Prasodjo, Darmawan (2011-05). An Economic Study of Carbon Capture and Storage System Design and Policy. Doctoral Dissertation.
Carbon capture and storage (CCS) and a point of electricity generation is a promising option for mitigating greenhouse gas emissions. One issue with respect to CCS is the design of carbon dioxide transport, storage and injection system. This dissertation develops a model, OptimaCCS, that combines economic and spatial optimization for the integration of CCS transport, storage and injection infrastructure to minimize costs. The model solves for the lowest-cost set of pipeline routes and storage/injection sites that connect CO2 sources to the storage. It factors in pipeline costs, site-specific storage costs, and pipeline routes considerations involving existing right of ways and land use. It also considers cost reductions resulting from networking the pipelines segment from the plants into trunk lines that lead to the storage sites. OptimaCCS is demonstrated for a system involving carbon capture at 14 Texas coal-fired power plants and three potential deep-saline aquifer sequestration sites. In turn OptimaCCS generates 1) a cost-effective CCS pipeline network for transporting CO2 from all the power plants to the possible storage sites, and 2) an estimate of the costs associated with the CO2 transport and storage. It is used to examine variations in the configuration of the pipeline network depending on differences in storage site-specific injection costs. These results highlight how various levels of cooperation by CO2 emitters and difference in injection costs among possible storage sites can affect the most cost-effective arrangement for deploying CCS infrastructure.
This study also analyzes CCS deployment under the features in a piece of legislation the draft of American Power Act (APA) - that was proposed in 2010 which contained a goal of CCS capacity for emissions from 72 Gigawatt (GW) by 2034. A model was developed that simulates CCS deployment while considering different combinations of carbon price trajectories, technology progress, and assumed auction prices. The model shows that the deployment rate of CCS technology under APA is affected by the available bonus allowances, carbon price trajectory, CCS incentive, technological adaptation, and auction process. Furthermore it demonstrates that the 72GW objective can only be achieved in a rapid deployment scenario with quick learning-by-doing and high carbon price starting at 25 dollars in 2013 with a 5 percent annual increase. Furthermore under the slow and moderate deployment scenarios CCS capacity falls short of achieving the 72 GW objective.