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Matindi R K
Queensland University of Technology, Australia
Posters & Accepted Abstracts: J Fundam Renewable Energy Appl
Key limitations of previous studies undertaken to assess the impact of bioenergy on greenhouse gas (GHG) mitigation (and energy security) is that the predictions are largely decoupled from any financial drivers. Financial drivers are dealt with implicitly and somewhat artificially by imposing limits on the fraction of available biomass resource diverted to biofuels and dictating which, when and at what rate bioenergy feedstocks are consumed. This would seem a significant weakness in such analyses given that the mitigations of GHG emissions will almost certainly be implemented through market mechanisms to ensure the associated costs are minimised. This paper therefore addresses a novel methodology of using predominantly cost based decision tree to predict the rate of uptake of specific technologies, and optimising biomass supply chain process as a means of increasing biomass availability, the two main uncertainities impeding commercial viability of any bioenergy project.