Operation System Optimization

  • Haslenda Hashim
  • Shuhaimi Mahadzir
  • Woon Kok Sin
  • Mahmoud Ahmed
Chapter
Part of the Energy Systems book series (ENERGY)

Abstract

This chapter presents a new advancement in energy minimization and CO2 mitigation research. It describes the development of a combined technique to simultaneously synthesize energy recovery network and offers fuel switching options to satisfy CO2 emission reduction target using graphical and mathematical programming approaches. The approach is illustrated using petroleum refinery and palm oil refining process as the case study. The application of this technique yields significant CO2 emission reduction with short payback period with or without clean development mechanism (CDM).

Keywords

Fuel switching Emission reduction Palm oil refinery Petroleum refinery Graphical technique Mathematical model Process integration 

1 Introduction

The emission of carbon dioxide (CO2) from the burning of fossil fuels has been identified as the major contributor to global warming and climate change. The challenge for the fossil fuel industry is to find cost-effective solutions that will improve energy savings as well as reduce the release of CO2 into the atmosphere. There are currently many technologies available to reduce CO2 emission significantly, with carbon capture being the leading technology. Among promising technologies to capture CO2 are chemical solvent absorption, physical absorption, physical adsorption in solid and liquid, cryogenic separation, membrane separation, O2/CO2 combustion process and biological capture process. Meanwhile, as fuel switching process (transferring from high carbon intensive fuels to low carbon intensive fuels or renewable energies) poses a gigantic impact on the environment, the study of fuel switching process is getting more attention from the researchers. Beside fuel switching, process integration is also an important activity to improve energy savings and hence reduce emissions from chemical process plants. In this chapter, a combined process integration and fuel switching strategy using graphical and mathematical programming approaches are presented. These cost-effective techniques offer a potential to improve the overall energy utilization in process industry and satisfy targeted carbon emission reduction. Application of these techniques on petroleum refinery and palm oil refinery showed significant energy recovery potentials and their ability to satisfy specific target for CO2 emission reduction.

2 Combined Process Integration and Fuel Switching Strategy: Graphical Technique

2.1 Case Study 1: Crude Oil Distillation Unit Pre-heat Train

Case study 1 demonstrates the application of the new graphical method, starting by fuel switching and then retrofit of heat exchanger network, HEN, for a preheat train of crude oil distillation unit [1]. As illustrated in Fig. 1, the crude oil is fed to the distillation tower from storage at ambient temperature. It is preheated in two sections by heat exchange with the hot fractions from the distillation column product streams. The first section runs from storage to a desalter unit. The second section runs from the desalter to the crude tower. The final process heating is provided by a furnace prior to the crude entering the fractionation tower. Any improvement in the heat recovery within the HEN will reduce the amount of the external heat required by the process, leading to lower fuel requirement and hence to emissions reduction.
Fig. 1

Flowsheet for the crude oil pre-heat train

2.2 Development of Graphical Technique

Emission reduction of CO2 by fuel switching is limited to alternative fuels availability and the ability of the boiler combustion system to accept different fuel type. In addition, there is no available practical and economical flue gas treatment to remove post combustion CO2 on-site [2, 3]. Therefore, a strategy to integrate fuel switching with retrofit of HEN is more useful to achieve a more practical emissions reduction target. For any given heat transfer process, the heat duty can be translated into fuel heat duty and hence to emissions flowrate using Eqs. 1, 2 and 3.
$$ {Q_{{FUEL}}} = \frac{{{Q_{{PROCESS}}}}}{{{\eta_F}}} $$
(1)
$$ {\eta_F} = \frac{{{T_{{TFT}}} - {T_{{STACK}}}}}{{{T_{{TFT}}} - {T_o}}} $$
(2)
$$ {M_{{pol}}} = \frac{{{Q_{{fuel}}}}}{{NHV}}*\beta *\phi $$
(3)
where
  • \( {Q_{{fuel}}} \) = heat duty from fuel (kW)

  • \( {Q_{{PROC}}} \) = process heat duty (kW)

  • \( {\eta_F} \) = furnace efficiency

  • \( {T_{{TFT}}} \) = theoretical flame temperature of the furnace flue gases (°C)

  • \( {T_{{STACK}}} \) = stack temperature (°C)

  • \( {T_o} \) = ambient temperature (°C)

  • \( {M_{{pol}}} \) = mass flow rate of pollutant

  • \( NHV \) = net heating value of the fuel

  • \( \beta \) = mass percentage of the pollutant in non-oxidized form

  • \( \varphi \) = ratio molar masses of the oxidized form to the non-oxidized form of the pollutant

The graphical technique of combined fuel switching with retrofit of HEN is demonstrated below. In Fig. 2, for target emissions reduction of C%, switching from fuel oil to natural gas fuel can achieve a limited emissions reduction amounting to A%. Suppose there is a set target for emission reduction, which is at B%. In order to reach the target emission reduction, B% of the existing emissions has to be reduced through retrofit of the HEN. The intersection of the lowest dotted horizontal line with the operating line of natural gas fuel shows the new point of the fuel consumption. Therefore savings in natural gas fuel consumption amounting to D% through the retrofit of the HEN need to be achieved. This amount of savings is required in order to meet the target B% emissions reduction from the existing emissions. The amount of B% emissions reduction as a result of HEN retrofit can be saved by investing on new heat exchanger surface area. The target added area due to retrofit of HEN can be predicted by retrofit of HEN through Pinch Design Method [4, 5, 6, 7, 8, 9].
Fig. 2

The graphical illustration of integrating fuel switching with the retrofit of heat exchanger network

The total capital investment of fuel switching with retrofit of HEN for emission reduction is made up of two parts. Firstly, the investment required to upgrade the burner for combustion of a new fuel. Secondly, an investment is also required to upgrade heat exchangers that require larger heat transfer area for the retrofit exercise. However, if replacing the fuel oil burners with natural gas burners is the only modification that will occur in the existing furnace to accommodate the new fuel, then the investment of changing burners will be smaller compared to that of the retrofit of HEN. Thus, if the total investment of combining fuel switching with the retrofit of the HEN is approximated to the investment of retrofitting the HEN, then the relationship between emissions reduction (%), investment and energy savings (%) can be set as shown in Fig. 3.
Fig. 3

Relating the total emissions reduction% to energy saving% from the retrofit of HEN

3 Results and Discussion

Figure 4 represents the grid diagram of the Crude Oil Distillation Unit pre-heat train heat exchanger network [10]. The hot streams are grouped together in the top part of the grid and labeled H1 to H6. The only cold stream is the crude feed, labeled C1. There are six process-to-process heat exchangers (E1–E6), five coolers (E7–E11) and a furnace (E12) in the crude pre-heat train HEN. The temperatures are shown at the two ends of the stream while the heat loads are shown below the heat exchangers. For example, stream H6 has an initial temperature of 290°C and a final temperature of 190°C. Stream H6 is cooled down by cooler E5 by exchanging the heat with stream C1 at heat load of 38,480 kW. Table 1 show the streams and cost data and Table 2 shows the existing process-to-process heat exchange area for the HEN of the case study. The two types of selected fuels and their properties are further shown in Table 3. For base case, the existing fuel in the combustion device is assumed to be fuel oil at 25°C. The combustion air is also assumed to be fed at the same temperature.
Fig. 4

Existing network for the crude oil pre-heat train

Table 1

Streams and cost data for the crude oil pre-heat train

Stream

Flow (kg/s)

Supply Ts (°C)

Target Tt (°C)

HTC (W/m2.°C)

H1

23

180

30

492.2

H2

44

270

40

477.8

H3

13

350

30

439.8

H4

56

380

50

470.7

H5

253

150

100

561.5

H6

148

290

190

432.6

C1

200

20

390

343.0

Note: Exchanger capital cost (£) = 8,600 + 0.83 × 670 × (area). Hot utility cost (£/kW.year) = 70

Cold utility cost (£/kW.year) = 7. Maximum area per shell = 580 m2. CP = 2,600 (J/kg °C) for all streams

Table 2

Existing process-to-process heat exchanger area of the crude oil pre-heat train

Heat exchanger

Heat load (kW)

Existing HT area (m2)

E1

6,000

280

E2

23,000

1,480

E3

750

280

E4

15,000

800

E5

38,480

2,760

E6

22,000

1,360

Table 3

Fuel properties

Compositions

Oil

Natural gas

Carbon (wt%)

87.26

76.0

Hydrogen (wt%)

10.94

22.8

Oxygen (wt%)

0.64

Nitrogen (wt%)

0.28

1.1

Sulfur (wt%)

0.84

0.1

Ash (wt%)

0.04

NHV (kJ. kg−1)

39,830

51,550

For the current heat requirement of the process of 80,418 kW, which is the amount of heat provided by furnace E12, the mass flowrate of a pollutant is calculated depending on the type of fuel used. The reductions in SOx and CO2 emissions due to fuel switching from oil to natural gas are illustrated in Figs. 5 and 6, respectively. Figure 5 shows that the reduction in SOx emissions can reach 90.8% because the sulfur content of natural gas fuel is very low compared to that of fuel oil. From Fig. 6, the reduction in CO2 is 32.7%. This is because the natural gas fuel has lower carbon-to-hydrogen ratio whilst maintaining high NHV.
Fig. 5

The effect of fuel switching on SOX emissions

Fig. 6

The effect of fuel switching on CO2 emissions

Fuel switching from fuel oil to natural gas can provide satisfactory emissions reduction for fuel NO, SOx and particulates. The emissions reduction of CO2 due to fuel switching is achieved by almost 32.7%. Furthermore, there is no available practical flue gas treatment to remove CO2 emissions. Consequently a combined strategy of fuel switching with retrofit of HEN is implemented to get more emissions reduction.

Figure 7 shows the application of the graphical method of combined fuel switching and HEN retrofit to cut down the emissions of CO2. For target emissions reduction of 50% (C), fuel switching from fuel oil to natural gas has achieved only 32.7% emissions reduction (A). So, in order to reach the target emission reduction, 17.3% of the existing emissions (B) have to be reduced through the retrofit of the HEN. The intersection of the lowest dotted horizontal line with the operating line of natural gas fuel shows the new point of the fuel consumption. Therefore 26% saving in fuel natural gas consumption (D) through the retrofit of the HEN have to be achieved to reach the 17.3% emissions reduction from the existing emissions.
Fig. 7

The graphical illustration of integrating fuel switching with the retrofit of the HEN of the case study

If replacing the fuel oil burners with natural gas fuel burners is the only modification that will occur in the existing combustion device to accommodate the new fuel, then the investment of changing burners will be smaller compared to that of the retrofit of the HEN. If the total investment of combining fuel switching with retrofit of the HEN is approximated to the investment of retrofitting the HEN, then the relationship between emissions reduction (%), investment and energy savings (%) can be built as shown in Fig. 8.
Fig. 8

Relating the total emissions reduction % to energy saving % from the retrofit of the HEN

Figure 8 indicates that the maximum emissions reduction from this is 69%. This is due to the fact that the thermodynamic minimum hot utility consumption of the process (i.e. Qprocess at ΔTmin = 0°C) is greater than 0.

However, the major contribution from this technique is that, it can determine the maximum Greenhouse Gas emissions (GHG) reduction which can be achieved for any given chemical process plant. Furthermore, it is able to determine the amount of energy savings which should be achieved through retrofit of heat exchanger network (HEN) for any target emissions reduction.

4 Combined Process Integration and Fuel Switching Strategy: Mathematical Modeling Techniques

4.1 Case Study 2: Palm Oil Refinery

Palm oil refining involves gigantic energy during its operation. According to Zainuddin et al., 20–30% of the production cost in a crude palm oil physical refining plant is due to the usage of energy [11]. Optimum usage of energy is therefore imperative in order to save the operating cost, reduce emission and increase the profitability of the crude palm oil refinery plant.

The flowsheet of the crude palm oil refinery plant is shown in Fig. 9.
Fig. 9

Flowsheet of the crude oil refinery

Firstly, the crude palm oil undergoes degumming process. Food grade phosphoric acid, which acts as a solvent, is added into the process. This is done at a temperature in excess of 100°C in order to get rid the oil from gums (phosphatide compounds). Then, it undergoes bleaching process at which the bleaching earth is used to remove color pigments from the degummed oil. The process is implemented under vacuum condition at 120°C. After that, the slurry product from the bleaching section travels through a series of Niagara Filter in order to remove the excess bleaching earth and impurities. After the filtration, the oil undergoes deodorization process at which free fatty acids, aldehyde and ketone compounds is removed from the bleached oil by stream stripping. The deodorizer column operates under high vacuum and temperature in the range of 240–270°C. The product is called as Refined, Bleached and Doedorised Palm Oil (RBDPO) [12]. A set of hot streams that must be cooled and a set of cold streams that must be heated for a palm oil refinery plant are given in Table 4.
Table 4

Process stream data for the palm oil refinery plant

Stream no.

Type

Stream name

Supply temperature, TS (°C)

Target temperature, TT (°C)

Heat capacity flow rate (kW/°C)

C1

Cold

Crude palm oil feed, CPO

50

97

11.83

C2

Cold

Degaser outlet, DEGAS

104

124

14.89

H1

Hot

Bleached palm oil, BPO

120

86

10.99

C3

Cold

Dried oil, DRIED

86

230

5.69

H2

Hot

Deodorizer outlet, DEO

260

160

6.04

H3

Hot

Free fatty acids, FFA

83.3

70

13.13

H4

Hot

Refined, bleached and deodorized palm oil, RBDPO

160

50

6.56

In this case study, auxiliary heating and cooling are available from hot steam and cooling water. Diesel is the typical fuel used to generate the steam for hot utility purpose in a palm oil refinery plant. However, due to the fact that diesel fuel produce high amount of carbon dioxide, which is one of the greenhouse gases, study on switching fuels to less carbon intensive fuel e.g. natural gas, biomass and biogas to generate heat and power in a refinery plant if of great interest. The data for fuel switching is provided is Table 5.
Table 5

Data for fuel switching analysis

Parameter

Diesel

Natural gas

Biomass (empty fruit bunch)

Palm oil mill effluent (POME)

Heating value (kJ/kg)

45,900

42,500

18,795

55,400

Capital cost of boiler (RM/MW)

0

617,000

15,900,000

1,530,000

Capital cost of steam turbine (RM/kW)

0

0

760

760

Efficiency of boiler

0.56

0.83

0.61

0.4

Fuel cost (RM/kg)

2.94

2.5289

0

0

Operating and maintenance cost (RM/MWh)

34.63

95.33

150

150

Efficiency of steam turbine

0

0

0.629

0.5

Heat to power ratio

1.0

1.0

0.8

0.7

Carbon dioxide emission (kg/kg fuel)

3.2

2.30

0

0

4.2 Mathematical Model Development

The objective of this study is to simultaneously synthesize maximum energy recovery and satisfy CO2 emission reduction via heat integration and fuel switching process. The total cost includes: retrofit or capital cost for switching fuel from diesel to natural gas or biomass, operational cost mainly for fuel price, operating and maintenance cost (O&M), carbon emission reduction (CER) revenue and electricity saving cost due to electricity generation from combined heat and power (CHP) system. This can be written as,
$$ \begin{array}{lllllll} Min\,\,cost{\mathbf{\;=\, }}\underbrace{{\sum\nolimits_i {({W_i} \times C{A_i} \times H{V_i} \times HTP{R_i})} }}_{{Capital\,\,Cost}} + \underbrace{{\sum\nolimits_i {({W_i} \times FUEL{C_i})} }}_{{Fuel\,\,Price}} + \hfill \\ \quad\underbrace{{\sum\nolimits_i {({W_i} \times OA{M_i} \times H{V_i} \times HTP{R_i})} }}_{{O\& M\,\,Cost}} - \underbrace{{\sum\nolimits_i {({W_i} \times CE{R_i} \times H{V_i})} }}_{{CER\,\,Revenue}} \hfill \\ \quad- \underbrace{{\sum\nolimits_i {({W_i} \times H{V_i} \times PTH{R_i} \times ETARIFF)} }}_{{Electricity\,\,Saving\,\,Cost}} \hfill \\\end{array} $$
(1)

Equation 1 represents the objective function at which the total cost is minimized. i is the only set which represents the alternative fuels used in the fuel options, includes, biomass (EFB), POME and natural gas with subsets BMS, MTHGAS and NG respectively. Wi (kg/year) is represents the flow rate of each fuels switching option. It is a variable of the model at which it will affect the capital and operational cost for fuel switching process. CAi (RM/kJ) is the capital cost of boiler of each alternative fuel. The more fuel is consumed, the larger size of the boiler is needed to generate more energy, hence the higher the capital cost incurred. HVi (kJ/kg) is the calorific value or heating value of respective alternative fuels. HTPRi is represents a heat to power ratio for co-generation system used biomass (EFB) and methane gas fuel to generate heat and electricity. In this case, the heat to power ratio for EFB and POME are 0.8 and 0.7 respectively. Meanwhile, FUELCi (RM/kg) is the fuel cost for each alternative fuels. In this case, the fuel cost for EFB and POME is considered zero due to the reason that it is assumed to be taken from nearby palm milling plant. OAMi (RM/kg) is the operating and maintenance cost for each alternative fuels. CERi (RM/kg) is the certified emission reduction cost at which the usage of green renewable energies will help to gain profit to the system. In this case study, it is expected that a reduction of 1 t of carbon dioxide will provide a profit of RM 72 to the plant owner. As electricity generation is considered in this case study, the saving cost of electricity generated from renewable energies using combined heat and power system, CHP system is considered in order to obtain minimum operational cost. PTHRi is the power to heat ratio used for EFB and POME in generating the electricity to the plant. The respective values are 0.2 and 0.3. Meanwhile, ETARIFF is a scalar which represents the electricity tariff in this case study. The given electricity tariff is RM 0.28 per kWh.

Equation 2 indicates the total heat required from different alternative fuels for generating the minimum hot utility target, \( {Q_s} \). EFFi is the efficiency of boiler for each alternative fuels. Meanwhile, f is the scalar factor which represents the demand factor. In this case, the value for the demand factor is 1. Should there is an increase in demand in future, the scalar factor will change accordingly in order to fulfill the heat demand requirement.
$$ \sum\nolimits_i {({W_i} \times H{V_i} \times EF{F_i} \times HTP{R_i}) = } \,\,{Q_s} \times f $$
(2)
For above equation, Qs is obtained using heat balance equation for each interval as shown in Eq. 2. In this case, global (shifted) temperature interval is used as which all supply temperatures and targeted temperatures are increased (cold stream) or reduced (hot stream) by half of the minimum temperature approach, ΔTmin (10°C) respectively and arranged from highest value to lowest value in order to build up the temperature interval as shown in Tables 6 and 7.
Table 6

Actual temperature and shifted temperature

Stream no.

Actual T

Shifted T

TS (°C)

TT (°C)

TS (°C)

TT (°C)

C1

50

97

55

102

C2

104

124

109

129

C3

86

230

91

235

H1

120

86

115

81

H2

260

160

255

155

H3

83.3

70

78.3

65

H4

160

50

155

45

Table 7

Set up temperature interval

Stream no.

TS/TT

Remove duplicates (if any)

Set up intervals (Tint)

C1

55

55

255

92

102

235

C2

109

109

155

119

129

129

C3

91

91

115

225

235

109

H1

125

115

102

81

81

91

H2

265

255

81

155

155

78.3

H3

88.3

78.3

65

65

65

55

H4

160

155 – remove duplicate

45

45

45

The K equations are heat balances around each temperature interval k. Heat residual entering interval k, Rk−1, and heat contents of hot stream i in interval k, ΔHk, balance to heat residual exiting interval k, Rk.
$$ {R_{{k - 1 }}}--{ }{R_k} + { }\Delta {H_k}{ } = { }0, k{ } = { }1, \ldots, K $$
(3)
If \( {R_k} = 0 \) at the optimal solution, the temperature at interval k will be corresponding to a pinch point and Qs is the minimum heat utility required for the process. Equations 4, 5 and 6 indicate the constraints which show that the hot utility/steam consumption, QS, cold utility, QCW, as well as residual heat, Rk, is a positive value at any interval.
$$ {Q_S}{ } \ge { }0 $$
(4)
$$ {Q_{{CW}}} \ge { }0 $$
(5)
$$ {R_{{k }}} \ge 0, k = 1, \ldots, K $$
(6)
Equation 7 is a constraint to indicate the electricity generation from CHP plant satisfies the annual electricity requirement for the plant. ECHPi represents the efficiency of turbine used in generating the electricity. The flow rate of alternative energy, Wi multiplies with the heating value, HVi, power to heat ratio, PTHRi efficiency of the turbine, ECHPi and efficiency of the boiler, EFFi to give the electricity consumption which is in unit of MWh.
$$ \sum\nolimits_i {({W_i} \times H{V_i} \times PTH{R_i} \times ECH{P_i} \times EF{F_i})} \,\, \le ELECONSM $$
(7)
Meanwhile, Eq. 8 shows that the appropriate fuel will be selected according to carbon dioxide emission reduction target. CDEi is the carbon dioxide emission in kg per year. Meanwhile, RPER represents the reduction of percentage of carbon dioxide emission in the plant. TCO2 is a scalar at which it represents the current carbon dioxide emission in the plant per year.
$$ \sum\nolimits_i {({W_i} \times CD{E_i})} \,\, \le (1 - RPER) \times TCO2 $$
(8)
Equations 9, 10, 11 and 12 show the constraints for total availability of the alternative fuels for plant generation respectively. In this case study, the total availability for biomass (EFB), SBMS methane gas (POME), SMTHGAS, diesel, SDIESEL and natural gas, SNG is 1,000,000 kg/year, 20,000 kg/year, 500,000 kg/year and 350,000 kg/year respectively. Therefore, the total flowrate of fuel required for biomass, WBMS, methane gas, WMTHGAS, diesel, WDIESEL, and natural gas, WNG, must be less than availability.
$$ {W_{{BMS}}} \le SBMS $$
(9)
$$ {W_{{MTHGAS}}} \le SMTHGAS $$
(10)
$$ {W_{{DIESEL}}} \le SDIESEL $$
(11)
$$ {W_{{NG}}} \le SNG $$
(12)
Equations 13 and 14 indicate the non-zero constraints for electricity consumption, ELECONSM, and total carbon dioxide emission, TCO2, respectively.
$$ ELECONSM \ge 0 $$
(13)
$$ TCO2 \ge 0 $$
(14)

4.3 Results and Discussion

Figure 10 illustrates the effect of different combination cases for heat integration and fuel switching process in terms of total operational cost.
Fig. 10

Total operational cost for different scenarios

From the figure, it can be seen that base case requires highest amount of total operational cost while the integration of diesel, heat integration and fuel switching process with clean development mechanism (CDM) requires lowest total operational cost. Compared to base case scenario, the introduction of different combination cases reduces the total operating cost as much as 90.5%, 18.1%, 16.7%, 93.9% and 92.5% respectively. This is mainly due to the fact that the implementation of heat integration will significantly reduce the amount of fuel usage, hence reducing the purchase cost and operating cost for respective fuels. As a conclusion, the integration of diesel, heat integration and fuel switching with CDM yields the best result among all in terms of total operational cost saving.

Figure 11 shows the effect of various combination cases towards the CO2 emission. From the figure, it can be seen that the introduction of heat integration and fuel switching process will reduce the emission of CO2 considerably compared to base case scenario. The introduction of heat integration, fuel switching process and combination of heat integration and fuel switching will reduce 92.3%, 42.3% and 96.9% of CO2 emission respectively. The introduction of heat integration will tremendously reduce the usage of diesel fuel. A reduction of usage of diesel fuel signifies a reduction in CO2 emission to environment. Meanwhile, through the application of methane gas release from POME and biomass (EFB), it will significantly reduce the release of CO2 as they are considered as green energy and will not release CO2 to atmosphere while burning. The effect will be more obvious while heat integration and fuel switching are implemented together. Therefore, the combination of heat integration and fuel switching shows the highest percentage reduction among all.
Fig. 11

CO2 emission for different scenarios

Figure 12 shows the percentage of CO2 reduction with energy consumption from conventional energy (diesel) and renewable energy due to fuel switching. Base case applied for this graph is after the implementation of heat integration. It can be seen that the percentage of fuel switching to renewable fuels is increased when the percentage of CO2 reduction is increased. The trend for conventional energy (diesel consumption) is in reverse order compared to renewable energy. From the figure, it shows that the usage of renewable fuels starts to outweigh the conventional fuels when 74.5% of CO2 reduction is intended to be achieved in the plant. As CER revenue keeps increasing for this time being, this will considerably give a handsome profit through the implementation of renewable energy in the future.
Fig. 12

Percentage of CO2 reduction versus energy consumption after the implementation of heat integration

Figure 13 shows the total cost and CO2 emission for four different combination cases, namely base case, heat integration, fuel switching and combination of heat integration and fuel switching.
Fig. 13

Total operational cost and CO2 emission for different scenarios

Generally, the introduction of heat integration and fuel switching will reduce the total cost as well as CO2 emission. From the figure, it can be seen that the implementation of heat integration will require less cost and release less CO2 compared to base case scenario. This is due to the fact that energy is provided via the hot streams in the plant operation when process heat integration is implemented. Therefore, a reduction of energy consumption will significantly reduce the usage of diesel fuel, causing the cost of operation and CO2 emission to be reduced greatly. Meanwhile, the implementation of fuel switching process reduces the operational cost and CO2 emission concurrently compared to base case scenario. This is the fact that renewable fuel such as methane gas (POME) and low carbon intensive fuel such as natural gas used in fuel switching. Moreover, the switching of conventional fuels to renewable fuels will reduce the emission of CO2 which will help to protect the environment.

Figure 14 illustrates the trend of CO2 emission reduction after the implementation of heat integration and fuel switching process. From the figure, it can be seen that the total cost is increasing while the percentage of CO2 emission is increased. In order to achieve significant reduction of CO2 emission, biomass (EFB) is favored to be implemented to replace conventional fuel consumption (diesel and natural gas). The increment of the operational cost is due to the fact that the implementation of biomass boiler will increase the total cost for its high capital cost and lower heating value, which means that more fuels need to be consumed to generate same amount of energy compared to other fuels. Though zero CO2 emission is highly recommended to be introduced in the plant, it requires high amount of operational cost at the same time. Hence, a trade-off point in between operational cost reduction and CO2 emission reduction is very important to achieve equilibrium while considering these two factors.
Fig. 14

Percentage of CO2 reduction versus energy consumption and total

5 Conclusion

A new combined process integration and fuel switching technique are developed using graphical technique and mathematical approaches. This work is unique since it can be used to simultaneously design maximum energy recovery network and offer fuel selection options in order to satisfy CO2 emission reduction target. The developed method has been effectively applied in two case studies of crude oil pre-heat train and palm oil refinery heat exchanger network. The method was prove to be an efficient integrated method for maximizing energy savings and targeting emissions reduction in chemical process plants.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Haslenda Hashim
    • 1
  • Shuhaimi Mahadzir
    • 2
  • Woon Kok Sin
    • 3
  • Mahmoud Ahmed
    • 2
  1. 1.Faculty of Chemical EngineeringUniversiti Teknologi MalaysiaJohorMalaysia
  2. 2.Department of Chemical EngineeringUniversiti Teknologi PETRONASTronohMalaysia
  3. 3.Civil and Environmental Engineering Department Hong KongUniversity of Science and TechnologyClear Water BayHong Kong

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