CHEMICAL ENGINEERING TRANSACTIONS
VOL. 78, 2020
A publication of
The Italian Association
of Chemical Engineering
Online at www.cetjournal.it
Guest Editors: Jeng Shiun Lim, Nor Alafiza Yunus, Jiří Jaromír Klemeš
Copyright © 2020, AIDIC Servizi S.r.l.
ISBN 978-88-95608-76-1; ISSN 2283-9216
Multi-stage Carbon Emission Pinch Analysis of an Integrated
Power Generation and Electric Vehicle System
Ahmad Fakrul Ramli, Ahmad Muzammil Idris, Zarina Ab Muis*, Wai Shin Ho
Process Systems Engineering Center (PROSPECT), Department of Chemical Engineering, School of Chemical and
Renewable Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
zarinamuis@utm.my
The introduction of electric vehicles to the transportation fleet has merged the power generation and
transportation sectors into an integrated system. Rather than fuel sources, electricity is used to charge electric
vehicles, so these vehicles play a vital role as an important green technology that could reduce carbon
emissions in the transportation sector. This study aimed to extent carbon emission pinch analysis for an
integrated system to optimise the energy mix for electricity generation in Malaysia. In the first stage, the
minimum number of electric vehicles required to reduce transportation emissions was determined. In the
second stage, the optimal energy mix for the power generation sector was determined while including the
electricity demand for the electric vehicle. Four scenarios namely S1, S2, S3, and S3 were developed based
on Peninsular Malaysia as a case study, to analyse the impact of different mitigation strategies based on the
performance of the integrated system (number of vehicles, fuel consumption, and energy mix) and economic
evaluation based on total cost and total cost per emission reduction. The emission reduction is based on the
45 % target based on 2005 level for the transportation and power generation sector. The results reveal that S1
has the lowest total cost (MYR 1.73x1012) and S4 has the highest total cost (MYR 3.13x1012) compared to
other scenarios proposed. However, in term of total cost per emission reduction, S4 shows the lowest (MYR
9.36x106) while S1 being the highest with MYR 13.1x106. The results generated from the scenarios proposed
give a clear visualisation on how the policies affect the demand growth. Pinch analysis technique is proven to
be a suitable tool in targeting and planning for emission reduction target and energy demand management.
1. Introduction
The transportation and power generation sectors are responsible for almost half of total global carbon
emissions. Lately, a rising awareness of environmental issues among the youth has increased the growth of
green technologies (Bhowmik et al., 2017). The same trend in carbon emissions can be observed in Malaysia,
where transportation and power generation have had a massive impact on total carbon emissions. To solve
this issue, the government has set a target to achieve 45 % carbon emission reduction by the year 2035 (Ali,
2015). One of the efforts under this vision is to introduce electric vehicles (EVs) to the transportation sector.
The EV is a very promising alternative, not only to reduce carbon emissions, but also to increase the efficiency
of energy usage. However, large-scale EV usage on the road will increase energy demand on the power
generation sector. In addition, the total carbon emissions for EV could then shift to power generation. This
means that the full benefits of EV can only be reaped if clean sources of power generation such as renewable
energy (RE) were used to generate electricity. Thus, this study proposes a multi-stage energy planning
technique for a system integrating power generation and transportation (electric vehicle) using a Carbon
Emission Pinch Analysis (CEPA). Besides, this study will provide an overview of the effect of EV
implementation on the power generation sector.
Tan and Foo (2007) were the first to propose CEPA, which is now the most well-known method for
optimisation based on pinch principles. Numerous studies relating to CO2 emissions have been done in
various countries and solutions to the emission problem have been proposed via the power generation sector
(Crilly and Zhelev 2009), carbon capture and storage (Ooi et al., 2013), water footprint analysis (Tan et al.,
2009), chemical processes (Tjan et al., 2010), the transportation sector (Walmsley et al., 2015), and waste
DOI: 10.3303/CET2078077
Paper Received: 15/05/2019; Revised: 05/09/2019; Accepted: 12/11/2019
Please cite this article as: Ramli A.F., Idris A.M., Ab Muis Z., Ho W.S., 2020, Multi-stage Carbon Emission Pinch Analysis of an Integrated
Power Generation and Electric Vehicle System, Chemical Engineering Transactions, 78, 457-462 DOI:10.3303/CET2078077
457
management (Tan et al., 2015). The most recent application of CEPA was that of Ramli et al. (2018) for the
transportation sector. The study proposed different mitigation strategies for the transportation sector to
achieve the target of carbon emission reduction and identified the minimum amount of energy needed for the
transportation sector to implement EV. Aziz et al. (2017) proposed an advanced pinch analysis framework for
low carbon dioxide emissions for industrial site planning. Idris et al. (2018) developed a framework for an
integrated water and energy system called the Water-Energy Nexus Cascade Analysis. CEPA has been
widely used in studies aiming to reduce carbon emissions. A few models have been developed to identify
optimal cost by implementing certain policy measures based on certain economic situations. However, fewer
studies have focused on an integrated system, especially the integration between the transportation and
power generation sectors. This study extends the work of Ramli et al. (2018) and determines the minimum
required RE percentage and the number of EV units needed on the road to achieve the carbon emissions
target. This study focusses on the impact of EV towards power generation sector by proposing different
mitigation strategies including the utilization of public transport and the electrification of car. The minimum
electricity required for EV were combined with the current electricity demand and pinch analysis technique
was used to determine the best energy mix for power generation sector.
2. Methodology
2.1 Carbon Emission Pinch Analysis Framework for an integrated system
The CEPA flow for the integrated system proposed in this study is shown in Figure 1. The first part of the
framework shows the development of CEPA for the transportation sector. It consists of data extraction, the
development of a demand and supply composite curve, and the identification of the minimum electricity
generation required. The second part of the framework is the CEPA for the power generation sector, which
includes data extraction, the development of a demand and supply composite curve, and the identification of
the optimal energy mix for the power generation sector. The CEPA method is based on Ramli et al. (2018),
who first used it for the transportation sector by constructing a composite curve for demand (based on
transport class) and supply (based on fuel sources) including EVs. This study proposed different mitigation
strategies including fuel switching and public transport utilisation for the transportation sector to determine the
minimum electricity that must be generated for the transportation sector. The results obtained were then used
as input for the power generation sector combined with the residential, commercial, and industrial electricity
demand to form a grand demand composite curve. The CEPA method was then reapplied to identify the
minimum amount of fossil fuels that must be shifted to RE after which the optimal energy mix for the power
generation sector could be determined.
Figure 1: CEPA flow for the integrated transportation and power generation sector
2.2 Case study
Peninsular Malaysia was taken as a case study for this work whereas the data needed for the CEPA
framework was obtained from MAMPU (2019). The current total transportation energy and the electricity
demand growth rates are 2.0 % and 3.5 %, as shown in Figure 2. The total number of vehicles on the road in
Malaysia is estimated to increase to up to 35 M units by 2035 based on a business-as-usual scenario, leading
to a 33,783 ktoe increase in the energy demand for the transportation sector. The total emissions based on
the 2005 level for the transportation sector and the power generation sector is 73430.00 kt-CO2. The
government intends to reduce the 2005-level total emissions by 45 %, which is equivalent to 33043.5 kt-CO2-
eq. For the transportation sector, the average travel demand is measured in passenger-km based on Eq. (1)
where TD is the total travel demand, NV is the number of vehicle units, DT is the average distance traveled
per year, and O is the occupancy level for each transport mode. For the power sector, the energy demand is
measured in ktoe.
(1)
Four scenarios were developed in this study, namely S1, S2, S3, and S4. In S1, it is assumed that 10 % of the
total emissions reduction is from the transportation sector, while 90 % is from the power generation sector.
Meanwhile, S2, S3, and S4 assumed a 20 %, 30 %, and 40 % reduction from the transportation sector, while
458
the rest was allocated to the power generation sector. S1 assumed no utilization of public transportation while
S2, S3, and S4 were set to low, medium, and high utilization of public transport. Table 1 summarizes all the
developed scenarios. To conduct the economic evaluation, all scenarios were compared in terms of total
energy cost, total maintenance cost, and total cost savings. The total cost savings were calculated by
comparing the total cost (summation of energy and maintenance cost) for each scenario to that of the baseline
scenario.
Figure 2: Population and energy growth in Malaysia (MAMPU, 2019)
Table 1: Economic evaluation for different scenarios proposed
Description S1 S2 S3 S4
Emission reduction for transportation sector 10 % 20 % 30 % 40 %
Emission reduction for power sector 90 % 80 % 70 % 60 %
Utilization of public transport none Low medium High
3. Results and discussion
Figure 3 shows an example of the CEPA results for both the transportation and power generation sectors.
Further analysis of each scenario is discussed in Section 3.1, 3.2, and 3.3 based on three main findings; i) the
CEPA results for the transportation sector; ii) the CEPA results for the power sector; and iii) the economic
evaluation outcome for an integrated system.
Figure 3: Example of CEPA results for S1 (a) transportation sector (b) power sector
Population
Projected data
Total vehicle
Transport
demand (energy)
Electricity
demand (energy)
0
0.5
1
1.5
2
2.5
3
3.5
4
0
0.5
1
1.5
2
2.5
3
3.5
4
1990 2000 2010 2020 2030
E
n
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rg
y
(
x
1
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5
k
to
e
)
N
o
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n
it
V
e
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ic
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s
/N
o
o
f
P
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p
le
(
x
1
0
7
)
Year
Current emission level
Bus
Car
Pinch
point
New emission target
0
100
200
300
400
500
600
0 400 800 1,200 1,600 2,000 2,400
e
m
is
s
io
n
(
M
T
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-e
q
)
Passenger-km (x109)
a) EV Petrol Diesel
Current emission level
New emission target
Pinch
point
0
20
40
60
80
100
120
0 10,000 20,000 30,000 40,000 50,000
e
m
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q
)
Energy demand (ktoe)
b) RE NG Oil Coal
459
3.1 Transportation management in 2035
Figure 4 shows the total number of vehicles and total fuel consumption for the transportation sector for all
scenarios. The results show that S1 had the highest number of vehicles and S4 had the lowest. This result is
due to the increase in the percentage utilization of public transportation. The number of EV units increased
linearly from S1 to S4 due to the increasing percentage of emission reduction for the transportation sector. In
terms of fuel consumption, petrol still dominates the fuel mix for the transportation sector. The number of
diesel cars is very low due to the limitation of this car variant in the market. Also, this type of fuel is mostly
used for heavy transportation such as lorries, buses, and trucks. Hence, consumers prefer to purchase petrol
cars compared to diesel cars.
The government targets to achieve 100,000 units of electric cars and 10,000 units of electric buses on the
road by the year 2020. They also target this number to keep increasing until the year 2035. Not only that, but
Malaysia also intends to become an electric mobility marketplace (Ali, 2015). Using the pinch technique as a
targeting tool, this study found that these targets could be achieved.
Figure 4: (a) Total number of vehicle (b) Total fuel consumption for transportation sector
3.2 Energy management for power sector in 2035
Based on the above results, the introduction of public transport alone will not be able to fulfill the emissions
target. Therefore, the focus should be on EV as an alternative option, as it clearly provides better efficiency
since it has zero tailpipe emissions compared to conventional vehicles. The main issue arises from the
electricity generation used to cater to EV demand. Based on the power sector, the results are presented in
terms of energy mix, the increase in energy demand due to EV, and the increase in RE share. Figure 5(a)
shows the energy mix for all scenarios. The innermost circle is for S1 while the outermost circle is for S4. The
RE share is a combination of hydro, biomass, biogas, and solar. Figure 5(b) shows the increase in energy
demand and the RE share for all scenarios. S1 had the most RE share for the power sector compared to the
other scenarios. This is because S1 has a higher percentage emission reduction (90 %) and S4 has the
lowest percentage emission reduction (60 %) for the power sector, as mentioned in Section 2.2. The increase
in energy demand due to EV depends on the total EV units involved, as shown in Figure 4. Hydro is not
considered a RE source; however, for CEPA targeting, this study treated hydro as a RE source together with
solar, biomass, and biogas to form a single RE curve.
Figure 5: (a) Energy mix (b) increase in energy demand and RE share for power generation sector
0.05 0.22 0.56 0.74
2.46
4.21
5.03
7.10
13.96
11.39 8.93
6.04
0.24
0.24
0.24
0.24
0
5
10
15
20
S1 S2 S3 S4
N
o
o
f
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it
v
e
h
ic
le
(
x
1
0
6
)
a) Bus Diesel Car EV Car Petrol Car Diesel
0.29
4.32
55.47
0.841.30
7.39
45.26
0.84
3.33
8.82
35.50
0.844.34
12.45
24.02
0.84
0
10
20
30
40
50
60
Diesel EV Petrol Diesel
Car
F
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C
c
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p
ti
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(
M
to
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)
b) S1 S2 S3 S4
67%
26%
8%
63%
25%
12%
60%25%
15%
57%
24%
19%
a)
RE
NG
Coal
0
10
20
30
S1 S2 S3 S4
E
n
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(
M
to
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)
b)
Increase in Energy Demand Increase in RE
460
3.3 Economic analysis for proposed scenario
Figure 6 shows the economic evaluation results of the integrated system (transportation sector and power
sector). The total cost of the system includes capital cost and fuel costs for the transportation and power
sectors. The results show that S1 had the lowest total cost (MYR 1.73x1012) while S4 had the highest (MYR
3.13x1012). S4 had the highest cost because it also has the highest number of EV units compared to the other
scenarios. However, in terms of total cost per emission reduction, the results show that S4 had the lowest total
cost per emission reduction (MYR 9.36x106) while S1 had the highest (MYR 13.1x106). Despite the higher
cost of S4, the total emissions reduced were also high, resulting in the lowest total cost per emission
reduction. Of all the scenarios proposed, S4 clearly provides the best results for EV implementation and RE
utilization for the proposed integrated system.
Figure 6: (a) Total Cost (b) Total cost per emission for the integrated transportation and power generation
sector
3.4 Limitation towards current policies
The main issue with EV is its higher price compared to conventional vehicles. Therefore, the government must
draw up a transportation policy to balance out the EV price and make it comparable to the conventional
vehicle. For example, by introducing subsidies such as tax-free incentives for EV or free charging schemes,
more people would be attracted to purchase EVs. Currently, the road tax for fully electric vehicles in Malaysia
is between MYR 10 and MYR 50 depending on the type of vehicle. The road tax for hybrid vehicles, on the
other hand, is charged based on the vehicle’s engine capacity. Recently, the government has been
considering implementing road tax charges based on the power output of the EV. Based on the current
electricity rates, it may be likely that EV owners might have to pay a lot more for the road tax. There has been
very little development on new incentives for car buyers to go fully electric or hybrid other than savings in
petrol cost and a lesser impact on the environment. In Malaysia, it is very costly to own fully electric vehicles
because almost all fully electric vehicles are imported and the import tax on cars in Malaysia is between 65 %
and 105 %. Another limitation of EV implementation in Malaysia is the lack of charging facilities. Up until now,
there are only 251 charging stations installed across Peninsular Malaysia. Of these recorded numbers, current
charging stations are mostly built in urban areas such as Kuala Lumpur, Melaka, and Johor Bahru
(GreenTech, 2019).
As for the power sector, the two main energy security issues in Malaysia are an ‘over-dependence on fossil
fuel’ and ‘increasing dependency on energy import’, both of which threaten the country’s future development.
The government has been introducing various initiatives over the years including, for example, the National
Energy Policy of 1979, the Four Fuel Diversification Policy of 1981, the Fifth Fuel Policy in the 8th and 9th
Malaysia Plans (2001–2005 and 2006–2010) and the setting up of a new energy model in the 10th Malaysia
Plan (2011–2015). The most recent initiative is the 11th Malaysia Plan (2016–2020), under which achieving
sustainability through cleaner energy sources is prioritized. Additionally, Malaysia has included RE as its fifth
fuel in the 'Fifth Fuel Policy'; but still the policy is not being utilized as planned. To tackle these issues,
Malaysian policymakers will need to revise existing policies to expand upon the supply and generation of
natural gas (to replace coal) and drastically incentivize low-carbon sources of energy such as solar to de-
carbonize the energy matrix and reach the target of 20 % renewable energy by 2025. The increasingly lower
cost of renewables is bringing competitive alternatives to energy generation. The electrification of the
economy, including the transportation sector, can reduce the demand for liquid fuels. Finally, policy and
consumer pressures can accelerate the shift towards a lower carbon footprint in the economy.
0 800 1,600 2,400 3,200
S1
S2
S3
S4
Total Cost (MYR x109)
a) Transport Power
0
2
4
6
8
10
12
14
S1 S2 S3 S4
C
o
s
t
(M
Y
R
x
1
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6
)
b)
461
4. Conclusion
In summary, the CEPA framework for an integrated transportation and power generation system was
developed in this study. The method provides insight into how energy planning can be performed in both
sectors simultaneously. In this study, several mitigation strategies for the transportation sector were proposed
to achieve the carbon reduction target. Besides, there are still numerous aspects that need to be considered
by researching on reducing emissions and energy planning for the transportation sector. For instance,
emission factors also depend on the driver’s age, utilisation pattern, and driving style. Thus, further study is
needed to explore the effect of these factors on the emissions and in different modes. However, CEPA is only
a technique that illustrates simple energy planning as a preliminary study. It illustrates only the surface-level
action on how the target can be achieved. For a complex optimisation problem that contains various
constraints, mathematical models need to be developed for better and accurate results that can comply with
all the constraints simultaneously. In general, CEPA can still be used to develop a baseline model and as a
preliminary study to solve problems related to supply and demand.
Acknowledgements
The authors would like to acknowledge the funding received from Universiti Teknologi Malaysia regarding
project process improvement and scheduling of biomass to bioenergy for centralised utility facilities (CUF),
vote number, Q.J130000.2546.17H86; and optimally integrated power generation and impact of electric
vehicle application on power generation, vote number, Q.J130000.2546.19H05
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