Article ID Journal Published Year Pages File Type
172049 Computers & Chemical Engineering 2016 14 Pages PDF
Abstract

•A multiobjective environmental and economic optimisation is carried out for a spatially explicit bioenergy supply chain model.•All stages from biomass cultivation until final usage in alternative vehicles are taken into account.•Biomass can be converted into bioethanol or bioelectricity.•Both bifuel (ethanol and petrol) and electric vehicles are considered.•Economic and environmental performances of different design configurations are critically discussed.

The identification of alternative and sustainable energy sources has been one of the fundamental research goals of the last two decades, and the transport sector plays a key role in this challenge. Electric cars and biofuel fed vehicles may contribute to tackle this formidable issue. According to this perspective, a multi-echelon supply chain is here investigated considering biomass cultivation, transport, conversion into bioethanol or bioelectricity, distribution, and final usage in alternative bifuel (ethanol and petrol) and electric vehicles. Multiperiod and spatially explicit features are introduced in a Mixed Integer Linear Programming (MILP) modelling framework where economic (in terms of Net Present Value) and environmental (in terms of Greenhouse Gases emissions) objectives are simultaneously taken into account. The first and second generation bioethanol production supply chain is matched with a biopower production supply chain assessing multiple technologies. Both corn grain and stover are considered as biomass sources. In the environmental analysis, the impact on emissions caused by indirect Land Use Change (iLUC) effects is also assessed. Results will show the efficacy of the methodology at providing stakeholders with a quantitative tool to optimise the economic and environmental performance of different supply chain configurations.

Related Topics
Physical Sciences and Engineering Chemical Engineering Chemical Engineering (General)
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