Analysing the effect of five operational factors on forest residue supply chain costs: A case study in Western Australia

Abstract In Australia the use of forest biomass has been developing in recent years and initial efforts are built on adopting and trialling imported European technology. Using a linear programming-based tool, BIOPLAN, this study investigated the impact of five operational factors: energy demand, moisture mass fraction, interest rate, transport distance, and truck payload on total forest residues supply chain cost in Western Australia. The supply chain consisted four phases: extraction of residues from the clear felled area to roadside by forwarders, storage at roadside, chipping of materials by mobile chippers, and transport of chips to an energy plant. For an average monthly energy demand of 5 GWh, the minimum wood supply chain cost was about 29.4 $ t −1 , which is lower than the maximum target supply cost of 30–40 $ t −1 , reported by many industry stakeholders as the breakeven point for economically viable bioenergy production in Australia. The suggested volume available for chipping in the second year was larger than in the first year indicating that the optimisation model proposed storing more materials in the first year to be chipped in the second year. The sensitivity analysis showed no strong correlation between energy demand and supply chain cost per m 3 . For higher interest rates, the total storage cost increased which resulted in larger operational cost per m 3 . Longer transport distances and lower truck payloads resulted in higher transport cost per unit of delivered chips. In addition, the highest supply chain costs occurred when moisture mass fraction ranged between 20% and 30%.