Rethinking CCS - strategies for technology development in times of uncertainty

Concerns over climate change and a reliance on CO₂-emitting fossil fuels for a majority of the world's energy supply have motivated the development of carbon dioxide capture and storage (CCS). However, CCS is not yet commercially available, and key technical roadblocks remain. However, the external circumstances for developing the technology, such as weak climate policy and tight public finances, have changed dramatically over the past four years and current RD&D roadmaps are poorly adapted to the new realities. In order to rethink U.S. CCS policy, and to provide a realistic roadmap for technology development, this thesis provides an overview of the key technical roadblocks, an analysis of the impact of the new realities on CCS investments, and a novel method for finding the optimal way of allocating scarce public resources to CCS RD&D. The U.S. has responded to the changing political context in two notable ways. First, Enhanced Oil Recovery (EOR) has received increased attention due to the positive value that EOR storage puts on CO₂. Second, the EPA has proposed a 1000 lbs CO₂/MWh emission standard that would require new coal plants to install CCS. Using a stochastic generation expansion model, this thesis concludes that low natural gas prices make fuel switching rather than CCS investment the most likely compliance method. Moreover, should these standards be gradually tightened, CCS will likely be deployed on natural gas plants before coal plants. More generally, the model highlights the importance of considering uncertainty when analyzing CCS investments, and results differ notably depending on whether probability distributions over parameters are considered or not. With limited funds available for technology development there is a striking need to ensure that limited resources are allocated strategically. Whereas designing optimal technology RD&D portfolios has traditionally been dealt with qualitatively, this thesis develops a quantitative model for choosing optimal portfolios of demonstration projects. The strength of new model is how it incorporates the different uncertainties associated with CCS, allowing decision makers to observe how different underlying assumptions affect project choices. Based on my analyses, I make six recommendations for CCS technology development in times of uncertainty, many of which are major departures from current U.S. CCS policy. First, the U.S. should focus more on pilot-scale development of novel capture concepts promising to significantly reduce cost. Second, if gradually tightening emission standards is to be the primary mechanism to reduce power sector CO2 emissions, then the U.S. should also demonstrate CCS on natural gas plants. Third, granting a limited number of coal plants a higher CO₂ emission standard could help bring CCS plants online in challenging times. Fourth, relying almost exclusively on projects with EOR storage is unlikely to be a sound long-term policy. Because of the significant variability across geologic storage reservoirs, at least some demonstration projects must focus on CO₂ storage in saline formations. Finally, with tightening public finances it becomes increasingly important to coordinate demonstration efforts globally to avoid unproductive overlap.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2013

Author dc:creator

• Eide, Jan

Advisor dc:contributor.advisor

• Howard Herzog and Mort D. Webster.

• Engineering Systems Division.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/81119

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/81119