This second webinar was held on Friday 25th April, for anyone who wasn't able to join us for the previous webinar held on Thursday 20th March. This webinar presented the findings of a study to assess the economic viability of natural gas combined-cycle power plants with CO2 capture and storage (NGCC-CCS) in climate change mitigation strategies, emphasising the use of renewable energy and natural gas for electric power generation. In this study, the cost of NGCC-CCS was compared on a level playing field to those of intermittent renewable energy systems (IRES) and energy storage technologies as a means of reducing power sector greenhouse gas emissions. Specifically, the levelised cost of electricity (LCOE) of NGCC-CCS was compared to that of offshore wind, photovoltaic systems, and concentrated solar power (CSP) together with pumped hydro storage (PHS), compressed air energy storage (CAES), and Li-ion, ZEBRA and Zn-Br battery storage systems. The cost of NGCC-CCS as a backup technology in conjunction with IRES also was assessed. At this webinar, Machteld van den Broek, senior researcher at the Utrecht University, presented the findings of the study. Her expertise is energy systems modelling and CCS. Among others, she is involved in the CATO-2 programme, the second Dutch national research programme on CCS. During the webinar Professor Edward Rubin from Carnegie Mellon University and co-author of this study, will assist during the Q&A session. Niels Berghout, from Utrecht University also contributed to this study.

1. The cost-effectiveness of natural gas combined cycle
power plants with CO2 capture and storage in a climate
change mitigation strategy
Webinar – 25 March 2014, 0000 AEDT

2. Machteld van den Broek
Machteld van den Broek is a senior researcher at the Utrecht University.
She specialises in energy systems modelling and, especially, investigated
the role of CO2 capture and storage in the energy system.
Among others, she is involved in the CATO-2 programme, the second
Dutch national research programme on CCS
Senior researcher, Utrecht University

3. Ed Rubin
Ed Rubin is a chaired professor in the Department of Engineering & Public
Policy, and Mechanical Engineering at Carnegie Mellon University.
He is an expert on technological learning and techno-economic
assessment of energy systems with CO2 capture and storage and
published many widely-cited papers on this subject.
Professor, Carnegie Mellon University

4. Niels Berghout
Niels Berghout works as a PhD student at the Energy & Resources group
of the Copernicus Institute of Sustainable Development (Utrecht
University).
His research involves among others techno-economic analyses
of CO2 capture in the industrial sector, and several other CCS topics, such
as CO2 pipeline transport and shipping. Furthermore, he contributed to the
research discussed today.
PhD student, Utrecht University

5. QUESTIONS
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6. The cost-effectiveness
of natural gas combined cycle power plants
with CO2 capture and storage
in a climate change mitigation strategy
Machteld van den Broek, UU
Niels Berghout, UU
Ed Rubin, Carnegie Mellon University
6

7. Background
• Target: stabilising concentration of greenhouse gases at 450 ppm
CO2-equivalent in the atmosphere
• Low carbon power systems
• What is role of NGCC-CCS in a low carbon power system
– providing baseload power
– providing backup services
7

8. Research questions
• Cost-effectiveness of NGCC-CCS
– in baseload role compared to intermittent renewable sources (IRES)
• offshore wind
• concentrated solar power (CSP)
• photovoltaic systems (PV)
– as backup service compared to
• pumped hydro storage (PHS)
• Compressed air energy storage (CAES)
• Li-ion battery
• ZiBr battery (Zinc-bromine)
• Zebra battery (Sodium-Nickel-Chloride, NaNiCl)
• What are the potential cost reductions over time due to learning?
8

9. Methodology – starting points
• Scope: costs for Europe
• Technological learning – experience curve method
– Progress ratio (PR): fraction of original cost after each doubling of cumulative installed
capacity
– Learning rate = 1 – progress ratio.
– Global learning
• Levelised costs of electricity including extra costs for intermittent
technologies
– Balancing
– Transmission
– Backup services
9

10. Levelised cost of electricity - LCOE
• Capital cost (CAPEX) and fixed operating and maintenance
cost (FOM)
– capacity factor is crucial parameter
• Variable operating and maintenance cost (VOC)
• Fuel cost
• CO2 emission cost
• Extra balancing and transmission costs
• CO2 transport and storage costs
• (costs for backup services included in system cost)
10

11. Techno-economic data
collection
Scenario data
Calculation LCOE per technology
Inventory extra costs
intermittency +
decentralized
Inventory of
progress ratios
Calculation LCOE per
technology as function
of cumulative capacity
Calculation LCOE per
TECHNOLOGY over time
Definition of system
configurations
Calculation LCOE per
SYSTEM over time
Historical CO2
emission allowance
and natural gas prices
11
2011

12. Techno-economic data
collection
Scenario data
Calculation LCOE per technology
Inventory extra costs
intermittency +
decentralized
Inventory of
progress ratios
Calculation LCOE per
technology as function
of cumulative capacity
Calculation LCOE per
TECHNOLOGY over time
Definition of system
configurations
Calculation LCOE per
SYSTEM over time
Historical CO2
emission allowance
and natural gas prices
12
2011

13. Inventory of techno-economic data
• Medium values
– Averages of the input data found in the literature.
– can be considered as most representative values for Europe.
• Values can be lower or higher in particular regions in Europe
• Full ranges between optimistic and pessimistic values
13

14. Medium values of techno-economic parameters and PRs
14

15. Medium values of techno-economic parameters and PRs
15

16. Techno-economic data
collection
Scenario data
Calculation LCOE per technology
Inventory extra costs
intermittency +
decentralized
Inventory of
progress ratios
Calculation LCOE per
technology as function
of cumulative capacity
Calculation LCOE per
TECHNOLOGY over time
Definition of system
configurations
Calculation LCOE per
SYSTEM over time
Historical CO2
emission allowance
and natural gas prices
16
2011

17. 0
100
200
300
400
500
600
700
800
900
1000
NGCC NGCC-
CCS
Wind
offshore
PV CSP NGCC-
CCS 40%
PHS CAES Li-ion Zebra Zn-br
LCOEin€2012/MWhor€2012/MWhintforIRES
Investments Natural gas Fixed O&M
Variable O&M CO2 emission costs CO2 transport and storage
Balancing costs Transmission costs Medium values with spec. discount rate
―― power generation ―― ―――― backup technologies ―――
Note: power costs to
charge storage systems
are not included
Baseload Intermittent
LCOEs in 2011: ranges
Gas price is 6.7 €2012/GJ and CO2 emission price is 13.5 €2012/t, Discount rate is 10%.
17

18. Techno-economic data
collection
Scenario data
Calculation LCOE per technology
Inventory extra costs
intermittency +
decentralized
Inventory of
progress ratios
Calculation LCOE per
technology as function
of cumulative capacity
Calculation LCOE per
TECHNOLOGY over time
Definition of system
configurations
Calculation LCOE per
SYSTEM over time
Historical CO2
emission allowance
and natural gas prices
18
2011

19. Inventory of scenarios to determine number of doublings
• Scenarios which reach 450 ppm target
– 44 scenarios: Global Energy Assessment (GEA, 2012).
– 1 scenario: Energy Technology Perspectives 2012 (IEA, 2012)
• Focus on 3 scenarios
– Base 450 scenario is the 450-ppm scenario (ETP scenario)
– High renewable scenario
– High NGCC-CCS scenario
19

20. Other
Ocean
Geothermal
Wind total
Wind offshore
Wind onshore
Solar CSP
Solar PV
Hydro
Other
Ocean
Geothermal
Wind total
Wind offshore
Wind onshore
Solar CSP
Solar PV
Hydro
Nuclear
Biomass w CCS
Biomass and waste
Oil w CCS
Oil
Natural gas w CCS
Natural gas
Coal w CCS
Coal0
5
10
15
20
25
30
2009 2020 2025 2030 2035 2040 2045 2050
InstalledcapacityinTW
ETP2012
Other
Ocean
Geothermal
Wind total
Wind offshore
Wind onshore
Solar CSP
Solar PV
Hydro
Nuclear
Biomass w CCS
Biomass and waste
Oil w CCS
Oil
Natural gas w CCS
Natural gas
Coal w CCS
Coal
0
5
10
15
20
25
30
2009 2020 2025 2030 2035 2040 2045 2050
InstalledcapacityinTW
GEA-efficiency - conventional transport - no beccs, no sinks, limited biomass
Other
Ocean
Geothermal
Wind total
Wind offshore
Wind onshore
Solar CSP
Solar PV
Hydro
Nuclear
Biomass w CCS
Biomass and waste
Oil w CCS
Oil
Natural gas w CCS
Natural gas
Coal w CCS
Coal
0
5
10
15
20
25
30
2009 2020 2025 2030 2035 2040 2045 2050
InstalledcapacityinTW
IMAGE-MIX
O
O
G
W
W
W
So
So
H
N
B
B
O
O
N
N
C
C
Our HIGH-REN 450 scenario Our HIGH-NGCC-CCS 450 scenario
Our BASE 450 scenario
20

21. Techno-economic data
collection
Scenario data
Calculation LCOE per technology
Inventory extra costs
intermittency +
decentralized
Inventory of
progress ratios
Calculation LCOE per
technology as function
of cumulative capacity
Calculation LCOE per
TECHNOLOGY over time
Definition of system
configurations
Calculation LCOE per
SYSTEM over time
Historical CO2
emission allowance
and natural gas prices
21
2011

22. LCOE versus cumulative capacity under medium conditions
Gas price is 6.7 €/GJ and CO2 price is 13.5 €/t.
0
50
100
150
200
250
0 1 10 100 1000 10000 100000
LCOEin€2012/MWhor€2012/MWhintforIRES
Cumulative capacity inGW
baseload NGCC
Baseload NGCC-CCS
Mid merit NGCC-CCS
Wind offshore
PV
CSP
Note: Power generation from
wind offshore, and PV is not
controllable, and CSP partly. In
contrast, mid-merit NGCC-CCS
is controllable.
22

23. LCOE versus cumulative capacity under medium conditions
Gas price is 6.7 €/GJ and CO2 price is 13.5 €/t.
Capacity factor is set at the availability factor (see table medium values)
0
100
200
300
400
500
600
0 1 10 100 1000 10000
LCOEin€2012/MWh
Cumulative capacity inGW
CAES
PHS
Li-ion
Zn-Br
ZEBRA
NGCC-CCS 40%
Note: power costs to
charge storage systems
are not included
23

24. Techno-economic data
collection
Scenario data
Calculation LCOE per technology
Inventory extra costs
intermittency +
decentralized
Inventory of
progress ratios
Calculation LCOE per
technology as function
of cumulative capacity
Calculation LCOE per
TECHNOLOGY over time
Definition of system
configurations
Calculation LCOE per
SYSTEM over time
Historical CO2
emission allowance
and natural gas prices
24
2011

25. Natural gas price and CO2 price development
2011 2020 2030 2040 2050
gas price * €/GJ 6,7 7,5 7,0 6,5 6,0
CO2
* €/tCO2 13,5 33 70 107 144
high gas price scenario** €/GJ 6,7 8,5 9,4 9,8 10,4
* Based on IEA – 450 scenario
** Based on IEA – current policy scenario
25

26. LCOE over time under medium conditions in the
Base 450 scenario
0
50
100
150
200
250
2010 2015 2020 2025 2030 2035 2040 2045 2050
LCOEin€2012/MWh
NGCC
NGCC-CCS
Wind offshore
PV
CSP
50
100
150
200
250
LCOEin€2012/MWhor€2012/MWhintforIRES
26

27. Sensitivities of LCOEs for different variants in 2040
27
0
100
200
300
400
500
600
700
800
NGCC NGCC-CCS Wind
offshore
PV CSP NGCC-CCS
40%
PHS CAES Li-ion Zebra Zn-br
LCOEin€2012perMWhorMWhvarforIRES
Investments Natural gas Fixed O&M
Variable O&M CO2 emission costs CO2 transport and storage
Balancing costs Transmission costs HIGH-REN + medium
HIGH-NGCC-CCS + medium
―― power generation ―― ―――― backup technologies ――――
Note: power costs to
charge storage systems
are not included
Baseload Intermittent
27

28. Techno-economic data
collection
Scenario data
Calculation LCOE per technology
Inventory extra costs
intermittency +
decentralized
Inventory of
progress ratios
Calculation LCOE per
technology as function
of cumulative capacity
Calculation LCOE per
TECHNOLOGY over time
Definition of system
configurations
Calculation LCOE per
SYSTEM over time
Historical CO2
emission allowance
and natural gas prices
28
2011

29. Taking into account cost for backup services
In order include additional costs for backup requirements, we designed four stylized
systems based on:
• NGCC-CCS
• IRES/NGCC
• IRES/NGCC-CCS
• IRES/energy storage
Note: All investigated scenarios have a broader portfolio of technologies than these four
stylized systems. We only use these stylized systems in order to make some estimates of
the backup costs.
We treat these stylized systems as isolated systems (e.g. on an island) in a world which
follows the BASE 450 scenario, the HIGH-REN 450 scenario, or the HIGH-NGCC-CCS 450
scenario.
29

30. Share of electricity generation in stylized systems
The percentage values indicate the capacity factors of the different technologies.
Capacity factors (CFs) of wind and PV in the IRES/STORAGE system are lower, because
part of the produced power is curtailed or used to charge power storage.
30

31. Taking into account adequacy requirements 31
0
50
100
150
200
250
0
50
100
150
200
250
CO2emissionsinkg/MWh
AverageLCOEin€2012/MWh
NGCC NGCC-CCS Wind offshore
PV PHS Curtailment
BASE 450 + medium HIGH-REN + medium HIGH-NGCC-CCS + medium
――― 2020 ――― ――― 2030 ――― ――― 2040 ―――
= CO2 emissions

32. Caveats -> further research
• No deployment projections on storage capacity in global energy scenarios
• More data required from power system simulation models of low carbon
electricity systems with power storage
• Demand side management is not included
• Techno-economic data uncertain, especially, for novel technologies like
ZEBRA and Zn-Br
• Progress ratios not always available or based on short historical time series.
32

33. Conclusions – NGCC-CCS as backup
• Cost of NGCC-CCS as backup
– Less reduction than batteries
– Less uncertain
– under medium conditions (charging cost not included)
• Somewhat higher than PHS, and CAES, and ZnBr
• Lower than Li-ion and ZEBRA.
33

34. Conclusions – NGCC-CCS as baseload
• Cost of NGCC-CCS as baseload power plant
– Less reduction than for IRES
– Less uncertain than IRES
– Under medium conditions (excluding cost for IRES backup):
• in same range as offshore wind and CSP
• lower than PV.
– Cost-effectiveness depends on deployment rate and location
• Cost for backup services
– Cost of IRES/NGCC-CCS system lower than system with IRES and PHS
(medium conditions)
34

35. QUESTIONS / DISCUSSION
Please submit your questions in
English directly into the
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36. Please submit any feedback to: webinar@globalccsinstitute.com