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Chemical engineering Thesis and Dissertations

2020-03-11

Design of Heat Exchanger Network

Using Pinch Analysis Method: case

study on Awash Melkassa sulfuric acid

production factory

Tesfay, Hailay

http://hdl.handle.net/123456789/10190

Downloaded from DSpace Repository, DSpace Institution's institutional repository

BAHIR DAR UNIVERSITY

BAHIR DAR INSTITUTE OF TECHNOLOGY

SCHOOL OF RESEARCH AND POSTGRADUATE STUDIES

FACULTY OF CHEMICAL AND FOOD ENGINEERING

MSc Program in Process Engineering

Design of Heat Exchanger Network Using Pinch Analysis Method: case study

on Awash Melkassa sulfuric acid production factory

By

Hailay Tesfay Sheka

Bahir Dar, Ethiopia

March, 2019

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Design of Heat Exchanger Network Using Pinch Analysis Method: case study

on Awash Melkassa sulfuric acid production factory

Hailay Tesfay Sheka

A Thesis in partial fulfillment of the requirements for the Degree of Master of Science in

Chemical Engineering (Process Engineering specialization)

Presented to the faculty of chemical and food engineering, Bahir Dar Institute of

Technology, Bahir Dar University

Supervised by: Zenamarkos Bantie (PhD)

Bahir Dar, Ethiopia

March, 2019

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© 2019

Hailay Tesfay Sheka

ALL RIGHTS RESERVED

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To my Family

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ACKNOWLEDGMENT

I thank my God for giving me strength and guidance to go through this thesis work.

I would like to express my deepest and heartfelt thanks to my advisor Zenamarkos Bantie (PhD)

for his unreserved and continuous assistance while doing this thesis. His encouragement,

excellent guidance, creative suggestions and critical comments have greatly contributed to this

thesis.

I wish to express my genuine appreciation to Nigus Gabbiye (PhD) for his unlimited, supports,

directions and vital comments from the initiation of this work. And I would like to say thanks to

Getu Adane (PhD candidate) for giving me important idea on process integration and

optimization especially on pinch analysis and Abshik Dutta (PhD) for making me to have deep

knowledge and more confidence on pinch analysis for heat exchanger network.

Constructive comments by questionnaire and interview respondents are thankfully

acknowledged. In particular, I want to thank Mr. Solomon Ake (product and operation

directorate), Gemechu Kumbi (operator), and others (Mr. Getachew Habtewold and Ms. Rahel

tsigie and Tigist Ngusie from different department of the company) for giving important data of

the plant. Receiving their kind respond, useful information and documents really made me feel

warm and motivation.

Moreover, Special thanks go to my best friends Feyissa Bekele, Lukas Gelibo, Tsehaye Yigzaw

and Tsegaluel Kindeya who added various colors on my school life.

Parental consideration and support is the last but not the least, my thanks goes to my parents who

have encouraged and inspired me for the successful completion of this thesis and provided me

with considerable continuous help in my work.

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ABSTRACT

This project uses pinch analysis techniques for the heat exchanger network design by aspen

energy analyzer software focusing on sulfuric acid production plant. The requirement of energy

in any processing industry is a most wanted utility. The increasing cost of energy and

environmental concerns are forcing industries to look for methods of reducing energy

consumption and wastage. As energy is the key for economic growth and is vital to the modern

economy, improving energy efficiency is one of the most important methods for cost saving and

tackling of climate change. In Awash Melkassa aluminum sulphate and sulfuric acid factory,

production of sulfuric acid is one of the most energy intensive processes. The aim of heat

exchanger network (HEN) design is to minimize the use of external utilities by increasing energy

recovery by transferring of heat from hot process stream to cold process stream applying the

principles of the first and second law of thermodynamics. In this study, the problem is threshold

problem which requires only cold utility.

Energy and economic savings were realized by pinch analysis. In Awash Melkassa aluminum

sulphate and sulfuric acid production factory, the amount of cold utility requirement is

167.69KW and it remains constant as ΔTmin varies up to the threshold temperature (13°C),

which is the optimum temperature value. The heat exchanger network design resulted in energy

savings of 100% for hot utilities, 42.83% for cold utilities and 59.97% from total utility

compared with the current energy consumption of the plant. Profitability analysis of the designed

HEN was made and found with a payback period and rate of return of 1.92 years and 42.77%

respectively.

The result of the study shows that design of HEN by pinch analysis for Awash Melkassa sulfuric

acid plant with new heat exchanger arrangement proves that energy integration can lead to a

minimum energy (utility) consumption, maximum energy recovery and financial savings of the

plant.

Keywords: Energy recovery, Pinch analysis, HEN, Aspen energy analyzer, Threshold problem

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TABLE OF CONTENTS

DECLARATION ............................................................................................................................. i

ACKNOWLEDGMENT................................................................................................................ iii

ABSTRACT .................................................................................................................................. vii

TABLE OF CONTENTS ............................................................................................................. viii

LIST OF ACRONYMS .................................................................................................................. x

LIST OF SYMBOLS ..................................................................................................................... xi

LIST OF FIGURES ...................................................................................................................... xii

LIST OF TABLES ....................................................................................................................... xiii

CHAPTER ONE ............................................................................................................................. 1

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

1.1 Back Ground ..................................................................................................................................... 1

1.2. Problem statement .............................................................................................................................. 3

1.3 Objectives ......................................................................................................................................... 4

1.3.1General objective .......................................................................................................................... 4

1.3.2 Specific objectives ....................................................................................................................... 4

1.4 Scope of the study ............................................................................................................................ 4

1.5 Significance of the study ................................................................................................................. 4

CHAPETR TWO .......................................................................................................................................... 6

LITERATURE REVIEW ............................................................................................................................. 6

2.1. Process description of sulfuric acid production plant ................................................................ 6

2.2. Pinch Analysis ................................................................................................................................. 8

2.2.1 Data extraction ........................................................................................................................... 10

2.2.2 Capital- energy cost trade off ..................................................................................................... 11

2.2.3 Composite Curves ...................................................................................................................... 14

2.3 Heat exchanger network ............................................................................................................... 15

CHAPTER THREE .................................................................................................................................... 19

METHODOLOGY ..................................................................................................................................... 19

3.1 Data Extraction............................................................................................................................... 19

3.1.1 Assumptions ............................................................................................................................... 20

3.1.2 Extraction of Process Stream ..................................................................................................... 20

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3.2 Data Feed to Aspen Energy Analyzer ......................................................................................... 21

3.3 Targeting ......................................................................................................................................... 22

3.3.1Energy targeting .......................................................................................................................... 22

3.3.2 Units Targeting .......................................................................................................................... 23

3.4. Stream splitting ............................................................................................................................. 25

CHAPTER FOUR ....................................................................................................................................... 28

RESULTS AND DISCUSSION ................................................................................................................. 28

4.1 Composite curves ........................................................................................................................... 28

4.2 Effect of ∆Tmin ............................................................................................................................. 29

4.2.1 Effect of ∆Tmin on utilities ....................................................................................................... 29

4.3 Heat Exchanger Network .............................................................................................................. 30

4.3.1 Network interval temperature calculations ................................................................................ 34

4.3.2 Optimization Of ∆Tmin Value ................................................................................................... 34

4.3.3 Optimization of Heat Exchanger Network ................................................................................. 35

4.3.4 Network performance and controllability analysis .................................................................... 38

4.3.5 Potential heating and cooling savings of the network ................................................................ 41

4.4 Network Economic Analysis ........................................................................................................ 41

4.4.1 Network Cost Estimation ........................................................................................................... 41

4.4.2 Network Profitability Analysis .................................................................................................. 46

CHAPTER FIVE ........................................................................................................................................ 51

CONCLUSION AND RECOMMENDATION .......................................................................................... 51

5.1 CONCLUSION ................................................................................................................................. 51

5.2 RECOMMENDATION .................................................................................................................... 52

REFERENCES ........................................................................................................................................... 53

APPENDICES ............................................................................................................................................ 57

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LIST OF ACRONYMS

AEA Aspen energy analyzer

AMASSASC Awash Melkassa Aluminum Sulfate and Sulfuric Acid Share Company

CC composite curve

DOF Degree of freedom

FCC Fixed capital cost

GCC Grand composite curve

HEN Heat exchanger network

LMTD Logarithmic mean temperature difference

MAR Minimum acceptable rate of return

MER Maximum energy recovery

OC Operating cost

PBP Payback period

PDM pinch design method

PI Process integration

PL Plant life

ROR Rate of return

TCC total capital cost

TDC Total depreciable cost

WCC Working capital cost

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LIST OF SYMBOLS

∆H Enthalpy change (Heat Load) of streams (KW)

∆Tmin Minimum Temperature Difference (oC)

TS Supply Temperature (oC)

TT Target Temperature (oC)

ṁ Mass flow rate (Kg/s)

Q heat transfer load (KW)

S Number of independent components

L Number of loops

NC Number of cold process streams

NH Number of hot process streams

U Minimum number of units

CP (m*Cp) Heat capacity (KJ/soC)

QHmin Minimum energy requirement for hot utility (KW)

QC min Minimum energy requirement for cold utility (KW)

CCU cold utilities costs ($/KJ)

HCU Hot utilities costs ($/KJ)

A heat transfer area (m2)

NShell number of heat exchanger shells

a installation cost of heat exchanger ($)

b duty related cost set coefficient of the heat exchanger

c area related cost set coefficient of the heat exchanger

D Depreciation

V Original value of equipment

Vs Salvage value of equipment at the end of service life

i Annual interest rate

GP Gross profit

Pc Production cost

I Income

NP Net profit

HX Heat exchanger

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LIST OF FIGURES

Figure 2.1 Simplified process flow diagram of Awash Melkassa sulfuric acid production plant .. 8

Figure 2.2 composite curves for both hot and cold streams ......................................................... 15

Figure 2.3 Onion skin diagram for organization of a chemical process and hierarchy of analysis

....................................................................................................................................................... 16

Figure 3.1 Schematic matching of heat loads for process streams ............................................... 24

Figure 3.2 Grid diagram representation for process streams ........................................................ 25

Figure 3.3 Flow diagrams for splitting of streams ........................................................................ 26

Figure 3.4 Grid diagram representation of process streams after stream splitting ....................... 27

Figure 4.1 Composite Curves ....................................................................................................... 28

Figure 4.2 Grand composite curves .............................................................................................. 29

Figure 4.3 Utility composite curves .............................................................................................. 29

Figure 4.4 Effect of ∆Tmin on utilities ......................................................................................... 30

Figure 4.5 Grid diagram of HEN for process to process heat transfer ......................................... 32

Figure 4.6 Heat exchanger networks for MER design .................................................................. 33

Figure 4.7 Loop in designed HEN ................................................................................................ 37

Figure 4.8 Optimized HEN design................................................................................................ 37

Figure 4.9 Detail information of heat exchanger .......................................................................... 38

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LIST OF TABLES

Table 3.1 Process streams data ..................................................................................................... 20

Table 3.2 Process stream tab ......................................................................................................... 21

Table 3.3 Utility stream tabs ......................................................................................................... 22

Table 3.4 Targets view tab ............................................................................................................ 24

Table 4.1 Unsatisfied streams ....................................................................................................... 32

Table 4.2 Exchangers interval temperatures in the network before optimization ........................ 34

Table 4.3 Optimization of ΔTmin value ....................................................................................... 35

Table 4.4 Network performance before optimization ................................................................... 38

Table 4.5 Network performance after optimization ...................................................................... 39

Table 4.6 Network controllability status before optimization ...................................................... 40

Table 4.7 Network controllability status after optimization ......................................................... 41

Table 4.8 Potential heating and cooling savings ........................................................................... 41

Table 4.9 Economics tab view for heat exchanger capital cost index parameters ........................ 42

Table 4.10 Parameters for heat exchanger E-129 ......................................................................... 43

Table 4.11 Total annualized fixed capital cost of heat exchangers .............................................. 44

Table 4.12 Utility streams tab for cost index of cold utility ......................................................... 45

Table 4.13 Energy consumed and cost index of cold utility streams............................................ 46

Table 4.14 Energy saved and cost index of cold utility streams ................................................... 47

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CHAPTER ONE

INTRODUCTION

1.1 Back Ground

Energy use in the world today is important for the world’s economic. However, the increasing

cost of energy and stricter environmental legislation require industrial firms to seek ways to

reduce their energy needs. Process integration has played an important role in seeking ways to

improve resource utilization (Rokni, 2016). Design and optimization procedures have the trend

to see the configurations by which less energy consumption can be attained (Corredor, 2012;

Leni C. Ebrada et al, 2014).

The availability of economical, environmentally friendly abundant energy is not always assured.

This is a concern as secure reliable and reasonable energy is crucial to both economic stability

and development (Musonye et al, 2014). In an economic environment where cost of production

is a major driving force, any technique of reducing cost exposure has to be of interest. In addition

there is also the issue of the environmental impact of energy utilize (Anantharaman, 2011;

Rokni, 2016). Process integration (PI) is a branch of process intensification and holistic approach

to process design, retrofitting, and operation of industrial plants with applications focused on

resource conservation, pollution prevention and energy management. Energy integration is a part

of PI which concerns about global allocation, generation, and exchange of energy during the

process (Mohanty, 2010).

Many strategies have been implemented, in order to reduce energy consumption, such as

changing of raw materials and production process path way, reusing and recycling waste

material, and recovering heat in the process etc (Anantharaman, 2011). In the field of process

integration the application of energy integration focuses on heat recovery between process

streams in order to save energy, minimize cost and environmental impacts (Rokni, 2016).

Most chemical processes need the heating and cooling of certain process streams before they

enter another process unit or released into the environment. This heating or cooling requirement

can be satisfied by matching of these process streams with each other and by providing external

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source of heating or cooling(Gadalla, 2015). These external sources are called utilities, and they

add additional cost to the operating cost of the plant. In industries, heat exchangers are use to

change the thermal condition and to minimize the energy consumption of the given process

(maximizes the energy recovery within the process and minimizes the use of external energy

sources) (Beabu K. Piagbo and Kenneth K. Dagde, 2013; Rokni, 2016).

In processes where heating and cooling is characterizing the processing operations pinch

technology is an outstanding method for energy saving (Musonye et al, 2014).Pinch technology

was originally developed since 1970s and it began to represent a new set of thermodynamically

based methods that guarantee minimum energy stage in design of heat exchanger networks

(Chouaibi Fathia et al, 2016; Mohanty, 2010).

Heat exchanger network synthesis (HENS) is one of the most extensively studied and single

most important industrial application area for process integration. Main aspect of HENS can be

found in the fact that most industrial processes involve transfer of heat, either from one process

stream to another process stream or from a utility stream to a process stream. Therefore, the

target in any industrial process design is to maximize the process to process heat recovery and to

reduce the utility consumptions (K. Singh and R. Crosbie, 2011; K. S. Telang et al, 2001).

Heat recovery between hot and cold streams is limited to the shape of the composite curves and

the fact that heat can only be transferred from higher to lower temperature. The minimum

allowed temperature difference (∆Tmin) is an economic parameter that indicates a near optimal

tradeoff between operating and capital cost (M.U.Pople and Vishal G. bokan , 2015; Gadalla,

2015).

Therefore, pinch analysis is applied as a method to network heat exchangers in the case of

sulfuric acid production plant, Awash Melkassa Aluminum Sulfate and Sulfuric Acid Share

Company (AMASSASC) because of its simplicity of its basic concepts and it has the ability to

identify performance targets before the design step is started. These target procedures help in the

evaluation of alternative HEN designs, guide the design in the right direction and help to search

for an optimum design.

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1.2. Problem statement

Energy is the most required utility in process industries. One of the challenges facing industrial

plants in reaching profitability is the minimization of costs related to utility utilization. In the

production of sulfuric acid under Awash Melkassa aluminum sulphate and sulfuric acid factory,

there are streams that need, either cooling or heating before they enter or leave to another process

unit. The factory uses external utilities for the purpose of cooling and heating systems. Energy as

utilities charges an additional operating cost for the company and at the end of the utility usage

they let to discharge as waste or waste heat to the environment but some is recycled as utility to

other process in the plant. As a result of this, external energy cost and a waste discharge to the

environment are specific problems which challenge the company.

Saving these utilities or minimizing the usage of these utilities is one method of cost

minimization in a process industry. These problems could be solved by applying pinch analysis

method identifying the process stream and utility stream in the process. In order to accomplish

the minimum usage of heating and cooling utilities, it is necessary to maximize the heat

exchange among process streams. Heat exchangers can be used to recover some of the demanded

heat while external heaters and coolers can be used to achieve the temperature demand of the

process streams.

Therefore, this research is intended to address a solution of identifying process streams and

utility streams, eliminating or minimizing of the external utilities and minimizing of the impact

on the environment. Thus, pinch analysis is applied to determine the potential reductions in both

the heating and cooling requirements for the process house of sulfuric acid plant by aspen energy

analyzer software to design the heat exchanger network.

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1.3 Objectives

1.3.1General objective

The main objective of this work is to design heat exchanger network using pinch analysis

method in the case of sulfuric acid production factory.

1.3.2 Specific objectives

To extract streams data, identify hot, cold and utility streams and extract process streams

To set minimum temperature approach (∆Tmin) value and perform targeting

To perform heat exchanger network (HEN) by aspen energy analyzer

To optimize the designed heat exchanger network

To perform network economic analysis

1.4 Scope of the study

The primary focus of this study is the conversion section due to its large energy consumption and

it includes the acid cooler section as well as the water pre heating sections but, this study doesn’t

consider the waste heat boiler because the company itself uses as primary steam source and its

cooling temperature range is very high which can make the heat capacity non linear with

temperature relative to the other hot streams.

This work begins by data extraction (both process and utility steams) from the plant followed by

extraction of process streams. All process streams are defined on the basis of their start and

target temperatures (T), heat capacity (Cp) and mass flow rate (m) in the form required for pinch

analysis and this data will be analyzed by aspen energy analyzer. Selection of ∆Tm in initial

value and targeting will perform prior to the heat exchanger network design. HEN design,

optimization of the designed HEN and network cost analysis are part of this work.

1.5 Significance of the study

This work provides information on the application of pinch analysis for heat exchanger network

design for case production of sulphuric acid. It applies to maximize heat recovery and minimum

use of utilities in the plant and support and improves environmental performance and

management. Therefore, it could be beneficiary for different process industries for these who

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have different steams that need heating and cooling utilities and to those who involve in the area

of energy analysis and optimization.

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CHAPETR TWO

LITERATURE REVIEW

2.1. Process description of sulfuric acid production plant

The process for production of sulphuric acid consists of three sections, which are the feed

preparation section, the reactor section, and the absorption section. In the feed preparation

section, molten sulfur feed is combusted with dry air in the sulfur burner. The reaction is

exothermic and goes to completion. In the sulfur burner, the dry compressed air reacts with

molten sulfur to produce sulfur dioxide. The sulfur dioxide, along with nitrogen and unreacted

oxygen enters the waste heat boiler (K. S. Telang et al, 2001).

The second section of the contact process plant is the reactor section. The reactor consists of four

beds packed with two different types of vanadium pent oxide catalyst. In the reactor section, the

gas mixture from the feed preparation section is further reacted in the fixed catalyst beds to

produce sulfur trioxide and heat. The reaction is exothermic and the equilibrium conversion

decreases with the increase in reaction temperature. For this reason, the process uses four packed

beds, and heat exchangers between each bed remove the produced energy to reduce the

temperature. Removing reaction heat from each reactor increases the conversion of sulfur

dioxide to sulfur trioxide and this removed heat is used to produce steam (K. S. Telang et al,

2001).

Also, the equilibrium conversion increases by decreasing the concentration of sulfur trioxide and

an inter-pass tower is used to absorb and remove sulfur trioxide from the gas stream between the

second and the third catalyst beds. This design ensures higher conversion in the reactor beds.

The final section of the contact process plant is the absorber section. In this section the sulfur

trioxide is absorbed from the reaction gas mixture into 96 %wt sulfuric acid to produce a more

concentrated acid (R.J. Forzatti et al, 2013).

Sulfuric acid production is one of the most heat intensive processes. There are streams that need

heating or cooling to be in their required temperature. Since the reaction in the bed is exothermic,

the equilibrium conversion decreases with the increase in reaction temperature. The process uses

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four packed beds and heat exchangers between each bed to remove the energy generated to

reduce the temperature and this consumes utilities for heat exchange (K. S. Telang et al, 2001).

Sulfuric acid production plant uses utilities like steam, water; fuel and compressed air are part of

the service facilities of the plant. The process requires water for its cooling systems. Cooling is

needed to reject surplus heat which is not recovered as steam. Minimizing water consumption

lowers the cost of sourcing reliable supplies of water and the cost associated with treating

effluent streams. It also helps improve the sustainability of the acid plant operation by reducing

the impact on surrounding communities (R.J. Forzatti et al, 2013; kumbi, 2018).The cooling

systems used in sulfuric acid plant are at the boiler section, adsorption section, economizer and

acid cooling. Cold water that is preheated by water pre heater to rise its temperature and then it

passes to the waste heat boiler and bono boiler Sulfuric acid production plant also uses fuel and

compressed air as utility for bono boiler and first bed output cooling section, respectively. The

steam systems used at the plant are for the sulfur melting and burning section, water pre heating

section, bono boiler section which consume steam as utility (K. S. Telang et al, 2001; Chouaibi

Fathia et al, 2016).

Currently, Awash Melkassa sulfuric acid production plant consumes 293.31kw of cold utility

around the beds and acid cooling and 125.62kwof hot utility at the water pre heater and steam

production section respectively. The plant uses steam recycling system to reuse some of the

utilities. The acid plant steam system is designed to recover the heat generated by the exothermic

reactions. Heat is also recovered from the sulphur burner by producing of saturated steam in a

waste heat boiler. Saturated steam from the boiler and bed exchangers flows to steam drum and

is used as steam input to other processes like sulfur melting and water preheating section. But

excess steam is produced as waste heat. This excess steam is one of the byproducts of sulfuric

acid plant. This waste heat from sulfuric acid production can be eliminated or minimized from its

source by transferring heat from the hot process streams to the cold process streams within the

process itself instead of consuming external utilities. Therefore, saving utilities or minimizing the

usage of these utilities is one of the most needed practices in a processing industry.

The process flow diagram for sulphuric acid is shown in the figure 2.1 below.

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Figure 2.1 Simplified process flow diagram of Awash Melkassa sulfuric acid production plant

2.2. Pinch Analysis

Process integration (PI) is a branch of process intensification and holistic approach to process

design, retrofitting, and operation of industrial plants, with applications concerns on energy

management, resource conservation, and pollution prevention. Process integration has two parts:

energy integration, deals with the global allocation, generation, and exchange of energy during

the process while mass integration provides a basic understanding of the global flow of mass

within the process and optimizes the allocation, separation, and generation of streams and

species (Mohanty, 2010; Kemp, 2007; Smith, 2005).

PI can lead to a substantial reduction in the energy consumption of a process. In recent years, a

lot of work has been done on developing methods for investigating energy integration and the

efficient design of heat exchanger networks. PI deals mainly with the optimal use of heat and

utilities and it includes environmental protection, controllability, safety and operability

(M.U.Pople and Vishal G. bokan , 2015; K. S. Telang et al, 2001; Mohanty, 2010).

The three major features of PI methods are heuristics methods, thermodynamics methods (pinch

analysis), and optimization techniques. There is significant overlap between the various methods

and the trend today is strongly towards methods using all three features mentioned above.

Among the PI methodologies, pinch analysis is now the most widely used method, due to its

simplicity of basic concepts (Mohanty, 2010).

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Even though several new methods for the synthesis and optimization of HEN have been

proposed, pinch analysis is the most complete and reliable thermodynamic method. Pinch

analysis is used for minimizing energy consumption of processes by calculating

thermodynamically feasible energy targets (minimum energy consumption) and achieving them

by optimizing heat recovery systems, energy supply methods, and process operating conditions

(Anna Gunnarsson and Carin Magnusson, 2011; Mohanty, 2010).

Pinch analysis shows a simple methodology for systematical analyzing of industrial processes

and the utility systems with the help of the first and second law of thermodynamics (Barnes,

2013). First law of thermodynamics deals with the energy equation to calculate the enthalpy

change of the streams passing through the heat exchanger and the second law determines the

direction of heat flow. That is, heat energy may only flow in the way of hot to cold and this

prohibits temperature crossovers of the hot and cold streams profiles through the exchanger unit

(Musonye et al, 2014; Je M. Smith et al, 2001).

Pinch technology helps to find the optimal network of heat exchangers, external coolers and

heaters with respect to the capital and operating cost. The maximum heat that can be transferred

in a heat exchanger is limited to the minimum allowed temperature difference (∆Tmin) between

hot and cold streams. The temperature level at which ∆Tmin is observed is pinch point and the

analysis to find this temperature with respect to the laws of thermodynamic is pinch analysis

(Rokni, 2016; March, 1998).

The complete heat exchanger network design by pinch technology has four stages (Deepa H

A,and Ravishankar R, 2015; Mirjanakije Vanin et al, 2004):

Data Extraction stage: The main purpose of this stage is to identify the process streams inside the

plant and potential utilities, which could be used for building of heat exchanger network. This is

a primal and is the most important step in pinch design.

Targeting stage: Where is possible to quantify targets for minimum utility requirements,

minimum number of units and minimum area ahead of the actual design step. This phase is used

to find the optimum level of heat recovery, by balancing energy and capital costs.

Design stage: Where a preliminary heat exchanger network, that achieves the previously defined

performance target, is established.

Optimization: The maximum energy recovery HEN from the preliminary design is simplified

and improved economically. The strict decomposition at the pinch usually results in networks

10

with at least one unit more than the minimum number. Manipulating with heat load loops and

paths, stream splitting and restoring ΔTmin the final solution is improved in order to attain

amore cost optimal HEN.

2.2.1 Data extraction

All the data obtained from plant measurement, and data gathered from the system may not be

important for pinch analysis. It is thus necessary to identify and extract only the information that

truly captures the related sources for hot and cold streams and their interactions with the process.

The starting point for a pinch analysis is to identify in the process streams, that needs to be

heated and streams be cooled. And this identifies the streams, flow rates, thermal properties,

phase changes, and the temperature ranges through which the streams to be heated or cooled.

This can be after mass balances have been completed and temperatures and pressures have been

established for the process streams and lastly energy quantities can be computed by

thermodynamic calculations (Mohanty, 2010).

After identifying the reliable process streams, the next step is to extract the hot and cold streams

in the form required for pinch analysis. Data extraction is the most time consuming task of a

pinch analysis step and it is essential that all the heating, cooling, and phase changes in the

process be identified. In existing processes, accurate information may not be readily available,

and the researcher has to go into the field to obtain it (Barnes, 2013; Anna Gunnarsson and Carin

Magnusson, 2011).

Heuristic rules have been developed as procedure and here are the most relevant rules:

Streams cannot mix at different temperatures values, such mixing may involve cross pinch heat

transfer, and should not become a fixed feature of the design. During data extraction, the

effective stream temperatures are more important than the actual stream temperatures. As heat

capacity rate (CP) is a function of temperature, the enthalpy change of some streams is

considerably nonlinear. This is particularly true when there is phase changing streams such as

condensing/vaporizing streams. In such a situation, sticking to just one value of CP might direct

to inaccurate results. Utility streams (steam, cooling water, refrigerant, and cooling air) are not

included as process stream. And distinguish between soft and hard stream data is quite important

in the sense that some stream data must be considered as hard or soft specifications. An inlet

temperature to a reactor or other unit operation must often be regarded as a hard specification

(Gorica R. Ivanis et al, 2015; Mohanty, 2010).

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The essential type of data for heat integration projects is obviously related to the need for

heating, cooling, evaporation and condensation in the process. In short, what is needed is a

quantification of the needed enthalpy changes of the process streams. From thermodynamics,

change in the total enthalpy flow (H (kW)) that a process stream undergoes when changing

conditions can be obtained using equation 1 (Rokni, 2016; Kemp, 2007).

∆𝐻 = ṁ. 𝑑ℎ eq 1

Where, ṁ is mass flow rate (kg/s) and h is specific enthalpy (kJ/kg), giving change in enthalpy

flow. Enthalpy is a complicated function of stream pressure, temperature and composition. In

energy integration, a process stream is defined as one that does not change mass flow rate or

composition. Whenever such changes take place, a new process stream is introduced. If we

assume constant mass flow rate and stream composition, and ignore the effect of pressure on

enthalpy, then equation 1 is simplified to equation 2 (Rokni, 2016; Kemp, 2007).

∆𝐻 = ṁ . 𝑐𝑝. 𝑑𝑇 𝑒𝑞(2)

Where, cp is the specific heat capacity at constant pressure (kJ/kg.K). In order to replace

numerical integration by simple summation, the assumption of a constant or a piece wise linear

relation between temperature and enthalpy has been extensively used in pinch analysis. If it is

assumed constant, and the supply and target temperatures of a process stream are denoted as Ts

and Tt respectively, as it shows in equation 3 (Rokni, 2016; Kemp, 2007).

∆H = ṁ. cp. dT

Tt

Ts

= Cp. Tt − Ts eq(3)

The heat capacity flow rate (CP) is the mass flow rate multiplied by specific heat capacity of the

fluid for the given temperature range. The heat load is the difference in enthalpy between the

supply and target stream properties, the maximum amount of heat that could be transferred to or

from a stream in a given temperature range and it determines the possible amount of heat transfer

between given streams and how much external heating or cooling is required (Barnes, 2013; Je

M. Smith et al, 2001).

2.2.2 Capital- energy cost trade off

Targets for heat recovery are limited to the specification of a minimum allowed temperature

difference for heat transfer, which is an economic parameter for the tradeoff between operating

12

and capital cost. Targets for minimum external heating and minimum external cooling can be

obtained by graphical or numerical methods for a given value of this parameter (Anna

Gunnarsson and Carin Magnusson, 2011; Leni C. Ebrada et al, 2014).

The design of any heat transfer equipment must always adhere to the second law of

thermodynamics that prohibits any temperature crossover between hot and cold stream. A

minimum heat transfer driving force must always exist for a feasible heat transfer design. Thus,

the temperature of the hot and cold streams at any point in the exchanger must always have a

minimum temperature difference (ΔTmin). This ΔTmin value represents the bottleneck in the

heat recovery (Rokni, 2016; March, 1998).

For a given value of heat transfer load (Q) and for smaller values of ΔTmin area requirements

increase. For higher values of ΔTmin the amount of heat recovery in exchanger decreases and

demand for external utilities is high. Generally, the optimum value for ∆Tmin is in the range of 3

to 40 oC for heat exchange networks, but it is unique for each network and needs to be

established before the pinch analysis is done. Thus, the selection of ΔTmin has its effect for both

capital and energy costs. To begin the process, an initial ΔTmin value is chosen and pinch

analysis is carried out. Typical ΔTmin values based on experience are available in literature.

ΔTmin for chemical plants ranges from 10-20 °C (K. Singh and R. Crosbie, 2011; Barnes, 2013;

Gorica R. Ivanis et al, 2015).

The physical meaning of ∆Tmin is that an ideal heat transfer within a heat exchanger that cool

the hot stream down to the minimum temperature difference of Tmin equal to zero. It means

that the heat exchanger area is infinite, Tmin approach to zero andheat exchanger size and

price approach to finite value. This of course is not possible in practical applications and Tmin

different from zero is always valid. To have small size of heat exchanger to an acceptable level

with reasonable price, it is assumed that there always exists a temperature difference, preferably

Tmin equal to 10 C for initial guess. There is a tradeoff between the capital and energy costs

to find the optimum value of ΔTmin by intersection of the capital and energy cost graphs to

determine the minimum cost in new designs. Therefore, the optimum ∆Tmin must be selected for

the best cost savings. The point at which the energy cost and the heat exchanger cost are equal

identifies the optimal ΔTmin (Deepa H A,and Ravishankar R, 2015; Douglas, 1988).

13

In pinch analysis there are three types of problems, these are single pinch, multiple pinch and

threshold problem and the capital-energy cost trade off for each problem is explained below (K.

Singh and R. Crosbie, 2011; Mohanty, 2010). Both single and multiple pinches are pinched

problems and have pinch point. The temperature level at which minimum allowable temperature

difference is observed in the process is pinch point. The pinch defines the minimum driving force

allowed in the exchanger unit (K. Singh and R. Crosbie, 2011; Anantharaman, 2011).The

minimum temperature difference between the hot and cold composite curves influence the pinch

temperature, the required external utilities, and the size of the heat exchangers. However, only

the heat exchangers that exist at the pinch point need to operate at ∆Tmin, because this is the

most constrained area of the network (M.U.Pople and Vishal G. bokan , 2015; K. Singh and R.

Crosbie, 2011).

As ∆Tmin is increased, the difference between the hot and cold composite curves increases,

which increases the energy required by external utilities. Due to this, heating and cooling duties

increase as the hot and cold composite curves are separated by a larger ΔTmin (Rokni, 2016; J.

Khorshidi et al, 2016).

The point on the composite curve where the heat flow is equal to zero is called the pinch point,

and the corresponding temperature is pinch temperature. The pinch divides the process into two

thermodynamically separate regions to above the pinch and below the pinch. Above the pinch,

only hot utility is required, but cold utility is required below the pinch.

However, a pinch does not occur in all HEN problems to divide the problem into two parts.

Certain problems remain free of a pinch until the minimum allowed driving force; ∆Tmin is

increased up to or beyond a threshold value ∆Tthresh (Mohanty, 2010). Such problems are kind

of threshold problems. Threshold problems needs only a single thermal utility, either hot or cold

but not both over a range of minimum temperature difference ranging from zero to threshold

temperature. The concept of a threshold problem can be exemplified as when heat is transfer

from very hot stream to a very cold stream. Although, threshold problems do not have a process

pinch, it is interesting to note that threshold problems are quite common in practice (Kemp, 2007

Akpa, J. G. and Okoroma, J. U., 2012).

The utility requirements remains constant under any specification of∆Tmin, providing the

specified ∆Tmin is less than the smallest temperature driving force in the exchanger. However,

when ∆Tmin exceeds ∆Tthresh there is need for both heating and cooling utility. Because, a

14

complete heat exchange between the two streams is no longer feasible without violating ∆Tmin.

A borderline situation occurs when at the specified ∆Tmin equals the threshold value. The

problem has become pinched, but the utility usage is the same as for lower values of ∆Tmin (K.

Singh and R. Crosbie, 2011; Mohanty, 2010). This borderline case is a general feature of a

threshold problem. When ∆Tmin is less than ∆Tthresh the result is no pinch and only one utility

is required, and if ∆Tmin equals ∆Tthresh a pinch is introduced into the problem and there is no

increase in utility usage. The utility usage rise only when the minimum allowed driving force is

increased above ∆Tthresh. Both hot and cold utilities are then required and then the problem

becomes pinched problem.

Threshold problems are divided into two broad categories for purpose of design. In the first type

when the closest temperature approach between the hot and cold composites is at the non‐utility

end and the curves diverge away from this point and in the second type, there is an intermediate

near‐pinch, which can be identified from the composite curves as a region of close temperature

approach (Mohanty, 2010; S B Thakore and B I Bhatt , 2007).

Pinch design method (PDM) has a design logic that is to start the design where the problem is

most constricted. If the design problem has a pinch then the problem is most constricted at the

pinch and thus it should start from pinch point moving away from it. If the most restricted part is

at the non‐utility end then it should start from there. The optimum value appears either when

∆Tmin is at Tthreshold or more than Tthreshold. But it never happens when ∆Tmin less than

Tthreshold. Because when ∆Tmin less than Tthreshold, the operating costs are constant since

utility demand is constant (March, 1998; Smith, 2005).

2.2.3 Composite Curves

After data extraction phase is complete, the next step is drawing of hot and cold composite

curves. Composite curves are temperature verses enthalpy profiles of heat available in the hot

process streams and heat demands in the cold process streams with the help of graphical

representations (Je M. Smith et al, 2001).

Pinch analysis gives composite curves for systems, one composite curve for all hot and cold

streams respectively as it shows in figure 2.2 below. The point of closest approach between the

hot and cold composite curves and the point on the grand composite curve where the heat flow is

15

equal to zero is the pinch temperature where, the design is most constrained (M.U.Pople and

Vishal G. bokan , 2015; Anna Gunnarsson and Carin Magnusson, 2011).

The minimum amount of hot and cold utilities and maximum amount of heat recovery can be

found from the composite curves. The gap between the start of the hot and cold composite curves

is the minimum cold utility required and the minimum hot utility required is the gap between the

end of the hot and cold composite curves. This concept is based on vertical heat transfer in the

internal exchanger area (Barnes, 2013; Anantharaman, 2011).

Figure1.2 composite curves for both hot and cold streams

2.3 Heat exchanger network

A heat exchanger is heat transfer equipment that is used for transfer of thermal energy between

two or more fluids available at different temperatures. Typical applications involve heating or

cooling of a fluid stream of concern and evaporation or condensation of fluid streams (Gadalla,

2015; Beabu K. Piagbo and Kenneth K. Dagde, 2013; Douglas, 1988). The importance of heat

exchangers has increased over the past quarter century immensely from the viewpoint of energy

conservation, conversion, recovery, and successful implementation of new energy sources. Its

significance is also increasing from the stand point of environmental concerns such as thermal

pollution, air pollution, water pollution, and waste disposal. Heat exchangers are used in the

process, power, transportation, air-conditioning and refrigeration, heat recovery, and

manufacturing industries, as well as they are key components of many industrial products (K. S.

Telang et al, 2001; S B Thakore and B I Bhatt , 2007). Heat transfer is energy transfer because of

a temperature difference in a medium. Heat exchanger in many industries, uses as part of the

process to change the thermal condition and to reduce the energy consumption (maximize the

16

energy recovery within the process or to reduce the use of external energy sources) of the process

(Rokni, 2016).

A typical chemical plant consists of hundreds of process units such as heat exchangers, reactors,

distillation columns, absorption towers and others. Chemical reactors optimization is followed by

the heat exchanger network optimization as it describes in onion diagram below in figure 2.3.

Most chemical processes need the heating and cooling of certain process streams before they

enter or leave another process unit or are released into the environment. This utility requirement

can be satisfied by matching of these streams with one another and by supplying external source

of heating or cooling. These external sources are utilities, and they increase the operating cost of

the plant (K. S. Telang et al, 2001; Silla, 2003).

Figure2.2 Onion skin diagram for organization of a chemical process and hierarchy of analysis

A heat exchanger network (HEN) is a grid of heat exchangers; in which cold and hot process

streams and hot and cold utility streams interchange energy. The HEN aims at reducing the use

of these external utilities by maximizing energy recovery within the process. The design

philosophy started at the heart of the onion with the reactor and moved out to the next layer of

the onion, the separation and recycle system and then to HEN and utilities as it describes in the

above figure 2.3 (S B Thakore and B I Bhatt , 2007; Smith, 2005).

The PDM gives a strategy for developing the network in a sequential manner deciding on one

heat exchanger at a time, with rules for matching hot and cold streams for these heat exchangers.

The pinch analysis also indicates when and how stream splitting should be applied. When the

process system consists of several heat exchangers, coolers and heaters, identification of the

pinch point is very important in order to recover energy within the system with maximum results

and decrease the need for the external heating and cooling energy. Thus energy target can be

realized by designing an optimum heat exchanger network (K. Singh and R. Crosbie, 2011;

Mohanty, 2010).

17

The following rules are immediately applied (Rokni, 2016; Anna Gunnarsson and Carin

Magnusson, 2011). 1) Above the pinch point external coolers cannot be used. 2) Below the pinch

point external heaters cannot be used. 3) Across the pinch point heat exchanger cannot be used.

4) During matching between hot and cold process streams in the pinch exchangers use the CP

rules. CP and stream numbers of cold are greater or equal to that of hot above the pinch. CP and

stream numbers of hot are greater or equal to that of cold below the pinch.

These rules are often called as pinch rules and pinch analysis uses stream splitting whenever the

above rules cannot be applied. During heat exchanger networks there are three different reasons

why it is often useful and profitable to split process streams into two or more branches: It

reduces energy requirements, total heat transfer area, and reduce the number of units. Heat

exchanger network can be represented in a number of ways. The common ones are grid diagram

and the mass content diagram but, the most common representation scheme is the grid diagram,

in which each heat exchange unit is symbolized as a vertical line connecting two streams. Grid

diagrams are important tools for designing and representing networks for heat integration. It has

the important benefit that it imitates the desirable counter current flow of heat exchangers and

thereby makes it simple to implement pinch decomposition in heat exchanger networks as well

as to study cross pinch heat transfer temperature. Grid diagram can be divided into sub problems

across the regions defined by the pinch points. Therefore, pinch analysis rules are applied to

design HEN in order to achieve the minimum heating and cooling utility duties (maximum heat

recovery) as well as the minimum number of heat exchangers (K. S. Telang et al, 2001 March,

1998).

Pinch analysis has been used in industrial applications across the world, and there are some

studies with their result in energy savings. Study on natural gas processing plant show that, the

HEN with energy savings are obtained with the appropriate use of utilities (save 42% for hot

utilities and 21% for cold utilities)(Corredor, 2012). And another study on VCM (vinyl chloride

monomer) distillation unit, the network result with most optimal value energy savings are

obtained with the appropriate use of utilities (save 15.38% for hot utilities, 47.52% for cold

utilities and percentage reduction in total operating cost is 18.3%)(M.U.Pople and Vishal G.

bokan , 2015).Study on pinch analysis of heat exchanger networks in the crude distillation unit of

port Harcourt refinery, hot utility load of 95928.3 kw is reduced to 86201.53 kw which saves

18

89.86% of hot utility, and cold utility load of 3560.21 kw is reduced to 0 kw (Akpa, J. G. and

Okoroma, J. U., 2012), which shows the problem is threshold problem.

Based on these literatures pinch analysis can apply for minimization of sulphuric acid production

plant energy consumption by heat exchanger network. The reason why this research focused on

design of heat exchanger network for Awash Melkassa sulfuric acid production plant is because

the process of sulfuric acid production is the most energy intensive process.

As a result of the above and other reasons, stated in the problem statement, this work is intended

to study on design of heat exchanger network for the case of sulfuric acid plant and address a

solution for the problem mentioned at the problem statement. Thus, pinch analysis is the primary

tool for the design of heat exchanger network applied to solve the problem.

19

CHAPTER THREE

METHODOLOGY

3.1 Data Extraction

Data extraction includes collecting of data about heating and cooling requirements of process

and utility streams. The amount of information available from plant that are relevant to the pinch

analysis are identified and extracted only the information that truly captures the relevant sources

for hot and cold streams(Mohanty, 2010).

Stream data where extracted from AMASSASC plant for process stream, external heating and

cooling, and heat exchanger streams properties are identified. Temperature and pressure for both

process and utility stream are extracted from the operator’s, engineers, manual and

documentation. Mass flow rate data are collected from material balance of sulfuric acid

production using 2160kg/hr of sulphuric acid in AMASSASC with purity of 96% as a base.

Specific heat capacity for each streams also collected from different thermodynamic property

table.

Aspen energy analyzer 2015 version 8.8 software from aspenOne product is used to carry out the

analysis. Aspen Energy Analyzer (AEA) is energy management software for performing optimal

heat exchanger network design to minimize process energy. AEA constructs a pinch diagram for

the heat exchanger network that gives the best organization of process streams and supplied

utilities to minimize utility consumption.

Pinch analysis is performed as a method on a sulfuric acid production plant to design the heat

exchanger network. This work is divided into five major steps: (1) extraction of stream data

(temperature, flow rate, and heat capacity) from the sulfuric acid production plant, (2) selection

of ΔTmin and targeting, (3) heat exchanger network design, (4) optimization of designed heat

exchanger network and (5) network cost analysis.

With consistent observation on the system for heating and cooling requirements, stream data are

extracted. Here only those flows which require heating or cooling are extracted from given

process. Seven streams are considered in this work for pinch analysis which are four hot streams

and three cold streams, whose characteristics are listed in table 3.1below.

20

3.1.1 Assumptions

At each heat exchanger unit, mass flow rate, stream composition, pressure and specific heat

values within the operation range are assumed to be constant. And in order to decrease the size of

heat exchanger to an acceptable level with reasonable price it was assumed that there always

exists a temperature difference.

3.1.2 Extraction of Process Stream

After process and utility data are obtained, the next step is identification of process heating and

cooling duties and extraction of process streams in the form required for pinch analysis.

All process streams are defined on the basis of their start and target temperatures (T), heating

value (Cp) and mass flow (m) and are divided into either hot or cold streams during pinch

analysis for HEN design. A hot or cold stream is defined as a stream which needs to be cooled or

heated to reach its target temperature.

Table3.1 Process streams data

Stream ID

Stream

Description

Ts

(oC)

Tt

(oC)

Stream

type

Mass flow

rate

m(Kg/s)

Heat capacity

Cp(KJ/Kg oC)

Heat load

Q (KW)

1 Bed -1

output

580 460 Hot 0.36 1.76 75.61

2 Bed -2

output

485 430 Hot 0.49 1.59 42.9

3

Bed -4

output

390 190 Hot 0.55 1.43 158

4

Input to

Acid cooler

80 60 Hot 0.6 1.4 16.8

5

Input to

dryer

27

80

Cold

2.25

1.0

119.25

6

Input to

bono boiler

81 150 Cold 0.012 4.197 3.45

7 Input to

water Pre-

heater

27 81 Cold 0.013 4.179

2.92

21

In table 3.1, the cooling effect and heating effect for the hot and cold streams which must be

supplied by external cooler and heater to satisfy the energy demand of the plant are calculated.

Using the heat transfer formula, the cold and hot utility requirements before HEN design are

calculated using equation 3.

𝑄 = 𝐶𝑝 ∗ ∆𝑇 𝑒𝑞(3)

Qcool= 0.63 x (580-400) + 0.78 x (485-430) +0.79(390-190) +0.84(80-60) = 293.31 kW

Qheat= 2.25x (80-27) + 0.05 x (150-81) + 0.054 x (81-27) = 125.62 kW

From this calculation the idea is now to find the lowest possible Qcool for the sulphuric acid

production plant.

3.2 Data Feed to Aspen Energy Analyzer

During utilizing pinch analysis, AEA guides in designing the network by recovering the heat

between heat sources and sinks and minimizes the usage of heating and cooling utilities in the

process plant. Pinch analysis in AEA is designed for analyzing and improving the performance

of HEN. It has process streams tab, utility stream tab and economics tab and some views like

targeting, HEN grid, HEN cost etc ( Burlington, 2011; Burlington, 2011).

Process stream tab

This tab allows for making specific information about the process streams in the HEN and the

extracted process stream data are providing below in the table3.2.

Table3.2 Process stream tab

Utility streams tab

This tab allows specifying the utilities consumed in the HEN to cool or heat the process streams.

The plant uses different utilities and provide as cooling utility and hot utility. The cost index of

22

these cold and hot utilities are specified below in table 3.3, by aspen energy analyzer on utility

streams tab.

Table3.3Utility stream tabs

3.3 Targeting An important feature of pinch analysis is the ability to identify performance targets before the

design stage is started. Targeting is forecasting of what is the best performance that can possibly

be achieved by the system before trying to achieve it. This procedure allows for finding the

number of units, minimum utility requirement, area of heat exchangers and the investment cost

prior to the actual design of the network for a specified minimum approach temperature. Results

obtained from the targeting step leads the design in right direction and help to search for an

optimum design (Mohanty, 2010; J. Khorshidi et al, 2016).

3.3.1Energy targeting

Energy targeting is a powerful heat integration concept, and it deals about targeting of minimum

energy consumption through external utility requirements. Energy targeting can be done through

composite curves, problem table algorithm, and grand composite curves (Rev, 2013; Burlington,

2011). This study deals with energy targeting using hot and cold composite curves.

It is first necessary to set ΔTmin values for the problem in order to generate the composite curves

during pinch analysis. ΔTmin is the smallest temperature difference to be allowed in any heat

exchange match between hot and cold streams. This parameter reflects the tradeoff between

energy consumption and the required capital cost for heat exchangers. ΔTmin values for

23

chemical processes and for matching utility levels against process streams are 10 to 20 oC. To

start targeting process in pinch analysis, it has to assume a value of ΔTmin. In this work, a

ΔTmin value of 10 oC, which is global value, is applied to all process to process streams and for

matching utilities against process steams as initial guess value (Rokni, 2016; Mohanty, 2010).

From the targets view tab it shows the following information at10 oC value of ∆Tmin, Minimum

heating load = 0 KW, minimum cooling load is equal to 167.69 KW. Therefore, HEN is designed

based on this minimum utility demand, which achieves this minimum energy demand for

maximum energy recovery (MER) to achieve.

3.3.2 Units Targeting

The fixed cost of a HEN depends upon the number of heat exchanger it uses. Thus, there exists a

possibility that a HEN with minimum number of heat exchanger has low cost and a strong

incentive to reduce matches between hot and cold streams (number of heat exchangers) in a

HEN. The first step required for this targeting process is to identify the number of heat

exchangers a HEN will require from the number of hot, cold and utility streams it handles

(Burlington, 2011).

In heat integration, establishing targets with small number of heat exchangers, also referred to as

units, is done by the N-1 rule. This is the simplified form of Euler’s rule from graph theory U =

N+L-S, and it is the analogy between graphs and a heat exchanger network is that nodes

represent streams, while edges represent heat exchangers. Where, N is the total number of

process streams and utility types, U is the number of units, L is the number of independent loops,

and S is the number of sub-networks. A loop is any path in the network that starts at some point

and returns to the same point and a sub problem is a set of streams which are perfectly matched

with each other (Mohanty, 2010; Kemp, 2007).

Since the objective is to establish a target for the number of units ahead of design, network

related features such as loops are not known. This is overcome by setting L is zero, as a result,

Euler’s rule is reduces to U = N-S.

From the energy targeting it shows that the problem is a threshold problem, it needs only cooling

and no heating requirement. The minimum cooling load required for the above system computed

using CC figure is 167.69KW. The heat load of different streams along with cold utility load is

24

shown below within the circles representing the streams in Fig.3.1.The predicted cold utility load

is also shown similarly.

Figure3.1 Schematic matching of heat loads for process streams

The minimum number of units needed to achieve a MER network can be calculated based on

Euler's Network Theorem. Here the number of independent sub problems or sub network (S) is

equal to three as it shown in figure 3.1 above, because the system uses multi utilities.

U = N-S

U = 7+3 -3=7

The targets view on the aspen energy analyzer allows observing all the target values for the

specified on the HI Case view below in table 3.4.

Table3.4Targets view tab

25

From the targets view tab in table 3.4 above, it shows the following information at10 oC value

of∆Tmin. Minimum heating load = 0 (kJ/hr), minimum cooling load = 167.69KW, no pinch

temperature (because it is threshold problem), Total minimum number of units = 7 and other

target values can observe from table 3.4 targets view tab above.

3.4. Stream splitting

Grid diagram is the most common representation scheme of HEN, in which each heat exchange

unit is represented as a vertical line connecting two streams. It represents the countercurrent

nature of the heat exchange and it is a useful visual tool to apply the rules of pinch analysis.

In a grid diagram as it shown in figure 3.2 below, horizontal lines at the top of the diagram

represent hot streams. These streams flow from the left to the right of the grid diagram.

Horizontal lines at the bottom of the diagram represent cold streams. These streams flow from

the right to the left of the diagram. Vertical lines represent heat exchange unit and each line

connect a hot and a cold stream, a hot stream and a cooling utility, or a cold stream and heating

utility in this work hot stream will connect with cold utility.

Figure3.2 Grid diagram representation for process streams The pinch analysis provides a strategy for developing the network in a sequential manner

deciding on one heat exchanger at a time, with rules for matching hot and cold streams for these

heat exchangers. In the application of the pinch analysis, situations are commonly encountered

where stream splitting is an absolute requirement in order to design HEN that achieves minimum

external utilities.

26

This threshold problem is treated as one half of a pinched problem (follow rules of below the

pinch). The rules of pinch analysis below the pinch are: CP and stream numbers of hot are

greater or equal to that of cold. Stream splitting rule is represented in the figure 3.3 below for

both number and heat capacity criteria.

Number of streams criterion: NH≥ NC

CP criterion: CPH≥ CPC

Where, NH is number of hot streams, NC is number of hot streams, CPH is heat capacity of hot

streams and CPC is heat capacity of hot streams

Figure3.3 Flow diagrams for splitting of streams As it shown from figure 3.2 the numbers of hot streams are greater than cold streams and it

illustrates that no stream splitting is required to develop a HEN design. In this case, the number

of streams criteria rule is satisfied. But considering the CP values, it is impossible to split any of

the cold streams into two branches that both have CP values large enough to bring a hot stream

to target temperature. So stream five must split into two streams (including branches) but, still

the CP rule is not satisfied. Then based on the CP rule stream five has to be split to three streams

(including branches). The result is then return to the problem where the number of cold streams

is larger than the number of hot streams, thus this is violating the pinch rule. So further stream

splitting is required and one of the hot streams will have to be split. Finally stream four is split to

27

two streams (including branches). Therefore, after making stream splitting using the above figure

3.3, the result is shown below in grid diagram figure 3.4 of process streams.

Figure3.4 Grid diagram representation of process streams after stream splitting

28

CHAPTER FOUR

RESULTS AND DISCUSSION

4.1 Composite curves

In heat integration, plot gives a visual analysis of important variables in a given stream data.

Pinch analysis gives composite curves (CC) for cold and hot streams separately, as shown below

in figure 4.1. The CC graph shows below in figure 4.1 the temperature profile with respect to

enthalpy indicating how much heat is recovered in the process and how much utility is needed.

Figure 4.1 Composite Curves From the above figure 4.1, it shows that the overlap between hot and cold composite curves

represents the maximum amount of heat that can be recovered within the process. The overshoot

of the hot composite curve represents the minimum amount of external cooling required in the

process and at the cold end the composite curves are in alignment, indicating that there is no

demand for hot utility. Therefore, from the above CC curve, the sulphuric acid process is a

threshold problem that requires only cold utility. This implies that there should be no net

requirement for heating of process streams with hot utility. There is no pinch in this problem

because it is a threshold problem with non-utility end.

Composite curves provide overall energy targets, but CC does not indicate the amount of energy

that should be supplied at different temperature levels through utilities. Grand composite curve

(GCC) is plotted with net enthalpy against shifted temperature from the data of shifted

temperature level composite curves as it shown below in figure 4.2. From the GCC graph it can

29

also be easily identified the point where enthalpy is zero; the GCC graph touches the temperature

axis. Also the GCC graph show that the problem needs only cold utility; this indicates the nature

of problem is a threshold problem.

Figure 4.2 Grand composite curves Utility composite curve and GCC are similar, but utility composite curve contains hot and cold

utility streams. From the utility composite curve graph (figure 4.3), it determines the minimum

hot and cold utility requirements for the network and check how much of each utility contributes

to the total utility target.

Figure 4.3 Utility composite curves 4.2 Effect of ∆Tmin

4.2.1 Effect of ∆Tmin on utilities

In heat recovery problems having a pinch point, the selection of ∆Tmin values has special

significance in the design. But, in this study the problem is threshold problem, so for threshold

30

problem the utility heat load remains constant (as a ∆Tmin value varies utility requirement

remains constant) as it is shown in figure 4.4 below.

Figure4.4 Effect of ∆Tmin on utilities 4.3 Heat Exchanger Network

With performance targets for energy and units, the next step is the actual design of the HEN. One

of the most important features of pinch analysis is that the insight obtained in establishing

performance targets ahead of design actually forms the core of the design methodology. From

the targeting step it was found that the problem is threshold problem which needs only cooling

utility. So the idea in pinch design is to start the design where it is most constrained. If the design

is pinched problem, the problem is most constrained at the pinch. If there is no pinch, the most

constrained of this type of problem is the non utility end. This is where temperature difference is

smallest. So the threshold problem is treated as one half of a pinched problem (follow rules of

below the pinch).

To design a heat exchange network is performing matching between streams. And five different

matches between process streams were developed.

a) Matching of stream 3 (H-3) and stream 5(1)(C-1)

Number of streams criterion: 5≥ 5

CP criterion: 0.79≥ 0.7479036

So both number of streams and CP criterion are satisfied. Stream three has 158KW total heat

amount. A vertical line is drawn from stream three to stream five (1) and 39.639KW amount of

heat duty of stream three is transferred to stream five (1) in exchanger (E-111) to reach the

31

interval target temperature. The remaining 118.36KW heat duty of stream three not removed in

exchanger (E-111) is removed in the next match.

b) Matching of stream 3(H-3) and stream 5(2)(C-2)

Number of streams criterion: 5≥ 5

CP criterion: 0.79≥ 0.7479036

Both number of streams and CP criterion are satisfied. Now Stream three has left with118.36KW

heat amount. A vertical line is drawn from stream three to stream five (2) and 39.639KW

amount of heat duty of stream three is transferred to stream five (2) in exchanger (E-114) to

reach the interval target temperature. The remaining 78.72KW heat duty of stream three not

removed in exchanger (E-114) is removed in the next utility match.

c) Matching of stream 2 (H-4) and stream 5(3)(C-3)

Number of streams criterion: 5≥ 5

CP criterion: 0.78≥ 0.75419287

Both pinch analysis criterion are satisfied and stream two has 42.9 KW heat amount. A vertical

line is drawn from stream two to stream five (3) and 39.97 KW amount of heat duty of stream

two is transferred to stream five (3) in exchanger (E-112) to reach the interval target temperature.

The remaining 2.92 KW heat duty of stream two not removed in exchanger (E-112) is removed

in the next match with stream seven.

d) Matching of stream 2 (H-5) and stream 7(C-5)

Number of streams criterion: 5≥ 5

CP criterion: 0.78≥ 0.054

Both the golden rules of pinch analysis criterion are satisfied. And now Stream two has left

with2.92 KW heat amount. A vertical line is drawn from stream two to stream seven and

2.92KW amount of heat duty of stream two is transferred to stream seven in exchanger (E-115)

to reach the target temperature of both streams.

e) Matching of stream 1(H-3) and stream 6(C-4)

Number of streams criterion: 5 ≥ 5

CP criterion: 0.63≥ 0.05

32

Both pinch analysis criterion are satisfied. Stream one has 75.61 KW heat amount. A vertical

line is drawn from stream one to stream six and 3.45 KW amount of heat duty of stream two is

transferred to stream six in exchanger (E-116)to reach the interval target temperature. The

remaining 72.16 KW heat duty of stream one not removed in exchanger (E-116) is removed in

the next match with utility. The maximum energy recovery is designed by transferring heat

between the process streams as shown below in figure 4.5.

Figure4.5 Grid diagram of HEN for process to process heat transfer After the maximum energy recovery is designed by transferring heat between the process

streams but, until now some streams are unsatisfied and these are displayed below in table4.1.

Table 4.1 Unsatisfied streams

When the heat recovery is maximized, the remaining thermal needs are supplied by external heat

utility and three different matches between process streams and utility are developed.

f) Matching of stream 1 (H-1) and cold utility

Stream one was left with 72.16KW heat and this amount of heat is removed in exchanger (E-

117) by external utility air which is available at 80 oC.

33

g) Matching of stream 3 (H-3) and cold utility

The amount of heat that has not matched with the process streams was satisfied with external

utility. 78.73KW amount of heat was left in stream three and this amount of heat is removed in

exchanger (E-118) by external utility water available at 81 oC.

h) Matching of stream 4(1) (H-1) and cold utility

Since stream four was split in to two streams, each with 8.4KW of heat amount. Stream four (1)

has 8.4KW of heat and it is removed in exchanger (E-119) by matching with external utility

water available at 30 oC. Stream four (2) has 8.4KW of heat and exchange with exchanger(E-

120) by matching with external utility water available at 30 oC. The design for both heat transfers

between process to process and process to utility is shown below in the grid diagram figure 4.6.

Figure4.6 Heat exchanger networks for MER design AEA performs a heat integration using pinch technology. This heat integration is displayed in a

HEN diagram, showing which process streams or utilities enter and leave a given heat

exchanger. The heat exchangers on the grid diagram appear as colored disc lay on top of the

stream flowing through it. Each color indicates a type of heat exchanger: Grey color defines that

heat exchanger as a process to process exchanger. The heat exchanger is attached to two process

streams.

Blue color defines that heat exchanger as a cooler. In other words, the heat exchanger is attached

to a hot process stream and a cold utility stream. Therefore, from figure 4.6 the minimum energy

requirement is 167.69KW, the designed network in figure 4.6 above is meet the energy target.

34

4.3.1Network interval temperature calculations

The temperatures between each exchanger can be calculated using the energy balance equation.

Interval temperatures for process to process and for process to utility matches are calculated

below in table 4.2.

Match a (Heat exchanger E-111)

The supply and target temperature of stream 3 are 390 oC and 190

oC respectivly and with heat

capacityrate 0.79KW/ o

C. But match a was perform to cool stream 3 from 390 oC to unknown

temperature X with 39.639KW amount of energy from stream five(1). So to calculate this X

value the energy balance equationis used.

Q = CP*∆T

(390 - X)*0.79 = 39.635

X=339.82oC

Th interval values of other heat exchanger ara summerized in below in table 4.2

Table 4.2 Exchangers interval temperatures in the network before optimization

4.3.2 Optimization Of ∆Tmin Value

Range targeting contains information relevant to the optimization of the minimum approach

temperature. An optimum minimum approach temperature is calculated by minimizing the total

annual cost and it is finding the best balance between utility requirements, heat exchanger area

35

and unit and shell number. As the minimum approach temperature is varied the total annual cost

of the network is calculated and there is a ΔTmin which yield a minimum total annual cost.

For threshold problem, the optimum value occurs at the threshold temperature or it can be higher

than the threshold value and cannot be below the threshold temperature. Energy cost is constant

below this temperature but, only capital cost varies with ∆Tmin values. But if we increase the

optimum value to greater than threshold, the system changes from non utility end to near/pseudo

pinch problem or to pinched problem and needs both hot and cold utility as the result of

increasing the value of ∆Tmin value and this increases the operating cost. Therefore, for

threshold problem the optimum value occurs at the point where the summation of capital and

energy cost or total cost becomes minimum which is 13 oC as it shows in table 4.3 below. So the

optimum value of ΔTmin with minmum value of cost is at 13 oC.

Table 4.3 Optimization of ΔTmin value

Therefore, from the optimization of ΔTmin value we can understand that the minimum energy

requirement is not change with the variation of minimum temperature value as it shown in figure

4.4 above. Therefore, the designed HEN doesn’t need farther design at 13 oC as new value of

ΔTmin, because no change is observed at this value.

4.3.3 Optimization of Heat Exchanger Network

Network evolution is performed by optimizing the preliminary HEN by identifying loops and

paths within preliminary designs and shifting heat loads away from small, inefficient heat

exchange units to create less and more cost effective units. When optimization is carried out,

36

HEN with the maximum energy recovery from the initial design is simplified in terms of cost.

Decomposition at the pinch normally results in networks with at least one more unit than the

minimum number in the target. Manipulating with heat load loops and paths, stream splitting and

restoring ΔTmin, the final solution is improved in order to achieve an optimal HEN design.

Optimization of HEN begin by relaxing the restrictions imposed on preliminary heat exchanger

networks and allowing individual exchangers to operate below minimum approach temperatures

or transfer heat across the pinch, because during loop breaking pinch rules are not applied.

Energy relaxation is a procedure of allowing the energy usage to increase in exchange for at least

one of the following reasons: reduction in area and number of heat exchangers, and reduction in

complexity (typically less splitting).

Therefore, as it is shown from figure 4.6, the minimum energy requirement is 167.69KW and

maximum energy recovery (MER) value is 251.24KW, the designed network meets the energy

target. However, the minimum numbers of heat exchanger in the network in figure 4.6 are nine

which are greater than the targeted one that is seven. This may be due to the additional split

streams and existing of loops. Therefore, two heat exchangers should be removed. So the design

needs farther optimization step that is to design the Non-MER design. In order to fulfill the

prediction in the targeting stage, the number of exchangers has to be reduced.

Reducing the number of exchangers will definitely lower the capital cost of exchangers.

However, it will increase the cost for utilities (operating cost) for pinched problems but in this

problem which is threshold, the operating cost is constant.

4.3.3.1Loop breaking

Loop is a circuit in the network which starts at one exchanger and ends in the same exchanger.

Path is a circuit in the network that starts at a heater and ends at a cooler. The important feature

of loop is that, heat loads can be shifted around the loop from one unit to another to cause loop

breaking. The presence of loops in a HEN design may involve two statements. The designed

HEN has more units than the minimum number required, and it has more constraints in its

controllability. Based on this to design HEN, it is better to avoid loops whenever possible.

During loop breaking, the load is subtracted from the next and so on around the loop and this

load shift always keep the correct stream heat loads but the exchanger duties are changed

(Mohanty, 2010; K. Singh and R. Crosbie, 2011).

37

A loop exists between exchanger E-111 and E-114 and this loop must be broken but no path

exists in the HEN design as shown in figure 3.7 below.

Figure4.7 Loop in designed HEN Two heat exchangers are reduced during the optimization stage. The first exchanger is removed

by combining E-111 and E-114 into one exchanger. And the second exchanger is reduced by

adding up stream four into one branch.

Figure4.8 Optimized HEN design Therefore, the final optimized design is shown above in figure 4.8 with seven numbers of units

that meets the number of exchanger units in the targeting stage.

Detail information about each heat exchanger like connectivity and parameters are displayed as

below in figure 4.9.

38

Figure4.9 Detail information of heat exchanger 4.3.4 Network performance and controllability analysis

4.3.4.1 Network performance analysis

The performance tab on AEA brings up the table shown below in table 4.4 which gives the detail

about the effectiveness of the base case (target) heat integration calculation.

Table 4.4 Network performance before optimization

Table 4.4 provides the total amount of heating and cooling requirements, as well as the number

of heat exchangers and their shells. Also includes the summation of heat exchanger area in the

network. The % of target column in the table is significant, because it shows whether an

optimization to the HEN is achieved. From the design before optimization, the percent target of

heating and cooling, number of units and shells, and total area is displayed on the performance

tab view. Therefore, the heat exchanger network needs farther optimization, because 9 numbers

of units represent 128.6% of the target units which is 28.6% above target. The number of units

39

can be reduced by as much as 28.6% through optimization of the heat exchanger network.

Similarly, reduction on total shells and area is an outcome once optimization is performed; the

total area of the heat exchangers in the network will decrease by up to 15.3%.

Table 4.5 Network performance after optimization

The performance of the network after optimization is shown in table 4.5 above. From the design

after optimization, the percent target of cooling, number of units and shells, and total area is

displayed. The result shows that the energy requirement and number of units in the design

matches with the target value. But, number of shells in the design is 29.17% below the target and

total area is 15% above the target. This design can further be optimized to reduce the total area

but again it turns to increasing in ∆Tmin which results on increasing energy requirements and

also on number of shells and units. Therefore, HEN design is a matter of trade off between

∆Tmin, energy cost and capital cost to find the optimum design.

4.3.4.2 Network controllability analysis

Controllability status of the HEN design can be affected by different factors. The main factors

are: manipulated variables, sub networks, controlled variable, control constraints and number of

degree of freedom.

In a HEN design, the variables to be control are the process streams' outlet temperatures

(controlled variables). If the output temperatures are in control, then no possibility of

temperature fluctuation from the process streams that can affect the rest of the process. To

control the output temperature of the streams in the HEN design, it needs well manipulated

variables and degrees of freedom (DOF) to implement controls on to the design. The number of

manipulated variables in the HEN design equals the total number of heat exchangers in the

40

design and the number of control constraints equals to the number of loops that exists within the

design. However, each loop reduces the number of manipulated variables by one.

Sub networks are another factor that affects the controllability status of the design. A sub

network in the grid diagram is a set of streams that are heated or cooled within the set and does

not affect other streams in the entire HEN and three sub networks exist in this work as shown

below. The value of the degrees of freedom indicates whether the HEN design can be controlled

or not. The number of DOF is the difference between the manipulated variables (units) and the

sum of controlled variables (controlled streams) and number of loops for each sub networks.

Table 4.6 Network controllability status before optimization

From the above table 4.6, before optimization, the number of degree of freedom is greater than

zero in sub network three, indicates that there are enough manipulated variables in the HEN

design and can implement more sophisticate control structures.

41

Table 4.7 Network controllability status after optimization

From the above table 4.7 after optimization the number of degree of freedom is zero in all sub

networks, indicates that there is enough manipulated variables in the HEN design to control the

target streams which are process streams whose output temperature is controlled.

4.3.5 Potential heating and cooling savings of the network

The process has a minimum cooling demand of 167.69 KW and a heating demand of 0 KW as it

is calculated before. By comparing the minimum utility demands with the utility demands of the

existing system, it is possible to establish the potential for savings, as shown below in Table 4.8.

Table 4.8 Potential heating and cooling savings

Utility Present demand

(KW)

Minimum demand

(KW) by AEA

Potential for saving

(KW)

Potential for

saving (%)

Heating 125.62 0 125.62 100

Cooling 293.31 167.69 125.62 42.83

Total 418.93 167.69 251.24 59.97

4.4 Network Economic Analysis

4.4.1Network Cost Estimation

The economic parameters in AEA are required to calculate the capital cost and the annualization

factor of the heat exchangers in the HEN. Depending on the type of heat exchanger used in the

HEN the economic parameters changes. AEA has two types of heat exchangers. Each type has

its own formula for calculating the capital cost. Heat exchanger: This option considers the shell

and tube type exchangers, which uses convection to transfer energy. The capital cost is based on

42

the heat transfer area. Fired heater: This option considers the fired heater type exchangers; which

uses radiation to transfer energy. But, this study is based on shell and tube type of exchanger,

because the heat transfer mechanism between the fluids is convection transfer mechanism. A

typical HEN can have multiple heat exchangers types, and may be different material used to

construct the heat exchangers. Aspen energy analyzer provides a default cost set based on a

shell& tube exchanger type with carbon steel as the construction material. The basic economic

parameters used to calculate the cost of the heat exchanger network are capital cost, operating

cost and total annualized fixed cost (Burlington, 2011; S B Thakore and B I Bhatt , 2007).

a) Capital cost of heat exchangers

Capital cost is the fixed cost for purchasing and installing the heat exchangers. For each

exchanger in the network the capital cost is calculated below based on the following heat

exchanger capital cost formula by equation 4 below (S B Thakore and B I Bhatt , 2007; Silla,

2003; Max S. Peters, and Klaus D. Timmerhaus , 1991).

CC = a + b ∗ Area

Nshell 𝑐

∗ Nshell eq(4)

Where,

CC= installed capital cost of a heat exchanger ($)

a = installation cost of heat exchanger ($)

b, c = duty/area related cost set coefficient of the heat exchanger

Area (A) = heat transfer area of heat exchanger in meter square

NShell = number of heat exchanger shells in the heat exchanger

The heat exchanger capital cost index parameters from the aspen energy analyzer economics tab

view are displayed in table 4.9 below.

Table 4.9 Economics tab view for heat exchanger capital cost index parameters

43

The economics tab displays the cost set and economic parameter values used to calculate the

capital cost of the exchangers. A default set of economic parameters is supplied by AEA. And

the heat exchanger cost index parameters are:

a = 10000, b = 800, c = 0.8

And the plant life and operation days are taken 10 years and 300day/year respectively. Capital

cost for each exchanger is calculated below and all costs are in dollar. The annualization factor

accounts for the depreciation of capital cost in the plant. It must be considered since the capital

cost and operating cost of a heat exchanger network do not have the same units. Annual capital

cost is capital cost of the exchanger times the annualization factor(S B Thakore and B I Bhatt ,

2007). Both capital and annual capital cost are calculated below for each heat exchanger.

Heat exchanger (E-129)

Table 4.10 Parameters for heat exchanger E-129

From the above table 4.10 the values of area and cost parameters for E-129 are given below:

Area = 2.89m2

Capital cost ($) = = 1.187*10^4

44

Annual capital cost ($/s) = 9.764*10^-5

The total fixed capital cost and total annualized fixed capital cost of the heat exchangers are

summarized in the table 4.11below.

Table 4.11 Total annualized fixed capital cost of heat exchangers

Exchanger Duty (KW) Area (m2) Fixed capital

cost($)x104

Annualized

fixed capital

Cost ($/s) x10-5

E-129 79.28 2.89 1.178 9.764

E-128 39.97 0.945 1.081 8.854

E-127 2.92 0.08 1.010 8.31

E-116 3.45 0.075 1.010 8.307

E-118 78.722 6.92 1.376 11.32

E-117 72.166 2.57 1.170 9.625

E-120 16.8 3.80 1.233 10.14

Total 8.06 66.282

So the total annualized fixed capital cost is the summation of all heat exchangers cost which is

$66.282x10-5

/s or $17,180.2944/year.

b) Operating cost of utilities

The operating cost is a time dependent cost that represents the energy cost to run the exchangers

(S B Thakore and B I Bhatt , 2007 ;Max S. Peters, and Klaus D. Timmerhaus , 1991). For AEA,

the operating cost is dependent on the calculated energy targets in the HEN. On the utility

streams tab, utilities have costs associated with them. This cost information is required to

calculate the operating cost for the design. Operating cost of minimum heating & cooling utilities

are as follows:

Total operating cost is the summation of operating cost of heating and cooling utilities.

OC = ∑ (QHmin*Chu) + ∑ (QCmin*Ccu)

Where,

45

OC =operating cost ($/s)

QHmin=minimum energy required of hot utility (KW)

Chu = utility cost for hot utility ($/KJ)

QCmin=minimum energy required of cold utility (KW)

Ccu = utility cost for cold utility ($/KJ)

Since the problem is a threshold problem with only cold utility, there is no hot utility

requirement, so minimum energy required of hot utility is zero this means no operating cost for

heating utility.

OC = ∑ (QCmin*Ccu)

The cost index for the cold utilities is given below in table 4.12 in the utility stream tab on AEA.

Table 4.12 Utility streams tab for cost index of cold utility

From the final HEN design some process streams consumes utility to get their final target

temperature. Exchanger E-118, E-117 and E-120 are the exchangers that are connected with the

utility streams.

46

Table 4.13 Energy consumed and cost index of cold utility streams

SN Exchanger Energy

consumed

(KW)

Cost index

($/KJ)

x10-6

1 E-118 78.72 3.171

2 E-117 72.17 0.001

3 E-120 16.8 0.02125

Total 167.69

The operating cost is the energy consumed times the cost index for each utility streams given in

table 4.13 above.

Which is expressed as OC= energy (KJ/s) * cost ($/KJ).

Operating cost for exchanger E-118 is calculated as

OC= energy (KJ/s) * cost ($/KJ) = 78.72KJ/s*3.171x10-6

$/KJ =0.0002496211($/s)=

$6470.179/year

Operating cost for exchanger E-117

OC= energy (KJ/s) * cost ($/KJ) = 72.17KJ/s*0.001x10-6

$/KJ =7.217x10-8

($/s)= $1.87/year

And also the operating cost for exchanger E-120 is calculated below.

OC= energy (KJ/s) * cost ($/KJ) = 16.8KJ/s*2.125x10-7

$/KJ =3.57x10-6

($/s) = $92.5344/year

The total operating cost is the summation of all the above operating cost and is $ 6564.58/year.

4.4.2 Network Profitability Analysis

The maximum energy recovered during pinch analysis in the heat exchanger network design is

the amount of energy saved. The amount of energy saved by transferring heat from process to

process streams in HEN design is 251.24KW. The amount of saved energy is the amount of

income multiplying by its cost index of each stream.

47

Income from the saved energy is calculated as:

Income = energy saved (KW)*cost index ($/KJ)

Cost index is the summation of the two utility streams.

Income from exchanger E-129 is:

Income = 79.28KJ/s *6.342x10-6 =$4.964391x10-4/s =$12867.7015/yr and the income for other

exchangers is calculated in the table 4.14 below.

Table 4.14 Energy saved and cost index of cold utility streams

Exchanger Energy saved

(KW)

Process

Stream

Utility Stream Income

($/yr) Cost

index($/KJ)

x10-6

Cost

index($/KJ)

x10-6

E-129 79.28 3&5 3.171 3.171 12867.70

15

E-128 39.97 2&5 3.171 3.171 6570.453

02

E-127 2.92 2&7 3.171 2.2 406.5116

54

E-116 3.45 1&6 0.001 3.5 313.8782

4

Total 125.62 20157.73

96

Total income is the summation of the above incomes, which is $20157.7396/yr.

Then gross profit is calculated from total income (I) minus total production cost (Pc). But, in this

study the total production cost represents only operating and depreciation cost. Operating cost is

calculated before which is $6564.58 /yr and the depreciation cost is calculated below:

The uniform annual payment which made at the end of each year is the annual depreciation cost

(D). Analysis of costs and profits for any business operation requires recognition of the fact that

physical assets reduce in value with age. This decrease in value may be due to physical

deterioration, technological advances, economic changes, or other factors which ultimately affect

life of the property (Max S. Peters, and Klaus D. Timmerhaus , 1991). Depreciation cost is

calculated using the formula below.

D = (V-Vs)*i/ (1+i) N

-1

48

Where,

V =original value, assume it is equal with the fixed capital cost=$17180.2944

Vs =salvage value at the end of service life, assume zero value

i = annual interest rate, 7%

N = number of years

D = (17180.2944)*0.07/ (1+0.07)10

-1 = $1243.4668/yr

Gross profit (GP) is the profit before tax and is calculate below.

GP =I-Pc =20157.7396 – (6564.58 +1243.4668) =$12349.693/yr

Net profit is the profit after tax, with tax rate (t) of 30%.

NP =GP (1-t) = (12349.693) (1-0.3) = $8644.7851/yr

Although there are different types of profitability measurements, but in this study rate of return

and payback period are discussed to show either the project is profitable or not.

A) Rate of return (ROR)

In engineering economic studies, ROR is ordinarily expressed on an annual percentage basis.

The yearly profit (net profit) divided by the total capital cost necessary represents the fractional

return, and this fraction times 100 is the standard percent return on investment (Warren D.sieder

et al, 2003; Max S. Peters, and Klaus D. Timmerhaus , 1991).

ROR = (net profit/ total capital cost)*100,

But, total capital cost is the summation between fixed capital and working capital cost.

Working capital cost is expressed as (10-20) % of total capital cost (Max S. Peters, and Klaus D.

Timmerhaus , 1991).By taking working capital as 15% of capital cost

TCC = FCC + WCC

TCC =FCC +15%TCC, FCC =$17180.2944/yr.

(1-0.15)TCC = 17180.2944, TCC =17180.2944/0.85 =$20212.1/yr.

49

So, ROR = (8644.7851/20212.1)*100 =0.4277*100

ROR =42.77%

Minimum acceptable rate of return (Mar) (10-16%) [38], taking Mar as 10%.

ROR must be greater than Mar to be the project acceptable. 42.77% ˃10% which implies the

project is acceptable.

B) Payback period (PBP)

A period of time that a project requires to recover the money that invested in it is payback

period. PBP is expressed as total depreciable capital cost dived by cash flow. Cash reception

minus cash payments over a given period of time is the cash flow (net profit plus depreciation)

And if PBP of a project is shorter or equal to the maximum desired PBP which is reference PBP,

the project is acceptable otherwise it will rejected (Warren D.sieder et al, 2003);(Max S. Peters,

and Klaus D. Timmerhaus , 1991).

The reference payback period (PBPref) which is the maximum period is calculated as:

(PBPref) = (FCC/TCC)/ (MAR + (FCC/TCC)/N)

Where,

PBPref= maximum payback period

TCC = total capital cost = $20212.1/yr

FCC = fixed capital cost (equipment cost) = $17180.2944/yr

Mar =minimum acceptable of rate of return, which is given above, 10%

N=plant life =10years

(PBPref) = (FCC/TCC) / (MAR + (FCC/TCC)/N) = (17180.2944/20212.1) / (0.1 +

(17180.2944/20212.1)/10) = 0.85/ (0.1+0.85/10) =0.85/0.185 =4.59 years.

Therefore, the maximum payback period of the investment is 4.59years. And the PBP of the

project is calculated as:

50

PBP = total depreciable capital cost/ (net profit +depreciation)

Total depreciable capital cost (TDCC) = total capital cost –depreciation cost

TDCC = $20212.1/yr – $1243.45/yr = $18968.65/yr

And Net profit + depreciation = $8644.7851/yr + $1243.45/yr = $9888.2351/yr

PBP = TDCC/cash flow = 18968.65/9888.2351 =1.92 years

Therefore, payback period of the project is 1.92 years, which is less than the maximum reference

period (1.92 ˂ 4.59) implies this project is acceptable.

51

CHAPTER FIVE

CONCLUSION AND RECOMMENDATION

5.1 CONCLUSION

The aim of this work was to design heat exchangers network on the reduction of the process

heating and cooling demands for the Awash Melkassa sulphuric acid production plant using

pinch analysis method. This study developed a network of heat exchangers with maximum heat

recovery among process streams by reducing the utility consumption.

Using the aspen energy analyzer software, it is possible to find alternatives to achieve large

energy consumption savings for Awash Melkassa sulphuric acid production Plant. It is a tool

with option to implement methodology for heat exchanger network design with the use of pinch

analysis method.

The problem for this study was a threshold problem which requires only cold utility. The amount

of cold utility requirement is 167.69kw and it keeps constant as ΔTmin varies up to the threshold

temperature which is 13°C. For threshold problem the optimum temperature value is at the

threshold temperature. The heat exchanger network with a ΔTmin of 13°C is the optimal where

the energy savings are obtained with the appropriate use of utilities (Save 100% for hot utilities,

42.83% for cold utilities and 59.97% from total utility is saved compared with the current

energy consumption of the plant). Profitability of the design was analyzed and is found with a

payback period of 1.92 years and rate of return of 42.77%, this implies the project is acceptable

in terms of its economic feasibility.

According to the results, designing the HEN with new heat exchanger arrangement leads to

improved energy utilization efficiency. This proves that using the pinch methodology for heat

exchanger network could lead to the significant energy savings for industrial plant.

52

5.2 RECOMMENDATION

Technology is growing faster and complexity decreases. So, it is possible to produce products

needed by customers with less production (operating) cost and minimum wastes. Therefore, the

following recommendations are recommended based on this study:

Cost and profitability analysis of this study is done based on the equipments of the network,

further study based on total cost and income of the plant is needed to analyze its profitability.

Use the updated Ethiopian tax and interest rate due to its effect on profitability analysis of the

project.

53

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APPENDICES

Appendix (3.1): Process and utility stream data of sulfuric acid plant

Process stream Utility stream SN

Exchanger name

Supply temperature ( oC)

Target temperature ( oC )

Pressure (Kpa)

Stream Supply temperature ( oC)

Target temperature ( oC )

Pressure (Kpa)

Utility name

1 Gas cooler -1 580 460 162kpa SO3 80 160 600kpa Air

2 Gas cooler -2 485 430 162kpa SO3 81 150 49.31Kpa Heated Water

3 Gas cooler -4 (Economizer)

390 190 162kpa SO3 81 150 49.31Kpa Heated Water

4 Acid cooler 80 60 2800Kpa

Acid 30 56 4.24kpa Water

5 Dryer

27 80 101.3kpa

Air 80 60 2800Kpa Acid

6 Bono boiler

81 150 49.31Kpa

Water 250 40 Fuel

7 Water Pre- heater

27 81 3.564kpa

Water 150 50 450kpa Steam

58

Appendix (4.1): Heat exchanger specification sheet

HX E-111 E-125 E-127 E-116 E-118 E-117 E-120

Heat load(KW) 79.28 39.97 2.92 3.45 78.72 72.17 16.8

Area (m2) 2.73 1.01 7.73x10

-2 7.49x10

-2 6.92 2.57 3.80

LMTD(oc) 294.8 397.1 377.1 461.0 123.7 397.0 26.89

Ft–factor 0.9863 0.9981 0.9998 0.9997 0.9197 0.9902 0.8654

U(KJ/h-m2- oc) 360 360 360 360 360 256.98 683.54

Annual cost($/s)

x10-5

9.693 8.887 8.31 8.307 11.32 9.625 10.14