Biofuels & Bioenergy

We present an optimization model to aid with biomass co-firing decisions in coal fired power plants. Co-firing is a strategy that can be used to reduce greenhouse gas emissions at coal plants. Co-firing is a practice that also impacts logistics-related costs, capital investments, plant efficiency, and tax credit collected. We present a nonlinear mixed integer programming model that captures the impact of biomass co-firing on the logistics-related costs, capital investments, plant efficiency, tax credit collected, and emission reductions. The objective of this model is to maximize the total profits. Profits are equal to the difference between the revenues generated from the tax credit and the additional logistics and investment costs. The constraints of this model represent the relationship between the amount of coal displaced and the amount of biomass used. These equations capture the reduced burners’ efficiencies due to burning a different product which has a lower heating value. In order to solve large instances of this problem we develop a linear approximation which is easier to solve. We test the performance of the models proposed on a case study developed using data from the State of Mississippi. We conducted a sensitivity analyses in order to evaluate the impact of biomass purchasing costs, biomass transportation costs, investment costs, and production tax credit on the cost of renewable electricity. Our results indicate that power plants would have no incentive to co-fire unless they are subsidized for their efforts. On the other side, increasing the tax credits beyond some threshold value would not necessary result in additional renewableenergy produced. That means, in order to increase the renewable energy production, instead of using a “flat rate” tax credit, a better system would be to make the tax credit a function of the amount of renewable electricity produced.