Evaluating Supply Chain Design Models for the Integration of Biomass Co-firing in Existing Coal Plants Under Uncertainty

Co-firing biomass with a primary fuel in existing power plants is a cost effective environmental strategy. Co-firing implementations are carried out considering the impact of emissions reduction, logistic-related costs, plant efficiency and incentive savings. The literature on mathematical programming models for co-firing can be grouped in two categories: supply chain network design and determination of optimal fuel combination. Our literature review reveals that there is a need for models to show the effect of uncertainties in both of these categories. In this chapter, we carry out a traditional sensitivity analysis and propose a stochastic mixed-integer linear programming model within a single-period planning framework for a supply chain design problem which integrates biomass co-firing in existing coal plants. Purchase costs of coal, biomass and the amount of available biomass are considered as the uncertain parameters. The performance of the proposed model is evaluated by computational tests using data from the State of Mississippi. The computational results reveal that the benefit of the two-stage stochastic programming approach is marginal although a considerable uncertainty is taken into account in the model, while our sensitivity analysis shows that strategies making the co-firing option profitable under uncertainties can be revealed by the model.