A novel risk analysis methodology to evaluate the economic performance of a biorefinery and to quantify the economic incentives for participating biomass producers

Abstract

In this paper, a novel risk analysis methodology is presented to evaluate the economic performance of a biorefinery given the volatility in the market price of the final product and the variability in the biomass delivered cost. In addition, potential economic incentives for participating biomass producers are quantified for different farm participation rates. The Monte Carlo simulation model, IBSAL-MC, is used to estimate the biomass delivered cost distribution, and a modified risk heat map is used to visualize the expected return on investment (ROI) for various combinations of the market price of the final product and the biomass delivered cost. The developed methodology is applied to an under-construction cellulosic sugar facility located in Sarnia, southwestern Ontario. Four farm participation rates of 20% (base-case scenario), 30%, 40% and 50% are studied. The results show that the expected annual ROI for the basecase scenario is estimated to be 1.3%. As the farm participation rate increases, the expected annual ROI increases from 1.3% at 20% farm participation rate to 3.4%, 4.6% and 5.1% at 30%, 40% and 50% rates, respectively. At high sugar market prices ($375-$525/tonne), the overall expected annual ROI increases to 9.5%, 11.4%, 12.6% and 13.0% in 20%, 30%, 40% and 50% farm participation rates, respectively. In this case, the economic incentives to share with biomass producers are estimated to be $14.10/dry tonne (dt), $15.77/dt and $16.33/dt by increasing the farm participation rate from 20% to 30%, 40% and 50%, respectively.

Towards an integrated decision‐making support framework for the sustainable production and use of biomass

“…The Canadian biomass availability assessment model (the biomass inventory mapping and analysis tool or BIMAT) 40 and the biomass logistics and supply chain simulation model (the biomass supply analysis and logistic model or IBSAL) 45,54 have been integrated to (1) identify the location of biomass storage sites; 55 (2) identify the potential location of the bio-conversion facility given the density of biomass in the supply area and access to the road infrastructure; 43,56 (3) identify the number of required logistics equipment and size of biomass storage sizes; 43 (4) estimate the biomass logistics costs and the GHG emissions associated with the biomass logistics operations; 43,56 and (5) provide risk analysis to evaluate the economic performance of a biorefinery given the availability of biomass resources within the supply area. 44 This integration improved the analytical capabilities of the IBSAL simulation model to estimate the biomass harvesting and collection costs based on the biomass yield (dry tonne/acre) in the supply area, and estimate the transportation costs based on the road infrastructure.…”

Current challenges of biomass refinery and prospects of emerging technologies for sustainable bioproducts and bioeconomy

“…In lignocellulose biorefinery, a diversity of biomass feedstocks (like energy crops, agro‐residues, forestry waste and many others) plays a key role. The biomass feedstock cost to lignocellulose biorefinery contains the cost of procurement from the landowner, losses during the storage of biomass and costs of storage and transportation to the biorefinery, which are all factors to consider 66 . Pretreatment is the most capital‐intensive processing step, accounting for 30–50% of the overall cost of equipment; operational expenditures in pretreatment account for 20–25% of the total cost of operation.…”

“…The biomass feedstock cost to lignocellulose biorefinery contains the cost of procurement from the landowner, losses during the storage of biomass and costs of storage and transportation to the biorefinery, which are all factors to consider. 66 Pretreatment is the most capital-intensive processing step, accounting for 30-50% of the overall cost of equipment; operational expenditures in pretreatment account for 20-25% of the total cost of operation. In general, enzyme costs account for up to 30% of the total cost of the process, which is much more than that for 1G products like sugar which account for only 3%.…”

A simplified logistics model for integrating BIMAT and IBSAL to estimate harvest costs, energy input and emissions

“…As discussed above, the calculation of the overall cost of delivered biomass to the biorefinery is a complex process that depends on critical factors like fluctuations in annual yields, the volumes to be shipped to the biorefinery, and incentive structures that could be available to biomass producer (Wang et al 2017(Wang et al , 2018. The research reported here is limited in scope dealing with the development of simple models that can be used to integrate harvest -baling cost with BIMAT.…”