industry cement

8/3/2019 Industry Cement

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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
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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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ARTICLE IN PRESS

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 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 fuel savings 10,601TJ 12.2 1302 7.2


TVA scenario






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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.



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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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