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The use of conservation supply curves in energy policy and economic
analysis: The case study of Thai cement industry
Ali Hasanbeigi a,, Christoph Menke a,b, Apichit Therdyothin c
a The Joint Graduate School of Energy and Environment, King Mongkut s University of Technology Thonburi, 126 Pracha-uthit Rd. Bangmod, Tungkru, Bangkok 10140, Thailandb Department of Building Engineering Services, Energy Technology Division, University of Applied Sciences Trier, Germanyc The School of Energy, Environment, and Material, King Mongkut s University of Technology Thonburi, Thailand
a r t i c l e i n f o
Article history:Received 5 July 2009
Accepted 22 September 2009Available online 17 October 2009
Keywords:
Energy-efficiency policy
Conservation supply curve
Cement industry
a b s t r a c t
The cement industry is one of the largest energy-consuming industries in Thailand with high carbondioxide (CO2) emissions. Using a bottom-up electricity Conservation Supply Curve (CSC) model, the cost
effective and the total technical electricity-efficiency potential for the Thai cement industry in 2008
is estimated to be about 265 and 1697 gigawatt-hours (GWh) which account for 8% and 51% of the total
electricity used in the cement industry in 2005, respectively. The fuel CSC model shows the cost-
effective fuel-efficiency potential to be 17,214 terajoules (TJ) and the total technical fuel-efficiency
potential equal to 21,202 TJ, accounting for 16% and 19% of the total fuel used in cement industry in
2005, respectively. The economic analysis in this paper shows how the information from the CSCs can
be used to calculate the present value (PV) of net cost savings over a period of time taking into account
the energy price escalation rate. The results from the policy scenario analysis show that the most
effective and efficient policy scenario is the introduction of an energy-related CO2 tax for the cement
industry under a voluntary agreement program. This scenario results in 16.9% primary energy-efficiency
improvement over a 5-year implementation period.
& 2009 Elsevier Ltd. All rights reserved.
1. Introduction
The industrial and transportation sectors are the largest
energy-consuming sectors in Thailand, and accounted for 36.1%
and 36.6% of total final energy consumption in 2007, respectively
(DEDE, 2008). There are many studies worldwide identifying a
wide variety of sector-specific and cross-cutting energy-efficiency
improvement opportunities for the industrial sector, particularly
for the cement industry. Worrell et al. (2000) at Lawrence
Berkeley National Laboratory (LBNL) carried out a comprehensive
study on energy efficiency and carbon dioxide (CO2) emission
reduction opportunities in the US cement industry. LBNL has also
developed a guidebook that comprises long lists of energy-efficiency improvement technologies and measures which are
commercially available for the cement industry (Worrell and
Galitsky, 2004; Worrell et al., 2008). There are also many
technology-specific studies such as Jankovic et al. (2004) in which
they discussed the optimization of ball mill cement grinding
circuits using certain type of crusher.
Different analytical approaches have been used to study the
energy efficiency and greenhouse gas emission reduction in
cement industry. Anand et al. (2006) used system dynamics
model based on the dynamic interactions among a number of
system components to estimate CO2 emissions from the cement
industry in India based on which they developed different CO2mitigation scenarios. The literatures mentioned above are just a
few of many studies that have been conducted on energy
efficiency in the cement industry. However, there are not many
sector-specific studies in Thailand for the energy intensive sectors,
particularly for the cement industry.
We used the concept of a Conservation Supply Curve to make
a bottom-up model in order to capture the cost effective as well as
the technical potential for energy efficiency and CO2 emission
reduction in the Thai cement sector. The Conservation SupplyCurve is an analytical tool that captures both the engineering and
the economic perspectives of energy conservation. It was first
introduced by Rosenfeld and his colleagues at Lawrence Berkeley
National Laboratory (Meier, 1982).
This study aims to give a comprehensive and easy to under-
stand perspective to Thai cement producers as well as policy
makers about the energy-efficiency potential, its associated cost,
and the effectiveness of some energy policies measures. This
paper, first, explains the steps of constructing the CSCs for the Thai
cement industry. Then, the economic analysis presented in this
paper which shall assist the cement producer to analyze the
financial benefit of investing in the energy-efficiency measures
ARTICLE IN PRESS
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/enpol
Energy Policy
0301-4215/$- see front matter & 2009 Elsevier Ltd. All rights reserved.
doi:10.1016/j.enpol.2009.09.030
Corresponding author. Tel.: + 66 8 55623894; fax: +66 2 8726736.
E-mail address: [email protected] (A. Hasanbeigi).
Energy Policy 38 (2010) 392405
http://-/?-http://www.elsevier.com/locate/enpolhttp://dx.doi.org/10.1016/j.enpol.2009.09.030mailto:[email protected]:[email protected]://dx.doi.org/10.1016/j.enpol.2009.09.030http://www.elsevier.com/locate/enpolhttp://-/?-8/3/2019 Industry Cement
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ARTICLE IN PRESS
listed here. The policy analysis, however, shall assist the Thai
policy makers in setting an appropriate cement sector-specific
mix of policies to capture energy-efficiency opportunities in
Thailands cement industry.
2. Overview of Thai cement industry
The cement industry has 8 companies that are comprised of14 plants and 31 kilns in 2006, yet a few kilns were decommis-
sioned during 2007 and 2008. The clinker production capacity
was 46.82 million tons in 2007, whereas the cement production
capacity was 56.302 in the same year. In 2007, the actual cement
production in Thailand was 29.98 million tons and the prediction
for the actual cement production in 2008 is 29.61 million tons
based on the forecast made by the Thai Cement Manufacturing
Association (TCMA) in November 2008 (TCMA, 2008).
In 2000, the cement industry consumed about 16% of the
overall manufacturing energy consumption in Thailand (DEDE,
2002). The use of energy in the cement manufacturing process
produces large amounts of CO2 and other local emissions. This
increases even more when we add the emissions from the
calcination process in cement production, which accounts for
about half of the total CO2 emission from the cement industry
(Hendriks et al.,2004). The calculated CO2 emission from Thai
cement industry was about 20.6 million tons of CO2 in 2005 (WRI,
1998; TCMA, 2008; ENCON Lab, 2008).1 Therefore, there is a
strong need for the assessment of different technologies and
measures to improve energy efficiency in and reduce GHG
emissions from this sector.
3. Methodology
3.1. Construction of energy conservation supply curves
Based on literature review for this study, we designed a
comprehensive questionnaire. We obtained the requested data
and technology-level information from main cement producers in
Thailand which together accounted for about 83% of total cement
production capacity in Thailand in 2008. For the other cement
producers that did not respond to our questionnaire and did not
want to participate in our study, we obtained some data about
their production capacity and other general information from the
Thai Cement Manufacturing Association (TCMA, 2008). For these
companies, which accounted for about 27% of cement production
capacity in Thailand in 2008, we assessed the potential applica-
tion of each energy-efficiency measure based on several factors
such as: the age of plants, the discussion with other cement
companies that participated in our study, and experts engineering
judgment. Because of the space constraint, we refer the readers to
Hasanbeigi and Menke (2008) for more details on the methodol-ogy for the construction of CSCs.
The Conservation Supply Curve (CSC) used in this study shows
the energy conservation potential as a function of the marginal
cost of conserved energy (Meier, 1982). The CCE can be calculated
from
Cost of conserved energy
annualized capital cost annual change in O&M costs
annual energy savings1
The annualized capital cost can be calculated from
Annualized capital cost Capital costd=1 1 dn 2
where d is the discount rate and n the lifetime of the energy-
efficiency measure.
In our study, we assumed the real discount rate equal to 30% to
reflect the barriers to energy-efficiency investment in Thai cement
industry such as: perceived risk, lack of information, management
concerns about production and other issues, capital constraints,
and preference for short payback periods and high internal rates
of return (Bernstein et al., 2007; Worrell et al., 2000). Since we
decided to plot CSCs for electricity and fuel separately, we
calculated the cost of conserved electricity (CCE) and cost of
conserved fuel (CCF) separately for respective technologies in
order to draw CSCs. After calculating the CCE or CCF for all energy-
efficiency measures, we ranked them in ascending order of CCE or
CCF. In CSCs we determine an energy price line. All measures that
fall below the energy price line are cost effective. On the curves,
the width of each measure (plotted on the x-axis) represents the
annual energy saved by that measure. The height (plotted on the
y-axis) shows the measures cost of conserved energy.
Finally, it should also be highlighted that the approach used in
this study and the model developed is a good screening tool to
present energy-efficiency measures and capture the potentials for
improvement. However, in reality, energy saving potential and
cost of each energy-efficiency measure and technology may vary
and depend on various conditions such as raw material quality,
country in which the plant is located, the technology provider,
production capacity, size of the kiln, fineness of the final product
and byproducts, etc. Moreover, it should be noted that some
energy-efficiency measures provide productivity and environ-
mental benefits in addition to energy savings, but it is difficult and
sometimes impossible to quantify those benefits. However,
including quantified estimates of other benefits could significantly
reduce the cost of conserved energy for the energy-efficiency
measures (Worrell et al., 2003). Furthermore, in the interpretation
of the results and their level of accuracy, the uncertainty of some
input data such as energy saving and cost of the energy-efficiencymeasures should be taken into account.
3.1.1. Energy-efficiency technologies and measures
for cement industry
Despite the extensive literature review in this study, informa-
tion and data about the 47 energy-efficiency technologies and
measures applied to the Thai cement industry has mainly been
obtained from the studies conducted at Lawrence Berkeley
National Laboratory (LBNL) (Worrell et al., 2000, 2008) as well
as Project Design Documents (PDDs) of CDM projects (UNFCCC,
2008ac; UNFCCC, 2007ae). Since there are only dry kilns in
Thailand, all the energy-efficiency measures are applicable for the
dry kiln process. Table 1 presents the data related to production
capacity in each step of cement production process in Thai cement
industry. It also presents the energy savings, capital costs and CO2emission reductions for each energy-efficiency technology and
measure applied to Thailands cement industry in 2008. In this
paper, we prefer not to explain the details of each energy-
efficiency measure, but rather prefer to present and discuss the
results. However, the detailed description of each energy-
efficiency measure listed can be found in Worrell et al. (2008),
UNFCCC (2007ae), and UNFCCC (2008ac).
3.2. Economic analysis
The CSC presented in this paper gives us some very useful
information. It presents the cost of conserved energy (CCE),
1 Since reliable data for energy consumption by the type of fuels are not
available, we calculated the CO2 emission in 2005 using the historical data and
production growth rate.
A. Hasanbeigi et al. / Energy Policy 38 (2010) 392405 393
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Table 1
Energy savings, capital costs and co2 emission reductions for energy efficiency technologies and measures applied to Thai cement industry.
No. Technology/measure Production
capacity
(Mton/year)
Fuel saving
(GJ/ton
cement)
Electricity
saving
(kWh/ton
cement)
Primary energy
saving (GJ/ton
cement)
Capital cost Change i
annual O
Cost (US$
Fuel preparation
1 Installation of variable
frequency drive &
replacement of coal mill
bag dust collectors fan
a 0.13 0.001 0.027($/ton clb) 0.0
2 Replacement of separator
in coal mill circuit with an
efficient grit separator
a 0.21 0.002 0.011($/ton cl) 0.0
Raw materials preparation
3 Efficient transport system 67.17 2.51 0.03 3.00 ($/ton raw) 0.0
4 Raw meal blending 67.17 2.14 0.02 3.70 ($/ton raw) 0.0
5 Raw meal process control
(vertical mill)
67.17 1.13 0.01 0.28 ($/ton raw) 0.0
6 High efficiency roller mill 67.17 8.17 0.09 5.50 ($/ton raw) 0.0
7 High efficiency classifiers 67.17 4.08 0.05 2.20 ($/ton raw) 0.0
8 Variable frequency drive
in raw mill vent fan
67.17 0.27 0.003 0.025($/ton cl) 0.0
9 Bucket elevator for raw
meal transport from raw
mill to homogenizing
silos
67.17 1.91 0.022 0.228 ($/ton cl) 0.0
10 Install ation 3-fan system
with a separate mill fan to
take care of vertical roller
mill operation
67.17 1.86 0.022 0.959 ($/ton cl) 0.0
11 High efficiency fan for
raw mill vent fan with
inverter
67.17 0.29 0.003 0.033 ($/ton cl) 0.0
Clinker making
12 Energy management and
process control systems
43.34 0.16 1.00 ($/ton cl) 0.0
13 Combustion system
improvement
43.34 0.24 0.24 1.00 ($/ton cl) 0.0
14 Kiln shell heat loss
reduction
43.34 0.21 0.21 0.25 ($/ton cl) 0.0
15 Optimize heat recovery/
upgrade clinker cooler
43.34 0.09 1.62c 0.07 0.20 ($/ton cl) 0.0
16 Convert to reci procatinggrate cooler
43.34 0.22 2.43c
0.19 2.80 ($/ton cl) 0.11
17 Low temp. waste heat
recovery power
generation
43.34 24.73 0.29 1828 ($/kW) 0.007
18 High temperature heat
recovery for power
generation
43.34 17.84 0.21 3.3 ($/ton cl) 0.27
19 Low pressure drop
cyclones for suspension
preheater
43.34 2.11 0.02 3.00 ($/ton cl) 0.0
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20 Upgrading of a preheater
kiln to a preheater/
precalciner
43.34 0.35 0.35 18.00 ($/ton cl) 1.10
21 Conversion of long dry
kiln to preheater/
precalciner
43.34 1.14 1.14 20.00 ($/ton cl) 0.0
22 Older dry kiln upgrade to
multi-stage preheater
kiln
43.34 0.73 0.73 35.00 ($/ton cl) 0.0
23 Adjustable speed drive for
kiln fan
43.34 4.95 0.06 0.23 ($/ton cl) 0.0
24 Upgrading the preheater
from 5 stages to 6 stages
43.34 0.09 0.95c 0.079 2.54 ($/ton cl) 0.0
25 Modifying clinker cooler
(mechanical flow
regulator)
43.34 0.07 0.00 0.069 0.489 ($/ton cl) 0.0
26 Efficient kiln drives 43.34 0.45 0.005 0.190 ($/ton cl) 0.0
27 VFD in cooler fan of grate
cooler
43.34 0.09 0.001 0.012 ($/ton cl) 0.0
28 Modification of inlet duct
of grate cooler fan
43.34 0.037 0.0004 0.0003 ($/ton cl) 0.0
29 Bucket elevators for kiln
feed
43.34 1.01 0.012 0.352 ($/ton cl) 0.0
30 High efficiency fan for
primary air fan along with
inverter for speed control
of the fan
43.34 0.089 0.001 0.006 ($/ton cl) 0.0
31 Installation of vortex
finder vanes on top stage
cyclones for reduction indifferential pressure
43.34 0.503 0.006 0.068($/ton cl) 0.0
32 Installation of SPRS (slip
power recovery system)
for precalciner s fan
speed control
43.34 0.503 0.006 0.07 ($/ton cl) 0.0
33 Replacement of preheater
fan with high efficiency
fan
43.34 0.568 0.007 0.068 ($/ton cl) 0.0
34 Optimization of the
diameter of preheaters
exit gas downcomer duct
43.34 0.259 0.003 0.06 ($/ton cl) 0.0
Finish grinding
35 Energy management &
process control in
grinding
53.45 3.24 0.04 0.50 ($/ton cement) 0.0
36 Improved grinding media
for ball mills
53.45 4.00 0.05 0.70 ($/ton cement) 0.0
37 Replacing a ball mill with
vertical roller mill
53.45 17.00 0.20 5.00 ($/ton cement) 0.0
38 Hi gh pressure roller press
as pre-grinding to ball
mill
53.45 16.00 0.18 5.00 ($/ton cement) 0.0
39 Hi gh-efficiency classi fiers
(for finish grinding)
53.45 4.00 0.05 2.00 ($/ton cement) 0.0
40 Replacement of cement
mill vent fan
53.45 0.11 0.001 0.009 ($/ton cl) 0.0
General measures
41 Preventative maintenance 53.45 0.04 2.43 0.07 0.01 ($/ton cement) 0.0
42 High efficiency motors 53.45 3.00 0.03 0.22 ($/ton cement) 0.0
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annualized cost of energy-efficiency measures, annualized energy
cost saving, annualized net cost saving, and annualized energy
saving by each individual technology or a group of technologies.
The calculation of CCE is already explained above. If dE is the
energy saving by a technology, then the annualized cost of energy-
efficiency measure, annualized energy cost saving, and the
annualized net cost saving of that technology can be calculated
from
AC dECCE 3
AECS dEP 4
ANC AECS AC dEP CCE 5
where AC is the annualized cost of energy-efficiency measure
(US$), AECS the annualized energy cost saving (US$), ANC the
annualized net cost saving (US$), P the energy price, and dE the
energy saving in CSC.
For the cost-effective energy-efficiency measures in the CSC,
the annual net cost saving is positive, yet for the measures whose
CCE or CCF is above the energy cost line, the annualized net cost
saving is negative.
However, we always talk about the Cost of energy-efficiency
improvement. The common use of the term Cost usually givesthe impression that we have to spend money. However, in many
cases, especially the case of cost-effective energy-efficiency
measures as we presented above, money is actually earned by
saving the cost of energy. The amount of revenue obtained by an
energy-efficiency measure can be accurately presented if we
calculate the life cycle cost (LCC) of the measure. By LCC, we mean
that we take into account the cost and benefits of an energy-
efficiency measure over its lifetime.
A CSC gives the annualized cost with a constant energy price in
the base year, whereas in reality the energy price is usually
changing from year to year. Thus, for policy analysis, when we
calculate the LCC of energy-efficiency measures, we should take
into account the changes in energy price; otherwise we sig-
nificantly overestimate/underestimate the energy cost savings.We have used 2008 as the base year and conducted the economic
analysis based on the constant 2008 dollar. Thus, the real discount
rate is also used in our analysis, which excludes the inflation rate.
In order to have the economic analysis in line with the policy
analysis, we have assumed a period of 15 years for the economic
analysis, as it is the scenario period used in the policy analysis
explained later in this paper. To calculate the present value (PV) of
net cost saving over the scenario period, i.e. 15 years, taking into
account the annual escalation rate for energy price we conducted
the following procedure. First, we calculated the present value of
energy cost saving over the scenario period with an annual
escalation rate for energy price using Eq. (6) (Fuller and Petersen,
1996):
PVECS dEP1 e
d e1
1 e
1 d
N
" #6
Where PVECS is the present value of energy cost saving over
scenario period (US$), dE the energy saving, P the energy price, d
the real discount rate, e the real energy price escalation rate, and N
the scenario period.
In this case, dEnP is the energy cost saving in the base year as
presented in Eq. (4). The escalation rate can be positive or
negative. It should be noted that this formula is for constant
escalation rate, while in reality the energy price escalation
changes from year to year. However, for simplicity, we assumed
a constant escalation rate for fuel and electricity prices based on
their historical trends. Since we conducted the economic analysis
in constant 2008 dollar, we used the real discount rate. The realTable1(continued
)
No.
Technology/measure
Production
capacity
(Mton/year)
Fuelsaving
(GJ/ton
cement)
Electricity
saving
(kWh/ton
cement)
Primaryenergy
saving(GJ/ton
cement)
Capitalcost
Changein
annualO&M
Cost(US$/ton)
CO
2
emission
reduction
(kgCO
2/ton
cement)
Shareof
production
capacitytowhich
themeasureis
applied(%)
43
Adjustablespeeddrives
53
.45
6.0
0
0.0
7
0.9
0($/toncement)
0.0
3.1
1
27
Product
Change
44
Blendedcement
53
.45
2.1
9
8
.9c
2.0
9
0.7
2($/toncement)
0
.06
212
.54d
5
45
Useofwaste-derived
fuels
53
.45
0.4
9
0.4
9
1.1
0($/toncl)
0.0
48
.26
5
46
Portlandlimestone
cement
53
.45
0.2
8
3.3
0
0.3
2
0.1
8($/toncement)
0.0
29
.86d
6
47
Useofsteelslaginthe
kiln(CemStar)
53
.45
0.1
5
0.1
5
0.4
0($/toncement)
0.0
15
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A. Hasanbeigi et al. / Energy Policy 38 (2010) 392405396
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discount rate is also assumed to be 30%, same as its value in
constructing CSC. Therefore, we had to use real energy price
escalation rate as well. From the historical data for electricity and
fuel prices in Thai cement industry (DEDE, 2008), we calculated
the average annual growth rate of energy prices for the cement
industry between 1990 and 2008. Since the prices of energy are
given in current dollar in DEDE (2008), we assumed this average
as the nominal energy price escalation. Then, we calculated the
real price escalation from the following formula:
e 1 E=1 I 1 7
where e is the real price escalation, Ethe nominal price escalation
and I the inflation rate (Fuller and Petersen, 1996). We calculatedthe average inflation rate2 between 1990 and 2008 in Thailand to
be about 4.0% (BOT, 2009), and we used that in Eq. (7). The results
of our calculations for nominal and real energy price escalation
are presented in Table 2. As can be seen from Table 2, since the
nominal electricity price escalation rate is less than the inflation
rate, the real electricity price escalation rate is negative. However,
since the nominal fuel price escalation is almost equal to the
inflation rate, the real fuel price escalation is zero. It should be
noted that this analysis is specific just to Thai cement industry.
The same analysis for other countries may result in positive real
price escalation. Finally, we assumed that the real price escalation
and inflation rate in the future over the scenario period are equal
to their value calculated based on the historical data in the way
explained above.
Then, we calculated the total industry-wide capital cost of each
energy-efficiency measure from
TCC CCPrS 8
TCC is the total industry-wide capital cost of energy-efficiency
measure (US$), CC the capital cost (US$/ton product), Pr is the
annual production capacity (ton), S is the share of production
capacity to which the measure is applied (%)
(sense not clear)Since the total capital cost is calculated in the
year 2008, that could be used as the present value of total
industry-wide investment required for each energy-efficiency
measure. Therefore, the PV of the net cost saving (US$) over the
scenario period taking into account the energy price escalation
can be calculated from
PVN PVECS TCC 9
PVN is the PV of the net cost saving over scenario period (US$).
All the above-mentioned calculations have been conducted
separately for electricity-efficiency measures and fuel-efficiency
measures related to the ECSC and FCSC. It should be noted that
this study is for the whole Thai cement industry; thus, all the
analyses are industry-wide. The analyses presented in this paper
are just related to the current installations which are studied. The
economic analysis presented in this section is used as the basis
for cost calculations in all the policy scenarios discussed in
Section 3.3.
3.3. Policy analysis
Using the results of energy CSCs developed for the Thai cement
industry, we conducted a policy analysis by developing several
energy policy scenarios. We assumed that the policies will be in
effect by the end of 2010 and that until then there will not be a
significant structural change in the Thai cement industry. All the
policy scenarios are in the framework of short-term voluntary
agreements (VA). Voluntary agreements are essentially a con-tract between the government and industry, or negotiated targets
with commitments and time schedules on the part of all
participating parties (Price, 2005). The duration for the envi-
sioned VA program is between 2011 and 2015. We, thus, assumed
that the implementation of energy-efficiency measures under
various VA scenarios will happen during this 5-year period. We
also assumed the constant cement production during 20112015.
To calculate the LCC of energy-efficiency measures implemented
in VA programs, we set the scenario period equal to 15 years after
2015. Hence, we calculated the energy savings and LCCs from 2016
to 2030. For simplification, we assumed the end of the VA
programs, i.e. year 2015 as the base year for calculation of the
costs and savings of the programs. However, it should be noted
that the lifetimes of some energy-efficiency measures is morethan 15 years; thus, more energy saving is achievable by those
measures beyond the scenario period. Business-as-usual scenario
and four other scenarios based on the four different portfolios of
energy-efficiency policies are developed. Each scenario is dis-
cussed in more detail below. The costs are in constant 2008
US dollars; thus, the real discount rate and the real annual
escalation rates for electricity and fuel prices are used. Finally, we
assumed that administrative costs of energy-efficiency programs
included in the voluntary agreements are negligible.
3.3.1. Business-as-usual scenario
In the business-as-usual (BAU) scenario, we assumed that
there will be no energy-efficiency policy intervention during
20112015. The real discount rate of 30% is used in BAU scenario.Furthermore, we assumed that just 25% of energy-efficiency
measures with positive PV of net cost saving over scenario period
(Section 3.2, Eq. (9)) will be implemented during 20112015.
However, it should be noted that the PV mentioned in the policy
analysis section is actually the value at the start of policy scenario
period, i.e. start of 2016 and not the value in 2008.
3.3.2. Moderate VA program (completely voluntary)
The Moderate VA program (MVA) consists of a portfolio of
energy policies to support energy-efficiency improvement in Thai
cement industry. The portfolio comprises several non-monetary
policies as well as fiscal incentives. The non-monetary policies are
information dissemination on energy-efficiency technologies for
cement industry in different ways, e.g. technical newsletters, casestudies reports, web-based information, etc. Furthermore, it
includes benchmarking data and tools. This MVA program also
creates an energy working group which is the network between
Thai cement companies under TCMA for the exchange of
experiences in energy-efficiency improvement. The fiscal incen-
tive in the MVA program is the 30% investment subsidy for the
energy-efficiency measures which have negative PV of net cost
saving over scenario period (Section 3.2, Eq. (9)). The participation
in the moderate VA program is completely voluntary. Further-
more, there are no consequences for not reaching the agreed
target by participating companies.
Since the participation in the program is completely voluntary
and the supporting policies are relatively soft, some cement
companies may not be interested in participating. Even if they do
Table 2
Nominal and real electricity and fuel price escalation rate for Thai cement industry.
Electricity(%) Fuel(%)
Nominal energy price escalation rate
(E) (average of annual growth rate
of energy price for cement industry
between 1990 and 2008)
2.3 3.9
Real energy price escalation rate (e) 1.6 0.0
2
This is the general inflation rate given by the Bank of Thailand.
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participate, experiences in other countries show that the VA
programs that are completely voluntary often do not meet their
targets and even may not go beyond the business-as-usual
scenario (Price, 2005; Chidiak, 2002). Hence, we assumed that
just 30% of energy-efficiency measures with positive PV of net
cost saving over the scenario period with or without subsidy will
be implemented in the MVA program during 20112015 (without
subsidy for cost-effective measures and with subsidy for non-
cost-effective measures, which will have positive net cost savingafter taking into account 30% investment subsidy). This is 5% more
than the BAU scenario. However, in the MVA scenario, we also
assumed that we can still get the participation of Thai cement
producers, as there are four main cement producers which
account for about 95% of cement production capacity in Thailand.
Thus, we assumed government can get their participation, yet as
mentioned above the companies may not act much beyond their
BAU. The real discount rate is assumed to be 30% in MVA program.
This shows that, in MVA scenario, companies still have some
uncertainty and non-monetary obstacles and may not have
enough motivation to act aggressively towards energy-efficiency
improvement.
3.3.3. Advanced VA program (without CO2 tax)
The Advanced VA program without CO2 tax (AVAW/O) consists
of a portfolio of energy policies, which is to some extent the same
as the MVA program. However, there are some major differences.
The most important difference is that AVAW/O is a virtually
mandatory program. That is, although the program is called
voluntary agreement, the Thai government would take some
actions that make it inevitable for cement companies to
participate. In other words, there will be some serious con-
sequences for non-participants. Thus, companies prefer to join the
program, and while benefiting from the supportive policies, they
commit to improve energy efficiency to a certain extent as agreed
upon between them and the government and take the actions
defined in the agreement. There are several ways that government
can actually force cement companies to participate in AVAW/O
program such as: implying the threat of future tighter energy and
environmental regulations, offering relief or exemption from
additional regulation, or setting penalties for non-compliance
with the regulation (Price, 2005). The fiscal incentive is also
included in AVAW/O program and is same as the one offered in
the MVA program.
As a result of the virtual mandate for participation in the
program and taking action towards energy-efficiency improve-
ment as well as supportive policies to remove barriers to energy
efficiency, we assumed a discount rate of 15% in AVAW/O
program. The discount rate of 15% for economic analysis under
this program can also be set by the government. Therefore, the
CCE of measures with 15% discount rates will decrease to about
half of those with 30% discount rates. In the advanced VAprogram, companies should take more aggressive actions toward
energy efficiency. Thus, we assumed that 50% of energy-efficiency
measures with positive PV of net cost saving over the scenario
period (after taking into account the subsidy as explained above)
will be implemented in AVAW/O programs during 20112015. The
experiences of virtually mandatory VA programs in other
countries also showed that companies take more serious action
and larger steps toward energy efficiency than that of in BAU or
completely VA programs (Togeby et al., 1998; Price, 2005). In The
Netherlands the Long-Term Agreements, which are an example of
an AVAW/O program, participating companies achieved an
energy-efficiency improvement of 22.3% between 1989 and
2000, exceeding the 20% goal set for the program (Reitbergen
et al., 2002; Price, 2005).
3.3.4. Advanced VA program (with CO2 tax)
The Advanced VA program with CO2 tax (AVAW) is slightly
different from the AVAW/O program mentioned above. The
difference is that we introduced an energy-related CO2 tax for
Thai cement companies in the AVAW program. It was outside of
the scope of this study to find out the best value of the energy-
related CO2 tax to be applied to Thai cement industry. Thus, we
used the experiences in other countries with some modification to
apply to Thailand. Specifically, we used the experience ofimplementing an energy-related CO2 tax applied to Danish
Industry under a voluntary agreement program (Togeby et al.,
1998; Price et al., 2005). In 1992, Denmark introduced a CO2 tax
on both household and business energy consumption. They also
introduced voluntary energy-efficiency agreements for industry.
The industrial companies that participated in the agreement
would benefit from substantial discount in their CO2 tax. The level
of the CO2 tax in the Danish voluntary agreement was different
depending on the size of the company and its CO2 emission. The
1999 Danish CO2 tax set for heavy process industry in which the
cement industry is included is h 3.4 per ton of CO2 without
agreement and h 0.4 per ton of CO2 with agreement (Price et al.,
2005).
However, since energy prices are different in Denmark
compared to Thailand (OECD, 2007) and because the economic
conditions of these two countries are different, we did not assume
the exact same price for energy-related CO2 tax. The Danish
government introduced the CO2 tax first in 1992 with much lower
price. Thus, any CO2 tax that is to be introduced for Thai cement
industry should start with lower prices than the current price of
CO2 for the Danish industry. We assumed that the energy-related
CO2 tax for Thai cement industry will be half of the price in the
1999 Danish CO2 tax proposal. Therefore, the CO2 tax for the Thai
cement industry under the AVAW program is THB 83.2 (h 1.73) per
ton of CO2 without agreement and THB 9.8 (h 0.2) per ton of CO2with agreement. Since all the Thai cement companies will join the
AVAW program because of the benefit from the CO2 tax cut, the
THB 9.8 (h 0.2) per ton of CO2 is used as the price of CO2 tax for the
calculation of revenue from CO2 taxation during the implementa-
tion period of VA, i.e. 20112015. Furthermore, we assumed that
50% of annual CO2 emission from the cement industry is energy-
related emission and the other 50% is from calcinations in the
cement production process (Hendriks et al., 2004). It should be
noted that the price of CO2 tax (even for Danish industry) is far
below the price of Certified Emission Reductions (CERs) in the
CDM projects. The price of CER used for the financial calculations
of recent CDM projects in Thai cement industry was THB 600
(UNFCCC, 2008a).
The discount rate of 15% is used in the AVAW scenario. In
addition in this case the investment subsidy is higher and is 50%
which is paid from the revenue of energy-related CO2 tax that is
introduced under the AVAW scenario for the energy-efficiency
measures with negative PV of net cost saving over the scenarioperiod (20112015). Thus, one other difference between the
Advanced VA program (without CO2 tax) and the Advanced VA
program (with CO2 tax) is that in AVAW/O scenario, the 30%
subsidy is provided from the government budget, whereas in the
AVAW scenario the 50% investment subsidy is provided from
the revenue from the energy-related CO2 tax. The rest of non-
monetary policies, i.e. information dissemination, benchmarking
data, etc. in the AVAW are same as those in the AVAW/O scenario.
Because of the same reason mentioned above for AVAW/O,
we assumed that 50% of energy-efficiency measures with positive
PV of net cost saving over the scenario period with or without
3
The exchange rate for THB/Euro in 2008=48.93 (BOT, 2008).
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subsidy will be implemented in AVAW scenario during
20112015.
3.3.5. Technology-oriented VA program (TVA)
The last policy scenario that we developed in this study is the
Technology-oriented Voluntary Agreement program (TVA). This
program is related to the implementation of low temperature
waste heat recovery (WHR) for power generation technology
using CDM program. We have chosen this technology for several
reasons: (1) this technology is already commercialized and widely
available from various companies in different countries with
different specification and capital cost, (2) many cement compa-
nies around the world have used this technology and many of
them, especially in China and India, have used CDM for the
implementation of this technology, and (3) this technology results
in significant energy saving (about 25 kWh/ton cement). Even
with the 30% discount rate, this measure is already cost effective if
we take into account the revenue from selling the certified
emission reductions (CERs) of the CDM project. Despite this, just
three Thai cement plants have implemented this technology using
CDM and some other are in the construction phase.
We assumed that Thai government can establish the agree-
ment with Thai cement producers to stimulate them to take
aggressive action in implementation of low temperature waste
heat recovery technology for power generation. Government can
provide assistance to cement companies in the development of
Project Design Document (PDD) of the CDM project. The
government can also assist them in all other procedures of
documentation, submission of PDD, communication, etc. In a
more aggressive scenario, the Thai government can show the
warning signs to the cement companies for the increased price of
electricity if they do not participate in the program and takeaction. We assumed that all the Thai cement companies will
participate in the TVA program, yet we exclude the cement plants
which have already installed or are installing this technology from
the potential application in our analysis. In this scenario, we use
15% discount rate, as the government intervention for the
implementation of this technology will remove many non-
monetary barriers. For all other technologies we assumed a 30%
discount rate in this policy scenario. There is no investment
subsidy in the TVA program.
We also assumed that 75% of the potential application of low
temperature waste heat recovery (WHR) for power generation
technology will be captured under TVA program. For the rest of
technologies, since they do not benefit from the TVA program, we
assumed just 25% of energy-efficiency measures with positive PV
of net cost saving over the scenario period will be implemented
during 20112015 (same as BAU scenario). For the price of carbon
credits, we used US$ 18.2 per ton of CO2 (THB 6004 per ton of CO2)
(UNFCCC, 2008a). For the revenue from selling the carbon credits,we multiplied the CO2 savings per year by the unit price of carbon
credit and divided by two. The reason that we divided it by two is
that the lifetime of low temperature waste heat recovery
technology is 20 years while the sale of carbon credits is just 10
years. Since the capital cost of the technology is annualized based
on 20 years lifetime, we divided the revenue from selling the
carbon credits by two so that it can be extended from 10 to 20
years. We can then subtract this annual revenue from annualized
capital cost in the CCE calculation. Table 3 shows the assumptions
for each energy policy scenario.
4. Results and discussions
4.1. Energy-efficiency improvements opportunities in the Thai
cement industry
Based on the methodology explained and information in
Table 1, we constructed an Electricity Conservation Supply Curve
(ECSC) and a Fuel Conservation Supply Curve (FCSC) separately
to capture the cost effective and total technical potential for
electricity- and fuel-efficiency improvement in Thai cement
industry. Furthermore, we calculated the CO2 emission reduction
potential from Thai cement industry. Out of 47 energy-efficiency
measures listed in Table 1, 38 measures were applicable to Thai
cement plants, 28 of which are electricity saving measures that
are included in ECSC and 10 of them are fuel saving measures that
form the body of FCSC.
4.1.1. Electricity conservation supply curve (ECSC)
Twenty-eight energy-efficiency measures form the basis of the
Electricity Conservation Supply Curve (ECSC). Table 4 shows the
list of these 28 technologies. We can see from Fig. 1 and Table 4
that 17 energy-efficiency measures fall under the electricity price
line for cement industry in 2008 (US$ 69.7/MWh). Therefore, for
these measures the CCE is less than the average electricity price.
In other words, the cost of investing on these 17 energy-efficiency
measures to save 1 MWh of electricity is less than purchasing
1 MWh of electricity with the given price. This is the so-
called cost effectiveness of an energy-efficiency measure. The
Table 3
Assumptions for sector-specific energy policy scenarios to improve energy efficiency in and reduce CO2 emissions from the Thai cement industry.
Parameters Business-
As-Usual
(BAU)
Moderate VA
program
(MVA)
Advanced VA program
(without CO2 tax)
(AVAW/O)
Advanced VA program (with CO2 tax)
(AVAW)
Technology-oriented VA
program (TVA)
Real discount rate 30% 30% 15% 15% 15% (for WHR technology)
30% (for all other
technologies)
Adoption rate of measures withpositive PV of net cost saving
25% 30% 50% 50% 75% (for WHR technology)25% (for all other
technologies)
Investment subsidy for measures
with negative PV of net cost
saving
30% 30% 50%
CO2 tax THB 83.2 per ton of CO2 (without
agreement) THB 9.8 per ton of CO2 (with
agreement)
Participation Completely
voluntary
Virtually mandatory Virtually mandatory Virtually mandatory
4
The exchange rate for THB/US$ in 2008=33.02 (BOT, 2008).
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cost-effective electricity-efficiency improvement potential for
Thai cement industry in 2008 is equal to 265 GWh per year. Thisis about 8% of the cement industrys total electricity use in 2005.
The total technical electricity saving potential is 1697GWh per
year, which is about 51% of the cement industrys total electricity
consumption in 2005 (Table 5).
Measure number 18, low temperature waste heat recovery for
power generation, has the highest electricity saving potential and
is very close to being cost effective. It should be noted that this
measure is implemented through CDM project in many plants,
which provides extra revenue from the implementation by selling
the CERs. In Section 3.3.5 of this paper we explained the
methodology of including the revenue from carbon credits into
the calculation of CCE of low temperature waste heat recovery for
power generation technology. Following that methodology, the
CCE is equal to 67.1 US$/MWh saved with the discount rate of 30%
if we take into account the revenue from carbon credits obtained
via CDM project. This CCE is lower than the 2008 electricity price(69.7 US$/MWh), thus making this technology cost effective.
Table 5 summarizes the results for electricity savings and
carbon dioxide emission reductions associated with the savings.
The reason for the small contribution of electricity savings to
reduction of total CO2 emission from the Thai cement industry
is that the electricity consumption is not the major source of
CO2 emission in cement plants. The major sources of CO2 emission
are fuel consumption as well as calcination in the clinker making
process.
4.1.2. Fuel conservation supply curve (ECSC)
Ten energy-efficiency measures construct the Fuel Conserva-
tion Supply Curve (FCSC). Fig. 2 shows that 9 energy-efficiency
Table 4
Electricity efficiency measures which are ranked by their cost of conserved electricity (CCE) and their annual net cost saving and PV of net cost saving over the period of
15 years
No. Efficiency Measure Electricity
saving
(GWh/yr)
CO2 emission
reduction
(kton CO2/yr)
Cost of Conserved
Electricity (US$/
MWh- saved)
Annual net cost saving (with
constant 2008 electricity
price) (1000 US$)
PV of the net cost saving over
15 years with electricity price
escalation (1000 US$)
1 Preventative maintenance 13.3 29.0 1.3 913 2795
2 Modification of inlet duct of grate cooler
fan
0.1 0.0 2.0 6 18
3 Adjustable speed drive for kiln fan 5.9 3.0 11.5 341 1032
4 Replacement of separator in coal mill
circuit with an efficient grit separator
2.5 1.3 12.9 142 430
5 High efficiency fan for Primary Air fan
along with inverter for speed control of
the fan
0.1 0.1 16.7 6 17
6 Replacement of cement mill vent fan 0.1 0.1 21.2 6 18
7 High efficiency motors 43.1 22.4 22.4 2035 6048
8 Variable frequency drive (VFD) in raw
mill vent fan
4.0 2.1 23.2 187 555
9 High efficiency fan for Raw Mill vent fan
with inverter
0.3 0.2 28.0 14 42
10 Bucket elevator for raw meal transport
from raw mill to homogenizing silos
2.3 1.2 29.7 90 264
11 Replacement of preheater fan with a
high efficiency fan
0.7 0.3 29.7 27 78
12 Installation of vortex finder vanes on topstage cyclones for reduction in
differential pressure
17.8 9.3 33.6 644 1854
13 Variable Frequency drives (VFD) in
cooler fan of grate cooler
3.1 1.6 33.7 110 317
14 Adjustable speed drives 86.1 44.7 45.9 2046 5479
15 Energy management & process control
in finish grinding
81.5 42.3 47.2 1832 4845
16 Installation of VFD & replacement of
coal mill Bag Dust Collectors fan
3.3 1.7 51.6 59 146
17 Optimization of the diameter of
preheater s exit gas downcomer duct
0.6 0.3 57.4 8 16
18 Low temperature waste heat recovery
for power generation
646.0 335.1 71.8a 1375 15,764
19 Bucket elevators for kiln feed 1.2 0.6 86.9 21 84
20 Replacing a ball mill with vertical roller
mill for finish grinding
427.2 221.6 88.7 8137 34,390
21 High pressure roller press as pre-grinding to ball mill for finish grinding
224.7 116.5 94.2 5525 22,218
22 Raw meal process control (Vertical mi ll) 22.0 11.4 95.2 562 ,144
23 Efficient kiln drives 2.4 1.3 105.7 8 322
24 Installation 3-fan system with a
separate mill fan to take care of vertical
roller mill operation
2.2 1.1 127.6 128 450
25 Hi gh-efficiency classifiers (for raw mill ) 4.8 2.5 207.1 666 2245
26 High efficiency roller mill 44.8 23.2 258.9 8479 28,341
27 Efficient transport system 3.0 1.5 459.0 1161 3836
28 Raw meal blending 53.7 27.8 666.0 32,014 105,381
a In calculation of CCE for the low temperature waste heat recovery system for power generation, the monetary value of CERs from a CDM project is not taken into
account. If the value of CERs is taken into account, the CCE will be 67.1 US$/MWh-saved with the discount rate of 30%.
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measures fall under the weighted average fuel price line forcement industry in 2008 (US$ 4.2/GJ). Therefore, for these
measures the CCF is less than the weighted average fuel price.
Table 6 shows the list of all fuel saving measures ranked by their
CCF.
The cost-effective fuel-efficiency improvement potential for
the Thai cement industry in 2008 is equal to 17,214TJ per year
which represents about 16% of the cement industrys total fuel use
in 2005, whereas the total technical fuel saving potential is
21,202TJ per year , about 19% of the cement industrys total fuel
consumption in 2005 (Table 7). It should be noted that the energy
saving of the product change measures (i.e. measures 1, 3, 5, and 7
in Table 6), highly depends on the plant specific situation and the
efficiency of current facilities. There are also preconditions for
increasing the share of other types of cement in the production
portfolio of the cement companies such as: supportive policy fromgovernment, the required regulations and standards, and the
market and public acceptance.
4.2. Economic analysis of energy-efficiency improvement potentials
Based of the methodology explained in Section 3.2 of this
paper, we calculated the annual net cost saving with a constant
2008 energy price for each energy-efficiency measure that is
applicable to Thai cement industry and already plotted in CSCs in
this paper. Furthermore, we have computed the present value (PV)
of net cost saving over the period of 15 years taking into account
the energy price escalation rate. The results are presented in
Tables 4 and 6 for electricity-efficiency and fuel-efficiency
Table 5
Cost effective and technical potential for electricity saving and CO2 emission reduction in Thai cement industry for the base year 2008.
Electricity saving potential (GWh/yr) Carbon dioxide emission reduction (ktCO2/yr)
Cost effective Technical Cost effective Technical
Base year: 2008 265 1697 159 902
Share from total cement industry in 2005a(%) 8 51 0.8 4.4
a Since the data for energy use in Thai cement industry in 2005 is more reliable than other recent years, we have chosen this year for the comparison.
0
1
2
3
4
5
6
7
8
9
10
0
Cos
to
fConserve
dFu
el(US$/GJ-save
d) Technical fuel saving
potential: 21,202 TJ
Weighted average fuel price for
cement industry in 2008 (US$ 4.2/ GJ)
1 2 435 6
7
98
10
Cost effective fuel saving
potential: 17,214 TJ
3,000 6,000 9,000 12,000 15,000 18,000 21,000
Fuel saving potential (TJ)
Fig. 2. Fuel conservation supply curve (FCSC) for Thai cement industry.
0
50
100
150
200
250
300
350
400
450
500
550
600
650
700
0
Energy saving potential (GWh)
Cos
tofC
onserve
dElec
tricity
(US
$/MWh-save
d)
Electricity price line
for cement industry in
2008 (US$ 69.7/ MWh)
1-5
6-13 1416-1715
1819 20
22-2421
25
26
27
28
Cost effective
electricity saving
potential: 265 GWh
Technical electricity
saving potential:
1,697 GWh
300 600 900 1,200 1,500 1,800
Fig. 1. Electricity conservation supply curve (ECSC) for Thai cement industry.
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measures, separately. Negative net cost saving occurs for non-
cost-effective measures. That is, the cost of the measure surpasses
the energy cost saving. However, for some non-cost-effective
measures, especially the ones which are closer to the energy price
line in the CSC, although their annual net cost saving always will
be negative, their PV of net cost saving over the scenario period
could be positive if the energy price escalation is positive and its
value is large enough.
As can be seen from Table 4, for measures number 117, the PV
of net cost saving over 15 years is positive. This is a significant
amount of money which can be considered as revenue from
investing in each specific energy-efficiency measure if all the cost-
effective potential is captured. However, in reality because of the
existence of various barriers, it is not possible to capture all the
cost-effective potential. This is further discussed in the policy
analysis section of this paper. From an economics point of view,
when the PV of a cash-flow in costbenefit analysis is positive,
the investment adds value to the company. If it is negative,the investment subtracts value from the company. If the PV is
zero, the investment neither adds nor subtracts value from the
company. In a very simplified analysis, we can assume that
the energy-efficiency measures with positive PV of net cost saving
over the period of 15 years could eventually be implemented
by cement plants and do not need fiscal incentive from
government, as they already add value to the companies over
the scenario period. However, the energy-efficiency measures
with negative PV of net cost saving over the period of 15 years
(non-cost-effective measures) need the fiscal incentive to be
realized. For the case of fuel-efficiency measures, all the
technologies except technology number 10, upgrading the
preheater from 5 stages to 6 stages, will result to positive PV of
net cost saving over 15 years (Table 6).
4.3. Policy implications for energy-efficiency improvements in Thai
cement industry
The results for different policy scenarios are presented in
Tables 8 and 9. Table 8 shows the total energy saving and
CO2 emission reduction as well as the total PV of net cost saving
over the scenario period (20162030) obtained from the
implementation of energy-efficiency measures in different
scenarios during the implementation period of policy scenarios,
i.e. 20112015. Table 9 shows the annual energy savings and CO2emission reductions resulted for 2008 CSC and the ones obtained
at the end of implementation period (20112015) in various
scenarios. The comparison with the values in 2010 is also
presented. This is to show the magnitude of the energy-
efficiency improvement and CO2 emission reduction resulting
from the implementations in different policy scenarios. The
comparison with 2010 as the base year (the year before the start
of the implementation period) can also be used to assess theeffectiveness of different scenarios. To forecast the primary energy
use in 2010, we assumed a 5% reduction in primary energy
intensity of Thai cement industry in 2010 compared to 2005.
Moreover, because of the current economic slowdown, it is less
likely that cement production will increase in the next few years5;
thus, the cement production in 2010 assumed to be 29 million
tons.
4.3.1. Results of business-as-usual scenario
Table 8 shows that 993 GWh and 64,553 TJ will be saved during
20162030 as the result of implementing electricity and
Table 6
Fuel efficiency measures which are ranked by their cost of conserved fuel (CCF) and their annual net cost saving and PV of net cost saving over the period of 15 years.
No. Efficiency Measure Fuel
saving
(TJ/yr)
CO2 emission
reduction (kton
CO2/yr)
Cost of
Conserved Fuel
(US$/GJ saved)
Annual net cost saving (with
constant 2008 electricity price)
(1000 US$)
PV of the net cost saving over 15
years with fuel price escalation
(1000 US$)
1 Blended cement 5850 909a 0.08b 24,046 78,767
2 Preventative maintenance 222 29 0.08 914 2992
3 Portland limestone cement 933 168a 0.17b 3747 12,189
4 Kiln shell heat loss reduction 5494 545 0.29 21,403 69,9985 Use of waste-derived fuels 1300 129 0.55 4723 15,430
6 Optimize heat recovery/upgrade
clinker cooler
383 34 0.69b 1339 4556
7 Use of steel slag in kiln (CemStar) 412 155a 0.78 1401 4572
8 Energy management and process
control systems in clinker making
process
2241 222 1.53 5945 19,478
9 Modification of clinker cooler (use
of mechanical flow regulator)
378 37 1.76 917 3005
10 Upgrading the preheater from 5
stages to 6 stages
3988 374 7.83b 14,518 36,611
a CO2 emission reduction from reduced energy use as well as reduced calcination in clinker making process.b For this measure, since we have both electricity and fuel savings, we used the primary energy saving to calculate CCF. However, since the share of fuel saving is more
than that of electricity saving, we have put this measure between fuel saving measures. Just for preventative maintenance we present it separately in ECSC and FCSC, as both
the electricity and fuel saving of this measure were in the same range.
Table 7
Cost effective and technical potential for fuel saving and CO2 emission reduction in Thai cement industry for the base year 2008.
Fuel saving potential (TJ/yr) Carbon dioxide emission reduction (ktCO2/yr)
Cost effective Technical Cost effective Technical
Base year: 2008 17,214 21,202 2229 2603
Share from total cement industry in 2005 (%)a 16 19 11 13
a Since the data for energy use in Thai cement industry in 2005 is more reliable than other recent years, we have chosen this year for the comparison.
5
TCMA, January 2009, personal communication.
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Table 8
Energy saving, CO2 emission reduction and the PV of net cost saving over scenario period (20162030) obtained from the implementation of energy efficiency measures
during 20112015 in various scenarios.
Total fiscal
incentive paid
(MUS$)
Cumulative energy
saving over scenario
period
Cumulative CO2 emission
reduction over scenario period
(kton CO2)
Efficiency of the fiscal
incentive paid (US$/MWh
saved)
Total PV of net cost saving
captured over scenario period
(Million US$)
BAU scenario
Electricity
efficiencymeasures
0.00 993GWh 598 5.99
Fuel efficiency
measures
0.00 64,553TJ 8360 52.65
MVA scenario
Electricity
efficiency
measures
25.18 6026 (GWh) 3225 5.21 17.29
Fuel efficiency
measures
0.00 77,463 (TJ) 10,032 63.18
AVAW/O scenario
Electricity
efficiency
measures
0.14 11,929 (GWh) 6353 8.34 101.3
Fuel efficiency
measures
0.00 159,012 (TJ) 19,523 201.6
AVAW scenarioElectricity
efficiency
measures
1.05 11,965 (GWh) 6372 19.85 101.5
Fuel efficiency
measures
0.00 159,012 (TJ) 19,523 201.6
TVA scenario
Electricity
efficiency
measures
0.00 10,683 (GWh) 5624 99.37
Fuel efficiency
measures
0.00 64,553 (TJ) 8360 52.65
Table 9
The annual energy savings and CO2 emission reductions resulted for 20 08 CSC and the ones obtained at the end of implementation period (20112015 ) in various scenarios.
Energy
savings
Share from energy use in Thai cement
industry in 2010 (%)
CO2 emission Reduction
(kton CO2)
Share from total CO2 emission of Thai cement
industry in 2010 (%)
2008 CSC results
Cost-effective electricity saving
potential
265GWh 8 159 0.8
Cost-effective fuel savings
potential
17,214TJ 16 2229 11
Cost-effective primary energy
savings potential
20,270TJ 14 2389 12
BAU scenario
Annual electricity savings 66GWh 2.5 40 0.2
Annual fuel savings 4304TJ 4.9 557 3.1
Annual primary energy savings 5067TJ 4.3 597 3.3
MVA scenarioAnnual electricity savings 402GWh 15.2 215 1.2
Annual fuel savings 5164TJ 5.9 669 3.7
Annual primary energy savings 9800TJ 8.3 884 4.9
AVAW/O scenario
Annual electricity savings 7 95GWh 30 424 2.3
Annual fuel savings 10,601TJ 12.2 1302 7.2
Annual primary energy savings 19,777TJ 16.8 1725 9.6
AVAW scenario
Annual electricity savings 798GWh 30.1 425 2.4
Annual fuel savings 10,601TJ 12.2 1302 7.2
Annual primary energy savings 19,805TJ 16.9 1726 9.6
TVA scenario
Annual electricity savings 712GWh 26.9 375 2.1
Annual fuel savings 4304TJ 4.9 557 3.1
Annual primary energy savings 12,521TJ 10.7 932 5.2
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fuel-efficiency measures in the period 20112015 in BAU scenario.
If we assume the same cement production level at the start and
end of implementation period, Table 9 shows the energy-
efficiency improvement equal to 4.3% as the result of measures
implemented in BAU scenario during 20112015. This is roughly
0.9% per year efficiency improvement during the 5-year imple-
mentation period. It should be noted that at the end of
implementation period, 2015, we get 4.3% annual primary energy
saving compared to 2010. This has happened during 5 yearsperiod. Thus we divide 4.3% by 5 and we get 0.9% energy saving
per year during policy implementation period. However, when we
are in 2015 we have accumulated energy-efficiency improvement
equal to 4.3% annually compared to 2010. The same analysis is
applicable for the results of other policy scenarios presented
below.
4.3.2. Results of moderate VA scenario
Around US$25.18 million is paid as the 30% investment subsidy
in the MVA scenario. The fiscal incentive paid for the fuel-
efficiency measures is equal to zero. The reason is that even a 30%
investment subsidy cannot make the PV of net cost saving over
the scenario period of any non-cost-effective fuel saving positive.
Thus, the subsidy is not applicable to this situation. The efficiencyof funds used for the 30% investment subsidy for electricity saving
measures is equal to 5.21 US$/MWh saved. This is far below the
unit price of electricity for Thai cement industry in 2008 (69.7
US$/MWh). About 8.3% energy-efficiency improvements as the
result of implementation of the short-term MVA program is
obtained compared to 2010.
4.3.3. Results of advanced VA (without CO2 tax) scenario
As can be seen from Table 8, both electricity and fuel saving
achieved in the AVAW/O scenario are significantly higher than the
MVA scenario. This is mostly because of the lower discount rate
we used in this scenario (15%) and the higher adoption rate for
energy-efficiency measures. A small amount of fund (US$ 0.14
million) is used in the 30% investment subsidy program in theAVAW/O scenario for electricity saving measures. The reason is
that all the other non-cost-effective measures under this scenario
will have negative PV of net cost saving over the scenario period
even after taking into account the 30% subsidy; thus, they are not
qualified to use the subsidy. All the fuel-efficiency measures will
be cost effective in AVAW/O scenario because of using 15%
discount rate. Therefore, the investment subsidy is not applicable
to fuel-efficiency measure in this scenario.
Because of the more aggressive actions taken in the AVAW/O
scenario, the energy-efficiency improvement of this portfolio of
policies is higher than that of the BAU and MVA scenarios. The
annual primary energy saving at the end of the implementation
period is 16.8%. The annual CO2 emission reduction is 9.6% at the
end of 2015 compared to 2010 (Table 9).
4.3.4. Results of advanced VA (with CO2 tax) scenario
The total amount of revenue from energy-related CO2 tax
collected in the 5-year period (2011-2015) in this policy scenario
is about US$13.84 million. However, as can be seen in Table 8, just
US$ 1.05 million is used to pay the 50% investment subsidy for
electricity-efficiency measures. The reason is that for the rest of
the non-cost-effective electricity measures, even after a 50%
investment subsidy, their PV of net cost saving over the scenario
period (20162030) will still be negative. Therefore, they are not
qualified to use the subsidy. Nonetheless, since government will
have more than US$12 million left after giving the US$1.05
subsidy, they may want to increase the percentage of subsidy, so
that some other energy-efficiency measures might become
qualified to use the higher subsidy. All of the fuel-efficiency
measures are already cost effective with the 15% discount rate
used; thus, 50% subsidy is not applicable to them. One of the main
advantages of AVAW compared to AVAW/O scenario is that in
the AVAW scenario the Thai government is using the revenue of
CO2 tax in paying even a higher rate investment subsidy without
using its own financial resources, whereas in AVAW/O scenario,
Thai government should pay 30% subsidy from its own budget.
The energy-efficiency improvement and CO2 emission reductionobtained by the AVAW is almost same as the ones obtained by
AVAW/O scenario (Table 9).
4.3.5. Results of technology-oriented VA scenario
As shown in Table 8, the electricity saving over the scenario
period is 10,683 GWh, which is about 10 times higher than that of
the BAU scenario. This is just the result of aggressive action
toward implementation of low temperature waste heat recovery
power generation technology. As we explained in the methodol-
ogy section, for the rest of the technologies we had the same
assumptions as we had for BAU scenario. The data for fuel-
efficiency measures are same as the ones in the BAU scenario, as
there is no change in the discount rate and the adoption rate forthese technologies. The annual primary energy saving achieved at
the end of the implementation period is 10.7%, which is slightly
higher than 2% improvement per year during the implementation
period (Table 9).
5. Conclusion
We conducted an economic and policy analysis based on the
use of bottom-up Energy Conservation Supply Curves constructed
in this study for the Thai cement industry. Using the bottom-up
electricity conservation supply curve model, the cost-effective
electricity-efficiency potential for Thai cement industry in 2008 is
estimated to be about 265 GWh, accounting for 8% of the total
electricity use in the cement industry in 2005. The total technical
electricity saving potential is 1697GWh accounting for 51% of
total electricity use in the cement industry in 2005. The fuel
conservation supply curve model shows the cost-effective fuel-
efficiency potential of 17,214 TJ and total technical fuel-efficiency
potential equal to 21,202TJ accounting for 16% and 19% of total
fuel used in the cement industry in 2005, respectively.
In the economic analysis, we showed how CSCs can be used to
calculate the annual net cost saving with the constant 2008
energy price for each energy-efficiency measure and the present
value (PV) of net cost saving over a period of time taking into
account the energy price escalation rate. The later is especially
useful for policy scenario analysis which is also presented in this
paper. Four cement sector-specific energy policy scenarios withthe framework of voluntary agreements were developed in order
to assess the relative effectiveness of the policy portfolios in
improving energy efficiency in the Thai cement industry.
The results from policy analysis show that the most effective
and efficient policy scenario is the introduction of an energy-
related CO2 tax for the cement industry under a voluntary
agreement program. This results in significant energy saving,
while the fiscal incentive paid can be compensated by the revenue
from the CO2 tax. The TVA scenario also shows that technology-
oriented VA programs for some important technologies can result
in significant energy saving. To maximize the savings in AVAW
program, Thai government can allocate a special subsidy for the
low temperature waste heat recovery for power generation
technology by the revenue earned from energy-related CO2 tax.
A. Hasanbeigi et al. / Energy Policy 38 (2010) 392405404
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Acknowledgment
Authors are grateful to management and engineers in the
cement companies that participated in this study and provided us
the required information and data. We also would like to thank
Ms. Somthida Piyapana, the director of Thai Cement Manufactur-
ing Association for her kind assistance. We are grateful to Prof.
Dr. Surapong Chirarattananon and Dr. Peter du Pont for their
comments on this study. Finally, we would like to thank Ms. LynnPrice from Lawrence Berkeley National Laboratory for her valuable
comments and input on this study.
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