pinch analysis a tool for efficient use of energy
DESCRIPTION
Pinch Analysis_A Tool for Efficient Use of EnergyTRANSCRIPT
1
Staff Development Programme One week Jan 05th
-09th
, 2009
Under the aegis of
All India Council of Technical Education
Pinch Analysis: A Tool for Efficient Use of Energy
Department of Chemical Engineering offers a one week Training Course on Pinch Technology which provides a basic grounding in Process Integration.
Learn the fundamental concepts of Pinch Technology and how these can be applied to reduce energy and capital costs and increase capacity. It is appropriate for candidates who wish to gain an understanding of how to achieve process energy efficiency improvements and
Reduce utility costs
Remove energy & capacity bottlenecks
Avoid or reduce capital expenditure
Optimum practical design
Department of Chemical Engineering National Institute of Technology Rourkela Rourkela – 769 008, Orissa
Coordinated by: Dr. Shabina Khanam
Co-coordinated by: Prof. K. C. Biswal
2
ACKNOWLEDGEMENT
The AICTE sponsored short term course on “Pinch Analysis: A Tool for Efficient Use
of Energy” is a culmination of Research and Teaching efforts of the Process Engineering
group of the Chemical Engineering Department, NIT Rourkela.
Thanks are also due to Prof. Sunil Kumar Sarangi, Director, NIT Rourkela for his
consistent support and encouragement.
We would like to express my sincere gratitude to Prof. S. K. Jena, Dean (SRICCE), NIT
Rourkela for his excellent cooperative attitude. I thank the staff of SRICCE to provide
invaluable help.
We extend our thanks to all faculty members of Department of Chemical Engineering for
their cooperation and continuous encouragement.
We are also grateful to the Prof. Bikash Mohanty, Resource person from Chemical
Engineering Department, IIT Roorkee for his significant contribution in delivering this
course.
We take this opportunity to express our appreciation to the Post-Graduate students and
Non-Teaching staff of Chemical Engineering Department for their support and
assistance. Without their support this course could not have reached to this stage.
We also realize that without a high level of receptivity, active involvement, and
cooperation from the participants, this course would not have accomplished its
objectives.
Last but not the least; we thank all those who have directly or indirectly contributed
towards the success of this course.
Dr. Shabina Khanam Prof. K.C. Biswal
Coordinator Co-Coordinator
HOD, CH
3
COURSE OVERVIEW
Process Integration (PI) is a general approach for the design of energy efficient process
systems and Pinch Technology is a tool to achieve it. In the late 1970s Pinch Technology
emerged as a tool for the design of heat exchanger networks against the backdrop of
energy crisis. Its key contribution was to provide the engineers with simple concept of
heat, power and thermodynamics, which can be used interactively in each stage of design.
In 1980s, Pinch Technology received prime attention as a heat exchanger network design
tool and it was found that this technology could save around 20–40% of energy bills of
the industry. Since then, the method has become broad based. However, its
thermodynamic principles, heuristic rules and its key strategy to set targets before design
remain intact. With time it has emerged as a powerful, matured integrated design and
retrofitting tool for overall process design.
The present course deals with concept to implementation of Pinch Technology in
integrated process design.
The one week duration course was specially tailored to provide enough resources to the
attending candidates to start a course on Process Integration in their respective
departments or to use it in the industries. This course is expected to be popular in near
future as it holds considerable promise for the conservation of energy in Chemical and
allied industries.
4
LIST OF PARTICIPANTS
S. No. Participant Photograph
1 Dr. RaviShankar R
Prof. and Head
Chemical Engineering Department
Dayananda Sagar College of Engineering
Shavige Malleswara Hills.
Kumaraswamy Layout, Bangalore 560078
Ph: 9448327476
Email:- [email protected]
2 Prof. Mahadeva Raju, G. K.
Assistant Professor
Chemical Engineering Department
Dayananda Sagar College of Engineering
Shavige Malleswara Hills.
Kumaraswamy Layout, Bangalore 560078
Ph: 9845772214
Email:- [email protected]
3 Mr. Jagadish H Patil
Assistant Professor
Chemical Engineering Department
R V College of Engineering,
Mysore Road
Bangalore 59
Ph: 080-67178046/67178109
Email: [email protected]
4 Mr. Anil Kumar Prasad
Lecturer,
Deptt. of Applied Mechanics,
NIT Jamshedpur – 831014
Jharkhand
Ph: 9835314761
Email: [email protected]
5 Mrs. Dipa Das
Lecturer
Chemical Engineering Dept.
Indira Gandhi Institute of Technology
Sarang, (Parjang) - 759146
Dist – Dhenkanal
Email: [email protected]
5
6 Mr. Karthik S. P.
Senior Engineer
Sanden Vikas India Ltd.
Plot No. 65, Sector – 27A
Faridabad – 121003, Haryana
Ph: 9958855998
Email: [email protected]
7 Mr. Bhabani Prasanna Pattnaik
Assis. Professor
Mechanical Engineering Dept.
KIIT University
Bhubaneswar, Orissa
Ph: 9437169040
Email: [email protected]
8 Dr. Shib Sankar Saha
Sr. Lecturer
Electrical Engineering
Govt. Gollege of Engg. and Textile Technology
Berhampore – 742 101 W.B.
Ph: 9434315226
Email: [email protected]
9 Dr. S. K. Agarwal
Professor
Chemical Engineering Dept.
NIT Rourkela – 769 008,
Orissa
Ph: 9861386942
Email: [email protected]
10 Dr. Basudeb Munshi
Asstt. Professor
Chemical Engineering Dept.
NIT Rourkela – 769 008, Orissa
Ph: 0661-2462265
Email: [email protected]
6
11 Dr. Arvind Kumar
Assistant Professor
Chemical Engineering Department.
National Institute of Technology Rourkela –
769 008, Orissa
Ph: 9438348807
e-mail:[email protected]
https://sites.google.com/site/arvindkumarnitr/
12 Dr. Mithilesh Kumar
Asstt. Professor
Department of Met. & Materials Eng.
NIT Rourkela – 769 008, Orissa
Ph: 0661-2463554
Email: [email protected]
13 Mr. Binod Kumar Singh
Research Scholar
Department of Met. & Materials Eng.
NIT Rourkela – 769 008,
Orissa
Email: [email protected]
14 Mr Achyut Kumar Panda
Sr. Lecturer
Department of Chemistry
Jagannath Institute for Tech. & Mgmt.
Gajapati – 761211, Orissa
Ph: 9437132916
Email: [email protected]
15 Mrs Hemalata Patra
Lecturer, G.I.E.T.,
Gunupur
Ph: 9437646933
Email: [email protected]
7
16 Dr. Sunil Kumar Maity
Assit. Professor
Chemical Engineering Dept.
NIT Rourkela – 769 008
Ph: 0661-2462266
Email: [email protected]
17 Mr. Akshaya Kumar Rout
Senior Lecturer
Mechanical Engineering Dept.
C.V. Raman College of Engineering
Janla, Bhubaneswar – 752054
Ph: 9437756207
Email: [email protected]
8
CONTENTS
S.No. Lecture(s) Speaker Page
1. Process Intensification Dr. B. Mohanty 9
2. Process Integration Dr. B. Mohanty 19
3. Pinch Technology – An Overview Dr. S. Khanam 28
4. Basic Elements of Pinch Technology Dr. B. Mohanty 37
5. Area Targeting Dr. B. Mohanty 49
6. Number of Unit, Shell and Cost Targeting Dr. S. Khanam 61
7. Pinch Design Methods – Heuristic Rules Dr. B. Mohanty 74
8. Design of HEN for Maximum Energy Recovery, Loop
Breaking & Path Relaxation
Dr. B. Mohanty 80
9. Driving Force Plot and Remaining Problem Analysis Dr. B. Mohanty 97
11. References 106
9
Lectures 1 & 2
PROCESS INTENSIFICATION
Bikash Mohanty
Professor
Department of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee – 247 667
Today, we are witnessing new developments that go beyond “traditional” chemical
engineering. Investigators at many universities and industrial research centers are
investigating on novel equipment and techniques that could transform our concept of
chemical plants and lead to compact, safe, energy-efficient and environment-friendly
sustainable processes. These developments share a common focus on “Process
Intensification (PI)” – an approach that has been around for quite some time but has truly
emerged only in the past few years as a special and interesting discipline of Chemical
Engineering.
PI refers to the technologies and strategies that enable the physical sizes of conventional
process engineering unit operations to be significantly reduced.
The concept of PI was pioneered in late 70’s by Colin Ramshaw, when the primary goal
was to reduce the capital cost of a production system. The virtue of PI approaches will be
recognized when it is appreciated that the main plant items involved in the process (i.e.
reactors, heat exchangers, separators etc.) only contribute around 20% of the cost of the
given plant. The balance is incurred by installation costs, which involve pipe work,
structural support, civil engineering and so on. A major reduction in equipment size,
coupled preferably with a degree of telescoping of equipment function – for example
reactor / heat exchangers or combined condenser/distillation/re-boilers - could generate
10
very significant cost savings by eliminating support structure, expensive column
foundations and long pipe runs.
Mercer, in 1993, defined the PI as “PI is a design philosophy aiming at radical reduction
of physical size of the process equipment”. These reductions can be a factor three to four
in magnitude. Because energy efficiency of a process is determined by the ability to
transfer the heat in a cost effective way, the design of processes using a small amount of
heat exchanger (using PI studies) or using innovative heat exchanger design (i.e compact
heat exchanger) can save energy.
In 1995, Ramshaw defined PI as a strategy for making dramatic reductions in the size of
a chemical plant so as to reach a given production objective. These reductions can come
from shrinking the size of individual pieces of equipment and also from cutting the
number of unit operations or apparatuses involved. Ramshaw speaks about volume
reduction of the order of 10 to 1000, which is quite a challenging number since then the
definition of PI has been enlarged considerably.
Benefits of Process Intensification
PI has a potential to deliver major benefits to the process industry and many other sectors,
by accelerating the response to market changes, facilitating scale-up and providing the
basis for rapid development of new products and processes. Additional benefits of PI
include reduced capital cost, improved intrinsic safety and reduce environmental impact.
Process Intensification and Its Components
11
Process Intensification, being driven by the need for break through changes in operations,
focuses mainly on novel methods and equipments. PI consists of the development of
novel apparatuses and techniques that are compared to those commonly used today and
are expected to bring dramatic improvements in manufacturing and processing,
substantially decreasing equipment-size/production- capacity ratio, energy consumption
or waste production and ultimately resulting in cheaper, sustainable techniques.
As evident in Fig. 1, the whole field can generally be divided into two areas:
Process-Intensification equipments
Process-Intensification methods
Many industries offer emerging technologies that are designed for various segments of
the process industries having one common feature - Process Intensification. PI is the
miniaturization of unit operations and processes whereas a smaller compact piece of
equipment takes the place of a larger one at the same given capacity and mass flow rate.
Process Intensification Equipments
Static Mixer Reactor (SMR)
SMR has mixing elements made of heat transfer tubes (Fig. 2), can successfully be
applied in processes in which simultaneous mixing and intensive heat removal or supply
are necessary, such as in nitration or neutralization reactions.
The main disadvantage of SMRs is their relative high sensitivity to clogging by solids.
Therefore, their utility for reactions involving slurry catalysis is limited.
12
Examples
Spinning disk reactor Static mixers Reverse-flow
reactors
Membrane
absorption
Centrifugal
fields
Supercritical
fluids
Static mixer reactor
(SMR)
Compact heat
exchanger
Reactive
distillation
Membrane
distillation
Ultrasound Dynamic
(periodic)
reactor
operation
Static mixing catalysts
(KATAPAKs)
Microchannel heat
exchangers
Reactive extraction Adsorptive
distillation
Solar energy
Monolithic reactors Rotor/Stator mixers Reactive
crystallization
Microwaves
Microreactors Rotating packed beds Chromatographic
reactors
Electric
fields
Heat exchanger reactors
(HEX)
Centrifugal adsorber Periodic separating
reactors
Plasma
technology
Supersonic gas/liquid
reactor
Membrane reactors
Jet-impingement reactor Reactive extrusion
Rotating packed-bed
reactor
Reactive
comminution
Fuel cells
Equipment Methods
Equipment for
carrying out
chemical
reactions
Equipment for
operations not
involving chemical
reactions
Multifunctional
reactors
Hybrid
separations
Alternative
energy
sources
Other
methods
Process Intensification
Fig. 1. Process Intensification and its components
13
Monolithic Catalysis
Monolithic substrates used for today’s catalytic applications are metallic or nonmetallic
bodies providing a multitude of straight narrow channels of defined uniform cross-
sectional shapes.
To ensure sufficient porosity and enhance the catalytically active surface, the inner walls
of the monolith channels usually are covered with a thin layer of wash coat, which acts as
the support for the catalytically active species.
The most important features of monoliths are:
Very low pressure drop in single & two-phase flow
Fig. 2. Proprietary reactor-mixer is a classic example of
process intensifying equipment.
Fig. 3. Monolithic catalyst
14
High geometric areas per reactor volume
High catalytic efficiency, practically 100 %
Exceptionally good performance in processes in which selectivity is hampered by
mass transfer resistances
Microchannel Heat Exchangers
The geometrical configuration of Microchannel heat exchangers given in Fig. 4
resembles that of the cross-flow monoliths, although the materials and fabrication
methods used differ.
The Microchannel heat exchangers exhibit high heat fluxes and convective-heat-transfer
coefficients. The reported values of heat transfer coefficients in Microchannel heat
exchangers range from 10000 to 35000 W/m2K.
Process Intensifying Methods
Reverse Flow Reactor
For exothermic processes, the periodic flow reversal in such units allows for almost
perfect utilization of the heat reaction by keeping it within the catalyst bed and after
reversion of the flow direction, using it for preheating the cold reactant gases.
Fig. 4. Microchannel heat exchanger
15
These reactors are used in following industrial processes: SO2 oxidation, total oxidation
of hydrocarbons in off-gases, and NOx reduction.
Reactive Distillation
Reactive distillation is one of the better-known examples of integrating reaction and
separation, and is used commercially.
In the column, reactants are converted on the catalyst while reaction products are
continuously separated by fractionation (thus overcoming equilibrium limitations).
The catalyst used for reactive distillation usually is incorporated into a fiberglass and
wire-mesh supporting structure, which also provides liquid redistribution and
disengagement of vapor.
Reactive Extrusion
Reactive extruders are being increasingly used in polymer industries.
They enable reactive processing of highly viscous materials without requiring the large
amounts of solvents that stirred-tank reactors do.
Particularly popular are twin-screw extruders, which offer effective mixing, the
possibility of operation at high pressure and temperatures, plug-flow characteristics, and
capability of multistaging.
Most of the reactions carried out in extruders are single- or two-phase reactions.
Sonochemistry
Sonochemistry is the use of ultrasound as a source of energy for chemical processing and
appears to be the most advanced. Formation of microbubbles (cavities) in the liquid
reaction medium via the action of ultrasound waves has opened new possibilities for
chemical syntheses. These cavities can be thought of as high-energy microreactors.
16
Supercritical Fluids
Supercritical fluids (SCFs) are used industrially for the processing of natural products.
Because of their unique properties, SCFs are attractive media for mass transfer
operations, such as extraction and chemical reactions.
Many of the physical and transport properties of a SCF are intermediate between those of
a liquid and a gas. Diffusivity in an SCF, for example, falls between that in a liquid and a
gas; this suggests that reactions that are diffusion limited in the liquid phase could
become faster in a SCF phase.
SCFs already have been investigated for a number of systems, including enzymes
reactions, Diels-Alder reactions, organometallic reactions, heterogeneously catalyzed
reactions, oxidations and polymerizations.
Case Study of Process Intensification
The isomerisation of pinene oxide to campholenic aldehyde (Equation 1) is an important
reaction for the fragrance industry.
The reaction is complex, and a simplified schematic (Equation 2) shows how there are
four other major products, besides the desired campholenic aldehyde, are formed and
how this product (campholenic aldehyde) itself can react further to another five by-
products. A novel silica-supported zinc triflate catalyst was selected for the work. A
number of other heterogeneous catalysts are used for the reaction, though homogeneous
zinc halides are used commercially.
The results described below are expressed as percentage disappearance of the pinene
oxide (conversion), and efficiency of conversion of the disappeared pinene oxide to
desired campholenic aldehyde product (selectivity).
17
An amount of optimization work was performed in stirred flasks. When stirring a 1 %
solution of pinene oxide in 1.2.dichloroethane solvent with catalyst at 85 C, conversion
achieved was 100 % after 5 min, with selectivity on a plateau of 63-65 % at between 3
18
and 10 min reaction time, and a peak of 65 % at 5 min. Multiplying conversion and
selectivity together to give a product yield, we see a peak of 63-65 % at between 5 and 10
min.
Spinning disc work was first performed as a series of 15 two-minute runs at 25 to test
catalyst stability. The catalyst was attached to the disc surface with adhesive, the
conversion remained constant for each run at 20 %. Three consecutive passes with the
same material gave 55 % conversion at 84 % selectivity – which was encouraging.
A range of runs was now performed at 85, varying disc. The disc residence times was
thus explored in the range 0.5 to 5 sec. The optimum condition proved to be using the
highest tested feed rate of 6 ml/s and a spin-speed of 1000-1200 rpm. Lower spin speeds
gave 100 % conversion and much reduced selectivity – presumably attributable to over-
reaction of product with the longer residence time on the disc surface at lower rpm. Even
higher spin speeds gave up to 62 % selectivity – but at a reduced conversion of 75 %. The
optimum yield (conversion*selectivity) was stable at approximately 55 % at between
1000 and 1500 rpm.
The results show that the catalyst can be extremely effective on the disc, whilst avoiding
the filtration and recovery step required in stirred ranks. A bonus – which is often
experienced with intensified devices – is that the rate of data collection and process
optimization was enormous compared with stirred flask development. A new data point
could be generated every few minutes, a the generous equilibration time given after
adjusting feed-rate or spin-speed was a matter of 10-20 sec, and sample collection time
was only one minute.
19
Lecture-3
PROCESS INTEGRATION
Bikash Mohanty
Professor
Department of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee – 247 667
Process integration, a part of Process Intensification, is a fairly new term that emerged in
80’s and has been extensively used in the 90’s to describe certain systems oriented
activities related primarily to process design. It has incorrectly been interpreted as Heat
Integration by a lot of people, probably caused by the fact that Heat Recovery studies
inspired by Pinch Concept initiated the field and is still core elements of Process
Integration. It appears to be a rather dynamic field, with new method and application
areas emerging constantly. The Process Integration is defined as “systematic and general
methods for designing integrated production systems, ranging from individual processes
to total sites, with special emphasis on the efficient use of energy and reducing
environmental effects”.
This definition brings Process Integration very close to Process Synthesis, which is
another systems oriented technology. Process Integration and synthesis belongs to
process systems engineering. Process Integration has evolved from a heat recovery
methodology in the 80’s to become what a number of leading industrial companies in
90’s regarded as a “major strategic design and planning technology”. With this
technology, it is possible to significantly reduce the operating cost of existing plants,
while new processes often can be designed with reduction in both investment and
operating costs.
20
Definition of Process Integration as per International Energy Agency (IEA)
• Process Integration is the common term used for the application of methodologies
developed for System- oriented and Integrated approaches to industrial process
plant design for both new and retrofit applications.
• Process Integration refers to Optimal Design; examples of aspects are: capital
investment, energy efficiency, emissions, operability, flexibility, controllability,
safety and yields. Process Integration also refers to some aspects of operation and
maintenance.
• Process integration, combined with other tools such as process simulation, is a
powerful approach that allows engineers to systematically analyze an industrial
process and the interactions between its various parts.
Current Status of Process Integration
Process Integration is a strongly growing field of Process Engineering. It is now standard
curriculum for process engineers in both Chemical and Mechanical Engineering at most
universities around the world, either as a separate topic or as part of a Process Design or
Synthesis course. Research at UMIST has for 25 years been supported by a large number
of industrial companies through a Consortium that was established in 1984. As part of the
International Energy Agency (IEA) project on Process Integration, more than 50 other
universities around the world involved in research in this field have been identified.
From History to the Future
Process Design has evolved through distinct "generations". Originally (first generation),
inventions that were based on experiments in the laboratory by the chemists, were tested
in pilot plants before plant construction.
21
The second generation of Process Design was based on the concept of Unit Operations,
which founded Chemical Engineering as a discipline. Unit Operations acted as building
blocks for the engineer in the design process.
The third generation considered integration between these units; for example heat
recovery between related process streams to save energy.
A strong trend today (fourth generation) is to move away from Unit Operations and focus
on Phenomena. Processes based on the Unit Operations concept tend to have many
process units with significant and complex piping arrangements between the units. By
allowing more than one phenomena (reaction, heat transfer, mass transfer, etc.) to take
place within the same piece of equipment, significant savings have been observed both in
investment cost and in operating cost (energy and raw materials).
Different Schools of Thoughts in Process Integration
The three major features of Process Integration methods are the use heuristics (insight),
about design and economy, the use of thermodynamics and the use of optimization
techniques. There is significant overlap between the various methods and the trend today
is strongly towards methods using all three features mentioned above. The large number
of structural alternatives in Process Design (and Integration) is significantly reduced by
the use of insight, heuristics and thermodynamics, and it then becomes feasible to address
the remaining problem and its multiple economic trade-offs with optimization techniques.
Despite the merging trend mentioned above, it is still valid to say that Pinch Analysis and
Exergy Analysis are methods with a particular focus on Thermodynamics. Hierarchical
Analysis and Knowledge Based Systems are rule-based approaches with the ability to
handle qualitative (or fuzzy) knowledge. Finally, Optimization techniques can be divided
22
into deterministic (Mathematical Programming) and non-deterministic methods
(stochastic search methods such as Simulated Annealing and Genetic Algorithms). One
possible classification of Process Integration methods is to use the two-dimensional
(automatic vs. interactive and quantitative vs. qualitative) representation in Fig. 1.
Application of Process Integration
Process Integration can be applied in following fields of chemical engineering such as:
1. Heat integration – heat exchange network
2. Distillation column targeting
3. Cogeneration and total site targeting
4. Batch process targeting
5. Emission targeting
6. Mass exchange network (water and wastes water management & recovery of
valuable materials)
7. Hydrogen management in refineries
Hierarchical
Analysis
Heuristic
Rules Knowledge
Based Systems
Thermodynamic
Methods Optimization
Methods
qualitative
quantitative
interactive automatic
Fig. 1 One possible Classification of Process Integration
Methods
23
Techniques Available for Process Integration
1. Pinch Technology Approach
2. MILP/MINLP Approach
3. State-Space Approach
4. Genetic Algorithm Approach
5. Process Graph Theory Approach
Concept of Pinch Technology
The term "Pinch Technology" was introduced by Linnhoff and Vredeveld to represent a
new set of thermodynamically based methods that guarantee minimum energy levels in
design of heat exchanger networks. Over the last two decades it has emerged as an
unconventional development in process design and energy conservation. The term ‘Pinch
Technology’ is often used to represent the application of the tools and algorithms of
Pinch Technology for studying industrial processes.
Reactor
Separator
Heat exchange network
Utilities
The heat and material
balance is at this
boundary
Site-Wide Utilities
Fig. 2 Onion Diagram
1
2
3
4
24
Pinch technology provides a systematic methodology for energy saving in processes and
total sites. Fig. 2 illustrates the role of Pinch Technology in the overall process design.
The process design hierarchy can be represented by the “onion diagram” as shown below.
The design of a process starts with the reactors (in the “core” of the onion). Once feeds,
products, recycle concentrations and flow rates are known, the separators (the second
layer of the onion) can be designed. The network (the third layer) can be designed. The
remaining heating and cooling duties are handled by the utility system (the fourth layer).
The process utility system may be a part of a centralized site-wide utility system.
A Pinch Analysis starts with the heat and material balance for the process. Using Pinch
Technology, it is possible to identify appropriate changes in the core process conditions
that can have an impact on energy savings (onion layers one and two). After the heat and
material balance is established, targets for energy saving can be set prior to the design of
the heat exchanger network.
Data Extraction
The most time consuming and often most critical step is the identification of the need for
heating, cooling, boiling and condensation in the process. This task is more art than
science, and if not carried out properly, the final design will not be the best possible. It is
quite easy to accept too many feature of the proposed flow sheet, which inevitably results
in the situation where many good opportunities are excluded from the analysis.
In practice, there are a number of situations where heat integration is not desirable.
Examples include long distances (costly piping), safety (heat exchange between
hydrocarbon streams and oxygen rich streams), product purity (potential leakage in heat
exchangers), operability (start-up and shut-down), controllability and flexibility. A
25
reasonable strategy is, however, to start by including all process streams and keep the
degrees of freedom open. Later, practical considerations can be used to exclude some of
these streams and degrees of freedom, and the engineer will then at any time be able to
establish the consequences with respect to energy consumption and total annual cost. A
central part of data extraction is the identification of heating and cooling requirements in
the process. The necessary data for each process stream are the following:
m = mass flowrate (kg/s, tons/h, etc.)
Cp = specific heat capacity (kJ/kgC)
Ts = supply temperature (C)
Tt = target temperature (C)
Hvap = heat of vaporization for streams with a phase change (kJ/kg)
Additionally, the following information must be collected on utilities and existing heat
exchangers for retrofit:
Existing heat exchanger area (m2)
Heat transfer coefficient for cold and hot sides of heat exchangers (kW / m2 C).
Utilities available in the process (water temperature, steam pressure levels, etc),
Marginal utility costs, as opposed to average utility costs.
Data extraction must be preformed carefully as the results strongly depend on this step. A
key objective of data extraction is to recognize which parts of the flowsheet are subject to
change during the analysis (e.g. possibility of making modifications to the piping, or
adding new heat exchangers, possibility of making temperature changes in the process or
modifying the utility that heats a given piece of equipment (MP steam instead of HP
26
steam for example), etc). If, during extraction, all features of the flowsheet are considered
to be fixed, there will clearly be no scope for improvement.
At the beginning of a project it is recommended that all process stream be included in the
data extraction. Constraints regarding issues such as distance between operations,
operability, control and safety concerns can be incorporated later on. By proceeding in
such a fashion, it is possible to have an objective evaluation of the costs of imposing such
constraints. PI specialists generally include some constraints form the beginning of the
data extraction procedure. This can speed up the overall analysis, but a lot of experience
is required to ensure that potentially interesting heat-recovery projects are not excluded.
There are a lot of sector specifics for data extraction. However, heuristic rules have been
developed as guidelines. The following are the most relevant:
Do not mix streams at different temperatures. Direct non-isothermal mixing acts as a heat
exchanger. Such mixing may involve cross-pinch heat transfer, and should not become a
fixed feature of the design. For example, if the pinch is located at 70C, mixing a stream
at 90C with a stream at 50C creates a cross pinch, and will increase the energy targets.
The way to extract these streams is to consider them independently, i.e., one stream with
a supply temperature of 50C and the required target temperature, and the other stream
with a supply temperature of 90C and the required temperature.
Do not include utility streams (stream, flu gas, cooling water, refrigerant, cooling air,
etc.) in the process data unless they are involved directly in the process or they cannot be
replaced. One of the goals of using pinch analysis is to reduce the usage of utilities.
Therefore, if utility streams are extracted in a similar way to process streams, they will be
considered as fixed requirements and no opportunities of reduction in utility use will be
27
identified. In some cases, utility streams can be included because it is not practical to
replace them by any form of heat recovery. For example, this is often the case for stream
dryers, ejectors and turbine drives.
Do not consider the existing plant layout. When selecting the inlet and outlet parameters
for a process stream, existing heat exchange equipment and plant topology should not be
taken into account at first. True utility targets (for cooling and heating) should be set
regardless of the existing plant layout. Current plant energy consumption can then be
compared with minimum energy targets. In retrofit of existing facilities, once these
targets have been determined, plant layout (existing heat exchangers and piping,
distances, etc) needs to be taken into account in order to identify practical and cost-
effective projects to reach or approach these targets.
Identify hard and soft constraints on temperature levels. For example, a hard constraint
would be the inlet temperature of a reactor that cannot be changed in any way, while a
soft constraint would be the discharged temperature of a product going to storage, for
which the target temperature is often flexible.
Data extraction is a complex issue, and a significant part of the pinch specialist’s
expertise is related to building a good pinch model during the data extraction phase.
28
Lecture – 4
PINCH TECHNOLOGY – AN OVERVIEW
Shabina Khanam
Lecturer
Department of Chemical Engineering
National Institute of Technology Rourkela, Rourkela – 769 008
One of the most practical tools to emerge in the field of process integration in the past 20
years has been pinch analysis, which may be used to improve the efficient use of energy,
hydrogen and water in industrial processes. Pinch analysis is a recognized and well-
proven method in each of the following industry sectors:
Chemical
Petrochemical
Oil refinery
Pulp and paper
Steel and metallurgy
Food and drink
Over the past 20 years, pinch analysis has evolved and its techniques perfected. It
provides tools that allow us to investigate the energy flows within a process, and to
identify the most economical ways of maximizing heat recovery and of minimizing the
demand for external utilities (e.g., steam and cooling water). The approach may be used
to identify energy-saving projects within a process or utility systems.
Pinch technology analyses process utilities (particularly energy and water) to find the
optimum way to use them, resulting in financial savings. Pinch Technology does this by
making an inventory of all producers and consumers of these utilities and then
29
systematically designing an optimal scheme of utility exchange between them. Energy &
water re-use are at the heart of pinch technology. With the application of pinch
technology, both capital investment and operating cost can be reduced. Emissions can be
minimised and throughput maximised.
The Pinch Concept
Pinch analysis (or pinch technology) is a rigorous, structured approach that may be used
to tackle a wide range of improvements related to process and site utility. This includes
opportunities such as reducing operating costs, debottlenecking processes, improving
efficiency, and reducing and planning capital investment.
Major reasons for the success of pinch analysis are the simplicity of the concepts behind
the approach, and the impressive results it has been obtained worldwide. It analyzes a
commodity, principally energy (energy pinch) hydrogen (hydrogen pinch), or water
(water pinch), in terms of its quality and quantity, recognizing the fact that the cost of
using that commodity will be a function of both.
In general, we are using high-value utilities in our process and rejecting waste at a low
value. For example, if we consider energy, we may be burning expensive natural gas to
provide the process with high temperatures heat, and are rejecting heat at low
temperatures to cooling water or air.
Pinch analysis now has an establishment track record in energy saving, water reduction,
and hydrogen system optimization. In all cases, the fundamental principle, behind the
approach is the ability to match individual demand for a commodity with suitable supply.
The suitability of the match depends on the quality required and the quality offered. In
the context of utility management, the commodity may be heat, with its quality measured
30
as temperature. By maximizing the match between supplies and demands, we minimize
the import of purchased utilities (Fig. 1).
Pinch Technology Versus Process Engineering
Pinch Technology is a vital subdivision of process engineering.
WASTE
(a)
Process
HIGH QUALITY UTILITY
QUANTITY
QU
AL
ITIY
(b)
Process
HIGH QUALITY UTILITY
WASTE
QUANTITY
QU
AL
ITY
Pinch Technology
Pinch
ENERGY: WATER: HYDROGEN
MINIMISE
MINIMISE
Fig.1 Schematic process utility use
31
Carrying out a process engineering project without the input of a pinch study will
lead to a less efficient design.
Our engineers have specialized knowledge of thermodynamics and computer
analysis tools. They can communicate effectively with clients and undertake
conceptual designs. This explains why we are uniquely qualified to help you get
the most out of your pinch projects.
How is Pinch technology different from other energy audits?
Pinch technology reveals all the possible savings and their corresponding Financial
benefits.
• It defines the maximum possible savings.
• It looks at the overall site.
• It does not bench-mark but takes into account all specific mill factors, age,
location, process equipment, operating preferences, product, etc.
• It reveals the maximum cogeneration potential.
Role of Thermodynamic Laws in Pinch Technology
Pinch technology presents a simple methodology for systematically analyzing chemical
processes and the surrounding utility systems with the help of the First and Second Laws
of Thermodynamics. The First Law of Thermodynamics provides the energy equation for
calculating the enthalpy changes (dH) in the streams passing through a heat exchanger.
The Second Law determines the direction of heat flow. That is, heat energy may only
flow in the direction of hot to cold. This prohibits ‘temperature crossovers’ of the hot and
32
cold stream profiles through the exchanger unit. In a heat exchanger unit neither a hot
stream can be cooled below cold stream supply temperature nor a cold stream can be
heated to a temperature more than the supply temperature of hot stream. In practice the
hot stream can only be cooled to a temperature defined by the ‘temperature approach’ of
the heat exchanger. The temperature approach is the minimum allowable temperature
difference Tmin) in the stream temperature profiles, for the heat exchanger unit. The
temperature level at which Tmin is observed in the process is referred to as "pinch point"
or "pinch condition". The pinch defines the minimum driving force allowed in the
exchanger unit.
What Processes does Pinch Apply to?
Pinch applies to a wide range of processes. Pinch originated in the petrochemical sector
and is now widely accepted in mainstream chemical engineering. With a wealth of
applications experience, benefits can now be realized in many other process industries.
Wherever heating and cooling of process materials takes places there is a potential
opportunity. A realistic approach addresses the practical problems specific to each and
every site, leading to:
• Meaningful targets
• Feasible projects
• Real savings
• Essential strategic insights
Benefits of Pinch Technology
Pinch tells the best that can be achieved in a given system.
33
Pinch gives the practical target to aim for that is less than this theoretical
maximum.
Both of the above are done before any detailed design. This target then set the
basis for the design. Most importantly, it gives clear rules about how to construct
a design to achieve the targets. It will also show where the inefficiency lie in the
existing design.
Pinch takes a system-wide view of the problem. This allows one to see interaction
that would be difficult to spot on a process flow diagram or a flow sheet of site
utility system.
Pinch can work with incomplete data. One can refine the data in the areas where
accuracy is most important. This is in the area around the pinch.
Pinch Technology is in contrast to other design tools, which require detailed
information about geometry, flow sheet structure, etc. Pinch technology is one of
the few tools that really can be used in conceptual design.
Problem Addressed by Pinch Technology
Generally two types of problem are addressed:
Creating new designs
This is related to the design of HEN for a new plant, which is in design stage.
The ideal time to apply pinch analysis is during the planning of process
modifications that will require major investments, and before the finalization of
process design. Maximum improvements in energy efficiency; along with reduced
34
investments can be obtained in a new plant design, since many plant layout and
process constraints can be overcome by redesign.
Retrofit – Revamping existing designs
This is related to the retrofitting of an already existing HEN in a plant to improve
its exchange efficiency.
However, in retrofit projects, energy efficiency improvements usually require
some capital expenditure. In this case, pinch analysis can be specifically aimed at
maximizing the return of investment. Pinch analysis techniques allow us to
evaluate combinations of project ideas simultaneously, in order to avoid “double –
counting” savings, as well as conflicting projects. Indeed, the final investment
strategy for the available opportunities will ensure that site development is
consistent and synergistic.
Typical Savings
• BASF AG (Ludwigshafen, Germany), for example, has completed more than 150
retrofit using pinch technology, achieving over 25 % in energy savings site wide.
• In natural gas sweetening, for example, The Ralph M. Parsons Co. (Pasadena,
Calif.) says that pinch technology led to a 10% drop in capital costs and energy
use in its amine absorption column.
• GE plastics was faced with a requirement of invest $15 million in doubling the
capacity of the wastewater handling system of its Silicones Production Facilities
in Netherlands. Linnhoff March aimed to avoid this investment cost by reducing
wastewater flow by 50 %.
• The following benefits have been obtained for refinery retrofits:
35
a) Energy reduced by 15-35 % through revamping of HENs based on
paybacks of 1.5-3 years.
b) Units debottlenecked by 10-20% without modifying fired heaters or major
pumps.
c) Lower fouling from improved understanding of the system dynamics.
d) Improved flexibility giving the lowest cost design for different operating
cases.
e) Reduced emissions at the source.
The potential energy and water consumption savings in major industries sectors
are given in Fig. 2 & 3.
Fig. 2 Potential energy savings
36
Fig. 3 Potential water consumption savings
37
Lecture – 5, 6, 7
BASIC ELEMENTS OF PINCH TECHNOLOGY – PART I, II & III
Bikash Mohanty
Professor
Department of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee – 247 667
KEY STEPS OF PINCH TECHNOLOGY
There are four key steps of pinch analysis in the design of heat recovery systems for both
new and existing processes:
1) Data Extraction, which involves collecting data for the process and the utility
system.
2) Targeting, which establishes figures for best performance in various respects.
3) Design, where an initial Heat Exchanger Network is established.
4) Optimization, where the initial design is simplified and improved economically.
Data Extraction
The details of data extraction are discussed in Lecture 3.
Targeting
An important feature of Process Integration is the ability to identify Performance Targets
before the design step is started. For heat recovery systems with a specified value for the
minimum allowable approach temperature (Tmin), targets can be established for
Minimum Energy Consumption (external heating and cooling), Fewest Number of Units
(process/process heat exchangers, heaters and coolers) and Minimum Total Heat Transfer
38
Area. In addition, the corresponding calculations will also identify the Heat Recovery
Pinch, which acts as a bottleneck for heat recovery.
Designing
Design of Heat Exchanger Networks in various industries is primarily carried out using
the now classical Pinch Design Method (Linnhoff and Hindmarsh, 1983). While the
original method focused on minimum energy consumption and the fewest number of
units, later graphical and numerical additions made it possible also to consider heat
transfer area and total annual cost during design.
The basic Pinch Design Method respects the decomposition at Process and Utility Pinch
points and provides a strategy and matching rules that enable the engineer to obtain an
initial network, which achieves the minimum energy target.
The Pinch Design Method also indicates situations where stream splitting is required to
reach the minimum energy target. Stream splitting is also important in area
considerations and the optimal use of temperature driving forces.
The design strategy mentioned above is simply to start design at the Pinch, where driving
forces are limited and the critical matches for maximum heat recovery must be selected.
Optimization
Heat exchange network for maximum energy recovery established by pinch design
method, should only be regarded as initial designs and some final optimization is
required. The matches in the initial network depend on pinch location and since the pinch
point depends on the value of Tmin, this becomes a key parameter in the pinch design
method. By repeating all calculations, for synthesis of HEN, for different values of Tmin,
39
it is possible to identify a good starting value for the level of heat recovery. This exercise
of pre-optimization has been referred to as “Supertargeting”. For a typical Problem, the
minimum total annual cost is obtained to be 240.42103 $/yr (Fig. 1). Thus, the optimum
ΔTmin is 13 °C.
BASIC ELEMENTS OF PINCH TECHNOLOGY
Grid Representation
The grid is used to represent heat exchange network more conveniently. The important
features of grid representations are:
Hot streams (streams which require cooling) are drawn at the top running let to
right.
Cold streams (streams which require heating) are drawn at the bottom running
right to left.
The Total Annual Cost Profile
0
50
100
150
200
250
300
350
400
0 20 40 60
Minimum temperature difference
TA
C (
1000 $
/yr)
Δ Tmin Optimum = 13 °
Fig. 1 The total annual cost profile
40
A heat exchanger is represented by a vertical line joining two open circles on the
streams being matched. The heat exchanger load can conveniently be written
under the lower open circle.
Heaters (H) and coolers (C) can be represented in an open circle on the stream
being heated or cooled.
Temperatures can be put on the grid as shown to allow an easy check on the
terminal approach temperature for each unit.
The stream data for the typical process is shown in Table 1. The grid representation for
this process, which includes two hot, H1 & H2, and two cold, C3 & C4, streams, are
shown in Fig.2.
Table 1 The Stream Data for the Process
Stream Ts (oC) Tt (
oC) MCp (kW/ C)
H1 175 45 10
H2 125 65 40
C3 20 155 20
C4 40 112 15
H
2
3
C
175
125
155
112
1400
98
85
1080
1300
1320
45
65
20
40
MCp (kW/ C)
10
40
20
15
Stream
H1
H2
C3
C4 2
Fig. 2 The grid representation of the process
3
41
Composite Curve
The Composite Curves (CCs) are constructed from ‘stream data’ representing a process
heat and material balance. The CCs allow the designer to predict-optimized-hot and cold
utility targets ahead of design, to understand driving forces for heat transfer, and to locate
the heat recovery ‘Pinch’. CCs consist of temperature-enthalpy (T-H) profiles of heat
availability in the process (the “hot composite curves”) and heat demands in the process
(the “cold composite curves”) together in a graphical representation. CCs also provide the
minimum requirement of hot and cold utilities in the process.
The construction of the hot composite curves (as shown in Fig.3) simply involves the
addition of the enthalpy changes of the streams in the respective temperature intervals.
The CCs for the stream data, given in Table 1, are shown in Fig.3. The QHmin and QCmin
are minimum hot and cold utilities.
0
50
100
150
200
0 1000 2000 3000 4000 5000
Heat Content Q (kW)
T (oC)
HCC CCC
Region of heat recovery by
process to process exchange
QHmin
QCmin
Tmin
Above
pinch Below
pinch
Fig. 3 The hot composite curves (HCC) and cold composite curves (CCC) respectively
show the heat availability and heat requirement for the overall process.
42
Problem Table Algorithm
This graphical manipulation of composite curves to generate minimum targets is time
consuming and clumsy. An alternative procedure is entirely based on simply arithmetic
and involves no trial and error.
The procedure is known as the problem table and is broken down into three stages.
1. Set up shifted temperature intervals from the stream supply and target
temperatures by subtracting ΔTmin /2 from the hot streams and adding ΔTmin /2 to
the cols streams.
It is important to note that shifting the curves vertically does not alter the
horizontal overlap between the curves. It therefore does not alter the amount by
which the cold composite curve extends beyond the start of hot composite curve
at the hot end of problem. Also, it does not alter the amount by which hot
composite curve extends beyond the start of cold composite curve at the cold end.
2. In each shifted temperature interval, calculate a simple energy balance from:
(1)
Where ΔHi = heat balance for shifted temperature interval i and ΔHi is the
temperature difference across it
CPc = specific heat capacity of a cold stream (MW/oC)
CPh = specific heat capacity of a hot stream (MW/oC).
If the cold streams dominate the hot streams in a temperature interval, then the
interval has a net deficit of heat, and ΔH is positive. If hot streams dominate cold
streams, the interval has a net surplus of heat, and ΔH is negative.
43
3. Now, cascade any surplus heat down the temperature scale from interval to
interval. This is possible because any excess heat available from the hot streams
in an interval is hot enough to supply a deficit in the cold streams in the next
interval down. First, assume no heat is supplied to the first interval from hot
utility. As a consequence of it some of the heat flows are negative, which is
infeasible. Heat cannot be transferred up the temperature scale. To make the
cascade feasible, sufficient heat must be added from hot utility to make the heat
flows to be at least zero. The smallest amount of heat needed from hot utility is
the largest negative heat flow.
Example
The problem table algorithm is explained using the stream data of a typical process given
in Table 2. The minimum approach temperature is 10 °C. The shifted temperatures for
each stream are detailed in Table 3.
Table 2 Stream data
Stream
Heat capacity flow rate
(MW/°C)
Ts (°C) Tt (°C)
Cold (C1) 0.2 20 180
Hot (H1) 0.15 250 40
Cold (C2) 0.3 140 230
Hot (H2) 0.25 200 80
44
Table 3 Stream Data with Shifted Temperature
Stream
Heat capacity flow rate
(MW/°C)
T*s (°C) T*t (°C)
Cold (C1) 0.2 25 185
Hot (H1) 0.15 245 35
Cold (C2) 0.3 145 235
Hot (H2) 0.25 195 75
The shifted temperatures are arranged in decreasing order. The stream population is
shown in Fig. 4 with a vertical temperature scale. The interval temperatures shown in Fig.
4 are set to ΔTmin /2 below hot stream temperatures and ΔTmin /2 above cold stream
temperatures.
Fig. 4 The stream population for stream
data shown in Table 2
45
Then a heat balance is carried out within each shifted temperature interval according to
Eq. 1. The result is given in Fig. 5, in which some of the shifted intervals are seen to have
a surplus of heat and some have a deficit.
Fig. 5 The temperature interval heat balances
Now, cascade any surplus heat down the temperature scale from interval to interval
assuming no heat is supplied to the first interval from hot utility (Fig. 6). The first interval
has a surplus of 1.5 MW, which is cascaded to the next interval. This second interval has
a deficit of 6 MW, which leaves the heat cascaded from this interval to be -4.5 MW and
so on. Some of the heat flows are negative, which is infeasible. To make the cascade
feasible, largest negative heat flow from Fig. 6 that is 7.5 MW is added from hot utility to
make the heat flows to be at least zero. The revised cascade is shown in Fig. 7 which
gives one heat flow of just zero at an interval temperature of 145 °C.
46
More than 7.5 MW could be added from hot utility to the first interval, but the objective
is to find minimum hot and cold utility. Thus, from Fig. 7 minimum hot and cold utilities
are 7.5 MW and 10 MW, respectively. The point where the heat flow goes to zero at
shifted temperature 145°C corresponds to the pinch. Thus, the actual hot and cold stream
pinch temperatures are 150 °C and 140 °C, respectively.
The composite curves are useful in providing conceptual understanding of the process but
the problem table algorithm is a more convenient calculation tool.
Fig. 6 Cascaded surplus heat from high to
low temperature
Fig. 7 Add heat from hot utility to make
all heat flows zero or positive
47
Grand Composite Curve
The grand composite curve (GCC) is a graphical representation of the heat cascade. GCC
is based on the same process stream data as Composite Curves. GCCs highlight the
process/utility interface. It gives clear visualization of hot and cold utility and provides an
easy approach to use multiple utilities in the process. For the stream data, shown in Table
1, the GCC is represented in Fig. 8.
Maximum Energy Recovery
The overlap between the hot and cold composite curves represents the maximum amount
of heat recovery possible within the process. The source/sink characteristics of process
heat exchange systems give five concepts.
Targets: Once the composite curves are known, we know exactly how much external
heating/cooling is required. Near-optimal processes are confirmed as such and non-
optimal processes are identified with great speed and confidence.
Pinch High temperature process
sink profile
Low temperature process
source profile
Hot utility
Cold Utility
Process to process
heat exchange
Above Pinch
Below Pinch
48
The pinch: The process needs external heating above the pinch and external cooling
below the pinch. This tells us where to place furnaces, steam heaters, coolers etc.
More in, more out: An inefficient process requires more than the minimum external
heating and therefore more than the minimum external cooling. For every units of excess
external heat in a process one has to provide heat transfer equipment twice. This insight
helps us to improve both energy and capital cost.
Freedom of choice: The “heat sink” and the “heat source” in Fig. 8 are separate. This
constraint helps the designer to choose plant-layouts, control arrangements etc. If
designer violates this constraint, he can evaluate the pinch heat flow and therefore predict
what overall penalties will be involved.
Trade-offs: A simple relationship exists between the number of streams (process streams
plus utilities) in a problem and the minimum number of heat exchange units (i.e. heaters,
coolers and interchangers).
Thus if designer goes for best energy recovery, designing the “heat source” and “heat
sink” section separately, he or she will incur the need for more units than if the pinch
division had been ignored. Hence a new type of trade-off has been identified, between
energy recovery and number of units. This insight adds to the traditional concept of a
trade-off between energy and surface area.
49
Lecture – 8
AREA TARGETING
Bikash Mohanty
Professor
Department of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee – 247 667
Area is important in determining heat exchanger network capital cost. Before explaining
the complete procedure to computation of area it is necessary to discuss the principles for
minimum area in heat exchanger networks.
Start by considering the example in Fig. 1a, where two hot streams exchange heat against
a single cold stream. If we assume the overall heat transfer coefficient U is constant for
all exchangers and these exchangers are countercurrent units then the network has an area
of 88 m2.
Fig. 1b shows a different network with stream splitting. Its area is 84 m2. The reason is
that it has better countercurrent behavior in terms of the overall network. In Fig. 1a the
matches are in temperature sequence whereas in Fig. 1b the matches share more of the
available temperature differences by splitting the cold stream. Fig. 1c shows that we can
do better still. The network area is now 77 m2. This is the minimum area for the stream
set as defined. The network has been developed by stream-splitting only where streams
compete for the same driving forces by overlap in temperature.
The composite curve of the data for example, shown through Fig. 1, is drawn in Fig. 2.
Overall countercurrent heat exchange now appears as vertical heat transfer on the
composite curves. Partitioning of the stream data to follow the temperatures of the
vertical model then leads to the minimum area design for this example.
50
Fig. 1 (a) network with exchangers in temperature sequence on cold stream; (b) network
with exchangers sharing temperature span of cold stream; and (c) network with
exchangers showing correct distribution of temperatures for minimum area.
51
Fig. 2 Resolving temperature contention using the composite curves: (a) overall
countercurrent heat exchange appears as vertical heat transfer on the composites; (b) the
temperatures of enthalpy intervals show where stream-splitting will be required, (c) these
temperatures can be marked on the grid; and (d) used to guide design for temperature
contention.
To calculate the heat exchanger network area from composite curve, utility streams must
be included with the process streams in the composite curves to obtain the balanced
composite curves (BCC). The resulting BCC (Fig. 3a) should have no residual demand
for utilities. The BCC are divided into vertical “enthalpy intervals”. The intervals are
defined whenever a change in slope occurs in either balanced composite profile. Next, a
network design is considered within each enthalpy interval, which can satisfy vertical
52
heat transfer. Fig. 3b demonstrates this for an interval, which contains two hot streams
and three cold streams. Each hot stream is split into the same number of branches as the
number of cold streams in that interval. Similarly, each cold stream is split into the same
number of branches as the number of hot streams in that interval. Hence, each hot stream
can be matched with each cold stream such that every match occurs between the corner
temperatures of the enthalpy interval. The heat exchanger of these matches must
therefore appear as vertical on the BCC.
Fig. 3. Example of general stream splitting and matching scheme for vertical heat
transfer in an enthalpy interval of the balanced composite curves.
The minimum total area could be taken as the sum of the areas of all such exchangers
from all enthalpy intervals. However, this is not necessary if U = constant. From the
composite curves, the area from vertical heat transfer in interval i is simply:
(1)
53
where ΔHi is the enthalpy width of interval i and ΔTLM,i is the logarithmic mean
temperature difference of interval i.
Hence, the total minimum network area is given by:
(2)
This shows that in order to derive an area target based on U = constant no design is
required.
Different heat transfer coefficients in the model for minimum area
Consider again the design in Fig. 3 for vertical heat transfer in enthalpy interval i of the
composite curves. If the heat transfer coefficients differ then the total area of these
exchangers is:
(3)
Where, Q13 is the duty of the match between streams 1 and 3, U13 its overall heat transfer
coefficient, etc.
Now,
(4)
where h1 is the heat transfer coefficient of stream 1 (including film, wall and fouling
resistances), etc.
54
So,
(5)
But
(6)
where (qj)i is the enthalpy change of stream j in enthalpy interval i.
so,
(7)
The argument applies in general for other enthalpy intervals. Summing up over all
intervals on the composite curves gives:
(8)
This simple formula incorporates stream individual heat transfer coefficients and allows a
“target” for the minimum heat exchange area to be calculated from the composite curves.
Further, within ith
enthalpy interval, all hot streams undergo the same temperature change
(dTh)i as do all the cold streams (dTc)i. As q = MCpdT, then
55
(9)
Example:
Stream Data of a typical process with Tmin = 20˚ C is given in following table.
Stream(s) Ts (C) Tt (C) MCp (kW/ C) h (kW/m2 C)
H1 175 45 10 0.2
C1 20 155 20 0.2
H2 125 65 40 0.2
C2 40 112 15 0.2
Steam (HU) 180 179 - 0.2
Cold Water (CU) 15 25 - 0.2
The step wise procedure is described below:
Calculation of minimum hot and cold utilities
Minimum hot and cold utilities are calculated by Problem Table Algorithm which are as
follows:
Hot utility, Qhu,min = 605 kW
Cold utility, Qcu,min = 525 kW
Calculation of utility flow rates
The MCp values of hot utility (hu) and cold utility (cu) are given as:
(MCp)hu = Qhu,min/(Tin-Tout)hu = 605/(180-179) = 605 kW/° C
(MCp)cu = Qcu,min/(Tout-Tin)cu = 525/(25-15) = 52.5 kW/° C
jc jc
p
ic
jh jh
p
ih
ervals
i
iLMh
MCdT
h
MCdTTA )()(/1
int
min
56
Plotting the Balanced Composite Curves
The procedure for plotting the Balanced Hot Composite Curve and Balanced Cold
Composite Curve is the same as the Hot Composite Curve and Cold Composite Curve,
except that the utilities are also considered as additional streams.
Balanced Hot composite Curve (BHCC)
For BHCC the temperatures of hot streams and hot utility are arranged in ascending order
(Fig. 4). The sum of the MCP values of hot streams and utility present in each interval is
calculated. Then this sum is multiplied by the temperature difference of each interval.
After that a cumulative enthalpy is calculated using the formula:
CumQhb, i = CumQhb, i-1 + Qint, hbi (10)
Fig. 4 Data for balanced hot composite curve
Now, BHCC is obtained by plotting temperature and CumQhb as shown in Fig. 5.
Similarly Balanced cold composite curve can be drawn. The two curves are
superimposed on each other to get BCC as shown in Fig. 6. The BCC are divided into
vertical “enthalpy intervals”. The intervals are defined whenever a change in slope
occurs in either balanced hot composite curve (BHCC) and balanced cold composite
CumQhb Qhb
45
65
125
175
179
180
1
2
3
4
5
H1
H2
H
U
10
40
605
10
50
10
0
605
MCp,hb
3000
500
0
605
200 200
3200
3700
3700
4305
57
curve (BCCC) profiles. The BCC on being divided into enthalpy intervals, allow
calculation of the area target based on a model of vertical heat transfer.
Fig. 5 Data for balanced hot composite curve
Fig. 6 The balanced composite curve for the example
0
20
40
60
80
100
120
140
160
180
200
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
Heat Content Q (kW)
T (
C)
BHCC
BCCC
Interval i Th,i.-1
Tc,i.-1
Th,i.
Tc,i.
0
20
40
60
80
100
120
140
160
180
200
0 1000 2000 3000 4000 5000
Heat content Q, kW
Te
mp
era
ture
, D
eg
C
58
Determination of enthalpies for intervals
CumQhb and CumQcb (for BCCC) are merged by omitting cumulative enthalpies common
to both values and the entries are then sorted in ascending order. This identifies all points
where composite curve has a vertex (change in slope).
Calculation of interval temperatures on BHCC
The following formula is used for calculation of interval temperature:
Th3 = Thb,row r – (CumQhb,row r- CumQ3)/MCp,hb row r
Where, Thb,row r and CumQhb,row r are temperature and CumQ in the row r (in which the
temperature is available), In this case, row r = 6
For CumQi = 262.5 kW, Thi = 125˚ - (3200-262.5)/50 = 66.25˚C.
For CumQi = 200 kW, Tci = 20˚ - (262.5-200)/52.5 = 18.81˚C.
Similarly other temperature intervals are found and shown in Fig. 7.
Fig. 7 Determination of the enthalpy intervals
Calculation of (MCp/h)h and (MCp/h)c for each interval
66.25
73.5
79.5
149.5
18.81
105
124.5
124.5
59
These are calculated in a manner similar to MCp,hb of Fig. 4. For example, consider first
interval of Fig. 7 where only stream H1 exists, therefore (MCp/h)h = 10/0.2 = 50. Next
four interval contain streams, H1 and H2, thus, (MCp/h)h = 50/0.2 = 50. These data are
shown in Table 1.
Calculation of (Q/h)
For first interval, (Q/h) = (65˚ - 45˚)50 + (18.81˚ - 15˚)262.5 = 2000
The complete data are shown in Table 1.
Calculation of log mean temperature difference, TLM
This is done by the following formula:
For first interval:
TLM, 1 = [(65-18.81)-(45-15)]/[ln(65-8.81)/(45-15) = 37.51˚ C.
The complete data are shown in Table 1.
Calculation of countercurrent exchanger area in each interval
This is calculated by dividing the (Q/h) by the corresponding TLM in for the interval.
For first interval: A1=2000/37.51 = 53.31 m2
The complete data are shown in Table 1.
Based on above calculation the minimum area is found as 1312.57 m2
for the example
undertaken.
1,1,
,,
1,1,,,
ln
)()(
icih
icih
icihicih
LM
TT
TT
TTTTT
60
Table 1 Calculation of countercurrent exchanger area
int Thi Tci (MCp/h)h (MCp/h)c (Q/h) TLM, i Ai
0 45 15 0 0 0 0 0
1 65 18.81 50 262.5 2000 37.51 53.31
2 66.25 20 250 262.5 625 46.22 13.52
3 73.5 25 250 362.5 3625 47.37 76.53
4 79.5 40 250 100 3000 43.85 68.42
5 125 105 250 175 22750 28.65 794
6 149.5 112 50 175 2450 27.84 88.01
7 175 124.75 50 100 2550 43.56 58.53
8 179 124.75 0 100 0 52.22 0
9 180 155 3025 100 6050 37.76 160.23
61
Lecture – 9 & 10
NUMBER OF UNIT, SHELL AND COST TARGETING
Shabina Khanam
Lecturer
Department of Chemical Engineering
National Institute of Technology Rourkela, Rourkela – 769 008
Number of unit targeting
The capital cost of chemical processes tends to be dominated by the number of items on
the flowsheet. This is certainly true of heat exchanger networks and there is a strong
incentive to reduce the number of matches between hot and cold streams.
To understand the minimum number of matches or units in a heat exchanger network,
Fig. 1 is considered which shows the heat loads on one hot stream and three cold streams
written within the circles representing the streams. The predicted hot utility load is shown
similarly. In this process only hot utility is required but no cold utility. The total system is
in enthalpy balance i.e. the total hot plus utility is equal to the total cold.
Matching Steam with Cold1 and maximizing the load completely satisfies or “tick off”
Steam, leaving 1165 units of heating required by Cold1. Matching Cold1 with Hot and
Steam
1068 Hot
2570
Cold1
2233
Cold2
413
Cold3
992
Fig. 1 Illustration of minimum number of units design.
1068
1165 413 992
62
maximizing the load on this match so that it “ticks off” the 1165 residual requirement on
Cold1, leaves 1405 residual heat available from Hot.
So following the principle of maximizing loads, i.e. “ticking off” stream or utility loads
or residuals, leads to a design with a total of four matches. This is in fact the minimum
for this problem.
Thus, Umin = N – 1
Where, Umin = minimum number of units (including heaters and coolers)
N = total number of streams (including utilities)
Another problem, Fig. 2(a) having two hot streams and two cold streams. Both hot and
cold utility are required. For this problem 5 (N-1) [Where, N = 6.0] units are required
which is obtained by putting the matches using ticking off loads or residuals loads to a
design.
Fig. 2(a). Number of unit is one less than the number of streams included utilities
63
Fig. 2(b). Same principle for separate components – “Subset Equality”
Fig. 2(c). One unit more for every loop
Fig. 2(b) shows a design having one unit less than previous design. The subset of streams
H2, C1 and CW is in enthalpy balance. Similarly, ST, H1 and C2 are in enthalpy balance
(which they must be if the total problem is in balance). What this means is that for the
given data set we can design two completely separate networks, with the formula Umin =
N – 1 applying to each individually. The total for the overall system is therefore (3-1)+(3-
1) = 4 units. This situation is termed “subset equality”
The new unit is placed between ST and C2 as shown in Fig. 2(c). The extra units
introduces what is known as a “loop” into a system. At the hot utility ST, the loop can be
64
traced through the connection to C1, from C1 to H1, from H1 to C2, and from C2 back to
ST.
Suppose the new match, which is between ST and C2, is given a load of X units. Then by
enthalpy balance the load on the match between ST and C1 is 30-X, between C1 and H1,
10 + X, and between H1 and C2, 60-X.
The features discussed above are described by a theorem from graph theory in
mathematics, known as Euler’s general network theorem. This theorem translates into the
terminology of HEN, states that
Umin = N + L – s
Where, Umin = minimum number of units (including heaters and coolers)
N = total number of streams (including utilities)
L = number of loops
s = number of separate components.
Normally we want to avoid extra units, and so design for L=0. Also, if there will be no
subset equality in the data set and then minimum number of unit targets is
Umin = N – 1
Since the pinch divides the problem into two thermodynamically independent regions, the
targeting formula must applied to each separately.
Shell Targeting
The shell and tube heat exchanger (SHE) is most common type of heat transfer
equipments used in heat exchanger networks (HENs) of chemical process industries.
Generally multipass SHE is employed in these industries because of its following
advantages: (1) the configuration gives a large surface area in a small volume, (2) good
65
mechanical layout: a good shape for pressure operation, (3) uses well established design
procedures and fabrication techniques, (4) can be constructed from a wide range of
materials and (5) easily cleaned.
Many HEN design methods described in literature make the simplifying assumption of
counter current exchanger. It has been seen that an optimal solution of the HEN problem
based on purely counter current heat exchanger only will remain optimal in practice if
each unit can be realized by one exchanger with single shell. However, it rarely occurs in
industry as multipass construction of SHE is used here. Therefore, it is practically
feasible to target number of shells than the units at the synthesis stage of HEN.
FT Correction Factor
In case of the simplest multipass SHE, the 1-2 type, the liquid in one tube pass flows in
counter flow while in the other pass flows in parallel relative to shell fluid. To account
counter and parallel flows in 1-2 SHE, a correction factor FT is introduced into the basic
heat exchanger design equation, shown through Eq. 1, to take into account the above
phenomena,
Q = UA (Tln) FT where 0< FT<1 (1)
Where,
Q = heat exchanger duty (kW)
U = overall heat transfer coefficient, (kW/m2 C)
A = Heat exchanger area (m2 )
Tln = log mean temperature difference (C)
66
The FT factor is represented as the ratio of actual mean temperature difference in a 1-2
SHE to counter flow Tln for the same terminal temperatures. FT is a function of
dimensionless ratios, R and P, where
Heat capacity ratio, R = CPH / CPC = ((TCo – TCi ) ((THi – THo ) (2a)
and thermal effectiveness, P = (THi - THO ) / (THi – TCi ) (2b)
where THi = Hot stream inlet temperature (oC)
THo = Hot stream outlet temperature (oC)
TCi = cold stream inlet temperature (oC)
TCo = cold stream outlet temperature (oC)
Based on the value of FT, feasible design of heat exchanger is screened amongst different
alternative designs. For this purpose a rule of thumb i.e. FT > 0.8 is used and each design
with unacceptably low FT value is discarded.
It is well known fact that for multipass exchangers heat recovery is limited by Tln
correction factor, FT. If FT<0.8 one should increase the number of shells till FT becomes
greater than 0.8. For a 1-2 SHE, FT falls sharply with increasing temperature cross. The
ability to accommodate a temperature cross increases rapidly as the number of shell
passes is increased. However, designers often encounter situations where the FT is too
low or the FT slope is too large. If this happens, the designers may be forced to consider
multiple shell arrangements of 1-2 type. Therefore, it is required to compute number of
shells for a HEN.
A method to account for design sensitivity, based on the fact that for any value of R there
is a maximum asymptotic value for P, say Pmax, which is given as FT tends to – , and is
evaluated by
67
)11 2/(R P 2
max R (3)
Practical designs will be limited to some fraction of Pmax that is:
P = XP Pmax 0 < XP < 1 (4)
Where XP is a constant defined by the designer. The value of XP = 0.9 is sufficient to
satisfy FT≥0.75, while also avoiding regions of steep slope and therefore assuring a more
reliable design.
Situations are often encountered where FT is too low (or within the present context the FT
slope too steep) for a single shell. If this happens the designer may be forced to consider
an arrangement of multiple shells in series. If multiple shells are required then the most
common practice is to adopt a trial and error approach in which the number of shells in
series is progressively increased until a satisfactory value of FT is obtained for each shell.
Using the constant XP approach any need for trial and error can be eliminated since an
explicit expression for the number of shells can be derived. This is done by using the
following equation for N number of 1-2 shells in series.
R ≠ 1
N
rP
RPYwhere
YR
YP )
1
1(
1
2
21
(5a)
R = 1
12121
21
PNP
NPP (5b)
P1-2 is the effectiveness of each single 1-2 shell (given by XP * Pmax) whereas P applies
overall to the series of shells. Equations (3) and (4) which together relate P1-2 to XP and
R, can then be used to eliminate P1-2 from equation (5) to give the following expressions:
68
R ≠ 1 N = 1n ((1- RP)/(1-P))/ln W (6a)
Where
)211/()211( 22
PP XRRRXRRW (6b)
R = 1 pP XX /))2/2( P))(1-(P/(1 N (6c)
In terms of R, P and P1-2, the number of shells can be computed using following
equations:
N = ln [(1-RP)/(1-P)]ln[(1-RP12)/(1-P12)] for R ≠ 1 (7a)
And
N = [P/(1-P)]/[P12/(1-P12)] for R = 1 (7b)
XP is chosen to satisfy the minimum allowable FT (for example, for FT ≥ 0.75, XP=0.90 is
used). The application of XP is valid under the same assumptions as those of FT. Eq. 6 or
7 then evaluates explicitly the number of shells required and, at the same time, ensures
that each shell in the design satisfies the required sensitivity criterion given by the
specification for XP .The number of shells predicted by Eq. 6 or 7 is a real (that is,
fractional or non-integer) number and the actual number of shells in practice would
obviously be taken to the next largest integer.
If each match enthalpy interval i requires Ni number of shells using temperatures of
interval i in equation (6) then the maximum shells count for the interval is:
Ni (Si – 1) (7)
Notice the temperatures defining Ni are achieved by a minimum of (Si – 1) matches
where S is the total number of streams present in ith
interval.
69
The real (non-integer) number of shells target is then simply the sum of the real number
of shells from all the enthalpy intervals:
M
i
iishell SNN1
)1( (8)
where M is the total number of enthalpy, intervals on the balanced composite curves.
Furthermore, actual designs will normally observe the pinch division. Hence, Nshell
should be evaluated and taken as the next largest integer for each side of the pinch. The
number of shells target is then:
])[(])[(][ belowpinchshellabovepinchshellshell NNN (9)
Where the symbol [N] represents the next largest integer to the real number N.
Example
The Stream Data, shown through Table 1, is considered for this purpose. Here Tmin =
20˚ C.
Table 1 Stream data for a typical process
Hot utility inlet and outlet temperature are 180 ° C and 179 ° C.
Cold utility inlet and outlet temperature are 15 ° C and 25 ° C.
Calculation of P and R for an interval
Stream
Type
Supply temp. TS (˚C)
Target temp. TT (˚C)
Heat capacity flow rate MCp
(kW/ ˚C)
H1
Hot
175
45
10
H2
Hot
125
65
40
C3
Cold
20
155
20
C4
Cold
40
112
15
70
The temperature effectiveness, P, is defined as the ratio of the temperature change in one
of the streams to the maximum possible temperature difference.
Pi = (Th,i. – Th,i.-1) / (Th,i. – Tc,i.-1)
For i= 1, P1 = (65˚ - 45˚) / (65˚ - 15˚) = 0.4
R is defined as the ratio of the heat capacity flow rates of the hot streams to the cold
streams.
Ri = (Tc,i. – Tc,i.-1) / (Th,i. – Th,i.-1)
For i=1, R1 = (18.81˚ - 15˚) / (65˚ - 45˚) = 0.1905
The complete calculation is shown in Table 2.
Calculation of the temperature effectiveness of an individual 1-2 exchanger
P12 = XP Pmax where )11 2/(R P 2
max R
For i.=1 and XP = 0.9,
P12,i.=1 = 0.9 * 2 / (0.1905+1+(0.19052+1)1/2) = 0.815
Calculation of number of 1-2 shells needed in series
N = ln [(1-RP)/(1-P)]ln[(1-RP12)/(1-P12)] for R ≠ 1
And
N = [P/(1-P)]/[P12/(1-P12)] for R = 1
For i = 1,
N = ln [(1-0.1905*0.4) / ln [(1-0.1905*0.815) / (1-0.815)]
= 0.2841.
The complete calculation is shown in Table 3.
71
Table 2 Determination of P and R for non countercurrent flow
Table 3 Determination of number of Shells for each enthalpy interval
Calculation of number of shells in an interval (Ni[Si – 1])
The minimum number of shells in an enthalpy interval, i, is Ni(Si – 1).
For i. = 3, Ni(Si – 1) = 0.0237*2 = 0.0474.
The complete calculation is shown in Table 4.
Int.
i.
Col. A
Th,i
Col. B
Tc,i
Col. A
P
Col. B
R
0
1
2
3
4
5
6
7
8
9
45
65
66.25
73.5
79.5
125
149.5
175
179
180
15
18.81
20
25
40
105
112
124.75
124.75
155
0.4000
0.0263
0.1355
0.1101
0.5353
0.5506
0.4048
0.0000
0.0181
0.1905
0.9524
0.6897
2.5000
1.4286
0.2857
0.5000
0.0000
30.250
Int.
i.
Col. A
Th,i
Col. B
Tc,i
Col. A
Pi
Col. B
Ri
Col. C
P12, i
Col. D
Ni
0
1
2
3
4
5
6
7
8
9
45
65
66.25
73.5
79.5
125
149.5
175
179
180
15
18.81
20
25
40
105
112
124.75
124.75
155
0.4000
0.0263
0.1355
0.1101
0.5353
0.5506
0.4048
0.0000
0.0181
0.1905
0.9524
0.6897
2.5000
1.4286
0.2857
0.5000
0.0000
30.250
0
0.8150
0.5400
0.6197
0.2907
0.4314
0.7740
0.6875
0.0000
0.0293
0.2841
0.0237
0.1160
0.2152
1.7304
0.5081
0.3944
0.0000
0.3630
72
Table 4 Number of Shell for present problem
Calculation of estimate of shells targets
The pinch occurs at 125 ˚ C/105 ˚ C. So,
Shells below pinch = 0.2841+0.0474+0.3481+0.4305+5.1912
= 6.3013, (rounded off to 7)
Shells above pinch = 1.0163+0.3944+0.3630
= 1.7737 (rounded off to 2).
Thus total number of shells required is 9.
Cost Targeting
The cost of the network basically comprises the operating cost and capital cost.
Operating cost
The operating cost is the function of energy requirements and is given by:
OC = Chu * Qhu,min + Ccu * Qcu, min (10)
Where Chu & Ccu are the costs of minimum loads of hot and cold utility respectively and
Qhu,min and Q cu,min are the minimum requirements of hot and cold utilities respectively.
0.0237
73
Capital cost
A simple linear cost law for individual heat exchanges is
CC = a + b Ak (11)
The capital cost of a network can then be predicted on the basis of targets for the number
of units for maximum energy recovery (Umin,MER ) and minimum network area (Amin ).
Thus:
.min.minmin,
minmin
bAaUAbaUCCCC MERk
U
k
MERk
U
k
network
MERMER
(12)
Most often, the cost law for individual exchangers takes the nonlinear form as:
CCk = a + b c
kA (13)
If nonlinear cost law is used in targeting, we assume the areas of individual units are all
identical:
MER
kU
AA
,min,
min (14)
This leads to the network capital cost given by:
c
MER
networkU
AbaUCC )(
min,
min
min (15)
Total annual cost (TAC)
TAC is given by:
TAC = OC + CCnetwork * Af (16)
Where Af = (1 + r)t /t
Where Af is the annualization factor, r, is the rate of return of capital interest and t is the
expected plant life.
74
Lecture – 11
PINCH DESIGN METHODS – HEURISTIC RULES
Bikash Mohanty
Professor
Department of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee – 247 667
The pinch design method incorporates two fundamentally important features. First, it
realizes the pinch is the most temperature constrained region. The design is started at the
pinch and developed moving away. Second, it allows the designer to choose between
options.
Feasibility Criteria at the Pinch
The identification of essential matches at the pinch, of a available design options and of
the need to split streams, is achieved by applying three feasibility criteria to the stream
data at the pinch. In developing these feasibility criteria reference is made to "pinch
exchangers" (sometimes called "pinch matches").
A pinch match
75
The number of process streams and branches
The first feasibility criterion concerns the stream population at the pinch. The population
of hot and cold streams has to be such that it will allow an arrangement of exchangers
compatible with minimum utility usage.
Consider a hot end design as in Fig. 1(a). Utility cooling above the pinch would violate
the minimum utility objective. Therefore, each hot stream has to be cooled to the pinch
temperature by process exchange. This is attempted in Fig. 1(a) by placing pinch matches
between hot stream No. 2 and cold stream No. 4 and hot stream No. 3 and cold stream
No. 5. Notice, however that having made these matches hot stream No. 1 cannot be
matched with either cold stream without violating the minT constraint. Utility cooling
Exchanger 2 is not a
pinch match
Exchanger 3 is not a pinch match
76
would now be required above the pinch to cool stream No. 1 to the pinch temperature. In
such circumstances we say the original stream data at the pinch is not compatible with a
minimum utility design.
When this incompatibility occurs the streams at the pinch need "correcting" by stream
splitting (see Fig. 1(b)). By splitting a cold stream an extra cold "branch" is created,
allowing a pinch match with hot stream No. 1.
To summarize, the hot end stream population at the pinch is compatible with a minimum
utility design only if a pinch match can be found for each hot stream. For this to occur
inequality (1a) must apply
NH NC (1a)
Where NH is the number of hot streams or branches and NC is the number of cold
streams or branches. Stream splitting may be needed to ensure that the inequality is
fulfilled.
Fig. 1. (a) An infeasible hot end design at the pinch. (b) Stream splitting at the pinch
77
The converse arguments apply below the pinch. To avoid utility heating each cold stream
must be brought to the pinch temperature by process exchange. As a result, a pinch
match is required for each cold stream at the pinch and this is possible only if inequality
(1b) holds
NH NC (1b)
Once again stream splitting may be necessary to ensure that the inequality is fulfilled.
The CP inequality for individual matches
The second feasibility criterion is concerned with temperature feasibility. As shown in
Fig. 2, temperature driving force in a pinch match cannot decrease away from the pinch.
For this condition to be fulfilled the following CP inequalities must apply in every pinch
match
Hot end pinch match
CPH CPC (2a)
Cold end pinch match
CPH CPC (2b)
Where CPH is the heat capacity flowrate of a hot stream or stream branch and CPC is the
heat capacity flowrate of a cold stream or stream branch.
If an arrangement of matches fulfilling these inequalities is not possible then it is
necessary to change one or more CPs by stream splitting.
It should be noted that inequalities (2a) and (2b) only apply at the pinch. Away from the
pinch, temperature driving forces may have increased sufficiently to allow matches in
which the CP's of the streams matched violate the inequalities.
78
The CP difference
To understand the third feasibility criterion at the pinch it is convenient to define the "CP
difference". It can be understood by Fig. 3a, 3b and 3c.
For a hot end pinch match
CP difference = CPC-CPH (3a)
For a cold end pinch match
CP difference = CPH - CPC (3b)
Similar equations can be written for differences in the overall sum of hot stream CPs and
cold stream CPs at the pinch.
Immediately above the pinch
Overall CP difference = NHNC
CPHCPC11
(4a)
Fig. 2 (a) A feasible pinch exchanger above the pinch (b) A feasible pinch exchanger
below the pinch
79
Immediately below the pinch
Overall CP difference = NCNH
CPCCPH11
(4b)
Fig. 3a The sum of the match CP
differences equals the overall
difference. All stream at the
pinch are involved in pinch
exchangers.
Fig. 3b The sum of the match CP differences
amount to less than the total. In this
case not all streams at the pinch are
involved in pinch match.
Fig. 3c The sum of the match CP differences
exceeds the total. The pinch match
shown is feasible by itself as it fulfills
CP inequality criterion but it is
incompatible with overall CP
difference. (the pinch match has a CP
difference of 6 whereas the total
available is only 4.) Thus, it is not
possible to complete this design.
80
Lecture – 12 & 13
DESIGN OF HEN FOR MAXIMUM ENERGY RECOVERY, LOOP
BREAKING & PATH RELAXATION
Bikash Mohanty
Professor
Department of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee – 247 667
Design of HEN for Maximum Energy Recovery
The pinch represents the most constrained region of a design; after all, Tmin exists
between all hot and cold streams at the pinch. As a result the number of feasible matches
in this region is severely restricted. Quite often there is a crucial or "essential" match. If
this match is not made, this will result in heat transfer across the pinch and thus in
increased hot and cold utility usage. The pinch design method, therefore
* recognizes the pinch division
* starts the design at the pinch developing it separately into two remaining problems.
This approach is completely different from the normal intuitive approach of starting the
design at the hot side and developing it towards the cold. When a design is started at the
hot side, initial design decisions may later necessitate follow-up decisions which violate
the pinch. On the other hand, when a design is started at the pinch, initial design
decisions are made in the most constrained part of the problem and are less likely to lead
to difficulties later.
Thus, commencing a design at the pinch has the distinct advantage of allowing the
designer to identify essential matches or topology options in the most constrained region
of the design, which are in keeping with minimum utility usage or maximum energy
81
recovery (MER).
Basic element for Design of HEN
The CP table
Fig. 1(a) and 1(b) show a step-by-step procedure for applying the feasibility criteria such
as: number of process streams & branches, CP inequality for individual matches and CP
difference. By following the sequence, the designer can
* identify essential matches at the pinch.
* identify available match options at the pinch.
* identify the need to split streams and generate stream splitting options at the pinch.
The procedure is aided by the use of another new concept, the "CP table". CP tables for
the hot and cold ends of a typical problem are shown in Figs. 2 and 3 respectively. In
these tables hot and cold stream CPs at the pinch are separately listed in numerical order.
The appropriate feasibility criteria are noted at the top of the table and the CPs
representing streams, which have to be involved in process exchange at the pinch, are
boxed for emphasis. A pinch match is represented in the table by pairing the CPs of a hot
and a cold stream. Stream splits are represented by writing the separate branch flowrate
CPs adjacent to the original CP (see Fig. 3(C)). The step by step procedure from Fig. 1 is
easily followed in the CP table.
82
Fig. 2. (a) The CP table for a typical problem hot end. (b) & (c) Feasible pinch matches
identified in the CP table
Fig. 1. (a) Hot end pinch design procedure. (b) Cold end pinch design procedure.
83
The "tick-off" heuristic
Once a pinch topology has been chosen, the design of both hot and cold ends must be
continued in such a manner as to keep capital costs at a minimum, i.e. the final designs
ought to be steered towards the minimum number of units. This can be achieved by
employing a "tick-off" heuristic to identify the heat loads on the pinch exchangers.
The targeting equation for the minimum number of units is satisfied if every match brings
one stream to its target temperature or exhausts a utility. In this case, the match is said to
"tick-off" the stream or utility, i.e. the stream or utility need no longer be considered part
of the remaining design task.
The pinch exchangers can usually be made to tick-off streams by choosing each
Fig. 3(a) The CP table for a
typical process cold end.
(b) Infeasible pinch
topologies.
(c) Feasible pinch topology
with two stream splits.
(d) Feasible pinch topology
with one stream split
84
exchanger load to equal the smaller heat load of the two streams matched. The CP
inequalities will guarantee the possibility of choosing pinch exchanger loads by ticking-
off streams as long as the stream CP remains constant with varying temperature and as
long as cold and hot stream temperature overlaps do not require an excessive number of
shells for a single pinch match.
The tick-off heuristic is a "heuristic" as it can occasionally penalize the design by
introducing the need for increased utility usage. Temperature driving force, essential
elsewhere, may be used up excessively in pinch exchangers that are extended too far into
the remaining problem. In such cases the designer can choose either to
* reduce the load on the offending pinch match and run the risk of needing more than
the minimum number of units.
* use another pinch topology in which the tick-off heuristic does not cause essential
driving force to be used up.
Design method summary
The pinch design method incorporates five important stages. These are:
1. The HEN problem is divided at the pinch into separate problems.
2. The design for these separate problems is started at the pinch and developed
moving away from the pinch. At the pinch essential matches, match options and stream
splitting requirements are identified by applying the feasibility criteria.
3. When options exist at the pinch, the engineer is free to base his selection to suit
the process requirements.
4. The heat loads of exchangers at the pinch are determined using the stream "tick-
off" heuristic. In case of difficulty (increased utility usage) a different exchanger
85
topology at the pinch can be chosen or the load on the offending match can be reduced.
5. Away from the pinch there is generally a "free choice" of matches. The procedure
does not insist on particular matches but allows the designer to discriminate between
matches based on his judgment and process knowledge.
Example
The stream data is shown below. For this problem Tmin = 10 °C and the hot and cold
utility requirements are 7.5 MW and 10 MW. Hot and cold pinch temperatures are 150
and 140 °C, respectively. Number of units required, including heaters and coolers, are 7
(4 above the pinch and 3 below the pinch). The grid representation of this data is shown
in Fig. 4.
Stream Type TS (°C) TT (°C) H (MW) CP (MW °C-1
)
1 Cold 20 180 32 0.2
2 Hot 250 40 - 31.5 0.15
3 Cold 140 230 27 0.3
4 Hot 200 80 - 30 0.25
Fig. 4 The grid diagram
86
Design above the pinch
Fig. 5a shows the grid diagram with CP-table for design above the pinch. Cold utility
must not be used above the pinch, which means that hot streams must be cooled to pinch
temperature by heat recovery. Hot utility can be used, if necessary, on the cold streams
above the pinch. Thus, it is essential to match hot streams above the pinch with a cold
partner. In addition, if the hot stream is at pinch conditions, the cold stream it is to be
matched with must also be at pinch conditions, otherwise the Tmin constraint will be
violated. Fig. 5a shows a feasible design arrangement above the pinch that does not use
temperature differences smaller than Tmin. Note again that the CP inequality only
applies when a match is made between two streams that are both at the pinch. Away from
the pinch, temperature differences increase, and it is no longer essential to obey the CP
inequalities.
Fig. 5 The CP table for the designs above and below the pinch
NHNC
NHNC
(a) (b)
87
Design below the pinch
Fig. 5b shows the grid diagram with CP-table for the design below the pinch. Hot utility
must not be used below the pinch, which means that cold streams must be heated to pinch
temperature by heat recovery. Cold utility can be used, if necessary, on the hot streams
below the pinch. Thus, it is essential to match cold streams below the pinch with a hot
partner. In addition, if the cold stream is at pinch conditions, the hot stream it is to be
matched with must also be at pinch conditions, otherwise the Tmin constraint will be
violated. Fig. 5b shows a design arrangement below the pinch that does not use
temperature differences smaller than Tmin.
Sizing the units above the pinch using the tick-off heuristic
Once the matches around the pinch have been chosen to satisfy the criteria for minimum
energy, the design should be continued in such a manner as to keep capital costs to a
minimum. One important criterion in the capital cost is the number of units (there are
others, of course, which shall be addressed later). Keeping the number of units to a
minimum can be achieved using the tick-off heuristic. To tick off a stream, individual
units are made as large as possible, that is, the smaller of the two heat duties on the
streams being matched.
Fig. 6a shows the matches around the pinch from Fig. 5a with their duties maximized to
tick off streams. It should be emphasized that the tick-off heuristic is only a heuristic and
can occasionally penalize the design. Methods will be developed later, which allow such
penalties to be identified as the design proceeds.
The design in Fig. 6a can now be completed by satisfying the heating and cooling duties
away from the pinch. Cooling water must not be used above the pinch. Therefore, if there
88
are hot streams above the pinch for which the pinch matches do not satisfy the duties,
additional process-to-process heat recovery is required. Fig. 6b shows an additional
match to satisfy the residual cooling of the hot streams above the pinch. Again, the duty
on the unit is maximized. Finally, above the pinch, the residual heating duty on the cold
streams must be satisfied. Since there are no hot streams left above the pinch, hot utility
must be used as shown in Fig. 6c.
Similarly sizing of units below the pinch can be done as shown in Fig. 7.
Fig. 6 Sizing of units above the pinch
Fig. 7 Sizing of units below the pinch
The complete HEN design for MER
The final design shown in Fig. 8 amalgamates the hot end design from Fig. 6c and cold
end design from Fig. 7c. The duty on hot utility of 7.5 MW agrees with QHmin and the
duty on cold utility of 10.0 MW agrees with QCmin predicted by the composite curves and
the problem table algorithm.
89
Note one further point from Fig. 8 that the number of units is 7 in total (including the
heater and cooler) which is equal to the targeted value. It therefore appears that there was
something in the procedure that naturally steered the design to achieve the target for the
minimum number of units.
Fig. 8 The completed design for the stream data undertaken
Design of HEN with Stream Splitting
The pinch design method developed earlier followed several rules and guidelines to allow
design for minimum utility (or maximum energy recovery) in the minimum number of
units. Occasionally, it appears not to be possible to create the appropriate matches
because one or other of the design criteria cannot be satisfied. In such cases stream
splitting is done. The algorithm of stream splitting is shown in Fig. 9.
90
Fig. 9 Stream splitting algorithm
Example
The grid representation for a high temperature process is shown in Fig. 10a where
Tmin=20 C. The process requires 9.2 MW of hot utility, 6.4 MW of cold utility and the
pinch is located at 520 C for hot streams and 500 C for cold streams.
Stream data
at pinch
NH NC ? CpH CpC for
pinch match
Split cold
stream
Split hot
stream
Place
match
Yes Yes
No
No
Stream data at
pinch
NH NC ? CpH CpC for
pinch match
Split hot
stream
Split cold
stream
Place
match
Yes Yes
No
No
(a) Stream splitting above pinch
(b) Stream splitting below pinch
91
Fig. 10b shows the CP tables for the above- and below-pinch designs. Following the
algorithms in Fig. 9, a hot stream must be split above the pinch to satisfy the CP
inequality, as shown in Fig. 10b.
The grid diagram
The splitting of hot stream
92
Fig. 10 Maximum energy recovery design with stream splitting
Identification of Loops & Paths and Loop Breaking and Path Relaxation
There will generally be scope to simplify minimum utility designs by a controlled
reduction in the number of units. By transferring heat across the pinch and therefore
increasing the utility usage the number of capital items can be reduced. There is a trade-
off between units (capital cost) and the utility usage (energy cost).
In order to explore the scope for a controlled reduction in the number of units it is
important to understand the concepts of heat load loops and heat load paths.
Heat Load Loops
A loop is a set of connections that can be traced through a network (via streams and
units) that starts at one exchanger and returns to the same exchanger.
Whenever a design features more than the target minimum number of units for the whole
problem, ignoring the pinch, it is due to the existence of heat load loops. There will be
one loop for each extra unit. As an example, the minimum utility design for a typical
93
problem has two more units than the definite minimum according to Fig. 11. Hence there
must be two loops in the design. Figs. 12(a) and (b) show these loops.
An important feature of every loop is that heat loads can be shifted around the loop from
one unit to another. The load is subtracted from the next and so on around the loop. This
load shift always maintains the correct stream heat loads but the exchanger duties are
changed and may cause a violation of Tmin. However, driving forces can be "restored"
using heat load paths.
(b)
Fig 11. (a) The number of units for
maximum energy recovery.
(b) The overall minimum number of
units.
94
Heat Load Paths
A path is a continuous connection in the grid between a heater, heat exchangers and a
cooler. Fig. 14 shows the simplest form of a path.
Load shifts along paths follow equivalent rules to load shifts around a loop. Load is
added to a heater, subtracted from an exchanger, added to the next exchanger in the path,
subtracted from the next, and so on along the path until it is finally added to a cooler.
Stream enthalpy balance is maintained but exchanger loads and operating temperatures
are changed. This last feature means that a path can be used to restore driving forces.
Loop Breaking and Path Relaxation
We will now illustrate the use of heat load loops and paths to reduce the number of units
of the design in Fig. 12a from seven to six.
Fig. 12 (a,b) A minimum utility design for
a typical problem showing the
two heat load loops
95
It is apparent that load shifts around loops can form the basic mechanism for the
reduction in the number of units. When the load shift around a loop leads to a reduction
in the heat load of a unit, which equals the load on that unit, then the unit is removed
from the design and the number of units is reduced by one.
Consider Fig. 12(a), which shows a minimum utility design with seven units. A good
choice of exchanger to remove is exchanger No. 4 as it has the smallest load and forms
part of the simplest loop. Fig. 13 shows the topology and temperatures after the load of
match No. 4 has been transferred to exchanger No. 1. The heat loads of all other units in
the design are unchanged as they were not part of the original loop. There is now a small
violation in Tmin as reflected by the difference in temperatures T1 and T2.
However, Tmin can be restored using the heat load path shown in Fig. 14. It is apparent
that T1 is fixed at 62C. It is therefore T2 which must be changed to restore Tmin.
Requiring T2 to equal 82C, the heat load of individual units can now be changed while
the stream heat loads are maintained by using the path through exchanger No. 1. It is a
trivial task to calculate the hot and cold utility increase x required. This load is 4 kW. In
other words, by supplying a further 4 kW of utility heating and cooling and by reducing
the heat load on exchanger No. 1 by 4 kW, the solution is brought back in line with the
Tmin.
Fig. 13 A six unit topology that is a result of
breaking Loop 1 (Fig. 12a).
96
The summary of this section is as follows
There is generally scope to reduce the number of units in a pinched problem
starting from a minimum utility design.
This reduction in the number of units can be achieved in a controlled manner. By
this we mean that the utility penalty incurred in reducing the number of units is
minimized.
Not all units exist in a suitable loop or along a suitable path. Thus, the procedure
would not be applicable to the "removal" of such units.
Fig. 14 Identifying a path
97
Lecturer - 14
DRIVING FORCE PLOT AND REMAINING PROBLEM ANALYSIS
Bikash Mohanty
Professor
Department of Chemical Engineering
Indian Institute of Technology Roorkee, Roorkee – 247 667
The Driving Force Plot
Fig. 1 shows two networks having the same CP-ratios for the pinch match. However,
network 2A comes to within 16% of the above pinch area target, while network 2B
requires 108% more area than target. Why is there such a large discrepancy? Examining
the Composite Curves, we suspect network 2B makes poor use of driving forces away
from the pinch. To take this further the concept of “Driving Force Plot” is used.
Fig. 1 Both networks have
identical CP-ratios for
pinch matches. There is,
however, significant
difference in network
areas
98
The area target is based on the vertical temperature differences along the whole balanced
composite curves. Ideally, we need to measure the temperature differences of individual
matches against the vertical driving forces available on the composites. A simple way of
expressing this is firstly to draw the vertical temperature difference T between the
composites as it changes with the temperature of say the cold composite Tcold (Fig. 2).
Equivalently, T=f(Thot) or Thot=f(Tcold) may also be used. The diagram is called the
"Driving force Plot" (Fig. 2).
Fig. 2 Construction of Driving Force Plot
Next, individual matches are shown in these coordinates (Fig. 3). Matches displaying
vertical heat transfer on the composites fit the Driving force Plot exactly, such as the
match shown in Fig. 3. Matches which are not vertical (or which criss-cross) on the
composites show a blatant misfit (Fig. 4, 5). Matches using excessive temperature
differences have less area than if they had been vertical, but cause other (subsequently
placed) matches to have smaller temperature differences. The net result overall is
increased heat exchange area for the network.
99
Fig. 3 The match with “vertical heat transfer”
Fig. 4 The match with “excessive driving force”
Fig. 5 The match under-utilizing driving force
The Driving Force Plot provides a rapid and easy way to use guideline for designing
networks, which are close to minimum area. However, it is only a guideline and does not
provide quantitative information.
100
Networks 2A and 2B are displayed against their Driving Force Plot in Fig. 6. The pinch
matches placed according to the CP-rules follow well the slope of the Driving Force Plot
near the pinch. Away from the pinch, however, network 2B shows a poorer overall fit to
the plot. Its pinch matches are too large to duty and under-utilize driving forces away
from the pinch. These duties were established using the “tick-off’ heuristic for obtaining
minimum number of units in the design.
Fig. 6 Networks 2A & 2B compared on the Driving Force Plot. Network 2B shows a
much poorer overall fit to the plot than network 2A.
The plot shows the tick-off heuristic is inappropriate here for achieving low network area.
Violation of the tick-off rule usually means additional units above target, as in network
2A. The significantly improved area performance in this example gives lower overall
capital cost. Designs achieving a good fit to the Driving Force Plot in minimum number
101
of units or within 10% of this (to the nearest integer number of units) are usually within
10% of the area target.
Remaining Problem Analysis
Suppose a design obtains a good fit to the Driving Force Plot but the final network area is
appreciably above target. Such an occurrence is infrequent considering the plot steers
design towards vertical heat transfer and minimum area. Fig. 7, however, demonstrates
the plot may not always be sufficient for minimum area. Networks 3A and 3B appear
remarkably similar in use of driving forces, but 3B has an area 22% in excess of the
above-pinch target whereas 3A is only 10% above this target.
Fig. 7 Both networks show very similar fit to the Driving Force Plot but differ appreciably
in area
102
The Driving Force Plot works in temperatures only, neglecting the effect of duty on heat
exchanger area. It is possible for matches to appear identical in Driving Force
coordinates, yet have very different duties. Generally, good utilization of driving forces
for matches of large duty is required in regions of small temperature difference.
When a match is placed, the duty needs to be chosen with some quantitative assessment
of the match in the context of the whole network, without having to complete the
network. This can be done by exploiting the powers of targeting using a technique known
as Remaining Problem Analysis.
Consider the design for minimum energy in a more complex problem. If a problem table
analysis (PTA) is performed on the stream data, QHmin and QCmin can be calculated. When
the network is designed and a match is placed, it would be useful to assess whether there
will be any energy penalty caused by some feature of the match without having to
complete the design. This penalty can be determined by performing a PTA on the
remaining problem.
The PTA is simply repeated on the stream data, leaving out those parts of the hot and
cold stream satisfied by the match. One of the two results would then occur:
1. The algorithm may calculate QHmin and QCmin to be unchanged. In this case, the
designer knows that the match will not penalize the design in terms of increased
utility usage.
2. The algorithm may calculate an increase in QHmin and QCmin. This means that the
match is transferring heat across the pinch or that there is some feature of the
design that will cause cross-pinch heat transfer if the design was completed. If the
103
match is not transferring heat across the pinch directly, then the increase in utility
will result from the match being too big as a result of the tick-off heuristic.
The remaining problem analysis (RPA) technique can be applied to any feature of the
network that can be targeted, such as a minimum area.
RPA can be used to approach the area target, as closely as a practical design permits,
using a minimum (or near minimum) number of units. Suppose a match is placed, then its
area requirement can be calculated. A RPA can be carried out by calculating the area
satisfied by the match. The area of the match is now added to the area target for the
remaining problem. Subtraction of original area target for the whole-stream data gives the
area penalty incurred.
Targets for number of shells, capital cost and total cost also can be set. Thus, RPA can be
used on these design parameters also.
The “Remaining Problem Analysis” is explained in Fig. 8. Suppose the minimum total
area possible for a design completed after accepting a match M is Atotal. M. This is the sum
of the match area aM and the area target for the remaining stream data Ar, M. Subtraction
of the original area target for the whole stream data Amin gives the minimum area penalty
incurred.
The analysis can quantify both surplus and deficit use of driving forces. A large T
match incurs area penalty from the small T caused in the remaining problem. A small
T match incurs area penalty from the match itself.
104
Fig. 8 Remaining Problem Analysis for area
Fig. 9 the Remaining Problem Analysis for match 4 in network 38 shows significant
penalty in area for the network.
105
The Remaining Problem Analyses for networks 3A and 3B are shown in Fig. 9. It is now
clear that match 4 in network 3B is not as good as the rest. Surprisingly, it looks similar
on the Driving Force Plot (Fig. 7) to matches 4 and 5 in network 3A, which return much
lower area penalties. The Remaining Problem Analysis improves on the Driving Force
Plot. At present, it is the only known method for quantifying approach to the targets
during design development.
The Remaining Problem Analysis discussed so far treats each match in isolation of the
others when several matches exist at any stage of design (as in Fig. 9). In other words, the
remaining problem is defined as the full stream data excluding only the hot and cold
stream sections of the match being analyzed.
106
REFERENCES
1. Linnhoff, B.; Dunford; H.; and Smit, R.; “Heat Integration of Distillation Columns
into Overall Process”; Chem. Engg. Science; Vol.38; No.8; pp-1175-1189, (1983).
2. Robin Smith, “Chemical Process Design”, McGraw Hill, 1995.
3. Linnhoff B, Townsend D W, Boland D, Hewitt G F, Thomas B E A, Guy A R &
Marsland R H, “User guide on process integration for the efficient use of energy”,
(The Institution of Chemical Engineers, Rugby, U.K.; available in the U.S. through
Pergamon Press, Inc. Elmsord, N.Y.), 1982.
4. Ahmad S and R .Smith, “Targets and design for minimum number of shell in heat
exchangers networks”, Chem. Eng. Res. Des., Vol. 67, Sep 1989, pp 481-494.
5. Linnhoff B. and S. Ahmad, “Cost optimal heat exchanger networks I Minimum
energy and capital cost using simple models for capital cost , Comp Chem Engg.,
Vol. 14, No. 7 1990, pp 729-767.
6. Linnhoff B. and E. Hindmarsh, “The pinch design methods for heat exchanger
networks”, Chem Engg. Sci, Vol. 38, No. 5 1983, pp 745-763.
7. Linnhoff B., “Pinch Analysis-A state-of-the- art overview”, Trans IchemE, Vol. 71,
Part A, Sep 1993, pp 503-522.
8. Linnhoff B. and J. R. Flower, “Synthesis of heat exchanger networks”, AIChE J,
Vol. 24, July 1978, pp 633-642.
9. Smith G. and A. Patel, “Step by step through pinch”, The Chem. Eng., Nov 1987,
pp 26-31.
10. Linnhoff B. and D. R. Vredeveld, “Pinch Technology has come of age”, CEP, July
1984, pp 33-39.
11. Uday V. Shenoy, “Heat Exchange Network Synthesis”, Gulf Publishing Company,
1995.
107