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This paper presents a linear programming (LP) methodology for estimating the cost of reducing a state's coal-fired power plant carbon dioxide emissions by cofiring switchgrass and coal. LP modeling allows interplay between regionally specific switchgrass production forecasts, coal plant locations, and individual coal plant historic performance data to determine an allocation of switchgrass minimizing cost or maximizing carbon reduction. The LP methodology is applied to two states, Pennsylvania (PA) and Iowa (IA), and results are presented with a discussion of modeling assumptions, techniques, and carbon mitigation policy implications. The LP methodology estimates that, in PA, 4.9 million tons of CO2/year could be mitigated at an average cost of less than $34/ton of CO2 and that, in IA, 7 million tons of CO2/year could be mitigated at an average Cost of Mitigation of $27/ton of CO2. Because the factors determining the cofiring costs vary so much between the two states, results suggest that cofiring costs will also vary considerably between different U.S. regions. A national level analysis could suggest a lowest-cost cofiring region. This paper presents techniques and assumptions that can simplify biomass energy policy analysis with little effect on analysis conclusions.