Calculation of the CO 2 Emission Reduction Costs in Markal Model

Transcription

1 Proceedings of he 6 h Inernaional Conference on Nuclear Opion in Counries wih Small and Medium Elecriciy Grids Dubrovnik, Croaia, May 2006 Paper Code. No. S3-38 Calculaion of he CO 2 Emission Reducion Coss in Markal Model ABSTRACT Helena Božić Hrvoje Požar Energy Insiue Savska cesa 163, Zagreb, Croaia hbozic@eihp.hr Possible inroducion of nuclear power plans belongs o he supply side long erm miigaion opions. This opions are modelled in MARKAL by describing he echnical, cos, availabiliy and environmenal daa of he corresponding echnologies. Model MARKAL (an acronym for MARke ALlocaion) is a demand-driven, muli-period linear programming model of he echnical energy sysem ha deals wih supply and demand side opions. I is a cos-minimizing energy-environmen sysem planning model used o invesigae long-erm responses o differen fuure echnological opions, emissions limiaions and policy scenarios of energy sysems. Measures for CO 2 reducion can be analysed wih MARKAL model in wo ways, like convenional approach and forced inroducion of echnologies ha do no appear in he baseline opimal soluion. The laer way is used for calculaion of he CO 2 emission reducion coss in he case of nuclear power plans candidaes in Croaian energy sysem. The differences in marginal coss are shown in he case of nuclear and coal power plans candidaes. This analysis are performed in he scope of complee energy sysem (no only power secor), from supply side o echnologies for energy ransformaion, and o demand side (secors for energy consumpion). This marginal coss are calculaed as he raio beween he differences in discouned oal sysem coss and emissions beween he baseline and nuclear (coal) scenario. The resuls show which opion is beer from he opimaliy side of emission reducion, associaed coss and possible final energy consumpion changes in energy sysem. 1 INTRODUCTION Model MARKAL (acronym for MARKe ALlocaion) is a dynamic, process oriened opimizaion model; sofware ha enable a user o represen a complex energy sysem - naional, regional, local or secorial, as linear program. MARKAL uses an inegraed sysem wide approach p modelling he energy sysem. MARKAL is a long erm muli-period energy echnology opimisaion model, ha represens all energy demand and supply aciviies and echnologies for a counry. The dynamic behaviour of he energy sysem is obained hrough maximising he consumer and producer surplus. Supply and demand clear he marke hrough price flucuaions, aking ino accoun any limi on emissions, resources or echnological opions [1]. In MARKAL he demand for energy services is linked o resources hrough a chain of processes, conversion and demand echnologies. Processes are conneced by energy carriers and maerials flows. The complee represenaion of all possible chains form primary energy supply o S3-38-1

2 demand for energy services is called he reference energy sysem (RES). The Figure 1. represens a simplified reference energy sysem on which srucure he general descripion of he daabase is based. Model opimises he echnology mix for each ime period using daa on he already exising and possible new echnologies. The araciveness of a echnology is deermined by invesmen cos, cos of energy carriers used, efficiency, availabiliy facor, emission facors and various consrains [2]. Figure 1: Example of reference energy sysem 2 GENERAL STRUCTURE OF CROATIAN RES Republic of Croaia RES is modelled as complee energy sysem from supply o demand side, including he par for energy ransformaions; he overall srucure is shown a Figure 2. This sysem consiss of [3]: 31 energy ypes (primary and ransformed) 8 impor energy ypes (elecriciy, oil derivaes, coal, crude oil, gas) 4 domesic producion energy ypes (elecriciy, oil derivaes, crude oil, gas) 10 expor energy ypes (elecriciy, oil derivaes) 3 plans for energy ransformaion (oil refinery, NGL plan, ciy gas plan) 30 power plans in power secor 37 demand caegories, grouped in 8 secors (households, services, indusry, agriculure, ranspor, consrucion, oher, own-use consumpion) 83 echnologies on demand side. S3-38-2

3 Supply Transformaion Demand Renewables Biomass Hydro energy Solar energy Wind energy Domesic produc. Crude oil Naural gas Impor Crude oil Naural gas Coal Oil derivaes Elecriciy Gas and oil pipelines Energy ransform. Oil refinery NGL plan Ciy gas plan Power secor Hydro PP Thermal PP Public&indusrial cogeneraions Public&indusrial hea plans Energy Transpor Disribuion Households Services Indusry Transpor Agriculure Consrucion Oher Expor Oil derivaes Figure 2: General srucure of Croaian RES GHG emissions can be reduced by changes in boh supply and demand (consumers) side of he energy sysem. Possible inroducion of nuclear power plans is he example of long-erm supply side miigaion measure for CO 2 reducion. All opions for emission miigaions are modelled in MARKAL by describing he echnical, cos, availabiliy and environmenal daa of he corresponding echnology. 3 MODELLING OF GHG REDUCTION MEASURES IN MARKAL MODEL GHG reducion can be analysed wih MARKAL in wo ways [2]: 1. Convenional approach (The Inegraed Sysem Approach), when cos daa are changed. MARKAL enables o model he marginal cos of CO 2 reducion as inpu daa in he form of CO 2 ax. In ha case he model finds he opimal soluion for each given CO 2 marginal cos level and we can found ou from he resuls he corresponding reducion of emissions and wha changes will ake place in he energy sysem. 2. Forced inroducion of echnologies (The Parial Soluion Approach) ha do no appear in he opimal soluion or whose marke peneraion is oo small under assumpions made due o heir high cos. In his case cos analysis of each CO 2 reducion opion can be made by comparing he oal sysem cos and emissions daa in he baseline and miigaion scenarios conaining his paricular opion. Marginal coss of specific CO 2 reducion opions ha do no appear or are no accouned in he baseline opimal soluion, can be calculaed wih: MRC where ( CR, CR ) ( R R, ) = (1) MRC - marginal reducion coss in he year S3-38-3

4 R - oal CO 2 emission in he year under baseline scenario R ` - oal CO 2 emission in he year under scenario wih specific opion CR - oal sysem cos in he year under baseline scenario CR ` - oal sysem cos in he year under scenario wih specific opion. Here R ` and CR ` correspond o he leas cos MARKAL soluion where specific reducion opion is added o he baseline assumpions. 4 MODEL OF CROATIAN POWER SYSTEM Croaian power sysem in MARKAL consiss of presen and fuure echnologies (power plans). Presens power plans are hydro plans (run of river, sorage, small), hermal plans and public and indusrial cogeneraion plans. For fuure echnologies (candidaes) differen sources are combined in order o model convenional and renewable plans candidaes. As a resuls of capaciy expansion model (WASP) one scenario is chosen for gas and coal power plans, ogeher wih renewable opions (wind, solar, biomass) from oher scenarios (Energy Sraegy) [3]. In he scenario of nuclear power plan impac on CO 2 emission model assumes sar of operaion of wo LWR power plans a 2010 and 2015 wih he capaciy of 660 MW. Number of coal power plans (C500) candidaes was differen per scenarios, as shown in Table 1. Elecriciy impor and CO 2 emission consrain were no in he scope of hese scenarios. Table 1: Scenarios wih nuclear power plans and coal power plans Sar of operaion for Elecriciy C500 Consrain on impor CO emission Scenario 4 NO NO Scenario 5 NO X NO Scenario 6 NO X X NO Scenario 7 NO X X X NO As a resul of nuclear scenarios, oal energy sysem coss and CO 2 emission is changed depending on scenario, as shown in Figures 3. and 4. Wih he operaion of coal power plans candidaes, CO 2 emission are higher and oal sysem coss are smaller. In he case of nuclear power plans operaion his conclusion is opposie; nuclear plans have impacs on CO 2 emissions decreasing and on oal sysem coss increasing Toal discouned sysem coss mil USD Scenario 4 Scenario 5 Scenario 6 Scenario 7 Figures 3: Toal discouned sysem coss S3-38-4

5 k Discouned CO 2 emissions Scenario 4 Scenario 5 Scenario 6 Scenario 7 Figures 4: Discouned CO 2 emissions Wih nuclear scenario possibiliy for CO 2 emission reducion is much higher han wih differen measures in oher demand secors (households, services ec.), so nuclear scenario is long erm measure for CO 2 emission reducion. Figure 5. shows poenial for (undiscouned) CO 2 emission reducion in nuclear scenarios. Scenario 4 has he highes poenial because here is no coal power plans candidaes and boh nuclear plans candidaes are in operaion. Wih he operaion of coal plans CO 2 emission reducion poenial becomes smaller. CO 2 emission k Scenario Scenario Scenario Sceario Scenario 4 Scenario 5 Scenario 6 Sceario 7 Figure 5: Poenial for CO 2 emission reducion in nuclear scenarios Marginal coss is anoher measure of emission reducion. For his calculaion oal sysem coss and emissions mus be discouned. This coss are calculaed based on forced inroducion of echnologies mehodology, like he difference beween coss and emissions in Reference scenario (wihou plan candidaes) and Scenarios wih plan candidaes. Wih he operaion of coal power plans candidaes, marginal coss of CO 2 emission reducion is higher and have negaive value (for 2020 in Scenario 6 his value is -61 USD/ and for Scenario 7 is -269 USD/). S3-38-5

6 Wih decreasing in number of coal power plans candidaes, marginal cos of CO 2 emission reducion has posiive values (for 2020 and Scenario 4 his is 95 USD/ and for Scenario 5 is 34 USD/). As he mos opimal from he cos side is Scenario 5 (wih one coal plan candidae in 2010), wih he poenial for CO 2 emission reducion in whole period (undiscouned) of k wih marginal cos of 34 USD/. Anoher impac of CO 2 emission reducion is fossil fuels consumpion decreasing in energy sysem for he amoun of 73.5 PJ in each period (5 years) saring from CONCLUSION Calculaion of CO 2 emission reducion poenials inroducing nuclear scenario can be obained wih he model of power secor only or wih he model of he whole energy sysem (in his case). The second opion is beer, because can answer on many quesions relaing o he impac on supply and demand sides of RES: changes in final energy consumpion, changes in fuel mix, impac in demand secors (households, services ec.). Besides his good sides, his model has he implicaion on complexiy and daa consuming. The final conclusion of which approach is beer, one mus ake ino consideraion all menioned aspecs. REFERENCES [1] The Belgium MARKAL daabase, CES-KULeuven-VITO, Apr 2001 [2] T.Kallase, O.Liik, A.Os: Possible Energy Secor Trends in Esonia - Conex of Climae Change, Socholm Environmen Insiue Tallin Cenre, Tallin Technical Universiy, Tallin, Esonia, 1999 [3] H.Božić: Modelling improvemen of he long erm planning for energy sysem developmen, PhD diseraion, Universiy of Zagreb, Faculy of Elecrical Engineering and Compuing, Zagreb, Dec 2005 S3-38-6