29-051

8/12/2019 29-051

1/5

The Online Journal on Power and Energy Engineering (OJPEE) Vol. (1) No. (4)

Reference Number: W09-0051 134

Effect of Carbon Tax on Power Generation and

Energy Security in Sri Lanka

Ram M. Shrestha and Chandrabhanu OpathellaSchool of Environment, Resources and Development, Asian Institute of Technology

P.O. Box 4, Klong Luang, Pathumthani 12120, ThailandEmail: [email protected]; [email protected]; Fax: +66 2 524 5439

Abstract- This paper analyzes the effects of carbon tax

on power generation system and energy security in the

case of Sri Lanka during 2005 to 2050 under the least cost

energy system planning based on the MARKAL

framework. Three different carbon tax cases are

considered in the present study. The paper discusses the

effects of carbon tax on energy mix and technology mix of

whole energy system and power generation system. It alsoanalyzes the effects of carbon tax on CO2 emission and

energy security of the country.

Keywords- power generation in Sri Lanka, effects of

carbon tax, energy security, MARKAL model

I. INTRODUCTION

The power sector is a major contributor to CO2emission inmany countries in the world. The level of CO2emission fromthe power sector is growing rapidly in many developingcountries. Yet, the long term prospects of greenhouse gases

(GHG) emission mitigation in the power sector have not beenassessed rigorously for most developing countries [12].Carbon tax is one of the economic policy instruments toreduce the CO2 emissions from various sectors of aneconomy.

This paper analyzes the effects of carbon tax on powersystem development (in particular, generation mix andtechnology mix in the power sector) as well as implicationsfor energy security and emissions of greenhouse gases fromthe energy system of Sri Lanka during a relatively longplanning horizon of 2005-2050. Implications of the carbontax on power system development as a part of overall effectsin the national energy system.

This paper is organized as follows: A brief overview of theSri Lankan energy system is given in Section 2. An outline ofthe methodology used in the study is presented in Section 3,followed by a description of the base case and carbon taxcases. Section 5 discusses the development of powergeneration system and CO2emissions from the power sectorduring the planning horizon in the base case. This is followedby discussions on effects of the carbon tax on power systemdevelopment in Section 6 and CO2 emission associated withpower generation in Section 7. Section 8 discusses the effectsof carbon tax on national energy security. Finally, a summaryof key findings is presented.

II. OVERVIEW OF SRI LANKAN ENERGY SECTOR

In 2005 the countrys total primary energy supply (TPES)was 9.6 Mtoe. Traditional biomass energy has the largestsharer (48%) in TPES followed by Oil import (43%) andhydropower (9%). Total final energy consumption was 8.0Mtoe in 2005 [1]. The level of electrification in the country

was 76.7% in 2005 [2].Sri Lanka is expected to continue growing rapidly during

the next decade. The economy is expected to grow at the rateof over 8% per annum during 2008-2011, and is expected togrow at a slower rate of 7.4% by 2017[6] and is assumed tocontinue to grow at that rate till 2050.

III. METHODOLOGY

A long term cost minimizing energy system model isdeveloped for Sri Lanka based on the framework ofMARKAL [14] for the purpose of the present study. Themodel reflects the full Reference Energy System (RES) of the

country including energy resource exploitation, conversion,transmission, distribution and end use for all sectors. Themodel considers not only the resources and technologies inuse currently but also the candidate resources andtechnologies that could be used to met the various types ofenergy service demands in future. Five economic sectorsnamely, residential, transport, industrial, commercial andagriculture are considered in the study. The residential sectoris disaggregated into rural and urban subsectors in the model.The future energy service demands are estimated using eitheran econometric method or a simpler approach that assumesthe service demand per unit of sectoral value-added to beconstant over time.

For the analysis of energy security implications of thecarbon tax, the following set of indicators is employed:

1. Net Energy Import Ratio(NEIR):

where,NEIis Net Energy Import,DSis Domestic Supplyof Energy.

2. Shannon-Weiner Index (SWI) [3,4]:

iii

SLnSSWI

NEIDS

NEINEIR
mailto:[email protected]:[email protected]:[email protected]:[email protected]

8/12/2019 29-051

2/5



where, Si is the share of primary energy sources i inprimary energy supply mix.

3. Vulnerability Index (VI) [7]

where, EEI is the expenditure on energy imports, andGDPis the Gross Domestic Product.

IV. DISCRIPTION OF CASES

The base case characterizes the technology options andenergy carriers in the power and other sectors during theplanning horizon without any environmental or climatepolicies. Specific power generation plants and projects ortechnology options that are committed by the relevantagencies for addition to the energy system in future yearsduring the planning horizon also form a part of the base case.

The base case also considers thelearning by doing effect(i.e., defined as the effect of the cumulative global salesvolume of a technology on the unit cost of the technology[14]) and autonomous energy efficiency improvement (AEEI)(i.e., non price induced technological change as it affectsenergy efficiency in long term energy projections [11]). Thelearning rates of new technologies that are estimated in [15,16] are used in this study. The rate of AEEI is assumed to be0.25% and 0.5% annually for demand side technologies andpower generation technologies. These rates are lower thanthat considered by Kainuma et al. [5] and Webster et al. [11].

Energy resource options considered in the study includecoal, petroleum products, Liquefied Natural Gas (LNG), aswell as renewable energy resources like biomass,hydropower, solar and wind. Sri Lanka has a wind powerpotential of 24,000 MW from excellent wind sites (sites withaverage wind speed 7.5-8.8 ms-1) [8]. Even though windenergy is an attractive primary energy resource, it has twomain technical aspects of wind based electricity generationthat needs to be considered: The first is the stability limit ofthe power system and the other is the contribution of windpower to meet the peak power demand of the system. Themaximum permissible share of wind power in total capacity isconsidered to be 30% in this study. Sri Lankas annualsustainable biomass potential is 672.5 PJ [9]. Clean coaltechnology options (such as IGCC and PFBC) are alsoconsidered in the study along with the options of carboncapture and storage (CCS) with coal and LNG generationtechnologies [10, 13]. Advanced demand side technologiessuch as hydrogen fuel cell vehicles, hybrid vehicles [5], andelectric transportation options are also considered in the basecase of the study.

Besides the base case, this study considers the followingthree different cases with carbon tax that correspond to three

different global GHG stabilization targets [17, 18]:

Carbon Tax Case 1: Using carbon tax of 0.7US$/tCO2 in2010 and increase up to 10.1US$/tCO2 by 2050. This is thecarbon tax level required to achieve the 650ppm stabilizationtarget (hereafter, this case is called CT650)Carbon Tax Case 2: Using carbon tax of 1.5US$/tCO2 in2010 and increase up to 20.7US$/tCO2by 2050. This is thecarbon tax level required to achieve the 550ppm stabilizationtarget. (hereafter, this case is called CT550)Carbon Tax Case 3: Using carbon tax of 8.3US$/tCO2 in2010 and increase up to 111.6US$/tCO2by 2050. This is thecarbon tax level required to achieve the 450ppm stabilizationtarget (hereafter the case is called CT450)

The variation of carbon tax used over the years under thethree carbon tax cases are presented in Figure 1.

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

2010 2015 2020 2025 2030 2035 2040 2045 2050

2005MillionUS$/ktC

Year

Case 3

Case 2

Case1

Figure (1): Three alternative carbon tax cases, 2005 MillionUS$/ktCO2

V. ELECTRICITY GENERATION IN BASE CASE

At present, electricity generation is based mainly on oil andhydropower. There is a small wind power plant and a smallbiomass plant in the present power system; however, theircapacities are negligible compared to the total generationcapacity. The total electricity generation was 33 PJ in 2005and was expected to grow at an average rate of 6.3% annuallyduring the period 2005-2030. During 2030-2050, the

generation is estimated to grow by 7.2% annually to reach thelevel of 618 PJ in 2050. Coal, wind and LNG basedgenerations would start as a major source of electricity supplyin 2010, 2020 and 2025 respectively. The generation capacityis estimated to grow at 5.3% during 2005-2040. This is a lowgrowth rate compared to that during 2040-2050, duringwhich, the electricity generation capacity is to grow at a rateof 9.5% annually. Accordingly, the total generation capacityof the system is estimated to grow to 36 GW by 2050.

Figure 2 shows the growth of total emission during theplanning period. The estimated total emission from all sectorsof the country is to grow from 11.8 MtCO2in 2005 to about242.5 MtCO2 in 2050. In terms of sectoral contributions to

total CO2emission, the transport sector accounted for 50% ofthe total emission in 2005. However, the share of the

GDP

EEIVI

8/12/2019 29-051

3/5



transport would decline during the planning horizon andreach to 30% in 2050. The energy conversion sector is thesecond largest contributor to the total CO2emission with itsshare being 30% on an average during 2005-2050. The shareof the industrial sector in CO2emissions would increase from8% in 2005 to 34% in 2050.

0

50000

100000

150000

200000

250000

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

ktCO2

Year

Residential

Transport

Industry

Conversion

Commercial

Agriculture

Figure (2): CO2Emission Profile during 2005-2050

VI. EFFECT OF CARBON TAX ON POWERGENERATION

The total share of renewable energy in cumulativeelectricity generation during the planning horizon is 19% inthe base case. With the carbon tax, the share is estimated toincrease to 21% under CT650 case mainly due to theincreased wind based electricity generation. In the higher taxcases of CT550 and CT450, sustainably produced biomass isalso found to be economically attractive for power generation.As a result, the shares of renewable energy based electricitygenerations are increased further to 23% and 37% underCT550 and CT450 cases.

Carbon tax is also expected to promote the use of moreefficient and cleaner thermal generation technologies ascleaner coal power plants would become relatively moreeconomical than conventional coal power plants. The presentanalysis shows that the share of coal based power plants(including conventional and super critical) in total electricitygeneration would drop from 36% in the base case to 34% inthe CT650 case. With the application of higher tax levels, itwould further decreased to 31% and 4% in CT550 and CT450cases. Besides, the share of the combined cycle power plantswould remain same at 43% in the base case and all threecarbon tax cases. Meanwhile, the share of cleaner coaltechnologies (integrated coal gasification combined cycleplants and pulverized coal plants with CCS) shows anincrease from 0% (both in base case and CT650 case) to 1%and 14% in CT550 and CT650 case.

VII. EFFECT OF CARBON TAX ON CO2EMISSIONS

Due to the reduced usage of coal under carbon tax, totalCO2 emission is expected to be reduced in all the tax cases as

compared with the base case. In the low carbon tax cases ofCT650 and CT550, significant emission reduction would takeplace only after 2015 while under the higher tax case ofCT450, significant reduction would start earlier (i.e., from2010). It is found that the cumulative CO2 emission duringthe planning horizon would be reduced by 2% under CT650as compared to the total base case emission, while thecorresponding figures under CT550, and CT450 cases wouldbe 7%, 41% respectively.

CT650 CT550 CT450

Agriculture 42 (4) (8) (7)

Commercial 338 0 0 0

Power Generation 1,213 47 102 682

Industry 1,342 27 175 1,058

Residential 12 (1) (2) (4)

Transport 1,305 25 25 26

Other 8 0 0 0

Total 4,252 94 292 1,755

Note : The figures in parenthesis denotes an increase in CO2emission from base case

Cumulative Emission Reduction from the base case

emission level under different carbon tax cases, MtCO2

Base case

cumulative CO2

emission, MtCO2

Sectors

Table 2: Sectoral Emission Reduction, MtCO2

Table 2 gives the estimated sectoral emission reductionunder different tax schemes. Power generation and industrysectors are the two largest contributors to CO2 emissionreduction under the carbon tax cases. Under CT450, these twosectors would account for over 99% of total CO2 emission

reduction in the country. Note that the power sector accountsfor the largest share in CO2 reduction at the low tax case(CT650), while the industry sector plays the most significantrole in emission reduction under the higher tax cases ofCT550 and CT450. The cumulative emission reduction fromthe transport sector remains almost unchanged with highercarbon tax. Although the transport sector accounts for 31% ofthe total CO2emission in the base case, its contribution in thetotal CO2 emission reduction decreases from 26.6% underCT650 to 8.5% under CT550 and to 1.5% under CT450.

VIII. EFFECT OF CARBON TAX ON ENERGYSECURITY

The effects of carbon tax on energy security of the countryare analyzed through the use of three indicators as was statedin Section III.

Import dependency

The temporal changes in net energy import ratio (NEIR)under the base and carbon tax cases are shown in Figure 3. Ascan be seen, net energy import dependency would grow overtime under both the base case and CT650; it would alsoincrease over time (except during 2010-2020) under CT550.Under CT450, the dependency would be significantly lowerthan that under the base case and lower carbon tax cases

throughout the planning horizon. Further, the dependency

8/12/2019 29-051

4/5



would remain almost unaffected over time till 2035 underCT450.

0

10

20

30

40

50

60

70

80

90

100

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

NetImportEnergyRatio(%

Year

Base Case

CT650

CT550

CT450

Figure (3): Net Energy Import Dependency under Carbon taxduring 2005-2050

Diversification of Energy Resources

Carbon tax is mostly found to have a positive effect ondiversification in the use of energy resources in the country.Figure 4 shows the Shannon-Wiener Index (SWI) fordiversification of primary energy use in the country under thedifferent cases considered in the present study. It is, however,interesting to note that a higher level of carbon tax does notnecessarily promotes the diversification of energy resources.For example, the SWI index under CT450 case is found to belower than that under the base and lower carbon tax case of

CT650 and CT550 during 2015-2040. The lower level ofdiversification during 2015-2040 under CT450 is a result ofmore uneven distribution in the use of energy resources inthat coal shares would get significantly reduced while that ofother resources would be increased. Near the end of theplanning horizon, the SWI values under the carbon tax casesare found to be higher than that under the base case as coalshares in the carbon tax cases would be decreased and energyresources are more evenly distributed than that under the basecase.

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Shannon-WienerIndex

Year

Base Case

CT650

CT550

CT450

Figure (4). Diversification of Energy Sources under CarbonTax during 2005-2050

Economic Vulnerability of Energy Imports

As shown in Figure 5, the vulnerability index (VI) (definedhere as net energy import as a percentage of GDP) wouldimprove with the application of carbon tax. In the base case,the annual vulnerability index ranges from 3.9% to 10.7%during 2010-2050. The index is not much different underCT650 and CT550 from that in the base case. The indexexhibits significant reduction only at the higher tax case ofCT450. There would be a sudden drop in VI during 2005-2010; it is mainly due to the introduction of coal in powergeneration and hence a reduction in the use (and import) ofoil.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

VulnerabilityIndex(%

Year

Base Case

CT650

CT550

CT450

.Figure (5). Economic Vulnerability Index under Carbon Tax

during 2005-2050

IX. CONCLUSIONS

The study shows that the carbon tax can affect the energyresource-mix and technology-mix significantly. In the case ofSri Lanka, a significant decrease in the use of coal firedpower generation is to take place under the carbon tax, whilethere would be an increase in biomass and wind based powergeneration. In addition, there would also be an increased useof cleaner coal technologies (with CCS) at higher carbontaxes. Significant reductions in net energy import dependencyand economic vulnerability to imported energy costs wouldalso result under the high carbon tax case (CT450), indicating

an increased energy security of the country over time. Thestudy also shows that carbon tax below certain levels wouldnot be so effective in reducing the CO2 emission nor inimproving the energy security.

REFERENCES

[1] ECF, Energy Conservation Fund, Sri Lanka EnergyBalance -2005, Energy Conservation Fund. Colombo.2005.

[2] CEB, Statistical Digest 2005, Statistical Unit,Commercial and Corporate Branch, Ceylon ElectricityBoard, Colombo, 2005.

8/12/2019 29-051

5/5



[3] M. Grubb, L. Butler, P. Twomey, Diversity and securityin UK electricity generation: The influence of low-carbon

objectives. Energy Policy 34 (18), 405062, 2006.[4] J. C. Jansen, W. G. van Arkel, M. G. Boots, Designing

indicators of long-term energy supply security.

http://www.ecn.nl/docs/library/report/2004/c04007.pdf(downloaded on 05/02/2008)

[5] M. Kainuma, Y. Matsuoka, T. Morita, (Eds.), 2003.Climate Policy Assessment: Asia-Pacific Integrated

Modeling. Springer-Verlag, Tokyo[6] Ministry of Finance and Planning,Mahinda Chinthatna:

A Vision for New Sri Lanka.

www.treasury.gov.lk/docs/MahindaChintanaTenYearDevelopmentPlan.pdf (downloaded on 01/02/2008)

[7] T. Nakawiro, S. C. Bhattacharyya,High gas dependencefor power generation in Thailand: The vulnerability

analysis. Energy Policy 35 (6), 33353346, 2007[8] NREL, Wind Energy Resource Atlas of Sri Lanka and

Maldives. National Renewable Energy Laboratory,http://www.nrel.gov/villagepower/wind_resources.html(downloaded on 11/04/2008)

[9] RWEDP, Regional Wood Energy DevelopmentProgramme in Asia. http://www.rwedp.org/c_srl.html(downloaded 03/04/2008)

[10]P.Viebahn, J. Nitsch, M. Fischedick, A. Esken, D.Schuwer, N. Supersberger, U. Zuberbuhler, O.Edenhofer, Comparison of carbon capture and storagewith renewable energy technologies regarding structural,

economic, and ecological aspects in Germany.

International journal o f greenhouse gas control. 1,(1), 121-133, 2007

[11] M. Webster, S. Paltsev, J. Reilly, Autonomous Energyefficiency improvement or income elasticity of demand:

does it matter?, Energy Economics, 2785-2798, 2008.[12]K.Siriwardena, P. D. C. Wijayatunga, W. J. L. S.

Fernando, R. M. Shrestha, & A. R. Attalage, Economywide emission impacts of carbon and energy tax in

electricity supply industry: A case study on Sri Lanka,Energy Conversion and Management, 48 (7), 19751982,2007.

[13]IAEA, Reference Technology Data Base RTDB,http://www.iaea.or.at/OurWork/ST/NE/Pess/RTDB/RTDB%20HOME.htm

[14] IEA, International Energy Agency, ETSAP, EnergyTechnology System Analysis Program,http://www.etsap.org/markal/main.htm

[15] US Department of Energy, Energy efficiency andRenewable Energy, Projected Benefits of Federal Energy

Efficiency and Renewable Energy Programs (FY 2007-

FY 2050)

http://wwwok 1.eere.energy.gov/ba/pba/pdfs/39684_app_D.pdf (downloaded on 10/08/2009)

[16] Global wind energy council, Global wind energy outlook2008. (download on 10/08/2009)

[17] J. Edmonds, L. Clarke, M. Wise, H. Pitcher, S. Smith,Implications for the USA of stabilization of radiative

forcing at 3.4 W/m2, Climate Policy, 8, 76-92, 2008.

[18] Personal communication with J. Edmonds.
http://www.ecn.nl/docs/library/report/2004/c04007.pdfhttp://www.treasury.gov.lk/docs/MahindaChintanaTenYearDevhttp://www.nrel.gov/villagepower/wind_resources.htmlhttp://www.rwedp.org/c_srl.htmlhttp://www.iaea.or.at/OurWork/ST/NE/Pess/RTDB/RTDhttp://www.etsap.org/markal/main.htmhttp://wwwok/http://wwwok/http://www.etsap.org/markal/main.htmhttp://www.iaea.or.at/OurWork/ST/NE/Pess/RTDB/RTDhttp://www.rwedp.org/c_srl.htmlhttp://www.nrel.gov/villagepower/wind_resources.htmlhttp://www.treasury.gov.lk/docs/MahindaChintanaTenYearDevhttp://www.ecn.nl/docs/library/report/2004/c04007.pdf

29-051

Documents

Transcript of 29-051