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Energy Procedia Energy Procedia 100 (2008) 000–000 Energy Procedia (2009) 3755–3762

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Greenhouse gas mitigation in a carbon constrained world – the role of CCS in Germany Katja Schumacher a, Ronald Sandsb,* a

b

Institute for Applied Ecology (Öko -Institut e.V.), Novalisstrasse 10, 10115 Berlin, Germany Joint Global Change Research Institute, Pacific Northwest National Laboratory, 8400 Baltimore Avenue, Suite 201, College Park, Maryland 20740, USA Elsevier use only: Received date here; revised date here; accepted date here

Abstract In a carbon constrained world, at least four classes of greenhouse gas mitigation options are ava ilable: energy efficiency, switching to low or carbon-free energy sources, introduction of carbon dioxide capture and storage along with electric generating technologies, and reductions in emissions of non -CO 2 greenhouse gases. The contribution of each option to overall greenhouse gas mitigation varies by cost, scale, and timing. In particular, carbon dioxide capture and storage (CCS) promises to allow for low-emissions fossil -fuel based power generation. This is pa rticularly relevant for Germany, where electricity generation is largely coal -based and, at the same time, ambitious climate targets are in place. Our objective is to provide a balanced analysis of the various classes of greenhouse gas mitigation options with a particular focus on CCS for Germany. We simulate the potential role of advanced fossil fuel based electricity generating technologies with CCS (IGCC, NGCC) as well the potential for retrofit with CCS for existing and currently built fossil plants from the present through 2050. We employ a computable general equilibrium (CGE) economic model as a core model and integrating tool.

2009 Elsevier under CC BY-NC-ND license. ©c 2008 ElsevierLtd. LtdOpen . Allaccess rights reserved Keywords: energy efficiency; fuel switching; ca rbon dioxide capture and storage; general equilibrium modeling; climate policy

* Corresponding author. Tel.: +1 -301-314-6765; fax: +1 -301-314-6719. E-mail address : [email protected]

doi:10.1016/j.egypro.2009.02.175

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1. Introduction Germany’s electricity generating system provides substantial opportunities for net reductions in carbon dioxide (CO 2 ) emissions, especially with a price on e mission s of CO 2. First, there can be shifts between technologies over time. For example, a natural gas generation technology can replace generation with coal. Second, carbon dioxide capture and storage (CCS) can be added to new coal and gas generating plants. Third, CCS can be applied to existing plants if the CO 2 price is high enough. This allows earlier adoption of CCS than waiting for all old generating plants to retire. We use three types of analytical tools to describe the potential for CCS in Germany. First, we constructed a computable general equilibrium energy -economy model that simulates economic activity and CO 2 emissions in Germany from 1995 through 2050 in five-year time steps. The electricity sector in this general equilibrium model is nested to represent many electricity generating technologies, including CCS. Second, we construct plots of levelized cost for each electricity-generating technology as a function of a CO 2 price. These plots show graphically the break -even CO 2 price where an owner is indifferent between deploying CCS or not. These plots also cover the possibility of CCS as a retrofit, where the CCS plant has a shorter lifetime than the generation plant. Third, we describe model output using a formal decomposition methodology to p artition a change in CO 2 emissions over time into several explanatory components. This decomposition clearly shows the role of CCS relative to other components that influence emissions. The explanatory components of a change in CO 2 emissions include: econ omic activity, changes in relative output of economic sectors (shifts away from energy -intensive industries), fuel shifting, improvements in energy efficiency, and CO 2 capture and storage used in electricity generation. These components are plotted over t ime in a scenario that gradually increases a CO 2 price to a maximum of 50 euros per metric ton of CO 2 (t -CO 2) in 2025 and then holds the CO 2 price constant until 2050. The economic activity component contributes to increases in CO 2 emissions over time, whi le the other four components contribute to decreases in emissions. Across industries, the electricity generating sector provides the majority of net decreases in CO 2 emissions, especially with CCS. Although we have not yet included a retrofit option in S GM -Germany, the diagrams of levelized cost, as a function of CO 2 price, provide guidance to the extent that CCS retrofits are economically feasible.

2. Methods We use the Second Generation Model (SGM) for Germany to simulate CO 2 emissions from 1995 through 2 050. SGM-Germany is a computable general equilibrium (CGE) model of the German economy and energy system with 18 production sectors, organized to emphasize energy production, transformation, and energy -intensive industries. Background on the SGM model is found in Sands (2004) and Schumacher and Sands (2006). Most of the production sectors in SGM-Germany are represented by constant -elasticity -of-substitution productions. But the electricity sector is an exception, with many electricity generating technol ogies organized in a nested structure as shown in Figure 1.

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electricity f rom fossil fuels and wind

peaking

oil

gas

base load

wind

PC

PCA

PCAccs

IGCC

IGCCccs NGCC

NGCCccs

Figure 1 Nested logit structure of electric generating technologies in SGM -Germany. The set of generating technologies includes pulverized coal (PC), advanced pulverized coal (PCA), coal integrated gasification combined cycle (IGCC), and natural gas combined cycle (NGCC). A suffix of “ccs” means carbon dioxide capture and storage is deployed.

Each nest has an elasticity that governs investment in new vintages of electricity generating techn ologies. Selection of technologies is based on levelized cost in euros per megawatt -hour (MWh). As relative costs change, perhaps due to a CO 2 price, investment is shifted toward technologies with lower relative levelized cost. Elasticities at the bottom of the nesting structure are greater than at the top: the decision to add CCS to a generating technology is very responsive to levelized cost. If the levelized cost of NGCC compared to NGCC+CCS is the same, then each technology provides half of the electricity generated in that nest. Three generating technologies can be constructed with or without carbon dioxide capture and storage (CCS): advanced pulverized coal (PCA), coal integrated gasification combined cycle (IGCC), and natu ral gas combined cycle (NGCC). Technology selection is b ased on levelized cost, in euros per M Wh, and how levelized cost varies with a CO 2 price. Say that electricity generating plants have a lifetime of 40 years and that generating plants are distributed across vintages at time a CO 2 price becomes effective. If CCS is constructed at the same time as a new generating plant, then the capital stock of the CCS plant has the same lifetime of 40 years. The break -even CO 2 price is defined as the point where the plant owner is indiffe rent between using CCS or not. The break-even CO 2 price is shown graphically as the intersection of two levelized cost lines, where levelized cost varies linearly with a CO 2 price. We assume here that all new generating plants have a lifetime of 40 years. However, the CCS plant will have a shorter lifetime, and therefore a greater levelized cost, if constructed as a retrofit to an existing electricity generating plant. We can construct a family of parallel levelized cost lines for each electric generatin g technology with CCS, which increase as the CCS plant lifetime decreases. The break-even CO 2 price for retrofits is also shown graphically as the intersection of two lines. For example, Figure 2a shows levelized cost as a function of the CO 2 price for e lectricity generation using pulverized coal (PC). Without CCS, the levelized cost line is quite steep. With CCS and a 90% CO2 capture rate, a family of levelized cost curves can be drawn for different lifetimes of the CO 2 plant. These lines intersect at the break -even CO 2 price for various lifetimes of the CCS plant. Figure 2b shows the same set of curves for coal integrated gasi fication combined cycle (IGCC) generating plants.


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60

40

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0 ¼0

¼ 20

¼ 40

¼ 60

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CO2 price (euros / t-CO2)

Figure 2a Levelized cost as a function of CO 2 price for pulverized coal (PC) technologies with and without CCS.

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no CCS (IGCC) 100


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CCS-5 CCS-10

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CCS-20 CCS-40

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0 ¼0

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Figure 2b Levelized cost as a function of CO 2 price for coal integrated gasification combined cycle (IGCC) technologies with and without CCS.

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CCS-5 CCS-10 CCS-20 CCS-40

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Figure 2c Levelized cost as a function of CO 2 price for natural gas combined cycle (NGCC) technologies with and without CCS.

We have constructed a hypothetical CO 2 price scenario to illustrate the role of CCS and other explanatory components of a change in CO 2 emissions. The price scenario begins with 10 euros per t-CO2 in 2005, 20 euros in 2010, 30 euros in 2015, 40 euros in 2020, and 50 euros in 2025 through 2050. This represents a gradual increase in the CO 2 price until 2025 and holding constant thereafter. A price of 50 euros per t -CO2 is high enough so that CCS is economical for the case where CCS is constructed along with new generating plants. This price is high enough to cover the cost of CCS retrofit to IGCC technologies, but not necessarily for pulverized coal or NGCC plants.

3. Simulation Results We have simulated CO2 emissions in SGM -Germany through 2050 for the stepwise price scenario just described. The change in emissions relative to the model base year of 1995 can be described in terms of explanatory components using a formal decomposition methodolo gy. We use a logarithmic mean Divisia index method (LMDI) as described by Ang (2005). This decomposition has the feature that the explanatory components sum exactly to the change in CO 2 emissions for each time step. We can write total CO 2 emissions acro ss all industries as:

C = ∑∑ C ij = Q∑ i

j

i

Eij Cij Qi E i ∑ Q Qi j Ei Eij

Total CO 2 emissions for fuel j in industrial sector i are written as the product of five components: total industrial output Q (economic activity); the share of output for industry i relative to total outpu t (output share); the ratio of energy consumption to output in industry i (energy efficiency); the ratio of fuel j to total energy consumption in industry i (fuel mix); and the ratio of CO 2 emissions to energy consumption for fuel j in industry i (emission factors). CO2 emission coefficients are held constant for industries except for electricity generation with CCS.

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Figure 3 provides the LMDI decomposition for a change in CO 2 emissions over time for all industries. Industrial output increases over time, resulting in a large positive economic activity component. This represents the amount that emissions would increase if there were no contribution from the other offsetting components. There are three large offsetting components: product mix (or output sh are), energy efficiency and CCS. The fuel mix provides a smaller negative component. The net change in CO 2 emissions relative to the base year is the sum of all five components. The net change in emissions relative to the base year of 1995 is negative.

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change in emissions since 1995

200 100

economic activity

0 product mix -100

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sum of components

fuel mix emission factors (CCS)

-400 -500

Figure 3 Decomposition of a change in CO 2 emissions over time, for all industries, with a stepwise CO 2 price scenario. CO 2 prices increase over time to a maximum of 50 euros per t -CO2 in year 2025. The LMDI decomposition can be further broken out by industry. This is done for the electricity generation sector in Figure 4, and it is clear that the electricity generation sector alone provides a very large share of the net change in emissions over time. The output share component for electricity generation is quite large: this reflects a decrease in electricity generation, relative to other industries over time. This is primarily due to the increase in electricity prices that goes along with the increase in CO 2 price.

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economic activity

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-200

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Figure 4 Decomposition of a change in CO 2 emissions over time for electricity generation, with a stepwise CO2 price scenario. CO 2 prices increase over time to a maximum of 50 euros per t -CO2 in year 2025. 4. Conclusion We conducted a simulation of the German economy and energy system from 1995 through 2050 with a stepwise increase in CO 2 prices and advanced options for electricity generation, including the option for CCS when constructed with new electricity generating plants. The contribution of CCS to a net decrease in CO 2 emis sions becomes quite large at higher CO 2 prices and as old generating plants retire. We also provide calculations of the CO 2 price needed to make CCS retrofits of existing generating plants economical. In this case, the CCS plant has a shorter lifetime than the generating plant and the capital costs for CCS are levelized over the shorter lifetime. A higher CO2 price is needed to pay the additional cost of retrofits, but remains below 50 euros per t -CO2 for IGCC plants. The higher CO 2 price for retrofits shoul d be considered a lower bound or necessary condition, as these calculations we re done on a plant-by-plant basis, assuming that the load factor remains constant. There may be other system considerations under a climate policy that change the way these plants are dispatched. There is also the consideration of the time it takes to build a CCS plant as a retrofit to an existing electricity generation plant.

5. Acknowledgements This work was funded in part by the US Environmental Protection Agency. The views exp ressed by the authors do not necessarily reflect the views of the Institute for Applied Ecology (Öko -Institut e.V.), the German Government, Pacific Northwest National Laboratory, the US Government, or any agency thereof.

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6. References Ang, B. W. (2005). T he LMDI approach to decomposition analysis: A practical guide. Energy Policy, 33, 867 –871. Sands, R. D. (2004). Dynamics of carbon abatement in the Second Generation Model. Energy Economics, 26(4), 721–738. Schumacher, K., and Sands, R. D. (2006). Innovative energy technologies and climate policy in Germany. Energy Policy, 34(18), 3929 –3941.