Multi-period synthesis of optimally integrated biomass and bioenergy supply network |
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| Affiliation: | 1. Faculty of Chemistry and Chemical Engineering, University of Maribor, 2000 Maribor, Slovenia;2. Department of Chemical Engineering, University of Salamanca, 37008 Salamanca, Spain;3. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA;1. Sustainable Process Integration Laboratory – SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology – VUT BRNO, Technická 2896/2, 616 69 Brno, Czech Republic;2. Department of Chemical Engineering, University of Cape Town, Private Bag X3, 7701 Rondebosch, South Africa;3. Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova ulica 17, 2000 Maribor, Slovenia;1. Department of Industrial and Management Engineering, Incheon National University, Incheon 406-772, South Korea;2. Department of Energy and Chemical Engineering, Incheon National University, Incheon 406-772, South Korea;1. Department of Civil Engineering, Ghent University, Vrijdagmarkt 10-301, B-9000, Ghent, Belgium;2. Chair of Technical Thermodynamics, RWTH Aachen University, Schinkelstraße 8, D-52062, Aachen, Germany;3. Unit Smart Energy & Built Environment, VITO NV, Boeretang 200, B-2400, Mol, Belgium;4. Electrical Energy Laboratory (EELAB), Department of Electrical Energy, Systems and Automation (EESA), Ghent University, Technologiepark Zwijn. 913, B-9052, Zwijnaarde, Belgium |
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| Abstract: | This contribution addresses the multi-period synthesis of an optimally integrated regional biomass and bioenergy supply network through a mixed-integer linear programing (MILP) approach. The production processes from different sources of biomass include first, second, and third generations of biofuels like bioethanol, biodiesel, hydrogen, Fischer Tropsch diesel, and green gasoline. The aim is to maximize the sustainably viable utilization of resources by accounting for the competition between fuels and food production. An MILP model for efficient bioenergy network optimization based on four layers is extended to include several features, such as seasonality and availability of resources, enabling recycles of products and total site heat integration in order to address real-world applications with a systematic decision-making approach. The multi-period optimization of a heat-integrated biorefinery's supply network is performed through maximization of the economic performance. Economically efficient solutions are obtained with optimal selection of raw materials, technologies, intermediate and final product flows, and reduced greenhouse-gas emissions. |
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| Keywords: | Biomass supply network Biorefinery Bioenergy generation Mathematical programing Multi-period synthesis |
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