Carbon Abatement Cost Curves for Power Generation in the United States

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Abstract/Contents

Abstract

Anthropogenic climate change is one of the largest challenges of the modern era. The impacts of climate change are already manifesting in abnormal weather patterns, rising seas, and stronger storms, and these issues will grow in severity as emissions continue. Electricity production is a major source of global carbon dioxide emissions, and so decarbonizing electricity production is crucial to lowering global emissions to limit climate change impacts. The United States accounts for 13% of annual global greenhouse gas emissions and 25% of its greenhouse gas emissions are due to electricity production.
Decreasing emissions associated with electricity production while maintaining reliable and affordable service is a serious challenge. We must consider how to replace current emissions' intensive infrastructure with low carbon technology at the minimal cost. A useful framework for decision-making is the marginal abatement cost curve (MACC). In this work, we develop marginal abatement cost curves for the US power system.
We estimate the costs and avoided emissions from replacing power generators in 2020. We use historic operations and emissions data from the Continuous Emissions Monitoring System (CEMS) with estimated costs from the Energy Information Agency (EIA) to create a marginal abatement cost curve based on retroactive replacement of all US plants.
Using a discount rate of 6% and assuming recent fuel prices, we find that electricity generation associated emissions can be reduced by 1/3 at negative cost over a replacement plant's. However, costs and emissions reductions are not equally distributed across the states. Some states with higher emitting infrastructure and can replace their production cheaply, while those already utilizing lower emission technologies need to pay much more.
Assumptions for power plants' useful lifetimes, discount rates, and replacement behavior underlie the values presented here, and the sensitivity analysis to our baseline assumptions shows that discount rate and fuel price have a significant impact when varied.
The findings here highlight that locations that are best for wind or solar are not always used, and that, in the short term, many plants can be replaced at a cost savings over a conservative lifetime, providing a reasonable transition solution towards decarbonization. In particular, coal to natural gas replacements are broadly cost effective allowing for roughly 31% of emissions reductions available for less than $200 per tonne. The results show that these cost-effective replacements are not equally distributed across the nation. Locations like Tennessee and Texas, with existing coal capacity can replace 0.17 and 0.05 GtCO2 of coal emissions cost effectively. California, which already has a relatively low emissions grid, can replace less than 0.0025 GtCO2 cost effectively from its grid. From this work, we emphasize the importance of national scale decision making to harness locational differences in abatement costs as well as creating concrete long-term emissions strategies to better plan for long lived infrastructural decisions that must happen in the near term.

Description

Type of resource text
Date modified December 5, 2022
Publication date June 7, 2022

Creators/Contributors

Author Huster, Jonathan
Thesis advisor Azevedo, Inês

Subjects

Subject Marginal Abatement Cost Curve
Subject Electricity Decarbonization
Genre Text
Genre Thesis

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User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
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This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International license (CC BY-NC).

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Preferred citation
Huster, J. (2022). Carbon Abatement Cost Curves for Power Generation in the United States. Stanford Digital Repository. Available at https://purl.stanford.edu/rv151kn6412

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Master's Theses, Doerr School of Sustainability

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