1. Joshua Linn (MIT and Resources for the Future)
Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies
Anya Castillo (MIT)
Joshua Linn (MIT and Resources for the Future)
June 25, 2010

2. Direction of Technology Adoption
Background
Methods
Findings
Question Motivation Related Work
Direction of Technology Adoption
Which technologies are favored most under the implementation of a price on carbon dioxide (CO2) emissions?
Research Focus
Free of Distributional Issues
Direct effects of CO2 Policy
on Electricity Prices
6/11/2019
Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

3. Incentives due to CO2 Regulation
Background
Methods
Findings
Question Motivation Related Work
Incentives due to CO2 Regulation
Higher Wholesale Power Prices ↓
Incentives for Innovation and Adoption of Clean Tech
CAVEAT: Clean Tech differs in performance and resource potential.
Wind
Solar
Nuclear
Coal + CCS
Hydro
Etc.
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

4. Unit Commitment Formulation
Background
Methods
Findings
Question Motivation Related Work
This Study:
Focuses on Directed Technology Incentives due to increases in Electricity Prices
Incorporates differences in operational characteristics and fuel availability across technologies (Connors 2004, Cullen 2009)
Unit Commitment Formulation
Preceding Studies:
Theoretical
Jung 1996, Fischer 2003,
Weber &Neuhoff 2010,
Goulder&Mathai 2000
Empirical
Carlson 2000, Popp 2003,
Linn 2008,
DOE NEMS, MIT EPPA
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

5. Electricity Market with No CO2 Price
Background
Methods
Findings
Stylized Model Empirical Model
Electricity Market with No CO2 Price
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

6. Electricity Market under Increasing CO2 Price
Background
Methods
Findings
Stylized Model Empirical Model
Electricity Market under Increasing CO2 Price
No change in merit order when price of Coal < Gas
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

7. Electricity Market under Increasing CO2 Price
Background
Methods
Findings
Stylized Model Empirical Model
Electricity Market under Increasing CO2 Price
Change in merit order when price of Coal > Gas
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

8. Research Approach Model ERCOT electricity market in 2008
Background
Methods
Findings
Stylized Model Empirical Model
Research Approach
Model ERCOT electricity market in 2008
Annual Simulations with Hourly Solutions
$0-50/tCO2 (at $10/tCO2 increments)
Cost-Minimization Unit-Commitment
Mixed Integer Problem with chronological Monet Carlo*
Analysis of Directed Incentives to Technologies
Current ERCOT: Nuclear, Coal, Gas, Wind
Hypothetical Units: Solar, Integrated Gasification Combined Cycle (IGCC), and Advanced Gas/Oil Combined Cycle (Adv CC)
Wind and Solar Resource Potential
No Transmission Network
*Memphis version 3.7, prepared by IIT for Red Electrica de España
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

9. ERCOT Supply Curve Marginal Cost ($/MWh) Capacity (GW) Background
Methods
Findings
Stylized Model Empirical Model
ERCOT Supply Curve
700
2 × Coal Fuel Price
2008 Avg Fuel Prices
Coal $1.33
Natural Gas $6.63
2 × Natural Gas Fuel Price
600
Actual in 2008
500
400
Natural Gas
Nuclear
Marginal Cost ($/MWh)
300
Avg Marginal Costs
Nuclear $5.61
Coal $18.96
Natural Gas $71.11
Here is the supply curve, illustrating that the average marginal costs for nuclear, coal and gas are $5.61, $18.96, and $71.11 respectively.
Since natural gas accounts for the most of the capacity in ERCOT and approx. half the generation share in 2008, fluctuations in natural gas fuel prices have the greatest impact on electricity prices.
The fuel price doubling has no material affect on how these units are dispatched.
200
Coal
100 10 20 30 40 50 60 70 80 90
Capacity (GW)
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

10. ERCOT (Texas) is renewable resource-rich
Background
Methods
Findings
Stylized Model Empirical Model
ERCOT (Texas) is renewable resource-rich
Wind
Solar
(NREL)
Competitive Renewable Energy Zones (CREZs)
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

11. Temporal Resource Potential
Background
Methods
Findings
Stylized Model Empirical Model
Temporal Resource Potential
Wind
Solar 1 1
0.9
Winter
0.9
Spring
0.8
0.8
Summer
Fall
0.7
0.7
0.6
0.6
Seasonal Average Probability
0.5
0.5
0.4
0.4
0.3
0.3
Winter
0.2
Spring
0.2
Summer
0.1
0.1
Fall 2 4 6 8 10 12 14 16 18 20 22 24 2 4 6 8 10 12 14 16 18 20 22 24
Hour of the Day
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

12. System Operations at No CO2 Price
Background
Methods
Findings
Simulation Results Discussion
System Operations at No CO2 Price 2 4 6 8 10 12 14 16 18 20 22 24
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9 1
Average Probability
Hour of the Day
Coal Marginal Unit
Wind Generation
Solar Generation
Generation-to-Load Correlation
Nuclear
Coal
Natural Gas 0.93
Wind
Solar
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

13. Effect of CO2 Price on Generation Share
Background
Methods
Findings
Simulation Results Discussion
Effect of CO2 Price on Generation Share 10 20 30 40 50 60
Price per ton of CO2
Generation Share (%)
Nuclear
Coal
Natural Gas
Wind
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

14. Marginal Abatement Cost Curve
Background
Methods
Findings
Simulation Results Discussion
Marginal Abatement Cost Curve 10 20 30 40 50 5 15 25
Offset Emissions (MtCO2)
Price per ton of CO2
Emissions = MtCO2
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

15. System operations change with a CO2 Price
Background
Methods
Findings
Simulation Results Discussion
System operations change with a CO2 Price
Coal Units
Natural Gas Units
100
100 90 90 80 80 70 70 60 60
Capacity Factor (%) 50 50
Upper Quartile 40 40 30
Median 30
Mean 20 20
Lower Quartile 10 10 10 20 30 40 50 10 20 30 40 50
Price per ton of CO2
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

16. Decrease in the Marginal Emissions Rate
Background
Methods
Findings
Simulation Results Discussion
Decrease in the Marginal Emissions Rate 10 20 30 40 50
0.1
0.2
0.3
0.4
0.5
Price per ton of CO2
Full Day
Night
Day (7am-7pm)
Probability Coal
is the
Marginal Unit
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

17. Which techs run when coal is marginal?
Background
Methods
Findings
Simulation Results Discussion
Which techs run when coal is marginal?
Nuclear 50
Wind
Solar
IGCC 40
Advanced CC 30
Price per ton of CO2 20 10 -1
-0.8
-0.6
-0.4
-0.2
0.2
0.4
0.6
0.8 1
Correlation Coefficient
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

18. Variations in Revenue Growth
Background
Methods
Findings
Simulation Results Discussion
Variations in Revenue Growth
Fossil Fuel Tech
Clean Tech
100
100
Coal µ0=5.14 ¢/kWh
Wind µ0=4.15¢/kWh 90 90
Natural Gas µ0=6.96
Nuclear µ0=4.83 80
IGCC µ0=4.99 80
Solar µ0=5.77
Advanced CC µ0=6.16 70 70 60 60 50 50
Growth from No CO2 Price (%) 40 40 30 30 20 20 10 10 10 20 30 40 50 10 20 30 40 50
Price per ton of CO2
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

19. Incremental Gains to Clean Tech Generating Units
Background
Methods
Findings
Simulation Results Discussion
Incremental Gains to Clean Tech Generating Units
-10 -8 -6 -4 -2 2 4 1 3 5 6
Demeaned Growth in Average Revenue
from Baseline (%)
Percentage of Total Units (%)
Growth in Average Revenue (from No CO2 Price)
Wind µ0→20=36.3%
Solar µ0→20=20.7%
Nuclear µ0→20=27.6%
-0.2
-0.1
0.1
0.2
0.3
0.4
0.5
0.6
0.7 1 2 3 4 5 6
Demeaned Average Revenue (¢/kWh)
Average Revenue
Wind µ20=5.65¢
Solar µ20=6.97¢
Nuclearµ20=6.17¢
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

20. Variations in Marginal Profit Growth
Background
Methods
Findings
Simulation Results Discussion
Variations in Marginal Profit Growth
Fossil Fuel Tech
Clean Tech
100
100
Coal µ0=3.38 ¢/kWh
Windµ0=4.15¢/kWh 80
Natural Gas µ0=1.77 80
Nuclear µ0=4.27
IGCC µ0=3.53
Solarµ0=5.77 60
Advanced CC µ0=1.48 60 40 40 20
Growth from No CO2 Price (%) 20
-20
-20
-40
-40
-60
-60 10 20 30 40 50 10 20 30 40 50
Price per ton of CO2
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

21. Background
Methods
Findings
Simulation Results Discussion
Main Points
Technologies that operate when the heavy-emitters are marginal reap the most benefit
Weak CO2 prices result in greater incremental gains since there is slight change to merit order
Resource potential across time and space matters for intermittent generation
CO2 prices as a cost-effective investment incentive in clean tech versus other policies
6/11/2019
Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

22. Anya Castillo anya.castillo@gmail.com Joshua Linn linn@rff.org
Thank You!
Anya Castillo
Joshua Linn
6/11/2019
Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

23. Supplemental Slides 6/11/2019
Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

24. Change in Cost, Revenue and Profit
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

25. Summary Statistics by Technology
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies

26. Simulation with Zero Carbon Price
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Incentives of Carbon Dioxide Regulation for Investment in Clean Electricity Technologies