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Procedia
Energy Procedia 4 (2011)6007-6014 ;
www.elsevier.com/locate/procedia
GHGT-10
The potential role of CCS to mitigate carbon emissions
in future China
Wenying CHEN*
Energy Environment and Economy (3E) Research Institute, Tsinghua University, Beijing 100084, China
Abstract
Coal is China's primary fuel for power generation and will almost certainly remain so for the foreseeable future. At present China's installed capacity of power generation plant totals about 900 GW with over 70% of that based on coal. Although major Chinese programmes are in place to improve energy efficiency, increase deployment of renewable energy technologies and increase the installed capacity of nuclear plant, coal-fired power plants will continue to be built in large numbers for many years to come. This paper presents the results of an energy systems analysis exercise using the China MARKAL model under the support of NZEC (China-UK Near Zero Emissions Coal) Initiative, to provide a perspective on the energy technologies that may be deployed in China to 2050 to meet its energy needs. The model also examines the cost and impact of deploying CCS in China by simulating several carbon emission constraint scenarios.
©2011 Published by Elsevier Ltd.
Key words: Carbon capture and storage; carbon emission mitigation; China MARKAL model; China
1. Introduction
NZEC (China-UK Near Zero Emissions Coal) Initiative Phase I aims to examine the merits of various options for carbon dioxide capture, transport and geological storage in China. Apart from assessing different capture technology options for the power sectors and geological storage potentials in some selected areas in China, NZEC Phase I also attempts to evaluate CCS's potential role to mitigate carbon for future China with application of an energy system model, China MARKAL, by simulating different carbon constraint scenarios. The model is updated to incorporate different capture technologies, for both power generation and coal liquefaction. The Work Package of capture technology case study in NZEC provides an important basis for the technical and economic parameters of the capture technologies considered in the model.
* Corresponding author. Tel.: + 86 10 62772756; fax: +86 10 62771150 E-mail address: chenwy@tsinghua.edu.cn
ELSEVIER
doi:10.1016/j.egypro.2011.02.604
2. Modeling methodology
The MARKAL (Market allocation) model is a dynamic linear programming energy system optimization model which has been adopted to study China's future energy development strategy. MARKAL is based on a Reference Energy System (RES). It incorporates the full range of energy processes e.g. exploitation, conversion, transmission, distribution and end-use, and it is able to consider existing technologies as well as advanced technologies which may be deployed in future. The objective function of the model is to minimize energy system cost, including the capital costs of end-use (demand) technologies, capital costs of electricity generating technologies, fuel costs, infrastructure costs (such as pipelines), and operating and maintenance costs.
The China MARKAL model is developed in 5-year intervals extending from 2000 through 2050 (Chen, 2004 [1]; Chen, 2005 [2]; Chen, 2007a [3]; Chen, 2007b [4]). It considers not only conventional fossil fuels such as coal, oil, natural gas, coal gas etc., but also new and renewable energy like hydro, nuclear, wind, solar, geothermal, and some synthetic fuels like methanol, DME etc. Current thermal power generation technologies, advanced thermal power generation technologies like IGCC, NGCC etc., new and renewable power generation technologies are included in China MARKAL. The process technologies include coal washing, coke making and oil refinery, as well as more advanced technologies such as coal gasification and coal liquefaction.
Five sectors, namely agriculture, industry, commercial, residential (divided into urban and rural) and transportation are considered in China MARKAL, which are further divided into several sub-sectors, as detailed in Figure 1. For example, agriculture is divided into irrigation, farming, and agro-process; industry is divided into five energy intensive sub-sectors (iron and steel, cement production, ammonia, paper making, aluminium), non energy use, and other sectors; transportation sector is divided into freight and passenger transport, and they are further divided into railway, highway, waterway and air transport; urban and rural residential is divided into space heating, cooking and water heating, air conditioning, lighting and other electric appliances; commercial sector is divided into space heating and water heating, cooling, lighting and other electric appliances.
End use demand sectors
Commercial
Figure 1 End-use demand sectors defined in the model
Energy systems analysis modelling by application of the China MARKAL energy model is used to determine the least-cost mix of technologies and fuels to meet the predicted energy service demands. This leads to the energy
demands and energy mix, both in the demand and supply sides. Final energy demand and its mix, primary energy demand and its mix, power generation capacity and output and their mix, as well as carbon emissions from 2005 to 2050 will be analyzed.
Carbon constraints will then be added to the model and it will be asked to meet the same energy service demands while constrained to limit CO2 emissions to a specified maximum level. Based on the specification of the NZEC project, the focus would be on running scenarios that might exclude CCS, those that might include CCS to differing extents and variations to the take-up of competing technologies. This analysis will provide an indication of the differences in marginal carbon cost. The model will also be used to assess the role of CCS in cutting carbon emissions.
3. Main assumptions for the modeling
3.1 Assumptions on future social economic growth and energy service demand projection results
The main assumptions on future social and economic growth used to update the energy service demand in China MARKAL are shown in Table 1. Chinese GDP is expected increase from 22366 billion US dollars in 2000 to 310942 billion US dollars in 2050, with an average annual growth rate of 6.28%. With continued economic development, it is expected that China's industrial structure will adjust following the trend seen in most developed countries. Thus, it is expected that the proportion of primary and secondary industry will drop to 1.7% and 36.1% respectively, while the proportion of the service industry will rise to 62.2 % by 2050. From 1978 to 2006, China's urbanization rate increased from 17.9% to 43.9%, with an average annual growth rate of 3.25%. With the rapid development of the economy and the constant adjustment of industrial structure, China's urbanization will continue to develop rapidly and it is expected to reach 72% by 2050, which is equivalent to the current level of moderately developed countries. Using the above mentioned assumptions, energy service demand for each sectors and sub-sectors are projected and detailed in literatures (Chen, 2009a [5]; Chen, 2009b [6])
Table 1 Assumptions on future social and economic growth
2005 2010 2020 2030 2040 2050
GDP/Billion 2005US$ 22366 36713 79260 141943 220433 310942
Population/ Million 130.8 137 145.4 148.3 148.3 144
Urbanization rate/% 42.3 45.7 53.7 60.8 66.8 72.2
Industrial structure
Primary/% 12.50 8.73 4.96 3.18 2.25 1.71
Secondary/% 47.50 46.08 43.73 40.89 38.32 36.12
Tertiary/% 40.00 45.19 51.30 55.93 59.43 62.17
3.2 Assumptions on main power generation technologies
Table 2 provides assumptions on the investment cost and efficiency for the main power generation technologies considered in the mode1 (Chen, 2009c [7]). NZEC Work Package 3 have carried out case studies on capture for supercritical/ultra supercritical (SC/USC), and the results show that the investment cost of power generation with capture is around 7000-9000 RMB/kW (1000 US$/kW-1300 US$/kW) before taking into account loan interest and tax, etc. Thus for SC/USC with capture technologies, we assume investment cost of 1400 US$/kW for the year 2010, 1200 US$/kW for 2020 and 1100 US$/kW for the year 2030 onwards. We also include IGCC with CCS in the model based on the author's own assumptions about cost. IGCC with capture is assumed to be 30% more expensive than IGCC without capture. In the model, the investment cost for IGCC with capture is assumed to reduce from 1856 US$/kW in 2010 to 1400 US$/kW in 2020 and 1300 US$/kW for the year 2030 onwards. We assume SC/USC's efficiency as 42% and SC/USC with capture as 32% with 10% energy penalty. This can be considered a conservative estimate as efficiencies of newly built USC plants may now reach 45%. For IGCC, efficiency is assumed as 45% and IGCC with capture is assumed as 37% with an energy penalty of 8%.
Table 2 Assumptions on investment cost for the main power generation technologies (US$/kW)
2005 2010 2020 2030 2040 2050
SC/USC 600 600 600 600 600 600
SC/USC with capture 1400 1200 1100 1100 1100
IGCC 1428 1428 1100 1000 1000 1000
IGCC with capture 1856 1430 1300 1300 1300
NGCC 550 550 550 550 550 550
Nuclear 1500 1500 1500 1500 1500 1500
Hydro 1200 1200 1200 1200 1200 1200
Onshore Wind 900 900 900 900 900 900
Offshore Wind 1500 1500 1500 1500 1500 1500
PV 2000 2000 2000 2000 2000 2000
Geothermal 1800 1700 1600 1500 1500 1500
4. Modeling results
4.1 Primary energy consumption and power capacity
A reference scenario with consideration of existing and planned policies to mitigate carbon emissions is firstly generated with application of the China MARKAL model. By 2050, primary energy consumption is expected to increase to 6883 Mtce with coal sharing around 40% in the total, as detailed in Figure 2. The corresponding carbon emissions are expected to increase to 34.4 MtC (126 MtCO2) by 2050.
7000 u 6000
0 5000 t
1 4000
ÈÏ 3000
" 2000 b
•p 1000 pH
□ Other
□ Hydro
□ Nuclear " □ Gas
□ Oil "□Coal
Figure 2 Primary energy consumption and its mix in the reference scenario
Cumulative carbon emissions during 2005 to 2050 in the reference scenario are 125 GtC. Four carbon constrain scenarios are designed, namely C110, C100, C90 and C80, in which cumulative carbon emissions during 2005 to 2050 is constrained to 110 GtC, 100 GtC, 90 GtC and 80 GtC respectively.
Figure 3 illustrates primary energy consumption and its mix under different carbon constraint scenarios in 2050. For the year 2020, coal share is expected to decrease from 57% in the reference scenario to 53%, 44%, 42% and 22% for C110, C100, C90 and C80 respectively, while nuclear is expected to increase from 2.7% to 6.7%, 16%, 19% and 26%. Since almost all hydro has been developed in the reference scenario, the role of hydro power in different carbon constraint scenarios are almost the same as that in the reference scenario. The share of other renewable energy is expected to keep around 2-3% for all scenarios. For the year 2030, coal share is expected to decrease from 57% in the reference scenario to 49%, 43%, 31% and 14% for C110, C100, C90 and C80 respectively,
while nuclear is expected to increase from 5.5% to 10%, 21%, 27% and 29%. Share of other renewable energy is expected to keep around 3%-4% for all scenarios except C80 (7%). For the year 2050, coal share is expected to decrease from 48% in the reference scenario to 23%, 19%, 11% and 22% for C110, C100, C90 and C80 respectively, while nuclear is expected to increase from 8.5% to 29%, 31%, 38% and 35%. Share of other renewable energy is expected to increase to 8%-16% for the carbon constraint scenarios. Nuclear and renewable energy such as wind, solar, geothermal and biomass will play a more important role in the more stringent carbon constraint scenarios. For example, nuclear would account for 45% in the total primary energy consumption by 2050 in C80. Reducing emissions sufficiently to achieve the C80 scenario indicates a substantial use would be made of CCS. The cost of SC/USC with capture is lower than nuclear, but investment cost and energy penalty for CCS are another important aspect to determine coal use. CCS technologies are expected to contribute to significant carbon emissions reductions for C80 by 2050. Application of CCS technologies would increase both the coal share and the total primary energy consumption. Thus the coal share increases between the C90 and C80 scenarios.
9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0
□ Other : Hydro
] Nuclear ] Gas
□ Oil
□ Coal
Figure 3 Comparisons of primary energy consumption and its mix for different scenarios
Figure 4 compares power capacity by mix for different scenarios. Total capacity for C80 is higher than the reference scenario, i.e., 4%, 7% and 39% higher for the year 2020, 2030 and 2050 respectively, while electricity output for C80 is 1%, 5% and 37% higher than the reference. There are two main reasons for this. The first is that the stringent carbon reduction target requires a significant change in the final energy consumption mix to increase the share of electricity while reducing the share of coal. For C80, electricity consumption is expected to increase 0.5%, 3.2% and 30% respectively for the year 2020, 2030 and 2050. The second is that 466 GW of coal-fired power plant with CCS will need to be developed by 2050 in C80 in order to achieve the reduction target while CCS deployment (both in power sector and coal liquefaction) would increase the energy demand for power generation.
Hydro power is a relatively cheap technology to achieve carbon emission reductions. In all scenarios, hydro power is expected to be around 300 GW in 2020, 343GW in 2030 and 378 GW in 2050. That means almost all hydro resource would be developed firstly to meet future energy demand and carbon constraints. Wind power is expected to be 250 GW and 265 GW by 2050 for C90 and C80 respectively. All onshore wind power resource (250 GW) is expected to be utilized in C90 and C80. By 2050, the use of other renewable energy including solar, geothermal and biomass is expected to increase from 130 GW in the reference scenario, to 170 GW, 180 GW, 265 GW and 390 GW for C110, C100, C90 and C80 respectively. Nuclear power is expected to play a very important role for carbon emissions reduction in the future. By 2050, nuclear power would increase from 200 GW in the reference scenario to 710 GW and 765 GW for C110 and C100 respectively. The model sets a limit of 1000 GW of nuclear by 2050. For both C90 and C80, nuclear power would need to expand to 1000 GW by 2050. 1000 GW would represent a very large step-change in the build rate for nuclear power stations. Coal-fired power plant with CCS would be less than 15 GW during 2020 to 2050 for all carbon constraint scenarios except C80 where it would increase to 466 GW in 2050 for C80. In C80 almost all NG is used in the end use sectors instead in power, while less coal is used in the end use sectors and more coal used in power sector. By 2050, coal-fired power plants with
CCS, nuclear power and renewable energy would account for 15%, 32% and 33% respectively in the total power capacity.
3,200 2,800 2,400 2,000 1,600 1,200 800 400 0
■ u u ■
C100 2050
□ Biomass
□ Geothermal
□ Solar
□ Wind
□ Hydro
□ Nuclear
□ CCS
□ NG
□ oil
□ coal
Figure 4 Comparisons of power capacity and its mix for different scenarios 4.2 coal liquefaction
The model assumes that future oil price would go up steadily to 100 US$/bbl by 2050. With consideration of coal liquefaction technologies in the model, the modelling shows that liquid fuel from coal is expected to reach 390 Mtce by 2050, contributing one third of the conventional oil supply from both domestic mining and imports. Figure 5 shows liquid fuel produced from coal liquefaction with CCS would increase to 55 Mtce by 2050 in C80. Coal liquefaction in the reference is much higher than in the carbon constraint scenarios. For all scenarios, carbon constraints are set for total emissions instead of for the power sector only. The increased emissions of the liquefaction plants has an effect on the emissions allowed, thus coal liquefaction drops significantly from the reference scenarios and all coal liquefaction is with CCS in the constraint scenarios. But compared with CCS in the power sector, coal liquefaction with CCS in C80 (56 Mtce in 2050) only accounts for a small proportion of the total storage capacity.
„ 60
§ 20 10
_ _ — r_(- 1
□ 2020
□ 2030
□ 2050
Figure 5 Liquid fuel produced from coal liquefaction with CCS 4.3 Carbon Sequestration
China's proved recoverable reserves for oil are around 2200 million tonnes. If oil and CO2 contact percentage is assumed as 75%, the extraction rate for CO2 enhanced oil recovery (EOR) as 5.3%, and 2.5 tonnes CO2 needed to produce 1 tonne oil, then total CO2 EOR storage capacity potential could be estimated as 2 GtCO2 and CO2 EOR potential as 800 Mt. For oil fields with different API value, extraction rate for CO2 EOR is in the range 5.3% to 18.3%. Considering not all oil fields are suitable for EOR and some small oil fields are suitable but their storage capacity might not be able to host at least 10 years worth of emissions, we use 2 GtCO2 EOR storage capacity potential and 800 Mt CO2 enhanced oil recovery potential in the model.
CO2 EOR provides additional revenue from enhanced oil production. Therefore, for all carbon constraint scenarios, all the available CO2 EOR potential is assumed to be used to store the CO2 captured from both the power sector and coal liquefaction. This equates to 2 GtCO2, as shown in Figure 6. For C80, an additional 26 GtCO2 will need to be sequestrated in aquifers since EOR is not able to provide enough capacity for the total CO2 captured.
I Aquifer•
Figure 6 Total CO2 sequestrated during 2005 to 2050 in different scenarios
4.4 Marginal abatement cost
Marginal abatement cost is another reflection of the solution of the model when a carbon emissions constraint is introduced. It is not the average abatement cost, instead it is the cost when one more tonne of carbon is needed to be further reduced. Figure 7 displays marginal abatement cost for different scenarios. With 50US$/C (14US$/tCO2), it is possible to constrain carbon emissions by 2050 at twice the 2005 emissions level (C110). To cut the carbon emissions by 2050 at 1.7 and 1.4 times the 2005 level, marginal abatement cost would go up to 160US$/tC (44 US$/tCO2) and 630 US$/tC (172 US$/tCO2) respectively. For C80, reduction requirement for 2050 is higher, so the marginal abatement cost would rise to 1700US$/tC (463 US$/tCO2). A high value of the marginal abatement cost such as 463 US$/tCO2 means that the reduction target would be very difficult to achieve.
C80 C90 C100 C110
0 — -----
2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Year
Figure 7 Marginal carbon mitigation cost in different scenarios
5. Concluding remarks
As a developing country with a coal dominated energy mix, China faces severe challenges when coping with climate change. With the accelerated urbanization and industrialization that comes with economic development and living standard improvement, China's carbon emissions are expected to continue to grow to 12.6 GtCO2 by 2050. But owing to China's continued effort on energy efficiency improvement and development of new and renewable energy, the annual growth rate of carbon emissions is expected to drop significantly from 5.7% during 2000-2005 to 2% during 2005-2050.
The modelling in this study considers a lot of advanced technologies both in the energy supply and demand sides. The availability of these technologies significantly reduces carbon emissions in the reference scenario, as well as the abatement costs. Policies and programs that encourage the development, demonstration and commercialization of advance energy technologies are needed.
Due to China's coal-dominated energy resource characteristic and limited renewable energy resource, carbon emission reductions will rely heavily on the development of nuclear power, in particular if more stringent reductions are required. For example, 1000 GW of nuclear would be needed for C80 and C90 scenarios. Such large scale of nuclear power development will be challenged by constraint factors like site selection, public acceptance, investment, safety and waste disposal. CCS technologies would provide another solution for future carbon emissions abatement, in particular, for the more stringent reduction targets. More than 400 GW coal-fired power plants with CCS by 2050 would be required to achieve the C80 reduction. More stringent carbon reduction targets would rely on more CCS technologies.
In the near term enhanced oil recovery with CCS is a cost-effective option and in total 2 GtCO2 could be sequestrated to produce 800 Mt of oil in the whole time horizon for all carbon constraint scenarios. For C80, an additional 26 GtCO2 in the whole time horizon would need to be sequestrated in aquifers.
Modelling results of marginal abatement cost show that with 50 US$/tC it is possible to control carbon emissions by 2050 at twice the 2005 emissions level. To cut the carbon emissions by 2050 to only 1.7 times of 2005 level, the marginal abatement cost would go up to 160 US$/tC. The marginal abatement cost would rise significantly if carbon emissions needed to be further cut.
The investment cost for nuclear power, offshore wind power, PV, SC/USC with capture and IGCC with capture are assumed as 1500 US$/KW, 1500 US$/KW, 2000 US$/KW, 1100 US$/KW and 1300 US$/KW by 2050 respectively. The energy penalty for capture is assumed as 10% for SC/USC and 8% for IGCC respectively. Further reduction in the investment cost for these key carbon abatement technologies and reduction in the energy penalty for CCS is crucial to reducing the marginal abatement cost. Cooperation between developed and developing countries as well as financial and technology transfer from developed to developing countries should be encouraged to further research, develop and demonstrate these advanced technologies including CCS.
In the near term, as announced by Chinese government, the priority for China's energy development is still energy conservation and development of new and renewable energy. But CCS offers an important strategy option for future carbon mitigation if CO2 concentration in the atmosphere has to been stabilized at 550 ppmveq or even lower. Two significant obstacles for CCS development exist, one is its relatively high investment cost, another is the energy penalty, which would put higher pressure on coal supply. It is very important to demonstrate CCS through international cooperation to overcome these obstacles.
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