
the distillation column and exchanger network on the performance of the overall system
have been discussed. These interactions are considered simultaneously in the retrofit
approach.
An optimisation framework has been established for the retrofit of heat-integrated crude
oil distillation systems. The overall retrofit problem is formulated as a non-linear model
by combing the individual retrofit models. The column retrofit models, the HEN model
and the other models are included in the optimisation framework. Successive quadratic
programming (SQP) method is employed for the non-linear optimisation problem. The
objective functions of the optimisation are flexible and account for various retrofit
objectives such as energy saving, throughput enhancement, emissions reduction, etc.
The procedure for applying the retrofit approach has been discussed.
Although the application of the retrofit approach has been presented individually for
certain objectives, the approach can apply for combined objectives or modifications.
This means that, for instance, preflash or prefractionator units can be installed in the
retrofit for the emissions reduction or the change in feed/product specifications.
Similarly, the gas turbine can be integrated with the process for the energy reduction
objectives.
The retrofit approach presented in this work has advantages over previous work. These
advantages are the simultaneous consideration of the distillation and exchanger network
systems, the accounting for the hydraulic limitations of the distillation columns.
Furthermore, the new approach handles various objectives; besides, it considers
structural modifications.
In the next chapter, case studies will be presented to illustrate the applications of the
retrofit approach to crude oil distillation units.
Chapter 6 Case studies
145
Chapter 6: Case studies
In this chapter, the retrofit approach, presented in Chapter 5, is applied to different case
studies for the purposes of illustration. Various retrofit goals are considered. Case
studies are based on industrial and textbook data. For each case study, the problem data
and specifications are presented, the objective is set, and the key results of the approach
are discussed. Supplementary data are given in appendices for each study. The case
studies are categorised according to the retrofit objectives.
Unit costs of utility and stripping steam, capital costs per unit area of exchanger units
and utility data will be given for the first case study. Then, the same data are used
throughout all case studies; otherwise, it is stated that the data are different and new
values are provided. This is valid for any problem data which are not given for a
particular case study.
6.1. Reducing energy consumption of an existing atmospheric crude oil distillation tower
6.1.1. Base case problem data
The base case for this case study is an atmospheric tower for crude oil distillation. The
existing column configuration, as shown in Figure 6.1, uses 3 side-strippers and 3
pump-arounds. Figure 6.1 also shows the equivalent sequence of four simple columns.
Steam at 4.5 bar and 260 oC is used for stripping at the bottom of the main column and
in the bottom side-stripper, while reboiling is employed in the top and middle side-
strippers. The distillation aspects of the case study are based on a textbook example of
an atmospheric crude oil distillation tower; the crude oil mixture is the assay of Tia
Juana Light (Venezuela) (Watkins, 1979). The column design was presented by
Suphanit (1999) as an illustrative case study for applying a new grassroots model for
design of crude oil distillation columns. The design was carried out by following the
design insights for crude oil distillation columns presented by Watkins (1979). These
design insights include the column configuration, limited number of stages in each
section for a specific separation, calculations of steam flow rates, crude oil feed
preheating temperature, etc. The existing heat exchanger network is based on industrial
Chapter 6 Case studies
146
data; the network structure is shown in Figure 6.2. The true boiling data of the crude oil
are given in Table 6.1. This assay is cut into 25 pseudo-components by using HYSYS
(1999) process simulator; the flow rates and normal boiling temperatures of these
components can be seen in Table C.1.1 (Appendix C).
The existing distillation tower processes 100,000 barrels per day (2610.7 kmol/h) of
crude oil to produce five products: light naphtha (LN), heavy naphtha (HN), light
distillate (LD), heavy distillate (HD) and residue (RES). The key components for the
separation of each pair of products are shown in Table 6.2. The crude oil, shown in
Figure 6.2 as the first cold stream, is heated from 25 oC to 226.5 oC by exchanging heat
with process hot streams in preheat train, and is then further heated in the furnace to 365 oC before entering the distillation tower. The existing numbers of stages in each section
of the atmospheric distillation tower are given in Table 6.3, for the various sections and
side-strippers. The actual column diameters are also provided in Table 6.3. The current
hot and cold utility requirements of the crude oil distillation tower are 99.0 MW and
83.3 MW respectively, with total operating cost of 17.018 MM$/yr, including stripping
steam cost. The unit operating costs of the individual utilities and stripping steam can be
seen in Table C.1.2 (Appendix C). The existing process requirements, including energy
requirement and operating costs, are summarised in Table C.1.3 (Appendix C). The
existing heat exchanger network contains 27 exchanger units, including the process
furnace, with a total area of 4015.8 m2. The detailed exchanger data of existing area,
heat loads, U×A values and temperature differences are summarised in Table C.1.4
(Appendix C). Data for process hot and cold streams and utility streams, which are
shown and numbered in Figure 6.2, are given in Table C.1.5 (Appendix C). Data
include supply and target temperatures, and the enthalpy change of each stream.
The current operating conditions of the distillation tower base case are summarised in
Table 6.4, for the equivalent simple sequence. These operating conditions are the feed
preheating temperature, flow rate and temperature difference of the liquid through
pump-arounds, flow rate of stripping steam and the reflux ratio. Table 6.4 also provides
the product flow rates and recoveries of light and heavy key components in each
Figure 6.1: Atmospheric crude oil distillation column, showing the equivalent sequence of simple columns (numbers in (a) refer to section numbers, while in (b) refer to column numbers)
Figure 6.2: Structure of existing heat exchanger network (streams data are given in Table C.1.5, Appendix C) (light shaded exchangers indicate heaters; dark shaded exchangers indicate coolers)
*: component recoveries are calculated based on the fresh feed to the distillation tower
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6.1.2. Retrofit objective and approach results
The purpose of the case study is to reduce the energy consumption and operating costs
of the existing unit. Therefore, the objective of the optimisation is to minimise the total
annualised costs of utility consumption and stripping steam and the exchanger network
modification costs. Before applying the retrofit approach to the case study, the retrofit
curve for the existing network is obtained, by following the procedure of Section 4.2
(Chapter 4). Details of the retrofit study are summarised in Appendix C.2. The
parameters of the retrofit model (see equation 4.7, Chapter 4), obtained from data
regression analysis (Figure C.2.1, Appendix C), are 9.731276·106 and -1.6959
respectively. Where the units of area are m2 and those of energy demand are MW.
To reduce the energy consumption and operating costs, the retrofit approach is applied
to the existing unit. The established retrofit approach procedure, presented in Chapter 5,
is applied. The existing column distillation design is fixed, including number of real
stages, column configuration and existing diameter. The structure of the existing heat
exchanger network is fixed, as are the exchanger area and heat loads. The operating
conditions of the distillation column, indicated in Table 6.5, are optimised
simultaneously to minimise the total annualised cost of utility and steam consumption,
and exchanger network modifications.
The lower and upper limits for the feed preheating temperature are 100 and 370 oC
respectively, while for the pump-around temperature drops, these limits are 10 and 80 oC respectively. The flow rate of stripping steam in optimisation is replaced by the
partial pressure at the feed stage; then, these limits are taken as that the lower limit is
1% of the column pressure and the upper limit is 99% of the column pressure (Suphanit,
1999). The reflux ratio boundaries are between the values 1.05 and 2.0 of the minimum
reflux ratio. The flow rates of the liquid between different columns are related to the
reflux ratio of hypothetical condenser at the top of the downstream column; therefore,
the limits of the liquid flow rates are corresponding to the reflux ratio limits. Similarly,
the flow rates of the liquid across the pump-arounds are calculated as function of the
degree of thermal coupling (Suphanit, 1999). Therefore, when the degree of thermal
coupling is equal to zero, the flow rate of the pump-around liquid is minimal (i.e. no
pump-around exists); on the other hand, at full thermal coupling (i.e. degree of thermal
coupling is 1.0), the liquid flow rate is maximal. These limits of the optimisation
Chapter 6 Case studies
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variables will be used throughout all studies in this chapter.
Table 6.5: Optimisation variables for crude oil distillation tower
Column Optimisation variables 1 1. Feed preheating temperature
2. Flow rate of pump-around liquid 3. Temperature drop across pump-around 4. Flow rate of stripping steam
2 5. Flow rate of pump-around liquid 6. Temperature drop across pump-around 7. Flow rate of stripping steam
3 8. Flow rate of pump-around liquid 9. Temperature drop across pump-around 10. Flow rate of liquid between columns 3 and 4
4 11. Reflux ratio
During the optimisation, the existing designs of distillation column and heat exchanger
network are fixed, while the feed preheating temperature, flow rate of steam and pump-
around liquid, pump-around temperature drop, flow rate of liquid between column
sections and the reflux ratio are changed at the same time in order to minimise the
operating cost of the process and the network modification capital costs. The existing
column diameter is imposed as a constraint to the optimisation; therefore, the results
will ensure that the optimum column operation is feasible. The flow rates of the various
products are also fixed.
The optimum operating conditions that give minimum total annualised cost are
summarised in Table 6.6, and are compared with the values of the base case. The
product flow rates of the optimum unit are given in Table C.3.1 (Appendix C), and
compared with those of the existing unit. Table C.3.2 (Appendix C) compares the key
component recoveries of the products for the optimum unit well with those for the
existing unit. The stream data of the optimum crude oil distillation unit are summarised
in Table C.3.3 (Appendix C).
Table 6.6 indicates that the existing crude oil distillation unit performs relatively far
from the optimum conditions. As seen, the crude oil feed temperature needs to be
increased by 5 oC over the current value. This affects the opportunities for recovering
more heat from the distillation hot products and internal streams. Also, the optimum
distribution of the pump-around duties changes from the existing unit. For example, the
optimum pump-around of column 1 will operate at higher temperature of 301.7 oC,
compared to 299.1 oC for the existing unit; this creates more opportunities for heat
Chapter 6 Case studies
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recovery. In addition, the pump-around of column 2 will operate optimally at 258.0 oC,
versus 252.1 oC in the existing unit. Therefore, the quality of heat sources is improved.
Furthermore, the optimum liquid flow rate between columns 3 and 4 and the reflux ratio
are reduced. This results in reduced heat loads in the reboilers of these columns from
9.4 and 6.7 MW for the existing unit to 5.8 and 3.1 MW for the optimum unit
respectively.
Table 6.6: Optimum values of operating conditions
Column Optimisation variable Base case value
Optimum value
Feed preheating temperature oC 365 370 Flow rate of pump-around liquid kmol/h 2186.56 1698.56 Temperature drop across pump-around oC 30.00 40.10
1
Flow rate of stripping steam kmol/h 1200.00 1078.04 Flow rate of pump-around liquid kmol/h 2305.66 2762.49 Temperature drop across pump-around oC 50.00 37.27
2
Flow rate of stripping steam kmol/h 250.00 218.63 Flow rate of pump-around liquid kmol/h 5790.85 8348.25 Temperature drop across pump-around oC 20.00 15.94
3
Flow rate of liquid between columns 3 and 4
kmol/h 1067.48 866.33
4 Reflux ratio 4.78 3.66
It is apparent that these process changes do not require expensive modifications to the
existing column equipment. This is because that while these conditions are obtained, the
hydraulic constraints of the existing distillation equipment are satisfied.
Table 6.7 summarises the energy consumption of the optimum crude oil distillation unit,
operating cost savings, and the capital cost of the modifications. Modifications are only
required to the existing heat exchanger network (Figure 6.3). One topological
modification to the existing exchanger network is determined from the optimisation
results, i.e. the optimum energy consumption of 86 MW corresponds to one structural
modification in the retrofit curve data. The HEN modifications include the addition of
exchanger area to some exchanger units, as indicated in Figure 6.3, and the relocation of
exchanger number 4 from the existing location to the location that is shown in the same
figure. This modification is the most beneficial one recommended by network pinch
analysis for the optimum process conditions. When the topology modification is
implemented in the exchanger network with the optimum process conditions, the energy
consumption is reduced significantly to 76 MW. The details of the additional area and
capital cost are given in Table C.3.4 (Appendix C). The capital cost, given in Table 6.7,
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is that required for the additional exchanger area. The cost of the resequence
modification is neglected; the costs of the piping work, as illustrated in Figure 6.4, are
expected to be minor. However, if the piping work and material costs, in other
situations, are significant, the cost implications can be included in the economic
analysis.
Table 6.7: Energy consumption and operating costs for optimum unit
Parameter Existing unit
Optimum unit
% Reduction
Hot utility demand MW 99.0 76.4 22.8 Cold utility demand MW 83.3 60.9 26.9 Furnace heat load MW 73.5 62.4 15.1 Crude oil temperature before furnace
oC 226.5 233.1 -
Utility operating cost MM$/yr 15.284 11.772 22.9 Stripping steam operating cost MM$/yr 1.734 1.551 10.6 Additional exchanger area m2 - 1407.3 - HEN capital investment MM$ - 0.393 - Total operating cost MM$/yr 17.018 13.323 22.5 ∆Tmin oC 30.0 25.0 - Payback yr - 0.11 -
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C)
8
3
9
7
6
1
2
2 5
1 82 2
1 5 7 9
1 3 2 6 8 1 0
11
12
14
4
5
13
1 2
10
1 41 13
2 1
1 9
1 6
1 7
1 5
2 6
2 7
2 4
2 3
2 8
Additional area
44
Relocation
4
Figure 6.3: Modifications to existing heat exchanger network
Chapter 6 Case studies
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4
2 2
2 7
2 1 1 8 1 5
10
1
3
621 31 4
Existing location
New location
Figure 6.4: Relocating exchanger number 4 in the existing exchanger
network
As seen in Table 6.7, the hot utility demand of the optimum unit reduces significantly to
76.4 MW (including furnace duty) with saving of 22.6 MW over the existing unit
demand. The total operating cost savings are approximately 3.7 MM$/yr, while the
capital investment required is relatively small. The savings in energy consumption and
operation costs are achieved without requiring any expensive modifications to the
existing column, because the results of the optimum operating conditions take into
account the existing diameter. The payback required is very low (0.1 year), as the
modifications required to the existing exchanger network are minor and relatively
inexpensive.
The case study considered in this section shows that the new retrofit design approach is
applicable to an existing crude oil distillation column and the associated heat recovery
system for reducing energy consumption and operating costs. Significant reductions in
energy consumption and operating cost are reached with low payback time. The
application of the retrofit approach reveals that existing designs of heat-integrated crude
oil distillation systems can perform more efficient by changing the operating conditions
of the distillation process. These changes are easy and do not demand expensive
modifications to the existing column structure; only minor changes to the exchanger
network are necessary.
The results of the above case study were obtained for the given crude oil specifications
(i.e. crude assay, density, etc.) and for fixed production capacity. If the specification of
Chapter 6 Case studies
154
crude oil changes due to processing new feedstock or mixing two different crude oils,
the results of the optimum operating conditions and network modification requirements
might not be optimum for the new case. Therefore, the retrofit approach needs to be
reapplied to the new feed specification case, in which the new data of the crude oil are
specified. A new set of optimum operating conditions can be obtained for the new feed
specifications; the modifications required by the existing exchanger network are also
evaluated. However, the retrofit approach can be repeatedly applied for various crude
feedstocks, each of which has different feed specifications; thus, satisfactory set of
operating conditions and exchanger network modifications can be selected which satisfy
the different feed specifications. The heat exchanger network modifications which can
handle the process heating and cooling requirements for all the range of feed
specifications are selected; therefore, the capital investment obtained will account for
the requirements of the different feed specifications. The operation of the distillation
column can then be manipulated using the control system with different set points, each
set point is for one set of optimum operating conditions required for a particular feed
specifications. Therefore, the distillation column operator can select the set point that
corresponds to the operating conditions which suits the processed feed specifications.
On the other hand, for increasing the crude oil capacity of the distillation unit, the
approach can be applied to the unit with the new conditions; this case will be considered
in Section 6.3.
6.1.3. Comparison of new retrofit approach with previous work
The new retrofit approach is compared with previous research work to emphasise the
advantages of the approach over conventional approaches. As mentioned in earlier
chapters, the major limitations of previous approaches are: none has considered the heat
exchanger network in retrofit at the same stage as the distillation column, they have
considered heat integration targets and not the details of the heat exchanger network and
they cannot guarantee feasible distillation operation. For the comparison of the new
retrofit approach with the previous research work, two previous approaches are selected
to be applied to the same existing heat-integrated crude oil distillation unit. The first
approach is network pinch analysis (Asante, 1996), whereas the second is the energy
target-based approach (Bagajewicz, 1998). These two approaches are selected for
comparison because they represent two different advantageous retrofit philosophies, i.e.
Chapter 6 Case studies
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the first is for retrofit of heat exchanger networks, while the second is for retrofit of
heat-integrated crude oil distillation systems (see Chapter 2).
The network pinch analysis is applied to the same existing heat exchanger network to
reduce the energy consumption and the utility costs. Note that the process streams data
are the same as those for the base case of the existing unit. The additional area required
to the existing exchanger units and the associated capital costs are summarised in Table
C.4.1 (Appendix C). An existing exchanger unit needs to be relocated to a new location,
as shown in Figure C.4.1 (Appendix C). The network pinch approach does not consider
changes to the distillation process operating conditions; it only considers modifying the
existing exchanger network for reducing energy consumption.
On the other hand, the approach based on the optimisation of the existing crude
distillation unit with respect to the energy target is applied. The operating conditions of
the existing distillation column are optimised to minimise the energy cost calculated
from energy target calculated in turn by pinch analysis. The details of the existing heat
exchanger network are not accounted for. Although for the purpose of comparison, the
retrofit of the existing heat exchanger network is considered to provide the additional
exchanger area and capital cost values. The results of the optimum operating conditions
from this approach are detailed in Table C.4.2 (Appendix C) and compared with those
obtained from the new retrofit approach. The additional area to the existing exchangers
and capital costs are given in Tables C.4.3 (Appendix C). The energy target-based
approach does not consider the distillation process simultaneously with the existing heat
exchanger network; it only optimises the operating conditions of the distillation process
to minimise energy cost. It also does not account for both the retrofit exchanger area and
the capital costs required during the optimisation.
The results of these approaches are given in Table 6.8, compared with the new retrofit
approach. Table 6.9 compares the different results of the additional area to the
individual exchanger units.
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Table 6.8: Comparison of new approach results with previous work
Parameter New approach
Energy based
Network pinch
Hot utility demand* MW 76.4 92.7 83.1 Cold utility demand MW 60.9 77.1 67.49 Furnace heat load MW 62.4 72.1 60.00 Crude oil temperature before furnace
oC 233.1 206.9 233.9
Utility operating cost MM$/yr 11.772 14.304 13.252 Stripping steam cost# MM$/yr 1.551 1.681 1.734 Additional exchanger area m2 1407.3 136.1 1668.0 ∆Tmin oC 25.0 25.0 25.0 HEN capital investment MM$ 0.393 0.111 0.414 Total operating cost+ MM$/yr 13.323 15.985 14.986 Total operating cost savings MM$/yr 3.695 1.033 2.032 Payback yr 0.11 0.11 0.21
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: base case energy consumption = 99.0 MW; +: base case total cost = 17.018 MM$/yr; #: base case steam cost = 1.734 MM$/yr
Table 6.9: Comparison of additional area to existing exchanger
*: utility consumption and stripping steam; +: income from products - operating costs - feed cost
The optimisation results are summarised in Table 6.11, including the optimum product
flow rates, operating costs, capital investment and the net profit. Table 6.11 shows that
the net profit of the optimum unit increases by about 6.7 MM$/yr above the profit of the
existing unit. The capital investment required by the modifications to the HEN is 0.4
MM$/yr. The exchanger network modifications are additional area to existing units and
relocating an existing exchanger, as shown in Figure D.1 (Appendix D); the detailed
additional area to exchanger units and the associated capital costs can be seen in Table
D.2 (Appendix D). The modification costs are for the capital costs of the additional area
to the existing HEN, since the cost of the relocation modification is not expected to be
significant (see Figure 6.4). The new product flow rates distribution shows that the
residue flow rate increases by 4.36%; and the light and heavy distillate flow rates
decrease by 0.90% and 1.30% respectively, based on the crude oil feed volumetric flow
rate. It is clear also from Table 6.11 that the flow rates of both the light and heavy
naphtha products do not change significantly with respect to the existing unit flow rates.
At the optimum operating conditions, the product flow rates allow the products value to
increase relative to that of the existing unit. The optimum operating conditions for
maximum profit are summarised in Table 6.12. Table D.3 (Appendix D) provides the
stream data of the optimum unit. As the product flow rates distribution changes with
respect to the existing unit, the product key component recoveries change. Table D.4
(Appendix D) provides the new recoveries of the product key components compared
with those of the existing unit.
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Table 6.11: Retrofit results of optimum unit with maximum profit
Stream Production capacity (bbl/d)
Products value (MM$/yr)
Light naphtha (LN) 12,100 220.736 Heavy naphtha (HN) 11,775 202.179 Light distillate (LD) 21,217 203.674 Heavy distillate (HD) 5,512 52.105 Residue (RES) 53,588 312.171 Energy and cost savings Operating* costs (MM$/yr) 14.386 Energy consumption (MW) 83.7 HEN additional area (m2) 1120.6 Capital+ investment (MM$) 0.384 Net++ profit (MM$/yr) 371.741 *: utility consumption and stripping steam costs; +: HEN additional area costs; ++: products value - operating costs - feed cost
Table 6.12: Optimum values of operating conditions for maximum profit
Column Optimisation variable Optimum value
Base case value
Feed preheating temperature oC 343.90 365.00 Flow rate of pump-around liquid kmol/h 1285.21 2186.56 Temperature drop across pump-around oC 33.99 30.00
1
Flow rate of stripping steam kmol/h 1017.30 1200.00 Flow rate of pump-around liquid kmol/h 1827.53 2305.66 Temperature drop across pump-around oC 46.81 50.00
2
Flow rate of stripping steam kmol/h 214.70 250.00 Flow rate of pump-around liquid kmol/h 5453.02 5790.85 Temperature drop across pump-around oC 24.79 20.00
3
Flow rate of liquid between columns 3 and 4
kmol/h 1037.57 1067.48
4 Reflux ratio 4.87 4.78
The results obtained were based on given prices of the product and crude oil feed (Table
D.1, Appendix D). Therefore, these results may not be optimum for any fluctuation
occurred in the prices, which are related to market needs. The study can then be
performed using different prices in order to find the best distribution of product flow
rates and optimum process changes that lead to maximum profit covering wide range of
unit prices. The study will result in different optimum operating conditions and
exchanger network modifications for the different product and crude oil prices
employed. The exchanger network modifications that can provide the process heating
requirements for all the different prices can be chosen. Therefore, the associated capital
cost will account for all capital costs required by the different product and crude oil
prices. On the other hand, the control system of the distillation column operation can
Chapter 6 Case studies
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use different set points for the different optimum operating conditions obtained. Then,
the distillation column operator can select the operation set point according to the
refinery policy and any changes in the market demands and prices.
As seen in this case study, the net profit of existing crude oil distillation unit can be
increased by changing the product flow rates distribution through new process operating
conditions, for the same crude oil feed capacity. Note that in the previous case study, the
operating cost and energy consumption were reduced for the same crude oil feed
capacity and the same product flow rates distribution. The two cases are compared in
Table 6.13. The comparison shows that when the product flow rates of the existing
process are allowed to change, the net profit increases significantly compared with the
case in which the product flow rates are fixed. The net profit in this case increases by
6.7 MM$/yr, compared with 3.7 MM$/yr for the case of fixed product flow rates. As
would be expected, the energy savings are greater when the objective is energy
reduction (22.6 MW) than when the objective is profit improvement (15.7 MW).
Therefore, according to the strategy of the refinery operator and the market demands,
the most appropriate retrofit objective can be chosen.
Table 6.13: Comparison of energy reduction and increasing profit optimum cases
Parameter Existing unit
Energy reduction
Increasing profit
Income from products * MM$/yr 382.074 382.024 386.127 Total+ operating costs MM$/yr 17.018 13.323 14.386 Energy consumption MW 99.0 76.4 83.7 Additional exchanger area m2 - 1361.4 1120.6 HEN capital investment MM$ - 0.404 0.384 ∆Tmin oC 30.0 25.0 25.0 Net++ profit MM$/yr 365.056 368.701 371.741 Increase in net profit MM$/yr Base 3.645 6.685
*: products value - feed cost; +: utility and steam costs; ++: income from products - operating costs
The case study of this section illustrates that the new retrofit approach can be applied to
increase the profit of existing crude oil distillation process. The objective is achieved
with minor modifications and low payback time. This will allow the refinery to increase
the profit significantly from the crude oil distillation unit with inexpensive
modifications; this profit improvement takes into account the price changes of the oil
products. In addition, the refinery will have more operational options to be selected, i.e.
reduce energy demand or increase profit.
Chapter 6 Case studies
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6.3. Increasing throughput of an existing atmospheric crude oil distillation tower
This section includes two parts for throughput enhancement of existing crude oil
distillation unit; the first is for increasing the current throughput by a given value, and
the second is for increasing the current capacity to the maximum. The maximum
capacity increase is the capacity that can be processed in the existing column without
requiring any structural modifications to the existing internals. A 20% increase in the
production capacity is set as an objective for the first part. In the second part, more
attention is paid to the hydraulic constraints of the existing distillation column to
evaluate the potential for increasing its capacity. Any enhancement retrofit project lies
within these two parts; however, in some situations, refineries aim to increase the
capacity above the maximum capacity. In this case, column modifications, such as
adding preflash unit or prefractionator column, or replacing column internals with
packing, are essential for debottlenecking purposes.
6.3.1. Increasing current throughput by 20% over base case capacity
The crude oil atmospheric distillation unit, presented in Section 6.1, is reconsidered in
this section as the base case. The data of the crude oil feed and the details of the existing
structures of distillation column and heat exchanger network are the same as those given
in Section 6.1 (Figures 6.1 and 6.2). The current process capacity is 100,000 barrels per
day of crude oil. Five products are obtained: light and heavy naphtha, light and heavy
distillate and residue. The operating conditions of the base case and the product flow
rates are summarised in Table E.1.1 (Appendix E). The details of the exchanger areas
and heat duties in the existing exchanger network are given in Table E.1.2 (Appendix
E); the process streams and utility data, including temperatures and enthalpy changes
are summarised in Table E.1.3 (Appendix E). Table 6.14 gives the energy consumption
of the existing unit, the operating costs and the current net profit. The current energy
consumption is 99.5 MW of hot utility; the total operating cost, including stripping
steam, is 17.093 MM$/yr. The existing exchanger network has total area of 3552.8 m2.
Table 6.15 provides the diameter required for separation in the base case, compared
with the actual column diameter.
The objective of the retrofit in this case study is to increase the current throughput of the
Chapter 6 Case studies
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existing crude oil distillation unit by 20% (i.e. the new capacity is 120,000 bbl/d) and
reduce the associated operating cost per barrel of feed and minimise capital investment.
Table 6.14: Energy consumption, operating costs and profit for base case
Parameter Base case Hot utility consumption MW 99.5 Cold utility consumption MW 83.8 Furnace heat load MW 73.9 Crude oil temperature before furnace oC 196.8 Utility operating cost* MM$/yr 15.359 Stripping steam operating cost* MM$/yr 1.734 Total operating cost MM$/yr 17.093 Existing exchanger network total area m2 3552.8 ∆Tmin oC 30.0 Crude oil cost MM$/yr 604.737 Income from products MM$/yr 986.487 Net+ profit MM$/yr 364.657
+: products value - operating costs - feed cost *: utility and steam unit costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C)
Table 6.15: Column diameter required for base case and actual diameter
Column diameter+ (m) Column section*
Base case Actual diameter
Main column section 1 3.63 5.50 Main column section 2 7.00 8.00 Main column section 3 6.78 8.00 Main column section 4 6.78 7.50 Main column section 5 6.12 7.00 Top side-stripper 2.37 3.00 Middle side-stripper 2.90 3.50 Bottom side-stripper 1.35 3.00
*: see Figure 6.1; +: model used for diameter calculations (Section 4.1.1, Chapter 4), tray spacing = 0.6 m, flooding factor = 0.7, down-comer area ratio = 0.12
The initial calculations of the 20% throughput increase result in the required diameter
given in Table 6.16. The calculation assumptions are given with Table 6.15. These
diameters are obtained by increasing the throughput of the base case by 20% using the
retrofit models presented in Chapter 3. The diameter results show that the operation of
the column with 20% increased capacity is feasible, i.e. the capacity increase is
achievable without any column bottlenecks. The flow rate of the stripping steam to the
main column and stripper, pump-around duties and liquid recycled at the top of the
column are also increased by 20% to yield the required product flow rates with the same
product specifications as those for the base case. The operating conditions of the unit
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with 20% capacity increase, including product flow rates, pump-around duties and flow
rates, etc., are summarised in Table E.2.1 (Appendix E). The resultant requirements of
the existing exchangers, to meet the new heating and cooling demands, are summarised
in Table 6.17.
Table 6.16: Column diameter for 20% increase in throughput on base case
Column diameter (m) Column section*
20% Increase Actual diameter
Main column section 1 3.97 5.50 Main column section 2 7.66 8.00 Main column section 3 7.50 8.00 Main column section 4 7.43 7.50 Main column section 5 6.70 7.00 Top side-stripper 2.59 3.00 Middle side-stripper 3.17 3.50 Bottom side-stripper 1.48 3.00
*: see Figure 6.1
Table 6.17: Process requirements for 20% increase in throughput
*: including steam to main column and stripper (see Figure 6.1) +: products value - operating costs - feed cost
As stated above, the required diameter for 20% increase in the throughput of the crude
oil distillation tower does not exceed the existing column diameter. However, if there is
violation of the existing diameter, the column will be bottlenecked. In this case, the
operating conditions of the distillation column need to be modified, as discussed in
Section 5.3 (Chapter 5), to remove the hydraulic bottlenecks. This may include
changing the pump-around temperature drop, flow rates of steam or recycled liquid in a
Chapter 6 Case studies
164
pump-around, or reflux ratio or the feed preheating temperature.
Table 6.17 shows that the distillation unit with 20% increase in capacity consumes
energy of 117.7 MW, with an increase of about 20% over the current energy capacity.
The heat load in the furnace also increases from 73.9 MW for the base case to 86.6
MW. This however may lead to energy bottleneck in the fired heater, if it currently
operates at the maximum heat load. Then, the study in this case becomes energy
debottlenecking and throughput enhancement. In this study, it will be assumed that the
maximum furnace duty is 73.9 MW. The exchanger units that need to be modified are
shown in Figure E.2.1 (Appendix E); the associated additional area and capital costs can
be seen in Table E.2.2 (Appendix E). The temperatures and enthalpy changes of the
exchanger network process streams are given in Table E.2.3 (Appendix E).
The retrofit approach can now be applied to the new case of 20% increased capacity.
The case then becomes similar to the case study considered in Section 6.1; some key
differences will be discussed later.
As the throughput of the distillation column increases, the product and internal stream
flow rates change significantly compared to the base case flow rates. The retrofit model
obtained in Section 6.1, for the existing heat exchanger network cannot be used for the
optimisation of the unit with 20% increased capacity. The reason is that this model,
however, accounts for the details of the existing heat exchanger network, it is obtained
for the stream data (i.e. temperatures, flow rates and enthalpy changes) of the existing
unit and not the enhanced unit. The model therefore does not account accurately for the
area and energy requirements for the unit with 20% increase in throughput; thus, a new
retrofit model needs to be obtained.
The retrofit model of the HEN unit with 20% enhanced throughput is obtained by
applying the procedure of Section 4.2 (Chapter 4). Details of the retrofit study
performed are summarised in Appendix E.3. The retrofit model parameters m and c (see
equation 4.7, Chapter 4), are calculated from data regression (Figure E.3.1, Appendix
E), and their values are 1.002176·108 and -2.1016 respectively, where the units of area
are m2 and of energy consumption are MW. Figure E.3.6 (Appendix E) compares the
retrofit model of the enhanced throughput with that of the existing unit. As seen in
Figure E.3.6 (Appendix E), the retrofit model of the existing unit underestimates the
retrofit area required for the unit with 20% increase in capacity.
Chapter 6 Case studies
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Now, the existing designs of the distillation column and the associated heat exchanger
network are fixed, the operating conditions of the distillation column, with 20%
increase in throughput, are optimised simultaneously to minimise the total annualised
cost of the utility consumption, stripping steam and the exchanger network
modifications. Throughout the optimisation, the existing column diameter is fixed. The
results of energy consumption, operating costs, profit, etc., are summarised in Table
6.18. The optimum values of the optimisation variables are given in Table 6.19.
Operating conditions of the optimum unit are detailed in Table E.4.1 (Appendix E). The
optimum modified exchanger network is shown in Figure E.4.1 (Appendix E); network
modifications are additional area and relocating an existing exchanger unit. The
additional area and the associated capital costs are detailed in Table E.4.2 (Appendix E).
Table E.4.3 (Appendix E) summarises the supply and target temperatures, and enthalpy
changes of the process streams.
Table 6.18: Optimisation results for optimum unit with 20% increase in capacity
Parameter Base case
20% Increase
20% Increase optimum
Hot utility consumption MW 99.5 117.7 87.8 Cold utility consumption MW 83.8 98.9 26.9 Furnace heat load MW 73.9 86.6 72.9 Utility operating cost MM$/yr 15.359 18.180 13.540 Stripping steam cost MM$/yr 1.734 2.081 1.699 Stripping steam flow rate kmol/h 1450.0 1740.0 1419.4 Additional exchanger area m2 - 776.2 1756.9 HEN capital investment MM$ - 0.274 0.468 Total operating cost MM$/yr 17.093 20.261 15.239 ∆Tmin oC 30.0 30.0 30.0 Crude oil cost MM$/yr 604.737 725.684 725.684 Income form products MM$/yr 986.487 1,183.467 1,184,569 Net+ profit MM$/yr 364.657 437.522 443.667 Increase in net profit MM$/yr Base 73.065 79.010
u1tility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) +: products value - operating costs - feed cost
The column diameter calculated for the separation after optimisation is given in Table
6.20, and compared with the actual column diameter. It is clear that the operation of the
optimum unit with 20% increase in capacity is feasible, because the required diameter
for separation from optimisation is less than the actual column diameter.
The values of the optimisation variables in Table 6.19 indicate that the optimum feed
temperature is about 4 oC hotter than the base case temperature. This creates more
Chapter 6 Case studies
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opportunities to recover heat from process hot streams. Also, the hottest pump-around
will operate optimally at 302.7 oC, compared with 300.2 oC for the base case (100,000
bbl/d). This improves slightly the quality of the pump-around heat source. Similarly, the
reduced liquid flow rate between columns 3 and 4 reduces the heat loads in the reboilers
of these columns. As overall result, the duties of the mentioned reboilers are 6.6 and 3.5
MW respectively for the optimum unit, compared to 11.3 and 8.1 MW for the base case
(100,000 bbl/d). These process changes lead to increase in the heat recovery in the
existing HEN.
Table 6.19: Optimum values of operating conditions for 20% capacity increase
Column Optimisation variable Optimum value
Base case value
Feed preheating temperature oC 364.30 360.00 Flow rate of pump-around liquid kmol/h 3693.65 1288.16 Temperature drop across pump-around oC 16.14 40.00
1
Flow rate of stripping steam kmol/h 1172.50 1200.00 Flow rate of pump-around liquid kmol/h 5806.56 2396.30 Temperature drop across pump-around oC 31.95 50.00
2
Flow rate of stripping steam kmol/h 246.87 250.00 Flow rate of pump-around liquid kmol/h 8018.72 5867.78 Temperature drop across pump-around oC 20.36 20.00
3
Flow rate of liquid between columns 3 and 4
kmol/h 500.14 1082.16
4 Reflux ratio 2.55 4.82
Table 6.20: Column diameter for optimum unit with 20% capacity increase
Column section* Optimum unit with 20% capacity increase (m)
Actual unit diameter (m)
Main column section 1 3.86 5.50 Main column section 2 7.88 8.00 Main column section 3 7.77 8.00 Main column section 4 6.80 7.50 Main column section 5 5.35 7.00 Top side-stripper 1.87 3.00 Middle side-stripper 2.63 3.50 Bottom side-stripper 1.41 3.00
*: see Figure 6.1
As seen in Table 6.18, after optimising the process with 20% increased throughput, the
energy consumption reduces from 117.7 MW to 87.8 MW with significant savings of
energy consumption and operating costs. The results show that the furnace of the
optimum enhanced unit still operates below the maximum load; therefore, there is no
energy bottleneck for the 20% capacity increase as was the case before optimisation.
Chapter 6 Case studies
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The operating cost savings of the optimum enhanced unit based on the base case (i.e.
before throughput enhancement) are 1.9 MM$/yr, with capital investment of 0.5 MM$.
Very short time is needed for paying the network modifications capitals back. The net
profit of the optimum unit with enhanced capacity is estimated to be 79.0 MM$/yr over
the base case profit. In addition to the cost savings and profit achieved using the
optimisation, the modifications to the existing exchanger network for the optimum unit
are minor compared to the case where the capacity of the base case is increased by 20%
without optimisation. The modifications in the case of the optimum unit are additional
area to 17 exchanger units and relocating one existing unit (Figure E.2.1, Appendix E).
However, without optimisation, 23 exchanger units need to be modified (Figure E.2.1,
Appendix E), in addition to modifying the furnace.
The above study illustrates that the new retrofit approach enables the existing unit to
increase its capacity and still save energy and reduce operating costs.
6.3.2. Increasing current throughput to maximum capacity
In this case study, the maximum throughput of an industrial existing crude oil
distillation unit is determined. The original objective of the project was to increase the
capacity by 16% over the current operation. For reasons of commercial sensitivity,
details of the case study cannot be reported.
The crude oil distillation unit is based on industrial data; Figure 6.5 shows the
atmospheric configuration of the crude oil distillation column. The column uses three
side-strippers and two pump-arounds, and separates the crude oil into naphtha,
kerosene, light gas oil (LGO), heavy gas oil (HGO) and residue. Stripping steam and
reboiler are used for heating in the bottom section; all strippers use steam. The existing
unit processes 130,000 barrels per day (2933 kmol/h) of crude oil. The crude oil feed is
mixture of two light and heavy oil feedstocks, and gas stream; the molar composition of
the mixture is 82.5, 15.8 and 1.7% respectively. The number of real stages and column
diameter are given in Table 6.21. The crude oil at 43 oC is heated in preheat train to a
temperature of 246 oC, and then in the fired heater to 330 oC. A sketch of the preheat
train is shown in Figure 6.6. The total hot utility consumption is 69.235 MW; the total
Figure 6.9: Simulated stage diameter for maximum capacity increase (stages
from column top-down) (tray sizing using HYSYS)
After determining the maximum capacity, the retrofit approach can be applied to the
enhanced unit for either reducing energy consumption and costs or increasing process
profit. The approach can also be applied to the existing unit with 16% capacity increase.
In these cases, the retrofit model will be obtained for the existing heat exchanger
network. Then, the operating conditions are optimised simultaneously for the fixed
designs of distillation column and preheat train to achieve the specified retrofit
objective. As mentioned above, the throughput of the existing unit can be increased
above the maximum value. In this case, column modifications are required to remove
column bottlenecks. Then, the retrofit approach is applied to the modified unit.
The case studies presented in this section show that the retrofit approach can be applied
for increasing the throughput of an existing unit. Large savings in operating costs and
reduction in energy consumption are obtained for inexpensive modifications and with
low payback time.
6.4. Reducing CO2 emissions from an existing crude oil distillation unit
In the previous case studies, attention was paid to energy and cost savings, profit
increase and capacity enhancement. However in some situations, environmental issues
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are of great concern. The purpose in this case study is to decrease carbon dioxide
emissions (atmospheric pollution) from an existing crude oil distillation unit. The base
case is the same atmospheric crude oil tower for which data are presented in Section
6.1.1. Two hot utilities, flue gases and HP steam, are used for the heating purposes in
the heat exchanger network. Data of the hot utilities, unit costs and heat loads are given
in Table F.1.1 (Appendix F).
The current flow rates of CO2 emissions from the base case are calculated from equation
4.25 (Chapter 4), and are summarised in Table 6.22. The heating fuel used in the heat
exchanger network is heavy fuel oil; the net heating value and carbon content are given
in Table F.1.2 (Appendix F). The total CO2 emissions are calculated from the utility
steam boiler and the furnace.
Table 6.22: CO2 emissions from base case of crude oil distillation tower
Parameter Existing unit Total hot utility consumption MW 99.0 Utility steam heat load MW 9.375 Flue gas heat load MW 80.281 Stripping steam heat load MW 9.344 CO2 emissions from steam boiler kg/h 4,155 CO2 emissions from flue gas kg/h 25,632 CO2 emissions from stripping steam kg/h 2,983 Total CO2 emissions kg/h 32,766 Crude oil temperature before furnace oC 226.5 Stripping steam flow rate kmol/h 1450.0 Total operating cost* MM$/yr 16.263 ∆Tmin in existing HEN oC 30.0
*: including utilities and steam; unit costs can be seen in Table F.1.1 (Appendix F)
Note that part of the heat load required by the stripping steam is provided by the flue
gas in the furnace; the other part is provided by the process streams. The reason is that
the stripping steam is produced at the refinery site from the heat recovered from the
distillation process and heat supplied by flue gas. Therefore, the heat load on the flue
gas includes that load required by the stripping steam. So, the emissions from steam
heat loads are calculated in similar way to those from flue gas.
Table 6.22 indicates that the existing unit produces total emissions of 32,766 kg/h from
the furnace and steam boiler. The retrofit approach is now applied to optimise the
operating conditions of the existing crude oil distillation tower to reduce the carbon
dioxide emissions. Integration of a gas turbine with the process furnace is considered as
Chapter 6 Case studies
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a design option in this context. The objective is to minimise the total annualised cost of
utility consumption, stripping steam, carbon tax and the capital costs of the gas turbine
and network modifications, less the value of the power generated by the gas turbine. A
carbon tax of 15 $/ton of CO2 is assumed (Chew, 2001; p. 101). Heavy fuel oil is
utilised in the steam boiler and central power station, while natural gas is burned in the
central power station. A summary of the retrofit approach results is presented in Table
6.23. Details of the results and the economic parameters can be seen in Tables F.2.1 and
F.2.2 (Appendix F).
Table 6.23: CO2 emissions from optimised unit with integrated gas turbine
Parameter Optimum unit Total energy consumption MW 79.780 Utility steam heat load MW 6.087 Flue gas total heat load# MW 73.693 Heat load on gas turbine MW 15.588 Heat load on furnace MW 58.105 CO2 emissions from steam boiler kg/h 2,698 CO2 emissions from gas turbine kg/h 9,092 CO2 emissions from furnace kg/h 18,552 Total local CO2 emissions kg/h 30,342 CO2 emissions saved at power station kg/h -13,411 Total global CO2 emissions kg/h 16,931 Power generated in gas turbine MW 14.0 Capital cost of gas turbine MM$ 5.261 Value of power generated MM$/yr 3.920 Stripping steam flow rate kmol/h 1255.0 Total operating costs* MM$/yr 13.232 HEN capital investment MM$ 0.429 Crude oil temperature before furnace oC 230.7 Total operating cost saving+ MM$/yr 6.951 Total capital investment MM$ 5.690 Payback yr 0.82 ∆Tmin in existing HEN oC 25.0
#: including stripping steam load; *: including utilities and steam +: including value of power generated
Note that when the gas turbine is integrated, the initial total heat load of 73.693 MW in
the furnace, which includes stripping steam load, is distributed into two parts. The gas
turbine provides the first part of 5.588 MW; then, the furnace supplies the remaining
part of 58.105 MW.
As seen in Table 6.23, the total carbon dioxide reduces in the refinery site from 32,766
kg/h for the base case to 30,342 kg/h for the optimum unit with gas turbine, with
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emissions reduction of 7.4%. This reduction, however, seems little, but the emissions of
the central power station will be reduced by 13,411 kg/h of CO2 because of the decrease
in the power demand of the site. This leads to considerable reduction of 48.3% of the
emissions globally, when the power station is considered at the same time. In addition to
the emissions reduction, the refinery can increase profit by producing electricity of 14.0
MW. This power can be consumed at the refinery site or exported to other consumers.
The total operating cost savings, including the value of generated power, are about 7.0
MM$/yr. Less than a year is required to pay back the capital investment required for the
gas turbine and exchanger network modifications. The exchanger network modifications
required are additional area and relocation of one existing unit.
The optimum values of the operating conditions, obtained from the retrofit approach,
are given in Table F.2.3 (Appendix F). Details of the additional exchanger area,
modified network and the process streams of the optimum unit are summarised in Table
F.2.4, Figure F.2.1, and Table F.2.5 (Appendix F) respectively.
The results of the optimisation variables (Table F.2.3, Appendix F) indicate that by
increasing the feed temperature by about 5 oC, reducing the steam flow rates and
recycling more hot liquid through the pump-arounds, the existing crude oil distillation
system is able to reduce the emissions locally by 7% and by 48% overall.
As studied above, CO2 emissions from existing crude oil distillation unit are reduced by
applying the retrofit approach. The emissions reduction is greatest when a gas turbine is
integrated with the process furnace. If the gas turbine is not to be integrated, the retrofit
approach can also be applied. The objective in this case will be to minimise the total
annualised cost of utility consumption, stripping steam, carbon tax and the exchanger
network modifications. The approach results are summarised in Table 6.24. The details
of the modifications required to the existing exchanger network, additional area and
capital cost, optimum operating conditions and the process stream data can be seen in
Appendix F.3.
The results in Table 6.24 illustrate that the emissions from the existing unit can be
reduced by 22% without considering gas turbine, versus 7% (locally) when gas turbine
is integrated. Savings in operating costs and energy consumption are also attained for
little capital investment and with low payback time. However, the gas turbine leads to
significant global reduction of 48% in the emissions, with big income from generating
Chapter 6 Case studies
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electricity at the refinery site. Note that the two scenarios for emissions reduction save
approximately the same amount of energy; this is because that the energy costs are
dominant in this problem.
Table 6.24: CO2 emissions from optimum unit without integrated gas turbine
Parameter Existing unit
Optimum unit
Optimum unit with GT
Energy consumption MW 99.0 78.020 79.780 Utility steam heat load MW 9.375 6.157 6.087 Flue gas heat load MW 80.281 71.873 73.693 Total CO2 emissions kg/h 32,766 25,677 30,342 Total global CO2 emissions kg/h 32,766 25,677 16,931 Total operating costs MM$/yr 16.263 12.976 9.312* HEN additional area m2 - 1239.2 1459.4 Total capital investment MM$ - 0.379 5.690+ Payback yr - 0.12 0.82 ∆Tmin in existing HEN oC 30.0 25.0 25.0
*: including value of power generated; +: including cost of gas turbine
The optimum results recommend that a gas turbine is to be integrated when the
emissions in both the refinery and central power station are of interest. On the other
hand, the existing configuration can also be optimised to reduce emissions, without
changing the infrastructure of the existing heating system (i.e. the furnace).
The cases studied in this section illustrate that the carbon dioxide emissions of an
existing crude oil distillation unit can be reduced significantly by changing the operating
conditions of the distillation process. Integrating a gas turbine with the existing process
is explored for further reduction in the emissions and site profit flexibility.
6.5. Changing product yields of an existing crude oil distillation unit
This case study accounts for the changes in product yields of an existing crude oil
distillation unit; the study is based on data presented in Suphanit (1999; p. 128). The
base case of the study is the atmospheric crude oil tower and the associated heat
exchanger network presented in Section 6.1. The existing exchanger network has a
structural constraint that only additional area is allowed and any topology modifications
are forbidden. The retrofit goal is to increase the product yield of heavy distillate and
reduce the yield of light distillate in order to meet the changes in the market demand.
The yields of the light and heavy naphtha and residue products are kept fixed. The
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objective is preferably achieved with low energy consumption and operating costs and
little capital investment. The product yields of the base case are given in Table 6.25.
Key components of the separation of the products for the base case can be seen in Table
6.2 (Section 6.1).
The study aims specifically at increasing the heavy distillate yield of the existing unit by
70%, i.e. the new flow rate of the heavy distillate is 1.70 times that of the base case
(heavy distillate) flow rate. This can be done by changing the key components of the
separation between light distillate and heavy distillate, as shown in Table 6.26. The
operating conditions of the distillation column also need to be changed to obtain the
required product yields. This step is performed using the shortcut models of Chapter 3,
in which the existing design is fixed and the key components are specified. Then, the
operating conditions are changed from the base case values to achieve the required
yields. Results of the operating conditions of the modified unit are summarised in Table
G.1 (Appendix G), compared with the base case values. The product yields obtained
from the new unit are given in Table 6.27.
Table 6.25: Product yields of base case
Product Base case yield (kmol/h)
Light naphtha (LN) 680.7 Heavy naphtha (HN) 493.5 Light distillate (LD) 652.8 Heavy distillate (HD) 149.8 Residue (RES) 633.9
Table 6.26: Key components of separation for product yield changes to increase HD
LK/HK Separation between products Base case New product yield
Table 6.28: Energy consumption and operating costs for new product yield units
Parameter Existing unit
New product
yield
Optimum unit
Energy consumption MW 99.0 98.8 90.8 Utility operating cost MM$/yr 15.284 15.266 14.016 Stripping steam flow rate kmol/h 1450 1800 1657 Stripping steam operating cost MM$/yr 1.734 2.153 1.981 Additional exchanger area m2 - 264.8 235.9 HEN capital investment MM$ - 0.140 0.115 Total operating cost MM$/yr 17.018 17.559 16.112 ∆Tmin oC 30.0 30.0 30.0 Payback yr Base - 0.13 utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C)
The existing unit with new product yields requires some additional area, although the
utility consumption is nearly the same as that of the base case. It is preferred if the
objective is achieved with minimum capital investment and with energy cost savings if
possible.
The retrofit optimisation approach can then be applied to the unit with new product
yield to reduce the energy consumption and operating costs. The existing design of the
distillation column and exchanger network are fixed; all operating conditions are
optimised to minimise the operating costs and capital investment. Ideally, the retrofit
model of the exchanger network needs to be obtained for the new process conditions;
however, the retrofit model obtained for the existing unit (see Section 6.1) can
Chapter 6 Case studies
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approximately be used since it accounts for the same structure of the existing exchanger
network. This will allow the retrofit goal to be studied without the need of analysing the
unit with new product yields and obtaining a new HEN retrofit model. The network
structural constraints can be applied during the optimisation. The structural constraints
will be related to the energy consumption level of the retrofitted unit; therefore, they can
be systematically imposed as constraints in terms of the energy consumption levels
during the optimisation. Alternatively, they can be taken into account in the detailed
retrofit analysis of the optimum exchanger network, which is the case used in this case
study.
The results of the retrofit approach are obtained for reducing the energy consumption
and the operating costs of the unit with new product yields. The results are shown in
Table 6.28, and are compared with those of the unit with new product yield (before
optimisation). Table 6.28 includes three different cases, existing unit or base case,
modified unit with new product yields but not optimised and optimised unit with new
product yields. The optimum operating conditions are given in Table G.4 (Appendix G),
and compared with those of the base case and the unit with new product yields (i.e. not
optimum). Results of exchanger area modifications and costs, and new process stream
data are summarised in Tables G.5 and G.6 (Appendix G).
The results of the optimisation (Table 6.28) indicate that the energy demand of the
optimum unit with new product yields reduces to 90.8 MW, with a saving of 8.0 MW
with respect to the unoptimised design with new product yields. Consequently, the
operating costs are reduced by 1.5 MM$/yr. The additional exchanger area is also
reduced. Very low payback time is therefore needed.
As illustrated in this case study, the retrofit approach can be applied to reduce the
energy demand and the operating costs for changing product yields of an existing crude
oil distillation unit. The approach achieves the retrofit objective with lower energy
consumption and less operating and capital costs than if the base case is retrofitted
without optimisation. In a similar manner, the approach can be applied to the existing
unit for any other product yield changes, for instance, if the yield of light distillate is to
be increased. In addition, the approach can be applied for other retrofit objectives such
as reducing emissions or increasing capacity.
Although the approach in this study is applied to a unit with new product yields, it can
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be similarly applied to an existing unit with any new process conditions. These process
conditions may include changes to the pump-around flow rates and duties for
debottlenecking, or changes to the feed preheating conditions, or for processing new
crude oil feedstock. For these cases, the existing unit is first simulated using the models
of Chapter 3, for the new process conditions. Then, the retrofit model is obtained for the
modified exchanger network with the new process conditions. The retrofit approach can
thus be applied for reducing utility costs or for any other retrofit objectives.
6.6. Installing preflash drum or prefractionator column in existing crude oil distillation unit
In the studies presented so far, retrofit was carried out by exploiting the existing column
equipment without considering the benefits of changing the existing structure. In this
section, the structure of the existing distillation process is modified for large and diverse
benefits.
The section accounts for modifying the structure of the existing crude oil distillation
process for reducing energy consumption and increasing tower capacity and process
profit, or producing different product flow rate distribution (e.g. increase light naphtha
yield). This includes the installation of a preflash drum or prefractionator column
upstream to an existing crude oil distillation unit.
6.6.1. Installing a preflash drum for reducing energy consumption and increasing capacity
In this case study, a preflash drum is added to the existing crude oil distillation process
presented in Section 6.1. Different retrofit goals will be considered in this situation. The
base case is the atmospheric crude oil distillation column and the associated heat
exchanger network, the existing design details and specifications of which are those
given in Section 6.1 and Appendix C.
First, we consider the addition of a preflash drum to reduce energy consumption and
operating costs of the existing crude oil unit. The preflash drum is placed somewhere in
the preheat train, before the furnace. The location of the preflash is determined
according to the temperature of the preflash. As the base case, the preflash temperature
is assumed to be 190 oC. As discussed in Chapter 4, there are four locations in which the
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preflash vapours may enter the main distillation column; we consider that, in this case,
the vapour enters at the bottom of the column. This means that the vapour is mixed with
the hot crude oil from the furnace, before entering the column.
The shortcut models presented in Chapters 3 and 4 are employed to simulate the
existing unit with a preflash drum (base case with preflash). The existing column design
is fixed; the preflash variables are calculated (see Section 4.3, Chapter 4). Then, the
main tower product flow rates, temperatures and compositions, and heat duties are
calculated. Also, the energy requirements for the new process conditions are evaluated
for the associated heat exchanger network. Results of product flow rates, energy
requirements and network modifications are summarised in Table 6.29. Note that the
base case unit with preflash drum is not optimised; this means that the operating
conditions of the base case are fixed.
Table 6.29 shows that the installed preflash drum reduces the energy consumption by
3.0 MW compared with the base case. Little time is required as a payback the capital
cost of the additional exchanger areas. In addition, no significant changes are observed
in the product flow rates obtained from the unit with preflash drum. Data of the process
streams of the new conditions and details of exchanger additional area and costs are
given in Tables H.1 and H.2 (Appendix H).
Table 6.29: Retrofit results for base case with preflash
Energy consumption MW 99.0 96.0 Utility operating cost MM$/yr 15.284 14.514 Stripping steam operating cost MM$/yr 1.734 1.734 Additional exchanger area m2 - 114.8* HEN capital investment MM$ - 0.077 Preflash capital cost# MM$ - 0.114+ Total operating cost MM$/yr 17.018 16.248 ∆Tmin oC 30.0 30.0 Payback yr Base 0.25
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: additional area only, #: installation cost = 45% purchase cost (Peters and Timmerhaus, 1980)
Chapter 6 Case studies
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+: diameter = 2.7 m; height = 15.1 m
The retrofit optimisation approach can now be applied to the existing unit with installed
preflash to reduce further the energy consumption and operating costs. The temperature
of the preflash can be optimised, together with all operating variables of the distillation
column. The optimum location of the preflash drum in the preheat train is determined
from the optimum preflash temperature. The existing exchanger network needs to be
reanalysed after installing the preflash drum to obtain the retrofit model; however, the
model obtained in Section 6.1 can still be used.
The retrofit approach optimises the preflash temperature, together with the operating
conditions of the distillation tower, to minimise the total annualised costs of the utility
consumption and stripping steam, and the capital costs of the preflash and network
modifications. The results are shown in Table 6.30.
The energy consumption of the optimum unit with preflash reduces to 89.8 MW, with
saving of operating costs of 1.5 MM$/yr, compared with the existing unit. The total
capital cost of exchanger area and preflash required is little, for which the payback time
required is 0.20 year. The optimum operating conditions, including the preflash
temperature, can be seen in Table H.3 (Appendix H). Note that not all the operating
conditions of the distillation tower are optimised; the reason is because this case is to
show the optimisation of the preflash temperature. Also, no topology changes are
considered. Therefore, the energy consumption could be reduced further by applying
structural changes. Details of process streams data, and additional area and costs, for the
optimum unit with preflash, are summarised in Tables H.4 and H.5 (Appendix H).
Table 6.30: Energy consumption and operating costs for optimum unit with preflash
Parameter Existing unit Optimum unit with preflash
Energy consumption MW 99.0 89.8 Utility operating cost MM$/yr 15.284 13.849 Stripping steam operating cost MM$/yr 1.734 1.698 Additional exchanger area m2 - 443.4* HEN capital investment MM$ - 0.155 Preflash capital cost MM$ - 0.114+ Total operating cost# MM$/yr 17.018 15.547 ∆Tmin oC 30.0 25.0 Payback yr - 0.20
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: additional area only, #: installation cost = 45% purchase cost (Peters and Timmerhaus, 1980) +: diameter = 2.8 m; height = 15.1 m
Chapter 6 Case studies
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Figure 6.10 shows the temperature profile of the optimum unit with preflash. As shown,
the optimum temperature of preflash is 179 oC. The base case value before optimisation
was 190 oC; this indicates that for the given vapour location, the optimum conditions
favour the lower temperature of preflash vapour. This is due to the mixing of the
preflash vapour with the incoming crude oil from the furnace, which leads to lower
crude oil temperature before entering the column.
25o
226.6o
178.9o
365o
To column
Figure 6.10: Temperature profile for existing unit with preflash
As a result of installing preflash drum into the existing unit, the crude oil stream routing
needs to be altered; this means that repiping works are necessary. Figure 6.11 shows
that when preflash is added to the existing exchanger network, the crude oil feed stream
enters the set of exchanger units prior to the preflash drum. Then, the bottom liquid of
the preflash is preheated further to the required temperature. This is accompanied by
repiping some specific exchangers; repiping time and costs are incurred. Also,
additional area to some exchangers is necessary. Repipe works and time are related to
the temperature value of the preflash drum, and they change accordingly. Throughout
the studies of this section, the cost implications of repiping are not included due to the
lack of data. However, the data can easily be incorporated where available.
As mentioned in the above study, preflash vapour enters the distillation column at the
bottom section, i.e. vapour is mixed with crude oil feed. Changing the location of
feeding the vapour inside the column has different implications on the opportunities for
energy saving and increasing capacity, or changing the product flow rates. To find the
most beneficial location of preflash vapour for minimum energy costs, screening study
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is necessary, in which all possible locations are tested. Then for each location, the
existing unit with installed preflash is optimised for minimising the total annualised cost
of operating and capital expenses. The location with the minimum total costs is then
selected.
1
1
1 5 7 9
1 3 2 6 8 1 04 1 24
1 13
1 5 7 9
1 3 2 6 8 1 04 1 24
1 13
Base case - crude oil stream routing
Unit with preflash - crude oil stream routing Figure 6.11: Crude oil stream routing in existing HEN with preflash
For increasing throughput, the hydraulic performance of the existing unit with preflash
and for given vapour location needs to be analysed, as seen in Section 6.3.2. This
determines the maximum capacity that can be processed in the existing unit with
preflash for given vapour location. Hence, the location, which shows maximum capacity
increase, can be chosen. Overall, the location that exhibits lower energy consumption
and more capacity can be explored.
Now, we consider another location of feeding the preflash vapour to the distillation
column, different from the location of the above case, in order to explore the effect on
energy consumption and product flow rate changes. The preflash vapour, in this case,
enters the main column at the middle section, as shown in Figure 6.12.
The base case temperature of the preflash is set to 195 oC. For this location, the existing
unit with preflash is first simulated using the shortcut models of Chapters 3 and 4. Since
the preflash vapour enters the distillation column at a higher section of the column, the
flow rates of the light products (i.e. light and heavy naphtha) are expected to increase.
Then, the preflash temperature, together with all operating conditions of the distillation
column, are optimised to minimise the total annualised costs of utility consumption,
stripping steam, exchanger network modifications and preflash capital cost. The
Chapter 6 Case studies
184
optimum unit energy consumption and operating costs are reported in Table 6.31, and
compared to the base case conditions. Results of the optimisation variables, product
flow rates, and the details of the additional exchanger area, capital costs and the process
streams of the optimum unit can be seen throughout Tables H.6 to H.9 (Appendix H).
1
2
3
4
Figure 6.12: Location of preflash vapour to enter main column
Table 6.31: Energy consumption and operating costs for optimum unit with preflash
Parameter Existing unit Optimum unit with preflash
Energy consumption MW 99.0 76.4 Utility operating cost MM$/yr 15.284 11.869 Stripping steam operating cost MM$/yr 1.734 1.584 Additional exchanger area m2 - 1916.5 HEN capital investment MM$ - 0.479 Preflash capital cost# MM$ - 0.112* Total operating cost MM$/yr 17.018 13.453 ∆Tmin oC 30.0 25.0 Payback yr - 0.17
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: diameter = 2.7 m; height = 14.9 m #: installation cost = 45% purchase cost (Peters and Timmerhaus, 1980)
The results given in Table 6.31 indicate that by optimising the preflash temperature and
the operating conditions of the distillation tower, the energy consumption is reduced
significantly by 22.6 MW of hot utility from the base case demand. The corresponding
savings of the base case operating costs, including steam, are 3.6 MM$/yr. The
optimum preflash temperature is 203.8 oC (see Figure 6.13). This high temperature
allows the separation of the light components from the crude oil (453.4 kmol/h of light
components), which are then fed to the upper sections of the distillation column. The
Chapter 6 Case studies
185
optimum modifications required by the existing exchanger networks are additional area
to some particular exchangers and relocating exchanger unit 8 (see Figure H.1,
Appendix H). Note that if the relocation modification is applied to exchanger unit
number 4, which is the beneficial modification of the case study of Section 6.1, the
energy consumption is 77.2 MW. The modifications have low cost expenses; the
payback time needed is 0.17 year. Table H.7 (Appendix H) indicates that the flow rate
of light naphtha product increases by 9.6% (by mole); similarly, the residue product
flow rate increases by 1.5%. The flow rates of the other products decrease (see Table
H.7, Appendix H). The changes in product flow rates have implications on the income
from products of the optimum unit. These implications need to be accounted for when
the objective is related to profit.
242.9o
203.8o
368.2o
To column
To column
25o
453.4kmol/h
2157.3kmol/h
2610.7kmol/h
Figure 6.13: Temperature profile for optimum unit with preflash
As seen in the above case, the location of preflash vapour affects the opportunities for
saving energy and yield of light products. Table 6.32 compares the results of the two
cases considered previously; case 1 indicates that the preflash vapour is mixed with the
crude oil before the distillation tower, and case 2 is for the unit where the preflash
vapour is entering the column at upper section.
Table 6.32: Comparison of results of unit with different locations of preflash vapours
Parameter Base case
Case 1 Case 2
Energy consumption MW 99.0 89.8 76.4 Reduction in energy consumption MW 9.2 22.6 Total operating cost# MM$/yr 17.018 15.547 13.453 Additional exchanger area m2 - 443.4* 1916.5+ HEN capital investment MM$ - 0.155 0.479 Preflash capital cost MM$ - 0.114 0.112 Saving in total operating cost MM$/yr 1.471 3.565 ∆Tmin oC 30.0 25.0 25.0 Payback yr - 0.20 0.17
Chapter 6 Case studies
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#: includes utility and steam; *: additional area only; +: includes area for resequencing
The comparison (Table 6.32) shows that case 2 achieves better savings in total operating
costs, and more reduction in energy demands, compared to case 1. Note that in case 1,
topology changes to the existing exchanger network were not considered. As mentioned
previously, all possible locations of preflash vapours may be examined along with the
optimisation; then, the most beneficial configuration for energy and operating cost
savings can be selected.
Now, if case study 2 is compared against the case study presented in Section 6.1 since
both cases have the same objective, you may notice that the two cases achieve almost
the same energy saving for one topology modification. However, it was expected that
preflash drum will show more energy saving. The unexpected results arise from the fact
that the preflash temperature and the given network structure affect the energy saving
opportunities. When preflash is installed, there is one constraint added to the
opportunities for heat recovery. This constraint is the preflash temperature, which must
be fixed by the column process conditions and cannot be changed. Fixing the preflash
temperature may lead to poor heat recovery opportunities. On the other hand, when
there is no preflash installed, the existing HEN has more flexibility, i.e. no temperature
constraints; hence, the intermediate temperatures between the exchanger units can be
changed in order to maximise the heat recovery. We may conclude that the energy
saving chances for installed preflash drums are much dependent on the value of preflash
temperature and the existing network structure.
The cases considered in the present section, so far, reveal that the installation of preflash
drum in an existing crude oil distillation tower creates opportunities for reducing energy
consumption and operating costs. In addition, as mentioned previously, preflash drum
allows more capacity to be processed in the existing distillation tower. Now, we
consider this feature in more detail. Figure 6.14 shows the column diameters for the
base case and the existing unit with preflash drum, compared with the actual column
diameters. The preflash vapour in this case enters the upper section of the main
distillation column, as shown earlier in Figure 6.12. The column diameter for the base
case is obtained by simulating the existing unit using rigorous (HYSYS) simulator.
Similarly, for the unit with preflash and the vapour location mentioned above, the
Chapter 6 Case studies
187
modified unit is rigorously simulated; the preflash temperature is set to 200 oC. The
simulated stage diameters are then plotted versus the stage number, and compared with
the existing diameter.
2
3
4
5
6
7
8
9
0 10 20 30 40
Stage number
Stag
e di
amet
er (m
)
Base case
Unit with preflash
Existing diameter
Figure 6.14: Column diameter for base case and unit with preflash (stages from top to bottom of the column) (tray sizing using HYSYS)
As shown in Figure 6.14, the column diameter required for separation when a preflash is
installed is smaller than that required by the base case. The preflash, as mentioned
previously, reduces the vapour and liquid flow rates inside the column; therefore, the
required diameter is reduced. Figure 6.14 indicates that the unit with preflash drum can
process more throughput than the base case. The maximum capacity that can be
processed can be estimated by calculating the FUA throughout the column (see Section
6.3.2). The FUA values along the column are then plotted in Figure H.2 (Appendix H);
the maximum FUA value indicates that the capacity can be increased maximally by
38% over the base case capacity. On the other hand, the maximum diameter of the base
case (7.01 m on stage 31; versus 8.0 m actual diameter) shows that the capacity can be
increased by up to 30% over the base case. This means that an extra capacity increase of
8% can be processed by installing preflash to the existing column structure.
The crude oil distillation tower with preflash is then rigorously simulated with 38%
increase in capacity; the column required diameter is shown in Figure 6.15, compared
Chapter 6 Case studies
188
with the existing diameter. It is obvious that the required diameter for 38% capacity
increase is equal to the existing diameter on particular stages. This indicates that the
capacity cannot easily be increased above that value, i.e. 38% capacity increase
represents the maximum level that can be achieved. However, if the production capacity
is to be increased above that maximum value, column modifications in this case are
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: calculated from Equation 4.62 (Chapter 4); average viscosity = 0.203 cP +: installation cost = 45% of purchase cost (Peters and Timmerhaus, 1980)
Table 6.33 indicates that the energy demand of the existing unit with prefractionator
becomes significantly lower than the base case demand, with a reduction of
approximately 15 MW. This reduces operating costs by about 2.4 MM$/yr, compared
with the base case. Modifications to the existing exchanger network include large
amount of additional area; the capital cost required is 0.6 MM$. Details of the additional
area and capital cost can be seen in Table I.8 (Appendix I).
It is clear from the results in Table 6.33 that the income from products on adding the
prefractionator increases significantly, compared to the existing unit. The increase in net
profit of the modified unit, accounting also for operating costs, is approximately six
million dollars per year.
Chapter 6 Case studies
193
The prefractionator column requires 4.7 and 12.1 theoretical stages in the rectifying and
stripping sections, respectively; the average column diameter is found to be
approximately 4 meters. The installed cost of the prefractionator column is about 0.8
MM$. The payback time for all modification expenditure, including exchanger network
and prefractionator capital costs, is less than eight months.
The above study recommends the addition of a prefractionator column to an existing
crude oil distillation unit to reduce energy consumption and operating costs. However,
the energy and cost savings can be further increased by optimising the operating
conditions of the prefractionator and the main distillation column. The retrofit approach
is then applied to the modified unit to minimise the total annualised costs of the utility
consumption and stripping steam, and the capital costs of prefractionator and exchanger
network modifications. Ideally, the HEN retrofit model needs to be obtained for the
modified exchanger network by following the procedure presented in Section 4.2
(Chapter 4). However, the model, obtained in Section 6.1.2, can still be used in the
optimisation, since it describes the same existing exchanger network.
During the optimisation, the existing designs of the main distillation column and
exchanger network are fixed; however, the design of the prefractionator column is
allowed to change to accommodate energy-capital trade-offs. The prefractionator
temperature is optimised to minimise the total annualised cost of the modified
distillation process; optimisation results are summarised in Table 6.34. Detailed results
of the optimum unit with prefractionator column, including operating conditions,
product flow rates and key component recoveries, process stream data, and additional
area and cost, can be seen in Tables I.9 to I.13 (Appendix I).
Table 6.34 indicates that the optimisation of the prefractionator temperature reduces
further operating cost and energy demand. Approximately 3 MW of hot utility
consumption and 0.5 MM$/yr of operating cost can be saved after optimising the
prefractionator temperature. Furthermore, the additional exchanger area required is
reduced by 606 m2 for the optimum unit, compared with base unit with prefractionator.
Note that only additional area is considered as modification to the existing network. The
capital cost of the prefractionator for the optimum unit is relatively expensive compared
with the base unit with prefractionator, although the payback time is still less than one
year. The costs of modifications to the existing exchanger network, which include only
Chapter 6 Case studies
194
additional area, are cheaper than those for the base unit with a prefractionator. The net
profit of the optimum unit, relative to the existing unit, increases to around 7.5 MM$/yr,
versus net profit of 6.0 MM$/yr for the base unit with a prefractionator (unoptimised).
Thus, optimising the prefractionator feed temperature increases net profit by
approximately 1.5 MM$/yr.
Table 6.34: Optimum results of unit with prefractionator
Unit with prefractionator Parameter Existing unit
Base Optimum
Prefractionator feed temperature oC 230.0 207.5 Energy consumption MW 99.0 83.8 80.6 Utility operating cost MM$/yr 15.284 12.932 12.435 Stripping steam operating cost MM$/yr 1.734 1.674 1.674 Additional exchanger area m2 - 2907.7 2301.7 HEN capital investment MM$ - 0.644 0.558 Prefractionator capital cost MM$ - 0.796+ 1.776+ ∆Tmin oC 30.0 25.0 25.0 Payback yr - 0.60 0.80 Income from products (products value – feed price)
MM$/yr 382.074 385.625 386.636
Net profit (income from products – operating costs)
MM$/yr 365.056 371.019 372.527
Increase in net profit MM$/yr Base 5.963 7.471 Prefractionator design specifications Feed preheat duty MW - 80.63 69.10 Main column feed preheat duty MW 154.50 59.99 61.00 Theoretical stages in rectifying section
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: calculated from Equation 4.62 (Chapter 4); average viscosity = 0.203 cP +: installation cost = 45% of purchase cost (Peters and Timmerhaus, 1980); #: R/Rmin = 1.01
The optimum design of the prefractionator column requires a large number of
theoretical stages in both the rectifying and stripping sections. The required number of
stages can be decreased by increasing the reflux ratio. For instance, when the reflux
ratio is increased by 38% to 1.73, the number of theoretical stages required in the
rectifying and stripping sections is decreased to 5.4 and 14.2 respectively. Accordingly,
Chapter 6 Case studies
195
the capital cost of the prefractionator column is reduced to 0.632 MM$. In this case, the
impact on heat recovery and operating costs needs to be considered.
In the above study, if both the prefractionator temperature and the operating variables of
the main distillation column are optimised for the same objective, the energy
consumption is reduced further, i.e. increasing the net profit. The results for this case are
summarised in Table 6.35. Tables I.14 to I.18 (Appendix I) give the details of the
optimum conditions, product flow rates, component recoveries, process streams and the
additional area for the optimum unit with prefractionator. Figure I.3 (Appendix I) shows
the topology modification that is applied to the existing exchanger network.
Table 6.35: Optimum results of unit with prefractionator (all operating conditions)
Unit with prefractionator Parameter Existing unit
Base Optimum
Prefractionator feed temperature oC 230.0 215.7 Energy consumption MW 99.0 83.8 63.8 Utility operating cost MM$/yr 15.284 12.932 9.897 Stripping steam operating cost MM$/yr 1.734 1.674 1.556 Additional exchanger area m2 - 2907.7 2979.8 HEN capital investment MM$ - 0.644 0.612 Prefractionator capital cost MM$ - 0.796+ 1.076+ ∆Tmin oC 30.0 25.0 25.0 Payback yr - 0.60 0.31 Income from products (products value – feed price)
MM$/yr 382.074 385.625 386.698
Net profit (income from product– operating costs)
MM$/yr 365.056 371.019 375.245
Increase in net profit MM$/yr Base 5.963 10.189 Prefractionator design specifications Feed preheat duty MW - 80.63 73.29 Main column feed preheat duty MW 154.50 59.99 60.59 Theoretical stages in rectifying section
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: calculated from Equation 4.62 (Chapter 4); average viscosity = 0.203 cP +: installation cost = 45% of purchase cost (Peters and Timmerhaus, 1980); #: R/Rmin = 1.01
Chapter 6 Case studies
196
Table 6.35 illustrates that when all operating conditions of the modified distillation unit
with prefractionator are optimised, large reductions in the energy consumption and
operating costs are achieved. The results show that the optimum unit consumes energy
of 63.8 MW, compared with 80.6 MW for the unit with prefractionator where the
prefractionator temperature is only optimised and 99.0 MW for the existing unit. The
profit of the optimum unit with prefractionator is improved by 10 MM$/yr over the
existing unit.
The studies considered above concentrate only, for the added prefractionator, on the
energy savings and profit increase for fixed crude oil feed capacity. In addition to these
benefits, a prefractionator may enable the existing crude oil distillation unit to increase
the production capacity considerably. The maximum capacity that can be achieved in
the existing distillation unit with the installed prefractionator can be determined, in a
similar way to that discussed in previous sections. The key difference for this design
option is that the new column can be designed as a grassroots in order to accommodate
increased flow rates.
The hydraulic performance of the base unit with a prefractionator unit is analysed using
rigorous simulation. The configuration of this base unit is that shown previously in
Figure 6.16; design specifications and operating conditions are the same as those given
in Tables I.1 to I.5 (Appendix I). The modified unit is simulated; the stage diameters
required for separation are obtained. Stage diameters are plotted in Figure I.4 (Appendix
I) versus stage numbers, and plotted against the existing column diameter The FUA
curve is obtained from the information of the stage diameters, together with the existing
column diameters (Figure 6.18). The maximum FUA value is found 0.628; it indicates
that the maximum capacity is 59% (≈1/0.628) over the existing unit capacity. This
means that the throughput of the unit with a prefractionator can be increased from the
current level by up to 59% without requiring any column modifications. Note that the
existing unit without a prefractionator allows the capacity to be increased by a
maximum of 30%; also the existing unit with a preflash drum shows potential of
increasing the capacity by up to 38% over the existing capacity (see Section 6.6.1). It is
clear that prefractionator shows huge capacity enhancement potential over the preflash
and the existing unit capabilities.
Chapter 6 Case studies
197
0.0
0.2
0.4
0.6
0.8
1.0
0 10 20 30 40
Stage number
FUA
Figure 6.18: FUA curve for unit with prefractionator (stages from column top-
down)
If the capacity of the crude distillation unit is to be increased by 59% over the current
capacity, the energy consumption and operating costs increase as well by 59% over the
existing values assuming that heat recovery is also increased proportionally. However,
the process profit will increase substantially. The capacity of the unit with a
prefractionator is increased to the maximum value, i.e. 59% over the current level.
Operating conditions, including steam flow rates and pump-around duties and flow
rates, are scaled by the factor 1.59. The simulated column diameter for the 59%
increased capacity is shown in Figure 6.19, compared with the actual column diameter.
It is clear that the column diameter required for separation on some specific stages
equals the existing column diameter. This means that the capacity of the unit reaches its
maximum.
Table 6.36 summarises the energy requirements, operating costs and profit analysis for
the unit with maximum capacity increase. As expected, there is huge increase in the
process profit when the capacity increases to the maximum level. However, the energy
consumption and the additional area required are also large, with considerable capital
investment and operating costs. In order to reduce the operating costs, energy
consumption and the additional area, the retrofit approach is applied to change all
operating conditions of the entire system to minimise the total annualised cost.
Optimisation results are summarised in Table 6.37, while detailed results, including
optimisation variables, optimum prefractionator design, additional exchanger area and
Chapter 6 Case studies
198
costs and process stream data, can be seen in Tables I.19 to I.24 (Appendix I).
2
3
4
5
6
7
8
9
0 10 20 30 40
Stage number
Stag
e di
amet
er (m
)
Existing diameter
Prefract with 59%
Figure 6.19: Simulated column diameter for 59% increased throughput to unit
with prefractionator (number of stages is top-down) (tray sizing using HYSYS)
Table 6.36: Energy and cost requirement and profit for maximum capacity increase
Unit with prefractionator Parameter Existing unit
Base 59% Increase
Prefractionator feed temperature oC 230.0 230.0 Energy consumption MW 99.0 83.8 133.4 Utility operating cost MM$/yr 15.284 12.932 20.595 Stripping steam operating cost MM$/yr 1.734 1.674 2.662 Additional exchanger area m2 - 2907.7 6049.3 HEN capital investment MM$ - 0.644 1.065 Prefractionator capital cost MM$ - 0.796+ 1.031+ ∆Tmin oC 30.0 25.0 25.0 Income from products (products value – feed price)
MM$/yr 382.074 385.625 613.144
Net profit (income from products – operating costs)
MM$/yr 365.056 371.019 589.887
Increase in net profit MM$/yr Base 5.963 224.831 utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) +: installation cost = 45% of purchase cost (Peters and Timmerhaus, 1980)
Table 6.37 shows that there is an improvement in the energy reduction and the cost
savings for the optimum unit, compared with the base unit without optimisation. About
Chapter 6 Case studies
199
10 MW of energy demand of the base unit with prefractionator and maximum capacity
increase is reduced by optimisation. In addition, the total exchanger area required is
reduced by 694 m2. Further energy reduction is expected when the topology changes to
the network structure are considered. The net profit increases after optimisation by
approximately one million dollars per year, compared to the unit with 59% increased
throughput (unoptimised).
Table 6.37: Optimisation results of optimum unit with maximum capacity increase
59% Increase on unit with prefractionator
Parameter Existing unit
Optimum Base
Prefractionator feed temperature oC 218.5 230.0 Energy consumption MW 99.0 123.6 133.4 Utility operating cost MM$/yr 15.284 19.062 20.595 Stripping steam operating cost MM$/yr 1.734 2.662* 2.662 Additional exchanger area m2 - 5355.8 6049.3 HEN capital investment MM$ - 0.967 1.065 Prefractionator capital cost MM$ - 1.274+ 1.031+ ∆Tmin oC 30.0 25.0 25.0 Income from products (products value – feed price)
MM$/yr 382.074 612.591 613.144
Net profit (income from products – operating costs)
MM$/yr 365.056 590.867 589.887
Increase in net profit MM$/yr Base 225.811 224.831 utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: steam is not optimised; +: installation cost = 45% of purchase cost (Peters and Timmerhaus, 1980)
The latter case study discussed in this section shows that an added prefractionator has
potential to reduce energy consumption and operation costs and enhance production
capacity more than that can be achieved with the existing hardware. It also shows that
the optimisation of the unit with a prefractionator reduces energy consumption,
operating costs and additional exchanger area and increases process profits
significantly.
Although the section focuses on energy demand and operating costs, preflash and
prefractionator units can also be considered for debottlenecking purposes, where the
existing column cannot accommodate the desired increase in throughput. In this case,
preflash or prefractionator units can be added to increase the capacity and remove
column bottlenecks.
Furthermore, the retrofit strategy followed in this section can be applied to situations
Chapter 6 Case studies
200
where an existing distillation column is bottlenecked and the bottlenecked section is to
be replaced with packing materials. In this case, the retrofit approach is applied in
parallel with the relevant models of Section 4.7 (Chapter 4).
6.7. Heat transfer enhancement in preheat train for retrofit of crude oil distillation tower
In this study, heat transfer enhancement is applied to retrofit preheat train for reducing
energy costs of existing crude oil distillation tower. The base case for this study is the
existing atmospheric crude oil tower and the associated preheat train, given in Section
6.1. The purpose in this case study is to reduce the energy consumption and operating
costs of the existing unit by using heat transfer enhancement in the preheat train. In this
study, we consider the case that heat transfer enhancement is applied to the exchangers
heating the crude oil feed stream, shown in Figure J.1 (Appendix J). Data for these
exchangers are given in Table J.1 (Appendix J). We assume that, in this study, the heat
transfer is controlled by tube side.
The retrofit model for the preheat train with heat transfer enhancement needs to be
obtained. The procedure, presented in Section 4.6.1 (Chapter 4, method 2), is applied to
the enhanced heat exchanger network. First, the maximum area, which can be achieved
by using heat transfer enhancement in exchanger unit, is calculated and shown in Table
J.2 (Appendix J). Then, for each energy consumption level, the additional exchanger
area required is eliminated or reduced based on the heat transfer area required and the
maximum area achievable by enhancement. Additional exchanger area combined with
enhancement is necessary when the retrofit area required is larger than the maximum
area for enhancement. However, for area requirements less than this maximum area,
enhancement alone is sufficient. Tables J.3 and J.4 (Appendix J) summarise the
calculation results. A detailed explanation of the calculations is provided with these
tables in Appendix J. Data of retrofit area with heat transfer enhancement are plotted
and regressed in Figure J.2 (Appendix J) to obtain the model parameters. Note that a
pressure drop correlation can also be obtained in this case by following the procedure
presented in Section 4.6.2 (Chapter 4). The correlation can then be used in parallel with
the retrofit model in the optimisation.
The retrofit approach can now be applied to the existing crude oil distillation tower and
Chapter 6 Case studies
201
the associated preheat train with heat transfer enhancement to minimise the total
annualised costs of utility consumption and stripping steam, and the capital costs of
additional area and heat transfer materials. The optimum energy consumption is
expected to be reduced to less than that if heat transfer enhancement is not applied, as is
the case in Section 6.1.
The retrofit approach results are summarised in Table 6.38, and compared with the
results obtained in Section 6.1, where no heat transfer enhancement is used. The
optimum values of the operating conditions are given in Table J.5 (Appendix J). Details
of the product flow rates and recoveries, additional and enhanced area and the
associated capital costs, and the process streams for the optimum unit can be found in
Tables J.6 to J.9 (Appendix J). The modifications required by the existing preheat train
include additional area, enhanced exchangers and relocating an existing exchanger unit
(Figure J.3, Appendix J).
Table 6.38: Retrofit approach results for optimum unit with heat transfer enhancement (HTE)
Optimum Parameter Existing unit with HTE No HTE
Energy consumption MW 99.0 73.2 76.4 Furnace heat load MW 73.5 58.7 62.4 Crude oil temperature before furnace
oC 226.5 240.4 233.1
Utility operating cost MM$/yr 15.284 11.282 11.772 Stripping steam operating cost MM$/yr 1.734 1.631 1.551 Additional exchanger area m2 - 1292.1 1407.3 Heat transfer enhancement area m2 - 615.1 - Enhancement material capital costs MM$ - 0.037* 0.- Additional area capital costs MM$ - 0.329 0.393 Total operating cost MM$/yr 17.018 12.913 13.323 ∆Tmin oC 30.0 25.0 25.0 Payback yr - 0.09 0.11
utility and steam unit and area costs can be seen in Table C.1.2 and Table C.3.2 (Appendix C) *: 60 $/m2 for coiled wire 5.5 material (Nie, 1998)
The results of the retrofit approach show that by using heat transfer enhancement, the
energy consumption of the optimum unit is reduced by 25.8 MW from the base case,
with an increase of 3.2 MW over that achieved for the optimum case without heat
transfer enhancement. Although the energy consumption is lower, the total additional
area required by the exchanger units is also smaller than that required by the optimum
existing unit. The reduction in the total operating costs is approximately 4 MM$/yr,
Chapter 6 Case studies
202
compared to the existing unit. The capital investment required is relatively small and
results in a very short payback time.
The above case study makes it clear that when heat transfer enhancement is applied to
an existing preheat train, further reductions in the operating costs and energy
consumption are achieved. Furthermore, the additional area required by the existing
exchanger units is also reduced. The pressure drop constraints of the existing exchanger
network can also be considered while achieving the retrofit objective with using heat
transfer enhancement. In this case, the retrofit model that accounts for the pressure drop
for the crude oil feed stream is obtained. Then, the maximum allowable pressure drop
for crude oil feed stream is imposed as a constraint to the optimisation. The results for
this case are expected to show less reduction in the energy consumption and operating
costs, compared with the case where the pressure drop constraints are not accounted for;
however, the results obtained will guarantee that no pumping capital costs are required.
6.8. Case studies comparison
The retrofit studies considered in this chapter demonstrate diverse objectives with
various design options, a comparison of options achieving similar goals can be made.
Table 6.39 summarises the various retrofit objectives for different design options.
Values in the table are given as percentage of the base case values; only profit values
are given as profit increase in MM$/yr over the base case.
Table 6.39: Case studies comparison
Optimum case Energy demand
Capacity* Profit Emissions
Base case value 99.0 MW
100,000 bbl/d
365.1 MM$/yr
32,766 kg/h
Existing unit -22.8% +30% +3.7 -21.6% Modified unit with heat transfer enhancement
-26.1% +4.1
Existing unit with added preflash drum
-22.8% +38% +2.1
Existing unit with installed prefractionator column
-35.6% +59% +10.2
Existing unit integrated with gas turbine
-19.4% +7.8+ -48.3%
*: maximum level; +: includes value of power generated
The results in this table may be used as guidance for retrofit projects in crude oil
distillation systems. Prefractionator columns show the maximum capacity increase,
Chapter 6 Case studies
203
energy savings and profit improvement; an integrated gas turbine displays the largest
potential for emissions reduction.
6.9. Summary and conclusions
This chapter presented different case studies to illustrate the application of the
established retrofit approach. Different retrofit objectives for crude oil distillation
systems were considered. The chapter explained how the retrofit approach is applied to
an existing crude oil distillation system to achieve a particular goal. For every case
study, the problem data were presented and the objective was defined. The retrofit
approach was applied to achieve the objectives. Results obtained were discussed and
key issues were concluded. Similar objectives with various design options were
compared. The base case column design was reasonably obtained by applying both the
grassroots design models for crude oil distillation columns (Suphanit, 1999) and the
design insights proposed by Watkins (1979). On the other hand, the heat exchanger
network was based on industrial data.
Several goals were covered in the studies, including reducing energy consumption and
operating costs, increasing plant capacity and process profit, changing production yields
and reducing environmental emissions. Case studies showed that the retrofit approach is
applicable to heat-integrated crude oil distillation systems to achieve retrofit aims with
minimal capital investment and great savings in the energy consumption and operating
costs. The existing crude oil distillation process could reduce its energy consumption
and operating costs by up to 23% of the base case values. No expensive modifications
are required to the existing distillation column; instead, beneficial changes to the
process conditions were identified. Modifications are only needed to the existing
exchanger network. The capital costs of modifications are minor, compared with the
savings achieved. These savings increase to up to 26% more by using heat transfer
enhancement in some particular exchanger units.
Process profit can be maximised by changing the production flow rates, for the same
feed capacity, using optimisation. Current profit can almost be doubled by applying the
approach to increase the products value, and obtain the optimum product flow rates
distribution.
It has been shown that the production capacity of an existing crude oil distillation unit
Chapter 6 Case studies
204
can be increased to achieve a target value, in parallel with the reduction in the operating
costs and energy consumption. In addition, the hydraulic performance of an existing
distillation column is analysed to determine the maximum capacity increase. The retrofit
approach can reduce significantly the process expenses, which are anticipated when the
capacity of existing unit is increased to the maximum amount.
Atmospheric emissions can be reduced considerably by applying the retrofit approach.
A gas turbine can be integrated for further emissions reduction and increasing profit.
Furthermore, a gas turbine enables the existing refinery distillation unit to produce
power and gain more flexibility. Typical results demonstrated that the emissions from
the existing unit are decreased by up to 22%; emissions reduction can be increased by
up to 48% when a gas turbine is integrated.
Product yields can be changed and while simultaneously operating costs are reduced.
Benefits of 8 % of reductions in energy costs are achieved together with the retrofit
objective.
A new column can be installed upstream of the existing crude oil distillation unit to
reduce operating costs and utility consumption and enhance throughput. This study
showed that a preflash drum could reduce operating costs and energy consumption by
up to 22% and enable the existing unit to increase its capacity by up to 8% over the
maximum increase that could be achieved by the existing equipment. Locations of the
preflash vapour feed to the main distillation column and the implications for energy
saving and throughput increase opportunities have been addressed by the retrofit
approach. Similarly, a prefractionator column led to savings in energy costs of 35% and
increased the capacity by up to 29% over the maximum increase achievable by the
existing hardware. In addition, the optimum location of the preflash or prefractionator in
the preheat train is determined by the optimisation approach. The preflash and
prefractionator feed temperature is a key degree of freedom that can be manipulated for
greater energy savings and capacity enhancement.
The chapter has conclusively showed that the new approach is applicable for retrofit of
heat-integrated crude oil distillation systems. It is capable of achieving various retrofit
objectives with relatively cheap solutions, and large savings in energy demand and
operating costs. The application of the new approach account for changes in the
specifications of the crude oil feed stream or to the product prices. The approach
Chapter 6 Case studies
205
presents diverse and flexible options for increasing process profit. The retrofit
optimisation solution takes approximately 3000 CPU seconds on a 1 GHz, 256 MB
RAM Pentium III PC.
It has been shown that, the results obtained in the studies presented in this chapter could
not have been achieved easily using simulations and sequential approaches or
engineering insights. Although the global optimisation solution is not guaranteed, the
results are still outstanding.
Although the approach was mainly applied to crude oil distillation systems, the retrofit
aspects discussed and the procedure are still valid and can be applied to other distillation
systems, such as naphtha fractionation and separation of catalytic cracking and
hydrocracking reactor products.
Chapter 7 Conclusions and future work
206
Chapter 7: Conclusions and future work
7.1. Conclusions
In this thesis, a retrofit design methodology, modelling and optimisation framework for
heat-integrated crude oil distillation systems, i.e. crude oil distillation column and
associated heat exchanger network, have been presented. The approach is optimisation
based, and considers the existing design of distillation unit and the associated exchanger
network simultaneously. Shortcut models have been developed for particular application
to retrofit design of distillation columns. Also, a model that characterises the details of
exchanger area, matches and heat duties of an existing heat exchanger network has been
proposed. In addition, models for retrofit design aspects of the entire system, such as
installing a preflash drum and prefractionator column upstream to the existing
distillation unit, replacing column internals with packing, integrating a gas turbine and
enhancing heat transfer in exchanger tubes, have been developed and included in the
retrofit design approach.
The main contributions of the work presented in this thesis are summarised below:
7.1.1. Shortcut models for retrofit design of distillation columns
Shortcut models for grassroots design of distillation columns have been widely
developed and extensively applied to many situations. However, shortcut models for
retrofit design do not exist.
In this thesis, new shortcut models have been developed specifically for retrofit design
of distillation columns. These models are based on the Fenske-Underwood-Gilliland
method. The models include the corrections of the fixed molar overflow and constant
relative volatility assumptions made in the Underwood model (Suphanit, 1999).
The new shortcut models have been developed for various types of distillation columns,
such as simple columns and complex column configurations; they are also valid for both
reboiled and steam-stripped distillation columns. Design of complex columns is carried
out by applying shortcut models to sequences of simple columns, where the sequence is
equivalent to the complex column in terms of mass and energy balances.
Chapter 7 Conclusions and future work
207
Many chemical industries use reboilers to provide vapour to the bottom of distillation
columns. For distillation columns using reboilers, new retrofit shortcut models have
been developed. The models are a reformulation of grassroots design models developed
by Suphanit (1999), where the Underwood method is modified to overcome the
underlying assumptions. The models are for design of simple columns and various
complex configurations including columns using side-strippers or rectifiers, side-
exchanger, prefractionators and Petlyuk columns. These models may be applied to
calculate product and intermediate stream flow rates, compositions and temperatures,
and the heat duties required for existing physical design and configuration of a
distillation column, feed data and operating parameters (e.g. reflux ratio, column
pressure, etc.). The new models have been applied to many illustrative examples. The
results compare very well with those of existing rigorous models. Agreement was
especially good for well-behaved mixtures with relatively few components and
conventional and simple column designs.
Some distillation applications, such as solvent recovery units and crude oil distillation,
utilise stripping steam to facilitate vaporisation in the column (at the bottom), new
shortcut models have been developed for retrofit of such distillation columns. The
models are based on the modified Underwood equation and consecutive flash
calculations for the rectifying and stripping sections, respectively. As for reboiled
columns, both simple and complex configurations using stripping steam have been
addressed. Many possible complex column arrangements are accommodated. These
configurations include sequences with side-columns and side-exchangers. The model
calculations are carried out for a given physical design of a distillation column and
given operating conditions (e.g. steam flow rate) and feed specifications to obtain the
various stream flow rates, temperatures and compositions and the process heating and
cooling requirements. The new models for steams-stripped distillation columns showed
good agreement when applied to various examples mostly of which were
multicomponent mixtures being separated in complex distillation columns.
Crude oil distillation columns are of major importance in refineries. These particular
columns may use reboilers, but primarily use stripping steam to provide vapour in the
main column and side-strippers; they process a large number of crude oil components
and have a very complex structure. A shortcut model has been developed for retrofit
design of such columns. The model includes models for reboiled and steam-stripped
Chapter 7 Conclusions and future work
208
distillation columns. The retrofit model is valid for different configurations for crude oil
distillation, including the conventional design of the atmospheric tower and progressive
column configuration (Rhode, 1997). The model has been successfully applied to
simulate an existing atmospheric crude oil distillation unit with a realistic number of
pseudo-components. Simulation results are the flow rates, temperatures and
compositions of product, key internal and pump-around streams, and the duties of the
condensers, reboilers and the pump-arounds.
One limitation of the model for crude oil distillation towers is the inflexibility regarding
the location of pump-arounds. They are forced to be on the same stage as liquid is
drawn to and vapour is returned from the side-strippers. Pump-arounds on intermediate
stages cannot be modelled currently. This limitation can be overcome by decomposing
the section that includes the pump-around stage. This section includes the stages that lie
between the two draw lines of the side products around the pump-around location. In
this case, two sections with thermal coupling connection will be obtained; lower section
includes the pump-around stage on top and the stages that are between the pump-around
stage and the draw-stage of the lower side product, and upper section includes those
sages above the pump-around stage and till the draw-stage of the upper side product.
The shortcut model can then be applied to the two sections simultaneously. The feed to
the lower section is the top vapour from the upstream section, while the top vapour of
this section enters the upper section. There is a liquid stream recycled (thermal coupling
connection) from the upper section to the lower section; also, the bottom liquid product
of the lower section is recycled to the upstream section.
7.1.2. Retrofit modelling for heat-integrated crude oil distillation systems
Modelling of existing heat-integrated crude oil distillation column is of major
importance to retrofit applications. The shortcut models developed for distillation
retrofit provide a foundation for considering other important issues, such as flue gas
emissions, and design options to achieve retrofit goals. A number of different features
and design options required for retrofit have been modelled in this thesis, including the
existing heat exchanger network, preflash and prefractionator units, hydraulic
performance and CO2 emissions. These issues are outlined below:
Chapter 7 Conclusions and future work
209
A model has been proposed for an existing heat exchanger network; this model is based
on network pinch analysis (Asante, 1996) for retrofit of heat exchanger networks. The
proposed model is expressed by a simple parametric correlation; it accounts for the
structure of an existing exchange network and incorporates detailed informations about
the exchanger areas and matches, heat duties and proposed retrofit modifications. The
model parameters are obtained by regression from the results of an extensive retrofit
study on the existing exchanger network.
A similar model, that accounts for pressure drop for the crude oil feed stream, has been
proposed. This model uses pressure drop correlations (Polley et al., 1990; Nie, 1998),
and is obtained alongside the retrofit model for the exchanger network. In addition, the
application of heat transfer enhancement in exchanger tubes has been modelled.
Installing a preflash drum upstream of an existing crude oil unit can have several
benefits. A retrofit model has been developed to address the addition of preflash drum
to existing distillation unit. The model is based on flash calculations and material and
energy balances, and is combined with the retrofit models for distillation design. The
consequences of different choices of vapour feed location to the distillation column to
which the preflash vapours may be sent have been modelled. This is done by
decomposing the complex column configuration into its equivalent simple sequence and
then allowing the preflash vapour to be mixed with the feed to each simple column. The
model has been validated by comparison with existing rigorous models; good agreement
has been found. Although the model is for retrofit design, it can be used for new design
as well.
Similarly, a prefractionator column may be installed upstream of an existing column
configuration to bring more benefits. A retrofit model has been proposed for such a
feature; the model involves the retrofit model developed for distillation and the
grassroots distillation column design model of Suphanit (1999). The overall model
divides the new problem (i.e. the existing distillation column with the added
prefractionator) into two sub-problems, grassroots design of the new column and retrofit
design of the existing unit. Reconfiguration options of the modified unit and the
associated heat recovery system have been presented.
In some situations, bottlenecked trays in an existing column may be replaced by
packing. To evaluate this option, a model based on packed bed design equation (e.g.
Chapter 7 Conclusions and future work
210
Kister, 1992) and hydraulic and pressure drop correlations has been suggested. This
model applies in parallel with the retrofit model for distillation design. The model
evaluates the potential for increasing capacity in the modified section. The proposed
model can also be used in grassroots design situations
Due to increased concern about emissions to the atmosphere and tighter legislative
requirements for pollution control, a model has been proposed for evaluating CO2
emissions from an existing crude oil distillation unit. This model is based on models and
correlations developed by Delaby and Smith (1995) and Manninen and Zhu (1999). The
model considers various sources for emissions and is valid for different types of fuels
used in boilers and fired heaters. Integration of a gas turbine with the existing heating
system has been addressed as a design option. Although the new model was proposed
for emissions from an existing unit, it can similarly be applied for new design purposes.
7.1.3. Retrofit design methodology and its application
In this thesis, a simultaneous approach has been proposed for retrofit design of heat-
integrated crude oil distillation systems. The distillation process and the associated heat
recovery system have been considered at the same time. All design parameters of the
distillation process have also been considered simultaneously, including crude oil feed
The approach is optimisation based; it incorporates the models for distillation retrofit,
existing exchanger network and the other relevant models, depending on the retrofit
design objectives and the design options being considered. The optimisation problem
was formulated as a non-linear programming (NLP) problem, because all retrofit
models are non-linear; successive quadratic programming (SQP) was utilised as the
optimisation algorithm.
A new optimisation framework for retrofit design has been developed. This framework
involves retrofit models and cost models, and uses a flexible objective function. For
retrofit applications, the existing design of process equipment is fixed; all operating
conditions (e.g. crude oil feed temperature, flow rate of stripping steam and pump-
around liquid, reflux, etc. ) of the distillation process are optimised to minimise or
maximise a specific objective function. Practical and physical equipment constraints,
such as hydraulic limitations of distillation columns, allowable pressure drop and
Chapter 7 Conclusions and future work
211
maximum heat loads of particular exchangers are taken into account during
optimisation. Several objectives have been considered for retrofit applications,
including energy reduction, throughput enhancement, profit improvement, product yield
changes and emissions reduction. Structural modifications to the distillation process and
the exchanger network have also been considered for retrofit.
The optimisation framework does not guarantee a global solution, since the problem is
non-linear optimisation. Hence, optimisation with different initial values of the
optimisation variables allow improved solutions to be obtained. This optimisation can
be carried out repeatedly until a confidence in the optimality of the best solution is
gained.
The main limitation of the new retrofit approach is that the retrofit model for the heat
exchanger network is obtained for fixed process conditions. However, during the
distillation process optimisation, these process conditions change. Therefore, the
capital-energy trade-off given by this retrofit model does not accurately represent the
simultaneous changes in the process conditions and the retrofit requirements to the
existing heat exchanger network. However, this shortcoming can be overcome, ideally,
by modelling the superstructure of the existing heat exchanger network and
incorporating the detailed existing design into the optimisation framework. In this case,
the given structure and details of the heat exchanger network will be considered
simultaneously with the change in the distillation process conditions. Thus, the
optimisation problem would be formulated as a rather complex mixed integer non-linear
programming (MINLP) problem. Alternatively, the problem can be partially overcome
by repeatedly applying the optimisation approach to the existing system. After each
optimisation run, a new retrofit model is obtained for the optimum process conditions.
Then, this model is used for the next optimisation step. The optimisation runs end when
there is no scope for a better solution to be obtained. Overall, a retrofit model is
obtained which relates the capital-energy trade-off in the existing heat exchanger
network and the process changes.
Another limitation involved in the new approach is that the structural modifications are
not considered during the optimisation; they need to be selected as retrofit decisions
prior to the optimisation. This can similarly be overcome by including the structural
decisions as part of the optimisation; the problem then becomes a mixed integer non-
Chapter 7 Conclusions and future work
212
linear programming problem. The main advantage of this is that the structural options
can be screened. However, the approach developed in this work leads to similar results
by considering each design option at a time.
The limitations of the shortcut models for retrofit design of distillation columns result
from their underlying assumptions. These underlying assumptions, for instance, are that
the Fenske equation assumes that the relative volatility is constant throughout the
column, and the minimum number of theoretical stages depends only on the degree of
separation of the two key components and their relative volatilities and not on the feed
condition (Seader and Henley, 1998). In addition, in the Gilliland correlation, the
number of theoretical stages is calculated based on the minimum reflux ratio, minimum
theoretical number of stages and the actual reflux ratio; no parameter that involves the
feed condition is included. Robinson and Gilliland (1950) stated that a more accurate
correlation should include the effect of the feed condition. The number of theoretical
stages decreases with increasing feed vaporisation and the Gilliland correlation appears
to be conservative for feeds with low values of the ratio of liquid to feed molar flow
rates (Seader and Henley, 1998). Furthermore, the feed stage location is influenced by
the feed condition and it is not only determined by the product flow rates and the key
component compositions in the feed and products as given in the Kirkbride correlation.
The new approach has been applied to a number of industrially-relevant cases of crude
oil distillation for different retrofit objectives. The retrofit results showed substantial
improvements to the energy and cost savings, profit, capacity increase and the emissions
reduction. Large benefits have been achieved by optimising simultaneously the design
parameters of the distillation process. The application of the retrofit approach examined
diverse design options for the same objective and revealed that prefractionator column
is the most attractive decision for profit improvement and energy saving, while a gas
turbine is favoured for emissions control.
7.2. Future work
Future research in this area could address some of the limitations of the work mentioned
above. Some of the other issues relevant to retrofit design of heat-integrated crude oil
distillation columns that still need to be addressed include:
Chapter 7 Conclusions and future work
213
1. The new retrofit models and approach presented in this thesis can be extended to
include other relevant issues for other distillation applications such as crude oil
vacuum distillation and other refining distillation processes, as well as
petrochemicals and chemicals distillation.
2. The new retrofit models and approach can be modified to consider reconfiguration
of an existing crude oil distillation system.
3. Retrofit of fired heaters (Jegla et al., 2000) can be addressed, modelled and
incorporated to the retrofit approach.
4. The new retrofit models can provide a foundation for overcoming the network pinch
in an existing heat exchanger network through automated identification of beneficial
changes to the existing distillation process. Also, the algorithm can be modified to
search for process changes to debottleneck an existing exchanger unit or furnace.
5. The shortcut models for distillation retrofit can be extended to systematically
identify debottlenecking process changes (e.g. pump-around liquid flow rates) for
capacity enhancement.
7.3. Closing remarks
The new retrofit models and approach presented in this thesis constitute a major step
forward in retrofit design of heat-integrated crude oil distillation systems. The
significance of the work is that it has moved the research and industrial benefits in this
area from the ‘state-of-the-art’ as it was previously forward to the simultaneous retrofit
design philosophy with a systematic and automated procedure for various retrofit
decisions and design alternatives. Furthermore, the new shortcut models presented in
this thesis for retrofit designs of distillation columns are a big step forward in the design
modelling of distillation processes; they now can fill the gap left by the previous
researchers. The application of these new shortcut models can go beyond the area of
retrofit of crude oil distillation processes; they can find importance in other research
areas, such as design of reaction-separation systems, where distillation process is
adopted.
214
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Polley, G. T., M. H. Panjeh Shahi, and F. O. Jegede, Pressure drop considerations in the retrofit of heat exchanger networks, Trans IChemE, May, 68(A), 211-220 (1990)
Rev, E., The Constant heat transport model and design of distillation columns with one single distributing component, Ind. Eng. Chem. Res., 29, 1935 (1990)
Rhode, A. K, Environmentally advanced refinery nears start-up in Germany, Oil & Gas Journal, March 17 (1997)
Rivero, R., and A. Anaya, Exergy analysis of a distillation tower for crude oil fractionation. Computer-aided energy systems analysis, Winter Annual Meeting of the ASME, Dallas, Texas, November 25-30, 21, 55-62 (1990)
Robbins, L. A., Improve pressure-drop prediction with a new correlation, Chemical Engineering Progress, May, 87-91 (1991)
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219
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Associated publications and conference presentations
Gadalla, M., M. Jobson, and R. Smith, Optimization of existing heat-integrated refinery distillation systems, accepted to be published in Trans IChemE in January, 81(A) (2003)
Gadalla M., Jobson M., Smith R., A Systematic Approach to Increasing Capacity and Decreasing Energy Demand of Existing Refinery Distillation Systems, accepted to be published in Chemical Engineering Progress (2003)
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220
Gadalla, M., M. Jobson, and R. Smith, Shortcut models for retrofit design of distillation columns, submitted to Chem. Eng. Res. Des. in July (2002)
Gadalla M., Jobson M., Smith R., Retrofit of refinery distillation systems, The International Conference on Distillation & absorption, Baden-Baden, Germany, September (2002)
Gadalla M., Jobson M., Smith R., Retrofit shortcut models for design of existing distillation systems, AIChE Spring Meeting, New Orleans, March (2002)
Gadalla M., Jobson M., Smith R., A systematic approach to increasing capacity and decreasing energy demand of existing refinery distillation systems, AIChE Spring Meeting, New Orleans, March (2002)
Appendix A: Pressure drop correlations
221
Appendix A: Pressure drop correlations
A.1. Parameters for pressure drop correlations of Polley et al. (1990)
5.31
321
kkk
K = (A.1)
3/18.0
1 Pr023.0
=
µλ dd
k (A.2)
2.0
2 092.0−
=
µρλ d
dk (A.3)
TVdk
43 = (A.4)
( ) 1.51
322
kkk
K′
′′= (A.5)
3/11 Pr36.0
dk λ
=′ (A.6)
18.02 2
vd
ke
ρΦ=′ (A.7)
( )S
tt
dVdPP
kπ
−=′ 4
3 (A.8)
A.2. Pressure drop for enhanced HEN
The pressure drop for the enhanced tubes is given by (Nie, 1998):
2
1
a
tube
entube
tube
en
hh
aPP
=
∆∆
(A.9)
The pressure drop for the plain tubes is defined as (Polley et al., 1990):
5.31 tubeexisttube hAKP =∆ (A.10)
Appendix A: Pressure drop correlations
222
tube
a
tube
entube Ph
haP ∆
=∆
2
1en (A.11)
The heat transfer coefficient of the enhanced tube is related to the plain tube heat
transfer coefficient as follows (Nie, 1998):
existtube
shell
existtube
shell
tube
entube
AA
hh
AA
hh
hh
∆−
∆+
=1
(A.12)
Substitute from equations A.10 and A.12 into equation A.9:
tube
a
existtube
tubeshellexist
exist
exist
tube
shell
en P
AhAhhA
AAA
hh
aP ∆
∆−
∆+
=∆
2
1 (A.13)
Simplifying equation A.13 results in the pressure drop for the enhanced exchanger, to
which the additional area is smaller than the maximum area achieved by enhancement:
( )tube
a
tubeshellexist
existshellen P
AhhAAAh
aP ∆
∆−
∆+=∆
2
1 (A.14)
For the case where the additional area is equal to the maximum, substituting ∆A =
∆Amax in equation A.14:
( )tube
a
tubeshellexist
existshellen P
hAhAAAh
aP ∆
∆−
∆+=∆
2
max
max1 (A.15)
tube
a
tubeshellexist
shellshellexisten P
hAhAhAhA
aP ∆
∆−∆+
=∆2
max
max1 (A.16)
The maximum area can be calculated as:
existtube
shellmax A
hh
A
−=∆ 1
21 (A.17)
Appendix A: Pressure drop correlations
223
12
+∆
=exist
max
tube
shell
AA
hh
(A.18)
Rewrite equation A.16 to the form:
tube
a
shell
tube
exist
existen P
hh
AA
AA
aP ∆
∆−
∆+
=∆
2
max
max
1
1
1 (A.19)
Solve equation A.18 and A.19 simultaneously:
tube
a
exist
exist
exist
existen P
AAA
AA
AA
aP ∆
+∆
∆−
∆+
=∆
2
max
max
max
1
21
1 (A.20)
tube
a
exist
existen P
AAA
AA
aP ∆
+∆∆
−
∆+
=∆
2
max
max
max
1
21
1 (A.21)
Rewrite equation A.21 in the following form:
tube
a
exist
exist
exist
exist
en P
AAAAA
AAA
aP ∆
+∆∆−+∆
∆+
=∆
2
max
maxmax
max
1
22
(A.22)
tube
a
exist
existen P
AAA
aP ∆
+∆=∆
2
max1
2 (A.23)
tube
a
existen P
AA
aP ∆
+
∆=∆
2
12 max
1 (A.24)
The last equation gives the pressure drop for the enhanced tubes with the maximum
area.
Appendix A: Pressure drop correlations
224
A.3. Pressure drop correlation for packed beds
The pressure drop correlation proposed by Coker (1991) is given by:
=
V
fluxL
pack
VP L
OHflux
ρκ∆ ρ
ρυ 22
10 (A.25)
The constant κ and υ can be found in Coker (1991), for different packing types and
sizes.
Appendix B: Heat exchanger costs
225
Appendix B: Heat exchanger costs
Figure B.1 summarises exchanger cost data obtained from various sources. These data
are collected, as shown, from Douglas (1988), Peters and Timmerhaus (1980) and
SPRINT (2002). The range of the exchanger areas used in this cost models is from 20 to
400 m2. It is clear that Sprint (2002) model underestimates capital cost of exchanger
units. The model that gives reasonable costs comparable with the various cost models is
shown in the figure. The cost parameters of the new model are obtained from data
regression as shown in Figure B.2. Table B.1 shows the exchanger area and cost data
used for model parameter regression.
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
0 50 100 150 200 250 300 350 400 450
Exchanger Area (m2)
Exch
ange
r Cos
t ($)
Douglas
Sprint
Peters(45%)
Peters(35%)
Model
Figure B.1: Exchanger cost data from various sources (45 and 35% represent
the ratios of the installation cost of exchangers to their purchase costs as recommended by Peters and Timmerhaus, 1980)
Appendix B: Heat exchanger costs
226
y = 1529.3x0.63
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
0 100 200 300 400 500
Exchanger area (m2)
Exch
ange
r cos
t ($)
Figure B.2: Exchanger cost curve, showing model regression parameters
5′ 79.2 5756.3 9771.3 Optimisation+ 29.0 hx: exchanger unit; +: for constant energy consumption (for details of exchanger locations in existing HEN, see Figure 6.2)
Appendix E: Data for case study 6.3
244
The new locations of the exchanger units considered in the retrofit study can be seen in
Figures E.3.2 to E.3.5.
Data of retrofit area and energy consumption are plotted (Figure E.3.1), and then are
regressed to obtain the retrofit model parameters m and c (see equation 4.7, Chapter 4).
Note that only the data points representing the optimum modified networks are plotted,
i.e. points 0, 1, 2′, 3′, 4′, 5′ and 6′ are only used to plot the retrofit curve. The existing
exchanger network on the retrofit curve corresponds to the first data point, while the
second point represents the data of the optimised existing HEN, etc. The model
parameters are obtained from data regression, and are then adjusted to minimise the
deviations between the retrofit area predicted by the model and those obtained from the
retrofit study. The best-fit values of the model parameters m and c, as shown in Figure
E.3.1, are 1.002176·108 (m2/MW) and -2.1016 respectively. The percentage average
deviation of the predicted values from those obtained from the retrofit study is reduced
Figure E.3.1: Retrofit curve and data regression (Aret: area obtained from retrofit study, Amodel: area obtained from regressed model)
Appendix E: Data for case study 6.3
245
1
1 5 7 91 3 2 6 8 1 0
4
4 1 241 41 131
71
1
82
Figure E.3.2: Relocation of exchanger 1 in existing HEN (points 2, 2′)
1
1 5 7 91 3 2 6 8 1 0
11
14
4 1 241 41 13
2 4
2 8
9
9
1 0
9
Figure E.3.3: Relocation of exchanger 9 in existing HEN (points 3, 3′)
1
1 5 7 91 3 2 6 8 1 0
8
4 1 241 41 13
2 6
Figure E.3.4: Introduction of new exchanger in existing HEN (points 4, 4′)
1
7 2 5
1 5 7 91 3 2 6 8 1 04 1 241 4
1 133
1 833
Figure E.3.5: Relocation of exchanger 3 in existing HEN (points 5, 5′)
Appendix E: Data for case study 6.3
246
0.0
2000.0
4000.0
6000.0
8000.0
10000.0
12000.0
14000.0
16000.0
18000.0
20000.0
0 20 40 60 80 100 120
Energy consumption (MW)
Ret
rofit
are
a (m
2 ) 20% Increase
Existing throughput
Figure E.3.6: Comparison of retrofit model of unit with 20% increased throughput with existing throughput (vertical dotted line represents existing energy demand)
E.4. Data of retrofit results for optimum unit with 20% capacity increase
Table E.4.1: Operating conditions of optimum unit with 20% capacity increase
*: total load = 99.0 MW; +: 260 oC and 4.5 bar; HP: high pressure; #: 42 bar
Table F.1.2: Data for heating fuels in CO2 emissions
NHV (kJ/kg) Carbon % Heavy fuel oil 39,771 86.5 Natural gas 51,600 75.4
NHV: net heating value
F.2. Results for retrofit with integrated gas turbine
The calculations in the following table are obtained by using the models presented in
Section 4.5, Chapter 4). Cost parameters used in calculations are given in Table F.2.2.
Note that the total heat load of the flue gas, including that for stripping steam, is
distributed on the gas turbine and the furnace.
Table F.2.1: CO2 emissions from optimum unit with integrated gas turbine
Parameter Existing unit
Total heat energy consumption MW 79.780 Flue gas heat load MW 67.136 Stripping steam heat load MW 6.557 Utility steam heat load MW 9.375 Heat load distributed on gas turbine MW 15.588 Heat load distributed on furnace MW 58.105 CO2 emissions from steam boiler kg/h 2,698 CO2 emissions from gas turbine kg/h 9,092 CO2 emissions from furnace kg/h 18,552 Total local CO2 emissions kg/h 30,342 Fuel consumption save at power station MW 46.669 CO2 emissions saved at power station kg/h -13,411 Total global CO2 emissions kg/h 16,931 Flue gas flow rate t/h 146.2 Exhaust temperature from gas turbine oC 499.0
Appendix F: Data for case study 6.4
250
Gas turbine efficiency % 73.7 Power generated in gas turbine MW 14.0 Capital cost of gas turbine MM$ 5.261 Price of power generated MM$/yr 3.920 Stripping steam flow rate kmol/h 1255.0 Total operating costs* MM$/yr 13.232 HEN capital investment MM$ 0.429 Crude oil temperature before furnace oC 230.7 Total operating cost saving+ MM$/yr 6.951 Total capital investment MM$ 5.690 Payback yr 0.82 ∆Tmin in existing HEN oC 25.0
*: including utilities and steam; +: including price of power generated
Table F.2.2: Cost and economic parameters for CO2 emissions calculation
Parameter Value Power electricity $/MW.h 35 Carbon tax $/t CO2 15 Gas turbine capital cost k$ 195.1 × (Power*) + 2529.2 Power station efficiency % 30 Furnace efficiency % 90 Boiler efficiency % 80 Atmospheric temperature oC 25 Flue gas temperature oC 1800 Stack temperature oC 150 Operation time yr/h 8600
*: in MW
Table F.2.3: Optimum values of operating conditions
Column Optimisation variable Base case value
Optimum value
Feed preheating temperature oC 365.00 370.00 Flow rate of pump-around liquid kmol/h 2186.56 3167.94 Temperature drop across pump-around oC 30.00 21.22
1
Flow rate of stripping steam kmol/h 1200.00 1072.80 Flow rate of pump-around liquid kmol/h 2305.66 2577.75 Temperature drop across pump-around oC 50.00 30.30
2
Flow rate of stripping steam kmol/h 250.00 182.23 Flow rate of pump-around liquid kmol/h 5790.85 6855.11 Temperature drop across pump-around oC 20.00 19.59
3
Flow rate of liquid between columns 3 and 4
kmol/h 1067.48 1095.35
4 Reflux ratio 4.78 4.27
Appendix F: Data for case study 6.4
251
Table F.2.4: Additional area and cost for optimum unit
-: refers to enthalpy of hot stream; *: product cooling target temperature
Appendix F: Data for case study 6.4
252
F.3. Results for retrofit without integrated gas turbine
Table F.3.1: Optimum values of operating conditions
Column Optimisation variable Base case value
Optimum value
Feed preheating temperature oC 365.00 369.99 Flow rate of pump-around liquid kmol/h 2186.56 5937.06 Temperature drop across pump-around oC 30.00 10.00
1
Flow rate of stripping steam kmol/h 1200.00 1006.80 Flow rate of pump-around liquid kmol/h 2305.66 7508.16 Temperature drop across pump-around oC 50.00 10.00
2
Flow rate of stripping steam kmol/h 250.00 187.96 Flow rate of pump-around liquid kmol/h 5790.85 9816.61 Temperature drop across pump-around oC 20.00 10.19
3
Flow rate of liquid between columns 3 and 4
kmol/h 1067.48 1382.58
4 Reflux ratio 4.78 4.89
Table F.3.2: Additional area and cost for optimum unit
-: refers to enthalpy of hot stream; *: product cooling target temperature
Appendix G: Data for case study 6.5
254
Appendix G: Data for case study 6.5
Table G.1: Operating conditions for new product yields
Parameter* Base case
New product
yield Steam flow in column 2 kmol/h 250 600 Flow of pump-around liquid in column 2 kmol/h 2305.7 3225.3 Flow rate of liquid between columns 2 and 3
kmol/h 167.7 232.2
Flow of pump-around liquid in column 3 kmol/h 5790.9 5015.9 Flow rate of liquid between columns 3 and 4
kmol/h 1067.5 896.2
Reflux ratio in column 4 4.78 4.40 variables are given for decomposed sequence (see Figure 6.1, Chapter 4) *: other operating conditions are same for both cases
Table G.2: Additional area and cost for unit with new product yields
-: refers to enthalpy of hot stream; *: product cooling target temperature
Table G.4: Optimum operating conditions for unit with new product yields
Colno.
Optimisation variable Base case
New product
yield
Optimum unit
Feed preheating temperature oC 365.0 365.0 367.8 Flow rate of pump-around liquid kmol/h 2186.5 2186.5 2662.5 Temperature drop across pump-around oC 30.00 30.00 25.05
1
Flow rate of stripping steam kmol/h 1200.0 1200.0 1110.5 Flow rate of pump-around liquid kmol/h 2305.7 3225.3 3151.0 Temperature drop across pump-around oC 50.00 50.00 41.99
2
Flow rate of stripping steam kmol/h 250.0 600.0 546.4 Flow rate of pump-around liquid kmol/h 5790.9 5016.0 5775.2 Temperature drop across pump-around oC 20.00 20.00 24.09
3
Flow rate of liquid between columns 3 and 4
kmol/h 1067.5 896.2 749.6
4 Reflux ratio 4.78 4.40 3.54
Appendix G: Data for case study 6.5
256
Table G.5: Additional area and cost for optimum unit with new product yields
+: Capital cost ($) = 1530 × (additional area) 0.63
Table H.6: Optimum operating conditions for unit with preflash drum
Column Optimisation variable Base case
Optimum unit
Preflash Feed preheating temperature oC - 203.8 Feed preheating temperature oC 365.0 368.2 Flow rate of pump-around liquid kmol/h 2186.56 3196.69 Temperature drop across pump-around
oC 30.00 17.07
1
Flow rate of stripping steam kmol/h 1200.00 1082.40 Flow rate of pump-around liquid kmol/h 2305.66 4254.87 Temperature drop across pump-around
oC 50.00 24.74 2
Flow rate of stripping steam kmol/h 250.00 242.40 Flow rate of pump-around liquid kmol/h 5790.85 7313.93 Temperature drop across pump-around
oC 20.00 13.51 3
Flow rate of liquid between columns 3 and 4
kmol/h 1067.48 2534.29
4 Reflux ratio 4.78 4.75
Table H.7: Product flow rates of optimum unit with preflash
-: refers to enthalpy of hot stream; *: product cooling target temperature
Appendix H: Data for case study 6.6.1
261
1
1 5 7 9
1 3 2 6 8 1 0 1 24
1 13
4
5 1 5
87
21
56
8
8
Figure H.1: Relocation of exchanger 8 for optimum unit with preflash
0
0.2
0.4
0.6
0.8
1
1.2
0 5 10 15 20 25 30 35 40 45
Stage number
FUA
With preflash_baseWith preflash_38%
Figure H.2: FUA curve for existing unit with preflash (stages from column top to bottom)
Appendix I: Data for case study 6.6.2
262
Appendix I: Data for case study 6.6.2
Steam
Steam
Residue
X1
3
4
5
Main column
TPA
MPA
BPA
2
Upper SS
Middle SS
Lower SS
Light distillate
Heavy distillate
Water
Heavy naphtha
Light distillate
Heavy distillate
Residue
Steam
Steam
1
2
3
4
5
+
BPA
MPA Middle SS
Lower SS
TPA
Figure I.1: Redistribution of stages into sections of decomposed column sequence of main distillation column
Table I.1: Number of stages and of main distillation tower sections
Parameter Column section 5 4 3 2 1
Middle SS
Lower SS
Number of stages 5 9 10 8 9 7 5 Diameter (m) 5.5 8.0 8.0 7.5 7.0* 3.5 3.0
*: taken as average diameter for sections 1 and 2
Note that for the new column section, which includes sections 1 and 2, the column
diameter is taken as the smaller one in the optimisation.
Table I.2: Design specifications of prefractionator column
Parameter Specification
Light key component 4 Heavy key component 6 Recovery of light key % 99.81* Recovery of heavy key % 98.66* Reflux ratio R/Rmin 1.01 Mechanism of reboiling Reboiler Temperature of feed oC 230.0 Column pressure bar 2.5
*: values are based on crude oil feed, obtained from base case (Table 6.4, Chapter 4)
Appendix I: Data for case study 6.6.2
263
Table I.3: Operating conditions of main column of unit with prefractionator
Added area after HTE 1157.8 34.4 871.5 1164.1 1670.6 1580.2
Net+ total area (m2) 3238.3 4081.0 5136.5 5366.9 5875.2 6744.2
*: existing exchanger area; HTE: heat transfer enhancement; +: physical area only
The types of modifications to the existing network and the locations of the modified
exchanger units for this study can be seen in Section C.2 (Appendix C).
Table J.3 gives the total additional area required by each exchanger unit on the crude oil
stream for every energy consumption level. These exchangers area are obtained from
the same retrofit study carried out in Section C.2 (Appendix C). However, Table J.4
gives the physical exchanger required after exploiting heat transfer enhancement (HTE)
capabilities. The exchanger additional area is then compared with the maximum area
(Table J.2) that can be achieved if the exchanger is enhanced.
For specific exchanger unit, if the total area required is larger than the maximum
amount, heat transfer enhancement is applied to this exchanger and extra physical area
will be necessary. This extra area is the difference between the total area required and
the maximum amount that can be provided through enhancement. Typical example for
this condition is exchanger unit number 2 and energy consumption of 83.8 MW. Total
exchanger area required is 298.3 m2 (Table J.3); while maximum area available with
enhancement is 142.6 m2 (Table J.2). Therefore, enhancement is applied for the
maximum area; then, extra physical area of 155.7 m2 (= 298.3 – 142.6) (Table J.4) will
be needed to provide the required area difference.
On the other hand, if the area required is less or equal to the maximum area available
with enhancement, no physical area is needed and only heat transfer enhancement is
sufficient to provide the total required area (e.g. exchange unit number 7; energy
consumption of 82.5 MW).
The above procedure is applied to all exchanger units alongside for all energy
consumption levels. Finally, for all energy consumption levels, the total exchanger area
that is required in addition to heat transfer enhancement is determined. Then, the net
area required by exchangers after applying heat transfer enhancement can be evaluated
(see Table J.4).
Appendix J: Data for case study 6.7
276
Data of net retrofit area and energy consumption are plotted (Figure J.2), and compared
with the data for existing HEN without enhancement. The data are then regressed to
obtain the retrofit model parameters m′ and c′ (see equation 4.48, Chapter 4). The
regressed model parameters m′ and c′, are 1.5145751·107 (m2/MW) and -1.8138
respectively.
y = 15145751.6090x-1.8138
y = 9883123.3138x-1.6959
2000
3000
4000
5000
6000
7000
8000
35 45 55 65 75 85 95 105
Energy consumption (MW)
Ret
rofit
are
a (m
2)
Existing unit
With HTE
Existing HEN
HEN with HTE
Figure J.2: Retrofit curve and data regression for existing HEN with heat transfer enhancement (HTE) (horizontal dotted line represents the existing exchanger total area)
Table J.5: Optimum operating conditions for unit with heat transfer enhancement
Column Optimisation variable Base case value
Optimum value
Feed preheating temperature oC 365.00 369.13 Flow rate of pump-around liquid kmol/h 2186.56 1794.31 Temperature drop across pump-around oC 30.00 37.70
1
Flow rate of stripping steam kmol/h 1200.00 1095.50 Flow rate of pump-around liquid kmol/h 2305.66 2987.95 Temperature drop across pump-around oC 50.00 44.64
2
Flow rate of stripping steam kmol/h 250.00 268.37 Flow rate of pump-around liquid kmol/h 5790.85 4278.45 Temperature drop across pump-around oC 20.00 30.34
3
Flow rate of liquid between columns 3 and 4
kmol/h 1067.48 632.58
4 Reflux ratio 4.78 3.10
Appendix J: Data for case study 6.7
277
Table J.6: Product flow rates of optimum unit with enhancement