Analyzing the Social Cost of Carbon of Co-firing Biomass in Coal-fired Power Plants Through a Mixed-Integer Linear Programing Model




Schier, Brittany Rose

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Coal provides roughly one third of the electricity generated in the United States. While coal remains a strong industry, it poses a threat to the environment due to the high rates of carbon dioxide emissions (among other gases) released into the atmosphere. In this research, an optimization model was implemented to design the logistic network and assess the cost of investment in co-firing a power plant with switchgrass. Based on the numerical results, it was calculated that co-firing is cost-competitive for the case study in Bexar county and reduces overall power plant carbon output by 9.54 percent, or roughly 580,000 metric tons annually, when co-firing at a 10 percent rate. The proposed optimal design can potentially benefit the surrounding community and ignite growth in the local agriculture sector.

This thesis reviews several methods to calculate the Social Cost of Carbon (i.e., the economic impact of potential damages due to increased emissions). The DICE model was implemented for the Bexar County to compute the Social Cost of Carbon for the case study. The DICE model uses current emission and population rates to project future temperature increases and applies an economic value to the damages associated with the release of carbon dioxide. Results from this work present an economic benefit from the initial investment of building a biomass supply network around an existing power plant.


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Mechanical Engineering