Economic Analysis of Carbon Capture in the Energy Sector

Abstract

The cost of carbon capture is a crucial factor for the deployment of the technologies in the electricity sector. In general, much higher electricity generation costs arise in case of carbon capture. With an increase of approximately 80 %, lignite-based CCS plants are particularly affected. The CO₂ avoidance costs are € 34–38/tCO₂ for lignite plants, € 41–48/tCO₂ for hard coal plants, and with approx. € 67/tCO₂ highest for natural gas plants. This depends on the lower level of CO₂ avoided in case of gas-fired power plants. Only when the price of allowances rises to these levels will the use of CCS power plants be cost-effective.

However, capture plants must be refinanced through the electricity market, as long as other market design options, e.g. capacity market or feed-in-tariffs, don’t render possible returns. In general, the question arises as to the degree to which higher revenues due to merit order effects can cover the additional investment costs for capture plants and the subsequent transport and storage of CO₂. With further increase of renewable energy, there is a danger that the power plant capacities of an existing fleet will be potentially underused. As a result, there would be a short-term cost recovery problem for fossil power plants. Regardless of the possible development of capacity markets, the comparatively high refinancing needs compared to conventional power plants will remain if capacity revenues are to be incorporated.

Appendix

1.1 LCOE

LCOE according to Global CCS Institute (2009), supplemented with a cost term for CO₂ allowances (IEA NEA OECD 2010):

$$ \begin{array}{l} LCOE\;\left[{\textsf{C}{-1.7ex}{=}} / MWh\right] = \frac{CRF\cdot I+{F}_{FOM}\cdot {C}_{FOM}}{CF\cdot {E}_{Annual}}+{F}_{VOM} \cdot {C}_{VOM}+{F}_{Fuel}\cdot {C}_{Fuel}\\ {}\kern8em +\kern0.5em {F}_{Carb}\cdot {C}_{Carb\;}\\ {} CRF=\frac{i}{1-{\left(1+i\right)}^{-n}}\kern0.72em \left(\mathrm{Capital}\ \mathrm{Recovery}\;\mathrm{Factor}\right)\\ {}{F}_j=\frac{K_j\;\left(1-{K}_j^n\right)}{A\;\left(1-{K}_j\right)}\kern0.24em \left(\mathrm{Levelisation}\;\mathrm{Factor}\right); \\ {}A=\frac{{\left(1+i\right)}^n-1}{i\;{\left(1+i\right)}^n}\kern0.24em \left(\mathrm{Present}\;\mathrm{Value}\kern0.37em \mathrm{Factor}\right);\kern0.48em {K}_j=\frac{1+{R}_j}{1+i}\kern0.36em \left(\mathrm{Escalation}\;\mathrm{Factor}\right)\\ {}\mathrm{with}\;i=\mathrm{interest}\;\mathrm{rate}\\ {}\mathrm{and}\\ {}{F}_{FOM}=\mathrm{Levelisation}\;\mathrm{Factor}\;\mathrm{fix}\;\mathrm{O}+\mathrm{M}\\ {}{F}_{VOM}=\mathrm{Levelisation}\;\mathrm{Factor}\;\mathrm{variable}\;\mathrm{O}+\mathrm{M}\\ {}{F}_{Fuel}=\mathrm{Levelisation}\;\mathrm{Factor}\;\mathrm{Fuel}\\ {}{F}_{Carb}=\mathrm{Levelisation}\;\mathrm{Factor}\;{\mathrm{CO}}_2\\ {}{R}_j=\mathrm{Escalation}\kern0.2em \mathrm{rate}\kern0.2em \mathrm{for}\kern0.2em \mathrm{cost}\ j\kern0.2em \left(\mathrm{excluding}\kern0.2em \mathrm{inflation}\right)\end{array} $$

1.2 CAC

$$ CAC\;\left[{\textsf{C}{-1.7ex}{=}} /t\;C{O}_2\right]=\frac{EG{C}_{CCS}-EG{C}_{REF}}{C{O}_{2,\;REF}-C{O}_{2,\;CCS}}+{C}_{Carb} $$

Where

• EGC _CCS : energy generation costs of a plant with carbon capture,

• EGC _REF : energy generation costs of the plant without carbon capture,

• CO _2,REF : specific CO₂ emissions without carbon capture,

• CO _2,CCS : specific CO₂ emissions with carbon capture

1.3 Learning Curves

$$ \begin{array}{l}\mathrm{Learning}\;\mathrm{Curve}\\ {}K={K}_0\cdot {X}^{-E}\kern0.36em \mathrm{with}\;E:\kern0.24em \mathrm{Learning}\;\mathrm{index};\kern0.24em X:\kern0.24em \mathrm{cumulative}\kern0.24em \mathrm{capacity}\\ {}\mathrm{Progress}\ \mathrm{Rate}\ \\ {}PR={2}^{-E}\;\mathrm{Cost}\ \mathrm{development}\ \mathrm{with}\ \mathrm{doubling}\ \mathrm{capacity}\\ {}\mathrm{Learning}\ \mathrm{Rate}\\ {}LR=1-PR\\ {}\Rightarrow E=-\frac{ \ln\;\left(1-LR\right)}{ \ln\;2}\end{array} $$

1.4 Methodological Approach for Merit Order Analyses

The methodological approach is based on the assumption of full competition on the electricity market. The price of electricity is regulated there depending on supply and demand. The price of electricity is determined by the marginal costs of the most expensive power plant needed to cover demand. The target function of the optimization formulation is thus:

$$ \min \kern0.2em {Z}_t={\displaystyle \sum_n}{\displaystyle \sum_i}{c}_i\cdot {s}_{i,n,t}\cdot {X}_{i,n}+{\displaystyle \sum_n}{\displaystyle \sum_m}{c}_lim{p}_{n,m,t} $$

where

• t: time index []

• n, m: country index

• i: index for power plant type

• c _i : electricity generation costs of power plant type i [€/MWh]

• s _i,n,t : utilization of power plant type i in country n at time t, where 0 ≤ s _i,n,t  ≤ 1 []

• X _i,n : installed capacity of power plant type i in country n [MW]

• c _l : costs for exchange of electricity [€/MWh]

• imp _n,m,t : net imports of electricity from country n to country m [€/MWh]

A secondary condition here is that demand must always be covered.

$$ {\displaystyle \sum_i}{s}_{i,n,t}\cdot {X}_{i,n}+{\displaystyle \sum_m}im{p}_{n,m,t}\ge {d}_{n,t}\kern2.75em \forall n $$

In addition, electricity import and export capacities must be considered.

$$ im{p}_{n,m,t}\le NT{C}_{n,m}\kern4.5em \forall \left(n,m\right) $$

with

• NTC _n,m : net transfer capacities.