EPSRC Thermal Management CPI Interim Report 16Feb

7/28/2019 EPSRC Thermal Management CPI Interim Report 16Feb

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Advanced Process Integration for Low GradeHeat Recovery

Ankur Kapil, Igor Bulatov, Robin Smith, Jin-Kuk Kim

Centre for Process IntegrationSchool of Chemical Engineering and Analytical Science

The University of Manchester

Manchester, M13 9PL, UK


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Abstract

A large amount of low-grade heat in the temperature range of 30o

C and 250o

Care readily available in process industries, and wide range of technologies can be

employed to recover and utilize low-grade heat. However, engineering and

practical limitations associated with the integration of these technologies with the

site has not been fully addressed so far in academic and industrial communities.

Also, the integration of non-conventional sources of energy with the total site can

be a cost-effective and promising option for retrofit, however, carrying out its

design and techno-economic analysis is not straightforward, due to variable

energy demands. One of the key performance indicators for the evaluation and

screening of the performance of various energy saving technologies within the

total site is the potential of cogeneration for the site. A new method has been

developed to estimate cogeneration potential by a combination of bottom-up and

top-down procedures. In this work, the optimization of steam levels of site utility

systems, based on a new cogeneration targeting model, has been carried out

and the case study illustrates the benefits of optimising steam levels for reducing

the overall energy consumption of the site.

There are wide range of low-grade recovery technologies and design options for

the recovery of low grade heat, including heat pump, organic Rankine cycle,

energy recovery from exhaust gas, absorption refrigeration and boiler feed water

heating. Simulation models have been developed for techno-economic analysis

of the design options for each technology and to evaluate the performance of

each with respect to quantity and quality of low grade heat produced on the site.

Integration of heat upgrading technologies with the total site has been studiedand its benefits have been illustrated with a case study for the retrofit design.


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List of contents

1 Introduction ................................................................................................................. 4

2 Cogeneration potential ................................................................................................ 53 Optimization of steam levels .................................................................................... 12

Case Study Cogeneration potential ............................................................................... 15

4 Technology for utilization of low Grade heat ........................................................... 22

4.1 Vapour compression heat pump........................................................................ 22

4.2 Absorption Systems .......................................................................................... 23

4.3 Boiler feed water (BFW) heating ...................................................................... 27

4.4 Organic Rankine Cycle (ORC) ......................................................................... 27

4.5 Thermo-compressor .......................................................................................... 284.6 Drying ............................................................................................................... 29

5 Algorithm .................................................................................................................. 29

6 Case study ................................................................................................................. 317 Conclusions & future work ....................................................................................... 44

References ......................................................................................................................... 458 Appendix A ............................................................................................................... 47

8.1 Optimization framework ................................................................................... 47

8.1.1 Objective function ..................................................................................... 47

Optimization constraints ........................................................................................... 498.1.2 Electric balances ....................................................................................... 49

8.1.3 Mass balances ........................................................................................... 49

8.1.4 Heat balance .............................................................................................. 51

8.2 Equipments ....................................................................................................... 52

8.2.1 Multi-fuel boilers ...................................................................................... 528.2.2 Gas turbines (GT) ..................................................................................... 53

8.2.3 Heat recovery steam generators (HRSG) .................................................. 548.2.4 Electric motors (EM) ................................................................................ 55

8.2.5 Steam turbines (ST) .................................................................................. 55


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1 IntroductionThe typical sources of low grade heat are listed in Table 1. The opportunity

includes the waste heat recovery from liquids and gases, CHP (combined heat

and power), drying, steam generation and distribution and waste heat utilization.

The industrial application of low grade heat recovery is relevant to process

industries, including chemical, petroleum, pulp and power, food and drink,

manufacturing, iron and steel, and cement industries.

Table 1: Sources of low grade heat[1]

Opportunity Areas Industry

Waste heat recovery from gases and

liquids

chemicals, petroleum, forest products

Combined heat and power systems chemicals, food, metals, machinery,

forest products

Heat recovery from drying processes chemicals, forest products, food

processing

Steam (improved generation,

distribution and recovery)

all manufacturing

Energy system integration chemicals, petroleum, forest products,

iron and steel, food, aluminium

Improved process heating/heat transfer

systems (improved heat exchangers, new

materials, improved heat transport)

petroleum, chemicals

Waste heat recovery from gases in metals

and non-metallic minerals manufacture

iron and steel, cement

To avoid unnecessary capital expenditure for oversized equipment and to

enhance controllability of the energy systems, dynamic feature of the energy

supply and demand along with integration with energy recovery technology must


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be incorporated into the energy study in a systematic and holistic manner. The

implementation of these integrated energy saving projects within or beyond the

plant may not be favoured, due to practical constraints, for example,

considerable civil and piping works required, legislative limitations, different

energy utilisation patterns between sources and sinks, etc. Therefore, it is vital to

quantify the economic benefits of employing low grade energy recovery and its

impacts on the industrial site.

2 Cogeneration potentialThe extent of heat recovery and cogeneration potential is closely related to the

configuration of site energy distribution systems in an industrial site, in which

multiple levels of steam pressure are introduced, for example, VHP (very high

pressure), HP (high pressure), MP (medium pressure) and LP (low pressure).

Steam levels and its corresponding pressure is an important design variable as

they can be adjusted to either minimize the fuel requirement or maximise profits

by exploiting site-wide trade-off of heat recovery and power generation.

Optimization of levels of steam mains is based on the manipulation of targeting

models for the cogeneration potential for the site utility systems.

The performance of the system can be either optimized to obtain the best design,

or to obtain the optimum operating conditions for an existing design, considering

the part load performance of the equipment based on the optimum number of

steam levels and their pressure. The simulation and optimization of the utility

systems require an accurate and yet simpler model for each element of thesystem. Accurate estimation of the cogeneration potential is vital for the total site

analysis as it aids in the evaluation of performance and profitability of the energy

systems. The overall cost-effectiveness of power and heat from the site is heavily

influenced by the optimum management and distribution of steam between

various steam levels. Furthermore, optimum import and export targets for

electricity can be obtained from steam levels, load and price of fuel and

electricity. Also, energy efficiency for the utilisation of low grade heat will be


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strongly influenced by operating and design conditions of existing energy

systems. Therefore, the accurate estimation of cogeneration potential is essential

for performing a meaningful economic evaluation of the design options

considered for heat upgrading and/or waste heat recovery.

A number of methods are available in the literature for estimating the

cogeneration potential of utility systems. The ideal shaftpower is calculated as

the exergy change of the steam passing the turbine[2]. The exergetic efficiency is

considered to be independent of the load and inlet-outlet conditions, and is

assumed to be a constant value. The steam conditions are approximated by thesaturated conditions, but the superheat in the inlet and outlet steam conditions

are neglected[3]. There is a difference of up to 30% in cogeneration potential in

comparison with simulations based on THM (turbine hardware model) developed

by Mavromatis and Kokossis[4].

Salisbury[5] observed that the specific enthalpy of steam (i.e. enthalpy per unit

mass flow) is approximately constant for all exhaust pressure values[6]. There is

a linear correlation between specific power w (power per unit mass flowrate of

steam) produced in the turbine and the outlet saturation temperatures. The

specific power corresponds to the area of the rectangle on a graphical

representation of the inlet and outlet saturation temperatures of the turbine with

respect to the heat loads of steam. This methodology is based on the following

assumptions: specific load (q) of steam is constant with variation in exhaust

pressure and specific power is linearly proportional to the difference of inlet and

outlet saturation temperatures.

Mavromatis and Kokossis[4] proposed a new shaftpower targeting tool called the

turbine hardware model (THM) based on the principle of Willans line. Willans line

approximates a linear relationship between steam flowrate and the power output.

THM has limitations as Varbanov addressed[7]: the effect of back pressure is not

taken into account, and modelling assumptions for part-load performance are too


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simplistic, such that the model assumes a linear relationship over the entire

range of operation.

Sorin and Hammache[8] introduced a different targeting method based on

thermodynamic insights and Rankine cycle. The ideal shaftpower is a function of

outlet heat loads and the difference in Carnot factor between the heat source and

heat sink. The deviation of the actual expansion from the ideal expansion is

defined in terms of isentropic efficiency.

New MethodCogeneration targeting in utility systems is used to determine fuel consumptions,

shaftpower production and cooling requirements before the actual design of the

utility systems[8]. The previous methods available in literature have the following

drawbacks. TH model does not consider the contribution of superheat in the inlet

and the outlet stream in the power generation. THM parameters are based on

regression parameters derived from a small sample of steam turbines, and

consequently are not applicable for all the possible sizes of turbines.

In order to overcome shortcomings of previous methods, new method for

cogeneration targeting has been proposed in this work, and isentropic efficiency

is used in the new targeting method.

TH model for targeting does not include the superheat conditions at each level

which results in significant error for estimating cogeneration potential. THM

model uses an iterative procedure based on specific heat loads to calculate the

mass flowrate for the turbines. The calculation of flowrates in Sorins

methodology is based on the flow of energy. Power produced by the system is

estimated with the isentropic efficiency, available heat for power generation and

inlet and outlet temperatures of Rankine cycle. However, there is no justification

for the assumption that thermodynamic behaviour of all the steam turbines to be

used acts as that of the Rankine cycle.


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The new algorithm calculates the minimum required flowrate from steam

generation unit (e.g. boiler) and the levels of superheat at each steam main

based on the heat loads specified by site profiles of heat sources and sinks.

The algorithm for the new procedure is given in Figure 1. The superheat

temperature calculation at each steam level is made, starting with a certain

superheat temperature of the steam from the boiler. The procedure is based on

the assumption that steam supplied to the site utility systems from a boiler is at

the superheated conditions required as VHP steam level. Figure 2 shows thetemperature entropy diagram for the process. The initial conditions of

superheated steam at higher pressure and temperature level are represented by

point 1. The steam at lower pressure level for an isentropic expansion is shown

as Point 2 on the curve. Isentrotpic expansion with an efficiency of x% is used to

determine the enthalpy at point 2. It is assumed during targeting stage that all the

steam turbines are operating at their full load. The cogeneration potential of the

system is dependent on the expansion efficiency of x. This parameter is

dependent on the capacity of the turbine and detailed calculation is given below.

Steam properties are calculated for the given entropy and pressure at the lower

steam level. If the degree of superheat in the resulting LP steam main is less

than required, then operating conditions of VHP is updated and then re-iterates

the procedure above until the acceptable superheated conditions for LP steam

main is met.


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Figure 1: Algorithm for new method based on isentropic expansion

Given steam levels, inlet superheat of VHP steam, processload, BFW, Condensate temperature

Isentropic efficiency

Calculate superheat temperatures at subsequent lower steamlevel using isentropic efficiencies (Equation 2)

Starting from the lowest level, calculate the mass flow ratesusing Equation 1.

Add flow rates to determine the overall flow rates through eachlevel (bottom up)

LP superheat temperature > LPsaturation temperature + T*

YES

STOP

IncreaseBoiler VHP

superheat

NO


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Figure 2: Temperature Entropy diagram for change in level

In the bottom up procedure, the temperature of the lowest steam level pressure

is first used to calculate the steam mass flowrate for the expansion of steam

between the lowest steam level and the higher pressure next to the lowest one.

This procedure is sequentially repeated until the interval for highest steam

pressure level. Flowrates at the higher levels are determined from the flowrate in

the lower levels. The flowrate of steam for each expansion interval is a function

of the heat load at that level and the enthalpy change to the condensate

temperature at the given level. Superheated steam is condensed and supplied to

downstream processes at condensate temperature of the steam.

H

Qm

=

&

& Eq 1

Where,

m& = mass flow rate

Q& = heat load for a given level

H = Enthalpy change from superheat conditions at the given level to

condensate conditions at that pressure

T

S

1

2

2

P1

P2Real

Isentropic


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Isentropic efficiency calculation

It is designers discretion to use the most appropriate value of isentropic

efficiency for the developed cogeneration targeting method presented in this

paper. On the other hand, information of isentropic efficiency available in the

literature can be also used. Mavromatis and Kokossis[4] developed a

thermodynamic model to estimate the isentropic efficiency of single and multiple

extraction turbines. Varbanov et al.[9] presented equations to determine the

parameters in terms of saturation temperature. Medina-Flores and Picn-

Nez[10] modified the correlations of Varbanov et al.[9] to obtain the regression

parameters as a function of inlet pressure. The regression parameters obtainedby Varbanov et al.[9] from the turbine data of Peterson and Mann[11] are shown

in Table 2.

max,

max

is

isW

W=

=

B

AWW is max,max

satTbbA += 10

satTbbB += 32

Eq 2

Where,

is = isentropic efficiency

isH = isentropic enthalpy change

3210 ,,,,, bbbbBA = Regression coefficients

satT = Inlet pressure of the steam

Table 2: Regression coefficients for single extraction turbines[12]

Single extraction back pressure turbines

Wmax< 2 MW Wmax>2 MW

0b (MW) 0 0


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The results are investigated with STAR, which is Process Integration software

for the design of utility systems for a single process or a group of processes

involving power (electricity) and heat (steam) generation, and associated heat

exchanging and distributing units. The design procedure of utility systems in

STAR requires information about steam flowrates, heat supply and loads, VHP

(very high pressure) steam specification (e.g. VHP steam generation capacity

and temperature at the outlet of the boiler). At the initial targeting stage, some of

these design parameters are not known. The parameters, such as flowrate from

the boiler, steam level conditions, have to be specified for the detailed design in

STAR. The information required for the calculation of cogeneration potential

from the utility systems is current flowrate of steam generated, maximum and

minimum flow rates of equipment, thermodynamic model and efficiency of steam

turbines, steam demand and surplus for each steam main, superheat condition of

steam generated from the boiler, etc. STARhas two models isentropic and THM

model for the calculation of power generation of steam turbine in the detailed

design, while it uses TH and THM model for cogeneration targeting.

3 Optimization of steam levels

As explained before, the choice of steam level in the design of site utility systems

are critical to ensure cost-effective generation of heat and power, and its

distribution in the site. In a new design, pressures of steam level can be readily

optimized. However, for the retrofitting of existing systems, opportunities for the

change of steam level conditions are limited. The mechanical limitation for the

steam mains limits a significant increase in steam pressure. However, long term

investment with a proper optimization of the steam levels may be economically

1b (MWoC

-1) 0.00108 0.00423

2b 1.097 1.155

3b (oC-1) 0.00172 0.000538


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viable in spite of the fact that the short term investment can not be justified[13].

VHP steam generation in the boiler and hence the fuel costs in the utility boilers

can be decreased by increasing number of steam mains which increases the

heat recovery potential. Number of steam mains has a significant impact on the

cogeneration potential. Therefore, to minimise fuel cost with maintaining high

cogeneration potential, the design should be thoroughly investigated.

Optimization model

In this study, the optimisation framework for determining the cost-effective

conditions of steam mains for the site utility systems had been proposed withincorporating new cogeneration targeting method proposed in the work. The

optimisation model is formulated in an NLP (non-linear programming) problem

and the details of models are as follows:

Objective Function

The objective function is to minimize the amount of hot utility to be supplied from

the steam generation unit (e.g. boiler). It should be noted that the method

presented in this paper is generic for taking different objective functions, for

example, overall fuel cost, operating profit, etc, as long as the relevant cost

parameters are available.

minimise VHPsourceheatVHPkshifted HH ,,sin

VHPkshiftedH ,sin Enthalpy of shifted heat sink for VHP

VHPsourceheatH

,

Enthalpy of heat source for VHP

Optimization Variables

iP Pressure at i Steam levels (VHP, HP, MP, LP)

Four steam mains are used in the current optimisation model, as this is most

common in the large-scale industrial plant, while different number of steam


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mains, for example, three levels (HP, MP and LP), can be considered based on

needs and operating characteristics on the plant.

Constraints

Total source and sink profiles are generated from stream data of the site. Design

procedure for manipulating stream data to generate the site profiles is not a part

of this study and those details can be found from Smith [13] and Klemes et al,

[14]. In order to maintain feasibility of heat recovery across steam mains,

constraint between sink and source site profiles is needed. First, the sink is

shifted until the enthalpy of heat source at either of steam levels is the same asthe enthalpy of heat source corresponding to the pinch point, and then enthalpy

difference at each steam levels is always greater than zero.

0,,sin isourceheatikshifted HH i Steam levels (VHP, HP, MP, LP)

Mass balance

The mass flow rate of steam between steam levels is given:

j

jkjji

HQmm

+=

&

&&

Where,

jim & Mass flow rate of steam through turbine between iandjsteam levels

kjm & Mass flow rate of steam through turbine betweenjand ksteam levels

jQ& Heat duty atjsteam level

jH Enthalpy extracted by process from superheated steam atjlevel to reach

condensate conditions

Power is calculated base on the new design algorithm as shown in Figure 1.

Figure 3 shows the model for the determination of optimal steam pressure levels

for a site utility system. The change in the steam pressure levels shifts the site

sink and surplus profiles along with heat demand and supply. Cogeneration


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potential for the site composite is calculated from the new algorithm. The process

is repeated until optimum pressure levels corresponding to minimum value of

objective function are found for the site.

Figure 3: Flowchart to determine optimum steam pressure level

Case Study Cogeneration potentialAn illustrative case study is used to test the different methodologies. The four

steam levels considered in this example are very high pressure (VHP), high

pressure (HP), medium pressure (MP), low pressure (LP) at 120, 50, 14 and 3

bar(a) respectively. The heat demand at HP, MP and LP steam levels is 50, 40

and 85 MW respectively. The efficiency of the boiler is assumed to be 100% for

the simplicity, which can be updated, according to boiler data available, and it is

supplying steam at a temperature of 575oC. Water supplied to the boiler and the

condensate returns are both assumed to be at a temperature of 105oC.

In this work, cogeneration targeting methods have been applied to the case

studies with only back pressure turbines. However, it can be easily extended to

condensing turbines. One of the additional constraints on condensing turbine is a

maximum wetness permitted at the exhaust. Wetness factor in the condensing

turbine can be controlled by adjusting the superheat in the steam mains, as

similary treated in the consideration of degree of superheat in LP steam.

New steam level pressure

Calculate shifted sink and source profiles & heat surplus or

deficit at each steam level

Cogeneration potential calculation from new algorithm

Minimum Utility requirement Optimum

Pressure

NO YES


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Table 3: Problem Data Parameters

VHP HP MP LP

Pressure (bara) 120 50 14 3

Saturation

Temperature (C) 324.7 264 195.1 133.6

Heat Demand

(MW) 0 50 40 85

The isentropic efficiency was calculated as given in Equation 2, while the

mechanical efficiency was assumed to be 100%.

TH Model: The shaftpower targets from TH method are shown in Table 4Error!

Reference source not found.. The overall shaftpower calculated from TH model

is 33.02 MW. The value of conversion factor (CF) is assumed to be 0.00135.

THM Model: The targets for the three sections VHP-HP, HP-MP and MP-LP for

THM model are 9.4, 4.7 and 0 MW respectively (Table 4Error! Reference source

not found.). The overall shaftpower target from THM model was 14.2 MW.

Sorins Methodology: The work in the bottom section is used to calculate the

heat load in subsequent top section as described in the methodology in the

previous section. Shaftpower targets for VHP-HP, HP-MP and MP-LP of 18.2,

14.46 and 8.77 MW are shown in Table 4Error! Reference source not found..

New Method

Error! Reference source not found. Table 4 shows the shaftpower targets for

VHP-HP, HP-MP and MP-LP sections of 14.99, 14.37 and 9.75 MW respectively.

The main difference between the new method and existing TH and THM model is

the calculation of superheat temperature for each steam main, as explained

previously. Superheat temperature of the outlet LP steam should be greater than

saturation temperature of LP steam to avoid condensation of vapour at the outlet


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of turbine and thereby reduced performance and efficiency. The amount of

superheat in VHP steam determines the superheat in LP steam. In the new

algorithm, the superheat in VHP steam from the boiler is a variable and is

adjusted by trial and error to ensure the superheat in LP steam.

Figure 4: Results of the new method

STARSimulation Constant Isentropic Efficiency

Once the steam levels and the heat surplus and deficit are known, a detailed

design procedure is used for the optimal design of the utility systems or to find

out the optimum operating conditions for an existing design. However, as

discussed before, the detailed design requires some additional parameters such

as flowrates and superheat steam temperatures. These additional parameters

are specified by trial and error. STAR was used to test the targeting potential

against the actual production from the steam turbine. The shaftpower was

calculated by the isentropic model with isentropic efficiency calculated as shown

in Equation 2. The utility systems consist of a boiler supplying VHP steam at

575oC. The steam is passed from the boiler to the higher pressure steam main to

lower pressure steam main, via a steam turbine. Any unused steam can be

passed through the vent. The process cooling and heating duty at each steam

VHP Supply

Qusage = 85 MW

Qusage = 40 MW

Qusage = 50 MW

Heat Demand (MW)

VHP

HP

MP

LP

Saturationtemperature(C)

14.99 MW

14.37 MW

9.75 MW

248.29 t/h

185.89 t/h

130.7 t/h


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main level is specified as given in Figure 3Error! Reference source not found..

The overall turbine shaftpower is 39.12 MW.

Comparison of Cogeneration Targeting Results

Table 4Error! Reference source not found. shows a comparison of

cogeneration targeting results from Sorins methodology, new method, TH and

THM model in STAR. A detailed design simulation in STAR with the constant

isentropic method is used to compare the shaftpower targets from the different

methodologies. As shown in Table 4Error! Reference source not found. the

total power target of 41.43 MW from Sorins methodology is significantly differentfrom the detailed design procedure of 39.0 MW with an error of 6.2%. The

shaftpower target obtained from TH model of 33.02 MW is 15.3% different from

the shaftpower obtained from the detailed design procedure. Similarly, THM

model target is 63.85% different from the actual shaftpower from the detailed

design procedure. These discrepancies in the shaftpower targets are due to the

assumptions used in these models. The shaftpower target obtained from the new

method of 39.12 MW is only 0.31% different from the detailed design procedure

in STAR.

Figure 5: STAR

simulation isentropic efficiency


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Table 4: Comparison of cogeneration targeting results

Optimization of steam levels

Site data was taken from an example available in the literature [15]. Site sink and

source profile is shown in Figure 6Error! Reference source not found.. Four

steam mains are available at very high pressure (VHP), high pressure (HP), low

pressure (LP) and medium pressure (MP) respectively. Sink profile is shifted by

the minimum of the enthalpy difference between the source and sink, which

identifies site pinch point for the utility system.

0

50

100

150

200

250

300

-500 -400 -300 -200 -100 0 100 200 300 400

Enthalpy (MW)

Temperature(oC)

Sink

Source

Shifted Sink Profile

Figure 6: Sink and source profiles for a given site

The site utility grand composite curve (SUGCC) plots the difference between the

hot and the cold composite curves as shown in Figure 7Error! Reference

source not found.. The heat generation and use at individual steam level is

Methodology Total(MW)

VHP-HP(MW)

HP-MP(MW)

MP-LP(MW)

Sorins methodology 41.43 18.2 14.46 8.77

New Method 39.12 14.99 14.37 9.75

TH Model in STAR 33.02 14.35 11.62 7.06

THM Model in STAR 14.1 9.4 4.7 0

STAR Simulation Constant

Isentropic Efficiency

39.0 14..85 14.78 9.37


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shown in Figure 7Error! Reference source not found. Error! Reference

source not found. and Error! Reference source not found. plot the

cogeneration potential between different steam levels as expansion zones for

steam turbines. The power output for these zones for the optimized case, based

on the new algorithm, is found to be 7.69 MW.

0

50

100

150

200

250

300

350

400

0 20 40 60 80 100 120 140 160 180 200

Enthalpy (MW)

Temperature(oC)

Figure 7: Site Utility Grand Composite Curve with the optimum steam levels

0

50

100

150

200

250

300

350

400

0 10 20 30 40 50 60 70 80

Enthalpy (MW)

Temperature(oC)

Figure 8: Site Utility Grand Composite Curve with cogeneration areas

0

50

100

150

200

250

300

350

400

-500 -400 -300 -200 -100 0 100 200 300 400

Enthalpy (MW)

Temperature(oC)

Sink

Source

Figure 9: Site profile targets for steam generation and steam usage


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0

50

100

150

200

250

300

350

400

-450 -400 -350 -300 -250 -200 -150 -100 -50 0 50 100

Enthalpy (MW)

Temperature(oC)

Figure 10: Site profile with cogeneration potential area

The objective function is the minimization of the utility cost. The hot utility is

supplied as VHP steam from the boiler. The optimization framework described in

previous section and the model calculations are performed in Microsoft Excel.

The size of the model and the optimization problem is small and therefore solver

function in Microsoft Excel can be effectively used for the minimization of the

utility cost. The number of steam levels has been assumed constant as four

corresponding to VHP, HP, MP and LP respectively. Steam pressures at each

level are the design variables. They affect both the level of heat recovery and the

cogeneration potential, via the steam turbine network[13].

Table 5Error! Reference source not found. shows the base case conditions for

the four steam levels. Optimum steam level pressure and temperature along

with heat load at each level is shown in Table 6Error! Reference source not

found.. The optimum pressure in the steam mains for the lowest utility cost are

180, 46.55, 12.26 and 2.25 bar in the VHP, HP, MP and LP steam loads

respectively. The minimum VHP steam generation required from the boiler is70.22 MW, while the VHP steam flowrate requirement from the boiler is 88.16

t/hr. Steam generation required at VHP mains has been reduced from 105.20

MW to 70.22 MW for the optimized case. However, the cogeneration potential

reduced from 8.8 MW for base case to 7.67 MW for the optimized case.

Therefore, increasing the heat recovery reduces the steam generation from the

boiler as well as the cogeneration potential for this particular example. If power


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generation in the site should be increased, then additional VHP steam is

generated to pass through steam mains.

Table 5: Base case steam levels[15]

Pressure (bar) Temperature (oC) Heat Load (MW) Saturation temperature (

oC)

180 625 105.20 357.14

50 458.74 137.01 264.09

10 322.1 125.29 180.04

2 143.63 81.98 120.36

Table 6: Optimized steam levels

Pressure (bar) Temperature (oC) Heat Load (MW) Saturation temperature (

oC)

180 625 70.22 357.14

46.65 449.21 113.45 259.7912.26 308.08 107.57 189.09

2.25 214.48 55.34 124.10

This optimisation framework can be extended to accommodate other economic

scenarios (e.g. to minimise the fuel costs with maintaining the same cogeneration

potential) or practical constraints (e.g. the number of steam levels allowed).

4 Technology for utilization of low Grade heatLow grade heat source can be very useful to provide energy to the heat sink by

upgrading low-grade energy (e.g. low pressure steam). The upgrade of low grade

heat can be carried out by heat pump, absorption refrigeration, thermo

compressor, etc, by recovering and/or upgrading waste heat from various

sources (e.g. gas turbine exhaust) and utilising them with the wide range of

applications (e.g. drying and boiler feedwater heating).

4.1 Vapour compression heat pumpHeat pump transfers the low grade heat at the lower temperature to higher

temperature heat by the compressor. Heat pump has been used in petroleum

refining, and petrochemicals, wood products, pharmaceuticals, utility system etc.

[16]. Figure 11 shows a typical closed cycle heat pump. The heat from lower

temperature source is transferred to the working refrigerant in the evaporator.

Electric or mechanical energy is used in the compressor to increase the pressure


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of the vapour from the evaporator. High grade heat at higher temperature is

released from the condenser. Pressure of the vapour is reduced by throttle valve

to lower its temperature and convert it to liquid to exchange heat with low grade

heat source. The main issue with the utilization of the heat pump is that it uses

expensive external energy to convert low grade heat into high grade heat. In

general, one unit of high grade electrical energy can produce 2-4 units of high

grade thermal energy.

Figure 11: Heat pump cycle [17]

Co

E

Q

QCOP =

Eq 3

Where,

COP= coefficient of performance

EQ = Heat received at low temperature by the evaporator

CoQ = Electric power supplied in the compressor

4.2 Absorption Systems

Low grade heat can be recovered by absorption with three different types of

equipments absorption refrigeration, absorption heat pump and absorption

Condenser

CompressorPrime

Mover

Evaporator

Heat from lower temperature source

Throttle

valve

Mechanical

work input


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transformers respectively. Iyoki and Uemura [18] compared the performance of

absorption refrigeration, absorption heat pump, and absorption transformer for

water-lithium bromide zinc chloride calcium bromide system.

a) Absorption refrigeration There has been extensive work in literature on

absorption refrigeration system, with both experimental [19] and simulation

studies [20, 21] to determine the performance of absorption refrigeration. A

schematic diagram of ammonia-water absorption refrigeration cycle is shown in

Figure 12. Ammonia vapour at high pressure transfers heat to neighbourhood in

the condenser. Liquid ammonia from the condenser is passed through an

expansion valve to reach the evaporator pressure. Heat is transferred from thelow temperature heat source to convert liquid ammonia to vapour state.

Ammonia vapour is absorbed by a weak solution of water and ammonia to form a

concentrated solution of ammonia-water at the bottom of absorber. This

concentrated solution is passed to the generator for the production of ammonia

vapour while the lean solution from the generator is passed back to the absorber

unit. Low grade heat is used in the generator for the production of ammonia

vapour. Lean ammonia solution from the generator exchanges heat with the high

concentration ammonia solution from the absorber.

Figure 12: Ammonia water absorption refrigeration cycle [19]


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The coefficient of performance for an absorption refrigeration system is defined

as the ratio of heat removed from the evaporator to heat supplied in the

generator.

G

E

Q

QCOP =

Eq 4

Where,



GQ = High temperature heat used in the generator

b) Absorption heat pump A single stage absorption heat pump consists of a

generator, absorber, evaporator, condenser and heat exchanger. High grade

heat is supplied at higher temperature to the generator to separate the refrigerant

from the solution. Low grade waste heat is supplied to the evaporator, while

medium temperature heat is released from the condenser. Thermal energy at

higher temperature is used to convert low grade heat into high grade heat.

Coefficient of performance of an absorption heat pump is the ratio of heat

removed from the medium temperature heat removed form the absorber and

condenser to the high grade heat supplied in the generator.

G

CA

Q

QQCOP

+=

Eq 5

Where,


AQ = Heat released by the absorber

CQ = Heat released by the condenser


c) Absorption heat transformer The basic schematic diagram of absorption

heat transformer is shown in Figure 13. Absorption heat transformer consists of


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the same units as absorption heat pump. However, the main difference is that

evaporator and absorber are maintained at a higher pressure, while in absorption

pump they are at a lower pressure. Low grade heat is used in the generator and

evaporator to produce heat at higher temperature in the absorber. The process

can be described briefly as follows: High pressure refrigerant vapour from an

evaporator is absorbed into the lean refrigerant absorbent solution in the

absorber. High pressure strong solution of refrigerant absorbent is passed via a

throttle valve to reduce the pressure. This solution exchanges heat with weak

solution from a generator, before it reaches the generator. Low temperature heat

in the generator is used to separate the refrigerant from the solution. Refrigerantvapour from the generator is condensed in a condenser. The refrigerant is

subsequently pumped to higher pressure where it gains heat at low temperature

to convert into vapour.

Figure 13: Absorption heat transformer (Ammonia water)

The ratio of high temperature heat from the absorber to the low grade heat

supplied in the generator and evaporator is defined as the coefficient of

performance of absorption transformer.

EG

A

QQ

QCOP

+=

Eq 6

Heat Exchanger

AbsorberEvaporator

GeneratorCondenser


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27

Where,


AQ = Heat released by the absorber

EQ = Heat consumed in the evaporator


4.3 Boiler feed water (BFW) heating

Low grade heat can be used to increase the temperature of make-up water to

reduce the fuel cost in the boiler. Additional heat exchanger capital cost isrequired for exchange of heat between the boiler make up water and low grade

heat. The increase in temperature of make up water using low grade heat

decreases the fuel consumption in the boiler.

4.4 Organic Rankine Cycle (ORC)

A Rankine cycle for extracting electricity from waste heat sources is possible with

the use of organic fluids as working fluids. Efficiency of operation of Rankine

cycle depends on conditions of the cycle and working fluid. A typical organic

Rankine cycle consists of an evaporator, turbine, condenser and pump

respectively (Figure 14). Organic fluid such as benzene, toluene, p-xylene and

refrigerants R113 and R123 [22] have been used as working fluids in ORC.

Working fluid vaporises by exchanging heat with low grade heat in the

evaporator. Vapour is passed through turbine for generation of electricity. Vapour

is condensed in condenser at lower temperature and releases heat to the outside

atmosphere. Organic fluid is raised from lower pressure to high pressure in the

pump. The amount of energy consumed in pumping the fluid is considerably low.


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Figure 14: Organic Rankine Cycle (ORC)

Efficiency of ORC is defined as the ratio of power generated by the turbine to the

low grade energy supplied in the evaporator.

E

turbORC

Q

P=

Eq 7

Where,

ORC = Efficiency of ORC


turbP = Electric power generated by the turbine

4.5 Thermo-compressor

Thermo-compressor uses high pressure steam to compress low or intermediate

pressure waste steam into medium pressure steam. Figure 15 shows a thermo-

compressor where high pressure steam enters as a high velocity fluid, which

entrains the low pressure steam by suction. The resulting mixture is compressed

and discharged as a medium pressure steam from the divergent section of the

thermo-compressor. The main advantage of thermo compressor is high reliability

and less compression power requirement.

Turbine

Pump

Condenser


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Figure 15: Thermo compressor1

4.6 Drying

Biomass (wood, bagasse, grass, straw, agriculture residues, etc.) have

significant amount of moisture. This moisture reduces the theoretical flame

temperature as a part of heat of combustion is used in evaporation of moisture

from the biomass [23]. Calorific value and theoretical flame temperature from the

biomass fuels can be increased by drying. Effective use of industrial waste heat

in drying of biomass increases the overall efficiency of the process, leading to

significantly lesser amount of fossil fuel to be burned and hence much less green

house emissions.

5 Algorithm

Once the number of steam levels and their pressure has been determined by

optimization in total site profiles, the performance of the system can be either

optimized to obtain the best design, or to obtain the optimum operating

conditions for an existing design, considering the part load performance of theequipment. The simulation and optimization of the utility systems require

accurate and yet simpler model for each element of the system. Varbanov [9]

and Aguillar [24] developed simple models for the equipments in the utility

systems. Models developed by Aguillar [24] have been adopted for the purpose

1(http://www.em-ea.org/Guide%20Books/book-2/2.8%20Waste%20Heat%20Recovery.pdf)


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of optimization which determines the optimum design (i.e. the configuration of

utility systems) or operating conditions in this work (Appendix A).

The algorithm for evaluation of integration of low grade heat upgrade

technologies with an existing site utility system is shown in Figure 16. The

characteristics of low grade energy such as available heat load at temperatures

for use in heat pump, ORC, and boiler feed water heating is obtained from total

site sink and source profiles. HYSYS simulation is used to obtain the

performance indicators such as COP, efficiency, purchase cost etc. for low grade

heat upgrade technology. Heat load is varied for the HYSYS simulation to

calculate the change in performance and purchase cost. This information is fedto the optimization framework for calculating the overall annual cost with

integration of these design technologies. The optimization framework [24] is used

for minimization of overall annual cost or operating cost minimization for a

multiperiod operational, retrofit or grassroots design problem. Linear models

have been derived for all the energy equipments so that MILP optimizers can be

used for optimization to reduce the computational cost.

Figure 16: Algorithm for evaluation of low grade heat upgrade technology


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6 Case study

The various design options for low grade heat upgrade are evaluated with thehelp of a case study. The base case design is shown in Figure 17. The base

design consists of four boilers each with capacity of 40 kg/s. There are four back

pressure turbines for generation of electricity from VHP to HP and one back

pressure turbine between HP and LP steam levels. Two multistage turbines are

available for expansion of steam between HP-MP and MP-LP respectively. Four

mechanical pumps having a steam turbo driver and an electric motor supply the

feed water to the boiler.

Figure 17: Base case design [24]

Site data for heat load, electricity demands, pump electricity demand,

condensate return and cooling water is shown in Table 7. The site operating

seasons are divided into two major categories summer and winter, with 67% of

year as winter. The ambient temperature, relative humidity, electricity natural gas

and fuel oil price is shown in Table 8. The total number of working hours for the


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site is assumed to be 8600 hrs per year. The latent heat values for fuel oil and

natural gas are 45 and 50.24 MJ/kg respectively.

Table 7: Total site data - Requirements for the utility system

Units Winter Summer

Electricity demand MW 62 68

VHP steam demand MW 116.36 110.82

HP steam demand MW 30.61 21.4

MP steam demand MW 16.67 9.34

LP steam demand MW 88.54 73.62

Total steam demand MW 252.17 215.17

Condensate return % 80 80

Power Pump 1 MW 5.2 5.0




Process CWdemand

MW 200 300

Table 8: Site conditions

Season Units Winter Summer

Fraction of the year % 67 33

Ambient temperature oC 10 25

Relative humidity % 60 60

Electricity prices Peak ($/kWh) 0.07 0.08

Off- Peak ($/kWh) 0.05 0.05

Peak hours /day Hrs 7 12

Fuel Oil price $/kg 0.19 0.19

Natural gas price $/kg 0.22 0.22

Raw water price $/ton 0.05 0.05

Grand composite curves (GCC) of the individual process are modified by

removing the pockets corresponding to additional heat recovery within the

process. These modified process GCC are then combined together to form the

total site sink and source profile (Figure 18(a)). Sink profile is shifted until the

source and shifted sink profile touch each other (Figure 18(b)) or the source and

the sink steam generation and consumption lines touch each other

corresponding to site pinch. Site utility grand composite curve (SUGCC)

represents the horizontal separation between the source and the sink. Steam

demand at VHP, HP, MP and LP levels are 110.8, 21.4, 9.3 and 73.6 MW


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respectively. Power generation potential is represented as areas in SUGCC with

VHP-HP, HP-MP and MP-LP cogeneration potential of 79.8, 58.4 and 49.1 MW

respectively (Figure 18(c)).

-400 -300 -200 -100 0 100 200 300 4000

50

100

150

200

250

300

350

Enthalpy (MW)

Temperature(oC)

-400 -300 -200 -100 0 100 200 300 4000

50

100

150

200

250

300

350

Enthalpy (MW)

Temperature(oC)

(a) (b)

0 50 100 150 200 2500

50

100

150

200

250

300

350

Enthalpy (MW)

Temperature(oC)

(c)

Figure 18: Site composite curves; (a) Site source and sink composite curve (b) Site source

and shifted composite curve with the cogeneration potential area (c) Site utility grand

composite curve (SUGCC)

Integration of heat pump

HYSYS model heat pump

A model of heat pump has been simulated in HYSYS. It consists of four

equipments evaporator (E-102), compressor (K-100), condenser (E-100) and a

throttle valve (VLV-100). Refrigerant R112-a is used as a working fluid. Low

grade heat is supplied in the evaporator at the temp of 115oC. High grade electric

energy is used in the compressor to raise the pressure of the vapour. LP steam


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is generated from the condenser at temperature of 150oC. Throttle valve is used

to reduce the pressure of the vapour liquid mixture from the condenser.

Figure 19: Vapour compression heat pump

Figure 20 shows the variation of COP for heat pump system with respect to

variation in the evaporator duty. COP varies within a small range from 3.24-3.31

and can be assumed to be constant for the refrigerant (R-112a) and the

corresponding heat pump cycle (Figure 19). COP of 3.3, means that 1 MW of

electric energy and 2.3 MW of low grade energy generate 3.3 MW of high grade

energy.


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3.23

3.24

3.25

3.26

3.27

3.28

3.29

3.3

3.31

0 10000 20000 30000 40000 50000 60000 70000 80000 90000

Evaporator Duty

COP

Figure 20: COP with respect to evaporator duty

Purchase cost of heat pump

Purchase cost of heat pump is calculated as the sum of the cost of evaporator,

condenser, and compressor. Purchase cost of heat pump is approximated based

on a linear correlation between the cost and the evaporator duty.

BHAPC evapumpheat += Eq 8

Where,

pumpheatPC = Purchase cost heat pump

evaH = Evaporator duty (MW)

A, B= Regression coefficients

A = 0.1 MM$/MW

B= 1.15 MM$

Purchase cost

y = 0.0001x + 1.1491

0

2

4

6

8

10

12

0 10000 20000 30000 40000 50000 60000 70000 80000 90000

Evaporator duty (kW)

PurchaseCost(MM$)

Figure 21: Linear correlation between purchase cost and evaporator duty


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The total site source and sink profile before and after integration of the heat

pump is shown in Figure 22 and Table 9. LP steam demand changes from 73.62to 18.67 MW in summer and from 88.54 to 33.59 MW in winter. Low grade heat

is extracted from the site source only till 115oC corresponding to temperature diff

of 10oC in the evaporator of the heat exchanger. COP of heat pump as

calculated from HYSYS simulations is 3.3. Therefore, the external electricity

consumption from the site increases as shown in Table 10 from 68.82 to 85.42

MW in summer and from 62.2 to 78.8 MW in winter.

Table 9: LP steam demand before and after integration of heat pump

Summer(MW) Winter(MW)

Before heat pump 73.62 88.54

After heat pump 18.67 33.59

Table 10: Electricity demands before and after integration of heat pump




-400 -300 -200 -100 0 100 200 300 4000

50

100

150

200

250

300

350

Enthalpy (MW)

Temperature(oC)

Figure 22: Site composite curve with heat pump integration

Annualized capital cost with operational optimization of the existing plant

Operational optimization of total site annual cost with the integration of heat

pump is shown in Table 10. External power cost increases from 22.67 MM$ to


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35.03 MM$ after integration of heat pump, while fuel cost decreases from 93.08

to 82.09 MM$. Total annual cost increases to 118.67 MM$/yr from 116.32

MM$/yr after integration of heat pump. Therefore, with these costs of fuel and

electricity and the capital cost of heat pump it is not economic to set up a heat

pump.

Table 11: Annual costs before and after integration of heat pump

External Power (MM$) Fuel Cost (MM$)



Integration of Organic Rankine Cycle (ORC)

HYSYS model ORC

HYSYS is used to calculate the efficiency and the purchase cost function for

ORC. ORC set up consists of an evaporator (E-100), turbine (K-100), condenser

(E-101) and a pump (P-100). Benzene is used as the organic working fluid. Low

grade heat at 110 oC is used to vaporize benzene at high pressures (1.145 bar).

Benzene vapour is used to drive a turbine along with reduction in pressure (14.5

kPa). Vapour stream from turbine at low pressure condensed in the condenser

(27oC). Pump is used to pump the low pressure organic liquid stream to high

pressure (1.145 bar) before being fed to the evaporator.


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Figure 23: Organic Rankine Cycle (ORC)

Efficiency of ORC

Figure 24 shows the variation of efficiency of ORC with respect to evaporator

duty. The efficiency of ORC is approximately constant around 11% with the

variation in evaporator duty.

0

2

4

6

8

10

12

0 2 4 6 8 10 12

Evaporator duty (MW)

Efficiency

Figure 24: ORC efficiency with evaporator duty

Purchase cost of ORC

Purchase cost of ORC is given as the total cost of equipments such as

condenser, evaporator and turbine. The cost of the evaporator and condenser is


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obtained from the online database2, while turbine cost is obtained from Peters et

al. [25]. Purchase cost of ORC is approximated based on a linear correlation

between the cost and the evaporator duty.

BHAPC evaORC += Eq 9

Where,

ORCPC = Purchase cost ORC

evaH = Evaporator duty (MW)

A, B= Regression coefficients

A = 0.01 MM$/MW

B= 25.1 MM$

y = 1E-05x + 0.2506

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 10000 20000 30000 40000 50000 60000 70000 80000

Evaporator Duty (kW)

PurchaseCost(MM$)

Figure 25: Linear correlation between purchase cost and evaporator duty

The total site source and sink profile after integration of heat pump is shown in

Figure 26. Low grade heat corresponding to 62.11 MW is saved corresponding to

a temperature of 105oC. Cold utility requirement is reduced by 62.11 MW. As

shown before with the efficiency of 11%, the amount of electrical energy is

reduced from 68.82 to 61.99 MW during summer and from 62.2 to 55.39 MW

during winter. Purchase cost of ORC corresponding to given evaporator duty is17.13 MM$.

2http://www.matche.com/EquipCost/Compressor.htm.


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-400 -300 -200 -100 0 100 200 300 4000

50

100

150

200

250

300

350

Enthalpy (MW)

Temperature(oC)

Figure 26: Site composite curve with ORC integration

Table 12: Electricity demands before and after integration of ORC




Absorption refrigeration

HYSYS model of absorption refrigeration

Absorption refrigeration system (Figure 27) consists of absorber (T-101), pump

(P-100), heat exchanger (E-104), generator (T-103), evaporator (E-100), and

condenser (E-103). Heat is released at temperature of 32oC to the surrounding at

a pressure of 13 bar in the condenser (E-103). Ammonia vapours are passed

through a throttle valve (VLV-101) to reduce the pressure to 14.50 kPa before

they can absorb heat from the surroundings at low temperature (-5o

C) asrefrigeration load in the evaporator (E-100). Ammonia vapour is absorbed with

the lean solution of ammonia in the absorber (T-101). Heat is released to the

surroundings from the absorber. Concentrated solution of ammonia water is

pumped from 14.59 kPa to 13 bar into the generator. Low grade heat is used in

the generator (T-100) to separate ammonia from the concentrated solution to

produce a lean solution of ammonia water. Heat is exchanged between outgoing


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lean solution of ammonia water and incoming strong solution in exchanger T-

103.

Figure 27: HYSYS model of absorption Refrigeration

Coefficient of performance

Low grade heat is used to provide the heat for refrigeration load for the system.

The low grade heat supplied in the generator is 265.4 kW, while 67.86 kW of

heat is removed as refrigeration load from the evaporator, with a COP of 0.26.


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-400 -300 -200 -100 0 100 200 300 4000

50

100

150

200

250

300

350

Enthalpy (MW)

Temperature(oC)

Figure 28: Low grade heat can be used for refrigeration load on site

Boiler feed water heating

Low grade heat is used to raise the temperature of make up water to deaerator

from 25oC to 101.3oC. This reduces the cost of fuel consumed in the boiler. The

benefits of BFW heating depends on condensate recycling process and

condensate management. BFW heating doesnt change the hot utility

requirement from the base case. However, the cost of fuel required to supply the

hot utility required decreases from 93.08 to 80.57 MM$/yr due to decrease in the

heating required for boiler feed water. The overall energy cost decreases from

117.83 MM$/yr in the base case to 107.63 MM$/yr.

Absorption Refrigeration


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-400 -300 -200 -100 0 100 200 300 4000

50

100

150

200

250

300

350

Enthalpy (MW)

Temperature(oC)

Figure 29: Temperature of make up water to deaerator is increased by low grade heat

Comparison of design options

Techno economic analysis

Table 13Error! Reference source not found. shows the comparison betweenthe various low grade heat upgrade options. Heat pump decreases the hot utility

requirement by reducing the low pressure steam demand for the system. Hot and

low utility cost in the system decreases from 93.08 to 82.09 MM$/yr and 0.98 to

0.90 MM$/yr respectively. However, heat pump increases the electricity import

cost for the site from 23.77 to 36.06 MM$/yr. The overall operating cost increases

from 117.83 to 119.06 MM$/yr with the introduction of heat pump. Therefore,

heat pump is not economic for the current case study with the given cost of

electricity and fuel. Integration of ORC decreases the cold utility requirement and

therefore reduces the total utility cost from 94.06 to 94.02 MM$/yr. Electricity

produced from ORC reduces the cost of electricity import from 23.77 to 20.21

MM$/yr. The total energy cost decreases from 117.82 MM$/yr in the base case

to 114.23 MM$/yr for integration with ORC. Absorption refrigeration reduces the

cold utility cost from 0.98 to 0.90 MM$/yr. However, the main advantage of

absorption refrigeration is reduction in electricity cost in vapour compression

Boiler feed water heating


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refrigeration by 5.46 MM$/yr. BFW heating reduces the cost of hot utility

requirement from 93.08 to 80.57 MM$/yr. Total energy cost decreases from

117.83 to 106.63 MM$/yr. This corresponds to an annual savings of 9.51% in the

operating cost. BFW heating is the most economical options amongst the heat

upgrade technologies. However, benefits of BFW heating depends on the

condensate recycle policy and condensate management.

Table 13: Techno economic evaluation of low grade heat upgrade technologies

Options Hot utility (MW) Cold utility (MW) Hotutilitycost(MM$/yr)

ColdUtilitycost(MM$/yr)

Totalutilitycost(MM$/yr)

Electricityimport(MM$/yr)

Totalenergycost(MM$/yr)

Winter Summer Winter Summer

Base case 252.17 215.17 368 368 93.08 0.98 94.06 23.77 117.83Heat Pump 197.23 160.23 344.11 344.11 82.09 0.90 82.99 36.07 119.06ORC 252.17 215.17 344.11 344.11 93.08 0.94 94.02 20.21 114.23Absorptionrefrigeration

252.17 215.17 344.11 344.11 93.08 0.90 93.98 23.77 117.75

BFWheating

252.17 215.17 368 368 80.57 0.98 81.55 25.08 106.63

7 Conclusions & future work

The selection of steam level conditions is important as this significantly affectsheat and power management for the industrial site. A new cogeneration targeting

model has been developed in this work, as existing models have been shown to

give misleading results, compared to detailed design procedure. This new model

is based on isentropic expansion and the results obtained from the new model

have been shown to agree well with the results from the detailed isentropic

design method simulated in STAR. The new method has been incorporated in

the optimisation study which systematically determines of the levels of steam

mains at minimum utility requirement.

Multiple options such as heat pumping, CHP, integrated gas turbines, absorption

refrigeration, drying, etc, are available for upgrading low grade heat. Heat pump

can reduce the LP steam requirement and subsequently the fuel consumed in

the boiler. However, electrical consumption in the site increases with the

integration of heat pump. The overall operating cost increases with the heat

pump for the current case study for the current ratio of fuel to electricity price.


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ORC decreases the annual operating cost for the total site by reducing the

electricity demand from the site. Absorption refrigeration only reduces the

demand of cold utility. However the major savings comes from reduction in the

electricity demand for an existing vapour compression refrigeration system on the

site. Heating of boiler feed water decreases the fuel consumption in boiler and

hence the overall operating cost of the site. In conclusion BFW heating the

optimum option for integration with the total site in this case study. However, the

best heat upgrade technology is dependent on the site fuel and electricity cost,

condensate management system, and characteristics of low grade heat (quality

and size). The developed methodology will be applied to further extended toother case studies. Integration of renewable energy sources such as solar, wind,

geothermal etc to the total site will be considered in future work. The variation in

renewable energy sources will be incorporate to the framework. The transfer of

low grade heat across the fence for neighbourhood integration will be considered

in future work. The cost benefit of over the fence process integration needs to be

evaluated.

Acknowledgement

Financial support from Research Councils UK Energy Programme

(EP/G060045/1; Thermal Management of Industrial Processes) is gratefully

acknowledged.

References

[1] Pellegrino JL, Margolis N, Justiniano M, Miller M, Thedki A. Energy Use,

Loss and Opportunities Analysis. In: Energy UDo, ed.: Energetics, Incorporated

and E3M 2004:169.

[2] Dhole VR, Linnhoff B. Total site targets for fuel co-generation, emissions,

and cooling. Computers and Chemical Engineering. 1993;17(Suppl):101-9.


46/58

46

[3] Kundra V. To Develop a systematic methodology for the implementation of

R-curve analysis and its use in site utility design and retrofit [MSc. Dissertation].

Manchester: University of Manchester; 2005.

[4] Mavromatis SP, Kokossis AC. Conceptual optimisation of utility networks

for operational variations - I. Targets and level optimisation. Chemical

Engineering Science. 1998;53(8):1585-608.

[5] Salisbury JK. The Steam-Turbine Regerative Cycle - An Analytical

Approach. Trans ASME. 1942;64:231-45.

[6] Raissi K. Total site integration [PhD Thesis]. Manchester: UMIST; 1994.

[7] Varbanov PS, Doyle S, Smith R. Modelling and optimization of utilitysystems Chemical Engineering Research and Design. 2004;82(5):561-78

[8] Sorin M, Hammache A. A new thermodynamic model for shaftwork

targeting on total sites. Applied Thermal Engineering. 2005;25(7 SPEC.

ISS.):961-72.

[9] Varbanov PS. Optimisation and synthesis of process utility systems.

Manchester: UMIST; 2004.

[10] Medina-Flores JM, Picn-Nez M. Modelling the power production of

single and multiple extraction steam turbines Chemical Engineering Science.

2010;65(9):2811-20

[11] Peterson JF, Mann WL. STEAM-SYSTEM DESIGN: HOW IT EVOLVES.

Chemical Engineering (New York). 1985;92(21):62-74.

[12] Varbanov PS, Doyle S, Smith R. Modelling and optimization of utility

systems. Chemical Engineering Research and Design. 2004;82(5):561-78.

[13] Smith R. Chemical Process Desing and Integration: John Wiley & Sons

Ltd. 2008.

[14] Klemes J, Friedler F, Bulatov I, Varbanov P. Sustainability in the Process

Industry: Integration and Optimization. New York, USA: McGraw Hill 2010.

[15] Perry S. Synthesis of total utility system Process Integration Research

Consortium. Manchester 2009.

[16] Chua KJ, Chou SK, Yang WM. Advances in heat pump systems: A review.

Applied Energy. 2010;87(12):3611-24.


47/58

47

[17] Singh H, Muetze A, Eames PC. Factors influencing the uptake of heat

pump technology by the UK domestic sector. Renewable Energy.

2010;35(4):873-8.

[18] Iyoki S, Uemura T. Performance-characteristics of the water lithium

bromide zinc-chloride calcium bromide absorption refrigerating machine,

absorption heat-pump and absorption heat transformer. International Journal of

Refrigeration-Revue Internationale Du Froid. 1990;13(3):191-6.

[19] Manzela AA, Hanriot SM, Cabezas-Gmez L, Sodr JR. Using engine

exhaust gas as energy source for an absorption refrigeration system. Applied

Energy. 2010;87(4):1141-8.[20] Dincer I, Dost S. Energy analysis of an ammonia-water absorption

refrigeration system. Energy Sources. 1996;18(6):727-33.

[21] Sozen A, Yucesu HS. Performance improvement of absorption heat

transformer. Renewable Energy. 2007;32(2):267-84.

[22] Hung TC. Waste heat recovery of organic Rankine cycle using dry fluids.

Energy Conversion and Management. 2001;42(5):539-53.

[23] Amos WA. Report on Biomass Drying Technology. 1998 [cited NREL/TP-

570-25885; Available from: http://www.nrel.gov/docs/fy99osti/25885.pdf

[24] Aguillar O. Design and optimisation of flexible utility systems [PhD Thesis].

Manchester: University of Manchester; 2005.

[25] Peters MS, Timmerhaus KD, West RE. Plant Design and Economics for

Chemical Engineers: McGraw-Hill 2003.

8 Appendix A

8.1 Optimization framework

8.1.1 Objective function

The present work used overall operating cost along with annual capital cost for

the new design heat upgrade technology as the minimization function.

( ) FixOpCstFEmmCstWatCstPowCstFuelCstOpCst opcst ++++= Eq10


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Where,

opcstF Factor to increase operating cost by a percentage (fraction)

OpCst Overall annual operating plant cost (MM$/yr)

FuelCst Overall fuel cost for the site utility system (MM$/yr)

PowCst Overall electricity cost for the site utility system (MM$/yr)

WatCst Overall water cost for the site utility system (MM$/yr)

EmmCst Overall emission cost for the site utility system (MM$/yr)

FixOpCst Fixed charge for operating cost (MM$/yr)

Capital cost for any additional unit is defined as a function of the purchase cost

( nPurCst ) for each piece of equipment.

fixn

ninstcepci CapPurCstFFCapCst +

=

Eq 11

Where,

cepciF Chemical engineering plant cost index

instF Installation factor to consider other plant expenses

fixCap Fixed capital cost for the whole plant (MM$)

nPurCst Purchase cost for nequipment unit (MM$)

Total cost for the whole site is given by the following expression

annFCapCstOpCstTotCst += Eq 12

Where,

TotCst Total annualized cost (MM$/yr)

Fann Annualisation factor


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Optimization constraints

8.1.2 Electric balances

The cost of electricity consumed or produced on a site on the overall annual

operating cost is calculated by the electrical balance between site sources and

sinks.

impgenlossauxdem WeWeWeWeWeWe +=+++ exp Eq 13

demWe Total electricity demand of the process in each period (kWe)

expWe Electricity exported by the utility system in each period (kWe)

auxWe Electricity consumed by auxillary units including boiler fans, pumps,

cooling fans, motor drivers (kWe)

lossWe Distribution and control electricity loss (kWe)

genWe Electricity generation from the site utility system (kWe)

impWe Electricity imported by the site (kWe)

8.1.3 Mass balances

The mass balance at each node is

= outin MM Eq 14

Mass flow of steam into the deaerator where water is scrubbed with LP steam

before it is delivered to the boiler as saturated water.

vntdea

bfwmkupcondretstmdea MMMMMM +=+++

Eq 15

Mass balance for the steam header is based on the mass flow from producers

(boilers, HRSG), receive or deliver steam to and from steam turbines, let down

valves or process etc.

+++

=+++++

k k k

vntk

outletk

k

outSTk

consk

k

dshk

k

inletk

k

inSTk

k

genk

k

HRk

k

boik

MMMM

MMMMMM

Eq16


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Make up water is equal to the condensate lost by the process, along with the

losses in the utility plant including losses in boiler, HRSG, vent, gas turbine, and

process etc.

( ) vntlossvntdea

ret

k

genk

consk

k

vntk

injGT

HRbldwn

boibldwn

mkup MMMMMMMMMM +++++++= Eq17Where,

k Steam header index in the utility plant

inM Mass flow into a mixing node (kg/s)

outM Mass of steam out from a mixing node (kg/s)

stm

dea

M Mass flow rate of steam into deaerator (kg/s)

retM Returning condensate from the process(kg/s)

condM Mass flow rate of the condensate (kg/s)

mkupM Water make up for the utility system (kg/s)

bfwM Mass flow of water to the boiler (kg/s)

vntdeaM Vented steam from the deaerator (kg/s)

boikM Steam delivered by boiler to header k(kg/s)

HRkM Steam delivered by HRSG to header k(kg/s)

genkM Steam generated by process and delivered to the header (kg/s)

inSTkM

Discharge from steam turbine into header k(kg/s)

inletkM

Letdown steam entering header k(kg/s)

dshkM De-superheating boiler feed water injected into header k(kg/s)

conskM Steam consumed by process at header k(kg/s)

outSTkM Steam release by steam turbine to header k(kg/s)

outletkM

Steam leaving header kby letdown (kg/s)

vntkM Vented steam for header k(kg/s)

mkupM Water make up for utility system (kg/s)

boibldwnM Blowdown for all boiler in utility system (kg/s)

HRbldwnM Blowdown from all HRSG in utility system (kg/s)


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injGTM Steam injected to all gas turbine in utility system (kg/s)

vntkM Steam vented from header k(kg/s)

8.1.4 Heat balance

Heat balance for two streams in adiabatic mixing is shown in Equation 18-19.

= outin QQ Eq 18

( ) ( ) = outoutinin MhMh Eq 19

Enthapy balance for the deaerator is given by Equation 20. The enthalpy balance

for a steam header consists of heat from the generator (boiler and HRSG), both

production and consumption from steam turbine, let down, and process

(Equation 21-22).

vntdea

gdea

bfwdea

fdea

mkupmkupcondcondretretstmdea

stmdea MhMhMhMhMhMh +=+++

Eq20

( ) ( ) ( ) ( )

( ) ( ) ( )

+++++

=++

++++

k k k k k k

vntk

dshk

outSTk

genk

bHRk

boik

hdrk

k

vntk

hdrk

k

dshk

bfwk

k

inletk

inletk

k

inST

k

inST

kk

gen

k

gen

kk

bhr

k

hdr

kk

boi

k

hdr

k

MMMMMMh

MhMhMh

MhMhMhMh

Eq

21

( ) ( )

+++

=+++

k k

dshk

inletk

inSTk

k

genk

hdrk

dshk

bfwk

k

inletk

inletk

k

inSTk

k

genk

genk

MMMMh

MhMhQMh

Eq22

Where,

k Steam header index

inQ Heat entering a mixing node (kW)

outQ Heat leaving a mixing node (kW)

inh Specific enthalpy of heat entering a mixing node (kJ/kg)


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outh Specific enthalpy of heat leaving a mixing node (kJ/kg)

fdeah Enthalpy of saturated steam at deaerator pressure(kJ/kg)

gdeah Enthalpy of saturated vapour at deaerator pressure(kJ/kg)

bfw

kh Enthalpy of feed water needed to de-superheat steam (kJ/kg)

stmdeah Enthalpy of stripping steam to the deaerator (kJ/kg)

reth Enthalpy of returning condensate from the process (kJ/kg)

condh Enthalpy of condensing water entering the deaerator (kJ/kg)

mkuph Enthalpy of make up water (kJ/kg)

genkh Enthalpy of steam generated by the process (kJ/kg)

hdrkh Enthalpy in steam header k(kJ/kg)

inletkh

Enthalpy of let down steam header k(kJ/kg)

inSTkh

Enthalpy of discharge from steam turbines at header k(kJ/kg)

8.2 Equipments

8.2.1 Multi-fuel boilersIn a boiler the chemical energy of the fuel is extracted to heat the condensate

or feed water to generate steam at the required temperature. There are

numerous types of boilers and control schemes along with different unit size

and actual load. This results in different performance trends. Aguillar [24]

assumed a linear relationship between fuel consumption and steam

production as shown in Equation Error! Reference source not found..

boiboi

boi

fboistm D

BQQ

=

Eq 23

Where,

boifQ Net heat from the fuel consumed inside the boiler (kW)

boistmQ Actual heat added to the water/steam inside the boiler (kg/s)

boiB , boiD Regression parameters


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With the assumptions that boiler blowdown is extracted at saturated

conditions and as a fixed fraction of boiler steam output, the heat supplied to

the water/steam cycle can be expressed as:

+=

boi

T

boi

bid

boi

ecoboiT

boistm

boistm

h

FhhMQ

.1..

Eq 24

Where,

boistmM Actual steam output from the boiler (kg/s)

boiTh Enthalpy difference between feedwater and outlet steam conditions

(kJ/kg)

boiecoh Enthalpy difference across boiler economiser (kJ/kg)

boibldF Boiler blowdown fraction taking as reference the outlet steam

flowrate (kg blowdown/kgsteam)

Equation Error! Reference source not found. is obtained by rearranging

Equations Error! Reference source not found. and Error! Reference

source not found.. The coefficients for this boiler model are obtained byregression from operating or design data.

+=

boi

T

boi

bid

boi

ecoboiT

boistm

boi

boi

boi

f

h

FhhMD

B

Q .1..

Eq 25

Here, boiB & boiD are regression coefficients.

8.2.2 Gas turbines (GT)

Gas turbines convert the chemical energy of fuels into electrical energy via a

three step process

Compression: The inlet pressure and temperature of the ambient air is

increased by the compressor.

Combustion: Heat is added at high pressure by fuel ignition.

Expansion: The hot combustion gases are expanded through the

turbine to drive the compressor and to provide power (electricity).


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The relationship between power output from the gas turbine to the required

heat input is approximated by a straight line which is known as the Willans

line.

gtgtgtgt WQCW int= Eq 26

gtW Gas turbine power output (kW)

gtQ Gas turbine fuel input (kW)

gtC , gtWint Regression parameters

8.2.3 Heat recovery steam generators (HRSG)

HRSG utilize the waste heat from the gas turbine to produce steam which can

be further used to generate power or provide heating to consumers. HRSG

can be further classified into the following types:

a) Unfired units: Steam production is limited by the temperature and

available energy in the exhaust gases.

b) Supplementary fired units: The remaining oxygen in the exhaust gases is

used to burn fuel to boost steam generation.

c) Fully fired units: Additional quantity of air is supplied for further

consumption of fuel and hence increases production of steam.

Aguillar [24] derived a simple equation for the steam production from a gas

turbine based on the mass and heat balance for the unfired HRSG.

( )( )( )gtgtD

gtgt

D

gthr

m

hr

satgt

D

gtgt

Dgtgt

Dhr

eva

hr

sh

hr

exh

hr

radhr QQQTTQ

QQkTexh

hh

CpFM

+

= 1

Eq

27

Where,

hrM Maximum HRSG steam production from GT exhausts (kg/s)

hrradF Radiation losses factor for the HRSG


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hrexhCp Average specific heat for the exhaust gases (kJ/kg-C)

hrshh ,

hrevah Steam enthalpy difference across HRSG superheater, evaporator

(kJ/kg)

hrmT Minimum temperature difference between gas and steam/water

profiles (C)

gtDTexh Design temperature at the exhaust of the gas turbine (

oC)

hrsatT Saturation temperature for the steam produced in the HRSG (C)

gtk , gt , gt Regression coefficients

gtDQ Design heat from the gas turbine

gtQ Actual heat from the gas turbine

8.2.4 Electric motors (EM)

Electric motors are devices that convert electricity into shaft power by

inducing electromagnetic forces in its rotational wounding (i.e. rotor). The

units are broadly classified into synchronous, direct current, three phase

induction and single phase [24].

Willans line describes the part load performance of the electric motors in

terms of regression parameters with the full load performance of the motor.

emem

D

emem

D BWAWe += Eq 28

em

DWe Design electric consumption of the motor (kWe)em

DW Design motor power output (kW)

emA , emB Regression parameters

8.2.5 Steam turbines (ST)

Steam turbines convert energy from steam into electrical energy by expanding to

lower pressure. They can be classified as single or multiple extraction turbines


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according to number of equipments attached to the shaft. The back pressure

steam turbine expands steam to a lower pressure, while steam is expanded to

liquid water in a condensing turbine.

Single stage steam turbine

Aguillar [24] developed linear models to describe the performance of steam

turbines. The design steam flow rate ( stDM ) in steam turbine is a function of

isentropic enthalpy change ( stish ) and the design capacity of the unit (st

DW ).

( )

st

D

stst

stis

st

D WBAhM+

=1

stsat

st TaaA += 10 st

satst TaaB += 32

Eq 29

Here a0, a1, a2, a3are regression coefficients,

stsatT is the saturation temperature difference across the turbine.

The power of the unit ( stW ) is proportional to the steam mass flow rate ( stM ) and

the ordinate intercept of the Willans line ( stWint ).

stststst WMnW int= Eq 30

The actual shaft power from a single stage turbine is a function of maximum

output size ( stDW ), actual steam flow (stM ) and inlet and outlet conditions of the

steam in the turbine.

( )st

ststst

Dstst

st

ststis

st ALWLMB

LhW 1

1+

+=

Documents

EPSRC Thermal Management CPI Interim Report 16Feb