Modeling the woody biomass supply chain for energy production in northwestern Ontario

Efficient procurement and optimal utilization of woody biomass for bioenergy production requires a good understanding of biomass supply-chain management. The general objective of this research is to develop decision support models for analyzing and aiding decision-making for optimal woody biomass supply chain management for energy production in northwestern Ontario (NWO). The specific objectives are: exploration of data sources and methods for assessing woody biomass availability, assessment of availability of woody biomass feedstock for energy production in the forest management units (FMUs) of NWO; development of a road network optimization model to optimize woody biomass feedstock transportation from forest cells (1 km x 1 km grid) to power plants; and development of optimization models for analyzing the optimal woody biomass supply from forest cells to one power plant with monthly production schedules (dynamic mathematical programming model) and to four competing power plants (modeling the woody biomass competition issues) in NWO.;The spatial assessment study found that in the 19,315 depletion cells (the forest areas where some level of timber harvest took place during 2002-2009) within the study area about 2.1 million green tonnes (gt) of forest harvest residue and 7.6 million gt of underutilized wood are technically available, which is enough to supply the annual biomass demand (2.21 million gt) of the four power plants were they to convert to using only renewable energy sources.;The road network optimization model incorporates speed and load constraints on different types of roads and seeks the minimum time and cost (or shortest distance) from any forest cell to any road containing cell in the study area. From this model variable cost zones of woody biomass feedstock transportation surrounding each of the four power plants are established. The results of the spatial woody biomass assessment and road network model are used as an input dataset for optimization models later.;An optimization model, based on dynamic mathematical programming, was developed and applied to estimate the monthly supply of optimal quantity and type of woody biomass required for the Atikokan Generating Station (AGS) based on its monthly electricity production schedules. The model selects optimal woody biomass harvest levels from 19,315 depletion cells in order to meet the monthly feedstock requirement, and calculates woody biomass procurement costs. Sixteen alternative scenarios are tested to analyze the sensitivities of changing economic and technological parameters on procurement costs. Changes in moisture contents and conversion efficiency show relatively higher changes in monthly and total costs of the woody biomass feedstock for the AGS.;Finally, two optimization models (cost minimization and profit maximization) were developed to test the sensitivities of changing various economic and technological parameters to the optimality of woody biomass competition issues among the four power plants in the region, thereby generating policy relevant costs and gross margin structures of woody biomass supply chains. The results of the cost minimization model in different scenarios, which are relevant for demand side management (power plants), determine that per unit procurement costs are directly proportional to the size of the power plants. The highest increase in unit woody biomass procurement cost is found in the increased truck charge rate scenario followed by the harvesting only forest harvest residue scenario. The profit maximization model, which is relevant from the woody biomass supplier's (contractors) perspective, explores the gross margin structures of woody biomass supplying FMUs. The FMUs that are closer to the power plants potentially offering higher prices make relatively higher gross margins at different levels of price increase on the part of bigger power plant scenarios.;The findings of this study are useful in understanding the cost structures of woody biomass procurement, given the spatial distribution of woody biomass feedstocks, for single and multiple competing power plants as well as the gross margin structures of each woody biomass supplying FMU in NWO. Moreover, the optimization models could be an important tool in decision support systems of woody biomass supply chains for bioenergy production in general.