Development of an optimization model for the location of biofuel production plants
Abstract: First generation biofuels have not achieved the expected greenhouse gas emission savings and the production may in some cases compete with food production. Issued from non arable land and certified wood, the production of the second generation biofuels are more adapted to tackle those issues. Very large production plants are however required to reach competitive production costs via economy of scale effects. This may cause large logistical issues as the biomass feedstock often is located on the countryside, while the production plants are situated near harbors to enable boat transports. Moreover negative social and environmental effects may occur due to heavy traffic from the transport of the raw material and the final product, such as road damaging, noise perturbation, pollutant emission increase. To face those intensive logistic issues, the geographical location and size of the plant should be determined optimally with respect to raw material and demand location prior to plant investment and construction. The main aim of this thesis has therefore been to develop a model for optimization of the geographical location of second generation biofuel production plants by minimizing the cost of the complete supply chain, which comprises biomass harvesting, biomass transport, biofuel production, biofuel transport and biofuel distribution. The model is not intended to be applied to maximize the profitability of one single plant, but to minimize the final cost of biofuel for the region's welfare. The development of the model is illustrated via several case studies, where also analysis of critical parameters affecting the fuel production cost and the production plant location has been carried out. The model is a mixed integer program. The production of two liquid biofuels for the transportation sector have been studied, methanol via biomass gasification and ligno-cellulosic ethanol via fermentation. The model has been applied on areas as large as country levels. A set of optimal production plant can be determined to fulfill the biofuel demand of a selected area. It can be applied for different biofuel production processes and take into account the by-products geographically explicitly if required. The model can manage demands, costs and prices that change with time. Existing biomass based industries can be integrated to the model, and thus the competition on the biomass between these plants and possible bioenergy plants can be modeled, giving a better estimation of the available biomass for biofuel production. Biofuel imports from long distances are taken into account and finally policy tools such as carbon tax can be applied to limit the emissions from the transports or as a subsidy to the amount of mitigated fossil fuel emissions from the bioenergy production. The developed model can be applied for any kind of biomass based production plant and feedstock as long as the input data is available. As geographical energy planning is important, the developed model may be a valuable tool for decision makers in order to determine the most suitable strategy regarding locations of new biofuel production plants.
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