• biofuels;
  • bioenergy;
  • forest residues;
  • optimization;
  • supply chain;
  • mathematical programming;
  • mixed integer programming


Forest residues are renewable materials for bioenergy conversion that have the potential to replace fossil fuels beyond electricity and heat generation. A challenge hindering the intensified use of forest residues for energy production is the high cost of their supply chain. Previous studies on optimal design of forest residue supply chains focused on biofuel or bioenergy production separately, mostly with a single time period approach. We present a multi-period mixed integer linear programming model that optimizes the supply chain of forest residues for the production of bioenergy and biofuels simultaneously. The model determines (i) the location, type and size of the technologies to install and the period to install them, (ii) the mix of biofuel and bioenergy products to generate, (iii) the type and amount of forest residues to acquire and the sourcing points, (iv) the amount of forest residues to transport from sources to facilities and (v) the amount of product to transport from facilities to markets. The objective of the model is to maximize the net present value of the supply chain over a 20-year planning horizon with yearly time steps. We applied the model to a case study in British Columbia, Canada, to investigate the production of heat, electricity, pellets and pyrolysis bio-oil from available forest harvesting residues and sawmill wastes. Based on current energy generation costs in the region and the predicted operating costs of new conversion plants, the results of our model recommended the installation of small biomass boilers coupled with steam turbines for electricity production (0.5 and 5 MW) and pyrolysis plants with a capacity of 200 and 400 odmt day−1. We performed a sensitivity analysis to evaluate the sensitivity of the optimal result to changes in the demand and price of products, as well as the availability and cost of forest residues. Copyright © 2014 John Wiley & Sons, Ltd.