W Integrated strategic and tactical optimization of forest-based biomass supply chains to consider medium-term supply and demand variations

Using forest-based biomass to produce bio-energy and bio-fuels could provide economic, environmental, and social benefits for communities. However, variability in biomass availability and high cost of delivered feedstock impact the profitability of the supply chain. Therefore, optimization models were developed in previous studies to design cost effective and profitable biomass-based supply chains at strategic level. Medium term variations in biomass supply and demand are not usually accounted for in strategic models. This may affect the feasibility of strategic plans prescribed by the optimization model at tactical level. To solve this issue, an integrated model is developed in this paper that includes strategic and tactical decisions simultaneously in order to optimize forest based biomass supply chains. In addition to yearly variations in biomass supply, which can occur due to changes in harvest level, monthly variations in biomass availability, bioenergy/biofuels demand, and losses during preprocessing and storage of biomass are incorporated in the model. Other unique features of this model compared to the few integrated models developed in previous studies are as follows. (1) Decision regarding opening a new conversion facility is made yearly, not just at the beginning of the planning horizon. (2) A multiproduct (heat, electricity, bio-oil and pellets) supply chain is considered. (3) The impact of fossil-based energy prices on bio-conversion investment decisions are accounted for in the model. (4) The optimization problem is modeled in a way that the global optimum solution is obtained within a reasonable time. Using a case study in Interior British Columbia, it is shown in the paper that the capacity of conversion technologies and the amount of procured biomass prescribed by the strategic model would not be sufficient to meet the monthly demand of bioenergy. Moreover, the net present value of the strategic model is overestimated due to underestimating the demand and procurement cost, and ignoring storage costs. It is shown that these issues are resolved using the integrated model.