Integration of next-generation biofuel production in the Swedish forest industry - A geographically explicit approach

被引:47
作者
Pettersson, Karin [1 ]
Wetterlund, Elisabeth [2 ]
Athanassiadis, Dimitris [3 ]
Lundmark, Robert [4 ]
Ehn, Christian [5 ]
Lundgren, Joakim [2 ]
Berglin, Niklas [5 ]
机构
[1] Chalmers Univ Technol, Environm & Energy Dept, Div Ind Energy Syst & Technol, SE-41296 Gothenburg, Sweden
[2] Lulea Univ Technol, Div Energy Sci, Energy Engn, SE-97187 Lulea, Sweden
[3] Swedish Univ Agr Sci, Dept Forest Biomat & Technol, SE-90183 Umea, Sweden
[4] Lulea Univ Technol, Econ Unit, SE-97187 Lulea, Sweden
[5] Innventia AB, Business Area Biorefining, SE-11486 Stockholm, Sweden
关键词
Biofuels; Bioenergy; Energy system optimisation; Process integration; Forest industry; KRAFT PULP; PAPER-MILL; BIOMASS GASIFICATION; BIODIESEL PRODUCTION; METHANOL PRODUCTION; EMISSION REDUCTION; ETHANOL; HEAT;
D O I
10.1016/j.apenergy.2015.04.041
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The geographic locations of biofuel production facilities should be strategically chosen in order to minimise the total cost of using biofuels. Proximity to biomass resources, possibilities for integration, and distance to biofuel users are aspects that need to be considered. In this paper, the geographically explicit optimisation model BeWhere Sweden was used to investigate the future production of next-generation biofuels from forest biomass in Sweden. A focus was placed on the integration of biofuel production with the existing forest industry, as well as on how different parameters affect biofuel production costs, the choice of technologies and biofuels, and the localisation of new biofuel plants. Six examples of different biofuel routes were considered. A methodology was developed considering detailed, site-specific conditions for potential host industries. The results show that the cost of biomass and the biofuel plant capital cost generally dominate the biofuel cost, but the cost for biomass transportation and biofuel distribution can also have a significant impact. DME produced via black liquor gasification (naturally integrated with chemical pulp mills) and SNG produced via solid biomass gasification (mainly integrated with sawmills), dominate the solutions. The distribution of these technology cases varies depending on a number of parameters, including criteria for sizing biofuel plants, the electricity price, the biofuel distribution cost and the cost of biomass, and is sensitive to changes in these parameters. Generally, plants with low specific investment costs (i.e., high biofuel production) and/or plants with low specific biomass transportation costs occur most frequently in the solutions. Because these properties often vary significantly among biofuel production facilities at different host industry sites of the same type, the results show the advantage of including site-specific data in this type of model. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:317 / 332
页数:16
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