thesis roger nordman kappa

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THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

New process integration methods forheat-saving retrofit projects

in industrial systems

ROGER NORDMAN

Heat and Power Technology

Department of Energy and Environment

CHALMERS UNIVERSITY OF TECHNOLOGY

Gteborg, Sweden 2005


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New process integration methods for heat-saving retrofit projects in industrial systems

ROGER NORDMAN

Gteborg, 2005

ISBN 91-7291-663-X

Roger Nordman, 2005

Doktorsavhandling vid Chalmers tekniska hgskola, Gteborg

Ny serie nr 2345

ISSN 0346-718X



Chalmers University of Technology

SE-412 96 Gteborg

Sweden

Telephone: + 46 (0)31 772 1000

ISRN CTH-VOM-PB--10/05-SE

ISSN 1404-7098

Printed by Chalmers Reproservice

Gteborg, Sweden, 2005

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New process integration methods for heat-saving retrofit projects in industrial systems

ROGER NORDMAN



Chalmers University of Technology

ABSTRACT

ew graphical methods have been developed for HEN retrofit (improvement of existing

tools), release of usable excess heat, and placement of supply tanks in HWWS systems.

In addition, the matrix method for HEN retrofit has been developed further. The methods

have been used in case studies, both as stand-alone tools and in different combinations.

N

Using the advanced composite curves together with the matrix method in HEN retrofit gives

new insights into which units should be chosen for retrofit, and how far the heat recoveryshould proceed. The extra information that must be collected to show the placement of

existing heaters and coolers gives valuable inputs to this method. Calculations have shown

that heaters and coolers placed close to the pinch are often cheaper by a factor of two or more

to retrofit.

A method to show the potential for releasing usable excess heat at high temperature levels

(but still below the pinch) has been developed. This method is based on the full set of stream

data from the process, and therefore shows the total potential. Case studies demonstrate that

much of the potential can also be released by making changes in the HEN with acceptableinvestments and PBPs.

Another method, to be used in HWWS systems for different setups of tanks and different

values ofTmin, has also been developed. It shows the potential usable excess heat versustemperature in this subsystem for a user-defined number of supply tanks and Tmin.By studying this subsystem, a large amount of the total potential can be exploited. This leaves

the remaining process without any changes at all.

A new optimisation routine has been developed and implemented into the matrix method.This method uses a recursive branch and bound algorithm to explore all relevant paths in the

retrofit task. A first solution is made and taken as an upper bound to the problem. All

following paths that exceed this bound are directly eliminated. The implementation has

proven to be reliable and fast to use, although there are still improvements to be made.

Keywords: Heat Exchanger Network, Method Development, Process Integration, Pulp &

Paper.

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Errata

Paper IV: A misprint on page 194, right row, third paragraph:

Reads: The THLC shows the lowest possible temperatures where heat would be supplied if

all thermodynamic possible measures for energy conservation had been usedShould read: The THLC shows the lowest possible temperatures where heat would be

supplied if all possible thermodynamic measures for heat exchange had been used

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To Gran, my dear brother.

Very little is needed to make a happy life.

Marcus Aurelius Antoninus (121 AD - 180 AD)

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List of appended papers

The thesis is based on the following papers, referred to by Roman numerals in the text.

I. New Pinch Technology Based HEN Analysis Methodologies for Cost-Effective

Retrofitting, Nordman, R , Berntsson, T. Canadian Journal of Chemical Engineering,

Vol. 79, No. 4, 2002, pp. 655-662.

II. Utilization of excess heat in the pulp and paper industry A case study of technical and

economic opportunities, Bengtsson, C., Nordman, R., Berntsson, T.Applied Thermal

Engineering, Vol. 22, No. 9, 2002, pp. 1069-1081.

III. Design of kraft pulp mill hot and warm water systems A new method that maximizes

excess heat, Nordman, R., Berntsson, T.Accepted for publication inApplied Thermal

Engineering.IV. Advanced pinch technology based composite curves for evaluating the usable excess

heat potential, Nordman R., Berntsson, T.In Proceedings of the 18th International

Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of

Energy System, Trondheim, Norway, 2005. Vol. 1, 2005, pp. 193-200.

V. Use of advanced composite curves for assessing cost effective HEN retrofit. I. Theory

and concepts, Nordman, R., Berntsson, T. Manuscript.

VI. Use of advanced composite curves for assessing cost effective HEN retrofit. II. Case

studies, Nordman, R., Berntsson, T., Manuscript.

Roger Nordman is the main author ofPapersI, III, IV, V and VI. PaperII is a joint effort

by Nordman, Berntsson and Cecilia Bengtsson. Bengtsson contributed to the paper with the

thermodynamic and economic opportunities for pre-evaporation of effluents and heat

pumping, while Nordman investigated the design constructions, constructed and analysed the

advanced curves. The planning, results analysis and conclusions of Paper II were a joint

effort between the two authors mentioned. Concepts and ideas, regarding the usable excess

heat potential, from the cooperation with Bengtsson in Paper II were pursued in Paper IV.

Professor Thore Berntsson supervised the work in all papers.

Related publ ications not included in this thesis

Process Integration Opportunities in Future Kraft Pulp Mills, Berntsson, T., Algehed, J.,

Bengtsson, C., Nordman, R., Wising, U., 2ndInternational Symposium on Process

Integration, Halifax, October 14-17, 2001.

Solving Large Scale Retrofit Heat Exchanger Network Synthesis Problems With Math-

ematical Optimization Methods, Bjrk, K-M., Nordman, R., Chemical Engineering and

Processing Vol. 44, No. 8 , pp. 869-876, 2005.

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Contents

Contents

1 Background 1

1.1 Introduction 1

1.2 Aims 2

1.3 Thesis outline 2

2 Related work 5

2.1 The field of Process Integration, past and present 5

2.2 HEN Synthesis 6

2.2.1 Grass-root HEN Design 6

2.2.1.1 Pinch Design Method 7

2.2.1.2 Mathematical Programming 9

2.2.1.3 Other Methods 12

2.2.2 RetrofitDesign 12

2.2.2.1 Pinch Design Method 12

2.2.2.2 Mathematical Programming 143 Technical and economic conditions 17

3.1 Technical and economic conditions 17

3.2 Scenarios 20

4 Advanced composite curves for retrofit 23

4.1 Background 23

4.2 Construction of the advanced curves 23

4.3 Heat exchanger network retrofit 29

4.4 Identifying the usable excess heat potential 34

4.5 Multiple utility levels 34

4.6 Heat pump integration 35

4.7 Combined heat and power integration 36

5 The matrix method 37

5.1 Original method by Carlsson 37

5.2 Further development 43

5.2.1 Basic observations 43

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5.2.2 New optimisation method 45

6 Tank curves 49

6.1 The P&P Mill 49

6.2 Method description 51

6.3 Optimum tank levels or demand levels? 53

6.4 Alternative use of Qxs 53

7 Results 55

7.1 General results 55

7.2 Results from case studies 55

8 Conclusions 63

9 Suggestions for further work 65

10 Nomenclature and abbreviations 67

References 69

Acknowledgements 77

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Background

1 Background

In science one tries to tell people, in such a way as to be understood by everyone, somethingthat no one ever knew before. But in poetry, it's the exact opposite.

[Paul Dirac (1902 - 1984)]1.1 Introduct ion

n a global context, it is essential to reduce the fossil-based energy consumption in order to

decrease the environmental impact of human activities. Industrys share of the total

energy consumption is very large, and thus reduction of energy use is highly motivated in this

sector.

I

The two problems of diminishing supplies of fossil fuels and increased CO2 levels motivate

research and development towards a sustainable energy system with less use of fossil fuels.To decrease this use, two main paths must be pursued:

Development and introduction of new energy production techniques, not relying onfossil fuels.

Energy conservation (intensification) measures to use fuels more effectively.

A number of different options are possible to reduce industrial energy use. Proposed measures

include e.g. heat pumping, combined heat and power generation, fuel switching, more

efficient unit operations, and increased heat recovery by heat exchange.

Saving energy in the industry could also result in exporting biomass from industry to the

surrounding society for use in municipal heating and power generation, thus potentially

saving more fossil fuel. For example, the potential export of biomass from the pulp and paper

industry could result in a fossil fuel decrease corresponding to about 10% of Swedens total

CO2 emissions.

This thesis contributes through method development in two specific energy recovery options:

increased heat recovery by increased heat exchange, and release of usable excess heat for use

by other processes. The options are treated in two ways:1. Identifying cost-effective projects for retrofitting of heat exchanger networks.

2. Treating cooling demands as excess heat that could be used by other process parts

if the cooling demand were present at a high enough temperature.

These methods could be used stand-alone, or be integrated as a part of larger energy system

analysis frameworks, for example the one proposed by dahl[1].

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1.2 Aims

any different methods for energy systems analysis are available. A literature review

of the subject of process integration is presented in Section 2. For heat exchanger

network (HEN) design, most of these methods originate from so-called grass-root design. Ingrass-root design all relevant stream data are known from process flow sheets, and a heat

recovery network can be designed without any plant layout considerations.

M

It is, however, not very often that new plants are built; instead, retrofitting of existing

processes is carried out. When this is done, already installed equipment must be taken into

consideration, and the topology (geographical location of equipment) plays an important role.

The extreme case would be to remove all existing equipment and build a new grass-root

optimised process from the beginning. But this would result in enormous capital waste, since

the existing equipment represents sunken costs. The challenge is therefore to make as good anoptimisation as possible with due regard to the existing equipment.

The aims of this thesis work are:

1. To further develop a graphical method in order to use it for HEN retrofitting. This

method should:

i. take the existing HEN and thereby existing plant layout into account;

ii. provide a basis for decision-making as to how far heat recovery can be

pursued in a cost-effective manner.

2. To develop a method that can:i. give insights on how to determine the amount of excess heat that can be

released by a process (the definition of excess heat as it will be used

throughout this thesis is found in section 4);

ii. suggest how the existing HEN should be retrofitted in order to release

the amount of excess heat thus quantified.

3. To develop a method for evaluating the optimum number of tanks and their

temperature levels when excess heat is released from a hot and warm water

system. This method is intended especially for the pulp and paper industry, butapplies generally to industries with hot and warm water systems.

1.3 Thesis outlinehis thesis is based on the six appended papers listed on page ix. Below, a short summary

of these papers is presented.TIn Paper I a set of advanced composite curves was used to evaluate the potential for cost-effective retrofitting of HENs. Two new curves were developed in addition to the existing

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Background

ones, one above and one below the pinch, called the EHLC and the ECLC. The new set of

curves gives upper and lower bounds on the temperatures at which utility heat should be

provided, with the actual utility consumption in the plant. Case studies representing these

upper and lower bounds were analysed in detail by using the matrix method for different heat

recovery levels. Results showed that the case representing the lower bound was much cheaperto retrofit; this was also predicted by the advanced curves. Much fewer units were also

affected in the case representing the lower bound.

Motivated by the results from Paper I, an industrial case study was performed in cooperation

with Cecilia Bengtsson in Paper II. The industry studied was the StoraEnso Skoghall pulp &

board mill. In this part of the project Bengtsson studied overall effects of a variety of energy

retrofit projects, including an evaporation philosophy developed by Algehed [2], named non-

conventional evaporation and later also referred to as process-integrated evaporation. In

this paper, the heat recovery potential by increased heat exchange was studied, but also the

ability to release usable excess heat to be used in the process-integrated evaporation. A

problem that arose in this work was the fact that water is used not only as process raw

material, but also at the same time as cold utility. This caused problems in constructing two of

the advanced curves, the CUC and the ACLC, and these curves were constructed with the

assumption that existing coolers placed high should be fully released, rather than parts of

streams. The problem of how to separate the water into cold utility and process raw material

was later systematized in Paper III. Results from Paper II, however, showed that by

retrofitting the HEN, excess heat could be released for use in an MVR heat pump or for

process-integrated evaporation. A total potential of 7.5 MW heat above 98C was identified

by the advanced curves. By using the matrix method combined with the advanced curves, itwas shown that 4.5 MW could be released with PBPs that are acceptable with the StoraEnso

group investment policy.

Paper III treated the problems encountered in Paper II by a systematic approach. In this

paper a new method for hot and warm water production system (secondary heat system)

design in kraft pulp mills is presented. In the new method, data from the hot and warm water

system is extracted and minimum process water demands are determined. A new composite

curve called the tank curve was introduced. Using this curve, the maximum theoretical

usable excess heat from the hot and warm water system could be determined for a number of

hot and warm water tanks, which is also an optimisation variable in the method. In a casestudy presented in this paper it was shown that 5 to 6 MW excess heat would be possible to

release from this system above 90C. HEN retrofit designs that would accomplish these heat

savings in a cost-efficient way were also proposed. An earlier study by Bengtsson [3]

indicated an excess heat potential of about 7.5 MW heat above 98C when the whole mill was

studied. The sub-optimisation revealed a large portion of the total potential in a limited part of

the whole plant in this case. Further developments of the new method are presented to

generalize it to include all parts of a plant, thus avoiding any sub-optimisation.

In Paper IV a methodology, based on the advanced composite curves, to evaluate the usable

excess heat potential in a process is presented. It was shown that part of the excess heat

potential could be released at utility temperature levels.

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Paper V and Paper VI return to the HEN retrofit issue ofPaper I. In Paper V heaters and

coolers placement in the existing network is discussed from a perspective of cost-efficiency

of retrofit. A detailed explanation of which factors contribute to the retrofit cost is provided.

Especially shifting of heat temperature-wise and its implications for the need for new and/or

extended heat exchangers is discussed. Factors requiring special attention, e.g. availablepressure drop and piping, are also treated.

Finally, Paper VI presents the results from two case studies where the advanced curves were

used to evaluate potential HEN retrofit projects and the matrix method was used in the retrofit

design stage. The first case consists of four different HEN designs for the same set of stream

data, two extreme designs and two realistic designs. It was shown that the investment cost

was more than doubled if a network with heaters placed high and coolers placed low was

retrofitted, compared to a network with heaters placed low and coolers high, although both

networks have the same utility requirements. In a network with heaters both low and high,

heaters placed low could be released as cheaply as the extreme case with all heaters low.

Heaters high were cheaper to release than in the case where all heaters were placed high,

because the cheap heaters low keep the total investment cost down.

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Related work

2 Related work

The most exciting phrase to hear in science, the one that heralds new discoveries, is not

'Eureka!' (I found it!) but 'That's funny ...'[Isaac Asimov (1920 - 1992)]

2.1 The field of Process Integration, past and present

he definition of Process Integration was first established within the International Energy

Agency (IEA) in 1993 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.

T

This definition has later been reformulated:

"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.

Such methodologies can be mathematical, thermodynamic and economic models, methods

and techniques. Examples of these methods include: Artificial Intelligence (AI), Hierarchical

Analysis, Pinch Analysis and Mathematical Programming.

Process Integration refers to Optimal Design; examples of aspects are: capital investment,

energy efficiency, emissions, operability, flexibility, controllability, safety and yields. ProcessIntegration also refers to some aspects of operation and maintenance."

This reformulation bears witness to the evolution of process integration that has taken place

during the last fifteen years. Today, synthesis and design of mass exchange networks (MEN)

[4, 5], distillation column integration and control [6], and property integration [7] are good

examples of the breadth that Process Integration has acquired.

Other important aspects are the designs of the reactor system, separation system, and control

system. Linnhoff [8] represented the hierarchy of a chemical process synthesis with the

"onion diagram", which starts with the design of the reactor system, continues with the

separation system and finishes with the construction of the heat exchanger network. The

onion diagram has later been expanded to include utility and power generation systems and

the important coupling to society [1]. With the development of computer calculation capacity

(CCC), Dhole [9] argued that simultaneous optimisation strategies could be used to minimise

the total annual cost of the plant.

In the following presentation of important literature in the field of Process Integration, only

Heat Exchanger Network (HEN) synthesis and design and related issues are reviewed.

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2.2 HEN Synthesis

eat exchanger network synthesis was first systematically studied in the 1960s. Work by

Westbrook [10] and Hwa [11], who created the superstructure based on mathematical

programming, and Masso and Rudd [12], who used heuristic rules to design the network,were among the pioneers. As the methods developed, two main algorithms for match selection

were being used, referred to by Nishida et al. [13] as simultaneous algorithms and sequential

algorithms.

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Kesler and Parker [14] suggested the assignment problem in linear programming, based on a

simultaneous algorithm. Each stream in the network is divided into equally small substreams

with a certain heat load. Hot substreams are then assigned to cold substreams while the sum

of the costs associated with each assignment is minimised. Further evolution is then required

to create a practical network of all the assigned substreams. Tree-searching methods and

decomposition methods are examples of sequential algorithms. Pho and Lapidus [15]

suggested a tree-searching method that developed the entire tree, but only systems with less

than 10 streams could be solved. In order to increase the number of streams and thereby the

problem size, the methods were combined with heuristic or bounding methods. One example

of a heuristic method is the approach presented by Ponton and Donaldson [16] who suggested

that the hot stream with the highest supply temperature should be matched with the coldest

stream with the highest target temperature.

Three fundamental concepts in heat exchanger network synthesis were discovered in the

1970s, two of them introduced by Hohmann [17]. He presented the first rigorous way ofestablishing the minimum utility usage prior to design. He also suggested the (N-1) rule for

the minimum number of units in the design, where N is the number of streams. These two

results were systematised and evolved by Linnhoff et al. [18]. The third discovery, and a

milestone in heat exchanger network synthesis, was the identification of the heat recovery

pinch as a bottleneck for further heat integration, independently discovered by Umeda et al.

[19] and Linnhoffet al. [18].

This literature survey will therefore start with a presentation of the most important

development of heat exchanger network synthesis in grass-root situations. A number ofreview papers have been published to cover process synthesis, such as Hendry et al. [20],

Nishida et al. [13] and, in heat exchanger network synthesis, Gundersen [21], Linnhoff [22],

Jezowski [23] and Fuhrman [24].

2.2.1 Grass-root HEN Design

oday two main approaches in heat exchanger network synthesis dominate: the pinch

design method and mathematical programming methods. In addition, there are methodsT

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employing heuristic and knowledge-based systems. This classification is rather rough, since

all the methods contain common elements such as basic thermodynamics. The pinch design

method and mathematical methods are discussed below.

2.2.1.1 Pinch Design Methodhe discovery of the heat recovery pinch led to development of a whole new

methodology for process synthesis, called pinch technology. Apart from its usefulness

in heat exchanger network synthesis, it has been applied to study the effects on a process

when new equipment is introduced. I will mention briefly some of these publications: Kemp

[25] on separation systems, Wallin et al. [26] on heat pumps, and Strmberg and Berntsson

[27] on combined heat and power.

T

Linnhoff and co-workers are the most important contributors to the development of the pinch

design method. Linnhoff et al. [18] provide the fundamental understanding of the basicconcepts involved in heat exchanger network design. They explain the relation between Tminand energy recovery, using the composite curves introduced by Huang and Elshout [28]. They

discuss loops and extend the (N-1) rule for minimum number of units suggested by Hohmann

[17], by applying Euler's theorem to the network problem. Their result (N+L-S) accounts for

the number of loops (L) and subsystems (S) in the network.

Linnhoff and Hindmarsh [8] presented the pinch design method for heat exchanger networks.

The approach behind this method is the recognition of the pinch point as the most constrained

region of a design. Therefore, the problem is split at the pinch point into two separatesystems, above and below the pinch point. The design of the network starts in the most

constrained region of each system, located immediately above or below the pinch point. Sets

of rules or feasibility criteria are applied to these streams to decide which ones are to be

matched. The feasibility criterion is derived from the FCp relation between the two streams

considered for a match. In order to achieve the minimum number of units in the network, the

tick-off heuristic is applied, which states that at least one of the streams considered for a

match must be satisfied. Further away from the pinch, these rules are not applied and are left

to the designers own judgement. The remaining problem analysis is also described and

recommended for use in more complex situations of the design stage.

Linnhoff and Vredeveld [29] introduced the driving force plot to evaluate how well an

existing or a suggested new match uses the temperature driving forces in the network.

The approaches to calculate maximum energy recovery and minimum number of units at

different Tmin values made it possible for design engineers to distinguish between good andbad network structures prior to design. Targeting for minimum heat exchanger area was

discussed by Nishida et al. [30] in relation to the heat content diagram, and by Nishida et al.

[13] in relation to the composite curves. Their approach was based on equal heat transfer

coefficients between all matches in the network, and on vertical counter-current heat transferbetween the composite curves. Townsend and Linnhoff [31] extended their work to account

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for individual heat transfer coefficients for the streams with the presentation of the Bath

formula, based on the spaghetti network. Their formulation is only an approximation but

works well in many situations.

Ahmad and Linnhoff [32] addressed the issue of cost targeting for the most economic Tminprior to design. They calculated the cost of energy, the cost of minimum number of units, andthe cost of heat exchanger area at different values of Tmin. These costs were added anddrawn in a cost-Tmin plot, from which the most cost-effective Tmin could then be selected.This targeting approach was later developed and presented as supertargeting by Linnhoff and

Ahmad [33]. Further refinement of the detail of the targeting procedure was the main concern

in the papers presented by Ahmad and Smith [34] and by Hall et al.[35]. Ahmad and Smith

[34] described a method for targeting the minimum number of shells and near-minimum area

in networks requiring 1-2 heat exchangers. Hall et al. [35] developed a method which allows

capital cost targets to take into account different materials of construction, pressure ratings,

and heat exchanger type. This was achieved by assigning weights to the heat transfer

coefficients of the Bath formula by Townsend and Linnhoff [31]. A review and update on

costs for heat exchangers was later published by Taal et al. [36]. Linnhoff and Ahmad [37]

used supertargeting for predicting the optimal Tmin and then used the driving force plot byLinnhoff and Vredeveld [29] and the remaining problem analysis by Linnhoff and

Hindmarsch [8] to construct the network. A concept similar to supertargeting was presented

by Marchal and Kalitventzeff [38], using a combination of pinch-based techniques and

mathematical programming.

The concept of the dual approach temperature, i.e. using two different temperature differencesto set the limits of the network, was first introduced by Challand et al. [39] and Colbert [40].

These two temperatures are the heat recovery approach temperature (HRAT), which is used to

determine the minimum utility requirements, and the exchanger minimum approach

temperature (EMAT). The first attempt to develop the dual approach temperature approach

into a synthesis method was made by Trivedi et al. [41, 42]. Based on these results, Wood et

al. [43] developed the pseudo-pinch design method. By using two different minimum

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heat transfer coefficients for the streams, a maximum allowable pressure drop is specified for

each stream. An approximate area contribution and a heat transfer coefficient for each stream

are then calculated iteratively within the area target calculation. Jegede and Polley [49]

developed a procedure to optimise single heat exchangers in a network. Simple relationships

were used to trade off heat exchanger area and power requirements of both streams for agiven heat load. Muralikrisnhna and Shenoy [50] presented a methodology that determines the

feasible region for shell-and-tube heat exchanger pressure drop by accounting for both

geometrical and operating constraints. The area target ensures an exchanger of the smallest

size with minimum capital cost, whereas the cost target yields the optimum pressure drops

accounting for the trade-off between power consumption and heat exchanger area.

Polley [51] introduced a method for selecting stream splits in heat exchanger network design,

based on a number of FCp-matrices.

Zhu et al. [52] proposed a heuristic method which does not rely on pinch point

decomposition. Instead the composite curves are decomposed into a number of blocks. The

segments of the composite curves located within each block are represented by a straight line,

called quasi-composites. Area requirements for all feasible matches are calculated, based on

maximum heat exchange in each block. These areas are compared with the ideal areas of the

quasi-composites. A good set of matches is then selected from the whole set of possible

matches of the block, taking matching constraints into consideration. Matches are selected for

all blocks simultaneously. The number of enthalpy intervals used to synthesise the heat

exchanger network is greatly reduced, compared with the spaghetti structure. Once the

matches in each block have been selected, the total cost of the network is minimised.

Amidpour and Polley [53] proposed a method that decomposes a large problem and solves

each sub-problem to the optimum. Heat transfer between zones or sub-problems should,

however, be avoided.

Westphalen et al. [54] introduced a controllability index for HENs that can be used as a

complement to design methods and also be used to identify trade-offs between controllability

and heat integration..

2.2.1.2 Mathematical Programming

he ideal way of finding the optimum solution to a heat exchanger network design with a

mathematical method would be to use an objective function that consists of the

annualised investment and operating costs. Unfortunately, the mathematical formulation of

the problem for such an objective function is very complicated. It requires a mixed-integer

non-linear program formulation, which involves non-convexities in the objective function and

a rather large number of variables. Therefore, the two most important issues in mathematical

methods are to find an efficient and reasonably sized representation of the problem and to use

or develop efficient optimisation techniques that can exploit the representation of the problem.

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Mathematical methods, as well as pinch-based methods, benefited immensely from the

discovery of the heat recovery pinch. It was now possible to establish the thermodynamic

limit and determine the minimum hot and cold utility requirements for any process. Cerda et

al. [55] presented a paper that formulated the minimum utility calculation for a heat

exchanger network synthesis as a transportation problem from linear programming, a well-known problem for which efficient algorithms exist. It is possible to add non-thermodynamic

constraints on matching certain streams, wholly or in part. Cerda and Westerberg [56] used

the transportation problem to calculate the minimum utility requirements. In order to find the

smallest number of matches in the process, a MILP model was relaxed into a linear

programming transportation problem and solved. However, the knowledge of the smallest

number of matches does not imply knowledge of the heat exchanger network structure, since

stream splits and loops may be involved and the actual structure therefore needs further

evolution.

A similar approach was suggested by Papoulias and Grossmann [57]. They solved the

minimum utility requirement by means of the transhipment model, which is a considerably

smaller variation of the transportation model. Non-thermodynamic constraints are taken into

account by an extension of the transhipment model. The minimum number of matches that

should take place in the network is determined by means of the transhipment model involving

the solution of a MILP, by means of a branch-and-bound method. The heat exchanger

network configuration is not obtained directly from the solution of the MILP transhipment

model, but it contains all necessary information to derive the network by hand. Since the

configuration is not obtained, several networks will sometimes have to be derived manually

and analysed in detail before a structure can be selected.

Floudas et al. [58] addressed the problem of how to automatically generate the network

structure that satisfies the minimum utility requirement, feature the fewest number of units,

and minimise the investment cost. Their approach relies on the LP transhipment model for

predicting the minimum utility target and the MILP transhipment model for the smallest

number of units. Based on the results from these models, a superstructure is created. In the

superstructure all networks are embedded that satisfy the minimum utility requirement and the

smallest number of units. The superstructure itself is created from independent stream

superstructures, which contain all the alternatives for splitting, mixing and bypassing. Thesuperstructure is used within a non-linear programming formulation to generate optimal

network configurations. Due to the non-convexities in the heat balances of the formulation, a

unique optimal solution cannot be guaranteed.

Floudas and Ciric [59] suggested an approach to overcome the decomposition of the synthesis

problem into the two stages of deriving of the smallest number of units and the actual

configuration of the network. This was done by introducing the so-called hyperstructure,

which was solved using MINLP. The difference between the superstructure by Floudas et al.

[58] and the hyperstructure is that the superstructure contains only matches that have been

selected previously, whereas in the hyperstructure all potential matches must appear since

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Related work

these will be determined simultaneously with the configuration. The MINLP is in turn

decomposed into a NLP sub-problem that derived the heat exchanger network for a single set

of matches and a MILP master problem that identified the sets of matches and heat loads that

satisfy the minimum utility requirements.

Yee and Grossmann [60, 61] proposed a method where the problem did not have to rely on

the sequential decomposition, but accounted simultaneously for the trade-off between energy

costs, fixed charges for units and cost for heat exchanger area. This has been achieved by

significantly simplifying the superstructure by dividing it into stages, which has similarities to

the spaghetti design of Linnhoff and co-workers. However, unlike the spaghetti design, the

proposed superstructure does not have to be equal to the number of energy intervals since the

temperatures corresponding to each interval are optimised. The superstructure is modelled and

solved as a MINLP problem.

Ciric and Floudas [62] also suggested an approach, without decomposition, to simultaneously

solve the utility consumption levels, the process stream matches, and the network

configuration. Their approach is based on the hyperstructure of Floudas and Ciric [59] and a

modified transhipment model to select heat loads. The problem is formulated as a MINLP

problem.

Briones and Kokossis [63] developed an area targeting method that replaced the transhipment

problem in the hypertargets approach. This eliminated the risk of ending up in inferior points

in the optimisation.

In 2003, Mitzutani et al. [64] proposed an optimisation model that incorporated detailed heat

exchanger design into the network optimisation problem. This model did not include piping

considerations.

Zhu et al. [65] automated a method for block decomposition before NLP optimisation, the

blocks containing streams with similar characteristics.

Daichendt and Grossmann [66] described a screening procedure for MINLP formulation to

overcome the computational complexities associated with binary variables. A base-casedesign is set as upper bound. Every solution to the aggregated model whose cost is greater

than the base cost can thus be eliminated.

Despite the substantial research on the synthesis of heat exchanger networks with

mathematical methods, there are still two major difficulties encountered in MINLP problems.

First, the size of the problems in terms of binary variables makes them impractical to solve.

Second, the non-convexities in the objective function may lead to poor sub-optimal solutions.

Daichendt and Grossmann [67] propose a preliminary screening method to overcome these

problems. The method uses an aggregated model, i.e. a simplified representation, of the

original problem. A base-case design is defined as a good solution to the original problem and

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Roger Nordman

provides an upper bound to the global optimum of the original model. The aggregated model

is then solved, and all solutions to it whose cost is higher than the base case are eliminated,

whereas other solutions remain within the superstructure of the original model, which can

then be solved.

Pettersson and Bjrk & Petterson [68, 69] presented methods that allow an increased number

of streams and thus a greater problem size. The drawback with these methods is that the

global optimum cannot be ensured.

Many authors have attacked the MINLP optimisation in diverse ways with varying success.

Different forms of evolutionary search approaches have been adapted, e.g. genetic algorithms

[70, 71], Tabu search [72], graph-theoretic principles [73] or randomisation techniques [74].

2.2.1.3 Other Methods

ome attempts have been made to combine pinch technology and exergy analysis in heat

integration [75-78]. Results show that exergy could provide additional benefits when

Heat Pumps or CHP are analysed simultaneously with the HEN.

S2.2.2 Retrof it Design

he interest in retrofitting of heat exchanger networks increased during the late 1970s

with the rising cost of energy. However, the first systematic approaches to retrofittingwere not presented until the mid-1980s. Early methods were based mainly on synthesis

methods for grass-root design. Jones et al. [79] used a commercial program to generate grass-

root designs, and then selected the design closest to the existing one for further development.

Saboo and Morari [80] used a similar concept but a more rigorous technique than Jones et al.

[79]. The main difference between grass-root design and retrofit design is the amount of

constraints imposed on the solution by the existing layout of the process in the retrofit

situation.

T

2.2.2.1 Pinch Design Method

joe and Linnhoff [81]) presented the first retrofit method based on pinch technology. A

new approach for predicting the Tmin prior to design in retrofit situations waspresented. As in the target procedure for grass-root design, they use the Bath formula to

calculate the area requirement for various values ofTmin. The area target corresponding tothe utility consumption (and consequently the corresponding Tmin ) of the existing networkwas then compared to the actual area installed in the existing network, and the scope for using

the existing area more efficiently was investigated. Linnhoff and Tjoe [82] continued work on

the targeting procedure. The ratio of minimum area requirement of the existing Tmin and the

actual existing area was introduced as a parameter in the target procedure. This ratio wascalled the area efficiency. A constant area efficiency curve was then used as the worst

T

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possible case to predict the required heat exchanger area and cost for the retrofitted network.

A trade-off curve between the energy target and surface area target was constructed. The

recommended approach to redesign of the existing network was based on rearranging those

heat exchangers transferring heat across the pinch point and designing the new network so

that as much as possible of the existing structure was kept, even if new area would have to beinstalled. Tjoe [83] improved the synthesis procedure of the targeted network. Each heat

exchanger in the network was analysed by means of the remaining area analysis. Heat

exchangers making poor use of the temperature driving force could thus be identified. The

rearrangement of the badly placed heat exchangers was guided by a slightly modified driving

force plot. Poorly placed heat exchangers were adjusted to the driving force plot of the

process by either shifting them in temperature or changing the FCp-value of one of the

streams in the heat exchanger by splitting it. New heat exchangers were then introduced into

the gaps. By investigating loops and paths in the resulting network, some of the heat

exchangers were merged or alienated from the design and the resulting Tmin was modifiedslightly.

Ahmad and Polley [84] addressed the effects of increased pressure drops in a network, which

arise from increased flow rates in de-bottlenecking. They were concerned mainly with retrofit

for de-bottlenecking of processes in order to increase the throughput, rather than with energy

conservation. Polley and Panjeh Shahi [85] considered pressure drop effects in energy-savings

retrofits. The targeting procedure for heat exchanger retrofits is modified to include a relation

between pressure drop and heat transfer coefficients. Maximum allowable pressure drops are

assigned to the streams, based on the stream pressure drops and existing area in the existing

network. The heat transfer coefficient is calculated from the stream pressure drop, heatexchanger area, and a constant dependent on fluid properties, volumetric flow rate and the

hydraulic diameter of the heat exchanger. The calculated heat transfer coefficients are then

used in the target procedure. Nie and Zhu [86] presented a two-stage decomposition method.

The first step in this method is to identify which of the existing units require additional area.

Second, area distribution, shell arrangements, heat transfer enhancements etc. are optimised

for these units. Units not requiring additional area are treated with simple models. By this

approach, the pressure drop can be calculated accurately, and the overall model can remain

simple.

Van Reisen et al. [87] introduced a method, called path analysis, to select and evaluate

fractions (or sub-networks) of an existing heat exchanger network considered for retrofitting.

The evaluation of the sub-networks is done by using established targeting tools for the sub-

networks as well as for the total network. The sub-networks are generated either by the design

engineer or by a rigorous algorithm that evaluates all sub-networks of the total network. Two

criteria for a sub-network are presented. First, it must be heat-balanced. Second, a heater and a

cooler must be included. The new network is designed using only the streams included in the

sub-network. This work was followed up by a new targeting method in retrofitting, based on

dividing the existing process into zones [88]. Thus, part of the original network with high

saving potential could be identified and treated separately.

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Lakshmanan and Baares-Alcntara introduced the concept of the Retrofit Thermodynamic

Diagram (RTD) and a set of guidelines for developing retrofit solutions by inspection [89,

90]. This method uses a graphical interface to view existing units, and the criss-cross involved

in the heat exchange. Guidelines are then applied to straighten up criss-cross to shift energyloads. The heuristics developed in this method were later used by Abbas [91] in an approach

to solve the retrofit problem by Constraint Logic Programming (CLP).

The concept of the Network Pinch was presented by Asante and Zhu [92-94]. The network

pinch is a characteristic of both the process streams and the HEN topology, since it shows

which exchanger unit is limiting the heat recovery. A three-stage procedure was proposed, in

which the network pinch concept was used in the first stage. In the first stage, a diagnosis

stage, promising candidates for modifications (relocation of existing units, adding new

exchangers and stream splitting) are identified. In the second stage, the evaluation stage, the

costs of modifications are estimated. In this stage, impractical options from the first stage are

screened out. In the final stage of optimisation, the options are optimised in terms of trade-off

between the capital investment and the heat recovery achieved.

2.2.2.2 Mathematical Programming

he first paper based on a mathematical method and wholly dedicated to the retrofit of

heat exchanger networks was presented by Yee and Grossmann [95]. They presented a

systematic procedure for predicting the smallest number of structural modifications in an

existing network. The objective of their model was to maximise the utilisation of existing heatexchanger units, minimise the number of new stream matches that require the installation and

purchase of new units, and minimise the reassignment of existing units to new required

matches. These objectives would lead to a network configuration as close as possible to the

existing one. Detailed costing information was not included for these objectives. The solution

is found by using a MILP assignment-transhipment model, which is an extension of the MILP

transhipment model by Papoulias and Grossmann [57]. Potential matches in the network were

listed in the following desirability order: (1) existing matches that can remain in position in

the retrofitted network, (2) new matches that can be accomplished by only changing one of

the streams in the existing match, and (3) new matches that require the purchase andinstallation of a new heat exchanger. To describe the desirability, weights are assigned to the

binary variables in the objective function, and special constraints are added to the grass-root

transhipment model to account for matches that requires the change of only one of the

streams. In certain cases there are several alternative solutions that may be equal in terms of

structural modifications, but that may differ a lot in area requirement, which was not taken

into account in the calculations.

T

Ciric and Floudas [96] presented a two-stage procedure for the optimal redesign of an existing

heat exchanger network. The first stage involves the formulation of a MILP, at match level.

The pairings of all possible matches (i.e. stream pairs) and heat exchangers are considered and

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classified in six different categories. (1) An existing match is housed in an existing heat

exchanger in both the original and the retrofitted network. (2) An existing match will be

housed in a new heat exchanger in the retrofitted network, which is being used elsewhere in

the existing network. (3) A new match that did not exist in the original network will be

housed in another heat exchanger in the existing network, which uses one of the streams ofthe new match. (4) A new match that did not exist in the original network will be housed in

another heat exchanger in the existing network. (5) A new heat exchanger is purchased for an

existing match. (6) A new heat exchanger is purchased for a new match. The objective

function consists of three main components: the cost of purchasing new heat exchangers, the

cost of additional heat exchanger area, and the piping cost resulting from structural

modifications. The solution to the objective function represents the minimum cost at match

level. Heat loads and selection of process stream matches are modelled by the transhipment

model of Papoulias and Grossmann [57]. An assignment problem is used to determine the

placement of new and reassigned heat exchangers. In the second stage a superstructure is

created, based on this information, and is formulated and solved as a NLP problem.

Ciric and Floudas [97] presented an MINLP formulation that selects process stream matches

and match-heat exchanger assignments, and optimises the network configuration

simultaneously. This approach allows for the match-heat exchanger assignments to be decided

on the basis of area requirement, as opposed to the estimates of area and piping costs in the

paper by Ciric and Floudas [96]. The formulation of the problem in this paper can instead be

extended to calculate piping costs from the actual network structure. It is possible to include

heat exchanger rating equations, different types of heat exchangers, variable heat transfer

coefficients, and pressure drop considerations. The MINLP formulation is composed of anobjective function that is based on the modification cost and subject to a set of constraints.

Heat loads and selection of process stream matches are modelled by the transhipment model

of Papoulias and Grossmann [57]. The network configuration is modelled by the generalised

match-network hyperstructure by Floudas and Ciric [96]. An assignment problem is used to

determine the placement of new and reassigned heat exchangers. The MINLP formulation is

decomposed into two sub-problems: the master sub-problem, an MILP, which selects process

stream matches and heat loads, and the primal sub-problem, an MINLP, which derives the

optimal network configuration and assigns heat exchangers to a certain match. The primal

sub-problem is solved as a NLP problem. A comprehensive retrofit optimisation model waslater proposed by Ciric and Floudas [98]. It consists of an MINLP model that incorporates all

possible stream matches, network configurations and existing exchanger reassignments. The

required area of each potential match is evaluated simultaneously with the re-piping cost and

additional area of existing units.

Yee and Grossmann [99] presented a two-stage approach involving a pre-screening stage and

an optimisation stage. The purpose of the pre-screening stage is to determine the economic

feasibility of the retrofit project. Lower bounds for the annual cost of utilities, additional area

requirement, and fixed cost for structural modifications are estimated for various levels of

heat recovery. These lower bounds are compared to the existing operating costs, and the

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Roger Nordman

potential for a retrofit can be evaluated. Utility requirements are calculated by the LP

transhipment model of Papoulias and Grossmann [57]. Additional area is calculated by the

method suggested by Townsend and Linnhoff [31]. Minimum structural modifications are

estimated by the method presented by Yee and Grossmann [95]. The optimisation stage

consists of the construction of a retrofit superstructure, which has all interesting retrofitdesigns embedded within. A novelty in this representation is that the heat exchanger units are

not committed to a particular pair of streams. The number of heat exchangers to include in the

superstructure is decided in the pre-screening stage. Existing units are explicitly embedded in

the superstructure. To determine the best retrofit design embedded in the superstructure, a

MINLP model is formulated and solved. Two difficulties arise when solving the MINLP

model. First, the MINLP model is of a large scale that requires long computational time.

Second, due to non-convexities in the heat balances and heat exchanger design equations,

only local optimality can be guaranteed. To overcome these problems a number of

simplifications are suggested, such as disallowing stream splits, bypasses or using the

arithmetic mean temperature difference instead of the logarithmic temperature difference.

Various methods were used for solving the MINLP. Sorsak and Kravanja [100] extended the

model of Yee and Grossmann to account for different exchanger types.

Briones and Kokossis also introduced a hypertargets method, which consists of two steps,

targeting and optimisation. The method was first developed for grass-root situations [63], but

further developed for retrofit [101]. Auditing of the existing network is made with the HEAT

model, before promising modifications are evaluated (TAME model). Both models are MILP,

so the problem size can be rather large and still manageable.

Evolutionary methods have also found their way into the field of HEN retrofit. Athieret al.

[102] proposed a method where the structural optimisation was carried out by a simulated

annealing procedure and, for each generated network, the required additional area was

optimised by an NLP procedure. Bjrk and Nordman [103] proposed a combined method

using a genetic algorithm and the Synheat model for retrofit of large-scale problems. The

genetic algorithm was used to decompose a large problem into smaller ones, which could be

solved by the Synheat model. The model seemed promising, but more work should be made

on the representation of existing heat exchangers.

Fuhrman and Sahinidis [104] proved that HEN synthesis problems are generally NP-hard,

meaning that they are not solvable in polynomial time with non-deterministic algorithms.

Kumana [105] worked through a number of problems using different HEN retrofit methods

and evaluated them. The Network Pinch method and the Path Analysis method were judged

by Kumana to be the most successful. Although the matrix method of Carlsson was only

briefly known, this method was considered a valuable contribution to retrofit design

methodology.

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Technical and economic conditions

3 Technical and economic condit ions

Research is what I'm doing when I don't know what I'm doing.

[Wernher von Braun]

3.1 Technical and economic conditions

n Papers I and VI the following cost equations were used:IExisting heat exchanger: Cinv = 25000 + 500A# (3.1)

New heat exchanger: Cinv = 50000 +500A (3.2)

These equations were based on work by Axelsson [106] but, due to changed material prices,they were adjusted up to reflect the current situation [107]. A# denotes the new area that is

added to an existing heat exchanger and A is the area installed in a new heat exchanger.

In PaperI cost of piping was not included, in order to investigate only the economic effect of

area and number of units. Piping costs are estimated as 40% of FOB price of new heat

exchangers in PaperVI.

Stream data for PaperI and VI are presented in Table 1.

Table 1. Stream data for the process in Paper I and VI.

Type Tstart Ttarget Q h(C) (C) (kW) (kW/m2K)

Hot 130 120 17710 0.8Hot 130 45 12019 0.8Hot 377 170 19520.1 0.8Hot 377 150 13506.5 0.8Hot 270 70 13180 0.8Hot 270 80 9842 0.8Hot 270 70 12540 0.8Cold 45 350 26443.5 0.8

Cold 120 214 6523.6 0.8Cold 190 348 3902.6 0.8Cold 120 219 5375.7 0.8Cold 120 170 25240 0.8Cold 120 250 11414 0.8Cold 35 70 15820 0.8

In Paper II, the cost data and equations presented in Table 2 were used. These data and

equations were discussed with mill engineers, and approved by mill management.

All heat pump calculations were made using the IEA Annex 21 heat pump selection and

analysis software Annex XXI. Stream data for the mill are presented in Table 3.

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Roger Nordman

Table 2. Data used for the economic evaluation in Paper II.

Cost data for the calculations.

Operating time 8760 hours/yearElectricity price 210 SEK/MWhOil price 191 SEK/MWhBoiler efficiency 0.92Heat exchanger cost (new) 40,000 + 400*A (m2) USDHeat exchanger cost (enhanced) 10,000 + 400*A (m2) USDPiping 3500 SEK/mDollar exchange rate 9.50 SEK 1 USD

Table 3. Stream data used in Paper II.

Type Tstart Ttarget Q(C) (C) (kW)

Hot 123 123 4560

Hot 123 65 502Hot 136 65 1124Hot 77 55 16523Hot 52 48 186Hot 110 100 1137

Hot 110 48 5291Hot 76 48 5622Hot 68 67 27725Hot 67 48 940

Hot 68 53 5252Hot 102 89 2838Hot 66 57 829Hot 90 78 1478Hot 90 81 810Hot 100 100 260Hot 80 50 3267Hot 67 60 5833Hot 75 48 6162Cold 144 145 8537Cold 53 110 4044Cold 100 110 21Cold 144 145 25495

Cold 7 45 810Cold 60 85 2198Cold 7 85 6858Cold 7 85 6858Cold 7 75 1309Cold 7 75 8016Cold 7 65 2148Cold 7 65 348Cold 7 45 1407Cold 7 45 3113Cold 184 185 332Cold 144 145 312Cold 7 65 8280

Cold 50 80 5000

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In PaperIII, the following cost equations are used:

Heat exchanger costs [36]:81.0164430800($) HXACost += (3.3)

Tank costs [108]:

55,012005,2() TankVCost = (3.4)

Evaporator costs [2]:

EvapAnCost += 333105,8($)5 (3.5)

Cost of lost electricity production:

eloplost CtECost =($/yr) (3.6)

Here the lost electricity production, Elost, is ( T = 0.80, m+g = 0.98 ) :

)()(

)()(('''

''''

LPhLPh

LPhHPhQE

gmTxs

tlos

= +

(3.7)

Savings from decreased fuel consumption:

fuelopfuel CtQV =($/yr) (3.8)

Here the amount of saved fuel, Qfuel, can be expressed as (b, oil = 0.92, b,bark = 0.83 ):

))()((

))()(('''

'''

LPhLPh

LPhHPhQQ

b

xsfuel

=

(3.9)

Income from sold Qxs to DH:

DHopxs CtQV =($/yr) (3.10)

Piping costs associated with new heat exchangers were calculated as 40% of FOB investment

cost of the heat exchanger.

The costs were, when necessary, adjusted with the chemical engineering plant cost index, and

all prices were converted to US$ using the exchange rate on August 25, 2004.

In this paper marginal fuels were assumed to be either oil or bark; the district heat price was

calculated as the avoided production price using wood fuel in the DH net (b=0.83). Districtheat is assumed sold 5500 h/yr.

Stream data for this paper are presented in Table 4.

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Roger Nordman

In Papers I and VI, only the investment cost was calculated, since utility cost data were

unknown. Therefore no PBP could be calculated. In Paper II on the other hand, such data

were known and, in addition, investment space was known from previous studies.

In Paper III the investments were analysed by using scenarios. Why scenario modelling is

important is discussed in the following section. The cost data used in the scenarios in thispaper are presented in Table 5. For a detailed discussion of the values, please refer to [1].

Table 4. Stream data representing the HWWS streams in the case study.

Type T start T target Q(C) (C) (kW)

Hot 70 20 3060Hot 66 57 810Hot 110 48 5390Hot 102 89 2860Hot 67 60 5830

Hot 110 100 1600Hot 76 42 6340Hot 68 67 24530Hot 67 48 830Hot 77 55 18960Hot 80 50 3270Hot 123 122 980Hot 122 43 1960Cold 7 85 6860Cold 7 85 6860Cold 7 75 1500Cold 7 65 8570Cold 7 85 5000

Cold 7 55 4210Cold 7 65 2150Cold 7 45 1410

Table 5. Cost parameters for the scenarios used in the economic evaluation.

Scenario Oil price Bark price Electric ity retail price District heat price(US$/MWh) (US$/MWh) (US$/MWh) (US$/MWh)

Scenario 1 26.9 13.4 38.7 20.2Scenario 2 22.0 13.9 40.3 20.8Scenario 3 29.3 18.2 52.5 26.0Scenario 4 41.1 26.4 76.2 35.8

3.2 Scenarios

W hen an energy retrofit project is evaluated from an economic viewpoint, not onlyinvestment costs must be evaluated. The cost savings from less use of fuels must alsobe calculated, as well as cost savings from less pollution. Society and world market prices,

rather than the plant, influence these two parameters. One example is the world market oil

price, which has changed dramatically in recent years. Other examples are governmental

policy instruments such as CO2 trading, green certificates for renewable electricity productionetcetera. These different parameters are often linked to each other by rather complex

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mechanisms. Sensitivity analysis of one parameter at a time could therefore give misleading

results.

Large energy models (such as the model of the Nordic energy system, Nordleden [109]) use

scenarios of future energy systems to study when certain energy production techniques enteror leave the energy production mix. In the modelling, either the forecasting or the back-

casting method is used. Forecasting implies that certain conditions are imposed at different

time steps, and the response to these changes is studied. Back-casting on the other hand is

based on a given situation (given by the scientist) in the end of the studied time frame. The

model then adjusts the energy production mix to arrive at the wanted situation.

This type of large models includes learning curves for different technologies; they also

include a large variety of production techniques, and both existing and new techniques that

may come into play in the future. Among the many results these models give are projected

prices of fuels and emissions abatement costs.

dahl [1] has proposed a framework for the integration of large energy models with results

from process integration studies on the plant level. By an iterative procedure, small-scale and

large-scale models results are used as inputs and outputs. Results from large-scale models are

e.g. energy and emission abatement costs, which could be used in the evaluation stage in

plant-scale retrofit projects. The largest benefit with this approach in small-scale analysis is

that the prices and costs reflect a proposed future scenario, e.g. a 25% decrease of CO2

emissions by the year 2050. By evaluating retrofit projects for a number of possible scenarios,

long-term reliable decisions can be made.

In this thesis work, results from dahls scenario modelling work were used for the economic

evaluation of the proposed solutions in PaperIII.

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Advanced composite curves for retrofit

4 Advanced composite curves for retrofi t

The important thing in science is not so much to obtain new facts as to discover new ways of

thinking about them.[Sir William Bragg (1862 - 1942)]

4.1 Background

arlier works in the research group have resulted in a set of advanced composite curves.

The works concerned optimum design and integration of industrial heat pumps [110] and

combined heat and power production integration to existing processes [27, 111]. In this thesis

work we have further developed a set of advanced composite curves to be used in HEN

retrofit. Traditional methods such as the grand composite curve (GCC) reveal no information

about where existing heat exchangers, heaters and coolers are placed in the network,something we have identified to be of great importance.

E

The aim with the advanced composite curves regarding HEN retrofit is twofold:

To identify heat recovery projects that reduce the problem size, and are economicallyfeasible, prior to detailed design calculations.

To identify temperature levels where usable excess heat can be extracted and used byother processes (cf. total sites, ecocyclic industrial parks).

4.2 Construction of the advanced curves

o study the proportion of the theoretical integration potential that can be utilized at a

reasonable cost, four composite curves are used above and below the pinch respectively,

Figure 1. The four curves above the pinch are called Hot Utility Curve (HUC), Theoretical

Heat Load Curve (THLC), Actual Heat Load Curve (AHLC) and Extreme Heat Load Curve

(EHLC). The corresponding names below the pinch are Cold Utility Curve (CUC),

Theoretical Cooling Load Curve (TCLC), Actual Cooling Load Curve (ACLC) and Extreme

Cooling Load Curve (ECLC).

T

The Hot Utility Curve (HUC) is a composite curve of the utility streams in existing heaters at

real temperatures. Correspondingly, the Actual Heat Load Curve (AHLC) is a composite of

the process streams in the existing heaters. The EHLC shows the temperatures where heat

would be supplied if the heat exchange were carried out so that all external heat was supplied

at highest possible temperature (with the same QH as the AHLC). This corresponds to the

overshoot part of the cold CC, the part that with traditional vertical heat exchange is covered

by hot utility.

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Roger Nordman

0

50

100

150

200

250

300

350

400

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Q (kW)

T

(C)

THLC AHLC EHLC HUC TCLC ACLC ECLC CUC

Figure 1. Example of advanced composite curves.

The THLC curve represents the lowest possible temperatures where heat can be supplied

when all thermodynamically possible opportunities for heat exchange, using a specified

Tmin,HX, have been exploited for the actual heat demand but no energy saving is made (i.e.original QH). This means that heat exchangers are put in only to shift the current heat demand

down in temperature. Correspondingly the TCLC curve shows the highest possible

temperature levels where heat could be removed from the system.

Below, a step-by-step procedure describing the construction of the THLC and TCLC is given:

1. Draw the composite curves with a Tmin that reflects the present utilityconsumption. Figure 2 shows an example of a composite curve. All heat demand is

located in the high temperature range of the cold composite curve in this case.

2. Divide the system at the pinch.

3. For the streams above pinch (Figure 3), calculate the heat cascade, now using

Tmin,HX, the temperature difference that would be used in the design of a new heatexchanger, e.g. 5K. This is, in this simple example, equal to shifting the hot

composite curve right until the new Tmin (=Tmin,HX) is reached (Figure 4).4. The heat demand is now scattered along the cold composite curve, but at lowest

possible temperatures. These heat demands compose the THLC.

5. The TCLC is constructed in the same way for the streams below pinch. The THLC

and TCLC are plotted in Figure 4. Since the original Tmin is larger than theTmin,HX and QH is not changed, the THLC and the TCLC will cross.

6. The amount of heat that could have been saved by heat recovery is indicated with a

dotted line in Figure 5. This amount of heat could be saved using less utility;therefore it is plotted at the utility temperature level Figure 6. The utility level

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should therefore be seen as a temperature-wise upper bound of potential heat

release.

Composite Curves

0

20

40

60

80

100

120

140

0 50 100 150 200 250 300 350 400 450Q (kW)

T

(C)

Figure 2. Example of composite curves.

Composite Curves

0

20

40

60

80

100

120

140

0 50 100 150 200 250 300 350 400 450

Q (kW)

T

(C)

QH

Figure 3. The system is split in two at the pinch. Here the streams above the pinch are viewed.

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Roger Nordman

Composite Curves

0

20

40

60

80

100

120

140

0 50 100 150 200 250 300 350

Q (kW)

T(C)

QH

Figure 4. The hot composite curve is shifted right until the new pinch, at Tmin, HX, is activated.

0

20

40

60

80

100

120

0 20 40 60 80 100 120 140 160

Q (kW)

T(

C)

TCLC THLC

Figure 5. The advanced composite curves are calculated from a heat cascade incorporating the streams

above the original pinch.

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0

20

40

60

80

100

120

140

160

0 20 40 60 80 100 120 140 160

Q (kW)

T

(C)

THLC TCLC

Figure 6. The amount of heat that could have been saved by removing pinch violations is identified, and

the advanced curves are adjusted to the utility levels.

In principle, the THLC and TCLC could have been constructed in a similar way:

Plot the GCC forTmin,HX and remove all pockets. Add, from the left, the amount of heat that corresponds to the difference in

temperature driving force (Tmin -Tmin,HX) at the utility levels.

This construction differs very marginally from the construction of the THLC/TCLC as

described above. The difference comes from the fact that the heat cascade, which is used in

both methods, is calculated for different values ofTmin. As is indicated in Figure 2 andFigure 3, the stream data are divided at the pinch for the current Tmin and then the heatcascade is calculated using Tmin,HX when the THLC and TCLC is constructed. If the curveswere constructed in the second proposed way, the stream data above and below pinch

respectively would differ compared to the first description, since the hot and cold composite

curves would be adjusted to reach Tmin = Tmin,HXbefore the system was split at the pinch(Figure 7).

The first described method should be chosen when constructing the advanced curves, because

this method shows the potentials when no changes have been made to the system. The

secondly described method shows the potential when changes corresponding to the possible

heat recovery have been made.

The point where the THLC and the TCLC cross is generally a good indicator of the amount of

heat that can be made available at utility levels. When the second method described above is

used, the amount of heat that can be made available at utility levels is found at the point where

the THLC and the TCLC are separated Tmin, HX to the left of where the crossing takes place.In the first described method, the crossing generally occurs in the same region described for

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Roger Nordman

the second method, but small deviations from this exact point are possible, due to the

difference in separation of the system above and below the pinch point.

Composite Curves

0

10

20

30

40

50

60

70

80

90

0 20 40 60 80 100 120

Q (kW)

T

(C)

Figure 7. The same composite curves as in Figure 2, but now shifted before splitting the system.

Composite Curves

0

10

20

30

40

50

60

70

80

90

0 20 40 60 80 100 120

Q (kW)

T

(C)

Figure 8. The streams above pinch, when the system is split at the pinch.

If all pinch violations are corrected, the part to the right of the correction point shows the

remaining heat demand. The pinch violations that are not corrected remain to the left of the

correction point. This heat can theoretically be released at the utility temperature levels.

The THLC should be plotted with as low T as would be acceptable when building a new

HX, e.g. 5K for water-water heat exchange, according to Gundersen [46]. In principle theTHLC could be plotted with a Tmin of 0K, but that would never be realistic in practice. The

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area where the AHLC lies close to the THLC corresponds to heaters placed low, and should

therefore be relatively cheaper to release than heaters placed high. This is discussed in detail

in Papers V and VI.

If the AHLC and the ACLC cross, this means that cold streams are heated by hot utility while

at the same time hot streams lying above the heated cold streams are cooled by cold utility.This allows both heater(s) and cooler(s) to be replaced by process-process exchange in one

unit. From the discussion above, it is clear that drawing the AHLC, EHLC and the THLC

gives a representation of where existing heaters are placed and how much of these could be

released. The same applies below the pinch with the ACLC, the ECLC and the TCLC.

4.3 Heat exchanger network retrofit

n HEN retrofit, three advanced curves are used above and below the pinch respectively.

These curves are the THLC, AHLC and EHLC above pinch, and the TCLC, ACLC and

ECLC below pinch. By studying how the AHLC is placed between the THLC and EHLC, and

how the ACLC is placed between the TCLC and ECLC, the potential for cost-effective

retrofit projects can be determined. In PaperI, it was found that heaters and coolers which are

placed close to the pinch are less expensive to release. This was further studied and discussed

in detail in Papers V and VI.

I

In general the following extreme cases could appear:

1 Heaters placed low and coolers placed high (best),Figure 9.

2 Heaters placed low and coolers placed low.3 Coolers placed high and heaters placed high.

4 Heaters placed high and coolers placed low (worst), Figure 10.

120 130 17710

45 130 12019

170 377 19520.1

150 377 13506.5

70 270 13180

80 270 9842

70 270 12540

45 350 26443.5

120 214 6523.6

190 348 3902.6

120 219 5375.7

120 170 25240

120 250 11414

35 70 15820

Q (kW)

135

135

135

125.8

148

130

61.6

122.1 125.8

311.4

140.6 250

234

165.3

238.8

162.1

141.7

120 124.9

156.5

Figure 9. All utility heat is supplied low, and all utility cooling is supplied high.

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Roger Nordman

Heaters and coolers could also be scattered temperature-wise as in Figure 12.

In Paper I, piping costs were not included, but the studies conducted in Papers V and VI

(including piping costs) showed that releasing heaters and coolers close to the pinch was also

less expensive regarding piping, since less new units were required in those cases.

120 130 17710

45 130 12019

170 377 19520.1

150 377 13506.5

70 270 13180

80 270 9842

70 270 12540

45 350 26443.5

120 214 6523.6190 348 3902.6

120 219 5375.7

120 170 25240

120 250 11414

35 70 15820

Q (kW)

95

135

103.5

67.8 89.6

121.1

263.6

120 221.8

367.5

138.4

367.5

168.2

135 234234

141.5

238.8

135

136.8

Figure 10. All utility heat is supplied high, and all cooling is supplied low.

Releasing heaters placed high requires many rearrangements of existing units, insertion ofnew units, and poorer temperature driving forces resulting in large heat exchanger areas and

many units. The advanced curves give an indication of the degree of criss-cross in the HEN

via the relative placement of the AHLC/ACLC to the THLC/TCLC and EHLC/ECLC, but

cannot determine the origin of the criss-cross. The way in which the criss-cross is distributed

in the network, and how this affects the placement of utility heaters/coolers, are important to

know. Criss-cross can originate from trade-offs or simply from bad engineering. Different

streams have different heat transfer coefficients, distances between matching streams lead to

trading off piping versus temperature driving forces, matches may be forbidden, and pinch

violations have been accepted in order to reduce the number of units used. All theseconditions lead to deviations from the minimum area principle [31], thus resulting in criss-

cross (Figure 11). Criss-cross could also stem from process constraints such as the use of

medium-pressure steam for pulp cooking in a pulp mill, and economic constraints such that

the total installed cost (piping, area, units) of a heat exchanger is minimised. It can also come

from a poor grass-root design and changes during time of operation, thus using more area than

necessary. Some basic observations can now be made.

No matter what the reason for the criss-cross is, criss-cross always implies that toomuch area has been installed, compared to the minimum area requirements. This is a

good basis for retrofit.

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If the HEN is well designed from the beginning, making use of the temperaturedriving forces, few if any heaters are placed low in temperature.

In fact, criss-cross, even for legitimate reasons, is a prerequisite for heaters being placed low.

Therefore existing systems with identified criss-cross are interesting for retrofit. There couldexist systems with heaters placed high, still containing criss-cross heat exchange. Also in this

case more area than the minimum area requirements is installed.

Q (kW)

T

(C)

Heaters

Q (kW)

T

(C)

Heaters

Figure 11. Criss-cross heat exchange between the hot and cold CC.

The network in Figure 10uses less heat exchanger area than the one in Figure 9for the same

utility requirements, and is therefore a good grass-root network. From a retrofit perspective,however, economically feasible heat recovery projects are easier to find when heaters are

placed low in temperature. Since more area is installed for the same utility requirements, the

installed area is poorly utilized via criss-cross heat exchange. Another reason is that a lesser

number of units are affected when releasing a heater placed low rather than one placed high in

temperature.

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Roger Nordman

120 130 17710

45 130 12019

170 377 19520.1

150 377 13506.5

70 270 13180

80 270 9842

70 270 12540

45 350 26443.5

120 214 6523.6

190 348 3902.6

120 219 5375.7

120 170 25240

120 250 11414

35 70 15820

Q (kW)

135

135

135

125

125

256

61.6 70

122.1 125.8

120

141.9

125

234

165.3

238.8

164.2

140.9

298.2

138.1 162.1

210.7

311

Figure 12. Network with heaters and coolers placed both high and low (but still not violating pinch rules).

When a heat recovery retrofit is carried out, the Tmin will decrease. Which heat recoverylevel should be chosen can be guided by analysis of the demand curves for the process in

combination with the advanced curves. In practice, many levels of heat recovery are usually

investigated, and a road map of retrofit solutions can be made. A trade-off between two

choices for the same level of heat recovery is then possible:

Correct all violations by using the targeted Tmin (Tmin,HX = Tmin at the pinch)(Tmin,HX is also referred to as EMAT [87] ).

Correct a few large violations by using a smaller value ofTmin,HX than Tmin, andleave some violations, thus reaching the same QH.

Correcting a few large pinch violations could be more favourable than correcting many small

violations, since fewer units are affected and a lower total cost is reached [112].

Consequently, one should find the heat exchangers with the largest potential for improvement,

and accept a small Tmin,HX in these units. All corrections of pinch violation stemming fromheat transfer from above to below the pinch will eventually result in decreased utility

consumption. To break the violating match and replace hot utility, heaters placed low in

temperature (close to the pinch) generally require fewer changes (Figure 13) than heaters

placed high in temperature (Figure 14). The heat released by breaking the violating match

may in the latter case have to be shifted temperature-wise a number of times to replace utility,

thus affecting a number of existing units. This shifting requires new area to be installed in

existing heat exchangers due to lower temperature driving forces, and may also require

installation of new units.

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Q (kW)

T

(C)

Heater

Heater

Q (kW)

T

(C)

Heater

Heater

Figure 13. By breaking the match that transfers heat through the pinch, a heater placed low is released

(dotted line indicates a new match).

When releasing a heater placed high requires new units, the probability of expensive pipingalso increases, since the hot streams that can be used for heat exchange may be far away from

the cold stream where the heater was released.

A worst case would be that in addition to the above-mentioned difficulties, matches to a

number of process streams are required to release one single heater. This not only implies

more units, but it also makes the network a lot more complex and hard to control. The path

size according to [87] increases when heaters are placed high rather than low, thus

complicating the retrofit.

Q (kW)

T

(C)

Heater

Q (kW)

T

(C)

Heater

Figure 14. Shifting heat to release a heater placed high requires many shifts, resulting in many heat

exchanger modifications.

Coolers above the pinch and heaters below the pinch are pinch violations. If a violating cooler

is placed above a heater, the cooler and the heater could be partly or fully unloaded with a

process-to-process heat exchanger. If no heaters are below the cooler, the heat released by

removing the cooler must be shifted in temperature until the heat can be utilised. Replacing

heaters placed below the pinch follows the same discussion as for coolers above the pinch.

The highest potential for cost-effective retrofit projects occurs when heaters are placed lowandcoolers are placed high as discussed above. By releasing a heater low, not only are fewer

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Roger Nordman

units affected, but unnecessary piping could also be avoided since fewer new units need to be

inserted. In conclusion, by including heaters low in a retrofit project, the total project cost is

thesis roger nordman kappa

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