Transcript Document

Interaction of a GHG Emissions Cap
With Energy Technologies and Markets
USAEE Annual Conference – Washington DC
October 11, 2011
Donald Hanson and David Schmalzer
Argonne National Laboratory
Acknowledgements
We want to thank the National Energy Technology Laboratory
for support. Particularly we want to thank Tim Fout, NETL
Project Manager, and John Marano, JJM Energy Consulting.
The runs shown here are preliminary results.
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Background on Carbon Capture for Existing
Fossil Energy Power Plants and Sequestration
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
Source: Ciferno, J., CO2 Capture from Existing Coal Fired Power Plants,
NETL, December 2007
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Deployment Barriers for CO2 Capture on Coal
Power Plants
Source: Ciferno, J., The U.S. Department of Energy’s Carbon Dioxide Capture RD&D Program, Pittsburgh, August 2011
4
Our Scenario Results Show Need for Existing
Plant CCS under a Wide Range of Conditions
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High Gas Shale Production, Slower Electricity Demand Growth (hG-rD)
High Gas Shale Production, Higher Electricity Demand Growth (hG-HD)
Lower Gas Shale Production, Slower Electricity Demand Growth (LG-rD)
Lower Gas Shale Production, Higher Electricity Demand Growth (LG-HD)
 In the results, we refer to Slower Electricity Demand Growth as
“Reference Electricity Demand” and Lower Gas Shale Production as
“Reference Gas Shale Production .“
 We assume a CO2 emissions reduction requirement by 2050
 We also assume continued R&D related cost reductions in postcombustion CO2 capture technology
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The AMIGA model system converges on a supply
and demand balance for major energy carriers.
All Modular Integrated Growth Assessment (AMIGA) System
simplified
Resource Supply and
Production
o Coal, biomass
o Petroleum
o Gas shales
Electric Capacity and
Generation
Resource demand
Q
Resource
demand
Electric
demand
Economic Model
o 90 sectors
o End-use energy demand
o Transportation
technologies, vehicles and
energy use
Q
Q
Fuels demand
o 21 technologies
o Power plant unit inventory
o Dispatch on load curve
Fuels Refining and
Blending Model
o 26 processes
o Includes biofuels
Q
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Relationship Between Demand and Generation
in the Electricity Market

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Solve for Supply and Demand Balance in Gas
Market.
 Simple, dynamic gas supply scenario model where current
production depends on wellhead gas price, state of technical
progress in extraction costs, and cumulative production.
 Downward sloping demand functions for gas in enduse
sectors
 Higher gas prices reduce investments in NGCC and increase
coal use:
– Existing coal units are more likely to continue to operate longer rather
than retire.
– In the midterm, an additional increment of new IGCC with CCS
operating at full capacity factors becomes economic relative to more
NGCC operating at shoulder-load capacity factors.
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Reference Demand and Reference Gas Shale
Scenario – Total Generation (Electric Power Sector & End Use)
7000
6000
Wind Solar Geo
Hydro Power
Biomass Techs
Gas - EndUse
Gas - CC & CT
Oil Gas Steam
Adv Coal CCS
Rest Exist PC
Pre-Retrofit
CCS Retrofit
Nuclear
5000
Wind-Solar-Renewables
4000
3000
Gas CC & CT
2000
1000
Coal – No Retrofit
Coal – Pre retrofit
0
2010
IGCC with CCS
Nuclear
2015
2020
2025
2030
2035
2040
2045
2050
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High Gas Shale Scenario: Gas Incrementally
Displaces Most Other Generation Sources
7000
6000
Wind Solar Geo
Hydro Power
5000
Biomass Techs
Gas - EndUse
4000
Gas - CC & CT
Oil Gas Steam
3000
Adv Coal CCS
Gas CC & CT
Rest Exist PC
2000
Pre-Retrofit
CCS Retrofit
1000
Nuclear
0
2010
2015
2020
2025
2030
2035
2040
2045
2050
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Higher Electricity Demand due to More Electric
Vehicles; Reference Gas Scenario
7000
6000
Wind Solar Geo
Hydro Power
5000
Biomass Techs
Gas - EndUse
4000
Gas - CC & CT
Oil Gas Steam
Gas – CC & CT
3000
Adv Coal CCS
Rest Exist PC
2000
Pre-Retrofit
CCS Retrofit
1000
Nuclear
0
2010
2015
2020
2025
2030
2035
2040
2045
2050
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We find that we need to do about the same number
of PC plant retrofits in the High Shale Gas Scenario.
The need for this technology is robust, given
emission reductions.
Compare the two shale gas scenarios: High and Low. With more gas:
1.
Some older, existing coal plants will be repowered with gas, reducing CO2
emissions.
2.
Some near-zero generation (i.e., renewables, IGCC with CCS, nuclear) will
be displaced on the margin with gas, increasing CO2 emissions.
Balancing 1 & 2, keeping the amount of CO2 emissions reduction unchanged,
we will need to get about the same amount of CO2 reduction from retrofitting
existing PC plants in both scenarios.
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Increasing Capacity Factors results in a “rebound”
effect on generation. Assume a parasitic load of 25%
based on improved retrofit technology. From example
below, (1 – 0.25)*(0.654)/0.544, yielding 10% reduced
generation. Further, non-retrofitted units will phase
down the load curve and finally retire.
UNIT CAPACITY
FACTOR RESULTS
Low Gas Shale
High Gas Shale
RetroUnit non-retro RetroUnit non-retro
Ref Elec Dmd
65.2
51.8
65.4
54.4
High Elec Dmd
67.2
52.5
67.4
54.5
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Margins at Which Economic Decisions Apply
 Existing coal-fired units in the unit inventory are sorted by the model in
order of highest return for refurbishment and CCS retrofit. NETL studies
show great diversity in the population of existing PC units. This is a classic
case for obtaining economic efficiency gains through emission trading,
relative to command and control regulation.
 Units which are not retrofitted continue to operate until no longer
profitable, given the price of electricity and the cost of tradable CO2
emission allowances.
 New NGCC capacity will enter in the loading order after base-load units
with lower variable costs. The (competitive market or regulated) price of
electricity must be sufficient to cover full investment costs of new capacity.
 New base-load advanced coal units (e.g., IGCC with CCS) compete with
shoulder load NGCC, where IGCC also gets a system cost reduction credit
for displacing a portion of higher cost generation, and, through learning,
lowering present value cost of future capacity needs (see Hanson
references on dynamic programming optimization).
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Future Planned Work
 Examine the savings in scarce investment dollars that could be obtained
from retrofitting existing power plants compared with building new plants.
 Examine impacts of proposed EPA regulations
 Examine regional power pool impacts in US
 Include the energy security benefits of maintaining the existing coal-fired
fleet (e.g., reduce oil imports through increased vehicle electrification)
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References
1. M.G.Shelby, A.Fawcett, E.Smith, D.Hanson, and R.Sands, “Representing technology
in CGE Models: A Comparison of SGM and AMIGA for Electricity sector CO2
Mitigation,” Int. J. Energy Technology and Policy, Vol 6, No. 4, 2008, pp. 323-342.
2. D.A.Hanson, Y.Kryukov, S.Leyffer, and T.Munson, “Optimal Control Model of
Technology Transition,” Int. J. Global Energy Issues, Vol. 33, Nos. 3-4, 2010, pp.154175.
3. D.A.Hanson, “Optimizing the Penetration of Advanced Low-Carbon Energy
Technologies,” USAEE Annual Conference, Houston TX, September 16-19, 2007.
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