(463b) Spatial Decomposition Techniques for Strategic and Tactical Design of Biomass-to-Co-Combustion Supply Chains

Mar Pérez-Fortes, José Miguel Laínez-Aguirre, Luis Puigjaner

Department of Chemical Engineering, Universitat Politècnica de Catalunya, Av. Diagonal, 647, E08028 Barcelona, Spain

The electricity generation sector needs to reduce its environmental impact and fossil fuel dependence, principally from coal. In terms of time to deployment and cost of the solution, co-combustion of biomass and coal is presented as a transition alternative towards a carbon-neutral energy sector. However, the use of biomass in large centralized systems requires the establishment of supply channels to provide the desired feedstock with the necessary attributes, at the right time and place. Hence, there is the need to evaluate the effective introduction of co-combustion projects in the current electricity production share. The purpose of this work is to investigate the application of an optimization-based supply chain (SC) design-planning approach to process seasonal and highly distributed biomass for raw material supply to an existing park of coal power plants. The problem is formulated as a multi-objective mixed integer linear program (MO-MILP); we integrate economic and environmental criteria: the net present value (NPV), measured in €₂₀₁₀, and Impact 2002+ methodology with its corresponding metric for a life cycle assessment (LCA).

Special consideration is given to biomass intrinsic heterogeneity (due to its different origins), high moisture content, low bulk density, low heating value (LHV), degradation and seasonality. Such characteristics make it difficult its direct use as a coal substitute. However, biomass may be improved when needed, using a pre-treatment in order to enhance its stability in front of degradation and moisture content variations.  Torrefaction, torrefaction combined with pelletization, pelletization, fast pyrolysis and fast pyrolysis combined with char grinding compose the superstructure of pre-treatment technologies considered in this work.

The starting point is a previous mathematical model for the biomass SC (Peréz-Fortes et al. 2014), which has been solved for a planning horizon of 10 years, with yearly strategic decisions and monthly tactical planning decisions. The model considers the following decisions: (i) selection of SC nodes and links among them (a node can be represented by processing or distribution activities), (ii) selection of the most cost-effective or environmentally friendly pre-treatment technologies, (ii) the corresponding capacity to install each planning period, (iii) the capacity utilization levels, (vi) fraction of coal replaced by biomass, and (vii) the amount of matter distributed along the different SC nodes.

The amount of potential suppliers and facility locations, the different technological alternatives, biomass properties characterization and the model granularity, can significantly increase the size of the optimization problem. Preliminary results demonstrate that this computational expense can be significantly reduced by using a decomposition approach.  To tackle more efficiently this problem, we propose an adapted Lagrangian relaxation based approach, the Optimal Condition Decomposition (OCD), proposed in Conejo et al. (2002). One of the advantages of the OCD is that the procedure to update the multipliers is embedded in the solution of the sub-problems, thus avoiding the solution of a master problem and allowing the algorithm convergence in fewer iterations. These promising characteristics are evaluated and compared using a real large scale problem of retrofit design of biomass-to-co-combustion supply chains in Spain (Peréz-Fortes et al. 2014). Significant results obtained are discussed and future development perspectives underway are also presented.

Keywords: Bio-based supply chain, biomass pre-treatments, biomass seasonality, co-combustion, MILP, Lagrangian relaxation.

References

Conejo, A. J.; Nogales, F.J., 2002, A decomposition procedure based on approximate Newton directions Mathematical Programming. Mathematical Programming, Series A, 93, 495—515.

Gómez, A., Zubizarreta, J., Rodrigues, M., Dopazo, C., Fueyo, N., 2010, An estimation of the energy potential of agro-industrial residues in Spain. Resources, Conservation and Recycling, 54, 972-984.

Pérez-Fortes, M., Laínez-Aguirre, J.M., Bojarski, A.D., Puigjaner, L., 2014, Optimization of pre-treatment selection for the use of woody waste in co-combustion plants, Chemical Engineering Research and Design, article in press: http://dx.doi.org/10.1016/j.cherd.2014.01.004